دانلود مقاله ISI انگلیسی شماره 153296
ترجمه فارسی عنوان مقاله

کاهش مدل برای شبیه سازی پویایی پرواز با استفاده از دینامیک سیالات محاسباتی

عنوان انگلیسی
Model reduction for flight dynamics simulations using computational fluid dynamics
کد مقاله سال انتشار تعداد صفحات مقاله انگلیسی
153296 2017 12 صفحه PDF
منبع

Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)

Journal : Aerospace Science and Technology, Volume 69, October 2017, Pages 15-26

ترجمه کلمات کلیدی
مدل سفارش کاهش یافته، دینامیک پرواز، دینامیک سیالات محاسباتی، شناسایی مودال، خست شبیه سازی،
کلمات کلیدی انگلیسی
Reduced order model; Flight dynamics; Computational fluid dynamics; Modal identification; Gust encounter simulations;
پیش نمایش مقاله
پیش نمایش مقاله  کاهش مدل برای شبیه سازی پویایی پرواز با استفاده از دینامیک سیالات محاسباتی

چکیده انگلیسی

Multidisciplinary simulation involving flight dynamics and computational fluid dynamics is required for high-fidelity gust loads analysis in transonic flow. However, the main limitation to a more routine use is prohibitive computational cost involved. A promising trade-off between accuracy and low-cost is model reduction of high-fidelity methods. Thus investigation of such reduction of coupled models is presented. The reduction technique relies on an expansion of the full order non-linear residual function in a truncated Taylor series and subsequent projection onto a small modal basis. Two procedures are discussed to obtain modes for the projection. First, an operator-based identification is exploited to calculate eigenpairs of the coupled Jacobian matrix related to the flight dynamics degrees-of-freedom. Secondly, proper orthogonal decomposition is used as a data-based method to obtain modes representing the system subject to external disturbance such as gusts. Benefits and limitations of the various methods are investigated by analysing results for initial disturbance and gust encounter simulations. Overall, reduced order models based on the presented approaches are able to retain the accuracy of the high-fidelity tools to predict accurately flight dynamics responses and loads while reducing the computational cost up to two orders of magnitude.