Zeinel Momynkulov^1,2, Azhar Tursynova^1,2,*, Olzhas Olzhayev^1,2, Akhanseri Ikramov^1,2, Sayat Ibrayev¹, Batyrkhan Omarov^1,2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.145, No.1, pp. 891-918, 2025, DOI:10.32604/cmes.2025.068615 - 30 October 2025

Abstract Robotic manipulators increasingly operate in complex three-dimensional workspaces where accuracy and strict limits on position, velocity, and acceleration must be satisfied. Conventional geometric planners emphasize path smoothness but often ignore dynamic feasibility, motivating control-aware trajectory generation. This study presents a novel model predictive control (MPC) framework for three-dimensional trajectory planning of robotic manipulators that integrates second-order dynamic modeling and multi-objective parameter optimization. Unlike conventional interpolation techniques such as cubic splines, B-splines, and linear interpolation, which neglect physical constraints and system dynamics, the proposed method generates dynamically feasible trajectories by directly optimizing over acceleration inputs while… More >

Jinghua Yang¹, Bin Gong^1,2,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.33, No.3, pp. 1-2, 2025, DOI: 10.32604/icces.2025.011889

Abstract Geological stratification interpretation divides geological strata based on acquired well-logging data, providing comparative analysis results for strata and structures. This process serves as a fundamental framework for subsequent drilling and development design plans, making it a crucial step in oil exploration and development process. Traditional geological stratification interpretation methods are based primarily on geological, logging, and experimental data, with manual determination of strata boundaries to obtain interpretation results. However, manual interpretation is characterized by strong subjectivity and reliance on experience, which may compromise the quality and consistency of the results. To eliminate the dependency on… More >

Duong Tien Dung^1,2,3, Ha Hai Nam⁴, Nguyen Long Giang³, Luong Thi Hong Lan^5,*

CMC-Computers, Materials & Continua, Vol.85, No.3, pp. 5625-5642, 2025, DOI:10.32604/cmc.2025.069636 - 23 October 2025

Abstract Semi-supervised clustering techniques attempt to improve clustering accuracy by utilizing a limited number of labeled data for guidance. This method effectively integrates prior knowledge using pre-labeled data. While semi-supervised fuzzy clustering (SSFC) methods leverage limited labeled data to enhance accuracy, they remain highly susceptible to inappropriate or mislabeled prior knowledge, especially in noisy or overlapping datasets where cluster boundaries are ambiguous. To enhance the effectiveness of clustering algorithms, it is essential to leverage labeled data while ensuring the safety of the previous knowledge. Existing solutions, such as the Trusted Safe Semi-Supervised Fuzzy Clustering Method (TS3FCM),… More >

Jianchang Hou¹, Zhanpeng Jiang¹, Fenghe Wu¹, Hui Lian¹, Zhaohua Wang², Zijian Liu³, Weicheng Li^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.144, No.2, pp. 1545-1572, 2025, DOI:10.32604/cmes.2025.068482 - 31 August 2025

Abstract In this paper, a topology optimization method for coordinated stiffness and strength design is proposed under mass constraints, utilizing the Solid Isotropic Material with Penalization approach. Element densities are regulated through sensitivity filtering to mitigate numerical instabilities associated with stress concentrations. A p-norm aggregation function is employed to globalize local stress constraints, and a normalization technique linearly weights strain energy and stress, transforming the multi-objective problem into a single-objective formulation. The sensitivity of the objective function with respect to design variables is rigorously derived. Three numerical examples are presented, comparing the optimized structures in terms More >

Yuming Luo¹, Wei Zhang², Anqi Zhao², Ling Gou¹, Li Chen¹, Yaling Yang¹, Xiaoping Wang¹, Shichang Liu¹, Huiqing Qi³, Shilai Hu^2,*

Energy Engineering, Vol.122, No.8, pp. 3201-3221, 2025, DOI:10.32604/ee.2025.066507 - 24 July 2025

Abstract This work proposes an optimization method for gas storage operation parameters under multi-factor coupled constraints to improve the peak-shaving capacity of gas storage reservoirs while ensuring operational safety. Previous research primarily focused on integrating reservoir, wellbore, and surface facility constraints, often resulting in broad constraint ranges and slow model convergence. To solve this problem, the present study introduces additional constraints on maximum withdrawal rates by combining binomial deliverability equations with material balance equations for closed gas reservoirs, while considering extreme peak-shaving demands. This approach effectively narrows the constraint range. Subsequently, a collaborative optimization model with… More >

Zhihui Feng¹, Jun Zhang¹, Jun Lu¹, Zhongdan Zhang¹, Wangwang Bai¹, Long Ma¹, Haonan Lu², Jie Lin^2,*

Energy Engineering, Vol.122, No.4, pp. 1531-1560, 2025, DOI:10.32604/ee.2025.060795 - 31 March 2025

Abstract In the background of the low-carbon transformation of the energy structure, the problem of operational uncertainty caused by the high proportion of renewable energy sources and diverse loads in the integrated energy systems (IES) is becoming increasingly obvious. In this case, to promote the low-carbon operation of IES and renewable energy consumption, and to improve the IES anti-interference ability, this paper proposes an IES scheduling strategy that considers CCS-P2G and concentrating solar power (CSP) station. Firstly, CSP station, gas hydrogen doping mode and variable hydrogen doping ratio mode are applied to IES, and combined with… More >

Ramesh Kumar^1,2, Abdullah Bin Queyam³, Manish Kumar Singla^1,4,*, Mohamed Louzazni⁵, Mishra Dipak Kumar⁶

Energy Engineering, Vol.122, No.4, pp. 1373-1386, 2025, DOI:10.32604/ee.2025.058058 - 31 March 2025

Abstract Enhancing the efficiency of Rankine cycles is crucial for improving the performance of thermal power plants, as it directly impacts operational costs and emissions in light of energy transition goals. This study sets itself apart from existing research by applying a novel optimization technique to a basic ideal Rankine cycle, focusing on a specific power plant that has not been previously analyzed. Currently, this cycle operates at 41% efficiency and a steam quality of 76%, constrained by fixed operational parameters. The primary objectives are to increase thermal efficiency beyond 46% and raise steam quality above… More >

Qinglei Zhang, Bai Hu^*, Jiyun Qin, Jianguo Duan, Ying Zhou

CMC-Computers, Materials & Continua, Vol.83, No.1, pp. 1257-1273, 2025, DOI:10.32604/cmc.2025.059955 - 26 March 2025

Abstract Grasping is one of the most fundamental operations in modern robotics applications. While deep reinforcement learning (DRL) has demonstrated strong potential in robotics, there is too much emphasis on maximizing the cumulative reward in executing tasks, and the potential safety risks are often ignored. In this paper, an optimization method based on safe reinforcement learning (Safe RL) is proposed to address the robotic grasping problem under safety constraints. Specifically, considering the obstacle avoidance constraints of the system, the grasping problem of the manipulator is modeled as a Constrained Markov Decision Process (CMDP). The Lagrange multiplier… More >

Jiayu Chen¹, Yingchun Bai^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.29, No.3, pp. 1-2, 2024, DOI:10.32604/icces.2024.011393

Abstract Mega-casting techniques are widely used to manufacture large piece of thin-walled structures for vehicle body in Automotive industries, especially with the rapid growing electric vehicle market. Topology optimization is effective design method to reach higher mechanical performance yet lightweight potential for casting structures [1-3]. Most of existing works is focused on geometric-type casting constraints such as drawn angle, partion line, undercut, and enclose holes. However, the challenges in mega-casting arise from the complexities in the casting process such as filling and solidification, and the corresponding defects have larger influences on the structural performances [4-6]. Partial… More >

Fuju Zhou^*, Li Li, Tengfei Jia, Yongchang Yin, Aixiang Shi, Shengrong Xu

Energy Engineering, Vol.121, No.6, pp. 1697-1711, 2024, DOI:10.32604/ee.2024.047680 - 21 May 2024

Abstract When a line failure occurs in a power grid, a load transfer is implemented to reconfigure the network by changing the states of tie-switches and load demands. Computation speed is one of the major performance indicators in power grid load transfer, as a fast load transfer model can greatly reduce the economic loss of post-fault power grids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient. The tedious training process of the reinforcement learning model can be conducted offline, so the model shows satisfactory performance in real-time operation, More >