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2022 IEEE International Multi-Conference on Engineering, Computer and Information Sciences, SIBIRCON 2022

作者： Markov, Sergey I. Shurina, Ella P. Itkina, Natalya B. Trofimuk Institute of Petroleum Geology and Geophysics SB RAS Lab. of Math. Modeling of Multiphysics Phenomena in Native and Artif. Multiscale Heterogeneous Media Department of Computer Technologies Novosibirsk State Technical University Novosibirsk Russia Laboratory of Analysis and Optimization of Nonlinear Systems Institute of Computational Technologies Novosibirsk State Technical University SB RAS Department of Computer Technologies Novosibirsk Russia

ISBN: (纸本)9781665464802

This work deals with the problem of reconstructing the thermal conductivity coefficient of ice-gas-hydrate rocks. It is proposed to use the results of direct mathematical simulation of heat transfer processes in a heterogeneous porous medium with different phase composition, and the principles of energy conservation law. The results of high-resolution X-ray tomography are applied to construct a digital model of the gas-hydrate-containing medium using machine learning procedure and special thresholding methods. A discrete geometrical model of the digital model is constructed by methods based on adapted symplectic partitions. In contrast to existing solutions to the above problem, our approach is not based on the application of phenomenological reduced models. We apply continuum models of the medium under study, and the heat transfer process. This approach makes it possible to obtain physically relevant results for determining the thermal conductivity coefficient of a heterogeneous medium using its digital analogue. The influence of the phase composition and contrast of the thermal characteristics on the value of thermal conductivity coefficient of ice-gas-hydrate-containing samples is presented. © 2022 IEEE.

关键词： Porous materials

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Coupled electromagnetic and thermoelastic response of conductive materials under mechanical loading and high current pulse conditions 41

Coupled electromagnetic and thermoelastic response of conduc...

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41st Computers and Information in Engineering Conference, CIE 2021, Held as Part of the ASME 2021 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference, IDETC-CIE 2021

作者： Michopoulos, J.G. Iliopoulos, A.P. Steuben, J.C. Apetre, N.A. Douglass, S. Lynn, A.G. Cairns, R.L. Computational Multiphysics Systems Lab. Code 6394 Center of Materials Physics and Technology U.S. Naval Research Laboratory WashingtonDC20375 United States Plasma Physics Division Code 6752 U.S. Naval Research Laboratory WashingtonDC20375 United States Alion Science and Technology McLeanVA221025 United States

ISBN: (纸本)9780791885376

Understanding, modeling and simulating the behavior of thermally and electrically conductive materials under simultaneous high electric current pulse and mechanical preload conditions has long been a topic of interest for various applications involving electromechanical systems. To this end, the present work describes a computational framework that enables the fully coupled electromagnetic and thermoelastic analysis of such systems. The partial differential equations (PDEs) representing the electrodynamic and thermodynamic conservation laws are utilized and encapsulated in a computational environment enabling their numerical solution. A specific contribution of the framework is that it is capable of solving the non-linear forms of the relevant PDEs that are formed due to the dependence of the material properties on state variables such as temperature. The proposed framework is applied for a specific high-current testing apparatus under construction in our laboratory. A high current pulse is conducted through a mechanically pretensioned specimen and generates Joule heating activating thermo-elastic strains in conjunction with Lorentz body forces influencing the associated dynamic thermo-structural response of specimens of interest. Application of the developed framework enables the generation of field predictions for the quantities of interest. Selective simulation results are presented to demonstrate the capabilities of the proposed framework followed by discussion and conclusions. Copyright © 2021 by The United States Government

关键词： Conductive materials

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Performance signature qualification for additively manufactured parts under conditions emulating in-service loading 3

Performance signature qualification for additively manufactu...

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3rd ASTM Symposium on Structural Integrity of Additive Manufactured Parts

作者： Michopoulos, John G. Steuben, John C. Iliopoulos, Athanasios P. Nguyen, Trung Phan, Nam Computational Multiphysics Systems Lab U.S. Naval Research Laboratory Code 6394 WashingtonDC20375 United States Structures Division Naval Air Systems Command 48110 Shaw Rd. Patuxent RiverMD20670 United States

ISBN: (纸本)9780803176867

The micro- and meso-scale material morphologies generated by additive manufacturing (AM) processes can differ remarkably from those arising from conventional manufacturing (CM) methods. A consequence of this fact is the substandard functional performance of the produced parts that can limit the use of AM in some applications. In the present work, a rapid functional qualification methodology for AM-produced parts is presented. This method is based on a concept defined as absolute and differential performance signature qualification. The concept of performance signature (PerSig) is introduced both as a vector of featured quantities of interest (QoIs) and as a graphic representation in the form of radar or spider graph, representing the QoIs associated with the performance of relevant parts. The PerSigs are defined for both the prequalified CM parts and the AM-produced parts. Comparison measures are defined and enable the construction of differential PerSigs (dPerSig) in a manner that captures the differential performance of the AM part versus the prequalified CM one. The dPerSigs enable AM part qualification based on how their PerSigs are different from those of prequalified CM parts. After defining the steps of the proposed methodology, a description of its application is given for a part of an aircraft landing gear assembly and demonstrate its feasibility for the case of static loads. Furthermore, the extension of this methodology is introduced for a multiaxial loading environment intended to reproduce the proper loading conditions of more complex structures, by using the custom-designed six degrees of freedom testing frames. © 2020 ASTM International.

关键词： 3D printers

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Inference and prediction of nanoindentation response in FCC crystals: Methods and discrete dislocation simulation examples

arXiv

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arXiv 2019年

作者： Tzimas, M. Michopoulos, J. Po, G. Reid, A.C.E. Papanikolaou, S. Department of Mechanical & Aerospace Engineering West Virginia University MorgantownWV United States Computational Multiphysics Systems Lab U.S. Naval Research Laboratory WashingtonDC Department of Mechanical Engineering University of Miami FL United States Material Measurement Laboratory National Institute of Standards and Technology GaithersburgMD United States Department of Physics & Astronomy West Virginia University MorgantownWV United States

Nanoindentation, a common technique for probing the mechanical properties of crystalline materials, exhibits both surface and bulk-dominated responses that are linked to the parent crystal's elasticity and plasticity. For FCC crystals, the nanoindentation response is primarily controlled by the indented-grain's crystalline orientation and dislocation density. However, the indentation properties, such as hardness, have ambiguous significance at the nanoscale due to tip-specific size effects. Through extensive discrete dislocation dynamics simulations of flat-punch nanoindentation on FCC single crystals, we show that a one-to-one correspondence between an indented location and the pre-existing dislocation density is possible with the help of statistical, machine-learning algorithms. We cluster and classify various experimentally plausible ensembles with varying dislocation density and/or crystalline orientation, using nanoindentation force-depth curves or post-indent surface displacement images. We use this classification to statistically predict the nanoindentation response of a given location, through the average response of classified load-displacement curves. In addition, we demonstrate that our simulation results qualitatively agree with experimental data on common FCC single crystals. Ultimately, we propose a novel pathway to uncover the depth dependence of local surface material properties for more complete, non-destructive, microstructural characterization, through nanoindentation. Copyright © 2019, The Authors. All rights reserved.

关键词： Machine learning

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Towards data-driven modeling and simulation of multiphysics degrading systems 16

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16th European Conference of Fracture

作者： Michopoulos, J.G. Farhat, C. Computational Multiphysics Systems Lab Center for Computational Material Science Special Projects Group WashingtonDC20375 United States Department of Mechanical Engineering Institute for Computational and Mathematical Engineering Stanford University StanfordCA94305 United States

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computational parameterization simplicity and filtering of data-driven inverse analysis for heat deposition processes

Computational parameterization simplicity and filtering of d...

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2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006

作者： Lambrakos, S.G. Michopoulos, J.G. Code 6390 Center for Computational Material Science Naval Research Laboratory Washington DC 20375 United States Computational Multiphysics Systems Lab. Special Projects Group Center for Computational Material Science Washington DC 20375 United States

ISBN: (纸本)079183784X

This paper underscores two important computational aspects associated with algorithms for data-driven inverse analysis and characterization of heat deposition processes. The first involves the fact that the mathematical foundation of these algorithms suggests that a very large class of temperature fields, associated with different types of heat deposition processes and different domain geometries can be represented parametrically by a relatively small set of functions. They include linear combinations of solutions to the heat conduction equation. Issues concerning the use of algorithms based on different types of parametric representations related to different types of heat deposition processes are discussed. A prototype analysis is presented to demonstrate many characteristics of these algorithms that are significant for their practical application. The second aspect relates to the filtering property of inversion itself due to the nature of the kernel function involved with the description of the heat source. Both of these aspects are crucially beneficial to developing methodologies that effect the real-time dynamic data-driven production parameter adjustments of manufacturing processes involving heat deposition. Copyright © 2006 by ASME.

关键词： computational geometry

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On data-driven modeling and simulation of aero-thermo-mechanically degrading nonlinear continuum systems

On data-driven modeling and simulation of aero-thermo-mechan...

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2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006

作者： Michopoulos, J.G. Farhat, C. Bou-Mosleh, C. Computational Multiphysics Systems Lab. Special Projects Group Center for Computational Material Science Washington DC 20375 United States Department of Mechanical Engineering Institute for Computational and Mathematical Engineering Stanford University Stanford CA 94305 United States

ISBN: (纸本)079183784X

Recent advances on data-driven application systems, sensor and computational technologies as well as long-term needs for efficient and accurate systemic behavior prediction monitoring in the context of realistic system design and maintenance, have brought degrading continuum systems modeling and simulation in the forefront of our activities. This paper outlines the initial steps of a methodology for applying a data-driven inverse-problem approach on the area of modeling mass-conserving degrading thermo-mechanical multi-domain nonlinear continuum structural and material systems. The methodology is applied for composite materials under simultaneous mechanical and thermal multi-field excitation and is based on mechatronic and computational automation. Furthermore, the multi-domain multiphysics modeling necessary for addressing the fluid-structure interaction involved in such systems is also discussed in the context of jet platforms with aerodynamically induced heating. Finally, simulation demonstrations are presented for the F-16 fighter jet and for a sensor-driven data solution reconstruction of an aircraft wing to demonstrate the potential for developing a material and structural health monitoring system based on he concept of dissipated energy density as a material health metric. Copyright © 2006 by ASME.

关键词： Continuum mechanics

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Effect of loading path and specimen shape on inverse identification of elastic properties of composites

Effect of loading path and specimen shape on inverse identif...

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2006 ASME International Design Engineering Technical Conferences and Computers and Information In Engineering Conference, DETC2006

作者： Michopoulos, J.G. Furukawa, T. Computational Multiphysics Systems Lab. Center for Computational Material Science Special Projects Group Washington DC 20375 United States School of Mechanical and Manufacturing Engineering University of New South Wales NSW 2052 Australia

ISBN: (纸本)079183784X

This paper presents a methodology for using sensor-generated data from multi-degree-of-freedom mechatronic loading systems to identify the elastic moduli of a composite laminate material system. This is done not to demonstrate the method itself but rather to study how various features of the experimental and analytical procedure can affect the identification process. The analytical formulation of the identification problem is described first given the geometry of a test specimen and a loading path. The concept of singular value decomposition (associated with pseudo inversion factorization) is introduced for the purpose of parameter identification as it applies to the elastic moduli. Also, the concepts of distinguishability and uniqueness are introduced to evaluate the quality of parameter identification. The analysis is performed on a continuum model basis in order to evaluate if the proposed technique can work for specimens of arbitrary shape. Elastic coefficients were identified using pseudo-experimental (numerically synthesized) data created by finite element analysis (FEA) and the effect of the introduced distinguishability and uniqueness on the identification was investigated through several numerical examples. The effects of the form of the chosen multidimensional loading path(s) and the shape of the specimen on various features of the inverse identification process related to the elastic moduli parameter estimation are also determined. The results of the numerical studies demonstrate the efficacy of the proposed methodology and suggests subsequent avenues for optimizing the specification of the loading path both a priori and in real-time. Copyright © 2006 by ASME.

关键词： Composite materials

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