Search

Accurate prediction of heat transport in porous media is important for understanding geoscience processes and properties and to design applications, for example geothermal energy systems. While heat transport is generally modelled assuming of local thermal equilibrium (LTE), i.e., instantaneous heat transfer between the fluid and solid phases, previous studies have demonstrated presence of local thermal non-equilibrium (LTNE), i.e., delayed heat transfer, in natural porous materials. However, factors that influence the rate of heat transfer between the phases and their significance for inherently heterogeneous natural systems remain unknown and untested. We develop an open-source fully coupled, finite-element application to numerically simulate heat transfer between the fluid and solid phases. This is based on the Multiphysics Object-Oriented Simulation Environment (MOOSE) and allows massively parallel modelling of heat transport including customized transfer rates. We verify our model using an analytical solution considering LTNE and illustrate several applications. The model can be used to investigate processes that affect heat transport such as heat transfer mechanisms and their dependence on different hydrogeological conditions.

Malaria is one of the deadliest vector-borne diseases in the world. Researchers are developing new genetic and conventional vector control strategies to attempt to limit its burden. Novel control strategies require detailed safety assessment to ensure responsible and successful deployments. Anopheles gambiae sensu stricto (s.s.) and Anopheles coluzzii, two closely related subspecies within the species complex Anopheles gambiae sensu lato (s.l.), are among the dominant malaria vectors in sub-Saharan Africa. These two subspecies readily hybridise and compete in the wild and are also known to have distinct niches, each with spatially and temporally varying carrying capacities driven by precipitation and land use factors.We model the spread and persistence of a population-modifying gene drive system in these subspecies across sub-Saharan Africa by simulating introductions of genetically modified mosquitoes across the African mainland and its offshore islands. We explore transmission of the gene drive between the two subspecies that arise from different hybridisation mechanisms, the effects of both local dispersal and potential wind-aided migration to the spread, and the development of resistance to the gene drive. Given the best current available knowledge on the subspecies’ life histories, we find that an introduced gene drive system with typical characteristics can plausibly spread from even distant offshore islands to the African mainland with the aid of wind-driven migration, with resistance taking over within a decade. Our model accounts for regional to continental scale mechanisms, and demonstrates a range of realistic dynamics including the effect of prevailing wind on spread and spatio-temporally varying carrying capacities for subspecies. As a result, it is well-placed to answer future questions relating to mosquito gene drives as important life history parameters become better understood.

Aquifer Thermal Energy Storage (ATES) uses excess thermal energy to heat water which is stored in an aquifer until it is needed, at which time the hot water is recovered and the heat used for some purpose e.g. electricity generation. The recovery efficiency (i.e. the ratio of heat energy recovered to heat energy injected, R ) is one of the most important factors dictating the viability of ATES systems. The variation of R with various aquifer properties and operating parameters is explored for high temperature (HT) ATES systems with injection temperatures ≥ 90 ∘ C , extending the results of previous studies to higher temperatures and a broader range of aquifer properties and operating conditions. R values are calculated using numerical models of a single-well ATES system, which is validated by comparison with previous field and modelling studies. The results show that HT-ATES may be viable with injection temperatures as high as 300 ∘ C , depending on the aquifer properties and operating parameters. Daily cycles are very efficient over a broad range of conditions, whereas the efficiency of annual cycles is much more variable. The most important parameters governing R are aquifer thickness, injection temperature, horizontal and vertical permeability, and dispersion length. The R values are used to derive an improved version of the Rayleigh number relationship proposed by Schout et al. (2014), extending the applicability of this relationship to daily cycles and improving its accuracy for annual cycles. An alternative method for estimating R using a convolutional neural network is proposed. The calculated R values may be considered best-case because aspects such as background groundwater flow and geochemical effects are ignored. Practical factors such as energy supply/demand requirements, reservoir and above-ground engineering, financial or regulatory aspects, and public acceptance are not considered. Nevertheless, the results of this study can be used for rapid screening of large areas for potential HT-ATES sites, defining requirements for potential sites, and estimating R values for specific sites, before performing detailed feasibility studies.