Engineering Computations

Wang, Yue; Yang, Yun-Bo; Xia, Yande

doi: 10.1108/ec-06-2024-0489pmid: N/A

We propose and analyze an Arrow–Hurwicz iterative finite element method for solving the stationary micropolar Navier–Stokes equations discretized by the mixed finite element method. Compared to the traditional iterative methods, the significant feature of this iterative method is that it does not need to solve any saddle-point system at each iteration, except for the determination of the initial functions.Design/methodology/approachArrow–Hurwicz iterative finite element method.FindingsUnder several reasonable conditions, it is proved that the solution solved by the proposed iterative method is uniformly bounded with respect to the mesh width and iteration numbers, and the method converges geometrically with a contraction number independent of the finite element mesh width. Finally, we test some numerical experiments to illustrate the effectiveness of the proposed algorithm.Originality/valueIt is proven that the solution solved by the proposed iterative method is uniformly bounded with respect to the mesh width and iteration numbers, and the method converges geometrically with a contraction number independent of the finite element mesh width. Finally, we test some numerical experiments to illustrate the effectiveness of the proposed algorithm.

Li, Xiaoke; Sun, Yuan; Li, Gaohui; Yin, Chunyang; Chen, Zhenzhong; Jiang, Zheng; Ma, Jun

doi: 10.1108/ec-02-2025-0149pmid: N/A

This study aims to address the inefficiency of conventional multidisciplinary design optimization (MDO) methods in handling the implicit relationship between structural parameters and performance responses, as well as the complex coupling relationships among multiple performance responses during intelligent large-scale equipment optimization.Design/methodology/approachAn improved collaborative optimization (CO) framework is developed through two key innovations. (1) An ensemble surrogate model combining radial basis function (RBF), Kriging and support vector regression (SVR) models is developed through linear weighting for enhanced approximation accuracy. (2) A modified CO algorithm incorporating dynamic penalty functions (ICO-DP) is proposed to effectively manage multiple coupling performance responses like mass minimization, fatigue life maximization and first-order modal frequency maximization. The methodology is validated using an earth pressure balance shield machine cutterhead as an engineering case study.FindingsThe optimization results show that the proposed ICO-DP method based on an ensemble surrogate model has obvious advantages over traditional methods, the mass is reduced by 3.2%, the first mode frequency is increased by 21.9% and the fatigue life is increased by 90%, which significantly improves the performance of the cutterhead.Originality/valueThis work makes three original contributions: (1) Ensemble surrogate model is applied to the design optimization of the cutterhead. (2) Integration of dynamic penalty functions with CO framework is conducted for coupled performance handling. (3) A complete methodological framework is built that bridges the gap between theoretical MDO research and practical large-scale equipment design applications.

Pham-Hong, Quan; Tran, Hung Viet; Nguyen Chi, Thanh; Bui Phuc, Loc; Mai-Duc, Anh

doi: 10.1108/ec-02-2025-0181pmid: N/A

The paper proposes a promising approach by integrating 1DCNN and BiGRU to enhance the detection and assessment of structural damage.Design/methodology/approachThis paper is organized into five main sections. Section 1 outlines the problem and highlights the innovative contributions of this paper. Section 2 introduces the theoretical background of the DL models, including 1DCNN, GRU, BiGRU, 1DCNN-GRU and the proposed 1DCNN-BiGRU hybrid. Section 3 details the dataset used in the model. Section 4 presents the results obtained from the proposed method. Lastly, the conclusion summarizes the key findings and outcomes of the study.FindingsThe proposed approach combines 1DCNN and BiGRU strengths. 1DCNN extracts key features from input data, while BiGRU learns and classifies sequential data bidirectionally, capturing vital temporal details effectively. Data augmentation uses random shifts, noise and reversal to enhance dataset diversity. A softmax layer calculates class probabilities, improving model confidence assessment per prediction. Validated on an experimental bridge, the method excels in detecting, analyzing and evaluating structural damage.Originality/valueThis paper is an original work authored by the authors and all rights are reserved. The content, including text, figures, tables and data, is the intellectual property of the authors unless otherwise cited. No part of this manuscript has been previously published or submitted elsewhere. The authors confirm that this work does not infringe upon any existing copyrights, and all sources have been appropriately acknowledged.

Yang, Luya; Zhang, Min; Gao, Yaxian; Song, Zhiwei

doi: 10.1108/ec-06-2025-0566pmid: N/A

With the rapid development of autonomous driving, vehicles can achieve real-time perception of the surrounding environment by installing cameras. Traffic signs provide rich environmental information, and their accurate recognition can enable autonomous vehicles to timely obtain road rules information. By combining image processing, computer vision technology and deep learning with the transportation field, intelligent and contactless detection of traffic signs can be achieved.Design/methodology/approachFirstly, to address the problems of poor quality and low visibility of some traffic sign images, a BF-IE-MSR enhancement algorithm is proposed. The contrast and information entropy of the enhanced image are higher than those of traditional algorithms and the image quality is significantly improved; Secondly, in response to the problems of large parameters and low accuracy in current models, a lightweight detection model GCS-YOLO11 is proposed. The GhostConv module is introduced to reduce the parameters and the CBAM module is introduced to optimize the detection accuracy of traffic sign targets.FindingsThe experiment showed that the mAP on the GTSRB dataset is 96.8%, with an overall improvement of 3.7%; the inference time is 10.5ms, with an overall reduction of 0.7ms. Various metrics such as mAP, Params and Inference time are superior to other common deep learning models. In addition, the TT100K dataset is also tested, with mAP increased by 1.6%, Params reduced by 0.46 M and Inference time reduced by 6.5ms, the accuracy and real-time performance improved. It can achieve intelligent and contactless detection of traffic signs, providing technical support for traffic signal control optimization and traffic flow adjustment.Originality/valueAt present, most research is based on open datasets for detection. However, in the GTSRB dataset, some images have blurry targets and poor visibility. When inputing into the detection model, it can affect the detection performance of the model. Therefore, before model detection, this paper first preprocesses the low-quality images in the dataset to enhance the features of the target to be detected in the images and then inputs them into the improved YOLO model for traffic sign recognition to improve the accuracy and efficiency of model detection.

Li, Tengyue; Cheng, Changzheng; Liao, Haifei; Hu, Zongjun

doi: 10.1108/ec-07-2025-0722pmid: N/A

The nearly singular integrals will occur when the interior points are closing to the boundary in the boundary element method. The conventional Gauss integral cannot effectively deal with the nearly singular integrals, which will lead to inaccurate numerical results for near-boundary interior points. Due to the determination of boundary unknown needing the information of interior points in the transient problem, the accurate numerical results for interior points are vital for the transient heat conduction boundary element method.Design/methodology/approachIn this paper, the dual reciprocity method is applied to transform the time-dependent domain integrals in transient heat conduction problems into pure boundary integrals by introducing the radial basis functions. The time-dependent terms are expressed in finite difference form using a set of coefficients that correspond with the radial basis functions. The nearly singular integrals are normalized on the local coordinate system. The analytical integral formulas for nearly singular integrals in boundary integral equations are derived through the Gaussian divergence theorem and integration by parts.FindingsBy introducing different coefficients that match the radial basis functions, the proposed method can be applied to analyze the transient heat conduction problems with heat sources or with variable heat conductivity coefficient. Three numerical examples show that the proposed method can evaluate the transient temperature field of interior points much closer to the boundary. The proposed method eliminates the need for domain discretization, which will reduce both the difficulty of element discretization and the computational cost.Originality/valueIn this paper, the dual reciprocity method is applied to transform the time-dependent domain integrals in transient heat conduction problems into pure boundary integrals by introducing the radial basis functions. The time-dependent terms are expressed in finite difference form using a set of coefficients that correspond with the radial basis functions. The nearly singular integrals are normalized on the local coordinate system. The analytical integral formulas for nearly singular integrals in boundary integral equations are derived through the Gaussian divergence theorem and integration by parts.

Tsai, Hsing-Chih; Shi, Jun-Yang; Ko, Cheng-Chun; Chen, You-Ren

doi: 10.1108/ec-06-2024-0513pmid: N/A

This paper introduces a novel algorithm, the Differential Evolution-based Backtracking Search Algorithm (DEBSA), designed to address the computational limitations of the Backtracking Search Algorithm (BSA) for complex constraint satisfaction problems.Design/methodology/approachDEBSA merges the core structure of BSA with three innovative mutation strategies derived from Differential Evolution (DE). These strategies focus on directing a random individual toward a historical individual and utilizing a random individual in conjunction with a perturbation vector as well as leveraging a historical best position with two perturbation vectors. Furthermore, DEBSA incorporates a unique crossover mechanism for combining solutions and a strategy selection approach to dynamically choose the most suitable mutation strategy during the search process.FindingsDEBSA’s performance is evaluated on constrained optimization problems and systems of nonlinear equations. The results demonstrate exceptional performance, particularly in terms of convergence speed, surpassing traditional benchmark evolutionary algorithms. DEBSA exhibits a high success rate in achieving globally optimal solutions.Originality/valueThe proposed DEBSA offers a potentially efficient solution for tackling general optimization challenges in engineering design and solving nonlinear equations in applied mathematics due to its enhanced performance and ability to find global optima.

Hussain, Mazhar; Tao, Wen-quan; He, Ya-Ling; Mohamed, Abdulmajeed

doi: 10.1108/ec-06-2025-0621pmid: N/A

The aim of this research is to promote modeling transient heat and volatile organic compound (VOC) diffusion in multilayered materials with different thermophysical characteristics and irregular interfaces. Although lattice Boltzmann method (LBM) has exhibited considerable promise for steady-state transport, efforts are still needed in accurately addressing flux continuity on interfaces. This research applies and contrasts two methods: the diffuse interface approach, dependent on a smoothness parameter, and the special interface treatment (SIT), which imposes directly flux and field continuity. This is to assess their efficiency, compare with analytical and existing results and illustrate practical use for energy efficiency and indoor air quality control.Design/methodology/approachThis study develops a lattice Boltzmann framework to model transient heat and VOC diffusion across multilayer materials with contrasting thermophysical properties and irregular boundaries. Two interface treatments were implemented: (1) the diffuse interface method, which smooths interfacial discontinuities using a tunable thickness parameter and (2) the SIT*, which directly enforces temperature/concentration and flux continuity without additional parameters. Numerical simulations were performed for porous and non-porous assemblies, Sandwich panels and room-scale models. Validation was conducted against analytical solutions and published data to ensure accuracy, robustness and practical applicability ([*]Mohamad et al., 2014).FindingsThis study demonstrates that while the diffuse interface LBM provides smoother transitions for heat diffusion at regular interfaces, its reliance on a tunable smoothness parameter can obscure sharp gradients and hinder calibration. In contrast, the SIT approach ensures strict continuity of temperature/concentration and fluxes without extra parameters, proving particularly effective for VOC diffusion in multilayer assemblies with abrupt property contrasts and sorption effects. Validation against analytical, numerical and literature results confirms its accuracy for layered materials, Sandwich panels and room-scale problems. Overall, the SIT-based framework offers a practical, reliable tool for optimizing multilayer systems in energy and indoor air applications.Originality/valueThis study is original in adapting and systematically comparing the diffuse interface method and the SIT within the LBM framework for transient heat and VOC diffusion in multilayer assemblies. While the diffuse interface approach smooths property jumps via a tunable parameter, SIT enforces strict flux and field continuity without extra calibration, offering a robust alternative for VOC transport where abrupt variations dominate. The originality lies in demonstrating SIT's practicality across layered walls, Sandwich panels and room-scale simulations, providing a validated, parameter-free tool with clear relevance to thermal management, energy efficiency and indoor air quality.

Liu, Ningning; Zhang, Zhiyi; Xu, Yang; Yao, Zaixing

doi: 10.1108/ec-04-2025-0328pmid: N/A

This study aims to elucidate the role of the main roof in highwall mining slope stability under localized coal pillar failure conditions. Prior research has not adequately addressed how large-scale pillar failures propagate instability through the mechanical linkage between the pillar support system and the slope sliding system. By analyzing fracture mechanisms and crack morphology of the main roof, this model seeks to clarify its control effect on highwall mining slope stability.Design/methodology/approachA CCCF (three edges clamped, one free) elastic foundation-supported thin rectangular plate model under trapezoidal load was established to analyze main roof fracturing in highwall mining. Using the derived governing equations and a second-order central difference method, the research examined key parameters influencing principal bending moments.FindingsPillar failure width and overburden depth increase all bending moments. Greater thickness and elastic modulus of the main roof amplify |M|z but reduce |M|c and |M|t, while higher foundation stiffness decreases |M|z and increases others. Three fracture sequences were identified, forming a horizontal “U-Y” pattern: U-shaped fractures develop around pillar failure zones, while Y-shaped fractures occur within failed pillars.Originality/valueThe mechanical model considers the CCCF boundary conditions, as well as the trapezoidal loads, and simplifies the edge of the coal pillar as Winkler elastic foundation to consider its mechanical effects. Validation through a case study demonstrated the model's accuracy in predicting fracture behavior aligned with actual mine pressure observations. The mechanical model and calculation method provide reliable theoretical support for assessing roof stability in similar engineering scenarios.

Jang, Bongsoo; Saeed, Umer; Din, Qamar

doi: 10.1108/ec-06-2025-0584pmid: N/A

The objectives of this study are threefold: (1) to introduce the tempered Chebyshev wavelet (TCW), (2) to propose the TCW method for solving linear tempered Caputo fractional diffusion-type equations and (3) to develop a fast tempered Chebyshev wavelet (fTCW) method for solving one- and two-dimensional nonlinear tempered Caputo fractional diffusion-type equations.Design/methodology/approachThe fTCW method integrates the TCW method with L2−1σ and sum-of-exponentials approximations of the tempered Caputo fractional time derivative. For this purpose, we introduce the TCW and derive its new operational matrices for tempered fractional integration by using the hypergeometric function. For nonlinear problems, we employ the interpolation technique in conjunction with operational matrices and fast approximations. The efficiency of the fTCW method is demonstrated through comparisons with the exact solution and the solution obtained using the TCW method.FindingsWe have derived the TCW operational matrix of tempered fractional integration and the TCW operational matrix of tempered fractional integration for boundary value problems. These matrices, in conjunction with the fast approximations of the tempered Caputo fractional time derivative and the interpolation technique, form the basis for the construction of the fTCW method. We present a detailed methodology for solving linear tempered Caputo fractional equations using the TCW method. Additionally, we provide a comprehensive methodology for solving both one- and two-dimensional nonlinear tempered Caputo fractional diffusion-type equations using the fTCW method. The convergence and error analysis of both methods are thoroughly discussed. Numerical simulations are presented to validate and illustrate the theoretical results. These simulations demonstrate the effectiveness and accuracy of the proposed methods by solving three test problems, including one linear and two nonlinear tempered Caputo fractional diffusion-type equations. The results are compared with analytical solutions or with each other to highlight the efficiency and precision of the TCW and fTCW methods.Originality/valueMany engineers and scientists can utilize the presented methods for solving their linear and nonlinear tempered Caputo fractional diffusion-type models.

Xu, Jiachen; Lu, Zhiwei; Jia, Beiyan; Lv, Yuanxing; Sun, Liang

doi: 10.1108/ec-06-2025-0601pmid: N/A

This paper aims to improve the quality of quadrilateral meshes by developing a method for cleaning and simplifying the topology structures generated by cross-field partitioning approaches, which significantly affect final mesh quality.Design/methodology/approachThe method extracts topology information from sub-regions obtained from streamline partitioning and establishes relationships among them. Slender quadrilateral blocks and short edges are first identified through intrinsic characteristics of the sub-regions. Virtual topology operations are applied to resolve identified problem features.FindingsThe method successfully identifies and resolves problematic features in block structures, including slender quadrilateral blocks, short edges, and limit cycles. Testing on various models demonstrates improved mesh quality, with results validated through comparison with automatically generated quad meshes using Ansys.Originality/valueThis research contributes a novel approach to topology cleaning in cross-field-based quadrilateral mesh generation, addressing a critical challenge in automated mesh generation.