skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Material-based Stratification

Abstract

A simple probability model was applied to detection sampling in a room or space in which different surface materials are present. The model assesses the overall detection capability when the sampling and analytical methods have different performance properties for the different materials. The results suggest that some common sampling strategies may not be ideal. In particular: (1) In a single room or area that includes different surface types with different detection properties, do not use a single sampling grid with a common spacing throughout. (2) If it is known or strongly suspected that one material has better detection properties than the other, place all samples on that material. (3) When it is completely unknown which material has the better detection properties, allocate the samples equally between them.

Authors:
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
919964
Report Number(s):
UCRL-TR-231455
TRN: US200825%%400
DOE Contract Number:
W-7405-ENG-48
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; DETECTION; PERFORMANCE; PROBABILITY; SAMPLING; STRATIFICATION

Citation Formats

MacQueen, D H. Material-based Stratification. United States: N. p., 2007. Web. doi:10.2172/919964.
MacQueen, D H. Material-based Stratification. United States. doi:10.2172/919964.
MacQueen, D H. Thu . "Material-based Stratification". United States. doi:10.2172/919964. https://www.osti.gov/servlets/purl/919964.
@article{osti_919964,
title = {Material-based Stratification},
author = {MacQueen, D H},
abstractNote = {A simple probability model was applied to detection sampling in a room or space in which different surface materials are present. The model assesses the overall detection capability when the sampling and analytical methods have different performance properties for the different materials. The results suggest that some common sampling strategies may not be ideal. In particular: (1) In a single room or area that includes different surface types with different detection properties, do not use a single sampling grid with a common spacing throughout. (2) If it is known or strongly suspected that one material has better detection properties than the other, place all samples on that material. (3) When it is completely unknown which material has the better detection properties, allocate the samples equally between them.},
doi = {10.2172/919964},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu May 31 00:00:00 EDT 2007},
month = {Thu May 31 00:00:00 EDT 2007}
}

Technical Report:

Save / Share:
  • This report documents the junction-based interphase drag and the modifications to the vertical stratification model in RELAP5/MOD3. Background information, model description and solution method, coding changes, input requirements, output description, and assessment of these changes are described in the report. The use of the junction-based interphase drag improved the void fraction data comparison for the JAERI TPTF tests. Modifications to the vertical stratification model gave the model a better physical and numerical basis, but further refinements will be needed. 26 refs., 29 figs., 1 tab.
  • The dimensionless parameters associated with the thermal stratification and pressure history of a heated container of liquid and its vapor were examined. The Modified Grashof number, the Fourier number, and an Interface number were parameterized using a single test liquid, Freon 113. Cylindrical test tanks with spherical dome end caps were built. Blanket heaters covered the tanks and thermocouples monitored the temperatures of the liquid, the ullage, the tank walls, and the foam insulation encapsulating the tank. A centrifuge was used for the 6 inch tank to preserve the same scaling parameter values between it and the larger tanks. Testsmore » were conducted over a range of Gr) values and the degree of scaling was checked by comparing the dimensionless pressures and temperatures for each scaled pair of tests. Results indicate that the bulk liquid temperature, the surface temperature of the liquid, and the tank pressure can be scaled with the three dimensionless parameters. Some deviation was, however, found in the detailed temperature profiles between the scaled pairs of tests. (GRA)« less
  • The identification and selection of materials survivable in an NBC environment is an important consideration throughout the Department of Defense. The US Army Chemical Research, Development and Engineering Center was asked by other services to evaluate the feasibility of compiling a list of materials that are survivable in a NBC environment and compatible with current decontamination substances. The feasible characteristics of a candidate NBCCS Materials Guide are discussed herein. Thermodynamic predictive methodologies evaluated in the studies included approaches on polymer solubility phase diagrams, equation-of-state, and universal group contribution activity coefficient estimates. The studies required to generate the guide and themore » resources required are estimated. The evaluation concluded that a limited but potentially useful NBCCS Materials Guide appears to be feasible.... NBCCS, Material compatibility, Chemical defense, Polymer-liquid interaction, Material(s) database, Chemical defense materials database.« less
  • The degradation of the material in critical components is shown to be an effective measure which can be used to compute the risk adjusted economic penalty associated with different maintenance decisions. The approach of estimating the probability, with confidence interval, of the time that a prescribed degradation level is exceeded is shown to be practical, as demonstrated in the analysis of irradiated fuel cladding. The methodology for the estimation of the probability is predicated on the existence of a parsimonious and robust mixed-effects model of the evolution of the degradation. This model, in general, relates measured surrogates of the degradationmore » level to computed or measured variables, which characterize the environment during the operating history of the component. We propose and demonstrate the efficacy of using an artificial neural network, constructed via a genetic supervisor, as an aid in developing the requisite mixed-effects model and testing its continued validity as new data are obtained.« less