Shape optimization of atmospheric icing sensor using cognitive computer aided approach

Abstract

This research paper deals with the use of advance computer aided engineering (CAE) tools in the cognitive communication process, involved in the geometric shape optimization of a geometric part of an atmospheric icing sensor, designed by atmospheric icing research team of Narvik University College. CAE tools (computer aided design and computational fluid dynamics) were used at different design steps during the geometric shape optimization process to perform advanced multiphase numerical simulations as well as analysing the data, where the effective communication between humans and virtual cognitive CAE systems allowed achieving optimized solutions for real time icing conditions. Two different geometric shapes (circular and hexagon) were used for this study, where the computer aided design (CAD) models were coupled with the multiphase computational fluid dynamics solver in a cognitive loop. CAD models generated the digital representation of the sensor's geometry, whereas CFD solvers were used to simulate the rate and shape of ice accretion on the selected geometries to understand the ice growth and estimate the resultant ice load in transient conditions. Different CAE tools help to link between the digital worlds of CAD and CFD which identified a complex bringing type of communication; that involves intra-inter communications skills inside the loop of optimization involving CAE tools.