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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 613 records · Page 34
All sourcesNASA NTRSDOE OSTI
DOE OSTI2013

Potential impacts of the Arctic on interannual and interdecadal summer precipitation over China

After the end of the 1970s, there has been a tendency for enhanced summer precipitation over South China and the Yangtze River valley and drought over North China and Northeastern China. Coincidentally, Arctic ice concentration has decreased since the late 1970s, with larger reduction in summer than spring. However, the Arctic warming is more significant in spring than summer, suggesting that spring Arctic conditions could be more important in their remote impacts. This study investigates the potential impacts of the Arctic on summer precipitation in China. The leading spatial patterns and time coefficients of the unfiltered, interannual, and interdecadal precipitation (1960-2008) modes were analyzed and compared using empirical orthogonal function (EOF) analysis, which shows that the first three EOFs can capture the principal precipitation patterns (northern, central and southern patterns) over eastern China. Regression of the Arctic spring and summer temperature onto the time coefficients of the leading interannual and interdecadal precipitation modes shows that interdecadal summer precipitation in China is related to the Arctic spring warming, but the relationship with Arctic summer temperature is weak. Moreover, no notable relationships were found between the first three modes of interannual precipitation and Arctic spring or summer temperatures. Finally, correlations between summer precipitation and the Arctic Oscillation (AO) index from January to August were investigated, which indicate that summer precipitation in China correlates with AO only to some extent. Overall, this study suggests important relationships between the Arctic spring temperature and summer precipitation over China at the interdecadal time scale.

Arctic↗
NASA NTRS1998

Estimation of Aircraft Nonlinear Unsteady Parameters From Wind Tunnel Data

Aerodynamic equations were formulated for an aircraft in one-degree-of-freedom large amplitude motion about each of its body axes. The model formulation based on indicial functions separated the resulting aerodynamic forces and moments into static terms, purely rotary terms and unsteady terms. Model identification from experimental data combined stepwise regression and maximum likelihood estimation in a two-stage optimization algorithm that can identify the unsteady term and rotary term if necessary. The identification scheme was applied to oscillatory data in two examples. The model identified from experimental data fit the data well, however, some parameters were estimated with limited accuracy. The resulting model was a good predictor for oscillatory and ramp input data.

Klein, Vladislav↗
NASA NTRS2002

Monitoring Photodeposition of Polymer Films from Diacetylene Monomer Solutions Using In Situ Real-Time Spectroscopic Ellipsometry

Photodeposition of thin polymer (PDAMNA) films from diacetylene monomer (DAMNA) solutions onto gold coated silica substrates with UV light was studied using the technique of in-situ real time spectroscopic ellipsometry. The dielectric function of PDAMNA was determined; and the thickness of the growing PDAMNA films over a 4 hour time interval was determined using a linear regression fit of the experimental data to a homogeneous four phase optical model. It was found that stirring the solution dramatically lowers the rate of film deposition, suggesting that convection can affect the attachment kinetics of the film to the substrate. Lastly, the morphology of the PDAMNA films was examined using non-contact mode atomic force microscopy.

Hui, Du↗
DOE OSTI2023

Complementing a continuum thermodynamic approach to constitutive modeling with symbolic regression

Here, an interpretable machine learning method, physics-informed genetic programming-based symbolic regression (P-GPSR), is integrated into a continuum thermodynamic approach to developing constitutive models. The proposed strategy for combining a thermodynamic analysis with P-GPSR is demonstrated by generating a yield function for an idealized material with voids, i.e., the Gurson yield function. First, a thermodynamic-based analysis is used to derive model requirements that are exploited in a custom P-GPSR implementation as fitness criteria or are strongly enforced in the solution. The P-GPSR implementation improved accuracy, generalizability, and training time compared to the same GPSR code without physics-informed fitness criteria. The yield function generated through the P-GPSR framework is in the form of a composite function that describes a class of materials and is characteristically more interpretable than GPSR-derived equations. The physical significance of the input functions learned by P-GPSR within the composite function is acquired from the thermodynamic analysis. Fundamental explanations of why the implemented P-GPSR capabilities improve results over a conventional GPSR algorithm are provided.

42 ENGINEERING↗
DOE OSTI2022

Cost function for low-dimensional manifold topology assessment

Abstract In reduced-order modeling, complex systems that exhibit high state-space dimensionality are described and evolved using a small number of parameters. These parameters can be obtained in a data-driven way, where a high-dimensional dataset is projected onto a lower-dimensional basis. A complex system is then restricted to states on a low-dimensional manifold where it can be efficiently modeled. While this approach brings computational benefits, obtaining a good quality of the manifold topology becomes a crucial aspect when models, such as nonlinear regression, are built on top of the manifold. Here, we present a quantitative metric for characterizing manifold topologies. Our metric pays attention to non-uniqueness and spatial gradients in physical quantities of interest, and can be applied to manifolds of arbitrary dimensionality. Using the metric as a cost function in optimization algorithms, we show that optimized low-dimensional projections can be found. We delineate a few applications of the cost function to datasets representing argon plasma, reacting flows and atmospheric pollutant dispersion. We demonstrate how the cost function can assess various dimensionality reduction and manifold learning techniques as well as data preprocessing strategies in their capacity to yield quality low-dimensional projections. We show that improved manifold topologies can facilitate building nonlinear regression models.

42 ENGINEERING↗
DOE OSTI2024

Uncertainty Quantification and Sensitivity Analysis of Non-Nuclear Advanced Controls Testbed Reactor Mockup

The research presented in this report describes our progress in applying stochastic methods and uncertainty quantification, parametric study, and variance-based sensitivity analysis (also known as Sobol sensitivity analysis) to a full-core model of a nuclear thermal propulsion (NTP) system simulated with Griffin, with the goal of developing a reduced order (surrogate) model which can be rapidly sampled while perturbing multiple input parameters. In this NTP system, reactivity and power feedback affect the rotation of control drums, which are controlled by a hybrid proportional, integral and derivative (PID) controller, actuated by the power demand and reactivity feedback from the numerical model. This model uses reactor kinetic feedback (mean generation time and $\beta$ from a transient Griffin simulation executed with the improved quasi-static method to provide the kinetic parameters) as inputs to functions which control the CD rotation angle. Using a number of stochastic method approaches, we developed a dual purpose training-surrogate model of the NTP system using polynomial regression. The trained model can be rapidly sampled while simultaneously perturbing various input parameters of the model, such as coefficients on the PID control, or temperature (directly affect the neutron cross section). The surrogate model delivers accurate results orders-of-magnitude faster (minutes, not days) than the base model. Once the base model has been trained, distributions of the uncertain parameters can be changed at will to investigate the effects of perturbing multiple inputs and their effect on the output. For example, coefficients used in the PID control system may vary due to some physical interference, or there may be uncertainty in the temperature of the neutron cross sections in various regions of the reactor. A distribution can be placed on these parameters and operational boundaries can be determined. The goal of this work is to support development of an advanced control system to operate CDs in a functioning NTP system.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2015

MicroRNA-224 targets ERG2 and contributes to malignant progressions of meningioma

MicroRNA-224 is overexpressed in various malignant tumors with poor prognosis, which plays a critical role in biological processes including cell proliferation, apoptosis and several developmental and physiological progressions. However, the potential association between miR-224 and clinical outcome in patients with meningiomas remains unknown. Here, we investigate miR-224 expression and biological functions in meningiomas. MiR-224 expression was measured by Northern blot analysis and quantitative reverse transcription-polymerase chain reaction (qRT-PCR) in meningioma and normal brain tissues. Kaplan–Meier analysis and Cox regression analysis were used to exam its correlation with clinicopathological features and prognostic value. The biological effects of miR-224 on the cell proliferation and apoptosis in meningioma cells were examined by MTT assay and apoptosis assay. We found the expression levels of miR-224 were significantly higher in meningioma tissues than that in normal brain, positively correlated with advanced pathological grade. Kaplan–Meier analysis indicated that meningioma patients with low miR-224 expression exhibited significantly prolonged overall and recurrence-free survival. Furthermore, we demonstrated that ERG2 was an identical candidate target gene of MiR-224 in vitro. Our results indicated that downregulation of miR-224 suppressed cell growth and resulted in the enhancement of cell apoptosis through activation of the ERG2-BAK-induced apoptosis pathway. Our findings imply the miR-224 expression could predict the overall survival and recurrence-free survival of patients with meningioma and it might be a promising therapeutic target for treating malignant meningiomas. - Highlights: • MiR-224 expression is correlates with prognosis in meningioma patients. • ERG2 is a novel downstream target of miR-224. • MiR-224 suppressed cell growth and enhanced apoptosis in IOMM-Lee and CH157 cells. • MiR-224 is an upstream regulator of the ERG2-BAK-induced apoptosis pathway.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2018

Using local knowledge and sustainable transport to promote a greener city: The case of Bucharest, Romania

Highlights: • Bicycle lane use is affected by parked cars and low accessibility to green spaces. • Criteria for developing bicycle lanes are determined by user experience and needs. • Public participation should play a key role for planning new bicycle lanes connecting green parks. Cities undergoing climate change and rapid urbanization are faced with significant transformational processes that affect the environment and society, challenging them to become more sustainable and resilient. The promotion of nature-based solutions represents an efficient approach to meet sustainability targets in cities and improve the quality of life of citizens. The association of large components of green infrastructure, such as urban parks, with physical activity can counteract the sedentary lifestyle endemic to cities and improve the overall health and well-being of individuals (Carrus et al., 2013, Scopelliti et al., 2016). By promoting a sustainable means of transport and connecting green spaces within a highly urbanized city, bicycle lanes represent an effective tool for associating physical activity with nature in cities allowing bicycle users to benefit from the positive health effects of nature-based solutions. Our study focuses on the potential of bicycle lanes to improve functional connectivity among green spaces. We administered 820 questionnaires in 34 green spaces (i.e., urban parks) in Bucharest, Romania, to identify the factors influencing the use of bicycle lanes connecting urban parks and to understand which planning criteria for bicycle lanes are considered as the most important by park visitors. We applied binary and ordinal logistic regressions and found that the factors affecting bicycle lane use are illegally parked cars and lack of accessibility to urban parks. The criteria preferred by park visitors for bicycle lane planning are determined by experience level and frequency of bicycle use. To develop a functional and integrated bicycle lane network that can make cities healthier and more sustainable, policy makers are advised to engage in a public participatory process and focus on the needs of bicycle users.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2013

Predicting objective function weights from patient anatomy in prostate IMRT treatment planning

Purpose: Intensity-modulated radiation therapy (IMRT) treatment planning typically combines multiple criteria into a single objective function by taking a weighted sum. The authors propose a statistical model that predicts objective function weights from patient anatomy for prostate IMRT treatment planning. This study provides a proof of concept for geometry-driven weight determination. Methods: A previously developed inverse optimization method (IOM) was used to generate optimal objective function weights for 24 patients using their historical treatment plans (i.e., dose distributions). These IOM weights were around 1% for each of the femoral heads, while bladder and rectum weights varied greatly between patients. A regression model was developed to predict a patient's rectum weight using the ratio of the overlap volume of the rectum and bladder with the planning target volume at a 1 cm expansion as the independent variable. The femoral head weights were fixed to 1% each and the bladder weight was calculated as one minus the rectum and femoral head weights. The model was validated using leave-one-out cross validation. Objective values and dose distributions generated through inverse planning using the predicted weights were compared to those generated using the original IOM weights, as well as an average of the IOM weights across all patients. Results: The IOM weight vectors were on average six times closer to the predicted weight vectors than to the average weight vector, usingl{sub 2} distance. Likewise, the bladder and rectum objective values achieved by the predicted weights were more similar to the objective values achieved by the IOM weights. The difference in objective value performance between the predicted and average weights was statistically significant according to a one-sided sign test. For all patients, the difference in rectum V54.3 Gy, rectum V70.0 Gy, bladder V54.3 Gy, and bladder V70.0 Gy values between the dose distributions generated by the predicted weights and IOM weights was less than 5 percentage points. Similarly, the difference in femoral head V54.3 Gy values between the two dose distributions was less than 5 percentage points for all but one patient. Conclusions: This study demonstrates a proof of concept that patient anatomy can be used to predict appropriate objective function weights for treatment planning. In the long term, such geometry-driven weights may serve as a starting point for iterative treatment plan design or may provide information about the most clinically relevant region of the Pareto surface to explore.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2018

Identifying an efficient, thermally robust inorganic phosphor host via machine learning

Abstract Rare-earth substituted inorganic phosphors are critical for solid state lighting. New phosphors are traditionally identified through chemical intuition or trial and error synthesis, inhibiting the discovery of potential high-performance materials. Here, we merge a support vector machine regression model to predict a phosphor host crystal structure’s Debye temperature, which is a proxy for photoluminescent quantum yield, with high-throughput density functional theory calculations to evaluate the band gap. This platform allows the identification of phosphors that may have otherwise been overlooked. Among the compounds with the highest Debye temperature and largest band gap, NaBaB 9 O 15 shows outstanding potential. Following its synthesis and structural characterization, the structural rigidity is confirmed to stem from a unique corner sharing [B 3 O 7 ] 5– polyanionic backbone. Substituting this material with Eu 2+ yields UV excitation bands and a narrow violet emission at 416 nm with a full-width at half-maximum of 34.5 nm. More importantly, NaBaB 9 O 15 :Eu 2+ possesses a quantum yield of 95% and excellent thermal stability.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
NASA NTRS1984

Structure function analyses of mesoscale VAS retrievals

Structure function analyses are used for a comparison of two VAS retrieval procedures, one obtained using a physical inversion technique and the other from a linear regression technique. Results from both procedures are evaluated and compared with those from a special mesoscale network of radiosonde stations, operated during March 6, 7, 1982 as part of the AVE-VAS field experiment. It is shown that both types of VAS retrievals underestimate the magnitudes of mean nondirectional gradients that are detected by the mesoscale radiosonde network. This result is expected since the VAS provides a volumetric sample of the atmosphere.

Meyer, P. J.↗
NASA NTRS2020

Mapping tree canopy cover and canopy height with L-band SAR using LiDAR data and Random Forests

Light detection and ranging (LiDAR) data can provide direct measurements of vegetation structures but are limited by the sparse spatial coverage. Polarimetric synthetic aperture radar (SAR) can perform large-scale high-resolution mapping without weather constraints but the information about vegetation and ground subsurface are mixed in the backscatter data. In this paper, we adopted the Random Forests algorithm to train an upscaling function using tree canopy cover (TCC) and canopy height model (CHM) derived from Goddard’s LiDAR, Hyperspectral and Thermal Imager (G-LiHT) data. The regression model is then applied to the L-band Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) data acquired during the 2017 Arctic-Boreal Vulnerability Experiment (ABoVE) airborne campaign to map the TCC and CHM over the Delta Junction area in interior Alaska.

Moghaddam, Mahta↗
DOE OSTI2019

Ligand-Dependent Energetics for Dehydrogenation: Implications in Li-Ion Battery Electrolyte Stability and Selective Oxidation Catalysis of Hydrogen-Containing Molecules

The hydrogen adsorption energetics on the surface of inorganic compounds can be used to predict electrolyte stability in Li-ion batteries and catalytic activity for selective oxidation of small molecules such as H 2 and CH 4 . Using first-principles density functional theory (DFT), the hydrogen adsorption was found to be unfavorable on high-band-gap insulators, which could be attributed to a lower energy level associated with adsorbed hydrogen relative to the bottom of the conduction band. In contrast, the hydrogen adsorption was shown to be the most favorable on metallic and semiconducting compounds, which results from an electron transfer from adsorbed hydrogen to the Fermi level or the bottom of the conduction band. Of significance, computed hydrogen adsorption energetics on insulating, semiconducting, and metallic oxides; phosphates; fluorides; and sulfides were decreased by lowering the ligand p band center, while the energy penalty for ligand vacancy formation was increased, indicative of decreased surface reducibility. A statistical regression analysis, where 16 structural and electronic parameters such as metal–ligand distance, electronegativity difference, Bader charges, bulk and surface metal and ligand band centers, band gap, ligand band width, and work function were examined, further showed that the surface ligand p band center is the most accurate single descriptor that governs the hydrogen adsorption tendency, and additional considerations of the band gap and average metal–ligand distance further reconcile the differences among compounds with different ligands/structures, whose ligand bands are different in shape and width. We discuss the implications of these findings for passivating coatings and design of catalysts and the need for novel theoretical methods to accurately estimate these quantities from first principles. Furthermore, these results establish a universal design principle for future high-throughput studies aiming to design electrode surfaces to minimize electrolyte oxidation by dehydrogenation in Li-ion batteries and enhance the H–H and C–H activation for selective oxidation catalysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

A compact and accurate semi-global potential energy surface for malonaldehyde from constrained least squares regression

We present a new approach to semi-global potential energy surface fitting that uses the least absolute shrinkage and selection operator (LASSO) constrained least squares procedure to exploit an extremely flexible form for the potential function, while at the same time controlling the risk of overfitting and avoiding the introduction of unphysical features such as divergences or high-frequency oscillations. Drawing from a massively redundant set of overlapping distributed multi-dimensional Gaussian functions of inter-atomic separations we build a compact full-dimensional surface for malonaldehyde, fit to explicitly correlated coupled cluster CCSD(T)(F12*) energies with a root mean square deviations accuracy of 0.3%–0.5% up to 25 000 cm{sup −1} above equilibrium. Importance-sampled diffusion Monte Carlo calculations predict zero point energies for malonaldehyde and its deuterated isotopologue of 14 715.4(2) and 13 997.9(2) cm{sup −1} and hydrogen transfer tunnelling splittings of 21.0(4) and 3.2(4) cm{sup −1}, respectively, which are in excellent agreement with the experimental values of 21.583 and 2.915(4) cm{sup −1}.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

WE-AB-202-02: Incorporating Regional Ventilation Function in Predicting Radiation Fibrosis After Concurrent Chemoradiotherapy for Lung Cancer

Purpose: To investigate the incorporation of pre-therapy regional ventilation function in predicting radiation fibrosis (RF) in stage III non-small-cell lung cancer (NSCLC) patients treated with concurrent thoracic chemoradiotherapy. Methods: 37 stage III NSCLC patients were retrospectively studied. Patients received one cycle of cisplatin-gemcitabine, followed by two to three cycles of cisplatin-etoposide concurrently with involved-field thoracic radiotherapy between 46 and 66 Gy (2 Gy per fraction). Pre-therapy regional ventilation images of the lung were derived from 4DCT via a density-change-based image registration algorithm with mass correction. RF was evaluated at 6-months post-treatment using radiographic scoring based on airway dilation and volume loss. Three types of ipsilateral lung metrics were studied: (1) conventional dose-volume metrics (V20, V30, V40, and mean-lung-dose (MLD)), (2) dose-function metrics (fV20, fV30, fV40, and functional mean-lung-dose (fMLD) generated by combining regional ventilation and dose), and (3) dose-subvolume metrics (sV20, sV30, sV40, and subvolume mean-lung-dose (sMLD) defined as the dose-volume metrics computed on the sub-volume of the lung with at least 60% of the quantified maximum ventilation status). Receiver operating characteristic (ROC) curve analysis and logistic regression analysis were used to evaluate the predictability of these metrics for RF. Results: In predicting airway dilation, the area under the ROC curve (AUC) values for (V20, MLD), (fV20, fMLD), and (sV20, and sMLD) were (0.76, 0.70), (0.80, 0.74) and (0.82, 0.80), respectively. The logistic regression p-values were (0.09, 0.18), (0.02, 0.05) and (0.004, 0.006), respectively. With regard to volume loss, the corresponding AUC values for these metrics were (0.66, 0.57), (0.67, 0.61) and (0.71, 0.69), and p-values were (0.95, 0.90), (0.43, 0.64) and (0.08, 0.12), respectively. Conclusion: The inclusion of regional ventilation function improved predictability of radiation fibrosis. Dose-subvolume metrics provided a promising method for incorporating functional information into the conventional dose-volume parameters for outcome assessment.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2025

Scattering insights into shear-induced scission of rod-like micelles

Understanding the scission of rod-like micelles under mechanical forces is crucial for optimizing their stability and behavior in industrial applications. This study investigates how micelle length, flexibility, and external forces interact, offering insights into the design of micellar systems in processes influenced by mechanical stress. Although significant, direct experimental observations of flow-induced micellar scission using scattering techniques remain scarce. Small angle neutron scattering (SANS) is used to explore the shear response of aqueous cetyltrimethylammonium bromide (CTAB) solutions with sodium nitrate. Rheological tests show shear thinning with no shear banding, ensuring a uniform flow field for reliable interpretation of scattering data. As shear rate increases, the scattering spectra show angular distortion, which is analyzed using spherical harmonic decomposition to characterize flow-induced scission and micelle orientation under shear. Two analysis steps are used: a model-independent spectral eigendecomposition reveals a decrease in micellar length, while regression analysis quantifies the evolution of the length distribution and mean length with shear rate. Additionally, micelle alignment increases with shear, quantified by the orientational distribution function. In conclusion, these findings provide experimental evidence for flow-induced alignment and scission, offering a new framework for understanding shear-induced phenomena in micellar systems.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Near-infrared chemical abundances of stars in the Sculptor dwarf galaxy

Owing to the recent identification of major substructures in our Milky Way (MW), the astronomical community has started to reevaluate the importance of dissolved and existing dwarf galaxies. In this work, we investigate up to 13 elements in 43 giant stars of the Sculptor dwarf galaxy (Scl) using high-signal-to-noise-ratio near-infrared (NIR) APOGEE spectra. Thanks to the strong feature lines in the NIR, we were able to determine high-resolution O, Si, and Al abundances for a large group of sample stars for the first time in Scl. By comparing the [α/Fe] (i.e., O, Mg, Si, Ca, and Ti) of the stars in Scl, Sagittarius, and the MW, we confirm the general trend that less massive galaxies tend to show lower [α/Fe]. The low [Al/Fe] (~ - 0.5) in Scl demonstrates the value of this ratio as a discriminator with which to identify stars born in dwarf galaxies (from MW field stars). A chemical-evolution model suggests that Scl has a top-light initial mass function (IMF), with a high-mass IMF power index of ~ - 2.7, and a minimum Type Ia supernovae delay time of ~100 Myr. Furthermore, a linear regression analysis indicates a negative radial metallicity gradient and positive radial gradients for [Mg/Fe] and [Ca/Fe], in qualitative agreement with the outside-in formation scenario.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2018

An Evaluation of Bang-Time Measurements from a Multichannel, Triaxial, nTOF Diagnostic for MagLIF Experiments at the Z facility

Neutron bang times for a series of MagLIF (Magnetic Liner Inertial Fusion) experiments with D 2 -filled targets have been measured at the Z facility. The emitted neutrons were detected as current-mode pulses in a multichannel, neutron time-of-flight (nTOF) diagnostic with conventional, scintillator-photomultiplier-tube (PMT) detectors. In these experiments, the detectors were fielded at known, fixed distances L (690-2510 cm) from the target, and on three, non-coplanar (but convergent) lines-of-sight (LOS). The primary goal of this diagnostic was to estimate a fiducial time (bang time) relative to an externally generated time-base for synchronizing all the diagnostics in an experiment. Recorded arrival times (A7) of the pulses were characterized experimentally by three numerical methods: a first-moment estimate (centroid) and two nodal measures — Savitzky-Golay (SG) smoothing and a single point peak estimate of the raw data. These times were corrected for internal detector time delays (transit and impulse-response function) — an adjustment that linked the recorded ATs to the corresponding arrival of uncollided neutrons at each detector. The bang time was then estimated by linearly regressing the arrival times against the associated distances to the source; t bang (on the system timescale) was taken as the temporal intercept of the regression equation at distance L = 0. This article reports the analysis for a representative shot #2584 for which (a) the recorded ATs — even without detector corrections — agreed by method in each channel to within 1-2 ns; (b) internal corrections were each ~3 — 5 ns; and (c) a 95% uncertainty (confidence) interval for t bang in this shot was estimated at ±3 ns with 4 degrees of freedom. A secondary goal for this diagnostic was to check that the bang time measurements corresponded to neutrons emitted by the D(d,n) 3 He reaction in a thermalized DD plasma. According to the theoretical studies by Brysk, such neutrons should be emitted with an isotropic Gaussian distribution of mean kinetic energy $ \overline{E}$ of 2.449 MeV; this energy translates to a mean neutron speed $ \overline{u}$ of 2.160 cm/ns [D. H. Munro, Nuclear Fusion, 56(3) 036001 (2016)]. In the MagLIF series of shots there was no evidence of spatial asymmetry in the time-distance regressions, and it was possible to extract the mean neutron speed from the slope of these fits. In shot 2584 $ \overline{u}$ was estimated at 2.152 cm/ns ± 0.010 cm/ns [95 % confidence, 4 dof] and the mean kinetic energy $ \overline{E}$ (with relativistic corrections) was 2.431 MeV ± 0.022 MeV [95 % confidence, 4 dof] — results supporting the assumption that D-D neutrons were, in fact, measured.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗