Mazdak Tootkaboni

Roughness-Induced Vehicle Energy Dissipation: Statistical Analysis and Scaling

AbstractThe energy dissipated in a vehicle suspension system due to road roughness affects rolling resistance and the resulting fuel consumption and greenhouse gas emission. The key parameters driving this dissipation mechanism are identified via dimensional analysis. A mechanistic model is proposed that relates vehicle dynamic properties and road roughness statistics to vehicle dissipated energy and thus fuel consumption. A scaling relationship between the dissipated energy and the most commonly used road roughness index, the International Roughness Index (IRI), is also established. It is shown that the dissipated energy scales with IRI squared and scaling of dissipation with vehicle speed V depends on road waviness number w in the form of Vw−2. The effect of marginal probability distribution of the road roughness profile on dissipated energy is examined. It is shown that although the marginal distribution of the road profile does not affect the identified scaling relationships, the multiplicative factor...

A variance decomposition approach to uncertainty quantification and sensitivity analysis of the Johnson and Ettinger model

The Johnson and Ettinger (J&E) model is the most widely used vapor intrusion model in the United States. It is routinely used as part of hazardous waste site assessments to evaluate the potential for vapor intrusion exposure risks. This study incorporates mathematical approaches that allow sensitivity and uncertainty of the J&E model to be evaluated. In addition to performing Monte Carlo simulations to examine the uncertainty in the J&E model output, a powerful global sensitivity analysis technique based on Sobol indices is used to evaluate J&E model sensitivity to variations in the input parameters. The results suggest that the J&E model is most sensitive to the building air exchange rate, regardless of soil type and source depth. Building air exchange rate is not routinely measured during vapor intrusion investigations, but clearly improved estimates and/or measurements of the air exchange rate would lead to improved model predictions. It is also found that the J&E model is more sensitive to effective diffusivity than to effective permeability. Field measurements of effective diffusivity are not commonly collected during vapor intrusion investigations; however, consideration of this parameter warrants additional attention. Finally, the effects of input uncertainties on model predictions for different scenarios (e.g., sandy soil as compared to clayey soil, and “shallow” sources as compared to “deep” sources) are evaluated. Our results not only identify the range of variability to be expected depending on the scenario at hand, but also mark the important cases where special care is needed when estimating the input parameters to which the J&E model is most sensitive. Implications:u2003The research described herein uses stochastic approaches to investigate the effect of individual input parameters on the J&E model. The results suggest that the J&E model is most sensitive to the building air exchange rate, regardless of soil type and source depth. Additional analysis reveals that chemical transport is more sensitive to effective diffusivity of the soil, rather than effective permeability of the soil. Accordingly, effective diffusivity and air exchange rates warrant additional attention when assessing vapor intrusion exposure risks at hazardous waste sites.