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  • Open Access


    Multi-Stage Multidisciplinary Design Optimization Method for Enhancing Complete Artillery Internal Ballistic Firing Performance

    Jipeng Xie1,2, Guolai Yang1,*, Liqun Wang1, Lei Li1

    CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 793-819, 2024, DOI:10.32604/cmes.2024.048174

    Abstract To enhance the comprehensive performance of artillery internal ballistics—encompassing power, accuracy, and service life—this study proposed a multi-stage multidisciplinary design optimization (MS-MDO) method. First, the comprehensive artillery internal ballistic dynamics (AIBD) model, based on propellant combustion, rotation band engraving, projectile axial motion, and rifling wear models, was established and validated. This model was systematically decomposed into subsystems from a system engineering perspective. The study then detailed the MS-MDO methodology, which included Stage I (MDO stage) employing an improved collaborative optimization method for consistent design variables, and Stage II (Performance Optimization) focusing on the independent optimization of local design variables and… More >

  • Open Access


    A Comparative Study of Metaheuristic Optimization Algorithms for Solving Real-World Engineering Design Problems

    Elif Varol Altay, Osman Altay, Yusuf Özçevik*

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 1039-1094, 2024, DOI:10.32604/cmes.2023.029404

    Abstract Real-world engineering design problems with complex objective functions under some constraints are relatively difficult problems to solve. Such design problems are widely experienced in many engineering fields, such as industry, automotive, construction, machinery, and interdisciplinary research. However, there are established optimization techniques that have shown effectiveness in addressing these types of issues. This research paper gives a comparative study of the implementation of seventeen new metaheuristic methods in order to optimize twelve distinct engineering design issues. The algorithms used in the study are listed as: transient search optimization (TSO), equilibrium optimizer (EO), grey wolf optimizer (GWO), moth-flame optimization (MFO), whale… More >

  • Open Access


    Multidisciplinary Modeling and Optimization Method of Remote Sensing Satellite Parameters Based on SysML-CEA

    Changyong Chu1,2,*, Chengfang Yin1, Shuo Shi1, Shaohui Su1, Chang Chen1

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.2, pp. 1413-1434, 2023, DOI:10.32604/cmes.2022.022395

    Abstract To enhance the efficiency of system modeling and optimization in the conceptual design stage of satellite parameters, a system modeling and optimization method based on System Modeling Language and Co-evolutionary Algorithm is proposed. At first, the objectives of satellite mission and optimization problems are clarified, and a design matrix of discipline structure is constructed to process the coupling relationship of design variables and constraints of the orbit, payload, power and quality disciplines. In order to solve the problem of increasing non-linearity and coupling between these disciplines while using a standard collaborative optimization algorithm, an improved genetic algorithm is proposed and… More > Graphic Abstract

    Multidisciplinary Modeling and Optimization Method of Remote Sensing Satellite Parameters Based on SysML-CEA

  • Open Access


    An Uncertainty Analysis and Reliability-Based Multidisciplinary Design Optimization Method Using Fourth-Moment Saddlepoint Approximation

    Yongqiang Guo1,2,*, Zhiyuan Lv3

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 1855-1870, 2023, DOI:10.32604/cmes.2022.022211

    Abstract In uncertainty analysis and reliability-based multidisciplinary design and optimization (RBMDO) of engineering structures, the saddlepoint approximation (SA) method can be utilized to enhance the accuracy and efficiency of reliability evaluation. However, the random variables involved in SA should be easy to handle. Additionally, the corresponding saddlepoint equation should not be complicated. Both of them limit the application of SA for engineering problems. The moment method can construct an approximate cumulative distribution function of the performance function based on the first few statistical moments. However, the traditional moment matching method is not very accurate generally. In order to take advantage of… More >

  • Open Access


    RBMDO Using Gaussian Mixture Model-Based Second-Order Mean-Value Saddlepoint Approximation

    Debiao Meng1,2,3, Shiyuan Yang1, Tao Lin4,5,*, Jiapeng Wang1, Hengfei Yang1, Zhiyuan Lv1

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.2, pp. 553-568, 2022, DOI:10.32604/cmes.2022.020756

    Abstract Actual engineering systems will be inevitably affected by uncertain factors. Thus, the Reliability-Based Multidisciplinary Design Optimization (RBMDO) has become a hotspot for recent research and application in complex engineering system design. The Second-Order/First-Order Mean-Value Saddlepoint Approximate (SOMVSA/FOMVSA) are two popular reliability analysis strategies that are widely used in RBMDO. However, the SOMVSA method can only be used efficiently when the distribution of input variables is Gaussian distribution, which significantly limits its application. In this study, the Gaussian Mixture Model-based Second-Order Mean-Value Saddlepoint Approximation (GMM-SOMVSA) is introduced to tackle above problem. It is integrated with the Collaborative Optimization (CO) method to… More >

  • Open Access


    Multidisciplinary Design Optimization of Long Endurance Unmanned Aerial Vehicle Wing

    S. Rajagopal1, Ranjan Ganguli2

    CMES-Computer Modeling in Engineering & Sciences, Vol.81, No.1, pp. 1-34, 2011, DOI:10.3970/cmes.2011.081.001

    Abstract The preliminary wing design of a low speed, long endurance UAV is formulated as a two step optimization problem. The first step performs a single objective aerodynamic optimization and the second step involves a coupled dual objective aerodynamic and structural optimization. During the first step, airfoil geometry is optimized to get maximum endurance parameter at a 2D level with maximum thickness to chord ratio and maximum camber as design variables. Leading edge curvature, trailing edge radius, zero lift drag coefficient and zero lift moment coefficient are taken as constraints. Once the airfoil geometry is finalized, the wing planform parameters are… More >

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