... imitations of actual engine performance. A nonlinear multiple point genetic algorithm based performance adaptation developed earlier by the authors using a set of nonlinear scaling factor functions has been proven capable of making accurate performance predictions over a wide range of operating conditions...

... by “modifying” initially implemented component characteristic maps in the gas turbine thermodynamic performance models. A genetic algorithm is used to search for an optimal set of nonlinear scaling factor functions for the maps via an objective function that measures the difference between the simulated...

... are based on the numerical solution of the Navier–Stokes equations for incompressible isothermal flow. To optimize the bearing performance, an optimization problem is formulated and solved by coupling the CFD code with an optimization tool based on genetic algorithms and local search methods. Here...

... and constraints. The complex design optimization problem is solved using heuristic optimization algorithms, such as genetic, and particle-swarm optimization. Whereas both algorithms found better design solutions than the initial design, the genetic algorithms exhibited the fastest convergence. A statistical...

... genetic algorithm II (NSGA II) ( Deb, K., Pratap, A., Agarwal, S., and Meyarivan, T., 2002, “A Fast and Elitist Multiobjective Genetic Algorithm: NSGA-II,” IEEE Trans. Evol. Comput., 6, pp. 182–197 ) performed better than other popular multiobjective genetic algorithms (MOGAs) in engine optimization...

... artificial intelligence diesel engines engine cylinders fuel economy genetic algorithms neurocontrollers regression analysis 10 03 2009 04 06 2009 19 01 2010 19 01 2010 The advantage of these process-relevant inputs and their functional coherence to the emission values...

... profitability. A production-planning approach has been developed, and genetic algorithm techniques have been adopted to implement the developed approach. Life consumption of gas turbines’ hot-section components has been considered as a key element required in simulating plants’ behaviors. As a result...

... of some uncertainties because of errors in measurements, manufacturing tolerances and so on. According to model uncertainties, the probability of satisfaction for dynamic performance requirements was computed as the objective function of a genetic algorithm, which was used to optimize the parameters...

..., they are not provided to the customer generally. Some scaling methods for gas turbine component maps using experimental data or data partially given by engine manufacturers had been proposed in a previous study. Among them the map generation method using experimental data and genetic algorithms had showed...

...Wang Qiuwang; Liang Hongxia; Xie Gongnan; Zeng Min; Luo Laiqin; Feng ZhenPing In recent years, the genetic algorithm (GA) technique has gotten much attention in solving real-world problems. This technique has a strong ability for global searching and optimization based on various objectives...

...; final manuscript received March 1, 2004. IGTI Review Chair: A. J. Strazisar. 13 June 2004 01 October 2003 01 March 2004 13 06 2006 thermal analysis genetic algorithms gas turbine power stations distributed power generation power markets power generation economics...

...Anders Angantyr; Jan-Olov Aidanpää This paper presents the constrained optimization of the tilting pad bearing design on a gas turbine rotor system. A real coded genetic algorithm with a robust constraint handling technique is used as the optimization method. The objective is to develop...

...Bryce Roth; Chirag Patel The objective of this paper is to demonstrate the application of genetic algorithms to the engine technology selection process. The “technology identification, evaluation, and selection” method is discussed in conjunction with genetic algorithm optimization as a technique...

... frequencies. The bearings and some geometrical variables of the rotor are used as the primary design variables in order to achieve a feasible design. This paper presents an alternative approach to search for feasible designs. The design problem is formulated as an optimization problem and a genetic algorithm...

...L. Elliott; D. B. Ingham; A. G. Kyne; N. S. Mera; M. Pourkashanian; C. W. Wilson This study uses a multi-objective genetic algorithm to determine new reaction rate parameters ( A ’s, β’s and E a ’s in the non-Arrhenius expressions) for the combustion of a methane/air mixture. The multi-objective...

... January 2003. Associate Editor: D. Assanis. 01 March 2002 01 January 2003 02 03 2004 internal combustion engines air pollution control combustion chemical variables control genetic algorithms nitrogen compounds The US Environmental Protection Agency (EPA...

...B. A. Roth; M. D. Graham; D. N. Mavris; N. I. Macsotai The objective of this paper is to describe a method for selecting optimal engine technology solution sets while simultaneously accounting for the presence of technology risk. This method uses a genetic algorithm in conjunction with technology...

...L. Elliott; D. B. Ingham; A. G. Kyne; N. S. Mera; M. Pourkashanian; C. W. Wilson This study presents a novel multiobjective genetic-algorithm approach to produce a new reduced chemical kinetic reaction mechanism to simulate aviation fuel combustion under various operating conditions. The mechanism...

... lower than that using the real component maps. Therefore, a component map generation method using experimental data and the genetic algorithms are newly proposed in this study. The engine test unit to be used for map generation has a free power turbine type small turboshaft engine. In order to generate...

...Suresh Sampath; Riti Singh This paper presents the development of an integrated fault diagnostics model for identifying shifts in component performance and sensor faults using the Genetic Algorithm and Artificial Neural Network. The diagnostics model operates in two distinct stages. The first stage...