Interconnected, autonomously driving cars shall realize the vision of a zero-accident, low energy mobility in spite of a fast increasing traffic volume. Tightly interconnected medical devices and health care systems shall ensure the health of an aging society. And interconnected virtual power plants based on renewable energy sources shall ensure a clean energy supply in a society that consumes more energy than ever before. Such open systems of systems will play an essential role for economy and society.
Open systems of systems dynamically connect to each other in order to collectively provide a superordinate functionality, which could not be provided by a single system alone. The structure as well as the behavior of an open system of system dynamically emerge at runtime leading to very flexible solutions working under various different environmental conditions. This flexibility and adaptivity of systems of systems are a key for realizing the above mentioned scenarios.
On the other hand, however, this leads to uncertainties since the emerging structure and behavior of a system of system can hardly be anticipated at design time. This impedes the indispensable safety assessment of such systems in safety-critical application domains. Existing safety assurance approaches presume that a system is completely specified and configured prior to a safety assessment. Therefore, they cannot be applied to open systems of systems. In consequence, safety assurance of open systems of systems could easily become a bottleneck impeding or even preventing the success of this promising new generation of embedded systems.
For this reason, this thesis introduces an approach for the safety assurance of open systems of systems. To this end, we shift parts of the safety assurance lifecycle into runtime in order to dynamically assess the safety of the emerging system of system. We use so-called safety models at runtime for enabling systems to assess the safety of an emerging system of system themselves. This leads to a very flexible runtime safety assurance framework.
To this end, this thesis describes the fundamental knowledge on safety assurance and model-driven development, which are the indispensable prerequisites for defining safety models at runtime. Based on these fundamentals, we illustrate how we modularized and formalized conventional safety assurance techniques using model-based representations and analyses. Finally, we explain how we advanced these design time safety models to safety models that can be used by the systems themselves at runtime and how we use these safety models at runtime to create an efficient and flexible runtime safety assurance framework for open systems of systems.
Compared to traditional software design, the design of embedded software is even more challenging: In addition to the correct implementation of the systems, one has to consider non-functional constraints such as real-time behavior, reliability, and energy consumption. Moreover, many embedded systems are used in safety-critical applications where errors can lead to enormous damages and even to the loss of human live. For this reason, formal verification is applied in many design flows using different kinds of formal verification methods.
The synchronous model of computation has shown to be well-suited in this context. Its core is the paradigm of perfect synchrony which assumes that the overall system behavior is divided into a sequence of reactions, and all computations within a reaction are completed in zero time. This temporal abstraction simplifies reactive programming in that developers do not have to bother about many low-level details related to timing, synchronization and scheduling. This thesis is dedicated to this design flow, and it presents the author's contributions to it.
The primary objective of this work is the development of robust, accurate and efficient simulation methods for the optimal control of mechanical systems, in particular of constrained mechanical systems as they appear in the context of multibody dynamics. The focus is on the development of new numerical methods that meet the demand of structure preservation, i.e. the approximate numerical solution inherits certain characteristic properties from the real dynamical process.
This task includes three main challenges. First of all, a kinematic description of multibody systems is required that treats rigid bodies and spatially discretised elastic structures in a uniform way and takes their interconnection by joints into account. This kinematic description must not be subject to singularities when the system performs large nonlinear dynamics. Here, a holonomically constrained formulation that completely circumvents the use of rotational parameters has proved to perform very well. The arising constrained equations of motion are suitable for an easy temporal discretisation in a structure preserving way. In the temporal discrete setting, the equations can be reduced to minimal dimension by elimination of the constraint forces. Structure preserving integration is the second important ingredient. Computational methods that are designed to inherit system specific characteristics – like consistency in energy, momentum maps or symplecticity – often show superior numerical performance regarding stability and accuracy compared to standard methods. In addition to that, they provide a more meaningful picture of the behaviour of the systems they approximate. The third step is to take the previ- ously addressed points into the context of optimal control, where differential equation and inequality constrained optimisation problems with boundary values arise. To obtain meaningful results from optimal control simulations, wherein energy expenditure or the control effort of a motion are often part of the optimisation goal, it is crucial to approxi- mate the underlying dynamics in a structure preserving way, i.e. in a way that does not numerically, thus artificially, dissipate energy and in which momentum maps change only and exactly according to the applied loads.
The excellent numerical performance of the newly developed simulation method for optimal control problems is demonstrated by various examples dealing with robotic systems and a biomotion problem. Furthermore, the method is extended to uncertain systems where the goal is to minimise a probability of failure upper bound and to problems with contacts arising for example in bipedal walking.
The main goal of this work is to examine various aspects of `inelastic continuum mechanics': first, fundamental aspects of a general finite deformation theory based on a multiplicative decomposition of the deformation gradient with special emphasis on the incompatibility of the so-called intermediate configuration are discussed in detail. Moreover, various balance of linear momentum representations together with the corresponding volume forces are derived in a configurational mechanics context. Subsequent chapters are consequently based on these elaborations so that the applied multiplicative decomposition generally serves as a fundamental modelling concept in this work; after generalised strain measures are introduced, a kinematic hardening model coupled with anisotropic damage, a substructure evolution framework as well as two different growth and remodelling formulations for biological tissues are presented.
A general framework for the thermodynamics of open systems is developed in the spatial and the material setting. Special emphasis is placed on the balance of mass which is enhanced by additional source and flux terms. Different solution strategies within the finite element technique are derived and compared. A number of numerical examples illustrates the features of the proposed approach.