Search Results for "python finite element heat"
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Showing 9 open source projects for "python finite element heat"
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FEATool Multiphysics - FEA & CFD Toolbox
FEATool Multiphysics is an easy-to-use FEA and CFD Simulation Toolbox
FEATool Multiphysics (https://www.featool.com) is a fully integrated toolbox for computer aided engineering CAE, finite element analysis & fluid dynamics simulations. With a very easy-to-use GUI, anyone is now able to quickly set up and perform large scale dynamical and complex engineering physics simulations, with coupled fluid flow, heat transfer, structural mechanics, chemical transport, and electromagnetics effects, without having to learn complex programming. ... -
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OpenNum
OpenNum lets you distribute solvers with a nice graphical interface
Typically, to program a GUI is time consuming and requires experience with graphic libraries. OpenNum lets you create a graphical interface adapted to your solvers by simply editing an XML configuration file. More specifically, OpenNum lets you · to collect a hierarchical dataset, · to call any executable file and · to visualize scalar and vector fields, plot graphs or show simple plain text files. It also has other useful utilities specifically designed for numerical... -
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Python/FEniCS Examples
phase-field simulation and other examples with Python/FEniCS
The main goal of this project was developing phase-field simulations of lithium dendrite growth with FEniCS programmed in Python. The problem was based in the grand potential-based model of Zijian Hong and Venkatasubramanian Viswanathan (https://doi.org/10.1021/acsenergylett.8b01009) . Some simpler examples were developed before for a first approach with FEniCS: heat equation and combustion model. -
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APBS
Biomolecular electrostatics software
This software has moved to http://www.poissonboltzmann.org/. -
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2D Structural Analysis
Determine the bending moments, shear forces, axial forces and displace
2D Structural Analysis in Python by Ritchie Vink A collection examples of 2D Finite Element Analysis (FEA) made with Jupyter Notebook Lab - https://jupyter.org/ To install Jupyter - https://jupyter.org/install ===== App is available on Play Store -> https://play.google.com/store/apps/details?id=com.ulm.struct If you want to download a python editor for your android smartphone follow this link -> https://play.google.com/store/apps/details? -
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NGSolve is a general purpose Finite Element Library on top of Netgen. With the basic library one can solve heat flow equations, Maxwell equations, and solid mechanical problems. Several add-ons are available for particular application classes. New paper: J. Schöberl: "C++11 Implementation of Finite Elements in NGSolve", ASC Report 30/2014, Institute for Analysis and Scientific Computing, Vienna University of Technology, 2014 http://www.asc.tuwien.ac.at/~schoeberl/wiki/publications/ngs-cpp11.pdf
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Advanced Numerical Instruments 2D
Advanced numerical instruments: adaptive meshing, FE methods, solvers
Ani2D provides portable libraries for each step in the numerical solution of systems of PDEs with variable tensorial coefficients: (1) unstructured adaptive mesh generation, (2) metric-based mesh adaptation, (3) finite element discretization and interpolation, (4) algebraic solvers. -
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fesslix
Stochastic Analysis
A brief summary of the main features of Fesslix: - Perform non-intrusive reliability analysis or Bayesian updating either --- by running commands on the command line or --- by means of an Octave interface or --- by means of a Python interface - Flexible input language for writing Fesslix parameter files --- Control flow statements (e.g. if, for, while) --- Most parameters can be defined as functions - Working with response surfaces - Linear finite element analysis using truss, beam and plane stress/strain elements - Spectral Stochastic Finite Elements - Bayesian networks This is the download page for Windows executables of Fesslix. -
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FEVal, the Finite Element Evaluator written in Python, provides easy conversion for many Finite Element data formats (both binary and ascii). Mesh modification is very easy. Values of model results can be accessed given coordinates in physical space.
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