As previously mentioned, IR4TD has focused mainly in three areas of research recently. Accordingly, the future research plans will include expanding on the aforementioned areas of focus. The following provides a summary of these expansions and the goals followed by our researchers.
The transition to a 100% renewable energy grid is faced with numerous challenges such as prediction uncertainty, renewable resource fluctuations, and the introduction of additional hazards associated with storage systems. While we have proposed various methods to address many of these challenges, including those described in references [1, 2, 3, 4], there are still gaps that need to be addressed. For instance, to implement the approach we proposed in reference [2], other aspects, such as grid stability in terms of variables like voltage and power dissipation through long-distance transmission, as well as factors pertaining to landscape and urban planning, must be investigated. Given that these challenging problems are multidisciplinary in nature, collaboration with researchers from diverse fields and backgrounds at various energy institutes throughout the University of Kentucky and beyond becomes essential to advance these projects. Moreover, we are currently investigating the feasibility of using the excess energy available from the renewable energy systems transition plan for various applications. Once these pieces are individually addressed, we plan to implement artificial neural network and multi-objective optimization algorithms, which we previously utilized for tuning energy systems, to achieve maximum efficient utilization of the renewable energy systems installed, thereby reducing waste and hazards while achieving a carbon-neutral energy sector.
Additionally, we are exploring various research topics under this area, such as:
• Developing a machine learning-based model to find the optimal PV/wind capacities with different energy storage systems. This model offers several advantages such as less computation cost and applicability anywhere, given the availability of solar and wind resources as well as the ambient temperatures.
• Efficient utilization of biogas using different power cycles, assessing their techno-economic feasibility, and incorporating the social cost of GHG emissions.
• Investigating different techniques and design improvements to enhance the efficiency of concentrated solar power system.
• Developing a methodology for fast EV battery replacement instead of charging.
• Investigating the techno-economic feasibility of carbon capture in countries such as Jordan, which have suitable natural reservoirs. We are also exploring whether these countries can sell their CO2 emission share to other countries.
• Conceptual to Actual Thermal Regenerative Electrochemical Cycles (TREC): Towards deployment and commissioning of optimized TREC modules in different sectors of low waste heat.
• Investigating the transition from high to low global warming potential refrigeration for sustainable cooling in different sectors.
In addition to the energy research, we see great potential for the integration of machine learning tools in wildfire modeling, which we plan to investigate in the coming years. We are also exploring the acoustic technique's ability to create reliable pressure estimates from micro-explosion decibels. Successful implementation of this technique will be of great use in estimating the pressure inside live fuels before they exhibit the micro-explosion behavior, which in turn will provide estimates needed for the scaling analysis and fire behavior modeling.
Additionally, we plan to focus on two main fire research projects in the future. The first project involves creating a well-controlled live fuel surrogate for experimental investigation and modeling of wildfires accurately. This problem is becoming of increasing importance, particularly in the United States, where we have witnessed fire outbreaks in the past few years. Researchers have developed fuel surrogates to simulate dead fuels behavior, however, after we discovered the fundamental difference in the burning behavior of live fuels [5], and since the latter various dramatically from species to species, and even seasonally withing the same species, it is important that we design a well-controlled surrogate that is able to replicate the fire behavior of live fuels. This will be a significant advancement in the field, as researchers have not yet found a good surrogate for experimental investigations. The second project involves examining the ability of live fuels to resist flame extinction at higher wind speeds. As mentioned earlier, live fuels burn with micro-explosion or jetting behaviors, which makes them dynamically more similar to torch flames as opposed to candle flames which better resembles dead fuels burning behavior. This means that live fuels are able to withstand higher gusts before extinction and therefore spread during windy conditions. This second project is also a very significant advancement in this field, as this have not been previously envisioned or examined by any other researcher.
Although these research areas are slightly different in nature, the experimental, simulations, machine learning and optimization tools that are developed can be used efficiently across the different areas, which we will exploit as we continue our endeavor towards sustainability, climate change and environmental hazards mitigation.
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