A Genetic Algorithm (GA) / Discrete Particle Swarm Optimization/ Hybrid (GA-PSO) for nuclear fuel optimization using ML surrogates (DNN, KNN, Random Forest, Ridge) and OpenMC. Optimizes fuel loading patterns for a target k-eff and minimal Power Peaking Factor (PPF).

This project focuses on tracking the operational distance covered by a company's vehicles and machinery. We utilized this data to analyze the variance between the company's budgeted allocation per vehicle and the actual expenditures incurred.