A numerical study has been undertaken to explore the details of forced convection heat transfer in finned aluminum foam heat sinks. Calculations are made using a finite-volume computational fluid dynamics (CFD) code that solves for the flow and heat transfer in conjugate fluid/porous/solid domains. The results indicate that using unfinned blocks of porous aluminum results in low convective heat transfer due to the relatively low effective thermal conductivity of the porous aluminum. The addition of aluminum fins to the heat sink significantly enhances the heat transfer with only a moderate pressure drop penalty. The convective enhancement is maximized when thermal boundary layers between adjacent fins merge together and become nearly developed for much of the length of the heat sink. It is found that the heat transfer enhancement is due to increased heat entrainment into the aluminum foam by conduction. A model for the equivalent conductivity of the finned/foam heat sinks is developed using extended surface theory. This model is used to explain the heat transfer enhancement as an increase in equivalent conductivity of the device. The model is also shown to predict the heat transfer for various heat sink geometries based on a single CFD calculation to find the equivalent conductivity of the device. This model will find utility in characterizing heat sinks and in allowing for quick assessments of the effect of varying heat sink properties.

Drag reduction in turbulent channel flows has significant practical relevance for energy savings. Various methods have been proposed to reduce turbulent skin friction, including microscale surface modifications such as riblets or superhydrophobic surfaces. More recently, macroscale surface modifications in the form of longitudinal grooves have been shown to reduce drag in laminar channel flows. The purpose of this study is to show that these grooves also reduce drag in turbulent channel flows and to quantify the drag reduction as a function of the groove parameters. Results are obtained using computational fluid dynamics (CFD) simulations with turbulence modeled by the k–ω shear-stress transport (SST) model, which is first validated with direct numerical simulations (DNS). Based on the CFD results, a reduced geometry model is proposed which shows that the approximate drag reduction can be quantified by evaluating the drag reduction of the geometry given by the first Fourier mode of an arbitrary groove geometry. Results are presented to show the drag reducing potential of grooves as a function of Reynolds number as well as groove wave number, amplitude, and shape. The mechanism of drag reduction is discussed, which is found to be due to a rearrangement of the bulk fluid motion into high-velocity streamtubes in the widest portion of the channel opening, resulting in a change in the wall shear stress profile.

During the COVID-19 pandemic, the Province of Ontario, Canada, launched a wastewater surveillance program to monitor SARS-CoV-2, inspired by the early work and successful forecasts of COVID-19 waves in the city of Ottawa, Ontario. This manuscript presents a dataset from January 1, 2021, to March 31, 2023, with RT-qPCR results for SARS-CoV-2 genes and PMMoV from 107 sites across all 34 public health units in Ontario, covering 72% of the province’s and 26.2% of Canada’s population. Sampling occurred 2–7 times weekly, including geographical coordinates, serviced populations, physico-chemical water characteristics, and flowrates. In doing so, this manuscript ensures data availability and metadata preservation to support future research and epidemic preparedness through detailed analyses and modeling. The dataset has been crucial for public health in tracking disease locally, especially with the rise of the Omicron variant and the decline in clinical testing, highlighting wastewater-based surveillance’s role in estimating disease incidence in Ontario.