Calculation of the diffusion coefficient in a heated turbulent medium using optimisation techniques

This paper develops a neural network architecture and a new processing method for solving in real time, the nonlinear equality constrained multiobjective optimization problem (NECMOP), where several nonlinear objective functions must be optimized in a conflicting situation. In this processing method, the NECMOP is converted to an equivalent scalar optimization problem (SOP). The SOP is then decomposed into several-separable subproblems processable in parallel and in a reasonable time by multiplexing switched capacitor circuits. The approach which we propose makes use of a decomposition-coordination principle that allows nonlinearity to be treated at a local level and where coordination is achieved through the use of Lagrange multipliers. The modularity and the regularity of the neural networks architecture herein proposed make it suitable for very large scale integration implementation. An application to the resolution of a physical problem is given to show that the approach used here possesses some advantages of the point of algorithmic view, and provides processes of resolution often simpler than the usual techniques.

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Solving Nonlinear Equality Constrained Multiobjective Optimization Problems Using Neural Networks

Mestari

Benzirar²,

Saber

et al. 2015

IEEE Trans. Neural Netw. Learning Syst.

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Measurement of the Root Mean Square (RMS) Temperature Fluctuations of a Turbulent Plane Jet Using an Optical Method

et al. 2016

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The purpose of this paper is to reach the root mean square (RMS) value of the fluctuating temperature along a jet plane by examining only the impact produced by a laser beam after having traversed the heated jet of air. This model is based on the Einstein–Fokker–Planck–Kolmogorov (EFPK) equation, which helped us to determine the value of the jet diffusion coefficient defined as a proportionality factor between the mean square of the deflection angle fluctuations and the length of the corresponding finite laser beam path. The numerical method of calculation in our work uses the value of the localized diffusion coefficient. This plays an essential role in measuring along the RMS of the temperature fluctuations. The obtained values are compared to the experimental measurements.

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Calculation of the diffusion coefficient in a heated turbulent medium using optimisation techniques

Cited by 2 publications

References 14 publications

Solving Nonlinear Equality Constrained Multiobjective Optimization Problems Using Neural Networks

Solving Nonlinear Equality Constrained Multiobjective Optimization Problems Using Neural Networks

Measurement of the Root Mean Square (RMS) Temperature Fluctuations of a Turbulent Plane Jet Using an Optical Method

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