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Interaction pressure tensor on high-order lattice Boltzmann models for nonideal fluids

Physical Review E 2019年第6期99卷 063318-063318页

作者： C. S. From E. Sauret S. A. Galindo-Torres Y. T. Gu Laboratory for Advanced Modelling and Simulation in Engineering and Science School of Chemistry Physics and Mechanical Engineering Science and Engineering Faculty Queensland University of Technology Queensland 4001 Australia Department of Civil Engineering and Industrial Design University of Liverpool Liverpool L69 3BX United Kingdom School of Engineering Westlake University Hangzhou Zhejiang Province 310024 China

In this work we address the application of pseudopotentials directly on high-order lattice Boltzmann models. We derive a general expression for the pressure tensor on high-order lattices considering all nonideal interactions, including intra- and intermolecular interactions, following the discrete lattice theory introduced by X. Shan [Phys. Rev. E 77, 066702 (2008)]. From the derived expression, a generalized continuum approximation, truncated at fourth-order isotropy, is obtained that is readily applicable to high-order lattices. With this, we demonstrate that high-order lattice models with pseudopotentials can satisfy thermodynamic consistency. The derived generalized expression and continuum approximation are validated for the case of a flat interface and compared against the standard definition available from the literature. The generalized expression is also shown to accurately reproduce the Laplace experiment for a variety of high-order lattice structures. This work sets the preliminary steps towards the application of high-order lattice models for simulating nonideal fluid mixtures.

关键词： Interactions in fluids Interparticle interactions Surface tension effects Complex fluids Lattice-Boltzmann methods

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Strain rate dependency of dislocation plasticity

arXiv

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arXiv 2020年

作者： Fan, Haidong El-Awady, Jaafar A. Wang, Qingyuan Raabe, Dierk Zaiser, Michael Department of Mechanics Sichuan University Chengdu610065 China Department Microstructure Physics and Alloy Design Max-Planck-Institut für Eisenforschung GmbH Düsseldorf40237 Germany Department of Mechanical Engineering Whiting School of Engineering The Johns Hopkins University BaltimoreMD21218 United States WW8-Materials Simulation Department of Materials Science FAU Universität Erlangen-Nürnberg Fürth90762 Germany

Dislocation slip is a general deformation mode and governs the strength of metals. Via discrete dislocation dynamics (DDD) and molecular dynamics (MD) simulations, we investigate the strain rate and dislocation density dependence of the strength of bulk copper single crystals using 192 simulations spanning over 10 orders of magnitude in strain rate Ε and 9 orders of magnitude in dislocation density ρ. Based on these large set of simulations and theoretical analysis, a new analytical relationship between material strength, dislocation density, strain rate and dislocation mobility is proposed, which is shown to be in excellent agreement with the current simulations as well as with experimental data. The results show that the material strength is a non-monotonic function of dislocation density and displays two universal regimes (first decreasing, then increasing) as the dislocation density increases. The first regime is a result of strain rate hardening, while the second regime is dominated by the classical Taylor forest hardening. Accordingly, the strength displays universally, as a function of strain rate, a rate-independent regime at low strain rates (governed by forest hardening) followed by a rate hardening regime at high strain rates (governed by strain rate hardening). All the results can be captured by a single scaling function, which relates the normalized strength to the coupling parameter (ρ / Ε 2/3 ) between dislocation density and strain rate. Finally, the fluctuations of dislocation flow are analyzed in terms of the strain rate dependent distribution of dislocation segment velocities. It is found that the fluctuations are governed by another universal scaling function and diverge in the rate independent limit, indicating a critical behavior. The current analysis provides a comprehensive understanding on how collective dislocation motions are governed by the competition between the internal elastic interactions of dislocations, and the stress required to d

关键词： Strain rate

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Model-based damage detection in piezoelectric fiber based composites 147th

Model-based damage detection in piezoelectric fiber based co...

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147th Annual Meeting and Exhibition, TMS 2018

作者： Shalan, Khalid M. AbdelMeguid, Mohamed E. Hatem, Tarek M. Hegazi, Hesham A. Bahei-El-Din, Yehia A. Centre for Simulation Innovation and Advanced Manufacturing The British University in Egypt El-Sherouk City Cairo11837 Egypt Mechanical Design and Production Department Faculty of Engineering Cairo University Giza12613 Egypt Microstructure Physics and Alloy Design Department Max-Planck-Institut Fur Eisenforschung Düsseldorf40237 Germany

ISBN: (纸本)9783319950211

Piezoelectric Fiber-based Composites (PFCs) have significant potential as smart materials given their superior mechanical properties over piezoelectric wafers. Therefore, reliable models are needed to accurately predict PFCs behavior including inherent heterogeneity and coupled electro-mechanical fields. This paper offers a multi-resolution model (micro and macro) that calculates the homogenized moduli of heterogeneous PFCs including the coupled electro-mechanical field based on Transformation Field Analysis (TFA). The calculated properties from TFA micro analysis is used in a macro-scale finite element analysis to model the dynamic behavior of PFCs in macro-scale. Numerical dynamic analysis incorporates a simple structure in pristine condition and in two damage conditions, namely a delamination damage and an impact-induced damage, modeled using both modal analysis and implicit dynamic analysis. © The Minerals, Metals & Materials Society 2018.

关键词： Modal analysis

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High-damping and conducting epoxy nanocomposite using both zinc oxide particles and carbon nanofibers

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Journal of Materiomics 2018年第3期4卷 187-193页

作者： Jae-Soon Jang Gyo Woo Lee Hyung-ick Kim Sung Yong Hong Lijie Ci Jae-Do Nam Jonghwan Suhr Simulation Group Battery R&D CenterSAMSUNG SDI CO.LTDSamsung-RoYeongtong-GuSuwon-SiGyeonggi-DoSouth Korea Division of Mechanical Design Engineering Chonbuk National UniversityJeonju561-756South Korea Dongnam Regional Division Korea Institute of Industrial TechnologyJinju 52845South Korea Department of Polymer Science and Engineering Sungkyunkwan University2066SeoburoJangan-guGyeonggi-doSouth Korea School of Materials Science&Engineering Shandong UniversityChina School of Mechanical Engineering Sungkyunkwan University2066SeoburoJangan-guGyeonggi-doSouth Korea Department of Energy Science Sungkyunkwan University2066SeoburoJangan-guGyeonggi-doSouth Korea

In this study,high-damping and conducting epoxy nanocomposites were developed with carbon nanofibers as conducting materials,and zinc oxide particles as piezoelectric *** mechanical and electrical properties,electrical impedance,and loss factors were investigated by uniaxial tensile tests,voltage measurement,impedance measurement,and 3-point bending *** percolation thresholds were found:the percolation threshold of resistivity due to the carbon nanofibers forming conductive networks in the matrix;and the impedance threshold due to the zinc oxide particles acting like electric barriers.A poling treatment of the high-damping and conducting epoxy nanocomposite was considered,and we found that poling treatment helped to make the networks more conductive and to generate voltage from ZnO particles.A high-damping and conducting epoxy nanocomposite with 3 wt%CNF and 10 wt%ZnO exhibited higher loss factor than those of others tested.

关键词： Damping Piezoelectric materials Impedance Poling treatment Loss factor

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Developments and applications of the OPTIMADE API for materials discovery, design, and data exchange

arXiv

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arXiv 2024年

作者： Evans, Matthew L. Bergsma, Johan Merkys, Andrius Andersen, Casper W. Andersson, Oskar B. Beltrán, Daniel Blokhin, Evgeny Boland, Tara M. Balderas, Rubén Castañeda Choudhary, Kamal Díaz, Alberto Díaz García, Rodrigo Domínguez Eckert, Hagen Eimre, Kristjan Montero, María Elena Fuentes Krajewski, Adam M. Mortensen, Jens Jørgen Duarte, José Manuel Nápoles Pietryga, Jacob Qi, Ji de Jesús Trejo Carrillo, Felipe Vaitkus, Antanas Yu, Jusong Zettel, Adam de Castro, Pedro Baptista Carlsson, Johan Cerqueira, Tiago F.T. Divilov, Simon Hajiyani, Hamidreza Hanke, Felix Jose, Kevin Oses, Corey Riebesell, Janosh Schmidt, Jonathan Winston, Donald Xie, Christen Yang, Xiaoyu Bonella, Sara Botti, Silvana Curtarolo, Stefano Draxl, Claudia Cobas, Luis Edmundo Fuentes Hospital, Adam Liu, Zi-Kui Marques, Miguel A.L. Marzari, Nicola Morris, Andrew J. Ong, Shyue Ping Orozco, Modesto Persson, Kristin A. Thygesen, Kristian S. Wolverton, Chris Scheidgen, Markus Toher, Cormac Conduit, Gareth J. Pizzi, Giovanni Gražulis, Saulius Rignanese, Gian-Marco Armiento, Rickard Chemin des Étoiles 8 Louvain-la-Neuve1348 Belgium Matgenix SRL 185 Rue Armand Bury Gozée6534 Belgium École Polytechnique Fédérale de Lausanne Avenue de Forel 3 Lausanne1015 Switzerland Institute of Biotechnology Life Sciences Center Vilnius University Sauletekio av. 7 VilniusLT-10257 Lithuania SINTEF P.O. Box 4760 Torgarden TrondheimNO-7465 Norway Materials Design and Informatics unit Department of Physics Chemistry and Biology Linköping University Sweden Baldiri i Reixac 10-12 Barcelona08028 Spain Tilde Materials Informatics Straßmannstraße 25 Berlin10249 Germany Materials Platform for Data Science Sepapaja 6 Tallinn15551 Estonia Computational Atomic-Scale Materials Design Technical University of Denmark Kgs. Lyngby Denmark Av. Miguel de Cervantes 120 Complejo Industrial Chihuahua Chihuahua Chih. 31136 Mexico Material Measurement Laboratory National Institute of Standards and Technology GaithersburgMD20899 United States Department of Mechanical Engineering and Materials Science Duke University DurhamNC27708 United States Center for Extreme Materials Duke University DurhamNC27708 United States École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Universidad Autónoma de Chihuahua Facultad de Ciencias Quimicas Chihuahua31125 Mexico Department of Materials Science and Engineering The Pennsylvania State University University ParkPA16802 United States Department of Materials Science and Engineering Northwestern University EvanstonIL60208 United States Department of NanoEngineering University of California 9500 Gilman Drive La Jolla San DiegoCA92093-0448 United States National Institute for Materials Science 1-2-1 Sengen Ibaraki Tsukuba305-0047 Japan Dassault Systèmes Germany GmbH Am Kabellager 11-13 Cologne51063 Germany CFisUC Department of Physics University of Coimbra Rua Larga Coimbra3004-516 Portugal Dassault Systèmes 22 Science Park CB4 0FJ United Kingdom Theory of Condensed Matter Cavendis

The Open Databases Integration for Materials design (OPTIMADE) application programming interface (API) empowers users with holistic access to a growing federation of databases, enhancing the accessibility and discoverability of materials and chemical data. Since the first release of the OPTIMADE specification (v1.0), the API has undergone significant development, leading to the v1.2 release, and has underpinned multiple scientific studies. In this work, we highlight the latest features of the API format, accompanying software tools, and provide an update on the implementation of OPTIMADE in contributing materials databases. We end by providing several use cases that demonstrate the utility of the OPTIMADE API in materials research that continue to drive its ongoing development. © 2024, CC BY.

关键词： Electronic data interchange

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Jacobi Spectral Collocation Method Based on Lagrange Interpolation Polynomials for Solving Nonlinear Fractional Integro-Differential Equations

引用

Advances in Applied Mathematics and Mechanics 2018年第6期10卷 1440-1458页

作者： Xingfa Yang Yin Yang Yanping Chen Jie Liu State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan UniversityChangsha 410082HunanChina Hunan Key Laboratory for Computation and Simulation in Science and Engineering Key Laboratory of Intelligent Computing&Information Processing of Ministry of EducationSchool of Mathematics and Computational ScienceXiangtan UniversityXiangtan 411105HunanChina School of Mathematical Sciences South China Normal UniversityGuangzhou 510631GuangdongChina Center for Research on Leading Technology of Special Equipment School of Mechanical and Electric EngineeringGuangzhou UniversityGuangzhou 510006GuangdongChina

In this paper,we study a class of nonlinear fractional integro-differential equations,the fractional derivative is described in the Caputo *** the properties of the Caputo derivative,we convert the fractional integro-differential equations into equivalent integral-differential equations of Volterra type with singular kernel,then we propose and analyze a spectral Jacobi-collocation approximation for nonlinear integro-differential equations of Volterra *** provide a rigorous error analysis for the spectral methods,which shows that both the errors of approximate solutions and the errors of approximate fractional derivatives of the solutions decay exponentially in L^(∞)-norm and weighted L^(2)-norm.

关键词： Spectral method nonlinear fractional derivative Volterra integro-differential equations Caputo derivative

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Screw dislocation structure and mobility in body centered cubic Fe predicted by a Gaussian Approximation Potential

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npj Computational Materials 2018年第1期4卷 90-96页

作者： Francesco Maresca Daniele Dragoni Gábor Csányi Nicola Marzari William A.Curtin Laboratory for Multiscale Mechanics Modeling(LAMMM) Institute of Mechanical EngineeringÉcole Polytechnique Fédérale de LausanneLausanne CH-1015Switzerland Theory and Simulation of Materials(THEOS) and National Centre for Computational Design and Discovery of Novel Materials(NCCR MARVEL)École Polytechnique Fédérale de LausanneLausanne CH-1015Switzerland Dipartimento di Scienza dei Materiali Universitàdi Milano-BicoccaVia R.Cozzi 55Milan I-20125Italy Department of Engineering University of CambridgeTrumpington StreetCambridge CB21PZUK

The plastic flow behavior of bcc transition metals up to moderate temperatures is dominated by the thermally activated glide of screw dislocations,which in turn is determined by the atomic-scale screw dislocation core structure and the associated kink-pair nucleation mechanism for *** complex plasticity phenomena requires the simulation of many atoms and interacting dislocations and *** sizes are beyond the scope of first-principles methods and thus require empirical interatomic *** for the technological important case of bcc Fe,existing empirical interatomic potentials yield spurious ***,the structure and motion of the screw dislocations in Fe are studied using a new Gaussian Approximation Potential(GAP)for bcc Fe,which has been shown to reproduce the potential energy surface predicted by density-functional theory(DFT)and many associated *** Fe GAP predicts a compact,non-degenerate core structure,a single-hump Peierls potential,and glide on{110},consistent with DFT *** thermally activated motion at finite temperatures occurs by the expected kink-pair nucleation and propagation *** stress-dependent enthalpy barrier for screw motion,computed using the nudgedelastic-band method,follows closely a form predicted by standard theories with a zero-stress barrier of~1 eV,close to the experimental value of 0.84 eV,and a Peierls stress of~2 GPa consistent with DFT predictions of the Peierls potential.

关键词： structure dislocation cubic

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Author Correction: Strain rate dependency of dislocation plasticity

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Nature communications 2021年第1期12卷 2470页

作者： Haidong Fan Qingyuan Wang Jaafar A El-Awady Dierk Raabe Michael Zaiser Department of Mechanics Sichuan University Chengdu China. hfan85@***. Department Microstructure Physics and Alloy Design Max-Planck-Institut für Eisenforschung GmbH Düsseldorf Germany. hfan85@***. Department of Mechanics Sichuan University Chengdu China. wangqy@***. Department of Mechanical Engineering Whiting School of Engineering The Johns Hopkins University Baltimore MD USA. Department Microstructure Physics and Alloy Design Max-Planck-Institut für Eisenforschung GmbH Düsseldorf Germany. WW8-Materials Simulation Department of Materials Science FAU Universität Erlangen-Nürnberg Fürth Germany.

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Application of artificial neural networks for the prediction of interface mechanics: a study on grain boundary constitutive behavior

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Advanced Modeling and simulation in engineering Sciences 2020年第1期7卷 1-1页

作者： Fernández, Mauricio Rezaei, Shahed Rezaei Mianroodi, Jaber Fritzen, Felix Reese, Stefanie Institute of Applied Mechanics University of Stuttgart Pfaffenwaldring 7 Stuttgart 70569 Germany Cyber-Physical Simulation Group Department of Mechanical Engineering Technische Universität Darmstadt Dolivostraße 15 Darmstadt 64293 Germany Institute of Applied Mechanics RWTH Aachen University Mies-van-der-Rohe-Str. 1 Aachen 52074 Germany Material Mechanics RWTH Aachen University Schinkelstrasse 2 Aachen 52062 Germany Microstructure Physics and Alloy Design Max-Planck-Institut für Eisenforschung Max-Planck-Straße 1 Düsseldorf 40237 Germany

The present work aims at the identification of the effective constitutive behavior of Σ 5 aluminum grain boundaries (GB) for proportional loading by using machine learning (ML) techniques. The input for the ML approach is high accuracy data gathered in challenging molecular dynamics (MD) simulations at the atomic scale for varying temperatures and loading conditions. The effective traction-separation relation is recorded during the MD simulations. The raw MD data then serves for the training of an artificial neural network (ANN) as a surrogate model of the constitutive behavior at the grain boundary. Despite the extremely fluctuating nature of the MD data and its inhomogeneous distribution in the traction-separation space, the ANN surrogate trained on the raw MD data shows a very good agreement in the average behavior without any data-smoothing or pre-processing. Further, it is shown that the trained traction-separation ANN captures important physical properties and is able to predict traction values for given separations not contained in the training data. For example, MD simulations show a transition in traction-separation behaviour from pure sliding mode under shear load to combined GB sliding and decohesion with intermediate hardening regime at mixed load directions. These changes in GB behaviour are fully captured in the ANN predictions. Furthermore, by construction, the ANN surrogate is differentiable for arbitrary separation and also temperature, such that a thermo-mechanical tangent stiffness operator can always be evaluated. The trained ANN can then serve for large-scale FE simulation as an alternative to direct MD-FE coupling which is often infeasible in practical applications. © 2020, The Author(s).

关键词： Artificial neural networks (ANN) Data-driven surrogate Grain boundary Interfaces Machine learning (ML) Molecular dynamics Traction-separation relation

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Operations & Supply Chain Management: Principles and Practice

arXiv

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arXiv 2025年

作者： Petropoulos, Fotios Akkermans, Henk Aksin, O. Zeynep Ali, Imran Babai, Mohamed Zied Barbosa-Povoa, Ana Battaïa, Olga Besiou, Maria Boysen, Nils Brammer, Stephen Brandon-Jones, Alistair Briskorn, Dirk Browning, Tyson R. Buijs, Paul Centobelli, Piera Chiarini, Andrea Cousins, Paul Cudney, Elizabeth A. Davies, Andrew Day, Steven J. de Koster, René Dekker, Rommert Denicol, Juliano Despeisse, Mélanie Disney, Stephen M. Dolgui, Alexandre Duong, Linh El-Qallali, Malek Fahimnia, Behnam Fakhredin, Fatemeh Gershwin, Stanley B. Ghamat, Salar Giannikas, Vaggelis Glock, Christoph H. Godsell, Janet Govindan, Kannan Hannibal, Claire Haug, Anders Hernaus, Tomislav Hsuan, Juliana Ivanov, Dmitry Jahre, Marianne Johansson, Björn Kalidoss, Madan Shankar Kanellopoulos, Argyris Kannan, Devika Karul, Elif Katsikopoulos, Konstantinos V. Kilic-Ararat, Ayse Begüm Kolisch, Rainer Koppenberg, Maximilian Kumar, Maneesh Kuo, Yong-Hong Kusiak, Andrew Lewis, Michael A. Lim, Stanley Frederick W.T. Limère, Veronique Liu, Jiyin Maghazei, Omid Marić, Matija Meissner, Joern Meuwissen, Miranda Micheli, Pietro Nanayakkara, Samudaya Özdemir, Bengü Nur Papadopoulos, Thanos Pavelin, Stephen Perera, Srinath Phillips, Wendy Prak, Dennis Pun, Hubert Qazi, Sharfah Ahmad Ramanathan, Usha Reiner, Gerald Reitsma, Ewout Roehrich, Jens K. Sanders, Nada R. Sarkis, Joseph Schmid, Nico André Schmidt, Christoph G. Schroeder, Andreas Selviaridis, Kostas Seuring, Stefan Shi, Chuan Son, Byung-Gak Spring, Martin Squire, Brian van der Valk, Wendy van Donk, Dirk Pieter van Houtum, Geert-Jan Wilhelm, Miriam Wynstra, Finn Zheng, Ting School of Management University of Bath Bath United Kingdom Department of Information Systems & Operations Management Tilburg School of Economics and Management Tilburg University Netherlands College of Administrative Sciences and Economics Koc University Turkey School of Business and Law Central Queensland University Australia Kedge Business School France Center for Management Studies Instituto Superior Técnico University of Lisbon Portugal Kühne Logistics University Hamburg Germany Friedrich-Schiller-Universität Jena Lehrstuhl für Operations Management Germany Bergische Universität Wuppertal Germany Neeley School of Business Texas Christian University Fort WorthTX United States Department of Operations University of Groningen Netherlands Department of Industrial Engineering University of Naples "Federico II" Italy Department of Management University of Verona Italy Management School University of Liverpool United Kingdom John E. Simon School of Business Maryville University of Saint Louis Missouri United States Science Policy Research Unit University of Sussex Business School Brighton United Kingdom School of Management Zhejiang University China Rotterdam School of Management Erasmus University Netherlands Erasmus School of Economics Erasmus University Netherlands Bartlett School of Sustainable Construction The Bartlett Faculty of the Built Environment University College London United Kingdom Department of Industrial and Material Sciences Chalmers University of Technology Sweden Center for Simulation Analytics and Modelling University of Exeter Business School United Kingdom IMT Atlantique LS2N-CNRS Nantes France College of Business and Law University of the West of England United Kingdom Rabdan Academy United Arab Emirates Institute of Transport and Logistics Studies The University of Sydney Business School Australia Kühne Logistics University Germany Department of Mechanical Engineering Massachusetts Institute of Technology Massachusetts United S

Operations and Supply Chain Management (OSCM) has continually evolved, incorporating a broad array of strategies, frameworks, and technologies to address complex challenges across industries. This encyclopedic article provides a comprehensive overview of contemporary strategies, tools, methods, principles, and best practices that define the field’s cutting-edge advancements. It also explores the diverse environments where OSCM principles have been effectively implemented. The article is meant to be read in a nonlinear fashion. It should be used as a point of reference or first-port-of-call for a diverse pool of readers: academics, researchers, students, and practitioners. © 2025, CC BY.

关键词： Supply chain management

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