Advances in Engineering Software最新文献_第2页

modOpt: A modular development environment and library for optimization algorithms modOpt：用于优化算法的模块化开发环境和库

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-12-08 DOI: 10.1016/j.advengsoft.2025.104084

Anugrah Jo Joshy, John T. Hwang

Applications of numerical optimization span a wide range of fields, from finance and economics to the natural sciences and engineering. Optimization techniques employed in each field are specialized to exploit the structure of the underlying problems. As optimization problems grow in scale and complexity, they uncover bottlenecks in existing optimization algorithms and necessitate further specialization of the algorithms. Such specialization requires expert knowledge of the underlying mathematical theory and the software implementation of current algorithms. However, currently available optimization libraries lack the modularity, transparency, and accessibility needed for customization and experimentation, as they often provide only monolithic implementations of algorithms. To overcome the challenges posed by this limitation in algorithm development and education, we present modOpt, an open-source Python framework designed to facilitate the construction, customization, and study of optimization algorithms. Its modular architecture enables students and researchers to tailor existing algorithms to new applications by only altering the relevant modules, eliminating the need to understand or reimplement an algorithm in its entirety. The framework is written entirely in Python and supports both novice and advanced users through clear documentation, built-in visualization, and fully transparent implementations of pedagogical algorithms. To facilitate testing and benchmarking of new algorithms, the framework features interfaces to modeling frameworks such as OpenMDAO and CSDL, interfaces to general-purpose optimization algorithms such as SNOPT and SLSQP, and an interface to the CUTEst test problem set. This level of interoperability—spanning 12 external algorithms, 10 pedagogical algorithms, 4 modeling tools, and a benchmark test set—is unique to modOpt and is not available in other optimization libraries. In this paper, we present the software architecture of modOpt, review its various features, discuss several educational and performance-oriented algorithms within modOpt, and present numerical studies illustrating its unique capabilities. modOpt is available as an open-source project on GitHub at https://github.com/lsdolab/modopt, with comprehensive documentation hosted at https://modopt.readthedocs.io/.

数值优化的应用跨越了广泛的领域，从金融和经济学到自然科学和工程。每个领域所采用的优化技术都是专门用于开发潜在问题的结构。随着优化问题在规模和复杂性上的增长，它们揭示了现有优化算法中的瓶颈，并需要进一步专业化算法。这种专业化要求对基础数学理论和当前算法的软件实现具有专业知识。然而，目前可用的优化库缺乏定制和实验所需的模块化、透明性和可访问性，因为它们通常只提供算法的整体实现。为了克服算法开发和教育中的这种限制所带来的挑战，我们提出了modOpt，一个开源Python框架，旨在促进优化算法的构建，定制和研究。它的模块化架构使学生和研究人员能够通过改变相关模块来定制现有算法以适应新的应用，从而消除了理解或重新实现整个算法的需要。该框架完全用Python编写，并通过清晰的文档、内置的可视化和教学算法的完全透明实现支持新手和高级用户。为了便于对新算法进行测试和基准测试，该框架提供了与建模框架（如OpenMDAO和CSDL）的接口、与通用优化算法（如SNOPT和SLSQP）的接口以及与CUTEst测试问题集的接口。这种级别的互操作性——跨越12个外部算法、10个教学算法、4个建模工具和一个基准测试集——是modOpt独有的，在其他优化库中是不可用的。在本文中，我们介绍了modOpt的软件架构，回顾了它的各种功能，讨论了modOpt中的几个教育和面向性能的算法，并提出了数值研究来说明其独特的功能。modOpt是GitHub上的一个开源项目，网址是https://github.com/lsdolab/modopt，全面的文档托管在https://modopt.readthedocs.io/。

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引用次数: 0

A geometric volume of fluid-based multiphase flow solver extension to the reacting flow solver, PeleLM 基于几何体积流体的多相流求解器对反应流求解器PeleLM的扩展

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-12-06 DOI: 10.1016/j.advengsoft.2025.104074

Hyoungwoo Kim , Robert Chiodi , Marc Day , Yong Jea Kim , Dong-hyuk Shin

A new algorithm is presented to simulate multiphase flows with surface tension in a pathway for spray combustion simulation. The algorithm combines capabilities from two open-source packages, including the interface reconstruction library (IRL), a library of computational geometry routines to enable the volume of fluid (VOF) method, and PeleLM, a solver for the reacting Navier-Stokes equations. Additionally, surface tension is implemented using the continuum surface force (CSF) model with an improved height function technique in the volume fraction field. Spurious errors in volume fraction arising from our combined strategy are corrected through a topology-based method that improves both numerical stability and accuracy. Multiple validation simulations are conducted, including (i) translations and rotations of Zalesak’s disk, (ii) a stationary circular droplet with surface tension, (iii) an oscillating elliptical droplet, and (iv) three-dimensional deformation of a spherical droplet. Results indicate that the combined scheme retains the favorable properties of each of the component algorithms.

提出了一种新的喷雾燃烧模拟路径中具有表面张力的多相流模拟算法。该算法结合了两个开源包的功能，包括接口重建库（IRL），一个支持流体体积（VOF）方法的计算几何例程库，以及PeleLM，一个反应Navier-Stokes方程的求解器。此外，使用连续表面力（CSF）模型和改进的体积分数场高度函数技术来实现表面张力。通过基于拓扑的方法修正了由我们的组合策略引起的体积分数的杂散误差，该方法提高了数值稳定性和精度。进行了多个验证模拟，包括(i) Zalesak圆盘的平移和旋转，（ii）具有表面张力的静止圆形液滴，（iii）振荡椭圆液滴，以及（iv）球形液滴的三维变形。结果表明，该组合方案保留了各组成算法的优点。

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引用次数: 0

Mb-RRT: A curvature-constrained path planning framework for cable-driven snake-arm manipulators in confined environments Mb-RRT：一个曲率约束的路径规划框架，用于受限环境下的电缆驱动蛇臂机械臂

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-12-05 DOI: 10.1016/j.advengsoft.2025.104081

Chang Liu, Detao Wan, Zhe Wang, Dean Hu

Robotic manipulators used in confined operational environments, such as next-generation nuclear facilities, must satisfy demanding requirements. These include remote operability, spatial adaptability, and resilience to environmental constraints. This paper presents a curvature-constrained path planning framework based on the Multi-branch Rapidly-Exploring Random Tree (Mb-RRT) algorithm, specifically designed for a cable-driven snake-arm manipulator tasked with inspection operations in restricted workspaces. The Mb-RRT algorithm integrates direction-aware nearest-node selection, curvature-compliant path extension, and a multi-path reuse mechanism enabled by a Path Pass Diagram (PP-Diagram) and Connection Relationship Matrix (CR-Matrix). These enhancements significantly improve search efficiency and path feasibility in cluttered environments with limited curvature freedom. Simulation studies indicate that under a 26° joint deflection constraint, feasible paths were successfully generated in 92.2 % of cases within 500 iterations. When the iteration limit was extended to 10,000, the success rate increased to 100 %. The proposed framework is further validated through experimental deployment, achieving terminal positioning errors below 2.02 mm. These results confirm the effectiveness and practical applicability of the Mb-RRT framework as a planning module for curvature-constrained motion in snake-arm manipulators operating under spatially restrictive conditions.

在诸如下一代核设施等受限操作环境中使用的机器人操作器必须满足苛刻的要求。这些包括远程操作性、空间适应性和对环境约束的弹性。本文提出了一种基于多分支快速探索随机树（Mb-RRT）算法的曲率约束路径规划框架，专门为在受限工作空间中执行检测任务的缆索驱动蛇臂机械臂设计。Mb-RRT算法集成了方向感知的最近节点选择、曲率兼容的路径扩展以及通过路径通道图（PP-Diagram）和连接关系矩阵（CR-Matrix）实现的多路径复用机制。这些改进显著提高了在曲率受限的杂乱环境下的搜索效率和路径可行性。仿真研究表明，在26°关节挠度约束下，500次迭代生成可行路径的成功率为92.2%。当迭代限制扩展到10,000次时，成功率增加到100%。通过实验部署进一步验证了该框架，实现了终端定位误差在2.02 mm以下。这些结果证实了Mb-RRT框架作为空间约束条件下蛇形臂机械臂曲率约束运动规划模块的有效性和实用性。

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引用次数: 0

Numerical study of explosive–soil contact angle effects on blast pressure and crater morphology with TNT and aluminized explosives 炸药-土接触角对TNT和镀铝炸药爆炸压力和爆坑形态影响的数值研究

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-12-05 DOI: 10.1016/j.advengsoft.2025.104085

Kyung Bo Lee , Tae Hee Lee , Yena Lee , Jung-Wuk Hong

Blast pressure propagation and crater morphology from surface detonations are governed by explosive type, geometry, soil properties, and the position of the explosive relative to the soil. In this study, multi-material arbitrary Lagrange–Eulerian (MMALE) simulations are conducted to investigate the effects of contact angle variations on blast pressure and crater morphology for TNT and Aluminized Enhanced Blast Explosive (AEBE). The discretized MMALE model is verified by comparing the results with experimental results, and the blast pressure and crater morphology are accurately predicted. Numerical simulations reveal that contact angle variations lead to nonlinear changes in blast pressure and crater morphology. AEBE produces consistently higher peak overpressure than TNT, and crater aspect ratio and volume are strongly influenced by contact angle. Polynomial regression models effectively characterize the nonlinear and systematic variations associated with contact angle changes. An effective methodology is established to evaluate the effects of variations in contact angle with both TNT and AEBE.

地表爆炸产生的爆炸压力传播和弹坑形态受炸药类型、几何形状、土壤性质以及炸药相对于土壤的位置的影响。本文采用多材料任意拉格朗日-欧拉（MMALE）模拟方法，研究了接触角变化对TNT和镀铝增强炸药（AEBE）爆炸压力和爆坑形态的影响。通过与实验结果的对比，验证了离散化MMALE模型的正确性，准确预测了爆炸压力和弹坑形态。数值模拟表明，接触角的变化会导致爆炸压力和弹坑形态的非线性变化。AEBE产生的峰值超压始终高于TNT，且弹坑长径比和体积受接触角的影响较大。多项式回归模型有效地表征了与接触角变化相关的非线性和系统变化。建立了一种有效的方法来评估TNT和AEBE对接触角变化的影响。

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引用次数: 0

Nonlinear dynamic behavior and fault diagnosis of rotor-bearing systems subjected to multi-source load unbalance in bulb-type turbine-generator units 多源负载不平衡下球泡式汽轮发电机组转子-轴承系统的非线性动态特性及故障诊断

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-12-03 DOI: 10.1016/j.advengsoft.2025.104068

Xudong Jiang , Taigui Bai , Peichao Du , Zhenyu Huang

Due to their compact structure and complex hydrodynamic environment, bulb-type turbine-generator units are highly susceptible to multi-source load unbalance rising from hydraulic, electromagnetic, and mechanical interactions, leading to nonlinear vibration behaviors in the rotor-bearing system and posing challenges to stable operation and fault diagnosis. To investigate such dynamics, a nonlinear rotor-bearing dynamic model is first developed based on the Jeffcott rotor theory, incorporating three typical sources of load unbalance: mass eccentricity, angular misalignment, and inadequate oil supply pressure. Nonlinear oil-film forces are modeled to reflect realistic hydrodynamic effects. A dedicated experimental platform is constructed with integrated modules for motor actuation, fault loading, and sensor-based data acquisition. Vibration signals in

X

and

Y

directions are collected under varying speeds and fault intensities. A comprehensive analysis using time-domain plots, frequency spectra, orbit diagrams and radar plots reveals distinct fault-specific features. Furthermore, 160 labeled samples across eight rotational speeds are collected, from which 16 time–frequency features are extracted to form a dataset. To enhance fault identification, a Hybrid CNN–Transformer diagnostic model is proposed for the first time in the context of hydropower units. The model integrates convolutional feature extraction with global temporal attention, achieving superior adaptability to varying operating states. Results demonstrate that the model achieves a high classification accuracy of 98.75% on the test set. Confusion matrices show clear decision boundaries, and the average AUC exceeds 0.995, indicating excellent discriminative power. Compared to conventional MLP and LSTM models, the proposed method outperforms in terms of accuracy, robustness, and convergence rate, highlighting its effectiveness and adaptability for fault diagnosis of nonlinear, multi-source load unbalance in bulb-type hydro-turbine units.

球型汽轮发电机组结构紧凑，水动力环境复杂，容易受到液压、电磁、机械等多源载荷不平衡的影响，导致转子-轴承系统出现非线性振动行为，给稳定运行和故障诊断带来挑战。为了研究这种动力学，首先基于Jeffcott转子理论建立了转子-轴承非线性动力学模型，该模型包含了三种典型的负载不平衡源：质量偏心、角不对中和供油压力不足。建立了非线性油膜力模型，以反映真实的水动力效应。构建了一个专用的实验平台，集成了电机驱动、故障加载和基于传感器的数据采集模块。在不同的速度和故障强度下采集X和Y方向的振动信号。利用时域图、频谱图、轨道图和雷达图进行综合分析，揭示了明显的故障特征。进一步，在8种转速下收集160个标记样本，从中提取16个时频特征形成数据集。为了提高故障识别能力，首次提出了一种基于CNN-Transformer的水电机组混合故障诊断模型。该模型将卷积特征提取与全局时间关注相结合，对不同的运行状态具有较好的适应性。结果表明，该模型在测试集上达到了98.75%的分类准确率。混淆矩阵具有清晰的决策边界，平均AUC超过0.995，具有较好的判别能力。与传统的MLP和LSTM模型相比，该方法在精度、鲁棒性和收敛速度等方面均有显著提高，突出了该方法在球型水轮机组非线性多源负载不平衡故障诊断中的有效性和适应性。

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引用次数: 0

Smooth geometry extraction from SIMP topology optimization: Signed distance function approach with volume preservation SIMP拓扑优化中的光滑几何形状提取：带体积保留的符号距离函数方法

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-11-25 DOI: 10.1016/j.advengsoft.2025.104071

Ondřej Ježek , Ján Kopačka , Martin Isoz , Dušan Gabriel , Pavel Maršálek , Martin Šotola , Radim Halama

This paper presents a novel post-processing methodology for extracting high-quality geometries from density-based topology optimization results. Current post-processing approaches often struggle to simultaneously achieve smooth boundaries, preserve volume fraction, and maintain topological features. We propose a robust method based on a signed distance function (SDF) that addresses these challenges through a two-stage process: first, an SDF representation of density isocontours is constructed, which is followed by geometry refinement using radial basis functions (RBFs). The method generates smooth boundary representations that appear to originate from much finer discretization, while maintaining the computational efficiency of coarse mesh optimization. Our approach can reduce maximum equivalent stress values compared to conventional methods. This reduction is achieved through continuous geometric transitions at boundaries. The resulting implicit boundary representation facilitates seamless export to standard manufacturing formats without intermediate reconstruction steps, providing a robust foundation for practical engineering applications where high-quality geometric representations are essential.

本文提出了一种从基于密度的拓扑优化结果中提取高质量几何图形的新型后处理方法。当前的后处理方法往往难以同时实现平滑边界、保持体积分数和保持拓扑特征。我们提出了一种基于有符号距离函数（SDF）的鲁棒方法，该方法通过两个阶段的过程来解决这些挑战：首先，构建密度等等值线的SDF表示，然后使用径向基函数（rbf）进行几何细化。该方法产生光滑的边界表示，似乎源于更精细的离散化，同时保持粗网格优化的计算效率。与传统方法相比，我们的方法可以降低最大等效应力值。这种减少是通过在边界处的连续几何转换来实现的。由此产生的隐式边界表示便于无缝导出到标准制造格式，而无需中间重建步骤，为高质量几何表示必不可少的实际工程应用提供了坚实的基础。

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引用次数: 0

Data-driven prediction for flexural strength of FRP bars reinforced concrete beams based on optimized machine learning and SHAP method 基于优化机器学习和SHAP方法的FRP筋混凝土梁抗弯强度数据驱动预测

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-11-25 DOI: 10.1016/j.advengsoft.2025.104067

Tianyong Jiang , Jun Tang , Chunjun Hu , Ke Huang , Xiang Tian , Lei Wang

Fiber-reinforced polymer (FRP) can substitute for steel bars to improve the durability problem of reinforced concrete (RC) beams attributed to corrosion. But A high-precision and interpretable prediction method for the flexural strength of FRP-RC beams has not yet been constructed. This study proposed a genetic algorithm optimized artificial neural network (GA-ANN) model to predict the flexural strength of FRP-RC beams. A database of 166 samples was established to train and validate the model. The input parameters include the FRP reinforcement area, FRP ultimate tensile strength, FRP type, elastic modulus of FRP, concrete compressive strength, beam width, and beam depth. The prediction accuracy and practicability of the GA-ANN model were assessed by comparison with other machine learning (ML) models and design guidelines. A parametric sensitivity analysis was performed based on the proposed model. Finally, the SHapley Additive exPlanation (SHAP) was introduced to investigate the intrinsic mechanisms and the parameter contribution of the ML prediction. The results revealed the GA-ANN model achieves superior prediction performance, with a coefficient of determination (R²) on the validation set of 0.992, which is 1.74% to 6.43% higher than that of other models. Moreover, the trends of flexural strength with the input parameters can be well captured, which is highly consistent with the design guidelines. Interpretability analysis shows that the beam depth and the FRP reinforcement area are the dominant factors affecting flexural strength. This study provides reliable support for the accurate prediction of flexural strength and effective reference for engineering applications.

纤维增强聚合物（FRP）可以代替钢筋来改善钢筋混凝土梁的腐蚀耐久性问题。但目前还没有一种高精度、可解释的FRP-RC梁抗弯强度预测方法。提出了一种遗传算法优化的人工神经网络（GA-ANN）模型来预测FRP-RC梁的抗弯强度。建立了包含166个样本的数据库，对模型进行训练和验证。输入参数包括FRP加固面积、FRP极限抗拉强度、FRP类型、FRP弹性模量、混凝土抗压强度、梁宽、梁深。通过与其他机器学习（ML）模型和设计指南的比较，评估了GA-ANN模型的预测精度和实用性。在此基础上进行了参数敏感性分析。最后，引入SHapley加性解释（SHAP）来研究机器学习预测的内在机制和参数贡献。结果表明，GA-ANN模型具有较好的预测性能，在验证集上的决定系数（R2）为0.992，比其他模型高1.74% ~ 6.43%。此外，可以很好地捕捉到抗折强度随输入参数的变化趋势，这与设计准则高度一致。可解释性分析表明，梁深和FRP加固面积是影响抗弯强度的主要因素。该研究为结构抗弯强度的准确预测提供了可靠的支撑，为工程应用提供了有效的参考。

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引用次数: 0

Topology optimization of fiber-reinforced composite structures considering fiber orientation and cross-sectional size 考虑纤维取向和截面尺寸的纤维增强复合材料结构拓扑优化

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-11-25 DOI: 10.1016/j.advengsoft.2025.104073

Pengfei Sun , Jiantao Bai , Ran Zhang , Fei Cheng , Xiaojiang Zhang , Wenjie Zuo

Fiber-reinforced composite structures (FRCs) are widely used in engineering. The design of the structural topology, together with fiber paths and cross-sectional size is important for enhancing their structural performance. Therefore, a topology optimization method is proposed that considers fiber orientation and cross-sectional size for FRCs. A bar-embedded model is employed to model the FRCs. The Solid Isotropic Material with Penalization method is applied to optimize the structural topology, whereas the Normal Distribution Fiber Optimization method is used to optimize the fiber orientation and cross-sectional size. The objective is to minimize compliance subject to prescribed matrix and fiber volume fractions. Numerical examples are provided to validate the effectiveness of the proposed method.

纤维增强复合材料结构在工程中有着广泛的应用。结构拓扑的设计、光纤路径和截面尺寸是提高其结构性能的重要因素。因此，提出了一种考虑纤维取向和纤维截面尺寸的纤维纤维结构拓扑优化方法。采用嵌条模型对FRCs进行建模。采用固体各向同性材料惩罚法对结构拓扑进行优化，采用正态分布纤维优化法对纤维取向和截面尺寸进行优化。目的是尽量减少依从性受到规定的基质和纤维体积分数。数值算例验证了该方法的有效性。

引用次数: 0

GeoWarp: An automatically differentiable and GPU-accelerated implicit MPM framework for geomechanics based on NVIDIA Warp GeoWarp：基于NVIDIA Warp的地质力学的自动可微分和gpu加速的隐式MPM框架

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-11-23 DOI: 10.1016/j.advengsoft.2025.104072

Yidong Zhao , Xuan Li , Chenfanfu Jiang , Jinhyun Choo

The material point method (MPM), a hybrid Lagrangian–Eulerian particle method, is increasingly used to simulate large-deformation and history-dependent behavior of geomaterials. While explicit time integration dominates current MPM implementations due to its algorithmic simplicity, such schemes are unsuitable for quasi-static and long-term processes typical in geomechanics. Implicit MPM formulations are free of these limitations but remain less adopted, largely due to the difficulty of computing the Jacobian matrix required for Newton-type solvers, especially when consistent tangent operators should be derived for complex constitutive models. In this paper, we introduce GeoWarp—an implicit MPM framework for geomechanics built on NVIDIA Warp—that exploits GPU parallelism and reverse-mode automatic differentiation to compute Jacobians without manual derivation. To enhance efficiency, we develop a sparse Jacobian construction algorithm that leverages the localized particle–grid interactions intrinsic to MPM. The framework is verified through forward and inverse examples in large-deformation elastoplasticity and coupled poromechanics. Results demonstrate that GeoWarp provides a robust, scalable, and extensible platform for differentiable implicit MPM simulation in computational geomechanics.

材料点法（MPM）是一种拉格朗日-欧拉混合粒子法，越来越多地用于模拟岩土材料的大变形和历史依赖行为。虽然显式时间积分由于其算法简单而主导了当前的MPM实现，但这种方案不适合地质力学中典型的准静态和长期过程。隐式MPM公式没有这些限制，但仍然很少被采用，这主要是由于计算牛顿型求解器所需的雅可比矩阵的困难，特别是当需要为复杂的本构模型导出一致的切线算子时。在本文中，我们介绍了geowarp——一个基于NVIDIA warp的隐式地质力学MPM框架，它利用GPU并行性和反向模式自动微分来计算雅可比矩阵而无需手动推导。为了提高效率，我们开发了一种稀疏雅可比构造算法，该算法利用了MPM固有的局部粒子网格相互作用。通过大变形弹塑性和耦合孔隙力学的正反算例对该框架进行了验证。结果表明，GeoWarp为计算地质力学中的可微隐式MPM模拟提供了一个鲁棒、可扩展和可扩展的平台。

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引用次数: 0

Damage control of CRTS Ⅲ track-bridge systems using multi-component multi-level seismic design under near-fault earthquakes 近断层地震下多分量多级抗震设计的CRTSⅢ轨桥系统损伤控制

IF 5.7 2区工程技术 Q2 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Advances in Engineering Software

Pub Date : 2025-11-21 DOI: 10.1016/j.advengsoft.2025.104070

Binqi Xiao , Biao Wei , Jun Chen , Ruimin Zhang , Mingyu Chen , Xianglin Zheng , Zhixing Yang

Near-fault earthquakes seriously endanger the structural safety and operational performance of high-speed railway track-bridge systems (HSRT-BS). To address this issue, this study proposes a multi-component multi-level seismic design (MMSD) method and develops a reduced-order model for parameter design. Using a CRTS Ⅲ track-continuous beam bridge as a case study, a finite element model is established based on the OpenSEES engineering seismic software to implement the MMSD and conduct numerical analyses. The seismic responses of key components in the MMSD system and the ordinary system are compared, while operational safety is evaluated using the velocity-related spectral intensity (VSI) index. Results indicate that the MMSD markedly reduces seismic responses of the track, girder, rail, bearings, and piers, showing stable behavior under earthquake, and lowers the VSI index by nearly 50 %, demonstrating its effectiveness and feasibility for HSRT-BS.

近断层地震严重危害高速铁路轨道-桥梁系统的结构安全和运行性能。针对这一问题，本文提出了一种多分量多级抗震设计方法，并建立了参数设计的降阶模型。以某CRTSⅢ轨道连续梁桥为例，基于OpenSEES工程地震软件建立有限元模型，实现MMSD并进行数值分析。比较了MMSD系统和普通系统中关键部件的地震反应，并利用速度相关谱强度（VSI）指数对运行安全性进行了评价。结果表明，MMSD可显著降低轨道、梁、轨、支座和桥墩的地震响应，在地震作用下表现稳定，VSI指数降低近50%，证明了该方法的有效性和可行性。

引用次数: 0