Input mapping for model calibration with application to wing aerodynamics

Siyu Tao, Daniel Apley, Wei Chen, Andrea Garbo, David J. Pate, Brian J. German

Research output: Contribution to journalArticle

Abstract

A wide range of model calibration methods and formulas have been introduced in the literature for calibrating low-fidelity (LF) computer models against high-fidelity (HF) computer models or data. Although most existing model calibration techniques assume that LF and HF models have identical inputs, in some engineering applications, for example, wing aerodynamics computations, inputs to LF and HF models are often defined differently due to different levels of abstraction in modeling or simulation. For these problems, this paper proposes a new model calibration method that calibrates a mapping from HF model inputs to LF inputs by matching HF and LF model outputs. The method incorporates regularization to prevent overfitting and to allow calibration parameter selection. In the application to calibrating aerodynamic simulation models, three advantages of the proposed method are demonstrated. First, it achieves higher calibration accuracy than the traditional bias correction method when HF data are scarce. Second, it provides convenient and effective calibration parameter selection in the calibration process. Finally, it enables physical insights to be drawn from the calibrated input mapping. Specifically, for the test cases examined, the calibration adjusts wing twist angles to compensate for the neglect of thickness in the vortex lattice representation of the wing geometry.

Original languageEnglish (US)
Pages (from-to)2734-2745
Number of pages12
JournalAIAA journal
Volume57
Issue number7
DOIs
StatePublished - Jan 1 2019

Fingerprint

Aerodynamics
Calibration
Vortex flow
Geometry

ASJC Scopus subject areas

  • Aerospace Engineering

Cite this

Tao, S., Apley, D., Chen, W., Garbo, A., Pate, D. J., & German, B. J. (2019). Input mapping for model calibration with application to wing aerodynamics. AIAA journal, 57(7), 2734-2745. https://doi.org/10.2514/1.J057711
Tao, Siyu ; Apley, Daniel ; Chen, Wei ; Garbo, Andrea ; Pate, David J. ; German, Brian J. / Input mapping for model calibration with application to wing aerodynamics. In: AIAA journal. 2019 ; Vol. 57, No. 7. pp. 2734-2745.
@article{29a5d88eaf3a4bcf88518505d752e7e5,
title = "Input mapping for model calibration with application to wing aerodynamics",
abstract = "A wide range of model calibration methods and formulas have been introduced in the literature for calibrating low-fidelity (LF) computer models against high-fidelity (HF) computer models or data. Although most existing model calibration techniques assume that LF and HF models have identical inputs, in some engineering applications, for example, wing aerodynamics computations, inputs to LF and HF models are often defined differently due to different levels of abstraction in modeling or simulation. For these problems, this paper proposes a new model calibration method that calibrates a mapping from HF model inputs to LF inputs by matching HF and LF model outputs. The method incorporates regularization to prevent overfitting and to allow calibration parameter selection. In the application to calibrating aerodynamic simulation models, three advantages of the proposed method are demonstrated. First, it achieves higher calibration accuracy than the traditional bias correction method when HF data are scarce. Second, it provides convenient and effective calibration parameter selection in the calibration process. Finally, it enables physical insights to be drawn from the calibrated input mapping. Specifically, for the test cases examined, the calibration adjusts wing twist angles to compensate for the neglect of thickness in the vortex lattice representation of the wing geometry.",
author = "Siyu Tao and Daniel Apley and Wei Chen and Andrea Garbo and Pate, {David J.} and German, {Brian J.}",
year = "2019",
month = "1",
day = "1",
doi = "10.2514/1.J057711",
language = "English (US)",
volume = "57",
pages = "2734--2745",
journal = "AIAA Journal",
issn = "0001-1452",
publisher = "American Institute of Aeronautics and Astronautics Inc. (AIAA)",
number = "7",

}

Tao, S, Apley, D, Chen, W, Garbo, A, Pate, DJ & German, BJ 2019, 'Input mapping for model calibration with application to wing aerodynamics', AIAA journal, vol. 57, no. 7, pp. 2734-2745. https://doi.org/10.2514/1.J057711

Input mapping for model calibration with application to wing aerodynamics. / Tao, Siyu; Apley, Daniel; Chen, Wei; Garbo, Andrea; Pate, David J.; German, Brian J.

In: AIAA journal, Vol. 57, No. 7, 01.01.2019, p. 2734-2745.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Input mapping for model calibration with application to wing aerodynamics

AU - Tao, Siyu

AU - Apley, Daniel

AU - Chen, Wei

AU - Garbo, Andrea

AU - Pate, David J.

AU - German, Brian J.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - A wide range of model calibration methods and formulas have been introduced in the literature for calibrating low-fidelity (LF) computer models against high-fidelity (HF) computer models or data. Although most existing model calibration techniques assume that LF and HF models have identical inputs, in some engineering applications, for example, wing aerodynamics computations, inputs to LF and HF models are often defined differently due to different levels of abstraction in modeling or simulation. For these problems, this paper proposes a new model calibration method that calibrates a mapping from HF model inputs to LF inputs by matching HF and LF model outputs. The method incorporates regularization to prevent overfitting and to allow calibration parameter selection. In the application to calibrating aerodynamic simulation models, three advantages of the proposed method are demonstrated. First, it achieves higher calibration accuracy than the traditional bias correction method when HF data are scarce. Second, it provides convenient and effective calibration parameter selection in the calibration process. Finally, it enables physical insights to be drawn from the calibrated input mapping. Specifically, for the test cases examined, the calibration adjusts wing twist angles to compensate for the neglect of thickness in the vortex lattice representation of the wing geometry.

AB - A wide range of model calibration methods and formulas have been introduced in the literature for calibrating low-fidelity (LF) computer models against high-fidelity (HF) computer models or data. Although most existing model calibration techniques assume that LF and HF models have identical inputs, in some engineering applications, for example, wing aerodynamics computations, inputs to LF and HF models are often defined differently due to different levels of abstraction in modeling or simulation. For these problems, this paper proposes a new model calibration method that calibrates a mapping from HF model inputs to LF inputs by matching HF and LF model outputs. The method incorporates regularization to prevent overfitting and to allow calibration parameter selection. In the application to calibrating aerodynamic simulation models, three advantages of the proposed method are demonstrated. First, it achieves higher calibration accuracy than the traditional bias correction method when HF data are scarce. Second, it provides convenient and effective calibration parameter selection in the calibration process. Finally, it enables physical insights to be drawn from the calibrated input mapping. Specifically, for the test cases examined, the calibration adjusts wing twist angles to compensate for the neglect of thickness in the vortex lattice representation of the wing geometry.

UR - http://www.scopus.com/inward/record.url?scp=85068820957&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85068820957&partnerID=8YFLogxK

U2 - 10.2514/1.J057711

DO - 10.2514/1.J057711

M3 - Article

VL - 57

SP - 2734

EP - 2745

JO - AIAA Journal

JF - AIAA Journal

SN - 0001-1452

IS - 7

ER -