Exponents (United States)

Abstract The physical forces and environmental stressors that occur during extreme weather events place facilities at risk for infrastructure failures, loss of operation and production, and highly impactful chemical releases, all of which directly affect a company's bottom line. Hurricane Harvey (2017) resulted in over 100 such failures and chemical releases. There is a pressing need today for risk predictions that incorporate and account for evolving environmental factors such as continuous sea level rise. Such nonstatic (nonstationary) risk management approaches will allow us to more accurately predict storm surge flooding as a function of time and provide more realistic short‐term and long‐term (on the order of decades) predictions to assist in actionable planning. An integrated three‐part approach to assessing the risk of infrastructure damage and chemical releases and the resulting business and legal consequences are presented in this work. This approach consists of (a) temporally variant and spatially localized probabilistic predictions of flooding and forces related to flooding (FloodScore) with unprecedented resolution; (b) detailed impact predictions on facility infrastructure including structural, mechanical, and electrical elements based on the predictions from step (a); and (c) a quantitative means of scoring the environmental/financial risk and consequences of chemicals released as derived from step (b). This integrated approach, which assesses risk of losses in both the near term and out to 50 years in the future, includes the assessment of ecological and human impact levels and provides actionable information for resiliency and risk mitigation planning.

This is the fourth in a series of papers through which the authors demonstrate how numerical transport modeling can assist the remediation design engineer in predicting the progress of enhanced reductive dechlorination remediation expected in the field. The first two papers dealt with the hydraulics of delivery and preliminary understanding of substrate‐limited degradation. The third paper compared a simulated substrate‐limited degradation progress to some early results measured at a site. Based on that comparison, conclusions were drawn regarding the differences in degradation rates between a field situation and laboratory studies, and inferences were made about the modeling steps needed to aid in designing enhanced reductive dechlorination systems. Since the presentation of those results, additional rounds of data have been obtained from the field, encompassing a more substantial range of degradation history. In this paper, the authors compare those results with the simulated predictions and present an illustrative example of design modification using the model. ©2016 Wiley Periodicals, Inc.