Monte-Carlo-simulation-based performance analysis of the heat transfer process in nuclear-based hydrogen production based on Cu-Cl Cycle.
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As a crucial step in nuclear-based hydrogen production based on Cu-Cl cycle, the performance analysis of heat transfer process is of paramount importance. However, as a newly built system, the major obstacle of applying standard performance analysis to the heat transfer process is the sparse data. In this thesis, the methodology of Monte-Carlo Simulation-based (MCS-based) performance analysis is developed, and it is shown that this method can be used to deal effectively with the problems caused by sparse data in the heat transfer process. This method expanded the database successfully and carried out the Monte-Carlo simulation through expanded database. The details of the heat transfer process in a nuclear-based hydrogen production based on a four-step Cu-Cl cycle is firstly listed and discussed. Afterwards, the modelling of the MCS-based performance analysis of heat transfer process is proposed and explained step by step. The confidence interval of the simulation results is demonstrated since the variations in results is a major issue for any performance analysis based on simulations. The final result indicated that the MCS-based performance analysis is a reasonable performance analysis method that can be used to evaluate the performance of the heat transfer process in the nuclear-based hydrogen production based on Cu-Cl cycle through sparse data.