Implementation of Tritium-Deuterium Fusion Experiments in Z-Machine, A Pulsed Power Facility
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Garcia, Wendy [Sandia National Laboratories (SNL-N↗
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Results for “fusion experiments”
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Deep Learning Enabled Bayesian Inference of Fuel Magnetization in Magnetized Liner Inertial Fusion Experiments on Z.
Abstract not provided.
Lewis, William↗
Connecting simulation to data analysis in MagLIF fusion experiments.
Abstract not provided.
Humane, Shailaja↗
Simultaneous analysis of collinear neutron time-of-flight (nToF) traces applied to pulsed fusion experiments
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Mitrani, James M.↗
Modern version of the uncited 1938 experiment that first observed DT fusion
Experiments are described, and results are provided, for the duplication of the first-ever triton-deuterium (colloquially referred to as DT) fusion experiment accidentally performed by A.J. Ruhlig in 1938, but forgotten in the published scientific literature. Here, we find that Ruhlig overestimated the ratio of the triton-deuterium over deuteron-deuterium neutron yields in his secondary reaction (Reaction-in-Flight) experiment compared to modern theoretical calculations and our duplication of his experiment using modern neutron detection methods. Nevertheless, Ruhlig’s observation provided the motivation for the application of DT fusion after World War II and its more recent importance in peaceful energy production at DT fusion facilities around the world. Additionally, the experimental technique used in the present work provides a novel approach for checking on low-energy triton stopping powers in deuterium containing compounds.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Inferring neutron yields using indium activation samples for small fractions of tritium added to deuterium fuel in inertial confinement fusion (ICF) experiments
In inertial confinement fusion experiments, the neutron yield is an important metric for thermonuclear fusion performance. Neutron activation diagnostics can be used to infer neutron yields. The material used for neutron activation diagnostic undergoes a threshold reaction so that only neutrons having energies above the threshold energy are observed. For thermonuclear experiments using deuterium (D) and tritium (T) fuel constituents, neutrons arising from D + D reactions (DD-neutrons) and neutrons resulting from D + T reactions (DT-neutrons) are of primary interest. Indium has two neutron activation reactions that can be used to infer yields of DD-neutrons and DT-neutrons. One threshold is high enough that only DT-neutrons can induce activation, the second reaction can be activated by both DD-neutrons and DT-neutrons. Thus, to obtain the DD-neutron yield, the contribution made by DT-neutrons to the total induced activity must be extracted. In DD-fuel experiments, DT-neutrons arise from secondary reactions, which are significantly lower in number than primary DD-neutrons, and their contribution to the inferred DD-neutron yield can be ignored. When the DD- and DT-neutron yields become comparable, such as when low tritium fractions are added to DD-fuel, the contribution of DT-neutrons must be extracted to obtain accurate yields. A general method is described for this correction to DD-neutron yields.
Mangan, M. A. (ORCID:000000034583700X)↗
Energy, angle, and temperature dependencies of the sticking of D atoms on Li surfaces
Detailed experimental and computational information on the response of lithium surfaces to irradiation by slow hydrogenic particles (ions, atoms, molecules) is sparse and mainly speculative. In this work, we present a computational study of the reflection and retention of deuterium (D) atoms at crystalline and amorphous lithium surfaces at 300 and 500 K, where the D atoms have an impact energy in the range of 0.025–5 eV and incident angles of 0° (perpendicular incidence) or 85° (near-grazing incidence). Classical molecular dynamics simulations are performed with the reactive bond-order force field (ReaxFF) potentials. This study provides quantitative information on the deuterium sticking probability and recycling coefficient for lithium surfaces. Further, our results support the ongoing work at the Lithium Tokamak eXperiment-β fusion experiment as well as relevant experiments in the laboratory setting.
74 ATOMIC AND MOLECULAR PHYSICS↗
Gas scintillation mitigation in gas Cherenkov detectors for inertial confinement fusion (invited)
Gas Cherenkov detectors provide a time resolved measurement of the fusion burn in inertial confinement fusion experiments. The fusion rate delivers critical benchmark figures, such as burn width and bang time. Recent detector improvements pushed temporal resolution to 10 ps to make burn width measurements on igniting targets possible. First high temporal resolution measurements using CO 2 gas fills had a background signal with a long decay length (tail), which was caused by gas scintillation. This gas scintillation limits the ability of the detector to resolve short burn width and high frequency features in the fusion rate measurements. A thorough investigation of the cause of the tail and mitigation options for gas scintillation is presented here. As a near-term resolution, neon gas is being used to extract fusion burn histories. Paths forward for the next generation of gas Cherenkov detectors are identified including the usage of oxygen as a Cherenkov medium.
47 OTHER INSTRUMENTATION↗
Fusion of Experiments and Simulations for Real-Time Identification of Pipeline Defects
In this study, we explored fusion of experiments and simulations for real time identification of pipeline defects across physical and non-physical domains. The challenges associated to data processing were addressed and a combined classification models was presented via CNN models. In addition, regression model based on XGBOOST is built to determine the defect location and defect dimension from data-driven features of guided wave signals captured by SMS fiber optic sensor.
deep learning↗
Fusion of Experiments and Simulations for Real-Time Identification of Pipeline Defects
In this study, we explored fusion of experiments and simulations for real time identification of pipeline defects across physical and non-physical domains. The challenges associated to data processing were addressed and a combined classification models was presented via CNN models. In addition, regression model based on XGBOOST is built to determine the defect location and defect dimension from data-driven features of guided wave signals captured by SMS fiber optic sensor.
deep learning↗
A generalized forward fit for neutron detectors with energy-dependent response functions
To date, most analysis of neutron time-of-flight data from inertial confinement fusion experiments has focused on the relatively small range of energies corresponding to the primary neutrons from DD and DT fusion, and have therefore employed instrument response functions (IRF’s) corresponding to monoenergetic 2.45-MeV or 14.03-MeV neutrons. For analysis of time-of-flight signals corresponding to broader ranges of neutron energies, accurate treatment of the data requires the use of an energy-dependent IRF. Here, this work describes interpolation of the IRF for neutrons of arbitrary energy, construction of an energy-dependent IRF, and application of this IRF in a forward fit via matrix multiplication. As an example of the application of this method, an analysis of synthetic data relevant to TT fusion experiments at the Omega Laser Facility is discussed. This example is used to illustrate the differences between a forward fit that uses an energy-dependent IRF and a forward fit that uses a monoenergetic IRF. Use of the energy-dependent IRF is shown to result in accurate inference of the fit parameters of interest.
47 OTHER INSTRUMENTATION↗
Near real-time streaming analysis of big fusion data
Experiments on fusion plasmas produce high-dimensional data time series with ever-increasing magnitude and velocity, but turn-around times for analysis of this data have not kept up. For example, many data analysis tasks are often performed in a manual, ad-hoc manner some time after an experiment. In this article, we introduce the Delta framework that facilitates near real-time streaming analysis of big and fast fusion data. By streaming measurement data from fusion experiments to a high-performance compute center, Delta allows computationally expensive data analysis tasks to be performed in between plasma pulses. This article describes the modular and expandable software architecture of Delta and presents performance benchmarks of individual components as well as of an example workflow. Focusing on a streaming analysis workflow where electron cyclotron emission imaging (ECEi) data is measured at KSTAR on the National Energy Research Scientific Computing Center's (NERSC's) supercomputer we routinely observe data transfer rates of about 4 Gigabit per second. In NERSC, a demanding turbulence analysis workflow effectively utilizes multiple nodes and graphical processing units and executes them in under 5 min. We further discuss how Delta uses modern database systems and container orchestration services to provide web-based real-time data visualization. For the case of ECEi data we demonstrate how data visualizations can be augmented with outputs from machine learning models. Here, by providing session leaders and physics operators, results of higher-order data analysis using live visualizations may make more informed decisions on how to configure the machine for the next shot.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Total fusion yield measurements using deuterium–tritium gamma rays
The deuterium–tritium (DT) fusion reaction, D ( T , γ ) 5 He , has a rare (4.2 × 10 – 5 ) branching ratio that releases a ~16 MeV gamma ray instead of the more common 14.1 MeV fusion neutron. These fusion gamma rays can be used as a complementary source of measuring the net fusion yield of experiments. Fusion gamma rays have the advantage of having negligible Doppler broadening, being isotropic and less down-scattered compared to fusion neutrons. At the National Ignition Facility, we measured the DT fusion gamma rays by the Gamma Reaction History diagnostic that thresholds to only measure >10 MeV gamma rays. After removing a ~12% contribution from neutron capture interactions in deuterium, D ( n , γ ) T , and carbon, 12 C ( n , γ ) 13 C , the deviation between GRH measurements and neutron-based yield measurements has been reduced to 10%. Further improvements are needed for detailed physics comparison.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
A coded aperture with sub-mean-free-path thickness for implosion geometry imaging on ICF and IFE experiments
Inertial confinement fusion and inertial fusion energy experiments diagnose the geometry of the fusion region through imaging of the neutrons released through fusion reactions. Pinhole arrays typically used for such imaging require thick substrates to obtain high contrast along with a small pinhole diameter to obtain high resolution capability, resulting in pinholes that have large aspect ratios. This leads to expensive pinhole arrays that have small solid angles and are difficult to align. Here, we propose a coded aperture with scatter and partial attenuation (CASPA) for fusion neutron imaging that relaxes the thick substrate requirement for good image contrast. These coded apertures are expected to scale to larger solid angles and are easier to align without sacrificing imaging resolution or throughput. We use Monte Carlo simulations (Geant4) to explore a coded aperture design to measure neutron implosion asymmetries on fusion experiments at the National Ignition Facility (NIF) and discuss the viability of this technique, matching the current nominal resolution of 10 µm. The results show that a 10 mm thick tungsten CASPA can image NIF implosions with neutron yields above 10 14 with quality comparable to unprocessed data from a current NIF neutron imaging aperture. Furthermore, this CASPA substrate is 20 times thinner than the current aperture arrays for fusion neutron imaging and less than one mean free-path of 14.1 MeV neutrons through the substrate. Since the resolution, solid angle, and throughput are decoupled in coded aperture imaging, the resolution and solid angle achievable with future designs will be limited primarily by manufacturing capability.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Suppressing simulation bias in multi-modal data using transfer learning
Abstract Many problems in science and engineering require making predictions based on few observations. To build a robust predictive model, these sparse data may need to be augmented with simulated data, especially when the design space is multi-dimensional. Simulations, however, often suffer from an inherent bias. Estimation of this bias may be poorly constrained not only because of data sparsity, but also because traditional predictive models fit only one type of observed outputs, such as scalars or images, instead of all available output data modalities, which might have been acquired and simulated at great cost. To break this limitation and open up the path for multi-modal calibration, we propose to combine a novel, transfer learning technique for suppressing the bias with recent developments in deep learning, which allow building predictive models with multi-modal outputs. First, we train an initial neural network model on simulated data to learn important correlations between different output modalities and between simulation inputs and outputs. Then, the model is partially retrained, or transfer learned, to fit the experiments; a method that has never been implemented in this type of architecture. Using fewer than 10 inertial confinement fusion experiments for training, transfer learning systematically improves the simulation predictions while a simple output calibration, which we design as a baseline, makes the predictions worse. We also offer extensive cross-validation with real and carefully designed synthetic data. The method described in this paper can be applied to a wide range of problems that require transferring knowledge from simulations to the domain of experiments.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Bayesian batch optimization for molybdenum versus tungsten inertial confinement fusion double shell target design
Access to reliable, clean energy sources is a major concern for national security. Much research is focused on the “grand challenge” of producing energy via controlled fusion reactions in a laboratory setting. For fusion experiments, specifically inertial confinement fusion (ICF), to produce sufficient energy, the fusion reactions in the ICF fuel need to become self-sustaining and burn deuterium-tritium (DT) fuel efficiently. The recent record-breaking NIF ignition shot was able to achieve this goal as well as produce more energy than used to drive the experiment. This achievement brings self-sustaining fusion-based power systems closer than ever before, capable of providing humans with access to secure, renewable energy. In order to further progress toward the actualization of such power systems, more ICF experiments need to be conducted at large laser facilities such as the United States's National Ignition Facility (NIF) or France's Laser Mega-Joule. The high cost per shot and limited number of shots that are possible per year make it prohibitive to perform large numbers of experiments. As such, experimental design relies heavily on complex predictive physics simulations for high-fidelity “preshot” analysis. These multidimensional, multi-physics, high-fidelity simulations have to account for a variety of input parameters as well as modeling the extreme conditions (pressures and densities) present at ignition. Such simulations (especially in 3D) can become computationally prohibitive to turn around for each ICF experiment. In this work, we explore using Bayesian optimization with Gaussian processes (GPs) to find optimal designs for ICF double shell targets, while keeping computational costs to manageable levels. These double shell targets have an inner shell that grades from beryllium on the outer surface to the higher Z material molybdenum, as opposed to the nominally used tungsten, on the inside in order to trade off between the high performance associated with high density inner shells and capsule stability. We describe our results for “capsule-only” xRAGE simulations to study the physics between different capsule designs, inner shell materials, and potential for future experiments.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Sirius I: prototype of a prime-power source for future 1 - 10 GJ fusion-yield experiments
We have designed, assembled, and tested a prototype coaxial impedance-matched Marx generator (IMG). An IMG is a pulsed-power device that achieves electromagnetic-power amplification by triggered emission of radiation. Hence an IMG is a pulsed-power analog of a laser, with an energy efficiency of 90%. We have demonstrated that the prototype performs as predicted theoretically, thereby proving the IMG concept. We propose that a system of IMGs drive a next-generation pulsed-power accelerator that delivers 90 MA to a physics load. Such a machine would attain thermonuclear-fusion yields as high as 1 – 10 GJ, and revolutionize high energy-density-physics experiments in support of the national-security mission.
42 ENGINEERING↗
High Performance Equilibrium Solvers for Integrated Magnetic Fusion Simulations
With the funding provided by this award, we developed numerical codes for the study of magnetically confined plasmas for fusion applications. Accordingly, our work can be divided into two separate categories: 1) the design and analysis of novel numerical methods providing high accuracy and high efficiency; 2) the study of the equilibrium and stability of magnetically confined plasmas with some of these numerical codes, as well as the study of the nature of the turbulent behavior which may arise in the presence of instabilities. We first developed new numerical schemes based on integral equation methods for the computation of steady-state magnetic configurations in fusion experiments, providing high accuracy for the magnetic field and its derivatives, which are required for stability and turbulence calculations. We employed different integral formulations depending on the application of interest: axisymmetric or non-axisymmetric equilibria, force-free or magnetohydrodynamic equilibria, fixed-boundary equilibria or free-boundary equilibria. While efficient, these methods do not yet apply to plasma boundaries which are not smooth, a situation which is fairly common in magnetic confinement experiments. To address this temporary weakness, we also constructed a new steady-state solver based on the Hybridizable Discontinuous Galerkin (HDG) method, which provides full geometric flexibility. In addition to these numerical tools focused on steady-states, we also contributed to the improvement of the speed and accuracy of codes simulating the plasma dynamics of fusion plasmas, by developing a novel velocity space representation for the efficient solution of kinetic equations, which most accurately describe the time evolution of hot plasmas in fusion experiments. Using the tools discussed above, we studied several questions pertaining to the equilibrium and stability of magnetically confined plasmas. In particular, we derived a new simple model for axisymmetric devices called tokamaks, to predict how elongated a fusion plasma can be before it becomes unstable and collapses. We also looked at the effect of the shape of the outer plasma surface on key properties of the steady-state magnetic configurations, and how these properties impact turbulence in fusion plasmas, and the corresponding transport of momentum. Likewise, we studied the role of large localized flows on the steady-state magnetic configurations, and how they may influence plasma stability and turbulence. Non-axisymmetric steady-state magnetic configurations are inherently more complex than axisymmetric steady-state configurations, and the subject of ongoing controversies regarding the regularity of the equations determining such steady-states, and their solutions. Implementing an existing NYU code in a new geometry, we studied the nature of the singularity of the solutions observed in the code, and methods to eliminate them. Our main conclusion is that by appropriately tailoring the plasma boundary, it is possible to eliminate the singularities otherwise appearing in our simulations, and to obtain steady-states which appear to be smooth. To gain further insights on incompletely understood turbulence phenomena, we proposed a new reduced model capturing most of these phenomena, which is simple enough to not require expensive numerical simulations on massive supercomputers to investigate them. We demonstrated the strong similarity between our simulations and published results obtained from computationally expensive simulations, and plan to rely on our reduced model to identify the key mechanisms determining the evolution and strength turbulent driven transport in fusion plasmas. Finally, we proposed a new framework for tokamak reactor design studies, enabling us to consider the relative merits of steady-state versus pulsed fusion reactors. We found that pulsed fusion reactors may benefit most from recent advances in magnet technology, and the availability of very high field magnets. As such, they may become more desirable than steady-state tokamak reactors for cost efficient electricity generation.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗