Experimental and CFD study on the optimization of valve lintel’s structural parameters under critical self-aerated conditions

Abstract

Self-aerated technology of valve lintel (SATVL) is widely used in high head navigation lock water delivery system to address the cavitation problem. To optimize the structural parameters of valve intel including the height of the throat ( $ h_1=20\,{\rm mm} $ ) and divergent part enhance ( $ h_2 $ ), the length of the throat part ( $ L_2 $ ) and the divergent part ( $ L_3 $ ), and the diffusion angle ( $ \beta $ ) for better self-aerated performance, the dimensionless structural parameters $ h_2/h_1, L_2/h_1, L_3/h_1 $ and beta were chosen as the variables. The conception of critical self-aerated conditions was proposed via theoretical analysis and experimental verification for the first time, and the slope m of critical self-aerated conditions was taken as the response to assess self-aerated performance. The method of combing Response Surface Methodology (RSM) with Central Composite Design (CCD) was introduced to systematically investigate the effects of the structural parameters on the self-aerated performance. A 1: 1 full-scale slicing physical model and CFD simulations were designed to capture the critical self-aerated conditions. Finally, though multiple regression analysis, a quadratic polynomial equation between m and structural parameters was obtained. It was found that: (i) the results of theoretical analysis and physical model verification confirmed the hypothesis of critical self-aerated conditions. (ii) with the aid of ANOVA, the sensitivity of structural parameters which influenced critical self-aerated conditions is $ {\rm F}(h_2/h_1) > {\rm F}(L_3/h_l) > {\rm F}(\beta) > {\rm F}(L_2/h_1) $ . (iii) the optimal structural parameters are $ h_2/h_1=1.25, L_2/h_1=3.5, L_3/h_1=160 $ and $ \beta =2.5^{\circ} $ . The result indicate that the substantial improvement of self-aerated performance can be achieve by using those optimal structural parameters.

Keywords

• self-aerated flow
• the critical self-aerated conditions
• response surface methodology
• optimization