A machine learning approach for propeller design and optimization: Part II

We propose and analyse an optimization method that uses a machine learning approach to solve multi-objective, constrained propeller optimization problems. The method uses an online learning strategy where explainable supervised classifiers learn the location of the Pareto front and advise search strategies. The classifiers are trained with...

A machine learning approach for propeller design and optimization: Part I

This paper introduces a machine learning approach for optimizing propellers. The method aims to improve the computational cost of optimization by reducing the number of evaluations required to find solutions. This is achieved by directing the search towards design clusters with good performance, i.e. high propulsive efficiency and low...

Shaping Forces: Review of two Bridge Design Methodologies towards Architectural and Structural Symbiosis

This paper investigates the symbiotic relationship between the architectural appearance of a bridge and the structural design. The research is done by reviewing and comparing the design methodology employed by the first author in the conceptualization of two of his bridges; an early work from 1997 and a recent work from 2017. The review of the...

Efficient trajectory parameterization for environmental optimization of departure flight paths using a genetic algorithm

In this study, a genetic optimization algorithm is applied to the design of environmentally friendly aircraft departure trajectories. The environmental optimization has been primarily focused on noise abatement and local NOx emissions, whilst taking fuel burn into account as an economical criterion. In support of this study, a novel...