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A controlled migration genetic algorithm operator for hardware-in-the-loop experimentationIn this paper, we describe the development of an extended migration operator, which combats the negative effects of noise on the effective search capabilities of genetic algorithms. The research is motivated by the need to minimize the num-ber of evaluations during hardware-in-the-loop experimentation, which can carry a significant cost penalty in terms of time or financial expense. The authors build on previous research, where convergence for search methods such as Simulated Annealing and Variable Neighbourhood search was accelerated by the implementation of an adaptive decision support operator. This methodology was found to be effective in searching noisy data surfaces. Providing that noise is not too significant, Genetic Al-gorithms can prove even more effective guiding experimentation. It will be shown that with the introduction of a Controlled Migration operator into the GA heuristic, data, which repre-sents a significant signal-to-noise ratio, can be searched with significant beneficial effects on the efficiency of hardware-in-the-loop experimentation, without a priori parameter tuning. The method is tested on an engine-in-the-loop experimental example, and shown to bring significant performance benefits.
Module layout optimization using a genetic algorithm in light water modular nuclear reactor power plants.The Small Modular Reactor (SMR) concept is designed such that it will solve some of the construction problems of large reactors. SMRs are designed to be “shop fabricated and then transported as modules to the sites for installation” (IAEA, 2018). As a consequence they theoretically have shorter build schedules and require less capitalinvestment(Locatelli etal.,2014).Factory builtmodulescanalsoincreasesafetyandproductivity, dueto higher quality tools and inspection available. A literature review has highlighted substantial work has been undertaken in the research, development and construction of diﬀerent types of reactors and reactor modules but the design of balance of plant modules has not been extensively researched (Wrigley et al., 2018). The focus of this paperis a casestudy for balanceofplant modulesin alightwaterreactorwhich alsocould haveapplications to other reactor types. Modules thataredesignedfor factorybuildandtransport maybebuiltinastandardized moduleapproach.By maximizing module size for transport, this maximizes work oﬀsite, to achieve the cost and schedule savings associated. A design method needs to be developed to help support this approach. To enable this, a three step method is proposed: group components into modules, layout the modules and arrange components inside the modules. The Shearon Harris nuclear power plant was chosen for its publically available data. A previous study on this plant used matrix reordering techniques to group components and heuristically assign them to large modules, built for construction in an assembly area on site, highlighting a potential capital cost savings of 15%. This paper utilizes the same allocation of components to modules as the previous study but aims to undertake the challenge of how balance of plant modules should be arranged. The literature review highlighted that although the facility and plant layout problem has been extensively researched, mathematical layout optimization has not been applied to nuclear power plants. Many techniques for layout optimization have been developed for facilities and process plants however. The work in this paper develops an optimization model using a genetic algorithm for module layout and allocation within a nuclear power plant. This paper analysed two conﬁgurations of modules, where balance of plant modules are located on either one or two sides of the nuclear island. The objective function was to minimise pipe length. In the original research, where the plant was conﬁgured for assembly on site, the balance of plant modules are located around three sides of the nuclear island. The objective function was calculated at 14,914. As the distances are calculated rectilinearly, this number would be higher in reality as pipework has to be routed around containment. The optimization reduced the objective function by 33.9% and 37.8% for the three and four ﬂoor layouts respectively when balance of plant modules are located on two sides of the nuclear island. Furthermore, when modules are located on one side of the nuclear island, the objective function was reduced by 45.4% and 46.1% for three and four ﬂoor layouts respectively. This will reduce materials used, reduce build time and hence reduce the cost of a nuclear power plant. This method will also save design time when developing the layout of modules around the plant.