Zhengyan Chang, Weiwei Wang, Mingliang Yang, Heng Yang, Qing Dong, Keyuan Zhao, Jie Yuwen^*

Structural Durability & Health Monitoring, Vol.20, No.1, 2026, DOI:10.32604/sdhm.2025.066572 - 08 January 2026

Abstract To address the neglect of seismic performance in conventional double-girder bridge crane optimization, this paper introduces a time-history analysis-based seismic optimization methodology for crane structures. Using a 25-t nuclear power crane as a case study, a bridge frame finite element model is established and validated through static analysis, confirming its accurate representation of the physical entity’s mechanical behavior. Furthermore, with bridge mass reduction as the objective and structural strength, stiffness, stability, and seismic mechanical performance as constraints, an optimization model is developed employing the Whale Optimization Algorithm (WOA). More >

Samira Rastbod¹, Mehdi Jahangiri^2,*, Behrang Moradi¹, Haleh Nazari¹

Energy Engineering, Vol.123, No.1, 2026, DOI:10.32604/ee.2025.070089 - 27 December 2025

Abstract Curtain wall systems have evolved from aesthetic façade elements into multifunctional building envelopes that actively contribute to energy efficiency and climate responsiveness. This review presents a comprehensive examination of curtain walls from an energy-engineering perspective, highlighting their structural typologies (Stick and Unitized), material configurations, and integration with smart technologies such as electrochromic glazing, parametric design algorithms, and Building Management Systems (BMS). The study explores the thermal, acoustic, and solar performance of curtain walls across various climatic zones, supported by comparative analyses and iconic case studies including Apple Park, Burj Khalifa, and Milad Tower. Key challenges—including… More > Graphic Abstract

Chenxi Xiu^1,2,*, Xihua Chu², Ao Mei¹, Liangfei Gong¹

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-39, 2026, DOI:10.32604/cmc.2025.073193 - 09 December 2025

Abstract Granular materials exhibit complex macroscopic mechanical behaviors closely related to their micro-scale microstructural features. Traditional macroscopic phenomenological elasto-plastic models, however, usually have complex formulations and lack explicit relations to these microstructural features. To avoid these limitations, this study proposes a micromechanics-based softening hyperelastic model for granular materials, integrating softening hyperelasticity with microstructural insights to capture strain softening, critical state, and strain localization behaviors. The model has two key advantages: (1) a clear conceptualization, straightforward formulation, and ease of numerical implementation (via Abaqus UMAT subroutine in this study); (2) explicit incorporation of micro-scale features (e.g., contact… More >

Alexander V. Savin^1,2, Elena A. Korznikova^3,4, Sergey V. Dmitriev^5,*

CMC-Computers, Materials & Continua, Vol.86, No.2, pp. 1-20, 2026, DOI:10.32604/cmc.2025.072786 - 09 December 2025

Abstract Due to their chiral structure, carbon nanosprings possess unique properties that are promising for nanotechnology applications. The structural transformations of carbon nanosprings in the form of spiral macromolecules derived from planar coronene and kekulene molecules (graphene helicoids and spiral nanoribbons) are analyzed using molecular dynamics simulations. The interatomic interactions are described by a force field including valence bonds, bond angles, torsional and dihedral angles, as well as van der Waals interactions. While the tension/compression of such nanosprings has been analyzed in the literature, this study investigates other modes of deformation, including bending and twisting. Depending… More >

Binchang Ma¹, Xinhai Yu², Gang Huang^3,*

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-21, 2026, DOI:10.32604/cmc.2025.071320 - 10 November 2025

Abstract Vacancy defects, as fundamental disruptions in metallic lattices, play an important role in shaping the mechanical and electronic properties of aluminum crystals. However, the influence of vacancy position under coupled thermomechanical fields remains insufficiently understood. In this study, transmission and scanning electron microscopy were employed to observe dislocation structures and grain boundary heterogeneities in processed aluminum alloys, suggesting stress concentrations and microstructural inhomogeneities associated with vacancy accumulation. To complement these observations, first-principles calculations and molecular dynamics simulations were conducted for seven single-vacancy configurations in face-centered cubic aluminum. The stress response, total energy, density of states More >

Abdullah Alourani¹, Mehtab Alam^2,*, Ashraf Ali³, Ihtiram Raza Khan⁴, Chandra Kanta Samal²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-32, 2026, DOI:10.32604/cmc.2025.070161 - 10 November 2025

Abstract The evolution of cities into digitally managed environments requires computational systems that can operate in real time while supporting predictive and adaptive infrastructure management. Earlier approaches have often advanced one dimension—such as Internet of Things (IoT)-based data acquisition, Artificial Intelligence (AI)-driven analytics, or digital twin visualization—without fully integrating these strands into a single operational loop. As a result, many existing solutions encounter bottlenecks in responsiveness, interoperability, and scalability, while also leaving concerns about data privacy unresolved. This research introduces a hybrid AI–IoT–Digital Twin framework that combines continuous sensing, distributed intelligence, and simulation-based decision support. The… More >

Yafei Liu^1,2, Yuling Chen^1,2,*, Xuewei Wang³, Yuxiang Yang², Chaoyue Tan²

CMC-Computers, Materials & Continua, Vol.86, No.1, pp. 1-21, 2026, DOI:10.32604/cmc.2025.069152 - 10 November 2025

Abstract As blockchain technology rapidly evolves, smart contracts have seen widespread adoption in financial transactions and beyond. However, the growing prevalence of malicious Ponzi scheme contracts presents serious security threats to blockchain ecosystems. Although numerous detection techniques have been proposed, existing methods suffer from significant limitations, such as class imbalance and insufficient modeling of transaction-related semantic features. To address these challenges, this paper proposes an oversampling-based detection framework for Ponzi smart contracts. We enhance the Adaptive Synthetic Sampling (ADASYN) algorithm by incorporating sample proximity to decision boundaries and ensuring realistic sample distributions. This enhancement facilitates the… More >

Kui Wang^*, Qianbing Tan, Yisen Liu

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.012404

Abstract To address the increasing demands for lightweight and passive safety in transportation equipment, a series of studies on the crashworthiness design of composite thin-walled structures were conducted. These investigations leveraged the high specific strength/stiffness advantages of carbon fiber-reinforced polyamide composites and the high-formability benefits of fused deposition modeling (FDM) additive manufacturing technology. Compared with traditional composite manufacturing processes, lattice-filled thin-walled structures, integrally fabricated via additive manufacturing, exhibited significant synergistic interactions between their internal lattice and outer walls during compression. This synergy effectively enhanced the energy absorption capacity of the structures and achieved a "1+1>2" synergistic… More >

Xiangru He¹, Ying Deng¹, Zefu Li¹, Jie Zhi^1,2, Yonglin Chen^1,2, Weidong Yang^1,2,3,*, Yan Li^1,2,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.012395

Abstract Coordinated control of structural accuracy and mechanical properties is the key to composites manufacturing and the prerequisite for aerospace applications. In particular, accurate and efficient prediction of curing-induced deformation (CID) is of vital importance for fiber reinforced polymer composites quality control. In this study, we explored a novel spatio-temporal prediction model, which incorporates the finite element method with a deep learning framework to efficiently forecast the curing-induced deformation evolution of composite structures. Herein, we developed an integrated convolutional neural network (CNN) and long short-term memory (LSTM) network approach to capture both the space-distributed and time-resolved… More >

Huijing Gao, Yisen Liu, Qianbing Tan, Kui Wang^*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.34, No.1, pp. 1-1, 2025, DOI:10.32604/icces.2025.012320

Abstract Assembled structures attracted increasing attention due to their ultimate flexibility, wide design space, manufacturing and transporting conveniences. In this study, a novel assembled multi-cell structure was proposed to achieve tunable energy absorption characteristics. The quasi-static compression experiments demonstrated that the crashworthiness of the assembled multi-cell structure could be effectively and rapidly tailored by varying the number and material of cells. Furthermore, to enhance the mechanical interlocking capability and energy absorption performance of existing assembled structures, three connection joints were further proposed. Tensile tests were conducted to investigate their mechanical properties, and the results revealed that… More >