Study of fluid–thermal–structural interaction in high-temperature high-speed flow using multi-fidelity multi-variate surrogates
D Huang, A Sadagopan, Ü Düzel… - Journal of Fluids and …, 2022 - Elsevier
This study investigates the impact of the high-temperature effect, especially the real gas
effect and chemical reactions, on hypersonic aerothermodynamic solutions of double cone …
effect and chemical reactions, on hypersonic aerothermodynamic solutions of double cone …
Physics-Infused Reduced-Order Modeling of Aerothermal Loads for Hypersonic Aerothermoelastic Analysis
C Vargas Venegas, D Huang - AIAA journal, 2023 - arc.aiaa.org
This paper presents a novel physics-infused reduced-order modeling (PIROM) methodology
for efficient and accurate modeling of nonlinear dynamical systems. The PIROM consists of a …
for efficient and accurate modeling of nonlinear dynamical systems. The PIROM consists of a …
Holistic characterization of an under-expanded high-enthalpy jet under uncertainty
Elaborate methodologies have been developed to study the thermo-chemical response of
materials in high-enthalpy flows. To reach the high magnitudes of heat flux encountered in …
materials in high-enthalpy flows. To reach the high magnitudes of heat flux encountered in …
Modal Analysis of Spatiotemporal Data via Multi-fidelity Multi-variate Gaussian Processes
View Video Presentation: https://doi. org/10.2514/6.2023-4350. vid This paper focuses on
the challenges associated with the existing dynamic mode decomposition (DMD) techniques …
the challenges associated with the existing dynamic mode decomposition (DMD) techniques …
Assessment of Multi-Fidelity Surrogate Methods for Expedient Loads Prediction in High-Speed Flows
TE Korenyi-Both - 2023 - rave.ohiolink.edu
Fast and accurate predictions about the flow field surrounding a hypersonic flight vehicle are
necessary for both early design phases and autonomous vehicle control. The complex flow …
necessary for both early design phases and autonomous vehicle control. The complex flow …
Credibility Assessment of Machine Learning in a Manufacturing Process Application
GA Banyay, CL Worrell… - Journal of …, 2021 - asmedigitalcollection.asme.org
We present a framework for establishing credibility of a machine learning (ML) model used
to predict a key process control variable setting to maximize product quality in a component …
to predict a key process control variable setting to maximize product quality in a component …
Modal Analysis of Spatiotemporal Data via Multivariate Gaussian Process Regression
Modal analysis has become an essential tool to understand the coherent structure of
complex flows. The classical modal analysis methods, such as dynamic mode …
complex flows. The classical modal analysis methods, such as dynamic mode …
Efficient Multidisciplinary Analysis and Optimization of Hypersonic Vehicles Using Multi-Fidelity Surrogate Models
JT Needels - 2024 - search.proquest.com
The trade between computational cost and model accuracy is a fundamental challenge in
engineering design: models of higher fidelity (ie physical accuracy) typically require …
engineering design: models of higher fidelity (ie physical accuracy) typically require …
Applications of Gaussian Process Regression in the Aero-Thermo-Servo-Elastic Analysis Towards Integrated Hypersonic Flight Dynamic Analysis
D Huang - 2021 60th IEEE Conference on Decision and …, 2021 - ieeexplore.ieee.org
This tutorial paper presents the surrogate modeling based on Gaussian process regression
(GPR) and its application in the hypersonic aero-thermo-servo-elastic analysis, a key …
(GPR) and its application in the hypersonic aero-thermo-servo-elastic analysis, a key …
Physics-Infused Reduced-Order Modeling of Aerothermal Loads for Fluid-Thermal-Structural Interactions
C Vargas Venegas - 2022 - etda.libraries.psu.edu
Although considerable advancements have been made during the past several decades in
hypersonic vehicle technologies, there are still numerous unresolved experimental and …
hypersonic vehicle technologies, there are still numerous unresolved experimental and …