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This study explores undergraduate engineering and education students’ perspectives on their interdisciplinary teams throughout the rapid transition to online learning and instruction from a face-to-face to a virtual format. In this qualitative study, students’ reflections and focus groups from three interdisciplinary collaborations were analyzed using the lens of Social Cognitive Theory. COVID-19 created a dramatic change in the environment such that the most immediate and direct impact on students’ experiences was on the environmental aspects of Bandura’s triadic reciprocal determinism model, which then triggered behavioral and personal responses to adapt to the new environment. Subsequent evidence of reciprocal effects between environmental, behavioral, and personal factors took place as students continued to adapt. Results suggest that the modifications made to transition the project fully online were meaningful experiences for students’ learning and teaching of engineering through teams. This interdisciplinary partnership provided both pre-service teachers and undergraduate engineering students with the opportunity to learn and practice content and professional skills that will be essential for success in future work environments. 

Current understanding of turbulence modulation by solid particles is incomplete as making reliable predictions on the nature and level of modulation remains a challenging task. Multiple modulation mechanisms may be simultaneously induced by particles, but the lack of reliable methods to identify these mechanisms and quantify their effects hinders a complete understanding of turbulence modulation. In this work, we present a full analysis of the turbulent kinetic energy (TKE) equation for a turbulent channel flow laden with a few fixed particles near the channel walls, in order to investigate how the wall generated turbulence interacts with the particles and how, as a result, the global turbulence statistics are modified. All terms in the budget equations of total and component-wise TKEs are explicitly computed using the data from direct numerical simulations. Particles are found to modify turbulence by two competing mechanisms: the reduction of the intrinsic turbulence production associated with a reduced mean shear due to the resistance imposed by solid particles (the first mechanism), and an additional TKE production mechanism by displacing incoming fluid (the second mechanism). The distribution of TKE in the wall-normal direction is also made more homogeneous due to the significantly enhanced pressure transport of TKE. Finally, the budget analysis of component-wise TKE reveals an enhanced inter-component TKE transfer due to the presence of particles, which leads to a more isotropic distribution of TKE among three velocity components. 

Understanding the two-way interactions between finite-size solid particles and a wall-bounded turbulent flow is crucial in a variety of natural and engineering applications. Previous experimental measurements and particle-resolved direct numerical simulations revealed some interesting phenomena related to particle distribution and turbulence modulation, but their in-depth analyses are largely missing. In this study, turbulent channel flows laden with neutrally buoyant finite-size spherical particles are simulated using the lattice Boltzmann method. Two particle sizes are considered, with diameters equal to 14.45 and 28.9 wall units. To understand the roles played by the particle rotation, two additional simulations with the same particle sizes but no particle rotation are also presented for comparison. Particles of both sizes are found to form clusters. Under the Stokes lubrication corrections, small particles are found to have a stronger preference to form clusters, and their clusters orientate more in the streamwise direction. As a result, small particles reduce the mean flow velocity less than large particles. Particles are also found to result in a more homogeneous distribution of turbulent kinetic energy (TKE) in the wall-normal direction, as well as a more isotropic distribution of TKE among different spatial directions. To understand these turbulence modulation phenomena, we analyse in detail the total and component-wise volume-averaged budget equations of TKE with the simulation data. This budget analysis reveals several mechanisms through which the particles modulate local and global TKE in the particle-laden turbulent channel flow. 

Two case studies of marine stratocumulus (one nocturnal and drizzling, the other daytime and nonprecipitating) are simulated by the UCLA large-eddy simulation model with bin microphysics for comparison with aircraft in situ observations. A high-bin-resolution variant of the microphysics is implemented for closer comparison with cloud drop size distribution (DSD) observations and a turbulent collision–coalescence kernel to evaluate the role of turbulence on drizzle formation. Simulations agree well with observational constraints, reproducing observed thermodynamic profiles (i.e., liquid water potential temperature and total moisture mixing ratio) as well as liquid water path. Cloud drop number concentration and liquid water content profiles also agree well insofar as the thermodynamic profiles match observations, but there are significant differences in DSD shape among simulations that cause discrepancies in higher-order moments such as sedimentation flux, especially as a function of bin resolution. Counterintuitively, high-bin-resolution simulations produce broader DSDs than standard resolution for both cases. Examination of several metrics of DSD width and percentile drop sizes shows that various discrepancies of model output with respect to the observations can be attributed to specific microphysical processes: condensation spuriously creates DSDs that are too wide as measured by standard deviation, which leads to collisional production of too many large drops. The turbulent kernel has the greatest impact on the low-bin-resolution simulation of the drizzling case, which exhibits greater surface precipitation accumulation and broader DSDs than the control (quiescent kernel) simulations. Turbulence effects on precipitation formation cannot be definitively evaluated using bin microphysics until the artificial condensation broadening issue has been addressed.