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Schlagworte
- Bauhaus-Kolloquium (395)
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- Architektur (168)
- 1986 (63)
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- 1992 (39)
- Architekturtheorie (37)
- 1979 (36)
- Maschinelles Lernen (29)
- Finite-Elemente-Methode (27)
- OA-Publikationsfonds2020 (27)
- OA-Publikationsfonds2022 (23)
- Simulation (23)
- Stadtplanung (23)
- Bautechnik (22)
- Wohnungsbau (22)
- Produktmodell (21)
- Technologie (21)
- CAD (20)
- Modellierung (20)
- Deutschland <DDR> (19)
- Städtebau (18)
- Fortschritt (17)
- Lernendes System (15)
- Machine learning (15)
- Kongress (14)
- Macht (14)
- Mehragentensystem (14)
- OA-Publikationsfonds2023 (14)
- Virtuelle Realität (14)
- Fiktion (13)
- Physikalisches Verfahren (11)
- Stadt (11)
- Bauwerk (10)
- Gropius (10)
- Neue Medien (10)
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- Walter (10)
- Großtafelbau (9)
- OA-Publikationsfonds2021 (9)
- Raumklima (9)
- Industriedesign (8)
- Ludwig (8)
- Mies van der Rohe (8)
- Moderne (8)
- OA-Publikationsfonds2018 (8)
- Optimierung (8)
- machine learning (8)
- Building Information Modeling (7)
- Deutschland <Bundesrepublik> (7)
- Erdbeben (7)
- Deep learning (6)
- Forschungskooperation (6)
- Industriebau (6)
- Journalismus (6)
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- Moholy-Nagy (6)
- Neues Bauen (6)
- OA-Publikationsfonds2019 (6)
- Technik (6)
- big data (6)
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While Public-Private Partnership (PPP) is widely adopted across various sectors, it raises a question on its meagre utilisation in the housing sector. This paper, therefore, gauges the perspective of the stakeholders in the building industry towards the application of PPP in various building sectors together with housing. It assesses the performance reliability of PPP for housing by learning possible take-aways from other sectors. The role of key stakeholders in the industry becomes highly responsible for an informed understanding and decision-making. To this end, a two-tier investigation was conducted including surveys and expert interviews, with several stakeholders in the PPP industry in Europe, involving the public sector, private sector, consultants, as well as other community/user representatives.
The survey results demonstrated the success rate with PPPs, major factors important for PPPs such as profitability or end-user acceptability, the prevalent practices and trends in the PPP world, and the majority of support expressed in favour of the suitability of PPP for housing. The interviews added more detailed dimensions to the understanding of the PPP industry, its functioning and enabling the formation of a comprehensive outlook. The results present the perspective, approaches, and experiences of stakeholders over PPP practices, current trends and scenarios and their take on PPP in housing. It shall aid in understanding the challenges prevalent in the PPP approach for implementation in housing and enable the policymakers and industry stakeholders to make provisions for higher uptake to accelerate housing provision.
Despite digitization and platformization, mass media and established media companies still play a crucial role in the provision of journalistic content in democratic societies. Competition is one key driver of (media) company behavior and is considered to have an impact on the media’s performance. However, theory and empirical research are ambiguous about the relationship. The objective of this article is to empirically analyze the effect of competition on media performance in a cross-national context. We assessed media performance of media companies as the importance of journalistic goals within their stated corporate goal system. We conducted a content analysis of letters to the shareholders in annual reports of more than 50 media companies from 2000 to 2014 to operationalize journalistic goal importance. When employing a fixed effects regression analysis, as well as a fuzzy set qualitative comparative analysis, results suggest that competition has a positive effect on the importance of journalistic goals, while the existence of a strong public service media sector appears to have the effect of “crowding out” commercial media companies.
In this study, a new approach to basis of intelligent systems and machine learning algorithms is introduced for solving singular multi-pantograph differential equations (SMDEs). For the first time, a type-2 fuzzy logic based approach is formulated to find an approximated solution. The rules of the suggested type-2 fuzzy logic system (T2-FLS) are optimized by the square root cubature Kalman filter (SCKF) such that the proposed fineness function to be minimized. Furthermore, the stability and boundedness of the estimation error is proved by novel approach on basis of Lyapunov theorem. The accuracy and robustness of the suggested algorithm is verified by several statistical examinations. It is shown that the suggested method results in an accurate solution with rapid convergence and a lower computational cost.
Tall buildings have become an integral part of cities despite all their pros and cons. Some current tall buildings have several problems because of their unsuitable location; the problems include increasing density, imposing traffic on urban thoroughfares, blocking view corridors, etc. Some of these buildings have destroyed desirable views of the city. In this research, different criteria have been chosen, such as environment, access, social-economic, land-use, and physical context. These criteria and sub-criteria are prioritized and weighted by the analytic network process (ANP) based on experts’ opinions, using Super Decisions V2.8 software. On the other hand, layers corresponding to sub-criteria were made in ArcGIS 10.3 simultaneously, then via a weighted overlay (map algebra), a locating plan was created. In the next step seven hypothetical tall buildings (20 stories), in the best part of the locating plan, were considered to evaluate how much of theses hypothetical buildings would be visible (fuzzy visibility) from the street and open spaces throughout the city. These processes have been modeled by MATLAB software, and the final fuzzy visibility plan was created by ArcGIS. Fuzzy visibility results can help city managers and planners to choose which location is suitable for a tall building and how much visibility may be appropriate. The proposed model can locate tall buildings based on technical and visual criteria in the future development of the city and it can be widely used in any city as long as the criteria and weights are localized.
Piping erosion is one form of water erosion that leads to significant changes in the landscape and environmental degradation. In the present study, we evaluated piping erosion modeling in the Zarandieh watershed of Markazi province in Iran based on random forest (RF), support vector machine (SVM), and Bayesian generalized linear models (Bayesian GLM) machine learning algorithms. For this goal, due to the importance of various geo-environmental and soil properties in the evolution and creation of piping erosion, 18 variables were considered for modeling the piping erosion susceptibility in the Zarandieh watershed. A total of 152 points of piping erosion were recognized in the study area that were divided into training (70%) and validation (30%) for modeling. The area under curve (AUC) was used to assess the effeciency of the RF, SVM, and Bayesian GLM. Piping erosion susceptibility results indicated that all three RF, SVM, and Bayesian GLM models had high efficiency in the testing step, such as the AUC shown with values of 0.9 for RF, 0.88 for SVM, and 0.87 for Bayesian GLM. Altitude, pH, and bulk density were the variables that had the greatest influence on the piping erosion susceptibility in the Zarandieh watershed. This result indicates that geo-environmental and soil chemical variables are accountable for the expansion of piping erosion in the Zarandieh watershed.
For this paper, the problem of energy/voltage management in photovoltaic (PV)/battery systems was studied, and a new fractional-order control system on basis of type-3 (T3) fuzzy logic systems (FLSs) was developed. New fractional-order learning rules are derived for tuning of T3-FLSs such that the stability is ensured. In addition, using fractional-order calculus, the robustness was studied versus dynamic uncertainties, perturbation of irradiation, and temperature and abruptly faults in output loads, and, subsequently, new compensators were proposed. In several examinations under difficult operation conditions, such as random temperature, variable irradiation, and abrupt changes in output load, the capability of the schemed controller was verified. In addition, in comparison with other methods, such as proportional-derivative-integral (PID), sliding mode controller (SMC), passivity-based control systems (PBC), and linear quadratic regulator (LQR), the superiority of the suggested method was demonstrated.
This paper reports the formation and structure of fast setting geopolymers activated by using three sodium silicate solutions with different modules (1.6, 2.0 and 2.4) and a berlinite-type aluminum orthophosphate. By varying the concentration of the aluminum orthophosphate, different Si/Al-ratios were established (6, 3 and 2). Reaction kinetics of binders were determined by isothermal calorimetric measurements at 20 °C. X-ray diffraction analysis as well as nuclear magnetic resonance (NMR) measurements were performed on binders to determine differences in structure by varying the alkalinity of the sodium silicate solutions and the Si/Al-ratio. The calorimetric results indicated that the higher the alkalinity of the sodium silicate solution, the higher the solubility and degree of conversion of the aluminum orthophosphate. The results of X-ray diffraction and Rietveldt analysis, as well as the NMR measurements, confirmed the assumption of the calorimetric experiments that first the aluminum orthophosphate was dissolved and then a polycondensation to an amorphous aluminosilicate network occurred. The different amounts of amorphous phases formed as a function of the alkalinity of the sodium silicate solution, indicate that tetrahydroxoaluminate species were formed during the dissolution of the aluminum orthophosphate, which reduce the pH value. This led to no further dissolution of the aluminum orthophosphate, which remained unreacted.
The Marmara Region (NW Turkey) has experienced significant earthquakes (M > 7.0) to date. A destructive earthquake is also expected in the region. To determine the effect of the specific design spectrum, eleven provinces located in the region were chosen according to the Turkey Earthquake Building Code updated in 2019. Additionally, the differences between the previous and updated regulations of the country were investigated. Peak Ground Acceleration (PGA) and Peak Ground Velocity (PGV) were obtained for each province by using earthquake ground motion levels with 2%, 10%, 50%, and 68% probability of exceedance in 50-year periods. The PGA values in the region range from 0.16 to 0.7 g for earthquakes with a return period of 475 years. For each province, a sample of a reinforced-concrete building having two different numbers of stories with the same ground and structural characteristics was chosen. Static adaptive pushover analyses were performed for the sample reinforced-concrete building using each province’s design spectrum. The variations in the earthquake and structural parameters were investigated according to different geographical locations. It was determined that the site-specific design spectrum significantly influences target displacements for performance-based assessments of buildings due to seismicity characteristics of the studied geographic location.
Welfare‐state transformation and entrepreneurial urban politics in Western welfare states since the late 1970s have yielded converging trends in the transformation of the dominant Fordist paradigm of social housing in terms of its societal function and institutional and spatial form. In this article I draw from a comparative case study on two cities in Germany to show that the resulting new paradigm is simultaneously shaped by the idiosyncrasies of the country's national housing regime and local housing policies. While German governments have successively limited the societal function of social housing as a legitimate instrument only for addressing exceptional housing crises, local policies on providing and organizing social housing within this framework display significant variation. However, planning and design principles dominating the spatial forms of social housing have been congruent. They may be interpreted as both an expression of the marginalization of social housing within the restructured welfare housing regime and a tool of its implementation according to the logics of entrepreneurial urban politics.
The economic losses from earthquakes tend to hit the national economy considerably; therefore, models that are capable of estimating the vulnerability and losses of future earthquakes are highly consequential for emergency planners with the purpose of risk mitigation. This demands a mass prioritization filtering of structures to identify vulnerable buildings for retrofitting purposes. The application of advanced structural analysis on each building to study the earthquake response is impractical due to complex calculations, long computational time, and exorbitant cost. This exhibits the need for a fast, reliable, and rapid method, commonly known as Rapid Visual Screening (RVS). The method serves as a preliminary screening platform, using an optimum number of seismic parameters of the structure and predefined output damage states. In this study, the efficacy of the Machine Learning (ML) application in damage prediction through a Support Vector Machine (SVM) model as the damage classification technique has been investigated. The developed model was trained and examined based on damage data from the 1999 Düzce Earthquake in Turkey, where the building’s data consists of 22 performance modifiers that have been implemented with supervised machine learning.
A new large‐field, high‐sensitivity, single‐mirror coincident schlieren optical instrument has been installed at the Bauhaus‐Universität Weimar for the purpose of indoor air research. Its performance is assessed by the non‐intrusive measurement of the thermal plume of a heated manikin. The schlieren system produces excellent qualitative images of the manikin's thermal plume and also quantitative data, especially schlieren velocimetry of the plume's velocity field that is derived from the digital cross‐correlation analysis of a large time sequence of schlieren images. The quantitative results are compared with thermistor and hot‐wire anemometer data obtained at discrete points in the plume. Good agreement is obtained, once the differences between path‐averaged schlieren data and planar anemometry data are reconciled.
Wind effects can be critical for the design of lifelines such as long-span bridges. The existence of a significant number of aerodynamic force models, used to assess the performance of bridges, poses an important question regarding their comparison and validation. This study utilizes a unified set of metrics for a quantitative comparison of time-histories in bridge aerodynamics with a host of characteristics. Accordingly, nine comparison metrics are included to quantify the discrepancies in local and global signal features such as phase, time-varying frequency and magnitude content, probability density, nonstationarity and nonlinearity. Among these, seven metrics available in the literature are introduced after recasting them for time-histories associated with bridge aerodynamics. Two additional metrics are established to overcome the shortcomings of the existing metrics. The performance of the comparison metrics is first assessed using generic signals with prescribed signal features. Subsequently, the metrics are applied to a practical example from bridge aerodynamics to quantify the discrepancies in the aerodynamic forces and response based on numerical and semi-analytical aerodynamic models. In this context, it is demonstrated how a discussion based on the set of comparison metrics presented here can aid a model evaluation by offering deeper insight. The outcome of the study is intended to provide a framework for quantitative comparison and validation of aerodynamic models based on the underlying physics of fluid-structure interaction. Immediate further applications are expected for the comparison of time-histories that are simulated by data-driven approaches.
Evaporation is a very important process; it is one of the most critical factors in agricultural, hydrological, and meteorological studies. Due to the interactions of multiple climatic factors, evaporation is considered as a complex and nonlinear phenomenon to model. Thus, machine learning methods have gained popularity in this realm. In the present study, four machine learning methods of Gaussian Process Regression (GPR), K-Nearest Neighbors (KNN), Random Forest (RF) and Support Vector Regression (SVR) were used to predict the pan evaporation (PE). Meteorological data including PE, temperature (T), relative humidity (RH), wind speed (W), and sunny hours (S) collected from 2011 through 2017. The accuracy of the studied methods was determined using the statistical indices of Root Mean Squared Error (RMSE), correlation coefficient (R) and Mean Absolute Error (MAE). Furthermore, the Taylor charts utilized for evaluating the accuracy of the mentioned models. The results of this study showed that at Gonbad-e Kavus, Gorgan and Bandar Torkman stations, GPR with RMSE of 1.521 mm/day, 1.244 mm/day, and 1.254 mm/day, KNN with RMSE of 1.991 mm/day, 1.775 mm/day, and 1.577 mm/day, RF with RMSE of 1.614 mm/day, 1.337 mm/day, and 1.316 mm/day, and SVR with RMSE of 1.55 mm/day, 1.262 mm/day, and 1.275 mm/day had more appropriate performances in estimating PE values. It was found that GPR for Gonbad-e Kavus Station with input parameters of T, W and S and GPR for Gorgan and Bandar Torkmen stations with input parameters of T, RH, W and S had the most accurate predictions and were proposed for precise estimation of PE. The findings of the current study indicated that the PE values may be accurately estimated with few easily measured meteorological parameters.
Due to the importance of identifying crop cultivars, the advancement of accurate assessment of cultivars is considered essential. The existing methods for identifying rice cultivars are mainly time-consuming, costly, and destructive. Therefore, the development of novel methods is highly beneficial. The aim of the present research is to classify common rice cultivars in Iran based on color, morphologic, and texture properties using artificial intelligence (AI) methods. In doing so, digital images of 13 rice cultivars in Iran in three forms of paddy, brown, and white are analyzed through pre-processing and segmentation of using MATLAB. Ninety-two specificities, including 60 color, 14 morphologic, and 18 texture properties, were identified for each rice cultivar. In the next step, the normal distribution of data was evaluated, and the possibility of observing a significant difference between all specificities of cultivars was studied using variance analysis. In addition, the least significant difference (LSD) test was performed to obtain a more accurate comparison between cultivars. To reduce data dimensions and focus on the most effective components, principal component analysis (PCA) was employed. Accordingly, the accuracy of rice cultivar separations was calculated for paddy, brown rice, and white rice using discriminant analysis (DA), which was 89.2%, 87.7%, and 83.1%, respectively. To identify and classify the desired cultivars, a multilayered perceptron neural network was implemented based on the most effective components. The results showed 100% accuracy of the network in identifying and classifying all mentioned rice cultivars. Hence, it is concluded that the integrated method of image processing and pattern recognition methods, such as statistical classification and artificial neural networks, can be used for identifying and classification of rice cultivars.
The effect of urban form on energy consumption has been the subject of various studies around the world. Having examined the effect of buildings on energy consumption, these studies indicate that the physical form of a city has a notable impact on the amount of energy consumed in its spaces. The present study identified the variables that affected energy consumption in residential buildings and analyzed their effects on energy consumption in four neighborhoods in Tehran: Apadana, Bimeh, Ekbatan-phase I, and Ekbatan-phase II. After extracting the variables, their effects are estimated with statistical methods, and the results are compared with the land surface temperature (LST) remote sensing data derived from Landsat 8 satellite images taken in the winter of 2019. The results showed that physical variables, such as the size of buildings, population density, vegetation cover, texture concentration, and surface color, have the greatest impacts on energy usage. For the Apadana neighborhood, the factors with the most potent effect on energy consumption were found to be the size of buildings and the population density. However, for other neighborhoods, in addition to these two factors, a third factor was also recognized to have a significant effect on energy consumption. This third factor for the Bimeh, Ekbatan-I, and Ekbatan-II neighborhoods was the type of buildings, texture concentration, and orientation of buildings, respectively.
Calculating hydrocarbon components solubility of natural gases is known as one of the important issues for operational works in petroleum and chemical engineering. In this work, a novel solubility estimation tool has been proposed for hydrocarbon gases—including methane, ethane, propane, and butane—in aqueous electrolyte solutions based on extreme learning machine (ELM) algorithm. Comparing the ELM outputs with a comprehensive real databank which has 1175 solubility points yielded R-squared values of 0.985 and 0.987 for training and testing phases respectively. Furthermore, the visual comparison of estimated and actual hydrocarbon solubility led to confirm the ability of proposed solubility model. Additionally, sensitivity analysis has been employed on the input variables of model to identify their impacts on hydrocarbon solubility. Such a comprehensive and reliable study can help engineers and scientists to successfully determine the important thermodynamic properties, which are key factors in optimizing and designing different industrial units such as refineries and petrochemical plants.
Carrier-bound titanium dioxide catalysts were used in a photocatalytic ozonation reactor for the degradation of micro-pollutants in real wastewater. A photocatalytic immersion rotary body reactor with a 36-cm disk diameter was used, and was irradiated using UV-A light-emitting diodes. The rotating disks were covered with catalysts based on stainless steel grids coated with titanium dioxide. The dosing of ozone was carried out through the liquid phase via an external enrichment and a supply system transverse to the flow direction. The influence of irradiation power and ozone dose on the degradation rate for photocatalytic ozonation was investigated. In addition, the performance of the individual processes photocatalysis and ozonation were studied. The degradation kinetics of the parent compounds were determined using liquid chromatography tandem mass spectrometry. First-order kinetics were determined for photocatalysis and photocatalytic ozonation. A maximum reaction rate of the reactor was determined, which could be achieved by both photocatalysis and photocatalytic ozonation. At a dosage of 0.4 mg /mg DOC, the maximum reaction rate could be achieved using 75% of the irradiation power used for sole photocatalysis, allowing increases in the energetic efficiency of photocatalytic wastewater treatment processes. The process of photocatalytic ozonation is suitable to remove a wide spectrum of micro-pollutants from wastewater.
A vast number of existing buildings were constructed before the development and enforcement of seismic design codes, which run into the risk of being severely damaged under the action of seismic excitations. This poses not only a threat to the life of people but also affects the socio-economic stability in the affected area. Therefore, it is necessary to assess such buildings’ present vulnerability to make an educated decision regarding risk mitigation by seismic strengthening techniques such as retrofitting. However, it is economically and timely manner not feasible to inspect, repair, and augment every old building on an urban scale. As a result, a reliable rapid screening methods, namely Rapid Visual Screening (RVS), have garnered increasing interest among researchers and decision-makers alike. In this study, the effectiveness of five different Machine Learning (ML) techniques in vulnerability prediction applications have been investigated. The damage data of four different earthquakes from Ecuador, Haiti, Nepal, and South Korea, have been utilized to train and test the developed models. Eight performance modifiers have been implemented as variables with a supervised ML. The investigations on this paper illustrate that the assessed vulnerability classes by ML techniques were very close to the actual damage levels observed in the buildings.
The growing complexity of modern practical problems puts high demand on mathematical modelling. Given that various models can be used for modelling one physical phenomenon, the role of model comparison and model choice is becoming particularly important. Methods for model comparison and model choice typically used in practical applications nowadays are computationbased, and thus time consuming and computationally costly. Therefore, it is necessary to develop other approaches to working abstractly, i.e., without computations, with mathematical models. An abstract description of mathematical models can be achieved by the help of abstract mathematics, implying formalisation of models and relations between them. In this paper, a category theory-based approach to mathematical modelling is proposed. In this way, mathematical models are formalised in the language of categories, relations between the models are formally defined and several practically relevant properties are introduced on the level of categories. Finally, an illustrative example is presented, underlying how the category-theory based approach can be used in practice. Further, all constructions presented in this paper are also discussed from a modelling point of view by making explicit the link to concrete modelling scenarios.
The derivation of nonlocal strong forms for many physical problems remains cumbersome in traditional methods. In this paper, we apply the variational principle/weighted residual method based on nonlocal operator method for the derivation of nonlocal forms for elasticity, thin plate, gradient elasticity, electro-magneto-elasticity and phase-field fracture method. The nonlocal governing equations are expressed as an integral form on support and dual-support. The first example shows that the nonlocal elasticity has the same form as dual-horizon non-ordinary state-based peridynamics. The derivation is simple and general and it can convert efficiently many local physical models into their corresponding nonlocal forms. In addition, a criterion based on the instability of the nonlocal gradient is proposed for the fracture modelling in linear elasticity. Several numerical examples are presented to validate nonlocal elasticity and the nonlocal thin plate.
Personalized ventilation (PV) is a mean of delivering conditioned outdoor air into the breathing zone of the occupants. This study aims to qualitatively investigate the personalized flows using two methods of visualization: (1) schlieren imaging using a large schlieren mirror and (2) thermography using an infrared camera. While the schlieren imaging was used to render the velocity and mass transport of the supplied flow, thermography was implemented to visualize the air temperature distribution induced by the PV. Both studies were conducted using a thermal manikin to simulate an occupant facing a PV outlet. As a reference, the flow supplied by an axial fan and a cased axial fan was visualized with the schlieren system as well and compared to the flow supplied by PV. Schlieren visualization results indicate that the steady, low-turbulence flow supplied by PV was able to penetrate the thermal convective boundary layer encasing the manikin's body, providing clean air for inhalation. Contrarily, the axial fan diffused the supplied air over a large target area with high turbulence intensity; it only disturbed the convective boundary layer rather than destroying it. The cased fan supplied a flow with a reduced target area which allowed supplying more air into the breathing zone compared to the fan. The results of thermography visualization showed that the supplied cool air from PV penetrated the corona-shaped thermal boundary layer. Furthermore, the supplied air cooled the surface temperature of the face, which indicates the large impact of PV on local thermal sensation and comfort.
Electric trains are considered one of the most eco-friendly and safest means of transportation. Catenary poles are used worldwide to support overhead power lines for electric trains. The performance of the catenary poles has an extensive influence on the integrity of the train systems and, consequently, the connected human services. It became a must nowadays to develop SHM systems that provide the instantaneous status of catenary poles in- service, making the decision-making processes to keep or repair the damaged poles more feasible. This study develops a data-driven, model-free approach for status monitoring of cantilever structures, focusing on pre-stressed, spun-cast ultrahigh-strength concrete catenary poles installed along high-speed train tracks. The pro-posed approach evaluates multiple damage features in an unfied damage index, which leads to straightforward interpretation and comparison of the output. Besides, it distinguishes between multiple damage scenarios of the poles, either the ones caused by material degradation of the concrete or by the cracks that can be propagated during the life span of the given structure. Moreover, using a logistic function to classify the integrity of structure avoids the expensive learning step in the existing damage detection approaches, namely, using the modern machine and deep learning methods. The findings of this study look very promising when applied to other types of cantilever structures, such as the poles that support the power transmission lines, antenna masts, chimneys, and wind turbines.
In this article, I show why it is necessary to abolish the use of predictive algorithms in the US criminal justice system at sentencing. After presenting the functioning of these algorithms in their context of emergence, I offer three arguments to demonstrate why their abolition is imperative. First, I show that sentencing based on predictive algorithms induces a process of rewriting the temporality of the judged individual, flattening their life into a present inescapably doomed by its past. Second, I demonstrate that recursive processes, comprising predictive algorithms and the decisions based on their predictions, systematically suppress outliers and progressively transform reality to match predictions. In my third and final argument, I show that decisions made on the basis of predictive algorithms actively perform a biopolitical understanding of justice as management and modulation of risks. In such a framework, justice becomes a means to maintain a perverse social homeostasis that systematically exposes disenfranchised Black and Brown populations to risk.
Scaling of concrete due to salt frost attack is an important durability issue in moderate and cold climates. The actual damage mechanism is still not completely understood. Two recent damage theories—the glue spall theory and the cryogenic suction theory—offer plausible, but conflicting explanations for the salt frost scaling mechanism. The present study deals with the cryogenic suction theory, which assumes that freezing concrete can take up unfrozen brine from a partly frozen deicing solution during salt frost attack. According to the model hypothesis, the resulting saturation of the concrete surface layer intensifies the ice formation in this layer and causes salt frost scaling. In this study an experimental technique was developed that makes it possible to quantify to which extent brine uptake can increase ice formation in hardened cement paste (used as a model material for concrete). The experiments were carried out with low temperature differential scanning calorimetry, where specimens were subjected to freeze–thaw cycles while being in contact with NaCl brine. Results showed that the ice content in the specimens increased with subsequent freeze–thaw cycles due to the brine uptake at temperatures below 0 °C. The ability of the hardened cement paste to bind chlorides from the absorbed brine at the same time affected the freezing/melting behavior of the pore solution and the magnitude of the ice content.
Marine macroalgae such as Ulva intestinalis have promising properties as feedstock for cosmetics and pharmaceuticals. However, since the quantity and quality of naturally grown algae vary widely, their exploitability is reduced – especially for producers in high-priced markets. Moreover, the expansion of marine or shore-based cultivation systems is unlikely in Europe, since promising sites either lie in fishing zones, recreational areas, or natural reserves. The aim was therefore to develop a closed photobioreactor system enabling full control of abiotic environmental parameters and an effective reconditioning of the cultivation medium in order to produce marine macroalgae at sites distant from the shore. To assess the feasibility and functionality of the chosen technological concept, a prototypal plant has been implemented in central Germany – a site distant from the sea. Using a newly developed, submersible LED light source, cultivation experiments with Ulva intestinalis led to growth rates of 7.72 ± 0.04 % day−1 in a cultivation cycle of 28 days. Based on the space demand of the production system, this results in fresh mass productivity of 3.0 kg m−2, respectively, of 1.1 kg m−2 per year. Also considering the ratio of biomass to energy input amounting to 2.76 g kWh−1, significant future improvements of the developed photobioreactor system should include the optimization of growth parameters, and the reduction of the system’s overall energy demand.
Antimicrobial resistance (AMR) is identified by the World Health Organization (WHO) as one of the top ten threats to public health worldwide. In addition to public health, AMR also poses a major threat to food security and economic development. Current sanitation systems contribute to the emergence and spread of AMR and lack effective AMR mitigation measures. This study assesses source separation of blackwater as a mitigation measure against AMR. A source-separation-modified combined sanitation system with separate collection of blackwater and graywater is conceptually described. Measures taken at the source, such as the separate collection and discharge of material flows, were not considered so far on a load balance basis, i.e., they have not yet been evaluated for their effectiveness. The sanitation system described is compared with a combined system and a separate system regarding AMR emissions by means of simulation. AMR is represented in the simulation model by one proxy parameter each for antibiotics (sulfamethoxa-zole), antibiotic-resistant bacteria (extended-spectrum beta-lactamase E. Coli), and antibiotic re-sistance genes (blaTEM). The simulation results suggest that the source-separation-based sanitation system reduces emissions of antibiotic-resistant bacteria and antibiotic resistance genes into the aquatic environment by more than six logarithm steps compared to combined systems. Sulfa-methoxazole emissions can be reduced by 75.5% by keeping blackwater separate from graywater and treating it sufficiently. In summary, sanitation systems incorporating source separation are, to date, among the most effective means of preventing the emission of AMR into the aquatic envi-ronment.
Bolted connections are commonly used in steel construction. The load-bearing behavior of bolt fittings has extensively been studied in various research activities and the bearing capacity of bolted connections can be assessed well by standard regulations for practical applications. With regard to tensile loading, the nut does not have strong influence on resistances, since the failure occurs in the bolts due to higher material strengths of the nuts. In some applications, so-called “blind holes” are used to connect plated components. In a manner of speaking, the nut is replaced by the “outer” plate with a prefabricated hole and thread, in which the bolt can be screwed and tightened. In such connections, the limit load capacity cannot solely be assessed by the bolt resistance, since the threaded hole in the base material has strong influence on the structural behavior. In this context, the available screw-in depth of the blind hole is of fundamental importance. The German National Annex of EN 1993-1-8 provides information on a necessary depth in order to transfer the full tensile capacity of the bolt. However, some connections do not allow to fabricate such depths. In these cases, the capacity of the connection is unclear and not specified. In this paper, first experiments on corresponding connections with different screw-in depths are presented and compared to limit load capacities according to the standard.
Besides their multiple known benefits regarding urban microclimate, living walls can be used as decentralized stand-alone systems to treat greywater locally at the buildings. While this offers numerous environmental advantages, it can have a considerable impact on the hygrothermal performance of the facade as such systems involve bringing large quantities of water onto the facade. As it is difficult to represent complex entities such as plants in the typical simulation tools used for heat and moisture transport, this study suggests a new approach to tackle this challenge by coupling two tools: ENVI-Met and Delphin. ENVI-Met was used to simulate the impact of the plants to determine the local environmental parameters at the living wall. Delphin, on the other hand, was used to conduct the hygrothermal simulations using the local parameters calculated by ENVI-Met. Four wall constructions were investigated in this study: an uninsulated brick wall, a precast concrete plate, a sandy limestone wall, and a double-shell wall. The results showed that the living wall improved the U-value, the exterior surface temperature, and the heat flux through the wall. Moreover, the living wall did not increase the risk of moisture in the wall during winter and eliminated the risk of condensation.
Few studies have investigated how search behavior affects complex writing tasks. We analyze a dataset of 150 long essays whose authors searched the ClueWeb09 corpus for source material, while all querying, clicking, and writing activity was meticulously recorded. We model the effect of search and writing behavior on essay quality using path analysis. Since the boil-down and build-up writing strategies identified in previous research have been found to affect search behavior, we model each writing strategy separately. Our analysis shows that the search process contributes significantly to essay quality through both direct and mediated effects, while the author's writing strategy moderates this relationship. Our models explain 25–35% of the variation in essay quality through rather simple search and writing process characteristics alone, a fact that has implications on how search engines could personalize result pages for writing tasks. Authors' writing strategies and associated searching patterns differ, producing differences in essay quality. In a nutshell: essay quality improves if search and writing strategies harmonize—build-up writers benefit from focused, in-depth querying, while boil-down writers fare better with a broader and shallower querying strategy.
In this paper we present a theoretical background for a coupled analytical–numerical approach to model a crack propagation process in two-dimensional bounded domains. The goal of the coupled analytical–numerical approach is to obtain the correct solution behaviour near the crack tip by help of the analytical solution constructed by using tools of complex function theory and couple it continuously with the finite element solution in the region far from the singularity. In this way, crack propagation could be modelled without using remeshing. Possible directions of crack growth can be calculated through the minimization of the total energy composed of the potential energy and the dissipated energy based on the energy release rate. Within this setting, an analytical solution of a mixed boundary value problem based on complex analysis and conformal mapping techniques is presented in a circular region containing an arbitrary crack path. More precisely, the linear elastic problem is transformed into a Riemann–Hilbert problem in the unit disk for holomorphic functions. Utilising advantages of the analytical solution in the region near the crack tip, the total energy could be evaluated within short computation times for various crack kink angles and lengths leading to a potentially efficient way of computing the minimization procedure. To this end, the paper presents a general strategy of the new coupled approach for crack propagation modelling. Additionally, we also discuss obstacles in the way of practical realisation of this strategy.
In this work, extensive reactive molecular dynamics simulations are conducted to analyze the nanopore creation by nano-particles impact over single-layer molybdenum disulfide (MoS2) with 1T and 2H phases. We also compare the results with graphene monolayer. In our simulations, nanosheets are exposed to a spherical rigid carbon projectile with high initial velocities ranging from 2 to 23 km/s. Results for three different structures are compared to examine the most critical factors in the perforation and resistance force during the impact. To analyze the perforation and impact resistance, kinetic energy and displacement time history of the projectile as well as perforation resistance force of the projectile are investigated.
Interestingly, although the elasticity module and tensile strength of the graphene are by almost five times higher than those of MoS2, the results demonstrate that 1T and 2H-MoS2 phases are more resistive to the impact loading and perforation than graphene. For the MoS2nanosheets, we realize that the 2H phase is more resistant to impact loading than the 1T counterpart.
Our reactive molecular dynamics results highlight that in addition to the strength and toughness, atomic structure is another crucial factor that can contribute substantially to impact resistance of 2D materials. The obtained results can be useful to guide the experimental setups for the nanopore creation in MoS2or other 2D lattices.
Durch internationale Fluchtbewegungen über die sogenannte Balkanroute bildete sich in Serbiens Hauptstadt Belgrad in den letzten Jahren ein sogenannter Refugee District heraus. Im Kontext von Migration und Flucht werden dabei zahlreiche Spannungsfelder auf unterschiedlichen räumlichen und politischen Ebenen sichtbar. Für Flüchtende kreieren diese eine Situation, die von Stillstand, Ausweglosigkeit, Kontrolle, Gefahr und Verdrängung geprägt ist. Allerdings führen die Vielschichtigkeit und die Diversität unterschiedlicher Akteur*innen, die bezüglich der Situation von Flüchtenden auf der Balkanroute wirkmächtig sind, auch zu Nischen, Widerständigkeiten und der Möglichkeit (neuer) Allianzen. Auf diese Weise entsteht eine kollektive Praktik der Nicht-Bewegung im Widerstand gegen die Unterdrückung und für globale Bewegungsfreiheit.
According to Eurocode, the computation of bending strength for steel cantilever beams is a straightforward process. The approach is based on an Ayrton-Perry formula adaptation of buckling curves for steel members in compression, which involves the computation of an elastic critical buckling load for considering the instability. NCCI documents offer a simplified formula to determine the critical bending moment for cantilevers beams with symmetric cross-section. Besides the NCCI recommendations, other approaches, e.g. research literature or Finite-Element-Analysis, may be employed to determine critical buckling loads. However, in certain cases they render different results. Present paper summarizes and compares the abovementioned analytical and numerical approaches for determining critical loads and it exemplarily analyses corresponding cantilever beam capacities using numerical approaches based on plastic zones theory (GMNIA).
The spread of breathing air when playing wind instruments and singing was investigated and visualized using two methods: (1) schlieren imaging with a schlieren mirror and (2) background-oriented schlieren (BOS). These methods visualize airflow by visualizing density gradients in transparent media. The playing of professional woodwind and brass instrument players, as well as professional classical trained singers were investigated to estimate the spread distances of the breathing air. For a better comparison and consistent measurement series, a single high note, a single low note, and an extract of a musical piece were investigated. Additionally, anemometry was used to determine the velocity of the spreading breathing air and the extent to which it was quantifiable. The results showed that the ejected airflow from the examined instruments and singers did not exceed a spreading range of 1.2 m into the room. However, differences in the various instruments have to be considered to assess properly the spread of the breathing air. The findings discussed below help to estimate the risk of cross-infection for wind instrument players and singers and to develop efficacious safety precautions, which is essential during critical health periods such as the current COVID-19 pandemic.
This paper presents numerical analysis of the discrete fundamental solution of the discrete Laplace operator on a rectangular lattice. Additionally, to provide estimates in interior and exterior domains, two different regularisations of the discrete fundamental solution are considered. Estimates for the absolute difference and lp-estimates are constructed for both regularisations. Thus, this work extends the classical results in the discrete potential theory to the case of a rectangular lattice and serves as a basis for future convergence analysis of the method of discrete potentials on rectangular lattices.
Global structural analyses in civil engineering are usually performed considering linear-elastic material behavior. However, for steel structures, a certain degree of plasticization depending on the member classification may be considered. Corresponding plastic analyses taking material nonlinearities into account are effectively realized using numerical methods. Frequently applied finite elements of two and three-dimensional models evaluate the plasticity at defined nodes using a yield surface, i.e. by a yield condition, hardening rule, and flow rule. Corresponding calculations are connected to a large numerical as well as time-consuming effort and they do not rely on the theoretical background of beam theory, to which the regulations of standards mainly correspond. For that reason, methods using beam elements (one-dimensional) combined with cross-sectional analyses are commonly applied for steel members in terms of plastic zones theories. In these approaches, plasticization is in general assessed by means of axial stress only. In this paper, more precise numerical representation of the combined stress states, i.e. axial and shear stresses, is presented and results of the proposed approach are validated and discussed.
Polylactic acid (PLA) is a highly applicable material that is used in 3D printers due to some significant features such as its deformation property and affordable cost. For improvement of the end-use quality, it is of significant importance to enhance the quality of fused filament fabrication (FFF)-printed objects in PLA. The purpose of this investigation was to boost toughness and to reduce the production cost of the FFF-printed tensile test samples with the desired part thickness. To remove the need for numerous and idle printing samples, the response surface method (RSM) was used. Statistical analysis was performed to deal with this concern by considering extruder temperature (ET), infill percentage (IP), and layer thickness (LT) as controlled factors. The artificial intelligence method of artificial neural network (ANN) and ANN-genetic algorithm (ANN-GA) were further developed to estimate the toughness, part thickness, and production-cost-dependent variables. Results were evaluated by correlation coefficient and RMSE values. According to the modeling results, ANN-GA as a hybrid machine learning (ML) technique could enhance the accuracy of modeling by about 7.5, 11.5, and 4.5% for toughness, part thickness, and production cost, respectively, in comparison with those for the single ANN method. On the other hand, the optimization results confirm that the optimized specimen is cost-effective and able to comparatively undergo deformation, which enables the usability of printed PLA objects.
Burning of clinker is the most influencing step of cement quality during the production process. Appropriate characterisation for quality control and decision-making is therefore the critical point to maintain a stable production but also for the development of alternative cements. Scanning electron microscopy (SEM) in combination with energy dispersive X-ray spectroscopy (EDX) delivers spatially resolved phase and chemical information for cement clinker. This data can be used to quantify phase fractions and chemical composition of identified phases.
The contribution aims to provide an overview of phase fraction quantification by semi-automatic phase segmentation using high-resolution backscattered electron (BSE) images and lower-resolved EDX element maps. Therefore, a tool for image analysis was developed that uses state-of-the-art algorithms for pixel-wise image segmentation and labelling in combination with a decision tree that allows searching for specific clinker phases. Results show that this tool can be applied to segment sub-micron scale clinker phases and to get a quantification of all phase fractions. In addition, statistical evaluation of the data is implemented within the tool to reveal whether the imaged area is representative for all clinker phases.
This study demonstrates the application and combination of multiple imaging techniques [light microscopy, micro-X-ray computer tomography (μ-CT), scanning electron microscopy (SEM) and focussed ion beam – nano-tomography (FIB-nT)] to the analysis of the microstructure of hydrated alite across multiple scales. However, by comparing findings with mercury intrusion porosimetry (MIP), it becomes obvious that the imaged 3D volumes and 2D images do not sufficiently overlap at certain scales to allow a continuous quantification of the pore size distribution (PSD). This can be overcome by improving the resolution and increasing the measured volume. Furthermore, results show that the fibrous morphology of calcium-silicate-hydrates (C-S-H) phases is preserved during FIB-nT. This is a requirement for characterisation of nano-scale porosity. Finally, it was proven that the combination of FIB-nT with energy-dispersive X-ray spectroscopy (EDX) data facilitates the phase segmentation of a 11 × 11 × 7.7 μm3 volume of hydrated alite.
Within the scope of literature, the influence of openings within the infill walls that are bounded by a reinforced concrete frame and excited by seismic drift forces in both in- and out-of-plane direction is still uncharted. Therefore, a 3D micromodel was developed and calibrated thereafter, to gain more insight in the topic. The micromodels were calibrated against their equivalent physical test specimens of in-plane, out-of-plane drift driven tests on frames with and without infill walls and openings, as well as out-of-plane bend test of masonry walls. Micromodels were rectified based on their behavior and damage states. As a result of the calibration process, it was found that micromodels were sensitive and insensitive to various parameters, regarding the model’s behavior and computational stability. It was found that, even within the same material model, some parameters had more effects when attributed to concrete rather than on masonry. Generally, the in-plane behavior of infilled frames was found to be largely governed by the interface material model. The out-of-plane masonry wall simulations were governed by the tensile strength of both the interface and masonry material model. Yet, the out-of-plane drift driven test was governed by the concrete material properties.
Realistic uncertainty description incorporating aleatoric and epistemic uncertainties can be described within the framework of polymorphic uncertainty, which is computationally demanding. Utilizing a domain decomposition approach for random field based uncertainty models the proposed level-based sampling method can reduce these computational costs significantly and shows good agreement with a standard sampling technique. While 2-level configurations tend to get unstable with decreasing sampling density 3-level setups show encouraging results for the investigated reliability analysis of a structural unit square.
Bauhaus-Gastprofessorin Mirjam Wenzel referierte am 30. Juni 2021 im Audimax der Bauhaus-Universität Weimar zur Entstehungsgeschichte und Konzeption Jüdischer Museen. Dabei ging sie darauf ein, inwiefern diese Museen besonders relevant für aktuelle gesellschaftliche und politische Fragestellungen sind. Prof. Wenzels zweiter öffentlicher Vortrag an der Bauhaus-Universität Weimar skizzierte die Potentiale von Kultureinrichtungen in Zeiten gesellschaftspolitischer Veränderungen im Allgemeinen und die Bedeutung Jüdischer Museen angesichts verbaler und tätlicher Gewalt gegen Jüdinnen und Juden im Besonderen.
Compiling and disseminating information about incidents and disasters are key to disaster management and relief. But due to inherent limitations of the acquisition process, the required information is often incomplete or missing altogether. To fill these gaps, citizen observations spread through social media are widely considered to be a promising source of relevant information, and many studies propose new methods to tap this resource. Yet, the overarching question of whether and under which circumstances social media can supply relevant information (both qualitatively and quantitatively) still remains unanswered. To shed some light on this question, we review 37 disaster and incident databases covering 27 incident types, compile a unified overview of the contained data and their collection processes, and identify the missing or incomplete information. The resulting data collection reveals six major use cases for social media analysis in incident data collection: (1) impact assessment and verification of model predictions, (2) narrative generation, (3) recruiting citizen volunteers, (4) supporting weakly institutionalized areas, (5) narrowing surveillance areas, and (6) reporting triggers for periodical surveillance. Furthermore, we discuss the benefits and shortcomings of using social media data for closing information gaps related to incidents and disasters.
Chemical glass frosting processes are widely used to create visual attractive glass surfaces. A commonly used frosting bath mainly contains ammonium bifluoride (NH4HF2) mixed with hydrochloric acid (HCl). The frosting process consists of several baths. Firstly, the preliminary bath to clean the object. Secondly, the frosting bath which etches the rough light scattering structure into the glass surface. Finally, the washing baths to clean the frosted object. This is where the constituents of the preceding steps accumulate and have to be filtered from the sewage. In the present contribution, phosphoric acid (H3PO4) was used as a substitute for HCl to reduce the amount of ammonium (NH4+) and chloride (Cl−) dissolved in the waste water. In combination with magnesium carbonate (MgCO3), it allows the precipitation of ammonium within the sewage as ammonium magnesium phosphate (MgNH4PO4). However, a trivial replacement of HCl by H3PO4 within the frosting process causes extensive frosting errors, such as inhomogeneous size distributions of the structures or domains that are not fully covered by these structures. By modifying the preliminary bath composition, it was possible to improve the frosting result considerably. To determine the optimal composition of the preliminary bath, a semi-automatic evaluation method has been developed. This method renders the objective comparison of the resulting surface quality possible.
Entrepreneurship and start-up activities are seen as a key response to recent upheavals in the media industry: Newly founded ventures can act as important drivers for industry transformation and renewal, pioneering new products, business models, and organizational designs (e.g. Achtenhagen, 2017; Buschow & Laugemann, 2020).
In principle, media students represent a crucial population of nascent entrepreneurs: individuals who will likely become founders of start-ups (Casero-Ripollés et al., 2016). However, their willingness to start a new business is generally considered to be rather low (Goyanes, 2015), and for journalism students, the idea of innovation tends to be conservative, following traditional norms and professional standards (Singer & Broersma, 2020). In a sample of Spanish journalism students, López-Meri et al. (2020) found that one of the main barriers to entrepreneurial intentions is that students feel they lack knowledge and training in entrepreneurship.
In the last 10 years, a wide variety of entrepreneurship education courses have been set up in media departments of colleges and universities worldwide.
These programs have been designed to sensitize and prepare communications, media and journalism students to think and act entrepreneurially (e.g. Caplan et al., 2020; Ferrier, 2013; Ferrier & Mays, 2017; Hunter & Nel, 2011). Entrepreneurial competencies
and practices not only play a crucial role for start-ups, but, in imes of digital transformation, are increasingly sought after by legacy media companies as well (Küng, 2015).
At the Department of Journalism and Communication Research, Hanover University of Music, Drama and Media, Germany, we have been addressing these developments with the “Media Entrepreneurship” program. The course, established in 2013, aims to provide fundamental knowledge of entrepreneurship, as well as promoting students‘ entrepreneurial thinking and behavior. This article presents the pedagogical approach of the program and investigates learning outcomes. By outlining and evaluating the Media Entrepreneurship program, this article aims to promote good practices of entrepreneurship education in communications, media and journalism, and to reflect on the limitations of such programs.
This article is focused on the research and development of new cellulose ether derivatives as innovative superplasticizers for mortar systems. Several synthetic strategies have been pursued to obtain new compounds to study their properties on cementitious systems as new bio-based additives. The new water-soluble admixtures were synthesized using a complex carboxymethylcellulose-based backbone that was first hydrolyzed and then sulfo-ethylated in the presence of sodium vinyl sulphonate. Starting with a complex biopolymer that is widely known as a thickening agent was very challenging. Only by varying the hydrolysis times and temperatures of the reactions was achieved the aimed goal. The obtained derivatives showed different molecular weight (Mw) and anionic charges on their backbones. An improvement in shear stress and dynamic viscosity values of CEM II 42.5R cement was observed with the samples obtained with a longer time of higher temperature hydrolysis and sulfo-ethylation. Investigations into the chemical nature of the pore solution, calorimetric studies and adsorption experiments clearly showed the ability of carboxymethyl cellulose superplasticizer (CMC SP) to interact with cement grains and influence hydration processes within a 48-h time window, causing a delay in hydration reactions in the samples. The fluidity of the cementitious matrices was ascertained through slump test and preliminary studies of mechanical and flexural strength of the hardened mortar formulated with the new ecological additives yielded values in terms of mechanical properties. Finally, the computed tomography (CT) images completed the investigation of the pore network structure of hardened specimens, highlighting their promising structure porosity.
The development of a hydro-mechanically coupled Coupled-Eulerian–Lagrangian (CEL) method and its application to the back-analysisof vibratory pile driving model tests in water-saturated sand is presented. The predicted pile penetration using this approachis in good agreement with the results of the model tests as well as with fully Lagrangian simulations. In terms of pore water pressure, however, the results of the CEL simulation show a slightly worse accordance with the model tests compared to the Lagrangian simulation. Some shortcomings of the hydro-mechanically coupled CEL method in case of frictional contact problems and pore fluids with high bulk modulus are discussed. Lastly, the CEL method is applied to the simulation of vibratory driving of open-profile piles under partially drained conditions to study installation-induced changes in the soil state. It is concluded that the proposed method is capable of realistically reproducing the most important mechanisms in the soil during the driving process despite its addressed shortcomings.
One of the most important subjects of hydraulic engineering is the reliable estimation of the transverse distribution in the rectangular channel of bed and wall shear stresses. This study makes use of the Tsallis entropy, genetic programming (GP) and adaptive neuro-fuzzy inference system (ANFIS) methods to assess the shear stress distribution (SSD) in the rectangular channel.
To evaluate the results of the Tsallis entropy, GP and ANFIS models, laboratory observations were used in which shear stress was measured using an optimized Preston tube. This is then used to measure the SSD in various aspect ratios in the rectangular channel. To investigate the shear stress percentage, 10 data series with a total of 112 different data for were used. The results of the sensitivity analysis show that the most influential parameter for the SSD in smooth rectangular channel is the dimensionless parameter B/H, Where the transverse coordinate is B, and the flow depth is H. With the parameters (b/B), (B/H) for the bed and (z/H), (B/H) for the wall as inputs, the modeling of the GP was better than the other one. Based on the analysis, it can be concluded that the use of GP and ANFIS algorithms is more effective in estimating shear stress in smooth rectangular channels than the Tsallis entropy-based equations.
This study proposes an efficient Bayesian, frequency-based damage identification approach to identify damages in cantilever structures with an acceptable error rate, even at high noise levels. The catenary poles of electric high-speed train systems were selected as a realistic case study to cover the objectives of this study. Compared to other frequency-based damage detection approaches described in the literature, the proposed approach is efficiently able to detect damages in cantilever structures to higher levels of damage detection, namely identifying both the damage location and severity using a low-cost structural health monitoring (SHM) system with a limited number of sensors; for example, accelerometers. The integration of Bayesian inference, as a stochastic framework, in the proposed approach, makes it possible to utilize the benefit of data fusion in merging the informative data from multiple damage features, which increases the quality and accuracy of the results. The findings provide the decision-maker with the information required to manage the maintenance, repair, or replacement procedures.
Biofeedback constitutes a well-established, non-invasive method to voluntary interfere in emotional processing by means of cognitive strategies. However, treatment durations exhibit strong inter-individual variations and first successes can often be achieved only after a large number of sessions. Sham feedback constitutes a rather untapped approach by providing feedback that does not correspond to the participant’s actual state. The current study aims to gain insights into mechanisms of sham feedback processing in order to support new techniques in biofeedback therapy. We carried out two experiments and applied different types of sham feedback on skin conductance responses and pupil size changes during affective processing. Results indicate that standardized but context-sensitive sham signals based on skin conductance responses exert a stronger influence on emotional regulation compared to individual sham feedback from ongoing pupil dynamics. Also, sham feedback should forego unnatural signal behavior to avoid irritation and skepticism among participants. Altogether, a reasonable combination of stimulus features and sham feedback characteristics enables to considerably reduce the actual bodily responsiveness already within a single session.
This paper outlines an important step in characterizing a novel field of robotic construction research where a cable-driven parallel robot is used to extrude cementitious material in three-dimensional space, and thus offering a comprehensive new approach to computational design and construction, and to robotic fabrication at larger scales. Developed by the Faculty of Art and Design at Bauhaus-University Weimar (Germany), the faculty of Architecture at the University of Applied Sciences Dortmund (Germany) and the Chair of Mechatronics at the University of Duisburg-Essen (Germany), this approach offers unique advantages over existing additive manufacturing methods: the system is easily transportable and scalable, it does not require additional formwork or scaffolding, and it offers digital integration and informational oversight across the entire design and building process. This paper considers 1) key research components of cable robotic 3D-printing (such as computational design, material exploration, and robotic control), and 2) the integration of these parameters into a unified design and building process. The demonstration of the approach at full-scale is of particular concern.
This article aims to develop a social theory of violence that emphasizes the role of the third party as well as the communication between the involved subjects. For this Teresa Koloma Beck’s essay ‘The Eye of the Beholder: Violence as a Social Process’ is taken as a starting point, which adopts a social-constructivist perspective. On the one hand, the basic concepts and the benefits of this approach are presented. On the other hand, social-theoretical problems of this approach are revealed. These deficits are counteracted by expanding Koloma Beck’s approach with a communicative-constructivist framework. Thus, the role of communicative action and the ‘objectification of violence’ is emphasized. These aspects impact the perception, judgement and (de-)legitimation of violence phenomena and the emergence of a ‘knowledge of violence’. Communicative actions and objectifications form a key to understanding violent interactions and the link between the micro and macro levels. Finally, the methodological consequences for the research of violence and Communicative Constructivism are discussed. Furthermore, possible research fields are outlined, which open up by looking at communicative action and the objectifications within the ‘triads of violence’.
Zu den diversen Unternehmungen sozialbewegter „Gegenwissenschaft“, die um 1980 auf der Bildfläche der BRD erschienen, zählte der 1982 gegründete Berliner Wissenschaftsladen e. V., kurz WILAB – eine Art „alternatives“ Spin-off der Technischen Universität Berlin. Der vorliegende Beitrag situiert die Ausgründung des „Ladens“ im Kontext zeitgenössischer Fortschritte der (regionalen) Forschungs- und Technologiepolitik. Gezeigt wird, wie der deindustrialisierenden Inselstadt, qua „innovationspolitischer“ Gegensteuerung, dabei sogar eine gewisse Vorreiterrolle zukam: über die Stadtgrenzen hinaus sichtbare Neuerungen wie die Gründermesse BIG TECH oder das 1983 eröffnete Berliner Innovations- und Gründerzentrum (BIG), der erste „Incubator“ [sic] der BRD, etwa gingen auf das Konto der 1977/78 lancierten Technologie-Transferstelle der TU Berlin, TU-transfer.
Anders gesagt: tendenziell bekam man es hier nun mit Verhältnissen zu tun, die immer weniger mit den Träumen einer „kritischen“, nicht-fremdbestimmten (Gegen‑)Wissenschaft kompatibel waren. Latent konträr zur historiographischen Prominenz des wissenschaftskritischen Zeitgeists fristeten „alternativen“ Zielsetzungen verpflichtete Unternehmungen wie „WILAB“ ein relativ marginalisiertes Nischendasein. Dennoch wirft das am WILAB verfolgte, so gesehen wenig aussichtsreiche Anliegen, eine andere, nämlich „humanere“ Informationstechnologie in die Wege zu leiten, ein instruktives Licht auf die Aufbrüche „unternehmerischer“ Wissenschaft in der BRD um 1980.
Object-Oriented Damage Information Modeling Concepts and Implementation for Bridge Inspection
(2022)
Bridges are designed to last for more than 50 years and consume up to 50% of their life-cycle costs during their operation phase. Several inspections and assessment actions are executed during this period. Bridge and damage information must be gathered, digitized, and exchanged between different stakeholders. Currently, the inspection and assessment practices rely on paper-based data collection and exchange, which is time-consuming and error-prone, and leads to loss of information. Storing and exchanging damage and building information in a digital format may lower costs and errors during inspection and assessment and support future needs, for example, immediate simulations regarding performance assessment, automated maintenance planning, and mixed reality inspections. This study focused on the concept for modeling damage information to support bridge reviews and structural analysis. Starting from the definition of multiple use cases and related requirements, the data model for damage information is defined independently from the subsequent implementation. In the next step, the implementation via an established standard is explained. Functional tests aim to identify problems in the concept and implementation. To show the capability of the final model, two example use cases are illustrated: the inspection review of the entire bridge and a finite-element analysis of a single component. Main results are the definition of necessary damage data, an object-oriented damage model, which supports multiple use cases, and the implementation of the model in a standard. Furthermore, the tests have shown that the standard is suitable to deliver damage information; however, several software programs lack proper implementation of the standard.
Quantification of cracks in concrete thin sections considering current methods of image analysis
(2022)
Image analysis is used in this work to quantify cracks in concrete thin sections via modern image processing. Thin sections were impregnated with a yellow epoxy resin, to increase the contrast between voids and other phases of the concrete. By the means of different steps of pre-processing, machine learning and python scripts, cracks can be quantified in an area of up to 40 cm2. As a result, the crack area, lengths and widths were estimated automatically within a single workflow. Crack patterns caused by freeze-thaw damages were investigated. To compare the inner degradation of the investigated thin sections, the crack density was used. Cracks in the thin sections were measured manually in two different ways for validation of the automatic determined results. On the one hand, the presented work shows that the width of cracks can be determined pixelwise, thus providing the plot of a width distribution. On the other hand, the automatically measured crack length differs in comparison to the manually measured ones.
In this paper, we present an open-source code for the first-order and higher-order nonlocal operator method (NOM) including a detailed description of the implementation. The NOM is based on so-called support, dual-support, nonlocal operators, and an operate energy functional ensuring stability. The nonlocal operator is a generalization of the conventional differential operators. Combined with the method of weighed residuals and variational principles, NOM establishes the residual and tangent stiffness matrix of operate energy functional through some simple matrix without the need of shape functions as in other classical computational methods such as FEM. NOM only requires the definition of the energy drastically simplifying its implementation. The implementation in this paper is focused on linear elastic solids for sake of conciseness through the NOM can handle more complex nonlinear problems. The NOM can be very flexible and efficient to solve partial differential equations (PDEs), it’s also quite easy for readers to use the NOM and extend it to solve other complicated physical phenomena described by one or a set of PDEs. Finally, we present some classical benchmark problems including the classical cantilever beam and plate-with-a-hole problem, and we also make an extension of this method to solve complicated problems including phase-field fracture modeling and gradient elasticity material.
In this study, we propose a nonlocal operator method (NOM) for the dynamic analysis of (thin) Kirchhoff plates. The nonlocal Hessian operator is derived based on a second-order Taylor series expansion. The NOM does not require any shape functions and associated derivatives as ’classical’ approaches such as FEM, drastically facilitating the implementation. Furthermore, NOM is higher order continuous, which is exploited for thin plate analysis that requires C1 continuity. The nonlocal dynamic governing formulation and operator energy functional for Kirchhoff plates are derived from a variational principle. The Verlet-velocity algorithm is used for the time discretization. After confirming the accuracy of the nonlocal Hessian operator, several numerical examples are simulated by the nonlocal dynamic Kirchhoff plate formulation.
We present a stochastic deep collocation method (DCM) based on neural architecture search (NAS) and transfer learning for heterogeneous porous media. We first carry out a sensitivity analysis to determine the key hyper-parameters of the network to reduce the search space and subsequently employ hyper-parameter optimization to finally obtain the parameter values. The presented NAS based DCM also saves the weights and biases of the most favorable architectures, which is then used in the fine-tuning process. We also employ transfer learning techniques to drastically reduce the computational cost. The presented DCM is then applied to the stochastic analysis of heterogeneous porous material. Therefore, a three dimensional stochastic flow model is built providing a benchmark to the simulation of groundwater flow in highly heterogeneous aquifers. The performance of the presented NAS based DCM is verified in different dimensions using the method of manufactured solutions. We show that it significantly outperforms finite difference methods in both accuracy and computational cost.
In machine learning, if the training data is independently and identically distributed as the test data then a trained model can make an accurate predictions for new samples of data. Conventional machine learning has a strong dependence on massive amounts of training data which are domain specific to understand their latent patterns. In contrast, Domain adaptation and Transfer learning methods are sub-fields within machine learning that are concerned with solving the inescapable problem of insufficient training data by relaxing the domain dependence hypothesis. In this contribution, this issue has been addressed and by making a novel combination of both the methods we develop a computationally efficient and practical algorithm to solve boundary value problems based on nonlinear partial differential equations. We adopt a meshfree analysis framework to integrate the prevailing geometric modelling techniques based on NURBS and present an enhanced deep collocation approach that also plays an important role in the accuracy of solutions. We start with a brief introduction on how these methods expand upon this framework. We observe an excellent agreement between these methods and have shown that how fine-tuning a pre-trained network to a specialized domain may lead to an outstanding performance compare to the existing ones. As proof of concept, we illustrate the performance of our proposed model on several benchmark problems.
In this work, we present a deep collocation method (DCM) for three-dimensional potential problems in non-homogeneous media. This approach utilizes a physics-informed neural network with material transfer learning reducing the solution of the non-homogeneous partial differential equations to an optimization problem. We tested different configurations of the physics-informed neural network including smooth activation functions, sampling methods for collocation points generation and combined optimizers. A material transfer learning technique is utilized for non-homogeneous media with different material gradations and parameters, which enhance the generality and robustness of the proposed method. In order to identify the most influential parameters of the network configuration, we carried out a global sensitivity analysis. Finally, we provide a convergence proof of our DCM. The approach is validated through several benchmark problems, also testing different material variations.
Subscription-based news platforms (such as “Apple News+” or “Readly”) that bundle content from different publishers into one comprehensive package and offer it to media users at a fixed monthly rate are a new way of accessing and consuming digital journalism. These services have received little attention in journalism studies, although they differ greatly from traditional media products and distribution channels. This article empirically investigates the perception of journalism platforms based on eight qualitative focus group discussions with 55 German news consumers.
Results show that the central characteristics these platforms should fulfill in order to attract users are strikingly similar to the characteristics of media platforms from the music and video industries, in particular regarding price points, contract features, and modes of usage. Against this background, the potential and perspectives of a subscription-based news platform for journalism’s societal role are discussed.
Immanuel Kant’s thought is a central historical and theoretical reference in Hans Blumenberg’s metaphorological project. This is demonstrated by the fact that in the Paradigms the author outlines the concept of absolute metaphor by explicitly referring to §59 of the Critique of the Power of Judgment and recognizing in the Kantian symbol a model for his own metaphorics. However, Kant’s name also appears in the chapter on the metaphor of the “terra incognita” that not only did he theorize the presence of symbolic hypotyposis in our language [...] but also made extensive use of metaphors linked to “determinate historical experiences”. In particular: geographical metaphors. In my essay, I would like to start from the analysis of Kant’s geographical metaphors in order to try to rethink Blumenberg’s archaeological method as an archaeology of media that grounds the study of metaphors in the materiality of communication and the combination of tools, agents and media.
Real-world labs hold the potential to catalyse rapid urban transformations through real-world experimentation. Characterised by a rather radical, responsive, and location-specific nature, real-world labs face constraints in the scaling of experimental knowledge. To make a significant contribution to urban transformation, the produced knowledge must go beyond the level of a building, street, or small district where real-world experiments are conducted. Thus, a conflict arises between experimental boundaries and the stimulation of broader implications. The challenges of scaling experimental knowledge have been recognised as a problem, but remain largely unexplained. Based on this, the article will discuss the applicability of the “typology of amplification processes” by Lam et al. (2020) to explore and evaluate the potential of scaling experimental knowledge from real-world labs. The application of the typology is exemplified in the case of the Bauhaus.MobilityLab. The Bauhaus.MobilityLab takes a unique approach by testing and developing cross-sectoral mobility, energy, and logistics solutions with a distinct focus on scaling knowledge and innovation. For this case study, different qualitative research techniques are combined according to “within-method triangulation” and synthesised in a strengths, weaknesses, opportunities, and threats (SWOT) analysis. The analysis of the Bauhaus.MobilityLab proves that the “typology of amplification processes” is useful as a systematic approach to identifying and evaluating the potential of scaling experimental knowledge.
For the safe and efficient operation of dams, frequent monitoring and maintenance are required. These are usually expensive, time consuming, and cumbersome. To alleviate these issues, we propose applying a wave-based scheme for the location and quantification of damages in dams.
To obtain high-resolution “interpretable” images of the damaged regions, we drew inspiration from non-linear full-multigrid methods for inverse problems and applied a new cyclic multi-stage full-waveform inversion (FWI) scheme. Our approach is less susceptible to the stability issues faced by the standard FWI scheme when dealing with ill-posed problems. In this paper, we first selected an optimal acquisition setup and then applied synthetic data to demonstrate the capability of our approach in identifying a series of anomalies in dams by a mixture of reflection and transmission tomography. The results had sufficient robustness, showing the prospects of application in the field of non-destructive testing of dams.
In this work, the degradation performance for the photocatalytic oxidation of eight micropollutants (amisulpride, benzotriazole, candesartan, carbamazepine, diclofenac, gabapentin, methlybenzotriazole, and metoprolol) within real secondary effluent was investigated using three different reactor designs. For all reactor types, the influence of irradiation power on its reaction rate and energetic efficiency was investigated. Flat cell and batch reactor showed almost similar substance specific degradation behavior. Within the immersion rotary body reactor, benzotriazole and methylbenzotriazole showed a significantly lower degradation affinity. The flat cell reactor achieved the highest mean degradation rate, with half time values ranging from 5 to 64 min with a mean of 18 min, due to its high catalysts surface to hydraulic volume ratio. The EE/O values were calculated for all micro-pollutants as well as the mean degradation rate constant of each experimental step. The lowest substance specific energy per order (EE/O) values of 5 kWh/m3 were measured for benzotriazole within the batch reactor. The batch reactor also reached the lowest mean values (11.8–15.9 kWh/m3) followed by the flat cell reactor (21.0–37.0 kWh/m3) and immersion rotary body reactor (23.9–41.0 kWh/m3). Catalyst arrangement and irradiation power were identified as major influences on the energetic performance of the reactors. Low radiation intensities as well as the use of submerged catalyst arrangement allowed a reduction in energy demand by a factor of 3–4. A treatment according to existing treatment goals of wastewater treatment plants (80% total degradation) was achieved using the batch reactor with a calculated energy demand of 7000 Wh/m3.
One of the most important renewable energy technologies used nowadays are wind power turbines. In this paper, we are interested in identifying the operating status of wind turbines, especially rotor blades, by means of multiphysical models. It is a state-of-the-art technology to test mechanical structures with ultrasonic-based methods. However, due to the density and the required high resolution, the testing is performed with high-frequency waves, which cannot penetrate the structure in depth. Therefore, there is a need to adopt techniques in the fields of multiphysical model-based inversion schemes or data-driven structural health monitoring. Before investing effort in the development of such approaches, further insights and approaches are necessary to make the techniques applicable to structures such as wind power plants (blades). Among the expected developments, further accelerations of the so-called “forward codes” for a more efficient implementation of the wave equation could be envisaged. Here, we employ electromagnetic waves for the early detection of cracks. Because in many practical situations, it is not possible to apply techniques from tomography (characterized by multiple sources and sensor pairs), we focus here on the question of whether the existence of cracks can be determined by using only one source for the sent waves.
The goal of architecture is changing in response to the expanding role of cities, rapid urbanization, and transformation under changing economic, environmental, social, and demographic factors. As cities increased in the early modern era, overcrowding, urbanization, and pollution conditions led reformers to consider the future shape of the cities. One of the most critical topics in contemporary architecture is the subject of the future concepts of living. In most cases, domed cities, as a future concept of living, are rarely considered, and they are used chiefly as “utopian” visions in the discourse of future ways of living. This paper highlights the reviews of domed cities to deepen the understanding of the idea in practice, like its approach in terms of architecture. The main aim of this paper is to provide a broad overview for domed cities in the face of pollution as one of the main concerns in many European cities. As a result, the significance of the reviews of the existing projects is focused on their conceptual quality. This review will pave the way for further studies in terms of future developments in the realm of domed cities. In this paper, the city of Celje, one of the most polluted cities in Slovenia, is taken as a case study for considering the concept of Dome incorporated due to the lack of accessible literature on the topic. This review’s primary contribution is to allow architects to explore a broad spectrum of innovation by comparing today’s achievable statuses against the possibilities generated by domed cities. As a result of this study, the concept of living under the Dome remains to be developed in theory and practice. The current challenging climatic situation will accelerate the evolution of these concepts, resulting in the formation of new typologies, which are a requirement for humanity.
Bolted connections are widely employed in structures like transmission poles, wind turbines, and television (TV) towers. The behaviour of bolted connections is often complex and plays a significant role in the overall dynamic characteristics of the structure. The goal of this work is to conduct a fatigue lifecycle assessment of such a bolted connection block of a 193 m tall TV tower, for which 205 days of real measurement data have been obtained from the installed monitoring devices. Based on the recorded data, the best-fit stochastic wind distribution for 50 years, the decisive wind action, and the locations to carry out the fatigue analysis have been decided. A 3D beam model of the entire tower is developed to extract the nodal forces corresponding to the connection block location under various mean wind speeds, which is later coupled with a detailed complex finite element model of the connection block, with over three million degrees of freedom, for acquiring stress histories on some pre-selected bolts. The random stress histories are analysed using the rainflow counting algorithm (RCA) and the damage is estimated using Palmgren-Miner's damage accumulation law. A modification is proposed to integrate the loading sequence effect into the RCA, which otherwise is ignored, and the differences between the two RCAs are investigated in terms of the accumulated damage.
The floods in 2002 and 2013, as well as the recent flood of 2021, caused billions Euros worth of property damage in Germany. The aim of the project Innovative Vulnerability and Risk Assessment of Urban Areas against Flood Events (INNOVARU) involved the development of a practicable flood damage model that enables realistic damage statements for the residential building stock. In addition to the determination of local flood risks, it also takes into account the vulnerability of individual buildings and allows for the prognosis of structural damage. In this paper, we discuss an improved method for the prognosis of structural damage due to flood impact. Detailed correlations between inundation level and flow velocities depending on the vulnerability of the building types, as well as the number of storeys, are considered. Because reliable damage data from events with high flow velocities were not available, an innovative approach was adopted to cover a wide range of flow velocities. The proposed approach combines comprehensive damage data collected after the 2002 flood in Germany with damage data of the 2011 Tohoku earthquake tsunami in Japan. The application of the developed methods enables a reliable reinterpretation of the structural damage caused by the August flood of 2002 in six study areas in the Free State of Saxony.
A safe and economic structural design based on the semi-probabilistic concept requires statistically representative safety elements, such as characteristic values, design values, and partial safety factors. Regarding climate loads, the safety levels of current design codes strongly reflect experiences based on former measurements and investigations assuming stationary conditions, i.e. involving constant frequencies and intensities. However, due to climate change, occurrence of corresponding extreme weather events is expected to alter in the future influencing the reliability and safety of structures and their components. Based on established approaches, a systematically refined data-driven methodology for the determination of design parameters considering nonstationarity as well as standardized targets of structural reliability or safety, respectively, is therefore proposed. The presented procedure picks up fundamentals of European standardization and extends them with respect to nonstationarity by applying a shifting time window method. Taking projected snow loads into account, the application of the method is exemplarily demonstrated and various influencing parameters are discussed.
Design-related reassessment of structures integrating Bayesian updating of model safety factors
(2022)
In the semi-probabilistic approach of structural design, the partial safety factors are defined by considering some degree of uncertainties to actions and resistance, associated with the parameters’ stochastic nature. However, uncertainties for individual structures can be better examined by incorporating measurement data provided by sensors from an installed health monitoring scheme. In this context, the current study proposes an approach to revise the partial safety factor for existing structures on the action side, γE by integrating Bayesian model updating. A simple numerical example of a beam-like structure with artificially generated measurement data is used such that the influence of different sensor setups and data uncertainties on revising the safety factors can be investigated. It is revealed that the health monitoring system can reassess the current capacity reserve of the structure by updating the design safety factors, resulting in a better life cycle assessment of structures. The outcome is furthermore verified by analysing a real life small railway steel bridge ensuring the applicability of the proposed method to practical applications.
Determining the earthquake hazard of any settlement is one of the primary studies for reducing earthquake damage. Therefore, earthquake hazard maps used for this purpose must be renewed over time. Turkey Earthquake Hazard Map has been used instead of Turkey Earthquake Zones Map since 2019. A probabilistic seismic hazard was performed by using these last two maps and different attenuation relationships for Bitlis Province (Eastern Turkey) were located in the Lake Van Basin, which has a high seismic risk. The earthquake parameters were determined by considering all districts and neighborhoods in the province. Probabilistic seismic hazard analyses were carried out for these settlements using seismic sources and four different attenuation relationships. The obtained values are compared with the design spectrum stated in the last two earthquake maps. Significant differences exist between the design spectrum obtained according to the different exceedance probabilities. In this study, adaptive pushover analyses of sample-reinforced concrete buildings were performed using the design ground motion level. Structural analyses were carried out using three different design spectra, as given in the last two seismic design codes and the mean spectrum obtained from attenuation relationships. Different design spectra significantly change the target displacements predicted for the performance levels of the buildings.
The seismic vulnerability assessment of existing reinforced concrete (RC) buildings is a significant source of disaster mitigation plans and rescue services. Different countries evolved various Rapid Visual Screening (RVS) techniques and methodologies to deal with the devastating consequences of earthquakes on the structural characteristics of buildings and human casualties. Artificial intelligence (AI) methods, such as machine learning (ML) algorithm-based methods, are increasingly used in various scientific and technical applications. The investigation toward using these techniques in civil engineering applications has shown encouraging results and reduced human intervention, including uncertainties and biased judgment. In this study, several known non-parametric algorithms are investigated toward RVS using a dataset employing different earthquakes. Moreover, the methodology encourages the possibility of examining the buildings’ vulnerability based on the factors related to the buildings’ importance and exposure. In addition, a web-based application built on Django is introduced. The interface is designed with the idea to ease the seismic vulnerability investigation in real-time. The concept was validated using two case studies, and the achieved results showed the proposed approach’s potential efficiency
In the wake of the news industry’s digitization, novel organizations that differ considerably from traditional media firms in terms of their functional roles and organizational practices of media work are emerging. One new type is the field repair organization, which is characterized by supporting high‐quality media work to compensate for the deficits (such as those which come from cost savings and layoffs) which have become apparent in legacy media today. From a practice‐theoretical research perspective and based on semi‐structured interviews, virtual field observations, and document analysis, we have conducted a single case study on Science Media Center Germany (SMC), a unique non‐profit news start‐up launched in 2016 in Cologne, Germany. Our findings show that, in addition to field repair activities, SMC aims to facilitate progress and innovation in the field, which we refer to as field advancement. This helps to uncover emerging needs and anticipates problems before they intensify or even occur, proactively providing products and tools for future journalism. This article contributes to our understanding of novel media organizations with distinct functions in the news industry, allowing for advancements in theory on media work and the organization of journalism in times of digital upheaval.
Paper-based data acquisition and manual transfer between incompatible software or data formats during inspections of bridges, as done currently, are time-consuming, error-prone, cumbersome, and lead to information loss. A fully digitized workflow using open data formats would reduce data loss, efforts, and the costs of future inspections. On the one hand, existing studies proposed methods to automatize data acquisition and visualization for inspections. These studies lack an open standard to make the gathered data available for other processes. On the other hand, several studies discuss data structures for exchanging damage information among different stakeholders. However, those studies do not cover the process of automatic data acquisition and transfer. This study focuses on a framework that incorporates automatic damage data acquisition, transfer, and a damage information model for data exchange. This enables inspectors to use damage data for subsequent analyses and simulations. The proposed framework shows the potentials for a comprehensive damage information model and related (semi-)automatic data acquisition and processing.
This dataset presents the numerical analysis of the heat and moisture transport through a facade equipped with a living wall system designated for greywater treatment. While such greening systems provide many environmental benefits, they involve pumping large quantities of water onto the wall assembly, which can increase the risk of moisture in the wall as well as impaired energetic performance due to increased thermal conductivity with increased moisture content in the building materials. This dataset was acquired through numerical simulation using the coupling of two simulation tools, namely Envi-Met and Delphin. This coupling was used to include the complex role the plants play in shaping the near-wall environmental parameters in the hygrothermal simulations. Four different wall assemblies were investigated, each assembly was assessed twice: with and without the living wall. The presented data include the input and output parameters of the simulations, which were presented in the co-submitted article [1].
Der Aufruf, die Begriffe Stadt und Kritik in das Zentrum einer Debatte zu stellen, bietet die große Chance, uns weit über begriffliche Klärungen unseres gemeinsamen Arbeitsgegenstands hinaus – die ja auch für sich selbst sehr fruchtbar sein können – über die Funktion zu verständigen, die wir in der Gesellschaft ausüben, wenn wir räumliche Planung praktizieren, erforschen und lehren. Da in der Bundesrepublik nicht nur ein großer Bedarf, sondern auch eine beträchtliche Nachfrage nach öffentlicher Planung besteht und die planungsbezogenen Wissenschaften sich eines insgesamt stabilen institutionellen Standes erfreuen, laufen wir Gefahr, die gesellschaftspolitische Legitimation von Berufsfeld und Wissenschaft zu vernachlässigen, sie als gegeben zu behandeln. Wir müssen uns ja kaum rechtfertigen.
Multi-criteria decision analysis (MCDA) is an established methodology to support the decision-making of multi-objective problems. For conducting an MCDA, in most cases, a set of objectives (SOO) is required, which consists of a hierarchical structure comprised of objectives, criteria, and indicators. The development of an SOO is usually based on moderated development processes requiring high organizational and cognitive effort from all stakeholders involved. This article proposes elementary interactions as a key paradigm of an algorithm-driven development process for an SOO that requires little moderation efforts. Elementary interactions are self-contained information requests that may be answered with little cognitive effort. The pairwise comparison of elements in the well-known analytical hierarchical process (AHP) is an example of an elementary interaction. Each elementary interaction in the development process presented contributes to the stepwise development of an SOO. Based on the hypothesis that an SOO may be developed exclusively using elementary interactions (EIs), a concept for a multi-user platform is proposed. Essential components of the platform are a Model Aggregator, an Elementary Interaction Stream Generator, a Participant Manager, and a Discussion Forum. While the latter component serves the professional exchange of the participants, the first three components are intended to be automatable by algorithms. The platform concept proposed has been evaluated partly in an explorative validation study demonstrating the general functionality of the algorithms outlined. In summary, the platform concept suggested demonstrates the potential to ease SOO development processes as the platform concept does not restrict the application domain; it is intended to work with little administration moderation efforts, and it supports the further development of an existing SOO in the event of changes in external conditions. The algorithm-driven development of SOOs proposed in this article may ease the development of MCDA applications and, thus, may have a positive effect on the spread of MCDA applications.
Operator Calculus Approach to Comparison of Elasticity Models for Modelling of Masonry Structures
(2022)
The solution of any engineering problem starts with a modelling process aimed at formulating a mathematical model, which must describe the problem under consideration with sufficient precision. Because of heterogeneity of modern engineering applications, mathematical modelling scatters nowadays from incredibly precise micro- and even nano-modelling of materials to macro-modelling, which is more appropriate for practical engineering computations. In the field of masonry structures, a macro-model of the material can be constructed based on various elasticity theories, such as classical elasticity, micropolar elasticity and Cosserat elasticity. Evidently, a different macro-behaviour is expected depending on the specific theory used in the background. Although there have been several theoretical studies of different elasticity theories in recent years, there is still a lack of understanding of how modelling assumptions of different elasticity theories influence the modelling results of masonry structures. Therefore, a rigorous approach to comparison of different three-dimensional elasticity models based on quaternionic operator calculus is proposed in this paper. In this way, three elasticity models are described and spatial boundary value problems for these models are discussed. In particular, explicit representation formulae for their solutions are constructed. After that, by using these representation formulae, explicit estimates for the solutions obtained by different elasticity theories are obtained. Finally, several numerical examples are presented, which indicate a practical difference in the solutions.
It is widely accepted that most people spend the majority of their lives indoors. Most individuals do not realize that while indoors, roughly half of heat exchange affecting their thermal comfort is in the form of thermal infrared radiation. We show that while researchers have been aware of its thermal comfort significance over the past century, systemic error has crept into the most common evaluation techniques, preventing adequate characterization of the radiant environment. Measuring and characterizing radiant heat transfer is a critical component of both building energy efficiency and occupant thermal comfort and productivity. Globe thermometers are typically used to measure mean radiant temperature (MRT), a commonly used metric for accounting for the radiant effects of an environment at a point in space. In this paper we extend previous field work to a controlled laboratory setting to (1) rigorously demonstrate that existing correction factors used in the American Society of Heating Ventilation and Air-conditioning Engineers (ASHRAE) Standard 55 or ISO7726 for using globe thermometers to quantify MRT are not sufficient; (2) develop a correction to improve the use of globe thermometers to address problems in the current standards; and (3) show that mean radiant temperature measured with ping-pong ball-sized globe thermometers is not reliable due to a stochastic convective bias. We also provide an analysis of the maximum precision of globe sensors themselves, a piece missing from the domain in contemporary literature.
Data acquisition systems and methods to capture high-resolution images or reconstruct 3D point clouds of existing structures are an effective way to document their as-is condition. These methods enable a detailed analysis of building surfaces, providing precise 3D representations. However, for the condition assessment and documentation, damages are mainly annotated in 2D representations, such as images, orthophotos, or technical drawings, which do not allow for the application of a 3D workflow or automated comparisons of multitemporal datasets. In the available software for building heritage data management and analysis, a wide range of annotation and evaluation functions are available, but they also lack integrated post-processing methods and systematic workflows. The article presents novel methods developed to facilitate such automated 3D workflows and validates them on a small historic church building in Thuringia, Germany. Post-processing steps using photogrammetric 3D reconstruction data along with imagery were implemented, which show the possibilities of integrating 2D annotations into 3D documentations. Further, the application of voxel-based methods on the dataset enables the evaluation of geometrical changes of multitemporal annotations in different states and the assignment to elements of scans or building models. The proposed workflow also highlights the potential of these methods for condition assessment and planning of restoration work, as well as the possibility to represent the analysis results in standardised building model formats.
This dataset consists mainly of two subsets. The first subset includes measurements and simulation data conducted to validate the simulation tool ENVI-met. The measurements were conducted at the campus of the Bauhaus-University Weimar in Weimar, Germany and consisted of recording exterior air temperature, globe temperature, relative humidity, and wind velocity at 1.5 m at four points on four different days. After the measurements, the geometry of the campus was modelled and meshed; the simulations were conducted using the weather data of the measurements days with the aim of investigating the accuracy of the model.
The second data subset consists of ENVI-met simulation data of the potential of facade greening in improving the outdoor environment and the indoor air temperature during heatwaves in Central European cities. The data consist of the boundary conditions and the simulation output of two simulation models: with and without facade greening. The geometry of the models corresponded to a residential buildings district in Stuttgart, Germany. The simulation output consisted of exterior air temperature, mean radiant temperature, relative humidity, and wind velocity at 12 different probe points in the model in addition to the indoor air temperature of an exemplary building. The dataset presents both vertical profiles of the probed parameters as well as the time series output of the five-day simulation duration. Both data subsets correspond to the investigations presented in the co-submitted article [1].
The fracture of microcapsules is an important issue to release the healing agent for healing the cracks in encapsulation-based self-healing concrete. The capsular clustering generated from the concrete mixing process is considered one of the critical factors in the fracture mechanism. Since there is a lack of studies in the literature regarding this issue, the design of self-healing concrete cannot be made without an appropriate modelling strategy. In this paper, the effects of microcapsule size and clustering on the fractured microcapsules are studied computationally. A simple 2D computational modelling approach is developed based on the eXtended Finite Element Method (XFEM) and cohesive surface technique. The proposed model shows that the microcapsule size and clustering have significant roles in governing the load-carrying capacity and the crack propagation pattern and determines whether the microcapsule will be fractured or debonded from the concrete matrix. The higher the microcapsule circumferential contact length, the higher the load-carrying capacity. When it is lower than 25% of the microcapsule circumference, it will result in a greater possibility for the debonding of the microcapsule from the concrete. The greater the core/shell ratio (smaller shell thickness), the greater the likelihood of microcapsules being fractured.
Im Heft zum zehnjährigen Jubiläum von sub\urban mit dem Themenschwerpunkt „sub\x: Verortungen, Entortungen" veröffentlichen wir eine Debatte, die von den bisherigen in unserer Zeitschrift in dieser Rubrik geführten textlichen Diskussionen abweicht. Im Vorfeld der Planungen für unsere Jubiläumsausgabe haben wir die aktuellen Mitglieder unseres wissenschaftlichen Beirats darum gebeten, zwei grundlegende Fragen von kritischer Stadtforschung in kurzen Beiträgen zu diskutieren: Was ist Stadt? Was ist Kritik?
Multi-criteria decision analysis (MCDA) is an established methodology to support the decision-making of multi-objective problems. For conducting an MCDA, in most cases, a set of objectives (SOO) is required, which consists of a hierarchical structure comprised of objectives, criteria, and indicators. The development of an SOO is usually based on moderated development processes requiring high organizational and cognitive effort from all stakeholders involved. This article proposes elementary interactions as a key paradigm of an algorithm-driven development process for an SOO that requires little moderation efforts. Elementary interactions are self-contained information requests that may be answered with little cognitive effort. The pairwise comparison of elements in the well-known analytical hierarchical process (AHP) is an example of an elementary interaction. Each elementary interaction in the development process presented contributes to the stepwise development of an SOO. Based on the hypothesis that an SOO may be developed exclusively using elementary interactions (EIs), a concept for a multi-user platform is proposed. Essential components of the platform are a Model Aggregator, an Elementary Interaction Stream Generator, a Participant Manager, and a Discussion Forum. While the latter component serves the professional exchange of the participants, the first three components are intended to be automatable by algorithms. The platform concept proposed has been evaluated partly in an explorative validation study demonstrating the general functionality of the algorithms outlined. In summary, the platform concept suggested demonstrates the potential to ease SOO development processes as the platform concept does not restrict the application domain; it is intended to work with little administration moderation efforts, and it supports the further development of an existing SOO in the event of changes in external conditions. The algorithm-driven development of SOOs proposed in this article may ease the development of MCDA applications and, thus, may have a positive effect on the spread of MCDA applications.
Plastic structural analysis may be applied without any difficulty and with little effort for structural member verifications with regard to lateral torsional buckling of doubly symmetric rolled I sections. Suchlike analyses can be performed based on the plastic zone theory, specifically using finite beam elements with seven degrees of freedom and 2nd order theory considering material nonlinearity. The existing Eurocode enables these approaches and the coming-up generation will provide corresponding regulations in EN 1993-1-14. The investigations allow the determination of computationally accurate limit loads, which are determined in the present paper for selected structural systems with different sets of parameters, such as length, steel grade and cross section types. The results are compared to approximations gained by more sophisticated FEM analyses (commercial software Ansys Workbench applying solid elements) for reasons of verification/validation. In this course, differences in the results of the numerical models are addressed and discussed. In addition, results are compared to resistances obtained by common design regulations based on reduction factors χlt including regulations of EN 1993-1-1 (including German National Annex) as well as prEN 1993-1-1: 2020-08 (proposed new Eurocode generation). Concluding, correlations of results and their advantages as well as disadvantages are discussed.
Vertical green system for gray water treatment: Analysis of the VertiKKA-module in a field test
(2022)
This work presents a modular Vertical Green System (VGS) for gray water treatment, developed at the Bauhaus-Universität Weimar. The concept was transformed into a field study with four modules built and tested with synthetic gray water. Each module set contains a small and larger module with the same treatment substrate and was fed hourly. A combination of lightweight structural material and biochar of agricultural residues and wood chips was used as the treatment substrate. In this article, we present the first 18 weeks of operation. Regarding the treatment efficiency, the parameters chemical oxygen demand (COD), total phosphorous (TP), ortho-phosphate (ortho-P), total bound nitrogen (TNb), ammonium nitrogen (NH4-N), and nitrate nitrogen (NO3-N) were analyzed and are presented in this work. The results of the modules with agricultural residues are promising. Up to 92% COD reduction is stated in the data. The phosphate and nitrogen fractions are reduced significantly in these modules. By contrast, the modules with wood chips reduce only 67% of the incoming COD and respectively less regarding phosphates and the nitrogen fraction.
Nonlocal theories concern the interaction of objects, which are separated in space. Classical examples are Coulomb’s law or Newton’s law of universal gravitation. They had signficiant impact in physics and engineering. One classical application in mechanics is the failure of quasi-brittle materials. While local models lead to an ill-posed boundary value problem and associated mesh dependent results, nonlocal models guarantee the well-posedness and are furthermore relatively easy to implement into commercial computational software.
Research into bio-based epoxy resins has intensified in recent decades. Here, it is of great importance to use raw materials whose use does not compete with food production. In addition, the performance of the newly developed materials should be comparable to that of conventional products. Possible starting materials are lignin degradation products, such as vanillin and syringaldehyde, for which new synthesis routes to the desired products must be found and their properties determined. In this article, the first synthesis of two amine hardeners, starting with vanillin and syringaldehyde, using the Smiles rearrangement reaction is reported. The amine hardeners were mixed with bisphenol A diglycidyl ether, and the curing was compared to isophorone diamine, 4-4′-diaminodiphenyl sulfone, and 4-Aminonbenzylamine by means of differential scanning calorimetry. It was found that the two amines prepared are cold-curing. As TG-MS studies showed, the thermal stability of at least one of the polymers prepared with the potentially bio-based amines is comparable to that of the polymer prepared with isophorone diamine, and similar degradation products are formed during pyrolysis.
Calcined clays are interesting starting materials to be used as SCMs (supplementary cementitious materials) in cements or to be converted to geopolymers by activation with a high alkaline activator. The adjustment of the properties in the fresh state, especially regarding the consistency of these binders, is almost exclusively achieved by the addition of water, since commercially available superplasticizers seem to be ineffective in low-calcium geopolymer systems. The aim of this study was a systematic investigation of various PCE (polycarboxylate ester/ether) superplasticizers (methacrylate ester PCE: MPEG, isoprenol ether PCE: IPEG, methallyl ether PCE: HPEG) with respect to their stability in different alkaline activators (NaOH, KOH, sodium and potassium silicate solutions). The effectiveness of superplasticizers (SPs) in low-calcium geopolymer binders was verified by rheological tests. Size exclusion chromatography was used to investigate if structural degradation of the superplasticizers occurs. The investigated PCE superplasticizers showed a thickening effect in the low-calcium geopolymer system. Depending on the alkalinity of the activator solution, a degradation process was detected for all the PCEs investigated. The side chains of the PCEs are cleaved off the backbone by basic ester and ether hydrolysis. The highest degree of degradation was found in sodium and potassium silicate solutions. In alkaline hydroxide solutions, the degradation process increases with increasing alkalinity.
Physical exercise demonstrates a special case of aerosol emission due to its associated elevated breathing rate. This can lead to a faster spread of airborne viruses and respiratory diseases. Therefore, this study investigates cross-infection risk during training. Twelve human subjects exercised on a cycle ergometer under three mask scenarios: no mask, surgical mask, and FFP2 mask. The emitted aerosols were measured in a grey room with a measurement setup equipped with an optical particle sensor. The spread of expired air was qualitatively and quantitatively assessed using schlieren imaging. Moreover, user satisfaction surveys were conducted to evaluate the comfort of wearing face masks during training. The results indicated that both surgical and FFP2 masks significantly reduced particles emission with a reduction efficiency of 87.1% and 91.3% of all particle sizes, respectively. However, compared to surgical masks, FFP2 masks provided a nearly tenfold greater reduction of the particle size range with long residence time in the air (0.3–0.5 μm). Furthermore, the investigated masks reduced exhalation spreading distances to less than 0.15 m and 0.1 m in the case of the surgical mask and FFP2 mask, respectively. User satisfaction solely differed with respect to perceived dyspnea between no mask and FFP2 mask conditions.
This paper addresses the scope for action by municipalities in a climate emergency and places it in the framework of ecomodern (urban) policy. We analyse the way in which two German ‘climate emergency municipalities’ translate conflicts of post-fossil transformation into concrete political and planning strategies. Although more than 2,200 authorities around the world have already declared a climate emergency, research on the impact of these resolutions on the political orientation of municipalities is very limited. Our research focus is on the (potentially agonistic) treatment of conflicts in planning. We argue that in times of a socio-ecological crisis, success in conflict resolution cannot refer to appeasement and depoliticisation. Instead, we propose a framework of five criteria, based on critical theory on ecomodern strategies, planning processes and degrowth. Thus, this practice-related and explorative paper connects empirical insights from the German cities of Constance and Berlin with an innovative normative framework. The findings tell a complex story of an, at least partial, admission of the failure of previous climate mitigation strategies, a lack of social institutions of limits, an instrumental relation to nature and a disregard for social injustices. The paper discusses how municipalities, in the context of ongoing tensions over the post-fossil transformation in Germany, on the one hand hold on to business-as-usual approaches, but on the other hand also set political impulses for change.
Obgleich redaktionelle Diversität regelmäßig als eine der Kernherausforderungen für den Journalismus gehandelt wird, tun sich journalistische Organisationen immer noch schwer damit, gleichberechtigte Zugangs-und Entfaltungschancen für Frauen, People of Color, Menschen aus Einwandererfamilien oder auf anderen Ebenen diskriminierungsbetroffene Journalist*innen zu schaffen. Stattdessen zeigt die gender-und diversitätsbezogene Redaktionsforschung, dass Redaktionen nach wie vor in ihren Strukturen, Praktiken und in ihrer Kultur gesellschaftliche Machtverhältnisse widerspiegeln und (re-)produzieren. Doch im Zuge des „Entrepreneurial Journalism“ entstehen heute vielerorts neue Organisationen. Diese journalistischen Neugründungen zeichnen sich unter anderem durch kleinere, offenere und flexiblere Organisationsstrukturen aus. Ihr veränderter organisationaler Charakter wurde jedoch bislang noch nicht tiefergehend im Hinblick auf seine Potenziale und möglichen Risiken für Diversität und (Anti-)Diskriminierung untersucht. Der Beitrag hat somit zum Ziel, journalistische Neugründungen als neuen Gegenstand auf der Agenda der organisations-und diskriminierungsbezogenen Journalismusforschung zu positionieren. Dazu werden ausgewählte Studien zum „Entrepreneurial Journalism“ im Hinblick auf Diversität und (Anti-)Diskriminierung aufgearbeitet und bestehende Desiderata identifiziert. Auf dieser Grundlage wird schließlich eine programmatische Forschungsagenda entwickelt, um empirische Folgeforschung zum Thema anzustoßen.
The present article aims to provide an overview of the consequences of dynamic soil-structure interaction (SSI) on building structures and the available modelling techniques to resolve SSI problems. The role of SSI has been traditionally considered beneficial to the response of structures. However, contemporary studies and evidence from past earthquakes showed detrimental effects of SSI in certain conditions. An overview of the related investigations and findings is presented and discussed in this article. Additionally, the main approaches to evaluate seismic soil-structure interaction problems with the commonly used modelling techniques and computational methods are highlighted. The strength, limitations, and application cases of each model are also discussed and compared. Moreover, the role of SSI in various design codes and global guidelines is summarized. Finally, the advancements and recent findings on the SSI effects on the seismic response of buildings with different structural systems and foundation types are presented. In addition, with the aim of helping new researchers to improve previous findings, the research gaps and future research tendencies in the SSI field are pointed out.
Die vorliegende Studie geht der Fragestellung nach, wie sich eine anbieterübergreifende, abonnementbasierte Plattform für den digitalen Journalismus, also eine Art Spotify im Journalismus, auf die Umsätze der Anbieter journalistischer Inhalte und die Abonnements im Digitaljournalismus in Deutschland auswirken würde. Auf Basis drei sich ergänzender Schätzmethoden für Zahlungsbereitschaft, die in zwei Repräsentativbefragungen der deutschen Online-Bevölkerung mit insgesamt 8.000 Teilnehmenden angewandt wurden, gelangt das Whitepaper zu den folgenden Schlüsselbefunden.
Antimicrobial resistances (AMR) are ranked among the top ten threats to public health and societal development worldwide. Toilet wastewater contained in domestic wastewater is a significant source of AMR entering the aquatic environment. The current commonly implemented combined sewer systems at times cause overflows during rain events, resulting in the discharge of untreated wastewater into the aquatic environment, thus promoting AMR. In this short research article, we describe an approach to transform combined sewer systems into source separation-modified combined sewer systems that separately treat toilet wastewater. We employ simulations for demonstrating that source separation-modified combined sewer systems reduce the emission of AMR- causing substances by up to 11.5 logarithm levels. Thus, source separation- modified combined sewer systems are amongst the most effective means of combating AMR.
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Resonance vibration of structures is an unpleasant incident that can be conventionally avoided by using a Tuned Mass Damper (TMD). The scope of this paper contains the utilization of engineered inclusions in concrete as damping aggregates to suppress resonance vibration similar to a TMD. The inclusions are composed of a stainless-steel core with a spherical shape coated with silicone. This configuration has been the subject of several studies and it is best known as Metaconcrete. This paper presents the procedure of a free vibration test conducted with two small-scaled concrete beams. The beams exhibited a higher damping ratio after the core-coating element was secured to them. Subsequently, two meso-models of small-scaled beams were created: one representing conventional concrete and the other representing concrete with the core-coating inclusions. The frequency response curves of the models were obtained. The change in the response peak verified the ability of the inclusions to suppress the resonance vibration. This study concludes that the core-coating inclusions can be utilized in concrete as damping aggregates.
Urban Heat Transition in Berlin: Corporate Strategies, Political Conflicts, and Just Solutions
(2023)
In the field of urban climate policy, heat production and demand are key sectors for achieving a sustainable city. Heat production has to shift from fossil to renewable energies, and the heat demand of most buildings has to be reduced significantly via building retrofits. However, analyses of heat transition still lack its contextualization within entangled urban politico-economic processes and materialities and require critical socio-theoretical examination. Asking about the embeddedness of heat transition within social relations and its implications for social justice issues, this article discusses the challenges and opportunities of heat transition, taking Berlin as an example. It uses an urban political ecology perspective to analyze the materialities of Berlin’s heating-housing nexus, its politico-economic context, implications for relations of inequality and power, and its contested strategies. The empirical analysis identifies major disputes about the future trajectory of heat production and about the distribution of retrofit costs. Using our conceptual approach, we discuss these empirical findings against the idea of a more just heat transition. For this purpose, we discuss three policy proposals regarding cost distribution, urban heat planning, and remunicipalization of heat utilities. We argue that this conceptual approach provides huge benefits for debates around heat transition and, more generally, energy justice and just transitions.
Beyond metropolitan areas, many peripheral regions and their cities in Europe have, in manifold ways, been significantly shaped by industrialisation. In the context of the relocation of industrial production to other countries over the last decades, the question has been raised as to the role this heritage can play in futural regional development as well as the potential local identification with this history. Hence, this article seeks to analyse the perception of the industrial heritage in the Vogtland region, located alongside the border of three German federal states and the Czech Republic. It inquires as to the perception of the industrial heritage by the local population and related potential future narrations. Based on spontaneous and explorative interviews with local people as an empirical base, a discrepancy between the perception of the tangible and intangible dimensions of the industrial heritage can be observed. On the one hand, the tangible heritage like older factories and production complexes are seen as a functional legacy and an “eyesore” narrative is attributed to them. On the other hand, people often reference the personal and familial connection to the industry and highlight its importance for the historical development and the wealth of the region. But these positive associations are mainly limited to the intangible dimension and are disconnected from the material artefacts of industrial production.