grseb9s / uq_matlab Goto Github PK
View Code? Open in Web Editor NEWThis project forked from gauss1986/uq_matlab
Matlab code for uncertainty quantification of stochastic ODEs.
This project forked from gauss1986/uq_matlab
Matlab code for uncertainty quantification of stochastic ODEs.
This package is tailored to compute results for paper 'Anchoored ANOVA Petrov-Galerkin projection schemes for linear stochastic structural dynamics', Author: Lin Gao, Christophe Audouze, Prasanth Nair. University of Toronto. 2015. The main routines (Monte Carlo simulation, gPC-Galerkin, GSD and AAPG) are contained in function main.m. The driveing functions beam.m and hex.m are used to set parameters for specific problem and compute solutions by calling main.m. Run beam.m would generate Figure 1-7. Run hex.m would generate Figure 9-10. Visulizaiton of the mesh for the hex shaped structure (Figure 8) was done in third-party software. Scaling study (Figure 11) was done by running hex.m multiple times, save relevant data and plot, where GS_ord=1. Data are saved in errors_M20.mat and CPU_M20.mat. The mass(M), damping(C), (stochastic) stiffness(K) and forcing(F) matrices are loaded from geobeam.mat and geohex5.mat respectively. For easy testing, default setting in hex.m and beam.m for Monte Carlo simulation sample size is 100. Results with relatively large number of sample size are provided. Default setting when generating figures is to use these results. See line 35-56 in hex.m and line 47-48 in beam.m for details. Consider the following ways to save time in testing: For Monte Carlo simulation: change sample size N. For Ghanem-Spanos(GS) method: set GS_ord to 1 instead of 2 or 3. For GSD method: set Kmodes = [5]. For AAPG method: set AAPG_GS_ord = 1 instead of 2 in main.m.
A declarative, efficient, and flexible JavaScript library for building user interfaces.
๐ Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
An Open Source Machine Learning Framework for Everyone
The Web framework for perfectionists with deadlines.
A PHP framework for web artisans
Bring data to life with SVG, Canvas and HTML. ๐๐๐
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
Some thing interesting about web. New door for the world.
A server is a program made to process requests and deliver data to clients.
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
Some thing interesting about visualization, use data art
Some thing interesting about game, make everyone happy.
We are working to build community through open source technology. NB: members must have two-factor auth.
Open source projects and samples from Microsoft.
Google โค๏ธ Open Source for everyone.
Alibaba Open Source for everyone
Data-Driven Documents codes.
China tencent open source team.