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Optimization design method for components parameter in space station ventilation system based on Flowmaster simulation
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DOI：10.1007/s12273-024-1186-6.png)
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Due to the challenges of adjustment after installation and the elevated failure rate associated with the use of electric valves, which contributes to increased weight among other issues, single-hole restrictors (SHRs) are commonly employed within the ventilation system of the manned space station. These restrictors are pre-configured with parameters to ensure that the airflow at the termination of the ventilation system meets the designated requirements. However, given their inability to be modified post-installation, a preliminary optimization design process becomes imperative. Past solutions relying solely on experience are insufficient in precise and optimal outcomes. While computational fluid dynamics (CFD) simulations offer accurate results, they encounter difficulties in modeling larger systems and are time-intensive due to multiple iterative simulations. Hence, an optimizing design method through quicker Flowmaster simulations is proposed in this study. Utilizing the Functional Mock-up Interface (FMI) protocol, the ventilation system model established in Flowmaster could be exported as FMU files and fine-tuned within Python using a genetic algorithm (GA), swiftly achieving a well-balanced ventilation system design by adjusting the parameters of the SHRs. The findings from CFD calculations can corroborate the simulations conducted in Flowmaster. The vents' unbalanced factor and the pressure drops of the system are used as optimization objectives. After optimization, the system unbalanced factor and total pressure drop were 5.51% and 5.99 Pa, respectively, both of which are better than the results obtained using CFD through empirical and trial-and-error methods, and the computation time was reduced by 99.16%.
Keyword:
ventilation system
space station
Flowmaster
FMI
genetic algorithm
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5.9
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1.6K
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4.5K
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