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- 2020 (123) (remove)
Radikale Pädagogik richtet ihre Aufmerksamkeit sowohl auf die alltäglichen Techniken pädagogischer Praxis – Techniken zur Aktivierung eines Begegnungsraumes, Techniken, sich um die Arbeit und einander zu kümmern, Techniken des kulturübergreifenden Zuhörens, Techniken, sich dem Mehr-als zuzuwenden – als auch auf Techniken zum »Überschreiten der Schwelle«. Das Überschreiten der Schwelle hängt mit der Art und Weise der Anpassung (accommodation) zusammen, die es ermöglicht, das Lernen in all seinen Erscheinungsformen wertzuschätzen.
Das spekulative Handbuch bietet vielfältige Techniken für ein radikales Lernen und Vermitteln. Es umfasst konkrete Anleitungen, Erfahrungen und theoretische Überlegungen. Die Texte beteiligen sich an der Konzeption einer Vermittlung, die das gemeinsame Experimentieren (wieder) einführt.
Im Seminarraum, in Workshops, auf Festivals, in Fluren, Parks und der Stadt finden Lernen und Verlernen statt. Texte und Anleitungen u. a. zu: Filmessays, Collagen, Banküberfällen, der Universität der Toten, wildem Schreiben, konzeptuellem speed Dating, neurodiversem Lernen, Format-Denken, dem Theater der Sorge, dem Schreiblabor, dem Körperstreik.
Der perfekte Bankraub
(2020)
Finanzielle Unabhängigkeit, überleben können, Superheld*in oder Pop-Star sein, Adrenalin-Kick, lebenslange Kompliz*innenschaft und ewige romanti- sche Verbundenheit, Verschwörung, siegreiches Über- listen, Täuschungstechniken – die Fantasien, die sich um die Idee des Bankraubs ranken, sind so verschieden wie die Menschen, die sie haben. Ein Banküberfall ist wahrscheinlich der Traum Vieler, angesichts der zuneh- menden Prekarisierung persönlicher Ökonomien und
– gleichzeitig oder gerade deswegen – ein spektakulari- siertes, fast popkulturelles Ereignis, das in den Medien gut dokumentiert und in unzähligen Filmen illustriert und weitergesponnen wird.
Körperstreik
(2020)
Das Innovationsmanagement von Medienorganisationen unterliegt derzeit erheblichen Veränderungen: Im veränderten Marktumfeld erweisen sich Flexibilität, schnelle Richtungswechsel und Anpassungsfähigkeit als zentral. Darauf muss auch die Medienmanagement-Forschung reagieren: Um die Agilität der gegenwärtigen Unternehmenspraxis valide zu erforschen, ist eine ebenso agile, adaptive Forschung gefordert. Zu diesem Zweck schlägt der Beitrag eine praxistheoretische Perspektive auf das Innovationsmanagement von Medienorganisationen vor. Empirische Forschungsdesigns, die aus einem solchen Zugriff resultieren, werden sowohl hinsichtlich ihrer methodischen Herausforderungen als auch ihres Forschungsprojektmanagements diskutiert. Der Beitrag greift außerdem neue Möglichkeitsräume des wissenschaftlichen Publizierens, des Universitätsmanagements sowie der Forschungsorganisation auf, die praxistheoretisch gegründete, empirische Innovationsforschung in der Medienwirtschaft einfordert.
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.
Material properties play a critical role in durable products manufacturing. Estimation of the precise characteristics in different scales requires complex and expensive experimental measurements. Potentially, computational methods can provide a platform to determine the fundamental properties before the final experiment. Multi-scale computational modeling leads to the modeling of the various time, and length scales include nano, micro, meso, and macro scales. These scales can be modeled separately or in correlation with coarser scales. Depend on the interested scales modeling, the right selection of multi-scale methods leads to reliable results and affordable computational cost. The present dissertation deals with the problems in various length and time scales using computational methods include density functional theory (DFT), molecular mechanics (MM), molecular dynamics (MD), and finite element (FE) methods.
Physical and chemical interactions in lower scales determine the coarser scale properties. Particles interaction modeling and exploring fundamental properties are significant challenges of computational science. Downscale modelings need more computational effort due to a large number of interacted atoms/particles. To deal with this problem and bring up a fine-scale (nano) as a coarse-scale (macro) problem, we extended an atomic-continuum framework. The discrete atomic models solve as a continuum problem using the computationally efficient FE method. MM or force field method based on a set of assumptions approximates a solution on the atomic scale. In this method, atoms and bonds model as a harmonic oscillator with a system of mass and springs. The negative gradient of the potential energy equal to the forces on each atom. In this way, each bond's total potential energy includes bonded, and non-bonded energies are simulated as equivalent structural strain energies. Finally, the chemical nature of the atomic bond is modeled as a piezoelectric beam element that solves by the FE method.
Exploring novel materials with unique properties is a demand for various industrial applications. During the last decade, many two-dimensional (2D) materials have been synthesized and shown outstanding properties. Investigation of the probable defects during the formation/fabrication process and studying their strength under severe service life are the critical tasks to explore performance prospects. We studied various defects include nano crack, notch, and point vacancy (Stone-Wales defect) defects employing MD analysis. Classical MD has been used to simulate a considerable amount of molecules at micro-, and meso- scales. Pristine and defective nanosheet structures considered under the uniaxial tensile loading at various temperatures using open-source LAMMPS codes. The results were visualized with the open-source software of OVITO and VMD.
Quantum based first principle calculations have been conducting at electronic scales and known as the most accurate Ab initio methods. However, they are computationally expensive to apply for large systems. We used density functional theory (DFT) to estimate the mechanical and electrochemical response of the 2D materials. Many-body Schrödinger's equation describes the motion and interactions of the solid-state particles. Solid describes as a system of positive nuclei and negative electrons, all electromagnetically interacting with each other, where the wave function theory describes the quantum state of the set of particles. However, dealing with the 3N coordinates of the electrons, nuclei, and N coordinates of the electrons spin components makes the governing equation unsolvable for just a few interacted atoms. Some assumptions and theories like Born Oppenheimer and Hartree-Fock mean-field and Hohenberg-Kohn theories are needed to treat with this equation. First, Born Oppenheimer approximation reduces it to the only electronic coordinates. Then Kohn and Sham, based on Hartree-Fock and Hohenberg-Kohn theories, assumed an equivalent fictitious non-interacting electrons system as an electron density functional such that their ground state energies are equal to a set of interacting electrons. Exchange-correlation energy functionals are responsible for satisfying the equivalency between both systems. The exact form of the exchange-correlation functional is not known. However, there are widely used methods to derive functionals like local density approximation (LDA), Generalized gradient approximation (GGA), and hybrid functionals (e.g., B3LYP). In our study, DFT performed using VASP codes within the GGA/PBE approximation, and visualization/post-processing of the results realized via open-source software of VESTA.
The extensive DFT calculations are conducted 2D nanomaterials prospects as anode/cathode electrode materials for batteries. Metal-ion batteries' performance strongly depends on the design of novel electrode material. Two-dimensional (2D) materials have developed a remarkable interest in using as an electrode in battery cells due to their excellent properties. Desirable battery energy storage systems (BESS) must satisfy the high energy density, safe operation, and efficient production costs. Batteries have been using in electronic devices and provide a solution to the environmental issues and store the discontinuous energies generated from renewable wind or solar power plants. Therefore, exploring optimal electrode materials can improve storage capacity and charging/discharging rates, leading to the design of advanced batteries.
Our results in multiple scales highlight not only the proposed and employed methods' efficiencies but also promising prospect of recently synthesized nanomaterials and their applications as an anode material. In this way, first, a novel approach developed for the modeling of the 1D nanotube as a continuum piezoelectric beam element. The results converged and matched closely with those from experiments and other more complex models. Then mechanical properties of nanosheets estimated and the failure mechanisms results provide a useful guide for further use in prospect applications. Our results indicated a comprehensive and useful vision concerning the mechanical properties of nanosheets with/without defects. Finally, mechanical and electrochemical properties of the several 2D nanomaterials are explored for the first time—their application performance as an anode material illustrates high potentials in manufacturing super-stretchable and ultrahigh-capacity battery energy storage systems (BESS). Our results exhibited better performance in comparison to the available commercial anode materials.
The thesis concerns a work of urban history intended not to describe the city but rather to interpret it. By doing so, I have interpreted the city by means of the role played by the so-called ‘great property’ in the European city-making process during the last three decades of the 20th century, specifically focused on the concrete case of military properties in Italy. I have also considered the role played by other kinds of great properties, i.e. industries and railway, which previously acted in the production of the built environment in a different way respect to the military one. As all of them have as common denominator the fact of being ‘capital in land’, I analysed great industrial and railway properties in order to extrapolate a methodology which helped me to interpret the relationship between military properties and city-making process in Europe in the late 20th century.
I have analysed the relationship between the capital in land and the city-making process on the ground of the understanding the interrelation between the great property, the urban development, and the agents involved in the urban and territorial planning. Here I have showed that urban planning is not the decisive factor influencing the citymaking process, but instead the power held by the capital in land. I have found that is the great property the trigger of the creation of new ‘areas of centrality’ intended as large areas for consumerism. As far as the role played by great property is concerned, I have also discovered that it has evolved over time. Originally, industrial and railway properties have been regenerated into a wide range of new profit-driven spaces; successively, I have found out that most of the regeneration of military premises aimed to materialise areas of centrality. The way of interpreting this factor has been based on focusing my attention on the military premises in Italy: I have classified their typology when they have been built and, most importantly, when they have been regenerated into new areas of centrality.
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.
Ausgehend von der vielfachen Verwertung der bäuerlichen Kleidung durch den Staat während des Sozialismus in Rumänien wird in der Arbeit das ‚Gemacht-Sein‘ von Volkstrachten befragt entlang von im untersuchten Zeitraum wirkenden Diskursen, wie dem Prozess der Modernisierung oder der Hervorhebung nationaler Werte. Die künstlerische Forschung setzt dabei auf Simulacra (Roland Barthes). Ziel war, tradierte Formate der Wissensaufbereitung und -verbreitung zu appropriieren, so auch von Strategien, die auf der Ebene von Bildern und Sprache agieren, um eine Re-Lektüre sowohl von ‚Volkstracht‘ im Sozialismus als auch von ihren Entsprechungen nach 1989 zu ermöglichen.
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.
Das Buch greift die enge Verknüpfung von Industrialisierung und Urbanisierung auf, die in den letzten gut 250 Jahren Europas Städte und ihre Stadtbaugeschichte maßgeblich geprägt hat. Damit stellen sich auch vielfältige Fragen und Aufgaben für die Denkmalpflege.
Die Habilitationsschrift leistet einen Beitrag, um die stadtbaugeschichtlichen und stadtbildprägenden Werte historischer Industriekomplexe zu erkennen und zu erhalten. Wie können wir die industriellen Stadtlandschaften erfassen? Wie gestalten wir Umnutzungen und Konversionen denkmalgerecht und beziehen im Rahmen eines Heritage-Managements Aspekte der nachhaltigen Stadtentwicklung ein?
Das vorliegende Gutachten befasst sich mit der Innovationslandschaft des deutschen Journalismus. Innovation wird als eine essenzielle Voraussetzung verstanden, um tragfähige Lösungsansätze für die gegenwärtigen Probleme des Journa-lismus zu entwickeln. Im Mittelpunkt des Gutachtens steht die Frage, wie Innovationspolitik im Journalismus – d. h. die Unterstützung von Innovation durch die öffentliche Hand – funktionstüchtig ausgestaltet werden kann. Dabei wird dem Innovationssysteme-Ansatz gefolgt, welcher Probleme, Barrieren und Hemmnisse identifiziert, die der Innovationsfähigkeit des Journalismus in Deutschland grundlegend im Wege stehen.
Im vorliegenden Beitrag werden Messungen und Berechnungen vorgestellt, die die Temperaturentwicklung in Betonzylindern aufgrund zyklischer Beanspruchung genau beschreiben. Die Messungen wurden in einem Versuchsstand, die Berechnungen im FEM-Programm ANSYS durchgeführt. Mit Hilfe der Temperaturmessungen konnten die Simulationen für die Temperaturentwicklung der Betonzylinder mit der verwendeten Betonrezeptur validiert werden. Die Untersuchungen lassen den Schluss zu, dass bei zyklischer Probekörperbelastung und der einhergehenden Probekörperdehnung Energie dissipiert wird und diese maßgeblich für die Erwärmung der Probe verantwortlich ist.
Wiederkehrende Belastungen, wie sie beispielsweise an Brücken oder Windenergieanlagen auftreten, können innerhalb der Nutzungsdauer solcher Bauwerke bis zu 1.000.000.000 Lastwechsel erreichen. Um das dadurch eintretende Ermüdungsverhalten von Beton zu untersuchen, werden diese zyklischen Beanspruchungen in mechanischen Versuchen mit Prüfzylindern nachgestellt. Damit Versuche mit solch hohen Lastwechselzahlen in akzeptablen Zeitdauern durchgeführt werden können, wird die Belastungsfrequenz erhöht. Als Folge dieser erhöhten Belas-tungsfrequenz erwärmen sich allerdings die Betonprobekörper, was zu einem früheren, unrealistischen Versagenszeitpunkt führen kann, weshalb die Erwärmung begrenzt werden muss. Um die Wärmefreisetzung in der Probe zu untersuchen, wurden Versuche und Simulationen durchgeführt. Im Beitrag wird die analytische und messtechnische Analyse des Wärmeübergangs an erwärmten Betonzylindern vorgestellt. Resultierend daraus wird eine Möglichkeit zur Reduktion der Erwärmung an zyklisch beanspruchten Betonzylindern vorgestellt.
The assessment of wind-induced vibrations is considered vital for the design of long-span bridges. The aim of this research is to develop a methodological framework for robust and efficient prediction strategies for complex aerodynamic phenomena using hybrid models that employ numerical analyses as well as meta-models. Here, an approach to predict motion-induced aerodynamic forces is developed using artificial neural network (ANN). The ANN is implemented in the classical formulation and trained with a comprehensive dataset which is obtained from computational fluid dynamics forced vibration simulations. The input to the ANN is the response time histories of a bridge section, whereas the output is the motion-induced forces. The developed ANN has been tested for training and test data of different cross section geometries which provide promising predictions. The prediction is also performed for an ambient response input with multiple frequencies. Moreover, the trained ANN for aerodynamic forcing is coupled with the structural model to perform fully-coupled fluid--structure interaction analysis to determine the aeroelastic instability limit. The sensitivity of the ANN parameters to the model prediction quality and the efficiency has also been highlighted. The proposed methodology has wide application in the analysis and design of long-span bridges.
What you are about to read is the very last issue of the ZMK. Since our overall research enterprise, the IKKM, has to cease all of its activities due to the end of its twelve years’ funding by the German federal government, the ZMK will also come to an end. Its last topic, Schalten und Walten has also been the subject of the concluding biannual conference of the IKKM, and we hope it will be a fitting topic to resume the research of the IKKM on Operative Ontologies.
Although this final issue is in English, we decided to leave its title in German: Schalten und Walten. As it is the case for the name of the IKKM, (Internationales Kolleg für Kulturtechnikforschung und Medienphilosophie), the term seems untranslatable to us, not only for the poetic reason of the rhyming sound of the words. Switching and Ruling might be accepted as English versions, but quite an unbridgeable difference remains. In German, Schalten und Walten is a rather common and quite widespread idiom that can be found in everyday life. Whoever, the idiom stipulates, is able to execute Schalten und Walten has the power to act, has freedom of decision and power of disposition.
Although both terms are mentioned together and belong together in the German expression Schalten und Walten, they are nevertheless complements to each other. They both refer to the exercise and existence of domination, disposal or power, but they nonetheless designate two quite different modes of being. Schalten is not so much sheer command over something, but government or management. It is linked to control, intervention and change, in short: it is operative and goes along with distinctive measures and cause-and-effect relations. The English equivalent switching reflects this more or less adequately.
Das Buch greift die enge Verknüpfung von Industrialisierung und
Urbanisierung auf, die in den letzten gut 250 Jahren Europas Städte und ihre Stadtbaugeschichte maßgeblich geprägt hat. Damit stellen sich auch vielfältige Fragen und Aufgaben für die Denkmalpflege.
Die Habilitationsschrift leistet einen Beitrag, um die stadtbaugeschichtlichen und stadtbildprägenden Werte historischer Industriekomplexe zu erkennen und zu erhalten. Wie können wir die industriellen Stadtlandschaften erfassen? Wie gestalten wir Umnutzungen und Konversionen denkmalgerecht und beziehen im Rahmen eines Heritage-Managements Aspekte der nachhaltigen Stadtentwicklung ein?