scholarly journals Process Design for Optimal Minimization of Resultant Cutting Force during the Machining of Ti-6Al-4V: Response Surface Method and Desirability Function Analysis

Procedia CIRP ◽  
2019 ◽  
Vol 84 ◽  
pp. 854-860 ◽  
Author(s):  
O.O. Daramola ◽  
I. Tlhabadira ◽  
J.L. Olajide ◽  
I.A. Daniyan ◽  
E.R. Sadiku ◽  
...  
Keyword(s):  
Cutting Force ◽  
Response Surface ◽  
Response Surface Method ◽  
Process Design ◽  
Function Analysis ◽  
Desirability Function ◽  
Surface Method ◽  
Desirability Function Analysis

Application of Response Surface Methodology to Predict the Optimized Input Quantities of Parabolic Trough Concentrator

2020 ◽  
Vol 9 (3) ◽  
pp. 393-400
Author(s):  
Vijayan Gopalsamy ◽  
Ramalingam Senthil ◽  
Muthukrishnan Varatharajulu ◽  
Rajasekaran Karunakaran
Keyword(s):  
Response Surface Methodology ◽  
Numerical Model ◽  
Response Surface ◽  
Function Analysis ◽  
Desirability Function ◽  
Parabolic Trough ◽  
Global Efficiency ◽  
Energy And Exergy ◽  
Parabolic Trough Solar Collector ◽  
Desirability Function Analysis

This work carries out a numerical investigation on aluminum oxide/de-ionized water nanofluid based shield-free parabolic trough solar collector (PTSC) system to evaluate, validate, and optimize the experimental output data. A numerical model is developed using response surface methodology (RSM) for evaluation (identifying influencing parameters and its level) and single objective approach (SOA) technique of desirability function analysis (DFA) for optimization. The experimental data ensured that global efficiency was enhanced from 61.8% to 67.0% for an increased mass flow rate from 0.02 kg/s to 0.06 kg/s, respectively. The overall deviation between experimental and numerical is only 0.352%. The energy and exergy error is varied from 3.0% to 6.0%, and the uncertainty of the experiment is 3.1%. Based on the desirability function analysis, the maximum and minimum efficiencies are 49.7% and 84.9%, as per the SOA technique. This numerical model explores the way to enhance global efficiency by 26.72%.©2020. CBIORE-IJRED. All rights reserved

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