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 extensively reviews Polypropylene (PP), the second most widely produced thermoplastic material, having been produced for over 60 years. Its synthesis, processing and application are still accompanied by vigorous R&D developments because the properties of PP are at the borderline between those of commodity and engineering thermoplastics. Readers are introduced to various tacticities and polymorphs of PP, and their effects on structural properties. Further, the book addresses the control of optical properties using nucleants, provides strategies for overcoming the limited cold/impact resistance of PP, examines in detail the effects of recycling, and presents guidelines for the property modification of PPs through foaming, filling and reinforcing with respect to target applications. Special attention is paid to descriptions and models of properties as a function of morphological variables. Last but not least, the book suggests potential practical applications of PP-based systems, especially in the packaging, appliances, building/construction, textile and automotive sectors. Each chapter, written by internationally respected scientists, reflects the current state-of-art in the respective field and offers a vital source of information for students, researchers and engineers interested in the morphology, properties, testing and modeling of PP and PP-based systems. The content is indispensable to the appropriate application of PPs and related composites.