This work presents novel simulation techniques for injection molding of fiber reinforced polymers. These include approaches for anisotropic flow modeling, hydrodynamic forces from fluid on fibers, contact forces between fibers, a novel fiber breakage modeling approach and anisotropic warpage analysis. Due to the coupling of fiber breakage and anisotropic flow modeling, the fiber breakage directly influences the modeled cavity pressure, which is validated with experimental data.

In this work, an extension of the federated averaging algorithm, FedAvg-Gaussian, is applied to train probabilistic neural networks. The performance advantage of probabilistic prediction models is demonstrated and it is shown that federated learning can improve driving range prediction. Using probabilistic predictions, routing and charge planning based on destination attainability can be applied. Furthermore, it is shown that probabilistic predictions lead to reduced travel time.

This work describes a method for weighted least squares approximation of an unbounded number of data points using a B-spline function. The method can shift the bounded B-spline function definition range during run-time. The approximation method is used for optimizing velocity trajectories for an electric vehicle with respect to travel time, comfort and energy consumption. The trajectory optimization method is extended to a driver assistance system for automated vehicle longitudinal control.

Ihrer Arbeit in der Originalsprache: This work aims at identifying relevant road surface characteristics to mitigate tire-road noise of free-rolling tires using a systematic approach. As using open porous roads is already known as an efficient measure to reduce tire rolling noise, this study will focus on compact road surfaces which have a low acoustic absorption. Measurements on standardized ISO 10844 test tracks and on public roads are used to study the norm's representativity and its completeness.

With the further development of automated driving, the functional performance increases resulting in the need for new and comprehensive testing concepts. This doctoral work aims to enable the transition from quantitative mileage to qualitative test coverage by aggregating the results of both knowledge-based and data-driven test platforms. The validity of the test domain can be extended cost-effectively throughout the software development process to achieve meaningful test termination criteria.

This book is a printed edition of the Special Issue "Discontinuous Fiber Composites" that was published in J. Compos. Sci.

This book covers fundamental principles and numerical methods relevant to the modeling of the injection molding process. As injection molding processing is related to rheology, mechanical and chemical engineering, polymer science and computational methods, and is a rapidly growing field, the book provides a multidisciplinary and comprehensive introduction to the subjects required for an understanding of the complex process. It addresses the up-to-date status of fundamental understanding and simulation technologies, without losing sight of still useful classical approaches. The main chapters of the book are devoted to the currently active fields of flow-induced crystallization and orientation evolution of fiber suspensions, respectively, followed by detailed discussion of their effects on mechanical property, shrinkage and warpage of injection-molded products. The level of the proposed book will be suitable for interested scientists, R&D engineers, application engineers, and graduate students in engineering.