Advances in Engineering Software最新文献

SA-PINN: A self-attention enhanced physics-informed neural network for multiaxial fatigue life prediction with small samples SA-PINN：用于小样本多轴疲劳寿命预测的自关注增强物理信息神经网络

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

Advances in Engineering Software

Pub Date : 2026-05-01 Epub Date: 2026-02-14 DOI: 10.1016/j.advengsoft.2026.104124

Yu Wang , Yue Li , ShunPeng Zhu , Ran Gu , Xinhao Shu , Zhengwei Fan , Shufeng Zhang

Multiaxial fatigue life prediction holds significant practical importance in the reliability analysis of equipment engineering structures. To address the high dependence on experimental data and low accuracy of long-term fatigue prediction in existing fatigue life prediction methods, this article proposes a self-attention mechanism enhanced physics-informed neural network (SA-PINN). This method introduces physical information into the loss function of artificial neural network (ANN) and jointly optimizes with the self-attention mechanism during training to enhance the accuracy of fatigue life prediction under small-sample conditions. Specifically, SA-PINN dynamically adjusts the weights of input features using the self-attention mechanism in the early stages of the network, performing global modeling of time-series stress-strain features. Under the constraint of the physical information loss functions, it further establishes accurate long-range feature dependencies, enhancing prediction accuracy and physical interpretability of the prediction results. Experiments were performed on six types of small samples material dataset. The results show that the Root Mean Square Error (RMSE) of the prediction results of the SA-PINN model is 0.153, and the coefficient of determination (R²) is 0.942. Compared with ANN, RMSE is reduced by 0.09 and R² is increased by 0.15. It significantly improves the accuracy and reliability of fatigue life prediction in small samples and multiple working conditions, and provides a new paradigm for fatigue life prediction.

多轴疲劳寿命预测在装备工程结构可靠性分析中具有重要的现实意义。针对现有疲劳寿命预测方法对实验数据依赖程度高、长期疲劳预测精度低的问题，提出了一种自关注机制增强物理信息神经网络（SA-PINN）。该方法将物理信息引入人工神经网络（ANN）的损失函数中，并在训练过程中与自关注机制共同优化，提高了小样本条件下疲劳寿命预测的精度。具体而言，SA-PINN在网络的早期阶段利用自注意机制动态调整输入特征的权重，对时间序列应力-应变特征进行全局建模。在物理信息损失函数的约束下，进一步建立准确的远程特征依赖关系，提高预测精度和预测结果的物理可解释性。在六种小样本材料数据集上进行了实验。结果表明，SA-PINN模型预测结果的均方根误差（RMSE）为0.153，决定系数（R2）为0.942。与人工神经网络相比，RMSE降低0.09，R2提高0.15。该方法显著提高了小样本、多工况下疲劳寿命预测的精度和可靠性，为疲劳寿命预测提供了新的范式。

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引用次数: 0

A resolution-independent DeepONet-ABC framework for inverse characterization of composite materials 用于复合材料逆表征的分辨率无关DeepONet-ABC框架

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

Advances in Engineering Software

Pub Date : 2026-04-01 Epub Date: 2026-02-04 DOI: 10.1016/j.advengsoft.2026.104116

Enying Li , Hu Wang

This study proposes a novel inverse method based on Approximate Bayesian Computation (ABC) integrated with a Resolution Independent Strategy (RIS) to determine the material parameters of Carbon Fiber Reinforced Polymer (CFRP). The proposed framework addresses a key challenge in materials science and engineering, particularly for CFRP composites. Unlike existing approaches, the method explicitly incorporates sample locations during modeling, which makes the sampling distribution for inversion less sensitive and relaxes the strict requirement for precise sensor placement. By integrating ABC with RIS, the framework successfully infers key parameters that govern the behavior of CFRP. The accuracy and effectiveness of the proposed method have been rigorously validated through numerical experiments, comparing posterior means and uncertainties of the inferred parameters with experimental data. An excellent agreement among experimental observations, posterior model predictions, and finite element simulations demonstrates the robustness of the methodology. These results underscore the potential of the DeepONet-augmented ABC inverse approach for the accurate characterization of CFRP material properties, offering a powerful tool to enhance the precision of inverse analysis in this field.

提出了一种基于近似贝叶斯计算（ABC）与分辨率无关策略（RIS）相结合的碳纤维增强聚合物（CFRP）材料参数反演方法。提出的框架解决了材料科学和工程中的一个关键挑战，特别是CFRP复合材料。与现有方法不同的是，该方法在建模时明确地考虑了样本位置，使得反演的采样分布不那么敏感，也放松了对传感器精确放置的严格要求。通过将ABC与RIS相结合，该框架成功地推断出控制CFRP行为的关键参数。通过数值实验，将后验均值和推断参数的不确定性与实验数据进行比较，验证了该方法的准确性和有效性。实验观察、后验模型预测和有限元模拟之间的良好一致性证明了该方法的稳健性。这些结果强调了deeponet增强ABC反演方法在准确表征CFRP材料性能方面的潜力，为提高该领域反演分析的精度提供了有力的工具。

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引用次数: 0

Multistage design of high-aspect-ratio wings: Geometrically nonlinear topology optimization with aero-structural coupling 高展弦比机翼多级设计：考虑气动-结构耦合的几何非线性拓扑优化

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

Advances in Engineering Software

Pub Date : 2026-04-01 Epub Date: 2026-02-09 DOI: 10.1016/j.advengsoft.2026.104119

Longlong Song , Pingchu Fang , Tong Gao , Jihong Zhu , Xiaohua Nie , Weihong Zhang

High-aspect-ratio wings for solar-powered UAVs (Unmanned Aerial Vehicles) require ultra-lightweight structural designs capable of withstanding large deformations induced by aerodynamic loads. Traditional topology optimization methods often overlook the interplay between geometric nonlinearity and aero-structural coupling, limiting their effectiveness for flexible wing systems. This study proposes a multi-material topology optimization framework that integrates geometric nonlinearity with weak aero-structural coupling. The three-field approach, incorporating directional length scale control and deformation control, is employed for the geometrically nonlinear multi-material optimization. A nodal displacement-based inverse modeling method enables efficient data transfer between aerodynamic and structural meshes, while a deformation-driven load update strategy reduces computational costs. A straight wing with four case studies demonstrates that incorporating aero-structural coupling shifts high-stiffness material toward the wing root, optimizing load transfer and reducing deformation. The reconstructed truss-based design achieves an 11.29 % mass reduction via size optimization while maintaining bending and torsional constraints. This framework bridges structural optimization with aero-structural coupling, providing a systematic approach for designing lightweight, main spar-ribs based, and deformation-resistant wings.

太阳能无人机的高展弦比机翼需要超轻的结构设计，能够承受空气动力载荷引起的大变形。传统的拓扑优化方法往往忽略了几何非线性和气动结构耦合之间的相互作用，限制了其对柔性翼系统的有效性。本研究提出了一种集成几何非线性和弱气动结构耦合的多材料拓扑优化框架。将定向长度尺度控制和变形控制相结合的三场方法用于几何非线性多材料优化。基于节点位移的逆建模方法可以在气动网格和结构网格之间实现有效的数据传输，而变形驱动的载荷更新策略可以降低计算成本。通过对一个直线型机翼的四个案例研究表明，结合气动结构耦合将高刚度材料转移到机翼根部，优化了载荷传递并减少了变形。在保持弯曲和扭转约束的同时，通过尺寸优化，基于桁架的重建设计实现了11.29%的质量减少。该框架通过气动结构耦合实现结构优化，为设计轻量化、基于主肋和抗变形的机翼提供了系统的方法。

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引用次数: 0

Explainable AI-driven prediction and interpretation of aerodynamic interference effect in complex high-rise building clusters 复杂高层建筑群气动干扰效应的可解释ai驱动预测与解释

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

Advances in Engineering Software

Pub Date : 2026-04-01 Epub Date: 2026-02-11 DOI: 10.1016/j.advengsoft.2026.104121

H.C. Deng, Z.Y. Zhang, Z.R. Shu, X.H. He

The rapid urban densification intensifies aerodynamic interference among high-rise buildings, which complicates the wind-resistant design and structural safety. However, the underlying flow mechanisms in complex building clusters remain under-explored, mainly due to their nonlinear and configuration-dependent behavior. This study integrates wind tunnel experiments with an explainable artificial intelligence (XAI) framework to provide high-fidelity prediction and physical interpretation of aerodynamic interference within triangular high-rise clusters. Systematic experiments varying streamwise and transverse spacing and rotational angles produced detailed surface pressure datasets. Four AI models, i.e., Support Vector Regression, Decision Tree, Random Forest, and XGBoost, were trained to predict mean and fluctuating pressure coefficients, with XGBoost yielding the best overall performance. Model interpretability, achieved through SHapley Additive exPlanations (SHAP), revealed that transverse spacing governs regime transitions between shielding and resonance amplification, while streamwise spacing primarily influences fluctuating pressures through aerodynamic damping. SHAP analysis also identified pronounced three-dimensional pressure non-uniformity and a rotation-induced converging nozzle effect that increases mean pressures while moderating fluctuations. The proposed XAI-assisted framework establishes a data-driven approach for uncovering aerodynamic interference mechanisms, thus providing insights for resilient and performance-informed wind design of high-rise building clusters.

城市密度的迅速增加加剧了高层建筑之间的气动干扰，使高层建筑的抗风设计和结构安全变得更加复杂。然而，复杂建筑群的潜在流动机制仍未得到充分探讨，这主要是由于它们的非线性和构型依赖行为。该研究将风洞实验与可解释的人工智能（XAI）框架相结合，为三角形高层集群内的空气动力干扰提供高保真预测和物理解释。系统实验改变了流向和横向间距以及旋转角度，产生了详细的地表压力数据集。采用支持向量回归（Support Vector Regression）、决策树（Decision Tree）、随机森林（Random Forest）和XGBoost四种人工智能模型来预测平均压力系数和波动压力系数，其中XGBoost的整体性能最好。通过SHapley加性解释（SHAP）实现的模型可解释性表明，横向间距控制屏蔽和共振放大之间的状态转换，而流向间距主要通过气动阻尼影响波动压力。SHAP分析还发现了明显的三维压力不均匀性和旋转引起的喷嘴聚合效应，该效应增加了平均压力，同时缓和了波动。提出的xai辅助框架建立了一种数据驱动的方法，用于揭示空气动力学干扰机制，从而为高层建筑群的弹性和性能信息风设计提供见解。

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引用次数: 0

A unified constitutive model for natural soils and a novel stress integration algorithm with the trust region method 天然土统一本构模型及信赖域法应力积分算法

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

Advances in Engineering Software

Pub Date : 2026-04-01 Epub Date: 2026-02-11 DOI: 10.1016/j.advengsoft.2026.104120

Kai Cui , Bohan Wu , Wenbin Xiao , Ran Yuan , Yi He

Constitutive models and stress integration algorithms are an essential part of computational modelling in geotechnics; selecting an appropriate constitutive model and a reliable stress integration algorithm are usually the key to successfully predicting the behaviour of geostructures. This paper develops a unified constitutive model, i.e., CASM-PSS, for natural structure clay and sand within the critical state framework, considering the influence of noncoaxial behaviour. By introducing the inclined yield surface, incorporating the influence of direction of stress increment on plastic flow rule, and introducing the super-subloading surface in the unified clay and sand model (CASM), the proposed model able to unified describe the mechanical behaviour of natural clay and sand. Novelty of the proposed model lies in its ability to consider the effects of anisotropy, destructuration, and direction of stress increment of natural soils. The CASM-PSS is then implemented into a finite difference software through the user-defined model platform (UDM), by a new semi-implicit integration algorithm integrated with the trust region method. Performance of the CASM-PSS is investigated and validated by a series of experimental and DEM evidence on soils under different loading paths, including drained and undrained conditions of triaxial compression and simple shear tests. Then, the newly proposed model is numerically applied to simulate centrifugal model testing and practical engineering problems, i.e., China Tsinghuayuan Tunnel, to identify effects of soil structure, anisotropy and noncoaxiality in boundary value problems.

本构模型和应力积分算法是岩土工程计算建模的重要组成部分；选择合适的本构模型和可靠的应力积分算法通常是成功预测土工结构行为的关键。本文建立了考虑非同轴特性影响的临界状态框架内天然结构粘土和砂土的统一本构模型CASM-PSS。该模型通过引入倾斜屈服面，考虑应力增量方向对塑性流动规律的影响，并在粘土与砂土统一模型（CASM）中引入超加载面，能够统一描述天然粘土与砂土的力学行为。该模型的新颖之处在于能够考虑天然土的各向异性、破坏和应力增量方向的影响。然后，通过用户定义模型平台（UDM），采用一种新的半隐式积分算法与信任域方法相结合，将CASM-PSS实现为有限差分软件。通过一系列试验和DEM证据，对CASM-PSS在不同加载路径下的性能进行了研究和验证，包括排水和不排水条件下的三轴压缩和简单剪切试验。然后，将该模型数值应用于离心模型试验和实际工程问题，即中国青花园隧道，以识别土结构、各向异性和非同轴性对边值问题的影响。

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引用次数: 0

An open-source computational wind load evaluation workflow for tall building design 面向高层建筑设计的开源计算风荷载评估工作流程

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

Advances in Engineering Software

Pub Date : 2026-04-01 Epub Date: 2026-02-07 DOI: 10.1016/j.advengsoft.2026.104117

Christopher J. Howlett, Girma T. Bitsuamlak

Wind load evaluation (WLE) of tall buildings is a complex process as multiple factors influence the final results. The reliability of the evaluation is dependent on the analysis accuracy of each factor. Traditionally, wind tunnels have been the primary method of performing WLE studies but recent growth in computational resources has led to a wider adoption of computational-based wind engineering. However, for these computational studies to be used in research and practice, it is imperative that they maintain a high level of accuracy. The current study presents the development of an open-source computational-based WLE workflow for the design of tall buildings. The proposed workflow adapts established methods from wind tunnel studies and integrates them into a computational fluid dynamics (CFD)-based pipeline. Each step within the WLE analysis is discusses, along with the relevant background information. Separating each step of the WLE pipeline into a unique and modular component provides engineers and researchers with the foundational knowledge required to perform computational WLE studies. Finally, the effectiveness of the proposed workflow is validated using a WLE study performed in the wind tunnel.

高层建筑风荷载评估是一个复杂的过程，影响最终结果的因素很多。评价的可靠性取决于各因素的分析准确性。传统上，风洞一直是进行WLE研究的主要方法，但最近计算资源的增长导致了基于计算的风工程的广泛采用。然而，为了使这些计算研究在研究和实践中得到应用，它们必须保持高水平的准确性。目前的研究提出了一个基于开源计算的WLE工作流程的开发，用于高层建筑的设计。提出的工作流程采用风洞研究的既定方法，并将其集成到基于计算流体动力学（CFD）的管道中。本文讨论了WLE分析中的每个步骤以及相关的背景信息。将WLE管道的每个步骤分离为一个独特的模块化组件，为工程师和研究人员提供了执行计算WLE研究所需的基础知识。最后，通过在风洞中进行的WLE研究验证了所提出工作流的有效性。

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引用次数: 0

Multi-objective optimization design of a pressure swirl nozzle for sodium spray in SFRs via adaptive surrogate model 基于自适应代理模型的SFRs钠喷雾压力旋流喷嘴多目标优化设计

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

Advances in Engineering Software

Pub Date : 2026-04-01 Epub Date: 2026-02-02 DOI: 10.1016/j.advengsoft.2026.104113

Rongdong Wang , Yang Li , Changming Li , Zhonghua Wang , Detao Wan , Gang Yang , Dean Hu

To address the challenge of safely and efficiently disposing of radioactive liquid sodium from sodium-cooled fast reactors (SFR), this study proposes an adaptive data-driven multi-objective optimization framework for pressure swirl nozzle designs. The spray performance is characterized by spray angle (ω) and outlet velocity (v), which are typically conflicting. The wider ω often leads to lower v. Balancing these objectives is crucial for effective dispersion. A deep neural network (DNN) surrogate model is developed to capture the nonlinear mapping between geometric variables and spray performance metrics. The model is trained on computational fluid dynamics (CFD) data and iteratively refined using an adaptive sampling strategy based on uncertainty. The well-trained surrogate model achieves a determination coefficient (R²) above 93%, and a maximum normalized squared error (NSE) below 0.03 on the testing set. The NSGA-II algorithm is employed to perform multi-objective optimization, generating a Pareto front that reveals the trade-off relationship between spray angle and outlet velocity. Three representative design schemes including maximum angle, maximum velocity, and Pareto inflection scheme were selected and validated via CFD. Compared to the baseline design, the nozzle scheme improved spray angle by up to 96.25% and outlet velocity by up to 37.18%. Furthermore, Sobol sensitivity analysis indicates that the outlet diameter contributes over 40% of the total first-order sensitivity for both objectives, demonstrating its dominant role in nozzle performance. This work provides an efficient and accurate design methodology for optimizing high-temperature sodium spray systems and can be extended to other complex multiphase flow applications.

为了解决安全高效地处理钠冷快堆（SFR）放射性液钠的挑战，本研究提出了一种自适应数据驱动的压力旋流喷嘴多目标优化设计框架。喷淋性能由喷淋角（ω）和出口速度(v)表征，两者通常是相互冲突的。更宽的ω通常导致更低的v。平衡这些目标对于有效色散至关重要。建立了一种深度神经网络（DNN）代理模型来捕捉几何变量与喷雾性能指标之间的非线性映射关系。该模型基于计算流体动力学（CFD）数据进行训练，并使用基于不确定性的自适应采样策略进行迭代改进。训练良好的代理模型在测试集上的决定系数（R2）在93%以上，最大归一化平方误差（NSE）在0.03以下。采用NSGA-II算法进行多目标优化，生成一个Pareto front，该Pareto front揭示了喷淋角与出口速度之间的权衡关系。选取了三种具有代表性的设计方案，包括最大角度、最大速度和Pareto弯曲方案，并通过CFD进行了验证。与基线设计相比，该喷嘴方案可使喷射角提高96.25%，出口速度提高37.18%。此外，Sobol灵敏度分析表明，出口直径对两个物镜的总一阶灵敏度贡献超过40%，表明其在喷嘴性能中起主导作用。这项工作为优化高温钠喷雾系统提供了一种高效、准确的设计方法，并可推广到其他复杂的多相流应用中。

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引用次数: 0

Free vibration characteristics and veering analysis of auxetic metamaterial plates 无氧超材料板的自由振动特性及转向分析

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

Advances in Engineering Software

Pub Date : 2026-04-01 Epub Date: 2026-02-09 DOI: 10.1016/j.advengsoft.2026.104118

Shang Lv , Wei Sun , Xuedong Sun , Yu Zhang , Hui Zhang , Dongxu Du , Hui Li

Honeycomb-reinforced composite sandwich plates (CSPs) have been widely used in the aerospace field due to their excellent mechanical properties, especially the Auxetic Hexagonal Honeycomb (AHH) sandwich plates with negative Poisson’s ratio effect. However, their vibration characteristics and modal coupling mechanisms have not been studied; therefore, this paper establishes a systematic research method that integrates modelling, fabrication, verification, and analysis. First, this paper develops a semi-analytical dynamic model for the AHH-CSP structure, based on the first-order shear deformation theory (FSDT) and the layer-wise zigzag theory. Second, AHH-CSP specimens are designed and fabricated, and their natural frequencies and modal shapes are determined via impact tests. Then, this paper verifies the accuracy and applicability of the semi-analytical model by combining it with finite element simulations, existing literature, and experimental results, and systematically analyzes honeycomb parameters on structural vibration characteristics. The results show that coupled vibration occurs between different modes of the AHH-CSP structure, thereby inducing frequency veering and mode shape exchange and revealing the inherent patterns of modal coupling. The findings provide both theoretical foundations and experimental support for the engineering application of novel honeycomb sandwich plate structures with negative Poisson’s ratio.

蜂窝增强复合材料夹层板（CSPs）以其优异的力学性能在航空航天领域得到了广泛的应用，特别是具有负泊松比效应的Auxetic hexonal Honeycomb夹层板。然而，对其振动特性和模态耦合机理的研究尚未得到深入的研究；因此，本文建立了一套集建模、制作、验证、分析为一体的系统研究方法。首先，基于一阶剪切变形理论（FSDT）和分层之字形理论，建立了AHH-CSP结构的半解析动力学模型。其次，设计制作AHH-CSP试件，通过冲击试验确定其固有频率和模态振型；然后，结合有限元仿真、已有文献和实验结果验证了半解析模型的准确性和适用性，系统分析了蜂窝参数对结构振动特性的影响。结果表明：AHH-CSP结构的不同模态之间存在耦合振动，从而引起频率转向和模态振型交换，揭示了模态耦合的内在规律；研究结果为新型负泊松比蜂窝夹层板结构的工程应用提供了理论基础和实验支持。

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引用次数: 0

Free vibration analysis of in-plane bidirectional functionally graded plates with piezoelectric layers using RPT-IGA method 基于RPT-IGA法的压电层内双向功能梯度板自由振动分析

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

Advances in Engineering Software

Pub Date : 2026-04-01 Epub Date: 2026-02-10 DOI: 10.1016/j.advengsoft.2026.104122

Zhenyang Gao , Yaqiang Xue , Yuan Gao , Chunyu Zhang

The free vibration of in-plane bidirectional functionally graded plates with piezoelectric layers (FGPPL) is investigated in this study, where isogeometric analysis (IGA) in conjunction with refined plate theory (RPT) is utilized. This paper proposes an original transverse shear stress function through thickness distribution, formulated by sine and power functions. The RPT offers a computational advantage over the first-order shear deformation theory (FSDT) by describing the field displacement vector field with only four variables and avoiding shear correction factors, thus markedly diminishing the quantity of degrees of freedom. The non-uniform rational B-spline (NURBS) functions have strong modeling capability and high-order continuity, easily meeting the C¹ continuity requirement of the RPT model. Vibration characteristics of square, skew, and elliptical plates are explored by RPT-IGA method. A novel bidirectional functionally graded material distribution of skew plate is introduced. The convergence was benchmarked against existing research data. This study finds that boundary conditions, geometric parameters, and the graded index significantly affect the dynamic response of in-plane non-uniform FGPPL.

利用等几何分析（IGA）和精细板理论（RPT）相结合的方法，研究了平面内双向压电层功能梯度板（FGPPL）的自由振动。本文通过厚度分布提出了一个原始的横向剪应力函数，由正弦函数和幂函数表示。与一阶剪切变形理论（FSDT）相比，RPT具有计算优势，它仅用四个变量描述场位移矢量场，避免了剪切校正因素，从而显著减少了自由度的数量。非均匀有理b样条（NURBS）函数具有较强的建模能力和高阶连续性，容易满足RPT模型的C1连续性要求。采用RPT-IGA方法对方形、倾斜和椭圆板的振动特性进行了研究。介绍了一种新型的斜板双向功能梯度材料分布。这种收敛是根据现有的研究数据进行基准测试的。研究发现，边界条件、几何参数和梯度指数对面内非均匀FGPPL的动力响应有显著影响。

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引用次数: 0

Wrapper-based integration of a thermo-hydro-mechanical hypoplastic bentonite model in OpenGeoSys via MFront 基于包装的热-水-力学膨润土模型在OpenGeoSys中的集成

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

Advances in Engineering Software

Pub Date : 2026-04-01 Epub Date: 2026-01-29 DOI: 10.1016/j.advengsoft.2026.104106

Eric Simo , Thomas Helfer , Tymofiy Gerasimov , Christoph Lehmann , Dmitri Naumov , Tomas Krejci , Tomáš Koudelka , Jaroslav Kruis , Thomas Nagel , David Mašín

This paper presents the implementation of a hypoplastic thermo-hydro-mechanical constitutive model for bentonite into the OpenGeoSys (OGS) simulation platform using a wrapper-based interface with the MFront code generation tool. The model, originally developed as a stand-alone model in the Triax platform, features a double-structure formulation that captures micro- and macroscale interactions, as well as suction and temperature-dependent mechanical responses of bentonite relevant to engineered barrier systems in deep geological repositories (DGR). The integration strategy preserves the validated legacy implementation of the model while enabling its use within modern multiphysics simulations through a modular MFront wrapper. Verification is performed using single-element benchmarks in Triax and MTest, demonstrating numerical consistency. The implementation is validated by simulating two laboratory experiments on Czech bentonite (BCV), showing good agreement with experimental measurements and with reference results from the Sifel code. The developed interface provides a robust and flexible framework for coupling advanced bentonite models with large-scale geotechnical simulations for application in the integrity and performance assessments of bentonite barriers in the scope of safety assessment of DGR.

本文利用基于包装器的接口和MFront代码生成工具，在OpenGeoSys （OGS）仿真平台中实现了膨润土的低塑性热-水-力学本构模型。该模型最初是作为Triax平台上的一个独立模型开发的，具有双重结构配方，可以捕获微观和宏观尺度的相互作用，以及与深层地质储库（DGR）工程屏障系统相关的膨润土的吸力和温度相关的机械响应。集成策略保留了模型的有效遗留实现，同时通过模块化的MFront包装器使其能够在现代多物理场模拟中使用。验证是使用Triax和MTest中的单元素基准执行的，以证明数值一致性。通过模拟捷克膨润土（BCV）的两个实验室实验，验证了该方法的实现，结果与实验测量结果和Sifel规范的参考结果吻合良好。所开发的界面为将先进的膨润土模型与大规模岩土力学模拟相结合提供了一个强大而灵活的框架，可用于DGR安全评估范围内的膨润土屏障的完整性和性能评估。

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引用次数: 0