Monitoring of temperature rise in global nuclear power plant thermal discharge from 2013 to 2022.

The development of nuclear power plants is progressing rapidly worldwide. However, there is currently a lack of dynamic monitoring of the thermal discharge temperature rise from these plants, making it unclear to governments where their nuclear power thermal discharges stand globally. We hypothesize that between 2013 and 2022, there are significant temporal and spatial differences in the thermal discharge temperature rise from nuclear power plants globally. Temporal differences are expected to reflect a country's nuclear power installed capacity and thermal discharge treatment capabilities, while spatial differences are related to the type of water bodies where nuclear power plants are located. To test these hypotheses, we utilized Landsat data to get the distribution range of thermal discharge and temperature rise levels ranging from 1 °C to 4 °C, and compared the temporal and spatial characteristics of temperature rise in different countries. The results indicate that: (1) Currently, China, the United States, and Canada rank among the top three globally in terms of the area experiencing temperature rise due to thermal discharge, which correlates with the total installed capacity of nuclear power in these countries. (2) Countries such as Russia, Finland, and Mexico exhibit larger areas with a 4 °C temperature rise level per unit installed capacity, with their thermal rise area per unit installed capacity (TRAUIC) exceeding the global average by more than 1.5 times. (3) The spatial dispersion trends of thermal discharges from nuclear power plants vary across different types of water bodies. For nuclear power plants located in bays, thermal discharges primarily disperse along the coast, while in open sea and lakes, thermal discharges tend to spread in a fan-shaped pattern. The findings of this study are crucial for understanding the efficiency of thermal discharge from nuclear power plants across different countries globally, assessing potential environmental risks during the operation of these plants, and promoting the safe and orderly development of nuclear power plants worldwide.

Low-Power Wireless Sensor Module for Machine Learning-Based Continuous Monitoring of Nuclear Power Plants.

This paper introduces the novel design and implementation of a low-power wireless monitoring system designed for nuclear power plants, aiming to enhance safety and operational efficiency. By utilizing advanced signal-processing techniques and energy-efficient technologies, the system supports real-time, continuous monitoring without the need for frequent battery replacements. This addresses the high costs and risks associated with traditional wired monitoring methods. The system focuses on acoustic and ultrasonic analysis, capturing sound using microphones and processing these signals through heterodyne frequency conversion for effective signal management, accommodating low-power consumption through down-conversion. Integrated with edge computing, the system processes data locally at the sensor level, optimizing response times to anomalies and reducing network load. Practical implementation shows significant reductions in maintenance overheads and environmental impact, thereby enhancing the reliability and safety of nuclear power plant operations. The study also sets the groundwork for future integration of sophisticated machine learning algorithms to advance predictive maintenance capabilities in nuclear energy management.

First measurements of chlorine 36 (36Cl) wet deposition fluxes in the vicinity of Orano La Hague nuclear reprocessing plant in France.

Chlorine 36 (36Cl) is a radionuclide of natural and anthropogenic origin, mainly used as a tracer in geochemical studies. Owing to analytical constraints and its low environmental levels, knowledge of 36Cl behavior in the environment is still very limited. In this study, we use environmental measurements to report for the first time the wet deposition fluxes of 36Cl downwind an anthropogenic source, the Orano nuclear reprocessing plant, which chronically emits 36Cl into the environment. Measurements of 36Cl in rainwater samples at our study site were 1-2 orders of magnitude above the environmental background. The isotope ratios 36Cl/Cl of the samples and the 36Cl content in the rainwater averaged 2.3x10-12 at at-1 and 1.7x108 at l-1 respectively. A decrease in these levels was observed 20 km away from the study site, outside the plant's gas plume, indicating that the marking of 36Cl on the study site is related to the plant discharges. Over the sampling period, wet deposition fluxes at the study site averaged 3.4x103 at m-2s-1, with significant values measured when precipitations scavenge the plant's gas plume down onto our study site. Analysis of these fluxes also revealed the presence of a significant rainout phenomenon in the study area. These results provide new data on the wet deposition flux of 36Cl and will thus enable better assessment of impact studies in a context of decommissioning or accidents involving nuclear power plants.

Anomaly Detection for Asynchronous Multivariate Time Series of Nuclear Power Plants Using a Temporal-Spatial Transformer.

Industrial process monitoring is a critical application of multivariate time-series (MTS) anomaly detection, especially crucial for safety-critical systems such as nuclear power plants (NPPs). However, some current data-driven process monitoring approaches may not fully capitalize on the temporal-spatial correlations inherent in operational MTS data. Particularly, asynchronous time-lagged correlations may exist among variables in actual NPPs, which further complicates this challenge. In this work, a reconstruction-based MTS anomaly detection approach based on a temporal-spatial transformer is proposed. It employs a two-stage temporal-spatial attention mechanism combined with a multi-scale strategy to learn the dependencies within normal operational data at various scales, thereby facilitating the extraction of temporal-spatial correlations from asynchronous MTS. Experiments on simulated datasets and real NPP datasets demonstrate that the proposed model possesses stronger feature learning capabilities, as evidenced by its improved performance in signal reconstruction and anomaly detection for asynchronous MTS data. Moreover, the proposed TS-Trans model enables earlier detection of anomalous events, which holds significant importance for enhancing operational safety and reducing potential losses in NPPs.

Securing Infrared Communication in Nuclear Power Plants: Advanced Encryption for Infrared Sensor Networks.

This study enhances infrared communication security in nuclear power plants' secondary systems, addressing the risk of mechanical and cyber failures. A novel random address generator, employing an innovative S-box, was developed to secure IoT sensor data transmissions to gateway nodes, mitigating eavesdropping, interference, and replay attacks. We introduced a structured IR communication protocol, generating unique, encrypted addresses to prevent unauthorized access. Key-dependent S-boxes, based on a compound chaotic map system, significantly improved encryption, increasing data transmission randomness and uniqueness. Entropy analysis and reduced duplicated addresses confirmed the effectiveness of our method, with the Hash-CCM algorithm showing the highest entropy and fewest duplicates. Integrating advanced cryptographic techniques into IR systems significantly enhances nuclear power plants' security, contributing to the protection of critical infrastructure from cyber threats and ensuring operational integrity.

Characterization and mapping of the neutron fields around Bruce Power's 177Lu isotope production system.

Bruce Power operates a first-of-its-kind isotope production system (IPS) that enables continuous production of 177Lu within Canada Deuterium Uranium (CANDU) commercial power reactors. Located on the reactivity mechanisms deck of Unit 7, just outside of reactor containment but in close proximity to the primary heat transport (PHT) pumps, this facility offers unique advantages for 177Lu production. However, employees working in this area encounter a radiation hazard which consists primarily of photoneutrons. These originate from the base of the PHT pumps and are only present when the reactor is operating. This study evaluates neutron exposure at Bruce Power's IPS by using a nested neutron spectrometer (NNS) to determine the neutron energy spectra and absolute dosimetric quantities such as the ambient dose equivalent, H*(10). The results from the NNS are then compared to surveys performed by a portable neutron rem meter (Model NP-2 by Nuclear Research Corporation), routinely used by Bruce Power staff for workplace monitoring. While the Model NP-2 generally showed consistent results across locations, a 50% dose correction factor was identified when operators were harvesting 177Lu from the IPS. This finding highlights an opportunity to reduce the neutron dose that is assigned to operators when producing 177Lu.

Long-term radiocarbon variation studies in the air and tree rings of Slovakia.

Fifty-five years of radiocarbon variation studies are reviewed with an emphasis on a better understanding of the impacts of the Bohunice nuclear power plant and fossil fuel CO2 on the atmosphere and biosphere of Slovakia. The maximum Δ14C levels in the air up to about 1200‰ were observed during the 1970s at the Zlkovce monitoring station, which after 2005 decreased to <30‰. A relative decrease in the atmospheric Δ14C levels due to increasing levels of fossil CO2 in the atmosphere has also been significant, for example, in Bratislava down to about -330‰, but after 2005 they were only <50‰ below the Jungfraujoch European clean-air level. The tree-ring data, averaging the annual Δ14C levels for several stations in Slovakia, have been in agreement with the atmospheric data, as well as with the newly established clean-air station at Jasná in central Slovakia. Future 14C levels will depend strongly on fossil CO2 levels in the atmosphere, which will change the bomb 14C era to the fossil CO2 era. New investigations of 14C variations in the atmosphere-biosphere-hydrosphere compartments represent a great challenge for radiocarbon science, important for better understanding of environmental processes, climate change, and impacts of human activities on the total environment. This new era of radiocarbon research will also need new developments in radiocarbon analytical technologies, as further progress in accuracy and precision of results (<1‰) will be needed to meet the new radiocarbon challenges.

Image Entropy-Based Interface Evaluation Method for Nuclear Power Plants.

The digital interface is crucial for nuclear plant operators, influencing their decision-making significantly. However, evaluations of these interfaces often overlook users' decision-making performance; lack established standards, typically occurring after the design phase; and are unsuitable for large-scale assessments. Recognizing the vital role of interface information, this paper built on our previous research and proposed a method tailored for nuclear power plant interfaces, utilizing image entropy to evaluate the impact of information on decision-making. A comparative analysis with an experimental evaluation method empirically validated the effectiveness of the proposed method. This research offers a unique decision-making-centric method to interface evaluation, providing a standardized, adaptable framework for various design phases and enabling extensive and rapid evaluations.

Increased Screening Rates for Thyroid Cancer Among Residents Living Near Nuclear Power Plants.

Frequent screening for thyroid cancer has been suggested as a probable explanation for the observed high risk of thyroid cancer in nuclear power plant (NPP) areas. We aimed to compare thyroid cancer screening rates of residents living near NPPs to those of the general population. This study utilized data from two national survey-based studies in 2016 and in 2014, respectively, for residents (n = 1,200) living in administrative districts within 5 km of NPP sites as the interest group, and the general population (n = 228,712) including distant-living residents (n = 19,100) in administrative districts within 30 km of NPP sites as reference groups. We observed an increase in screening rates in residents near NPPs, which may lead to a higher possibility of thyroid cancer detection. Therefore, further epidemiological studies investigating radiation-induced thyroid cancer risk among residents near NPPs should be carefully designed and interpreted considering possible detection bias.

Comparative Analysis of Driver Mutations and Transcriptomes in Papillary Thyroid Cancer by Region of Residence in South Korea.

BACKGRUOUND: Radiation exposure is a well-known risk factor for papillary thyroid cancer (PTC). South Korea has 24 nuclear reactors in operation; however, no molecular biological analysis has been performed on patients with PTC living near nuclear power plants. METHODS: We retrospectively included patients with PTC (n=512) divided into three groups according to their place of residence at the time of operation: inland areas (n=300), coastal areas far from nuclear power plants (n=134), and nuclear power plant areas (n=78). After propensity score matching (1:1:1) by age, sex, and surgical procedure, the frequency of representative driver mutations and gene expression profiles were compared (n=50 per group). Epithelial-mesenchymal transition (EMT), BRAF, thyroid differentiation, and radiation scores were calculated and compared. RESULTS: No significant difference was observed in clinicopathological characteristics, including radiation exposure history and the frequency of incidentally discovered thyroid cancer, among the three groups. BRAFV600E mutation was most frequently detected in the groups, with no difference among the three groups. Furthermore, gene expression profiles showed no statistically significant difference. EMT and BRAF scores were higher in our cohort than in cohorts from Chernobyl tissue bank and The Cancer Genome Atlas Thyroid Cancer; however, there was no difference according to the place of residence. Radiation scores were highest in the Chernobyl tissue bank but exhibited no difference according to the place of residence. CONCLUSION: Differences in clinicopathological characteristics, frequency of representative driver mutations, and gene expression profiles were not observed according to patients' region of residence in South Korea.

Trends of Eurasian Perch (Perca fluviatilis) mtDNA ATP6 Region Genetic Diversity within the Hydro-Systems of the Eastern Part of the Baltic Sea in the Anthropocene.

The intraspecific genetic diversity of freshwater fish inhabiting hydro-systems of the macrogeographic area spreading from the Black to Baltic Seas requires comprehensive investigation from fundamental and practical perspectives. The current study focused on the involvement of the mtDNA ATP6 region in the adaptability and microevolution of Perca fluviatilis within phylogeographic and anthropogenic contexts. We sequenced a 627 bp fragment encompassing the ATP6 region and used it for genetic analysis of 193 perch caught in Latvia, Lithuania, Belarus, and Ukraine, representing natural and anthropogenically impacted populations. We evaluated patterns of intraspecific genetic diversity in the ATP6 region and phylogeographic trends within the studied area compared with previously established D-loop trends. Evaluation of ATP6 coding sequence variability revealed that among 13 newly detected haplotypes, only two were caused by non-synonymous substitutions of amino acids of the protein. PCoA revealed three genetic groups (I-III) based on the ATP6 region that encompassed four previously described genetic groups established based on the mtDNA D-loop. The two mtDNA regions (D-loop and ATP6) have microevolved at least partially independently. Prolonged anthropogenic impacts may generate new point mutations at the ATP6 locus, but this phenomenon could be mainly concealed by natural selection and reparation processes.

Nuclear Anxiety Amid the Russian-Ukrainian War 2022 (RUW-22): Descriptive Cross-Sectional Study.

Nuclear anxiety, which refers to the fear of nuclear war and its consequences, is expected to increase amid the Russian-Ukrainian War of 2022 (RUW-22). This study aimed to evaluate the prevalence of nuclear anxiety and its associated variables among university students in the Czech Republic during the first weeks of RUW-22. A cross-sectional survey-based study was carried out from March-April 2022, utilizing a digital self-administered questionnaire (SAQ) to collect data from the target population. The SAQ consisted of multiple-choice items inquiring about demographic characteristics; generalized anxiety symptoms using generalized anxiety disorder-7 (GAD-7); depressive symptoms using patient health questionnaire-9 (PHQ-9); and attitudes towards civilian uses of nuclear power, and nuclear war-related anxiety. Of the 591 participating students, 67.7% were females, 68.2% were Czech nationals, and 61.8% followed the RUW-22 news at least once daily. The mean GAD-7 score of our participants was 7.86 ± 5.32 (0-21); and their mean PHQ-9 score was 8.66 ± 6.29 (0-27). Regarding the civilian uses of nuclear power, most participants agreed that nuclear power was safe (64.5%), denied being afraid that civilian use of nuclear power might deteriorate their health (79.7%), and thought that public acceptance was important for building new nuclear power plants (56.9%). About 42.1% and 45.5% of the participants reported feeling depressed at the possibility of nuclear war and agreed that the chances that there would be a nuclear war in their lifetime were very high, respectively. When asked about their preparedness measures during the previous four weeks, less than one quarter (23.9%) reported looking for recommendations for protection against nuclear accidents, and less than one-fifth (19.3%) were looking for the nearest bomb shelter. The depression about nuclear war possibility was positively and relatively strongly correlated with the level of "feeling concerned about the RUW-22" (rs = 0.401), and it was moderately correlated with GAD-7 (rs = 0.377) and PHQ-9 (rs = 0.274) scores and weakly correlated with RUW-2-related news-following frequency (rs = 0.196). Within the limitations of the present study, nuclear anxiety was common among Czech university students. Its associated factors may include but are not limited to the female gender; common psychological disorders such as generalized anxiety and depression; RUW-22-related news following-frequency; and the level of "feeling concerned".

The Predictors of Unsafe Behaviors among Nuclear Power Plant Workers: An Investigation Integrating Personality, Cognitive and Attitudinal Factors.

Unsafe behaviors, such as violations and human errors, have long been recognized as the main causes of accidents in nuclear power plants (NPPs). However, personal factors that influence unsafe behaviors among NPP workers have not been well examined, especially in an integrated model. This study proposes an integrated contextual mediated model to examine personality, cognitive and attitudinal predictors of unsafe behaviors among commissioning workers at NPPs. The model was verified using structural equation modeling technique with survey data from 177 commissioning workers in two Chinese NPPs. Results show that personality traits (i.e., conscientiousness, neuroticism, openness and agreeableness), executive function and safety attitudes exerted significant effects on unsafe behaviors. In addition, the effects of agreeableness and executive function were partly mediated by safety attitudes. Both conscientiousness and neuroticism indirectly influenced unsafe behaviors through the mediating role of executive function. The findings shed light on the design of evidence-based interventions for safety performance in NPPs.

Domain- and task-analytic workload (DTAW) method: a methodology for predicting mental workload during severe accidents in nuclear power plants.

Excessive mental workload reduces operators' performance and threatens the safety of nuclear power plants (NPPs) in severe accident management (SAM). Given the lack of suitable mental workload measurement methods for SAM tasks, we proposed a Domain- and Task-Analytic Workload (DTAW) method to predict SAM workload. The DTAW method is developed in three stages: scenario construction based on work domain analysis, task analysis, and workload estimation with eight workload components scored through task-analytic and projective methods. To demonstrate its utility, we applied the method to construct two SAM scenarios and predict the mental workload demand of operators in these scenarios as compared to two design basis accident scenarios. With statistical analysis, the DTAW method can predict the overall subjective workload rated by NPP operators, be used to identify high-load tasks, cluster tasks with similar workload patterns, and provide direct implications for improving SAM strategies and supporting systems.Practitioner summary: To predict mental workload in severe accident management (SAM) scenarios in nuclear power plants, we proposed an analytic method and applied it to estimate mental workload in two SAM scenarios and two design basis accident (DBA) scenarios. We found that the workload pattern in SAM scenarios is different from that in DBA scenarios.

Study Protocol for Radiation Exposure and Cancer Risk Assessment: The Taiwan Nuclear Power Plants and Epidemiology Cohort Study (TNPECS).

BACKGROUND: This cohort was established to evaluate whether 38-year radiation exposure (since the start of nuclear reactor operations) is related to cancer risk in residents near three nuclear power plants (NPPs). METHODS: This cohort study enrolled all residents who lived within 8 km of any of the three NPPs in Taiwan from 1978 to 2016 (n = 214,502; person-years = 4,660,189). The control population (n = 257,475; person-years = 6,282,390) from three towns comprised all residents having lived more than 15 km from all three NPPs. Radiation exposure will be assessed via computer programs GASPAR-II and LADTAP-II by following methodologies provided in the United States Nuclear Regulatory Commission regulatory guides. We calculated the cumulative individual tissue organ equivalent dose and cumulative effective dose for each resident. This study presents the number of new cancer cases and prevalence in the residence-nearest NPP group and control group in the 38-year research observation period. CONCLUSION: TNPECS provides a valuable platform for research and opens unique possibilities for testing whether radiation exposure since the start of operations of nuclear reactors will affect health across the life course. The release of radioactive nuclear species caused by the operation of NPPs caused residents to have an effective dose between 10-7 and 10-3 mSv/year. The mean cumulative medical radiation exposure dose between the residence-nearest NPP group and the control group was not different (7.69; standard deviation, 18.39 mSv and 7.61; standard deviation, 19.17 mSv; P = 0.114).

Monitoring land use and land cover change near a nuclear power plant construction site: Akkuyu case, Turkey.

Land use and land cover (LULC) change analysis of the construction site and its surroundings of the Akkuyu Nuclear Power Plant project in southern Turkey was undertaken in this case study, which was supported by remotely sensed Landsat 8 image composites. The composite images compiled in 2017 and 2021 were prepared on the Google Earth Engine platform. The Random Forest algorithm was used as the classifier model. A high classification performance was obtained for both images (kappa > 0.88, overall accuracy > 90%). After the classification process, LULC maps for both years were generated, and statistical calculations for the LULC change were computed for both the entire study area (15 × 25 km) and a buffer zone with a radius of 1 km around the power plant. In the whole study area, artificial surfaces significantly increased (78.46%), whereas forests (- 8.31%) and barren lands experienced a considerable decrease (- 6.11%). In the 1 km buffer, artificial surfaces predominantly increased (113.94%), while forests and barren lands decreased dramatically (- 69.13% and - 74.28%, respectively). The agricultural areas in the study area were changed into other LULC classes: 9.1% to artificial surfaces, 27.6% to barren lands, and 21.7% to forest. The rise in the area of artificial surfaces was especially noticeable within the 1 km buffer zone: construction activities converted 36.1% of agricultural fields, 54.1% of forests, and 23.2% of barren lands into artificial surfaces. The filling activities on the seashore resulted in a loss of water bodies of up to 26.5%. The study provides an overview of how the LULC classes have evolved on the construction site and in the region. In the end, the study discusses how the current land use preferences in the region contradict the issues and concerns mentioned in the existing body of literature.

Characteristics of Patients Transported by Doctor-Requested Helicopters After Japan's 2011 Nuclear Incident.

OBJECTIVES: This study examined the characteristics of severe patients after the Great East Japan Earthquake in 2011. METHODS: Cases in the Futaba area were extracted using the dispatch database of the doctor helicopter and flight-nurse records from March 11, 2008, till March 10, 2014. The period before March 11, 2011, was defined as 'pre-earthquake' and the period after March 11, 2011, as 'post-earthquake' to compare the recorded data. RESULTS: Of the 128 total recorded cases, 78 were dispatched during the pre-earthquake period and 50 during the post-earthquake period. The number of patients with physical trauma following the earthquake included 4 patients (33.3%) in 2011, 7 patients (43.7%) in 2012, and 13 patients (59.1%) in 2013. However, the increase in number of requests was not statistically significant (P = 0.33). All 4 incidents of physical trauma in 2011, and 3 out of 7 incidents in 2012, occurred at the power plants. A total of 4 incidents occurred at decontamination worksites in 2013. CONCLUSIONS: It is of primary importance for hospitals to anticipate physical trauma cases during the reconstruction phase following a disaster, and develop a system for patients with physical trauma in the short- and long-term.

Site suitability-based spatial-weighted multicriteria analysis for nuclear power plants in Indonesia.

Nuclear energy is a choice to meet the electricity needs of West Kalimantan, Indonesia to support new industrial areas. Nuclear Power Plants (NPPs) require an appropriate location in terms of biogeophysical, socio-economic, and disaster considerations. This study aims to determine potential sites for NPPs using spatial-weighted multicriteria analysis. GIS and analytical hierarchical processes (AHP) were combined to produce suitable NPPs site. This study showed that West Kalimantan has a very high suitability area covering 16,321.66 Km2 (25.81 %) for NPPs. The NPPs are proposed to operate with water reactor coolants, thereby prioritizing areas of about five kilometres from the shoreline. We discovered twelve sites, but only two suitable priority sites for NPPs were found in Ketapang after overlapping with national/regional planning and the existing state. These sites will not significantly impact the environment, socio-economic, and policies, also will support electricity for the new capital region for Indonesia.

Application of a Bayesian network to quantify human reliability in nuclear power plants based on the SPAR-H method.

Human error is an important factor leading to nuclear power plant (NPP) accidents. Human reliability analysis (HRA) is considered an effective method to reduce human error. Therefore, this article proposes a method to quantify human reliability based on the standardized plant analysis risk-human reliability analysis (SPAR-H) method. Firstly, the method used the performance shaping factors of SPAR-H to build a human reliability model. Secondly, the triangular fuzzy number was used to quantify the qualitative information of root nodes, and the fuzzy IF-THEN rule was used to determine the prior probability distribution of intermediate nodes. Finally, Bayesian reasoning was used to quantify human reliability based on the human reliability model. The result of the developed method is consistent with the result of cognitive reliability and error analysis methods (CREAM). The developed method can be used as a tool to quantify human reliability in the NPP system.

Analysis of causes and countermeasures against marine organisms blocking event at cold source intake of coastal nuclear power plant / 中华放射医学与防护杂志

The cold source system of a nuclear power plant, as important part of a nuclear power project, is of great significance to guarantee the safe operation of a nuclear power plant. In recent years, there have been some cases of marine organism blockage at cold source intake at coastal nuclear power plants in China, which has adversely affected the safety and economy of nuclear power plants. According to the research result of cold source safety in coastal nuclear power plants in China and in compliance with the requirements of nuclear safety regulatory control and the engineering practice experience, the causes of, and countermeasures against, marine organism blockage at cold source intake are analyzed to further improve the safety and economy of nuclear power plants.