[1] Particle tracking in the time domain has received increasing attention as a technique for robustly simulating transport along one-dimensional subsurface pathways. Using a stochastic Lagrangian perspective, integral representations of transport including the effects of advection, longitudinal dispersion, and a broad class of retention models are derived; Monte Carlo sampling of that integral leads directly to new time domain particle tracking algorithms that represent a wide range of physical phenomena. Retention-time distributions are compiled for key retention models. An extension to accommodate linear transformations such as decay chains is also introduced. Detailed testing using first-order decay chains and four retention models (equilibrium sorption, limited diffusion, unlimited diffusion, and first-order kinetic sorption) demonstrate that the method is highly accurate. Simulations using flow fields produced by large-scale discrete-fracture network simulations, a transport problem that is difficult for conventional algorithms, demonstrate that the new algorithms are robust and highly efficient.
The US government has focused considerable attention on enhancing our society's ability to protect critical systems and services from disruptive events. Over the past decade, federal agencies have bolstered their efforts to identify and minimize threats using traditional risk-based approaches such as continuity of operations and disaster risk reduction processes. However, these valuable risk identification and management tools are limited because they rely upon foreseeable factor analyses of steady-state systems with predictable hazard frequencies and severities. In assessing the capability of complex adaptive systems to cope with disruptions, an overemphasis upon engineering resilience through risk management and planning for what is predictable may cloud or detract from our efforts to better understand a system's emergent capabilities to withstand disruptions that are unforeseeable. This article contends that augmenting traditional risk approaches through the incorporation of methodologies grounded in socio-ecological system (SES) resilience principles offers a potential avenue for improving our agencies' abilities to assess and manage both known and unknown risks. We offer a notional rationale for broadening our examination of system vulnerabilities and present a conceptual model that combines engineering and SES resilience paradigms to facilitate the identification, assessment, and management of system vulnerabilities. The Military Installation Resilience Assessment model described herein applies risk and resilience principles to evaluate whole systems, focusing on interconnections and their functionality in facilitating response and adaptation.
As the regulatory authority for transportation of spent nuclear fuel (SNF) in the United States, the Nuclear Regulatory Commission (NRC) requires that SNF transportation packages be designed to endure a fully engulfing fire with an average temperature of 800 °C (1,475 °F) for 30 minutes, as prescribed in Title 10 of the Code of Federal Regulations (CFR) Part 71. The work described in this paper was performed to support NRC in determining the types of accident parameters that could produce a severe fire with the potential to fully engulf a SNF transportation package. This paper describes the process that was used to characterize the important features of rail accidents that would potentially lead to a spent nuclear fuel transport package being involved in a severe fire. Historical rail accidents involving hazardous material and long duration fires in the United States have been analyzed using data from the Federal Railroad Administration (FRA) and the Pipeline and Hazardous Materials Safety Administration (PHMSA). Parameters that were evaluated from this data include, but were not limited to, class of track where the accident occurred, class of hazardous material that was being transported, and number of railcars involved in the fire. The data analysis revealed that in the past 34 years of rail transport, roughly 1,800 accidents have led to the release of hazardous materials resulting in a frequency of roughly 1 accident per 10 million freight train miles. In the last 12 years, there have only been 20 accidents involving multiple car hazardous material releases that led to a fire. This results in an accident rate of 0.003 accidents per million freight train miles that involved multiple car releases and a fire. In all the accidents analyzed, only one involved a railcar carrying Class 7 (i.e., radioactive) hazardous material (HAZMAT).
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