Non-Intrusive Computational Method and Uncertainty Quantification Tool for isolator operability calculations, Phase I

Metadata Updated: February 28, 2019

Computational fluid dynamics (CFD) simulations are extensively used by NASA for hypersonic aerothermodynamics calculations. The physical models used in CFD codes and initial/boundary conditions for numerical simulations carry significant uncertainties. There are also inherent errors in experiments designed for model validation, and numerical discretization. Despite this knowledge, only a limited number of efforts have been undertaken to formally characterize these uncertainties and to evaluate their impact on the predictive capability of CFD tools for hypersonic applications such as isolator dynamics. Major challenges with uncertainty quantification for such simulations include lack of sufficient data to characterize the associated uncertainties in the isolator dynamics phenomena and the computational cost of the required large number of cases. CFDRC in partnership with Virginia Tech and UTSI proposes to directly address these issues and deliver an non-intrusive tool for uncertainty quantification that can be integrated with the state-of-the-art CFD tools currently utilized by NASA and its customers. During Phase I, this team will develop and demonstrate a dimensionally adaptive sparse grid approach for uncertainty quantification coupled with NASA LaRC VULCAN-CFD code. In phase I, the developed tool will be demonstrated on the test rig developed and characterized at the NASA-LaRC Isolator Dynamics Research Lab. Surrogate models including polynomial response surface and gradient-enhanced Kriging will be developed based upon the samples generated from the adaptively sparse grid algorithm, thereby providing a modeling tool to estimate the operability of isolator over the relevant flight regime and ultimately to optimize design of isolator to prevent scramjet unstart. In Phase II, the framework will be further developed to include uncommon probability density distributions of uncertain parameters, and will be validated and demonstrated on more complex problems.

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Public: This dataset is intended for public access and use. License: U.S. Government Work

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Metadata Created Date August 1, 2018
Metadata Updated Date February 28, 2019

Metadata Source

Harvested from NASA Data.json

Additional Metadata

Resource Type Dataset
Metadata Created Date August 1, 2018
Metadata Updated Date February 28, 2019
Publisher Space Technology Mission Directorate
Unique Identifier TECHPORT_93668
Maintainer Email
Public Access Level public
Bureau Code 026:00
Metadata Context
Metadata Catalog ID
Schema Version
Catalog Describedby
Harvest Object Id c4fe5a49-fafb-4ae0-b8b0-f1c69624349f
Harvest Source Id 39e4ad2a-47ca-4507-8258-852babd0fd99
Harvest Source Title NASA Data.json
Data First Published 2017-12-01
Homepage URL
Data Last Modified 2018-07-19
Program Code 026:027
Source Datajson Identifier True
Source Hash 29083efa5b232d7b5a9f6fcef66c1d57dea908ce
Source Schema Version 1.1

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