Hongbing Lu

Geometric deviations in unsupported overhang features pose one of the most persistent quality challenges in Laser Powder Bed Fusion (LPBF), where even small deviations from the intended geometry can undermine part functionality and reliability. This study presents a geometrically informed conditional Generative Adversarial Network (cGAN), implemented through the Pix2Pix framework, to predict layer-wise geometric deviations in LPBF-printed parts with overhang geometries, using paired two-dimensional Computer-Aided Design (2D CAD) slices and corresponding X-ray Computed Tomography (XCT)-derived ground truth slices. The study investigates how geometric information can be encoded within the conditional input of the Pix2Pix framework to more effectively guide deviation prediction. A total of 18 models were trained and evaluated across multiple overhang geometry groups and batch size configurations, assessed through a combination of perceptual, structural, and boundary-focused metrics, namely Peak Signal-to-Noise Ratio (PSNR), Structural Similarity Index Measure (SSIM), Learned Perceptual Image Patch Similarity (LPIPS), Fréchet Inception Distance (FID), and Edge Intersection over Union (Edge IoU). The results demonstrated that color-coded inputs consistently improved prediction fidelity, perceptual similarity, and edge alignment relative to their non-color-coded counterparts. Furthermore, a model trained on a balanced multi-geometry dataset showed improved prediction performance on withheld 30° and 60° overhang configurations within the benchmark geometry family. The proposed framework offers a data-driven, design-stage tool for anticipating geometry-dependent deviations in LPBF overhang structures, supporting design for additive manufacturing.

Background: To enable systematic characterization under controlled laboratory conditions, inert surrogate materials have been developed to reproduce the key thermomechanical response of PBXs without the associated energetic hazards. Among these surrogates, idoxuridine (IDOX) has emerged as effective replacements, providing comparable mechanical and thermal properties and facilitating investigations across granular, mesoscale, and continuum length scales. Objective: This work provides detailed experimental data on the structural evolution of an idoxuridine (IDOX)/Estane bonded granular composite, serving as a surrogate for PBX under deformation. The findings support the calibration and validation of direct numerical simulations (DNS) focused on microstructural changes for improved computational modeling of bonded granular composites. Methods: X-ray micro-computed tomography (μCT) was used to capture the internal microstructure of the IDOX/Estane granular composite for finite element modeling. Cylindrical specimens were subjected to both quasi-static and high strain-rate compression. Under quasi-static loading, volumetric imaging was used to track internal granular evolution, while digital image correlation (DIC) measured surface deformations. High strain-rate behavior was characterized by a modified split Hopkinson pressure bar (SHPB), paired with high-speed imaging and DIC analysis. Results: DIC provided full-field surface deformation measurements during quasi-static and high strain-rate compression. The surface deformations as measured by DIC under quasi-static loading were compared with DNS data for assessment. In-situ quasi-static µCT experiments revealed the evolution of internal granular structure and damage, including microcrack initiation, propagation, and macro-fracture. High-strain rate experiments captured the surface strain localization in the IDOX/Estane composite cylinder. Conclusion: This experimental work bridges laboratory observations with computational modeling to advance the understanding of PBX-like materials under mechanical stresses and to support the development of efficient predictive models for bounded granular composite behavior.

Enhanced electrical and mechanical performance of Poly(3,4-ethylenedioxythiophene): poly(styrene sulfonate) (PEDOT:PSS) through sustainable additive modification for flexible electronic device applications

To study the mechanical behavior of mock high explosives, an experimental and simulation program was developed to calibrate, with quantified uncertainty, a material model of the bonded granular material Idoxuridine and nitroplasticized Estane-5703. This paper reports on the efficacy of such a framework as a generalizable methodology for calibrating material models against experimental data with uncertainty quantification. Additionally, this paper studies the effect of two manufacturing temperatures and three initial granular configurations on the unconfined compressive behavior of the resulting bonded granular materials. In each of these cases, the same calibration framework was used; in that, hundreds of high-fidelity direct numerical simulations using a new, graphics processing unit-enabled, high-performance finite element method software, Ratel, were run to calibrate a finite-strain phase-field fracture model against experimental data. It was found that manufacturing temperature influenced the elastic response of the mock high explosives, with higher temperatures yielding a stiffer response. By contrast, it was found that the initial configuration of the grains had a negligible impact on the overall behavior of the mock high explosives though it remains possible that local damage accumulation within the specimens could be altered by the initial configurations. Overall, the calibration framework was successful at creating well-calibrated models, showing its usefulness as an engineering and scientific tool.