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DOE OSTI2019

Neutron Time-of-Flight Measurements of Charged-Particle Energy Loss in Inertial Confinement Fusion Plasmas

Neutron spectra from secondary 3 H(d,n)α reactions produced by an implosion of a deuterium-gas capsule at the National Ignition Facility have been measured with order-of-magnitude improvements in statistics and resolution over past experiments. Furthermore, these new data and their sensitivity to the energy loss of fast tritons emitted from thermal 2 H(d,p) 3 H reactions enable the first statistically significant investigation of charged-particle stopping via the emitted neutron spectrum. Radiation-hydrodynamic simulations, constrained to match a number of observables from the implosion, were used to predict the neutron spectra while employing two different energy loss models. This analysis represents the first test of stopping models under inertial confinement fusion conditions, covering plasma temperatures of k B T ≈ 1–4 keV and particle densities of n ≈ (12–2) × 10 24 cm –3 . Under these conditions, we find significant deviations of our data from a theory employing classical collisions whereas the theory including quantum diffraction agrees with our data.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2015

Investigation of peeling-ballooning stability prior to transient outbursts accompanying transitions out of H-mode in DIII-D

The H-mode transport barrier allows confinement of roughly twice as much energy as in an L-mode plasma. Termination of H-mode necessarily requires release of this energy, and the timescale of that release is of critical importance for the lifetimes of plasma facing components in next step tokamaks such as ITER. H-L transition sequences in modern tokamaks often begin with a transient outburst which appears to be superficially similar to and has sometimes been referred to as a type-I edge localized mode (ELM). Type-I ELMs have been shown to be consistent with ideal peeling ballooning instability and are characterized by significant (up to ∼50%) reduction of pedestal height on short (∼1 ms) timescales. Knowing whether or not this type of instability is present during H-L back transitions will be important of planning for plasma ramp-down in ITER. This paper presents tests of pre-transition experimental data against ideal peeling-ballooning stability calculations with the ELITE code and supports those results with secondary experiments that together show that the transient associated with the H-L transition is not triggered by the same physics as are type-I ELMs.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2016

Validation of IRDFF in 252Cf standard and IRDF-2002 reference neutron fields

The results of validation of the latest release of International Reactor Dosimetry and Fusion File, IRDFF-1.03, in the standard 252Cf(s.f.) and reference 235U(nth,f) neutron benchmark fields are presented. The spectrum-averaged cross sections were shown to confirm the recommended spectrum for 252Cf spontaneous fission source; that was not the case for the current recommended spectra for 235U(nth,f). IRDFF was also validated in the spectra of the research reactor facilities ISNF, Sigma-Sigma and YAYOI, which are available in the IRDF- 2002 collection. Before this analysis, the ISFN spectrum was resimulated to remove unphysical oscillations in spectrum. IRDFF-1.03 was shown to reasonably reproduce the spectrum-averaged data measured in these fields except for the case of YAYOI.

IRDFF↗

DOE OSTI2026

Search for Higgs bosons produced in association with a high-energy photon via vector-boson fusion and decaying to a pair of b -quarks in the ATLAS detector

A search for Standard Model Higgs bosons produced in association with a high-energy photon and decaying to $b\bar{b}$ is performed using 133 fb −1 of $\sqrt{s}$ = 13 TeV pp collision data collected with the ATLAS detector at the Large Hadron Collider at CERN. The photon requirement reduces the multijet background, and the H → $b\bar{b}$ decay is the dominant decay mode. Event selection requirements target events produced by vector-boson fusion, the dominant production mode in this channel. Several improvements enhance the search sensitivity compared to previous measurements. These improvements include better background modelling and characterization, the use of a neural-network classifier, and an updated signal extraction strategy adopting a direct binned-likelihood fit to the classifier output. With these improvements, the Higgs boson signal strength is measured to be 0.2 ± 0.7 relative to the Standard Model prediction. This corresponds to an observed significance of 0.3 standard deviations, compared to an expectation of 1.5 standard deviations assuming the Standard Model.

ATLAS experiment↗

DOE OSTI2025

Data Readiness for Scientific AI at Scale

This paper examines how Data Readiness for AI (DRAI) principles apply to leadership-scale scientific datasets used to train foundation models. We analyze archetypal workflows across four representative domains—climate, nuclear fusion, bio/health, and materials—to identify common preprocessing patterns and domain-specific constraints. We introduce a two-dimensional readiness framework that combines canonical preprocessing patterns with a five-level operational readiness scale, both tailored to high-performance computing (HPC) environments. This framework helps outline key challenges in transforming large-scale scientific data into formats suitable for scalable AI training. Together, these dimensions form a conceptual maturity matrix that characterizes scientific data readiness and guides infrastructure development toward standardized, cross-domain support for scalable and reproducible AI for science.

Brewer, Wes [ORNL] (ORCID:0000000236393956)↗

DOE OSTI2023

DLIO: A DATA-CENTRIC BENCHMARK FOR DEEP LEARNING APPLICATIONS

SF-22-136 Deep learning has been shown as a successful method for various tasks, and its popularity results in numerous open-source deep learning software tools. Deep learning has been applied to a broad spectrum of scientific domains such as cosmology, particle physics, computer vision, fusion, and astrophysics. Scientists have performed a great deal of work to optimize the computational performance of deep learning frameworks. However, the same cannot be said for I/O performance. As deep learning algorithms rely on big-data volume and variety to effectively train neural networks accurately, I/O is a significant bottleneck on large-scale distributed deep learning training. DLIO, is a novel representative benchmark suite built based on the I/O profiling of the selected workloads. DLIO can be utilized to accurately emulate the I/O behavior of modern deep learning applications. Using DLIO, application developers and system software solution architects can identify potential I/O bottlenecks in their applications and guide optimizations to boost the I/O performance leading to lower training times. The storage vendor can also use DLIO as a guide for designing and optimize the storage and filesystem targeting at deep learning application.

ZHENG, HUIHUO↗

DOE OSTI2019

Tomographic Reconstruction of the Neutron Time-Energy Spectrum from a Dense Plasma Focus

A dense plasma focus (DPF) nuclear fusion generator is an attractive pulsed neutron source in many applications, due to its relatively large neutron yield, produced in a short time duration. In order to design a DPF that generates neutrons within a specified time profile, or generates a neutron energy spectrum with specific properties, it is necessary to understand and be able to fully characterize the results of the fusion process releasing the neutrons. The time-energy spectrum of fusion neutrons is an ideal quantity to use to validate multiphysics codes that simulate the pinch and fusion processes, because it is a quantity that requires the physics of each of the stages leading up to and ending in the fusion reaction to be simulated correctly. In particular, since DPF fusion neutrons are not monoenergetic – and there can often be several fusion pinches creating neutrons – a computer simulation matching high quality neutron spectrum measurements provides great confidence in the fidelity of the simulation. In order to make such a comparison, it is first necessary to have quality measurements from which to infer the spectrum. In this work we pose neutron spectroscopy as the classical tomographic inverse problem from neutron time of flight data at multiple distances, but enhanced by using detector pairs designed to reduce the scatter background and with an additional measurement of the time profile of the fusion pinch near its source. The detector pairs enhance the quality of the time of flight measurements and the additional constraint posed by the measured time profile allows for temporal resolution in the spectrum reconstruction that is equal to the measurement resolution, which can be subnanosecond, and energy resolution in the 10’s of keV, without the problem being underconstrained. We present results from a Deuterium-fueled DPF at the U.S. Department of Energy’s Nevada National Security Site and show that we can infer the time-energy spectrum from our measurements for both single and multi-pinch fusion reactions with equal fidelity.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2017

Ensemble simulations of inertial confinement fusion implosions

The achievement of inertial confinement fusion ignition on the National Ignition Facility relies on the collection and interpretation of a limited (and expensive) set of experimental data. These data are therefore supplemented with state-of-the-art multi-dimensional radiation-hydrodynamic simulations to provide a better understanding of implosion dynamics and behavior. We present a relatively large number (~4000) of systematically perturbed 2D simulations to probe our understanding of low-mode fuel and ablator asymmetries seeded by asymmetric illumination. We find that Gaussian process surrogate models are able to predict both the total neutron yield and the degradation in performance due to asymmetries. Furthermore, the surrogates are then applied to simulations containing new sources of degradation to quantify the impact of the new source.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS2023

Additive Manufacturing of Oxide Dispersion Strengthened Multi Principle Element Alloys for Future Aerospace Applications

Oxide Dispersion Strengthened (ODS) materials have long been of interest for their high temperature applications, and additive manufacturing enables their manufacturing viability. The ODS multi-principle element alloy NiCoCr was prepared using powder metallurgy techniques, additively manufactured, and evaluated for its processingmicrostructure-property relationships. The high temperature foundations of nickel-base superalloys and ODS materials were combined with the manufacturing advantages of 3D printing and the chemical simplicity of NiCoCr to inspire this work, which was divided into powder and printed material assessments. The project was achieved through multiple iterative project loops to assess the processing parameters’ impact on the microstructure and mechanical properties of the feedstock powder and printed material. The powder investigations (Chapter 3) focused on understanding the oxide coating that formed on the metal powder following acoustic mixing. Time of Flight Secondary Ion Mass Spectrometry was used to semi-quantitatively assess the amount of yttrium on the surface of the mixed powders, and indicated that a combination of higher mixing condition energy and moderate mixing time resulted in the most oxide coating on the NiCoCr powder. The results were supported by a qualitative assessment of scanning electron images of coated powder particles. Following mixing, the ODS NiCoCr was consolidated by Laser Powder Bed Fusion. The evaluations of the printed material (Chapter 4) frst considered screening experiments including Archimedes’ density, porosity, and grain size and number metrics from electron backscatter diffraction data. After the ideal additive manufacturing parameters were identifed, both the oxide homogeneity and yield strength were discussed for the idealized printed material. Overall, the project suggests that the combined use of qualitative or semi-quantitative powder surface analysis with Archimedes’ density analyses can be a valid high-throughput technique which can lead to process optimization of Laser Powder Bed Fusion additively manufactured ODS material.

Laura G Wilson↗

DOE OSTI2021

Uranium Bed Design Parameters for Tritium Plants Supporting Fusion Reactors

Uranium hydride is commonly used to store hydrogen or its isotopes in a solid state. The Self-Assaying Tritium Accountancy and Containment Unit for ITER (STACI) is a 5.2-kg bed of depleted uranium (dU) capable of holding up to 33 mol of hydrogen or its isotopes. Here we summarize the data analysis of past experimental campaigns with STACI, with the aim of describing the kinetics and thermodynamics of the hydriding process. Computed tomography imaging was performed on STACI both before and after its experimental campaign, and a high degree of swelling was observed in the dU. Literature on studies in regard to the swelling of large (multikilogram) quantities of uranium hydride for storage applications was not identified during this study. Data from the experimental campaign, as well as data on the formation reaction, are presented. The authors hope to create an analytical model of STACI based on these data.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2013

What is Data-Intensive Science?

What is Data Intensive Science? Today we are living in a digital world, where scientists often no longer interact directly with the physical object of their research, but do so via digitally captured, reduced, calibrated, analyzed, synthesized and, at times, visualized data. Advances in experimental and computational technologies have lead to an exponential growth in the volumes, variety and complexity of this data and while the deluge is not happening everywhere in an absolute sense, it is in a relative one. Science today is data intensive. Data intensive science has the potential to transform not only how we do science, but how quickly we can translate scientific progress into complete solutions, policies, decisions and ultimately economic success. Critically, data intensive science touches some of the most important challenges we are facing. Consider a few of the grand challenges outlined by the U.S. National Academy of Engineering: make solar energy economical, provide energy from fusion, develop carbon sequestration methods, advance health informatics, engineer better medicines, secure cyberspace, and engineer the tools of scientific discovery. Arguably, meeting any of these challenges requires the collaborative effort of trans-disciplinary teams, but also significant contributions from enabling data intensive technologies. Indeed for many of them, advances in data intensive research will be the single most important factor in developing successful and timely solutions. Simple extrapolations of how we currently interact with and utilize data and knowledge are not sufficient to meet this need. Given the importance of these challenges, a new, bold vision for the role of data in science, and indeed how research will be conducted in a data intensive environment is evolving.

Data Intensive Science↗

DOE OSTI2018

Energy levels and radiative rates for transitions in Cr-like Kr XIII, Tc XX and Xe XXXI

Energy levels, radiative transition probabilities, Landé g-factors, and radiative lifetimes are reported for 144 levels of the 3p{sup 6}3d{sup 6} and 3p{sup 5}3d{sup 7} configurations of the Cr-like ions Kr XIII, Tc XX and Xe XXXI. Since to our knowledge no prior data for energy levels or A-values, experimental or theoretical, are available in the literature for these ions, calculations have been performed with three independent atomic structure codes, namely GRASP, FAC and a code implementing the QR approach, with increasing configuration interaction (CI) basis with each code. This is to establish the accuracy of the calculated results so that data can be confidently applied in the modeling of plasmas. Our recommended data are determined within the QR approach, because not only has the largest CI basis been included in this calculation, the reliability has already been established in our earlier work for other Cr-like ions, for which some experimental and theoretical data were available for comparison. Results for radiative rates (A-values) and transition wavelengths (λ) are listed for all strong E1, E2 and M1 transitions among the 144 levels of each ion.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

NASA NTRS1990

A sensor fusion field experiment in forest ecosystem dynamics

The background of the Forest Ecosystem Dynamics field campaign is presented, a progress report on the analysis of the collected data and related modeling activities is provided, and plans for future experiments at different points in the phenological cycle are outlined. The ecological overview of the study site is presented, and attention is focused on forest stands, needles, and atmospheric measurements. Sensor deployment and thermal and microwave observations are discussed, along with two examples of the optical radiation measurements obtained during the experiment in support of radiative transfer modeling. Future activities pertaining to an archival system, synthetic aperture radar, carbon acquisition modeling, and upcoming field experiments are considered.

Smith, James A.↗

DOE OSTI2021

Search for dark photons in Higgs boson production via vector boson fusion in proton-proton collisions at $ \sqrt{s} $ = 13 TeV

A search is presented for a Higgs boson that is produced via vector boson fusion and that decays to an undetected particle and an isolated photon. The search is performed by the CMS collaboration at the LHC, using a data set corresponding to an integrated luminosity of 130 fb$^{−1}$, recorded at a center-of-mass energy of 13 TeV in 2016–2018. No significant excess of events above the expectation from the standard model background is found. The results are interpreted in the context of a theoretical model in which the undetected particle is a massless dark photon. An upper limit is set on the product of the cross section for production via vector boson fusion and the branching fraction for such a Higgs boson decay, as a function of the Higgs boson mass. For a Higgs boson mass of 125 GeV, assuming the standard model production rates, the observed (expected) 95% confidence level upper limit on the branching fraction is 3.5 (2.8)%. This is the first search for such decays in the vector boson fusion channel. Combination with a previous search for Higgs bosons produced in association with a Z boson results in an observed (expected) upper limit on the branching fraction of 2.9 (2.1)% at 95% confidence level.[graphic not available: see fulltext]

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Uranium integral fission product yields for a spectrally-shaped 14.1 MeV neutron source at the National Ignition Facility

This paper describes the experimental results for an energy tuning assembly created to modify the National Ignition Facility deuterium–tritium fusion neutron source into a notional thermonuclear and prompt fission neutron spectrum, which has applications in integral measurements, nuclear data benchmarks, and radiation effects on microelectronics. The Monte Carlo neutron transport utilized MCNP5 to estimate the ETA-modified fluence using the ENDF-B/VIII.0 and IRDFF-II continuous energy nuclear data libraries, and SCALE Sampler was used to estimate the systematic nuclear data covariance using ENDF-B/VII.1 and IRDFF-II in a 252-group structure. The experiment fielded eight activation foils and a highly enriched uranium sample. This provided fifteen reaction channels that were used in a forward-fit comparison to the modeled results and to unfold the neutron spectrum using STAYSL. Gamma-ray spectrometry was performed on the activation and highly enriched uranium foils, and the reduced Χ 2 between the modeled and experimental values was 1.21. The results from the STAYSL unfold, reduced Χ 2 = 1.62, indicated that the modeled neutron spectrum was achieved and the systematic nuclear data uncertainty associated with the neutron transport and activation product cross sections was representative of the experiment. Integral cumulative fission product yield data were collected for 37 mass chains with a combination of gamma-ray spectrometry and radiochemical analysis. Fission product analysis was generally in agreement with two models using a semi-empirical fit and the General Observables of Fission code, with the exception of mass chains 88, 109, 111, 112, 113, 129, 139, 142, 144, 151, and 156.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

DOE OSTI2024

Quantification and visualization of uncertainties in reconstructed penumbral images of implosions at Omega

Penumbral imaging is a technique used in plasma diagnostics in which a radiation source shines through one or more large apertures onto a detector. To interpret a penumbral image, one must reconstruct it to recover the original source. The inferred source always has some error due to noise in the image and uncertainty in the instrument geometry. Interpreting the inferred source thus requires quantification of that inference’s uncertainty. Markov chain Monte Carlo algorithms have been used to quantify uncertainty for similar problems but have never been used for the inference of the shape of an image. Because of this, there are no commonly accepted ways of visualizing uncertainty in two-dimensional data. This paper demonstrates the application of the Hamiltonian Monte Carlo algorithm to the reconstruction of penumbral images of fusion implosions and presents ways to visualize the uncertainty in the reconstructed source. This methodology enables more rigorous analysis of penumbral images than has been done in the past.

Instruments & Instrumentation↗

DOE OSTI2023

A Co-Registered In-Situ and Ex-Situ Tensile Properties Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-11)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from five Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L builds containing 6,299 SS-J3 individually tracked tensile coupons. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, room-temperature static tensile test results, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Application of Machine Learning to Monitor Metal Powder-Bed Fusion Additive Manufacturing Processes

The use of additive manufacturing (AM) is increasing for high-value, critical applications across a range of disparate industries. This article presents a discussion of high-valued engineering components predominantly used in the aerospace and medical industries. Applications involving metal AM, including methods to identify pores and voids in AM materials, are the focus. The article reviews flaw formation in laser-based powder-bed fusion, summarizes sensors used for in situ process monitoring, and outlines advances made with in situ process-monitoring data to detect AM process flaws. It reviews investigations of ML-based strategies, identifies challenges and research opportunities, and presents strategies for assessing anomaly detection performance.

Reutzel, Edward W.↗