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Title: Modeling Porous PMDI-based Polyurethane Foam Decomposition in Pressurizing Systems.

Abstract

Abstract not provided.

Authors:
; ; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-CA), Livermore, CA (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1424561
Report Number(s):
SAND2017-2123C
651150
DOE Contract Number:
AC04-94AL85000
Resource Type:
Conference
Resource Relation:
Conference: Proposed for presentation at the 10th U. S. National Combustion Meeting held April 23 - February 22, 2017 in College Park, Maryland.
Country of Publication:
United States
Language:
English

Citation Formats

Scott, Sarah Nicole, Dodd, Amanda B., Brunini, Victor, and Keedy, Ryan Michael. Modeling Porous PMDI-based Polyurethane Foam Decomposition in Pressurizing Systems.. United States: N. p., 2017. Web.
Scott, Sarah Nicole, Dodd, Amanda B., Brunini, Victor, & Keedy, Ryan Michael. Modeling Porous PMDI-based Polyurethane Foam Decomposition in Pressurizing Systems.. United States.
Scott, Sarah Nicole, Dodd, Amanda B., Brunini, Victor, and Keedy, Ryan Michael. Wed . "Modeling Porous PMDI-based Polyurethane Foam Decomposition in Pressurizing Systems.". United States. doi:. https://www.osti.gov/servlets/purl/1424561.
@article{osti_1424561,
title = {Modeling Porous PMDI-based Polyurethane Foam Decomposition in Pressurizing Systems.},
author = {Scott, Sarah Nicole and Dodd, Amanda B. and Brunini, Victor and Keedy, Ryan Michael},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Wed Feb 01 00:00:00 EST 2017},
month = {Wed Feb 01 00:00:00 EST 2017}
}

Conference:
Other availability
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  • Abstract not provided.
  • Rigid polyurethane foams are used as encapsulants to isolate and support thermally sensitive components within weapon systems. When exposed to abnormal thermal environments, such as fire, the polyurethane foam decomposes to form products having a wide distribution of molecular weights and can dominate the overall thermal response of the system. Decomposing foams have either been ignored by assuming the foam is not present, or have been empirically modeled by changing physical properties, such as thermal conductivity or emissivity, based on a prescribed decomposition temperature. The hypothesis addressed in the current work is that improved predictions of polyurethane foam degradation canmore » be realized by using a more fundamental decomposition model based on chemical structure and vapor-liquid equilibrium, rather than merely fitting the data by changing physical properties at a prescribed decomposition temperature. The polyurethane decomposition model is founded on bond breaking of the primary polymer and formation of a secondary polymer which subsequently decomposes at high temperature. The bond breaking scheme is resolved using percolation theory to describe evolving polymer fragments. The polymer fragments vaporize according to individual vapor pressures. Kinetic parameters for the model were obtained from Thermal Gravimetric Analysis (TGA) from a single nonisothermal experiment with a heating rate of 20 C/min. Model predictions compare reasonably well with a separate nonisothermal TGA weight loss experiment with a heating rate of 200 C/min.« less
  • Polymer foam encapsulants provide mechanical, electrical, and thermal isolation in engineered systems. It can be advantageous to surround objects of interest, such as electronics, with foams in a hermetically sealed container to protect the electronics from hostile en vironments, such as a crash that produces a fire. However, i n fire environments, gas pressure from thermal decomposition of foams can cause mechanical failure of the sealed system . In this work, a detailed study of thermally decomposing polymeric methylene diisocyanate (PMDI) - polyether - polyol based polyurethane foam in a sealed container is presented . Both experimental and computational workmore » is discussed. Three models of increasing physics fidelity are presented: No Flow, Porous Media, and Porous Media with VLE. Each model us described in detail, compared to experiment , and uncertainty quantification is performed. While the Porous Media with VLE model matches has the best agreement with experiment, it also requires the most computational resources.« less