Application of monotonic adaptive kernel for optimization: A case study

Abstract

Optimization is considered to be the integral part of designing a wide range of engineering solutions. Manual optimization is a hectic job to obtain desired optimized results using hit and trial method. Monotonic adaptive kernel algorithm optimizes the solution to the target stress by using linear interpolation function and checking current values on every iterative step and computing differential load. Using monotonic adaptive kernel algorithm, numerical simulations are conducted on gasketed bolted flange pipe joints to achieve required preload in the bolts as per industrial guidelines for their optimized performance. It is observed that the monotonic adaptive kernel algorithm produces more accurate and fast results conforming to the desired target values as compared to the manual and semiautomatic optimization techniques implemented for the gasketed bolted flange pipe joint.