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  • Open Access

    PROCEEDINGS

    Deep Learning-Based Prediction of Material Elastic Constants and Residual Stresses of Orthotropic Materials from Moiré Interferometry

    Dong-Wook Lee1,*, Heungjo An2, Tae Yeon Kim3, Sungmun Lee4, Jide Oyebanji1, Prabakaran Balasubramanian1

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.31, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.011286

    Abstract This work analyzes the problems of material elastic constants identification and residual stresses determination in an orthotropic materials using hole drilling method. These problems are very important to understand mechanical performance of materials. A lot of optical method such as Moiré, laser speckle interferometry, digital image correlation or photoelasticity is developed to estimate displacement (or strain) fields or applied loads (or stresses) from images. These methods require a very complicated techniques, skill, and efforts to analysis images. But deep learning method based on a convolution neural network shows better performance in image analysis problems such… More >

  • Open Access

    ARTICLE

    Instruments Assessing Problematic Use of the Internet and Their Associations with Psychological Distress among Ghanaian University Students

    Yu-Ting Huang1,#, Daniel Kwasi Ahorsu2,#, Emma Sethina Adjaottor3,*, Frimpong-Manso Addo3, Mark D. Griffiths4, Amir H. Pakpour5, Chung-Ying Lin1,6,7,8,*

    International Journal of Mental Health Promotion, Vol.26, No.11, pp. 875-885, 2024, DOI:10.32604/ijmhp.2024.057049 - 28 November 2024

    Abstract Background: The present study evaluated the psychometric properties of Problematic Internet Use (PIU) instruments and their correlation with psychological distress and time spent on Internet activities among university students in Ghana. Methods: In the present cross-sectional survey design study, 520 participants (35.96% female) were recruited with a mean age of 19.55 years (SD = 1.94) from several university departments (i.e., Behavioral Sciences, Materials Engineering, Nursing and Midwifery, and Biochemistry and Biotechnology) of Kwame Nkrumah University of Science and Technology (KNUST) between 19 July and 04 August, 2023. Participants completed a survey that included the following… More >

  • Open Access

    PROCEEDINGS

    Improved XFEM (IXFEM): Accurate, Efficient, Robust and Reliable Analysis for Arbitrary Multiple Crack Problems

    Lixiang Wang1, Longfei Wen2,3, Rong Tian2,3,*, Chun Feng1,4,*

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.011137

    Abstract The extended finite element method (XFEM) has been successful in crack analysis but faces challenges in modeling multiple cracks. One challenge is the linear dependence and ill-conditioning of the global stiffness matrix, while another is the geometric description for multiple cracks. To address the first challenge, the Improved XFEM (IXFEM) [1–9] is extended to handle multiple crack problems, effectively eliminating issues of linear dependence and ill-conditioning. Additionally, to overcome the second challenge, a novel level set templated cover cutting method (LSTCCM) [10] is proposed, which combines the advantages of the level set method and cover More >

  • Open Access

    ARTICLE

    IQAOA for Two Routing Problems: A Methodological Contribution with Application to TSP and VRP

    Eric Bourreau1, Gérard Fleury2, Philippe Lacomme2,*

    Journal of Quantum Computing, Vol.6, pp. 25-51, 2024, DOI:10.32604/jqc.2024.048792 - 25 October 2024

    Abstract The paper presents a novel quantum method for addressing two fundamental routing problems: the Traveling Salesman Problem (TSP) and the Vehicle Routing Problem (VRP), both central to routing challenges. The proposed method, named the Indirect Quantum Approximate Optimization Algorithm (IQAOA), leverages an indirect solution representation using ranking. Our contribution focuses on two main areas: 1) the indirect representation of solutions, and 2) the integration of this representation into an extended version of QAOA, called IQAOA. This approach offers an alternative to QAOA and includes the following components: 1) a quantum parameterized circuit designed to simulate… More >

  • Open Access

    ARTICLE

    A Discrete Multi-Objective Squirrel Search Algorithm for Energy-Efficient Distributed Heterogeneous Permutation Flowshop with Variable Processing Speed

    Liang Zeng1,2,3, Ziyang Ding1, Junyang Shi1, Shanshan Wang1,2,3,*

    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 >

  • Open Access

    ARTICLE

    African Bison Optimization Algorithm: A New Bio-Inspired Optimizer with Engineering Applications

    Jian Zhao1,2,*, Kang Wang1,2, Jiacun Wang3,*, Xiwang Guo4, Liang Qi5

    CMC-Computers, Materials & Continua, Vol.81, No.1, pp. 603-623, 2024, DOI:10.32604/cmc.2024.050523 - 15 October 2024

    Abstract This paper introduces the African Bison Optimization (ABO) algorithm, which is based on biological population. ABO is inspired by the survival behaviors of the African bison, including foraging, bathing, jousting, mating, and eliminating. The foraging behavior prompts the bison to seek a richer food source for survival. When bison find a food source, they stick around for a while by bathing behavior. The jousting behavior makes bison stand out in the population, then the winner gets the chance to produce offspring in the mating behavior. The eliminating behavior causes the old or injured bison to More >

  • Open Access

    PROCEEDINGS

    Topology Optimization for Conjugate Heat Transfer Problems Based on the k-omega Turbulence Model

    Ritian Ji1, Zhiguo Qu1,*, Hui Wang1, Binbin Jiao2, Yuxin Ye2

    The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.2, pp. 1-1, 2024, DOI:10.32604/icces.2024.012210

    Abstract In this manuscript, a finite volume discrete topology optimization method based on the continuous adjoint method is proposed to simulate turbulent flow using the k-omega turbulence model for solving the topology optimization problem of conjugate heat transfer at high Reynolds number. The manuscript simulates the conjugate turbulent convective heat transfer problem at high Reynolds number with a set of Reynolds-Averaged Navier-Stokes (RANS) equations coupled with energy transport equations and control equations of the k-omega turbulence model, and implements the methodology by using the variable density method, interpolates the material values of thermal conductivity, heat capacity,… More >

  • Open Access

    ARTICLE

    An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for Engineering Problems and Its Applications in Breast Cancer Problem

    Feyza Altunbey Özbay1, Erdal Özbay2, Farhad Soleimanian Gharehchopogh3,*

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.2, pp. 1067-1110, 2024, DOI:10.32604/cmes.2024.054334 - 27 September 2024

    Abstract Artificial rabbits optimization (ARO) is a recently proposed biology-based optimization algorithm inspired by the detour foraging and random hiding behavior of rabbits in nature. However, for solving optimization problems, the ARO algorithm shows slow convergence speed and can fall into local minima. To overcome these drawbacks, this paper proposes chaotic opposition-based learning ARO (COARO), an improved version of the ARO algorithm that incorporates opposition-based learning (OBL) and chaotic local search (CLS) techniques. By adding OBL to ARO, the convergence speed of the algorithm increases and it explores the search space better. Chaotic maps in CLS… More > Graphic Abstract

    An Improved Artificial Rabbits Optimization Algorithm with Chaotic Local Search and Opposition-Based Learning for Engineering Problems and Its Applications in Breast Cancer Problem

  • Open Access

    ARTICLE

    High-Order DG Schemes with Subcell Limiting Strategies for Simulations of Shocks, Vortices and Sound Waves in Materials Science Problems

    Zhenhua Jiang1,*, Xi Deng2,3, Xin Zhang1, Chao Yan1, Feng Xiao4, Jian Yu1

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.10, pp. 2183-2204, 2024, DOI:10.32604/fdmp.2024.053231 - 23 September 2024

    Abstract Shock waves, characterized by abrupt changes in pressure, temperature, and density, play a significant role in various materials science processes involving fluids. These high-energy phenomena are utilized across multiple fields and applications to achieve unique material properties and facilitate advanced manufacturing techniques. Accurate simulations of these phenomena require numerical schemes that can represent shock waves without spurious oscillations and simultaneously capture acoustic waves for a wide range of wavelength scales. This work suggests a high-order discontinuous Galerkin (DG) method with a finite volume (FV) subcell limiting strategies to achieve better subcell resolution and lower numerical More >

  • Open Access

    ARTICLE

    Solving the Generalized Traveling Salesman Problem Using Sequential Constructive Crossover Operator in Genetic Algorithm

    Zakir Hussain Ahmed1,*, Maha Ata Al-Furhood2, Abdul Khader Jilani Saudagar3, Shakir Khan4

    Computer Systems Science and Engineering, Vol.48, No.5, pp. 1113-1131, 2024, DOI:10.32604/csse.2024.053574 - 13 September 2024

    Abstract The generalized travelling salesman problem (GTSP), a generalization of the well-known travelling salesman problem (TSP), is considered for our study. Since the GTSP is NP-hard and very complex, finding exact solutions is highly expensive, we will develop genetic algorithms (GAs) to obtain heuristic solutions to the problem. In GAs, as the crossover is a very important process, the crossover methods proposed for the traditional TSP could be adapted for the GTSP. The sequential constructive crossover (SCX) and three other operators are adapted to use in GAs to solve the GTSP. The effectiveness of GA using More >

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