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Reference Architecture and Ontology Framework for Digital Twin Construction

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SSRN

SSRN 2024年

作者： Schlenger, Jonas Urs Pluta, Kacper Mathew, Alwyn Yeung, Timson Sacks, Rafael Borrmann, André Computational Modeling and Simulation School of Engineering and Design Technical University of Munich Arcisstraße 21 Munich80333 Germany Faculty of Civil and Environmental Engineering Technion - Israel Institute of Technology Haifa32000 Israel Université Gustave Eiffel CNRS LIGM Marne-la-ValléeF-77454 France Inria Université Côte d’Azur ValbonneF-06902 France University of Cambridge CambridgeCB3 0FA United Kingdom

Digital twins, revolutionizing product and process management in manufacturing and transportation industry, face integration challenges to their application to the process of building construction. A significant obstacle is the lack of guidance on implementing essential data management layers. We propose a novel reference architecture for digital twin construction, focusing on the internal data structures required to address this gap. The architecture provides a concept for managing planning information, raw monitoring data, and derived information and knowledge as a holistic system. Moreover, we introduce the Digital Twin Construction Ontology, forming the internal data schema needed for interoperability between platform services. Unlike existing ontologies, the DTC Ontology facilitates direct comparison of the planned project evolution with the project status. To assess the proposed data structures, we conducted a case study using the ConSLAM dataset. This study showcases the practicality and relevance of the developed system architecture and data structures in real-world settings. © 2024, The Authors. All rights reserved.

关键词： Interoperability

Physics informed neural networks for continuum micromechanics

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arXiv 2021年

作者： Henkes, Alexander Wessels, Henning Mahnken, Rolf Institute for Computational Modeling in Civil Engineering Technical University of Braunschweig Pockelsstr. 3 Braunschweig38106 Germany Chair of Engineering Mechanics University of Paderborn Warburger Str. 100 Paderborn33098 Germany

Recently, physics informed neural networks have successfully been applied to a broad variety of problems in applied mathematics and engineering. The principle idea is the usage of a neural network as a global ansatz function for partial differential equations. Due to the global approximation, physics informed neural networks have difficulties in displaying localized effects and strong nonlinear solution fields by optimization. In this work we consider nonlinear stress and displacement fields invoked by material inhomogeneities with sharp phase interfaces. This constitutes a challenging problem for a method relying on a global ansatz. To overcome convergence issues, adaptive training strategies and domain decomposition are studied. It is shown, that the domain decomposition approach is capable to accurately resolve nonlinear stress, displacement and energy fields in heterogeneous microstructures obtained from real-world µCT-scans. © 2021, CC BY.

关键词： Domain decomposition methods

Bending behavior of additively manufactured lattice structures: Numerical characterization and experimental validation

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arXiv 2021年

作者： Korshunova, Nina Alaimo, Gianluca Hosseini, Seyyed Bahram Carraturo, Massimo Reali, Alessandro Niiranen, Jarkko Auricchio, Ferdinando Rank, Ernst Kollmannsberger, Stefan Chair of Computational Modeling and Simulation Technische Universität München Germany Department of Civil Engineering and Architecture University of Pavia Italy Institute for Advanced Study Technische Universität München Germany Department of Civil Engineering Aalto University Finland

Selective Laser Melting (SLM) technology has undergone significant development in the past years providing unique flexibility for the fabrication of complex metamaterials such as octet-truss lattices. However, the microstructure of the final parts can exhibit significant variations due to the high complexity of the manufacturing process. Consequently, the mechanical behavior of these lattices is strongly dependent on the process-induced defects, raising the importance on the incorporation of as-manufactured geometries into the computational structural analysis. This, in turn, challenges the traditional mesh-conforming methods making the computational costs prohibitively large. In the present work, an immersed image-to-analysis framework is applied to efficiently evaluate the bending behavior of AM lattices. To this end, we employ the Finite Cell Method (FCM) to perform a three-dimensional numerical analysis of the three-point bending test of a lattice structure and compare the as-designed to as-manufactured effective properties. Furthermore, we undertake a comprehensive study on the applicability of dimensionally reduced beam models to the prediction of the bending behavior of lattice beams and validate classical and strain gradient beam theories applied in combination with the FCM. The numerical findings suggest that the SLM octet-truss lattices exhibit size effects, thus, requiring a flexible framework to incorporate high-order continuum theories. © 2021, CC BY-NC-ND.

关键词： Finite element method

The FluidFlower International Benchmark Study: Process, modeling Results, and Comparison to Experimental Data

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arXiv 2023年

作者： Flemisch, Bernd Nordbotten, Jan M. Fernø, Martin Juanes, Ruben Class, Holger Delshad, Mojdeh Doster, Florian Ennis-King, Jonathan Franc, Jacques Geiger, Sebastian Gläser, Dennis Green, Christopher Gunning, James Hajibeygi, Hadi Jackson, Samuel J. Jammoul, Mohamad Karra, Satish Li, Jiawei Matthäi, Stephan K. Miller, Terry Shao, Qi Spurin, Catherine Stauffer, Philip Tchelepi, Hamdi Tian, Xiaoming Viswanathan, Hari Voskov, Denis Wang, Yuhang Wapperom, Michiel Wheeler, Mary F. Wilkins, Andrew Youssef, AbdAllah A. Zhang, Ziliang Department of Hydromechanics and Modelling of Hydrosystems University of Stuttgart Stuttgart Germany Center for Modeling of Coupled Subsurface Dynamics Department of Mathematics University of Bergen Bergen Norway Center of Sustainable Subsurface Resources Norwegian Research Center Bergen Norway Department of Physics and Technology University of Bergen Bergen Norway Department of Civil and Environmental Engineering Massachusetts Institute of Technology CambridgeMA United States Center for Subsurface Modeling Oden Institute for Computational Engineering and Sciences The University of Texas at Austin AustinTX United States Institute of Geoenergy Engineering Heriot Watt University Edinburgh United Kingdom CSIRO Energy Clayton North Australia Department of Energy Science and Engineering Stanford University StanfordCA United States Department of Geoscience and Engineering Delft University of Technology Delft Netherlands Computational Earth Science Los Alamos National Laboratory Los AlamosNM United States Peter Cook Center for CCS Research Department of Infrastructure Engineering The University of Melbourne Parkville Australia CSIRO Mineral Resources Queensland Centre for Advanced Technologies Kenmore Australia

Successful deployment of geological carbon storage (GCS) requires an extensive use of reservoir simulators for screening, ranking and optimization of storage sites. However, the time scales of GCS are such that no sufficient long-term data is available yet to validate the simulators against. As a consequence, there is currently no solid basis for assessing the quality with which the dynamics of large-scale GCS operations can be forecasted. To meet this knowledge gap, we have conducted a major GCS validation benchmark study. To achieve reasonable time scales, a laboratory-size geological storage formation was constructed (the "FluidFlower"), forming the basis for both the experimental and computational work. A validation experiment consisting of repeated GCS operations was conducted in the FluidFlower, providing what we define as the true physical dynamics for this system. Nine different research groups from around the world provided forecasts, both individually and collaboratively, based on a detailed physical and petrophysical characterization of the FluidFlower sands. The major contribution of this paper is a report and discussion of the results of the validation benchmark study, complemented by a description of the benchmarking process and the participating computational models. The forecasts from the participating groups are compared to each other and to the experimental data by means of various indicative qualitative and quantitative measures. By this, we provide a detailed assessment of the capabilities of reservoir simulators and their users to capture both the injection and post-injection dynamics of the GCS operations. © 2023, CC BY-SA.

关键词： Digital storage

Parameter identification using finite elements and full-field data in the all-at-once context

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PAMM 2024年第3期24卷

作者： Stefan Hartmann Jendrik-Alexander Tröger Ulrich Römer Henning Wessels Institute of Applied Mechanics Clausthal University of Technology Clausthal-Zellerfeld Germany Institute for Acoustics and Dynamics Technische Universität Braunschweig Braunschweig Germany Institute for Computational Modeling in Civil Engineering Technische Universität Braunschweig Braunschweig Germany

Material parameter identification within the field of mechanics of materials is driven by different issues: experiments affecting the parameters, constitutive models describing the physical behavior of a material, discretization schemes for solving the initial boundary-value problem of the underlying tests, as well as schemes calibrating the parameters at experimental observations. Furthermore, the question of the quality of the parameters must be addressed. The result concerns the issue of which influence parameter uncertainties have on the uncertainty of simulation results and can be addressed during validation. In this contribution, we provide a short overview of concurrent approaches to identify the parameters, where most of the methods can be distinguished into the reduced formulation, which is based on the implicit function theorem, and a particular form of the all-at-once approach. The latter represents the weighted sum of two contributions, first, the distances between physical state equations and zero, and, second, the distance between model response (simulation result) and experimental data. Since the formulation of the all-at-once approach is not well-known in computational solid mechanics, it is investigated for the simple example of linear elasticity employing artificially noised data. It turns out that the all-at-once approach is not as robust as the well-established reduced approach, especially for problems considering full-field data. Moreover, a strong sensitivity to the noise and the initialization of the optimized parameters are observed indicating a pronounced ill-posedness of the all-at-once formulation for specific applications.

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Global sensitivity analysis based on Gaussian-process metamodelling for complex biomechanical problems

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arXiv 2022年

作者： Wirthl, Barbara Brandstaeter, Sebastian Nitzler, Jonas Schrefler, Bernhard A. Wall, Wolfgang A. Institute for Computational Mechanics Technical University of Munich Garching b. München Germany Institute of Continuum and Materials Mechanics Hamburg University of Technology Hamburg Germany Data-Driven Materials Modeling Technical University of Munich Garching b. München Germany Department of Civil Environmental and Architectural Engineering University of Padua Padua Italy Institute of Advanced Study Technical University of Munich Garching b. München Germany

Biomechanical models often need to describe very complex systems, organs or diseases, and hence also include a large number of parameters. One of the attractive features of physics-based models is that in those models (most) parameters have a clear physical meaning. Nevertheless, the determination of these parameters is often very elaborate and costly and shows a large scatter within the population. Hence, it is essential to identify the most important parameter (worth the effort) for a particular problem at hand. In order to distinguish parameters which have a significant influence on a specific model output from non-influential parameters, we use sensitivity analysis, in particular the Sobol method as a global variance-based method. However, the Sobol method requires a large number of model evaluations, which is prohibitive for computationally expensive models. We therefore employ Gaussian processes as a metamodel for the underlying full model. Metamodelling introduces further uncertainty, which we also quantify. We demonstrate the approach by applying it to two different problems: nanoparticle-mediated drug delivery in a complex, multiphase tumour-growth model, and arterial growth and remodelling. Even relatively small numbers of evaluations of the full model suffice to identify the influential parameters in both cases and to separate them from non-influential parameters. The approach also allows the quantification of higher-order interaction effects. We thus show that a variance-based global sensitivity analysis is feasible for complex, computationally expensive biomechanical models. Different aspects of sensitivity analysis are covered including a transparent declaration of the uncertainties involved in the estimation process. Such a global sensitivity analysis not only helps to massively reduce costs for experimental determination of parameters but is also highly beneficial for inverse analysis of such complex models. Copyright © 2022, The Authors. All rights

关键词： Sensitivity analysis

Corrigendum to “Asymptotically accurate and locking-free finite element implementation of first order shear deformation theory for plates” [Comput. Struct. 298 (2024) 107387]

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Computers & Structures 2024年 299卷

作者： K.C. Le H.-G. Bui Division of Computational Mechanics Institute for Advanced Study in Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Faculty of Civil Engineering Ton Duc Thang University Ho Chi Minh City Viet Nam Institute of Material Systems Modeling Helmholtz-Zentrum Hereon Geesthacht Germany

Prediction of Effluent Arsenic Concentration of Wastewater Treatment Plants Using Machine Learning and Kriging-Based Models

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Research Square

Research Square 2021年

作者： Zounemat-Kermani, Mohammad Alizamir, Meysam Keshtegar, Behrooz Batelaan, Okke Hinkelmann, Reinhard Department of Water Engineering Shahid Bahonar University of Kerman Kerman Iran Department of Civil Engineering Hamedan branch Islamic Azad University Hamedan Iran Division of Computational Mathematics and Engineering Institute for Computational Science Ton Duc Thang University Ho Chi Minh City Viet Nam National Centre for Groundwater Research and Training College of Science and Engineering Flinders University Adelaide Australia Chair of Water Resources Management and Modeling of Hydrosystems Technische Universität Berlin Berlin Germany

We evaluate the potential of kriging-based (kriging and kriging-logistic) and machine learning models (MARS, GBRT, and ANN) in predicting the effluent arsenic concentration of a wastewater treatment plant. Two distinct input combination scenarios were established, using seven quantitative and qualitative independent influent variables. In the first scenario, all of the seven independent variables were taken into account for constructing the data-driven models. For the second input scenario, we used the forward selection k-fold cross-validation method to select effective explanatory influent parameters. The results obtained from both input scenarios show that the kriging-logistic and machine learning models are effective and robust. However, using the feature selection procedure in the second scenario, made not only the architecture of the model simpler and more effective, but also enhanced the performance of the developed models. Although the standard kriging method failed to provide fair predictive results, it was revealed that the kriging-logistic method gave the best performance among the applied models. © 2021, CC BY.

关键词： Kriging

Image-based numerical characterization and experimental validation of tensile behavior of octet-truss lattice structures

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arXiv 2020年

作者： Korshunova, Nina Alaimo, Gianluca Hosseini, Seyyed Bahram Carraturo, Massimo Reali, Alessandro Niiranen, Jarkko Auricchio, Ferdinando Rank, Ernst Kollmannsberger, Stefan Chair of Computational Modeling and Simulation Technische Universität München Germany Department of Civil Engineering and Architecture University of Pavia Italy Department of Civil Engineering Aalto University Finland Institute for Advanced Study Technische Universität München Germany

The production of lightweight metal lattice structures has received much attention due to the recent developments in additive manufacturing (AM). The design flexibility comes, however, with the complexity of the underlying physics. In fact, metal additive manufacturing introduces process-induced geometrical defects that mainly result in deviations of the effective geometry from the nominal one. This change in the final printed shape is the primary cause of the gap between the as-designed and as-manufactured mechanical behavior of AM products. Thus, the possibility to incorporate the precise manufactured geometries into the computational analysis is crucial for the quality and performance assessment of the final parts. Computed tomography (CT) is an accurate method for the acquisition of the manufactured shape. However, it is often not feasible to integrate the CT-based geometrical information into the traditional computational analysis due to the complexity of the meshing procedure for such high-resolution geometrical models and the prohibitive numerical costs. In this work, an embedded numerical framework is applied to efficiently simulate and compare the mechanical behavior of as-designed to as-manufactured octet-truss lattice structures. The parts are produced using laser powder bed fusion (LPBF). Employing an immersed boundary method, namely the Finite Cell Method (FCM), we perform direct numerical simulations (DNS) and first-order numerical homogenization analysis of a tensile test for a 3D printed octet-truss structure. Numerical results based on CT scan (as-manufactured geometry) show an excellent agreement with experimental measurements, whereas both DNS and first-order numerical homogenization performed directly on the 3D virtual model (as-designed geometry) of the structure show a significant deviation from experimental data. © 2020, CC BY-NC-ND.

关键词： 3D printers