Search Results (361)

Some of nuclear power’s primary detractors are the unique environmental challenges and impacts of radioactive wastes generated during fuel cycle operations. Key benefits of spent fuel reprocessing (SFR) are reductions in primary high active waste (HAW) masses, volumes, and lengths of radiotoxicity at the expense of secondary waste generation and high capital and operational costs. By employing advanced waste management and resource recovery concepts in SFR beyond the existing standard PUREX process, such as minor actinide and fission product partitioning, these challenges could be mitigated, alongside further reductions in HAW volumes, masses, and duration of radiotoxicity. This work assesses various current and proposed SFR and fuel cycle options as base cases, with further options for fission product partitioning of the high heat radionuclides (HHRs), rare earths, and platinum group metals investigated. A focus on primary waste outputs and the additional energy that could be generated by the reprocessing of high-burnup PWR fuel from Gen III(+) reactors using a simple fuel cycle model is used; the effects of 5- and 10-year spent fuel cooling times before reprocessing are explored. We demonstrate that longer cooling times are preferable in all cases except where short-lived isotope recovery may be desired, and that the partitioning of high-heat fission products (Cs and Sr) could allow for the reclassification of traditional raffinates to intermediate level waste. Highly active waste volume reductions approaching 50% vs. PUREX raffinate could be achieved in single-target partitioning of the inactive and low-activity rare earth elements, and the need for geological disposal could potentially be mitigated completely if HHRs are separated and utilised. Full article

To ensure the safety of nuclear power production, nuclear power plants deploy numerous sensors to monitor various physical indicators during production, enabling the early detection of anomalies. Efficient anomaly detection relies on complete sensor data. However, compared to conventional energy sources, the extreme physical environment of nuclear power plants is more likely to negatively impact the normal operation of sensors, compromising the integrity of the collected data. To address this issue, we propose an anomaly detection method for nuclear power data: Neural Normal Stochastic Process (NNSP). This method does not require imputing missing sensor data. Instead, it directly reads incomplete monitoring data through a sequentialization structure and encodes it as continuous latent representations in a neural network. This approach avoids additional “processing” of the raw data. Moreover, the continuity of these representations allows the decoder to specify supervisory signals at time points where data is missing or at future time points, thereby training the model to learn latent anomaly patterns in incomplete nuclear power monitoring data. Experimental results demonstrate that our model outperforms five mainstream baseline methods—ARMA, Isolation Forest, LSTM-AD, VAE, and NeutraL AD—in anomaly detection tasks on incomplete time series. On the Power Generation System (PGS) dataset with a 15% missing rate, our model achieves an F1 score of 83.72%, surpassing all baseline methods and maintaining strong performance across multiple industrial subsystems. Full article

Nuclear Magnetic Resonance (NMR) and Magnetic Resonance Imaging (MRI) are powerful techniques that have been employed to analyze foodstuffs comprehensively. These techniques offer in-depth information about the chemical composition, structure, and spatial distribution of components in a variety of food products. Quantitative NMR is widely applied for precise quantification of metabolites, authentication of food products, and monitoring of food quality. Low-field ¹H-NMR relaxometry is an important technique for investigating the most abundant components of intact foodstuffs based on relaxation times and amplitude of the NMR signals. In particular, information on water compartments, diffusion, and movement can be obtained by detecting proton signals because of H₂O in foodstuffs. Saffron adulterations with calendula, safflower, turmeric, sandalwood, and tartrazine have been analyzed using benchtop NMR, an alternative to the high-field NMR approach. The fraudulent addition of Robusta to Arabica coffee was investigated by ¹H-NMR Spectroscopy and the marker of Robusta coffee can be detected in the ¹H-NMR spectrum. MRI images can be a reliable tool for appreciating morphological differences in vegetables and fruits. In kiwifruit, the effects of water loss and the states of water were investigated using MRI. It provides informative images regarding the spin density distribution of water molecules and the relationship between water and cellular tissues. ¹H-NMR spectra of aqueous extract of kiwifruits affected by elephantiasis show a higher number of small oligosaccharides than healthy fruits do. One of the frauds that has been detected in the olive oil sector reflects the addition of hazelnut oils to olive oils. However, using the NMR methodology, it is possible to distinguish the two types of oils, since, in hazelnut oils, linolenic fatty chains and squalene are absent, which is also indicated by the ¹H-NMR spectrum. NMR has been applied to detect milk adulterations, such as bovine milk being spiked with known levels of whey, urea, synthetic urine, and synthetic milk. In particular, T2 relaxation time has been found to be significantly affected by adulteration as it increases with adulterant percentage. The ¹H spectrum of honey samples from two botanical species shows the presence of signals due to the specific markers of two botanical species. NMR generates large datasets due to the complexity of food matrices and, to deal with this, chemometrics (multivariate analysis) can be applied to monitor the changes in the constituents of foodstuffs, assess the self-life, and determine the effects of storage conditions. Multivariate analysis could help in managing and interpreting complex NMR data by reducing dimensionality and identifying patterns. NMR spectroscopy followed by multivariate analysis can be channelized for evaluating the nutritional profile of food products by quantifying vitamins, sugars, fatty acids, amino acids, and other nutrients. In this review, we summarize the importance of NMR spectroscopy in chemical profiling and quality assessment of food products employing magnetic resonance technologies and multivariate statistical analysis. Full article

As a promising nuclear technology, molten salt reactors (MSRs) have a bright future in the energy sector due to their unique advantages such as high efficiency, safety, and fuel flexibility. However, the accurate analysis of fission products in MSRs requires reliable fission yield data. Current reactor burnup analysis often uses the ORIGEN2 code, whose fission yield libraries mainly originate from the outdated 1970s ENDF/B-VI nuclear database, thus risking data obsolescence. This study evaluates ORIGEN2’s fission yield libraries (THERMAL, PWRU, PWRU50) against the modern ENDF/B-VIII.0 library. Through a comprehensive comparative analysis of Oak Ridge National Laboratory’s Molten Salt Reactor Experiment (MSRE) model, numerical simulations reveal library-dependent differences in MSR burnup characteristics. The PWRU library best matches ENDF/B-VIII.0 for U-235-fueled cases in keff results, while the PWRU50 library has minimal keff deviation in U-233-fueled setups. Moreover, in both fuel cases, the fission yield library was found to significantly affect the activity of key radionuclides, including Kr-85, Kr-85m, I-133m, Cs-136, Sn-123, Sn-125, Sn-127, Sb-124, Sb-125, Cd-115m, Te-125m, Te-129m, etc. Additionally, the fission gas decay heat power calculated via the ORIGEN2 library is over 20% lower than that from the ENDF/B-VIII.0 library tens of days after shutdown, mainly due to differences in long-lived Kr-85 production. These findings highlight the need to update traditional fission yield libraries in burnup codes. For next-generation MSR designs, this is crucial to ensure accurate safety assessments and the effective development of this promising energy technology. Full article

Access to clean and sustainable energy technologies is critical for all nations, particularly developing countries in Africa. Ghana has committed to ambitious greenhouse gas emission reduction targets, aiming for 10% and 20% variable renewable energy integration by 2030 and 2070, respectively. This study explores potential pathways for Ghana to achieve its renewable energy production targets amidst a growing energy demand. An open-source energy modelling tool was used to assess four scenarios accounting for current policies and additional alternatives to pursue energy transition goals. The scenarios include Business as Usual (BAU), Government Target (GT), Renewable Energy (REW), and Net Zero (NZ). The results indicate that total power generation and installed capacity would increase across all scenarios, with natural gas accounting for approximately 60% of total generation under the BAU scenario in 2070. Total electricity generation is projected to grow between 10 and 20 times due to different electrification levels. Greenhouse gas emission reduction is achievable with nuclear energy being critical to support renewables. Alternative pathways based on clean energy production may provide cost savings of around USD 11–14 billion compared to a Business as Usual case. The findings underscore the necessity of robust policies and regulatory frameworks to support this transition, providing insights applicable to other developing countries with similar energy profiles. This study proposes a unique contextualized open-source modelling framework for a data-constrained, lower–middle-income country, offering a replicable approach for similar contexts in Sub-Saharan Africa. Its novelty also extended towards contributing to the knowledge of energy system modelling, with nuclear energy playing a crucial role in meeting future demand and achieving the country’s objectives under the Paris Agreement. Full article

In support of global efforts to strengthen the nuclear non-proliferation regime, the IVG.1M research water-cooled thermal reactor at the National Nuclear Center of the Republic of Kazakhstan was successfully converted to low-enriched uranium (LEU, 19.75% ²³⁵U) fuel in 2023. The reactor’s operability with innovative bimetallic, fiber-type, dual-blade LEU fuel rods was experimentally verified during power start-up experiments. The test program included investigations of power distribution in the core, evaluation of temperature, power, and hydrodynamic reactivity effects, and the measurement of fission product release to the coolant. The results were in good agreement with safety calculations, confirming that the enrichment reduction did not degrade reactor performance characteristics. It was shown that the power reactivity effect increased by more than 1.5 times at a power level of 9 MW. The measured temperature reactivity coefficient (≈0.021 β_eff/°C) and the level of fission product release remained within acceptable and expected limits. Full article

Weather-dependent, volatile energy sources, such as wind power and solar photovoltaics (PV), contribute considerably to the German electric energy supply. The current German government aims to substantially increase their market share. Using high-resolution time-series data from energy production and demand measurements, we replicate and analyze scenarios from the “Klimaneutrales Deutschland 2045” (KND2045) study. KND2045 was the basis for the German Government’s 2021 decision to move the abolition of CO₂ emissions from 2050 to 2045. The primary question in KND2045 is whether security of supply can be maintained by relying primarily on an effective duopoly of wind and solar power. We simulate scenarios for 2023, 2030, and 2045 using 15-min time-resolved measurements of wind and solar energy production and demand from 2023 and 2024, incorporating battery and gas storage systems into our model. We assess the overall economic costs for these scenarios. Our calculations demonstrate that the KND2045 scenarios are infeasible, as significant supply gaps persist during dark wind lulls, compromising security of supply. Instead, we propose improvements to these scenarios by incorporating nuclear energy as a backup to address KND2045’s shortcomings. Full article

Motivated by the growth of global energy demand and the goal of carbon neutrality, lead-cooled fast reactors, which are core reactor types of fourth-generation nuclear energy systems, have become a global research hotspot due to their advantages of high safety, nuclear fuel breeding capability, and economic efficiency. However, its engineering implementation faces key challenges, such as material compatibility, closed fuel cycles, and irradiation performance of structures. This paper comprehensively reviews the latest progress in the core design of lead-cooled fast reactors in terms of the innovation of nuclear fuel, optimization of coolant, material adaptability, and design of assemblies and core structures. The research findings indicate remarkable innovation trends in the field of lead-cooled fast reactor core design, including optimizing the utilization efficiency of nuclear fuel based on the nitride fuel system and the traveling wave burnup theory, effectively suppressing the corrosion effect of liquid metal through surface modification technology and the development of ceramic matrix composites; replacing the lead-bismuth eutectic system with pure lead coolant to enhance economic efficiency and safety; and significantly enhancing the neutron economy and system integration degree by combining the collaborative design strategy of the open-type assembly structure and control drums. In the future, efforts should be made to overcome the radiation resistance of materials and liquid metal corrosion technology, develop closed fuel cycle systems, and accelerate the commercialization process through international standardization cooperation to provide sustainable clean energy solutions for basic load power supply, high-temperature hydrogen production, ship propulsion, and other fields. Full article

The mechanical properties of grouting materials and their cured grouts significantly impact the reinforcement effectiveness in deep coal mine roadways. This study employed shear rheology tests of slurry, structural tests, NMR (nuclear magnetic resonance), and uniaxial compression tests to comparatively analyze the mechanical characteristics of a composite cement-based grouting material (HGC), ordinary Portland cement (OPC), and sulfated aluminum cement (SAC) slurry and their cured grouts. The HGC (High-performance Grouting Composite) slurry is formulated with 15.75% sulfated aluminum cement (SAC), 54.25% ordinary Portland cement (OPC), 10% fly ash, and 20% mineral powder, achieving a water/cement ratio of 0.26. The results indicate that HGC slurry more closely follows power-law flow characteristics, while OPC and SAC slurries fit better with the Bingham model. The structural recovery time for HGC slurry after high-strain disturbances is 52 s, significantly lower than the 312 s for OPC and 121 s for SAC, indicating that HGC can quickly produce hydration products that re-bond the flocculated structure. NMR T2 spectra show that HGC cured grouts have the lowest porosity, predominantly featuring inter-nanopores, whereas OPC and SAC have more super-nanopores. Uniaxial compression tests show that the uniaxial compressive strength of HGC, SAC, and OPC samples at various curing ages gradually decreases. Compared to traditional cementitious materials, HGC exhibits a rapid increase in uniaxial compressive strength within the first seven days, with an increase rate of approximately 77.97%. Finally, the relationship between micropore distribution and strength is analyzed, and the micro-mechanisms underlying the strength differences of different grouting materials are discussed. This study aids in developing a comparative analysis system of mechanical properties for deep surrounding rock grouting materials, providing a reference for selecting grouting materials for various engineering fractured rock masses. Full article

As is well known, due to carbon dioxide emissions, the combustion of lignite in power plants creates environmental pollution. In contrast, nuclear fuels do not produce carbon dioxide emissions. This paper investigates the effects of replacing lignite thermal power plants with small modular nuclear reactors (SMRs) of equivalent rated power and related characteristics. In terms of the emissions criterion, nuclear fuels belong to the same category of clean sources as the sun and wind. A second criterion is the economic one and concerns the operating cost of the nuclear–thermal power plant. Based on the economic criterion, although nuclear reactors require a higher initial invested capital, they have lower fuel costs and lower operating costs than lignite plants, which is important due to their long service life. A third criterion is the effect of the operation mode of an SMR, constant or variable, on the cost of energy production. In terms of the operation mode criterion, two cycles were investigated: the production of a constant amount of energy and the production of a variable amount of energy related to fluctuations in the electric load demand or the operation load-following. Using multi-criteria managerial scenarios, the results of the research demonstrate that the final mean minimal cost of energy generated by hybrid thermal units with small nuclear reactors in constant power output operation is lower than the mean minimal cost of the energy generated in the load-following mode by 2.45%. At the same time, the carbon dioxide emissions in the constant power output operation are lower than those produced in the load-following mode by 2.14%. In conclusion, the constant power output operation of an SMR is more sustainable compared to the load-following operation and also is more sustainable compared to generation by lignite thermal power plants. Full article

Nuclear energy is a cornerstone of the global energy mix, delivering reliable, low-carbon power essential for sustainable energy systems. However, the safety of nuclear reactors is critical to maintaining operational reliability and public trust, particularly during accidents like a Loss of Coolant Accident (LOCA) or a Steam Line Break Inside Containment (SLBIC). This study introduces a Bayesian Network (BN) framework used to enhance nuclear energy safety by predicting accident severity and identifying key factors that ensure energy production stability. With the integration of simulation data and physical knowledge, the BN enables dynamic inference and remains robust under missing-data conditions—common in real-time energy monitoring. Its hierarchical structure organizes variables across layers, capturing initial conditions, intermediate dynamics, and system responses vital to energy safety management. Conditional Probability Tables (CPTs), trained via Maximum Likelihood Estimation, ensure accurate modeling of relationships. The model’s resilience to missing data, achieved through marginalization, sustains predictive reliability when critical energy system variables are unavailable. Achieving R² values of 0.98 and 0.96 for the LOCA and SLBIC, respectively, the BN demonstrates high accuracy, directly supporting safer nuclear energy production. Sensitivity analysis using mutual information pinpointed critical variables—such as high-pressure injection flow (WHPI) and pressurizer level (LVPZ)—that influence accident outcomes and energy system resilience. These findings offer actionable insights for the optimization of monitoring and intervention in nuclear power plants. This study positions Bayesian Networks as a robust tool for real-time energy safety assessment, advancing the reliability and sustainability of nuclear energy production. Full article

The creep properties of 15Kh2NMFAA nuclear WWER (water–water energetic reactor) vessel steel in the range of 500–1200 °C temperatures, which may appear during severe nuclear reactor accidents, were investigated. The present paper attempts to analyze the creep curves obtained from tensile testing at high temperatures using the Larson–Miller parametric technique. The power law rate and material coefficient of Norton’s equation with the Monkman–Grant relationship coefficient were found for each test temperature. It is shown that in accordance with the Monkman–Grant relationship coefficient values, changing the creep type from dislocation glide to high temperature dislocation climb occurs in the temperature range of 600–700 °C, which leads to a slope change in the Larson–Miller parameter plot and the conversion of steel creep behavior. It is also shown that in the range of $A_1$–$A_3$ temperatures, a stepwise change in creep characteristics occurs, which is associated with phase transformations. In addition, the constancy of the product of the time to rupture ${\tau }_r$ and the minimum creep rate ${\dot{ϵ}}_{min}$ in the ranges of 600–700 °C and $A_3$—1200 °C was noted. The proposed approach improves the accuracy of time to rupture estimation of 15Kh2NMFAA steel by at least one order of magnitude. Based on the research results, the calculated dependence of the steel’s long-term strength limit on temperature was obtained for several time bases, allowing us to increase the accuracy of material survivability prediction in the case of a severe accident at a nuclear reactor. Full article

Stilbenes are plant secondary metabolites with remarkable antidiabetic, anti-inflammatory, antimicrobial, antioxidant, antitumor, and neuroprotective properties. As these compounds are valuable constituents in healthcare products and promising drug candidates, exploring new sources of stilbenes is essential for therapeutic advancement. The present study reports the isolation of two stilbene glycosides, resveratroloside and pinostilbenoside, from Pinus cembra L. bark. Their antioxidant activity and cytotoxic effects against HeLa cells were evaluated in comparison to the raw bark extract. The structures of resveratroloside and pinostilbenoside were confirmed by nuclear magnetic resonance (NMR) and mass spectrometry (MS) data analyses. Antioxidant activity was assessed by 2,2-diphenyl-1-picrylhydrazyl (DPPH) radical scavenging and reducing power assays. Cell viability, apoptosis, cell proliferation, and cell cycle assays were used to evaluate the cytotoxic potential against HeLa cells. Resveratroloside and pinostilbenoside exhibited lower activity as free radical scavengers and reducing agents. However, they showed greater efficacy in reducing viability and suppressing proliferation in human cervical carcinoma HeLa cells. Given the promising findings of our study, the therapeutic potential of resveratroloside and pinostilbenoside should be further investigated. Full article

A comparison of the net present value, the payback period, and the levelized cost of electricity for three different projects of construction and exploitation of plants for electricity production with the aim of decarbonizing the energy sector is conducted. The first project is the building of a large-scale nuclear power plant with a light-water reactor, the second one is the deployment of several identical small modular reactors, and the third project is based on solar and wind power plants. Given that the sun and wind are intermittent renewable energy sources, it is inevitable to take into account the construction of an energy storage facility in the last project. The results show that the most profitable are the small modular reactors, while the investment into solar and wind power plants is burdened with the necessary electricity storage plant costs. Another drawback of an investment in solar and wind power plants is their shorter exploitation lifetime of 25 years compared to the long-term operation of nuclear power plants of 60 years or even more. Full article

This study aimed to assess the production of Smilax brasiliensis seedlings in an in vitro environment and their adaptation to natural conditions, as well as the callus induction, the chemical profile of calli extracts, and their antioxidant potential. The seedlings were obtained from S. brasiliensis seeds germinated in Murashige and Skoog (MS) medium. The germination rate was 33%, and about 22% of the seeds produced whole seedlings. Three-month-old seedlings were acclimatized for two months, resulting in an 80% survival rate and improved physiological characteristics. Callus induction was initiated from leaf explants obtained from seedlings and plant growth regulators (PGRs), with and without light exposure. Calli extracts were obtained using methanol; phenolic compound and flavonoid quantification were performed, and the chemical profile was determined by nuclear magnetic resonance (¹H NMR). For comparison, methanol extract from S. brasiliensis leaves collected in Brazilian Cerrado were also analyzed. Antioxidant activity was assessed using the 2,2-diphenyl-1-picryl-hydrazyl method and the ferric-reducing antioxidant power assay. All samples exhibited antioxidant activity according to the methods employed. Furthermore, ¹H NMR revealed metabolic profile changes in the calli extracts compared to the leaf extract. This study yielded promising results, suggesting that in vitro culture could improve productivity and conserve the species, although changes were observed in the metabolic profile of S. brasiliensis. Full article