Multiprocessor modeling of parallel Particle Swarm Optimization applied to nuclear engineering problems

Particle Swarm Optimization (PSO) is a population-based metaheuristic (PBM), in which solution candidates evolve through simulation of a simplified social adaptation model. Putting together robustness, efficiency and simplicity, PSO has gained great popularity. Many successful applications of PSO are reported, in which PSO demonstrated to have advantages over other well-established PBM. However, computational costs are still a great constraint for PSO, as well as for all other PBMs, especially in optimization problems with time consuming objective functions. To overcome such difficulty, parallel computation has been used. The default advantage of parallel PSO (PPSO) is the reduction of computational time. Master-slave approaches, exploring this characteristic are the most investigated. However, much more should be expected. It is known that PSO may be improved by more elaborated neighborhood topologies. Hence, in this work, we develop several different PPSO algorithms exploring the advantages of enhanced neighborhood topologies implemented by communication strategies in multiprocessor architectures. The proposed PPSOs have been applied to two complex and time consuming nuclear engineering problems: i) reactor core design (CD) and ii) fuel reload (FR) optimization. After exhaustive experiments, it has been concluded that: i) PPSO still improves solutions after many thousands of iterations, making prohibitive the efficient use of serial (non-parallel) PSO in such kind of real-world problems and ii) PPSO with more elaborated communication strategies demonstrated to be more efficient and robust than the master-slave model. Advantages and peculiarities of each model are carefully discussed in this work.     

Processus physicochimiques intervenant dans la preparation des membranes de diacetate de cellulose— recherche de criteres pour l'optimisation des performances I—Collodions renfermant des additifs mineraux

The fabrication of desalination membranes from cellulose acetate casting dopes containing aqueous solution of inorganic salts has been analysed by determining the water concentration required for precipitating the polymer from concentrated solutions and the time necessary for coagulation. The results enable us to correlate the water concentration to the flow rate and the coagulation time to the salt rejection.     

A Real-Time Artificially Intelligent Monitoring System for Nuclear Power Plants Operators Support

In this paper, we describe the artificially intelligent monitoring system (AIMS), a framework for power plants real-time monitoring systems (RT/MS), developed at Federal University of Rio de Janeiro (COPPE/UFRJ) and applied to the Brazilians Angra-1 and Angra-2 nuclear power plants. The kernel of AIMS is an object-oriented knowledge-base system, in which acquired and calculated variables, as well as their interdependencies, are mapped into a hierarchical objects network where the rules and real-time constraints are implicit in objects operators and network topology. The state of monitored variables updates a fact-base, which is used by a real-time inference-machine (RT/IM) to activate and synchronize the fire of the knowledge-base (KB) rules. The operators man–machine interface (MMI) are, then, updated. Besides, also following the object-oriented paradigm, AIMS provides many facilities for building and maintaining the KB and the operators MMI. In order to illustrate the use of AIMS, we show part of a real application in Angra-2 NPP.     

Treatment of saline wastewater contaminated with hydrocarbons by the photo-Fenton process

The application of the photo-Fenton process to the treatment of saline wastewater contaminated with hydrocarbons is investigated. Aqueous saline solutions containing raw gasoline were used as a model oil-field-produced water. The dependence on concentrations of the following reagents has been appropriately evaluated: hydrogen peroxide (100-200 mM), iron ions (0.5-1 mM), and sodium chloride (200-2000 ppm). The reactions were monitored by measurement of the absorption spectra and total organic carbon (TOC). Experimental results demonstrate that the photo-Fenton process is feasible for the treatment of wastewaters containing hydrocarbons, even in the presence of high concentrations of salt. The effect of the salt in this process is described through a series of reactions. A simple feedforward neural network model was found to correlate well the observed data for the degradation process.