Huayi Zhang¹, Maobin Song², Lei Shen^1,*, Nizar Faisal Alkayem¹, Maosen Cao³

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 55-75, 2025, DOI:10.32604/sdhm.2024.052869 - 15 November 2024

Abstract The concrete panel of earth-rock dams in cold regions tends to crack due to the combination effect of non-uniform foundation settlement, ice expansion loads, and freeze-thaw damage. In this work, simulations are designed to investigate the effects of freeze-thaw damage degrees on the fracture behavior caused by the partial detachment and ice expansion loads on concrete panels. Results show that the range of detached panels and freeze-thaw damage degree are the dominant factors that affect the overall load-bearing capacity of the panel and the failure cracking modes, whereas the panel slope is a secondary factor. More >

Mujahid Ali^*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2161-2194, 2024, DOI:10.32604/cmc.2024.058888 - 18 November 2024

Abstract Forecasting travel demand requires a grasp of individual decision-making behavior. However, transport mode choice (TMC) is determined by personal and contextual factors that vary from person to person. Numerous characteristics have a substantial impact on travel behavior (TB), which makes it important to take into account while studying transport options. Traditional statistical techniques frequently presume linear correlations, but real-world data rarely follows these presumptions, which may make it harder to grasp the complex interactions. Thorough systematic review was conducted to examine how machine learning (ML) approaches might successfully capture nonlinear correlations that conventional methods may… More >

Jian Feng^*, Tian Liu, Cailing Du

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2895-2909, 2024, DOI:10.32604/cmc.2024.056434 - 18 November 2024

Abstract Unsupervised learning methods such as graph contrastive learning have been used for dynamic graph representation learning to eliminate the dependence of labels. However, existing studies neglect positional information when learning discrete snapshots, resulting in insufficient network topology learning. At the same time, due to the lack of appropriate data augmentation methods, it is difficult to capture the evolving patterns of the network effectively. To address the above problems, a position-aware and subgraph enhanced dynamic graph contrastive learning method is proposed for discrete-time dynamic graphs. Firstly, the global snapshot is built based on the historical snapshots… More >

Zeyu Deng¹, Yuan Liang^1,*, Gengdong Cheng¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-1, 2024, DOI:10.32604/icces.2024.012504

Abstract Compared to single-material optimization, topology optimization of multi-material structures offers a larger design space. It also requires efficient material selection methods to provide guidance for designers. The predominant methods are based on interpolation schemes, which introduce order-dependence issues during the optimization process. This means the sequence in which materials are arranged can significantly impact the optimization outcomes and may lead to notable issues with material gradation. This paper identifies the mathematical essence of multi-material topology optimization as a nonlinear multi-valued integer programming problem. In this paper, we propose a novel stochastic discrete steepest descent multi-valued More >

Yuhang Lyu¹, Shaohai Dong¹, Li Ting Gao¹, Zhan-Sheng Guo^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-1, 2024, DOI:10.32604/icces.2024.012815

Abstract Drying and calendering processes are crucial in electrode manufacturing, as they significantly affect the mechanical and electrochemical performances of lithium-ion batteries. In this study, we established a three-dimensional (3D) representative volume element (RVE) of electrodes composed of active material particles, carbon binder domain particles, solvent, and different particle contact types. We continuously simulated the 3D macroscopic and microscopic structural evolutions of the RVE during drying and calendering using the discrete element method (DEM). Based on the evolution of the particle coordination numbers and contact networks during drying, we propose a three-stage-drying scheme, consistent with the More >

Kaituo Jiao¹, Dongxu Han^2,*, Bo Yu²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-3, 2024, DOI:10.32604/icces.2024.011520

Abstract Motivated by the fractures being very thin compared to the size of rock matrix, utilizing the non-conforming grid is an efficient approach to simulate fluid flow in fractured porous media. The embedded discrete fracture model (EDFM) is the typical one that using the conforming grid and modelled based on the finite volume method (FVM) framework. The EDFM maintains advantages of mass conservation and low computational complexity, but it cannot characterize blocking fractures and has a low accuracy on the mass exchange between fractures and matrix [1]. In our previous work [2], we developed the enriched-EDFM… More >

Weitao Zhang¹, Dongxu Han^2,*, Yujie Chen², Tingyu Li³, Liang Gong^1,*, Bo Yu²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-2, 2024, DOI:10.32604/icces.2024.011484

Abstract As climate change accelerates due to fossil fuel use, geothermal energy emerges as an indispensable renewable solution 1. Hot dry rock (HDR) reservoirs, accounting for more than 90% of total geothermal resources 2, have gained wide attention worldwide for their abundant reserves, wide distribution, and carbon-free, stable, and efficient supply characteristics 3. While HDR geothermal energy offers significant potential, its development faces challenges, including the complex interaction between fluid flow, heat transfer, reactive solute transport, and the rock’s mechanical processes, referred to as the THMC coupling process 4. Cracks, ubiquitous in HDR geothermal reservoirs, exhibit… More >

Liming Yang^1,*, Linchang Han¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.010890

Abstract This work introduces an efficient improved discrete velocity method (IDVM) with inner iteration for simulating steady flows across all flow regimes. Building upon our prior implicit IDVM, this extension achieves a significantly enhanced convergence rate. In the previous method, simultaneous solution of the discrete velocity Boltzmann equation (DVBE) and corresponding macroscopic governing equations was performed. However, the computational cost was primarily driven by the DVBE calculations due to the substantial difference in the number of discrete distribution functions compared to macroscopic conservative variables. Additionally, the convergence rate was influenced by the predicted equilibrium state derived… More >

Liang Zeng^1,2,3, Ziyang Ding¹, Junyang Shi¹, Shanshan Wang^1,2,3,*

CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 1757-1787, 2024, DOI:10.32604/cmc.2024.055574 - 15 October 2024

Abstract In the manufacturing industry, reasonable scheduling can greatly improve production efficiency, while excessive resource consumption highlights the growing significance of energy conservation in production. This paper studies the problem of energy-efficient distributed heterogeneous permutation flowshop problem with variable processing speed (DHPFSP-VPS), considering both the minimum makespan and total energy consumption (TEC) as objectives. A discrete multi-objective squirrel search algorithm (DMSSA) is proposed to solve the DHPFSP-VPS. DMSSA makes four improvements based on the squirrel search algorithm. Firstly, in terms of the population initialization strategy, four hybrid initialization methods targeting different objectives are proposed to enhance… More >

Chongdong Lin^1,2,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.1, pp. 1-1, 2024, DOI:10.32604/icces.2024.011631

Abstract In many real-world scenarios, such as high-speed combustion processes and re-entry flows in aerospace vehicles, the flow conditions often involve complex interactions between multiple chemical species and energy modes, leading to thermodynamic nonequilibrium effects. Traditional computational fluid dynamics (CFD) methods struggle to accurately capture these phenomena due to their simplifying assumptions regarding equilibrium thermodynamics. To solve this issue, the Multicomponent Discrete Boltzmann Method (MDBM) is proposed as a numerical approach to simulate compressible reactive flows with thermodynamic nonequilibrium effects. Based on kinetic theory, this method can capture the complex interactions between different species and energy… More >