This article proposes a toward zero-support design method for irregular manifold manufacturing of composite materials based on layered adhesion equalization (LAE). Especially, external support in holes of irregular 3D manifold manufacturing by additive manufacturing (AM) is difficult to remove, which means toward zero-support design is indispensable to some complex curved surface components. AM largely depends on three main constraints, such as external support, layer thickness, and build time, which are mainly affected by building orientation and infill trajectory. Moreover, considering problems that variable layer thickness will bring material imbalance and residual stress heterogeneity, the layered orthogonal projection areas of the virtual printing prototype on the orthogonal planes, such as the positive plane and side plane in the 3D printing coordinate system, are introduced as LAE constraints to realize equilibrium reinforcement design (ERD) for both LAE and external support. Subsequently, using transient thermal structure coupling via finite element analysis, the transient thermal structure coupling analysis of fiber composite under multiple working conditions is further obtained. In particular, the influence mechanism of continuous fiber forming on the mechanical behavior of the topological configuration is revealed. Taking the irregular three-way manifold by concept design as an example, a specimen was fabricated using polylactic acid (PLA) with carbon fiber on the strength of fused deposition modeling. The infrared thermographs using thermal field measurement were carried out to obtain the temperature distribution during manufacture. The innovatively proposed LAE method is propitious to improve the additive manufacturability and adaptability of lightweight thin-wall structures, especially for fiber-reinforced composites. This is advantageous for utilisation in the domain of aerospace components.

To address the dual requirements of lightweight and high-performance structural design, this study investigated the compressive properties of three aluminum-based mechanical metamaterials with different lattice structures but the same mass, which were fabricated by laser fusion additive manufacturing. The three structures are porous structure, truss structure, and gyroid structure. Through quasi-static compression tests, numerical simulations, and microstructure analysis, we examined the effects of geometric design, micro-defects, and local deformation on the mechanical response and deformation mechanism. The research results indicated that the uniformity of stress distribution, the defect sensitivity, and the grain refinement significantly affect the energy absorption capacity and strength of the material. Reducing local strain concentration, improving surface quality, and promoting grain fragmentation are the keys to enhancing the mechanical properties of the material during compression. These findings provide unique insights into the structure-performance relationship of alloy lattice metamaterials and offer support for the optimization design of aluminum-based metamaterials in lightweight structural applications.

Hybrid continuous fiber-reinforced composite structures are widely used in aerospace, but they show poor printing quality and unstable performance. Thus, the additive manufacturing process and mechanical behaviors of carbon–Kevlar intralayer hybrid continuous fiber composite corrugated sandwich structures are experimentally investigated. All samples are fabricated using an in-situ impregnation method based on the one-stroke path planning. The inherent intralayer fiber hybridization mechanism and the effects of 3D printing parameters (layer thickness, temperature, and speed) on printing quality and mechanical performance are focused. The protection mechanism based on intralayer hybridization, meso-structural characteristics, and failure modes is analyzed. Results reveal that Kevlar fibers protect carbon fibers during printing, reducing nozzle friction and preventing brittle fractures. However, parameter mismatches (e.g., extrusion amount and temperature) between carbon and Kevlar fibers lead to surface defects and uneven impregnation. Quasi-static crushing tests demonstrate that hybrid samples exhibit superior energy absorption and load stability compared to single-fiber samples, attributed to the synergy effect of high-strength carbon and tough Kevlar fibers. Optimal printing parameters enhance impregnation and interlayer bonding, minimizing the defects. This study provides valuable exploration for the 3D-printing and mechanics of intralayer hybrid fiber composite structures.

Lattice structure has been widely used to replace the solid structure because of the excellent performances such as ultra-light and high specific stiffness. But the advantages of the lattice structure cannot be fully reflected when the density of crystal cell is uniform. In order to better utilize the advantages of lattice structure, this paper presents an adaptive design method for lattice structure with nonuniform density crystal cells based on load path. First, the forces of any regions in a given structure are calculated and expressed by the load path theory. Then the normalized forces are mapped with the control parameters of triply periodic minimal surface to guide the density adjustment of each crystal cell. Finally, the nonuniform density lattice structure is obtained. Taking cantilever plates and cuboid as examples, the uniform density and non-uniform density lattice structure are filled, respectively, and the mechanical performances are analyzed and validated through simulations and experiments. Compared to the structure filled with uniform density lattice structure, the maximum displacement and maximum stress of the cantilever plate filled with nonuniform density lattice structure decrease by 15.15% and 3.43%, respectively, and the maximum strength of cuboid filled with nonuniform density lattice structure is improved by 14.9%, while the maximum deformation is reduced by 0.8%.

Designing and fabricating structures with specific mechanical properties requires understanding the intricate relationship between design parameters and performance. Understanding the design-performance relationship becomes increasingly complicated for nonlinear deformations. Though successful at modeling elastic deformations, simulation-based techniques struggle to model large elastoplastic deformations exhibiting plasticity and densification. We propose a neural network trained on experimental data to learn the design-performance relationship between 3D-printable shells and their compressive force-displacement behavior. Trained on thousands of physical experiments, our network aids in both forward and inverse design to generate shells exhibiting desired elastoplastic and hyperelastic deformations. We validate a subset of generated designs through fabrication and testing. Furthermore, we demonstrate the network’s inverse design efficacy in generating custom shells for several applications.

To improve the crashworthiness, the 3D-printed Gyroid lattices coupled with column struts are designed to regulate the failure mechanism by synergistic effects. There are four types of combining form to reveal their different synergistic effects, including Gyroid lattice with side column, Gyroid lattice with diagonal column, and Gyroid lattice with topology-optimized (TO) column. To improve Gyroid lattice with TO column, both gradient and nongradient column structs are further optimized. All samples are fabricated using fused deposition modeling rapid prototyping technique, and the typical 3D-printing defects are characterized to confirm their usability. By the axial crushing tests, the load–displacement responses, energy absorption, and failure mechanisms are evaluated. The results show that the significant improvements in the load-bearing and energy absorption are identified for the Gyroid lattice with diagonal column strut and TO-column struts, compared with pure Gyroid lattice. Under the synergistic effects, the failure mechanisms of Gyroid lattice with different column struts vary significantly, presenting a great effect on crashworthiness. The failure regulation mechanisms of Gyroid lattice induced by different single-column struts are revealed extensively. This work provides an effective guide for the lightweight crashworthiness design of complex coupling structures.

This article proposes a support equilibrium design methodology for laser additive manufacturing of lightweight components based on geometric deformation minimization (GDM). Controlling geometric deformation commonly induced by material residual stress is especially significant for lightweight components, as slight deviation will be amplified, thereby inducing severe imbalance that makes premature failures. Aiming to investigate the impacts of support structures on photocurable manufactured parts and further conduct support equilibrium designs, a mechanically constrained volume shrink model was constructed jointly considering the chemical reaction kinetics and evolution of material properties. The deformation and stress distributions of manufactured parts with various conceptual support structures were confirmed, and the geometric deformation were mapped to the designed ideal model to generate the deformed manifold. The bidirectional fluid–solid coupling simulation, as well as buckling response analysis were conducted to verify the effectiveness of GDM in terms of improving working performance of lightweight components under variable working conditions. In addition, the balance analysis of mass distribution was conducted by calculating the offset distance of gravity center to examine the ability of the GDM-based support equilibrium design in reducing imbalance phenomena. The physical experiment is conducted on unmanned aerial vehicle (UAV) parts to verify GDM via digital light processing and microscopic images. The geometric deformation during manufacturing process is reduced by 13.08%, and the average centroid shift is improved by 27.44% based on GDM, which effectively improved the working performance of lightweight components.

This article presents a significant advancement in the field of three-dimensional (3D) printing. We have developed a fast parallel computation algorithm that predicts the optimal orientation of 3D printing using a general-purpose graphic processor unit (GPU). Initially designed for the central processing unit (CPU) version support structure tomography, our algorithm has been successfully adapted for NVIDIA graphic processors and the CUDA toolkit. Despite encountering several challenges, we have achieved a remarkable improvement in calculation speed. Two CPUs and four GPUs of various prices and performances were used for the speed comparison. The high-end GPU showed a surprising multiprocessing performance; a maximum of 16.2 times for Dragon mesh data and 11.2 times on average than the high-end CPU. The proposed method assumes that the input triangle should have a bigger size than the voxel size and a relatively smaller number of triangles, about tens of thousands. Nevertheless, the algorithm has the potential to significantly enhance the efficiency and quality of 3D printing, addressing some constraints and expanding its practical applications.

Additively manufactured metallic lattice biomaterials have revolutionized the mechanical properties of lower-extremity bone and joint implants. Most designers have followed a quasi-static approach, where material properties are solely represented by their elastic modulus. In reality, however, the human body experiences repeated dynamic and impact loads in vivo , and bone acts as a passive shock absorber and wave modulator. Most importantly, bone cells sense no load under quasi-static loading and must rather be subjected to impact loads at frequencies near their natural frequencies and high enough accelerations to conduct optimum mechanotransduction. This indicates the necessity of developing a dynamic design strategy that further considers damping and natural frequency. This research is an attempt to study the dynamic performance of selective laser melted lattice implants with the help of design of experiments and finite-element method (FEM). In many cases, lattice implants exhibit up to 80% similar values of elastic modulus and natural frequency to the bone. Regarding the damping, however, the similarity rarely reaches 10%. For the most part, the dynamic material properties of the implants are more significantly affected by their geometry and printability rather than process parameters. Damping decreases with power and increases with porosity and scanning speed. Natural frequency increases with power and remains almost constant with scanning speed. Generally, any change to the process parameters and geometry that improves the elastic modulus affects the natural frequency and damping directly and inversely, respectively. Capturing the main trends of dynamic behavior successfully, FEM accuracy is controlled by the geometry and hence can be distorted by manufacturing defects. All in all, there is a balance between the elastic modulus and damping. Dynamic performance improves with porosity, albeit up to an optimum point.

Multimaterial additive manufacturing has enabled the fabrication of components with highly tailored mechanical responses. However, as both manufacturing processes and constituent materials become more sophisticated, the large number of process variables makes design increasingly challenging. Here, we investigate the design space for multimaterial thermoplastic composites produced by a commercially available fused filament fabrication printer. We consider the uniaxial compression of neat materials with sample geometry and toolpath variations, as well as composites comprised of a soft elastic matrix with stiff reinforcement material in different reinforcement fractions and geometries. We find that some changes to the toolpath can have a significant impact on the compressive behavior of the samples due to the high anisotropy of the filaments. The composite geometries were found to exhibit different specific strengths relative to reinforcement fraction, and their compressive behavior matched qualitatively but not quantitatively to predictions from finite element analysis. To understand the performance space, we analyzed the experimental dataset with truncated singular value decomposition. Surprisingly, despite the complexity of the system, 97.8% of the variance in stress–strain curves of our samples was captured by the first component and 99.9% by the first two. The shape of the components indicates that while the stress–strain curves of samples may vary quantitatively, very limited modes are controllable with the design variables considered here. In effect, the strength of the composite could be controlled by manipulating reinforcement mass fraction, but the shape of the nonlinear behavior was largely baked into the constituent materials despite changing the reinforcement geometry. This result has important consequences that must be considered early in the design process when developing new multimaterial systems to achieve tailored mechanical responses.