Performance Optimization of the Magnetohydrodynamic Generator at the Scramjet Inlet

Kulkarni, Nilesh; Phan, Minh Q.

doi:10.2514/1.1454

Cited by 12 publications

(4 citation statements)

References 11 publications

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“…These are given in more detail in Ref. [21]. Posing the optimization as a minimization problem, one candidate cost function that implements the requirements enumerated above is given as:…”

Section: Performance Measure Definitionmentioning

confidence: 99%

Reinforcement-Learning-based Magneto-hydrodynamic Control of Hypersonic Flows

Kulkarni

Phan

2007

2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning

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In this work, we design a policy-iterationbased Q-learning approach for on-line optimal control of ionized hypersonic flow at the inlet of a scramjet engine. Magneto-hydrodynamics (MHD) has been recently proposed as a means for flow control in various aerospace problems. This mechanism corresponds to applying external magnetic fields to ionized flows towards achieving desired flow behavior. The applications range from external flow control for producing forces and moments on the air-vehicle to internal flow control designs, which compress and extract electrical energy from the flow. The current work looks at the later problem of internal flow control. The baseline controller and Q-function parameterizations are derived from an off-line mixed predictive-control and dynamic-programming-based design. The nominal optimal neural network Q-function and controller are updated on-line to handle modeling errors in the off-line design. The on-line implementation investigates key concerns regarding the conservativeness of the update methods. Value-iteration-based update methods have been shown to converge in a probabilistic sense. However, simulations results illustrate that realistic implementations of these methods face significant training difficulties, often failing in learning the optimal controller on-line. The present approach, therefore, uses a policyiteration-based update, which has time-based convergence guarantees. Given the special finite-horizon nature of the problem, three novel on-line update algorithms are proposed. These algorithms incorporate different mix of concepts, which include bootstrapping, and forward and backward dynamic programming update rules. Simulation results illustrate success of the proposed update algorithms in re-optimizing the performance of the MHD generator during system operation.

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“…These are given in more detail in Ref. [21]. Posing the optimization as a minimization problem, one candidate cost function that implements the requirements enumerated above is given as:…”

Section: Performance Measure Definitionmentioning

confidence: 99%

Reinforcement-Learning-based Magneto-hydrodynamic Control of Hypersonic Flows

Kulkarni

Phan

2007

2007 IEEE International Symposium on Approximate Dynamic Programming and Reinforcement Learning

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“…This is known as magnetofluid energy bypass [3]. Since then, based on AJAX, scholars from various countries have carried out a great deal of research and theoretical analysis on the MHD energy bypass system of scramjet engine [4][5][6], proving the feasibility of using the MHD energy bypass system of scramjet engine, and making the MHD acceleration technology become a research hotspot in the current international aerospace industry. Generally, MHD dynamic equations are simplified in MHD acceleration simulation research, which may result in large discrepancies between simulation and actual results.…”

Section: Introductionmentioning

confidence: 99%

Numerical simulation of diverging plasma magneto-hydrodynamic acceleration channels

Wei,

Lu,

Yan

et al. 2023

Phys. Scr.

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This paper presents a numerical study of plasma flow in a magneto-hydrodynamic acceleration channel. The results show that in the channel with equal electrode pair spacing, increasing the magnetic field strength reduces the Joule heat dissipation and the temperature.Increasing the applied voltage increases the external energy input, increasing both the exitMach number and the internal temperature. Reducing the electrical conductivity achieves a balance between acceleration and temperature rise. For acceleration channels of different shapes, a constant cross section channel can only accelerate the fluid to near sonic speeds, whereas a diverging channel can achieve supersonic speeds. In addition, maintaining constant electrode spacing in the diverging channel effectively prevents fluid deceleration at the rear of the acceleration channel caused by the reverse Lorentz force under high magnetic field strength.

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“…"AJAX" hypersonic vehicle concept [3] As an important part of AJAX concept, MHD-enhanced control for aerodynamic and operability performance of hypersonic vehicles is actively being investigated abroad. The major MHD applications proved by elementary researches in hypersonic vehicles can be classified as inlet flow control [4], power generation [5], jet acceleration [6] and fuel mixing enhancement [7].…”

Section: Introductionmentioning

confidence: 99%

Progress in Hypersonic Inlet Flow Controls by Magnetohydrodynamic

Zhang

Hong

Zhang

et al. 2015

AMM

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The magnetohydrodynamic (MHD) flow control techniques for inlet based on “AJAX” vehicle concept have attracted many researchers’ attention for its potential wide applications in the supersonic flights or the hypersonic ones. In this paper, a preliminary discussion for basic problems that are ionization and magnetic field in the MHD applications is presented. And three major MHD techniques for enhancing inlet aerodynamic performance and operability, which are large scale flow control for enlarging flight scope in Mach/angle-of-attack, near surface flow control for shock wave/boundary layer interaction and leading edge heating-transfer control for enormous thermal load on leading edge of the compression ramp, are briefly explained and reviewed.

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Performance Optimization of the Magnetohydrodynamic Generator at the Scramjet Inlet

Cited by 12 publications

References 11 publications

Reinforcement-Learning-based Magneto-hydrodynamic Control of Hypersonic Flows

Reinforcement-Learning-based Magneto-hydrodynamic Control of Hypersonic Flows

Numerical simulation of diverging plasma magneto-hydrodynamic acceleration channels

Progress in Hypersonic Inlet Flow Controls by Magnetohydrodynamic

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