Abdallah Wazzan, a doctoral candidate in nuclear engineering, will defend their dissertation titled “Higher-Order Statistics and Normalized Decay Analysis for Detector Deadtime Characterization.” Their advisor, Dr. Shoaib Usman, is an associate professor in the nuclear engineering and radiation science department. The dissertation abstract is provided below.

Detector deadtime significantly affects radiation measurement accuracy at high count rates, yet current methods rely on idealized paralyzable or non-paralyzable models. Real detectors exhibit hybrid behavior requiring advanced characterization approaches. This study investigates detector deadtime characterization using two Monte Carlo simulation approaches: higher-order statistical analysis of inter-arrival times and simplified deadtime correction with hybrid models.

Using MATLAB (PULSE-WIZ), we analyzed complete radioactive decay curves spanning ~4.5 half-lives of Cobalt-60 and Vanadium-52 sources, examining coefficient of variation (CV), skewness, and kurtosis of inter-arrival time distributions, plus normalized decay curves with Full Width at Half Maximum (FWHM) analysis. Hybrid models incorporated paralyzable and non-paralyzable components with dead times of 2.5-50 microseconds and paralysis factors of 0.1-0.99.

Results showed distinct sensitivity patterns among statistical measures. Coefficient of variation demonstrated exceptional correlation with paralysis factor via exponential relationship (PF = 0.0015e^(12.657×CV), R² = 0.9998), enabling direct paralysis factor determination. Normalized FWHM showed sixth-degree monomial dependence (R² = 0.9878). Using FWHM-derived paralysis factors and statistical parameters, deadtime was predicted within 11-12% accuracy. These techniques enable hybrid detector parameter determination using laboratory-accessible count rates.

This work demonstrates that higher-order statistical analysis and normalized decay curve analysis contain valuable diagnostic information typically discarded in conventional counting statistics, enabling automated detector characterization and real-time performance assessment in radiation detection systems.