Advances in Engineering Software最新文献_第8页

A domain evolution method to suppress the eigenfrequency and eigenmode errors caused by low-density elements in dynamic topology optimization 一种抑制动态拓扑优化中低密度元素引起的特征频率和特征模态误差的域演化方法

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

Advances in Engineering Software

Pub Date : 2025-11-15 Epub Date: 2025-08-20 DOI: 10.1016/j.advengsoft.2025.104011

Qiangwei Zhao , Chong Wang , Tongxing Zuo , Qianglong Wang , Zhenyu Liu

In dynamic topology optimization involving eigenfrequencies, the solution of the direct problem is expected to reasonably reflect the mechanical performance of the real structure. However, due to the presence of low-density elements in the fixed design domain, there are always some errors compared to the real structure obtained through post-processing. These errors include errors in eigenfrequencies and eigenmodes, which may adversely affect the optimization process. This issue becomes especially pronounced when optimizing higher-order eigenfrequencies, where the errors can lead to discontinuities in the solution space and hinder convergence. To overcome this issue, this paper proposes a domain evolution method (DEM). In this method, the fixed design domain is divided into three domains: the solid domain, the narrow-band, and the low-density domain. The direct problem analysis is solved within the computational domain, which consists of the solid domain and the narrow-band, while the low-density domain remains inactive. Several examples are used to validate the proposed method. Numerical results indicate that the errors primarily arise during the form-finding process and become more significant with increasing order of eigenfrequency. The proposed method effectively mitigates these errors, ensuring stable convergence of the optimization process. Furthermore, a comparative analysis between the proposed method and the traditional approach shows that, in higher-order problems, low-density elements are closely related to classical issues in dynamic topology optimization, including localized modes, repeated eigenfrequencies, and mode switching phenomena. This provides further insight into the intrinsic difficulties of high-order eigenfrequency topology optimization.

在涉及特征频率的动态拓扑优化中，期望直接问题的解能合理地反映实际结构的力学性能。然而，由于在固定的设计域中存在低密度元素，与后处理得到的真实结构相比，总是存在一定的误差。这些误差包括特征频率误差和特征模态误差，它们可能对优化过程产生不利影响。当优化高阶特征频率时，这个问题变得特别明显，其中的误差可能导致解空间中的不连续并阻碍收敛。为了克服这一问题，本文提出了一种领域演化方法（DEM）。该方法将固定设计域划分为三个域：固体域、窄带域和低密度域。直接问题分析在计算域内解决，计算域由实体域和窄带域组成，而低密度域则不活动。算例验证了该方法的有效性。数值结果表明，误差主要出现在寻形过程中，并随着特征频率阶数的增加而增大。该方法有效地减轻了这些误差，保证了优化过程的稳定收敛。此外，通过与传统方法的对比分析表明，在高阶问题中，低密度元素与动态拓扑优化中的经典问题密切相关，包括局部模态、重复特征频率和模式切换现象。这为高阶特征频率拓扑优化的内在困难提供了进一步的见解。

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引用次数: 0

Deep reinforcement learning-based control algorithm for flight kinematics of insect-scale flyers 基于深度强化学习的昆虫尺度飞行器飞行运动学控制算法

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

Advances in Engineering Software

Pub Date : 2025-11-15 Epub Date: 2025-08-27 DOI: 10.1016/j.advengsoft.2025.104014

Seungpyo Hong , Sejin Kim , Innyoung Kim , Donghyun You

An autonomous flight control algorithm based on deep reinforcement learning (DRL) is developed for insect-scale flyers with flexible wings in complex flow environments, addressing the challenges posed by highly unsteady and nonlinear aeroelastic dynamics. Unlike conventional model-based approaches, this study employs high-fidelity computational fluid–structural dynamics (CFD-CSD) simulations that fully resolve the governing equations of both the fluid and the flyer, providing physically consistent data for training the DRL agent. To mitigate the computational cost, a novel physics-guided data augmentation strategy is introduced, which synthetically expands the training dataset by replicating CFD-CSD data across diverse virtual flight scenarios while preserving the underlying physics. This approach enables the DRL agent to learn a robust control policy that generalizes across a broad range of aerodynamic conditions, demonstrating strong control performance even in complex and untrained flow environments. This work establishes a scalable framework for the autonomous control of flexible, bio-inspired flyers under realistic aerodynamic conditions, representing a significant step toward fully autonomous insect-scale flight.

针对具有柔性翼的昆虫级飞行器在复杂流动环境中的飞行控制问题，提出了一种基于深度强化学习（DRL）的自主飞行控制算法。与传统的基于模型的方法不同，该研究采用了高保真的计算流体-结构动力学（CFD-CSD）模拟，完全解决了流体和飞片的控制方程，为训练DRL代理提供了物理上一致的数据。为了降低计算成本，引入了一种新的物理引导数据增强策略，该策略通过复制不同虚拟飞行场景的CFD-CSD数据来综合扩展训练数据集，同时保留底层物理。这种方法使DRL智能体能够学习一种鲁棒的控制策略，该策略可以在广泛的空气动力学条件下进行推广，即使在复杂和未经训练的流动环境中也能表现出强大的控制性能。这项工作为在现实空气动力学条件下自主控制灵活的仿生飞行器建立了一个可扩展的框架，代表了迈向完全自主昆虫级飞行的重要一步。

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引用次数: 0

Prediction and analysis of temperature recovery after arch closure grouting of Baihetan Arch Dam 白鹤滩拱坝闭拱注浆后温度恢复预测与分析

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

Advances in Engineering Software

Pub Date : 2025-11-15 Epub Date: 2025-08-28 DOI: 10.1016/j.advengsoft.2025.104012

Jingyu Yan , Feng Wang , Yuhang Li , Chunbo Ma , Junchi Zhou , Hu Yu

Arch closure grouting is an essential procedure for attaining structural completion during the construction of a concrete arch dam. After the closure, due to the continuous heat emission from cement hydration, the internal temperature of concrete rises rapidly, which affects stress distribution and structural stability. In order to accurately predict the temperature evolution of concrete pouring blocks after arch closure, this paper conducted a comparative study using neural networks and finite element methods. First, a hybrid model, CNN-BiLSTM, was constructed. This model integrates a Convolutional Neural Network (CNN) and a Bidirectional Long Short-Term Memory (BiLSTM). The Weighted Mean of Vectors algorithm (INFO) was then introduced to optimize the model parameters. The temperature variation trend of concrete pouring blocks after arch closure was predicted using this approach. Simultaneously, considering the factors such as external temperature, cooling water, adiabatic temperature rise and concrete age, a three-dimensional finite element model of concrete pouring blocks was established to simulate the temperature field distribution of concrete. The comparison results indicate that both methods can achieve the prediction accuracy required by the project (with an error of less than 2 °C). Among them, the finite element simulation performs better in terms of stability (with a difference of less than 1 °C from the measured value). At the same time, the INFO-CNN-BiLSTM model exhibits significant temperature fluctuations during certain periods and demonstrates insufficient generalization ability. However, it offers the advantage of high computational efficiency.

在混凝土拱坝施工中，闭拱灌浆是保证结构完工的重要工序。闭合后，由于水泥水化持续放热，混凝土内部温度迅速升高，影响应力分布和结构稳定性。为了准确预测混凝土浇筑块合拱后的温度演变，本文采用神经网络和有限元方法进行了对比研究。首先，构建了CNN-BiLSTM混合模型。该模型集成了卷积神经网络（CNN）和双向长短期记忆（BiLSTM）。然后引入向量加权平均算法（INFO）对模型参数进行优化。利用该方法预测了混凝土浇筑块合拱后的温度变化趋势。同时，考虑外部温度、冷却水、绝热温升和混凝土龄期等因素，建立混凝土浇筑块三维有限元模型，模拟混凝土温度场分布。对比结果表明，两种方法均能达到工程要求的预测精度（误差小于2°C）。其中，有限元模拟在稳定性方面表现较好（与实测值相差小于1℃）。同时，INFO-CNN-BiLSTM模型在特定时期温度波动较大，泛化能力不足。然而，它具有计算效率高的优点。

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引用次数: 0

IGA_RDTOP: A compact MATLAB framework for reaction-diffusion-based topology optimization using isogeometric analysis IGA_RDTOP：一个紧凑的MATLAB框架，用于使用等几何分析的基于反应扩散的拓扑优化

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

Advances in Engineering Software

Pub Date : 2025-11-15 Epub Date: 2025-08-05 DOI: 10.1016/j.advengsoft.2025.104001

He Li , Peng Wei , Jianhu Shen , Xuyu Zhang , Sihan Ruan , Shiwei Zhou

Isogeometric analysis offers significant advantages in precise geometric representation, higher-order continuity, seamless integration with CAD systems, and improved accuracy for complex geometries in structural topology optimization. However, the complexity of its implementation and the rigorous coding requirements present notable challenges for researchers and students. To tackle this issue, we have developed a concise MATLAB code consisting of just 198 lines that incorporates isogeometric methods into 2D reaction-diffusion-based structural optimization. Furthermore, we introduce a streamlined 3D framework for constructing NURBS-based geometries, performing matrix operations, managing boundary conditions, handling initializations, and visualizing structures. Numerical experiments reveal robust convergence within 30 iterations, surpassing the efficiency of existing public codes. The open-source implementations in this study significantly lower the barrier to entry for isogeometric topology optimization, offering a powerful computational tool and a valuable educational resource.

等几何分析在精确的几何表示、高阶连续性、与CAD系统的无缝集成以及在结构拓扑优化中提高复杂几何形状的精度方面具有显著的优势。然而，其实现的复杂性和严格的编码要求对研究人员和学生提出了显着的挑战。为了解决这个问题，我们开发了一个简洁的MATLAB代码，该代码仅由198行组成，将等几何方法集成到基于二维反应扩散的结构优化中。此外，我们引入了一个流线型的3D框架，用于构建基于nurbs的几何图形，执行矩阵操作，管理边界条件，处理初始化和可视化结构。数值实验表明，该算法在30次迭代内具有较强的收敛性，优于现有的公共编码。本研究中的开源实现大大降低了等几何拓扑优化的进入门槛，提供了强大的计算工具和宝贵的教育资源。

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引用次数: 0

Dynamic analysis of prestressed laminated stepped spherical-cylindrical shells 预应力层合阶梯球圆柱壳动力分析

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

Advances in Engineering Software

Pub Date : 2025-11-15 Epub Date: 2025-08-23 DOI: 10.1016/j.advengsoft.2025.104018

Tianchen Huang , Kunpeng Zhu , Qingshan Wang , Rui Zhong

A dynamic analysis model for the laminated spherical-cylindrical shell structures under prestress is established to investigate its vibration characteristics. Based on the first-order shear deformation theory, the constitutive equations of the structural system are derived. The displacement and rotational components of the shell segments are expanded using a combination of Jacobi polynomials and Fourier series. To handle the complexities of boundary conditions and interfacial continuity between substructures, virtual spring stiffness, treated as penalty parameters, is introduced, and the dynamic characteristics of the structure are solved using the Ritz method. The reliability and accuracy of the proposed method are verified through comparisons with results from existing literature and simulations data of finite element method (FEM). Additionally, prestress is applied through continuously distributed surface loads. The study focused on examining the effects of key factors, including prestress magnitude, structural dimensions, and boundary conditions, on the free and forced vibration characteristics of the stepped shell system. This investigation aimed to elucidate the intrinsic relationship between parameter variations and dynamic responses. The computational results can provide safety guidance for the preliminary design of composite shells under prestressed conditions in engineering applications.

建立了预应力作用下层合球圆柱壳结构的动力分析模型，研究了层合球圆柱壳结构的振动特性。基于一阶剪切变形理论，推导了结构体系的本构方程。利用雅可比多项式和傅立叶级数的组合展开了壳段的位移和转动分量。为了处理边界条件的复杂性和子结构之间的界面连续性，引入了虚拟弹簧刚度作为惩罚参数，并采用里兹法求解结构的动力特性。通过与已有文献结果和有限元模拟数据的比较，验证了所提方法的可靠性和准确性。此外，预应力是通过连续分布的表面荷载施加的。研究的重点是检查关键因素，包括预应力大小，结构尺寸和边界条件，对阶梯壳系统的自由和强制振动特性的影响。本研究旨在阐明参数变化与动力响应之间的内在关系。计算结果可为工程应用中预应力条件下复合材料壳的初步设计提供安全指导。

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引用次数: 0

Complex profile optimization of marine diesel engine piston pin bore using hybrid GA-BP neural network and NSGA-II algorithm 基于GA-BP神经网络和NSGA-II算法的船用柴油机活塞销孔复杂轮廓优化

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

Advances in Engineering Software

Pub Date : 2025-11-15 Epub Date: 2025-08-26 DOI: 10.1016/j.advengsoft.2025.104015

Guoxi Jing , Qiqiang Tong , Yafei Fu , Libin Zhao , Yi Han , Chao Liu

To address deformation mismatch and stress concentration in the pin holes of a steel-topped aluminum-skirted combined piston under service conditions, this study proposes a surface optimization methodology integrating axial and circumferential bore profiles. By constructing a genetic algorithm-optimized backpropagation neural network surrogate model combined with the NSGA-II multi-objective optimization algorithm and CRITIC weighting decision mechanism, this approach achieves multi-parameter collaborative optimization for the pin hole's intricate geometric configuration. Results demonstrate that compared to the original design, the optimized complex surface reduces peak contact pressure by 66.7 %, decreases equivalent stress by 52.0 %, and lowers equivalent stress at bolt counterbores by 44.1 %. Relative to axial profile-only optimization, the contact pressure is further reduced by 12.4 %. The proposed method effectively resolves stress inhomogeneity induced by elliptical deformation, with finite element simulations verifying that axial-circumferential collaborative optimization significantly enhances load distribution uniformity and fatigue resistance. This work provides a systematic algorithmic approach for high-reliability piston design, advancing the application of intelligent optimization techniques in engine component engineering.

为了解决钢顶铝裙边组合活塞在使用条件下销孔变形失配和应力集中问题，提出了一种轴向和周向孔型相结合的表面优化方法。该方法通过构建遗传算法优化的反向传播神经网络代理模型，结合NSGA-II多目标优化算法和CRITIC加权决策机制，实现了销孔复杂几何构型的多参数协同优化。结果表明：与原设计相比，优化后的复合表面峰值接触压力降低了66.7%，等效应力降低了52.0%，螺栓顶孔等效应力降低了44.1%。与仅轴向型面优化相比，接触压力进一步降低12.4%。该方法有效地解决了椭圆变形引起的应力不均匀性，并通过有限元仿真验证了轴向-周向协同优化显著提高了载荷分布均匀性和抗疲劳性。为高可靠性活塞设计提供了系统的算法方法，促进了智能优化技术在发动机零部件工程中的应用。

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引用次数: 0

A stochastic linear neural network-based differential evolution algorithm for optimizing reluctance actuator 基于随机线性神经网络的磁阻执行器优化差分进化算法

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

Advances in Engineering Software

Pub Date : 2025-11-01 Epub Date: 2025-07-15 DOI: 10.1016/j.advengsoft.2025.103983

Yunlang Xu , Datong Pan , Longbin Jiang , Haibo Zhou

Reluctance actuators encounter significant challenges in active gravity compensation due to nonlinear effects including dynamic stiffness, leakage flux, and fringing flux, which cause unstable thrust output during operation. This study focuses on suppressing thrust fluctuations in open-loop reluctance actuator gravity compensation systems through design parameter optimization. We first establish a parametric optimization model based on equivalent magnetic circuit principles to characterize nonlinear thrust dynamics. To address limitations in conventional optimization approaches, we develop a differential evolution algorithm enhanced by a stochastic linear neural network (DE-SLNN). This hybrid method combines conventional linear neural networks (CLNN) with a stochastic dynamic opposite learning mechanism (SDOLM) to strengthen DE’s search capability. Comprehensive validation using CEC 2014 benchmark confirms DE-SLNN’s accelerated convergence speed and superior search performance. Application to reluctance actuator optimization demonstrates DE-SLNN’s ability to maintain full-stroke thrust output with a small deviation of less than 2.69% for stable gravity compensation, as confirmed by thrust distribution analysis. Comparative validation with finite element analysis (FEA) reveals thrust error control within 0.16%, verifying the optimization model’s precision. Experimental results demonstrate the framework’s effectiveness in mitigating nonlinearities and achieving stable thrust output within the actuator’s operational stroke.

由于动刚度、泄漏磁通和边缘磁通等非线性影响，磁阻执行器在运行过程中推力输出不稳定，因此在主动重力补偿中遇到了很大的挑战。通过设计参数优化，研究了开环磁阻作动器重力补偿系统中推力波动的抑制问题。首先建立了基于等效磁路原理的参数优化模型来表征非线性推力动力学。为了解决传统优化方法的局限性，我们开发了一种由随机线性神经网络（DE-SLNN）增强的微分进化算法。该方法将传统线性神经网络（CLNN）与随机动态反向学习机制（SDOLM）相结合，增强了神经网络的搜索能力。使用CEC 2014基准的综合验证证实了DE-SLNN的加速收敛速度和优越的搜索性能。在磁阻执行器优化中的应用表明，DE-SLNN能够保持全行程推力输出偏差小于2.69%，实现稳定的重力补偿，推力分布分析证实了这一点。与有限元分析（FEA）对比验证表明，推力误差控制在0.16%以内，验证了优化模型的精度。实验结果表明，该框架在减轻非线性和实现执行器工作行程内稳定的推力输出方面是有效的。

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引用次数: 0

Integrated software platform for the structural health control of historical constructions and numerical model calibration (HH-Structures) 历史建筑结构健康控制与数值模型标定集成软件平台（HH-Structures）

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

Advances in Engineering Software

Pub Date : 2025-11-01 Epub Date: 2025-07-11 DOI: 10.1016/j.advengsoft.2025.103994

Y. Cruz, B. Conde, M. Cabaleiro, B. Riveiro

Currently, BIM systems applied to new building construction are highly developed, standardised and widely implemented. However, this situation contrasts with the existing difficulties in their application to the field of built heritage, where important limitations persist. Among the main shortcomings is the lack of commercial or end-user tools to efficiently structure the information needed for the management and assessment of structural health in historic bridges. In this context, it is essential to enable robust bi-directional communication between 3D models generated in Building Information Modelling (BIM) environments and structural analysis software based on the Finite Element Method (FEM), thus promoting interoperability between platforms. Furthermore, to reduce the impact of uncertainties inherent in the modelling of in-service structures, it is essential to complement numerical models with experimental data and to apply advanced calibration methodologies. In response to these challenges, HH-Structures, a comprehensive platform for structural health monitoring of historic bridges, is presented. This platform combines non-destructive techniques with automated numerical model calibration processes, and enables the interoperable exchange of information between BIM environments and FEM analysis software, in order to provide rigorous support for structural analysis of heritage constructions.

目前，BIM系统在新建建筑施工中的应用已经高度发达、标准化和广泛实施。然而，这种情况与它们在建筑遗产领域的应用存在的困难形成了鲜明对比，在建筑遗产领域仍然存在重要的局限性。主要缺点之一是缺乏商业或最终用户工具来有效地组织管理和评估历史桥梁结构健康所需的信息。在这种情况下，在建筑信息建模（BIM）环境中生成的3D模型与基于有限元法（FEM）的结构分析软件之间实现强大的双向通信至关重要，从而促进平台之间的互操作性。此外，为了减少在役结构建模中固有的不确定性的影响，有必要用实验数据补充数值模型并应用先进的校准方法。为了应对这些挑战，HH-Structures，一个用于历史桥梁结构健康监测的综合平台，被提出。该平台将非破坏性技术与自动化数值模型校准过程相结合，实现BIM环境与FEM分析软件之间的信息互操作交换，为遗产建筑结构分析提供严格的支持。

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引用次数: 0

Numerical investigation on fretting wear in steel wires by introducing system stiffness and dissipated friction energy 引入系统刚度和耗散摩擦能的钢丝微动磨损数值研究

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

Advances in Engineering Software

Pub Date : 2025-11-01 Epub Date: 2025-07-30 DOI: 10.1016/j.advengsoft.2025.103999

Zhen Hu , Kai Liang , Enyuan Wang , Xiaofei Liu , Fuyin Jia

In the mining hoisting system, the reliability of wire ropes has a significant influence on the safety of the entire system. Subjected to coupled alternating stresses and small cyclic motions, fretting wear occurs in the internal steel ropes, leading to fatigue damage and reduced service life. Studying fretting behaviour through experiments is economically costly and cumbersome. This study numerically investigated the effects of system tangential stiffness (Ks), Crossing Angle (CA), and contact load (P) on fretting contact and wear behaviours of steel wires. Firstly, the fretting wear model for contact wires was established based on Archard’s wear model, and the accuracy of the model was compared with the published literature. Then, the fretting characteristics, such as wear morphology, relative slip amplitude (δ_a), and hysteresis loop, were investigated, and the action mechanism on wear depth was analysed. Finally, a more streamlined approach was proposed to predict wear depth by using dissipated friction energy. The results show that with an increase in the number of cycles, the relative slip amplitude gradually decreases, and non-Coulomb friction behaviour intensifies. The wear depth is influenced by the crossing angle and system stiffness mainly through the contact pressure and relative slip amplitude. Specifically, larger crossing angles and system stiffness result in more severe wear. An increase in contact load lead to a competition between contact pressure and relative slip, resulting in the initially increasing and then decreasing of wear depth. The effective dissipated friction energy, for the first time, was employed in wear prediction of steel wires. Compared to Archard's model, the prediction accuracy of the proposed model improves with the increasing system stiffness and the decreasing contact load. The proposed method offers a practical tool for wear prediction of steel wires, greatly enhancing the efficiency of wear calculations.

在矿山提升系统中，钢丝绳的可靠性对整个系统的安全有着重要的影响。在交变应力和小周期运动耦合作用下，钢索内部发生微动磨损，导致疲劳损伤，降低使用寿命。通过实验研究微动行为在经济上既昂贵又繁琐。本文研究了系统切向刚度（Ks）、交叉角（CA）和接触载荷(P)对钢丝微动接触和磨损行为的影响。首先，基于Archard磨损模型建立了接触导线微动磨损模型，并与已有文献进行了精度比较；研究了微动磨损形态、相对滑移幅值（δa）和磁滞回线等微动特性，分析了微动对磨损深度的作用机理。最后，提出了一种利用耗散摩擦能预测磨损深度的简化方法。结果表明：随着循环次数的增加，相对滑移幅值逐渐减小，非库仑摩擦行为加剧；磨损深度主要通过接触压力和相对滑移幅值受交叉角和系统刚度的影响。具体来说，较大的交叉角和系统刚度会导致更严重的磨损。接触载荷的增大导致接触压力和相对滑移之间的竞争，导致磨损深度先增大后减小。首次将有效耗散摩擦能用于钢丝的磨损预测。与Archard模型相比，该模型的预测精度随着系统刚度的增大和接触载荷的减小而提高。该方法为钢丝的磨损预测提供了实用工具，大大提高了磨损计算的效率。

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引用次数: 0

Proposed methodology for determining the optimal preload of rolling bearings 提出了确定滚动轴承最佳预紧力的方法

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

Advances in Engineering Software

Pub Date : 2025-11-01 Epub Date: 2025-08-05 DOI: 10.1016/j.advengsoft.2025.104000

Slavomir Hrcek , Robert Kohar , Frantisek Brumercik , Daniel Kozarik , Jan Steininger , Witold Glowacz , Zhixiong Li

Rolling bearings are key components in various mechanical systems, where their proper preload ensures optimal operational performance, enhances bearing life, and minimises wear. Inadequate preload adjustment or improper clearance settings in bearings can lead to increased wear and premature failure, adversely affecting the overall reliability and efficiency of machinery. This study aims to develop a methodology for determining the optimal preload of rolling bearings, tailored to the load conditions and duty cycles of a selected structural node - in this case, the gearbox of a railway vehicle's drive unit. The proposed methodology considers the effects of preload on contact pressure, fatigue life, and the dynamic behaviour of bearings, drawing upon insights from previous studies and experimental findings. By implementing this methodology, the reliability and efficiency of systems in various applications, including high-speed machinery, automotive components, and wind turbines, can be significantly improved.

滚动轴承是各种机械系统中的关键部件，其适当的预紧力可确保最佳的操作性能，提高轴承寿命，并最大限度地减少磨损。预紧调整不足或轴承间隙设置不当会导致磨损增加和过早失效，对机械的整体可靠性和效率产生不利影响。本研究旨在开发一种方法来确定滚动轴承的最佳预紧力，根据所选结构节点的负载条件和占空比进行定制-在这种情况下，是铁路车辆驱动单元的齿轮箱。所提出的方法考虑了预载荷对接触压力、疲劳寿命和轴承动态行为的影响，借鉴了以往研究和实验结果的见解。通过实施这种方法，系统在各种应用中的可靠性和效率，包括高速机械，汽车部件和风力涡轮机，可以显着提高。

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引用次数: 0