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DOE OSTI2026

Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels (Final Scientific/Technical Report)

The project, "Advanced Facility Design and AI/ML Enabled Safeguards to Establish Secure, Economical Recycling of Fast Reactor Fuels," represents a significant advancement in nuclear fuel recycling technology. It integrates cutting-edge multimodal sensor fusion, machine learning (ML), and digital twin (DT) technologies to address challenges in material safeguarding, process optimization, and regulatory compliance for pyroprocessing facilities. This research has significantly enhanced the understanding of pyrochemical fuel recycling processes by developing innovative tools and methodologies. The Multimodal Safeguards Monitoring Unit (MSMU) combines electroanalytical techniques, Raman spectroscopy, and differential thermal analysis (DTA) to enable high-fidelity, near-real-time material accountancy measurements. Machine learning techniques, such as Long Short-Term Memory (LSTM) autoencoders, are utilized to detect anomalies in material balances and sensor data, improving the reliability of safeguards monitoring. Additionally, digital twin technology has been established to provide real-time system-level monitoring and diagnostics, integrating physics-based models with sensor data to optimize process safety and efficiency.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2026

Sodium Chemistry Assessment and Initiation of Sodium Exposure Experiment on A709 Commercial Heats and LPBF 316H SS

This report documents sodium chemistry characterization and the initiation of forced‑convection sodium exposure experiments for two structural materials for sodium‑cooled fast reactors (SFRs): Alloy 709 (solution‑annealed and with an additional 775 °C/10 h precipitation treatment) and laser powder bed fusion (LPBF) 316H stainless steel tensile specimens printed with an as‑built surface condition. The sodium exposure experiment was conducted in a forced‑convection sodium loop with two vessels operated at 550 °C and 600 °C, and a cold trap maintained at <130 °C. Carbon activity in sodium was quantified using a nickel‑foil equilibration method. Initial post‑exposure evaluation after ~1,000 h indicates negligible thickness change for Alloy 709 and a small but measurable mass decrease. To isolate thermal effects from sodium effects, parallel thermal‑aging experiments were performed on Alloy 709 at 550 °C and 600 °C. Baseline tensile tests at room temperature, 550 °C, and 600 °C show expected reduction in strength with increasing temperature and serration tensile curves at elevated temperatures, consistent with dynamic strain aging. After 3,000 h thermal aging, Alloy 709 exhibits modest strengthening and reduced ductility at 550 °C. Together, these results establish the loop chemistry conditions and provide the initial corrosion and mechanical property results for ongoing long‑duration sodium exposure of Alloy 709 and LPBF 316H stainless steel.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

A FeCrAl-Al2O3 Composite Produced via Laser Powder Bed Fusion of a Mixed Powder for Porous Catalyst Scaffolds

This study proposes a novel approach for synthesizing and etching bicontinuous FeCrAl-Al2O3 composites as a means for replacing FeCrAl foams as catalyst scaffolds in bio-driven alcohol reactors for jet-fuel production. Conventional FeCrAl foams suffer from poor availability and consequent high costs. New additive manufacturing techniques provide an opportunity to produce tailored foams in reasonable times and at acceptable costs. This research aimed to generate a porous FeCrAl structure by etching a bicontinuous FeCrAl-Al2O3 composite produced by laser powder bed fusion of amalgamated FeCrAl and Al2O3 powders. The composite powder for laser powder bed fusion is created by ball-milling FeCrAl and Al2O3 powders. This research focuses on achieving a bi-continuous FeCrAl-Al2O3 structure, essential for the selective removal of the ceramic phase. The influence of laser processing parameters on the microstructure was examined across a range of laser powers (60-120 W) and scan speeds (100-400 mm/s), showing that higher powers and speeds produce finer metal struts. A bi-continuous microstructure was consistently obtained, marking a key achievement. The Al2O3 removal process involved a two-step etching method using hydrochloric and phosphoric acids, tested across various etching times. The alumina phase was reduced from 36 vol% to 17 vol% (corresponding to an increase in porosity from 24 vol% to 43 vol%), showing the potential for use as a porous catalyst scaffold. This research demonstrates the potential for using additive manufacturing to produce porous FeCrAl structures capable of replacing hard-to-source FeCrAl foams.

Son, Kwangtae↗

DOE OSTI2026

RuKY Catalyst‐Packed Permeation Membrane for Quantitative Ammonia and d3‐Ammonia Dehydrogenation to Ultrapure Hydrogen

Ammonia is a promising carbon-free hydrogen carrier, but incomplete ammonia dehydrogenation (cracking) generates atmospheric emissions of NO x , a potent greenhouse gas. Additionally, incomplete cracking of ammonia leads to regulatory challenges in nuclear and fusion power, where tritiated ammonia (NT 3 ) emissions are strictly controlled. Therefore, we report the use of low-temperature ammonia dehydrogenation catalysts (3%Ru/1%Y/12%K/Al 2 O 3 ) in a palladium alloy H 2 permeation membrane for quantitative conversion of ammonia into hydrogen and nitrogen at industry-relevant conditions. This catalytic membrane reactor system achieved an astonishing effluent concentration of <1 ppm at 450°C under a 100% NH 3 stream, which is far beyond the 99.6% conversion target required for the adoption of ammonia as a vehicle fuel. The low-temperature ammonia dehydrogenation catalyst was tested in a packed bed reactor with NH 3 and ND 3 to both elucidate the reaction mechanism and to quantify the kinetic isotope effect of the membrane reactor. The rate-limiting step at temperatures relevant to the palladium membrane are isotope independent, indicating that the isotopologue content will not modify the desired reaction kinetics. By reducing emissions to below-trace levels with no additional separation, this work provides a path to greatly simplified and miniaturized ammonia cracking processes.

ammonia decomposition↗

DOE OSTI2024

Importance of gas heating in capacitively coupled radiofrequency plasma-assisted synthesis of carbon nanomaterials

In pursuit of diamond nanoparticles, a capacitively-coupled radio frequency flow-through plasma reactor was operated with methane-argon gas mixtures. Signatures of the final product obtained microscopically and spectroscopically indicated that the product was an amorphous form of graphite. This result was consistent irrespective of combinations of the macroscopic reactor settings. To explain the observed synthesis output, measurements of C 2 and gas properties were carried out by laser-induced fluorescence and optical emission spectroscopy. Strikingly, the results indicated a strong gas temperature gradient of 100 K per mm from the center of the reactor to the wall. Based on additional plasma imaging, a model of hot constricted region (filamentation region) was then formulated. It illustrated that, while the hot constricted region was present, the bulk of the gas was not hot enough to facilitate diamond sp 3 formation: characterized by much lower reaction rates, when compared to sp 2 , sp 3 formation kinetics are expected to become exponentially slow. This result was further confirmed by experiments under identical conditions but with a H 2 /CH 4 mixture, where no output material was detected: if graphitic sp 2 formation was expected as the main output material from the methane feedstock, atomic hydrogen would then be expected to etch it away in situ, such that the net production of that sp 2 -hybridized solid material is nearly a zero. Finally, the crucial importance of gas heating was corroborated by replacing RF with microwave source whereby facile sp 3 production was attained with H 2 /CH 4 gas mixture.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Report on PTT Imaging of Defects in AM Metallic Materials-Part 2

36 MATERIALS SCIENCE↗

DOE OSTI2022

Pulsed Thermal Tomography Nondestructive Examination of Additively Manufactured Reactor Materials and Components (Final Technical Report)

Metal Additive Manufacturing (AM) is a promising method for cost-efficient fabrication of complex shape structures for applications in harsh environment, such as in a nuclear reactor. However, internal defects (pores) occur in high-strength AM alloys, which are manufactured with Laser Powder Bed Fusion (LPBF) AM method. Pulsed Infrared Thermography (PIT) is an efficient nondestructive evaluation (NDE) method to examine actual structures, because this method offers one-sided non-contact measurements, and fast processing of large sample areas. However, imaging of material defects, particularly defects with sizes at microscopic level, is challenging. In this report, we benchmark the performance of several Unsupervised Learning (UL) algorithms designed to enhance imaging of microscopic defects in metals with PIT. UL aims to learn the latent principal patterns (dictionaries) in PIT data to detect defects with minimal human supervision. Performance of Independent Component Analysis (ICA), Sparse Coding (SC), Principal Component Analysis (PCA) and Exploratory Factor Analysis (EFA) was compared using F-score, UL model training time and defects reconstruction time. We obtained the average F-score of 0.75, and a highest F-score of 0.89 for the EFA algorithm. Overall, EFA outperforms other UL algorithms considered in this study. In another approach, we investigate Thermal Tomography (TT), which is a computational method for reconstruction of depth profile of internal material defects from PIT nondestructive evaluation (NDE). TT algorithm obtains depth reconstructions of thermal effusivity, which has been shown to provide visualization of subsurface internals defects in metals. In many applications, one needs to determine the defect shape and orientation from reconstructed effusivity images. Interpretation of TT images is non-trivial because of blurring, which increases with depth due to heat diffusion-based nature of image formation. We have developed a deep learning convolutional neural network (CNN) to classify size and orientation of subsurface material defects in TT images. CNN was trained with TT images produced with computer simulations of 2D metallic structures (thin plates) containing elliptical subsurface voids. Performance of CNN was investigated using test TT images developed with computer simulations of plates containing elliptical defects, and defects with shape imported from scanning electron microscopy (SEM) images. CNN demonstrated the ability to classify radii and angular orientation of elliptical defects in previously unseen test TT images. We have also demonstrated that CNN trained on TT images of elliptical defects is capable of classifying shape and orientation of irregular defects. Training the CNN on irregular defect shapes instead of on elliptical shapes would make the resulting classifications more descriptive of actual defect shapes. However, this requires a much higher volume of SEM images of material defects, which are difficult to obtain because of random occurrence of defects in LPBF. To address this challenge, we developed a generative adversarial network (GAN) to augment the existing dataset of SEM defect images. The GAN model is demonstrated to create novel yet realistic defect shapes that can be used as input for simulated PTT images to train CNN. We also investigate several approaches based on Gaussian Random Circle and Bezier Curves for constructing parametric models of irregular-shape defects.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Analysis of RF Sheath-Driven Tungsten Erosion at RF Antenna in the WEST Tokamak

This study applies the newly developed STRIPE (Simulated Transport of RF Impurity Production and Emission) framework to analyze tungsten (W) erosion at RF antenna structures in the WEST tokamak. STRIPE integrates SolEdge3x for edge plasma backgrounds, COMSOL for 3D RF sheath potentials, RustBCA for sputtering yields, and GITR for impurity transport and ion energy–angle distributions. Building on prior work by Kumar et al. (2025) Nuclear Fusion, 65, 076039, which validated STRIPE for WEST ICRH discharge #57877, the present study provides a spatially resolved assessment of gross W erosion at both Q2 antenna limiters under ohmic and ICRH conditions. Simulations using 2D SolEdge3x profiles in COMSOL capture rectified sheath potentials exceeding 300 V, leading to strong upper-limiter localization. Both poloidal and toroidal asymmetries are observed and attributed to RF sheath effects, with modeled erosion patterns deviating from experiment—highlighting sensitivity to sheath geometry and plasma resolution. Erosion is driven primarily by high-charge-state oxygen ions (O6+–O8+), while D+ plays a negligible role. Assuming a plasma composition of 1% oxygen and 98% deuterium, STRIPE predicts a 30-fold increase in gross W erosion from ohmic to ICRH phases, consistent with a >25-fold rise in W-I (400.9 nm) brightness. Quantitative agreement is within 5% in the ohmic phase and 30% under ICRH, demonstrating predictive capability. Importantly, the study shows that the magnitude of ICRH-driven W erosion depends strongly on the concentration of light impurities (O, B, N, C), which drive sputtering through high charge states. Cleaner plasma conditions with reduced impurity content are therefore expected to substantially mitigate antenna W sources in WEST and other toroidal fusion devices. These findings establish STRIPE as a predictive framework for RF-induced plasma–material interactions and support its application to reactor-scale antenna design.

Kumar, Atul [ORNL] (ORCID:0000000277475210)↗

DOE OSTI2023

Mechanical Properties of Additively Manufactured 316L Stainless Steel Before and After Neutron Irradiation–FY23

This report presents the observed mechanical behavior of the additively manufactured (AM) 316L stainless steel (SS) before and after neutron irradiation. In the Advanced Materials and Manufacturing Technologies (AMMT) program, a variety of mechanical and physical property data are generated and accumulated to assess the AM austenitic alloy for nuclear reactor applications. The testing and evaluation task in the FY 2023 focused on elucidating the effects of sampling location and build size on the mechanical properties of AM 316L SS (in stress-relieved condition) before and after neutron irradiation. The laser powder bed fusion (LPBF) process produced 316L plates of three distinct sizes from which SS-J3 miniature tensile specimens were machined from six different locations. The tensile specimens were irradiated in the High Flux Isotope Reactor (HFIR) normally to 2 and 10 dpa at the target temperatures of 300 °C and 600 °C. Post-irradiation tensile testing was performed at room temperature, 300 °C, and 600 °C. The mechanical properties of AM 316L SS were significantly influenced by the characteristic microstructures of printed materials, which include fine grains and high-density dislocations. Compared with the traditional 316L SS, AM 316L showed higher initial strength and lower ductility. Regardless of sampling location, the AM 316L steel retained relatively high strength and ductility to the highest irradiation dose. A prompt necking at yield (with little uniform ductility) was observed after irradiation at 300 °C but no embrittlement was observed up to 10 dpa. Ductilization by irradiation–the radiation-induced increase of ductility–was observed for the 600 °C irradiation only and it occurred in low dose range only. The neutron irradiation increased the data variation in many tensile property datasets, particularly after 600 °C irradiation, and no clear dependence of tensile properties on build thickness or sampling location was observed.

36 MATERIALS SCIENCE↗

DOE OSTI2022

New proposed ITER divertor design using carbon insert on tungsten to mitigate ELMs and secondary radiation effects on nearby components

Abstract Building a successful device for the magnetic fusion energy production is a great challenge. ITER is an international project of the tokamak based magnetic fusion design being developed for the demonstration of the feasibility of thermonuclear technologies for future realization of successful commercial fusion energy. A key obstacle to a successful magnetic fusion energy production is however, the performance during abnormal events including plasma disruptions and edge-localized modes (ELMs). A credible reactor design must tolerate at least a few of these transient events without serious consequences such as melting of the structure. This paper investigates and compares the performance of the current ITER tokamak design during two types of transient events, i.e., ELMs occurring at normal operation and disruptions during abnormal operation. We simulated the divertor components response using our integrated 3D HEIGHTS package. The simulations include self-consistent modeling of the interaction of the released core plasma particles with the initial solid divertor material, energy deposition processes, vaporization of divertor material, secondary plasma formation and MHD evolution, incident core particles collisions and scattering from this dense secondary plasma, photon radiation of secondary plasma, and the resulting heat loads on nearby components. Our simulations showed that using a small carbon insert around the strike point can significantly reduce the overall expected damage on the tungsten dome structure, reflector plates, and prevent tungsten vaporization and its potential core plasma contamination.

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Final CRADA Report – NFE-21-08693

TAE Technologies is developing a magnetic fusion energy concept known as the beam-driven field-reversed configuration (FRC) with the ultimate goal of developing a reactor for commercial electricity production capable of burning aneutronic pB11 fuel. To achieve the high plasma temperatures this requires, auxiliary radiofrequency (RF) heating will likely be needed. High Harmonic Fast Wave (HHFW) heating has been identified as a candidate RF heating scheme to overcome the unique challenges posed to RF heating by the FRC, including the large distance from the plasma edge to the last closed flux surface and a magnetic field profile with strength decreasing from edge to core and reversing sign at a null point inside the plasma. The purpose of this project was to develop the experimental capabilities to test HHFW on TAE’s C-2W device through the design of a phased array antenna and accompanying matching network. The design was performed by ORNL and informed by experiments with a prototype four-strap phased antenna-array that was manufactured and installed on the LArge Plasma Device (LAPD) at UCLA and simulations conducted with the Petra-M code under the purview of a previous INFUSE grant. The ORNL team completed the conceptual design of the antenna and matching network which was then handed off to the TAE Mechanical Design team. The design was then iterated on to ensure changes to the mechanical design did not interfere with the RF performance. This process is now complete, and, with mechanical design in hand, TAE is proceeding with plans for final integration.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Novel intrinsic helical cores and MHD dynamo flux pumping evidence in DIII-D

Evidence of a MHD dynamo brought about by intrinsic helical core structures in negative triangularity (NT) and ITER baseline scenario (IBS) plasmas demonstrates paths to operating tokamaks without seeds for deleterious global MHD modes. A stationary sawtooth- and edge localized mode-free state maintains high performance for long durations in a strong NT shape in the DIII-D tokamak. Disparity between minimum safety factor values predicted by magnetic flux diffusion theory and derived from experiment suggests anomalous flux diffusion by an MHD dynamo, driven by flows associated with quasi-interchange modes. Stability calculations with the GATO code find NT and IBS experimental equilibria unstable to quasi-interchange modes, in agreement with observed saturated activity. IBS discharges with similar magnetic winding structure occupy robust helical core states following a transition from sawtooth instabilities. These states agree with prior modeling of helical core bifurcation thresholds with the VMEC equilibrium code.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Comparative Analysis of Confidence Metrics for Nuclear Criticality Safety

Nuclear criticality safety standards provide guidance on the requirements and recommendations to establish confidence in computerized model results used to support operation with fissionable materials. By design, the guidance is not prescriptive, leaving the analysts free to determine how various sources of uncertainties are to be statistically aggregated. This report compares the analyses and key assumptions behind four notable methodologies documented in the nuclear criticality safety literature: the parametric, nonparametric, Whisper, and TSURFER methodologies. Because of the involved use of statistics entangled with heuristic recipes, the results of these methodologies are often difficult to interpret. Also, they are augmented by additional large administrative margins, eliminating the incentive to understand their differences. With the new resurgent wave of advanced nuclear systems focused on economizing operation—including advanced reactors, fuel cycles, and fuel concepts—there is a strong need to develop a clear understanding of uncertainties and their fusion methodologies to reduce uncertainties in a scientifically defensible manner. This report offers a deep dive into the various assumptions of the four noted methodologies, their adequacy, and their limitations, to provide guidance on developing confidence for the emergent nuclear systems. These systems are expected to be challenged by the scarcity of experimental data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Performance Validation of Pulsed Thermal Imaging System for In-Service Applications

42 ENGINEERING↗

NASA NTRS2001

Magnetic Flux Compression Reactor Concepts for Spacecraft Propulsion and Power (MSFC Center Director's Discretionary Fund; Project No. 99-24)

This technical publication (TP) examines performance and design issues associated with magnetic flux compression reactor concepts for nuclear/chemical pulse propulsion and power. Assuming that low-yield microfusion detonations or chemical detonations using high-energy density matter can eventually be realized in practice, various magnetic flux compression concepts are conceivable. In particular, reactors in which a magnetic field would be compressed between an expanding detonation-driven plasma cloud and a stationary structure formed from a high-temperature superconductor are envisioned. Primary interest is accomplishing two important functions: (1) Collimation and reflection of a hot diamagnetic plasma for direct thrust production, and (2) electric power generation for fusion standoff drivers and/or dense plasma formation. In this TP, performance potential is examined, major technical uncertainties related to this concept accessed, and a simple performance model for a radial-mode reactor developed. Flux trapping effectiveness is analyzed using a skin layer methodology, which accounts for magnetic diffusion losses into the plasma armature and the stationary stator. The results of laboratory-scale experiments on magnetic diffusion in bulk-processed type II superconductors are also presented.

Litchford, R. J.↗

DOE OSTI2021

Performance of Compact Pulsed Thermal Imaging System for In-Service Applications. Pulsed thermal tomography nondestructive examination of additively manufactured reactor materials and components

Additive manufacturing (AM) is an emerging method for cost-efficient fabrication of complex topology nuclear reactor parts from high-strength corrosion resistance alloys, such as stainless steel and Inconel. AM of metallic structures for nuclear energy applications is currently based on laser powder bed fusion (LPBF) process, which has the capability of melting metallic powder and net shaping the structures with relatively high precision. Some of the challenges with using LPBF method for nuclear manufacturing include the possibility of introducing pores into metallic structures. Integrity of AM structures needs to be evaluated nondestructively because material flaws could lead to premature failures due to creep in high temperature nuclear reactor environment. Currently, there exist limited capabilities to evaluate actual AM structures nondestructively. Pulsed Thermography (PT) imaging provides a capability for non-destructive evaluation (NDE) of sub-surface defects in arbitrary size structures. The PT method is based on recording material surface temperature transients with infrared (IR) camera following thermal pulse delivered on material surface with flash light. The PT method has advantages for NDE of actual AM structures because the method involves one-sided non-contact measurements and fast processing of large sample areas captured in one image. The data cube of PT measurements consists of surface temperature taken at sequential time intervals T(x,y,t). Material defects can be detected either by analyzing the thermograms T(x,y,t) data cube, or by using thermal tomography (TT) algorithm to obtain 3D spatial reconstruction of thermal effusivity e(x,y,z). To reduce the cost and enable in-service NDE in spatially constrained environment, it is highly desirable to develop PT with compact and inexpensive IR camera. Following initial qualification of an AM component for deployment in a nuclear reactor, a compact PT system can also be used for in-service nondestructive evaluation (NDE) applications. However, data cube obtained with PT based on compact IR camera suffers from strong thermal noises and loss of features due to relatively low sampling rate. In this report we describe two unsupervised machine learning (ML) algorithms for enhancement of PT images obtained with compact IR camera. In one approach, we introduce Sparse Coding Discrete Cosine Transform (SC/DCT) algorithm to remove additive white Gaussian noise (AWGN) from spatial thermal effusivity reconstructions. In another approach we introduce a Spatial Temporal Denoised Thermal Source Separation (STDTSS) ML algorithm to process thermograms. The STDTSS algorithm consists of spatial and temporal denoising using Gaussian and Savitzky–Golay filtering, followed by the matrix decomposition using Principal Component Analysis (PCA), and Independent Component Analysis (ICA) to automatically detect flaws. In the work described in this report, we constructed a compact PT system using a relatively small and low-cost FLIR A65 camera, consisting on uncooled microbolometer detector. Performance of SC/DCT algorithm was demonstrated on enhancing TT images of Inconel 718 AM plate. Performance of the STDTSS methods was investigated using thermography data obtained from imaging stainless steel 316L specimens produced with LPBF method with imprinted calibrated porosity defects.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Nonlinear burn control in ITER using adaptive allocation of actuators with uncertain dynamics

Abstract ITER will be the first tokamak to sustain a fusion-producing, or burning, plasma. If the plasma temperature were to inadvertently rise in this burning regime, the positive correlation between temperature and the fusion reaction rate would establish a destabilizing positive feedback loop. Careful regulation of the plasma’s temperature and density, or burn control, is required to prevent these potentially reactor-damaging thermal excursions, neutralize disturbances and improve performance. In this work, a Lyapunov-based burn controller is designed using a full zero-dimensional nonlinear model. An adaptive estimator manages destabilizing uncertainties in the plasma confinement properties and the particle recycling conditions (caused by plasma–wall interactions). The controller regulates the plasma density with requests for deuterium and tritium particle injections. In ITER-like plasmas, the fusion-born alpha particles will primarily heat the plasma electrons, resulting in different electron and ion temperatures in the core. By considering separate response models for the electron and ion energies, the proposed controller can independently regulate the electron and ion temperatures by requesting that different amounts of auxiliary power be delivered to the electrons and ions. These two commands for a specific control effort (electron and ion heating) are sent to an actuator allocation module that optimally maps them to the heating actuators available to ITER: an electron cyclotron heating system (20 MW), an ion cyclotron heating system (20 MW), and two neutral beam injectors (16.5 MW each). Two different actuator allocators are presented in this work. The first actuator allocator finds the optimal mapping by solving a convex quadratic program that includes actuator saturation and rate limits. It is nonadaptive and assumes that the mapping between the commanded control efforts and the allocated actuators (i.e. the effector model) contains no uncertainties. The second actuator allocation module has an adaptive estimator to handle uncertainties in the effector model. This uncertainty includes actuator efficiencies, the fractions of neutral beam heating that are deposited into the plasma electrons and ions, and the tritium concentration of the fueling pellets. Furthermore, the adaptive allocator considers actuator dynamics (actuation lag) that contain uncertainty. This adaptive allocation algorithm is more computationally efficient than the aforementioned nonadaptive allocator because it is computed using dynamic update laws so that finding the solution to a static optimization problem is not required at every time step. A simulation study assesses the performance of the proposed adaptive burn controller augmented with each of the actuator allocation modules.

Physics↗

DOE OSTI2026

Lessons Learned from Open-Source Software Training Toward Expanding the Fusion Workforce

Within the United States (U.S.), the Fusion Innovation Research Engine (FIRE) Collaboratives seek to accelerate fusion technology development through wide-ranging community-driven research activities that bring together industry, laboratories, research institutes, and academia. Increasing the maturity of key components and systems for future fusion power plants (FPPs) toward commercialization, will, by necessity, increase the need for knowledgeable engineers, designers, and researchers in industry capable of integrating and further improving these technologies within industry FPP concepts. Further, various modeling and simulation packages support these programs and are under-development within them to drive design iteration and the development of FPP digital twins. To derive the greatest benefit from model output and capabilities, training these same specialists will be vital. Thus, the development of effective and accessible software onboarding and professional development opportunities focused on fusion will be key to keeping the pace of growth high in the coming decade and beyond. A similar need exists within the advanced fission reactor community, driven by an ever-growing need for carbon-free baseload power for industrial and data center applications. Within the U.S. and around the world, several open-source packages and frameworks exist to support this endeavor, and two we will highlight here are the Multiphysics Object Oriented Simulation Environment (MOOSE) framework and OpenMC. These packages, notably, are also being utilized in the FIRE Collaboratives program. In this presentation, we will highlight the lessons learned from over 30 years of combined software development and training experience, focused on developing strong technical software foundations within the nuclear workforce, from students to professional engineers & scientists. We will connect this experience to present and emerging needs in the fusion energy community, and, finally, will outline possible paths forward to develop a large, robust, global fusion workforce.

70 - PLASMA PHYSICS AND FUSION TECHNOLOGY↗