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Textsammlung mit allen für den Datenschutz in Kirchen maßgeblichen Regelwerken: DSGVO, KDG, KDR-OG und DSG-EKD sowie begleitende Verordnungen KDO-DVO und ITSVO-EKD. Die vorliegende Textsammlung enthält neben dem zentralen Regelwerk, der Datenschutz-Grundverordnung (DSGVO) in ihrer letzten korrigierten Fassung vom 19. April 2018, die Normen des kirchlichen Rechts, die aufgrund der DSGVO neu erlassen wurden. Auf Seiten der katholischen Kirche sind dies das Gesetz über den Kirchlichen Datenschutz (KDG) und die Kirchliche Datenschutzregelung der Ordensgemeinschaft päpstlichen Rechts (KDR-OG); zudem findet die Verordnung zur Durchführung der Anordnung über den kirchlichen Datenschutz (KDO-DVO) weiterhin entsprechende Anwendung. Die evangelische Kirche novellierte das Kirchengesetz über den Datenschutz der Evangelischen Kirche in Deutschland (DSG-EKD) und hielt an der Verordnung zur Sicherheit der Informationstechnik (ITSVO-EKD) fest. Ergänzt wird das Werk durch Verweise auf maßgebliche Veröffentlichungen der Artikel-29-Datenschutzgruppe und der weltlichen und kirchlichen Datenschutzaufsichtsbehörden. Damit richtet sich das vorliegende Werk vor allem an kirchliche Gemeinden sowie Unternehmen in kirchlicher Trägerschaft und ihre Datenschutzbeauftragten wie gleichermaßen an private Unternehmen, Kanzleien und Berater mit kirchlicher Kundschaft bzw. Mandantschaft.
Resilience as a concept has found its way into different disciplines to describe the ability of an individual or system to withstand and adapt to changes in its environment. In this paper, we provide an overview of the concept in different communities and extend it to the area of mechanical engineering. Furthermore, we present metrics to measure resilience in technical systems and illustrate them by applying them to load-carrying structures. By giving application examples from the Collaborative Research Centre (CRC) 805, we show how the concept of resilience can be used to control uncertainty during different stages of product life.
The UN sets the goal to ensure access to water and sanitation for all people by 2030. To address this goal, we present a multidisciplinary approach for designing water supply networks for slums in large cities by applying mathematical optimization. The problem is modeled as a mixed-integer linear problem (MILP) aiming to find a network describing the optimal supply infrastructure. To illustrate the approach, we apply it on a small slum cluster in Dhaka, Bangladesh.
The energy-efficiency of technical systems can be improved by a systematic design approach. Technical Operations Research (TOR) employs methods known from Operations Research to find a global optimal layout and operation strategy of technical systems. We show the practical usage of this approach by the systematic design of a decentralized water supply system for skyscrapers. All possible network options and operation strategies are modeled by a Mixed-Integer Nonlinear Program. We present the optimal system found by our approach and highlight the energy savings compared to a conventional system design.
The overall energy efficiency of ventilation systems can be improved by considering not only single components, but by considering as well the interplay between every part of the system. With the help of the method "TOR" ("Technical Operations Research"), which was developed at the Chair of Fluid Systems at TU Darmstadt, it is possible to improve the energy efficiency of the whole system by considering all possible design choices programmatically. We show the ability of this systematic design approach with a ventilation system for buildings as a use case example.
Based on a Mixed-Integer Nonlinear Program (MINLP) we model the ventilation system. We use binary variables to model the selection of different pipe diameters. Multiple fans are model with the help of scaling laws. The whole system is represented by a graph, where the edges represent the pipes and fans and the nodes represents the source of air for cooling and the sinks, that have to be cooled. At the beginning, the human designer chooses a construction kit of different suitable fans and pipes of different diameters and different load cases. These boundary conditions define a variety of different possible system topologies. It is not possible to consider all topologies by hand. With the help of state of the art solvers, on the other side, it is possible to solve this MINLP.
Next to this, we also consider the effects of malfunctions in different components. Therefore, we show a first approach to measure the resilience of the shown example use case. Further, we compare the conventional approach with designs that are more resilient. These more resilient designs are derived by extending the before mentioned model with further constraints, that consider explicitly the resilience of the overall system. We show that it is possible to design resilient systems with this method already in the early design stage and compare the energy efficiency and resilience of these different system designs.
Highly competitive markets paired with tremendous production volumes demand particularly cost efficient products. The usage of common parts and modules across product families can potentially reduce production costs. Yet, increasing commonality typically results in overdesign of individual products. Multi domain virtual prototyping enables designers to evaluate costs and technical feasibility of different single product designs at reasonable computational effort in early design phases. However, savings by platform commonality are hard to quantify and require detailed knowledge of e.g. the production process and the supply chain. Therefore, we present and evaluate a multi-objective metamodel-based optimization algorithm which enables designers to explore the trade-off between high commonality and cost optimal design of single products.
To increase pressure to supply all floors of high buildings with water, booster stations, normally consisting of several parallel pumps in the basement, are used. In this work, we demonstrate the potential of a decentralized pump topology regarding energy savings in water supply systems of skyscrapers. We present an approach, based on Mixed-Integer Nonlinear Programming, that allows to choose an optimal network topology and optimal pumps from a predefined construction kit comprising different pump types. Using domain-specific scaling laws and Latin Hypercube Sampling, we generate different input sets of pump types and compare their impact on the efficiency and cost of the total system design. As a realistic application example, we consider a hotel building with 325 rooms, 12 floors and up to four pressure zones.
Given industrial applications, the costs for the operation and maintenance of a pump system typically far exceed its purchase price. For finding an optimal pump configuration which minimizes not only investment, but life-cycle costs, methods like Technical Operations Research which is based on Mixed-Integer Programming can be applied. However, during the planning phase, the designer is often faced with uncertain input data, e.g. future load demands can only be estimated. In this work, we deal with this uncertainty by developing a chance-constrained two-stage (CCTS) stochastic program. The design and operation of a booster station working under uncertain load demand are optimized to minimize total cost including purchase price, operation cost incurred by energy consumption and penalty cost resulting from water shortage. We find optimized system layouts using a sample average approximation (SAA) algorithm, and analyze the results for different risk levels of water shortage. By adjusting the risk level, the costs and performance range of the system can be balanced, and thus the
system’s resilience can be engineered
On obligations in the development process of resilient systems with algorithmic design methods
(2018)
Advanced computational methods are needed both for the design of large systems and to compute high accuracy solutions. Such methods are efficient in computation, but the validation of results is very complex, and highly skilled auditors are needed to verify them. We investigate legal questions concerning obligations in the development phase, especially for technical systems developed using advanced methods. In particular, we consider methods of resilient and robust optimization. With these techniques, high performance solutions can be found, despite a high variety of input parameters. However, given the novelty of these methods, it is uncertain whether legal obligations are being met. The aim of this paper is to discuss if and how the choice of a specific computational method affects the developer’s product liability. The review of legal obligations in this paper is based on German law and focuses on the requirements that must be met during the design and development process.
Nahezu 100.000 denkbare Strukturen kann ein Getriebe bei gleicher Funktion aufweisen - je nach Ganganzahl und gefordertem Freiheitsgrad. Mit dem traditionellen Ansatz bei der Entwicklung, einzelne vielversprechende Systemkonfigurationen manuell zu identifizieren und zu vergleichen, können leicht innovative und vor allem kostenminimale Lösungen übersehen werden. Im Rahmen eines Forschungsprojekts hat die TU Darmstadt spezielle Optimierungsmethoden angewendet, um auch bei großen Lösungsräumen zielsicher ein für die individuellen Zielstellungen optimales Layout zu finden.