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Die späten 1960er Jahre und vor allem die 1970er Jahre waren eine Hochphase der Mieter_innenproteste in der BRD. Dieser Beitrag verfolgt die These, dass die Krise der fordistischen Wohnraumversorgung in den 1960er Jahren, bzw. die von der Politik implementierten Lösungsstrategien dieser Krise, eine Klassenallianz in wohnungsbezogenen Protesten ermöglichte und, dass sich diese Klassenallianz im Laufe der 1970er und 1980er Jahre aufspaltete, was zur Einhegung des Protests in das entstehende neoliberale Projekt führte. Im Folgenden beschreibe ich also zunächst die Wohnungsfrage 1968 als Krise der fordistischen Wohnraumproduktion und damit die materielle Basis der Klassenallianz. Daran anschließend illustriere ich anhand von Protesten in den drei Bereichen Massenwohnungsbau, Sanierungsgebiete und Hausbesetzungen die Klassenallianz und vollziehe ich deren Aufspaltung nach. Und schließlich stelle ich die Frage, was heute aus dieser Geschichte gelernt werden kann.
Für eine Abschätzung des Heizwärmebedarfs von Gebäuden und Quartieren können thermisch-energetische Simulationen eingesetzt werden. Grundlage dieser Simulationen sind geometrische und physikalische Gebäudemodelle. Die Erstellung des geometrischen Modells erfolgt in der Regel auf Basis von Bauplänen oder Vor-Ort-Begehungen, was mit einem großen Recherche- und Modellierungsaufwand verbunden ist. Spätere bauliche Veränderungen des Gebäudes müssen häufig manuell in das Modell eingearbeitet werden, was den Arbeitsaufwand zusätzlich erhöht. Das physikalische Modell stellt die Menge an Parametern und Randbedingungen dar, welche durch Materialeigenschaften, Lage und Umgebungs-einflüsse gegeben sind. Die Verknüpfung beider Modelle wird innerhalb der entsprechenden Simulations-software realisiert und ist meist nicht in andere Softwareprodukte überführbar.
Mithilfe des Building Information Modeling (BIM) können Simulationsdaten sowohl konsistent gespeichert als auch über Schnittstellen mit entsprechenden Anwendungen ausgetauscht werden. Hierfür wird eine Methode vorgestellt, die thermisch-energetische Simulationen auf Basis des standardisierten Übergabe-formats Industry Foundation Classes (IFC) inklusive anschließender Auswertungen ermöglicht. Dabei werden geometrische und physikalische Parameter direkt aus einem über den gesamten Lebenszyklus aktuellen Gebäudemodell extrahiert und an die Simulation übergeben. Dies beschleunigt den Simulations-prozess hinsichtlich der Gebäudemodellierung und nach späteren baulichen Veränderungen. Die erarbeite-te Methode beruht hierbei auf einfachen Modellierungskonventionen bei der Erstellung des Bauwerksinformationsmodells und stellt eine vollständige Übertragbarkeit der Eingangs- und Ausgangswerte sicher.
Thermal building simulation based on BIM-models. Thermal energetic simulations are used for the estimation of the heating demand of buildings and districts. These simulations are based on building models containing geometrical and physical information. The creation of geometrical models is usually based on existing construction plans or in situ assessments which demand a comparatively big effort of investigation and modeling. Alterations, which are later applied to the structure, request manual changes of the related model, which increases the effort additionally. The physical model represents the total amount of parameters and boundary conditions that are influenced by material properties, location and environmental influences on the building. The link between both models is realized within the correspondent simulation soft-ware and is usually not transferable to other software products.
By Applying Building Information Modeling (BIM) simulation data is stored consistently and an exchange to other software is enabled. Therefore, a method which allows a thermal energetic simulation based on the exchange format Industry Foundation Classes (IFC) including an evaluation is presented. All geometrical and physical information are extracted directly from the building model that is kept up-to-date during its life cycle and transferred to the simulation. This accelerates the simulation process regarding the geometrical modeling and adjustments after later changes of the building. The developed method is based on simple conventions for the creation of the building model and ensures a complete transfer of all simulation data.
Overheating is a major problem in many modern buildings due to the utilization of lightweight constructions with low heat storing capacity. A possible answer to this problem is the emplacement of phase change materials (PCM), thereby increasing the thermal mass of a building. These materials change their state of aggregation within a defined temperature range. Useful PCM for buildings show a phase transition from solid to liquid and vice versa. The thermal mass of the materials is increased by the latent heat. A modified gypsum plaster and a salt mixture were chosen as two materials for the study of their impact on room temperature reduction. For realistic investigations, test rooms were erected where measurements were carried out under different conditions such as temporary air change, alternate internal heat gains or clouding. The experimental data was finally reproduced by dint of a mathematical model.
The human body is surrounded by a micro‐climate which results from its convective release of heat. In this study, the air temperature and flow velocity of this micro‐climate were measured in a climate chamber at various room temperatures, using a thermal manikin simulating the heat release of the human being. Different techniques (Particle Streak Tracking, thermography, anemometry, and thermistors) were used for measurement and visualization. The manikin surface temperature was adjusted to the particular indoor climate based on simulations with a thermoregulation model (UCBerkeley Thermal Comfort Model). We found that generally, the micro‐climate is thinner at the lower part of the torso, but expands going up. At the head, there is a relatively thick thermal layer, which results in an ascending plume above the head. However, the micro‐climate shape strongly depends not only on the body segment, but also on boundary conditions: the higher the temperature difference between the surface temperature of the manikin and the air temperature, the faster the air flow in the micro‐climate. Finally, convective heat transfer coefficients strongly increase with falling room temperature, while radiative heat transfer coefficients decrease. The type of body segment strongly influences the convective heat transfer coefficient, while only minimally influencing the radiative heat transfer coefficient.
The production of a desired product needs an effective use of the experimental model. The present study proposes an extreme learning machine (ELM) and a support vector machine (SVM) integrated with the response surface methodology (RSM) to solve the complexity in optimization and prediction of the ethyl ester and methyl ester production process. The novel hybrid models of ELM-RSM and ELM-SVM are further used as a case study to estimate the yield of methyl and ethyl esters through a trans-esterification process from waste cooking oil (WCO) based on American Society for Testing and Materials (ASTM) standards. The results of the prediction phase were also compared with artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS), which were recently developed by the second author of this study. Based on the results, an ELM with a correlation coefficient of 0.9815 and 0.9863 for methyl and ethyl esters, respectively, had a high estimation capability compared with that for SVM, ANNs, and ANFIS. Accordingly, the maximum production yield was obtained in the case of using ELM-RSM of 96.86% for ethyl ester at a temperature of 68.48 °C, a catalyst value of 1.15 wt. %, mixing intensity of 650.07 rpm, and an alcohol to oil molar ratio (A/O) of 5.77; for methyl ester, the production yield was 98.46% at a temperature of 67.62 °C, a catalyst value of 1.1 wt. %, mixing intensity of 709.42 rpm, and an A/O of 6.09. Therefore, ELM-RSM increased the production yield by 3.6% for ethyl ester and 3.1% for methyl ester, compared with those for the experimental data.
Management strategies for sustainable sugarcane production need to deal with the increasing complexity and variability of the whole sugar system. Moreover, they need to accommodate the multiple goals of different industry sectors and the wider community. Traditional disciplinary approaches are unable to provide integrated management solutions, and an approach based on whole systems analysis is essential to bring about beneficial change to industry and the community. The application of this approach to water management, environmental management and cane supply management is outlined, where the literature indicates that the application of extreme learning machine (ELM) has never been explored in this realm. Consequently, the leading objective of the current research was set to filling this gap by applying ELM to launch swift and accurate model for crop production data-driven. The key learning has been the need for innovation both in the technical aspects of system function underpinned by modelling of sugarcane growth. Therefore, the current study is an attempt to establish an integrate model using ELM to predict the concluding growth amount of sugarcane. Prediction results were evaluated and further compared with artificial neural network (ANN) and genetic programming models. Accuracy of the ELM model is calculated using the statistics indicators of Root Means Square Error (RMSE), Pearson Coefficient (r), and Coefficient of Determination (R2) with promising results of 0.8, 0.47, and 0.89, respectively. The results also show better generalization ability in addition to faster learning curve. Thus, proficiency of the ELM for supplementary work on advancement of prediction model for sugarcane growth was approved with promising results.
Occupant needs with regard to residential buildings are not well known due to a lack of representative scientific studies. To improve the lack of data, a large scale study was carried out using a Post Occupancy Evaluation of 1,416 building occupants. Several criteria describing the needs of occupants were evaluated with regard to their subjective level of relevance. Additionally, we investigated the degree to which deficiencies subjectively exist, and the degree to which occupants were able to accept them. From the data obtained, a hierarchy of criteria was created. It was found that building occupants ranked the physiological needs of air quality and thermal comfort the highest. Health hazards such as mould and contaminated building materials were unacceptable for occupants, while other deficiencies were more likely to be tolerated. Occupant satisfaction was also investigated. We found that most occupants can be classified as satisfied, although some differences do exist between different populations. To explain the relationship between the constructs of what we call relevance, acceptance, deficiency and satisfaction, we then created an explanatory model. Using correlation and regression analysis, the validity of the model was then confirmed by applying the collected data. The results of the study are both relevant in shaping further research and in providing guidance on how to maximize tenant satisfaction in real estate management.
A broadband soil dielectric spectra retrieval approach ( 1 MHz– 2 GHz) has been implemented for a layered half space. The inversion kernel consists of a two-port transmission line forward model in the frequency domain and a constitutive material equation based on a power law soil mixture rule (Complex Refractive Index Model - CRIM). The spatially-distributed retrieval of broadband dielectric spectra was achieved with a global optimization approach based on a Shuffled Complex Evolution (SCE) algorithm using the full set of the scattering parameters. For each layer, the broadband dielectric spectra were retrieved with the corresponding parameters thickness, porosity, water saturation and electrical conductivity of the aqueous pore solution. For the validation of the approach, a coaxial transmission line cell measured with a network analyzer was used. The possibilities and limitations of the inverse parameter estimation were numerically analyzed in four scenarios. Expected and retrieved layer thicknesses, soil properties and broadband dielectric spectra in each scenario were in reasonable agreement. Hence, the model is suitable for an estimation of in-homogeneous material parameter distributions. Moreover, the proposed frequency domain approach allows an automatic adaptation of layer number and thickness or regular grids in time and/or space.
Elitenkritik, populare Bündnisse und inklusive Solidaritär. Interview zur Debatte um Linkspopulismus
(2018)
In der aktuellen ökonomischen und politischen Krise haben Debatten um linke Strategien wieder Hochkonjunktur. Besonders kontrovers werden Vorschläge diskutiert, die einen Linkspopulismus als Alternative zum rechten politischen Projekt, zum Neoliberalismus und als Transformationsstrategie hin zu einer sozialistischen Gesellschaft propagieren. Thomas Goes und Violetta Bock haben mit ihrem Buch Ein unanständiges Angebot? Mit linkem Populismus gegen Eliten und Rechte (2017) eine programmatische Aufarbeitung existierender linker Populismuskonzepte und ihre eigene Vorstellung davon, wie ein linker Populismus gelingen kann, vorgelegt. Damit haben sie die Debatte um Linkspopulismus in Deutschland befeuert. Im Interview werden sie nach ihren Positionen und den Kontroversen um das Buch befragt. Das Interview soll als Aufschlag für eine Debatte dienen. Antworten zu den dargestellten Positionen und Bezüge zu städtischen Themen und städtischen sozialen Bewegungen sind sehr willkommen.