In this preprint, we look onto the theory of linear thermoelasticity. At the beginning, this theory is shortly repeated and afterwards applied to transversely isotropic materials. Then, the corresponding weak formulation is derived, which is the starting point for a FE-discretisation. In the last part, we explain how we added this material behaviour to an adaptive Finite-Element-code and show some numerical results.

In this preprint, we look onto the theory of linear thermoelasticity. At the beginning, this theory is shortly repeated and afterwards applied to transversely isotropic materials. Then, the corresponding weak formulation is derived, which is the starting point for a FE-discretisation. In the last part, we explain how we added this material behaviour to an adaptive Finite-Element-code and show some numerical results.:1 Introduction 2 Theoretical Background 3 Special Cases of Linear Thermoelasticity 4 Weak Formulation 5 Implementation 6 Numerical Examples A. Results of the Computation

Lightweight structures became more and more important over the last years. One special class of such structures are short fibre reinforced composites, produced by injection moulding. To avoid expensive experiments for testing the mechanical behaviour of these composites proper material models are needed. Thereby, the stochastic nature of the fibre orientation is the main problem. In this thesis it is looked onto the simulation of such materials in a linear thermoelastic setting. This means the material is described by its heat conduction tensor κ(p), its thermal expansion tensor T(p), and its stiffness tensor C(p). Due to the production process the internal fibre orientation p has to been understood as random variable. As a consequence the previously mentioned material quantities also become random. The classical approach is to average these quantities and solve the linear hermoelastic deformation problem with the averaged expressions. Within this thesis the incorpora- tion of this approach in a time and memory efficient manner in an existing finite element software is shown. Especially for the time and memory efficient improvement several implementation aspects of the underlying software are highlighted. For both - the classical material simulation as well as the time efficient improvement of the software - numerical results are shown. Furthermore, the aforementioned classical approach is extended within this thesis for the simulation of the thermal stresses by using the stochastic nature of the heat conduc tion. This is done by developing it into a series w.r.t. the underlying stochastic. For this series known results from uncertainty quantification are applied. With the help of these results the temperature is developed in a Taylor series. For this Taylor series a suitable expansion point is chosen. Afterwards, this series is incorporated into the computation of the thermal stresses. The advantage of this approach is shown in numerical experiments.