کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
6630707 1424936 2018 19 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Diesel engine optimization with multi-objective performance characteristics by non-evolutionary Nelder-Mead algorithm: Sobol sequence and Latin hypercube sampling methods comparison in DoE process
موضوعات مرتبط
مهندسی و علوم پایه مهندسی شیمی مهندسی شیمی (عمومی)
پیش نمایش صفحه اول مقاله
Diesel engine optimization with multi-objective performance characteristics by non-evolutionary Nelder-Mead algorithm: Sobol sequence and Latin hypercube sampling methods comparison in DoE process
چکیده انگلیسی
This research deals with the diesel engine optimization by Nelder-Mead algorithm and initial points distribution done by Sobol sequence and Latin hypercube sampling methods. Nelder-Mead algorithm is a non-evolutionary algorithm which needs some initial points in order to start the optimization process and then understand the relationship between input parameters and output objective functions. In this study, these points are produced once by Sobol sequence and once by Latin Hypercube in order to make a comparison between these two sequences and investigate the effect of sequence on the results. The input parameters are Da (outer bowl diameter), Dm (bowl middle diameter), Tm (bowl center depth), nozzle hole half outer cone angle and nozzle hole outer diameter, and objective functions are combustion noise, swirl and indicated torque. Final results show that although in both cases the results are close to each other, in Sobol mode it takes just 7 RunIDs (Run Identification) to find the solution but in Latin Hypercube method the algorithm needs 27 RunIDs to find the solution. In both cases almost the combustion noise changes just 0.2%, swirl improves 20.4% and the indicated torque increases about 7.65%.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Fuel - Volume 228, 15 September 2018, Pages 349-367
نویسندگان
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