arXiv - CS - Computational Engineering, Finance, and Science最新文献_第4页

Data-driven methods for computational mechanics: A fair comparison between neural networks based and model-free approaches 计算力学的数据驱动方法：基于神经网络的方法与无模型方法的公平比较

arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2024-08-27 DOI: arxiv-2409.06727

Martin Zlatić, Felipe Rocha, Laurent Stainier, Marko Čanađija

{"title":"Data-driven methods for computational mechanics: A fair comparison between neural networks based and model-free approaches","authors":"Martin Zlatić, Felipe Rocha, Laurent Stainier, Marko Čanađija","doi":"arxiv-2409.06727","DOIUrl":"https://doi.org/arxiv-2409.06727","url":null,"abstract":"We present a comparison between two approaches to modelling hyperelastic\u0000material behaviour using data. The first approach is a novel approach based on\u0000Data-driven Computational Mechanics (DDCM) that completely bypasses the\u0000definition of a material model by using only data from simulations or real-life\u0000experiments to perform computations. The second is a neural network (NN) based\u0000approach, where a neural network is used as a constitutive model. It is trained\u0000on data to learn the underlying material behaviour and is implemented in the\u0000same way as conventional models. The DDCM approach has been extended to include\u0000strategies for recovering isotropic behaviour and local smoothing of data.\u0000These have proven to be critical in certain cases and increase accuracy in most\u0000cases. The NN approach contains certain elements to enforce principles such as\u0000material symmetry, thermodynamic consistency, and convexity. In order to\u0000provide a fair comparison between the approaches, they use the same data and\u0000solve the same numerical problems with a selection of problems highlighting the\u0000advantages and disadvantages of each approach. Both the DDCM and the NNs have\u0000shown acceptable performance. The DDCM performed better when applied to cases\u0000similar to those from which the data is gathered from, albeit at the expense of\u0000generality, whereas NN models were more advantageous when applied to wider\u0000range of applications.","PeriodicalId":501309,"journal":{"name":"arXiv - CS - Computational Engineering, Finance, and Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211280","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Epidemic Information Extraction for Event-Based Surveillance using Large Language Models 利用大型语言模型为基于事件的监控提取流行病信息

arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2024-08-26 DOI: arxiv-2408.14277

Sergio Consoli, Peter Markov, Nikolaos I. Stilianakis, Lorenzo Bertolini, Antonio Puertas Gallardo, Mario Ceresa

引用次数: 0

Efficient FGM optimization with a novel design space and DeepONet 利用新型设计空间和 DeepONet 高效优化烟气脱硫装置

arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2024-08-26 DOI: arxiv-2408.14203

Piyush Agrawal, Ihina Mahajan, Shivam Choubey, Manish Agrawal

{"title":"Efficient FGM optimization with a novel design space and DeepONet","authors":"Piyush Agrawal, Ihina Mahajan, Shivam Choubey, Manish Agrawal","doi":"arxiv-2408.14203","DOIUrl":"https://doi.org/arxiv-2408.14203","url":null,"abstract":"This manuscript proposes an optimization framework to find the tailor-made\u0000functionally graded material (FGM) profiles for thermoelastic applications.\u0000This optimization framework consists of (1) a random profile generation scheme,\u0000(2) deep learning (DL) based surrogate models for the prediction of thermal and\u0000structural quantities, and (3) a genetic algorithm (GA). From the proposed\u0000random profile generation scheme, we strive for a generic design space that\u0000does not contain impractical designs, i.e., profiles with sharp gradations. We\u0000also show that the power law is a strict subset of the proposed design space.\u0000We use a dense neural network-based surrogate model for the prediction of\u0000maximum stress, while the deep neural operator DeepONet is used for the\u0000prediction of the thermal field. The point-wise effective prediction of the\u0000thermal field enables us to implement the constraint that the metallic content\u0000of the FGM remains within a specified limit. The integration of the profile\u0000generation scheme and DL-based surrogate models with GA provides us with an\u0000efficient optimization scheme. The efficacy of the proposed framework is\u0000demonstrated through various numerical examples.","PeriodicalId":501309,"journal":{"name":"arXiv - CS - Computational Engineering, Finance, and Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211281","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Automated model discovery of finite strain elastoplasticity from uniaxial experiments 从单轴实验中自动发现有限应变弹塑性模型

arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2024-08-26 DOI: arxiv-2408.14615

Asghar A. Jadoon, Knut A. Meyer, Jan N. Fuhg

{"title":"Automated model discovery of finite strain elastoplasticity from uniaxial experiments","authors":"Asghar A. Jadoon, Knut A. Meyer, Jan N. Fuhg","doi":"arxiv-2408.14615","DOIUrl":"https://doi.org/arxiv-2408.14615","url":null,"abstract":"Constitutive modeling lies at the core of mechanics, allowing us to map\u0000strains onto stresses for a material in a given mechanical setting.\u0000Historically, researchers relied on phenomenological modeling where simple\u0000mathematical relationships were derived through experimentation and curve\u0000fitting. Recently, to automate the constitutive modeling process, data-driven\u0000approaches based on neural networks have been explored. While initial naive\u0000approaches violated established mechanical principles, recent efforts\u0000concentrate on designing neural network architectures that incorporate physics\u0000and mechanistic assumptions into machine-learning-based constitutive models.\u0000For history-dependent materials, these models have so far predominantly been\u0000restricted to small-strain formulations. In this work, we develop a finite\u0000strain plasticity formulation based on thermodynamic potentials to model mixed\u0000isotropic and kinematic hardening. We then leverage physics-augmented neural\u0000networks to automate the discovery of thermodynamically consistent constitutive\u0000models of finite strain elastoplasticity from uniaxial experiments. We apply\u0000the framework to both synthetic and experimental data, demonstrating its\u0000ability to capture complex material behavior under cyclic uniaxial loading.\u0000Furthermore, we show that the neural network enhanced model trains easier than\u0000traditional phenomenological models as it is less sensitive to varying initial\u0000seeds. our model's ability to generalize beyond the training set underscores\u0000its robustness and predictive power. By automating the discovery of hardening\u0000models, our approach eliminates user bias and ensures that the resulting\u0000constitutive model complies with thermodynamic principles, thus offering a more\u0000systematic and physics-informed framework.","PeriodicalId":501309,"journal":{"name":"arXiv - CS - Computational Engineering, Finance, and Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211239","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An optimization-based coupling of reduced order models with efficient reduced adjoint basis generation approach 基于优化的减阶模型耦合与高效减阶邻接基生成方法

arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2024-08-26 DOI: arxiv-2408.14450

Elizabeth Hawkins, Paul Kuberry, Pavel Bochev

{"title":"An optimization-based coupling of reduced order models with efficient reduced adjoint basis generation approach","authors":"Elizabeth Hawkins, Paul Kuberry, Pavel Bochev","doi":"arxiv-2408.14450","DOIUrl":"https://doi.org/arxiv-2408.14450","url":null,"abstract":"Optimization-based coupling (OBC) is an attractive alternative to traditional\u0000Lagrange multiplier approaches in multiple modeling and simulation contexts.\u0000However, application of OBC to time-dependent problem has been hindered by the\u0000computational costs of finding the stationary points of the associated\u0000Lagrangian, which requires primal and adjoint solves. This issue can be\u0000mitigated by using OBC in conjunction with computationally efficient reduced\u0000order models (ROM). To demonstrate the potential of this combination, in this\u0000paper we develop an optimization-based ROM-ROM coupling for a transient\u0000advection-diffusion transmission problem. The main challenge in this\u0000formulation is the generation of adjoint snapshots and reduced bases for the\u0000adjoint systems required by the optimizer. One of the main contributions of the\u0000paper is a new technique for efficient adjoint snapshot collection for\u0000gradient-based optimizers in the context of optimization-based ROM-ROM\u0000couplings. We present numerical studies demonstrating the accuracy of the\u0000approach along with comparison between various approaches for selecting a\u0000reduced order basis for the adjoint systems, including decay of snapshot\u0000energy, iteration counts, and timings.","PeriodicalId":501309,"journal":{"name":"arXiv - CS - Computational Engineering, Finance, and Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

FFT-based surrogate modeling of auxetic metamaterials with real-time prediction of effective elastic properties and swift inverse design 基于 FFT 的辅助超材料代用建模，可实时预测有效弹性特性并快速进行逆向设计

arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2024-08-24 DOI: arxiv-2408.13532

Hooman Danesh, Daniele Di Lorenzo, Francisco Chinesta, Stefanie Reese, Tim Brepols

{"title":"FFT-based surrogate modeling of auxetic metamaterials with real-time prediction of effective elastic properties and swift inverse design","authors":"Hooman Danesh, Daniele Di Lorenzo, Francisco Chinesta, Stefanie Reese, Tim Brepols","doi":"arxiv-2408.13532","DOIUrl":"https://doi.org/arxiv-2408.13532","url":null,"abstract":"Auxetic structures, known for their negative Poisson's ratio, exhibit\u0000effective elastic properties heavily influenced by their underlying structural\u0000geometry and base material properties. While periodic homogenization of auxetic\u0000unit cells can be used to investigate these properties, it is computationally\u0000expensive and limits design space exploration and inverse analysis. In this\u0000paper, surrogate models are developed for the real-time prediction of the\u0000effective elastic properties of auxetic unit cells with orthogonal voids of\u0000different shapes. The unit cells feature orthogonal voids in four distinct\u0000shapes, including rectangular, diamond, oval, and peanut-shaped voids, each\u0000characterized by specific void diameters. The generated surrogate models accept\u0000geometric parameters and the elastic properties of the base material as inputs\u0000to predict the effective elastic constants in real-time. This rapid evaluation\u0000enables a practical inverse analysis framework for obtaining the optimal design\u0000parameters that yield the desired effective response. The fast Fourier\u0000transform (FFT)-based homogenization approach is adopted to efficiently\u0000generate data for developing the surrogate models, bypassing concerns about\u0000periodic mesh generation and boundary conditions typically associated with the\u0000finite element method (FEM). The performance of the generated surrogate models\u0000is rigorously examined through a train/test split methodology, a parametric\u0000study, and an inverse problem. Finally, a graphical user interface (GUI) is\u0000developed, offering real-time prediction of the effective tangent stiffness and\u0000performing inverse analysis to determine optimal geometric parameters.","PeriodicalId":501309,"journal":{"name":"arXiv - CS - Computational Engineering, Finance, and Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227898","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

STAResNet: a Network in Spacetime Algebra to solve Maxwell's PDEs STAResNet：用于求解麦克斯韦 PDE 的时空代数网络

arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2024-08-24 DOI: arxiv-2408.13619

Alberto Pepe, Sven Buchholz, Joan Lasenby

{"title":"STAResNet: a Network in Spacetime Algebra to solve Maxwell's PDEs","authors":"Alberto Pepe, Sven Buchholz, Joan Lasenby","doi":"arxiv-2408.13619","DOIUrl":"https://doi.org/arxiv-2408.13619","url":null,"abstract":"We introduce STAResNet, a ResNet architecture in Spacetime Algebra (STA) to\u0000solve Maxwell's partial differential equations (PDEs). Recently, networks in\u0000Geometric Algebra (GA) have been demonstrated to be an asset for truly\u0000geometric machine learning. In cite{brandstetter2022clifford}, GA networks\u0000have been employed for the first time to solve partial differential equations\u0000(PDEs), demonstrating an increased accuracy over real-valued networks. In this\u0000work we solve Maxwell's PDEs both in GA and STA employing the same ResNet\u0000architecture and dataset, to discuss the impact that the choice of the right\u0000algebra has on the accuracy of GA networks. Our study on STAResNet shows how\u0000the correct geometric embedding in Clifford Networks gives a mean square error\u0000(MSE), between ground truth and estimated fields, up to 2.6 times lower than\u0000than obtained with a standard Clifford ResNet with 6 times fewer trainable\u0000parameters. STAREsNet demonstrates consistently lower MSE and higher\u0000correlation regardless of scenario. The scenarios tested are: sampling period\u0000of the dataset; presence of obstacles with either seen or unseen\u0000configurations; the number of channels in the ResNet architecture; the number\u0000of rollout steps; whether the field is in 2D or 3D space. This demonstrates how\u0000choosing the right algebra in Clifford networks is a crucial factor for more\u0000compact, accurate, descriptive and better generalising pipelines.","PeriodicalId":501309,"journal":{"name":"arXiv - CS - Computational Engineering, Finance, and Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211242","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extremal Structures with Embedded Pre-Failure Indicators 嵌入失效前指标的极端结构

arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2024-08-23 DOI: arxiv-2408.13113

Christoffer Fyllgraf Christensen, Jonas Engqvist, Fengwen Wang, Ole Sigmund, Mathias Wallin

{"title":"Extremal Structures with Embedded Pre-Failure Indicators","authors":"Christoffer Fyllgraf Christensen, Jonas Engqvist, Fengwen Wang, Ole Sigmund, Mathias Wallin","doi":"arxiv-2408.13113","DOIUrl":"https://doi.org/arxiv-2408.13113","url":null,"abstract":"Preemptive identification of potential failure under loading of engineering\u0000structures is a critical challenge. Our study presents an innovative approach\u0000to built-in pre-failure indicators within multiscale structural designs\u0000utilizing the design freedom of topology optimization. The indicators are\u0000engineered to visibly signal load conditions approaching the global critical\u0000buckling load. By showing non-critical local buckling when activated, the\u0000indicators provide early warning without compromising the overall structural\u0000integrity of the design. This proactive safety feature enhances design\u0000reliability. With multiscale analysis, macroscale stresses are related to\u0000microscale buckling stability. This relationship is applied through tailored\u0000stress constraints to prevent local buckling in general while deliberately\u0000triggering it at predefined locations under specific load conditions.\u0000Experimental testing of 3D-printed designs confirms a strong correlation with\u0000numerical simulations. This not only demonstrates the feasibility of creating\u0000structures that can signal the need for load reduction or maintenance but also\u0000significantly narrows the gap between theoretical optimization models and their\u0000practical application. This research contributes to the design of safer\u0000structures by introducing built-in early-warning failure systems.","PeriodicalId":501309,"journal":{"name":"arXiv - CS - Computational Engineering, Finance, and Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211295","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A manifold learning approach to nonlinear model order reduction of quasi-static problems in solid mechanics 固体力学中准静态问题的非线性模型阶次缩减的流形学习方法

arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2024-08-22 DOI: arxiv-2408.12415

Lisa Scheunemann, Erik Faust

{"title":"A manifold learning approach to nonlinear model order reduction of quasi-static problems in solid mechanics","authors":"Lisa Scheunemann, Erik Faust","doi":"arxiv-2408.12415","DOIUrl":"https://doi.org/arxiv-2408.12415","url":null,"abstract":"The proper orthogonal decomposition (POD) -- a popular projection-based model\u0000order reduction (MOR) method -- may require significant model dimensionalities\u0000to successfully capture a nonlinear solution manifold resulting from a\u0000parameterised quasi-static solid-mechanical problem. The local basis method by\u0000Amsallem et al. [1] addresses this deficiency by introducing a locally, rather\u0000than globally, linear approximation of the solution manifold. However, this\u0000generally successful approach comes with some limitations, especially in the\u0000data-poor setting. In this proof-of-concept investigation, we instead propose a\u0000graph-based manifold learning approach to nonlinear projection-based MOR which\u0000uses a global, continuously nonlinear approximation of the solution manifold.\u0000Approximations of local tangents to the solution manifold, which are necessary\u0000for a Galerkin scheme, are computed in the online phase. As an example\u0000application for the resulting nonlinear MOR algorithms, we consider simple\u0000representative volume element computations. On this example, the manifold\u0000learning approach Pareto-dominates the POD and local basis method in terms of\u0000the error and runtime achieved using a range of model dimensionalities.","PeriodicalId":501309,"journal":{"name":"arXiv - CS - Computational Engineering, Finance, and Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142211282","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The continuous accumulation of civilization core in the cycle of elements-creature, benefits and weapons 文明核心在要素--生物、利益和武器--循环中不断积累

arXiv - CS - Computational Engineering, Finance, and Science Pub Date : 2024-08-21 DOI: arxiv-2408.11317

Hongfa Zi, Zhen Liu

{"title":"The continuous accumulation of civilization core in the cycle of elements-creature, benefits and weapons","authors":"Hongfa Zi, Zhen Liu","doi":"arxiv-2408.11317","DOIUrl":"https://doi.org/arxiv-2408.11317","url":null,"abstract":"The comprehensive strength of a country varies from strong to weak, divided\u0000into three condition: descending, periodicity destruction or rapidly rising,\u0000Exploring the differences can solve the development crisis. the most important\u0000things for a country are interests, weapons and creature, corresponding to\u0000money, technology and people. The ship industry has two attribute of financial\u0000benefits and technological weapons. Commercial ships can transport massive\u0000commodity and warships carry updating of massive technological weapons; But a\u0000new core: equity incentives have emerged, and it has helped the rapid\u0000development of the computer industry. This article uses comparative analysis\u0000and comparative historical analysis to observe the changes in the United States\u0000and China after the mutual circulation of two elements and the double\u0000circulation of three elements in history, such as the growth rates of GDP and\u0000patent applications. Then, it summarizes the changes brought by the core of\u0000civilization to the country.Through this article, it can be concluded that the\u0000core of civilization consists of ships and equity incentives; Through the\u0000circulation of new elements, a country can transform into civilizations with\u0000three cycles, achieving mutual circulation among the three and enhancing\u0000endogenous power; The core of civilization can enhance the stability of\u0000economic development, prevent economic crises, and achieve a more balanced\u0000civilization.","PeriodicalId":501309,"journal":{"name":"arXiv - CS - Computational Engineering, Finance, and Science","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2024-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142227903","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0