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Abstract Transpiration cooling is one of the most efficient cooling technologies to protect hot section components such as turbine airfoils, missile heads and shells of rockets or space craft. This external cooling method has much higher efficiency than film cooling when consuming the same amount of coolant, due to the uniformity of coolant distribution. However, pore plugging, which frequently occurs during the operation of transpiration cooled components, has limited its long term stability and prevented its application in industrial components. Dust deposition is one of the main reasons causing plugging of pores for transpiration cooling. Although a lot of effort has been devoted into explaining dust deposition and erosion mechanisms of transpiration cooled components, reducing plugging impact remained difficult as the plugging caused by dusts was unpredictable for traditional porous media. Additive manufacturing, with capability to precisely construct structures in small scales, has emerged as considerable new tool to enhance the controllability of porous media, and furthermore, to achieve a good solution to minimize the plugging disadvantage. The present study selected a transpiration cooling configuration perforated by straight holes with an additive manufacturable diameter of 0.4 mm. Computational Fluid Dynamics (CFD) methods were employed to model the pore plugging and its effect on heat transfer. A scripting code in addition to the ANSYS CFX solver was utilized to simulate the random plugging conditions of the holes. Two hundred numerical cases with four different plugging probabilities were calculated and statistically evaluated to quantify the disadvantage of pore plugging on the cooling effectiveness. A theoretic model with convolution functions was developed to predict the local cooling effectiveness. Results obtained from the numerical analysis indicated that the overall plugging ratio was a dominating parameter for the cooling effectiveness but this single parameter was not adequate to scale the cooling effectiveness for all locations. On the contrary, the unique pair of discrete convolution parameters indexing all other transpiration holes in the array developed in this study had a significantly higher accuracy in predicting the cooling effectiveness than the overall plugging ratio. The present study was among one of the earliest to use convolution modeling method to predict transpiration cooling and related plugging disadvantages. This effort could provide a quantitative understanding of the random plugging on the specific transpiration cooling configuration, and could benefit further optimization effort to reduce the plugging disadvantage of transpiration cooling using additive manufacturing.

Abstract Transpiration cooling is one of the most efficient cooling technologies to protect hot section components such as turbine airfoils, missile heads and shells of rockets or space craft. This external cooling method has much higher efficiency than film cooling when consuming the same amount of coolant, due to the uniformity of coolant distribution. However, pore plugging, which frequently occurs during the operation of transpiration cooled components, has limited its long term stability and prevented its application in industrial components. Dust deposition is one of the main reasons causing plugging of pores for transpiration cooling. Although a lot of effort has been devoted into explaining dust deposition and erosion mechanisms of transpiration cooled components, reducing plugging impact remained difficult as the plugging caused by dusts was unpredictable for traditional porous media. Additive manufacturing, with capability to precisely construct structures in small scales, has emerged as considerable new tool to enhance the controllability of porous media, and furthermore, to achieve a good solution to minimize the plugging disadvantage. The present study selected a transpiration cooling configuration perforated by straight holes with an additive manufacturable diameter of 0.4 mm. Computational Fluid Dynamics (CFD) methods were employed to model the pore plugging and its effect on heat transfer. A scripting code in addition to the ANSYS CFX solver was utilized to simulate the random plugging conditions of the holes. Two hundred numerical cases with four different plugging probabilities were calculated and statistically evaluated to quantify the disadvantage of pore plugging on the cooling effectiveness. A theoretic model with convolution functions was developed to predict the local cooling effectiveness. Results obtained from the numerical analysis indicated that the overall plugging ratio was a dominating parameter for the cooling effectiveness but this single parameter was not adequate to scale the cooling effectiveness for all locations. On the contrary, the unique pair of discrete convolution parameters indexing all other transpiration holes in the array developed in this study had a significantly higher accuracy in predicting the cooling effectiveness than the overall plugging ratio. The present study was among one of the earliest to use convolution modeling method to predict transpiration cooling and related plugging disadvantages. This effort could provide a quantitative understanding of the random plugging on the specific transpiration cooling configuration, and could benefit further optimization effort to reduce the plugging disadvantage of transpiration cooling using additive manufacturing.

Peer-reviewed journal article Applied Rheology

Peer-reviewed journal article Applied Rheology

Abstract Effusion cooling has been recognized as the next generation of cooling technologies for gas turbine engines. Concurrent effusion cooling configurations generally consist of a large number of film cooling holes to form full coverage coolant films on the protected surfaces. Coolant superposition effect consequently became a dominating factor for effusion cooling, and increased the difficulty to correlate the effectiveness with geometric parameters. This study proposed a machine learning approach using the convolution modeling method to predict the local adiabatic cooling effectiveness for effusively cooled surfaces. The model was trained by the numerical simulation data of several regular film cooling hole arrays, then validated by the data of randomly distributed film cooling hole rows. This model utilized convolution calculations in the regression process and successfully reconstructed the cooling effectiveness distribution for the entire surfaces. Results showed a good accuracy for both the training group and the validation group. Additionally, the convolution kernel of the model visualized the effect of coolant superposition by quantifying the contribution of a neighbor coolant ejection to the target location. This machine learning approach could serve as a strong tool to regress the adiabatic cooling effectiveness effusion cooling. Additional capability of this method could be exploited in other film cooling sections in turbine engines, including combustors liners, turbine blades and turbine endwall.

Abstract Effusion cooling has been recognized as the next generation of cooling technologies for gas turbine engines. Concurrent effusion cooling configurations generally consist of a large number of film cooling holes to form full coverage coolant films on the protected surfaces. Coolant superposition effect consequently became a dominating factor for effusion cooling, and increased the difficulty to correlate the effectiveness with geometric parameters. This study proposed a machine learning approach using the convolution modeling method to predict the local adiabatic cooling effectiveness for effusively cooled surfaces. The model was trained by the numerical simulation data of several regular film cooling hole arrays, then validated by the data of randomly distributed film cooling hole rows. This model utilized convolution calculations in the regression process and successfully reconstructed the cooling effectiveness distribution for the entire surfaces. Results showed a good accuracy for both the training group and the validation group. Additionally, the convolution kernel of the model visualized the effect of coolant superposition by quantifying the contribution of a neighbor coolant ejection to the target location. This machine learning approach could serve as a strong tool to regress the adiabatic cooling effectiveness effusion cooling. Additional capability of this method could be exploited in other film cooling sections in turbine engines, including combustors liners, turbine blades and turbine endwall.

Impingement cooling has been widely used in turbine components, including endwalls, vanes and blades. Numerous investigations focus on single or multiple arrays of jets, which are typically in parallel connection. Very few studies considered jets in series connection, except for some impingement structures used in the trailing edge. Present study selected a series of double wall cooling structures using impinging jets both in series connection and parallel connection. Structures with different connections and geometry parameters were located inside a piece of super alloy to protect the substrate from the high temperature on the external side. Conjugate heat transfer simulation was implemented in this paper with a CFX solver to get the aero-thermal characteristics of the cooling channels. Work condition with power plant operating temperature and pressure was applied. Results indicate that jets linked in series enhance the heat transfer on the target surface both upstream and downstream. The increase of pressure drop induced by series-linked jets is slower than the increase of heat transfer. Conjugate heat transfer analysis implies a potential of coolant saving and pressure saving for series-linked jets.

Impingement cooling has been widely used in turbine components, including endwalls, vanes and blades. Numerous investigations focus on single or multiple arrays of jets, which are typically in parallel connection. Very few studies considered jets in series connection, except for some impingement structures used in the trailing edge. Present study selected a series of double wall cooling structures using impinging jets both in series connection and parallel connection. Structures with different connections and geometry parameters were located inside a piece of super alloy to protect the substrate from the high temperature on the external side. Conjugate heat transfer simulation was implemented in this paper with a CFX solver to get the aero-thermal characteristics of the cooling channels. Work condition with power plant operating temperature and pressure was applied. Results indicate that jets linked in series enhance the heat transfer on the target surface both upstream and downstream. The increase of pressure drop induced by series-linked jets is slower than the increase of heat transfer. Conjugate heat transfer analysis implies a potential of coolant saving and pressure saving for series-linked jets.

The last 50 years has witnessed significant improvement in film cooling technologies while transpiration cooling is still not implemented in turbine airfoil cooling. Although transpiration cooling could provide higher cooling efficiency with less coolant consumption compared to film cooling, the fine pore structure and high porosity in transpiration cooling metal media always raised difficulties in conventional manufacturing. Recently, the rapid development of additive manufacturing has provided a new perspective to address such challenge. With the capability of the innovative powder bed selective laser metal sintering (SLMS) additive manufacturing technology, the complex geometries of transpiration cooling part could be precisely fabricated and endued with improved mechanical strength. Present study utilized the SLMS additive manufacturing technology to fabricate the transpiration cooling and film cooling structures with Inconel 718 supperalloy. Five different types of porous media including two perforated plates with different hole pitches, metal sphere packing, metal wire mesh and blood vessel shaped passages for transpiration cooling were fabricated by EOS M290 System. One laidback fan-shaped film cooling coupon was also fabricated with the same printing process as the control group. Heat transfer tests under 3 different coolant mass flow rates and 4 different mainstream temperatures were conducted to evaluate the cooling performance of the printed coupons. The effects of geometry parameters including porosity, surface outlet area ratio and internal solid-fluid interface area ratio were investigated as well. The results showed that the transpiration cooling structures generally had higher cooling effectiveness than film cooling structure. The overall average cooling effectiveness of blood vessel shaped transpiration cooling reached 0.35, 0.5 and 0.57 respectively with low (1.2%), medium (2.4%) and high (3.6%) coolant injection ratios. The morphological parameters analysis showed the major factor that affected the cooling effectiveness most was the internal solid-fluid interface area ratio for transpiration cooling. This study showed that additive manufactured transpiration cooling could be a promising alternative method for turbine blade cooling and worthwhile for further investigations.