The high-efficiency Shock Vectoring Control Serpentine Nozzle(SVCSN)takes into account both thrust vectoring and infrared stealth,and significantly improves the comprehensive performance of the aero-engines through an...The high-efficiency Shock Vectoring Control Serpentine Nozzle(SVCSN)takes into account both thrust vectoring and infrared stealth,and significantly improves the comprehensive performance of the aero-engines through an additional auxiliary duct.In this paper,the schlieren photographs at the exit of the high-efficiency SVCSN and the wall static pressure distributions were obtained by experiments,and the numerical results were used to enrich the thrust vectoring characteristics.The effects of the auxiliary injection were analyzed first to reveal the advantages of the high-efficiency SVCSN compared to the conventional SVCSN.Then,the aerodynamic parameters and the structural parameters of the high-efficiency SVCSN were investigated,including the Nozzle Pressure Ratio(NPR),the Secondary flow Pressure Ratio(SPR),the secondary flow relative area and the secondary flow injection angle.Finally,the coupling performance of the high-efficiency SVCSN is studied by using the approximate modeling technology.Results show that the auxiliary injection increases the range between the two shock legs of the “k”shock wave induced by the secondary flow,then causes the separation zone and high-pressure boss of the down wall to expand upstream,and finally results in a prominent increase in the thrust vectoring performance.The thrust vectoring angle and Vectoring Efficiency(VE)of the high-efficiency SVCSN are about 61.6%and 75.7%,respectively,higher than those of the conventional SVCSN at NPR=6.The effects of the NPR and the SPR on the thrust vectoring performance of the high-efficiency SVCSN are coupled with each other.A larger NPR matched with a smaller SPR shows better thrust vectoring performance.The maximum fluctuations in thrust vectoring angle and VE caused by the NPR and SPR are about 22%and 64%.The VE decreases monotonously with the increase of the secondary flow relative area.Smaller secondary flow injection angle shows better thrust vector performance,and the thrust vectoring angle and VE of the secondary flow injection angle of 90are about 20%higher than those of the secondary flow injection angle of 110at NPR=6.Therefore,the secondary flow relative area of 0.06 and the secondary flow injection angle of 90are recommended.展开更多
Rate of penetration(ROP) of a tunnel boring machine(TBM) in a rock environment is generally a key parameter for the successful accomplishment of a tunneling project. The objectives of this work are to compare the accu...Rate of penetration(ROP) of a tunnel boring machine(TBM) in a rock environment is generally a key parameter for the successful accomplishment of a tunneling project. The objectives of this work are to compare the accuracy of prediction models employing partial least squares(PLS) regression and support vector machine(SVM) regression technique for modeling the penetration rate of TBM. To develop the proposed models, the database that is composed of intact rock properties including uniaxial compressive strength(UCS), Brazilian tensile strength(BTS), and peak slope index(PSI), and also rock mass properties including distance between planes of weakness(DPW) and the alpha angle(α) are input as dependent variables and the measured ROP is chosen as an independent variable. Two hundred sets of data are collected from Queens Water Tunnel and Karaj-Tehran water transfer tunnel TBM project. The accuracy of the prediction models is measured by the coefficient of determination(R2) and root mean squares error(RMSE) between predicted and observed yield employing 10-fold cross-validation schemes. The R2 and RMSE of prediction are 0.8183 and 0.1807 for SVMR method, and 0.9999 and 0.0011 for PLS method, respectively. Comparison between the values of statistical parameters reveals the superiority of the PLSR model over SVMR one.展开更多
基金supported by the Science Center for Gas Turbine Project,China(Nos.P2022-B-Ⅱ-010-001 and P2022-B-I-002-001)the National Natural Science Foundation of China(Nos.52376032 and 52076180)+2 种基金the Funds for Distinguished Young Scholars of Shaanxi Province,China(No.2021JC-10)the National Science and Technology Major Project,China(No.J2019-Ⅱ-0015-0036)the Fundamental Research Funds for the Central Universities,China(No.501XTCX2023146001).
文摘The high-efficiency Shock Vectoring Control Serpentine Nozzle(SVCSN)takes into account both thrust vectoring and infrared stealth,and significantly improves the comprehensive performance of the aero-engines through an additional auxiliary duct.In this paper,the schlieren photographs at the exit of the high-efficiency SVCSN and the wall static pressure distributions were obtained by experiments,and the numerical results were used to enrich the thrust vectoring characteristics.The effects of the auxiliary injection were analyzed first to reveal the advantages of the high-efficiency SVCSN compared to the conventional SVCSN.Then,the aerodynamic parameters and the structural parameters of the high-efficiency SVCSN were investigated,including the Nozzle Pressure Ratio(NPR),the Secondary flow Pressure Ratio(SPR),the secondary flow relative area and the secondary flow injection angle.Finally,the coupling performance of the high-efficiency SVCSN is studied by using the approximate modeling technology.Results show that the auxiliary injection increases the range between the two shock legs of the “k”shock wave induced by the secondary flow,then causes the separation zone and high-pressure boss of the down wall to expand upstream,and finally results in a prominent increase in the thrust vectoring performance.The thrust vectoring angle and Vectoring Efficiency(VE)of the high-efficiency SVCSN are about 61.6%and 75.7%,respectively,higher than those of the conventional SVCSN at NPR=6.The effects of the NPR and the SPR on the thrust vectoring performance of the high-efficiency SVCSN are coupled with each other.A larger NPR matched with a smaller SPR shows better thrust vectoring performance.The maximum fluctuations in thrust vectoring angle and VE caused by the NPR and SPR are about 22%and 64%.The VE decreases monotonously with the increase of the secondary flow relative area.Smaller secondary flow injection angle shows better thrust vector performance,and the thrust vectoring angle and VE of the secondary flow injection angle of 90are about 20%higher than those of the secondary flow injection angle of 110at NPR=6.Therefore,the secondary flow relative area of 0.06 and the secondary flow injection angle of 90are recommended.
基金Project(2010CB732004)supported by the National Basic Research Program of ChinaProjects(50934006,41272304)supported by the National Natural Science Foundation of China
文摘Rate of penetration(ROP) of a tunnel boring machine(TBM) in a rock environment is generally a key parameter for the successful accomplishment of a tunneling project. The objectives of this work are to compare the accuracy of prediction models employing partial least squares(PLS) regression and support vector machine(SVM) regression technique for modeling the penetration rate of TBM. To develop the proposed models, the database that is composed of intact rock properties including uniaxial compressive strength(UCS), Brazilian tensile strength(BTS), and peak slope index(PSI), and also rock mass properties including distance between planes of weakness(DPW) and the alpha angle(α) are input as dependent variables and the measured ROP is chosen as an independent variable. Two hundred sets of data are collected from Queens Water Tunnel and Karaj-Tehran water transfer tunnel TBM project. The accuracy of the prediction models is measured by the coefficient of determination(R2) and root mean squares error(RMSE) between predicted and observed yield employing 10-fold cross-validation schemes. The R2 and RMSE of prediction are 0.8183 and 0.1807 for SVMR method, and 0.9999 and 0.0011 for PLS method, respectively. Comparison between the values of statistical parameters reveals the superiority of the PLSR model over SVMR one.
