Advances in Engineering Software最新文献_第10页

Layout optimization design method for thermo-elastic thin-walled structures with lattices and stiffeners 带有加劲肋的热弹性薄壁结构布局优化设计方法

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-10-01 Epub Date: 2025-06-07 DOI: 10.1016/j.advengsoft.2025.103962

Yang Li , Tong Gao , Yongbin Huang , Longlong Song , Weihong Zhang

This work proposes a layout optimization design method for thermo-elastic thin-walled structures with lattices and stiffeners in the framework of multi-material topology optimization, in which both the steady-state temperature field and mechanical loads are considered. Firstly, taking into account the design requirements, suitable lattice unit cells are chosen and their equivalent mechanical properties are obtained by the homogenization method. Thus, the candidate lattice unit cells are represented as corresponding virtual homogeneous materials. Meanwhile, the stiffeners are modelled with solid material. Afterwards, a multi-material thermo-elastic structural optimization formulation is established and solved iteratively through gradient-driven optimization algorithms to obtain the optimized layouts of the lattices and stiffeners. In addition, the maximum size constraint and the overall volume constraint with a lower bound are introduced. The former ensures that the solid material takes the form of 'ribs' in the optimization results and the latter could meet the requirement that the design space is filled with lattice or solid material. Finally, numerical tests are conducted to demonstrate the detailed application process and validate the effectiveness of the proposed design method. This work provides an effective design tool for the application of additively manufactured lattice structures in thermo-elastic coupled load-bearing structures.

本文提出了一种在多材料拓扑优化框架下兼顾稳态温度场和机械载荷的格筋热弹性薄壁结构布局优化设计方法。首先，根据设计要求，选择合适的点阵单元，并采用均匀化方法获得其等效力学性能；因此，候选晶格单元被表示为相应的虚拟均质材料。同时，用固体材料对加强筋进行建模。然后，建立了多材料热弹性结构优化公式，并通过梯度驱动优化算法进行迭代求解，得到了优化的格和加强筋布局。此外，还引入了最大尺寸约束和带下界的总体体积约束。前者确保固体材料在优化结果中以“肋”的形式存在，后者可以满足设计空间以晶格或固体材料填充的要求。最后，通过数值试验验证了该方法的具体应用过程，验证了该设计方法的有效性。本工作为增材制造晶格结构在热弹性耦合承重结构中的应用提供了有效的设计工具。

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引用次数: 0

Probabilistic slope stability analysis based on the Hermite-logistic regression approach 基于Hermite-logistic回归方法的概率边坡稳定性分析

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-10-01 Epub Date: 2025-06-11 DOI: 10.1016/j.advengsoft.2025.103973

Yi Liang , Zhengpeng Jia , Qinglong Wu , Kefeng Xiao , Ran Yuan , Haizuo Zhou , Yi He

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 c-φ 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.

在边坡可靠度分析中，传统的基于代理模型的分析方法，如响应面法、Kriging法、神经网络法等，往往依赖于边坡的安全系数进行分析。然而，安全系数的计算需要使用强度折减法进行反复迭代，导致可靠性分析效率较低。针对这一挑战，本文提出了一种改进的边坡可靠度分析方法，以提高分析效率。该方法基于二元分类概念，考虑了土壤参数的空间变异性。采用karhunen - lo (K-L)展开对边坡土体进行离散化，生成随机场。将Hermite多项式与logistic回归方法相结合，建立了一个代理模型。利用FLAC3D中的固有程序进行收敛判定，在不降低土强度参数（使用原土强度参数）的情况下，对每个边坡进行稳定性分类（稳定或不稳定）。分类结果作为Hermite-logistic回归代理模型的响应值，建立了随机变量与边坡稳定性之间的隐式关系。通过不排水饱和粘土边坡和c-φ土边坡实例验证了该方法的有效性。研究结果表明，与传统的随机有限元计算相比，Hermite-logistic回归模型具有显著的计算效率，同时保持了较高的计算精度。具体而言，该方法在确保获得精确结果的同时，将计算成本降低了至少十倍。此外，还对边坡几何参数和空间变异性参数对边坡稳定性和可靠度的影响进行了敏感性分析。

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引用次数: 0

Optimizing foam padding of the advanced combat helmet to maximize protection of blast-induced brain injury and wearing comfort 优化先进战斗头盔的泡沫填充物，最大限度地保护爆炸引起的脑损伤和佩戴舒适性

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-10-01 Epub Date: 2025-06-23 DOI: 10.1016/j.advengsoft.2025.103980

Chaokai Zhang , Feng Zhu , Wenye He , Zhiqing Cheng , Songbai Ji

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.

先进战斗头盔（ACH）对于降低爆炸引起的创伤性脑损伤（bTBI）的风险至关重要。头盔泡沫垫与头部持续接触，提供机械支撑。它们对于头盔bTBI缓解效果和佩戴舒适性至关重要。在本研究中，我们参数化研究了泡沫垫厚度和相对密度对降低爆炸后颅内压峰值的意义。此外，我们通过量化由重力引起的ach -头皮压力分布均匀性（称为舒适度指数）来研究它们如何影响感知舒适度。模拟使用了三种特定的垫层厚度和随机相对密度，以及放置在头盔-头部复合物前部或侧面的三硝基甲苯（TNT）质量范围。来自ConWep模型的入射压力被用作爆炸加载的输入。采用数据驱动的方法分析了胼胝体ICP峰值与入射压力峰值之间的比值以及舒适度指数。基于用户偏好加权因子，采用多功能设计方法Pareto front来确定ICP降低和水头表面压力分布的最优参数集。最后，运用决策树方法对优化设计规则进行细化。对于同等权重的ICP减少和表面压力分布，垫厚度为10毫米，相对密度为7.7%。本研究证明了将Pareto front和决策树相结合用于ACH最优设计参数识别的有效性。

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引用次数: 0

An isogeometric approach to supersonic flutter analysis of lightweight-designed plates with graphene reinforcement 石墨烯配筋轻量化板的超音速颤振分析等几何方法

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-10-01 Epub Date: 2025-06-06 DOI: 10.1016/j.advengsoft.2025.103955

Nam V. Nguyen, Thoai N. Tran

In recent years, there has been an increasing emphasis on implementing high-performance, lightweight designs in a wide range of contemporary interdisciplinary applications. The primary objective of this paper, therefore, is to present a NURBS-based isogeometric approach for a comprehensive investigation into the supersonic flutter characteristics of graphene-reinforced functionally graded (FG) metal foam plates. The lightweight structures are designed using a combination of two porosity distributions and two graphene dispersion patterns, featuring both uniform and non-uniform configurations. The mathematical equations governing the dynamic behavior of the porous plates are derived using a computational approach based on generalized higher-order shear deformation theory (HSDT) within a NURBS-based isogeometric analysis (IGA). A first-order approximation of piston theory is employed to model the fluid–structure interaction by estimating the aerodynamic forces induced by high-speed airflow. The accuracy of the current approach is assessed and validated against the analytical approach and other existing benchmark results. Several extensive parametric investigations are subsequently conducted to fulfill the primary goal of this research: to clarify the influence of internal porosity and graphene nanofiller on the flutter boundaries and associated vibrational modes of lightweight-designed plate structures. The obtained results demonstrate that graphene-reinforced FG cellular plates possess exceptional properties, such as high stiffness and reduced weight, making them well-suited for advanced technological applications. Furthermore, the present findings offer valuable insights that can assist in the design and fabrication, with the goal of improving the robustness and efficacy of future practical engineering structures.

近年来，人们越来越重视在广泛的当代跨学科应用中实现高性能、轻量化设计。因此，本文的主要目标是提出一种基于nurbs的等几何方法来全面研究石墨烯增强功能梯度（FG）金属泡沫板的超音速颤振特性。轻质结构的设计结合了两种孔隙率分布和两种石墨烯分散模式，具有均匀和非均匀的配置。在基于nurbs的等高几何分析（IGA）中，使用基于广义高阶剪切变形理论（HSDT）的计算方法推导了控制多孔板动态行为的数学方程。采用一阶近似活塞理论，通过估计高速气流引起的气动力来模拟流固耦合。根据分析方法和其他现有基准结果评估和验证当前方法的准确性。随后进行了几项广泛的参数研究，以实现本研究的主要目标：阐明内部孔隙率和石墨烯纳米填料对轻量化板结构颤振边界和相关振动模式的影响。结果表明，石墨烯增强FG细胞板具有优异的性能，如高刚度和减轻重量，使其非常适合于先进的技术应用。此外，目前的研究结果提供了有价值的见解，可以帮助设计和制造，以提高未来实际工程结构的稳健性和有效性。

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引用次数: 0

An efficient multi-fidelity space-division assisted optimization approach for computationally expensive problems 一种高效的多保真度空间分割辅助优化方法

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-10-01 Epub Date: 2025-06-25 DOI: 10.1016/j.advengsoft.2025.103979

Chengshan Li , Junxiao Liu , Yuqin Ma , Xiaoyi An , Da Lyu , Yufan Cao

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.

针对计算量大的问题，提出了一种多保真度优化方法，旨在利用MF模型高效地找到全局最优解。首先，分别选取高保真度（HF）和低保真度（LF）样本进行计算。然后，根据高频和低频样本的响应将设计空间划分为四种类型：重叠子空间、高频有希望子空间、合并子空间和全局空间。这些定义的空间交替探索，以找到全局最优。为了进一步减少计算费用，引入了相关分析过程来确定在当前子空间中是使用HF模型还是LF模型作为目标函数。为了避免错过全局最优，在这些子空间中采用了局部开发和全局勘探策略。通过23个数学测试问题，将本文提出的多保真度空间分割辅助优化方法（MFSDO）与4种常用方法进行了比较，结果表明MFSDO在降低计算成本方面具有优势。此外，还将MFSDO应用于翼体混合水下滑翔机的结构优化。结果表明，在保证安全的前提下，结构质量显著降低，计算成本大大降低，验证了本文方法的有效性和工程适用性。

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引用次数: 0

Effect of frequency content of ground motion on seismic response of buildings with variable aspect ratio including soil-structure interaction 地震动频率含量对含土-结构相互作用变宽比建筑物地震反应的影响

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-10-01 Epub Date: 2025-06-30 DOI: 10.1016/j.advengsoft.2025.103981

Dilek Kaya , Tufan Cakir , Kasif Furkan Ozturk , Onur Araz

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.

土-结构相互作用（SSI）可能导致结构响应的减小、放大或可忽略不计的变化，这取决于激励性质和底土条件之间的关系。由于忽略SSI效应可能会在抗震设计中造成不确定性，因此在设计过程中考虑SSI效应至关重要。影响结构与地面相互作用动力性能的另一个重要因素是结构的动力特性。为了考虑这种影响，根据土耳其建筑地震规范（tbc -2018）对三栋分别为4层、8层和12层的建筑进行了分析。这些结构的纵横比分别为2、4和6，分别对应于深、普通和细长结构。本研究的主要目的是模拟这些关键参数对钢筋混凝土结构动力响应的综合影响。在时程分析中，考虑了按三种不同频率分量分类的六种地震动。利用ANSYS软件建立了SSI系统的三维有限元模型。通过三种不同的分析方法，证明了数值模型在SSI和固定基数情况下的可用性。位移、加速度和应力响应通过时间历史分析进行检验。结果表明，SSI是不可忽略的，忽略SSI是一种过度简化，不会导致总是保守的预测。此外，发现激励频率含量和结构长径比是地震反应的决定性参数。

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引用次数: 0

Hybrid material topology optimization of solid-lattice structures for natural frequency maximization 基于固有频率最大化的混合材料固体晶格结构拓扑优化

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-10-01 Epub Date: 2025-06-02 DOI: 10.1016/j.advengsoft.2025.103961

Yuhan Liu, Zhen Liu, Yedan Li, Wei-Zhi Luo, Liang Xia

This paper presents a topology optimization design approach for hybrid materials used to generate solid-lattice structures. Specifically, the approach aims to maximize the natural frequencies of hybrid structures by optimizing the topological distribution of solid and lattice materials, as well as the lattice relative density. For this purpose, a hybrid material interpolation model is developed. In this approach, the modal assurance criterion (MAC) is applied to optimize the target-order natural frequency accurately. Additionally, a hybrid structure post-processing framework based on the signed distance field (SDF) is proposed. This framework adaptively refines the lattice resolution at model boundaries, ensuring geometric integrity. Moreover, a circular geometry transition strategy is employed to improve structural connectivity, which significantly reduces model errors in non-transition regions. 2D and 3D numerical examples demonstrate the proposed method’s effectiveness in maximizing the natural frequency of hybrid structures. In particular, the dynamic performance of hybrid structures surpasses that of pure solid structures under multiple mass loading cases.

本文提出了一种用于生成固体晶格结构的杂化材料的拓扑优化设计方法。具体来说，该方法旨在通过优化固体和晶格材料的拓扑分布以及晶格相对密度来最大化混合结构的固有频率。为此，建立了一种混合材料插值模型。该方法采用模态保证准则（MAC）对目标阶固有频率进行精确优化。此外，提出了一种基于符号距离域（SDF）的混合结构后处理框架。该框架自适应细化模型边界的格分辨率，保证几何完整性。此外，采用圆形几何过渡策略提高了结构连通性，显著降低了非过渡区域的模型误差。二维和三维数值算例验证了该方法在最大化混合结构固有频率方面的有效性。特别是混合动力结构在多重质量荷载作用下的动力性能优于纯实体结构。

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引用次数: 0

Machine learning-based two-stage damage prediction method for RC slabs under blast loads 基于机器学习的两阶段爆炸荷载下RC板损伤预测方法

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-10-01 Epub Date: 2025-06-04 DOI: 10.1016/j.advengsoft.2025.103959

Chunfeng Zhao , Jian Su , Yufu Zhu , Xiaojie Li

Reinforced concrete (RC) slabs are extremely vulnerable to damage in explosions and terrorist attacks as the force members of building structures. It is necessary to evaluate and predict the damage of the RC slabs to improve the explosion protection of building structures. In this study, a two-stage damage prediction method for RC slabs under blast loads is developed using machine learning method. In the first stage, the parameters related to the RC slab and the explosion are used as input feature variables, and a machine learning algorithm is adopted to establish a displacement prediction model for the RC slab under explosion loading. In the second stage, the prediction of the maximum displacement of the RC slab under blast loads is carried out using the proposed model, and the damage of the RC slab is evaluated following the damage assessment criteria. Finally, the accuracy and reliability of the two-stage prediction method is validated by the present empirical methods. The results show that the two-stage prediction method under the damage assessment criterion of the support rotation has the best damage identification results with an accuracy of 93.1 %. Furthermore, the two-stage prediction method has better generalization performance with an accuracy of 90 % compared with the present empirical prediction methods.

钢筋混凝土板作为建筑物结构的受力构件，在爆炸和恐怖袭击中极易受到破坏。为了提高建筑结构的防爆性能，对钢筋混凝土板的损伤进行评估和预测是十分必要的。本文采用机器学习方法，提出了一种两阶段爆炸荷载作用下RC板损伤预测方法。第一阶段将RC板与爆炸相关参数作为输入特征变量，采用机器学习算法建立爆炸荷载作用下RC板位移预测模型。第二阶段，利用本文提出的模型预测爆炸荷载作用下RC板的最大位移，并根据损伤评估准则对RC板进行损伤评估。最后，通过本文的经验方法验证了两阶段预测方法的准确性和可靠性。结果表明，基于支架旋转损伤评估准则的两阶段预测方法损伤识别效果最好，准确率为93.1%。此外，与现有的经验预测方法相比，两阶段预测方法具有更好的泛化性能，准确率达到90%。

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引用次数: 0

Multi-objective optimisation of complex mechanisms using Moving Spheres: An application to suspension elasto-kinematics 基于运动球体的复杂机构多目标优化：在悬架弹性运动学中的应用

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-10-01 Epub Date: 2025-06-20 DOI: 10.1016/j.advengsoft.2025.103974

Lorenzo De Santanna, Massimiliano Gobbi, Riccardo Malacrida, Gianpiero Mastinu

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

k

-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.

本文提出了一种新的迭代方法，称为移动球体（MS），用于解决涉及三维机构的多目标设计优化问题。该方法适用于大多数设计变量属于三维欧几里德空间的问题。MS方法能够有效地探索设计空间并识别最优解所在的区域，从而使最优解具有清晰的空间表示。本文将质谱法应用于某汽车悬架系统的弹性运动学优化。在参考悬架的球面邻域内寻找悬架节点的最佳位置。这既保留了机构的运动兼容性，又便于通过参考悬架的迭代更新探索设计空间。采用严格的k-最优性度量，在帕累托最优集中引入层次排序，对最优设计方案进行排序。在悬架试验用例中，考虑相似的计算时间，将移动球法逼近的pareto最优集与参数空间调查和多目标优化排序遗传算法（KEMOGA）方法逼近的pareto最优集进行了比较。移动球体法产生了更精确的帕累托最优集近似值。

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引用次数: 0

A lightweight convolutional neural network-based model and system for defect detection and navigation on bridge road surface 基于轻量级卷积神经网络的桥梁路面缺陷检测与导航模型与系统

IF 4 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-10-01 Epub Date: 2025-06-07 DOI: 10.1016/j.advengsoft.2025.103972

Ronghua Fu , Yufeng Zhang , Drahomír Novák , Alfred Strauss , Maosen Cao

The Faster Region-based Convolutional Neural Network (Faster R-CNN) is widely used for detecting defects on road surface. However, its effectiveness in this task is limited by its large model size and slow detection speed. To address these challenges, two versions of the Faster R-CNN model—small and large—were developed. First, the models were structurally optimized by integrating inverted residual blocks, depthwise separable convolutions, and attention mechanisms to improve efficiency and performance. The large version also incorporated multi-scale feature extraction for enhanced detection capabilities. Second, model pruning was applied to further compress the networks. Extensive ablation experiments were conducted to investigate the relationship between the model's internal structure and its impact on crack detection accuracy and efficiency. The experimental results demonstrate that the proposed models outperform general CNN-based models in bridge surface defect detection, achieving superior detection speed while maintaining high accuracy. The large version exhibits better performance but at the cost of increased model complexity. Testing was conducted on a real-life bridge in Nanjing, China. Additionally, a software application, integrated with a laptop and a smartphone, was deployed to identify defects and map their locations on the bridge, streamlining the detection process. The source code of this software is freely available at https://github.com/DUYA686686/detection-software.git

基于更快区域的卷积神经网络（Faster R-CNN）被广泛应用于路面缺陷检测。然而，由于模型规模大，检测速度慢，限制了该方法在该任务中的有效性。为了应对这些挑战，我们开发了两个版本的Faster R-CNN模型——小型和大型。首先，通过整合倒立残差块、深度可分卷积和注意机制对模型进行结构优化，以提高效率和性能。大型版本还集成了多尺度特征提取，以增强检测能力。其次，采用模型剪枝进一步压缩网络；通过广泛的烧蚀实验来研究模型内部结构及其对裂纹检测精度和效率的影响。实验结果表明，该模型在桥梁表面缺陷检测方面优于一般基于cnn的模型，在保持较高精度的同时，检测速度更快。大版本表现出更好的性能，但代价是增加了模型的复杂性。测试是在中国南京一座真实的桥梁上进行的。此外，还部署了一个集成了笔记本电脑和智能手机的软件应用程序来识别缺陷，并绘制出它们在桥上的位置，简化了检测过程。该软件的源代码可在https://github.com/DUYA686686/detection-software.git免费获得

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引用次数: 0