The interaction between a fixed particle and decaying homogeneous isotropic turbulence is studied numerically using an overset grid that provides resolution of all scales of fluid motion. A description of the numerical technique and validation of the solution procedure are presented. An ensemble of 64 simulations with the particle in different regions of the flow is computed. The particle diameter in the simulations is approximately twice the size of the unladen Kolmogorov length scale, and the maximum value of the particle Reynolds numbers due to the turbulent fluctuations is close to 20. Ensemble averages of quantities from the numerical solutions are used to investigate the turbulence modification and the fluid forces on the particle. Volume-averaged profiles of the turbulent kinetic energy and dissipation rate from the overset grid simulations reveal that the displacement of fluid by the particle and the formation of the boundary layer at the particle surface lead to turbulence modification in a local region. Time histories of the force applied to the particle from each overset grid simulation are compared to those predicted by a particle equation of motion. The particle equation of motion is shown to underpredict the root mean square (RMS) force applied to the particle by the turbulence. RMS errors between the forces from the overset grid simulation and those predicted by the particle equation of motion are shown to be between 15% and 30% of the RMS force on the particle. The steady viscous drag force is shown to be the dominant term in the particle equation of motion while the history integral term is negligible.

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The technology focus in the automotive sector has moved toward battery electric vehicles (BEVs) over the last few years. This shift has been ascribed to the importance of reducing greenhouse gas (GHG) emissions from transportation to mitigate the effects of climate change. In Europe, countries are proposing future bans on vehicles with internal combustion engines (ICEs), and individual United States (U.S.) states have followed suit. An important component of these complex decisions is the electricity generation GHG emission rates both for current electric grids and future electric grids. In this work we use 2019 U.S. electricity grid data to calculate the geographically and temporally resolved marginal emission rates that capture the real-world carbon emissions associated with present-day utilization of the U.S. grid for electric vehicle (EV) charging or any other electricity need. These rates are shown to be relatively independent of marginal demand at the highest marginal demand levels, indicating that they will be relatively insensitive to the addition of renewable electricity generation capacity up to the point at which curtailment occurs regularly unless the most carbon-intensive electricity sources are preferentially deactivated. We propose a simplified methodology for comparing emissions from BEVs and hybrid electric vehicles (HEVs) based on the marginal emission rates and other publicly available data and apply it to comparative case studies of BEVs and HEVs. We find that currently there is no evidence to support the idea that BEVs lead to a uniform reduction in vehicle emission rates in comparison to HEVs and in many scenarios have higher GHG emissions. This suggests that a mix of powertrain technologies is the best path toward reducing transportation sector emissions until the U.S. grid can provide electricity for the all-electric fleet infrastructure and vehicle operations with a carbon intensity that produces a net environmental benefit.