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- Type:
- Image
- Descripción/Resumen:
- Arm, pinnules, and tube feet of O. bennetti
- Creador/Autor:
- Meyer, David L.
- Peticionario:
- David L. Meyer
- Fecha modificada:
- 02/13/2017
- Fecha modificada:
- 02/13/2017
- Fecha de creacion:
- 2017-02-13
- Licencia:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Image
- Descripción/Resumen:
- Oxycomanthus bennetti, looking downcurrent
- Creador/Autor:
- Meyer, David L.
- Peticionario:
- David L. Meyer
- Fecha modificada:
- 02/13/2017
- Fecha modificada:
- 02/13/2017
- Fecha de creacion:
- 2017-02-13
- Licencia:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Image
- Descripción/Resumen:
- Oxycomanthus bennetti, with Phanogenia gracilis at bottom
- Creador/Autor:
- Meyer, David L.
- Peticionario:
- David L. Meyer
- Fecha modificada:
- 02/13/2017
- Fecha modificada:
- 02/13/2017
- Fecha de creacion:
- 2017-02-13
- Licencia:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Image
- Descripción/Resumen:
- Oxycomanthus bennetti, current from right
- Creador/Autor:
- Meyer, David L.
- Peticionario:
- David L. Meyer
- Fecha modificada:
- 02/13/2017
- Fecha modificada:
- 02/13/2017
- Fecha de creacion:
- 2017-02-13
- Licencia:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Image
- Descripción/Resumen:
- Oxycomathus bennetti
- Creador/Autor:
- Meyer, David L.
- Peticionario:
- David L. Meyer
- Fecha modificada:
- 02/13/2017
- Fecha modificada:
- 02/13/2017
- Fecha de creacion:
- 2017-02-13
- Licencia:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Image
- Descripción/Resumen:
- Oxycomanthus bennetti
- Creador/Autor:
- Meyer, David L.
- Peticionario:
- David L. Meyer
- Fecha modificada:
- 02/13/2017
- Fecha modificada:
- 02/13/2017
- Fecha de creacion:
- 2017-02-13
- Licencia:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Image
- Descripción/Resumen:
- Oxycomathus bennetti with Pontiometra andersoni above; current from left
- Creador/Autor:
- Meyer, David L.
- Peticionario:
- David L. Meyer
- Fecha modificada:
- 02/13/2017
- Fecha modificada:
- 02/13/2017
- Fecha de creacion:
- 2017-02-13
- Licencia:
- Attribution-NonCommercial 4.0 International
-
- Type:
- Article
- Descripción/Resumen:
- Not available.
- Creador/Autor:
- Gregory, Irene; Figueroa, Fernando; Cohen, Kelly; Ingham, Michel; Atkins, Ella; Obayashi, Shigeru; Truszkowski, Walt; Garg, Sanjay; Blackmore, Lars; Doyle, Richard, and Nguyen, Nhan
- Peticionario:
- Kelly Cohen
- Fecha modificada:
- 02/10/2017
- Fecha modificada:
- 04/05/2017
- Fecha de creacion:
- 2009-03
- Licencia:
- All rights reserved
-
- Type:
- Article
- Descripción/Resumen:
- For the systematic development of feedback flow controllers, a numerical model that captures the dynamic behaviour of the flow field to be controlled is required. This poses a particular challenge for flow fields where the dynamic behaviour is nonlinear, and the governing equations cannot easily be solved in closed form. This has led to many versions of low-dimensional modelling techniques, which we extend in this work to represent better the impact of actuation on the flow. For the benchmark problem of a circular cylinder wake in the laminar regime, we introduce a novel extension to the proper orthogonal decomposition (POD) procedure that facilitates mode construction from transient data sets. We demonstrate the performance of this new decomposition by applying it to a data set from the development of the limit cycle oscillation of a circular cylinder wake simulation as well as an ensemble of transient forced simulation results. The modes obtained from this decomposition, which we refer to as the double POD (DPOD) method, correctly track the changes of the spatial modes both during the evolution of the limit cycle and when forcing is applied by transverse translation of the cylinder. The mode amplitudes, which are obtained by projecting the original data sets onto the truncated DPOD modes, can be used to construct a dynamic mathematical model of the wake that accurately predicts the wake flow dynamics within the lock-in region at low forcing amplitudes. This low dimensional model, derived using nonlinear artificial neural network based system identification methods, is robust and accurate and can be used to simulate the dynamic behaviour of the wake flow. We demonstrate this ability not just for unforced and open-loop forced data, but also for a feedback-controlled simulation that leads to a 90% reduction in lift fluctuations. This indicates the possibility of constructing accurate dynamic low-dimensional models for feedback control by using unforced and transient forced data only.
- Creador/Autor:
- Luchtenburg, D. M.; Cohen, Kelly; Seidel, Jurgen; Fagley, Casey, and Siegel, Stefan G.
- Peticionario:
- Kelly Cohen
- Fecha modificada:
- 02/10/2017
- Fecha modificada:
- 04/05/2017
- Fecha de creacion:
- 2008-09
- Licencia:
- All rights reserved
-
- Type:
- Article
- Descripción/Resumen:
- The effectiveness of a small array of body-mounted sensors, for estimation and eventually feedback flow control of a D-shaped cylinder wake is investigated experimentally. The research is aimed at suppressing unsteady loads resulting from the von-Kármán vortex shedding in the wake of bluff-bodies at a Reynolds number range of 100–1,000. A low-dimensional proper orthogonal decomposition (POD) procedure was applied to the stream-wise and cross-stream velocities in the near wake flow field, with steady-state vortex shedding, obtained using particle image velocimetry (PIV). Data were collected in the unforced condition, which served as a baseline, as well as during influence of forcing within the “lock-in” region. The design of sensor number and placement was based on data from a laminar direct numerical simulation of the Navier-Stokes equations. A linear stochastic estimator (LSE) was employed to map the surface-mounted hot-film sensor signals to the temporal coefficients of the reduced order model of the wake flow field in order to provide accurate yet compact estimates of the low-dimensional states. For a three-sensor configuration, results show that the estimation error of the first two cross-stream modes is within 20–40% of the PIV-generated POD time coefficients. Based on previous investigations, this level of error is acceptable for a moderately robust controller required for feedback flow control.
- Creador/Autor:
- Cohen, Kelly; Stalnov, Oksana; Fono, Ilan; Seifert, Avi, and Palei, Vitali
- Peticionario:
- Kelly Cohen
- Fecha modificada:
- 02/10/2017
- Fecha modificada:
- 04/05/2017
- Fecha de creacion:
- 2007-02
- Licencia:
- All rights reserved