Optimizing the Design of Radiator using Genetic Algorithms
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problem statementIt is generally desired to find a solution for radiator design that simultaneously meets both the performance requirements and cost targets. Since a number of parameters affect both the performance and the cost, it is important to evaluate the search space thoroughly to obtain the best possible solution. The radiator heat transfer model is linearized about a known configuration from a flattened tube / fin array (surface 9.68 –0.87)14. This paper presents a solution approach in which a genetic algorithm manipulates the parameters to find a near-optimum solution. This study reveals the details of the approach that solves the problem of searching the cost-effective design of an automotive radiator for a pre-defined level of performance of a radiator. This is accomplished by providing the details of the configuration of the tubes and the fins along with the details of the cross-section of the tube for the specific design problem. literature rEview The automobile industry is a field in which an abundance of research has been conducted. Since radiators play an integral role in the operation of an automobile, these devices have been explored extensively. The concentration has always been on evaluating the radiator together with the cooling system of the engine4. A work in the early 1970’s focused on heat dissipation from a radiator to cool vehicle engines1. Further, during that time a computer program for selecting a radiator to provide a desired level of engine cooling and for predicting the engine cooling performance with a given radiator was formulated2. Simulations were developed for evaluating the performance of a radiator as a single part of an entire cooling system. As time passed researchers started analyzing the material of the radiator and now aluminum is considered to produce the best performance based upon the statistics available because of a better method of manufacturing and new metallurgical combinations3. Chiou9 conducted a study to understand the effect of the tube length on the heat transfer capability of a heat exchanger. Further, Emmaenthal and Hacho10 presented a method to design the cooling system of an automobile where the individual components were first described using experimental data and then the study was carried out to achieve the low cost design. But, genetic algorithms have not been previously applied to the problem of optimizing the design of a radiator. Download 251.97 Kb. Share with your friends:
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