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Wissenschaftliches Kolloquium vom 27. bis 30. Juni 1989 in Weimar an der Hochschule für Architektur und Bauwesen zum Thema: ‚Produktivkraftentwicklung und Umweltgestaltung. Sozialer und wissenschaftlich-technischer Fortschritt in ihren Auswirkungen auf Architektur und industrielle Formgestaltung in unserer Zeit. Zum 100. Geburtstag von Hannes Meyer'
Nach dem aufgeregten Palaver um den Computer als 'Medium' und die akademische Begleitrhetorik zum Internet wird erneut die Frage nach der Leistung von Medienphilosophie gestellt - in diesem Beitrag als medienanthropologische Vergewisserung: welche technischen Überschreitungen definieren das Neue unserer Lage?
Seit mehreren Jahren wird im Fachbereich Gestaltung, Studiengang Innenarchitektur 3D-Computergrafik und -animation in Lehrveranstaltungen ausgebildet und in Projekt- und Diplomarbeiten als Darstellungsmedium angewandt. Eine besondere Herausforderung stellen dabei die 3D-Visualisierungen von historischen Gebäuden dar. Mit den beiden nachfolgenden Beispielen soll der Einsatz und die curricularen Verknüpfung der CA-Technologie mit Studienarbeiten und Projekten zum Thema >Denkmalpflege< aufgezeigt werden. Rekonstruktion und Visualisierung des ehemaligen >Jagdschlosses Platte< bei Wiesbaden. Mit Unterstützung einer Kunsthistorikerin wurde in einer Studienarbeit das im Krieg zerstörte ehemalige Jagdschloß im Computer nachgebildet. Neben der Darstellung des Gebäudeäußeren und des zentralen Innenbereiches wurde eine Animation über die Triangulierung der klassizistischen Geometrie erstellt. Umnutzung historischer Bausubstanz am Beispiel der ehemaligen Klostersanlage >Schiffenberg< bei Gießen. Im Rahmen einer Projektarbeit wurden mehrer Konzepte entwickelt, Entwürfe erstellt und mittels Computeranimationen öffentlich präsentiert. In Kooperation mit dem Studiengang Fernsehtechnik (FH-Wiesbaden) wurde von zwei Studenten eine Videodokumentation über den gesamten Projektverlauf erstellt. Neben dem Aufzeigen der Arbeitsprozesse und dem Vorstellen des Lehrkonzeptes für die curriculare Einbindung der CA-Technologie werden aktuelle Studienergebnisse anhand von Videoprojektionen vorgestellt.
Wissenschaftliches Kolloquium vom 27. bis 30. Juni 1989 in Weimar an der Hochschule für Architektur und Bauwesen zum Thema: ‚Produktivkraftentwicklung und Umweltgestaltung. Sozialer und wissenschaftlich-technischer Fortschritt in ihren Auswirkungen auf Architektur und industrielle Formgestaltung in unserer Zeit. Zum 100. Geburtstag von Hannes Meyer'
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.
The primary objective of initial shape analysis of a cable stayed bridge is to calculate initial installation cable tension forces and to evaluate fabrication camber of main span and pylon providing the final longitudinal profile of the bridge at the end of construction. In addition, the initial cable forces depending on the alternation of the bridge’s shape can be obtained from the analysis, and will be used to provide construction safety during construction. In this research, we conducted numerical experiments for initial shape of Ko-ha bridge, which will be constructed in the near future, using three different typical methods such as continuous beam method, linear truss method, and IIMF (Introducing Initial Member Force) method
A categorical perspective towards aerodynamic models for aeroelastic analyses of bridge decks
(2019)
Reliable modelling in structural engineering is crucial for the serviceability and safety of structures. A huge variety of aerodynamic models for aeroelastic analyses of bridges poses natural questions on their complexity and thus, quality. Moreover, a direct comparison of aerodynamic models is typically either not possible or senseless, as the models can be based on very different physical assumptions. Therefore, to address the question of principal comparability and complexity of models, a more abstract approach, accounting for the effect of basic physical assumptions, is necessary.
This paper presents an application of a recently introduced category theory-based modelling approach to a diverse set of models from bridge aerodynamics. Initially, the categorical approach is extended to allow an adequate description of aerodynamic models. Complexity of the selected aerodynamic models is evaluated, based on which model comparability is established. Finally, the utility of the approach for model comparison and characterisation is demonstrated on an illustrative example from bridge aeroelasticity. The outcome of this study is intended to serve as an alternative framework for model comparison and impact future model assessment studies of mathematical models for engineering applications.
Methods with the convergence order p 2 (Newton`s, tangent hyperbolas, tangent parabolas etc.) and their approximate variants are studied. Conditions are presented under which the approximate variants preserve their convergence rate intrinsic to these methods and some computational aspects (possibilities to organize parallel computation, globalization of a method, the solution of the linear equations versus the matrix inversion at every iteration etc.) are discussed. Polyalgorithmic computational schemes (hybrid methods) combining the best features of various methods are developed and possibilities of their application to numerical solution of two-point boundary-value problem in ordinary differential equations and decomposition-coordination problem in convex programming are analyzed.
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.
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.
Recently, the demand for residence and usage of urban infrastructure has been increased, thereby resulting in the elevation of risk levels of human lives over natural calamities. The occupancy demand has rapidly increased the construction rate, whereas the inadequate design of structures prone to more vulnerability. Buildings constructed before the development of seismic codes have an additional susceptibility to earthquake vibrations. The structural collapse causes an economic loss as well as setbacks for human lives. An application of different theoretical methods to analyze the structural behavior is expensive and time-consuming. Therefore, introducing a rapid vulnerability assessment method to check structural performances is necessary for future developments. The process, as mentioned earlier, is known as Rapid Visual Screening (RVS). This technique has been generated to identify, inventory, and screen structures that are potentially hazardous. Sometimes, poor construction quality does not provide some of the required parameters; in this case, the RVS process turns into a tedious scenario. Hence, to tackle such a situation, multiple-criteria decision-making (MCDM) methods for the seismic vulnerability assessment opens a new gateway. The different parameters required by RVS can be taken in MCDM. MCDM evaluates multiple conflicting criteria in decision making in several fields. This paper has aimed to bridge the gap between RVS and MCDM. Furthermore, to define the correlation between these techniques, implementation of the methodologies from Indian, Turkish, and Federal Emergency Management Agency (FEMA) codes has been done. The effects of seismic vulnerability of structures have been observed and compared.
The synchronous distributed processing of common source code in the software development process is supported by well proven methods. The planning process has similarities with the software development process. However, there are no consistent and similarly successful methods for applications in construction projects. A new approach is proposed in this contribution.
A coupled thermo-hydro-mechanical model of jointed hard rock for compressed air energy storage
(2014)
Renewable energy resources such as wind and solar are intermittent, which causes instability when being connected to utility grid of electricity. Compressed air energy storage (CAES) provides an economic and technical viable solution to this problem by utilizing subsurface rock cavern to store the electricity generated by renewable energy in the form of compressed air. Though CAES has been used for over three decades, it is only restricted to salt rock or aquifers for air tightness reason. In this paper, the technical feasibility of utilizing hard rock for CAES is investigated by using a coupled thermo-hydro-mechanical (THM) modelling of nonisothermal gas flow. Governing equations are derived from the rules of energy balance, mass balance, and static equilibrium. Cyclic volumetric mass source and heat source models are applied to simulate the gas injection and production. Evaluation is carried out for intact rock and rock with discrete crack, respectively. In both cases, the heat and pressure losses using air mass control and supplementary air injection are compared.
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.
A comprehensive framework of information management system for construction projects in China has been established through extensive literature survey and field investigation. It utilizes the potential information technologies and covers the practical management patterns as well as the major aspects of construction project management. It can be used to guide and evaluate the design of the information management systems for construction projects in order to make the system to be applicable to a wide variety of construction projects and survive the changes in project management.
We apply keyquery-based taxonomy composition to compute a classification system for the CORE dataset, a shared crawl of about 850,000 scientific papers. Keyquery-based taxonomy composition can be understood as a two-phase hierarchical document clustering technique that utilizes search queries as cluster labels: In a first phase, the document collection is indexed by a reference search engine, and the documents are tagged with the search queries they are relevant—for their so-called keyqueries. In a second phase, a hierarchical clustering is formed from the keyqueries within an iterative process. We use the explicit topic model ESA as document retrieval model in order to index the CORE dataset in the reference search engine. Under the ESA retrieval model, documents are represented as vectors of similarities to Wikipedia articles; a methodology proven to be advantageous for text categorization tasks. Our paper presents the generated taxonomy and reports on quantitative properties such as document coverage and processing requirements.
A Machine Learning Framework for Assessing Seismic Hazard Safety of Reinforced Concrete Buildings
(2020)
Although averting a seismic disturbance and its physical, social, and economic disruption is practically impossible, using the advancements in computational science and numerical modeling shall equip humanity to predict its severity, understand the outcomes, and equip for post-disaster management. Many buildings exist amidst the developed metropolitan areas, which are senile and still in service. These buildings were also designed before establishing national seismic codes or without the introduction of construction regulations. In that case, risk reduction is significant for developing alternatives and designing suitable models to enhance the existing structure’s performance. Such models will be able to classify risks and casualties related to possible earthquakes through emergency preparation. Thus, it is crucial to recognize structures that are susceptible to earthquake vibrations and need to be prioritized for retrofitting. However, each building’s behavior under seismic actions cannot be studied through performing structural analysis, as it might be unrealistic because of the rigorous computations, long period, and substantial expenditure. Therefore, it calls for a simple, reliable, and accurate process known as Rapid Visual Screening (RVS), which serves as a primary screening platform, including an optimum number of seismic parameters and predetermined performance damage conditions for structures. In this study, the damage classification technique was studied, and the efficacy of the Machine Learning (ML) method in damage prediction via a Support Vector Machine (SVM) model was explored. The ML model is trained and tested separately on damage data from four different earthquakes, namely Ecuador, Haiti, Nepal, and South Korea. Each dataset consists of varying numbers of input data and eight performance modifiers. Based on the study and the results, the ML model using SVM classifies the given input data into the belonging classes and accomplishes the performance on hazard safety evaluation of buildings.
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.
A Multi-objective Model for Optimizing Construction Planning of Repetitive Infrastructure Projects
(2004)
This paper presents the development of a model for optimizing resource utilization in repetitive infrastructure projects. The model provides the capability of simultaneous minimization of both project duration and work interruptions for construction crews. The model provides in a single run, a set of nondominated solutions that represent the tradeoff between these two objectives. The model incorporates a multiobjective genetic algorithm and scheduling algorithm. The model initially generates a randomly selected set of solutions that evolves to a near optimal set of tradeoff solutions in subsequent generations. Each solution represents a unique scheduling solution that is associated with certain project duration and a number of interruption days for utilized construction crews. As such, the model provides project planners with alternative schedules along with their expected duration and resource utilization efficiency.
The K-nearest neighbors (KNN) machine learning algorithm is a well-known non-parametric classification method. However, like other traditional data mining methods, applying it on big data comes with computational challenges. Indeed, KNN determines the class of a new sample based on the class of its nearest neighbors; however, identifying the neighbors in a large amount of data imposes a large computational cost so that it is no longer applicable by a single computing machine. One of the proposed techniques to make classification methods applicable on large datasets is pruning. LC-KNN is an improved KNN method which first clusters the data into some smaller partitions using the K-means clustering method; and then applies the KNN for each new sample on the partition which its center is the nearest one. However, because the clusters have different shapes and densities, selection of the appropriate cluster is a challenge. In this paper, an approach has been proposed to improve the pruning phase of the LC-KNN method by taking into account these factors. The proposed approach helps to choose a more appropriate cluster of data for looking for the neighbors, thus, increasing the classification accuracy. The performance of the proposed approach is evaluated on different real datasets. The experimental results show the effectiveness of the proposed approach and its higher classification accuracy and lower time cost in comparison to other recent relevant methods.
The amount of adsorbed styrene acrylate copolymer (SA) particles on cementitious surfaces at the early stage of hydration was quantitatively determined using three different methodological approaches: the depletion method, the visible spectrophotometry (VIS) and the thermo-gravimetry coupled with mass spectrometry (TG–MS). Considering the advantages and disadvantages of each method, including the respectively required sample preparation, the results for four polymer-modified cement pastes, varying in polymer content and cement fineness, were evaluated.
To some extent, significant discrepancies in the adsorption degrees were observed. There is a tendency that significantly lower amounts of adsorbed polymers were identified using TG-MS compared to values determined with the depletion method. Spectrophotometrically generated values were lying in between these extremes. This tendency was found for three of the four cement pastes examined and is originated in sample preparation and methodical limitations.
The main influencing factor is the falsification of the polymer concentration in the liquid phase during centrifugation. Interactions in the interface between sediment and supernatant are the cause. The newly developed method, using TG–MS for the quantification of SA particles, proved to be suitable for dealing with these revealed issues. Here, instead of the fluid phase, the sediment is examined with regard to the polymer content, on which the influence of centrifugation is considerably lower.
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.
This paper presents a novel numerical procedure based on the combination of an edge-based smoothed finite element (ES-FEM) with a phantom-node method for 2D linear elastic fracture mechanics. In the standard phantom-node method, the cracks are formulated by adding phantom nodes, and the cracked element is replaced by two new superimposed elements. This approach is quite simple to implement into existing explicit finite element programs. The shape functions associated with discontinuous elements are similar to those of the standard finite elements, which leads to certain simplification with implementing in the existing codes. The phantom-node method allows modeling discontinuities at an arbitrary location in the mesh. The ES-FEM model owns a close-to-exact stiffness that is much softer than lower-order finite element methods (FEM). Taking advantage of both the ES-FEM and the phantom-node method, we introduce an edge-based strain smoothing technique for the phantom-node method. Numerical results show that the proposed method achieves high accuracy compared with the extended finite element method (XFEM) and other reference solutions.
Increasing complexity of today's buildings requires a high level of integration in the planning process. Common planning strategies, where individual project partners cooperate mainly to exchange results, are not suitable to jointly develop project goals and objectives. Integrated planning, a more holistic approach to deal with complex problems, is based on a high degree of communication amoung team members and leads to a goal oriented cooperation. Current approaches in the reasearch area of Computer Supported Cooperative Work (CSCW) poorly meet the requirements in planning. A planning process model, based on the principles of integrated planning will be introduced, aimed to provide the background for the implementation of a CSCW-platform.
The displacements and stresses in arch dams and their abutments are frequently determined with 20-node brick elements. The elements are distorted near the contact plane between the wall and the abutment. A cantilever beam testbed has been developed to investigate the consequences of this distortion. It is shown that the deterioration of the accuracy in the computed stresses is significant. A compatible 18-node wedge element with linear stress variation is developed as an alternative to the brick element. The shape of this element type is readily adapted to the shape of the contact plane. It is shown that the accuracy of the computed stresses in the vicinity of the contact plane is improved significantly by the use of wedge elements.
A Product Model of a Road
(1997)
Many errors and delays frequently appear when data is exchanged between particular tasks in the lifecycle of the road. Inter-task connections are therefore of great importance for the quality of the final product. The article describes a product model of a road wich is the kernel of an integrated information system intended to support all important stages of the road lifecycle: design, evaluation (through different analysis procedures), construction, and maintainance. Since particular tasks are often executed at different places and in different companies, the interconnections are supported by a special metafile which contains all specific data of the product model. The concept of the integrated system is object and component oriented. Additionally, existing conventional program packages are included to support some common tasks (methods). A conventional relational database system as well as an open spatial database system with the relevant GIS functionality are included to support the data structures of the model.
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.
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.
A simple multiscale analysis framework for heterogeneous solids based on a computational homogenization technique is presented. The macroscopic strain is linked kinematically to the boundary displacement of a circular or spherical representative volume which contains the microscopic information of the material. The macroscopic stress is obtained from the energy principle between the macroscopic scale and the microscopic scale. This new method is applied to several standard examples to show its accuracy and consistency of the method proposed.
This paper presents a new design environment based on Multi-Agents and Virtual Reality (VR). In this research, a design system with a virtual reality function was developed. The virtual world was realized by using GL4Java, liquid crystal shutter glasses, sensor systems, etc. And the Multi-Agent CAD system with product models, which had been developed before, was integrated with the VR design system. A prototype system was developed for highway steel plate girder bridges, and was applied to a design problem. The application verified the effectiveness of the developed system.
Rice husk ash (RHA) is classified as a highly reactive pozzolan. It has a very high silica content similar to that of silica fume (SF). Using less-expensive and locally available RHA as a mineral admixture in concrete brings ample benefits to the costs, the technical properties of concrete as well as to the environment. An experimental study of the effect of RHA blending on workability, strength and durability of high performance fine-grained concrete (HPFGC) is presented. The results show that the addition of RHA to HPFGC improved significantly compressive strength, splitting tensile strength and chloride penetration resistance. Interestingly, the ratio of compressive strength to splitting tensile strength of HPFGC was lower than that of ordinary concrete, especially for the concrete made with 20 % RHA. Compressive strength and splitting tensile strength of HPFGC containing RHA was similar and slightly higher, respectively, than for HPFGC containing SF. Chloride penetration resistance of HPFGC containing 10–15 % RHA was comparable with that of HPFGC containing 10 % SF.
In this Paper, we explored the relation between the electricity consumption in residential sector and the automobile energy consumption in transportation sector in accordance with the location of city by employing Geographic Information System (GIS). We found in the study that the electricity consumption per capita has a tendency that is higher in city center and lower in suburbs in Utsunomiya city. It is also noted that there is little difference among total consumption between city center and suburbs, despite the fact that the density of electric appliances tends to increase in a small size house of city center and the amount of automobile energy consumption from residence is lower in city center than in suburbs.
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.
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.
An architecture of a distributed planning system for the building industry has been developed. The emphasis is on highly collaborative environments in steelwork, timber construction etc. where designers concurrently handle 3D models. The overall system connects local design systems by the so-called Design Framework DFW. This framework consists of the definition of distributed components and protocols which make the collaborative design work. The process of collaborative design has been formalized on an abstract level. This paper describes how this has been done. A sample is given to illustrate the mapping of concrete scenarios of the ‘real design world’ to an abstract scenario level. This work is funded by the Deutsche Forschungsgemeinschaft DFG as part of the project SPP1103 (Meißner et al. 2003).
Expert systems integrating fuzzy reasoning techniques represent a powerful tool to support practicing engineers during the early stages of structural design. In this context fuzzy models have proved themselves to be very suitable for the representation of complex design knowledge. However their definition is a laborious task. This paper introduces an approach for the design and the optimization of fuzzy systems based upon Genetic Programming. To keep the emerging fuzzy systems transparent a new framework for the definition of linguistic variables is also introduced.
Framed-tube system with multiple internal tubes is analysed using an orthotropic box beam analogy approach in which each tube is individually modelled by a box beam that accounts for the flexural and shear deformations, as well as the shear-lag effects. A simple numerical modeling technique is proposed for estimating the shear-lag phenomenon in tube structures with multiple internal tubes. The proposed method idealizes the framed-tube structures with multiple internal tubes as equivalent multiple tubes, each composed of four equivalent orthotropic plate panels. The numerical analysis is based on the minimum potential energy principle in conjunction with the variational approach. The shear-lag phenomenon of such structures is studied taking into account the additional bending moments in the tubes. A detailed work is carried out through the numerical analysis of the additional bending moment. The moment factor is further introduced to identify the shear lag phenomenon along with the additional moment.
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.
The laser beam is a small, flexible and fast polishing tool. With laser radiation it is possible to finish many outlines or geometries on quartz glass surfaces in the shortest possible time. It’s a fact that the temperature developing while polishing determines the reachable surface smoothing and, as a negative result, causes material tensions. To find out which parameters are important for the laser polishing process and the surface roughness respectively and to estimate material tensions, temperature simulations and extensive polishing experiments took place. During these experiments starting and machining parameters were changed and temperatures were measured contact-free. The accuracy of thermal and mechanical simulation was improved in the case of advanced FE-analysis.