Advances in Engineering Software最新文献

{"title":"Effect of frequency content of ground motion on seismic response of buildings with variable aspect ratio including soil-structure interaction","authors":"Dilek Kaya ,&nbsp;Tufan Cakir ,&nbsp;Kasif Furkan Ozturk ,&nbsp;Onur Araz","doi":"10.1016/j.advengsoft.2025.103981","DOIUrl":"10.1016/j.advengsoft.2025.103981","url":null,"abstract":"<div><div>Soil-structure interaction (SSI) may lead to reduction, amplification or negligible change in structural responses depending on the relationship between the nature of excitations and subsoil conditions. Since neglecting SSI effects may cause uncertainties in seismic design, it is crucial to consider them during the design process. Another important factor affecting the dynamic behavior of structures interacting with the ground is the dynamic properties of the structures. To consider this effect, three buildings with 4, 8, and 12 stories designed in accordance with the Turkish Building Earthquake Code (TBEC-2018) are analyzed. The aspect ratios of these structures are 2, 4, and 6, corresponding to squat, ordinary, and slender structures, respectively. The primary objective of this study is to simulate the combined effects of these key parameters on the dynamic response of reinforced concrete structures. In the time history analyses, six ground motions classified by three different frequency contents are considered. 3D finite element models of SSI systems are established using ANSYS software. The usability of the numerical models is demonstrated for both SSI and fixed-base cases through three different analytical approaches. The displacement, acceleration, and stress responses are examined through time history analyses. The results indicate that the SSI is not negligible and neglecting the SSI is an oversimplification that does not lead to always-conservative predictions. Moreover, both the frequency content of the excitation and the structural aspect ratio are found to be decisive parameters in seismic response.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"208 ","pages":"Article 103981"},"PeriodicalIF":4.0,"publicationDate":"2025-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144514019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Bilinear-inverse-mapper: Analytical solution and algorithm for inverse mapping of bilinear interpolation of quadrilaterals","authors":"Indrajeet Sahu","doi":"10.1016/j.advengsoft.2025.103975","DOIUrl":"10.1016/j.advengsoft.2025.103975","url":null,"abstract":"<div><div>The challenge of finding parametric coordinates of bilinear interpolation of a point with respect to a quadrilateral in 2D or 3D frequently arises as a subproblem in various applications, e.g. finite element methods, computational geometry, and computer graphics. The accuracy and efficiency of inverse mapping in such cases are critical, as the accumulation of errors can significantly affect the quality of the overall solution to the broader problem. This mapping is nonlinear and typically solved with Newton’s iterative method, which is not only prone to convergence issues but also incurs high computational cost. This paper presents an analytical solution to this inverse mapping, along with a comprehensive geometric analysis covering all possible quadrilateral configurations. It describes the invertibility of all points and extends the discussion to 3D and concave quadrilaterals. The proposed algorithm is robust, free from failure due to convergence issues or oscillations in iterative methods, and achieves approximately <span><math><mrow><mn>2</mn><mo>.</mo><mn>4</mn><mo>×</mo></mrow></math></span> higher computational speed compared to Newton’s method for quadrilaterals with non-parallel opposite edges. This enables an efficient calculation of shape functions or interpolation functions at all invertible spatial points. The high-accuracy, high-speed computational solution will be particularly advantageous in applications involving high spatial or temporal discretisation (i.e. fine mesh and small timesteps) where iterative methods will be computationally expensive. The analytical solution based algorithm is available as an open-source library at <span><span>https://github.com/sahu-indrajeet/Bilinear-Inverse-Mapper</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"208 ","pages":"Article 103975"},"PeriodicalIF":4.0,"publicationDate":"2025-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144481081","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An efficient multi-fidelity space-division assisted optimization approach for computationally expensive problems","authors":"Chengshan Li ,&nbsp;Junxiao Liu ,&nbsp;Yuqin Ma ,&nbsp;Xiaoyi An ,&nbsp;Da Lyu ,&nbsp;Yufan Cao","doi":"10.1016/j.advengsoft.2025.103979","DOIUrl":"10.1016/j.advengsoft.2025.103979","url":null,"abstract":"<div><div>This paper presents a multi-fidelity optimization approach for computationally expensive problems, aiming to efficiently find the global optimum by utilizing MF models. Firstly, high-fidelity (HF) and low-fidelity (LF) samples are selected and calculated, respectively. Subsequently, the design space is categorized into four types based on the responses of the HF and LF samples: overlapped subspace, HF promising subspace, merged subspace, and global space. These defined spaces are explored alternately to find the global optimum. To further reduce computational expenses, a correlation analysis process is introduced to determine whether the HF or LF model should be used as the objective function in the present subspace. To avoid missing the global optima, both local exploitation and global exploration strategies are employed in these subspaces. The proposed method named multi-fidelity space-division assisted optimization (MFSDO) is compared with four popular methods using twenty-three mathematical test problems, results demonstrate that MFSDO offers advantages in reducing computational costs. Additionally, MFSDO is applied to optimize the structure of a blended-wing-body underwater glider. Results indicate that the structure mass is significantly reduced with much less computational cost while ensuring safety, which verifies the efficiency and engineering applicability of our proposed method.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"208 ","pages":"Article 103979"},"PeriodicalIF":4.0,"publicationDate":"2025-06-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144471300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Optimizing foam padding of the advanced combat helmet to maximize protection of blast-induced brain injury and wearing comfort","authors":"Chaokai Zhang ,&nbsp;Feng Zhu ,&nbsp;Wenye He ,&nbsp;Zhiqing Cheng ,&nbsp;Songbai Ji","doi":"10.1016/j.advengsoft.2025.103980","DOIUrl":"10.1016/j.advengsoft.2025.103980","url":null,"abstract":"<div><div>The Advanced combat helmet (ACH) is critical for mitigating the risk of blast-induced traumatic brain injury (bTBI). Helmet foam pads are in continuous contact with the head to provide mechanical support. They are essential for helmet bTBI mitigation effectiveness and wearing comfort. In this study, we parametrically investigate the significance of foam pad thickness and relative density on reducing the peak intracranial pressure (ICP) from blast. In addition, we study how they influence the perceived comfort, by quantifying the distribution uniformity of ACH-to-scalp pressure resulting from gravity, referred to as the Comfort Index. Three specific pad thicknesses and random relative densities coupled with a range of trinitrotoluene (TNT) masses placed to the front or side of the helmet-head complex were used for simulation. The incidence pressures from the ConWep model were used as input for blast loading. The ratios between peak ICP in the corpus callosum and the peak incident pressure as well as the comfort indices were analyzed using a data-driven approach. A multi-functional design method, Pareto front, was used to identify sets of optimal parameters based on user preferred weighting factors for ICP reduction and head surface pressure distribution. Finally, a decision tree was applied to refine the rules for optimal designs. For an equal weighting on ICP reduction and surface pressure distribution, a pad thickness of 10 mm and relative density of 7.7 % were identified. This study demonstrates the effectiveness of combining Pareto front and decision trees for the identification of optimal design parameters for the ACH.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"208 ","pages":"Article 103980"},"PeriodicalIF":4.0,"publicationDate":"2025-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144365765","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-objective optimisation of complex mechanisms using Moving Spheres: An application to suspension elasto-kinematics","authors":"Lorenzo De Santanna,&nbsp;Massimiliano Gobbi,&nbsp;Riccardo Malacrida,&nbsp;Gianpiero Mastinu","doi":"10.1016/j.advengsoft.2025.103974","DOIUrl":"10.1016/j.advengsoft.2025.103974","url":null,"abstract":"<div><div>This paper presents a new iterative method, called Moving Spheres (MS), for solving multi-objective design optimisation problems involving three-dimensional mechanisms. The method is suited to problems in which most of the design variables belong to the three-dimensional Euclidean space. MS method is able to explore efficiently the design space and identifies the regions where the optimal solutions are located, resulting in a clear spatial representation of optimal solutions. In this paper, MS method is applied to the elasto-kinematic optimisation of an automotive suspension system. The optimal locations of suspension joints are sought within spherical neighbourhoods of a reference suspension. This preserves the kinematic compatibility of the mechanism and facilitates the exploration of the design space through iterative updates of the reference suspension. The rigorous <span><math><mi>k</mi></math></span>-optimality metric, which introduces a hierarchical sorting in the Pareto-optimal set, is employed to rank optimal design solutions. In the suspension test case, the Pareto-optimal set of approximated through Moving Spheres method is compared with the Pareto-optimal sets resulting from Parameter Space Investigation and multi-objective optimisation Genetic Algorithm with sorting (KEMOGA) methods, considering similar computational time. Moving Spheres method yields a more accurate approximation of the Pareto-optimal set.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"208 ","pages":"Article 103974"},"PeriodicalIF":4.0,"publicationDate":"2025-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144329967","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning based optimal design of superelastic friction pendulum for controlling underground blast-induced vibration of building","authors":"Mohammad Yasir Mohammad Hasan Shaikh,&nbsp;Sourav Gur","doi":"10.1016/j.advengsoft.2025.103978","DOIUrl":"10.1016/j.advengsoft.2025.103978","url":null,"abstract":"<div><div>This study shows the machine learning (ML) based optimal design and response controllability of superelastic shape memory alloy (SMA) integrated friction pendulum (SMA-FP) isolator under the blast induced ground motion (BIGM), and compared with the FP isolator. An elastic steel shear building isolated with the FP or SMA-FP system is analysed through nonlinear time-history analysis (NLTHA). Design of base isolators (BIs) are obtained through optimizing two conflicting objectives, i.e. top floor peak acceleration (TFPA) and peak isolator displacement (PID). A multi-objective optimization (MOO) algorithm is used to estimate the optimal combination of friction coefficient and SMA wire strength. Comparison of the pareto optimal front clearly reveals a better trade-off between two objective functions for SMA-FP BI than FP BI. Robustness of optimal design and control effectiveness is studied through extensive parametric studies, for various parameters of isolator, building, and BIGM. Study results reveal that, SMA-FP can substantially reduce the TFPA (up to 30 %) in conjunction with the PID and residual isolator displacement (RID), reduction up to 42 % and 60 %, respectively, than FP BI. Finally, employing different ML based regression methods (multilinear, ridge, lasso, elastic-net regression), predictive models have been proposed for optimal design and optimum responses of structure and isolator.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"208 ","pages":"Article 103978"},"PeriodicalIF":4.0,"publicationDate":"2025-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144312746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"An improved YOLOv10-based lightweight multi-scale feature fusion model for road defect detection and its applications","authors":"Jianxi Ou ,&nbsp;Jianqin Zhang ,&nbsp;Haoyu Li ,&nbsp;Bin Duan","doi":"10.1016/j.advengsoft.2025.103976","DOIUrl":"10.1016/j.advengsoft.2025.103976","url":null,"abstract":"<div><div>Intelligent road damage detection is critical for ensuring traffic safety and extending the lifespan of roads. However, existing methods struggle to balance high accuracy and real-time performance in complex detection scenarios and resource-constrained environments. To address this issue, this study proposes a lightweight multi-scale feature fusion model based on an improved YOLOv10—GAS-YOLO. The model utilizes a novel lightweight architecture (GSF-ST) designed through a combination of feature generation, asymmetric convolution, and grouped channel shuffling optimization strategies, significantly reducing computational complexity and parameter count while enhancing both global and local feature representation. To improve multi-scale damage detection performance, GAS-YOLO incorporates an improved bidirectional feature pyramid network (BiFPN) and Swin Transformer module. A resolution halving and channel doubling strategy enhances the detection ability of small targets. Moreover, the WiOU loss function further optimizes bounding box regression accuracy, mitigating errors caused by sample imbalance. Channel pruning techniques are applied to achieve secondary lightweight compression of the model, resulting in significant resource savings. Through comparative experiments and ablation analysis with several advanced damage detection models, this study demonstrates a significant performance improvement of GAS-YOLO. Experimental results show that GAS-YOLO exhibits outstanding performance in multi-scale damage detection tasks, with 5.6 M parameters, 8.4GFLOPs of computational complexity, and a model size of only 5.8 MB. Compared to baseline models, detection accuracy improves by 10.8 %, computational complexity is reduced by 2.57 times, and parameter count is reduced by 1.29 times, with an average detection accuracy of 86.5 % and a single image processing time of 6.1 ms. Validation on both public datasets and self-constructed datasets further proves its real-time processing capability while maintaining high accuracy. The GAS-YOLO model proposed in this study not only provides a practical solution for road damage detection in resource-constrained environments but also offers new insights for intelligent management of intelligent transportation and urban infrastructure, with broad application prospects.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"208 ","pages":"Article 103976"},"PeriodicalIF":4.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144270709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced numerical modeling for nonlinear responses of sandwich multiphase composite plates with viscoelastic damping core","authors":"Ho-Nam Vu ,&nbsp;Duy-Khuong Ly ,&nbsp;Umut Topal ,&nbsp;Tan Nguyen ,&nbsp;T. Nguyen-Thoi","doi":"10.1016/j.advengsoft.2025.103958","DOIUrl":"10.1016/j.advengsoft.2025.103958","url":null,"abstract":"<div><div>This study introduces an advanced numerical model for the nonlinear dynamic analysis of sandwich multiphase composite plates composed of carbon nanotubes (CNT), carbon fibers, and epoxy, featuring a viscoelastic core modeled using the Golla–Hughes–McTavish (GHM) method. The proposed framework uniquely combines the Cell-Based Smoothed Discrete Shear Gap Method (CS-DSG3) with the sinusoidal–zigzag shear deformation theory, pioneering their integration to improve layerwise modeling and viscoelastic damping analysis. The sinusoidal–zigzag theory effectively captures the continuous in-plane displacement distributions, yielding superior predictions of the layered structure’s mechanical response compared to classical theories. By incorporating the von Kármán displacement–strain relationship, the model effectively captures the passive damped dynamic behavior of viscoelastic core plate under large deformations. The Newmark time integration scheme and Picard’s methods are employed to efficiently solve the resulting nonlinear equations of motion at each time step. Validation against benchmark studies demonstrates the model’s accuracy and reliability in capturing the complex dynamic responses of laminated systems. A comprehensive parametric investigation further explores the impact of material properties, including the volume fractions and configurations of CNTs and carbon fibers, on the nonlinear dynamic behavior. These advancements position the model as a computationally efficient and high-fidelity tool for analyzing the nonlinear dynamics of complex laminated composite structures.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"208 ","pages":"Article 103958"},"PeriodicalIF":4.0,"publicationDate":"2025-06-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144270708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Probabilistic slope stability analysis based on the Hermite-logistic regression approach","authors":"Yi Liang ,&nbsp;Zhengpeng Jia ,&nbsp;Qinglong Wu ,&nbsp;Kefeng Xiao ,&nbsp;Ran Yuan ,&nbsp;Haizuo Zhou ,&nbsp;Yi He","doi":"10.1016/j.advengsoft.2025.103973","DOIUrl":"10.1016/j.advengsoft.2025.103973","url":null,"abstract":"<div><div>In slope reliability analysis, conventional surrogate model-based analysis methods, such as response surface method, Kriging method, and neural networks method, often rely on the safety factor of slopes for analysis. However, the calculation of safety factors requires repeated iterations using strength reduction, leading to low efficiency in reliability analysis. Addressing this challenge, this manuscript proposes an improved slope reliability analysis method to improve analysis efficiency. This method, which considers the spatial variability of soil parameters, is based on the principles of binary classification concept. It employs the Karhunen-Loève (K-L) expansion to discretize the soil of the slope and generate a random field. By combining Hermite polynomials with logistic regression approach, a surrogate model is established. Using the intrinsic program in FLAC^3D for convergency determination, the stability classification (stable or unstable) for each slope is carried out without reducing the soil strength parameters (using original soil strength parameters). The classification results serve as response values for the Hermite-logistic regression surrogate model, establishing an implicit relationship between random variables and slope stability. The effectiveness of this Hermite-logistic regression method is verified through examples of undrained saturated clay slopes and <em>c</em>-<em>φ</em> soil slopes. The findings indicate that the Hermite-logistic regression model demonstrates remarkable computational efficiency when compared to conventional random finite element calculations, all while maintaining high computational accuracy. Specifically, the proposed method reduces the computational cost by at least a factor of ten while ensuring the attainment of precise results. In addition, a sensitivity analysis is performed to investigate the influence of slope geometric parameters and spatial variability parameters on slope stability and reliability.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"208 ","pages":"Article 103973"},"PeriodicalIF":4.0,"publicationDate":"2025-06-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144253653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Metaheuristic algorithms-optimized machine learning models for FRP-concrete interfacial bond strength prediction","authors":"Peng Ge ,&nbsp;Ou Yang ,&nbsp;Jia He ,&nbsp;Zhiyu Liu ,&nbsp;Hao Chen","doi":"10.1016/j.advengsoft.2025.103971","DOIUrl":"10.1016/j.advengsoft.2025.103971","url":null,"abstract":"<div><div>Globally, the technique of reinforcing concrete structures with bonded fiber-reinforced polymers (FRP) has become widely adopted. The integrity of the interface between concrete and FRP significantly influences the behavior of the reinforced structure. Consequently, precise prediction of the bond strength at the concrete and FRP interface is crucial for the logical design and assessment of structures that are repaired and reinforced using FRP. This paper utilizes two emerging metaheuristic algorithms, the Slime Mould Algorithm (SMA) and the Dung Beetle Optimization Algorithm (DBO), to improve the performance of machine learning (ML) techniques, including KNN, SVR, GBDT, and XGBoost. Optimizing the ML models with metaheuristic algorithms significantly enhanced the prediction accuracy compared to the non-optimized models. The SMA-GBDT performed better than other ML models, achieving an <em>R</em>² of 0.9492, an MAE of 1.5294, an MSE of 6.4159, an RMSE of 2.5329, and a MAPE of 8.6916, based on the testing dataset. Specifically, the SMA-GBDT model exhibited improvements of 5.83%, 39.04%, 50.75%, 29.82%, and 43.84% in <em>R</em>², MAE, MSE, RMSE, and MAPE, respectively, compared to the non-optimized GBDT. The predictions made by the SMA-GBDT model were higher precision than those provided by the current design codes and existing models.</div></div>","PeriodicalId":50866,"journal":{"name":"Advances in Engineering Software","volume":"208 ","pages":"Article 103971"},"PeriodicalIF":4.0,"publicationDate":"2025-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144229745","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}