To reduce the influence of adverse flow conditions at the fan hub and improve fan aerodynamic performance, a modification of conventional axial fan blades with numerical and experimental investigation is presented. Ho...To reduce the influence of adverse flow conditions at the fan hub and improve fan aerodynamic performance, a modification of conventional axial fan blades with numerical and experimental investigation is presented. Hollow blade root is manufactured near the hub. The numerical and experimental results show that hollow blade root has some effect on the static performance. Static pressure of the modified fan is generally the same with that of the datum fan, while, the efficiency curve of the modified fan has a different trend with that of the datum fan. The highest efficiency of the modified fan is 10% greater than that of the datum fan. The orthogonal experimental re- suits of fan noise show that hollow blade root is a feasible method of reducing fan noise, and the maximum value of noise reduction is about 2 dB. The factors affecting the noise reduction of hollow blade root are in the order of importance as follows： hollow blade margin, hollow blade height and hollow blade width. The much smoother pressure distribution of the modified fan than that of the datum fan is the main mechanism of noise reduction of hollow blade root. The research results will provide the proof of the parameter optimization and the structure de- sign for high performance and low noise small axial fans.展开更多
The three-dimensional solidification simulation of the investment castings of single crystal hollow turbine blade at the withdrawal rates of 2 mm/min, 4.5 mm/min and 7 mm/min has been performed with the finite element...The three-dimensional solidification simulation of the investment castings of single crystal hollow turbine blade at the withdrawal rates of 2 mm/min, 4.5 mm/min and 7 mm/min has been performed with the finite element thermal analysis. The calculated results are in accordance with the experimental ones. The results show that with the increase of withdrawal rate the concave curvature of the liquidus isotherm is larger and larger, and the temperature gradients of the blades increase. No effects of withdrawal rate on the distribution of the temperature gradients of the starter and helical grain selector of the blades are observed at withdrawal rates of 2 mm/min, 4.5 mm/min and 7 mm/min. The relatively high temperature gradient between 500℃/cm and 1000℃/cm in the starter and helical grain selector is obtained at three withdrawal rates.展开更多
The control of grain size in superalloys is critical in the manufacture of gas turbine blades.The aim of the present research is to provide the technology for producing complicated hollow turbine blades with fine surf...The control of grain size in superalloys is critical in the manufacture of gas turbine blades.The aim of the present research is to provide the technology for producing complicated hollow turbine blades with fine surface grains and better comprehensive mechanical properties.By melt superheating treatment and coating the internal surfaces of shell mould using a cobalt aluminate-bearing coating material,the in-uence of cobalt aluminate as inoculant on the surface grain sizes of turbine blade was studied with addition of cobalt aluminate:0,35%,45%-65% and 100% respectively.At the same time,the effects of cooling circumstances of the blades on surface grain sizes were also experimented under the same addition of cobalt aluminate.The results showed that the melt superheating treatment plays a significant role in the grain size and carbide morphology;and fine surface grains were obtained when the internal surfaces of shell mould were coated using cobalt aluminate coatings.When the addition of cobalt aluminate in coating is between 45%-65%,and the melt is poured into preheated shell moulds with fine silica sand as backing sand,the blades satisfied the surface grain size requirement is over 90%.In addition,comparisons of the surface grain size and the mechanical properties were also conducted between home-made and foreign-made blades.展开更多
The deviation in wall thickness caused by core shift during the investment casting process significantly impacts the strength and service life of hollow turbine blades.To address this issue,a core shift limitation met...The deviation in wall thickness caused by core shift during the investment casting process significantly impacts the strength and service life of hollow turbine blades.To address this issue,a core shift limitation method is developed in this study.Firstly,a shift model is established based on computational fluid dynamics and motion simulation to predict the movement of the ceramic core in investment casting process.Subsequently,utilizing this model,an optimization method for fixturing layout inside the refractory ceramic shell is devised for the ceramic core.The casting experiment demonstrates that by utilizing the optimized fixture layout,not only can core shift during the investment casting pouring process be effectively controlled,but also the maximum wall thickness error of the blade can be reduced by 42.02%.In addition,the core shift prediction is also validated,with a prediction error of less than 26.9%.展开更多
Wax pattern fabrication in the investment casting of hollow turbine blades directly determines the dimension accuracy of subsequent casting,and therefore significantly affects the quality of final product.In this work...Wax pattern fabrication in the investment casting of hollow turbine blades directly determines the dimension accuracy of subsequent casting,and therefore significantly affects the quality of final product.In this work,we develop a machine learning-based multi-objective optimization framework for improving dimension accuracy of wax pattern by optimizing its process parameters.We consider two optimization objectives on the dimension of wax pattern,i.e.,the surface warpage and core offset.An active learning of Bayesian optimization is employed in data sampling to determine process parameters,and a validated numerical model of injection molding is used to compute objective results of dimension under varied process parameters.The collected dataset is then leveraged to train different machine learning models,and it turns out that the Gaussian process regression model performs best in prediction accuracy,which is then used as the surrogate model in the optimization framework.A genetic algorithm is employed to produce a non-dominated Pareto front using the surrogate model in searching,followed by an entropy weight method to select the most optimal solution from the Pareto front.The optimized set of process parameters is then compared to empirical parameters obtained from previous trial-and-error experiments,and it turns out that the maximum and average warpage results of the optimized solution decrease 26.0%and 20.2%,and the maximum and average errors of wall thickness compared to standard part decrease from 0.22 mm and 0.0517 mm using empirical parameters to 0.10 mm and 0.0356 mm using optimized parameters,respectively.This framework is demonstrated capable of addressing the challenge of dimension control arising in the wax pattern production,and it can be reliably deployed in varied types of turbine blades to significantly reduce the manufacturing cost of turbine blades.展开更多
基金supported by National Natural Science Foundation of China(No.51249003,No.51006090)Major Special Project of Technology Office in Zhejiang Province(No.2011C16038,No.2011C11073)
文摘To reduce the influence of adverse flow conditions at the fan hub and improve fan aerodynamic performance, a modification of conventional axial fan blades with numerical and experimental investigation is presented. Hollow blade root is manufactured near the hub. The numerical and experimental results show that hollow blade root has some effect on the static performance. Static pressure of the modified fan is generally the same with that of the datum fan, while, the efficiency curve of the modified fan has a different trend with that of the datum fan. The highest efficiency of the modified fan is 10% greater than that of the datum fan. The orthogonal experimental re- suits of fan noise show that hollow blade root is a feasible method of reducing fan noise, and the maximum value of noise reduction is about 2 dB. The factors affecting the noise reduction of hollow blade root are in the order of importance as follows： hollow blade margin, hollow blade height and hollow blade width. The much smoother pressure distribution of the modified fan than that of the datum fan is the main mechanism of noise reduction of hollow blade root. The research results will provide the proof of the parameter optimization and the structure de- sign for high performance and low noise small axial fans.
文摘The three-dimensional solidification simulation of the investment castings of single crystal hollow turbine blade at the withdrawal rates of 2 mm/min, 4.5 mm/min and 7 mm/min has been performed with the finite element thermal analysis. The calculated results are in accordance with the experimental ones. The results show that with the increase of withdrawal rate the concave curvature of the liquidus isotherm is larger and larger, and the temperature gradients of the blades increase. No effects of withdrawal rate on the distribution of the temperature gradients of the starter and helical grain selector of the blades are observed at withdrawal rates of 2 mm/min, 4.5 mm/min and 7 mm/min. The relatively high temperature gradient between 500℃/cm and 1000℃/cm in the starter and helical grain selector is obtained at three withdrawal rates.
文摘The control of grain size in superalloys is critical in the manufacture of gas turbine blades.The aim of the present research is to provide the technology for producing complicated hollow turbine blades with fine surface grains and better comprehensive mechanical properties.By melt superheating treatment and coating the internal surfaces of shell mould using a cobalt aluminate-bearing coating material,the in-uence of cobalt aluminate as inoculant on the surface grain sizes of turbine blade was studied with addition of cobalt aluminate:0,35%,45%-65% and 100% respectively.At the same time,the effects of cooling circumstances of the blades on surface grain sizes were also experimented under the same addition of cobalt aluminate.The results showed that the melt superheating treatment plays a significant role in the grain size and carbide morphology;and fine surface grains were obtained when the internal surfaces of shell mould were coated using cobalt aluminate coatings.When the addition of cobalt aluminate in coating is between 45%-65%,and the melt is poured into preheated shell moulds with fine silica sand as backing sand,the blades satisfied the surface grain size requirement is over 90%.In addition,comparisons of the surface grain size and the mechanical properties were also conducted between home-made and foreign-made blades.
基金the National Natural Science Foundation of China(Grant No.52005311)the Scientific and the National Science and Technology Major Project(Grant No.J2019-VII-0013-0153)Research Project Supported by Shanxi Scholarship Council of China(Grant No.2023-003).
文摘The deviation in wall thickness caused by core shift during the investment casting process significantly impacts the strength and service life of hollow turbine blades.To address this issue,a core shift limitation method is developed in this study.Firstly,a shift model is established based on computational fluid dynamics and motion simulation to predict the movement of the ceramic core in investment casting process.Subsequently,utilizing this model,an optimization method for fixturing layout inside the refractory ceramic shell is devised for the ceramic core.The casting experiment demonstrates that by utilizing the optimized fixture layout,not only can core shift during the investment casting pouring process be effectively controlled,but also the maximum wall thickness error of the blade can be reduced by 42.02%.In addition,the core shift prediction is also validated,with a prediction error of less than 26.9%.
基金funded by the National Key Research and Development Program of China(Grant No.2019YFA0705302)the National Science and Technology Major Project“Aeroengine and Gas Turbine”of China(Grant No.2017-VII-0008-0102).
文摘Wax pattern fabrication in the investment casting of hollow turbine blades directly determines the dimension accuracy of subsequent casting,and therefore significantly affects the quality of final product.In this work,we develop a machine learning-based multi-objective optimization framework for improving dimension accuracy of wax pattern by optimizing its process parameters.We consider two optimization objectives on the dimension of wax pattern,i.e.,the surface warpage and core offset.An active learning of Bayesian optimization is employed in data sampling to determine process parameters,and a validated numerical model of injection molding is used to compute objective results of dimension under varied process parameters.The collected dataset is then leveraged to train different machine learning models,and it turns out that the Gaussian process regression model performs best in prediction accuracy,which is then used as the surrogate model in the optimization framework.A genetic algorithm is employed to produce a non-dominated Pareto front using the surrogate model in searching,followed by an entropy weight method to select the most optimal solution from the Pareto front.The optimized set of process parameters is then compared to empirical parameters obtained from previous trial-and-error experiments,and it turns out that the maximum and average warpage results of the optimized solution decrease 26.0%and 20.2%,and the maximum and average errors of wall thickness compared to standard part decrease from 0.22 mm and 0.0517 mm using empirical parameters to 0.10 mm and 0.0356 mm using optimized parameters,respectively.This framework is demonstrated capable of addressing the challenge of dimension control arising in the wax pattern production,and it can be reliably deployed in varied types of turbine blades to significantly reduce the manufacturing cost of turbine blades.
