New Concepts for Virtual Testbeds : Data Mining Algorithms for Blackbox Optimization based on Wait-Free Concurrency and Generative Simulation

Virtual testbeds have emerged as a key technology for improving and streamlining complex engineering processes by delivering long-term simulation and assessment of complex designs in virtual environments. In contrast to existing simulation technology, virtual testbeds focus on long-term physically-based simulation of the overall design in its (virtual) environment instead of only focussing on isolated, specific parts for short periods of time. This technology has the major advantage that costly testing, prototyping, and assessment in real-life environments are replaced by a cost-efficient simulation in virtual worlds for comprehensive and long-term analysis of designs. For this purpose, engineering models and their requirements are abstracted into software simulation models and objectives which are executed in virtual assessments. Simulation models are used to predict complex, real systems which can be further a subject to random influences. These predictions are used to examine the effects of individual configuration alternatives without actually realizing them and causing possible negative effects on the real system. Virtual testbeds further offer engineers the opportunity to immersively and naturally interact with their simulation model in these virtual assessments. This enables a greater and comprehensive understanding of possible design flaws early-on in the design process for engineers because they can directly assess their design in the virtual environment, based on the simulation objectives. The fact that virtual testbeds enable these realtime interactive virtual assessments, makes their underlying software infrastructure very complex. One major challenge is to minimize the development time of virtual testbeds in order to efficiently integrate them into the overall engineering process. Usually, this can be achieved by minimizing the underlying concurrency of the testbed and by simplifying its software architecture. However, this may result in a degradation of their very concurrent and asynchronous behavior, which is usually required for immersive and natural virtual interaction. A major goal of virtual testbeds in the engineering process is to find a set of optimal configurations of the simulation model which maximizes all simulation objectives for the specified virtual assessments. Once such a set has been computed, engineers can interactively explore it in the virtual environment. The main challenge is that sophisticated simulation models and their configuration are subject to a multiobjective optimization problem, which usually can not be solved manually by engineers or simulation analysts in feasible time. This is further aggravated because the relationships between simulation model configurations and simulation objectives are mostly unknown, leading to what is known as blackbox simulations. In this thesis, I propose novel data mining algorithms for computing Pareto optimal simulation model configurations, based on an approximation of the feasible design space, for deterministic and stochastic blackbox simulations in virtual testbeds for achieving above stated goal. These novel data mining algorithms lead to an automatic knowledge discovery process that does not need any supervision for its data analysis and assessment for multiobjective optimization problems of simulation model configurations. This achieves the previously stated goal of computing optimal configurations of simulation models for long-term simulations and assessments. Furthermore, I propose two complementary solutions for efficiently integrating massively-parallel virtual testbeds into engineering processes. First, I propose a novel multiversion wait-free data and concurrency management based on hash maps. These wait-free hash maps do not require any standard locking mechanisms and enable low-latency data generation, management and distribution for massively-parallel applications. Second, I propose novel concepts for efficiently code generating above wait-free data and concurrency management for arbitrary massively-parallel simulation applications of virtual testbeds. My generative simulation concept combines a state-of-the-art realtime interactive system design pattern for high maintainability with template code generation based on domain specific modelling. This concept is able to generate massively-parallel simulations and, at the same time, model checks its internal dataflow for possible interface errors. These generative concept overcomes the challenge of efficiently integrating virtual testbeds into engineering processes. These contributions enable for the first time a powerful collaboration between simulation, optimization, visualization and data analysis for novel virtual testbed applications but also overcome and achieve the presented challenges and goals

Critical Making? : Praktiken in Makerspaces zwischen Widerständigkeit und Affirmation

Vor dem Hintergrund der vielfach artikulierten Annahme, Makerspaces seien potenzielle Keimzellen von Gesellschaftskritik und Orte für visionäre Neuentwürfe eines nachhaltigen Lebensstils, beleuchtet der vorliegende Beitrag die Frage, ob und wie sich in Makerspaces Praktiken zeigen, die als kritisch klassifizierbar sind. Die Ausführungen stützen sich dabei auf die Ergebnisse einer ethnographischen Studie, die in zwei selbstorganisierten Makerspaces durchgeführt wurde. Der Beitrag stellt, ausgehend von einem Kritikverständnis im Anschluss an Michel Foucault und Hartmut Rosa, anhand exemplarischer Befunde die den ambivalenten Charakter kritisch konnotierter Praktiken in Makerspaces dar.Taking the frequently expressed assumption of makerspaces as potential spaces for social criticism and the development of sustainbale innovations into consideration, the following article questions if and how practices, which are performed in makerspaces, can be classified as critical. For that purpose the findings of an ethnographic research project, which was conducted in two self-organized makerspaces, will be discussed. On the basis of exemplary findings of this research and an understandig of critic following Michel Foucault and Hartmut Rosa this article outlines the ambivalent character of critical practices in makerspace

Social Media und Geschlecht in der Offenen Kinder- und Jugendarbeit

Social Media spielt in den Lebenswelten von Kindern und Jugendlichen bekanntermassen eine bedeutsame Rolle und die entsprechenden Plattformen können als sozialisationsrelevant begriffen werden. Um identitätsbildende Prozesse, etwa im Zusammenhang mit geschlechtlicher Selbstverortung oder sexueller Orientierung, nachvollziehen zu können, ist eine Auseinandersetzung mit den Medienpraktiken von Kindern und Jugendlichen von hoher Relevanz. Dies betrifft auch das pädagogische Handlungsfeld der Offenen Kinder- und Jugendarbeit, das jungen Menschen als ausserschulisches Tätigkeitsfeld Bildungsgelegenheiten bietet und dabei die Heterogenität der Zielgruppe bestmöglich zu berücksichtigen hat. In diesem Schnittfeld verortet sich der Beitrag, indem er nach der Bedeutung der Kategorien Geschlecht und Sexualität im Kontext der Nutzung von Social Media-Plattformen durch Jugendliche fragt und anhand einer qualitativen Studie relevante Aspekte herausarbeitet, welche Anknüpfungspunkte für eine sich als inklusiv verstehende Medienbildung bieten können

‹Making› the subject: A material-discursive perspective on learning processes in Makerspaces and FabLabs

Der Beitrag rückt die Frage «Was verstehen wir unter ‹Lernen› im Zusammenhang mit Medien?» ins Zentrum und skizziert auf Grundlage der Ergebnisse eines ethnographischen Forschungsprojektes, bei dem FabLabs und Makerspaces im Rahmen einer teilnehmenden Beobachtung erkundet wurden, ein relationales Konzept von Lernen. Im Forschungsprojekt wurde das beobachtete Geschehen unter einer praxis- und diskurstheoretischen Rahmung analysiert, wobei insbesondere die Frage nach der Rolle von Artefakten im Vordergrund stand. Ausgehend von der Untersuchung materiell-diskursiver Praxis lässt sich Lernen mit Medien in dieser Herangehensweise als performatives Relationierungsgeschehen begreifen, an dem heterogene (d.h. menschliche und nichtmenschliche) Entitäten beteiligt sind. Der Beitrag stellt die Eckpunkte des Forschungsprojektes sowie ausgewählte Ergebnisse vor und diskutiert diese vor dem Hintergrund post-anthropozentrischer Lerntheorien.The paper focuses on the question «What do we understand by media-related learning?» and draws on a relational concept of learning, based on the results of an ethnographic research project in which fab labs and makerspaces were explored in a participatory observation. In the context of the research project, the observed events were examined using a framework of practice- and discourse theory, whereby the focus was on the role of artifacts. Starting from the investigation of material-discursive practice, learning with media in this approach is understood as a performative and relational process involving heterogeneous (human and non-human) entities. The article presents key points of the research project as well as selected results and discusses them against the background of post-anthropocentric learning theories

Business case analysis of hybrid systems consisting of battery storage and power-to-heat on the German energy market

Declining prices on frequency containment reserve (FCR) markets endanger the profitability of battery energy storage systems (BESS). BESS combined with power-to-heat units could improve the economics both by supplying higher power rates on FCR markets and by converting excessive power into heat. Two cases were investigated with a techno-economic model using primary operation and market data of 2018/2019. The system amortises after 12 years with a net present value of two million € operating on the FCR market. No improvement was realized by additional arbitrage trading. Taxes, levies and charges frameworks are crucial for the economic success of hybrid systems

Neue Konzepte für virtuelle Testbeds : Data-Mining-Algorithmen für Blackbox-Optimierung basierend auf warte-freier Nebenläufigkeit und generativer Simulation

Virtual testbeds have emerged as a key technology for improving and streamlining complex engineering processes by delivering long-term simulation and assessment of complex designs in virtual environments. In contrast to existing simulation technology, virtual testbeds focus on long-term physically-based simulation of the overall design in its (virtual) environment instead of only focussing on isolated, specific parts for short periods of time. This technology has the major advantage that costly testing, prototyping, and assessment in real-life environments are replaced by a cost-efficient simulation in virtual worlds for comprehensive and long-term analysis of designs. For this purpose, engineering models and their requirements are abstracted into software simulation models and objectives which are executed in virtual assessments. Simulation models are used to predict complex, real systems which can be further a subject to random influences. These predictions are used to examine the effects of individual configuration alternatives without actually realizing them and causing possible negative effects on the real system. Virtual testbeds further offer engineers the opportunity to immersively and naturally interact with their simulation model in these virtual assessments. This enables a greater and comprehensive understanding of possible design flaws early-on in the design process for engineers because they can directly assess their design in the virtual environment, based on the simulation objectives. The fact that virtual testbeds enable these realtime interactive virtual assessments, makes their underlying software infrastructure very complex. One major challenge is to minimize the development time of virtual testbeds in order to efficiently integrate them into the overall engineering process. Usually, this can be achieved by minimizing the underlying concurrency of the testbed and by simplifying its software architecture. However, this may result in a degradation of their very concurrent and asynchronous behavior, which is usually required for immersive and natural virtual interaction. A major goal of virtual testbeds in the engineering process is to find a set of optimal configurations of the simulation model which maximizes all simulation objectives for the specified virtual assessments. Once such a set has been computed, engineers can interactively explore it in the virtual environment. The main challenge is that sophisticated simulation models and their configuration are subject to a multiobjective optimization problem, which usually can not be solved manually by engineers or simulation analysts in feasible time. This is further aggravated because the relationships between simulation model configurations and simulation objectives are mostly unknown, leading to what is known as blackbox simulations. In this thesis, I propose novel data mining algorithms for computing Pareto optimal simulation model configurations, based on an approximation of the feasible design space, for deterministic and stochastic blackbox simulations in virtual testbeds for achieving above stated goal. These novel data mining algorithms lead to an automatic knowledge discovery process that does not need any supervision for its data analysis and assessment for multiobjective optimization problems of simulation model configurations. This achieves the previously stated goal of computing optimal configurations of simulation models for long-term simulations and assessments. Furthermore, I propose two complementary solutions for efficiently integrating massively-parallel virtual testbeds into engineering processes. First, I propose a novel multiversion wait-free data and concurrency management based on hash maps. These wait-free hash maps do not require any standard locking mechanisms and enable low-latency data generation, management and distribution for massively-parallel applications. Second, I propose novel concepts for efficiently code generating above wait-free data and concurrency management for arbitrary massively-parallel simulation applications of virtual testbeds. My generative simulation concept combines a state-of-the-art realtime interactive system design pattern for high maintainability with template code generation based on domain specific modelling. This concept is able to generate massively-parallel simulations and, at the same time, model checks its internal dataflow for possible interface errors. These generative concept overcomes the challenge of efficiently integrating virtual testbeds into engineering processes. These contributions enable for the first time a powerful collaboration between simulation, optimization, visualization and data analysis for novel virtual testbed applications but also overcome and achieve the presented challenges and goals

Environmental and economic analysis of sector-integrating hybrid battery energy storage systems

Battery energy storage systems (BESS) are advocated as crucial elements for ensuring grid stability in times of increasing infeed of intermittent renewable energy sources (RES) and therefore paving the way for more sustainable energy systems. Under the current regulative framework for frequency containment reserve, BESSs are required to reserve portions of their capacity available, which limits their use for further applications. Hence, resources deployed in the BESS are not fully utilised from a macroeconomic and environmental perspective. Hybridisation of BESS facilities with consumer units, such as power-to-heat modules or electrolysers, enables unlimited energy infeed and is discussed as potential means to overcome this constraint. Simultaneously, they make use of excess RES in other carbon-intensive sectors. Whilst, a couple of studies have investigated the economic advantages of hybrid BESS, environmental consequences of hybrid systems were hardly analysed, so far. Sector integration could form an integral part of the sustainable energy transition. In this regard, including environmental aspects in such analyses are expected to turn the page favouring hybrid solutions. This study analyses the environmental and macroeconomic impacts of a hybrid pilot-plant consisting of an 18 MW Li-Ion battery and a power-to-heat unit based on the life cycle thinking approach. It is shown that different scenarios (e.g. use of curtailed RES in the heat sector) can affect the environmental and macroeconomic performance of such hybrid systems and the heat sector. Finally, recommendations are given for the further development of sector integrating solutions

Environmental and economic analysis of sector-coupling battery energy storage systems used for frequency containment reserve

Battery energy storage systems (BESSs) are advocated as crucial elements for ensuring grid stability in times of increasing infeed of intermittent renewable energy sources (RES) and are therefore paving the way for more sustainable energy systems. Providing frequency containment reserve (FCR) is an attractive business model for capital intensive stationary BESSs, but the current German FCR regulative framework restricts the BESS usage for other applications as capacity shares have to be reserved (FCR energy capacity requirement). Hence, stationary BESSs operating at the FCR market are not fully utilised from an economic and environmental perspective. Linking BESSs with other sectors as potential sinks such as power-to-heat modules or electrolysers, enables unlimited energy infeed and is discussed as potential means to diminish this constraint. Whilst, a couple of studies investigated the economic advantages of such sector-coupling BESSs, their environmental consequences were hardly analysed so far. Based on the life cycle thinking approach, the environmental and economic impacts of FCR provision in Germany by standalone and sector-coupling BESSs (i.e. with power-to-heat unit or electrolyser) were studied in this work. The sector-coupling BESSs were considered regarding different FCR energy capacity requirements (E/P ratios). It was shown that the CAPEX for the sector-coupling unit were primarily critical for the economic performance of BESSs favouring power-to-heat over electrolysers and standalone BESSs. The results of the environmental life cycle assessment indicated to potential benefits due to the reduced battery capacities depending on the varied FCR energy capacity requirement. The environmental implications of the operational stage showed that electrolysers can increase the environmental impacts by up to 10 % due to higher conversion losses compared to power-to-heat units. Finally, it was concluded that future energy system and market designs should foster the implementation of sustainable sector-coupling solutions considering technology-specific economic and environmental characteristics

Multidimensional assessment of passenger cars: Comparison of electric vehicles with internal combustion engine vehicles

In the pursuit of transforming the transportation sector towards sustainability, a technological shift in vehicle drive systems is being promoted worldwide. Conventional gasoline or diesel fueled cars powered by internal combustion engines (internal combustion engine vehicle, ICEV) are to be replaced with alternative cars that are electrically driven (electric vehicle, EV) and powered by a battery, which is either externally charged (battery-electric vehicle, BEV) or internally charged via a hydrogen fuel cell (fuel cell electric vehicle, FCEV). However, whether or not EVs are superior to ICEVs throughout their entire life cycle is still subject to debate. Though considerable numbers of environmental life cycle assessment (eLCA) studies and—to a much lesser extent—life cycle costing (LCC) and social life cycle assessment (sLCA) studies have already been conducted, their individual results alone do not allow decision-makers to draw conclusions concerning the overall sustainability performance of the various vehicle technologies. Therefore, we are presenting a novel approach to analyze ICEV-, BEV-, and FCEV-type passenger cars on a multidimensional basis. This approach is based upon and combines existing studies about eLCA, LCC, sLCA, and further assessments to carry out a comprehensive meta-analysis by using multi-criteria decision making (MCDM) methods. Through a transparent and differentiated presentation of the results, the adopted approach furthermore enables decision-makers to identify specific aspects influencing the overall performance of each vehicle technology and to take measures that allow for the implementation of sustainable vehicle concepts