Advances in Engineering Software最新文献_第4页

Domain-embedded deep learning frameworks for topology optimization: Enhancing structural performance under data scarce environments 面向拓扑优化的领域嵌入式深度学习框架：增强数据稀缺环境下的结构性能

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

Advances in Engineering Software

Pub Date : 2025-11-08 DOI: 10.1016/j.advengsoft.2025.104064

Geonwoo Lee , Mingyu Lee , Ikjin Lee

Recently, the rapid advancement of deep learning technology has led to the development of numerous topology optimization approaches, significantly reducing computational costs. However, conventional deep learning-based methods inherently suffer from a chronic limitation. They require large-scale data to extract features from the data itself. In particular, in the worst-case scenario where the data is insufficient, these methods may fail to capture the physical characteristics of the structure accurately, potentially leading to physically meaningless and unrealistic results. To solve this problem, this paper proposes an enhanced deep learning model suitable for topology optimization. The main novelty of this study is embedding the feature of topology optimization into a deep learning model. To effectively embed the topology domain, the proposed method introduces three key strategies. Firstly, topology convolutional neural network (CNN) filter layers are incorporated into the neural network model. A CNN is a specialized deep learning architecture designed for grid-structured data such as images, and the topology CNN filter layers are specifically designed to enhance structural connectivity by considering the influence of neighboring elements. Secondly, the pixel-based loss function is augmented with physics-informed loss functions that encapsulate the physical knowledge of topology optimization. Thirdly, a modified output layer is added to prevent zero values in the structure, thereby enhancing numerical stability. Numerical experiments demonstrate that the proposed deep learning approach successfully overcomes the limitations of conventional deep learning methods in data-scarce environments. Furthermore, the results confirm that the proposed method produces designs comparable to the traditional SIMP method.

近年来，深度学习技术的快速发展导致了许多拓扑优化方法的发展，大大降低了计算成本。然而，传统的基于深度学习的方法固有地受到长期限制。它们需要大规模的数据来从数据本身中提取特征。特别是，在数据不足的最坏情况下，这些方法可能无法准确捕获结构的物理特性，可能导致物理上毫无意义和不切实际的结果。为了解决这一问题，本文提出了一种适用于拓扑优化的增强型深度学习模型。本研究的主要新颖之处在于将拓扑优化的特征嵌入到深度学习模型中。为了有效地嵌入拓扑域，该方法引入了三个关键策略。首先，在神经网络模型中加入拓扑卷积神经网络（CNN）滤波层；CNN是一种专门为图像等网格结构数据设计的深度学习架构，拓扑CNN滤波器层是专门设计的，通过考虑相邻元素的影响来增强结构连通性。其次，将基于像素的损失函数扩展为包含拓扑优化物理知识的物理通知损失函数。第三，增加修正输出层，防止结构出现零值，提高数值稳定性。数值实验表明，所提出的深度学习方法成功地克服了传统深度学习方法在数据稀缺环境中的局限性。此外，结果证实了该方法产生的设计可与传统的SIMP方法相媲美。

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引用次数: 0

Rigid-flexible coupling dynamic modeling and adaptive intelligent composite control for a novel redundantly actuated flexible parallel robot 一种新型冗余驱动柔性并联机器人的刚柔耦合动力学建模与自适应智能复合控制

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

Advances in Engineering Software

Pub Date : 2025-11-06 DOI: 10.1016/j.advengsoft.2025.104048

Dong Liang , Manjun Cui , Shiyou Li , Boyan Chang , Zhen Wang , Junpeng Zhang

Due to complex nonlinear closed-loop constraints and structural flexibility, the dynamic modeling and control issue on flexible parallel robots is much more challenging compared to serial counterparts. Oriented to the demand of the high-end manufacturing field, this paper proposes a novel lightweight redundant parallel robot with cross layout of guide rail. Based on assumed mode discretization and Kane’s formulation, a general rigid-flexible coupling dynamic model of arbitrary branch incorporating n-order modes is derived. Leveraging modular ideology, the complete rigid-flexible coupling dynamic model of the system is established combining with nonlinear constraint equations, which is solved by the Runge-Kutta algorithm, modal truncation and forward dynamics methodology. The dynamic response comparison results between the redundant parallel robot and the non-redundant parallel robot reveal that the redundant actuation can suppress the elastic vibration. The rigid-flexible coupling dynamic model is then validated by a physical simulation model developed through the MATLAB/Simscape® platform using the finite segment approach. The electromechanical coupling dynamic model is further formulated by integrating the rigid-flexible coupling dynamic model with the permanent magnet synchronous motor and smart material. An adaptive intelligent composite control strategy is proposed to achieve trajectory tracking and vibration suppression. The comparison results with the other three control strategies demonstrate that the adaptive intelligent composite control strategy has superior control performance, exhibiting potential application prospects.

由于复杂的非线性闭环约束和结构的灵活性，柔性并联机器人的动力学建模和控制问题比串行机器人更具挑战性。针对高端制造领域的需求，提出了一种新型导轨交叉布置的轻型冗余并联机器人。基于假设模态离散化和Kane公式，推导了包含n阶模态的任意分支刚柔耦合动力学一般模型。利用模块化思想，结合非线性约束方程，建立了系统的完整刚柔耦合动力学模型，采用龙格-库塔算法、模态截断和正演动力学方法进行求解。将冗余并联机器人与非冗余并联机器人的动态响应进行对比，结果表明冗余驱动可以抑制弹性振动。然后通过MATLAB/Simscape®平台使用有限段方法开发的物理仿真模型验证刚柔耦合动态模型。将刚柔耦合动力学模型与永磁同步电机和智能材料相结合，进一步建立机电耦合动力学模型。提出了一种自适应智能复合控制策略来实现轨迹跟踪和振动抑制。与其他三种控制策略的对比结果表明，自适应智能复合控制策略具有优越的控制性能，具有潜在的应用前景。

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引用次数: 0

A physics-informed machine learning computational framework for solving Mohr-Coulomb plasticity in geomechanics 一个物理信息的机器学习计算框架，用于求解地质力学中的莫尔-库仑塑性

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

Advances in Engineering Software

Pub Date : 2025-11-06 DOI: 10.1016/j.advengsoft.2025.104061

Ran Yuan , Xi-Long Huang , Yong Fang , Kiyonobu Kasama , Yin Cheng , Yi He

This paper develops a Physics-Informed Neural Network (PINN) framework for solving Mohr-Coulomb (M-C) plasticity in geomechanics, and the plane strain layered perforated soils subjected to surface compression pressure are employed to validate the PINN solutions, through comparisons with parallel numerical experiments conducted in OptumG2. To incorporate the physical information for the elasto-plastic problem into neural networks (NNs), two modified multi-objective loss functions, respectively known as the collocation loss function and the Least Squares Weighted Residual (LSWR) loss function, are constructed through coarse data-driven information and physical constrains, consisting of M-C constitutive relations, associated/non-associated flow rules, Karush-Kuhn-Tucker (KKT) conditions, equilibrium conditions, and boundary conditions. The total loss function incorporates terms obtained from Finite Element Method (FEM) solutions for a range of elastoplastic field variables, i.e., stress and displacement, to inform the physical knowledge fitting. By employing several independently operating and densely connected artificial neural networks (ANNs), the PINN framework achieves the M-C plastic solutions by minimizing the designed total loss functions. Furthermore, influences of sample size, sampling strategy, and the loss function, on performances of the proposed PINN framework, are investigated for parametric analysis. In all cases, the PINN predictions were compared with finite element solutions at 145,023 mesh points, showing that over 90% of points had relative errors within 10%. The proposed PINN model is effective for data-scarce geotechnical problems, though its performance in regions with significant rates of change in physical quantity still requires further improvement.

本文建立了求解地质力学中moh - coulomb （M-C）塑性问题的物理信息神经网络（PINN）框架，并利用表面压缩压力作用下的平面应变分层穿孔土与OptumG2并行数值实验进行了对比，验证了PINN解的有效性。为了将弹塑性问题的物理信息整合到神经网络中，通过粗数据驱动的信息和物理约束，包括M-C本构关系、关联/非关联流动规则、Karush-Kuhn-Tucker （KKT）条件、平衡条件、约束条件和约束条件，构建了两个改进的多目标损失函数，分别称为搭配损失函数和最小二乘加权残差（LSWR）损失函数。还有边界条件。总损失函数结合了从有限元法（FEM）解中获得的一系列弹塑性场变量（即应力和位移）的项，以告知物理知识拟合。通过使用多个独立运行且紧密连接的人工神经网络（ann）， PINN框架通过最小化设计的总损失函数来实现M-C塑性解决方案。此外，研究了样本大小、采样策略和损失函数对所提出的PINN框架性能的影响，以进行参数分析。在所有情况下，将PINN预测与145,023个网格点的有限元解进行比较，显示超过90%的点的相对误差在10%以内。提出的PINN模型对于数据稀缺的岩土工程问题是有效的，尽管其在物理量变化速率较大的地区的表现仍需进一步改进。

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引用次数: 0

Numerical boundary treatment in meshfree collocation for lid-driven cavity flow in stream function-vorticity form 流函数涡量型盖驱动腔流无网格配置的数值边界处理

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

Advances in Engineering Software

Pub Date : 2025-11-04 DOI: 10.1016/j.advengsoft.2025.104062

Judy P. Yang, Yu-Hui Kao

A nonlinear collocation method incorporating numerical boundary treatment is developed to solve lid-driven cavity flow problems governed by the Navier-Stokes equations in the stream function-vorticity form. In contrast to approaches that rely solely on the vorticity formulation, the present method avoids the computational challenges associated with evaluating fourth-order derivatives of reproducing kernel shape functions. To address the difficulties posed by non-physical vorticity boundary conditions, a higher-order finite difference-based numerical boundary scheme is introduced, in which Neumann boundary conditions for the stream function are implicitly enforced. The effectiveness and accuracy of the method are validated through a series of benchmark investigations, demonstrating its robustness and capability to handle a wide range of Reynolds numbers in lid-driven cavity flow problems.

提出了一种结合数值边界处理的非线性配点法，用于求解流函数涡量形式的Navier-Stokes方程下的盖驱动腔体流动问题。与仅依赖涡量公式的方法相比，本方法避免了与评估再现核形状函数的四阶导数相关的计算挑战。为了解决非物理涡度边界条件带来的困难，引入了一种基于高阶有限差分的数值边界格式，其中隐式执行流函数的诺伊曼边界条件。通过一系列的基准研究，验证了该方法的有效性和准确性，证明了其鲁棒性和处理大范围雷诺数的能力。

引用次数: 0

Optimal local truncation error method for 3-D elastodynamics interface problems on unfitted Cartesian meshes 非拟合笛卡尔网格三维弹性动力学界面问题的最优局部截断误差方法

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

Advances in Engineering Software

Pub Date : 2025-11-01 DOI: 10.1016/j.advengsoft.2025.104049

A. Idesman, W. Ajwad, M. Mobin

This study expands the optimal local truncation error method (OLTEM) with unfitted Cartesian meshes, designed for 2-D elastodynamics with interfaces (wave propagation and structural dynamics), to the general 3-D case and non-homogeneous interface conditions. The technique employs compact 27-point stencils, similar to those used in linear finite elements, while avoiding the introduction of additional unknowns at material interfaces. Importantly, the global semi-discrete equations retain a similar structure for homogeneous and heterogeneous materials. OLTEM with the diagonal mass matrix, suitable for explicit time-integration schemes, represents a subset of the broader formulation using the non-diagonal mass matrix.

A significant innovation in this work is a new 3-D post-processing procedure for stress calculations. It improves accuracy by incorporating accelerations and the governing elastodynamics equations into the analysis. Like the primary computations, this post-processing technique utilizes compact 27-point stencils. The new post-processing procedure outperforms traditional methods that depend solely on displacements.

OLTEM with unfitted Cartesian meshes shows superior accuracy compared to linear finite elements with equivalent stencils and conformal meshes, while requiring significantly fewer degrees of freedom (DOF). For instance, at an accuracy of 0.1% for the displacements, OLTEM with the non-diagonal mass matrix reduces the number of DOF by more than

1 0^{4}

times; at an accuracy of 0.1% for the stresses, OLTEM with the new post-processing procedure reduces the number of DOF about

2 \times 1 0^{6}

times compared to linear finite elements. OLTEM also provides increased computational efficiency compared to high-order finite elements, despite their wider stencils and conformal meshes.

本研究将非拟合笛卡尔网格的最优局部截断误差法（OLTEM）扩展到一般三维情况和非均匀界面条件下，该方法适用于具有界面（波传播和结构动力学）的二维弹性动力学。该技术采用紧凑的27点模板，类似于线性有限元中使用的模板，同时避免了在材料界面引入额外的未知元素。重要的是，对于均匀和非均匀材料，全局半离散方程保持了类似的结构。具有对角质量矩阵的OLTEM，适用于显式时间积分方案，代表了使用非对角质量矩阵的更广泛公式的子集。这项工作的一项重大创新是用于应力计算的新的三维后处理程序。通过将加速度和控制弹性动力学方程纳入分析，提高了精度。与初级计算一样，这种后处理技术使用紧凑的27点模板。新的后处理程序优于仅依赖位移的传统方法。与具有等效模板和保形网格的线性有限元相比，具有非拟合笛卡尔网格的OLTEM具有更高的精度，同时所需的自由度（DOF）显着降低。例如，在位移精度为0.1%的情况下，使用非对角质量矩阵的OLTEM将自由度数量减少了104倍以上；与线性有限元相比，具有新的后处理程序的OLTEM在0.1%的应力精度下减少了大约2×106次的自由度。尽管OLTEM具有更宽的模板和保形网格，但与高阶有限元相比，OLTEM还提供了更高的计算效率。

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引用次数: 0

An efficient multiscale coupling method for simulations of reactor-scale chemical vapor deposition with microstructural features 具有微结构特征的反应器级化学气相沉积多尺度耦合模拟方法

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

Advances in Engineering Software

Pub Date : 2025-10-30 DOI: 10.1016/j.advengsoft.2025.104051

Taegeun Kim , Hyoungsoo Ko , Jaewon Jang , Sejin Kim , Sunyoung Park , Jae Myung Choe , Young-gu Kim , Dae Sin Kim , Sangseung Lee , Donghyun You

An efficient multiscale coupling method is proposed for simulations of reactor-scale chemical vapor deposition (CVD) with microstructural features. Reactor-scale and microstructure-resolved feature-scale models are coupled through an effective reaction rate formalism, enabling high-resolution deposition simulations while significantly reducing computational cost. A parameterized microstructural model is introduced, in which the relationship between the effective reaction rate and local species consumption rates in the reactor-scale model is directly mapped using precomputed Monte Carlo simulation data. This eliminates the need for iterative calculations or direct numerical simulations of the surface reaction across all the discretized grid points on the wafer, ensuring predictive accuracy while enhancing computational efficiency. Furthermore, an adaptive time-stepping method is developed, dynamically adjusting the time-step size for the feature-scale model based on variations in the effective reaction rate. Through this approach, simulation time is reduced by more than one-third compared to conventional fixed time-step methods, while preserving the accuracy of the effective reaction rate model. The proposed method enables practical and scalable multiscale CVD simulations applicable to industrial reactor design and process optimization, establishing a computationally efficient strategy for integrating reactor-scale and microstructure-resolved feature-scale models.

提出了一种高效的多尺度耦合方法来模拟具有微观结构特征的反应器尺度化学气相沉积过程。反应器尺度和微结构分辨率特征尺度模型通过有效的反应速率形式相结合，实现高分辨率沉积模拟，同时显著降低计算成本。引入参数化微结构模型，利用预先计算的蒙特卡罗模拟数据直接映射反应器尺度模型中有效反应速率与局部物质消耗率之间的关系。这消除了对晶圆上所有离散网格点的表面反应进行迭代计算或直接数值模拟的需要，确保了预测的准确性，同时提高了计算效率。在此基础上，提出了一种基于有效反应速率变化动态调整特征尺度模型时间步长的自适应时间步长方法。通过该方法，与传统的固定时间步长方法相比，模拟时间减少了三分之一以上，同时保持了有效反应速率模型的准确性。该方法实现了适用于工业反应器设计和工艺优化的实用和可扩展的多尺度CVD模拟，为集成反应器尺度和微观结构分辨率特征尺度模型建立了一种计算效率高的策略。

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引用次数: 0

Dynamic modeling and vibration analysis for functionally graded graphene platelet reinforced porous composite coupled conical-cylindrical-conical shells with annular plates 功能梯度石墨烯血小板增强多孔复合材料环板锥形-圆柱-锥形壳耦合动力学建模及振动分析

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

Advances in Engineering Software

Pub Date : 2025-10-29 DOI: 10.1016/j.advengsoft.2025.104060

Peng Zuo , Zhao Du , Xianjie Shi , Huiyong Feng , Zhengyang Gao , Bing Hu

This study proposed a dynamic analysis model to systematically investigate the free vibration and stationary random vibration problems of functionally graded graphene platelet reinforced porous composite (FG-GPLRPC) coupled conical-cylindrical-conical shells with annular plates under stationary random excitation. Based on the closed-cell theory, the effective material properties with respect to FG-GPLRPC are characterized using the Halpin–Tsai micromechanics model combined with rule of mixture. Also, the artificial spring approach is adopted to describe different boundary restraints and coupling conditions that existed in the model. Within the shell theoretical framework of the first-order shear deformation theory (FSDT), the dynamic model for analyzing the free vibration and random vibration responses of the studied FG-GPLRPC coupled structures is established based on the Rayleigh-Ritz method. The spectro-geometric method (SGM) and pseudo-excitation method (PEM) are employed to calculate the vibration response results of the FG-GPLRPC coupled structures. The validity of the presented model is verified through implementing several numerical cases associated with the comparative analysis of free vibration and random vibration response results. Furthermore, some physical mechanisms regarding the influences of porosity coefficient, weight fraction, and the length of cylindrical shell, etc., on the model frequencies and random response behaviors of the FG-GPLRPC coupled structures are revealed.

本研究提出了一种动态分析模型，系统研究了静随机激励下功能梯度石墨烯血小板增强多孔复合材料（FG-GPLRPC）锥形-圆柱-锥形壳与环形板耦合的自由振动和静随机振动问题。基于闭孔理论，采用Halpin-Tsai细观力学模型结合混合规律对FG-GPLRPC的有效材料性能进行了表征。采用人工弹簧的方法来描述模型中存在的不同边界约束和耦合条件。在一阶剪切变形理论（FSDT）的壳体理论框架下，基于瑞利-里兹法建立了FG-GPLRPC耦合结构自由振动和随机振动响应的动力学模型。采用几何谱法（SGM）和伪激励法（PEM）计算FG-GPLRPC耦合结构的振动响应结果。通过对自由振动与随机振动响应结果的对比分析，验证了该模型的有效性。揭示了孔隙率系数、质量分数、柱壳长度等因素对FG-GPLRPC耦合结构模型频率和随机响应行为影响的一些物理机制。

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引用次数: 0

A real-time dynamic simulation platform for multi-DOF rigid body systems based on a novel explicit modelling method 基于新型显式建模方法的多自由度刚体系统实时动态仿真平台

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

Advances in Engineering Software

Pub Date : 2025-10-24 DOI: 10.1016/j.advengsoft.2025.104047

Feifei Chen , Xiaoting Rui , Hehua Ju , Kaimeng Wang

Dynamic simulation is critical for the design and control of complex multi-DOF rigid body systems. Existing general-purpose dynamics software often relies on pre-built toolkits or open source libraries, which provide versatile functions but face challenges such as functional constraints and difficulty in error tracking. This study presents a self-developed, modular simulation platform based on an explicit joint space canonical dynamics formulation. The proposed approach extends the explicit dynamics theory by exploiting its block matrix structure: rotational and prismatic joints are classified, and the joint space mass matrix and bias force vector are assembled explicitly at the block level, enabling parallel computation of only half of the symmetric matrix, thus allowing real-time performance for multi-DOF systems. The entire numerical pipeline from topology initialization to forward and inverse dynamics solving is transparent, lightweight, and implemented in C++, ensuring full controllability and solver traceability. The platform demonstrates real-time simulation in millisecond level for a 6-DOF robotic arm, a 25-DOF Mars rover, and a 48-DOF multi-satellite system on standard CPUs, validating its accuracy, stability, and engineering applicability. This work highlights a way from traditional recursive solvers to an explicit dynamics framework for robotic and aerospace systems.

动态仿真是复杂多自由度刚体系统设计与控制的关键。现有的通用动态软件通常依赖于预构建的工具包或开源库，它们提供了多种功能，但面临功能限制和错误跟踪困难等挑战。本研究提出了一个基于显式关节空间正则动力学公式的自主开发的模块化仿真平台。该方法通过利用其分块矩阵结构扩展了显式动力学理论：旋转和移动关节被分类，关节空间质量矩阵和偏置力向量在分块级显式组装，仅实现对称矩阵的一半并行计算，从而实现多自由度系统的实时性能。从拓扑初始化到正向和逆动力学求解的整个数值管道是透明的，轻量级的，并在c++中实现，确保了完全的可控性和求解器的可追溯性。该平台在标准cpu上对6自由度机械臂、25自由度火星探测器和48自由度多卫星系统进行了毫秒级实时仿真，验证了其精度、稳定性和工程适用性。这项工作强调了从传统的递归求解器到机器人和航空航天系统的显式动力学框架的方法。

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引用次数: 0

Stress intensity factor evaluation for non-planar cracks using virtual grid stress recovery (VGSR) and interaction integral methods 基于虚拟网格应力恢复和相互作用积分法的非平面裂纹应力强度因子评价

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

Advances in Engineering Software

Pub Date : 2025-10-23 DOI: 10.1016/j.advengsoft.2025.104042

Nastaran Movahedi, Jongyeop Kim, Kyoungsoo Park

This study proposes a straightforward method for computation of stress intensity factors (SIFs) for three-dimensional cracks featuring curved crack fronts and curved crack surfaces, without concerning the mesh topology around a crack tip. The key idea is to utilize a virtual grid-based stress recovery (VGSR) method on arbitrary nonplanar crack geometries along with the interaction energy integral to extract SIFs correspond to different modes. Since the VGSR technique reduces errors related to numerical differentiation and integral domain, it provides accurate computation of SIFs even with arbitrary unstructured meshes. Validation against benchmark problems shows excellent agreement with analytical solutions, highlighting the efficacy of this conjugated approach for precise SIF evaluation. Computational results demonstrate the convergence to analytical solutions while effectively reducing the pointwise oscillations of SIFs under mesh refinement. Additionally, parametric studies are comprehensively performed concerning the characteristics associated with virtual grid domain size, virtual grid element size, finite element sizes, and number of numerical integration points.

本研究提出了一种直接计算具有弯曲裂纹前沿和弯曲裂纹表面的三维裂纹的应力强度因子（SIFs）的方法，而无需考虑裂纹尖端周围的网格拓扑结构。其核心思想是利用基于虚拟网格的应力恢复（VGSR）方法和相互作用能量积分对任意非平面裂纹几何形状提取不同模态对应的SIFs。由于VGSR技术减少了与数值微分和积分域相关的误差，因此即使在任意非结构化网格下也能精确计算SIFs。针对基准问题的验证显示与分析解决方案非常一致，突出了这种共轭方法用于精确SIF评估的有效性。计算结果表明，该方法收敛于解析解，同时有效地降低了网格细化后SIFs的点向振荡。此外，还对虚拟网格域尺寸、虚拟网格单元尺寸、有限元尺寸、数值积分点数量等相关特征进行了参数化研究。

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引用次数: 0

A dual-stage combined displacement prediction model for concrete dam based on adaptive time series decomposition noise reduction and residual chaotic feature separation 基于自适应时间序列分解降噪和残差混沌特征分离的混凝土坝双阶段联合位移预测模型

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

Advances in Engineering Software

Pub Date : 2025-10-15 DOI: 10.1016/j.advengsoft.2025.104045

Yu Gu , Zhiping Wen , Huaizhi Su , Zheng Fang

High-precision analysis and prediction of dam displacement is a crucial strategy to grasp the working attitude of dams and diagnose dam anomalies. However, the existing models often fail to accurately identify the interference noise existing in the form of short-frequency and small-fluctuations, resulting in the masking of the true deformation features. Meanwhile, existing studies often focus on one-stage prediction models, discarding the rich and valuable information contained in the residual sequence. Furthermore, the existing dual-stage models often fail to deeply consider the chaotic characteristics existing in the residuals. Therefore, this paper proposes a dual-stage combined displacement prediction model for concrete dam identifying the displacement sequence interference noise and considering the chaotic characteristics of the residual sequence. Firstly, the adaptive noise complete empirical mode decomposition, the improved sparrow search algorithm and the threshold evaluation index are combined to adaptively achieve the optimal decomposition noise reduction and retain the effective deformation features. Secondly, a gradient boosting tree is utilized to fit the effective component and combine it with the processed noise component to build a high-quality residual sequence that is rich in information. Thirdly, the residual sequence is decomposed into intrinsic mode functions with different temporal characteristics by utilizing the optimized variational mode decomposition. Finally, construct a chaotic time series based on chaos theory. Taking the sample entropy as the basis of judgement, for high-frequency components, the gradient boosting tree algorithm is utilized to capture their dynamic features. For low-frequency components, the depth-separable convolutional neural network, multi-head attention mechanism and bidirectional long short-term memory neural network are organically combined to comprehensively learn the deformation features. Case analysis shows that the RMSE of the model proposed in this paper in the measurement point PL11–5 sequence has reached an astonishing 0.0794, and the maximum improvement degree compared with the control model has reached 79.35 %. The results show that this model obtains strong generalization ability and high robustness, and can provide reference for dam safety monitoring.

大坝位移的高精度分析与预测是掌握大坝工作状态、诊断大坝异常的重要手段。然而，现有的模型往往不能准确识别以短波小波动形式存在的干扰噪声，从而掩盖了真实的变形特征。同时，现有的研究往往侧重于单阶段预测模型，而忽略了残差序列中包含的丰富而有价值的信息。此外，现有的双级模型往往没有深入考虑残差中存在的混沌特性。为此，本文提出了一种识别位移序列干扰噪声并考虑残差序列混沌特性的混凝土坝双阶段联合位移预测模型。首先，结合自适应噪声完成经验模态分解、改进的麻雀搜索算法和阈值评价指标，自适应实现最优分解降噪并保留有效变形特征；其次，利用梯度增强树对有效分量进行拟合，并与处理后的噪声分量结合，构建信息丰富的高质量残差序列；第三，利用优化后的变分模态分解方法，将残差序列分解为具有不同时间特征的内禀模态函数。最后，基于混沌理论构造一个混沌时间序列。以样本熵为判断依据，对高频分量采用梯度增强树算法捕获其动态特征。低频分量将深度可分卷积神经网络、多头注意机制和双向长短期记忆神经网络有机结合，全面学习变形特征。实例分析表明，本文提出的模型在测量点PL11-5序列上的RMSE达到了惊人的0.0794，与控制模型相比，最大改善程度达到了79.35%。结果表明，该模型具有较强的泛化能力和较高的鲁棒性，可为大坝安全监测提供参考。

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引用次数: 0