Adding-point strategy for reduced-order hypersonic aerothermodynamics modeling based on fuzzy clustering

Chen, Xin; Liu, Li; Zhou, Si-Da; Yue, Zhenjiang

doi:10.3901/cjme.2016.0128.016

Cited by 4 publications

(2 citation statements)

References 25 publications

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“…The results show that the Kriging-based ROM is more accurate than the POD-based ROM, but the POD method is more efficient. Chen et al [29,30] used three methods, namely, the radial basis function (RBF), POD-RBF and Kriging method, to construct a reduced-order aerothermodynamic modeling framework for hypersonic vehicles. Yan et al [31] proposed the POD-Chebyshev aerodynamic thermal reduced model, which can be used to predict the heat balance state of a hypersonic vehicle, with higher computational efficiency and accuracy than Kriging method.…”

Section: Introductionmentioning

confidence: 99%

Parameterized Reduced-Order Models for Probabilistic Analysis of Thermal Protection System Based on Proper Orthogonal Decomposition

Zhang,

Yao,

Zhu

et al. 2024

Aerospace

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The thermal protection system (TPS) represents one of the most critical subsystems for vehicle re-entry. However, due to uncertainties in thermal loads, material properties, and manufacturing deviations, the thermal response of the TPS exhibits significant randomness, posing considerable challenges in engineering design and reliability assessment. Given that uncertain aerodynamic heating loads manifest as a stochastic field over time, conventional surrogate models, typically accepting scalar random variables as inputs, face limitations in modeling them. Consequently, this paper introduces an effective characterization approach utilizing proper orthogonal decomposition (POD) to represent the uncertainties of aerodynamic heating. The augmented snapshots matrix is used to reduce the dimension of the random field by the decoupling method of independently spatial and temporal bases. The random variables describing material properties and geometric thickness are also employed as inputs for probabilistic analyses. An uncoupled POD Gaussian process regression (UPOD-GPR) model is then established to achieve highly accurate solutions for transient heat conduction. The model takes random heat flux fields as inputs and thermal response fields as outputs. Using a typical multi-layer TPS and thermal structure as two examples, probabilistic analyses are conducted. The mean square relative error of a typical multi-layer TPS is less than 4%. For the thermal structure, the averaged absolute error of the radiation and insulation layer is less than 25 ∘C and 6 ∘C when the maximum reaches 1200 ∘C and 150 ∘C, respectively. This approach can provide accurate and rapid predictions of thermal responses for TPS and thermal structures throughout their entire operating time when furnished with input heat flux fields and structural parameters.

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Section: Introductionmentioning

confidence: 99%

Parameterized Reduced-Order Models for Probabilistic Analysis of Thermal Protection System Based on Proper Orthogonal Decomposition

Zhang,

Yao,

Zhu

et al. 2024

Aerospace

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“…However, the Kriging approach was of lower efficiency than the POD method. Chen 17,18 adopted three approaches, namely, radial basis function (RBF), POD-RBF and Kriging, to construct ROMs and found that Kriging-based ROM has the highest accuracy but the lowest efficiency.…”

Section: Introductionmentioning

confidence: 99%

Model reduction of aerothermodynamic for hypersonic aerothermoelasticity based on POD and Chebyshev method

Yan

Jing

Zhang

et al. 2018

Proceedings of the Institution of Mechanical Engineers, Part G:

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Accurate modeling of aerothermodynamics with low computational cost takes on a crucial role for the optimization and control of hypersonic vehicles. This study examines three reduced-order models (ROMs) to provide a reliable and efficient alternative approach for obtaining the aerothermodynamics of a hypersonic control surface. Coupled computational fluid dynamics (CFD) and computational thermostructural dynamics (CTSD) approaches are used to generate the snapshots for ROMs considering the interactions between aerothermodynamics, structural dynamics and heat transfer. One ROM adopts a surrogate approach named Kriging. The second ROM is constructed by the combination of Proper Orthogonal Decomposition (POD) and Kriging, namely, POD-Kriging. The accuracy of Kriging-based ROM is higher than that of POD-Kriging-based ROM, but the efficiency is lower. Therefore, to address the shortcomings of the above two approaches, a new ROM is developed that is composed of POD and modified Chebyshev polynomials, namely, POD-Chebyshev. The ROM based on POD-Chebyshev has the best precision and efficiency among the three ROMs and generally has less than 2% average maximum error for the studied problem.

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A real-time information integration framework for multidisciplinary coupling of complex aircrafts: an application of IIIE

Zhao

Bao

et al. 2021

Journal of Industrial Information Integration

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Adding-point strategy for reduced-order hypersonic aerothermodynamics modeling based on fuzzy clustering

Cited by 4 publications

References 25 publications

Parameterized Reduced-Order Models for Probabilistic Analysis of Thermal Protection System Based on Proper Orthogonal Decomposition

Parameterized Reduced-Order Models for Probabilistic Analysis of Thermal Protection System Based on Proper Orthogonal Decomposition

Model reduction of aerothermodynamic for hypersonic aerothermoelasticity based on POD and Chebyshev method

A real-time information integration framework for multidisciplinary coupling of complex aircrafts: an application of IIIE

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