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Hampshire
Originally known as Henpeck, the village of Hampshire began when Zenas Allen of Vermont became its first settler in 1836. From 1837 to 1845, Henpeck existed along the Chicago-Galena Stagecoach Trail at Old State (Route 20), Big Timber, and Brier Hill Roads. Hampshire Township was organized in 1845, and the village's name was changed to Hampshire. In 1876, the village relocated so that it could be along the Chicago-Pacific Railroad line. Hampshire was officially incorporated that same year with Samuel Rowell as its first village president. In 1893, the farming community grew to become the second largest milk-producing and shipping station in Illinois. Residents have served in the US military since the Civil War. During World War II, Hampshire was chosen as the site for a prisoner of war camp for 250 German soldiers who worked at the Inderrieden Canning Company. In 1994, the village annexed north to the I-90/US 20 interchange, which included the community's original Henpeck area.
Process simulation of wet compression moulding for continuous fibre-reinforced polymers
Interdisciplinary development approaches for system-efficient lightweight design unite a comprehensive understanding of materials, processes and methods. This applies particularly to continuous fibre-reinforced plastics (CoFRPs), which offer high weight-specific material properties and enable load path-optimised designs. This thesis is dedicated to understanding and modelling Wet Compression Moulding (WCM) to facilitate large-volume production of CoFRP structural components.
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AI and IoT Meet Mobile Machines: Towards a Smart Working Site
Infrastructure construction is society's cornerstone and economics' catalyst. Therefore, improving mobile machinery's efficiency and reducing their cost of use have enormous economic benefits in the vast and growing construction market. In this thesis, I envision a novel concept smart working site to increase productivity through fleet management from multiple aspects and with Artificial Intelligence (AI) and Internet of Things (IoT).
Simulation of damage mechanisms in weave reinforced materials based on multiscale modeling
A weave reinforced composite material with a thermoplastic matrix is investigated by using a multiscale chain to predict the macroscopic material behavior. A large-strain framework for constitutive modeling with focus on material non-linearities, i.e. plasticity and damage is defined. The ability of the geometric and constitutive models to predict the deformation and failure behavior is demonstrated by means of selected examples.
Manufacturing-constrained multi-objective optimization of local patch reinforcements for discontinuous fiber reinforced composite parts
In this work, contributes to the optimization of local continuous fiber reinforcement patches, under consideration of manufacturing constraints. This approach requires specific optimization strategies. Therefore, an multi-objective optimization strategy for the placement of local reinforcement patches, under consideration of manufacturing constraints, has been developed. During the multi objective optimization, structural and process related objectives are considered.
Probabilistic Prediction of Energy Demand and Driving Range for Electric Vehicles with Federated Learning
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.
