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Risk Assessment of Hydrogen Fuel Cell Electric Vehicles in Tunnels

Fire Technology

Ehrhart, Brian D.; Brooks, Dusty M.; Muna, Alice B.; LaFleur, Chris B.

The need to understand the risks and implications of traffic incidents involving hydrogen fuel cell electric vehicles in tunnels is increasing in importance with higher numbers of these vehicles being deployed. A risk analysis was performed to capture potential scenarios that could occur in the event of a crash and provide a quantitative calculation for the probability of each scenario occurring, with a qualitative categorization of possible consequences. The risk analysis was structured using an event sequence diagram with probability distributions on each event in the tree and random sampling was used to estimate resulting probability distributions for each end-state scenario. The most likely consequence of a crash is no additional hazard from the hydrogen fuel (98.1–99.9% probability) beyond the existing hazards in a vehicle crash, although some factors need additional data and study to validate. These scenarios include minor crashes with no release or ignition of hydrogen. When the hydrogen does ignite, it is most likely a jet flame from the pressure relief device release due to a hydrocarbon fire (0.03–1.8% probability). This work represents a detailed assessment of the state-of-knowledge of the likelihood associated with various vehicle crash scenarios. This is used in an event sequence framework with uncertainty propagation to estimate uncertainty around the probability of each scenario occurring.

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State-of-the-art reactor consequence analyses project uncertainty analyses: Insights on offsite consequences

PSA 2019 - International Topical Meeting on Probabilistic Safety Assessment and Analysis

Tina Ghosh, S.; Esmaili, Hossein; Hathaway, Alfred; Bixler, Nathan E.; Brooks, Dusty M.; Osborn, Douglas M.; Wagner, Kenneth C.

This paper is the third paper in a special session on the State-of-the-Art Reactor Consequence Analyses (SOARCA) Uncertainty Analyses (UAs), and summarizes offsite consequence insights from the three SOARCA UAs. The U.S. Nuclear Regulatory Commission (NRC) with Sandia National Laboratories has completed three UAs for particular station blackout scenarios as part of the SOARCA research project: for a boiling-water reactor with a Mark I containment in Pennsylvania State (Peach Bottom), for a pressurized-water reactor (PWR) with an ice condenser containment in Tennessee State (Sequoyah), and for a PWR with subatmospheric large dry containment in Virginia State (Surry). The Sequoyah and Surry SOARCA UAs focused on an unmitigated short-term station blackout (SBO) scenario involving an immediate loss of offsite and onsite AC power. In the Surry UA, induced steam generator tube rupture was also modeled. The Sequoyah study focused on issues unique to the ice condenser containment and the potential for early containment failure due to hydrogen combustion. The Peach Bottom UA focused on an unmitigated long-term SBO scenario, where battery power is initially available. The MELCOR Accident Consequence Code System (MACCS) suite of codes was used for offsite radiological consequence modeling. This paper presents the offsite consequence results, individual latent cancer fatality risk and the individual early fatality risk, for the three SOARCA UAs and summarizes some of the insights and features of the analyses.

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Margins Associated with Loss of Assured Safety for Systems with Multiple Time-Dependent Failure Modes

Helton, J.C.; Brooks, Dusty M.; Sallaberry, Cedric S.

Representations for margins associated with loss of assured safety (LOAS) for weak link (WL)/strong link (SL) systems involving multiple time-dependent failure modes are developed. The following topics are described: (i) defining properties for WLs and SLs, (ii) background on cumulative distribution functions (CDFs) for link failure time, link property value at link failure, and time at which LOAS occurs, (iii) CDFs for failure time margins defined by (time at which SL system fails) – (time at which WL system fails), (iv) CDFs for SL system property values at LOAS, (v) CDFs for WL/SL property value margins defined by (property value at which SL system fails) – (property value at which WL system fails), and (vi) CDFs for SL property value margins defined by (property value of failing SL at time of SL system failure) – (property value of this SL at time of WL system failure). Included in this presentation is a demonstration of a verification strategy based on defining and approximating the indicated margin results with (i) procedures based on formal integral representations and associated quadrature approximations and (ii) procedures based on algorithms for sampling-based approximations.

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Results 26–50 of 67
Results 26–50 of 67