Abstract: Buckling of slender bars subject to axial compressive loads represents a critical design constraint for light-weight truss structures. Active buckling control by actuators provides a possibility to increase the maximum bearable axial load of individual bars and, thus, to stabilize the truss structure.For reasons of cost, it is in general not economically viable to use such actuators in each bar of the truss structure. Hence, it is an important practical question where to place these active bars. Optimized structures, especially when coupled with active elements to further decrease the number of necessary bars, however, lead to designs, which, while cost-efficient, are especially prone to bardamages, caused, e.g., by material failures. Therefore, this paper presents a mathematical optimization approach to optimally place active bars for buckling control in a way that secures both buckling and general stability constraints even after failure of any combination of a certain number of bars. This allows us to increase the resilience of the system and guarantee stable behavior even in case of failures.
Abstract: We consider the problem of finding the optimal shape of a force-sensing element which is integrated into a tubular structure. The goal is to make the sensor element sensitive to specific forces and insensitive to other forces. The problem is stated as a PDE-constrained minimization program with both nonconvex objective and nonconvex constraints. The optimization problem depends on uncertain parameters, because the manufacturing process of the structures underlies uncertainty, which causes unwanted deviations in the sensory properties. In order to maintain the desired properties of the sensor element even in the presence of uncertainty, we apply a robust optimization method to solve the uncertain program.The objective and constraint functions are continuous but not differentiable with respect to the uncertain parameters, so that existing methods for robust optimization cannot be applied. Therefore, we consider the nonsmooth robust counterpart formulated in terms of the worst-case functions, and show that subgradients can be computed efficiently. We solve the problem with a BFGS--SQP method for nonsmooth problems recently proposed by Curtis, Mitchell and Overton.
Abstract: Ontologies represent inter-related semantic information. The automated integration of new knowledge helps to detect and reduce data-induced conflicts and model-based uncertainty in ontologies. However, automatic extension of an existing ontology from heterogeneous distributed sources can often lead to incomplete and contradictory entities. In order to resolve these conflicts and to complete entities, inductive inference mechanisms should be applied in addition to the deductive mechanisms already in use. This paper first describes various inductive inference mechanisms and compares these with each other according to pre-defined requirements and other criteria. Finally, the mechanisms’ suitability for an information model for the exchange and visualization of uncertainty in load-carrying systems and possible combinations of the individual mechanisms are discussed, also with respect to the necessity of further modifications of these mechanisms.
Abstract: Narrow tolerances are commonly used to control uncertainty in the production of technicalcomponents. However, narrow tolerances lead to financial expense and limit flexibility. In this paperthe concept of a resilient process chain is presented. This concept covers the product life cycle phases ofproduction and usage. It is enabled by the digitalization in mechanical engineering and offers access tovariable process windows instead of rigid tolerances. First steps of this concept are then applied to the TU Darmstadt active air spring. The active air spring can be used to increase the driving comfort in avehicle or, for instance, to minimize kinetosis during autonomous driving. The focus hereby is toidentify possible production influences on the behaviour of the components usage. For this purpose, theactuator of the active air spring is specifically manufactured with typical uncertainty of high precisionmachining of the bore and characterized experimentally in a test rig. The results show an influenceof the production on the efficiency of the actuator. The measurements are fundamental to establish aresilient process chain on the active air spring.
Abstract: Newly developed technologies and methods for the purpose of controlling uncertainty in technical systems must be proven and validated against reliable experimental studies. The availability of descriptive metadata is mandatory to enable long term usability and sharing of such experimental research data. This article introduces a concept for a software independent solution for managing data in collaborative research environments. The proposed approach leverages the advantages of capturing metadata in a uniform, modular data structure and providing software independent access to a centralized data repository as well as its contents by means of a web-application. The article presents a prototype implementation of the proposed approach and discusses its application on the demonstrator test rig of a collaborative research centre in the field of mechanical engineering.
Abstract: 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.
Abstract: Resilience of a technical system is the ability to overcome minor failures and thus to avoid a complete breakdown of its vital functions. A possible failure of the system's components is one critical case the system designer should keep in mind. From another perspective resilience can be interpreted as the existence of alternative paths in a process network if resources break down. In this context we deal with process networks corresponding to systems which must be designed to operate in different scenarios. In order to ensure the system's functionality and to step in as a replacement in case of failure a set of optional resources must be available. This means that the process network must have several degrees of freedom allowing to react to uncertain events. With those restrictions we try to find a preferably resource-efficient network. Hence, an optimization problem arises which can be modeled using quantified mixed-integer linear programming. As an example of a process which can be modeled using process networks we investigate the problem of finding cost-efficient resilient topologies of fluid systems that are able to fulfill different load scenarios.
Abstract: High-rise water supply systems provide water flow and suitable pressure in all levels of tall buildings. To design such state-of-the-art systems, the consideration of energy efficiency and the anticipation of component failures are mandatory. In this paper, we use Mixed-Integer Nonlinear Programming to compute an optimal placement of pipes and pumps, as well as an optimal control strategy.Moreover, we consider the resilience of the system to pump failures. A resilient system is able to fulfill a predefined minimum functionality even though components fail or are restricted in their normal usage. We present models to measure and optimize the resilience. To demonstrate our approach, we design and analyze an optimal resilient decentralized water supply system inspired by a real-life hotel building.
Abstract: In the field of autonomous systems, manufacturers still face a high level of uncertainty, especially in the development phase. These systems are characterized by their ability to adapt to new conditions without any further action by the developer. One of the future challenges will be that autonomous systems continue to evolve during the use phase. These changes are hard to predict because they are affected by the specific product environment. Nevertheless, manufacturers are exposed to liability claims if damage events occur. Uncertainty about the question of the specific conditions for liability results in an incalculable risk for the manufacturer. This paper takes an interdisciplinary approach. The first step is to identify the manufacturers' legal obligations for the entire product lifecycle. These obligations are then checked for their technical feasibility and evaluated in terms of efficiency. Manufacturers can only be obligated to take measures that are sustainable. The aim of the study is to translate the legal requirements for manufacturers of autonomous systems into concrete solutions that are both practical and manageable.
Abstract: 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.