Pinned Repositories
cogen_eval
Uncertainty Quantification in the energy management of a CHP system
cst
EasyVVUQ
Python 3 framework to facilitate verification, validation and uncertainty quantification (VVUQ) for a wide variety of simulations.
K-RVEA
kufan-cst
MCMCPy
Python module for uncertainty quantification using a Markov chain Monte Carlo sampler
OpenMDAO-Framework
OpenMDAO is an open-source Multidisciplinary Design Analysis and Optimization (MDAO) framework, written in Python. It helps users solve complex problems by allowing them to link together analysis codes from multiple disciplines at multiple levels of fidelity. The development effort for OpenMDAO is being led out of the NASA Glenn Research Center in the MDAO branch. The development effort is being funded by the Fundamental Aeronautic Program, Subsonic Fixe Wing project. The ultimate goal is to provide a flexible common analysis platform that can be shared between industry, academia, and government.
pce
Polynomial Chaos Expansion
plantom007
Config files for my GitHub profile.
POD
implementation of the proper orthogonal decomposition
plantom007's Repositories
plantom007/cogen_eval
Uncertainty Quantification in the energy management of a CHP system
plantom007/cst
plantom007/EasyVVUQ
Python 3 framework to facilitate verification, validation and uncertainty quantification (VVUQ) for a wide variety of simulations.
plantom007/K-RVEA
plantom007/kufan-cst
plantom007/MCMCPy
Python module for uncertainty quantification using a Markov chain Monte Carlo sampler
plantom007/OpenMDAO-Framework
OpenMDAO is an open-source Multidisciplinary Design Analysis and Optimization (MDAO) framework, written in Python. It helps users solve complex problems by allowing them to link together analysis codes from multiple disciplines at multiple levels of fidelity. The development effort for OpenMDAO is being led out of the NASA Glenn Research Center in the MDAO branch. The development effort is being funded by the Fundamental Aeronautic Program, Subsonic Fixe Wing project. The ultimate goal is to provide a flexible common analysis platform that can be shared between industry, academia, and government.
plantom007/pce
Polynomial Chaos Expansion
plantom007/plantom007
Config files for my GitHub profile.
plantom007/POD
implementation of the proper orthogonal decomposition
plantom007/POD-PINN
POD-PINN code and manuscript
plantom007/polynomial_surrogates
Tools to construct surrogate models based on Hermitian polynomial bases. Includes full-factorial and sparse polynomial chaos expansions via least-angle regression as well as continuous-space low-rank approximations in canonical polyadics format.
plantom007/prog_algs
The Prognostic Algorithm Package is a python framework for model-based prognostics (computation of remaining useful life) of engineering systems, and provides a set of algorithms for state estimation and prediction, including uncertainty propagation. The algorithms take as inputs prognostic models (from NASA's Prognostics Model Package), and perform estimation and prediction functions. The library allows the rapid development of prognostics solutions for given models of components and systems. Different algorithms can be easily swapped to do comparative studies and evaluations of different algorithms to select the best for the application at hand.
plantom007/PyLdB
Calculates the perceived loudness of a pressure signature
plantom007/real_sga
标准遗传算法(简单遗传算法)，参照官方C语言版本进行python2.7语言重构。实数编码，轮盘赌选择，模拟二进制交叉(SBX),多项式变异。
plantom007/SAMOEAs
A Library of Surrogate-Assisted Multi-Objective Evolutionary Algorithms (SAMOEAs).
plantom007/SMCPy
Python module for uncertainty quantification using a parallel sequential Monte Carlo sampler
plantom007/sonicBoom_prediction
plantom007/Udacity_capstone
Udacity nanodegree capstone project
plantom007/vkikriging
Kriging and Gradient-Enhanced Kriging for the VKI Lecture Series