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Proceedings Papers

Constraint Handling in Bayesian Optimization -- A Comparative Study of Support Vector Machine, Augmented Lagrangian and Expected Feasible Improvement

Yuan Jin, Zheyi Yang, Shiran Dai, Yann Lebret, Olivier Jung

Proc. ASME. GT2021, Volume 2D: Turbomachinery — Multidisciplinary Design Approaches, Optimization, and Uncertainty Quantification; Radial Turbomachinery Aerodynamics; Unsteady Flows in Turbomachinery, V02DT36A003, June 7–11, 2021

Paper No: GT2021-58562

DOI: https://doi.org/10.1115/GT2021-58562

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Topics: Optimization, Support vector machines, Experimental design, Design, Disks, Pressure, Turbines

Proceedings Papers

Automatically Designed Deep Gaussian Process for Turbomachinery Application

Yuan Jin, Jin Chai, Olivier Jung

Paper No: GT2021-58469

DOI: https://doi.org/10.1115/GT2021-58469

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Topics: Turbomachinery, Turbines, Design, Artificial neural networks, Blades, Dimensions, Pressure, Robustness, Stochastic processes

Proceedings Papers

Prediction of Non-Linear Mechanical Behavior With Deep Neural Network: Application on Low Pressure Turbine Disc

Yuan Jin, Weichen Li, Zheyi Yang, Olivier Jung

Proc. ASME. GT2020, Volume 2D: Turbomachinery, V02DT38A005, September 21–25, 2020

Paper No: GT2020-14382

DOI: https://doi.org/10.1115/GT2020-14382

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Topics: Artificial neural networks, Disks, Mechanical behavior, Pressure, Turbines, Constitutive equations, Displacement, Design, Engineering simulation, Elastoplasticity

Proceedings Papers

Prediction of Flow Properties on Turbine Vane Airfoil Surface From 3D Geometry With Convolutional Neural Network

Yuan Jin, Shan Li, Olivier Jung

Proc. ASME. GT2019, Volume 2D: Turbomachinery, V02DT46A007, June 17–21, 2019

Paper No: GT2019-90811

DOI: https://doi.org/10.1115/GT2019-90811

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Topics: Airfoils, Artificial neural networks, Flow (Dynamics), Geometry, Turbines, Design, Computational fluid dynamics, Engineering simulation, Simulation, Accuracy and precision

Journal Articles

Offline Predictive Control of Out-of-Plane Shape Deformation for Additive Manufacturing

Yuan Jin, S. Joe Qin, Qiang Huang

J. Manuf. Sci. Eng. December 2016, 138(12): 121005.

Paper No: MANU-15-1375

DOI: https://doi.org/10.1115/1.4033444

Published Online: July 25, 2016

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Topics: Deformation, Errors, Shapes, Modeling

Journal citation

NARROW

Constraint Handling in Bayesian Optimization -- A Comparative Study of Support Vector Machine, Augmented Lagrangian and Expected Feasible Improvement

Automatically Designed Deep Gaussian Process for Turbomachinery Application

Prediction of Non-Linear Mechanical Behavior With Deep Neural Network: Application on Low Pressure Turbine Disc

Prediction of Flow Properties on Turbine Vane Airfoil Surface From 3D Geometry With Convolutional Neural Network

Offline Predictive Control of Out-of-Plane Shape Deformation for Additive Manufacturing

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Constraint Handling in Bayesian Optimization -- A Comparative Study of Support Vector Machine, Augmented Lagrangian and Expected Feasible Improvement

Automatically Designed Deep Gaussian Process for Turbomachinery Application

Prediction of Non-Linear Mechanical Behavior With Deep Neural Network: Application on Low Pressure Turbine Disc

Prediction of Flow Properties on Turbine Vane Airfoil Surface From 3D Geometry With Convolutional Neural Network

Offline Predictive Control of Out-of-Plane Shape Deformation for Additive Manufacturing

Journals

Conference Proceedings

eBooks

Resources

Opportunities

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