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arXiv 2021年

作者： Himpe, Christian Grundel, Sara Benner, Peter Computational Methods in Systems and Control Theory Group The Max Planck Institute for Dynamics of Complex Technical Systems Sandtorstraße 1 MagdeburgD-39106 Germany

To overcome many-query optimization, control, or uncertainty quantification work loads in reliable gas and energy network operations, model order reduction is the mathematical technology of choice. To this end, we enhance the model, solver and reductor components of the morgen platform, introduced in HIMPE ET AL [J. Math. Ind. 11:13, 2021], and conclude with a mathematically, numerically and computationally favorable model-solver-reductor ensemble. Copyright © 2021, The Authors. All rights reserved.

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Machine learning for material characterization with an application for predicting mechanical properties

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GAMM Mitteilungen 2021年第1期44卷 e202100003-e202100003页

作者： Stoll, Anke Benner, Peter Data-Mining and Machine Learning Fraunhofer Institute for Machine Tools and Forming Technology IWU Chemnitz Germany Computational Methods in Systems and Control Theory The Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany

Currently, the growth of material data from experiments and simulations is expanding beyond processable amounts. This makes the development of new data-driven methods for the discovery of patterns among multiple lengthscales and time-scales and structure-property relationships essential. These data-driven approaches show enormous promise within materials science. The following review covers machine learning (ML) applications for metallic material characterization. Many parameters associated with the processing and the structure of materials affect the properties and the performance of manufactured components. Thus, this study is an attempt to investigate the usefulness of ML methods for material property prediction. Material characteristics such as strength, toughness, hardness, brittleness, or ductility are relevant to categorize a material or component according to their quality. In industry, material tests like tensile tests, compression tests, or creep tests are often time consuming and expensive to perform. Therefore, the application of ML approaches is considered helpful for an easier generation of material property information. This study also gives an application of ML methods on small punch test (SPT) data for the determination of the property ultimate tensile strength for various materials. A strong correlation between SPT data and tensile test data was found which ultimately allows to replace more costly tests by simple and fast tests in combination with ML. © 2021 The Authors. GAMM - Mitteilungen published by Wiley-VCH GmbH.

关键词： Machine learning

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An artificial neural network for surrogate modeling of stress fields in viscoplastic polycrystalline materials

arXiv

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arXiv 2022年

作者： Khorrami, Mohammad S. Mianroodi, Jaber Rezaei Siboni, Nima H. Goyal, Pawan Svendsen, Bob Benner, Peter Raabe, Dierk Microstructure Physics and Alloy Design Max-Planck-Institut für Eisenforschung Düsseldorf Germany Computational Methods in Systems and Control Theory Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg Germany Material Mechanics RWTH Aachen University Aachen Germany

The purpose of this work is the development of an artificial neural network (ANN) for surrogate modeling of the mechanical response of viscoplastic grain microstructures. To this end, a U-Net-based convolutional neural network (CNN) is trained to account for the history dependence of the material behavior. The training data take the form of numerical simulation results for the von Mises stress field under quasi-static tensile loading. The trained CNN (tCNN) can accurately reproduce both the average response as well as the local von Mises stress field. The tCNN calculates the von Mises stress field of grain microstructures not included in the training dataset about 500 times faster than its calculation based on the numerical solution with a spectral solver of the corresponding initial-boundary-value problem. The tCNN is also successfully applied to other types of microstructure morphologies (e.g., matrix-inclusion type topologies) and loading levels not contained in the training dataset. Copyright © 2022, The Authors. All rights reserved.

关键词： Deep learning

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Large-scale analysis of energy system vulnerability using in-memory data grid 2

Large-scale analysis of energy system vulnerability using in...

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2nd International Workshop on Information, Computation, and control systems for Distributed Environments, ICCS-DE 2020

作者： Edelev, A.V. Sidorov, I.A. Gorsky, S.A. Feoktistov, A.G. Melentiev Energy Systems Institute Lermontov St. 130 Irkutsk664033 Russia Matrosov Institute for System Dynamics and Control Theory SB RAS Lermontov St. 134 Irkutsk664033 Russia

Nowadays, determining critical components of energy systems is a relevant problem. The complexity of its solving increases significantly when it is necessary to take into account the simultaneous failures of such components. Usually, in problem-solving, processing a large number of failure variants and their consequences is required. Processing such data using traditional relational database management systems does not allow us to quickly identify the most critical components. In the paper, our successful practical experience in applying an in-memory data grid within large-scale analyzing of the energy system vulnerability is provided. The experimental analysis showed the good scalability of distributed computing and significant reduction in data processing time compared to using an open-source SQL relational database management system. In developing and applying the distributed applied software package for solving the aforementioned problem we have used the Orlando Tools framework. Within its applying, we have implemented continuous integration of the package software taking into account the preparing and processing of subject-oriented data through the in-memory data grid. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Information management

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Application of high-performance computing for determining critical components of an energy system

Application of high-performance computing for determining cr...

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2020 Sustainable Development and Smart Management, ENERGY-21

作者： Edelev, Aleksey Feoktistov, Alexander Bychkov, Igor Basharina, Olga Melentiev Energy Systems Institute Sb Ras Lermontov St. 130 Irkutsk664033 Russia Matrosov Institute for System Dynamics and Control Theory Sb Ras Lermontov St. 134 Irkutsk664033 Russia

This article presents a package for analyzing the energy system vulnerability developed with new technology for continuous integration, delivery, and deployment of applied software. It implements a framework that allows combining and optimally using various methods for modelling energy systems and provides the comprehensive assessment of their vulnerability with regard to various uncertainties. The essential principles to identify and rank critical elements of an energy system are considered in the article. The investigations made with the package shown that the principles seem to be logical for the subsequent construction of the invariant set of measures for improving the energy system resilience. © The Authors, published by EDP Sciences, 2020.

关键词： Uncertainty analysis

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Identification of the energy system critical elements using the PARMONC library

Identification of the energy system critical elements using ...

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International Conference on Marchuk Scientific Readings 2020, MSR 2020

作者： Edelev, A.V. Marchenko, M.A. Basharina, O.Yu. Melentiev Energy Systems Institute SB RAS Lermontov St. 130 Irkutsk664033 Russia Institute of Computational Mathematics and Mathematical Geophysics SB RAS 6 Ac. Lavrentieva ave. Novosibirsk630090 Russia Novosibirsk State University Novosibirsk-90 2 630090 Russia Matrosov Institute for System Dynamics and Control Theory SB RAS Lermontov St. 134 Irkutsk664033 Russia

In this paper, we presented a Monte Carlo-based approach for vulnerability analyse of energy systems. For high-performance Monte Carlo simulation the PARMONC software library was used. The PARMONC is implemented on high-performance clusters of the Siberian Supercomputer Center. The PARMONC effectively launches parallel stochastic simulation on supercomputers with different architectures. The proposed approach was applied was applied for the identification and ranking the most important elements of a real-world natural gas supply system. © 2021 institute of Physics Publishing. All rights reserved.

关键词： Supercomputers

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Workbench for vulnerability analysis of Vietnam energy sector 3

Workbench for vulnerability analysis of Vietnam energy secto...

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3rd Scientific-Practical Workshop Information Technologies: Algorithms, Models, systems, ITAMS 2020

作者： Edelev, A.V. Fereferov, E.S. Hmelnov, A.E. Melentiev Energy Systems Institute of Siberian Branch of SB RAS Lermontov Str. 130 Irkutsk664033 Russia Matrosov Institute for System Dynamics and Control Theory of SB RAS 134 Lermontov St. Irkutsk664033 Russia

The paper addresses the problem of supporting research of the Vietnam energy sector vulnerability. The vulnerability study is understood as search for system weak points. A mathematical model has been developed to describe the energy sector of Vietnam. The model takes into account the characteristics and constraints of all objects of the energy sector: suppliers, consumers and the transport system. To study the vulnerability of the energy sector and make decisions, we have created a workbench that allows simulating increased loads and calculating the consequences. Specification-based database application development technology was applied to create the workbench. This technology allows you to quickly develop applications that provide interaction with databases and digital maps, as well as support interaction with external software modules. The main advantage of the proposed workbench is its flexibility and applicability at all stages of the study of the Vietnam energy sector vulnerability starting from gathering the energy operation and development information and ending with evaluation of satisfying demand in energy. © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Decision support systems

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A software platform to support the energy system resilience study 2

A software platform to support the energy system resilience ...

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2nd International Workshop on Information, Computation, and control systems for Distributed Environments, ICCS-DE 2020

作者： Edelev, A.V. Fereferov, E.S. Melentiev Energy Systems Institute of Siberian Branch of SB RAS Lermontov Str. 130 Irkutsk664033 Russia Matrosov Institute for System Dynamics and Control Theory of SB RAS Lermontov Str. 134 Irkutsk664033 Russia

The paper addresses the problem of supporting research of the energy systems resilience. The resilience is concerned with the energy system ability to withstand large disturbances. To reach the goal of creating user-friendly software for decision making support in that field, a software platform is considered. It includes some original frameworks for retrieving, gathering, querying and analysing data, and building thematic maps to produce disturbance scenarios and evaluate consequences of their impact. The main advantage of the proposed platform is its applicability for all the stages of the energy system resilience research starting from risk mitigation assessment and ending with comparing alternative recovering or reconstruction strategies. Copyright © 2020 for this paper by its authors. Use permitted under Creative Commons License Attribution 4.0 International (CC BY 4.0).

关键词： Decision making

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PD controllers to solve single-input, index-1 DAE based LQR problems

PD controllers to solve single-input, index-1 DAE based LQR ...

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European control Conference (ECC)

作者： Chayan Bhawal Jan Heiland Peter Benner Department of Computational Methods in Systems and Control Theory Max Planck Institute for Dynamics of Complex Technical Systems Magdeburg

ISBN: (数字)9783907144022

ISBN: (纸本)9781728188133

In this paper, we present a method to compute the optimal trajectories of a linear quadratic regulator (LQR) problem corresponding to a single input, index-1 constant coefficient DAE system. Further, we also show that using a suitably designed proportional-derivative (PD) state-feedback controller one can force the trajectories of the corresponding DAE system to its optimal trajectories. Unlike the results present in the literature, the results in this paper are applicable for any arbitrary initial condition of the system.

关键词： Trajectory Indexes Matrix converters PD control Optimal control Regulators controllability

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On the loss of orthogonality in low-synchronization variants of reorthogonalized block classical Gram-Schmidt

arXiv

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arXiv 2024年

作者： Carson, Erin Lund, Kathryn Ma, Yuxin Oktay, Eda Department of Numerical Mathematics Faculty of Mathematics and Physics Charles University Sokolovská 49/83 Praha 8186 75 Czech Republic Computational Mathematics Theme Building R71 STFC Rutherford Appleton Laboratory Harwell Oxford Didcot OxfordshireOX11 0QX United Kingdom Computational Methods in Systems and Control Theory Max Planck Institute for Dynamics of Complex Technical Systems Sandtorstr. 1 Magdeburg39106 Germany Department of Mathematics Chemnitz University of Technology Reichenhainer Str. 41 Chemnitz09126 Germany

Interest in communication-avoiding orthogonalization schemes for high-performance computing has been growing recently. This manuscript addresses open questions about the numerical stability of various block classical Gram-Schmidt variants that have been proposed in the past few years. An abstract framework is employed, the flexibility of which allows for new rigorous bounds on the loss of orthogonality in these variants. We first analyze a generalization of (reorthogonalized) block classical Gram-Schmidt and show that a "strong" intrablock orthogonalization routine is only needed for the very first block in order to maintain orthogonality on the level of the unit roundoff. Then, using this variant, which has four synchronization points per block column, we remove the synchronization points one at a time and analyze how each alteration affects the stability of the resulting method. Our analysis shows that the variant requiring only one synchronization per block column cannot be guaranteed to be stable in practice, as stability begins to degrade with the first reduction of synchronization points. Our analysis of block methods also provides new theoretical results for the single-column case. In particular, it is proven that DCGS2 from [Bielich, D. et al. Par. Comput. 112 (2022)] and CGS-2 from [Świrydowicz, K. et al, Num. Lin. Alg. Appl. 28 (2021)] are as stable as Householder QR. Numerical examples from the BlockStab toolbox are included throughout, to help compare variants and illustrate the effects of different choices of intraorthogonalization *** Codes 65-04, 65F25, 65G50, 65Y20 Copyright © 2024, The Authors. All rights reserved.

关键词： Subroutines

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