A Software Platform for Nanoscale Device Simulation and Visualization
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English Translation of the German by Tom Hammond
Richard Strauss Susan Bullock Sally Burgess John Graham-Hall John Wegner Philharmonia Orchestra Sir Charles Mackerras CHAN 3157(2) (1864 –1949) © Lebrecht Music & Arts Library Photo Music © Lebrecht Richard Strauss Salome Opera in one act Libretto by the composer after Hedwig Lachmann’s German translation of Oscar Wilde’s play of the same name, English translation of the German by Tom Hammond Richard Strauss 3 Herod Antipas, Tetrarch of Judea John Graham-Hall tenor COMPACT DISC ONE Time Page Herodias, his wife Sally Burgess mezzo-soprano Salome, Herod’s stepdaughter Susan Bullock soprano Scene One Jokanaan (John the Baptist) John Wegner baritone 1 ‘How fair the royal Princess Salome looks tonight’ 2:43 [p. 94] Narraboth, Captain of the Guard Andrew Rees tenor Narraboth, Page, First Soldier, Second Soldier Herodias’s page Rebecca de Pont Davies mezzo-soprano 2 ‘After me shall come another’ 2:41 [p. 95] Jokanaan, Second Soldier, First Soldier, Cappadocian, Narraboth, Page First Jew Anton Rich tenor Second Jew Wynne Evans tenor Scene Two Third Jew Colin Judson tenor 3 ‘I will not stay there. I cannot stay there’ 2:09 [p. 96] Fourth Jew Alasdair Elliott tenor Salome, Page, Jokanaan Fifth Jew Jeremy White bass 4 ‘Who spoke then, who was that calling out?’ 3:51 [p. 96] First Nazarene Michael Druiett bass Salome, Second Soldier, Narraboth, Slave, First Soldier, Jokanaan, Page Second Nazarene Robert Parry tenor 5 ‘You will do this for me, Narraboth’ 3:21 [p. 98] First Soldier Graeme Broadbent bass Salome, Narraboth Second Soldier Alan Ewing bass Cappadocian Roger Begley bass Scene Three Slave Gerald Strainer tenor 6 ‘Where is he, he, whose sins are now without number?’ 5:07 [p. -
Fenics-Shells Release 2018.1.0
FEniCS-Shells Release 2018.1.0 Aug 02, 2021 Contents 1 Subpackages 1 2 Module contents 13 3 Documented demos 15 4 FEniCS-Shells 61 Bibliography 65 Python Module Index 67 Index 69 i ii CHAPTER 1 Subpackages 1.1 fenics_shells.analytical package 1.1.1 Submodules 1.1.2 fenics_shells.analytical.lovadina_clamped module Analytical solution for clamped Reissner-Mindlin plate problem from Lovadina et al. 1.1.3 fenics_shells.analytical.simply_supported module Analytical solution for simply-supported Reissner-Mindlin square plate under a uniform transverse load. 1.1.4 fenics_shells.analytical.vonkarman_heated module Analytical solution for elliptic orthotropic von Karman plate with lenticular thickness subject to a uniform field of inelastic curvatures. fenics_shells.analytical.vonkarman_heated.analytical_solution(Ai, Di, a_rad, b_rad) 1 FEniCS-Shells, Release 2018.1.0 1.1.5 Module contents 1.2 fenics_shells.common package 1.2.1 Submodules 1.2.2 fenics_shells.common.constitutive_models module fenics_shells.common.constitutive_models.psi_M(k, **kwargs) Returns bending moment energy density calculated from the curvature k using: Isotropic case: .. math:: D = frac{E*t^3}{24(1 - nu^2)} W_m(k, ldots) = D*((1 - nu)*tr(k**2) + nu*(tr(k))**2) Parameters • k – Curvature, typically UFL form with shape (2,2) (tensor). • **kwargs – Isotropic case: E: Young’s modulus, Constant or Expression. nu: Poisson’s ratio, Constant or Expression. t: Thickness, Constant or Expression. Returns UFL form of bending stress tensor with shape (2,2) (tensor). fenics_shells.common.constitutive_models.psi_N(e, **kwargs) Returns membrane energy density calculated from e using: Isotropic case: .. math:: B = frac{E*t}{2(1 - nu^2)} N(e, ldots) = B(1 - nu)e + nu mathrm{tr}(e)I Parameters • e – Membrane strain, typically UFL form with shape (2,2) (tensor). -
Optimization Design by Coupling Computational Fluid Dynamics and Genetic Algorithm 125
DOI: 10.5772/intechopen.72316 Provisional chapter Chapter 5 Optimization Design by Coupling Computational Fluid OptimizationDynamics and Design Genetic by Algorithm Coupling Computational Fluid Dynamics and Genetic Algorithm Jong-Taek Oh and Nguyen Ba Chien Jong-TaekAdditional information Oh and is availableNguyen at Bathe endChien of the chapter Additional information is available at the end of the chapter http://dx.doi.org/10.5772/intechopen.72316 Abstract Nowadays, optimal design of equipment is one of the most practical issues in modem industry. Due to the requirements of deploying time, reliability, and design cost, bet- ter approaches than the conventional ones like experimental procedures are required. Moreover, the rapid development of computing power in recent decades opens a chance for researchers to employ calculation tools in complex configurations. In this chapter, we demonstrate a kind of modern optimization method by coupling computational fluid dynamics (CFD) and genetic algorithms (GAs). The brief introduction of GAs and CFD package OpenFOAM will be performed. The advantage of this approach as well as the difficulty that we must tackle will be analyzed. In addition, this chapter performs a study case in which an automated procedure to optimize the flow distribution in a manifold is established. The design point is accomplished by balancing the liquid-phase flow rate at each outlet, and the controlled parameter is a dimension of baffle between each chan- nel. Using this methodology, we finally find a set of results improving the distribution of flow. Keywords: computational fluid dynamics, VOF, optimization, OpenFOAM, genetic algorithm, open sourced 1. Introduction Computational fluid dynamics (CFD)-based optimization approach has been growing rap- idly in the past decades. -
Fenics-HPC: Automated Predictive High-Performance Finite Element
FEniCS-HPC: Automated predictive high-performance finite element computing with applications in aerodynamics Johan Hoffman1, Johan Jansson2, and Niclas Jansson3 1 Computational Technology Laboratory, School of Computer Science and Communication, KTH, Stockholm, Sweden and BCAM - Basque Center for Applied Mathematics, Bilbao, Spain [email protected] 2 BCAM - Basque Center for Applied Mathematics, Bilbao, Spain and Computational Technology Laboratory, School of Computer Science and Communication, KTH, Stockholm, Sweden [email protected] 3 RIKEN Advanced Institute for Computational Science, Kobe, Japan [email protected] Abstract. Developing multiphysics finite element methods (FEM) and scalable HPC implementations can be very challenging in terms of soft- ware complexity and performance, even more so with the addition of goal-oriented adaptive mesh refinement. To manage the complexity we in this work present general adaptive stabilized methods with automated implementation in the FEniCS-HPC automated open source software framework. This allows taking the weak form of a partial differential equation (PDE) as input in near-mathematical notation and automati- cally generating the low-level implementation source code and auxiliary equations and quantities necessary for the adaptivity. We demonstrate new optimal strong scaling results for the whole adaptive framework applied to turbulent flow on massively parallel architectures down to 25000 vertices per core with ca. 5000 cores with the MPI-based PETSc backend and for assembly down to 500 vertices per core with ca. 20000 cores with the PGAS-based JANPACK backend. As a demonstration of the high impact of the combination of the scalability together with the adaptive methodology allowing prediction of gross quantities in turbulent flow we present an application in aerodynamics of a full DLR-F11 aircraft in connection with the HiLift-PW2 benchmarking workshop with good match to experiments. -
OCCT V.6.5.4 Release Notes
Open CASCADE Technology & Products Products Version6. features, Highlights Technology CASCADE Open Overview , so applications linked against a previous version must berecompiled to run with this Version 6. Open CASCADE Technology & Products Technology Open CASCADE improvements and bug fixes over 6 Universal locale global current on independent made export / Import TKOpenGl libraries support plotter and viewer 2D obsolete of Removal Accelerated text visualization management texture of Redesign R and XCode Cocoa API with native visualization X, Mac OS On of support Official New automated testing system testing New automated and 3D graphics 2D both to way render unified the become input parameters and results and generation of data for bug rep bug for data of generation and results and parameters input . 0 efactored is binary incompatible withtheprevious versions CMake build scripts build CMake is nowis link Open CASCADE Open Boolean operations algorithm operations Boolean andProducts Mac OS X and Products Products and www. www. ed at build time, not at run time run at not time, build at ed opencascad Release Notes Notes Release opencascade M , Windows 8 and Visual Studio 2012 Studio Visual , and Windows 8 maintenance ; use of FTGL library is dropped FTGL of library ; use in version or e .co Release .org 6. m releas . Possibility to enable automatic check of of check automatic enable to Possibility . 6 . 0 ver. 6. ver. Technology is a Copyright © 2013 by OPEN CASCADE Page Copyright OPEN CASCADE 2013by © e 6. minor 5. 5 of . release, which includes 6 OpenCASCADE Technology . 0 4 project files files project ort . 3Dviewer over libraries 1 2 5 of 0 32 new 6 and and . -
Development of a Coupling Approach for Multi-Physics Analyses of Fusion Reactors
Development of a coupling approach for multi-physics analyses of fusion reactors Zur Erlangung des akademischen Grades eines Doktors der Ingenieurwissenschaften (Dr.-Ing.) bei der Fakultat¨ fur¨ Maschinenbau des Karlsruher Instituts fur¨ Technologie (KIT) genehmigte DISSERTATION von Yuefeng Qiu Datum der mundlichen¨ Prufung:¨ 12. 05. 2016 Referent: Prof. Dr. Stieglitz Korreferent: Prof. Dr. Moslang¨ This document is licensed under the Creative Commons Attribution – Share Alike 3.0 DE License (CC BY-SA 3.0 DE): http://creativecommons.org/licenses/by-sa/3.0/de/ Abstract Fusion reactors are complex systems which are built of many complex components and sub-systems with irregular geometries. Their design involves many interdependent multi- physics problems which require coupled neutronic, thermal hydraulic (TH) and structural mechanical (SM) analyses. In this work, an integrated system has been developed to achieve coupled multi-physics analyses of complex fusion reactor systems. An advanced Monte Carlo (MC) modeling approach has been first developed for converting complex models to MC models with hybrid constructive solid and unstructured mesh geometries. A Tessellation-Tetrahedralization approach has been proposed for generating accurate and efficient unstructured meshes for describing MC models. For coupled multi-physics analyses, a high-fidelity coupling approach has been developed for the physical conservative data mapping from MC meshes to TH and SM meshes. Interfaces have been implemented for the MC codes MCNP5/6, TRIPOLI-4 and Geant4, the CFD codes CFX and Fluent, and the FE analysis platform ANSYS Workbench. Furthermore, these approaches have been implemented and integrated into the SALOME simulation platform. Therefore, a coupling system has been developed, which covers the entire analysis cycle of CAD design, neutronic, TH and SM analyses. -
The DUNE-Fem-DG Framework
Extendible and Efficient Python Framework for Solving Evolution Equations with Stabilized Discontinuous Galerkin Methods Andreas Dedner, Robert Klofkorn¨ ∗ Abstract This paper discusses a Python interface for the recently published DUNE-FEM- DG module which provides highly efficient implementations of the Discontinuous Galerkin (DG) method for solving a wide range of non linear partial differential equations (PDE). Although the C++ interfaces of DUNE-FEM-DG are highly flexible and customizable, a solid knowledge of C++ is necessary to make use of this powerful tool. With this work easier user interfaces based on Python and the Unified Form Language are provided to open DUNE-FEM-DG for a broader audience. The Python interfaces are demonstrated for both parabolic and first order hyperbolic PDEs. Keywords DUNE,DUNE-FEM, Discontinuous Galerkin, Finite Volume, Python, Advection-Diffusion, Euler, Navier-Stokes MSC (2010): 65M08, 65M60, 35Q31, 35Q90, 68N99 In this paper we introduce a Python layer for the DUNE-FEM-DG1 module [14] which is available open-source. The DUNE-FEM-DG module is based on DUNE [5] and DUNE- FEM [20] in particular and makes use of the infrastructure implemented by DUNE-FEM for seamless integration of parallel-adaptive Finite Element based discretization methods. DUNE-FEM-DG focuses exclusively on Discontinuous Galerkin (DG) methods for var- ious types of problems. The discretizations used in this module are described by two main papers, [17] where we introduced a generic stabilization for convection dominated problems that works on generally unstructured and non-conforming grids and [9] where we introduced a parameter independent DG flux discretization for diffusive operators. -
GPUSPH User Guide
GPUSPH User Guide version 5.0 — October 2016 Contents 1 Introduction 2 2 Anatomy of a project apart from the use of SALOME 2 3 Setting up and running the simulation without using the user in- terface 3 3.1 Case Examples .............................. 6 3.1.1 Framework setup ......................... 8 3.1.2 Generic simulation parameters .................. 11 3.1.3 SPH parameters .......................... 12 3.1.4 Physical parameters ....................... 13 3.1.5 Results parameters ........................ 14 3.2 Building and initializing the particle system .............. 14 4 Running your simulation 18 5 Setting up and running the simulation with the SALOME user in- terface 18 5.1 Preparing the geometry in GEOM .................... 18 5.2 Generating the mesh (optional) ..................... 20 5.3 Generating particle files with the Particle preprocessor ........ 21 5.4 Setting up and running the simulation with the GPUSPH solver ... 21 6 Visualizing the results 22 1 1 Introduction There are two ways to set up cases for GPUSPH: coding a Case file, or using the SALOME module GPUSPH solver. When coding the case file, it is possible to create the geometrical elements using built-in functions of GPUSPH (only for particle-type boundary conditions at the moment) or to read particle files generated by the Particle Preprocessor module of SALOME. Creating a case by hand corresponds to the creation of a new cusource file, with the associated header (e.g. MyCase.cu and MyCase.h), placing them under src/problems/user. This folder does not exist by default in GPUSPH, but it is recognised as a place to be scanned for case sources. -
Universidade Federal Do Rio Grande Do Sul
UNIVERSIDADE FEDERAL DO RIO GRANDE DO SUL ESCOLA DE ENGENHARIA FACULDADE DE ARQUITETURA PROGRAMA DE PÓS-GRADUAÇÃO EM DESIGN Eduardo da Cunda Fernandes DESIGN NO DESENVOLVIMENTO DE UM PROJETO DE INTERFACE: Aprimorando o processo de modelagem em programas de análise de estruturas tridimensionais por barras Dissertação de Mestrado Porto Alegre 2020 EDUARDO DA CUNDA FERNANDES Design no desenvolvimento de um projeto de interface: aprimorando o processo de modelagem em programas de estruturas tridimensionais por barras Dissertação apresentada ao Programa de Pós- Graduação em Design da Universidade Federal do Rio Grande do Sul, como requisito parcial à obtenção do título de Mestre em Design. Orientador: Prof. Dr. Fábio Gonçalves Teixeira Porto Alegre 2020 Catalogação da Publicação Fernandes, Eduardo da Cunda DESIGN NO DESENVOLVIMENTO DE UM PROJETO DEINTERFACE: Aprimorando o processo de modelagem em programas de análise de estruturas tridimensionais por barras / Eduardo da Cunda Fernandes. -- 2020. 230 f. Orientador: Fábio Gonçalves Teixeira. Dissertação (Mestrado) -- Universidade Federal do Rio Grande do Sul, Escola de Engenharia, Programa de Pós- Graduação em Design, Porto Alegre, BR-RS, 2020. 1. Design de Interface. 2. Análise Estrutural. 3.Modelagem Preditiva do Comportamento Humano. 4.Heurísticas da Usabilidade. 5. KLM-GOMS. I. Teixeira, Fábio Gonçalves, orient. II. Título. FERNANDES, E. C. Design no desenvolvimento de um projeto de interface: aprimorando o processo de modelagem em programas de análise de estruturas tridimensionais por barras. 2020. 142 f. Dissertação (Mestrado em Design) – Escola de Engenharia / Faculdade de Arquitetura, Universidade Federal do Rio Grande do Sul, Porto Alegre, 2020. Eduardo da Cunda Fernandes DESIGN NO DESENVOLVIMENTO DE UM PROJETO DED INTERFACE: aprimorando o processo de modelagem em programas de análise de estruturas tridimensionais por barras Esta Dissertação foi julgada adequada para a obtenção do Título de Mestre em Design, e aprovada em sua forma final pelo Programa de Pós-Graduação em Design da UFRGS. -
Alternative Pre-Processing Tools for Elmer
Alternative pre-processing tools for Elmer ElmerTeam CSC – IT Center for Science, Finland CSC, 2018 Mesh generation capabilities of Elmer suite • ElmerGrid onative generation of simple structured meshes • ElmerGUI oplugins for tetgen, netgen and ElmerGrid • No geometry generation tools to speak about • No capability for multibody Delaunay meshing • Limited control over mesh quality and density • Complex meshes must be created by other tools! Open Source software for Computational Engineering Open source software in computational engineering • Academicly rooted stuff is top notch oLinear algebra, solver libraries oPetSc, Trilinos, OpenFOAM, LibMesh++, … • CAD and mesh generation not that competitive oOpenCASCADE legacy software oMesh generators netgen, tetgen, Gmsh are clearly academic oAlso for OpenFOAM there is development of commercial preprocessing tools • Users may need to build their own workflows from the most suitable tools oAlso in combination with commerial software Open Source Mesh Generation Software for Elmer • ElmerGrid: native to Elmer • Gmsh oSimple structured mesh generation oIncludes geometry definition tools oSimple mesh manipulation oElmerGUI/ElmerGrid can read the format oUsable via ElmerGUI msh format • ElmerMesh2D • SALOME oObsolite 2D Delaunay mesh generator oElmerGrid can read the unv format usable via the old ElmerFront written by SALOME oPreliminary version for direct interface to • Netgen Elmer oCan write linear meshes in Elmer format oUsable also as ElmerGUI plug-in • FreeCAD • Tetgen oOpen source community -
SALOME 7.2.0 Release Notes
SALOME : The Open Source Integration Platform for Numerical Simulation SALOME 7.2.0 Major release announcement May 2013 GENERAL INFORMATION CEA/DEN, EDF R&D and OPEN CASCADE are pleased to announce SALOME version 7.2.0. It is a major release that contains the results of planned major and minor improvements and bug fixes against SALOME version 6.6.0 released in December 2012. SALOME Platform SALOME Platform Copyright © 2001- 2013. All rights reserved. Page 1 of 32 SALOME : The Open Source Integration Platform for Numerical Simulation Table of Contents GENERAL INFORMATION ........................................................................................................................1 NEW FEATURES AND IMPROVEMENTS ................................................................................................3 PREREQUISITES CHANGES .................................................................................................................................3 License restrictions......................................................................................................................................4 MAJOR CHANGES ..............................................................................................................................................5 Removal of med v2.1 support .....................................................................................................................5 Removal of MEDMEM API..........................................................................................................................5 -
Abstractions and Automated Algorithms for Mixed Domain Finite Element Methods
Abstractions and automated algorithms for mixed domain finite element methods CÉCILE DAVERSIN-CATTY, Simula Research Laboratory, Norway CHRIS N. RICHARDSON, BP Institute, University of Cambridge, United Kingdom ADA J. ELLINGSRUD, Simula Research Laboratory, Norway MARIE E. ROGNES, Simula Research Laboratory, Norway Mixed dimensional partial differential equations (PDEs) are equations coupling unknown fields defined over domains of differing topological dimension. Such equations naturally arise in a wide range of scientific fields including geology, physiology, biology and fracture mechanics. Mixed dimensional PDEs arealso commonly encountered when imposing non-standard conditions over a subspace of lower dimension e.g. through a Lagrange multiplier. In this paper, we present general abstractions and algorithms for finite element discretizations of mixed domain and mixed dimensional PDEs of co-dimension up to one (i.e. nD-mD with jn −mj 6 1). We introduce high level mathematical software abstractions together with lower level algorithms for expressing and efficiently solving such coupled systems. The concepts introduced here have alsobeen implemented in the context of the FEniCS finite element software. We illustrate the new features through a range of examples, including a constrained Poisson problem, a set of Stokes-type flow models and a model for ionic electrodiffusion. CCS Concepts: • Mathematics of computing → Solvers; Partial differential equations; • Computing methodologies → Modeling methodologies. Additional Key Words and Phrases: FEniCS project, mixed dimensional, mixed domains, mixed finite elements 1 INTRODUCTION Mixed dimensional partial differential equations (PDEs) are systems of differential equations coupling solution fields defined over domains of different topological dimensions. Problem settings that call for such equations are in abundance across the natural sciences [27, 47], in multi-physics problems [13, 48], and in mathematics [8, 29].