Search Results for "partial differential"
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Showing 46 open source projects for "partial differential"
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VoronoiFVM.jl
Solution of nonlinear multiphysics partial differential equations
Solver for coupled nonlinear partial differential equations (elliptic-parabolic conservation laws) based on the Voronoi finite volume method. It uses automatic differentiation via ForwardDiff.jl and DiffResults.jl to evaluate user functions along with their jacobians and calculate derivatives of solutions with respect to their parameters. -
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MethodOfLines.jl
Automatic Finite Difference PDE solving with Julia SciML
MethodOfLines.jl is a Julia package for automated finite difference discretization of symbolically defined PDEs in N dimensions. It uses symbolic expressions for systems of partial differential equations as defined with ModelingToolkit.jl, and Interval from DomainSets.jl to define the space(time) over which the simulation runs. This project is under active development, therefore the interface is subject to change. The docs will be updated to reflect any changes, please check back for current usage information. -
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hermiteSolvers
Hermite based solvers for Partial Differential Equations
Solve partial differential equations using Hermite methods. Includes Matlab codes for problems in one and two dimensions, -
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Gridap.jl
Grid-based approximation of partial differential equations in Julia
Gridap provides a set of tools for the grid-based approximation of partial differential equations (PDEs) written in the Julia programming language. The library currently supports linear and nonlinear PDE systems for scalar and vector fields, single and multi-field problems, conforming and nonconforming finite element (FE) discretizations, on structured and unstructured meshes of simplices and n-cubes. -
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ReachabilityAnalysis.jl
Compute reachable states of dynamical systems
...In the scope of this package are systems modeled by continuous or hybrid dynamical systems, where the dynamics change with discrete events. Systems are modeled by ordinary differential equations (ODEs) or semi-discrete partial differential equations (PDEs), with uncertain initial states, uncertain parameters or non-deterministic inputs. -
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FourierFlows.jl
Tools for building fast, hackable, pseudospectral equation solvers
This software provides tools for partial differential equations on periodic domains using Fourier-based pseudospectral methods. A central intent of the software's design is also to provide a framework for writing new, fast solvers for new physical problems. The code is written in Julia. -
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101-0250-00
ETH course - Solving PDEs in parallel on GPUs
This course aims to cover state-of-the-art methods in modern parallel Graphical Processing Unit (GPU) computing, supercomputing and code development with applications to natural sciences and engineering. -
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NeuralPDE.jl
Physics-Informed Neural Networks (PINN) Solvers
NeuralPDE.jl is a Julia library for solving partial differential equations (PDEs) using physics-informed neural networks and scientific machine learning. Built on top of the SciML ecosystem, it provides a flexible and composable interface for defining PDEs and training neural networks to approximate their solutions. NeuralPDE.jl enables hybrid modeling, data-driven discovery, and fast PDE solvers in high dimensions, making it suitable for scientific research and engineering applications. -
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ApproxFun.jl
Julia package for function approximation
...The ApproxFun Documentation contains detailed information, or read on for a brief overview of the package. The documentation contains examples of usage, such as solving ordinary and partial differential equations. The ApproxFun Examples repo contains many examples of using this package, in Jupyter notebooks and Julia scripts. Note that this is independently maintained, so it might not always be in sync with the latest version of ApproxFun. We recommend checking the examples in the documentation first, as these will always be compatible with the latest version of the package. -
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DeepXDE
A library for scientific machine learning & physics-informed learning
DeepXDE is a library for scientific machine learning and physics-informed learning. DeepXDE includes the following algorithms. Physics-informed neural network (PINN). Solving different problems. Solving forward/inverse ordinary/partial differential equations (ODEs/PDEs) [SIAM Rev.] Solving forward/inverse integro-differential equations (IDEs) [SIAM Rev.] fPINN: solving forward/inverse fractional PDEs (fPDEs) [SIAM J. Sci. Comput.] NN-arbitrary polynomial chaos (NN-aPC): solving forward/inverse stochastic PDEs (sPDEs) [J. Comput. Phys.] PINN with hard constraints (hPINN): solving inverse design/topology optimization [SIAM J. ... -
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NeuralOperators.jl
DeepONets, Neural Operators, Physics-Informed Neural Ops in Julia
Neural operator is a novel deep learning architecture. It learns an operator, which is a mapping between infinite-dimensional function spaces. It can be used to resolve partial differential equations (PDE). Instead of solving by finite element method, a PDE problem can be resolved by training a neural network to learn an operator mapping from infinite-dimensional space (u, t) to infinite-dimensional space f(u, t). Neural operator learns a continuous function between two continuous function spaces. The kernel can be trained on different geometry, which is learned from a graph. ... -
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Book-Reviews-In-Mathematica
Partial Differential Equations, Complex Analysis, Mathematica, Farlow
Cliff* Notes, Mathematica Evaluatable "Partial Differential Equations for Scientists and Engineers", Farlow "Physics for Scientists and Engineers", Serway "A First Course in Complex Analysis", Beck "PDE", Asmar "PDE, An Introduction", Colton "Elementary Differential Equations", 7th, Rainville "Ordinary Differential Equations", Tenenbaum "Linear Algebra And It's Applications", Lay "Swokowski Calculus", 5th, Swokowski "Chemistry Concepts & Problems, A Self-Teaching Guide", Houk "Openstax Chemistry" "College Algebra and Trigonometry", 2nd, Kaufman * 2nd order cannonicalization SOLVER, cannonical form automatically * nth order PDE to System of n first order PDE matrices generator with ODE Decouple Solving (pde not yet) * radial probability plot for Hydrogen, pde shrodinger's * Planck blackbody, Rutherford essay * fermi free electron essay * Table of Nucleon positions for all Isotope w/Manipulate * p-p separation nucleus plot using the above -
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overtureFramework
A framework for solving partial differential equations
Overture is a framework for solving partial differential equations (PDEs) in complex, possibly moving geometry. Overture uses overlapping grids to represent the geometry. The software includes grid generation capabilities, PDE solvers for fluids, solids, and fluid-structure interactions (FSI) as well as electromagnetics. -
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Elmer finite element software
Open source finite element software for multiphysical problems
Elmer is a finite element software for numerical solution of partial differential equations and multiphysical problems. It includes models of structural mechanics, fluid dynamics, heat transfer, electromagnetics etc. Elmer home is www.csc.fi/elmer -
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XMDS
Fast integrator of stochastic partial differential equations
XMDS is a code generator that integrates equations. You write them down in human readable form in a XML file, and it goes away and writes and compiles a C++ program that integrates those equations as fast as it can possibly be done in your architecture. -
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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. In addition to... -
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GiNaCDE
A software for solving Nonlinear Differential Equations
GiNaCDE is free and open-source software that solves entirely automatically linear or nonlinear differential equations. In searching traveling wave solutions, this application converts the Nonlinear Partial Differential Equations (NLPDEs) into Nonlinear Ordinary Differential Equations (NLODEs) and gives the exact solutions when they exist. The Differential Equations are solved by F-expansion and first integral methods. In this project, we provide windows binary file for GiNaCDE. ... -
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DiffEqOperators.jl
Linear operators for discretizations of differential equations
DiffEqOperators.jl is a package for finite difference discretization of partial differential equations. It allows building lazy operators for high order non-uniform finite differences in an arbitrary number of dimensions, including vector calculus operators. For the operators, both centered and upwind operators are provided, for domains of any dimension, arbitrarily spaced grids, and for any order of accuracy. -
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OpenMCDF
Structured Storage .net component - pure C#
OpenMCDF is a 100% .net / C# component that allows developers to manipulate Microsoft Compound Document File Format for OLE structured storage. It supports read/write operations on streams and storages and traversal of structures tree. Development and issue tracking has moved to github platform at https://github.com/ironfede/openmcdf -
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Algorithms Math Models
MATLAB implementations of algorithms
...The repository gathers implementations and case studies across many topics commonly used in contest solutions: optimization (linear, integer, goal and nonlinear programming), heuristic and metaheuristic methods (simulated annealing, genetic algorithms, immune algorithms), neural networks and time-series methods, interpolation and regression, graph theory, cellular automata, grey systems, fuzzy models, partial/ordinary differential equations, and multivariate analysis, among others. The codebase is organized into topic folders (e.g., HeuristicAlgorithm, IntegerProgramming, NeuralNetwork, TimeSeries) and includes dozens of worked examples and links to textbook/source materials that the author used to assemble the collection. -
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ClimateMachine.jl
Earth System Model that automatically learns from data
The ClimateMachine is a software package that models the evolution of the Earth system over weeks to centuries. The ClimateMachine solves three-dimensional partial differential equations for the distributions of water, momentum, energy, and tracers such as carbon in the atmosphere, oceans, and on land. The ClimateMachine will harness a wide range of Earth observations and data generated computationally to predict the evolution of Earth’s climate and features such as droughts, rainfall extremes, and high-impact storms. -
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Radial++ is a C++ template library for scattered data interpolation in any dimension and also the numerical solution of partial differential equations. It provides generalized Radial Basis Functions (p.e. multiquadric, this-plate spline, etc).
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CFD Python
Sequence of Jupyter notebooks featuring the 12 Steps to Navier-Stokes
CFD Python, a.k.a. the 12 steps to Navier-Stokes, is a practical module for learning the foundations of Computational Fluid Dynamics (CFD) by coding solutions to the basic partial differential equations that describe the physics of fluid flow. The module was part of a course taught by Prof. Lorena Barba between 2009 and 2013 in the Mechanical Engineering department at Boston University (Prof. Barba since moved to George Washington University). The module assumes only basic programming knowledge (in any language) and some background in partial differential equations and fluid mechanics. ... -
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DEVSIM
TCAD Device Simulator
TCAD Device Simulator. DEVSIM is a semiconductor device simulation software, using the finite volume method. This software solves partial differential equations on a mesh. The Python interface allows the user to specify their own equations. -
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TIDES
Taylor series Integrator for Differential Equations
Taylor series Integrator for Differential EquationS. This software is developed by Profs. A. Abad, R. Barrio, F. Blesa and M. Rodriguez, (GME, University of Zaragoza, Spain). It consists on a C (Fortran) library, libTIDES, and a Mathematica package, MathTIDES. (MathTIDES requires Mathematica version >= 7.0) . Basic references: * A. Abad, R. Barrio, F. Blesa, M. Rodriguez, 2012. Algorithm 924: TIDES, a Taylor series Integrator for Differential EquationS, ACM TOMS. 39, no. 1, art. 5....
