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DOE OSTI2024

Formation of a spherical plasma liner for plasma-jet-driven magneto-inertial fusion

Plasma-jet-driven magneto-inertial fusion is an alternative approach to controlled nuclear fusion, which aims to utilize a line-replaceable dense plasma liner as a repetitive spherical compression driver. In this experiment, first measurements of the formation of a spherical argon plasma liner formed from 36 discrete pulsed plasma jets are obtained on the Plasma Liner Experiment. Properties including liner uniformity and morphology, plasma density, temperature, and ram pressure are assessed as a function of time throughout the implosion process and indicate an apparent transition from initial kinetic inter-jet interpenetration to collisional regime near stagnation times, in accordance with theoretical expectation. A lack of primary shock structures between adjacent jets during flight implies that arbitrarily smooth liners may be formed by way of corresponding improvements in jet parameters and control. The measurements facilitate the benchmarking of computational models and understanding the scaling of plasma liners toward fusion-relevant energy density.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2023

MORS Phalax Ad for Systems Analysis

At Lawrence Livermore National Laboratory, applying cutting-edge science and technology to challenging security questions is an everyday thing. Systems Analysis is one way we solve problems—by bringing analytic rigor to missions like strategic deterrence and critical infrastructure defense. Working with the brightest minds in science, technology, and engineering, systems analysts at LLNL bring state-of-the-art analytic tools to bear on problems of national importance. From ensuring the safety, security, and effectiveness of our nation’s nuclear stockpile to shaping the future of inertial fusion energy—if you have a penchant for problem-solving using modeling and analysis tools—we have a place for you.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2023

Process Optimization

Process optimization is the discipline of adjusting a process to optimize a specified set of parameters without violating engineering constraints. This article reviews data-driven optimization methods based on genetic algorithms and stochastic models and demonstrates their use in powder-bed fusion and directed energy deposition processes. In the latter case, closed-loop feedback is used to control melt pool temperature and cooling rate in order to achieve desired microstructure.

Sprayberry, Michael↗

DOE OSTI2024

Prediction of performance and turbulence in ITER burning plasmas via nonlinear gyrokinetic profile prediction

Burning plasma performance, transport, and the effect of hydrogen isotope (H, D, D-T fuel mix) on confinement has been predicted for ITER baseline scenario (IBS) conditions using nonlinear gyrokinetic profile predictions. Accelerated by surrogate modeling (Rodriguez-Fernandez et al 2022 Nucl. Fusion 62 076036), high fidelity, nonlinear gyrokinetic simulations performed with the CGYRO code (Candy et al 2016 J. Comput. Phys. 324 73), were used to predict profiles of T i , T e , and n e while including the effects of alpha heating, auxiliary power (NBI + ECH), collisional energy exchange, and radiation losses inside of $r/a$ = 0.9. Predicted profiles and resulting energy confinement are found to produce fusion power and gain that are approximately consistent with mission goals ($P_\textrm{fusion} = 500$ MW at Q = 10) for the baseline scenario and exhibit energy confinement that is within 1σ of the H-mode energy confinement scaling. The power of the surrogate modeling technique is demonstrated through the prediction of alternative ITER scenarios with reduced computational cost. These scenarios include conditions with maximized fusion gain and an investigation of potential resonant magnetic perturbation (RMP) effects on performance with a minimal number of gyrokinetic profile iterations required (3–6). These predictions highlight the stiff ITG nature of the core turbulence predicted in the ITER baseline and demonstrate that $Q \gt$ 17 conditions may be accessible by reducing auxiliary input power while operating in IBS conditions. Prediction of full kinetic profiles allowed for the projection of hydrogen isotope effects around ITER baseline conditions. The gyrokinetic fuel ion species was varied from H, D, and 50/50 D-T and kinetic profiles were predicted. Results indicate that a weak or negligible isotope effect will be observed to arise from core turbulence in IBS conditions. The resulting energy confinement, turbulence, and density peaking, and the implications for ITER operations will be discussed.

gyrokinetics↗

DOE OSTI2023

Ray-based cross-beam energy transfer modeling for broadband lasers

Broadband lasers have the potential to mitigate cross-beam energy transfer (CBET) in direct-drive inertial confinement fusion (ICF) experiments. Furthermore, a quantitative assessment of the bandwidth required for CBET mitigation necessitates the development of broadband ray-based CBET models that can be implemented in the radiation-hydrodynamic codes that are used to design ICF experiments. Two different approaches to broadband ray-based CBET modeling (discrete and fixed spectrum) are developed and compared to wave-based calculations. Both approaches give good agreement with wave-based calculations in ICF-relevant configurations. Full-scale 3D calculations show that the bandwidth required for adequate CBET mitigation increases with increasing scale and drive intensity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Impact of shell structure on the fusion of neutron-rich mid-mass nuclei

The influence of shell effects on fusion of mid-mass nuclei is explored using isotopic chains of K and Ar ions on an oxygen target. Comparison of the reduced excitation functions reveals that the fusion cross section for the open neutron-shell projectile nuclei 41 K and 45 K is systematically larger than for the closed neutron-shell projectiles 39 K and 47 K. Furthermore, the São Paulo fusion model using matter densities from systematics fails to describe the measured excitation functions. Use of more realistic densities from a Dirac-Hartree-Bogoliubov (DHB) approach performs significantly better though it still overpredicts the closed-shell nuclei.

39 ≤ A ≤ 58↗

DOE OSTI2026

Time-dependent scenario modeling for the ST-E1 fusion power plant

ST-E1 is a low aspect ratio fusion power plant being designed by Tokamak Energy targeting 1.5 GW of fusion power. Characterization of the ST-E1 flat-top scenario is described elsewhere McNamara et al (2026 Nucl. Fusion 66 086008); here we focus on addressing the question of how to ramp-up the ST-E1 plasma from an initial state following breakdown and flux-surface formation to the target flat-top state. Being low-aspect ratio, the available solenoid flux of ST-E1 is limited. Therefore, particular consideration is placed on developing ramp-up scenarios that predominantly use inductive flux provided by external vertical field coils. Through time-dependent modeling with METIS, we show that this is possible when the ramp-up is performed at relatively high plasma density: although auxiliary current drive efficiency is reduced, this is significantly outweighed by (1) higher electron-ion collisional equilibration, (2) higher fusion power once ions become sufficiently hot, (3) higher poloidal beta for increased vertical-field flux, and (4) potentially favorable exhaust compatibilities. Ultimately, we show the target ST-E1 flat-top performance can be reached after a ramp-up period lasting 150 s using less than 40 Vs of solenoid flux (with vertical field providing ∼ 90 Vs of flux). The sensitivity to model assumptions are presented, with the general observation that deleterious effects can be mitigated through minor alterations of the auxiliary power temporal waveform and/or total auxiliary power level. The impact of a solenoid and the auxiliary power mix (electron cyclotron heating only versus electron and ion cyclotron heating) on the ST-E1 ramp-up success are also discussed in appendices. On this latter topic, we show that the effect of direct-ion heating during ramp-up is obscured by the uncertainty in the pedestal dynamics, identifying a clear line of future work required to make a definite decision on the ST-E1 auxiliary power mix.

current ramp-up↗

DOE OSTI2024

Liquid lithium divertor analysis using coupled plasma material interaction model

A liquid lithium divertor can improve performance of future fusion devices by creating efficient power exhaust and improving the energy confinement via pumping of the hydrogen isotopes. In addition, significantly higher heat fluxes can be handled if controlled vapor shielding is used to redistribute the divertor heat flux over a wider area. Design and optimization of such a system calls for an analysis model which includes a strong two-way coupling between the plasma and divertor material. The incoming plasma heat and particle flux will affect the divertor surface temperature, which is a defining factor of the lithium evaporative and sputtered flux going into the plasma. Results of the coupled model based on the plasma edge code SOLPS-ITER and the computational fluid dynamics (CFD) code ANSYS-CFX will be presented for different configurations. An analytical slab flow model is used as a heat transfer boundary condition for SOLPS, defining particle flux from the wall via calculation of the surface temperature. At the final step, results of the SOLPS analysis are verified using a 3D CFD magnetohydrodynamics (MHD) analysis which uses heat and particle flux from SOLPS as a boundary condition. In addition to plasma heat flux, both analytical and CFD temperature models include several plasma material interaction effects, such as lithium evaporation, condensation and sputtering based on deuterium target flux. New adatom sputtering model based on the available experimental data is presented. Analytical model is expanded to include free surface axisymmetric configurations. Results of parametric studies of the divertor configurations with different lithium inlet temperature and velocity will be presented leading to the optimal design resulting in the lowest possible lithium contamination in the core.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2021

Predicting phase transformation kinetics during metal additive manufacturing using non-isothermal Johnson-Mehl-Avrami models: Application to Inconel 718 and Ti-6Al-4V

Here, a computational model was developed to predict solid-state phase transformation kinetics within mechanical parts during metal additive manufacturing processes. This model is a modified version of the Johnson-Mehl-Avrami model for non-isothermal phase transformations that can be applied to various material systems undergoing solid-state phase transformations. Using the thermal history of an additive manufacturing fabricated mechanical part, along with the necessary thermodynamic data and kinetic information as inputs, the model outputs the history of phase fraction evolution during the build process. The model was applied to an Inconel 718 part built by powder bed fusion and a Ti-6Al-4V part built by directed energy deposition. Microstructure characterization and mechanical testing were performed for the validation of the model.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Development of a high current density, high temperature superconducting cable for pulsed magnets

Abstract A low AC loss Rare Earth Barium Copper Oxide (REBCO) cable, based on the VIPER cable technology has been developed by Commonwealth Fusion Systems for use in high field, REBCO based tokamaks. The new cable is composed of partitioned and transposed copper ‘petals’ shaped to fit together in a circular pattern with each petal containing a REBCO tape stack and insulated from each other to reduce AC losses. A stainless steel jacket adds mechanical robustness—also serving as a vessel for solder impregnation—while a tube runs through the middle for cooling purposes. Additionally, fiber optic sensors are placed under the tape stacks for quench detection. To qualify this design, a series of experiments were conducted as part of the SPARC tokamak Central Solenoid Model Coil program—to retire the risks associated with full scale, fast ramping, high flux HTS Central Solenoid (CS) and Poloidal Field (PF) coils for tokamak fusion power plants and net energy demonstrators. These risk study and risk reduction experiments include (1) AC loss measurement and model validation in the range of ~5 T/s, (2) an IxB electromagnetic loading of over 850 kN/m at the cable level and up to 300 kN/m at the stack level, (3) a transverse compression resilience of over 350 MPa, (4) manufacturability at tokamak relevant speeds and scales, (5) cable to cable joint performance, (6) fiber optic based quench detection speed, accuracy, and feasibility, and (7) overall winding pack integration and magnet assembly. The result is a cable technology, now referred to as PIT VIPER, with AC losses that measure fifteen times lower (at ~5 T/s) than its predecessor technology; a 2% or lower degradation of critical current (Ic) at high IxB electromagnetic loads; no detectable Ic degradation up to 570 MPa of transverse compression on the cable unit cell; end to end magnet manufacturing, consistently producing Ic values within 7% of the model prediction; cable to cable joint resistances at 20 K on the order of ~15 nΩ; and fast, functional quench detection capabilities that do not involve voltage taps. This cable technology will be tested comprehensively in a Central Solenoid Model Coil to prove its readiness for compact, high field tokamak operation.

Sanabria, Charlie (ORCID:0000000150175309)↗

DOE OSTI2024

Prediction of laser beam spatial profiles in a high-energy laser facility by use of deep learning

We adapt the significant advances achieved recently in the field of generative artificial intelligence/machine-learning to laser performance modeling in multipass, high-energy laser systems with application to high-shot-rate facilities relevant to inertial fusion energy. Advantages of neural-network architectures include rapid prediction capability, data-driven processing, and the possibility to implement such architectures within future low-latency, low-power consumption photonic networks. Four models were investigated that differed in their generator loss functions and utilized the U-Net encoder/decoder architecture with either a reconstruction loss alone or combined with an adversarial network loss. We achieved inference times of 1.3 ms for a 256 × 256 pixel near-field beam with errors in predicted energy of the order of 1% over most of the energy range. It is shown that prediction errors are significantly reduced by ensemble averaging the models with different weight initializations. These results suggest that including the temporal dimension in such models may provide accurate, real-time spatiotemporal predictions of laser performance in high-shot-rate laser systems.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

BESS-STAIR: a framework to estimate daily, 30m, and all-weather crop evapotranspiration using multi-source satellite data for the US Corn Belt

Abstract. With increasing crop water demands and drought threats, mapping andmonitoring of cropland evapotranspiration (ET) at high spatial and temporalresolutions become increasingly critical for water management andsustainability. However, estimating ET from satellites for precise waterresource management is still challenging due to the limitations in bothexisting ET models and satellite input data. Specifically, the process of ETis complex and difficult to model, and existing satellite remote-sensing datacould not fulfill high resolutions in both space and time. To address theabove two issues, this study presents a new high spatiotemporal resolution ETmapping framework, i.e., BESS-STAIR, which integrates a satellite-drivenwater–carbon–energy coupled biophysical model, BESS (Breathing Earth SystemSimulator), with a generic and fully automated fusion algorithm, STAIR(SaTallite dAta IntegRation). In this framework, STAIR provides daily 30'mmultispectral surface reflectance by fusing Landsat and MODIS satellite datato derive a fine-resolution leaf area index and visible/near-infrared albedo,all of which, along with coarse-resolution meteorological and CO 2 data, are used to drive BESS to estimate gap-free 30 m resolution daily ET.We applied BESS-STAIR from 2000 through 2017 in six areas across the US CornBelt and validated BESS-STAIR ET estimations using flux-tower measurementsover 12 sites (85 site years). Results showed that BESS-STAIR daily ETachieved an overall R2=0.75, with root mean square error RMSE=0.93 mm d -1 and relative error RE =27.9 % when benchmarkedwith the flux measurements. In addition, BESS-STAIR ET estimations capturedthe spatial patterns, seasonal cycles, and interannual dynamics well indifferent sub-regions. The high performance of the BESS-STAIR frameworkprimarily resulted from (1) the implementation of coupled constraints onwater, carbon, and energy in BESS, (2) high-quality daily 30 m data from theSTAIR fusion algorithm, and (3) BESS's applicability under all-skyconditions. BESS-STAIR is calibration-free and has great potentials to be areliable tool for water resource management and precision agricultureapplications for the US Corn Belt and even worldwide given the globalcoverage of its input data.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

2D kinetic-ion simulations of inverted corona fusion targets

Laser-driven “inverted corona” fusion targets have attracted interest as a low-convergence neutron source and platform for studying kinetic physics. The scheme consists of a hollow or gas-filled spherical shell made of deuterated plastic. The shell has one or more laser entrance holes (LEH), resembling a spherical hohlraum. The laser passes through the LEH’s and illuminates the interior surface of the shell, ablating a plasma that travels inward towards the target center. Long ion mean free paths in the converging plasma can lead to significant interpenetration, atomic mix, and other kinetic effects. Here, in this work we report on numerical simulations of inverted corona targets using the kinetic-ion, fluid–electron hybrid particle-in-cell (PIC) approach in 2D RZ geometry. 2D simulations suggest that shape effects do not have a significant impact on plasma evolution and observed yield trends are primarily the result of 1D kinetic mix mechanisms. Simulations are also compared against available experimental data recorded at the OMEGA laser facility. In particular, synthetic x-ray emission images show good qualitative agreement with experimental results, albeit with an apparent timing discrepancy for the two-sided vacuum target. More generally, we demonstrate the potential of hybrid-PIC simulations for full-system modeling and experimental design, including collisional absorption of laser energy, plasma evolution, mix, and fusion burn.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Search for beyond-mean-field signatures in heavy-ion fusion reactions

Examination of high-resolution, experimental fusion excitation functions for 16,17,18 O + 12 C reveals a remarkable irregular behavior that is rooted in the structure of both the colliding nuclei and the quasi-molecular composite system. The impact of the l-dependent fusion barriers is assessed using a time-dependent Hartree-Fock model, viewed as a mean-field reference. Barrier penetrabilities, taken directly from a density-constrained calculation, provide a significantly improved description of the experimental data as compared to the standard Hill-Wheeler approach. Furthermore, the remaining deviations between the parameter-free theoretical mean-field predictions and experimental fusion cross sections are exposed and discussed.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2021

Constraining computational modeling of indirect drive double shell capsule implosions using experiments

Double shell capsule implosions are an alternative approach to achieving alpha heating on the National Ignition Facility. Current machining techniques construct the outer shell as two hemispheres that are glued together, and the deuterium and tritium (DT) liquid inside the inner shell will be injected by a fill tube. These features introduce asymmetries and jetting that may disrupt the confinement of the DT fuel if not carefully controlled. Simulations indicate that in order to achieve high yields in the laboratory, these features as well as susceptibility to the Rayleigh–Taylor instability (RTI) must be mitigated. Furthermore, due to uncertainties in computational models and the expense of using the best physics models at adequate resolution in three dimensions, our computational modeling must be constrained by experiments. We report on the results of recent hydrogrowth radiography and dual-axis keyhole experiments with double shell targets that have been used to evaluate our modeling of the outer shell joint as well as the impacts of high-energy x-ray preheat that strongly impacts RTI growth. Our simulations show good agreement with the experimental data and inform several important modeling choices.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2024

Quantum computation of stopping power for inertial fusion target design

Stopping power is the rate at which a material absorbs the kinetic energy of a charged particle passing through it—one of many properties needed over a wide range of thermodynamic conditions in modeling inertial fusion implosions. First-principles stopping calculations are classically challenging because they involve the dynamics of large electronic systems far from equilibrium, with accuracies that are particularly difficult to constrain and assess in the warm-dense conditions preceding ignition. Here, we describe a protocol for using a fault-tolerant quantum computer to calculate stopping power from a first-quantized representation of the electrons and projectile. Our approach builds upon the electronic structure block encodings of Su et al. [ PRX Quant. 2 , 040332 (2021)], adapting and optimizing those algorithms to estimate observables of interest from the non-Born–Oppenheimer dynamics of multiple particle species at finite temperature. We also work out the constant factors associated with an implementation of a high-order Trotter approach to simulating a grid representation of these systems. Ultimately, we report logical qubit requirements and leading-order Toffoli costs for computing the stopping power of various projectile/target combinations relevant to interpreting and designing inertial fusion experiments. We estimate that scientifically interesting and classically intractable stopping power calculations can be quantum simulated with roughly the same number of logical qubits and about one hundred times more Toffoli gates than is required for state-of-the-art quantum simulations of industrially relevant molecules such as FeMoco or P450.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2026

Multi‐Scale Model‐Informed Deep Learning for Plasma‐Nanoparticle Interaction

The Overarching Goal of this proposed research is to understand and quantitively determine the interactions between non-thermal plasma (hot electrons, reactive radicals, vibrationally excited species) and surface reactions on influencing the activity and selectivity of the desired reactions via developing multi-scale model informed deep learning algorithm. Investigating non-thermal plasma-surface interaction is feasible due to the low bulk temperature in the discharge region. To investigate the role of plasma-nanoparticle interaction on enhancing the reaction kinetics, we will focus on ammonia cracking to generate clean hydrogen over earth-abundant, non-critical metallic nanoparticles, which is of great significance for decarbonization. We hypothesize that (1) reactive radicals interacting with surface reaction species via Eley–Rideal mechanism will significantly lower the energetics of the potential rate-limiting step of nitrogen formation; (2) the surface will be charged heterogeneously under non-thermal plasma conditions and the charged site will lower the energetics of ammonia cracking through Langmuir– Hinshelwood mechanism; (3) vibrationally excited ammonia will further promote the initial N-H bond cleavage. To access the hypothesis, we will (1) reveal the surface charge effects on tunning the reaction energetics via interpretable, physics-informed deep learning accelerated density functional theory (DFT) calculations; (2) determine the reactive radicals interacting with surface reaction species on tuning the reaction energetics via DFT; (3) reveal the surface charge effects on tunning the reaction energetics via DFT and deep learning models, (4) quantify how vibrationally excited species, reactive radicals, and surface charging effects on enhancing the catalysis via developing DFT-based microkinetic modeling (MKM) and active learning. Deep and active learning of plasma-nanoparticle interactions effects on enhancing ammonia cracking to generate hydrogen represents a new paradigm for designing high performance plasma materials. The fundamental science of how plasma-nanoparticle interactions will change the plasma kinetics and will improve the energy efficiency for decarbonization and sustainability. The interpretable and physics-informed machine learning model will accelerate low temperature plasma chemistry and material discovery with physics rules and model interpretation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Photonuclear Physics in SCALE

Radiation shielding modeling involves a wide range of applications, such as power reactors, critical experiments, portable sources, linear accelerators, and fusion systems. Particle energy ranges vary from thermal energies to fast energy spectra. MAVRIC, as the radiation shielding sequence of the SCALE code system [1] developed and maintained by Oak Ridge National Laboratory, is capable of modeling both neutron and photon interactions in matter and is widely used by the US Nuclear Regulatory Commission, Department of Energy, the National Nuclear Security Administration, and radiation shielding practitioners all around the world. Although most applications don’t involve highly energetic photons that can cause photonuclear reactions and create coupled chains of high energy, ionized electrons and bremsstrahlung radiation within a material medium, when present, these reactions can have a significant impact upon the downstream particle fluxes from incident photons above 20 MeV. For example, linear accelerators used for medical isotope production are examples of applications in which high-energetic photons are generated and used for driving or controlling other components of a complex facility. Radiation shielding analyses of such a facility would require accounting for any and all significant sources of radiation. Unfortunately, MAVRIC included no data and methods to model either photonuclear reactions or the bremsstrahlung photons until this work, which enabled accounting for both. Photonuclear reaction cross sections were imported from the Evaluated Nuclear Data File libraries, and corresponding methods were implemented in the SCALE code system; see Section 2 for how the nuclear data are imported and used. Bremsstrahlung photons were modeled by assuming thick-target approximation whereby all generated electrons and positrons due to photon interactions are assumed to be absorbed within the same material in which they were born, yielding a quick particle transport simulation method by using fast lookup tables for generating subsequent gammas; see Section 4 for details. A suite of verification models was used to test implemented methods and associated data. Tests yielded satisfactory results for the new features. Enhancements will be released as part of the next major SCALE release (v7.0), which is anticipated to be deployed in 2025, with beta releases available in the interim.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗