An adjoint-based approach to computing the time-domain sensitivity of systems described by reduced-order models

Author(s):  
T. Ahmed ◽  
E. Gad ◽  
M. Yagoub
AIAA Journal ◽  
2017 ◽  
Vol 55 (7) ◽  
pp. 2437-2449 ◽  
Author(s):  
Rakesh Sarma ◽  
Richard P. Dwight

2012 ◽  
Vol 22 (2) ◽  
pp. 175-189
Author(s):  
Peter Hippe

Regular design equations for the discrete reduced-order Kalman filter In the presence of white Gaussian noises at the input and the output of a system Kalman filters provide a minimum-variance state estimate. When part of the measurements can be regarded as noise-free, the order of the filter is reduced. The filter design can be carried out both in the time domain and in the frequency domain. In the case of full-order filters all measurements are corrupted by noise and therefore the design equations are regular. In the presence of noise-free measurements, however, they are not regular so that standard software cannot readily be applied in a time-domain design. In the frequency domain the spectral factorization of the non-regular polynomial matrix equation causes no problems. However, the known proof of optimality of the factorization result requires a regular measurement covariance matrix. This paper presents regular (reduced-order) design equations for the reduced-order discrete-time Kalman filter in the time and in the frequency domains so that standard software is applicable. They also allow to formulate the conditions for the stability of the filter and to prove the optimality of the existing solutions.


2021 ◽  
Author(s):  
Celso P. Pesce ◽  
Giovanni A. Amaral ◽  
Bruno Mendes ◽  
Everton L. Oliveira ◽  
Guilherme R. Franzini

Abstract As well known, VIM is a complex phenomenon that requires nonlinear models to be constructed and simulated, either through computationally demanding CFD approaches or by making use of reduced-order models (ROM), which are based on phenomenological schemes to emulate the vortex wake dynamics. However, even ROM approaches might be relatively time demanding to be used efficiently during initial stages of design, particularly within optimization schemes. A simple model is herein proposed to treat this rather complex problem in the design context. For a range of current intensities and for a complete turn of current directions, offsets and headings are determined, for which maps of natural periods and corresponding modes of oscillations are constructed. A criterion to inspect modes that are prone to resonance is proposed and polar maps of susceptibility to VIM are plotted. The criterion considers ratios between exciting and natural frequencies. Dominances of translational or yaw motions on resonant modes are quantified and discussed. To assess the proposed strategy, VIM susceptibility polar maps are confronted with results of time domain simulations, using a nonlinear ROM. The OC4-DEEPCWIND Floating Wind Turbine is taken as case-study.


2020 ◽  
Vol 124 (1281) ◽  
pp. 1798-1818 ◽  
Author(s):  
S. Lee ◽  
H. Cho ◽  
H. Kim ◽  
S.-J. Shin

ABSTRACTThe aeroelastic phenomenon of limit-cycle oscillations (LCOs) is analysed using a projection-based reduced-order model (PROM) and Navier–Stokes computational fluid dynamics (CFD) in the time domain. The proposed approach employs incompressible Navier–Stokes CFD to construct the full-order model flow field. A proper orthogonal decomposition (POD) of the snapshot matrix is conducted to extract the POD modes and corresponding temporal coefficients. The POD modes are directly projected to the incompressible Navier–Stokes equation to reconstruct the flow field efficiently. The methodology is applied to a plunging cylinder and an aerofoil undergoing LCOs. This scheme decreases the computational time while preserving the capability to predict the flow field accurately. The ROM is capable of reducing the computational time by at least 70% while maintaining the discrepancy within 0.1%. The causes of LCOs are also investigated. The scheme can be used to analyse non-linear aeroelastic phenomena in the time domain with reduced computational time.


Sign in / Sign up

Export Citation Format

Share Document