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At least 235 records · Page 13

Affordable Development of a Nuclear Cryogenic Propulsion Stage

The fundamental capability of Nuclear Thermal Propulsion (NTP) is game changing for space exploration. A first generation Nuclear Cryogenic Propulsion Stage (NCPS) based on NTP could provide high thrust at a specific impulse above 900 s, roughly double that of state of the art chemical engines. The foundation provided by development and utilization of a NCPS could enable development of extremely high performance systems. The role of the NCPS in the development of advanced nuclear propulsion systems could be analogous to the role of the DC-3 in the development of advanced aviation. Progress made under the NCPS project could help enable both advanced NTP and advanced Nuclear Electric Propulsion (NEP).

Houts, M. G.↗

Nuclear Cryogenic Propulsion Stage for Mars Exploration

The fundamental capability of Nuclear Thermal Propulsion (NTP) is game changing for space exploration. A first generation Nuclear Cryogenic Propulsion Stage (NCPS) based on NTP could provide high thrust at a specific impulse above 900 s, roughly double that of state of the art chemical engines. Characteristics of fission and NTP indicate that useful first generation systems will provide a foundation for future systems with extremely high performance. The role of the NCPS in the development of advanced nuclear propulsion systems could be analogous to the role of the DC-3 in the development of advanced aviation. Progress made under the NCPS project could help enable both advanced NTP and advanced Nuclear Electric Propulsion (NEP).

Houts, M. G.↗

Safe, Affordable, Nuclear Thermal Propulsion Systems

The fundamental capability of Nuclear Thermal Propulsion (NTP) is game changing for space exploration. A first generation Nuclear Cryogenic Propulsion Stage (NCPS) based on NTP could provide high thrust at a specific impulse above 900 s, roughly double that of state of the art chemical engines. Characteristics of fission and NTP indicate that useful first generation systems will provide a foundation for future systems with extremely high performance. The role of the NCPS in the development of advanced nuclear propulsion systems could be analogous to the role of the DC-3 in the development of advanced aviation. Progress made under the NCPS project could help enable both advanced NTP and advanced Nuclear Electric Propulsion (NEP).

Houts, M. G.↗

The Nuclear Cryogenic Propulsion Stage

The fundamental capability of Nuclear Thermal Propulsion (NTP) is game changing for space exploration. A first generation Nuclear Cryogenic Propulsion Stage (NCPS) based on NTP could provide high thrust at a specific impulse above 900 s, roughly double that of state of the art chemical engines. Characteristics of fission and NTP indicate that useful first generation systems will provide a foundation for future systems with extremely high performance. The role of the NCPS in the development of advanced nuclear propulsion systems could be analogous to the role of the DC-3 in the development of advanced aviation. Progres made under the NCPS project could help enable both advanced NTP and advanced Nuclear Electric Propulsion (NEP).

Houts, Michael G.↗

The Nuclear Cryogenic Propulsion Stage

The fundamental capability of Nuclear Thermal Propulsion (NTP) is game changing for space exploration. A first generation Nuclear Cryogenic Propulsion Stage (NCPS) based on NTP could provide high thrust at a specific impulse above 900 s, roughly double that of state of the art chemical engines. Characteristics of fission and NTP indicate that useful first generation systems will provide a foundation for future systems with extremely high performance. The role of the NCPS in the development of advanced nuclear propulsion systems could be analogous to the role of the DC-3 in the development of advanced aviation. Progress made under the NCPS project could help enable both advanced NTP and advanced Nuclear Electric Propulsion (NEP). Nuclear propulsion can be affordable and viable compared to other propulsion systems and must overcome a biased public fear due to hyper-environmentalism and a false perception of radiation and explosion risk.

Houts, Michael G.↗

Report Summarizing the Mechanical Properties of a Large ODS Ferritic Alloy Ingot by Forging at High Temperatures for Future Mother Tube Production

Oxide dispersion strengthened (ODS) ferritic alloys are considered the benchmark fuel cladding and core structural material in advanced nuclear energy reactors that require high-temperature strength and creep properties and resistance to radiation damage. The ODS ferritic alloys including 14YWT are produced by mechanical alloying (MA), which is time-consuming and is associated with high manufacturing costs that are not beneficial to being used in advanced nuclear energy reactors. This report summarizes the accomplishments in FY24 in the INM program for producing an ODS ferritic alloy by high-deformation, high-temperature processing of reactive and ferritic alloy powders for advanced reactor fuel cladding applications. Following four hot forging experiments, it was concluded that several significant challenges were encountered that were difficult to overcome. These challenges were related to using high annealing temperatures for pressure assisted sintering processes to produce dense microstructures, but the high annealing temperatures result in long range diffusion of Ti through the bcc Fe lattice and react with the YIG particles that are distributed on the prior surfaces of the ferritic alloy powders. In addition, it was determined that the high deformations induced by forging at high temperatures were not very effective for fracturing the reactive YIG particles into smaller particles and distributing them into the interior of the ferritic alloy powders. Spark plasma sintering was attempted for shortening the time at high temperatures, which led to full densification but the microstructure characterization results still showed that Ti atoms diffused over long distances in the bcc Fe lattice and reacted with the YIG particles. Finally, a short 30 minute high intensity ball milling experiment was conducted on blended 14WT and YIG powders for inducing severe deformations that caused the initially spherical powders of 14WT decorated with the YIG particles on the surfaces to transform to flakes and fracturing of YIG particles into smaller particles that were incorporated into the bcc Fe lattice. Two forgings were performed with the high intensity milled powders: first annealing for 20 minutes at 850ºC followed by forging and second annealing for 20 minutes at 1,100ºC followed by forging. At 850ºC, Ti atoms are effectively immobile, thus allowing for densification albeit incomplete. The deformation by forging after annealing for 20 minutes at 1,100ºC favored dynamic recrystallization processes that led to nano-size grains with very high stored energy due to high dislocation density. The corresponding VH data showed significant hardening that correlated with estimated strengthening of ~1650 MPa. This hybrid processing approach combining high intensity ball milling of powder with annealing and forging showed the most promise for producing an oxide dispersing strengthened ferritic alloy.

36 MATERIALS SCIENCE↗

A comparative study on deep learning models for condition monitoring of advanced reactor piping systems

Advanced nuclear reactors offer innovative applications due to their portability, reliability, resiliency, and high capacity factors. To operate them on a wider scale, reducing maintenance life-cycle costs while ensuring their integrity is essential. Autonomous operations in advanced nuclear reactors using augmented Digital Twin (DT) technology can serve as a cost-effective solution by increasing awareness about the system’s health. A key component of nuclear DT frameworks is the condition monitoring of safety systems, such as piping-equipment systems, which involves acquiring and monitoring the plant’s sensor data. Here, this research proposes a condition monitoring methodology utilizing deep learning algorithms, such as multilayer perceptions (MLP) and convolutional neural networks (CNNs), to detect degradation and its severity in nuclear piping-equipment systems. Sensor signals are processed to obtain the power spectral density and the Short-Time Fourier transform, and feature extraction methodologies are proposed to develop degradation-sensitive data repositories. The performance of MLP, one-dimensional (1D) CNN, and 2D CNN within the proposed condition monitoring framework is compared using a finite element model of a 3D piping system subjected to seismic loads as the application case study. Various approaches, such as dropout, k-Fold validation, regularization, and early stopping of training the network, are investigated to avoid overfitting the models to the input sensor data. The predictive capability and computational capacity of the deep learning algorithms are also compared to detect degradation in the Z-pipe system of the Experimental Breeder Reactor II (EBRII). The Z-pipe system is subjected to harmonic excitations that represent normal operating loads, such as pump-induced vibrations. The findings of the study indicate that the proposed artificial intelligence (AI)-driven condition monitoring framework demonstrates superior prediction accuracies with a 2D CNN, whereas the MLP exhibits higher computational efficiency.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Visualization Tool for Comparing Low-Carbon Energy Options

This project developed a web based visualization tool for comparing current and future nuclear fuel cycle options to low-carbon and conventional energy technologies in the United States. While nuclear power is well established as the gold-standard for baseload power production and also as the technology with the lowest overall carbon intensity of any commercial form of electricity generation. This project develop a web-based tool for electricity producers and consumers to compare renewable and conventional energy technologies to the conventional and advanced nuclear fuel cycle options. The work leveraged data on land use, carbon intensity, unit cost and pricing data for renewables from the open literature. Input data from the Advanced Fuel Cycle Cost Basis report will be used for current and advanced nuclear power systems. We coupled these data to energy flow and lifecycle models for user-selected energy generation and storage types. We will display economic comparisons from the perspectives of generators and consumers, as well as carbon production, land use, and reliability comparisons.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Creating a Simulation Platform for Research and Development of Advanced Control Methods

Advanced nuclear reactors are essential to meet the changing energy requirements throughout both the United States and the rest of world. In addition to other features, they are designed to enable deployment in remote locations and operate in a fully (or near-fully) autonomous manner, which will require a new control paradigm. To realize autonomously operating reactors, the U.S. Department of Energy’s Nuclear Energy Enabling Technologies Advanced Sensors and Instrumentation (NEET ASI) program conducts research and development into the enabling technologies and methods needed, including digital twins, machine learning, and risk modeling, in addition to various types of control methods. These technologies and methods are the key foundations needed to achieve fully autonomous systems. To develop and evaluate the technologies and methods necessary for achieving autonomous operations, it is critical to identify a software tool capable of integrating all the required elements. In surveying the available solutions, no software platforms were identified that could accomplish what was needed without introducing drawbacks. This challenge was the motivation for the current effort: to develop a software platform that can seamlessly integrate autonomouscontrol-enabling technologies and methods, allowing for accelerated research and development and transfer of ideas. The resulting platform, known as the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND), is Python-based, and leverages open-source tools to provide flexibility and facilitate building upon prior research. It is designed to enable advanced reactor developers to deploy and test advanced control technologies and methods coupled with their own models, solutions, and hardware. Given the substantial undertaking of developing such a platform, the current effort focused on laying down scalable, flexible software foundations and infrastructure, then demonstrating the platform via a use case. These foundations included developing generic modules, which contain the base variable and system blocks (the information and functional building blocks, respectively, that can be used to design a simulation) and the data handling and storage blocks needed to exchange information between the various blocks; as well as enablingtechnology-specific modules. This platform was evaluated via a use case, which was to simulate and control a process for the Microreactor Automated Control System (MACS) test bed. While MACS is not currently directly coupled to any specific microreactor physics, it was initially developed in concert with the Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor, and so the MARVEL physics are used here. As part of this use case, several enabling-technology-specific blocks within COMMAND were integrated, including a proportional integral derivative (PID) control block, a Reactor Excursion and Leak Analysis Program (RELAP5-3D) block, and an anomaly detection block. The COMMAND software platform was successfully demonstrated to achieve the scalability and flexibility objectives of this effort and will be leveraged by the program’s research efforts to advance state of the art control methodologies towards autonomous operations of advanced reactors. As new use cases are created and implemented, it is anticipated that COMMAND will continue to grow and evolve to meet new requirements.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Practical Insights on Applying Simulation-Based Control Methods in Experimental Studies

Advanced nuclear reactors are crucial to the future of energy both in the United States and around the globe. In contrast to the current operating fleet, they are characterized as being deployable in remote locations and able to operate in semi-autonomous or autonomous fashion. This leap forward necessitates a new reactor control paradigm. Because advanced nuclear reactors are still under development in the United States, the creation of new control methods to achieve autonomous operations has been based on systems modeling and simulation. However, an important factor in successfully deploying these new control methods is the ability to seamlessly transition from simulation environments to real-world settings. Control methods tested in both simulation and experimental settings need to be investigated in the context of advanced reactor applications. This work developed a series of simple controllers for Idaho National Laboratory (INL)’s Microreactor Applications Research Validation and Evaluation (MARVEL) microreactor operating in load-following scenarios. These controllers were tested in both simulation and experimental settings, and a comparative performance analysis was performed. The simulation tests leveraged the Control and Optimization Modular Modeling Application for Nuclear Deployment (COMMAND) software developed in a previous stage of the current effort, along with the MARVEL Reactor Excursion and Leak Analysis Program (RELAP5-3D) and Monte Carlo N-Particle (MCNP) models. The experimental tests leveraged the COMMAND software, MARVEL models, and the U.S. Department of Energy Microreactor Program’s Microreactor Automated Control System (MACS). MACS was developed to serve as a control method testbed. It was customized to mirror the MARVEL microreactor, and COMMAND enabled MACS to emulate the physics of MARVEL. The load-following controller was developed using the simulation platform, with efforts to emulate real systems by introducing actuator saturation and noise. These factors were incrementally accounted for in the controller design. After finalizing the controller design, it was implemented with the experimental setup. The experimental conditions tested included an initial test under conditions similar to the final simulation test, and two additional scenarios. The first scenario introduced additional actuator saturation to account for equipment aging over time, which was unknown to the controller. The second scenario introduced sensor delay, a phenomenon anticipated with the use of remote operations or wireless communication in advanced reactors. These tests revealed several notable differences. While the controller performed well in simulation, it exhibited several limitations when transitioning to hardware. The main challenges involved maintaining the steady-state target power, as evidenced by larger error values between the true reactor power and setpoint power, as well as persistent oscillations in controlled reactor power. These issues could lead to unacceptable transient conditions in real reactor testing. Introducing actuator aging and stochastic delays in the experimental setup significantly impacted controller performance, resulting in increased overshoot and undershoot, and exacerbated error and oscillations previously mentioned. These findings underscore the importance of experimental testbeds for testing and validating control methods, as controllers developed using only theory and/or simulation may perform unexpectedly when applied to actual hardware. This research emphasizes the need for an experimental testbed for achieving such validation.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

An Overview of Emerging Nuclear Sensor Technologies: Challenges, Advancements and Applications

Nuclear sensors are essential for detecting and measuring nuclear radiation in various applications, including nuclear power plants, medical imaging, and environmental monitoring. Traditional nuclear sensors have served these fields for decades, but recent advancements in emerging sensor technologies offer novel improvements in accuracy, sensitivity, and reliability. This review presents an up-to-date overview of recent progress in the advancements of nuclear sensor technologies, their diverse applications, challenges in implementation, and opportunities for future research.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Employing MACS/ViBRANT as a Surrogate MARVEL Reactor for Startup Reactivity Tuning and Supervisory Control Processes

Advanced nuclear reactors are a key part of the future of nuclear energy both in the United States and globally. They offer unique benefits for various energy-demanding applications, including use in remote locations, compact size, modular manufacturing, remote monitoring, low and/or variable power rating operation, and reliance on novel technologies to enhance operational safety. To achieve economic feasibility, advanced reactors must significantly reduce their workforces in comparison with the current fleet. Achieving this reduction will occur through reducing staff workloads using technology to achieve autonomous or semi-autonomous operations, demonstrated by comprehensive testing and validation activities. These operations will require both software and hardware platforms during the design and testing phases. While simulations are useful during the design phase, their performance can significantly deviate during actual deployment on hardware. This report presents the outcomes of a collaborative technical initiative between the U.S. Department of Energy (DOE) Microreactor Program (MRP) and Advanced Sensors and Instrumentation (ASI) Program. The collaboration utilized the Microreactor Automated Control System (MACS) hardware platform to bridge the gap between theoretical reactor design and actual startup and control operations. Two key use cases were investigated: facilitating the startup testing period and demonstrating supervisory control. The first use case details the key Microreactor Applications Research Validation and Evaluation (MARVEL) reactor startup physics testing activities conducted using the MACS platform. These activities included drum worth measurements, shutdown margin assessment, temperature feedback analysis, and scram time evaluation, as well as unique testing that would apply to the MARVEL reactor to demonstrate the testing methodologies in a low-risk environment. The MACS platform, serving as a surrogate representation of the MARVEL reactor, proved instrumental in performing these tests. The exercise revealed aspects that led to optimized processes, refined hardware design, and enhanced base software capabilities. By maturing methods and technologies in this manner, the initiative promises to reduce wasted time in the actual on-site reactor deployment effort, thereby saving significant time and resources. The second use case focuses on the development and implementation of supervisory control methods aimed at managing core tilt, which can result from asymmetrical operations or manufacturing imperfections in fuel rods or reactivity control devices. A key objective was to assess and compare the use of artificial intelligence (AI) for supervisory control. The effort aimed to define the role of supervisory control to enhance performance without risking control instability. This effort explored three distinct approaches: rules-based (RB) methods, optimization techniques, and reinforcement learning (RL) algorithms. Each approach was evaluated for its ease of implementation, its usability, and its effectiveness in responding to asymmetries in neutron flux. Comparative analysis of these approaches provided valuable insights into their applicability and effectiveness, offering a robust framework for advanced reactor operations. Together, these two use cases highlight the potential of hardware test beds to help streamline the design, operation, and control of advanced nuclear reactors. This collaborative effort underscores the importance of continued innovation and experimentation in achieving the next generation of safe, reliable, and economically viable nuclear energy solutions.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

ACCELERATING MICROREACTOR DEVELOPMENT AND DEPLOYMENT THROUGH JOINT PUBLIC TEST BEDS AND PRIVATE ADVANCED REACTOR DEVELOPMENT

The United States Department of Energy (DOE) has funded the National Reactor Innovation Center (NRIC) to accelerate the development and commercialization of small modular reactors and other advanced reactor technologies. As part of this effort NIRC is building two strategic assets at the Idaho National Laboratory (INL) to facilitate public-private partnerships for the development and testing of advanced nuclear microreactors and Small Modular Reactors (SMR). One will provide a safe, secure, and affordable location for High-Assay Low Enriched Uranium (HALEU) fueled reactors and a second for Highly Enriched Uranium (HEU) fueled reactors. Together these testbeds fill a nuclear testing infrastructure gap. The availability of such comprehensive testing facilities at the national labs eliminates the significant financial and operational burdens associated with each developer building and licensing their own test facilities. Consequently, this approach will not only accelerate technological innovation and reduce time-to-market for advanced nuclear solutions but it also underscores the DOE's commitment to fostering an ecosystem where nuclear energy will thrive as a clean, reliable, and efficient source of power. The Demonstration of Microreactor Experiments (DOME) and Laboratory for Operations and Testing in the United States (LOTUS) have planned availability in 2026, and 2027 respectively.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

NRIC Asset Suite Engineering and Operations Data Integration Plan

The National Reactor Innovation Center (NRIC), established by the U.S. Department of Energy (DOE) in August 2019, accelerates the demonstration and deployment of advanced nuclear energy through its mission to inspire stakeholders and the public, empower innovators, and deliver successful outcomes through efficient coordination of partners and resources. NRIC is a national program led by Idaho National Laboratory (INL), enabling collaborators to harness the world-class capabilities of the U.S. National Laboratory System. Committed to demonstrating advanced reactors by the end of 2025, NRIC is designed to bridge the gap between research, development, and the marketplace to help convert some of the Nation’s most promising advanced nuclear reactors into commercial applications by 2030. To meet these needs, NRIC is developing two reactor demonstration test beds at Idaho National Laboratory (INL), the Laboratory for Operation and Testing in the United States (LOTUS) and the Demonstration and Operation of Microreactor Experiments (DOME) test bed. Each test bed involves the modification of existing facilities at INL’s Materials and Fuels Complex (MFC). Retrofitting these facilities to accommodate novel reactors, as well as subsequent but similar NRIC projects, is a non-trivial engineering task and is expected to generate a significant amount of new and revised documentation. Leveraging digital engineering practices, this documentation will be managed in a purpose-built data management tool to facilitate origination, review, and approval while coordinating with the design contractor. The subsequent upload and review of documentation to INL’s existing document control system comprises a long and unnecessarily manual task. An opportunity exists to automate this upload process and save job-hours while continuing to adhere to INL/MFC document management procedures.

99 GENERAL AND MISCELLANEOUS↗

Report on Preliminary Detailed Experimental Plan for Neutron Irradiation of A709 at ATR and HFIR

Advanced nuclear power technologies will use higher temperatures as a means to extract energy at a higher efficiency than current plants and therefore put a larger demand on the structural materials. Improved performance of structural materials could enable greater safety margins, longer plant lifetimes, and reduce maintenance costs. Alloy 709 is championed as the next generation of austenitic alloys for advanced nuclear reactors. In parallel to the ASME code case pursued, the AMMT program is initiating a neutron irradiation campaign to provide first-of-a-kind engineering data to establish operational design parameters and how the mechanical response is modified by environmental factors. This document refines the AMMT neutron irradiation campaign to a 4 year program to support the generation of creep knockdown factors for Alloy 709 and welded Alloy 709. The campaign is divided among two national laboratories, Oak Ridge National Laboratory and Idaho National Laboratory, to use the strengths of each laboratory. Through a cooperative plan, time-independent properties and time-dependent properties will be obtained across a large temperature window, nominally 300°C to 800°C, damage levels up to 10 dpa, and with and without the impacts of transmutation produced helium.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Progress on Producing an ODS Ferritic Alloy by High Deformation Processing of Reactive Powders

Oxide dispersion-strengthened (ODS) ferritic alloys, such as 14YWT, are considered as benchmarks for fuel cladding and core structural materials in advanced nuclear energy reactor systems that require high temperature strength and creep properties as well as resistance to radiation damage. Unfortunately, the popular processing method of mechanical alloying (MA) is time-consuming, incurs high manufacturing costs, and typically produces anisotropy in the microstructure and mechanical properties of ODS ferritic alloys. These considerations hinder their acceptance in many high-performance, high-temperature materials for advanced nuclear energy reactors. This work package is pursuing an alternative solid-state processing to MA involving high deformation at high temperatures for producing an ODS ferritic alloy for fuel cladding. This report summarizes the concept for this processing method and the progress toward selecting the reactive and ferritic alloy powders, preparing 316L stainless steel cans for filling with blended powder followed by degassing, and choosing the heat treatments and forging parameters for performing the first two forging experiments. The preliminary results of optical microscopy performed on polished samples that were cut in three orthogonal directions revealed remnant porosity in both samples. The analysis of the porosity using ImageJ revealed a lesser amount of ~2.49% in the HiLoMe-1 sample that was processed with the three heat treatments and forging parameters compared to ~5.70% for the Hi-1 sample that was processed with only the first sintering heat treatment and forging parameter. These initial results will provide insights that can be leveraged to improve the densification of the powders in future forging experiments that will be continued into FY24 for determining the optimum heat treatments and forging parameters coupled with detailed microstructure characterization studies for producing the ODS ferritic alloy.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Recent Improvements in Pronghorn for Advanced Reactor Modeling

Pronghorn is a thermal-hydraulics computational tool developed using the Idaho National Laboratory's Multiphysics Object-Oriented Simulation Environment (MOOSE). It is designed to support Computational Fluid Dynamics (CFD) modeling, ranging from subchannel and porous media analysis to Reynolds Averaged Navier-Stokes (RANS) turbulence modeling. As an integral part of the MOOSE-based suite of tools, Pronghorn seamlessly couples with other MOOSE-based applications to simulate a variety of physical phenomena. This article highlights recent significant enhancements to Pronghorn's CFD modeling capabilities and demonstrates their application to advanced nuclear reactor designs. The recent improvements in Pronghorn primarily focus on modifications to its turbulence modeling capabilities, near-wall corrections and numerical schemes. In terms of turbulence modeling, the two-equation $k-\epsilon$ and $k-\omega$ SST models have been implemented and validated with both equilibrium and non-equilibrium wall treatments. Additionally, corrections for wall roughness, and curvature, and wall-channeling in pebble beds have been introduced in the near-wall modeling. These developments enable more accurate simulations of advanced nuclear reactors. Two case studies are presented in this work: a pool-type Molten Chloride Reactor and a salt-cooled Pebble-Bed High Temperature Reactor. In both cases, the previous models in Pronghorn are compared with the new implementations, demonstrating the improved accuracy achieved with the updated models.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Optimization of the FRIB beam dump: a hybrid genetic algorithm and reinforcement learning approach

The operational envelope of high-power-density systems, such as particle accelerators and advanced nuclear energy systems, is critically constrained by the need to manage extreme thermal loads. To address this, we present a novel hybrid optimization framework combining a genetic algorithm (GA) with a soft actor-critic (SAC) deep reinforcement learning agent. This framework was applied to a practical high-heat-flux problem: redesigning the beam dump at the Facility for Rare Isotope Beams (FRIB) for a power upgrade from 20 kW to 50 kW. The resulting design, validated by three-dimensional conjugate heat transfer simulations, suppresses hazardous hot spots and yields a markedly more uniform temperature distribution. This provides a robust operating margin, increasing the average power-handling capability by 72% relative to the current design, demonstrating the framework’s potential to solve complex thermal management challenges in both accelerator technology and advanced nuclear systems.

Accelerator↗