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Creating dynamic equivalent PV circuit models with impedance spectroscopy for arc-fault modeling.

Description: Article 690.11 in the 2011 National Electrical Code{reg_sign} (NEC{reg_sign}) requires new photovoltaic (PV) systems on or penetrating a building to include a listed arc fault protection device. Currently there is little experimental or empirical research into the behavior of the arcing frequencies through PV components despite the potential for modules and other PV components to filter or attenuate arcing signatures that could render the arc detector ineffective. To model AC arcing signal propagation along PV strings, the well-studied DC diode models were found to inadequately capture the behavior of high frequency arcing signals. Instead dynamic equivalent circuit models of PV modules were required to describe the impedance for alternating currents in modules. The nonlinearities present in PV cells resulting from irradiance, temperature, frequency, and bias voltage variations make modeling these systems challenging. Linearized dynamic equivalent circuits were created for multiple PV module manufacturers and module technologies. The equivalent resistances and capacitances for the modules were determined using impedance spectroscopy with no bias voltage and no irradiance. The equivalent circuit model was employed to evaluate modules having irradiance conditions that could not be measured directly with the instrumentation. Although there was a wide range of circuit component values, the complex impedance model does not predict filtering of arc fault frequencies in PV strings for any irradiance level. Experimental results with no irradiance agree with the model and show nearly no attenuation for 1 Hz to 100 kHz input frequencies.
Date: June 1, 2011
Creator: Johnson, Jay Dean; Kuszmaul, Scott S.; Strauch, Jason E. & Schoenwald, David Alan
Partner: UNT Libraries Government Documents Department

Survey of sampling-based methods for uncertainty and sensitivity analysis.

Description: Sampling-based methods for uncertainty and sensitivity analysis are reviewed. The following topics are considered: (1) Definition of probability distributions to characterize epistemic uncertainty in analysis inputs, (2) Generation of samples from uncertain analysis inputs, (3) Propagation of sampled inputs through an analysis, (4) Presentation of uncertainty analysis results, and (5) Determination of sensitivity analysis results. Special attention is given to the determination of sensitivity analysis results, with brief descriptions and illustrations given for the following procedures/techniques: examination of scatterplots, correlation analysis, regression analysis, partial correlation analysis, rank transformations, statistical tests for patterns based on gridding, entropy tests for patterns based on gridding, nonparametric regression analysis, squared rank differences/rank correlation coefficient test, two dimensional Kolmogorov-Smirnov test, tests for patterns based on distance measures, top down coefficient of concordance, and variance decomposition.
Date: June 1, 2006
Creator: Johnson, Jay Dean; Helton, Jon Craig; Sallaberry, Cedric J. & Storlie, Curt B.
Partner: UNT Libraries Government Documents Department

Representation of analysis results involving aleatory and epistemic uncertainty.

Description: Procedures are described for the representation of results in analyses that involve both aleatory uncertainty and epistemic uncertainty, with aleatory uncertainty deriving from an inherent randomness in the behavior of the system under study and epistemic uncertainty deriving from a lack of knowledge about the appropriate values to use for quantities that are assumed to have fixed but poorly known values in the context of a specific study. Aleatory uncertainty is usually represented with probability and leads to cumulative distribution functions (CDFs) or complementary cumulative distribution functions (CCDFs) for analysis results of interest. Several mathematical structures are available for the representation of epistemic uncertainty, including interval analysis, possibility theory, evidence theory and probability theory. In the presence of epistemic uncertainty, there is not a single CDF or CCDF for a given analysis result. Rather, there is a family of CDFs and a corresponding family of CCDFs that derive from epistemic uncertainty and have an uncertainty structure that derives from the particular uncertainty structure (i.e., interval analysis, possibility theory, evidence theory, probability theory) used to represent epistemic uncertainty. Graphical formats for the representation of epistemic uncertainty in families of CDFs and CCDFs are investigated and presented for the indicated characterizations of epistemic uncertainty.
Date: August 1, 2008
Creator: Johnson, Jay Dean (ProStat, Mesa, AZ); Helton, Jon Craig (Arizona State University, Tempe, AZ); Oberkampf, William Louis & Sallaberry, Cedric J.
Partner: UNT Libraries Government Documents Department

Probability of loss of assured safety in temperature dependent systems with multiple weak and strong links.

Description: Relationships to determine the probability that a weak link (WL)/strong link (SL) safety system will fail to function as intended in a fire environment are investigated. In the systems under study, failure of the WL system before failure of the SL system is intended to render the overall system inoperational and thus prevent the possible occurrence of accidents with potentially serious consequences. Formal developments of the probability that the WL system fails to deactivate the overall system before failure of the SL system (i.e., the probability of loss of assured safety, PLOAS) are presented for several WWSL configurations: (i) one WL, one SL, (ii) multiple WLs, multiple SLs with failure of any SL before any WL constituting failure of the safety system, (iii) multiple WLs, multiple SLs with failure of all SLs before any WL constituting failure of the safety system, and (iv) multiple WLs, multiple SLs and multiple sublinks in each SL with failure of any sublink constituting failure of the associated SL and failure of all SLs before failure of any WL constituting failure of the safety system. The indicated probabilities derive from time-dependent temperatures in the WL/SL system and variability (i.e., aleatory uncertainty) in the temperatures at which the individual components of this system fail and are formally defined as multidimensional integrals. Numerical procedures based on quadrature (i.e., trapezoidal rule, Simpson's rule) and also on Monte Carlo techniques (i.e., simple random sampling, importance sampling) are described and illustrated for the evaluation of these integrals. Example uncertainty and sensitivity analyses for PLOAS involving the representation of uncertainty (i.e., epistemic uncertainty) with probability theory and also with evidence theory are presented.
Date: December 1, 2004
Creator: Johnson, Jay Dean (ProStat, Mesa, AZ); Oberkampf, William Louis & Helton, Jon Craig (Arizona State University, Tempe, AZ)
Partner: UNT Libraries Government Documents Department

Verification test problems for the calculation of probability of loss of assured safety in temperature-dependent systems with multiple weak and strong links.

Description: Four verification test problems are presented for checking the conceptual development and computational implementation of calculations to determine the probability of loss of assured safety (PLOAS) in temperature-dependent systems with multiple weak links (WLs) and strong links (SLs). The problems are designed to test results obtained with the following definitions of loss of assured safety: (1) Failure of all SLs before failure of any WL, (2) Failure of any SL before failure of any WL, (3) Failure of all SLs before failure of all WLs, and (4) Failure of any SL before failure of all WLs. The test problems are based on assuming the same failure properties for all links, which results in problems that have the desirable properties of fully exercising the numerical integration procedures required in the evaluation of PLOAS and also possessing simple algebraic representations for PLOAS that can be used for verification of the analysis.
Date: June 1, 2006
Creator: Johnson, Jay Dean (ProStat, Mesa, AZ); Oberkampf, William Louis & Helton, Jon Craig (Arizona State University, Tempe, AZ)
Partner: UNT Libraries Government Documents Department

Radionuclide transport in the vicinity of the repository and associated complementary cumulative distribution functions in the 1996 performance assessment for the Waste Isolation Pilot Plant

Description: The following topics related to radionuclide transport in the vicinity of the repository in the 1996 performance assessment for the Waste Isolation Pilot Plant are presented (1) mathematical description of models, (2) uncertainty and sensitivity analysis results arising from subjective (i.e., epistemic) uncertainty for individual releases, (3) construction of complementary cumulative distribution functions (CCDFs) arising from stochastic (i.e., aleatory) uncertainty, and (4) uncertainty and sensitivity analysis results for CCDFs. The presented results indicate that no releases to the accessible environment take place due to radionuclide movement through the anhydrite marker beds, through the Dewey Lake Red Beds or directly to the surface, and also that the releases to the Culebra Dolomite are small. Even when the effects of uncertain analysis inputs are taken into account, the CCDFs for release to the Culebra Dolomite fall to the left of the boundary line specified in the US Environmental Protection Agency's standard for the geologic disposal of radioactive waste (40 CFR 191, 40 CFR 194).
Date: May 22, 2000
Creator: STOCKMAN,CHRISTINE T.; GARNER,J.W.; HELTON,JON CRAIG; JOHNSON,JAY DEAN; SHINTA,A. & SMITH,L.N.
Partner: UNT Libraries Government Documents Department