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Possessing excellent stiffness and strength, carbon fiber reinforced polymers (CFRPs), however, have a limited toughness. The first damage in CFRPs usually occurs in transverse plies where stiff carbon fibers are microscopic stress concentrators in the matrix. The toughness of CFRPs can be enhanced by adding carbon nanotubes (CNTs) – nano-reinforcements of a high aspect ratio and exceptional stiffness – into the polymer. CNTs are believed to redistribute matrix stresses by lowering the matrix stress concentration scale from micro-level – around carbon fibers – to nano-level – around CNT tips – thereby hindering damage onset.The aim of this work was to understand the effect of CNTs on the stress distribution in CFRPs using a numerical approach. A novel finite element model was developed that represents thousands of individual CNTs with a “true-to-life” morphology in a composite with microscopic fibers in a single simulation. A numerically efficient “embedded elements” method was verified against analytical and numerical solutions. The developed model captured the matrix stresses between individual CNTs, thereby allowing the microscopic matrix stresses within the CNT-rich matrix regions to be captured as well.The discovered heterogeneity of the matrix stress fields in nano-engineered fiber reinforced composites with CNTs (nFRCs) was found to be strongly affected by the length, position, orientation, waviness and concentration of the CNTs. CNT agglomerates were shown to behave as stiff microscopic particles and to exacerbate the existent stress concentrations. CNTs introduced at fiber surfaces by fiber grafting or sizing/coating with CNTs were found to increase stresses in resin-rich zones between the fibers. CNTs grown on fibers were also shown to effectively suppress stress concentrations in the matrix close to the fiber surface.The conventional CNT configurations in FRCs were shown to be suboptimal for the purpose of suppressing microscopic stress concentrations: this was at the cost of stress magnification in other matrix regions. To address this issue, a novel concept of intelligent hierarchical nFRCs was proposed and modeled. Combining precise localization and orientation of CNTs, a complete elimination of microscopic inter-fiber stress concentrations was achieved by aligned CNT “bridges” constructed interdependently with the fiber positions in FRC.The modeling results presented in this thesis are the first step towards practical realizations of such hierarchical structures. Designed to suppress micro-scale stress concentrations in the material, the intelligent CNT networks are, hence, designed to postpone the damage onset in the fiber composites.

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Ease of manufacturing and favorable performance properties at a low weight make short fiber reinforced composites (SFRC) an attractive material for industrial applications. A pre-requisite for industrial deployment is the proper understanding and simulation of damage and fatigue in SFRC, which is still a challenge today. Typically SFRC components have a variable local statistical distribution of fiber orientation leading to different material properties and mechanical and fatigue behavior at different points. For a component simulation, each element in the FE model corresponds to the center of a Representative Volume Element (RVE). The effective stiffness, damage and fatigue behavior must be modelled for every element.First, different approaches to the appropriate mean field homogenization scheme are compared. The predictive abilities for stresses in individual inclusions are compared against full FE model results. It is confirmed that the full Mori-Tanaka formulation is the adequate homogenization approach for damage modelling in SFRC.Next, a micromechanical model for modelling the non-linear stress-strain behavior of SFRC is developed. Particular attention is given to fiber-matrix debonding. Debonded fibersnbsp;treated by replacing them with equivalent bonded inclusion (EqBI) with modifiednbsp;FE validation is used to confirm the mechanical equivalence of the debonded fiber and the EqBI. Apart from fiber-matrix debonding, matrix non-linearity is also modelled. A method to predict the ultimate tensile strength of the SFRC is proposed and experimentally validated.Furthermore, a hybrid multiscale method is presented to predict the local SN curves of SFRC. This method involves both multiscale mechanics and tests. Both the SN curve predictions and key assumptions of the scheme are validated with the help of extensive experiments. Apartnbsp;own experiments, the proposed models (for both static loading and fatigue) are validated using representative published datasets. Finally a frameworknbsp;fatigue simulation of an SFRC component is proposed. Static and fatigue tests are performed on a representative industrial component and the framework for fatigue simulation is validated.Apartnbsp;elastic properties of the constituents (matrix and fiber) and strength of the matrix, the input for proposed fatigue simulation methodology is only one input SN-curve with no specific requirements to the fiber orientation of the test coupon. Test coupons could have either uniform fiber orientation in the thickness or aldquo;skin core” orientation variation. The fact that limited test data is required could be a breakthrough in view of further industrial deployment ofnbsp;solutions in industry, since collection of experimental fatigue data is often a major bottleneck for industrial deployment.