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    Navigating the Nuclear Renaissance Economic Viability, Zero Emissions, and the Future of Nuclear Energy with Generation IV Reactors and SMRs with Artificial Intelligence Integration
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    Abstract:
    As global efforts intensify to combat climate change and achieve sustainable energy goals, nuclear power is re-emerging as a vital component of the energy mix. This article explores modern nuclear technologies' economic and environmental potential, focusing on the nuclear fuel cycle, Generation IV reactors, Small Modular Reactors (SMRs), and the transformative role of Artificial Intelligence (AI). The nuclear fuel cycle, encompassing fuel production, utilization, and disposal, is evolving to become more efficient and sustainable, reducing costs and environmental impacts. Generation IV reactors and SMRs represent significant advancements, offering enhanced safety, efficiency, and flexibility, making nuclear power more accessible and adaptable. AI integration revolutionizes nuclear operations by optimizing performance, predictive maintenance, and safety monitoring. These technologies collectively enhance nuclear power's economic viability and environmental benefits, positioning it as a cornerstone of global zero-emission strategies. The return on involvement in nuclear energy is substantial, driven by economic growth, energy security, and technological advancements. Continued investment and innovation in these areas are essential for realizing the full potential of nuclear energy in a sustainable and carbon-neutral future. This article underscores the importance of nuclear power in achieving global climate objectives and fostering a sustainable energy landscape.
    Keywords:
    Zero emission
    Zero (linguistics)
    Nuclear transmutation
    Zero (linguistics)
    Zero-point energy
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    Zero-knowledge proof
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    Transmutation of the nuclear waste which contains MA and FP is important and necessary. Because the major MA and FP’s nucleus densities is large in transmutation calculation, now existing multi-group WIMS libraries are not suitable for transmutation calculation. This paper makes a study for the parameters value choice such as weight spectrum and background cross-section σ0 in NJOY. With the new parameters value, produce suitable multi-group data of FP and a new library for transmutation calculation. In purpose of comparing these two libraries, build a simple transmutation cell model in HFETR. Achieve the cell calculation separately by WIMSD with new library and original library. Then compare the results of parameters such as K-INF, flux, and absorption reactions. The results show that the values of these parameters are different in resonance energy range, so it is necessary to think over the resonance of FP when a multi-group library is produced for thermal reactor transmutation.
    Nuclear transmutation
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    Citations (1)