Numerical modeling and characteristic analysis of the pneumatic noise of spring-loaded pressure relief valves
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High-intensity turbulence and interactions among multiple structural parameters are the main factors hindering effective noise prediction in spring-loaded pressure relief valve (SLPRV). On this basis, an in-depth numerical modeling and mechanism analysis are carried out in this paper, where the Computational Fluid Dynamics (CFD) method and Computational Air Acoustic (CAA) are implemented to analysis the noise characteristics of the transient flow field when gas flows through the valve,on this basis, the attenuation characteristics and directivity of the noise were analyzed. In addition, a noise experimental platform for the SLPRV and an acoustic acquisition matrix were set up to verify the accuracy of the simulation results. In order to accurately predict its noise directivity, three key parameters at the valve orifice were selected for research, and a Kriging high-fidelity surrogate model (KHFSM) of the valve structure and noise directivity was constructed. The results show that, under different key structures of the valve, the determination coefficient R2 of the noise predicted by KHFSM reaches 0.969, and the maximum error is less than 1 dB, it can accurately predict the noise directivity of SLPRV, and establish a theoretical and methodological framework underpinning the acoustic optimization of safety valves in nuclear power systems
Abstract
High-intensity turbulence and interactions among multiple structural parameters are the main factors hindering effective noise prediction in spring-loaded pressure relief valve (SLPRV). On this basis, an in-depth numerical modeling and mechanism analysis are carried out in this paper, where the Computational Fluid Dynamics (CFD) method and Computational Air Acoustic (CAA) are implemented to analysis the noise characteristics of the transient flow field when gas flows through the valve,on this basis, the attenuation characteristics and directivity of the noise were analyzed. In addition, a noise experimental platform for the SLPRV and an acoustic acquisition matrix were set up to verify the accuracy of the simulation results. In order to accurately predict its noise directivity, three key parameters at the valve orifice were selected for research, and a Kriging high-fidelity surrogate model (KHFSM) of the valve structure and noise directivity was constructed. The results show that, under different key structures of the valve, the determination coefficient R2 of the noise predicted by KHFSM reaches 0.969, and the maximum error is less than 1 dB, it can accurately predict the noise directivity of SLPRV, and establish a theoretical and methodological framework underpinning the acoustic optimization of safety valves in nuclear power systems