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Manuscript Title: PUQ: a code for non-intrusive uncertainty propagation in computer simulations
Authors: Martin Hunt, Benjamin Haley, Michael McLennan, Marisol Koslowski, Jayathi Murthy, Alejandro Strachan
Program title: PUQ
Catalogue identifier: AEWP_v1_0
Distribution format: tar.gz
Journal reference: Comput. Phys. Commun. 194(2015)97
Programming language: Python, C.
Computer: Workstations.
Operating system: Linux, Mac OSX.
Keywords: Uncertainty Quantification, Surrogate Model, Sensitivity Analysis.
Classification: 4.11, 4.12, 4.13.

External routines: SciPy, Matplotlib, h5py

Nature of problem:
Uncertainty propagation and creation of response surfaces.

Solution method:
Generalized Polynomial Chaos (gPC) using Smolyak sparse grids.

Running time:
PUQ performs uncertainty quantification and sensitivity analysis by running a simulation multiple times using different values for input parameters. Its run time will be the product of the run time of the chosen simulation code and the number of runs required to achieve the desired accuracy.