Hao Sun, Xiaohong Ding^*, Min Xiong, Heng Zhang

CMC-Computers, Materials & Continua, Vol.89, No.2, 2026, DOI:10.32604/cmc.2026.087308 - 15 September 2026

Abstract Designing two-dimensional anisotropic mechanical metamaterial unit cells from prescribed effective properties remains a challenging inverse problem, particularly when directional stiffness and material usage need to be controlled simultaneously. In this work, a data-driven conditional diffusion framework is developed for generating unit-cell structures with target effective elastic moduli and volume fractions. A structure–property database containing 57,000 binary unit-cell images is first established through a random target-property-driven inverse homogenization method. The effective elastic moduli in the x and y directions, together with the volume fraction, are used as conditional labels, denoted as (E_x, E_y, V). A conditional denoising diffusion probabilistic… More >

Zongzheng Jiao¹, Shuaikang Yang¹, Junlong Yin¹, Shaohui Wang², Minpo Jung^1,*

FDMP-Fluid Dynamics & Materials Processing, Vol.22, No.8, 2026, DOI:10.32604/fdmp.2026.087218 - 04 September 2026

Abstract Hydro-mechanical (HM) simulations of porous-media systems—such as those used in geotechnical engineering, groundwater flow, formation consolidation, and underground-structure safety assessment—become computationally expensive when large material- and load-parameter spaces must be explored for design optimization, uncertainty quantification, or real-time decision support. Although data-driven surrogate models can accelerate such analyses, it remains unclear whether explicitly conditioning a history-based predictor on physical parameters offers a meaningful advantage over learning directly from the temporal evolution of the physical fields. This study systematically benchmarks five physical-parameter conditioning strategies—token concatenation, feature-wise linear modulation (FiLM), weak FiLM, adaptive instance normalization (AdaIN), and… More >

Peng Guan^*, Ming-Ran Li, Si-Bo-Wen Wang

Frontiers in Heat and Mass Transfer, Vol.24, No.4, 2026, DOI:10.32604/fhmt.2026.082595 - 31 August 2026

Abstract This paper develops a thermomechanical optimization method for turbo guide vane (TGV) weight reduction under restrictive conditions and highly sensitive variables. The proposed method integrates a flow-thermo-structural model, orthogonal experimental design (OED), and an optimization framework based on response surface methodology (RSM) and a genetic algorithm (GA). To address both the plastic limit and temperature distribution of the TGV, a new parameter termed the stress ratio is introduced as a constraint during optimization. Six highly sensitive variables were selected from ten cooling channel diameters using OED. Simulation results based on the thermal-fluid coupling model were… More >

Haitao Liu^1,*, Xuyang Wang¹, Shengcheng Quan¹, Qiaosheng Guo², Aichun Wang³, Lie Yang¹, Tingfang Zhang¹, Xiaojian Wu^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.085747 - 28 August 2026

Abstract Rapid advances in information and automation technologies have accelerated the development of smart manufacturing, thereby heightening the importance of reliable fault diagnosis for mechanical equipment. Although neural network-based algorithms are widely adopted in industrial applications due to their strong feature extraction and classification capabilities, their deployment in safety-critical fields such as aerospace remains limited. This limitation mainly arises from poor model interpretability and a heavy reliance on large-scale labeled training data. To address these challenges, this paper proposes an interpretable neural network framework that integrates discrete wavelet transform (DWT) with neural networks. Specifically, discrete wavelet… More >

Mengyao Wang¹, Ailian Zhu², Longji Zhu^3,*, Chen Lan^4,*, Yang Li⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.148, No.2, 2026, DOI:10.32604/cmes.2026.085279 - 28 August 2026

Abstract Accurate prediction of asphalt pavement distress is essential for proactive maintenance and life-cycle infrastructure management. However, existing data-driven methods often struggle to jointly represent multi-source inspection data, distress evolution mechanisms, and spatial propagation relationships among pavement sections. To address these limitations, this study proposes a Dual-Layer Progressive Physics-Constrained Graph Neural Network (DLPC-GNN) for asphalt pavement distress prediction and maintenance strategy classification. The proposed model represents pavement deterioration using a dual-layer graph structure. At the microscopic level, cracks, surface deterioration, and structural moisture-induced damage are modeled as physically associated distress nodes. At the macroscopic level, pavement-section… More >

Nurhasnah¹, Naresworo Nugroho^1,*, Sarah Augustina^2,*, Silvia Uthari Nuzaverra Mayang Mangurai³, Deazy Rachmi Trisatya^1,2

Journal of Renewable Materials, Vol.14, No.8, 2026, DOI:10.32604/jrm.2026.02026-0027 - 26 August 2026

Abstract Randu wood is a fast-growing wood species with a low density, ranging from 0.21 to 0.28 g/cm³. This limits the utilization of this species, particularly for structural purposes. Improving the quality and strength of wood can be done by applying a densification process. The effectiveness of this process may be improved by applying in-situ delignification using peracetic acid as a pretreatment. Therefore, this study aimed to analyze the physical (moisture content and density), dimensional stability (TR-ratios, water absorption, and thickness swelling), spring-back (compression set, and compression-set recovery) and mechanical properties (Modulus of Rupture/MOR and Modulus of… More > Graphic Abstract

Xinzhan Li¹, Haixin Sun², Li Li^1,3,*, Zongjin Li³, Guangming Xie⁴, Guangzhao Li⁴

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.081014 - 24 August 2026

Abstract To utilize waste clay bricks and reduce carbon emissions, recycled brick powder (RBP) was prepared from waste brick-concrete structures and used to produce alkali-activated slag-recycled brick powder foam concrete (ASRFC). This paper evaluated the impact of RBP replacement rates and water-binder ratio on the physical and mechanical properties of foam concrete, including its thermal conductivity, strength, and pore structure. The results demonstrated that the addition of 10% RBP resulted in decreases in the apparent density and thermal conductivity of ASRFC, while flexural strength and the flexural-compressive strength ratio exhibited significant increases. These phenomena can all… More >

Hongyan Liu, Fang Wang, Jie Zhao, Feng Wu^*

Structural Durability & Health Monitoring, Vol.20, No.5, 2026, DOI:10.32604/sdhm.2026.079457 - 24 August 2026

Abstract This study investigates the thermo-mechanical behavior and residual strength of full-scale reinforced concrete (RC) beams subjected to ISO-834 fire exposure, emphasizing temperature-dependent material degradation and bond-slip effects. A sequentially coupled numerical framework was developed in ABAQUS, integrating a temperature-indexed Concrete Damage Plasticity (CDP) model for concrete, elastoplastic steel constitutive laws, and a temperature-dependent bond-slip model implemented via nonlinear SPRING2 elements. The model explicitly accounts for post-peak concrete softening, steel yield degradation, and interface deterioration, and was calibrated against full-scale experiments. Experimental measurements included internal and surface temperatures, load–midspan deflection, and residual strength after natural cooling. More >

Nathan Jourdainne^1,2, Mathilda Ekholm¹, Nawel Belkessa¹, Antonin Vignon¹, Nicolas Sbirrazzuoli¹, Christelle Combeaud², Jean-Luc Bouvard², Nathanael Guigo^1,2,*

Journal of Renewable Materials, Vol.14, No.7, 2026, DOI:10.32604/jrm.2026.02026-0040 - 28 July 2026

Abstract This study investigates the valorization of mussel shell waste as a bio-derived filler in poly(L-lactic acid) (PLLA) to promote sustainable materials aligned with circular economy principles. Mussel shells, a seafood industry byproduct rich in biogenic calcium carbonate, were ground into powder and incorporated into PLLA at 10–50 wt%. The resulting composites were thoroughly characterized using scanning electron microscopy and energy dispersive X-ray spectroscopy (SEM-EDX), Fourier transform infrared spectroscopy (FTIR), thermogravimetric analysis (TGA), differential scanning calorimetry (DSC), dynamic mechanical thermal analysis (DMTA), and uniaxial tensile testing to assess morphological, chemical, thermal, and mechanical properties. Incorporation of… More > Graphic Abstract

Harmiansyah^1,2, Maisy Pitaloka Sinaga¹, Sheilla Ika Amalia¹, Salma Hanan Arwinda¹, Al Aqib Anugerah Ramadhan¹, Hervianna Indira Kusuma Riandara¹, Mohamad Haafiz Mohamad Kassim^3,4,5, Mohd Shahrieel Mohd Aras⁶, Melbi Mahardika^3,7,*

Journal of Renewable Materials, Vol.14, No.7, 2026, DOI:10.32604/jrm.2026.02026-0007 - 28 July 2026

Abstract The limited mechanical performance of starch-based bioplastic films, particularly their low strength and stiffness, remains a major challenge for their broader application as sustainable packaging materials. This study aims to address this issue by utilizing cellulose fibers extracted from oil palm empty fruit bunch (OPEFB) waste as a reinforcing agent in corn starch–based bioplastic films. The bioplastic films were fabricated using a solution casting method with varying cellulose contents and subsequently characterized to evaluate their mechanical properties, crystalline structure, and thermal stability. The results demonstrate that the incorporation of cellulose fibers significantly enhances the tensile… More >