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Relevant bibliographies by topics / Proper Orthogonal Decomposition, Surrogate Model, Optimization, External Aerodynamic

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Journal articles
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Academic literature on the topic 'Proper Orthogonal Decomposition, Surrogate Model, Optimization, External Aerodynamic'

Author: Grafiati

Published: 14 March 2023

Last updated: 31 July 2025

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Journal articles on the topic "Proper Orthogonal Decomposition, Surrogate Model, Optimization, External Aerodynamic"

1

Dolci, Valentina, and Renzo Arina. "Proper Orthogonal Decomposition as Surrogate Model for Aerodynamic Optimization." International Journal of Aerospace Engineering 2016 (2016): 1–15. http://dx.doi.org/10.1155/2016/8092824.

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A surrogate model based on the proper orthogonal decomposition is developed in order to enable fast and reliable evaluations of aerodynamic fields. The proposed method is applied to subsonic turbulent flows and the proper orthogonal decomposition is based on an ensemble of high-fidelity computations. For the construction of the ensemble, fractional and full factorial planes together with central composite design-of-experiment strategies are applied. For the continuous representation of the projection coefficients in the parameter space, response surface methods are employed. Three case studies

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2

Luo, Jiaqi, Zhen Fu, and Jiaxing Li. "Aero-Structural Design Optimization of a Transonic Fan Rotor Using an Adaptive POD-Based Hybrid Surrogate Model." Aerospace 12, no. 6 (2025): 504. https://doi.org/10.3390/aerospace12060504.

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In this study, an optimization framework for turbomachinery blades using a hybrid surrogate model assisted by proper orthogonal decomposition (POD) is introduced and then applied to the aero-structural multidisciplinary design optimization of a transonic fan rotor, NASA Rotor 67. The rotor blade is optimized through blade sweeping controlled by Gaussian radial basis functions. Calculations of aerodynamic and structural performance are achieved through computational fluid dynamics and computational structural mechanics. With a number of performance snapshots, singular value decomposition is emp

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3

Karafi, Y., Z. Moussaoui, and B. Abou El Majd. "Simultaneous surrogate modeling and dimension reduction using unsupervised learning. Application to parametric wing shape optimization." Mathematical Modeling and Computing 11, no. 1 (2024): 154–65. http://dx.doi.org/10.23939/mmc2024.01.154.

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This paper presents a machine-learning-based approach that enables simultaneous surrogate modeling and dimension reduction and applies it to aerodynamic parametric shape optimization. Aerodynamic shape optimization is a crucial process in various industries, including aerospace, automotive, and renewable energy. It involves iteratively improving the properties of a system by evaluating an objective function and driving its minimization or maximization using an optimization algorithm. However, the evaluation of aerodynamic objective functions requires computationally expensive operations, such

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4

Hu, Kaibin, Yaping Ju, Yi Feng, and Chuhua Zhang. "A Dimension Reduction-Based Multidisciplinary Design Optimization Method for High Pressure Turbine Blades." Journal of Engineering for Gas Turbines and Power, August 9, 2022. http://dx.doi.org/10.1115/1.4055186.

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Abstract The complex aero-thermal coupling between fluid and solid regions within high-pressure turbines makes it important to perform multidisciplinary design optimization of high-pressure turbine blades. However, most published work failed to consider the correlations between blade profiles and cooling structures that could best compromise the aerodynamic and thermal performance of high-pressure turbine blades, and the related optimization problems were so far limited to be single- or bi-objective ones. In this study, a dimension reduction-based multidisciplinary design optimization method i

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Dissertations / Theses on the topic "Proper Orthogonal Decomposition, Surrogate Model, Optimization, External Aerodynamic"

1

DOLCI, VALENTINA. "Proper Orthogonal Decomposition for Surrogate Models in Aerodynamics." Doctoral thesis, Politecnico di Torino, 2017. http://hdl.handle.net/11583/2678186.

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This study describes the design and implementation of surrogate models for aerodynamic optimization or database generations. Two different methods are presented: the first one follows the classical methodology: a parametric POD is applied to a set of initial solutions or snapshots obtained with an high fidelity CFD model. With respect to approaches presented in literature, in this research work no truncation of the POD modes is performed and they are all used to construct the surrogate model. Several applications are presented: a backward facing step case, the analysis of the flow around a NAC

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