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DOE OSTI2025

Improvement and Verification of Online Cross Section Generation Capability of Griffin for TRISO-fueled Reactors

Griffin, a MOOSE-based reactor multiphysics code jointly developed by Idaho National Laboratory and Argonne National Laboratory under the DOE Office of Nuclear Energy’s NEAMS program, has pursued the development of an online multigroup cross section generation capability for a few years to enable high-fidelity, problem-dependent neutronics analyses of advanced thermal reactors. Recent advancements in Griffin’s online multigroup cross section generation capability have significantly improved the accuracy, robustness, and efficiency of self-shielding calculations for both prismatic and pebble-bed TRISO-fueled reactor applications. Key developments include a unified fuel self-shielding method applicable to both TRISO and annular compact/spherical shell fuel zone geometries; an advanced Dancoff Category-based Equivalence Theory using a bell function for non-fuel resonance treatment, achieving more than an order-of-magnitude speedup compared to the Tone method; an on-the-fly multigroup equivalence approach to mitigate group condensation errors; and a streaming correction method for pebble-bed homogenization. A proof-of-concept demonstration of on-the-fly group condensation with consistent P0 transport correction was also achieved. The method reproduced direct fine-group solutions with excellent accuracy (eigenvalue errors within 10 pcm and pin-power differences within 0.5%), but due to performance limitations of the current fixed-source solver, improvements to solver efficiency will be addressed in future work. Verification tests were performed on graphite-moderated TRISO-fueled two-dimensional core benchmark problems representing gas-cooled microreactors, heat pipe-cooled microreactors, gas-cooled pebble-bed reactors, and fluoride salt-cooled high-temperature reactors. Across all cases, Griffin showed excellent agreement with Serpent2 continuous energy Monte Carlo solutions: eigenvalue errors within 200 pcm, pin-power root-mean-square errors within 2%, and control rod and drum worth errors less than 2%. It should be noted that, for the benchmark problem, cross section generation contributed less than 3% of the total simulation times. These results demonstrate that Griffin’s online cross section generation capability delivers accurate and efficient reactor physics solutions across a wide spectrum of TRISO-fueled advanced reactor designs. With further improvements to the fine-group fixed-source solver and planned extensions to depletion, transients, and coupled neutron–gamma transport, Griffin will be well-positioned to become a powerful and comprehensive tool for advanced reactor analysis.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2018

Testing Results from the Low Activity Waste Pretreatment System (LAWPS) Full-Scale Ion Exchange Column Test and Engineering Scale Integrated System Test - 18634

The U.S. Department of Energy (DOE), Office of River Protection's (ORP) primary mission is to retrieve and treat Hanford's tank waste and close the Tank Farms to protect the Columbia River. Mixed radioactive waste is stored in 177 underground tanks at the Hanford Site as reported in DOE/ORP 2003- 02, Environmental Impact Statement for Retrieval, Treatment, and Disposal of Tank Waste and Closure of the Single Shell Tanks at the Hanford Site, Richland WA, Inventory and Source Term Data Package. The 177 underground tanks are estimated to contain about 56 million gallons of waste. The Low Activity Waste Pretreatment System (LAWPS) Project provides for the early production of immobilized low activity waste (ILAW) by feeding LAW directly from Tank Farms to the Hanford Waste Treatment Plant's (WTP's) LAW Facility, bypassing the Pretreatment Facility. Prior to the transfer of feed to the WTP LAW Vitrification Facility, tank supernatant waste will be pretreated in the LAWPS to meet the WTP LAW waste acceptance criteria. The LAWPS will also facilitate the return of secondary liquid wastes from the WTP LAW Vitrification Facility to the Tank Farms. In November of 2015 DOE's Tank Operations Contractor, Washington River Protection Solutions (WRPS), awarded a contract to the AECOM team to design, fabricate and operate two test platforms to generate performance data at two different scales and demonstrate technology maturation. The first platform models the ion exchange (IX) columns at full scale, and the second platform models the integrated flowsheet (cross flow filter (CFF) and IX) at 1/9. scale. Overarching technical objectives of performing the full-scale ion exchange test and the engineering-scale integrated test are to: 1. Test interactions between unit process operations; 2. Test removal of non-radioactive cesium from process stream; 3. Test removal of undissolved solids from process stream; 4. Confirm operational flow rate range and stability; 5. Confirm volumetric throughput of waste stream over flow operating range; 6. Confirm range of process temperatures over planned operating range; 7. Establish system hydraulics and process criteria; 8. Coordinate key control and monitoring components; 9. Establish treated product chemistry meets requirements (cesium, solids, and pH); and 10. Test the hazard control strategy for a no flow condition through the IX column. Data collected during testing will be used by WRPS to validate the preliminary design, inform the final design of the permanent plant equipment, and demonstrate that the critical technology elements have advanced to a technology readiness level of 6 (prototypical system validation in a relevant environment). Testing on both platforms started in fall of 2016 generating NQA-1 data. This paper covers test results from the first five phases of testing on the 1/9. scale integrated test platform. A further three phases of testing are currently being executed, these including a 5.6 M sodium simulant containing foulant, a high viscosity simulant and finally a run performed with a lower Cs concentration (all earlier tests were spiked to 4 x Cs to reduce volume and cost). Results from these tests were not available at the time of writing available. Results are also presented from the full scale IX testing. Eight test were performed covering column loading, elution and regeneration; column loading, elution and regeneration with upflow displacement; IX column loading and gas migration; resin removal; solids accumulation; and IX column emergency recirculation and vent. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2016

Investigation of Portable Event-Based Monte Carlo Transport Using the NVIDIA Thrust Library

Power consumption considerations are driving future high performance computing platforms toward many-core computing architectures. Los Alamos National Laboratory's Trinity machine, available in 2016, will use both Intel Xeon Haswell processors and Intel Xeon Phi Knights Landing many integrated core (MIC) architecture coprocessors. Lawrence Livermore National Laboratory's Sierra machine, available in 2018, will use an IBM PowerPC architecture along with Nvidia graphics processing unit (GPU) architecture accelerators. These different advanced architectures make the computing landscape in upcoming years complex. Traditional approaches to Monte Carlo transport do not work efficiently on these new computing platforms. MIC architectures require vectorization to operate efficiently, and vectorization is difficult to achieve in Monte Carlo transport. GPU architectures require additional code to explicitly use the hardware, requiring significant code changes or hardware specific branches in the source code. A significant challenge for Monte Carlo transport projects is to simultaneously support within a single source code base efficient simulations for both the current generation of architectures and the different advanced computing architectures. In order to address these challenges, two important changes are typically required: a new algorithmic approach for solving Monte Carlo transport, and explicit use of hardware specific software. In this paper, we describe initial research investigations of an event-based Monte Carlo transport algorithm implemented using the Nvidia Thrust library on a GPU for a Monte Carlo test code. The event-based algorithm targets many-core architectures by increasing SIMD (single instruction multiple data) parallelism, while Thrust potentially provides portable performance by allowing one source code base to compile code targeted for both CPUs and GPUs. We described preliminary investigations of portable event-based Monte Carlo algorithms implemented using the Nvidia Thrust library in a research Monte Carlo test code. We found that an explicit CUDA implementation of an event-based Monte Carlo algorithm performed significantly more efficiently than a Thrust implementation on GPU platforms, most likely as a result of additional flexibility in access to different memory spaces on the GPU. Additionally, we showed that on GPU platforms and at large enough problem sizes the event-based implementations perform more efficiently than the serial history-based implementation running on the host CPU. While investigating this problem, we also discovered that the performance of the event-based algorithm is affected by what tallies are being used. A zonal scalar flux tally requires atomic operations that significantly impacted the performance of the code, in some cases producing slowdowns instead of speedups. We decided to remove the tally in order to focus on the effectiveness of the event-based algorithm. Future work will be required to research more effective ways of handling such tallies. Additionally, we would like to consider new ways for optimizing both the Thrust and CUDA versions, in order to see how much performance we have yet to achieve. The potential trade-off between portability and performance was demonstrated in this investigation. Thrust provides both CPU and GPU versions of the code in one code base, but it does so at a cost. We discovered approximately a factor of 2-5 performance difference between Thrust and CUDA on each GPU platform we tested. Thrust provides a tool to access the GPUs with less effort and specialization, but it does so by giving up fine grained control where extra performance can be found for this application. Future work will be required to determine whether this performance differential between Thrust and CUDA can be reduced for event-based Monte Carlo transport. (authors)

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2015

Effectiveness of purging on preventing gas emission buildup in wood pellet storage

Storage of wood pellets has resulted in deadly accidents in connection with off-gassing and self-heating. A forced ventilation system should be in place to sweep the off-gases and control the thermal conditions. In this study, multiple purging tests were conducted in a pilot scale silo to evaluate the effectiveness of a purging system and quantify the time and volume of the gas needed to sweep the off-gases. To identify the degree of mixing, residence time distribution of the tracer gas was also studied experimentally. Large deviations from plug flow suggested strong gas mixing for all superficial velocities. As the velocity increased, the system dispersion number became smaller, which indicated less degree of mixing with increased volume of the purging gas. Finally, one-dimensional modelling and numerical simulation of the off-gas concentration profile gave the best agreement with the measured gas concentration at the bottom and middle of the silo.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2019

Environmental Systems Biology Approach to Bioremediation

Pollution is everywhere. Microbes are also everywhere, and many have the ability to degrade environmental contaminants. Understanding how these microbial communities work to degrade environmental contaminants will enable us to use these microbes to clean up the pollution. Understanding, monitoring, and controlling the environment with biological processes, i.e., an environmental systems biology approach to bioremediation, answer the need which is everywhere. By using an environmental systems approach to bioremediation, we make sure we know of any “fatal flaws” in the approach, get a much better handle on life-cycle cost analysis, and can grade an engineered solution into a natural attenuation solution. The whole is greater than the sum of its parts. By using an environmental systems biology approach to bioremediation and cross-linkage of systems at all levels providing multiple lines of evidence involving environmental observations, laboratory testing, microcosm simulations, hypothesis refinement, field testing and validation, and multiple iterations of this circle, we will be able to make new theories and paradigms for bioremediation of contaminated environments.

Hazen, Terry C.↗

DOE OSTI2025

A digital twin platform for building performance monitoring and optimization: Performance simulation and case studies

Advancements in sensor technology, data analytics, affordable compute, and communication infrastructure have paved the way for Digital Twin technology in optimizing building operations and controls. This study presents the development of an open and interoperable web-based Digital Twin platform for integrating diverse data streams and facilitating effective user interactions. The platform utilizes modern technologies for the web framework and time-series data management, ensuring scalability and responsiveness. The backend supports seamless integration of diverse data sources and emulators, incorporating data from building sensors and meters, external weather Application Programming Interfaces, and advanced EnergyPlus simulation models of the building and its energy systems including the Distributed Energy Resources that are formulated in Functional Mockup Units. A simulation case study was conducted with FlexLab, a test facility on Lawrence Berkeley National Laboratory campus. The case study includes normal operations, Distributed Energy Resource integration, and power outage scenarios, to illustrate the Digital Twin’s ability to provide critical insights into energy performance and thermal resilience. The results demonstrated the platform’s potential as a decision-support tool for optimizing building energy performance and enhancing resilience against extreme weather events. Future work will focus on deploying the Digital Twin platform to a real building for field validation, extending its capabilities to cover more scenarios such as bidirectional Electric Vehicle interactions, and enhancing user engagement.

EnergyPlus↗

DOE OSTI2023

Using the Gerchberg-Saxton algorithm to reconstruct nonmodulated pyramid wavefront sensor measurements

Adaptive optics (AO) is a technique to improve the resolution of ground-based telescopes by correcting, in real-time, optical aberrations due to atmospheric turbulence and the telescope itself. With the rise of Giant Segmented Mirror Telescopes (GSMT), AO is needed more than ever to reach the full potential of these future observatories. One of the main performance drivers of an AO system is the wavefront sensing operation, consisting of measuring the shape of the above mentioned optical aberrations. Aims. The non-modulated pyramid wavefront sensor (nPWFS) is a wavefront sensor with high sensitivity, allowing the limits of AO systems to be pushed. The high sensitivity comes at the expense of its dynamic range, which makes it a highly non-linear sensor. We propose here a novel way to invert nPWFS signals by using the principle of reciprocity of light propagation and the Gerchberg-Saxton (GS) algorithm. We test the performance of this reconstructor in two steps: the technique is first implemented in simulations, where some of its basic properties are studied. Then, the GS reconstructor is tested on the Santa Cruz Extreme Adaptive optics Laboratory (SEAL) testbed located at the University of California Santa Cruz. This new way to invert the nPWFS measurements allows us to drastically increase the dynamic range of the reconstruction for the nPWFS, pushing the dynamics close to a modulated PWFS. The reconstructor is an iterative algorithm requiring heavy computational burden, which could be an issue for real-time purposes in its current implementation. However, this new reconstructor could still be helpful in the case of many wavefront control operations. In conclusion, this reconstruction technique has also been successfully tested on the Santa Cruz Extreme AO Laboratory (SEAL) bench where it is now used as the standard way to invert nPWFS signal.

47 OTHER INSTRUMENTATION↗

DOE OSTI2023

Fidelity Analysis of Complex Large-Scale Simulation Models of PEs (MARS) in Future Power Grids

With the proliferation of power electronic (PE)-based resources in the electric grid, there have been numerous different kinds of simulation models developed and studied to understand their dynamic behavior. Study of PE-based resources using each simulation model has its own distinct advantages and disadvantages. Therefore it is very important to carefully select the appropriate model for the evaluation of the PE-based resources. In this paper, one such effort is made to analyze the different types of models in the case of a multi-port autonomous reconfigurable solar power plant (MARS). The MARS integrates a hybrid photovoltaic (PV)-energy storage system (ESS) plant to high-voltage direct current (HVdc) system and transmission alternating current (ac) grid. The dynamic models are evaluated under different test cases varying the short-circuit ratio (SCR) and control algorithms. Recommendations are provided on the equipment study needs based on the analysis completed.

Marthi, Phani Ratna Vanamali↗

DOE OSTI2023

Preliminary Development of Heat Transfer Model-Based Control Algorithms of Liquid Sodium Purification System: Advanced Sensors and Instrumentation Advanced Controls

Monitoring the operation of sodium purification system is essential for efficient operation of sodium fast reactors. In this work, a heat transfer model has been developed for monitoring the plugging meter and cold trap systems at the Mechanisms Engineering Test Loop (METL) liquid sodium facility at Argonne National Laboratory. The model of the purification system was developed by treating the respective aspects of the cold trap purification loop and plugging meter diagnostic loop as two separate control volumes using information from the METL piping and instrumentation diagram (P&ID). A model predictive controller was designed using first order differential equations with the specified boundary conditions. The system behavior was studied with a tuned optimized procedure using the internal cold trap temperature and plugging meter outlet temperature as control variables, and the air blower temperature as an independent variable respectively. Results of computer simulations obtained in this study compared favorably with experimental data showing very good reference tracking response with negligible overshoot as both plugging meter and cold trap physical models approach the setpoint.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2023

Measurement of the pion charge exchange differential cross section on Argon with the ProtoDUNE-SP detector

The Deep Underground Neutrino Experiment (DUNE) utilizes Liquid Argon Time Projection Chamber (LArTPC) technology in its pursuit of uncovering the origins of matter. As a crucial prototype for the DUNE far detector (FD) module, ProtoDUNE-SP at CERN Neutrino Platform Facility employs a hadron test beam with a momentum range of 0.3 to 7 GeV/c to study the detector response to particles that could be produced in the neutrino interactions at the DUNE FD. Furthermore, ProtoDUNE-SP is dedicated to testing event reconstruction and performing detector calibration under controlled conditions. Neutral pion reconstruction performance is an important benchmark of the calorimetric and tracking capability of LArTPC, and understanding neutral pion in LArTPC is crucial to characterize backgrounds to oscillation measurements and rare searches. To improve neutral pion reconstruction in LArTPC, a kinematic fitting algorithm is developed, achieving a 12% resolution in neutral pion energy in ProtoDUNE-SP. This enhancement enables the first measurements of the pion-argon charge exchange differential cross-section. By comparing these results with the current model, valuable constraints can be made to improve generator simulations in the future DUNE experiment.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2020

An error-controlled adaptive time-stepping method for particle advancement in coupled CFD-DEM simulations

Coupled Computational-Fluid-Dynamics (CFD) and Discrete-Element-Method (DEM) models provide an accurate description of multiphase physical systems where a solid granular particle phase exists in an underlying gaseous continuous medium. The time integration of the granular phase in these simulations is typically handled using an explicit scheme with a constant time-step among all particles that is invariant in time to resolve inter-particle collisions. A locally third-order accurate adaptive time integration technique for particles that employs an embedded locally second-order scheme for error determination is presented in this work. The particle time-step size is dynamically adapted based on solution error, thus leading to significant savings in computational time. The efficacy of our scheme is quantified using four test cases of varying complexity (binary collision, homogeneous cooling system, fluidized bed and hopper discharge). The adaptive time-stepping method exhibits improved performance (~ 2–3 times in most of the cases studied) compared to three commonly used non-adaptive time-step methods (first-order Euler-explicit, second-order Adams-Bashforth and third-order Runge-Kutta schemes), while maintaining the same level of accuracy and parallel scalability.

42 ENGINEERING↗

DOE OSTI2023

Efficient learning of power grid voltage control strategies via model-based deep reinforcement learning

Here this article proposes a model-based deep reinforcement learning (DRL) method to design emergency control strategies for short-term voltage stability problems in power systems. Recent advances show promising results for model-free DRL-based methods in power systems control problems. But in power systems applications, these model-free methods have certain issues related to training time (clock time) and sample efficiency; both are critical for making state-of-the-art DRL algorithms practically applicable. DRL-agent learns an optimal policy via a trial-and-error method while interacting with the real-world environment. It is also desirable to minimize the direct interaction of the DRL agent with the real-world power grid due to its safety-critical nature. Additionally, the state-of-the-art DRL-based policies are mostly trained using a physics-based grid simulator where dynamic simulation is computationally intensive, lowering the training efficiency. We propose a novel model-based DRL framework where a deep neural network (DNN)-based dynamic surrogate model (SM), instead of a real-world power grid or physics-based simulation, is utilized within the policy learning framework, making the process faster and more sample efficient. However, having stable training in model-based DRL is challenging because of the complex system dynamics of large-scale power systems. We addressed these issues by incorporating imitation learning to have a warm start in policy learning, reward-shaping, and multi-step loss in surrogate model training. Finally, we achieved 97.5% reduction in samples and 87.7% reduction in training time for an application to the IEEE 300-bus test system.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Priming mechanisms providing plants and microbes access to mineral-associated organic matter

Mineral-associated organic matter (MAOM) is considered a stable reservoir for soil nutrients that influences long-term soil carbon (C) and nitrogen (N) dynamics. However, recent experimental and theoretical evidence shows that root exudates may mobilize MAOM, thereby providing plants and microbes access to a large and N-rich pool. Given the mechanisms underlying MAOM C and N mobilization remain largely untested, we examined direct and indirect pathways by which root exudates destabilize this nutrient pool in laboratory mesocosms. We simulated root exudation with 13 C-labeled oxalic acid to test whether root exudates are directly capable of mobilizing MAOM from mineral surfaces; and with 13 C-labeled glucose to test whether indirect stimulation of microbial and extracellular enzyme activity leads to MAOM decomposition. We also tested the potential for oxalic acid and glucose to mobilize MAOM in an additional subset of sterilized soils to clarify the potential for non-microbial pathways of MAOM destabilization. Over the course of the 12-day MAOM incubation with and without simulated exudates, we measured C cycling (CO 2 respiration rates, 13 C–CO 2 efflux), N cycling (inorganic N pools, gross N mineralization) and related microbial processes (enzyme activities and microbial community composition via phospholipid fatty acid analysis). Both of the simulated root exudates enhanced MAOM-C mineralization, with cumulative respiration increasing 35–89% relative to the water-only control. Likewise, glucose additions enhanced the production of an exo-cellulase and a chitinase by up to 130% and 39%, respectively, while oxalic acid enhanced oxidative enzyme activities up to 91% greater than control rates. We observed a positive association between glucose-induced shifts in enzyme activities, MAOM-C mineralization, and gross ammonification. Oxalic acid additions were associated with initial increases in fungal relative abundance and in sterile soils appeared to stimulate the release of metals and dissolved organic nitrogen into exchangeable pools. Our results indicate that common root exudates, like glucose and oxalic acid, can significantly increase the turnover and potential release of C and N from MAOM through indirect (e.g., enzyme induction) and direct (e.g., mobilization of metal oxides) mechanisms.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Supplemental Immobilization of Hanford Low-Activity Waste: Cast Stone Augmented Formulation Matrix Tests

More than 56 million gallons of radioactive and hazardous waste are stored in 177 underground storage tanks at the U.S. Department of Energy’s (DOE’s) Hanford Site in Washington State. The HLW will be vitrified in the HLW facility for ultimate disposal at an offsite federal repository. A portion (~35%) of the LAW will be vitrified in the LAW vitrification facility for disposal onsite at the Integrated Disposal Facility (IDF). The pretreatment and HLW vitrification facilities will have the capacity to treat and immobilize all of the wastes destined for those facilities. However, a second facility will be needed for the expected volume of LAW requiring immobilization. Cast Stone, a cementitious waste form, is being considered to provide the required additional LAW immobilization capacity. The Cast Stone waste form must be acceptable for disposal in the IDF. The Cast Stone waste form and immobilization process must be tested to demonstrate that the final Cast Stone waste form can comply with the waste acceptance criteria for the disposal facility and that the immobilization processes can be controlled to consistently provide an acceptable waste form product. A testing program was developed in fiscal year (FY) 2012 describing in detail the work needed to develop and qualify Cast Stone as a waste form for the solidification of Hanford LAW. A statistically designed test matrix was used to evaluate the effects of key parameters on the properties of the Cast Stone as it is initially prepared and after curing. For the processing properties, the water-to-dry-blend mix ratio was the most significant parameter in affecting the range of values observed for each property. The single shell tank (SST) Blend simulant also showed differences in measured properties compared to the other three simulants tested. A review of the testing matrix and results indicated that an additional set of tests would be beneficial to improve the understanding of the impacts noted in the Screening Matrix tests. A set of Cast Stone formulations were devised to augment the original screening test matrix and focus on the range of the test conditions. Fly ash and blast furnace slag were limited to either northwest or southeast and the salt solutions were narrowed to the Average and the SST Blend at the 7.8M Na concentration. To fill in the matrix, a mix ratio of 0.5 was added. In addition, two admixtures, Xypex Admix C-500 and Rheomac SF100 (silica fume), were added as an additional dry material binder in select compositions. As in the Screening Matrix, both fresh and cured properties were evaluated for the formulations. In this study, properties that were influenced by the W/DM ratio in the Screening Matrix; flow diameter, plastic viscosity, density, and compressive strength, showed consistent behavior with respect to W/DM. The leach index for highly soluble components, sodium and nitrate, were not influenced by changes in formulation or the admixtures. The leach index for both iodine and Tc-99 show an influence from the addition of the admixture, Xypex Admix C-500. Additional testing should be performed to further evaluate the influence of Xypex Admix C-500 on the leach index over a range of admixture concentrations, Cast Stone formulations, and curing and storage conditions.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Accelerated version of NUBEAM capabilities in DIII-D using neural networks

A neural network model of the effects of neutral beam injection on DIII-D has been developed. The training and testing data used by the model have been generated by the NUBEAM module of TRANSP for experimental discharges from the 2018 DIII-D campaign. Using a principle component analysis to reduce the dimensionality of profile data, the model has been shown to reproduce the results of the Monte Carlo code NUBEAM with a high level of accuracy and an execution time orders of magnitude faster than the execution time of NUBEAM. Furthermore, this makes the neural network model uniquely suited to applications in model-based scenario planning (off-line) and active control (on-line), where a large number of simulation runs are required by the associated optimization tasks that need to be performed before and during the discharge.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

Scenario optimization for the tokamak ramp-down phase in RAPTOR: Part B. safe termination of DEMO plasmas

An optimized plasma current ramp-down strategy is critical for safe and fast termination of plasma discharges in a tokamak demonstration fusion reactor (DEMO), both in planned and emergency scenarios, avoiding plasma disruptions and excessive heat loads to the first wall. Plasma stability limits and machine-specific technical requirements constrain the stable envelope through which the plasma must be navigated. Large amounts of auxiliary heating are required throughout the ramp-down phase, to avoid a radiative collapse in the presence of intrinsic tungsten and seeded xenon impurities, as quantitatively estimated in this work. As the plasma current is reduced, the current density becomes increasingly peaked, reflected by a growing value of the internal inductance $\ell$ $i3$ , resulting in reduced controllability of the vertical position of the plasma. The feasibility of different plasma current ramp-down rates is tested by applying an automated optimization framework embedding the RAPTOR core transport solver. Optimal time traces for plasma current $I$ $p$ $(t)$ and plasma elongation $κ(t)$ are proposed, to satisfy an $I$ $p$ -dependent upper limit on the plasma internal inductance, as obtained from vertical stability studies using the CREATE-NL code, as well as a constraint on the time evolution of $q$ 95 , to avoid an ideal MHD mode. A negative current density near the plasma edge is observed in our simulations, even for the most conservative $I$ $p$ ramp-down rate, indicating significant transient dynamics due to a large resistive time.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Automating Traffic Microsimulation from SYNCHRO UTDF to SUMO

Modern transportation research relies on seamlessly integrating traffic signal data with robust network representation and simulation tools. This study presents utdf2gmns, an open-source Python tool that automates conversion of the Universal Traffic Data Format, including network representation, signalized intersections, and turning volumes into the General Modeling Network Specification (GMNS) Standard. The resulting GMNS-compliant network can be converted for microsimulation in SUMO. By automatically extracting intersection control parameters and aligning them with GMNS conventions, utdf2gmns minimizes manual preprocessing and data loss. utdf2gmns also integrates with the Sigma-X engine to extract and visualize key traffic control metrics, such as phasing diagrams, turning volumes, volume-tocapacity ratios, and control delays. This streamlined workflow enables efficient scenario testing, accurate model building, and consistent data management. Validated through case studies, utdf2gmns reliably models complex urban corridors, promoting reproducibility and standardization. Documentation is available on GitHub and PyPI, supporting easy integration and community engagement.

Luo, Roy [ORNL] (ORCID:0009000312909983)↗

DOE OSTI2025

Unified differentiable digital twin for the IOTA/FAST facility

As the design complexity of modern accelerators grows, there is more interest in using advanced simulations that have fast execution time or produce insights about accelerator state. One notable example of additional information are gradients of physical observables with respect to design parameters produced by differentiable simulations. The IOTA/FAST facility has recently begun a program to implement and experimentally validate a unified start-to-end differentiable digital twin to serve as a virtual accelerator test stand, allowing for rapid prototyping of new software and experiments with minimal beam time costs. In this contribution we will discuss our plans and progress. Specifically, we will cover the selection and benchmarking of both physics and ML codes, the development of generic interfaces between device models and surrogate or physics-based sections, and the export of the parameters through either a deterministic event loop or a fully asynchronous EPICS soft input/output controller. We will also discuss challenges in model calibration and uncertainty quantification, as well as future plans to support larger proton accelerators like PIPII and Booster.

Kuklev, Nikita [Fermilab]↗