Speaker
Description
Radiological emergencies, such as those involving contamination of food supplies and inhalation of radioactive isotopes like I-131, pose a significant threat to both public health and environmental safety. The accurate detection and quantification of radiological contamination are critical for implementing effective countermeasures, minimizing exposure, and guiding emergency response efforts. The availability of reliable, field-deployable screening tools is essential for mitigating the consequences of accidental or deliberate radiological releases. To address these challenges, two advanced systems, FOOMON and THYMON, emphasizing a rigorous scientific approach to ensure accuracy and applicability in field scenarios, ensuring portability (< 25 kg), rapid deployment (< 5 minutes), and ease of installation and use, yet maintaining appropriate detection reliability and measurement accuracy.
This work focuses on the development and validation of these two systems, detailing the methodologies employed in their design, the role of Monte Carlo simulations in performance evaluation, and the experimental campaigns carried out to verify their accuracy under real-world operational conditions.
FOOMON, designed for the radiological screening of food samples, employs a 2” × 2” NaI(Tl) detector. The system is self-contained in a rugged, high-protection case to ensure reliability across diverse environmental conditions, including temperature variations and high humidity levels. This system enables quantitative analysis of radionuclides, specifically I-131, Cs-134, and Cs-137. Comprehensive Monte Carlo simulations were conducted to model detection efficiency across various food matrices, accounting for density and composition variations. These simulations revealed Minimum Detectable Concentrations (MDCs) as low as 30 Bq/kg for I-131 and 40-50 Bq/kg for Cs isotopes within a 10-minute measurement period. The accuracy of these predictions was confirmed through dedicated experimental campaigns.
THYMON, a system for thyroid monitoring, addresses the critical need to assess internal contamination from inhaled I-131. It integrates a collimated 1.5” × 1.5” NaI(Tl) detector with precise hardware to ensure optimal positioning and minimize measurement uncertainties. The system supports both handheld and hands-free operation, with an ergonomic design that ensures correct detector placement to reduce operator variability. Monte Carlo modelling was used to refine detection efficiency and positional alignment, achieving Minimum Detectable Activities (MDAs) below 100 Bq. This value corresponds to the threshold for no significant thyroid exposure in the most critical accident scenario considered by the TMT handbook. The system also limits dose estimation uncertainties to within ± 20%, which remains lower than the variability introduced by anatomical differences among individuals. A dedicated age-dependent numerical thyroid phantom was eventually developed to refine detection efficiency and then implement age-specific activityto-dose conversion coefficients for five defined age groups: 1, 5, 10, 15 years old (Adult Female), and Adult Male.
Monte Carlo simulations played a dual role in both projects, not only evaluating key detection quantities but also serving as a predictive tool to guide system design and optimization, both hardware and software. Dedicated validation campaigns were performed employing reference radioactive sources of different energies, intensities, and geometries. The experimental campaigns were designed to cover a broad range of operational conditions, assessing accuracy, precision, and reproducibility of the detection methods. The experimental campaigns demonstrated the appropriateness of the implemented Monte Carlo models, both qualitatively and quantitatively, with observed discrepancies always lower than 15% for energies ranging from about 30 keV up to
2.8 MeV, with both Marinelli and point-like sources, and in different measurement geometries. The agreement between simulated and measured data demonstrates the robustness of the implemented models and supports the reliability of the proposed monitoring solutions. The systematic approach adopted in this study ensures that FOOMON and THYMON meet the highest scientific standards for radiological assessment while being applied to emergency CBRN scenarios.
These systems effectively bridge the gap between laboratory-grade instrumentation and field deployable solutions for first responders, offering reliable, portable tools for radiological monitoring in CBRN emergencies. Their integration of numerical modelling with experimental validation highlights the robustness of the simulation-guided design approach. The results obtained provide a solid foundation for further developments.
