A Framework for Fatigue Analysis of Carbon Fiber Reinforced Polymer Structures

Sammanfattning: Our society depends on functional road communication, and Heavy Duty Vehicles (HDVs) offer convenient and limitless possibilities of transport and services. However, HDVs account for a quarter of the European Union's CO2 road emissions. There is a substantial need to reduce the CO2 emissions of HDVs to ensure a low negative environmental impact. To reduce the CO2 emissions of HDVs, their energy usage must be reduced. One way to reduce energy usage is to improve the structural efficiency of the vehicle and use high-performance composite materials such as Carbon Fiber Reinforced Polymers (CFRP). HDVs are continuously exposed to road-induced vibrations, and the fatigue loading often sets the design criteria for HDV components. Therefore, flexible simulation frameworks are needed to encourage and simplify the implementation of composite materials in engineering structural designs dimensioned for fatigue. This doctoral thesis proposes a probabilistic modeling framework for fatigue assessment of CFRP. The thesis aims to provide knowledge and insights into the fatigue modeling of composite materials and a better understanding of the proposed modeling framework.A combination of experimental investigations and numerical modeling is conducted. To carry out fatigue testing, a fatigue testing procedure was established. Fatigue testing of anisotropic material involves accurately selecting process parameters to obtain specimens that fail in the gauge length. The fatigue damage progression of CFRP laminates was monitored throughout the fatigue tests by analyzing the stiffness change, finding that the initial stiffness loss can be related to the damage development of the specimens. Composite materials are multi-scale, where constituents and damage are of a much lower order length scale than the laminate and structure. Therefore, the numerical modeling uses a two-scale modeling approach to capture the variability of a composite laminate. First, the micro-scale modeling uses Representative Volume Elements (RVE) to determine the effective macro-mechanical properties of a composite lamina. The RVE models are generated based on experimental data capturing micro-geometrical variations that could affect the composite laminate behavior. Second, macro-scale models, capturing the complexity and variability of composite materials, are used in a probabilistic modeling approach for fatigue assessment. A Weibull distribution in a weakest link formulation is used to consider the combined effect of material variability of a CFRP laminate. The work proposes a probabilistic fatigue modeling framework for implementation in an industrial design process. The methodology is highly valuable in the progress of fatigue modeling of composites. It aims to encourage and simplify the implementation of composites in engineering structural designs and components dimensioned for fatigue. The insights and outcomes of this doctoral thesis play a crucial role in the advancement of future resource-efficient vehicles and an optimal selection of materials to design for the right material in the right place.