Radiological Materials Research Articles

Catastrophe in Rio Grande do Sul/Brazil in 2024: sensing for survey on the radiological sources of submerged equipment and their possible environmental damage

The increasing occurrence of environmental catastrophes has heightened global concern regarding the management of radiological sources. This study addresses the challenges related to the detection and assessment of radiological damage in the state of Rio Grande do Sul, Brazil. Given the growing use of radiological materials for industrial, medical, and energy production purposes, the risk of environmental contamination from accidental or intentional releases has intensified. Our research focuses on the implementation of advanced sensing technologies capable of detecting low-level radiological emissions over large areas. The study highlights the need for precise, real-time data acquisition methods to mitigate the effects of radiological exposure and protect both ecosystems and human populations from potential harm. Additionally, we explore the role of early warning systems in reducing the response time during environmental disasters, particularly in regions vulnerable to radiological threats. Field experiments conducted in Rio Grande do Sul demonstrate the effectiveness of our proposed detection methodologies in identifying radiological contamination and assessing the extent of environmental damage. The findings underscore the importance of continuous monitoring and development of more sophisticated detection techniques in areas prone to radiological hazards. This work contributes to improving regional preparedness for radiological incidents, safeguarding public health, and preserving environmental integrity.

ASYMMETRICAL CORTICAL VEIN SIGN (ACVS) PREDICT NEUROLOGICAL AND RADIOLOGICAL IMPROVEMENT IN LARGE AND DISTAL VESSEL OCCLUSION POST REPERFUSION THERAPY

ABSTRACT Purpose To investigate the dynamic changes in ACVS on SWIs in patients who underwent reperfusion therapy and evaluate their association with neurological and radiological improvement Materials and Methods All patients treated for acute ischemic stroke between June 2020 and June 2022, in a single tertiary centre (Hospital Sultan Abdul Aziz Shah) who underwent reperfusion therapy and MRI imaging were retrospectively identified based on clinical and radiology reports. Expected Results This study hypothesizes an improvement in ACVS is expected to correlate with favourable neurological outcomes (MRS at 3 months and NIHSS score) and radiological outcome (DWI / ASPECT scores and Modified Mori score). Conversely, a worsening of ACVS is anticipated to be associated with unfavourable neurological and radiological outcomes. Conclusion Asymmetrical Cortical Vein Signs (ACVS) can serve as a valuable predictor of neurological and radiological outcomes in patients with large and distal vessel occlusion after reperfusion therapy Keywords: ACVS (The Asymmetrical cortical vein sign), Ischemic penumbra , Large vessel occlusion (LVO), Distal vessel occlusion (DVO)

Prediction of hemoptysis in patients with anomalous systemic arterial supply to normal basal segments of the lower lobe using a combination of CT features and clinical materials.

Anomalous systemic arterial supply to the normal basal segments of the lower lobe (ASALL) is a rare anomaly with a common complication of hemoptysis. To estimate the risk of hemoptysis, this study aims to investigate the value of contrast-enhanced computed tomography (CT) and construct a risk-scoring model based on radiological features and clinical materials of patients with ASALL. Forty-three eligible individuals (17 women and 26 males), who underwent multiphase contrast-enhanced CT, were included in this study. Hemoptysis was predicted by combined systemic arterial features (CD-A) and combined demographic and radiological features (CD-R). Potential hemoptysis predictors were identified using multivariate regression analysis. A receiver operating characteristic (ROC) curve analysis was used to assess the prediction efficiency. The coefficient of regression model was used to build a combined risk scoring (CRS) model for hemoptysis. The decision curve analysis (DCA) was performed to evaluate the clinical usefulness of the risk-scoring model. Hemoptysis was present in 17 (39.5%) ASALL patients. The areas under the curve (AUCs) for the predicted performance of CD-A and CD-R were 0.869 and 0.890, respectively. Independent predictors generated a scoring model using the formula CRS = 3 × age + 3 × sex + 4 × [ground glass opacity (GGO)] + 3 × (CD-A >0.522). The prediction performance of this model was displayed with an AUC of 0.939. This scoring model was demonstrated to be significantly preferable to CD-A (P=0.046) and CD-R (P=0.02) by the Hanley and McNeil test. The DCA showed that the CRS model was more beneficial when the threshold probability was between 5% and 92%. The scoring model offers a viable method for evaluating the risk of hemoptysis in patients with ASALL by combining radiological and clinical data.

Contrastive Machine Learning with Gamma Spectroscopy Data Augmentations for Detecting Shielded Radiological Material Transfers

Data analysis techniques can be powerful tools for rapidly analyzing data and extracting information that can be used in a latent space for categorizing observations between classes of data. Machine learning models that exploit learned data relationships can address a variety of nuclear nonproliferation challenges like the detection and tracking of shielded radiological material transfers. The high resource cost of manually labeling radiation spectra is a hindrance to the rapid analysis of data collected from persistent monitoring and to the adoption of supervised machine learning methods that require large volumes of curated training data. Instead, contrastive self-supervised learning on unlabeled spectra can enhance models that are built on limited labeled radiation datasets. This work demonstrates that contrastive machine learning is an effective technique for leveraging unlabeled data in detecting and characterizing nuclear material transfers demonstrated on radiation measurements collected at an Oak Ridge National Laboratory testbed, where sodium iodide detectors measure gamma radiation emitted by material transfers between the High Flux Isotope Reactor and the Radiochemical Engineering Development Center. Label-invariant data augmentations tailored for gamma radiation detection physics are used on unlabeled spectra to contrastively train an encoder, learning a complex, embedded state space with self-supervision. A linear classifier is then trained on a limited set of labeled data to distinguish transfer spectra between byproducts and tracked nuclear material using representations from the contrastively trained encoder. The optimized hyperparameter model achieves a balanced accuracy score of 80.30%. Any given model—that is, a trained encoder and classifier—shows preferential treatment for specific subclasses of transfer types. Regardless of the classifier complexity, a supervised classifier using contrastively trained representations achieves higher accuracy than using spectra when trained and tested on limited labeled data.

(Invited) Multi-Modal Solid-State Gas Sensors-Based Breath Analysis System with Convolutional Neural Network (CNN) for Early Detection of Lung Cancer

Currently, digital healthcare technologies based on Internet of Things (IOT) are emerging, and the market for digital healthcare was estimated to be 151.5 billion dollars by 2020. Among the digital healthcare technologies, disease diagnosis is attracting maximum attention. Traditional diagnostic methods, such as radiology and human biological material analysis, have limitations of long study time, high cost, radiation exposure, and pain. Therefore, non-invasive diagnostics methods, for early diagnosis of specific diseases and personal healthcare management, have attracted attention.Breath sensors are one of the promising candidates for the realization of non-invasive diagnosis owing to their ease of use, safety, and cost effectiveness. The exhaled breath analysis technique holds great promise as a non-invasive method for diagnosing lung cancer. In the breath of lung cancer patients, various volatile organic compounds (VOCs) markers are generated during metabolic processes. Analyzing these VOCs markers presents a compelling avenue for early and non-invasive lung cancer diagnosis. Solid state gas sensors capable of measuring specific VOCs are currently being researched and utilized as commercial gas sensors for this purpose. However, the concentration of lung cancer VOCs markers in exhaled breath is commonly very low, and individual commercial gas sensors often lack the necessary sensitivity and selectivity to accurately diagnose lung cancer. In this study, we propose a multimodal solid state electronic biosensor system designed to differentiate lung cancer VOCs characteristics among multiple VOCs, enabling exhalation-based lung cancer diagnosis. Initially, we developed multimodal biosensors using more than 20 gas sensors, consisting of metal oxide semiconductor sensors, electrochemical sensors, photoionized detectors, metalorganic frame sensors and so on. And each exhibiting varying sensitivity profiles for complex gas mixtures. Additionally, we designed a classification algorithm based on convolutional neural networks (CNN) and multi-layered perceptron (MLP) to distinguish between lung cancer patients and healthy individuals using the output from these diverse multimodal gas sensors. To evaluate the system's performance, we collected exhaled air samples from 74 lung cancer patients and 107 normal subjects, conducting clinical trials with our developed system. We did model evaluation with confusion matrix and ROC curve. The results of these tests confirmed that our system achieved a high predictive accuracy of over 95% in classifying lung cancer patients. The simplicity of the sensor configuration in our developed system makes it suitable for large-scale screening tests to identify potential candidates for precise lung cancer diagnosis. This technology has the potential to contribute to reduced national welfare costs and improved patient survival rates through early diagnosis.

Nuclear and Radiological Material Smuggling in the Indian Ocean: Implications for India’s Coastal Security

Incidents of nuclear and radiological smuggling in the Indian Ocean are a matter of concern. Attempts to smuggle nuclear material within India have also been reported as recently as 2021. Indian security agencies previously have also seized natural uranium in coastal states such as Gujarat, Maharashtra and Bengal indicating how vulnerable the Indian coast is to radiological and nuclear smuggling. The Nuclear Security Index has also consistently ranked India below China and Pakistan despite their poor record on nuclear non-proliferation. These facts highlight concerns regarding the possible misuse of nuclear and radiological material by criminal and terrorist networks. Since India is targeted by terrorist groups and lies in the vicinity of countries and routes that see frequent nuclear and radiological trafficking, there are inevitable implications for the Indian coastal security system. This article identifies and analyses these security implications and argues for a beefing up of India’s coastal security.

Implementing Content-Based Instruction in Online ESP Course within the System of Professional Training of Future Officers

The article examines the capabilities of content-based instruction (CBI) within the system of professional training of future officers of the State Border Guard Service of Ukraine, specifically within the online English for Specific Purposes (ESP) course. The authors argue that nowadays, due to the quarantine restrictions and ongoing war initiated by Russia, it is crucial to enhance the border guards’ foreign language competence through a distance learning system. The study showed positive results in applying the CBI strategy to deliver an ESP course. This approach contributes immensely to developing context-appropriate language competence, boosts motivation-driven engagement, and increases retention and long-term academic success rates. The course content includes such topics as intercultural communication, illicit trafficking of radiological and nuclear materials, human trafficking, and fundamental rights. To deliver the content of the CBI course, the authors had to consider its online format and work out such learning activities as reading and listening to authentic job-related content, completing online interactive activities, and engaging in case-studying and problem-solving activities. The course results showed a considerable improvement in learners’ ability to effectively communicate in English within the professional border guard context, use the foreign language to build knowledge and skills around human values, recognise, analyse, and solve various border-related incidents involving topics covered in the course. The effectiveness of the online ESP course studied based on CBI has shown that implementing this approach in online education deserves recognition and acceptance.

COST ASSESSMENT OF COMPUTED RADIOGRAPHY TOWARDS CONVENTIONAL RADIOGRAPHY

Introduction: With the expansion of the development of computer equipment and the improvement of software interfaces, there is also a sudden development of radiology without film, through computerized radiography (CR) systems. The CR system made it possible to improve the quality of the radiological image, and thus to make a more accurate and faster diagnosis.Objective: To estimate the costs of computed radiography compared to conventional radiography.Materials and methods: The analysis used data on the costs of radiological materials and existing radiological information systems from the plans and signed contracts for 2019 and 2022 in the Croatian Hospital "Dr. Fr. Mato Nikolić" Nova Bila.Results: Thecosts of conventional radiology are exceptionally high, including the procurement of X-ray films, processing chemicals, and equipment maintenance. The analysis compares the number of procedures and the displayed costs for the hospital.Conclusion: Computerized radiography is more cost-effective than conventional radiography due to reusable phosphor imaging plates and reduced chemical and film expenses.Keywords: Diagnostic Imaging, Radiography, Cost-Effectiveness Analysis,Radiology Information Systems

Vorbereitung deutscher Notaufnahmen auf Notfälle mit chemischen, biologischen, radiologischen und nuklearen (CBRN) Gefahrstoffen

Abstract Background Post-pandemic considerations, as well as lessons learned from terrorist attacks, wars, and disasters worldwide demonstrate that emergency departments must be prepared for mass casualty events related to chemical, biological, radiological, and nuclear (CBRN) hazardous materials. Our aim was to evaluate whether German emergency departments are sufficiently prepared for such events. Methods We developed a survey and distributed it to all chairpersons of emergency departments in Germany via the German Emergency Department Directory. Results of the survey were described using total numbers and percentages. Capacity for decontamination at different sites was graphically displayed using box-and-whisker plots. The primary endpoint of this study was whether German emergency departments are sufficiently prepared for CBRN incidents. Results Of 963 emergency departments, 262 (27.21%) answered the survey: 80.43% (189/235) of the hospitals had a plan for biological incidents, 49.36% (116/235) for chemical incidents, and 34.47% (81/235) for radionuclear incidents. Furthermore, 50% (116/232) reported some kind of decontamination site, but only 31.42% (71/226) reported having a water supply to their decontamination area. Sufficient protective equipment was only available in 27.51% (63/229) of emergency departments. Only 12.02% (25/208) of hospitals were able to decontaminate supine patients properly, following a decontamination scheme. Conclusion Most German hospitals are not adequately prepared to handle casualties resulting from chemical, biological, radiological, or nuclear hazardous materials. Given these results, there is a need for systemic intervention at the national level in order to improve preparedness.

Microscopic and Macroscopic Characterization of Hydrogels Based on Poly(vinyl-alcohol)-Glutaraldehyde Mixtures for Fricke Gel Dosimetry.

In recent decades, hydrogels have emerged as innovative soft materials with widespread applications in the medical and biomedical fields, including drug delivery, tissue engineering, and gel dosimetry. In this work, a comprehensive study of the macroscopic and microscopic properties of hydrogel matrices based on Poly(vinyl-alcohol) (PVA) chemically crosslinked with Glutaraldehyde (GTA) was reported. Five different kinds of PVAs differing in molecular weight and degree of hydrolysis were considered. The local microscopic organization of the hydrogels was studied through the use of the 1H nuclear magnetic resonance relaxometry technique. Various macroscopic properties (gel fraction, water loss, contact angle, swelling degree, viscosity, and Young's Modulus) were investigated with the aim of finding a correlation between them and the features of the hydrogel matrix. Additionally, an optical characterization was performed on all the hydrogels loaded with Fricke solution to assess their dosimetric behavior. The results obtained indicate that the degree of PVA hydrolysis is a crucial parameter influencing the structure of the hydrogel matrix. This factor should be considered for ensuring stability over time, a vital property in the context of potential biomedical applications where hydrogels act as radiological tissue-equivalent materials.

Radiometric survey of sediments and health risk assessments from the southern coastal area of Delta State, Nigeria

Over the years, the release of potential radiological components around the oil exploration environment has increased with potential health implications.Yet; the mechanism and health associated assessment have remained fuzzy to most experimental scientists. The current study determines the activity concentration of radionuclides in sediments and the corresponding health risk assessments from the hydrocarbon exploration environment of the southern coastal area of Delta State, Nigeria. A Sodium-iodide NaI(Tl) detector, with a well-calibrated multichannel analyzer (MCA) to ensure efficiency and energy was utilized. A total of seventy-five sediment samples (Five sediment samples each per community) were collected from the southern coastal area of Delta State, Nigeria. The mean activity concentrations of 40K, 238U, and 232Th of the sediment samples were 3361.48 ± 194.26 Bqkg−1, 40.11 ± 16.17 Bqkg−1, and 45.73 ± 19.27 Bqkg−1 respectively. The obtained mean values exceeded the world standard limit of 400 Bqkg−1, 35 Bqkg−1, and 30 Bqkg−1 respectively. Also, the computed mean radiological health hazard risk of radium equivalent activity (Raeq), representative level index (Iyr), external hazard index (Hex), internal hazard index (Hin), absorbed gamma dose rate (D), annual effective dose equivalent outdoor and indoor (AEDE) and lifetime cancer risk (ELCR) values are 363.94 ± 32.37 Bkgl−1, 2.9657 Bkgl−1, 0.9839, 1.0919, 175.82 nGyh−1, 2.1556 mSvyr−1, 0.8625 mSvyr−1, and 7.5447 mSvyr−1 respectively. The values were found to be slightly higher than the world standard limit. Therefore, the residents that are using the sediments of the southern coastal area for the construction of buildings as well as dwelling in houses built with such sediments are exposed to these radiological materials. This may pose a radiological health risk concern. The obtained results will serve as radiation and radiological baseline data for sediments of the southern coastal area of Delta State, Nigeria.

Spectroscopic analysis of Pu-bearing compounds in double-walled cells

Spectroscopic analysis of radiological materials has been historically limited to radiological labs with older or less advanced scientific instrumentation. The development of double-walled cells (DWCs) at the Savannah River National Laboratory (SRNL) has enabled Pu-bearing compounds to be removed from radiological laboratories and studied in our radiologically clean spectroscopy laboratory with state-of-the-art instrumentation. In this manuscript, we discuss the contributions of DWCs that have allowed the application of Raman spectroscopy, diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS), diffuse reflectance spectroscopy (DRS) in the shortwave infrared, and gamma spectroscopy at SRNL. Significant advances have been made in the understanding of the thermal decomposition of Pu(III) and Pu(IV) oxalates, alpha-induced damage to the PuO2 crystal lattice, and the effect of calcination temperatures on the quality of PuO2. These techniques have enabled methods to conduct PuO2 age dating since last calcination and estimate the calcination temperature with Raman spectroscopy and DRS. Additional spectroscopic information measured with DRIFTS has enabled the observation of the evolution of carbon species with calcination temperature, while gamma spectroscopy provides information on age dating since last purification.

Ophthalmic implications of biological threat agents according to the chemical, biological, radiological, nuclear, and explosives framework.

As technology continues to evolve, the possibility for a wide range of dangers to people, organizations, and countries escalate globally. The United States federal government classifies types of threats with the capability of inflicting mass casualties and societal disruption as Chemical, Biological, Radiological, Nuclear, and Energetics/Explosives (CBRNE). Such incidents encompass accidental and intentional events ranging from weapons of mass destruction and bioterrorism to fires or spills involving hazardous or radiologic material. All of these have the capacity to inflict death or severe physical, neurological, and/or sensorial disabilities if injuries are not diagnosed and treated in a timely manner. Ophthalmic injury can provide important insight into understanding and treating patients impacted by CBRNE agents; however, improper ophthalmic management can result in suboptimal patient outcomes. This review specifically addresses the biological agents the Center for Disease Control and Prevention (CDC) deems to have the greatest capacity for bioterrorism. CBRNE biological agents, encompassing pathogens and organic toxins, are further subdivided into categories A, B, and C according to their national security threat level. In our compendium of these biological agents, we address their respective CDC category, systemic and ophthalmic manifestations, route of transmission and personal protective equipment considerations as well as pertinent vaccination and treatment guidelines.

ESTIMATION OF GIRTH OF HUMERAL HEAD BY MEASURING THE BIEPICONDYLAR DISTANCE: A VALIDITY AND RELIABILITY STUDY

Aim: The aim of this study was to estimate the girth of humeral head (GOHead) by analysing the reliability and validity of biepicondylar distance (BED). Materials and Methods: The study was carried out on 66 dry humeruses (36 right and 30 left) at the Ondokuz Mayis, Ordu and Erciyes Universities, Faculty of Medicine, Departments of Anatomy. The BED and the GOHead were measured, and the related ratio was determined. The validity between the obtained values was analysed by Bland Altman analysis and the reliability by intraclass correlation coefficient (ICC). Results: The BED was measured to be 57.70±5.18 mm, while the GOHead was 132.77±12.17 mm. The relative ratio between the two data was determined to be (RR:2.30). The GOHeadRR (BED x RR) value was defined to be 132.82±12.01 mm. While the results of this study showed agreement in validity according to Bland Altman analysis, an excellent reliability ratio (Cronbach Alpha's: 0.930) was determined in this study. Estimation of the GOHead using the formula (BED x 2.30) shows agreement in terms of validity and reliability. Conclusion: This result we obtained shows that the BED can be used to estimate the GOHead without requiring any imaging method. Based on the results of this study, it is expected to play an important role in reducing the use of radiological materials in GOHead measurements and reducing the radiological footprint.

Encryption Gradient of Patients’ EMR using Forms of DICOM

Data protection is important. it is especially required for competent patient protection. If it is not done well, it can pose various problems. The problems of leakage can make patients vulnerable. This literally means that the healthcare environment can be threatened in this aspect. DICOM is a digitalized image compression technique using radiologic materials. It restores CT, PET-CT, and X-ray images in order to gain a specific image. It is then compiled to be sent as PACS. These imaging techniques use matrix as a data presenting method. However, it is sent in a linear form. It does not mean that it is not protected, but it means that there are various risks to be managed. In our report, we review that, in the future, a double layer of encryption with patient voice can dramatically evolve the probability of accessing patient healthcare data. This can also be applied in EMR or EHR in the future. The limitations of this study are that there are still risks of cyber-attack. The DDoS can totally make the system function down. However, we see this as a different problem as this is an electronic source matter rather than a hack of preserved data.

Using synthetic case studies to explore the spread and calibration of ensemble atmospheric dispersion forecasts

Abstract. Ensemble predictions of atmospheric dispersion that account for the meteorological uncertainties in a weather forecast are constructed by propagating the individual members of an ensemble numerical weather prediction forecast through an atmospheric dispersion model. Two event scenarios involving hypothetical atmospheric releases are considered: a near-surface radiological release from a nuclear power plant accident and a large eruption of an Icelandic volcano releasing volcanic ash into the upper air. Simulations were run twice-daily in real time over a 4-month period to create a large dataset of cases for this study. The performance of the ensemble predictions is measured against retrospective simulations using a sequence of meteorological fields analysed against observations. The focus of this paper is on comparing the spread of the ensemble members against forecast errors and on the calibration of probabilistic forecasts derived from the ensemble distribution. Results show good overall performance by the dispersion ensembles in both studies but with simulations for the upper-air ash release generally performing better than those for the near-surface release of radiological material. The near-surface results demonstrate a sensitivity to the release location, with good performance in areas dominated by the synoptic-scale meteorology and generally poorer performance at some other sites where, we speculate, the global-scale meteorological ensemble used in this study has difficulty in adequately capturing the uncertainty from local- and regional-scale influences on the boundary layer. The ensemble tends to be under-spread, or over-confident, for the radiological case in general, especially at earlier forecast steps. The limited ensemble size of 18 members may also affect its ability to fully resolve peak values or adequately sample outlier regions. Probability forecasts of threshold exceedances show a reasonable degree of calibration, though the over-confident nature of the ensemble means that it tends to be too keen on using the extreme forecast probabilities. Ensemble forecasts for the volcanic ash study demonstrate an appropriate degree of spread and are generally well-calibrated, particularly for ash concentration forecasts in the troposphere. The ensemble is slightly over-spread, or under-confident, within the troposphere at the first output time step T + 6, thought to be attributable to a known deficiency in the ensemble perturbation scheme in use at the time of this study, but improves with probability forecasts becoming well-calibrated here by the end of the period. Conversely, an increasing tendency towards over-confident forecasts is seen in the stratosphere, which again mirrors an expectation for ensemble spread to fall away at higher altitudes in the meteorological ensemble. Results in the volcanic ash case are also broadly similar between the three different eruption scenarios considered in the study, suggesting that good ensemble performance might apply to a wide range of eruptions with different heights and mass eruption rates.

Advanced cartridge design for a gas respiratory protection system using experiments, CFD simulation and virtual reality

Gas masks are critical for protection against chemical, biological, radiological, and nuclear materials. Efforts are underway to develop advanced cartridges for next-generation gas respirators in civil-military combined use to improve wearability and protection for users (firefighters, military personnel, and environmental and safety-related workers). Herein, the performance of three newly designed cartridges for a next-generation gas respirator was evaluated using flow analysis, along with adsorption characteristics. The adsorption kinetics of cyclohexane gas on ASC (a copper-silver-hexavalent chromium impregnated activated carbon in the study) was measured by breakthrough experiments in a packed bed, and the obtained parameters were used in the computational fluid dynamics (CFD) model for the designed plate-type cartridges. To apply the physical properties of the adsorbent to the CFD simulation, porous materials were expressed using the granular technique and packed bed technique. The CFD model was verified through a gas adsorption experiment using a prototype cartridge. The respiration resistance and breakthrough time for the filled-adsorbent efficiency and lifespan were compared among the three designed cartridges according to the gas inflow conditions. Additionally, virtual engineering was performed by grafting the CFD results to a virtual reality (VR) system with which 3-dimensional performance visuals of the cartridges could be observed. The developed VR system provides detailed information for cartridge design and optimization. Overall, the developed procedure of virtual engineering can be used to improve CFD simulation results.

Networked Sensing for Radiation Detection, Localization, and Tracking

The detection, identification, and localization of illicit radiological and nuclear material continue to be key components of nuclear non-proliferation and nuclear security efforts around the world. Networks of radiation detectors deployed at strategic locations in urban environments have the potential to provide continuous radiological/nuclear (R/N) surveillance and provide high probabilities of intercepting threat sources. The integration of contextual information from sensors such as video, Lidar, and meteorological sensors can provide significantly enhanced situational awareness, and improved detection and localization performance through the fusion of the radiological and contextual data. In this work, we present details of our work to establish a city-scale multi-sensor network testbed for intelligent, adaptive R/N detection in urban environments, and develop new techniques that enable city-scale source detection, localization, and tracking.

Microscale Electrochemical Corrosion of Uranium Oxide Particles.

Understanding the corrosion of spent nuclear fuel is important for the development of long-term storage solutions. However, the risk of radiation contamination presents challenges for experimental analysis. Adapted from the system for analysis at the liquid-vacuum interface (SALVI), we developed a miniaturized uranium oxide (UO2)-attached working electrode (WE) to reduce contamination risk. To protect UO2 particles in a miniatured electrochemical cell, a thin layer of Nafion was formed on the surface. Atomic force microscopy (AFM) shows a dense layer of UO2 particles and indicates their participation in electrochemical reactions. Particles remain intact on the electrode surface with slight redistribution. X-ray photoelectron spectroscopy (XPS) reveals a difference in the distribution of U(IV), U(V), and U(VI) between pristine and corroded UO2 electrodes. The presence of U(V)/U(VI) on the corroded electrode surface demonstrates that electrochemically driven UO2 oxidation can be studied using these cells. Our observations of U(V) in the micro-electrode due to the selective semi-permeability of Nafion suggest that interfacial water plays a key role, potentially simulating a water-lean scenario in fuel storage conditions. This novel approach offers analytical reproducibility, design flexibility, a small footprint, and a low irradiation dose, while separating the α-effect. This approach provides a valuable microscale electrochemical platform for spent fuel corrosion studies with minimal radiological materials and the potential for diverse configurations.

The Effect of Fuel Aerosol Particle Size on Aerosol Release Potential in Energetic Core Disruptive Accident Studies

In nuclear reactor accident safety studies, the radiological source term is a metric that quantifies the release of radiological material from the reactor to the environment. The present work evaluates heat transfer between high-temperature vapor bubbles and the surrounding coolant and the effect these interactions have on the source term for postulated core disruptive accident scenarios associated with an oxide-fueled, liquid metal–cooled fast reactor class. It is shown that aerosol particle size can influence heat transfer, and it is suggested that the extent of the influence depends on the fineness of the particles in the aerosol. The results are consistent with legacy experiments conducted in the Fuel Aerosol Simulant Test (FAST) facility at Oak Ridge National Laboratory and offer a more comprehensive assessment of vapor condensation by treating the bubble constituents, in the context of radiation heat transfer, as participating media. The model, which couples classical scattering theory to the equation of radiative transfer and the energy equation, provides a means for estimating size-affected radiative cooling times. Solutions are obtained via the P-1 method of spherical harmonics with improved, higher-order boundary conditions. Outcomes include the development of an “extinction-time ratio” criterion for assessing whether ejection of aerosol from the bubble to the cover region is likely. Aerosol release from the coolant pool is evaluated using this criterion with the potential to extend this work to reactor-scale accidents. A baseline evaluation is provided that shows that omission of participatory effects could lead, in a relative sense, to cooling time offsets in excess of 14%. In addition to enhancing previous evaluations of FAST results, these modeling outcomes contribute to knowledge management efforts aimed at developing a more mechanistic assessment of the source term while suggesting potential enhancements to severe accident safety analysis through the use of more comprehensive radiative heat transfer models.