The field of fluid mechanics is rapidly advancing, driven by unprecedented volumes of data
from experiments, field measurements, and large-scale simulations at multiple …

Surrogate-assisted, or meta-model based evolutionary computation uses efficient
computational models, often known as surrogates or meta-models, for approximating the …

The bio-inspired algorithms are novel, modern, and efficient tools for the design of electrical
machines. However, from the mathematical point of view, these problems belong to the most …

Evolutionary algorithms (EAs) have received increasing interests both in the academy and
industry. One main difficulty in applying EAs to real-world applications is that EAs usually …

Evolutionary algorithms often have to solve optimization problems in the presence of a wide
range of uncertainties. Generally, uncertainties in evolutionary computation can be divided …

It is not unusual that an approximate model is needed for fitness evaluation in evolutionary
computation. In this case, the convergence properties of the evolutionary algorithm are …

High-resolution flow field reconstruction is prevalently recognized as a difficult task in the
field of experimental fluid mechanics, since the measured data are usually sparse and …

Aerodynamic design optimization of the blade profile is a critical approach to improve
performance of turbomachinery. This paper aims to achieve the performance prediction with …

A comprehensive overview of fluid dynamic models and experimental results that can help
solve problems in centrifugal compressors and modern techniques for a more efficient …

A multidisciplinary optimization system and its application to the design of a small radial
compressor impeller are presented. The method uses a genetic algorithm and artificial …