Engineering topics

Kegerise, M. A.

Publications and source records attributed to Kegerise, M. A..

5 records

NASA NTRS2017

CFD Analysis in Advance of the NASA Juncture Flow Experiment

NASA through its Transformational Tools and Technologies Project (TTT) under the Advanced Air Vehicle Program, is supporting a substantial effort to investigate the formation and origin of separation bubbles found on wing-body juncture zones. The flow behavior in these regions is highly complex, difficult to measure experimentally, and challenging to model numerically. Multiple wing configurations were designed and evaluated using Computational Fluid Dynamics (CFD), and a series of wind tunnel risk reduction tests were performed to further down-select the candidates for the final experiment. This paper documents the CFD analysis done in conjunction with the 6 percent scale risk reduction experiment performed in NASA Langley's 14- by 22-Foot Subsonic Tunnel. The combined CFD and wind tunnel results ultimately helped the Juncture Flow committee select the wing configurations for the final experiment.

Flow Experiment↗

NASA NTRS2017

CFD Analysis in Advance of the NASA Juncture Flow Experiment

NASA through its Transformational Tools and Technologies Project (TTT) under the Advanced Air Vehicle Program, is supporting a substantial effort to further investigate the formation and origin of separation bubbles found on wing-body juncture zones. The flow behavior in these regions is highly complex, difficult to measure experimentally, and challenging to model numerically. Multiple wing configurations were designed and evaluated using Computational Fluid Dynamics (CFD), and a series of wind tunnel risk reduction tests were performed to further down-select the candidates for the final experiment. This paper documents the CFD analysis done in conjunction with the 6 percent scale risk reduction experiment performed in NASA Langley’s 14- by 22-Foot Subsonic Tunnel. The combined CFD and wind tunnel results ultimately help the Juncture Flow committee select the wing configurations for the final experiment.

Lee, H. C.↗

NASA NTRS2006

Real-Time Feedback Control of Flow-Induced Cavity Tones: Fixed-Gain Control - Part 1

A generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The control algorithm demonstrated multiple Rossiter-mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. Controller performance was evaluated with a measure of output disturbance rejection and an input sensitivity transfer function. The results suggest that disturbances entering the cavity flow are collocated with the control input at the cavity leading edge. In that case, only tonal components of the cavity wall-pressure fluctuations can be suppressed and arbitrary broadband pressure reduction is not possible with the present sensor/actuator arrangement. In the control-algorithm development, the cavity dynamics were treated as linear and time invariant (LTI) for a fixed Mach number. The experimental results lend support to that treatment.

Kegerise, M. A.↗

NASA NTRS2006

Real-Time Feedback Control of Flow-Induced Cavity Tones: Adaptive Control - Part 2

An adaptive generalized predictive control (GPC) algorithm was formulated and applied to the cavity flow-tone problem. The algorithm employs gradient descent to update the GPC coefficients at each time step. Past input-output data and an estimate of the open-loop pulse response sequence are all that is needed to implement the algorithm for application at fixed Mach numbers. Transient measurements made during controller adaptation revealed that the controller coefficients converged to a steady state in the mean, and this implies that adaptation can be turned off at some point with no degradation in control performance. When converged, the control algorithm demonstrated multiple Rossiter mode suppression at fixed Mach numbers ranging from 0.275 to 0.38. However, as in the case of fixed-gain GPC, the adaptive GPC performance was limited by spillover in sidebands around the suppressed Rossiter modes. The algorithm was also able to maintain suppression of multiple cavity tones as the freestream Mach number was varied over a modest range (0.275 to 0.29). Beyond this range, stable operation of the control algorithm was not possible due to the fixed plant model in the algorithm.

Kegerise, M. A.↗

NASA NTRS2002

Adaptive Identification and Control of Flow-Induced Cavity Oscillations

Progress towards an adaptive self-tuning regulator (STR) for the cavity tone problem is discussed in this paper. Adaptive system identification algorithms were applied to an experimental cavity-flow tested as a prerequisite to control. In addition, a simple digital controller and a piezoelectric bimorph actuator were used to demonstrate multiple tone suppression. The control tests at Mach numbers of 0.275, 0.40, and 0.60 indicated approx. = 7dB tone reductions at multiple frequencies. Several different adaptive system identification algorithms were applied at a single freestream Mach number of 0.275. Adaptive finite-impulse response (FIR) filters of orders up to N = 100 were found to be unsuitable for modeling the cavity flow dynamics. Adaptive infinite-impulse response (IIR) filters of comparable order better captured the system dynamics. Two recursive algorithms, the least-mean square (LMS) and the recursive-least square (RLS), were utilized to update the adaptive filter coefficients. Given the sample-time requirements imposed by the cavity flow dynamics, the computational simplicity of the least mean squares (LMS) algorithm is advantageous for real-time control.

Kegerise, M. A.↗