Introduction to Nuclear Data Analysis

Nuclear data analysis involves the study and interpretation of experimental data related to nuclear processes, interactions, and properties. It encompasses statistical techniques, modeling, and simulations to extract meaningful information from experimental measurements, providing valuable insights for nuclear physics, reactor design, nuclear medicine, and related fields.

Cross-Section Measurements and Analysis:

• Analyzing experimental data on nuclear cross-sections, which represent the probability of a specific nuclear reaction occurring, and utilizing statistical methods to derive accurate and precise values.

Nuclear Reaction Modeling and Simulation:

• Developing and employing theoretical models and simulations to interpret nuclear reactions and predict reaction outcomes based on experimental and theoretical input.

Nuclear Data Evaluation and Compilation:

• Curating, evaluating, and compiling nuclear data from various experimental sources and theoretical predictions, ensuring the availability of accurate and up-to-date nuclear data for scientific and practical applications.

Uncertainty Quantification and Sensitivity Analysis:

• Assessing and quantifying uncertainties associated with nuclear data, employing statistical and sensitivity analyses to understand the impact of uncertainties on final results and applications.

Applications in Reactor Physics and Nuclear Engineering:

• Applying nuclear data analysis techniques to reactor physics and nuclear engineering problems, including reactor core design, safety assessments, fuel cycle optimization, and neutron transport simulations, to enhance nuclear energy technologies.