Exergetic optimization of a thermoacoustic engine using the particle swarm optimization method

Characterizing premixed laminar flame–acoustics nonlinear interaction

“…Low-emission propulsion/combustion systems are more susceptible to combustion instability. When combustion instability occurs [6][7][8][9][10][11], overheating might occur or the flame may be blow out. Such pressure oscillations may cause structural vibrations and other operational problems.…”

Theoretical and experimental investigation of thermoacoustics transfer function

“…These oscillations are mainly caused by the http://dx.doi.org/10.1016/j.apenergy.2015.04.026 0306-2619/Ó 2015 Elsevier Ltd. All rights reserved. energy transferred from the heat source to sound waves [10][11][12][13][14][15][16][17], which depends upon the nature of coupling between the flame and oncoming flow fluctuations [18,19]. Small amplitude flow disturbances can excite natural modes of combustion chamber and cause them to grow into a nonlinear limit cycle.…”

Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method

“…Step 3 On the basis of the adaptive degree, the so-far best position pbest for each particle, the so-far best position for the entire swarm gbest are calculated and the new particles will be generated using Equations (14-18) mentioned above and Equation (19), Equation (19) is expressed as follows: (19) where d = 1, 2,…., D − 1, i = 1, 2,…., N, t = 1, 2,…., t max , and satisfies the following restrictions: (20) Step 4 Check whether the termination criteria are satisfied. The termination criteria are either achieving the forecasting precision or reaching the maximum iteration number.…”

“…The PSO algorithm is considered an effective tool for solving engineering optimization problems for ordinary differential equations [19]. Each individual in the PSO flies in the search space with a velocity which is dynamically adjusted according to its own flying experience and flying experience of its companions [20]. In a PSO system, each particle saves its own best position and also saves the best position found so far in the search-space by which all the swarm is expected to move toward it [21].…”