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Advanced Molecular Dynamics in Openfoam✩ S.M
Computer Physics Communications 224 (2018) 1–21 Contents lists available at ScienceDirect Computer Physics Communications journal homepage: www.elsevier.com/locate/cpc Feature article mdFoam+: Advanced molecular dynamics in OpenFOAMI S.M. Longshaw a,*, M.K. Borg b, S.B. Ramisetti b, J. Zhang b, D.A. Lockerby c, D.R. Emerson a, J.M. Reese b a Scientific Computing Department, The Science & Technology Facilities Council, Daresbury Laboratory, Warrington, Cheshire WA4 4AD, UK b School of Engineering, University of Edinburgh, Edinburgh EH9 3FB, UK c School of Engineering, University of Warwick, Coventry, CV4 7AL, UK article info a b s t r a c t Article history: This paper introduces mdFoam+, which is an MPI parallelised molecular dynamics (MD) solver imple- Received 6 March 2017 mented entirely within the OpenFOAM software framework. It is open-source and released under the Received in revised form 17 August 2017 same GNU General Public License (GPL) as OpenFOAM. The source code is released as a publicly open Accepted 25 September 2017 software repository that includes detailed documentation and tutorial cases. Since mdFoam+ is designed Available online 23 October 2017 entirely within the OpenFOAM C++ object-oriented framework, it inherits a number of key features. The Keywords: code is designed for extensibility and flexibility, so it is aimed first and foremost as an MD research tool, OpenFOAM in which new models and test cases can be developed and tested rapidly. Implementing mdFoam+ in Molecular dynamics OpenFOAM also enables easier development of hybrid methods that couple MD with continuum-based MD solvers. Setting up MD cases follows the standard OpenFOAM format, as mdFoam+ also relies upon Computational fluid dynamics the OpenFOAM dictionary-based directory structure. -
Introduction to Nuclear Reactor Modelling Using Openfoam Carlo Fiorina 2
Introduction to nuclear reactor modelling using OpenFOAM Carlo Fiorina 2 Disclaimer C. Fiorina ▪ Focus on the use of OpenFOAM for multiphysics ○ Use of OpenFOAM as CFD tool widely covered by documentation, forums, courses, etc. ▪ Focus on already existing tool (GeN-Foam) as an example ○ Programming from scratch is not that difficult, but unsuited for a 75 minutes lecture ▪ In the slides, more material than can actually be covered in this lecture ○ Can help better understanding the slides after the lecture 3 Content C. Fiorina ▪ General Introduction ▪ Introduction to the use of OpenFOAM ▪ Basics of GeN-Foam ▪ Short introduction on the use of GeN-Foam 4 Objective C. Fiorina What is it about? ▪ Provide you with general information, references, suggestions, terminology and lessons learnt that can facilitate your approach to the OpenFOAM world ▪ Provide with slides that can help you out orienting yourself if you decide to embrace the use of OpenFOAM What is not about? ▪ Detailed course on the use of OpenFOAM ▪ Hands-on training 5 The IAEA-facilitated ONCORE initiative C. Fiorina ONCORE to support the open-source nuclear community and help addressing typical shortcomings of open-source development (scattered community, documentation, QA, loss of knowledge) ▪ Promote collaboration and facilitate communication (connect the community) ▪ Provide guidelines for code contribution (documentation, QA) ▪ Provide development best practices (QA) ▪ Preserve knowledge ○ Incl. compiling a list of open-source codes https://www.iaea.org/topics/nuclear-power-reactors/open-source-nuclear-cod e-for-reactor-analysis-oncore 6 A first important outcome: list of C. Fiorina available codes ▪ https://nucleus.iaea.org/sites/oncore/SitePages/List%20of%20Codes.aspx ▪ A vibrant community with an impressive R&D output ▪ ~35 codes already identified so far: ○ OpenMC ○ Raven ○ Dragon ○ MOOSE ○ Salome platform (Code_Saturne, Code_Aster) ○ TrioCFD ○ … ○ Several OpenFOAM-based tools 7 A central tool for open-source simulation C. -
15Th Openfoam Workshop - June 22, 2020 - Technical Session I-D a Flexible and Precice Solver Coupling Ecosystem
15th OpenFOAM Workshop - June 22, 2020 - Technical Session I-D A flexible and preCICE solver coupling ecosystem Gerasimos Chourdakis, Technical University of Munich [email protected] Benjamin Uekermann, Eindhoven University of Technology [email protected] Find these slides on GitHub https://github.com/MakisH/ofw15-slides The Big Picture e r ic r te c e p e lv a r o d p s a lib structure fluid solver solver The Big Picture e r ic r te c e p e lv a r o d p s a lib structure fluid solver solver in-house commercial solver solver The Big Picture e r ic r te c e p e lv a r o d p s a lib structure fluid solver solver OpenFOAM CalculiX SU2 Code_Aster foam-extend FEniCS deal-ii Nutils MBDyn in-house commercial solver solver API in: C++ Python Matlab ANSYS Fluent C Fortran COMSOL The Big Picture e r ic r te c e p e lv a r o d p s a lib structure fluid solver A Coupling Library for Partitioned Multi-Physics Simulations solver OpenFOAM CalculiX SU2 Code_Aster . foam-extend FEniCS deal-ii . Nutils MBDyn communication data mapping in-house commercial solver solver coupling schemes time interpolation API in: C++ Python Matlab ANSYS Fluent C Fortran COMSOL News preCICE v2.0 Simplified config & API Better building & testing XML reference & visualizer xSDK member Faster initialization Better Python bindings Spack / Debian / AUR New Matlab bindings packages Upgrade guide in the wiki Other news deal.ii adapter new non-linear example for FSI FEniCS adapter new example for FSI code_aster adapter revived for code_aster 14 and preCICE v2 The OpenFOAM adapter -
Model Order Reduction for Aerodynamic Lifting Surfaces Aerospace Engineering
Model Order Reduction for Aerodynamic Lifting Surfaces Gonçalo da Cunha Laboreiro Mendonça Thesis to obtain the Master of Science Degree in Aerospace Engineering Supervisors: Prof. Fernando José Parracho Lau Dr. Frederico José Prata Rente Reis Afonso Examination Committee Chairperson: Prof. Filipe Szolnoky Ramos Pinto Cunha Supervisor: Prof. Fernando José Parracho Lau Member of the Committee: Prof. Afzal Suleman November 2017 ii Dedicated to my family and friends, who were always there for me. iii iv Acknowledgments I would like to thank dearly my supervisors Prof. Lau and Dr. Afonso who gave me constant support throughout this thesis up until the very end. Their insights on aerodynamics and CFD models guided me in my research of model order reduction methods and allowed me to better understand the models with which I had to work. Their demands for rigor and quality also pushed me to better my work, and in the end write a better thesis. v vi Resumo Nesta tese o tema de reduc¸ao˜ de modelos e a sua aplicac¸ao˜ a Mecanicaˆ de Fluidos Computacional sao˜ abordados. E´ mostrada a necessidade da industria´ aeroespacial, seja nacional ou Europeia, de modelos mais rapidos´ mas fieis´ a` realidade. Isto e´ devido ao elevado tempo de calculo´ associado aos modelos de alta-fidelidade. Estes mostram-se pouco viaveis´ para aplicac¸oes˜ do tipo Optimizac¸ao˜ Multi- disciplinar, como a plataforma de optimizac¸ao˜ NOVEMOR. Tendo por objectivo testar e aplicar reduc¸ao˜ de modelos a modelos CFD de superf´ıcies sustentadoras, uma pesquisa bibliografica´ abrangendo a reduc¸ao˜ de modelos nao-lineares,˜ dinamicosˆ e ou estaticos´ foi feita. -
The One-Way FSI Method Based on RANS-FEM for the Open Water Test of a Marine Propeller at the Different Loading Conditions
Journal of Marine Science and Engineering Article The One-Way FSI Method Based on RANS-FEM for the Open Water Test of a Marine Propeller at the Different Loading Conditions Mobin Masoomi 1 and Amir Mosavi 2,3,* 1 Department of Mechanical Engineering, Babol Noshirvani University of Technology, Babol, Iran; [email protected] 2 Faculty of Civil Engineering, Technische Universität Dresden, 01069 Dresden, Germany 3 John von Neumann Faculty of Informatics, Obuda University, 1034 Budapest, Hungary * Correspondence: [email protected] Abstract: This paper aims to assess a new fluid–structure interaction (FSI) coupling approach for the vp1304 propeller to predict pressure and stress distributions with a low-cost and high-precision approach with the ability of repeatability for the number of different structural sets involved, other materials, or layup methods. An outline of the present coupling approach is based on an open- access software (OpenFOAM) as a fluid solver, and Abaqus used to evaluate and predict the blade’s deformation and strength in dry condition mode, which means the added mass effects due to propeller blades vibration is neglected. Wherein the imposed pressures on the blade surfaces are extracted for all time-steps. Then, these pressures are transferred to the structural solver as a load condition. Although this coupling approach was verified formerly (wedge impact), for the case in-hand, a further verification case, open water test, was performed to evaluate the hydrodynamic part of the solution with an e = 7.5% average error. A key factor for the current coupling approach is Citation: Masoomi, M.; Mosavi, A. -
Wind Field Simulation in a Wind Farm Using Openfoam and Actuator Line Model
ParCFD'2019 31st International Conference on Parallel Computational Fluid Dynamics May-14-17 2019, Antalya TURKEY WIND FIELD SIMULATION IN A WIND FARM USING OPENFOAM AND ACTUATOR LINE MODEL Huseyin Can Onel∗ & Dr. Ismail H. Tuncery ∗ Middle East Technical University (METU) Department of Aerospace Engineering 06800 Ankara, TURKEY e-mail: [email protected] yMiddle East Technical University (METU) Department of Aerospace Engineering 06800 Ankara, TURKEY e-mail: [email protected] - Web page: http://www.ae.metu.edu.tr/tuncer/ Key words: Aerospace applications, Wind turbine, HAWT, Actuator Line Model, Wake calculation Abstract. In this study, a horizontal axis wind turbine (HAWT) is modeled using so called Actuator Line Model (ALM), where full resolution of boundary layer over turbine blades is not needed and hence computation is cheaper. Results are validated against other numerical and experimental studies as well as panel method (XFOIL) and Blade Element Momentum Theory (BEMT) results which are still widely employed in today's wind energy industry. Important simulation and operation parameters and their effects on accuracy are discussed. It is concluded that within a certain range of tip speed ratios, ALM gives acceptable results and is a promising model for full-scale wind farm simulations to estimate energy production. 1 INTRODUCTION Market share of renewable energy grows at ever highest rates and wind turbine and wind farm design processes becomes more sophisticated with the advancements in computation technologies. There are two main design problems in wind energy: • Design of an individual wind turbine at its ideal operation conditions, where classical methods like 2D airfoil theory, potential flow theory and Blade Element Momentum Theory (BEMT) are still widely used, • Design of a complete wind farm, in which statistical meteorological data is used for macro-siting and simple analytical or empirical methods are used for micro-siting. -
EOF-Library: Open-Source Elmer FEM and Openfoam Coupler For
EOF-Library: Open-source Elmer FEM and OpenFOAM coupler for electromagnetics and fluid dynamics (CC BY-SA 4.0) Motivation for MHD - controlling liquid metals Liquid metal pump rotating permanent pipe magnets F1 F2 F FL FL Mechanically FL FL Electromagnetically Required physics Modelling coupled ● Electromagnetics ● Fluid dynamics Extra ● Free surface ● Heat transfer Liquid metal pump - modelling requires two-way ● Solidification / melting coupled electromagnetics and fluid dynamics 1 Required numerical models Fluid dynamics ● 3D, transient Electromagnetics ● High Reynolds ● Complex geometries, turbulence models multi-regions ● Complex A−V ● Volume of Fluid magnetic vector ● Advanced pre- and potential (VOF) for free post-processing tools surface modelling formulation ● Parallelization with ● Conductivity ● Viscosity good scaling dependence on dependence on temperature ● User community, temperature documentation 2 Existing Open Source codes Best for Best for Electromagnetics (EM) Fluid dynamics (FD) FEM FVM getDP OpenFOAM Elmer SU2 ... ... 3 Choosing Electromagnetics solver (1) GetDP + Designed for EM in mind, great for eddy-current problems + Uses PETSc iterative solvers, PETSc is MPI parallelized - Matrix assembly is not parallel (neither MPI nor OpenMP) - Weak integration with external post-processing tools MaxFEM, FreeFem++, deal.II, … Pictures from getdp.info ● I have no opinion 4 Choosing Electromagnetics solver (2) Elmer by CSC (Finland) + Multiphysics out-of-the-box (>40 solvers) + Build-in linear & nonlinear iterative solvers, -
Openfoam and Third Party Structural Solver for Fluid–Structure Interaction Simulations Robert L
OpenFOAM and Third Party Structural Solver for Fluid–Structure Interaction Simulations Robert L. Campbell Brent A. Craven [email protected] [email protected] Fluids and Structural Mechanics Office Applied Research Laboratory The Pennsylvania State University 6th OpenFOAM Workshop Penn State University University Park, Pa 13-17 June 2011 Objective ● Demonstrate a method to include a third-party, structural solver of choice for FSI simulations (quasi-steady) ● Why important? Structural analysts seem to have strong ties to their structural software and want to carry them forward for FSI simulations 2 Outline ● Brief Introduction to Fluid–Structure Interaction – Monolithic – Partitioned • Loose coupling • Tight coupling ● Solver Implementation – Flow solver – Structure solver – Solver interface ● Example Problem – Setup – Solution 3 FSI Introduction ● Fluid–Structure Interaction (FSI) modeling is a type of multi- physics modeling that combines physical models of fluids and structures ● FSI, in this context, implies two-way coupling ● Two approaches to FSI modeling – Monolithic • Governing equations for both the fluid and solid cast in terms of the same primitive variables • Single discretization scheme applied to entire domain – Partitioned • Fluid and solid domains modeled separately • Separate discretizations of each domain • Stress and displacement communication across the domain interface • Two coupling schemes: Loose and Tight 4 FSI Loose Coupling ● Loose coupling approach does START not check for convergence at each time step: Estimate -
Simulation in CFD of a Pebble Bed: Advanced High Temperature Reactor
2017 International Nuclear Atlantic Conference - INAC 2017 Belo Horizonte, MG, Brazil, October 22-27, 2017 ASSOCIAC¸ AO˜ BRASILEIRA DE ENERGIA NUCLEAR - ABEN SIMULATION IN CFD OF A PEBBLE BED - ADVANCED HIGH TEMPERATURE REACTOR CORE USING OPENFOAM Pamela M. Dahl1 and Jian Su1 1Programa de Engenharia Nuclear, COPPE Universidade Federal do Rio de Janeiro 21941-972 Rio de Janeiro, RJ [email protected] ABSTRACT Numerical simulations of a Pebble Bed nuclear reactor core are presented using the multi-physics tool-kit OpenFOAM. The HTR-PM is modeled using the porous media approach, accounting both for viscous and inertial effects through the Darcy and Forchheimer model. Initially, cylindrical 2D and 3D simulations are compared, in order to evaluate their differences and decide if the 2D simulations carry enough of the sought information, considering the savings in computational costs. The porous medium is considered to be isotropic, with the whole length of the packed bed occupied homogeneously with the spherical fuel elements. Steady-state simulations for normal equilibrium operation are performed, using a semi- sine function of the power density along the vertical axis as the source term for the energy balance equation.Total pressure drop is calculated and compared with that obtained from literature for a similar case. At a second stage, transient simulations are performed, where relevant parameters are calculated and compared to those of the literature. 1. INTRODUCTION The modular high temperature gas-cooled reactor (HTR) is quickly becoming a strong candidate for the IVth Generation of nuclear energy system technology, because of its inherent safety features, modularity, relatively low cost and a shorter construction time, which are obvious attractive features for a commercial reactor [1]. -
VMD User's Guide
VMD User’s Guide Version 1.9.4a48 October 13, 2020 NIH Biomedical Research Center for Macromolecular Modeling and Bioinformatics Theoretical and Computational Biophysics Group1 Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 405 N. Mathews Urbana, IL 61801 http://www.ks.uiuc.edu/Research/vmd/ Description The VMD User’s Guide describes how to run and use the molecular visualization and analysis program VMD. This guide documents the user interfaces displaying and grapically manipulating molecules, and describes how to use the scripting interfaces for analysis and to customize the behavior of VMD. VMD development is supported by the National Institutes of Health grant numbers NIH P41- GM104601. 1http://www.ks.uiuc.edu/ Contents 1 Introduction 11 1.1 Contactingtheauthors. ....... 12 1.2 RegisteringVMD.................................. 12 1.3 CitationReference ............................... ...... 12 1.4 Acknowledgments................................. ..... 13 1.5 Copyright and Disclaimer Notices . .......... 13 1.6 For information on our other software . .......... 15 2 Hardware and Software Requirements 17 2.1 Basic Hardware and Software Requirements . ........... 17 2.2 Multi-core CPUs and GPU Acceleration . ......... 17 2.3 Parallel Computing on Clusters and Supercomputers . .............. 18 3 Tutorials 19 3.1 RapidIntroductiontoVMD. ...... 19 3.2 Viewing a molecule: Myoglobin . ........ 19 3.3 RenderinganImage ................................ 21 3.4 AQuickAnimation................................. 21 3.5 An Introduction to Atom Selection . ......... 22 3.6 ComparingTwoStructures . ...... 22 3.7 SomeNiceRepresenations . ....... 23 3.8 Savingyourwork.................................. 24 3.9 Tracking Script Command Versions of the GUI Actions . ............ 24 4 Loading A Molecule 26 4.1 Notes on common molecular file formats . ......... 26 4.2 Whathappenswhenafileisloaded? . ....... 27 4.3 Babelinterface ................................. -
Gpu-Accelerated Applications Gpu‑Accelerated Applications
GPU-ACCELERATED APPLICATIONS GPU-ACCELERATED APPLICATIONS Accelerated computing has revolutionized a broad range of industries with over five hundred applications optimized for GPUs to help you accelerate your work. CONTENTS 1 Computational Finance 2 Climate, Weather and Ocean Modeling 2 Data Science & Analytics 4 Deep Learning and Machine Learning 8 Defense and Intelligence 9 Manufacturing/AEC: CAD and CAE COMPUTATIONAL FLUID DYNAMICS COMPUTATIONAL STRUCTURAL MECHANICS DESIGN AND VISUALIZATION ELECTRONIC DESIGN AUTOMATION 17 Media & Entertainment ANIMATION, MODELING AND RENDERING COLOR CORRECTION AND GRAIN MANAGEMENT COMPOSITING, FINISHING AND EFFECTS EDITING ENCODING AND DIGITAL DISTRIBUTION ON-AIR GRAPHICS ON-SET, REVIEW AND STEREO TOOLS WEATHER GRAPHICS 24 Medical Imaging 27 Oil and Gas 28 Research: Higher Education and Supercomputing COMPUTATIONAL CHEMISTRY AND BIOLOGY NUMERICAL ANALYTICS PHYSICS SCIENTIFIC VISUALIZATION 39 Safety and Security 42 Tools and Management Computational Finance APPLICATION NAME COMPANY/DEVELOPER PRODUCT DESCRIPTION SUPPORTED FEATURES GPU SCALING Accelerated Elsen Secure, accessible, and accelerated back- • Web-like API with Native bindings for Multi-GPU Computing Engine testing, scenario analysis, risk analytics Python, R, Scala, C Single Node and real-time trading designed for easy • Custom models and data streams are integration and rapid development. easy to add Adaptiv Analytics SunGard A flexible and extensible engine for fast • Existing models code in C# supported Multi-GPU calculations of a wide variety of pricing transparently, with minimal code Single Node and risk measures on a broad range of changes asset classes and derivatives. • Supports multiple backends including CUDA and OpenCL • Switches transparently between multiple GPUs and CPUS depending on the deal support and load factors. -
Gpu-Accelerated Applications Gpu‑Accelerated Applications
GPU-ACCELERATED APPLICATIONS GPU-ACCELERATED APPLICATIONS Accelerated computing has revolutionized a broad range of industries with over five hundred applications optimized for GPUs to help you accelerate your work. CONTENTS 1 Computational Finance 2 Climate, Weather and Ocean Modeling 2 Data Science and Analytics 4 Artificial Intelligence DEEP LEARNING AND MACHINE LEARNING 8 Federal, Defense and Intelligence 10 Design for Manufacturing/Construction: CAD/CAE/CAM COMPUTATIONAL FLUID DYNAMICS COMPUTATIONAL STRUCTURAL MECHANICS DESIGN AND VISUALIZATION ELECTRONIC DESIGN AUTOMATION INDUSTRIAL INSPECTION 19 Media & Entertainment ANIMATION, MODELING AND RENDERING COLOR CORRECTION AND GRAIN MANAGEMENT Test Drive the COMPOSITING, FINISHING AND EFFECTS World’s Fastest EDITING ENCODING AND DIGITAL DISTRIBUTION Accelerator – Free! ON-AIR GRAPHICS ON-SET, REVIEW AND STEREO TOOLS Take the GPU Test Drive, a free and WEATHER GRAPHICS easy way to experience accelerated computing on GPUs. You can run 29 Medical Imaging your own application or try one of the preloaded ones, all running on a 30 Oil and Gas remote cluster. Try it today. 31 Research: Higher Education and Supercomputing www.nvidia.com/gputestdrive COMPUTATIONAL CHEMISTRY AND BIOLOGY NUMERICAL ANALYTICS PHYSICS SCIENTIFIC VISUALIZATION 47 Safety and Security 49 Tools and Management Computational Finance APPLICATION NAME COMPANY/DEVELOPER PRODUCT DESCRIPTION SUPPORTED FEATURES GPU SCALING Accelerated Elsen Secure, accessible, and accelerated back- • Web-like API with Native bindings for Multi-GPU Computing Engine testing, scenario analysis, risk analytics Python, R, Scala, C Single Node and real-time trading designed for easy • Custom models and data streams are integration and rapid development. easy to add Adaptiv Analytics SunGard A flexible and extensible engine for fast • Existing models code in C# supported Multi-GPU calculations of a wide variety of pricing transparently, with minimal code Single Node and risk measures on a broad range of changes asset classes and derivatives.