Abstract
Engineers are often challenged by designing new equipment without any prior knowledge or guidance from an existing similar product. The large degree of freedom that this generates can become a bottleneck as it could lead to a loss of global oversight and may even lead to wrong, uninformed choices. It is essential to have a large exploration of the design space to allow for innovative solutions, on the other hand it is important to introduce a high level of detail as early as possible in the design process to increase the reliability of the model predictions, which drive the decision process. This leads to a well-known conflict where more knowledge is needed upfront in the design process in the early stages of the design, and a larger degree of freedom is needed near the end of the design process where typically more knowledge is available. In this work it is demonstrated how modern design optimization tools can be effectively used to integrate the preliminary with the detailed design process. The key to achieve a good balance between design exploration and detailed design is obtained by reducing the parameters that are fixed during the preliminary design to an absolute minimum, such that the detailed design phase has still a large degree of freedom. The parameters that are fixed in the preliminary design phase are moreover those parameters that have a pronounced influence on the design performance and can be reliably predicted by a lower detail analysis code. Both preliminary and detailed design processes rely heavily on optimization techniques. Due to the larger computational cost in the detailed design phase, a surrogate model based optimization is used opposed to an evolutionary algorithm in the preliminary design phase. The application within this paper is the design of a liquid-metal pump for the primary cooling system of the advanced nuclear reactor MYRRHA conceived by the Belgian research center (SCK\(\cdot \)CEN). This single stage axial-flow pump has unique design requirements not met by any previously designed pump, and hence demands for a novel approach.
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Verstraete, T., Mueller, L. (2015). Design Optimization of the Primary Pump of a Nuclear Reactor. In: Greiner, D., Galván, B., Périaux, J., Gauger, N., Giannakoglou, K., Winter, G. (eds) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-319-11541-2_11
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DOI: https://doi.org/10.1007/978-3-319-11541-2_11
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