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

Title: Capability 2 - Predictive Simulation.

Abstract

Abstract not provided.

Authors:
;  [1]; ;
  1. (NREL)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1367307
Report Number(s):
SAND2017-5384D
653479
DOE Contract Number:
AC04-94AL85000
Resource Type:
Conference
Resource Relation:
Conference: Proposed for presentation at the NREL/SNL/BNL Photovoltaic Reliability Workshops held February 28 - March 2, 2017 in Lakewood, CO.
Country of Publication:
United States
Language:
English

Citation Formats

Van Benthem, Mark, Barnes, Teresa, Van Benthem, Mark, and Roberts, Scott Alan. Capability 2 - Predictive Simulation.. United States: N. p., 2017. Web.
Van Benthem, Mark, Barnes, Teresa, Van Benthem, Mark, & Roberts, Scott Alan. Capability 2 - Predictive Simulation.. United States.
Van Benthem, Mark, Barnes, Teresa, Van Benthem, Mark, and Roberts, Scott Alan. Mon . "Capability 2 - Predictive Simulation.". United States. doi:. https://www.osti.gov/servlets/purl/1367307.
@article{osti_1367307,
title = {Capability 2 - Predictive Simulation.},
author = {Van Benthem, Mark and Barnes, Teresa and Van Benthem, Mark and Roberts, Scott Alan},
abstractNote = {Abstract not provided.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Mon May 01 00:00:00 EDT 2017},
month = {Mon May 01 00:00:00 EDT 2017}
}

Conference:
Other availability
Please see Document Availability for additional information on obtaining the full-text document. Library patrons may search WorldCat to identify libraries that hold this conference proceeding.

Save / Share:
  • No abstract prepared.
  • Sandia National Laboratories conducted two heavily instrumented single borehole cratering tests during 1983 at the Anvil Points Mine. These tests, one stemmed and one unstemmed, were executed expressly to provide baseline data for correlation with existing rock fragmentation models, to provide input for the development and verification of rock motion models, and to investigate the effect of minimum gas pressure on rubblization. An extensive array of embedded sensors was employed to obtain diagnostic and response measurements. Photometric coverage with high speed framing cameras, monitoring anchored target movement, provided independent measurements of rock motion. Rubble excavation and screening provided data onmore » crater volumes and shapes, void percent, and fragment size distribution. Diagnostic measurements verified satisfactory and repeatable explosive and stemming performance. Crater depths and volumes were less than predicted and nearly equal for the stemmed and unstemmed tests. The particle size distributions were almost identical. The detonation-induced stress wave amplitudes and initial velocity changes were essentially the same. Rock motion measurements from sensor and photometric data compared favorably. Post-test calculations, using a finite element program, DYNA2D, compared well with early-time response measurements. Later-time rock motion data are being used in the development of discrete element programs, BLOCKS and BUMP. Use of the experimental data in the development of these models is discussed, along with comparisons of BLOCK model calculations with experimental results. These comparisons indicate that the BLOCKS model simulates later-time rock motion adequately.« less
  • Thirty-two grade profiles across the high grade dome of a porphyry copper deposit are fit by six possible element distribution functions. All six functions have a single maximum, approach or achieve a zero value away from the maximum, and are never negative. Four of the six functions are symmetric and have three parameters - symmetric triangle (SYT), ellipse (EPS), second order reciprocal (SOR), and second order exponential (SOE). Both remaining functions are asymmetric and have four parameters - sliding power exponential (SPE) and asymmetric triangle (AST). All six functions achieve reasonable fits of the Kriged grades for the complete profiles.more » In general, the four-parameter functions yield somewhat lower average absolute errors than do the three-parameter functions. Among the three-parameter functions, considering all profiles, the SOE function yields the best fit, with the SYT function a close second. The EPS function regularly underestimates grade in the halos whereas the SOR function overestimates it. Both four-parameter functions are asymmetric forms of a three parameter function. The better fits for complete profiles of the asymmetric forms do not differ significantly from those for the corresponding symmetric ones. Predictive capabilities for exploration applications are tested by fitting partial profiles, then comparing the resulting distributions with the remaining data of the complete profile. These predictions are of questionable value if all the known data are located prior to the element maximum. However, from the maximum onward, useful predictions of eventual deposit size may be made.« less
  • Indoor radon concentrations one to two orders of magnitude higher than the US average of approx.60 Bq m/sup -3/ (approx.1.5 pCi L/sup -1/) are not uncommon, and concentrations greater than 4000 Bq m/sup -3/ have been observed in houses in areas with no known artificially-enhanced radon sources. In general, source categories for indoor radon are well known: soil, domestic water, building materials, outdoor air, and natural gas. Soil is thought to be a major source of indoor radon, either through molecular diffusion (usually a minor component) or convective flow of soil gas. While soil gas flow into residences has beenmore » demonstrated, no detailed understanding of the important factors affecting the source strength of radon from soil has yet emerged. Preliminary work in this area has identified a number of likely issues, including the concentration of radium in the soil, the emanating fraction, soil type, soil moisture content, and other factors that would influence soil permeability and soil gas transport. Because a significant number of dwellings are expected to have indoor radon concentrations above guideline levels, a predictive capability is needed that would help identify geographical areas having the potential for high indoor concentrations. This paper reviews the preliminary work that has been done to identify important soil and building characteristics that influence the migration of radon and outlines the areas of further research necessary for development of a predictive method. 32 refs., 4 figs.« less