Effective decision-making in a nuclear emergency is an essential element of achieving the goals of Emergency Preparedness and Response (EPR). Within the International Atomic Energy Agency's (IAEA) General Safety Requirements (GSR) Part 7, preparedness goals are stated generally as having adequate capabilities in place for an effective response. Past nuclear accident experience has demonstrated the complexities involved in urgent and early phase protective action decision-making which is characterized by a distinct lack of information resulting in poor or inappropriate decisions that do more harm than good. The Operational Planning Process (OPP) has been developed by many professional militaries around the world as a means of dealing with equally complex situations. In this work we explore a component of the OPP, wargaming, and apply it to the preparedness phase of a nuclear emergency to validate response planning. The work demonstrates the usefulness of the activity at improving urgent and early phase decision-making and decision-making tool development. The concept effectively addresses several lessons learned from past nuclear incidents as well as continued observations calling for improved tools to better integrate a scientific and technical understanding into a justified and optimised, all hazards emergency response environment.

Conventional occupational radiation exposure monitoring relies on cumulative dose data from personal dosimeters without providing information on when, where, or under what conditions exposure occurs. This lack of context limits analysis of causal factors, evaluation of protective behaviors, and the effectiveness of safety education. This study aimed to develop and clinically implement an integrated information system for occupational radiation exposure by combining dose data, spatiotemporal movement records, and angiography-related radiation information. We also assessed its utility and potential for improving radiation safety management. The system was implemented for 1 mo in a clinical angiography suite. It integrated (1) personal digital dosimeters recording dose and time, (2) Bluetooth Low Energy beacons tracking healthcare workers' positions and movements, and (3) Radiation Dose Structured Reports providing exposure details. Data were synchronized to reconstruct when, where, and under what conditions exposure occurred. The system identified high-risk positions near x-ray tubes (Beacon IDs 1-3), where exposure was greatest. Avoidance behaviors were also detected, such as movement to low-risk areas (e.g., Beacon ID 8) before irradiation. We successfully developed, implemented, and evaluated the system, demonstrating its utility for improving radiation safety management. The insights gained support targeted interventions and the refinement of safety protocols, with potential for broader use in diverse radiation-controlled settings.

End-of-life (EOL) management of high-activity radioactive sources is made uniquely challenging by the inherent risks associated with storage and transportation of these sources, the complex logistics involved, and the strict requirements for regulatory compliance. Traditional methods lack comprehensive tools for accurate site assessments and precision planning for the transportation of radioactive sources. They also frequently fail to provide the adaptability required to consider diverse operational environments, resulting in inefficiencies and potential safety concerns. This paper introduces a novel software solution developed to address these issues by integrating advanced technologies such as light detection and ranging (LiDAR)-based 3D environment modeling, smart dynamic route planning, and customizable measurement functionalities. This software enables detailed terrain visualizations, facilitating thorough environmental assessments and enabling users to virtually navigate, analyze, and plan site-specific operations. Among the key features are a user-centric interface for virtual navigation, precise site measurement tools for site evaluations, interactive visualizations that highlight potential operational hazards, dynamic route planning capabilities, and real-time collision detection to promote safe workflows. By demonstrating the effectiveness of this tool through real-world application, the present work underscores the tool's potential to revolutionize radioactive source EOL management by improving operational efficiencies, minimizing risk, and advancing the state of practice to achieve suitable and secure radioactive material handling.

The radiopharmaceutical therapy field is experiencing a surge of novel treatments and expanded uses for existing treatments, broadening the range of patients that can be treated. This expansion presents new challenges for managing patient release due to new patient populations with additional comorbidities, increasing the incidence of patients requiring care shortly after administration. This paper outlines the challenges and potential solutions for managing readmitted radiopharmaceutical therapy patients. It discusses the importance of having radiation protection policies and procedures in place for staff who may be unfamiliar with radiation. The paper also highlights the need for just-in-time training and radiation monitoring equipment for care staff, as well as the development of a notification system within the electronic health record to ensure staff can safely care for these patients. Preparing for these eventualities is essential for implementing a radiopharmaceutical therapy program that is ready for the expansion of existing and novel treatments.

This study establishes a robust and clinically applicable calibration protocol for optically stimulated luminescence dosimeters (OSLDs) in diagnostic radiology, with the aim of improving the accuracy of patient dose assessment. A total of 144 OSLDs were systematically irradiated under controlled conditions to assess their dosimetric response across a wide range of tube voltages (40-150 kVp) and square field sizes (10 × 10 cm² to 30 × 30 cm²). The dosimeters exhibited a sensitivity variation of ±6.6%, with an average background dose of 0.0185 mGy. The experimental data revealed a high dependence of OSLD response on photon energy, with dose values increasing by a factor of 11.5, from 0.1393 mGy at 40 kVp to 1.6072 mGy at 150 kVp for a constant field size of 10 × 10 cm². A pronounced non-linear dose escalation was observed in the mid-kVp range (70-100 kVp), where dose measurements increased by 72-90% as field size expanded. Energy and geometry-specific correction factors were derived, showing significant variation with field size, reaching maximum values of 9.81 for the 30 × 30 cm² field at 150 kVp and 7.43 for the 10 × 10 cm² field under the same conditions. Additionally, notable discrepancies were observed between experimentally derived effective beam energies and reference values reported by the International Atomic Energy Agency (IAEA), highlighting the need for localized calibration standards. These findings contribute to the standardization of OSLD calibration protocols in diagnostic radiology and support their implementation for accurate patient dose monitoring in clinical settings.

Substitute materials that accurately reproduce the radiological properties of human tissues are required for direct in vivo measurement of internally deposited radioactive materials to estimate associated health risk, especially for the respiratory tract. The Livermore torso phantom, the de facto standard for calibrating detector systems that measure radioactive materials deposited in the lungs, liver, and thoracic lymph nodes, was designed with tissue substitute materials that match the density and attenuation coefficient exhibited by natural human tissue when exposed to single low-energy x rays associated with the decay of plutonium. In this study, we evaluated the radiometric tissue equivalence of new tissue substitutes for muscle, rib, sternum, lung, and cartilage that are suitable for a continuous low photon energy spectrum from approximately 30 to 120 keV. The formulation for each of the tissue substitutes was developed using a novel method that determines the optimized quantity of base material and additives to produce a material that best matches the density and photon transmission exhibited by the natural human tissue present in the thoracic cavity. Measurements of the mass attenuation coefficient (i.e., ) from approximately 30 keV up to 120 keV for each substitute tissue were within 8% or better to expected values calculated using the photon cross section database XCOM from the National Institute for Standards and Technology.

For identifying natural trends, hotspots, hazardous areas, and mitigating potential health risk to the public and environment, spatial analysis of radiation levels is crucial. Machine learning models' implementation for prediction of background radiation levels and anomaly detection can bring a revolutionary change in radiation monitoring. Also, emergency evacuation routes with minimum radiation exposure are needed in times of radiological and nuclear emergencies. Traditional radiation monitoring systems lack advanced data analytics capabilities for comprehensive situational awareness and emergency response planning. Building on a companion paper that details a IoT connected radiation detector and monitoring website, this work fills the gap of the radiation monitoring analytics to map radiation via different interpolation techniques, anomaly detection, and evaluation of multiple machine learning models for background radiation prediction and emergency escape route planning using A* algorithm with minimum exposure to radiation in times of nuclear or radiological emergencies. The study setup involves using the mobile radiation detector from the companion paper and real data collection from around the Military Institute of Science and Technology (MIST), Dhaka, Bangladesh, and Institute of Nuclear Science and Technology (INST), Dhaka, Bangladesh. Collected data are visualized by plotting interpolated radiation heatmaps, anomaly detection, and background radiation prediction using machine learning and determining effective escape routes following the "as low as reasonably achievable" (ALARA) principle. To revolutionize the radiation monitoring system, simplifying the decision-making for the radiation protection professionals and public officials to develop radiation protection strategies has great potential.

To ensure the accuracy of single-point sampling for airborne effluents in nuclear facilities, it is critical to clarify how stack and duct configurations regulate the flow field uniformity (velocity distribution) and aerosol distribution of the effluents. Taking the exhaust system of nuclear facilities as the research object, this study built a modular experimental platform covering seven duct configurations. Combined with experimental measurements and computational fluid dynamics (CFD) simulations, it systematically explored the impacts of duct configurations (including I, L, S, U types with smooth or right-angle transitions) and Reynolds numbers (Re = 5 × 104-1.5 × 105) on the coefficient of variation (COV) of velocity distribution and that of polydisperse aerosol distribution (average particle size: 5.2 μm). The CFD model established achieved excellent validation accuracy: over 93% of velocity data points showed a deviation between simulated and experimental values within ±15%, and the ratio of simulated to experimental aerosol concentration values followed a log-normal distribution with a mean (μ) of 1.13 and a standard deviation (σ) of 0.26. For flow field uniformity: long straight ducts lacked sufficient turbulence, resulting in a velocity COV >14% even at a length-to-hydraulic diameter ratio (L/D) of 20; elbows effectively reduced the velocity COV, with right angle transition elbows having a stronger turbulence effect than smooth-transition ones (e.g., L2 circular ducts reached a velocity COV <20% at L/D = 8, while L1 ducts required an L/D of 16 to achieve the same level); the S-type double-elbow ducts presented the highest flow field homogenization efficiency (S2 circular ducts achieved a velocity COV <20% at L/D = 7). For aerosol distribution: long straight ducts exhibited extremely poor aerosol mixing (COV >140% at L/D = 20); elbows promoted aerosol diffusion by enhancing vortex flow, with the right-angle transition S2 circular ducts performing the best (aerosol COV <20% at L/D = 4 and <10% at L/D = 20). When Re exceeded 104, further increasing the Re did not significantly improve flow velocity uniformity or aerosol mixing. The CFD method and regulatory requirements revealed in this study can provide technical support for optimizing sampling cross-sections in existing nuclear facilities and designing duct configurations for proposed ones.

Naturally occurring radioactive materials, especially radon, can contaminate groundwater and pose health risks through drinking and inhalation. This study analyzed radon activity in 30 groundwater samples from Sulaymaniyah Governorate, Iraq, alongside their physicochemical properties and radiological safety. Radon activity ranged from 2.1 to 33.7 Bq L-1, with an average of 12.6 Bq L-1. Nearly 47% of samples surpassed the US EPA threshold of 11.1 Bq L-1, though all remained well below the WHO maximum of 100 Bq L-1. Health risk parameters were computed for three age categories (adults, children, and infants), including annual doses from ingestion and inhalation, plus excess lifetime cancer risk. Combined annual doses stayed below the WHO's 0.1 mSv y-1 recommendation, and cancer risk estimates for all groups fell within acceptable USEPA limits. Statistical analyses (skewness, kurtosis, Shapiro-Wilk test, P-values, and Pearson correlation) explored relationships between radon and water quality parameters. Elevated radon levels in certain areas require targeted mitigation strategies. Continuous monitoring and public awareness programs are essential to minimize long-term health risks from waterborne radon exposure.