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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 397 records · Page 22

Dynamic modeling and simulation of pressure swing adsorption processes using toPSAil

Pressure swing adsorption (PSA) has attracted significant recent interest for chemical process intensification due to its potential for high energy efficiency and amenability to small, modular designs. However, the lack of simulation tools that are readily available, transparent, and trusted, has been identified as a serious impediment to widespread adoption of PSA, as well as to further research on PSA modeling, numerical solution, optimization, and control. This paper presents a complete framework for dynamic modeling and simulation of PSA processes and its implementation in an open-source simulator called toPSAil. Further, the presentation is tutorial and includes many modeling and implementation details often overlooked in existing literature. Novel methods are presented for handling flow reversals and implementing various pressure–flow relationships, along with controlled boundary conditions. Finally, the code contains several innovations designed to improve efficiency and reduce the extensive trial-and-error tuning often required to produce a working PSA cycle.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Comprehensive assessment of deep reinforcement learning approaches for economic dispatch in nuclear-driven microgrids

As the electrical grid integrates more variable renewable energy sources such as wind and solar, the demand for distributed and flexible systems to address this increased variability becomes critical. Nuclear-driven microgrids provide a promising solution by offering stable generation to complement intermittent renewables, ensuring grid reliability and operating efficiency. This paper proposes a recurrent deep reinforcement learning framework for optimal economic dispatch in a nuclear-powered microgrid integrating renewable energy sources, small modular reactors, battery storage systems, and balance-of-plant dynamics. A three-agent control architecture is developed, where demand and renewable energy agents act as forecasters, and a reinforcement learning-based dispatch agent performs real-time energy allocation. A nonlinear programming formulation is first used to generate an optimal baseline for benchmarking. The proposed dispatch controller, based on Proximal Policy Optimization enhanced with Long Short-Term Memory networks, exploits temporal correlations in system dynamics by taking advantage of the time series used as inputs to improve policy robustness under uncertainty. Comparative analysis against established deep reinforcement learning methods, including Proximal Policy Optimization with a feedforward architecture, Soft Actor-Critic, and Twin Delayed Deep Deterministic Policy Gradient, demonstrates superior performance. Numerical results indicate that the proposed controller achieves a 0.39% cost reduction relative to the nonlinear programming benchmark and outperforms other learning-based methods by generating additional revenue of up to 0.35%. All reinforcement learning controllers compute dispatch actions in less than 0.3 s, resulting in a computational speedup of more than three orders of magnitude over the nonlinear programming baseline. The findings of this paper highlight their applicability for real-time operation and control in nuclear-integrated microgrids under volatile operating conditions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Regional Analysis of Building Distributed Energy Costs and CO2 Abatement: A U.S. - China Comparison

The following paper conducts a regional analysis of the U.S. and Chinese buildings? potential for adopting Distributed Energy Resources (DER). The expected economics of DER in 2020-2025 is modeled for a commercial and a multi-family residential building in different climate zones. The optimal building energy economic performance is calculated using the Distributed Energy Resources Customer Adoption Model (DER CAM) which minimizes building energy costs for a typical reference year of operation. Several DER such as combined heat and power (CHP) units, photovoltaics, and battery storage are considered. The results indicate DER have economic and environmental competitiveness potential, especially for commercial buildings in hot and cold climates of both countries. In the U.S., the average expected energy cost savings in commercial buildings from DER CAM?s suggested investments is 17percent, while in Chinese buildings is 12percent. The electricity tariffs structure and prices along with the cost of natural gas, represent important factors in determining adoption of DER, more so than climate. High energy pricing spark spreads lead to increased economic attractiveness of DER. The average emissions reduction in commercial buildings is 19percent in the U.S. as a result of significant investments in PV, whereas in China, it is 20percent and driven by investments in CHP. Keywords: Building Modeling and Simulation, Distributed Energy Resources (DER), Energy Efficiency, Combined Heat and Power (CHP), CO2 emissions 1. Introduction The transition from a centralized and fossil-based energy paradigm towards the decentralization of energy supply and distribution has been a major subject of research over the past two decades. Various concerns have brought the traditional model into question; namely its environmental footprint, its structural inflexibility and inefficiency, and more recently, its inability to maintain acceptable reliability of supply. Under such a troubled setting, distributed energy resources (DER) comprising of small, modular, electrical renewable or fossil-based electricity generation units placed at or near the point of energy consumption, has gained much attention as a viable alternative or addition to the current energy system. In 2010, China consumed about 30percent of its primary energy in the buildings sector, leading the country to pay great attention to DER development and its applications in buildings. During the 11th Five Year Plan (FYP), China has implemented 371 renewable energy building demonstration projects, and 210 photovoltaics (PV) building integration projects. At the end of the 12th FYP, China is targeting renewable energy to provide 10percent of total building energy, and to save 30 metric tons of CO2 equivalents (mtce) of energy with building integrated renewables. China is also planning to implement one thousand natural gas-based distributed cogeneration demonstration projects with energy utilization rates over 70percent in the 12th FYP. All these policy targets require significant DER systems development for building applications. China?s fast urbanization makes building energy efficiency a crucial economic issue; however, only limited studies have been done that examine how to design and select suitable building energy technologies in its different regions. In the U.S., buildings consumed 40percent of the total primary energy in 2010 [1] and it is estimated that about 14 billion m2 of floor space of the existing building stock will be remodeled over the next 30 years. Most building?s renovation work has been on building envelope, lighting and HVAC systems. Although interest has emerged, less attention is being paid to DER for buildings. This context has created opportunities for research, development and progressive deployment of DER, due to its potential to combine the production of power and heat (CHP) near the point of consumption and delivering multiple benefits to customers, such as cost

25 ENERGY STORAGE↗

Dynamic Analysis of Hybrid Energy Systems under Flexible Operation and Variable Renewable Generation -- Part I: Dynamic Performance Analysis and Part II: Dynamic Cost

Dynamic analysis of hybrid energy systems (HES) under flexible operation and variable renewable generation is considered in order to better understand various challenges and opportunities associated with the high system variability arising from the integration of renewable energy into the power grid. Unique consequences are addressed by devising advanced HES solutions in which multiple forms of energy commodities, such as electricity and chemical products, may be exchanged. Dynamic models of various unit operations are developed and integrated within two different HES options. One HES option, termed traditional, produces electricity only and consists of a primary heat generator (PHG) (e.g., a small modular reactor), a steam turbine generator, a wind farm, and a battery storage. The other HES option, termed advanced, includes not only the components present in the traditional option but also a chemical plant complex to repurpose excess energy for non-electricity services, such as for the production of chemical goods (e.g., transportation fuel). In either case, a given HES is connected to the power grid at a point of common coupling and requested to deliver a certain electricity generation profile as dictated by a regional power grid operator based on a predicted demand curve. Dynamic analysis of these highly-coupled HES are performed to identify their key dynamical properties and limitations and to prescribe solutions for best managing and mitigating the high variability introduced from incorporating renewable energy into the energy mix. A comparative dynamic cost analysis is also conducted to determine best HES options. The cost function includes a set of metrics for computing fixed costs, such as fixed operations and maintenance (O&M) and overnight capital costs, and also variable operational costs, such as cost of variability, variable O&M cost, and cost of environmental impact, together with revenues. Assuming different options for implementing PHG (e.g., natural gas, coal, nuclear), preliminary results identify the level of renewable penetration at which a given advanced HES option (e.g., a nuclear hybrid) becomes increasingly more economical than a traditional electricity-only generation solution. Conditions are also revealed under which carbon resources may be better utilized as carbon sources for chemical production rather than as combustion material for electricity generation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Nuclear—thermal energy storage configurations for industrial combined heat and power supply—conceptual and thermodynamic study with high temperature gas-cooled reactor

Nuclear systems are promising candidates for delivering resilient heat and power for future energy security and independence. Traditionally, nuclear plants have been used for baseload electricity production and cogeneration of heat has seen relatively limited application utilizing typically only small portion of a reactor's thermal output. This paradigm may shift due to the increasing penetration of intermittent renewables and need for resource flexibility, various decarbonization efforts aimed at both electricity and heat demands, along with the perspective of small modular nuclear reactor applications, which can be sized based on local industrial needs. Here, this study provides a comprehensive guide for the nuclear and industrial sectors, emphasizing controllability in the combined heat and power configuration options for high temperature gas-cooled reactor and process steam supply. It investigates the integration of thermal energy storage to improve nuclear energy's responsiveness to varying industrial demands. The study emphasizes placing thermal energy storage between the nuclear primary loop and steam cycle to achieve greater efficiency and flexibility in power and heat output, surpassing traditional combined heat and power systems and avoiding efficiency losses seen in other thermal energy storage integration approaches.

combined heat and power (CHP)↗

The pursuit of net-positive sustainability for industrial decarbonization with hybrid energy systems

We report signatories of the Paris Agreement are set to miss their climate targets. The net-zero pledges announced to date across many countries and private industries are insufficient to achieve carbon neutrality, which requires implementation of far-reaching and significantly scaled-up climate-positive actions. All technology options that pertain to deep decarbonization and carbon removal must be part of the mitigation portfolio. Transformative action plans must be established in which every individual/organization around the globe is an actor of changes in relation to net-zero goals. Such plans must involve governmental policy support but also encourage voluntary efforts to boost innovations, investments, initiatives, and behavioral changes. Recognition of these efforts is made quantifiable with the concepts of carbon handprint and net positivity. This paper presents a carbon handprint perspective on characterizing the environmental benefits of hybrid energy systems (HESs)—a widely applicable solution to cleaner production leveraging the capabilities of a portfolio of low-carbon energy sources—that provide heat and electricity to industrial processes. First, the carbon handprint and net positivity concepts and their calculation approach are introduced. The state of the art of HES-enabled industrial cogeneration is then surveyed, and the greenhouse gas emission intensities of different energy sources that power HESs are compared. Next, drawing on a case study about a US chemical facility's voluntary initiative to explore replacing its fossil fuel–based cogeneration infrastructure with a clean energy–generated HES, several technically viable scenarios are evaluated—especially those with small modular nuclear reactors—to illustrate how the positive-thinking handprint approach helps encourage and inform the search for widespread influence pathways in pursuit of net-positive sustainability. Finally, current knowledge gaps in the case study are identified, and opportunities to scale up the proposed handprint-based analysis are outlined with consideration of an expanded role of HESs in fulfilling climate objectives.It is envisioned that like-minded decision makers in the industry sector and beyond will adopt this perspective and act synergistically to enhance their environmental stewardship through voluntary actions and make greater contributions to the planet's climate future.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Irradiation of UC1+x kernels using the MiniFuel vehicle: Microstructure, phase analysis, and initial post-irradiation examination

Uranium carbide is a candidate fuel form for a wide range of advanced reactors, including larger Generation IV reactors as well as small modular reactors and microreactors. However, its commercial deployment timeline faces challenges via traditional qualification approaches. To address this issue, an accelerated fission rate irradiation test was performed to collect basic fuel performance data to inform fuel performance models and potential future integral tests. Hyperstoichiometric UC (UC1+x) kernels were irradiated in the High Flux Isotope Reactor using the MiniFuel irradiation vehicle. The test matrix spanned two temperature regimes (700 °C and 800 °C) and burnup levels (1.8 % FIMA and 2.8 % FIMA). Between 21 and 63 kernels were tested at each unique temperature and burnup condition. As-fabricated microstructural analysis revealed a multiphase composition with UC, UC2, UC2−y, and U-C-O bearing phases for the irradiated kernels. Following irradiation, fission gas release, swelling, and microstructures were analyzed. Measured fission gas release was below 5 % for all irradiation conditions, reaching a maximum at the highest temperature and burnup condition. A binary swelling response was observed; the lower burnup and temperature conditions resulted in negligible swelling, but the higher burnup and temperature conditions produced significant anisotropic swelling and densification in a subset of kernels. The basic microstructural exams of kernels following irradiation were not capable of showing a correlation between kernels that exhibited excessive swelling and those that did not. Characterization of a subset of samples using the Advanced Photon Source and more detailed microstructural examination of unirradiated kernels revealed that a subset of kernels contained very high UC2 phase fractions. The anomalous swelling response is hypothesized to have been driven by this chemical variation. The results of this irradiation highlight the potential of accelerated fission rate irradiation testing to explore such behaviors and inform the development of fuel specifications.

Adorno Lopes, Denise [ORNL] (ORCID:000900023705987↗

Nuclear safety Enhanced: A Deep dive into current and future RAVEN applications

As the horizon of nuclear energy expands with the advent of small modular reactors, IV generation reactors, and fusion reactors, there is a growing perspective that the licensing process could benefit from a more comprehensive approach. Moving beyond traditional deterministic and PRA analysis might pave the way for a novel safety analysis paradigm propelled by the increasing computational power at our disposal. This paper explores different methodologies that can improve the outcomes of nuclear safety analysis. These range from uncertainty quantification techniques, aimed at enhancing the precision of safety margins, to deploying dynamic event trees by driving system code simulations, capturing the potential evolutions of severe accidents. These methodologies introduce innovative dimensions to safety analysis, considering the consequences of postulated events and the dynamics of accident sequences. However, they also bring forth challenges, especially in managing the complexity and sheer volume of potential scenarios. The paper touches upon some strategies to counter these challenges, emphasizing the importance of adaptability and continuous evolution in the face of emerging nuclear safety concerns. Additionally, the paper sheds light on the need for advanced tools to apply these methodologies. Among these tools is RAVEN, an open-source software designed for parametric and probabilistic analyses. Its core components, including distribution, sampler, and reduced order model, enable various applications, from risk assessment and mitigation to dynamic learning and plant control logic simulations.

97 - MATHEMATICS AND COMPUTING↗

SMR safety through HTTF modeling and benchmark efforts for code validation for gas-cooled reactor applications

Accurate modeling and simulation tools for thermal-hydraulics calculations are a key element needed to design and license new advanced reactors including Small Modular Reactors (SMR) and Microreactors. Uncertainties in modeling and simulation can have significant safety and economic implications. The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a scaled integral effects experiment designed to investigate transient behavior in high-temperature gas-cooled prismatic-block nuclear reactors. High-quality measurement data is available from the HTTF that is suitable for a thermal-hydraulics code validation benchmark for gas-cooled reactor simulations. Here, this paper summarizes individual HTTF modeling efforts to date for tool validation at Idaho National Laboratory (INL), Argonne National Laboratory (ANL), Oregon State University (OSU) and Canadian Nuclear Laboratories (CNL) using system thermal-hydraulics codes, Computational Fluid Dynamics (CFD) codes and system-CFD code couplings. Also, the paper introduces the ongoing OECD Nuclear Energy Agency (NEA) High Temperature Gas Reactor Thermal-Hydraulics (HTGR T/H) benchmark that allows for better comparisons of results between different international modeling teams. The benchmark provides well defined computational problems that include code-to-code comparisons and comparisons to measured data. These problems provide an avenue for quantifying accuracy and identifying sources of uncertainty in thermal-hydraulics calculations, including in measured thermophysical properties, as part of validation for gas-cooled reactor simulation tools.

21 - SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLAN↗

BISON analyses of TRISO fuel performance, its dependence on time-at-temperature, and possible implications for fuel design and qualification

The Advanced Gas Reactor Fuel Development and Qualification (AGR) program has established a substantial technical foundation to support private entry into the U.S. high-temperature gas-cooled reactor market. However, emerging tristructural isotropic (TRISO)-fueled reactor applications include small modular reactors and microreactors with longer fuel residence times, which may expose fuels to higher time-at-temperature (TAT) values than were explored by the AGR program. Increased TAT could affect diffusive and thermomechanical behaviors such as Pd penetration, fission gas release, creep, and fission product transport. In this work, we applied multiscale best-estimate BISON fuel performance modeling to assess these effects within a representative design space based on the AGR-5/6/7 experiment and analyzed trends in predicted particle and compact fuel performance metrics with possible implications for near-term fuel design and qualification. BISON unambiguously predicted that TRISO fuel performance is sensitive to TAT. Increasing TAT was not predicted to increase the magnitude of failure-inducing tangential stresses in particle coating layers. Predictions obtained using a mechanistic model for Pd penetration indicated that penetration depth does not depend strongly on TAT. While these observations suggest that AGR testing provides a conservative upper bound for the steady-state operation of TRISO particles at lower powers and higher residence times, BISON also predicted that the release of poorly retained Ag would increase with TAT. Because these analyses applied models to extrapolate beyond the available experimental data, the authors recommend performing targeted experiments to confirm these predictions. Nevertheless, these predictions may provide reactor developers with enough confidence to make near-term design decisions associated with the potential fuel performance trade-offs of increasing TAT.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Data recovery via covert cognizance for unattended operational resilience

One of the important premises of unattended operation, a highly promoted characteristic of fission batteries and advanced microreactors, is the ability to automate the analysis of sensors data used in support of operational monitoring and control. Here, to meet this vision, this work proposes a new monitoring and data recovery paradigm to ensure resilience against data corruption which may be the result of malicious intrusion into the reactor operational network. This is paramount to ensure 100% availability under contingency scenarios such as cyberattacks. In support of this vision, earlier work has presented the concept of covert cognizance and demonstrated its mathematical ability to identify and embed cognizance parameters under the noise-dominated null space of the sensors data. This work extends this concept and applies it in real-time to demonstrate three key characteristics: zero-impact, zero-observability, and data recovery, where the first characteristic is to ensure no impact on operation, the second is immunity to discovery by pattern recognition techniques, and the third is to allow recovery of corrupt or falsified data. Recognizing that fission batteries are designed to operate under steady state most of the time, we elect to employ a small modular reactor model under transient operational conditions to demonstrate the operational resilience enabled by the covert cognizance paradigm. Specifically, the PI controller is augmented with the covert cognizance modules to develop self-awareness and enable automatic data recovery. The developed modules are expected to be equally applicable to a wide range of advanced reactor technologies relying on full or partial unattended control.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

Simulating self-powered neutron detector responses to infer burnup-induced power distribution perturbations in next-generation light water reactors

Understanding how 3D power distribution will be monitored throughout reactor core volumetric space in next-generation nuclear power reactors is crucial to the design, deployment, and licensing of these reactors. Although numerous techniques exist for 3D power distribution monitoring based on the response of both in situ and ex situ sensors currently implemented or proposed for use in the US reactor fleet, crucial details about these techniques are often unclear. The publicly available documentation does not include information such as how well these techniques are characterized and optimized in their implementations and the levels of uncertainty in the inferred 3D power distribution. The work described herein investigated a recently developed 3D power distribution inferencing method as applied to two next-generation reactor simulations: (1) the NuScale small modular reactor design and (2) the Westinghouse AP1000 design, both of which contain in-core strings of vanadium self-powered neutron detectors (SPNDs). This investigation considered a range of SPND string sensor densities, as well as a range of 3D power distribution axial segment sizes. In this work, SPND response simulation is informed by neutron flux calculations in representative homogenized cores. For the different sensor densities and power distribution axial segment sizes in these simulations, the average solution error, solver iterations, and run time were tracked to parameterize the sensor-core configuration.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Accident event progression, gaps, and key performance indicators for steam generator tube rupture events in water-cooled SMRs: A review

According to historical records of reactor-related incidents, a steam generator tube rupture (SGTR) is one of the most common occurrences at operating pressurized water reactors (PWRs). Such design-basis accidents (DBAs) could lead to a direct path for radionuclides to be released to the atmosphere via the safety and relief valves, making assessments of radionuclide discharge from operating nuclear power plants (NPPs) into the environment crucial for ensuring safety. In such analyses, the primary focus has been on the extent of radioactive release, not the potential damage to the core. Moreover, significant and timely intervention by operators is needed during the initial stages of SGTRs in order to avert overfilling of the SGs, as well as to restrict the dissemination of radioactive materials. Determining the event sequence and phases that occur during an SGTR incident in an advanced passive (e.g., AP1000) water-cooled nuclear reactor is crucial for implementing effective passive safety systems (PSSs) for a specific water-cooled small modular reactor (SMR) design. Here this study provides a comprehensive review of the accident event progression, associated physical phenomena, knowledge gaps, and key performance indicators that must be evaluated and assessed in thermal-hydraulics models, based on relevant test data, respectively.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Applying U.S. metal fuel experience to new fuel designs for fast reactors

With the increasing interest in small modular reactors or microreactors, developers are working to design and submit licensing approval requests of U–10Zr-fueled fast reactors. The developers and their proponents cite prior metal fuel experience (worldwide, but U.S. experience in particular for many developers) as the motivation and justification for their reactor concepts. The experience with metal fuel deployment in sodium-cooled fast reactors as well as the underlying irradiation testing database, provide a suitable basis for analytically justifying the use of metal fuel in new reactors. The evolution of metal fuel design and capability illustrates the importance of key fuel design parameters to consider in new applications of the prior experience: fuel smeared density, plenum-to-fuel volume ratio, the ratio of cladding radius to thickness, fuel composition, and cladding and duct materials. In-service operating and deployment conditions to be considered include fuel linear heat generation rate, fuel temperature, cladding temperature, peak burnup and peak fast fluence. Fuel designs and in-service conditions that are bounded by the database and experience are most easily addressed, but deviations from those previous parameters and conditions can be addressed by considering impacts on previously established behavior and applying other mitigating conservatisms, as appropriate. Here, the authors recommend any new deployment proceed with fuel surveillance and monitoring to mitigate risk, application of conservative measures to address uncertainties, and a fuel qualification program that addresses a range of in-service operating conditions with production fuel. The work reported should be of interest to students and regulators unfamiliar with metal fuel in fast reactors.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Investigating the impact of a multi-module operation environment on the task performance time of human operators – An explanatory study

The worldwide demand for Small Modular Reactors (SMRs) has surged in recent years due to their enhanced safety and versatility in supporting diverse industrial sectors. A unique feature of SMR operation is that a single human operator is responsible for managing multiple modules. Therefore, securing a sufficient amount of human performance data pertaining to this new environment is essential for the safe operation of SMRs. In this explanatory study, a series of experiments were conducted using the NuScale simulator, a representative SMR design, with student operators. A total of 12 student operators were assigned two types of off-normal events and asked to cope with them using paper-based procedures. Subsequently, their task performance times were compared with those of student operators responsible for a single unit based on the Task Complexity (TACOM) measure. Results indicate that the performance of student operators under the experimental conditions of this study degraded by a factor of 2 to 3, depending on the characteristics of the off-normal events.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Advanced nuclear reactor integration opportunities for the pulp and paper industry in the U.S. context: Technical perspectives, gap analysis, and preliminary technoeconomic assessment

Pulp and paper (P&P) manufacturing requires a large amount of low-pressure (LP) steam to digest, wash wood fibers and dry pulp into paper. Most of the LP steam is extracted from backpressure turbines that produce power from high-pressure (HP) steam. This HP steam is generated from burning wood waste material; bark is burned in hog boilers, and lignin is boiled in a black liquor recovery boiler. In a typical integrated P&P mill, 50–100% of the steam is produced from these sources, while additional steam is produced in natural gas (NG), fuel oil, or coal boilers. The other energy-intensive process in the plant is the chemical-recovery section (e.g., lime kiln), which requires high-temperature processing from NG combustion to retrieve and recirculate spent chemicals. This paper assesses the energy and heat demand and material balances of a typical generic kraft pulp mill, along with the nuclear heat, steam, and power integration opportunities to replace conventional combustion systems. The paper also addresses steam and electricity generation through a comprehensive technical and engineering gap analysis of five different nuclear-integration opportunities and their process economics, thus enabling the lignin and bark to be further processed into biobased chemicals or fuels, as well as the potential to reduce overall emissions from kraft pulping. Preliminary findings have shown that the P&P industry could achieve technological benefits by integrating their current manufacturing process with small modular nuclear reactors (SMNRs) on a national level. This research aims to set the path forward for a cleaner and more resilient P&P industry.

Advanced nuclear reactor↗