Optimization of isotopic binary and multi-component separation cascades using a novel nature-inspired horse herd algorithm

ABSTRACT

The gas centrifuge process is widely used in the world to separate binary and multi component mixtures of isotopes. The majority of a plant cost is related to the number of centrifuges in a cascade. The cascade should be built so that it uses the fewest possible centrifuges for a given product and waste concentrations. Minimizing the number of centrifuges and the total flow rates, is a key point in designing and optimizing isotope separation cascades. The main purpose of this paper is to present a novel swarm intelligence based algorithm to solve these kinds of problems. This novel algorithm, called the Horse Herd Optimization Algorithm (HOA), is inspired by the behavioral patterns of horses in their habitats. In this work, it is demonstrated that the suggested algorithm can solve complicated multidimensional problems. HOA is tested by some test functions of high-dimensions and the results are compared with the strongest available optimization algorithms. In next, the proposed algorithm is used to optimize gas centrifuge cascades for the separation of binary and multicomponent mixtures of isotopes in several cases. Also, ideal and optimum cascades are compared in different separating regimes of the stages, using this method. Considering the performance of HOA in solving multidimensional problems, this algorithm is proposed for the optimization of long cascades.

KEYWORDS:

• Swarm intelligence
• HOA
• gas Centrifuge
• cascade
• Optimization

Disclosure statement

No potential conflict of interest was reported by the author(s).