Yassir M. Abbas^*, Abdulaziz Alsaif^*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.2, pp. 1789-1819, 2025, DOI:10.32604/cmes.2025.073088 - 26 November 2025

Abstract The rapid advancement of three-dimensional printed concrete (3DPC) requires intelligent and interpretable frameworks to optimize mixture design for strength, printability, and sustainability. While machine learning (ML) models have improved predictive accuracy, their limited transparency has hindered their widespread adoption in materials engineering. To overcome this barrier, this study introduces a Random Forests ensemble learning model integrated with SHapley Additive exPlanations (SHAP) and Partial Dependence Plots (PDPs) to model and explain the compressive strength behavior of 3DPC mixtures. Unlike conventional “black-box” models, SHAP quantifies each variable’s contribution to predictions based on cooperative game theory, which enables… More >

Ruiqi Li^1,2, Hongda Chen^1,2,*, Haixiao Hu^1,2,3, Yu Zhang², Shuxin Li^1,2,3,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.2, pp. 1-1, 2025, DOI:10.32604/icces.2025.011327

Abstract Composite hydrogen cylinders are recognized as the most efficient solution for storage and transportation of high-pressure gaseous hydrogen. The plastic-lined and fully carbon fiber-wound Type IV composite cylinders are one of the most attractive advanced hydrogen storage technologies. The design of carbon fiber reinforcements on the dome section of the cylinder is one of the critical challenges in the development of Type IV composite hydrogen cylinders. Conventional design approaches ignored the variable angle of fiber-wound layers and the influence of fiber angle and thickness variations in the dome section on design and often result in… More >

Miloš Sedak^*, Maja Rosić, Božidar Rosić

CMES-Computer Modeling in Engineering & Sciences, Vol.142, No.2, pp. 2111-2145, 2025, DOI:10.32604/cmes.2025.059319 - 27 January 2025

Abstract This paper introduces a hybrid multi-objective optimization algorithm, designated HMODESFO, which amalgamates the exploratory prowess of Differential Evolution (DE) with the rapid convergence attributes of the Sailfish Optimization (SFO) algorithm. The primary objective is to address multi-objective optimization challenges within mechanical engineering, with a specific emphasis on planetary gearbox optimization. The algorithm is equipped with the ability to dynamically select the optimal mutation operator, contingent upon an adaptive normalized population spacing parameter. The efficacy of HMODESFO has been substantiated through rigorous validation against established industry benchmarks, including a suite of Zitzler-Deb-Thiele (ZDT) and Zeb-Thiele-Laumanns-Zitzler (DTLZ) More >

Dattu Ghane^*, Vishnu Wakchaure

Energy Engineering, Vol.121, No.11, pp. 3199-3220, 2024, DOI:10.32604/ee.2024.050952 - 21 October 2024

Abstract Wind energy provides a sustainable solution to the ever-increasing demand for energy. Micro-wind turbines offer a promising solution for low-wind speed, decentralized power generation in urban and remote areas. Earlier researchers have explored the design, development, and performance analysis of a micro-wind turbine system tailored for small-scale renewable energy generation. Researchers have investigated various aspects such as aerodynamic considerations, structural integrity, efficiency optimization to ensure reliable and cost-effective operation, blade design, generator selection, and control strategies to enhance the overall performance of the system. The objective of this paper is to provide a comprehensive design… More >

Huile Zhang^1,2,*, Shikang Li², Yurui Wu³, Pengpeng Zhi¹, Wei Wang^1,4, Zhonglai Wang^1,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.2, pp. 1975-1996, 2024, DOI:10.32604/cmes.2024.050185 - 20 May 2024

Abstract Carbon fiber composites, characterized by their high specific strength and low weight, are becoming increasingly crucial in automotive lightweighting. However, current research primarily emphasizes layer count and orientation, often neglecting the potential of microstructural design, constraints in the layup process, and performance reliability. This study, therefore, introduces a multiscale reliability-based design optimization method for carbon fiber-reinforced plastic (CFRP) drive shafts. Initially, parametric modeling of the microscale cell was performed, and its elastic performance parameters were predicted using two homogenization methods, examining the impact of fluctuations in microscale cell parameters on composite material performance. A finite… More >

Xue-Qin Li¹, Lu-Kai Song^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 665-684, 2024, DOI:10.32604/cmes.2024.048445 - 16 April 2024

Abstract Fatigue reliability-based design optimization of aeroengine structures involves multiple repeated calculations of reliability degree and large-scale calls of implicit high-nonlinearity limit state function, leading to the traditional direct Monte Claro and surrogate methods prone to unacceptable computing efficiency and accuracy. In this case, by fusing the random subspace strategy and weight allocation technology into bagging ensemble theory, a random forest (RF) model is presented to enhance the computing efficiency of reliability degree; moreover, by embedding the RF model into multilevel optimization model, an efficient RF-assisted fatigue reliability-based design optimization framework is developed. Regarding the low-cycle More >

Jipeng Xie^1,2, Guolai Yang^1,*, Liqun Wang¹, Lei Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 793-819, 2024, DOI:10.32604/cmes.2024.048174 - 16 April 2024

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 More >

Debiao Meng^1,2,*, Yipeng Guo^1,2, Yihe Xu³, Shiyuan Yang^1,2,*, Yongqiang Guo⁴, Lidong Pan⁴, Xinkai Guo²

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2329-2359, 2024, DOI:10.32604/cmes.2024.047507 - 11 March 2024

Abstract The escalating need for reliability analysis (RA) and reliability-based design optimization (RBDO) within engineering challenges has prompted the advancement of saddlepoint approximation methods (SAM) tailored for such problems. This article offers a detailed overview of the general SAM and summarizes the method characteristics first. Subsequently, recent enhancements in the SAM theoretical framework are assessed. Notably, the mean value first-order saddlepoint approximation (MVFOSA) bears resemblance to the conceptual framework of the mean value second-order saddlepoint approximation (MVSOSA); the latter serves as an auxiliary approach to the former. Their distinction is rooted in the varying expansion orders… More >

Xiaoyi Wang¹, Xinyue Chang², Wenxuan Wang^1,*, Zijie Qiao³, Feng Zhang^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.2, pp. 1775-1796, 2024, DOI:10.32604/cmes.2023.043913 - 29 January 2024

Abstract The objective of reliability-based design optimization (RBDO) is to minimize the optimization objective while satisfying the corresponding reliability requirements. However, the nested loop characteristic reduces the efficiency of RBDO algorithm, which hinders their application to high-dimensional engineering problems. To address these issues, this paper proposes an efficient decoupled RBDO method combining high dimensional model representation (HDMR) and the weight-point estimation method (WPEM). First, we decouple the RBDO model using HDMR and WPEM. Second, Lagrange interpolation is used to approximate a univariate function. Finally, based on the results of the first two steps, the original nested More >

Dazhi Wang^*, Pengyi Pan, Bowen Niu

CMC-Computers, Materials & Continua, Vol.77, No.2, pp. 1535-1555, 2023, DOI:10.32604/cmc.2023.042286 - 29 November 2023

Abstract The permanent magnet eddy current coupler (PMEC) solves the problem of flexible connection and speed regulation between the motor and the load and is widely used in electrical transmission systems. It provides torque to the load and generates heat and losses, reducing its energy transfer efficiency. This issue has become an obstacle for PMEC to develop toward a higher power. This paper aims to improve the overall performance of PMEC through multi-objective optimization methods. Firstly, a PMEC modeling method based on the Levenberg-Marquardt back propagation (LMBP) neural network is proposed, aiming at the characteristics of… More >