An evolutionary algorithm for multi-objective optimization of combustion processes
نویسندگان
چکیده
We study the optimization of the spatial distribution of fuel injection rates in a gas turbine burner. An automated procedure is implemented for the optimization. The procedure entails an evolutionary optimization algorithm and an automated interface for the modification of the parameters in the experimental setup for the fuel injection and for the post-processing. The evolutionary algorithm is capable of handling multiple objectives in a Pareto setup and of efficiently accounting for noise in the objective function. The parameterization considers eight analogue valves for controlling the fuel distribution, and the evaluation tool is an experimental test-rig for a gas turbine burner. A measurement chamber and a microphone are used to analyze the emissions and the pulsation of the burner, respectively. These two values are taken as objectives for the evolutionary algorithm. The algorithm is shown to converge to a Pareto front and the analysis of the resulting parameters elucidates further relevant physical processes.
منابع مشابه
Solving Multi-objective Optimal Control Problems of chemical processes using Hybrid Evolutionary Algorithm
Evolutionary algorithms have been recognized to be suitable for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier. This paper applies an evolutionary optimization scheme, inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategi...
متن کاملAn Approach to Reducing Overfitting in FCM with Evolutionary Optimization
Fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. In this research, FCM is chosen for fuzzy clustering. Parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. These two parameters require tuning to reduce the overfitting in the...
متن کاملMulti-objective optimization design of plate-fin heat sinks using an Evolutionary Algorithm Based On Decomposition
This article has no abstract.
متن کاملOPTIMIZATION OF STEEL MOMENT FRAME BY A PROPOSED EVOLUTIONARY ALGORITHM
This paper presents an improved multi-objective evolutionary algorithm (IMOEA) for the design of planar steel frames. By considering constraints as a new objective function, single objective optimization problems turned to multi objective optimization problems. To increase efficiency of IMOEA different Crossover and Mutation are employed. Also to avoid local optima dynamic interference of mutat...
متن کاملA Method for Pre-Calibration of DI Diesel Engine Emissions and Performance Using Neural Network and Multi-Objective Genetic Algorithm
Diesel engine emission standards are being more stringent as it gains more publicity in industry and transportation. Hence, designers have to suggest new controlling strategies which result in small amounts of emissions and a reasonable fuel economy. To achieve such a target, multi-objective optimization methodology is a good approach inasmuch as several types of ...
متن کاملPresenting an evolutionary improved algorithm for the multi-objective problem of distribution network reconfiguration in the presence of distributed generation sources and capacitor units with regard to load uncertainty.
Reconfiguration of distribution network feeders is one of the well-known and effective strategies in the distribution network to obtain a new optimal configuration for the distribution feeders by managing the status of switches in the distribution network. This study formulates the multi-objective problem of reconfiguration of a distribution network in the optimal presence of distributed genera...
متن کامل