Alya Badawi

Partial Loading of Thorium-Plutonium Fuel in a Pressurized Water Reactor

Abstract This research focuses on the utilization of thorium-plutonium fuel in pressurized water reactors (PWRs). The reference PWR selected in this research was the Westinghouse AP1000. Thorium-plutonium mixed-oxide (MOX) fuel assemblies partially replaced the uranium oxide fuel assemblies to reduce uranium demand. The cases studied contained 36, 48, 60, 72, and 84 thorium-plutonium MOX fuel assemblies, with the rest of the 193 fuel assemblies loaded with UO2 fuel. The core cycle length, the amount of plutonium incinerated, the amount of generated 233U in the spent fuel, and the conversion ratios were determined using MCNP6. For the different cases, safety parameters such as the power peaking factor and delayed neutron fraction (βeff) were evaluated. The study showed that using thorium-plutonium MOX can achieve good peaking power factors with delayed neutron fractions within the safety limits. Also a conversion factor of about 10% was achieved.

Towards a methodology for bulk sample neutron activation analysis

Abstract The main challenge in large sample neutron activation analysis (LSNAA) is the determination of neutron self-shielding and gamma ray self-attenuation corrections. After these corrections are determined, the analysis proceeds as in normal neutron activation analysis (NAA), as if the sample were infinitely small. In this paper, these corrections are calculated using the MCNP code for different standard sample geometries with different diameters. Modelling studies for LSNAA using an external neutron beam were performed. An analytical formula for the correction factors for neutron self-shielding and gamma ray self-attenuation is derived. The correction factors as well as flux parameters are calculated analytically. The analytical formula is verified using the MCNP code. All of the calculated parameters were tabulated and graphed. From the calculated data, other unknown material parameters could be obtained based on tabulated data or graphs. This method is a direct and easy method to perform large sample neutron activation analysis without complex calculations. In addition, for the user who does not have good experience with codes such as MCNP, she/he can use the chart or the tabulated information to define their unknown sample with the required information for the LSNAA experiment.

Optimizing the dynamic response of the H. B. Robinson nuclear plant using multiobjective particle swarm optimization

Abstract In this paper, the Particle Swarm Optimization (PSO) algorithm is modified to deal with Multiobjective Optimization Problems (MOPs). A mathematical model for predicting the dynamic response of the H. B. Robinson nuclear power plant, which represents an Initial Value Problem (IVP) of Ordinary Differential Equations (ODEs), is solved using Runge-Kutta formula. The resulted data values are represented as a system of nonlinear algebraic equations by interpolation schemes for data fitting. This system of fitted nonlinear algebraic equations represents a nonlinear multiobjective optimization problem. A Multiobjective Particle Swarm Optimizer (MOPSO) which is based on the Pareto optimality concept is developed and applied to maximize the above mentioned problem. Results show that MOPSO efficiently cope with the problem and finds multiple Pareto optimal solutions.

Design optimization of shell-and-tube heat exchangers using single objective and multiobjective particle swarm optimization

Abstract The Particle Swarm Optimization (PSO) algorithm is used to optimize the design of shell-and-tube heat exchangers and determine the optimal feasible solutions so as to eliminate trial-and-error during the design process. The design formulation takes into account the area and the total annual cost of heat exchangers as two objective functions together with operating as well as geometrical constraints. The Nonlinear Constrained Single Objective Particle Swarm Optimization (NCSOPSO) algorithm is used to minimize and find the optimal feasible solution for each of the nonlinear constrained objective functions alone, respectively. Then, a novel Nonlinear Constrained Multobjective Particle Swarm Optimization (NCMOPSO) algorithm is used to minimize and find the Pareto optimal solutions for both of the nonlinear constrained objective functions together. The experimental results show that the two algorithms are very efficient, fast and can find the accurate optimal feasible solutions of the shell and tube heat exchangers design optimization problem.

Evaluation of the Efficiency of Gamma Spectrometers for Analyzing Environmental Samples with Unknown Elemental Composition

Abstract A method was proposed to transfer the efficiency of gamma-ray spectrometers calibrated with a standard water source to suit other samples. In our method, it is not important to know the concentration of the major elements of the sample to be measured. This gives a special importance to our method for low-energy photon detection where the self-absorption is strongly material dependent.