Lattice structures produced by additive manufacturing are increasingly used in lightweight, load-bearing applications, yet their mechanical performance is strongly influenced by geometry, process parameters, and boundary conditions. This study investigates the compressive behavior of body-centered cubic (BCC) 316L stainless steel lattices fabricated by laser powder bed fusion (LPBF). Four relative densities (20%, 40%, 60%, and 80%) were achieved by varying the strut diameter, and specimens were built in both vertical and horizontal orientations. Quasi-static compression tests characterized the elastic modulus, yield strength, energy absorption, and mean force, while finite element simulations reproduced the deformation and hardening behavior. The experimental results showed a direct correlation between density and mechanical properties, with vertically built specimens performing slightly better due to reduced processing defects. Simulations quantified the effect of strut–joint rounding and the need for multi-cell configurations to closely match the experimental curves. Regardless of the boundary conditions, for a density of 20%, simulating a single cell underestimated stiffness because of unconstrained strut buckling. For higher densities and thicker struts, this sensitivity to boundary conditions strongly decreased, indicating the possibility of using a single cell for shorter simulations—a point rarely discussed in the literature. Both experiments and simulations confirmed Gibson–Ashby scaling for elastic modulus and yield strength, while the tangent modulus was highly sensitive to boundary conditions. The combined experimental and numerical results provide a framework for the reliable modeling and design of metallic lattices for energy absorption, biomedical, and lightweight structural applications.

This study aims to improve the energy absorption and mechanical properties of auxetic structures by optimizing their design and analyzing the influence of different resin matrices in composite fabrication. Auxetic materials exhibit unique deformation behavior due to their negative Poisson’s ratio, making them promising for energy absorption applications. However, their practical implementation is often constrained by their intrinsic mechanical properties, particularly their strength under realistic loading conditions. This research investigates the effect of resin matrix selection on the energy absorption capacity, Young’s modulus, and yield strength of auxetic composites. A systematic experimental campaign was conducted, subjecting auxetic structures reinforced with various resin matrices to compressive loading. The results indicate that embedding the auxetic structure within a resin matrix significantly enhances energy absorption compared to pure resin samples. Notably, vinylester resin composites exhibited the highest Young’s modulus, yield strength, and energy absorption capacity. This superior performance is attributed to the synergistic interaction between the auxetic structure, which efficiently distributes stress, as well as the intrinsic toughness and load-bearing capacity of the vinylester resin. These findings contribute to the optimization of auxetic composites for energy absorption applications and the development of high-performance materials for impact mitigation in aerospace and automotive industries.

Numerical modeling of the compressive behavior of 316L body-centered cubic lattice structures RÍOS Ignacio, MARTÍNEZ Alex, SAGGIONETTO Enrico, MERTENS Anne,

Passive metallic dampers are critical for the seismic resilience of structures, yet their design has historically relied on incremental modifications rather than systematic optimization. This study introduces and validates a data-driven workflow that combines the Taguchi method with nonlinear finite element analysis to design novel U-shaped seismic dampers (USSDs) with superior performance. Building on an experimentally validated computational model from prior work, an L25 orthogonal array was employed to systematically investigate key geometric parameters, with an Analysis of Variance (ANOVA) identifying height, thickness, and length as the most influential factors on damper behavior. This statistical insight guided the creation of two optimized models, with the UD-M4 model demonstrating a nearly seven-fold increase in total energy dissipation (340.6 kJ vs. 51.2 kJ), a nine-fold increase in stiffness, and a 50% improvement in deformability compared to the commercial UD-40 baseline. The primary contribution of this work is the validation of an efficient statistical–computational methodology for the performance-based design of next-generation seismic protection devices, moving beyond traditional trial-and-error approaches.