Handling Spatial Heterogeneity in Reservoir Parameters Using Proper Orthogonal Decomposition Based Ensemble Kalman Filter for Model-Based Feedback Control of Hydraulic Fracturing

2018 ◽  
Vol 57 (11) ◽  
pp. 3977-3989 ◽  
Author(s):  
Abhinav Narasingam ◽  
Prashanth Siddhamshetty ◽  
Joseph Sang-Il Kwon
Keyword(s):  
Kalman Filter ◽  
Feedback Control ◽  
Hydraulic Fracturing ◽  
Spatial Heterogeneity ◽  
Proper Orthogonal Decomposition ◽  
Ensemble Kalman Filter ◽  
Orthogonal Decomposition ◽  
Model Based ◽  
Proper Orthogonal

scholarly journals Proper Orthogonal Decomposition as Surrogate Model for Aerodynamic Optimization

2016 ◽  
Vol 2016 ◽  
pp. 1-15 ◽  
Author(s):  
Valentina Dolci ◽  
Renzo Arina
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Parameter Space ◽  
Surrogate Model ◽  
Orthogonal Decomposition ◽  
High Fidelity ◽  
Aerodynamic Optimization ◽  
Model Based ◽  
Flow Past ◽  
First Case ◽  
Proper Orthogonal

A surrogate model based on the proper orthogonal decomposition is developed in order to enable fast and reliable evaluations of aerodynamic fields. The proposed method is applied to subsonic turbulent flows and the proper orthogonal decomposition is based on an ensemble of high-fidelity computations. For the construction of the ensemble, fractional and full factorial planes together with central composite design-of-experiment strategies are applied. For the continuous representation of the projection coefficients in the parameter space, response surface methods are employed. Three case studies are presented. In the first case, the boundary shape of the problem is deformed and the flow past a backward facing step with variable step slope is studied. In the second case, a two-dimensional flow past a NACA 0012 airfoil is considered and the surrogate model is constructed in the (Mach, angle of attack) parameter space. In the last case, the aerodynamic optimization of an automotive shape is considered. The results demonstrate how a reduced-order model based on the proper orthogonal decomposition applied to a small number of high-fidelity solutions can be used to generate aerodynamic data with good accuracy at a low cost.

scholarly journals Feedback control of an HBV model based on ensemble kalman filter and differential evolution

2018 ◽  
Vol 15 (3) ◽  
pp. 667-691 ◽  
Author(s):  
Junyoung Jang ◽  
◽  
Kihoon Jang ◽  
Hee-Dae Kwon ◽  
Jeehyun Lee ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Feedback Control ◽  
Differential Evolution ◽  
Ensemble Kalman Filter ◽  
Model Based ◽  
Hbv Model

Preserving Stability Properties in Reduced Models of Time-Periodic Systems Using Proper Orthogonal Decomposition

2011 ◽  
Author(s):  
Thomas Pumhoessel ◽  
Peter Hehenberger ◽  
Klaus Zeman
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Stability Parameter ◽  
Reduced Model ◽  
Periodic Coefficients ◽  
Reduced Models ◽  
Model Based ◽  
Wide Range ◽  
Proper Orthogonal ◽  
Time Periodic

The necessity of providing reduced models of dynamical systems is growing continuously. Model-based control and model-based design are exemplary fields of applications. In this contribution, the reduction of a controlled drivetrain of a rolling mill using the method of Proper Orthogonal Decomposition is investigated, where the specific choice of the control law leads to equations of motion with time-periodic coefficients. Depending on amplitudes and frequency parameters of the time-periodic coefficients, artificial damping is introduced, referred to as parametric control. The maximum damping effect depends on these parameters in a nonlinear manner, as it is shown by means of a stability-parameter from Floquet theory. The reduced model set-up approximates the stability-parameter of the full model in an appropriate way within a wide range of the parameters. A measure based on the linear time-invariant system is developed that gives insight into the effect of the simulated timeseries on the properties of the reduced model.

Kalman Filter Development for Real Time Proper Orthogonal Decomposition Disc Temperature Model

2016 ◽  
Author(s):  
Andrew van Paridon ◽  
Marko Bacic ◽  
Peter T. Ireland
Keyword(s):  
Kalman Filter ◽  
Proper Orthogonal Decomposition ◽  
Real Time ◽  
Best Practice ◽  
Simulated Data ◽  
Flight Simulation ◽  
Orthogonal Decomposition ◽  
Life Assessment ◽  
Thermal Dynamics ◽  
Proper Orthogonal

Extending disc life through online health monitoring has been a proven method of minimising engine downtime and maintenance costs. To properly monitor the disc requires a robust model of the disc’s non-linear thermal dynamics. A model can be improved by filtering the output using a measurement of the disc in real time. The damage models can then be computed with higher statistical confidence leading to increased safe life prediction. Recently, a model of disc temperature has been developed based on the proper orthogonal decomposition of simulated data. The model produced detailed thermal gradients for use in damage calculation and life assessment. This paper presents the development and implementation of a Kalman filter to augment that model. The location of the measurement has been assessed in order to select the most appropriate target for instrumentation. Points all around the front and back of the disc have been assessed, and the best practice result is found to be near the centre of the disc neck. Matching temperatures at this point represents a compromise between the fast dynamic response of the rim, with the slower response of the cob. The new model has been validated against an independent flight simulation that had previously been excluded from any training process. The addition of the Kalman filter allows the model to match aircraft dynamics outside the regular training trajectories. The accuracy is approximately ±30K, and there is a root-mean-square error of only 2K over the whole model at any one point in time.

Nonlinear Aeroelasticity Modeling Using a Reduced Order Model Based on Proper Orthogonal Decomposition

2007 ◽  
Author(s):  
Zhengkun Feng ◽  
Azzeddine Soulaimani
Keyword(s):  
Proper Orthogonal Decomposition ◽  
Orthogonal Decomposition ◽  
Reduced Order Model ◽  
Dynamic Responses ◽  
Cfd Model ◽  
Nonlinear Aeroelasticity ◽  
Order Model ◽  
Reduced Order ◽  
Model Based ◽  
Proper Orthogonal

Investigations of nonlinear aeroelasticity of flexible structures subjected to unsteady transonic flows were carried out by means of an aeroelasticity model coupled with a reduced order CFD model based on POD (proper orthogonal decomposition) method. The reduced order model is a three-dimensional with moving fluid boundaries. The CFD model order was reduced from more than 150000 of the full order model to 200 of the reduced order model and Limit Oscillation Cycle (LCO) was observed. The dynamic responses of the system were simulated with the coupled model. Qualitatively, the numerical simulations on AGARD 445.6 from the nonlinear aeroelasticity model coupled with the reduced order CFD model agree with those from the model coupled with the full order CFD model.

Optimal Feedback Control of Vortex Shedding Using Proper Orthogonal Decomposition Models

2001 ◽  
Vol 123 (3) ◽  
pp. 612-618 ◽  
Author(s):  
Sahjendra N. Singh ◽  
James H. Myatt ◽  
Gregory A. Addington ◽  
Siva Banda ◽  
James K. Hall
Keyword(s):  
Feedback Control ◽  
Proper Orthogonal Decomposition ◽  
Control Function ◽  
Orthogonal Decomposition ◽  
Wake Flow ◽  
Optimal Feedback Control ◽  
Stabilizing Feedback Control ◽  
Decomposition Models ◽  
System Mode ◽  
Proper Orthogonal

This paper treats the question of control of two-dimensional incompressible, unsteady wake flow behind a circular cylinder at Reynolds number Re=100. Two finite-dimensional lower order models based on proper orthogonal decomposition (POD) are considered for the control system design. Control action is achieved via cylinder rotation. Linear optimal control theory is used for obtaining stabilizing feedback control systems. An expression for the region of stability of the system is derived. Simulation results for 18-mode POD models obtained using the control function and penalty methods are presented. These results show that in the closed-loop system mode amplitudes asymptotically converge to the chosen equilibrium state for each flow model for large perturbations in the initial states.

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