Name: Ramakant Gadhewal
Type: User
Company: Newtrace Pvt Ltd
Bio: Ph.D. PEM Fuel Cell Modeling, Chemical Engineering at NIT, Warangal, India
Location: Bengaluru ,India
Blog: https://www.linkedin.com/in/ramakant-gadhewal-34086661/
Ramakant Gadhewal's Projects
Numerical Linear Algebra, Trefethen and Bau, 1997.
This repository is for Numerical Method Lab Practice. Solving 7 problem with c++.
Numerical Methods class C++ implementations
Numerical Methods written in Python for Univeristy Project
Repository for numerical methods of linear algebra and calculus.
A collection of numerical linear algebra course assignments using MATLAB
Numerical methods implementation in C++.
Numerical Methods in Python.
My Computer Engineering course subject NMA problem activities with my own solution.
Numerical Methods Implementation in C++
Jupyter notebook class notes for Numerical Methods for PDEs
Finite element analysis of a 1D uniaxial bar system
A collection of programs implementing numerical methods to solve ordinary and partial differential equations (ODEs and PDEs). Methods include: Finite Differences, Method of Characteristics, Lax-Wendroff, Shooting Method, and GCL Spectral Collocation. A variety of time-stepping schemes are also utilized.
MATLAB Implementations of common Optimisation Methods
Implementing algorithms from Nocedal and Wright's "Numerical Optimization"
Some algorithms on numeric approximation and calculus using matlab. The files in pdf contain discussion on the respective algorithms, comparing methods for achieving given tasks, explaining how the code works and analyzing computational efficiency.
Numerical Gaussian Processes for Time-dependent and Non-linear Partial Differential Equations
The aim of the project is to numerically model Rutherford scattering and investigate how an α-particle is affected by the nucleus of an atom. The repository includes the source code, word document of the paper and a PDF format version of the paper. This paper was written as an entry to the Computational Physics Prize of Eton College in 2022. The project received a overall of 2nd runner up ('Highly Commendable'), and it was the winner of the non-specialist class (Y11 and below).
Some open material relating to the Southampton Numerical Methods course
Es una biblioteca desarrollada en C++ 11 para implementar métodos numéricos
University course homework: numerical methods of linear algebra
Steepest Descent, Newton, Quasi-Newton, Conjugate Gradient, Simplex Method
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