Parameter Optimization of Thermal Barrier Coatings used in Two Stoke Externally Scavenged S.I. Engine using Non-Traditional Optimization Algorithms

Parameter Optimization of Thermal Barrier Coatings used in Two Stoke Externally Scavenged S.I. Engine using Non-Traditional Optimization Algorithms

Shailesh Dhomne, Ashish M. Mahalle
DOI: 10.4018/IJMMME.2016100104
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Abstract

Various researchers have studied and introduced, although limited, varieties of thermal barrier coatings (TBC) materials. Each of these TBC materials has their own respective properties. Considering all these properties which one will be the effective choice among the available lot is very difficult to estimate. The optimisation is carried out using non-traditional optimisation techniques namely simple additive weighting method (SAW), weighted product method (WPM), technique for order preference by similarity to ideal solution (TOPSIS) & preference ranking organization method for enrichment evaluations (PROMETHEE) are used to find out the best optimal choice for the specified engine. The results of the above mentioned algorithms are compared and presented in this paper to decide which tbc material will perform comparatively better & give accordingly the good results.
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2. Multiple Attribute Decision Making (Madm) Methods

The Multiple Attribute Decision Making (MADM) methods are used to solve the problems of selecting the best optimal alternatives among the given multiple alternatives which are having multiple attributes. The objective of all these attributes have to be decided based on the problem statements. For some attributes it may be maximization & for some it may be minimization. Again these attributes will have its weight or relative importance. All this information is represented in Table 1.

Various MADM methods include weighted sum method (WSM), weighted product method (WPM), technique for order preference by similarity to ideal solution (TOPSIS), analytic hierarchy process (AHP), Preference Ranking Organization Method for Enrichment Evaluations (PROMETHEE), etc. among these, TOPSIS and PROMETHEE are very widely used. Both these methods give a very close Ideal preference of choices as per the given data.

The TOPSIS technique gives the best optimal alternatives which have the shortest Euclidean distance from the ideal solution. It means that TOPSIS gives a solution which is not only closest to the hypothetically best, but also farthest from the hypothetically worst.

The method, PROMETHEE, is introduced by Brans et al30. The literature survey reveals that PROMETHEE has also have a lot of applications in various fields of science & technology29. However, it had limited applications in the field of mechanical engineering. Recently in wee years its applications have been increased.

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