Additive manufacturing (AM) processes have proven to be a perfect match for topology optimization (TO), as they are able to realize sophisticated geometries in a unique layer-by-layer manner. From a manufacturing viewpoint, however, there is a significant likelihood of process-related defects within complex geometrical features designed by TO. This is because TO seldomly accounts for process constraints and conditions and is typically perceived as a purely geometrical design tool. On the other hand, advanced AM process simulations have shown their potential as reliable tools capable of predicting various process-related conditions and defects. Thus far, geometry design by topology optimization and multiphysics manufacturing simulations have been viewed as two mostly separate paradigms, whereas one should really conceive them as one holistic computational design tool. More specifically, AM process models provide input to physics-based TO, where consequently, not only the designed component will function optimally, but also will have near-to-minimum manufacturing defects. In this regard, we aim at giving a thorough overview of holistic computational design tool concepts applied within AM. First, literature on TO for performance optimization is reviewed and then the most recent developments within physics-based TO techniques related to AM are covered. Process simulations play a pivotal role in the latter type of TO and serve as additional constraints on top of the primary end-user optimization objectives. As a natural consequence of this, a comprehensive and detailed review of non-metallic and metallic additive manufacturing simulations is performed, where the latter is divided into micro-scale and deposition-scale simulations. Material multi-scaling techniques, which are central to the process-structure-property relationships, are reviewed next, followed by a subsection on process multi-scaling techniques, which are reduced-order versions of advanced process models and are incorporable into physics-based TO due to their lower computational requirements. Finally the paper is concluded and suggestions for further research paths discussed.

Over the last 70 years, pultrusion has matured into an industry-leading process when it comes to providing high throughput and automated composite manufacture at a competitive price point. In this paper, we review recent innovations that have advanced pultrusion to a versatile manufacturing technology and thereby allowed composite materials to penetrate markets in, e.g., the automotive, construction, aerospace, and wind turbine industries. We accompany our review with discussions on how pultrusion has enabled new innovations within additive manufacturing and sustainable composite manufacturing, and finally, we provide an outlook and suggestions for where we see the potential for research and new industrial applications of pultrusion technology.

Pultruded fiber-reinforced polymer composites are susceptible to microstructural nonuni-formity such as variability in fiber volume fraction (V_f ), which can have a profound effect on process-induced residual stress. Until now, this effect of non-uniform V_f distribution has been hardly addressed in the process models. In the present study, we characterized the V_f distribution and accompanying nonuniformity in a unidirectional fiber-reinforced pultruded profile using optical light microscopy. The identified nonuniformity in V_f was subsequently implemented in a mesoscale thermal–chemical–mechanical process model, developed explicitly for the pultrusion process. In our process model, the constitutive material behavior was defined locally with respect to the corresponding fiber volume fraction value in different-sized representative volume elements. The effect of nonuniformity on the temperature and cure degree evolution, and residual stress was analyzed in depth. The results show that the nonuniformity in fiber volume fraction across the cross-section increased the absolute magnitude of the predicted residual stress, leading to a more scattered residual stress distribution. The observed V_f gradient promotes tensile residual stress at the core and compressive residual stress at the outer regions. Consequently, it is concluded that it is essential to take the effects of nonuniformity in fiber distribution into account for residual stress estimations, and the proposed numerical framework was found to be an efficient tool to study this aspect.

This study presents a detailed material characterization study of a pultrusion specific polyurethane resin system. Firstly, the chemical behaviour was characterized by utilizing differential scanning calorimetry. The cure kinetics was fitted well to an autocatalytic cure kinetics model with Arrhenius temperature dependency. The resin system did not show any inhibition time. Then, the viscosity evolution was observed using a rheometer. From these measurements, the gelation point was estimated from the criterion of cross-over point of storage and loss modulus curves. The corresponding cure degree of gelation point was found to be 0.79 using the cure kinetics model. The complex viscosity evolution through dynamic scans was predicted well with a cure degree and temperature dependent viscosity model. The elastic modulus and glass transition temperature of fully and partially cured samples were measured by means of DMA in tension mode. A five step cure hardening instantaneous linear elastic model was fitted well to a wide range of cure degree values after gelation. Lastly, the fitted material models were employed in a case study of a typical pultrusion process to visualize the effects of pulling speed on the material property evolution.

Process-induced stress and deformation are critical factors when ensuring product quality and structural integrity of composite profiles manufactured using thermoset pultrusion processes. In this paper, we present a new steady-state 3D-Eulerian numerical framework that enables 9–35 times faster computations compared to the current state-of-the-art quasi-static 3D-methods. In addition, we show how process-induced effects from the profile-advancing pulling force and an initial compressive stress state can be modelled. We demonstrate in theoretical parameter studies that the pulling force advances die-detachment and reduces die-swelling, while the initial compressive stress state has the opposite but a more pronounced effect.

This paper concerns non-isothermal flow in a thermoset resin-injection pultrusion process. Supported by temperature measurements from an industrial pultrusion line and a material characterisation study (curing kinetics, chemorheology, and permeability), the material flow was analysed for the manufacture of a thick glass-fibre profile saturated with a pultrusion-specific polyurethane resin. A central finding is that the heating configuration, together with the strongly convective flow near inlets resulted in phase transitions that were both concave and convex-shaped. This is different from existing literature that commonly describes curing being initiated from die-walls, resulting in the concave phase-transitions.

The resin injection pultrusion is an automated composite manufacturing method in which the resin is injected in a chamber. The flow and the thermo chemical mechanical (TCM) models have been studied for the pultrusion process to improve the reliability of the final products. Flow models are needed to understand and describe the fiber impregnation, filling time and presence of dry spots or voids. Also pressure field in the injection chamber can be estimated with flow models. TCM models are needed to predict residual stress distributions and to optimize the process conditions. A non-uniform fiber distribution strongly affects the results of both types of models. In this study, different strategies are carried out to implement non-uniform fiber distributions into the models. The cross-sectional image and fiber distribution of a 19×19 mm glass fiber reinforced polyester unidirectional pultruded composite is used. Non-uniform fiber distribution is observed and implemented into the flow model by means of permeability variations. The results of this study are compared with uniform fiber distribution results. In the TCM model, the non-uniform fiber volume content is implemented within different sized patches. The results show that the non-uniform fiber fraction should be taken into account for the process models of composites in order to capture the local process induced stresses and probability of dry spots or voids due to poor fiber impregnation.