Showing papers on "Nuclear power published in 2022"

Identifying the strategic priorities of nuclear energy investments using hesitant 2-tuple interval-valued Pythagorean fuzzy DEMATEL

Abstract: This study aims to determine the strategic priorities for the nuclear energy investments in Turkey. In this context, nine different factors affecting nuclear energy projects are evaluated with the hesitant 2-tuple interval-valued Pythagorean fuzzy DEMATEL. Pythagorean fuzzy sets contribute significantly to the solution of uncertainty problem. Similarly, owing to the hesitant approach, it will be possible to manage the different opinions that may arise among experts more effectively. According to the results, factors related to security risk and technological infrastructure adequacy should be considered most in the nuclear energy investment decision. Important concern in this process is that Turkey does not have any experience in the process of building a nuclear power plant. Hence, there is a risk that the necessary security measures may not be taken in the new nuclear power plant planned to be established. Therefore, building nuclear power stations using uranium in Turkey does not seem very reasonable. Instead, Turkey should focus on the nuclear energy projects by using thorium. The main reason is that thorium element produces much less radioactive waste compared to uranium. Also, in the process of nuclear energy using thorium, no more neutrons emerge. Thus, the use of thorium eliminates the risk of explosion in nuclear power plants. In this context, Turkey should make investment in the proton accelerator technology. With the help of this issue, security risks can be minimized in these planned nuclear power plants.

Nuclear energy: A pathway towards mitigation of global warming

Abstract: Global warming is the ongoing rise in the average temperature of Earth's climate system. Over the past 50 years, the average temperature has increased at the fastest rate in recorded history due to uncontrolled generation of greenhouse gases. Nuclear power is low carbon energy, and it is contributing on a large scale to a low carbon economy and a green energy grid. 442 nuclear power reactors are operating worldwide generating 393 GWe of electricity providing continuous and reliable low carbon power. Nuclear electricity accounts for 11% of total global electricity generation, and this amounts to a third of the low-carbon electricity produced in the world. New innovations are taking place which make nuclear power a more affordable and attractive energy option. These include advances in large reactors, emerging technologies such as advanced fuel and small modular reactors, engineering breakthroughs extending the operational lifetime of existing reactors, and new developments in materials and better waste management. Fast breeder reactor technology has become a commercial reality and it helps not only in generating electricity, but also in producing more fuel than it consumes, besides burning nuclear waste more efficiently compared to any of the existing commercial reactor technologies. The Sun's energy is generated by nuclear fusion. Mastering nuclear fusion technology can guarantee energy security in terms of clean, safe and affordable energy. Nuclear fusion, and plasma physics research of very complex nature are being carried out in many countries. Fusion reactions have been successfully demonstrated although for a fraction of a second and without demonstrating a net gain of electric power. The world's largest international fusion reactor facility called ITER is in an advanced stage of construction with the aim of demonstrating the scientific and technological success of fusion energy research for commercial production. Fusion fuel is plentiful and easily accessible. It is expected that fusion energy is the pathway towards energy security for thousands of years. Nuclear fission and fusion reactors do not emit greenhouse gases into the atmosphere and play a major role in mitigating climate change.

Does nuclear energy consumption mitigate carbon emissions in leading countries by nuclear power consumption? Evidence from quantile causality approach

Abstract: Nuclear energy has sparked international attention as one of the most important strategies for reducing emissions thanks to its ability to provide low-carbon power. Based on this interesting fact, the current research explores the effect of nuclear energy on CO2 emissions in the leading countries by nuclear power consumption using a quarterly dataset from 1990 to 2019. The study employs the quantile-on-quantile (QQ) estimator, which accounts for both non-parametric and conventional analyses and enhances the provision of unbiased and consistent estimates. In addition, the Granger causality in quantiles approach is adopted to assess the causality in quantiles between the variables of investigation. The outcomes from the QQ estimator reveals that in the majority of the quantiles, nuclear energy contributes to decreased degradation of the environment in the USA, France, Russia, South Korea, Canada, Ukraine, Germany, and Sweden. Contrawise, the feedbacks from Spain and China expose that Nuclear Energy Consumption (NUC) contributes to the deterioration of the environment. Moreover, the outcomes of the causality test disclose that nuclear energy and CO2 emissions can predict each other in the majority of the quantiles. The findings above provide profound ramifications for policymakers planning nuclear energy and CO2-emission policies towards achieving sustainable environment in the sample countries and beyond..

Investigation into the Current State of Nuclear Energy and Nuclear Waste Management—A State-of-the-Art Review

Abstract: Nuclear power can replace fossil fuels and will have a decisive impact on the change in the approach to conventional energy. However, nuclear (or radioactive) wastes are produced by the operation of the nuclear reactors should be safely and properly disposed of. This paper assesses the uranium resources and the global state of nuclear power plants and determines the energy mixes in different countries using the most nuclear energy. Furthermore, this paper analysed the nuclear waste management and disposal and the depletion of abiotic resources, and the primary energy sources of a basic production process using electricity mix and nuclear electricity for a basic production (PET bottle manufacturing) process. The life cycle assessment was completed by applying the GaBi 8.0 (version 10.6) software and the CML method. In this study, we limit our discussion to high-level nuclear waste (HLW) and spent nuclear fuel (SNF) waste. We do not consider waste generated from uranium mining and milling, which is usually disposed of in near-surface impoundments close to the mine or the mill. The investigation of waste management methods is limited to European countries. This research work is relevant because determining abiotic resources is important in a life cycle assessment and current literature available on LCA analysis for nuclear powers remains under-developed. These results can guide and compare manufacturing processes involving a nuclear electricity and electricity grid mix input. The results of this research can be used to develop production processes using nuclear energy with lower abiotic depletion impacts. This research work facilitates the industry in making predictions for a production-scale plant using an LCA of production processes with nuclear energy consumption.

Nuclear waste from small modular reactors

Abstract: Significance Small modular reactors (SMRs), proposed as the future of nuclear energy, have purported cost and safety advantages over existing gigawatt-scale light water reactors (LWRs). However, few studies have assessed the implications of SMRs for the back end of the nuclear fuel cycle. The low-, intermediate-, and high-level waste stream characterization presented here reveals that SMRs will produce more voluminous and chemically/physically reactive waste than LWRs, which will impact options for the management and disposal of this waste. Although the analysis focuses on only three of dozens of proposed SMR designs, the intrinsically higher neutron leakage associated with SMRs suggests that most designs are inferior to LWRs with respect to the generation, management, and final disposal of key radionuclides in nuclear waste.

The Private and External Costs of Germany’s Nuclear Phase-Out

Abstract: Many countries have phased out nuclear power in response to concerns about nuclear waste and the risk of nuclear accidents. This paper examines the shutdown of more than half of the nuclear production capacity in Germany after the Fukushima accident in 2011. We use hourly data on power plant operations and a machine learning approach to estimate the impacts of the phase-out policy. We find that reductions in nuclear electricity production were offset primarily by increases in coal-fired production and net electricity imports. Our estimates of the social cost of the phase-out range from 3-8 billion euros per year. The majority of this cost comes from the increased mortality risk associated with exposure to the local air pollution emitted when burning fossil fuels. Policymakers would have to significantly over-estimate the risk or cost of a nuclear accident to conclude that the benefits of the phase-out exceed its social costs. We discuss the likely role of behavioural biases in this setting, and highlight the importance of ensuring that policymakers and the public are informed about the health effects of local air pollution.

Recent Trends in Advanced Radiation Shielding Concrete for Construction of Facilities: Materials and Properties

Abstract: Nuclear energy offers a wide range of applications, which include power generation, X-ray imaging, and non-destructive tests, in many economic sectors. However, such applications come with the risk of harmful radiation, thereby requiring shielding to prevent harmful effects on the surrounding environment and users. Concrete has long been used as part of structures in nuclear power plants, X-ray imaging rooms, and radioactive storage. The direction of recent research is headed toward concrete’s ability in attenuating harmful energy radiated from nuclear sources through various alterations to its composition. Radiation shielding concrete (RSC) is a composite-based concrete that was developed in the last few years with heavy natural aggregates such as magnetite or barites. RSC is deemed a superior alternative to many types of traditional normal concrete in terms of shielding against the harmful radiation, and being economical and moldable. Given the merits of RSCs, this article presents a comprehensive review on the subject, considering the classifications, alternative materials, design additives, and type of heavy aggregates used. This literature review also provides critical reviews on RSC performance in terms of radiation shielding characteristics, mechanical strength, and durability. In addition, this work extensively reviews the trends of development research toward a broad understanding of the application possibilities of RSC as an advanced concrete product for producing a robust and green concrete composite for the construction of radiation shielding facilities as a better solution for protection from sources of radiation. Furthermore, this critical review provides a view of the progress made on RSCs and proposes avenues for future research on this hotspot research topic.

Control automation in the heat-up mode of a nuclear power plant using reinforcement learning

Abstract: Next-generation nuclear instrumentation and control technology is aimed at higher levels of automation and lower operation burden. In recent years, studies have been conducted to contribute to the operation of power plants using artificial intelligence technology. This paper proposes an automatic control method for plant heat-up mode using deep reinforcement-learning technology as a basic study for plant automation. First, the existing compact nuclear simulator (CNS) is expanded to enable reinforcement learning, and key elements for reinforcement learning are designed to be suitable for the heat-up mode. A deep neural-network structure and a CNS deep reinforcement-learning mechanism are then presented for automatic control. The experimental results demonstrate that deep reinforcement-learning has the potential to perform automatic control operation.

Capital cost estimation for advanced nuclear power plants

Abstract: The first-of-a-kind (FOAK) nuclear plants built in the last 20 years are 2X over budget and schedule in the US and some European countries. One of the nuclear industry's proposed remedies is the small modular reactor (SMR). SMR designs leverage five factors to be more economically competitive than large reactors: 1) multiple units; 2) increased factory production and learning; 3) reduced construction schedules; 4) plant design simplification and 5) unit timing. There are currently no bottom-up studies that quantitatively account for these factors and compare different near-term light water reactor SMRs with Gen III + large plants. This work presents a nuclear plant cost estimating methodology using a detailed bottom-up approach for over 200 structures, systems, and components. The results compare relative costs for two large pressurized water reactors, one with active safety and one with passive safety, to two SMR designs, one with multiple reactor power modules and one with a single reactor module. Passive safety systems showed noticeable savings at both the large and small-scale reactors. The power uprating of an SMR by 20% resulted in ∼15% savings in the overnight unit capital cost. Overall, if built by an inexperienced vendor and work force, the two SMRs' overnight costs were higher than large reactors, since significant on-site labor still remains while losing economy of scale. However, the single-unit SMR had significantly less total person-hours of onsite labor, and if built by an experienced workforce, it could avoid cost-overrun risks associated with megaprojects.