Botros Hanna, PhD, is a Modeling & Simulation Nuclear Engineer at Idaho National Laboratory (INL) with expertise spanning nuclear reactor techno-economics, computational fluid dynamics (CFD), AI/machine learning, and software development.

At INL, he contributes to the Microreactor Program by developing optimization tools that bridge reactor design and economics—integrating core simulations (e.g., OpenMC), simplified balance-of-plant modeling, and cost data to generate bottom-up cost estimates and levelized cost of energy across multiple microreactor concepts (including liquid-metal, gas-cooled, and heat-pipe designs). He also supports system analysis and integration techno-economics efforts, including development of an advanced nuclear reactor capital cost reduction pathway tool that received national-level visibility, and optimization frameworks exploring nuclear-powered data center configurations by combining technical performance, demand profiles, connection architecture, pricing, and financing assumptions.

In integrated energy systems (IES) program, Botros developed and extended HERON software to accelerate techno-economic analysis of diverse energy portfolios by connecting IES tools with commercial process and cost software.

His research portfolio also includes methods for uncertainty quantification in neutronics (enhancing representativity-based approaches for transient physics) and AI-enabled workflow automation—such as an LLM-assisted reviewer-matching system that leverages large technical databases to reduce proposal review time.

Botros earned his PhD and MS in Nuclear Engineering from North Carolina State University, where his doctoral work focused on machine-learning-based error prediction for coarse-grid CFD. He previously served as a postdoctoral researcher in computer science at New Mexico State University, developing automated operator support for nuclear power plant management, and began his INL career as an intern supporting post-Fukushima containment venting analysis using 3D CFD. He is a member of the American Nuclear Society, and has been recognized through multiple awards, including INL LDRD co-PI awards.

• Nuclear Reactor Techno-economics
• Computational Fluid Dynamics
• Software Development
• Uncertainty quantification
• AI/Machine Learning.