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A simplistic regression-based genetic algorithm optimization of tool-work interface temperature

Utkarsh, Kumar Saumya, Kumar Saaransh, Kiran G. Uday, Mukhopadhyay Arkadeb, Barman Manik

Engineering Transactions

2022

Vol. 70, iss. 2

141--156

This work aims to investigate the average tool-work interface temperature for the HSS tool and AISI 1040 steel pair. A tool-work thermocouple is proposed for the measurement of temperature because of its simple construction in addition to the low cost. The machining process of AISI 1040 steel is considered due to its extensive application, including industry usage. The changes in cutting temperature are studied for combinations of cutting speed, feed and the depth of cut during turning operation. The orthogonal array L9 by Taguchi is adopted for designing the experiments within a restricted set of runs. The average cutting temperature shows an increasing curve with functions of speed versus depth of cut and speed versus feed. But no clear trend is observed for a combination of feed versus depth of cut. A second-order regression equation with reasonable accuracy (R 2 = 0.99) is fitted using the data. Analysis of variance (ANOVA) reveals the highest contribution from cutting speed, which influences average temperature at the interface of tool and work. Further, the genetic algorithm predicts an optimal combination of parameters, which is 82.542 m/min cutting speed, 0.276 mm/rev feed rate and 0.2 mm depth.

Optimized electroless Ni-Cu-P coatings for corrosion protection of steel rebars from pitting attack of chlorides

Mukhopadhyay Arkadeb, Sahoo Sarmila

Engineering Transactions

2021

Vol. 69, iss. 3

315--332

Structures, constructions and bridges in coastal areas are greatly affected by the corrosive attack of chlorides. This reduces their lifetime and leads to losses due to their maintenance. This study aims to improve the lifetime and corrosion-proof behavior of steel rebars in the saline environment (3.5% NaCl) by applying electroless Ni-Cu-P coatings with high corrosion resistance. Ni-Cu-P coating was deposited on Fe-600 steel rebars. The coating was deposited by varying bath condition parameters, such as concentration of nickel sulphate, sodium hypophosphite and copper sulphate. This led to a variation in Ni, P and Cu content, and finally, the optimal bath combination was obtained using the Taguchi-based grey relational analysis. For concentrations of 25, 10 and 0.3 g/l nickel sulphate, sodium hypophosphite and copper sulphate, enhanced corrosion resistance of the coated rebars could be achieved with −350 mV Ecorr and 0.4 µA/cm2 Icorr. At the same time, the bare rebars had Ecorr of − 653 mV and Icorr of 11.7 µA/cm2 . .