Topology optimization methods are used to design high performance structural components that often have complex geometric layouts. In several industries, components are required to be cleanable, and for this research cleaning by jetting is considered. Thus, being able to ensure jet access on the entire surface of a structure is of interest in topology optimization. In this paper, a jetting filter is proposed, that turns a blueprint design into a jet accessible design. Two methods are considered to find an access field for each jet. These individual jet access fields are then combined into a total access field, to obtain a cleanable design. Consistent sensitivity analysis is used and the additional computational cost of the jetting filter is modest compared to the finite element analysis. The performance of the two methods is demonstrated with 2D and 3D numerical examples for mechanical and thermal topology optimization problems.

Wire arc additive manufacturing (WAAM) enables the manufacturing of efficient and lightweight structural elements in which material can be utilised wherever needed in an optimised shape, in contrast to standard prismatic profiles used in construction. However, the specific energy consumption (SEC) of WAAM is higher than that of conventional manufacturing (CM) techniques (i.e., hot-rolling) for standard profiles. Therefore, it is an open question whether the material savings through computational design realised via WAAM is environmentally beneficial or not. This systematic study aims to provide a better understanding of the environmental impact of hybrid manufacturing, which is defined as the combination of WAAM and CM rather than using any of them alone. Topology optimisation (TO) is used to design a series of beams with an identical performance (i.e., stiffness) but with a reduced material consumption depending on the hybrid ratio. The environmental impact of the designs has been used to determine when and how hybridisation can become advantageous. The results show that although the optimal proportions of WAAM and CM are dependent on their relative SEC, the hybrid solutions have always been environmentally superior compared to that of WAAM or CM alone for the realistic SEC values, exhibiting up to a 60% reduction in environmental impact compared to that of CM.

Overheating is a major issue especially in metal Additive Manufacturing (AM) processes, leading to poor surface quality, lack of dimensional precision, inferior performance and/or build failures. A 3D density-based topology optimization (TO) method is presented which addresses the issue of local overheating during metal AM. This is achieved by integrating a simplified AM thermal model and a thermal constraint within the optimization loop. The simplified model, recently presented in literature, offers significant computational gains while preserving the ability of overheating detection. The novel thermal constraint ensures that the overheating risk of optimized designs is reduced. This is fundamentally different from commonly used geometry-based TO methods which impose a geometric constraint on overhangs. Instead, the proposed approach takes the process physics into account. The proposed method is validated via an experimental comparative study. Optical tomography (OT) is used for in-situ monitoring of process conditions during fabrication and obtained data is used for evaluation of overheating tendencies. The novel TO method is compared with two other methods: standard TO and TO with geometric overhang control. The experimental data reveals that the novel physics-based TO design experienced less overheating during the build as compared to the two classical designs. A study further investigated the correlation between overheating observed by high OT values and the defect of porosity. It shows that overheated regions indeed show higher defect of porosity. This suggests that geometry-based guidelines, although enhance printability, may not be sufficient for eliminating overheating issues and related defects. Instead, the proposed physics-based method is able to deliver efficient designs with reduced risk of overheating.

Wire and Arc Additive Manufacturing (WAAM) emerged as a manufacturing process for large scale structures with extensive form and design freedom. WAAM can be fully exploited once the relation between the transient thermal history and its relation to microstructure development and resultant mechanical properties is established. This relation can be further used for computational design tools such as Topology Optimization. This paper presents a model to predict the relation between the thermal history and solid-state phase transformations in a widely applicable High Strength Low Alloy steel ER110S-G. The transient thermal history of parts manufactured by WAAM is modelled using finite element analysis. The modelled thermal history is validated with thermocouple measurements. Our results show that a critical cooling cycle is responsible for the solid-state phase transformation in an AM part. The cooling rate of this particular cooling cycle is superimposed onto an experimentally constructed Continuous Cooling Transformation (CCT) diagram to determine the local solid-state phase fractions. The predicted phase fractions in three wall samples with different design and processing conditions of AM parts are used to predict the hardness. The predicted hardness is 10% higher than the measured hardness of AM samples. The effect of tempering is also considered in the model through JMAK equation. The results show that the tempering is caused in regions with high martensite content and it lowers the hardness by 8 − 10%. The micrographs of the AM parts show that the microstructural features are same for the AM parts with similar critical cooling rates.

Computational process modelling of metal additive manufacturing has gained significant research attention in recent past. The cornerstone of many process models is the transient thermal response during the AM process. Since deposition-scale modelling of the thermal conditions in AM is computationally expensive, spatial and temporal simplifications, such as simulating deposition of an entire layer or multiple layers, and extending the laser exposure times, are commonly employed in the literature. Although beneficial in reducing computational costs, the influence of these simplifications on the accuracy of temperature history is reported on a case-by-case basis. In this paper, the simplifications from the existing literature are first classified in a normalised simplification space based on assumptions made in spatial and temporal domains. Subsequently, all types of simplifications are investigated with numerical examples and compared with a high-fidelity reference model. The required numerical discretisation for each simplification is established, leading to a fair comparison of computational times. The holistic approach to the suitability of different modelling simplifications for capturing thermal history provides guidelines for the suitability of simplifications while setting up a thermal AM model.

Sub-size specimen testing offers a potentially elegant solution to accompany fatigue life assessments in determining vital fatigue parameters such as effective fatigue crack growth propagation thresholds (ΔK_th,eff). Additively manufactured parts stand to benefit from this in potential build-by-build fatigue validation without foregoing process-inherent material saving and low lead times. In this study, sub-size Laser Powder Bed Fusion (LPBF) produced Ti-6Al-4 V SENB specimens built in two orientations with stress relieved and annealed material states are considered. Scanning electron microscopy with electron backscatter diffraction is used to consider both meso- and microstructural features, complimented by digital image correlation (DIC) for determining local stress intensity and triaxiality around the crack tip. Results show inconsistent near-threshold fatigue behaviour linked to the microstructure of annealed material, where the fatigue threshold in sub-size specimens is reduced. Furthermore, reducing specimen size influences both in- and out-of-plane crack tip constraint, with higher constraint experienced by the sub-size specimens. Overall, this study presents and discusses the domain and suitability in using sub-size specimen FCGR threshold testing for LPBF produced Ti-6Al-4 V builds considering their unique meso- and microstructural features.

In metal Additive Manufacturing (AM), the deposited material is subjected to a series of heating and cooling cycles. The locally occurring temperature extremes and cooling rates determine solid-state phase fractions, material microstructure, texture, and ultimately the local material properties. As the shape of a part determines the local thermal history during AM, this offers an opportunity to influence these material properties through design. In this paper, we present a way to obtain desired properties by controlling the local thermal history. This is achieved through topology optimization of the printed part while considering its entire transient thermal history. As an example of this approach, this work focuses on high strength low alloy steels, where resulting phase fractions significantly influence mechanical properties such as yield strength and ductility. These solid-state phase fractions depend on cooling rates in a particular critical temperature range. The phase composition and hence the local yield strength in target regions can be controlled by constraining the cooling time in this range. Numerical examples illustrate the capability of the proposed approach in adapting part designs to achieve various desired material properties.

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.

A novel constraint to prevent local overheating is presented for use in topology optimization (TO). The very basis for the constraint is the Additive Manufacturing (AM) process physics. AM enables fabrication of highly complex topologically optimized designs. However, local overheating is a major concern especially in metal AM processes leading to part failure, poor surface finish, lack of dimensional precision, and inferior mechanical properties. It should therefore be taken into account at the design optimization stage. However, including a detailed process simulation in the optimization would make the optimization intractable. Hence, a computationally inexpensive thermal process model, recently presented in the literature, is used to detect zones prone to local overheating in a given part geometry. The process model is integrated into density-based TO in combination with a robust formulation, and applied in various numerical test examples. It is found that existing AM-oriented TO methods which rely purely on overhang control do not ensure overheating avoidance. Instead, the proposed physics-based constraint is able to suppress geometric features causing local overheating and delivers optimized results in a computationally efficient manner.

A remarkable elastic anisotropy in plates of austenitic stainless steel produced by the Wire and Arc Additive Manufacturing process is recently reported. The Young's modulus depends on the angle of orientation with respect to the material deposition direction. Here, for the first time, this anisotropy is exploited to maximize structural stiffness by simultaneously optimizing the structural design layout and the local deposition path direction for WAAM. The results obtained indicate deposition that is commonly preferred along the load-path directions for WAAM is sub-optimal and stiffness can be increased at least 53% upon optimizing the deposition directions.

Discrete dislocation plasticity is a modeling technique that treats plasticity as the collective motion of dislocations. The dislocations are described through their elastic Volterra fields, outside of a cylindrical core region, with a few Burgers vectors of diameter. The contribution of the core fields to the dislocation dynamics is neglected, because it is assumed that their range is too short to be of influence. The aim of this work is to assess the validity of this assumption. In recent ab-initio studies it has been demonstrated that the dislocation core fields are significant up to a distance of ten Burgers vector from the dislocation line. This is a longer range influence than expected and can give rise to changes in the evolving dislocation structure and in the overall response of a plastically deforming body. It is indeed experimentally observed that dislocations pile up against strong interfaces, and that the spacing between dislocations at the front of these pile-ups can be less than ten Burgers vectors. In this work, 2-D discrete dislocation plasticity simulations are performed to investigate the effect of core fields on edge dislocation interactions. The results of the simulations, which include core fields for the first time, show indeed that dislocations that are very closely spaced experience additional glide or climb due to core fields. The effect is however negligible when compared to glide and climb due to Volterra fields or due to the external load.

Hydrogen plays a vital role in the utilisation of renewable energy, but ingress and diffusion of hydrogen in a gas turbine can induce hydrogen embrittlement on its metallic components. This paper aims to investigate the hydrogen transport in a non-hydride forming alloy such as Alloy 690 used in gas turbines inspired by service conditions of turbine blades, i.e. under the combined effects of stress and temperature. An appropriate hydrogen transport equation is formulated, accounting for both stress and temperature distributions of the domain in the non-hydride forming alloy. Finite element (FE) analyses are performed to predict steady-state hydrogen distribution in lattice sites and dislocation traps of a double notched specimen under constant tensile load and various temperature fields. Results demonstrate that the lattice hydrogen concentration is very sensitive to the temperature gradients, whilst the stress concentration only slightly increases local lattice hydrogen concentration. The combined effects of stress and temperature result in the highest concentration of the dislocation trapped hydrogen in low-temperature regions, although the plastic strain is only at a moderate level. Our results suggest that temperature gradients and stress concentrations in turbine blades due to cooling channels and holes make the relatively low-temperature regions susceptible to hydrogen embrittlement.

Topology optimization typically generates designs that exhibit significant geometrical complexity, which can pose difficulties for manufacturing and assembly. The number of occurrences of an important design feature, in particular intersections, increases with geometrical complexity. Intersections are essential for load transfer in many engineering structures. For certain upcoming manufacturing processes, such as direct metal deposition, the size of an intersection plays a role. During metal deposition, slim intersections are more prone to manufacturing defects than bulkier ones. In this study, a computationally tractable methodology is proposed to both control occurrence and size of intersections in topology optimization. To identify intersections, a stress-based quantity is proposed, denoted as Intersection Indicator. This quantity is based on the local degree of multi-axiality of the stress state, and identifies material points at intersections. The proposed intersection indicator can identify intersections in both single as well as multi-load case problems. To detect the relative size of intersections, the average density in the vicinity of an intersection is used to penalize or promote intersection sizes of interest. The corresponding sensitivity analysis involves solving a set of adjoint equations for each load case. Numerical 2D experiments demonstrate a controllable reduction of penalized slim intersections compared to the designs obtained from conventional compliance minimization. The overall geometrical complexity of the design is reduced due to the promotion of bulkier intersections which leads to an increase in compliance. The designs obtained are more suitable for manufacturing processes such as direct metal deposition.

The effects of five different types of imperfection (fractured cell walls, missing cells, cell wall waviness, cell wall misalignment, and non-uniform cell wall thickness) on actuation performance are numerically investigated for the Kagome lattice and two of its variants: Double Kagome (DK) and Kagome with concentric triangles (KT). The lattice materials of interest are excited by deploying a single linear actuator located at their centre. The actuation performance of the lattices is determined by measuring the energy spent by the actuator and the attenuation distance of the deformation induced by the actuator. The deformation localises in a narrow corridor approximately one unit cell-wide for all three lattices in the absence of imperfections. The finite element calculations show that the critical parameter determining the actuation performance is the stiffness along the actuation corridor rather than the macroscopic Young's modulus of the lattice. The less stiff the actuation corridor is, the smaller the actuation energy and the larger the attenuation distance (except when there is a fractured or wavy cell wall or a missing cell along the actuation corridor that immediately attenuates the displacement field). When imperfections are randomly distributed outside the actuation corridor, cell wall misalignment and non-uniform cell wall thickness barely affect the actuation performance, although cell wall misalignment considerably reduces the macroscopic Young's modulus of the lattice. The actuator feels the presence of fractured or wavy cell walls or missing cells, whether placed inside or outside the actuation corridor. These three types of imperfection cause the largest knock-down both in the macroscopic Young's modulus of the block and the actuation energy while increasing the attenuation distance. The increase in the attenuation distance due to imperfections is, however, impotent, as the accompanying reduction in stiffness makes the lattice more vulnerable to failure. However, if a defect is introduced slightly beyond the attenuation distance of the perfect lattice as an intentional design feature, it is beneficial for the actuation performance without decreasing the macroscopic Young's modulus.

Residual stresses and distortions are major obstacles against the more widespread application of wire arc additive manufacturing. Since the steep temperature gradients due to a moving localised heat source are inevitable in this process, accurate prediction of the thermally induced residual stresses and distortions is of paramount importance. In the present study, a computationally efficient thermo-mechanical model based on a semi-analytical thermal approach incorporating Goldak heat sources is developed for the process modelling of wire arc additive manufacturing. The semi-analytical thermal model makes use of the superposition principle, and thereby decomposes the temperature field into an analytical temperature field to account for the heat sources in a semi-infinite space and a complementary temperature field to account for the boundary conditions. Since the steep temperature gradients are captured by the analytical solution, a coarse spatial discretisation can be used for the numerical solution of the complementary Tˆ field. Thermal evolution is coupled to an elasto-plastic mechanical boundary value problem that computes the thermal stresses and distortions. The accuracy of the proposed model is evaluated extensively by comparing the thermal and mechanical predictions with the corresponding experimental measurements as well as the simulation results obtained by a non-linear transient model from the literature. A thin wall structure with a length of 500 mm and consisting of 4 layers is modelled. The peak normal stress along the deposition direction can be predicted with less than 10% error. Furthermore, the simulations show that the part distortions are very sensitive to the boundary conditions.

Although additive manufacturing (AM) allows for a large design freedom, there are some manufacturing limitations that have to be taken into consideration. One of the most restricting design rules is the minimum allowable overhang angle. To make topology optimization suitable for AM, several algorithms have been published to enforce a minimum overhang angle. In this work, the layer-by-layer overhang filter proposed by Langelaar (Struct Multidiscip Optim 55(3):871–883, 2017), and the continuous, front propagation-based, overhang filter proposed by van de Ven et al. (Struct Multidiscipl Optim 57(5):2075–2091, 2018) are compared in detail. First, it is shown that the discrete layer-by-layer filter can be formulated in a continuous setting using front propagation. Then, a comparison is made in which the advantages and disadvantages of both methods are highlighted. Finally, the continuous overhang filter is improved by incorporating complementary aspects of the layer-by-layer filter: continuation of the overhang filter and a parameter that had to be user-defined are no longer required. An implementation of the improved continuous overhang filter is provided.

Additive Manufacturing (AM) processes intended for large-scale components deposit large volumes of material to shorten process duration. This reduces the resolution of the AM process, which is typically defined by the deposition nozzle size. If the resolution limitation is not considered when designing for Large-Scale Additive Manufacturing (LSAM), difficulties can arise in the manufacturing process, which may require the adaptation of deposition parameters. This work incorporates the nozzle size constraint into Topology Optimisation (TO) in order to generate optimised designs suitable to the process resolution. This article proposes and compares two methods, which are based on existing TO techniques that enable control of minimum and maximum member size, and of minimum cavity size. The first method requires the minimum and maximum member size to be equal to the deposition nozzle size, thus design features of uniform width are obtained. The second method defines the size of solid members sufficiently small for the resulting structure to resemble a structural skeleton, which can be interpreted as the deposition path. Through filtering and projection techniques, the thin structures are thickened according to the chosen nozzle size. Thus, a topology tailored to the deposition nozzle size is obtained along with a deposition proposal. The methods are demonstrated and assessed using 2D and 3D benchmark problems.

In this paper, a finite element (FE) model is developed to investigate lattice hydrogen diffusion in a solid metal under the influence of stress and temperature gradients. This model is applied to a plate with a circular hole which is subjected to temperature and hydrogen concentration gradients. It is demonstrated that temperature gradients significantly influence hydrogen diffusion and hence susceptibility to hydrogen embrittlement when utilizing hydrogen for gas turbines.