Kamlesh Paswan¹, Rajnish Singh², Vivekanand Singh³, Brihaspati Singh⁴, Ankur Saxena⁵, Chandrmani Yadav^6,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.080581 - 15 June 2026

Abstract Electrical Discharge Machining (EDM) is governed by highly coupled, nonlinear electro-thermal-mechanical phenomena involving plasma-mediated energy transfer, rapid heat conduction, phase transformation, and resolidification over micro to nanosecond time scales. From a computational materials science perspective, EDM serves as a prototypical problem of extreme, localised energy–matter interaction, where predictive modelling requires rigorous treatment of multiphysics coupling and scale bridging. This review presents a critical synthesis of theoretical and numerical frameworks for modelling advanced EDM configurations, including vibration-assisted and turning-based EDM, powder- and nano-additive-assisted EDM, and alternative dielectric environments. The review consolidates continuum-based formulations that describe the… More >

Zhen Yan¹, Jiani Huang¹, Yanlin Gu¹, Qingqing Xu¹, Yuyu Guo¹, Kun Lin², Juan Hou^1,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.079204 - 15 June 2026

Abstract This study addresses the challenge of balancing “high deposition efficiency with large layer thickness” and “component mechanical integrity” in Laser Powder Bed Fusion (LPBF) additive manufacturing. Using 304L stainless steel as an example, a hybrid modeling strategy combining physical mechanism models and residual machine learning was proposed, achieving accurate prediction of densification at H = 60, 90, and 120 μm (test set R² = 0.833, MAE = 0.104). Within the Doehlert matrix experimental design framework, the coupled effects of laser power, scanning speed, and scanning spacing on densification behavior, microstructure evolution, and mechanical response at different… More >

Junzhe Zhao^1,2, Wencan Zhu^1,3, Qiang Wang¹, Hui Chen², Yan Liu², Kaihong Zheng³, Zhibo Zhang^2,3,*

CMC-Computers, Materials & Continua, Vol.88, No.2, 2026, DOI:10.32604/cmc.2026.078880 - 15 June 2026

Abstract Vacancy defects in graphene are inevitably introduced during the fabrication of graphene-reinforced metal matrix composites through mechanical processing, chemical reactions, or in-service environmental exposure. Despite their prevalence, the precise atomic-scale impact of these vacancies on dislocation motion, strengthening mechanisms, and failure behavior remains incompletely understood. To address this gap, we employ molecular dynamics simulations to construct aluminum-graphene interface models featuring systematically varied vacancy defect concentrations, enabling a detailed investigation of dislocation–interface interactions and the underlying reinforcement and failure mechanisms under shear deformation. Compared to pristine graphene, interfaces containing vacancy defects exhibit significantly enhanced out-of-plane buckling… More >

Pavlo Bekhta^1,2,*, Iryna Lytvyn¹

Journal of Renewable Materials, Vol.14, No.5, 2026, DOI:10.32604/jrm.2026.02026-0035 - 28 May 2026

Abstract The modification of melamine–urea–formaldehyde (MUF) adhesives with lignosulfonates (LS) represents a promising strategy for developing more sustainable wood-based panels. However, the influence of the counterion type remains poorly understood. In this study, the effect of lignosulfonate counterions on adhesives performance and properties of MUF-bonded particleboards was investigated, with a focus on sodium (NaLS) and magnesium (MgLS) lignosulfonates incorporated at 2.5%, 5.0%, and 7.5%. Adhesives performance was characterized by measuring dry solids content, dynamic viscosity, gelation time, and pH. The produced particleboards were evaluated in terms of density, bending strength, modulus of elasticity, internal bond strength… More > Graphic Abstract

I. Nur Azreena^*, H. A. Aisyah, A. W. Noorshamsiana

Journal of Renewable Materials, Vol.14, No.5, 2026, DOI:10.32604/jrm.2025.02025-0178 - 28 May 2026

Abstract This study examined the impact of various pre-treatment techniques on the physical and mechanical characteristics of particleboards derived from oil palm trunks (OPT). Thermal and chemical pre-treatments of the fibers, including hot water, sodium hydroxide (NaOH), and acetic acid, were applied prior to board production. In addition, antifungal agents were incorporated as supplementary additives during the manufacturing process at varying percentages to evaluate their effect on panel performance. Morphology of the treated OPT fibers was examined, and panel properties such as thermal behavior, bending strength, bonding strength, and dimensional stability were evaluated. Statistically significant improvements (p… More >

Bahareh Ramzikhalesi^1,*, Ali Rakhsh-Mahpour¹, Josep Claramunt-Blanes², Ernest Bernat-Maso³

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.080138 - 27 May 2026

Abstract The mechanical behavior of nonwoven fabrics as reinforcement in cementitious composites remains insufficiently explored, particularly from a numerical modeling perspective, despite their growing interest as sustainable alternatives to conventional textiles. This study presents a simplified, engineering-oriented numerical modeling framework for reproducing the flexural mechanical response of cementitious composites reinforced with flax nonwoven fabric. Four-point bending (flexural) behavior of nonwoven fabric–reinforced cementitious composites was numerically simulated using ANSYS software. The model is developed using Finite Element Analysis (FEA) and incorporates a Representative Volume Element (RVE) approach to account for the heterogeneous fiber–matrix interaction. The required material… More >

Jiaoyan Li¹, James D. Lee^2,*

CMES-Computer Modeling in Engineering & Sciences, Vol.147, No.2, 2026, DOI:10.32604/cmes.2026.077471 - 27 May 2026

Abstract The key points of micromorphic theory, including the balance laws and entropy principle, are briefly introduced. Maxwell’s equations and the Lorentz Transformation of E and B fields in both relativistic and non-relativistic electromagnetic theory are discussed. The link between the thermomechanical part and the electromagnetic part of the micromorphic electromagnetic theory is established through the body force, body moment, and energy source. The constitutive theory for thermo-visco-elastic-plastic-electromagnetic (TVEP-EM) materials is formulated. Then the constitutive relations are reduced to the materially linear constitutive equations. Onsager’s postulate is utilized for the derivation of viscosity. Return-Mapping-Algorithm is invoked for plasticity.… More >

Wenwen Hu¹, Xinzhan Li², Tao Luo^2,*, Li Li²

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.077120 - 18 May 2026

Abstract This study experimentally investigates the Hybrid Effect of Steel Fiber (SF) and Recycled Rubber Powder (RRP) on Freeze-Thaw (F-T) Resistance and Pore Structure of Concrete. With respect to the mechanical properties of Steel Reinforced Concrete (SRC) before and after F-T cycles, the mixture incorporating 1.5% SF and 10% RRP achieves the optimal performance, exhibiting a distinct positive hybrid effect with the γ of the tensile-to-compressive strength ratio of 1.427. The synergistic interaction between SF and RRP preserves the compressive strength and significantly enhances the tensile performance of SRC. Meanwhile, it alleviates the degradation of mechanical More >

Hui Zhang^1,*, Yingying Xie¹, Yu Zhang^2,*, Zhan Gao¹, Aijun Li¹, Sheng Shi¹, Xingyue Li¹, Zheming Zhou¹, Haotian Wang¹

Structural Durability & Health Monitoring, Vol.20, No.3, 2026, DOI:10.32604/sdhm.2026.075835 - 18 May 2026

Abstract A composite bridge deck system consisting of an orthotropic steel deck and a normal-temperature-cured reactive powder concrete (RPC) layer is proposed to address the problems of pavement damage and fatigue cracks in steel bridge decks. In this study, a local finite element model of a bridge segment was established using ANSYS to calculate and compare the stress states of four deck systems: normal-temperature-cured RPC composite box girders, high-temperature-cured RPC composite box girders, pure steel box girders, and ordinary concrete composite box girders. Additionally, static load tests were conducted on a scaled local model to validate… More > Graphic Abstract

Chuhan Zhang¹, Jinguo You^1,*, Jialin Xu¹, Mingqian Li¹, Xiaofeng Chen², Jingmei Tao², Caiju Li², Jianhong Yi²

CMC-Computers, Materials & Continua, Vol.88, No.1, 2026, DOI:10.32604/cmc.2026.079587 - 08 May 2026

Abstract With the rapid development of artificial intelligence and data-driven modeling, deep learning has become an effective tool for analyzing scientific discovery such as predicting material behaviors. Graphene-reinforced copper-based composites, which exhibit excellent mechanical, electrical, and thermal properties, have attracted extensive attention in advanced engineering applications; however, accurate prediction of their stress–strain behavior still relies heavily on computationally expensive molecular dynamics simulations or experiments. In this work, we propose a Graph-based Spatio-Temporal Attention Network, termed GraphSTAN, for stress–strain behavior prediction of copper-based composites. Specifically, atomic-scale initial microstructures are encoded as graphs and integrated with static physical More >