• Korean Chemical Engineering Research
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• v.54 no.3
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• pp.350-359
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• 2016

For accurate estimation over the change of pressure and temperature of the vessel during blowdown period, a new dynamic blowdown model was developed in this work. In particular, heat transfer from the vessel wall to discharge gas at both laminar or turbulent flow in the vessel was embedded to the model to increase the accuracy of blowdown estimation. For thermodynamics, the whole blowdown period was discretized into finite pressure decrement steps, and the step size was adjusted so that the calculation can be more efficiently carried out, while maintaining the model's accuracy. Both Peng-Robinson and Soave-Redlich-Kwong equation of states were applied to the model, and the results were compared each other. Finally, the simulation results was compared with Haque and coworkers' experimental results, and it proved high accuracy of the model.

• Nuclear Engineering and Technology
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• v.54 no.11
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• pp.4181-4194
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• 2022

Main steam safety valves are commonly used in nuclear power plants to provide final protections from overpressure events. Blowdown and dynamic stability are two critical characteristics of safety valves. However, due to the parameter sensitivity and multi-parameter features of safety valves, using traditional method to design and/or optimize them is generally difficult and/or inefficient. To overcome these problems, a surrogate model-based valve design optimization is carried out in this study, of particular interest are methods of valve surrogate modeling, valve parameters global sensitivity analysis and valve performance optimization. To construct the surrogate model, Design of Experiments (DoE) and Computational Fluid Dynamics (CFD) simulations of the safety valve were performed successively, thereby an ensemble surrogate model (E-AHF) was built for valve blowdown and stability predictions. With the developed E-AHF model, global sensitivity analysis (GSA) on the valve parameters was performed, thereby five primary parameters that affect valve performance were identified. Finally, the k-sigma method is used to conduct the robust optimization on the valve. After optimization, the valve remains stable, the minimum blowdown of the safety valve is reduced greatly from 13.30% to 2.70%, and the corresponding variance is reduced from 1.04 to 0.65 as well, confirming the feasibility and effectiveness of the optimization method proposed in this paper.