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Uncertainty Analysis of Decomposing Polyurethane FoamSensitivity/uncertainty analyses are necessary to determine where to allocate resources for improved predictions in support of our nation's nuclear safety mission. Yet, sensitivity/uncertainty analyses are not commonly performed on complex combustion models because the calculations are time consuming, CPU intensive, nontrivial exercises that can lead to deceptive results. To illustrate these ideas, a variety of sensitivity/uncertainty analyses were used to determine the uncertainty associated with thermal decomposition of polyurethane foam exposed to high radiative flux boundary conditions. The polyurethane used in this study is a rigid closed-cell foam used as an encapsulant. Related polyurethane binders such as Estane are used in many energetic materials of interest to the JANNAF community. The complex, finite element foam decomposition model used in this study has 25 input parameters that include chemistry, polymer structure, and thermophysical properties. The response variable was selected as the steady-state decomposition front velocity calculated as the derivative of the decomposition front location versus time. An analytical mean value sensitivity/uncertainty (MV) analysis was used to determine the standard deviation by taking numerical derivatives of the response variable with respect to each of the 25 input parameters. Since the response variable is also a derivative, the standard deviation was essentially determined from a second derivative that was extremely sensitive to numerical noise. To minimize the numerical noise, 50-micrometer element dimensions and approximately 1-msec time steps were required to obtain stable uncertainty results. As an alternative method to determine the uncertainty and sensitivity in the decomposition front velocity, surrogate response surfaces were generated for use with a constrained Latin Hypercube Sampling (LHS) technique. Two surrogate response surfaces were investigated: 1) a linear surrogate response surface (LIN) and 2) a quadratic response surface (QUAD). The LHS techniques do not require derivatives of the response variable and are subsequently relatively insensitive to numerical noise. To compare the LIN and QUAD methods to the MV method, a direct LHS analysis (DLHS) was performed using the full grid and timestep resolved finite element model. The surrogate response models (LIN and QUAD) are shown to give acceptable values of the mean and standard deviation when compared to the fully converged DLHS model.
Document ID
Acquisition Source
Legacy CDMS
Document Type
Conference Paper
Hobbs, Michael L.
(Sandia National Labs. Albuquerque, NM United States)
Romero, Vicente J.
(Sandia National Labs. Albuquerque, NM United States)
Date Acquired
August 20, 2013
Publication Date
November 1, 2000
Publication Information
Publication: JANNAF 1st Modeling and Simulation Subcommittee Meeting
Subject Category
Nonmetallic Materials
Meeting Information
Meeting: Modeling and Simulation Subcommittee
Location: Monterey, CA
Country: United States
Start Date: November 13, 2000
End Date: November 17, 2000
Sponsors: Department of the Navy, Department of the Army, NASA Headquarters, Department of the Air Force
Distribution Limits
Work of the US Gov. Public Use Permitted.

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