Finite Element Analysis of Hip Implants with Different Lattice Structures Using Additive Manufacturing Materials

Chapter 1 - Overview of additive manufacturing technology and materials

Total hip arthroplasty (THA) is an increasingly common procedure that replaces all or part of the hip joint. The average age of patients is decreasing, which in turn increases the need for more durable implants. Revisions in hip implants are frequently caused by three primary issues: femoral loading, poor fixation, and stress shielding. First, as the age of hip implant patients decreases, the hip implants are seeing increased loading, beyond what they were traditionally designed for. Second, traditional implants may have roughened surfaces but are not fully porous which would allow bone to grow in and through the implant. Third, traditional implants are too stiff, causing more load to be carried by the implant and shielding the bone from stress. Ultimately this stress shielding leads to bone resorption and implant loosening. Additive manufacturing (AM) presents a unique opportunity for enhanced performance by allowing for personalized medicine and increased functionality through geometrically complex parts. Much research has been devoted to how AM can be used to improve surgical implants through lattice structures. To date, the authors have found no studies that have performed a complete 3D lattice structure optimization in patient specific anatomy. This paper discusses the general design of an AM hip implant that is personalized for patient specific anatomy and proposes a workflow for optimizing a lattice structure within the implant. Using this design workflow, several lattice structured AM hip implants of various unit cell types are optimized. A solid hip implant is compared against the optimized hip implants. It appears the AM hip implant with a tetra lattice outperforms the other implant by reducing stiffness and allowing for greater bone ingrowth. Ultimately it was found that AM software still has many limitations associated with attempting complex optimizations with multiple materials in patient specific anatomy. Though software limitations prevented a full 3D optimization in patient specific anatomy, the challenges associated such an approach and limitations of the current software are discussed.

The influence of processing methods on creep of wrought and additively manufactured CrCoNi multi-principal element alloys

Purpose The purpose of this study is to introduce methodologies for detailed characterisation of process-induced defects in 3D printed lattice structures, independent of the manufacturing process. Detailed characterisation of imperfections, particularly internal voids, including their geometry and distribution, provides insights into their impact on the mechanical properties of lattice structures. Furthermore, the correlation between defect severity, distribution and printing conditions, such as the printing direction, can be captured using the proposed methods. These correlations can be used to optimise printing parameters and lattice designs to achieve workpieces with minimal imperfections. Design/methodology/approach Due to the significant role of polymers and their composites in diverse industrial sectors, such as bioengineering, and the existing research gap regarding the impact of process-induced defects on the mechanical properties of polymeric lattices, the cellular structures were fabricated from the polymer in this study using the selective laser sintering process. To characterise additive manufacturing-induced defects in polymeric lattice structures, X-ray computed tomography is employed to scan the printed lattices, and image processing techniques using MATLAB scripts are developed to extract and analyse the characteristics of inspected defects, including their morphology and distribution. Findings This study reveals that polymeric lattice structures manufactured by powder bed fusion exhibit various defects, including geometry-related imperfections and internal voids. Geometry-related defects are more pronounced near strut junctions, with significant variations in strut thickness and cross-sectional shape. The analysis of voids’ morphology indicates that the lack of fusion during additive manufacturing leads to their formation, with voids exhibiting diverse shapes, sizes and orientations. This highlights the importance of detailed characterisation of process-induced voids and their incorporation into the structural analyses to improve the accuracy of the mechanical performance predictions for lattice structures. Originality/value The novelty of this work lies in the detailed characterisation of voids within manufactured polymeric lattices, including their 3D dimensions, aspect ratio and orientation. This comprehensive analysis of process-induced voids offers new insights into their impact on the mechanical performance of lattice structures, addressing the limitations of prior research that often simplified voids as spheres and overlooked the influence of void geometry on the mechanical properties of lattices. Furthermore, the methods developed for defect characterisation, especially for internal voids, are applicable to any lattice unit cell topology, regardless of the additive manufacturing method or material used.

Additively manufactured materials and structures: A state-of-the-art review on their mechanical characteristics and energy absorption

The topology optimization (TO) process has the objective to structurally optimize products in various industries, such as in biomechanical engineering. Additive manufacturing facilitates this procedure and enables the utility of advanced structures in order to achieve the optimal product design. Currently, orthopedic implants are fabricated from metal or metal alloys with totally solid structure to withstand the applied loads; nevertheless, such a practice reduces the compatibility with human tissues and increases the manufacturing cost as more feedstock material is needed. This article investigates the possibility of applying bioinspired lattice structures (cellular materials) in order to topologically optimize an orthopedic hip implant, made of Inconel 718 superalloy. Lattice structures enable topology optimization of an object by reducing its weight and increasing its porosity without compromising its mechanical behavior. Specifically, three different bioinspired advanced lattice structures were investigated through finite element analysis (FEA) under in vivo loading. Furthermore, the regions with lattice structure were optimized through functional gradation of the cellular material. Results have shown that optimal design of hip implant geometry, in terms of stress behavior, was achieved through functionally graded lattice structures and the hip implant is capable of withstanding up to two times the in vivo loads, suggesting that this design is a suitable and effective replacement for a solid implant.

Advancing precision: Exploring nanomachining techniques in additive manufacturing

A lattice structure is defined by a network of interconnected structural members whose architecture exhibits some degree of regularity. Although the overall architecture of a lattice may contain many members, its generation can be a simple process in which a unit cell composed of a small amount of members, in comparison to the overall structure, is mapped throughout the Euclidean space. However, finding the right lattice architecture in a vast search space that customizes the behavior of a design for a given purpose, subject to mechanical and manufacturing constraints, is a challenging task. In response to this challenge, this work investigates a Voronoi diagram-based tessellation of a body-centered cubic cell for applications in structural synthesis and computational design of 3D lattice structures. This work contributes by exploring how the Voronoi tessellation can be utilized to parametrically represent the architecture of a lattice structure and what the implications of the parametrization are on the optimization, for which a global direct search method is used. The work considers two benchmark studies, a cubic and a cantilever lattice structure, as well as the effect of isotropic and anisotropic material property models, stemming from applications to additive manufacturing. The results show that the proposed parameterization generates complex search spaces using only four variables and includes four different lattice structure types, a Kelvin cell, a hexagonal lattice, a diamond-core lattice structure, and a box-boom type lattice structure. The global direct search method applied is shown to be effective considering two different material property models from an additive manufacturing (AM) process.

Impact of intragranular misorientation on void swelling and inter-granular cavities after ion irradiation in standard and additive manufacturing 316L austenitic steels

Additively manufactured (AM) components offer superior design flexibility compared to their conventionally manufactured counterparts and require process parameter optimization to achieve high-quality depositions with desirable and predictable mechanical properties. This study was focused on 4340 steel fabricated using laser powder bed fusion (LPBF), and 42 laser power and scan speed combinations have been systematically investigated to optimize the melt pool geometry and ensure fully dense parts. The AM material was compared with a wrought 4340 equivalent and studied in both as-fabricated and heat-treated conditions. Two heat treatments were designed and used to optimize the materials for strength and toughness, respectively. Microstructure, tensile, and fractographic studies were conducted to assess build integrity and establish processing–structure–performance relationships. Tensile properties of the AM materials in all studied conditions were equivalent or better than the comparable wrought materials. The high performance of the AM materials was attributed to the absence of both manganese sulfide inclusions and rolling-induced banding, typically found in the wrought materials. The fine cellular substructure is thought to additionally contribute to the high strength of the as-fabricated AM material. Complementary to the knowledge that has emerged from the experimental investigations, the dataset was further leveraged to make recommendations for future design of experiments to optimize AM build parameters in other material systems. A statistical Monte Carlo analysis was used to predict the interpolation error produced when using reduced datasets and to enable informed processing parameters selection. These findings are discussed to make recommendations for the use of AM materials for high-integrity structural applications.

A parametric model of joint-enhanced truss lattices with optimization for superior mechanical properties

The development of lightweight, corrosion-resistant metallic lattice structures has gained significant attention in aerospace, defense, and structural applications, where material durability and weight optimization are critical. This study investigates the corrosion behavior of Laser Powder Bed Fusion (LPBF)-fabricated A286 steel honeycomb, Body-Centered Cubic (BCC), and gyroid lattices, comparing their performance against conventional materials such as Rolled Homogeneous Armor (RHA), Maraging High Strength Steel (MHA), and High-Nitrogen Steel (HNS). Corrosion testing was conducted using accelerated salt spray exposure, and the results were validated through computed tomography (CT)-based structural integrity analysis and machine learning-based predictive modeling. The experimental findings revealed that lattice structures exhibited significantly lower corrosion rates than conventional bulk materials, with the honeycomb lattice demonstrating the highest corrosion resistance (1.218 mm/year), followed by BCC (1.311 mm/year) and gyroid (1.671 mm/year). Compared to RHA, the honeycomb lattice exhibited a 57.23% reduction in corrosion rate, confirming its superior electrochemical stability. CT scan evaluations further highlighted differences in density distribution and geometric fidelity, with honeycomb lattices showing the most uniform porosity, while BCC structures displayed localized density variations at nodal intersections. To enhance predictive capabilities, various machine learning (ML) algorithms were employed to model corrosion behavior based on weight-loss measurements and lattice topology. Bayesian Ridge regression outperformed other models, achieving an R² of 0.99849 and RMSE of 0.00049, confirming its robustness in capturing corrosion trends. Linear Regression also performed well, while ensemble models such as Random Forest and XGBoost exhibited higher error margins due to dataset linearity constraints. Residual analysis and graphical interpretations further validated the stability and predictive reliability of ML-based corrosion assessments, demonstrating their feasibility as an alternative to traditional experimental methods. This study presents a comprehensive framework for integrating experimental corrosion testing, computational modeling, and CT-based defect analysis, offering a scalable approach to optimizing micro-lattice designs for corrosion-sensitive applications. The findings highlight the potential of LPBF-fabricated metallic lattices for aerospace, defense, and marine structures, where enhanced corrosion resistance, reduced material degradation, and predictive maintenance strategies are essential for long-term operational performance.

The diffusion of design tools suitable for regular lattice structures was recently stimulated by the spread of additive manufacturing technologies that enable the fabrication of complex geometries, exceeding the limits of traditional manufacturing methods. Fillet radii play a fundamental role in the design of lattice materials, reducing the stress concentration and improving fatigue life. However, only simplified beam and 2D models are available in the literature, which are unable to capture the actual stiffness and stress concentrations in the cell nodes of the 3-D beam based lattice structures with fillets. In this paper, four types of polyamide 12 cells, fabricated by selective laser sintering technology, based on cylindrical elements, are studied by finite element (FE) analysis, evaluating the influence of struts and fillet radii on the mechanical properties. In order to study a single cell, specific boundary conditions, simulating the presence of adjacent cells, were adopted in FE analysis. As a result, a model describing mechanical properties as a function of geometrical characteristics is obtained. By this model, it is possible to replace the complex shape of a lattice structure with its boundary, simplifying numerical analyses. This approach, called homogenization, is very useful in the design process of lightweight structures and can be adopted in optimization strategies. Numerical outcomes show that the effect of fillet radius is not negligible, especially in cells having a large number of struts. Moreover, experimental tests were also carried out showing a good agreement with the numerical analysis. Finally, an interactive design process for lattice structures based on experimental and numerical outcomes is proposed.

Additive manufacturing through stereolithography (SLA) offers promising capabilities for producing flexible photopolymer composites with tailored mechanical properties for advanced engineering applications. However, the influence of printing parameters and material composition on the performance of such composites remains underexplored. This study aims to evaluate the effects of layer thickness and print orientation on the mechanical and structural behavior of SLA-printed flexible composites reinforced with Kevlar fibers. Twelve composite formulations were developed using varying proportions of elastic resin (ER), standard resin (SR), and Kevlar fibers (KF). The printed samples were analyzed for tensile strength, strain, hardness, surface roughness, fiber distribution, and topographical characteristics. Among the tested formulations, sample S9 (ER: 90%, SR: 9.80%, KF: 0.20%) exhibited the highest tensile strength (7.27 MPa) and significant strain (161.60%) when printed flat at a 0.050 mm layer thickness. In contrast, pure ER (S1) demonstrated superior strain capacity (228.48%) but lower tensile strength (1.98 MPa). Hardness improved with Kevlar reinforcement, reaching up to 34.38D. Surface roughness analysis revealed the lowest values in S7 (0.49 μm, lateral orientation) and S10 (0.30 μm, flat orientation). FESEM imaging confirmed strong interlayer bonding, while topographic and particle analyses indicated enhanced particle density in S9 (0.2329 particles/mm 2 ). Fiber distribution varied significantly, with sample S11 showing the highest coverage (56.90%). These results highlight the synergistic role of SLA parameters and composite formulations in optimizing mechanical performance and structural integrity, offering valuable insights for the design of next-generation flexible materials in additive manufacturing.

In situ neutron diffraction measurements were completed during tensile and compressive deformation of stainless steel 304L additively manufactured (AM) using a high power directed energy deposition process. Traditionally produced wrought 304L material was also studied for comparison. The AM material exhibited roughly 200 MPa higher flow stress relative to the wrought material. Crystallite size, crystallographic texture, dislocation density, and lattice strains were all characterized to understand the differences in the macroscopic mechanical behavior. The AM material’s initial dislocation density was about 10 times that of the wrought material, and the flow strength of both materials obeyed the Taylor equation, indicating that the AM material’s increased yield strength was primarily due to greater dislocation density. Also, a ~50 MPa flow strength tension/compression asymmetry was observed in the AM material, and several potential causes were examined.