This study presents a newly developed program that seamlessly converts G-code into formats compatible with Abaqus, enabling precise finite element simulations for FDM 3D printing. The tool operates on a two-pronged framework: a mathematical model incorporating key print parameters (layer thickness, extrusion temperature, print speed, and raster width) and a shape generator managing geometric parameters (fill density, pattern, and raster orientation). Initially, a predefined virtual section, based on predetermined dimensions, enhanced the correlation between experimental results and simulations. Subsequently, a corrected virtual section, derived from the mathematical model using the Box–Behnken methodology, improves accuracy, achieving a virtual thickness error of 1.06% and a width error of 8%. The model is validated through tensile testing of ASTM D638 specimens at 0°, 45°, and 90° orientations, using adaptive C3D4 mesh elements (0.35–0.6 mm). Results demonstrate that the corrected cross-section significantly improved simulation accuracy, reaching correlations above 95% in the elastic zone and 90% in the elastoplastic zone across all orientations. By optimizing the workflow from design to manufacturing, this program offers substantial benefits for the aerospace, medical, and automotive sectors, enhancing both the efficiency of the printing process and the reliability of simulations.

This study presents an experimentally calibrated methodology to enhance the predictive accuracy of finite element simulations for Fused Deposition Modeling (FDM) parts in Abaqus by replacing idealized filament geometry with a physically accurate “corrected virtual raster section.” A Box-Behnken Design of Experiments (DoE) across 27 ABS specimens systematically quantifies how key printing parameters, layer thickness, raster width, extrusion temperature, and print speed, influence the true cross-sectional geometry of deposited filaments, as measured via Scanning Electron Microscopy (SEM). These data inform a predictive mathematical model that transforms the conventional circular filament shape into an experimentally grounded oval-rectangular profile, accurately capturing extrusion-induced flattening and lateral spreading. The calibrated virtual section is integrated into a custom Python-based tool that parses G-code toolpaths and sweeps the corrected geometry along deposition trajectories to generate high-fidelity, mesh-ready Abaqus models. The workflow is validated through tensile testing of ASTM D638 specimens printed at 0°, 45°, and 90° raster orientations (n=3 per orientation). Error analysis against the experimental mean demonstrates that the corrected model reduces simulation errors from catastrophic levels in the non-corrected approach (7–92% relative error, 2.5–19 MPa absolute) to engineering-grade precision (0.03–7% relative error, ≤1.3 MPa absolute). This workflow bridges G-code to physical behavior, enabling reliable simulation of FDM anisotropy.

A significant amount of mechanical and thermal energy is lost when typing on a laptop keyboard. To address this, hybrid energy harvesters must increase the generated power density and mitigate energy fluctuation issues. This paper explores the potential enhancement of energy harvesting by combining thermoelectric and piezoelectric effects within a multilayered structure integrated into a laptop keyboard button. Through numerical simulation, the study assesses how these two behaviors can synergistically increase the power density generated by the hybrid device. The focus is on optimizing energy efficiency by harnessing the heat losses from integrated circuits and the mechanical stresses due to the act of typing. The point is to refine the design of such a system to maximize the conversion of ambient energy into electricity. The findings indicate that the hybrid structure combining both piezoelectric and thermoelectric effects, effectively captures energy from a laptop keyboard, producing a substantial amount of electricity. This investigation shows that the generator can produce up to 2.07 mW of power using PU-40%PZT as piezoelectric material and an additional 71.93 μW through the PEDOT: PSS as thermoelectric material from a single keystroke when pressed and heated. This study underscores the potential for improving energy-harvesting efficiency in laptop keyboards, contributing to more sustainable and energy-efficient electronic devices.