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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Gravitational-wave signal of a core-collapse supernova explosion of a 15M ⊙ star

In this paper we report on the gravitational-wave signal computed in the context of a three-dimensional simulation of a core-collapse supernova explosion of a 15 M ⊙ star. The simulation was performed with our neutrino hydrodynamics code chimera . We detail the gravitational wave strains as a function of time, for both polarizations, and discuss their physical origins. We also present the corresponding spectral signatures. Gravitational wave emission in our model has two key features: low-frequency emission (less than 200 Hz) emanates from the gain layer as a result of neutrino-driven convection and the standing accretion shock instability (SASI), and high-frequency emission (greater than 600 Hz) emanates from the proto–neutron star due to Ledoux convection within it. The high-frequency emission dominates the gravitational wave emission in our model and emanates largely from the convective layer itself, not from the convectively stable layer above it, due to convective overshoot. Moreover, the low-frequency emission emanates from the gain layer itself, not from the proto–neutron star, due to accretion onto it. We provide evidence of the SASI in our model and demonstrate that the peak of our low-frequency gravitational wave emission spectrum corresponds to it. Given its origin in the gain layer, we classify the SASI emission in our model as p-mode emission and assign a purely acoustic origin, not a vortical–acoustic origin, to it. We compare the results of our three-dimensional model analysis with those obtained from the model’s two-dimensional counterpart and find a significant reduction in the strain amplitudes in the former case, as well as significant reductions in all related quantities. Our dominant proto–neutron star gravitational wave emission is not well characterized by emission from surface g modes, complicating the relationship between peak frequencies observed and the mass and radius of the proto–neutron star expressed by analytic estimates under the assumption of surface g-mode emission. We present our frequency normalized characteristic strain along with the sensitivity curves of current- and next-generation gravitational wave detectors. This simple analysis indicates that the spectrum of gravitational wave emission between approximately 20 Hz and approximately 1 kHz, stemming from neutrino-driven convection, the SASI, accretion onto the proto–neutron star, and proto–neutron star convection, will be accessible for a Galactic event.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

Tensorized Feature Spaces for Feature Explosion

In this paper 1 1 This manuscript has been authored by UT-Battelle, LLC under Contract No. DE-AC05-000R22725 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the United States Government retains a nonexclusive, paid-up, irrevocable, worldwide license to publish or reproduce the published form of this manuscript, or allow others to do so, for United States Government purposes. The Department of Energy will provide public access to these results of federally sponsored research in accordance with the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan) This research used resources of the Oak Ridge Leadership Computing Facility, which is a DOE Office of Science User Facility supported under Contract DE-AC05-000R22725., we present a novel framework that uses tensor factorization to generate richer feature spaces for pixel classification in hyperspectral images. In particular, we assess the performance of different tensor rank decomposition methods as compared to the traditional kernel-based approaches for the hyperspectral image classification problem. We propose Orion, which takes as input a hyperspectral image tensor and a rank and outputs an enhanced feature space from the factor matrices of the decomposed tensor. Our method is a feature explosion technique that inherently maps low dimensional input space in $\mathbb{R}^{K}$ to high dimensional space in $\mathbb{R}^{R}$ , where $R\gg K$ , say in the order of 1000x, like a kernel. We show how the proposed method exploits the multi-linear structure of hyperspectral three dimensional tensor. We demonstrate the effectiveness of our method with experiments on three publicly available hyperspectral datasets with labeled pixels and compare their classification performance against traditional linear and non-linear supervised learning methods such as SVM with Linear, Polynomial, RBF kernels, and the Multi-Layer Perceptron model. Finally, we explore the relationship between the rank of the tensor decomposition and the classification accuracy using several hyperspectral datasets with ground truth.

Pasricha, Ravdeep Singh↗
DOE OSTI2024

Deep Koopman Neural Network for Analyzing High-Energy-Density Simulations of Electrical Wire Explosions

Megaampere-scale electrical wire experiments (EWEs) provide a platform for studying magnetohydrodynamic (MHD) instability growth in magneto-inertial fusion (MIF) devices. Even when nonlinear simulations of these experiments can digitally reproduce much of the experimentally observed instability growth, interpreting the results and understanding mode growth and evolution can be non-trivial. As a first step toward providing better interpretation of these simulation features, this work investigates the use of a deep neural network that uses Koopman operator theory to analyze the dynamics of pulsed-power-driven explosions of EWEs. This deep neural network is trained on 1-D resistive MHD simulations of EWEs. This neural network learns to transform the nonlinear data into a lower-dimensional representation where the time dynamics are linear. Layers of this neural network are shown to learn features of the simulations, including the locations of shock waves and different physical regimes of the simulation. Using the learned features, the network can compress a time state of the simulation consisting of 5120 data point into a 36-parameter lower-dimensional latent space embedding. Furthermore, these embeddings are shown to be clustered in the latent space by initial radius and time state.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Characterization and differentiation of aluminum powders used in improvised explosive devices. Part 2: Micromorphometric method refinement and preliminary statistical analysis

Abstract Aluminum (Al) powder is commonly encountered in improvised explosive devices (IEDs) as a metallic fuel due to its availability and low cost. Although available commercially in powder form, amateur bomb‐makers also produce their own Al powder via simple methods found online. In order to provide investigative leads and forensic intelligence, it is important to evaluate not only the composition of homemade devices, but also to distinguish between the various forms of Al powder they contain. To achieve this goal, a method using automated microscopy in combination with statistical techniques has been demonstrated to have the potential to provide source discrimination and investigative leads in source attribution of Al powders in IEDs. The present research refined this method and investigated 59 industrially and amateurly produced Al powder sources with seven subsamples per source using two traditional linear discriminant analyses (LDA), one with a standard data split for training and testing, and another using leave‐one‐out cross‐validation. Averaging the classification accuracies for the two LDA‐based analyses, LDA has the ability to correctly classify 59.26%, 83.35%, and 80.69% of the samples based on their powder source, type, and production method, respectively. This classification accuracy represents a 3407%, 317%, and 61.38% increase in accuracy from random class assignment, respectively. Further, in most instances of incorrect data attribution to a particular source, the subsample has been misidentified with another sample of the same powder type or production method.

Ommen, Danica M.↗
DOE OSTI2023

Growing Pacific Linkage with Western North Atlantic Explosive Cyclogenesis

Abstract Explosive cyclones (ECs), defined as extratropical cyclones that experience normalized pressure drops of at least 24 hPa in 24 h, are impactful weather events in the North Atlantic sector, but year-to-year changes in the frequency and impacts of these storms are sizeable. To analyze the sources of this interannual variability, we track cases of ECs and dissect them into two spatial groups: those that formed near the east coast of North America (coastal) and those in the north central Atlantic (high latitude). The frequency of high-latitude ECs is strongly correlated with the North Atlantic Oscillation, a well-known feature, whereas coastal EC frequency is statistically linked with an atmospheric wave train emanating from the North Pacific in the last 30 years. This wave train pattern of alternating high and low pressure is associated with heightened upper-level divergence and Eady growth rates along the east coast of North America, likely resulting in a stronger correspondence between the atmospheric wave train and coastal EC frequency. Using coupled model experiments, we show that the tropical and North Pacific oceans are an important factor for this atmospheric wave train and the subsequent enhancement of seasonal baroclinicity in the North Atlantic.

58 GEOSCIENCES↗
DOE OSTI2021

Exascale models of stellar explosions: Quintessential multi-physics simulation

The ExaStar project aims to deliver an efficient, versatile, and portable software ecosystem for multi-physics astrophysics simulations run on exascale machines. The code suite is a component-based multi-physics toolkit, built on the capabilities of current simulation codes (in particular Flash-X and Castro), and based on the massively parallel adaptive mesh refinement framework AMReX. It includes modules for hydrodynamics, advanced radiation transport, thermonuclear kinetics, and nuclear microphysics. The code will reach exascale efficiency by building upon current multi- and many-core packages integrated into an orchestration system that uses a combination of configuration tools, code translators, and a domain-specific asynchronous runtime to manage performance across a range of platform architectures. The target science includes multi-physics simulations of astrophysical explosions (such as supernovae and neutron star mergers) to understand the cosmic origin of the elements and the fundamental physics of matter and neutrinos under extreme conditions.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Nonlinearities in Magnetic Confinement, Ionospheric Physics, and Population Explosion Leading to Profile Resilience Нелінійності в магнетному утриманні, фізиці іоносфери та процесі демографічного вибуху, які приводять до стійкості профілю

Nonlinearities play an important role in many fields. In the field of thermonuclear fusion, they are involved in questions such as profile resilience and fluid closure. A nonlinear phenomenon common to both fusion and astrophysical planets is the generation of zonal flows. These flows play a significant role in determining the level of turbulence and fluid closure in fusion. The effects of resonance broadening and nonlinearities are investigated, specifically focusing on the case of nonlinear instability that has appeared in drift waves. Similarities and differences between our systems are discussed, with population explosion and the dynamics of nonlinear systems for drift waves by different states in profile resilience described with great precision. The aim of our study is to put our fluid model for drift waves in tokamaks within the wider framework of statistical physics principles. This reinforces our belief in the broad application of our drift wave model, which encompasses current tokamaks, ITER, and the fusion pilot plant.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2021

Explosion Discrimination Using Seismic Gradiometry and Spectral Filtering of Data

Here, we present a new method to discriminate between earthquakes and buried explosions using observed seismic data. The method is different from previous seismic discrimination algorithms in two main ways. First, we use seismic spatial gradients, as well as the wave attributes estimated from them (referred to as gradiometric attributes), rather than the conventional three-component seismograms recorded on a distributed array. The primary advantage of this is that a gradiometer is only a fraction of a wavelength in aperture compared with a conventional seismic array or network. Second, we use the gradiometric attributes as input data into a machine learning algorithm. The resulting discrimination algorithm uses the norms of truncated principal components obtained from the gradiometric data to distinguish the two classes of seismic events. Using high-fidelity synthetic data, we show that the data and gradiometric attributes recorded by a single seismic gradiometer performs as well as a conventional distributed array at the event type discrimination task.

58 GEOSCIENCES↗
DOE OSTI2024

Joint Inversion of Regional Waveform, First-Motion Polarity, and Synthetic Aperture Radar Surface Displacement for the Fourth and Sixth North Korean Declared Nuclear Explosions

Here, this study analyzed the Democratic People’s Republic of Korea’s (DPRK) fourth (DPRK4, 6 January 2016 M w 4.49) and sixth (DPRK6, 7 September 2017 M w 5.2) declared nuclear tests, employing a joint seismic and Interferometric Synthetic Aperture Radar (InSAR) inversion to improve understanding of these events and enhance moment tensor (MT) inversion capabilities. The recent efforts have focused on employing seismic waveform and InSAR geodetic deformation data separately to analyze these and the previous nuclear tests (e.g., Chiang et al., 2018; Myers et al., 2018; Wang et al., 2018). Building upon our previous work (Chi-Durán et al., 2021), we performed a joint regional waveform, first-motion (FM) polarity, and surface displacement inversion, which demonstrated improved source-type discrimination, a revised MT solution with reduced scalar moment uncertainty, and an independently constrained location. In this article, we build on the previous results for DPRK6 by including an analysis using a four-layered velocity model with free-surface topography to compute the near-source static deformation Green’s functions. The model consists of a 50 m basalt layer (⁠V P = 2.07 km/s, V S = 1.2 km/s⁠), a 250 m stratified volcanic deposit layer (⁠V P = 1.73 km/s, V S = 1.0 km/s⁠), a 700 m weathered granodiorite layer (⁠V P = 2.5 km/s, V S = 1.3 km/s⁠⁠), and a granodiorite half-space (⁠V P = 5.35 km/s, V S = 3.09 km/s⁠⁠). The half-space shares the velocity of the regional MDJ2 velocity model (Ford et al., 2010), which has proven effective for waveform inversion in the region. This model considers the range of reported values for various lithologies and weathering effects. Our findings show that using the layered velocity model enhances the recovery of source location and depth for both the explosions by improving fits and reducing uncertainties. The joint inversion also improves source-type discrimination and better constrains the scalar seismic moment necessary for downstream yield estimation.

58 GEOSCIENCES↗
DOE OSTI2021

Data supporting the article titled "Heterogeneous Multiphase Flow Properties of Volcanic Rocks and Implications for Noble Gas Transport from Underground Nuclear Explosions"

The submission is a Reproducible Research (RR) data archive that contains the supporting multiphase fluid flow and curve fitting results of the Vadose Zone Journal article titled: "Heterogeneous Multiphase Flow Properties of Volcanic Rocks and Implications for Noble Gas Transport from Underground Nuclear Explosions." The article's DOI number is the following: https://doi.org/10.1002/vzj2.20123. Please see the "Methods and Materials" section of the journal article and the ReadMe.txt in the RR_ARCHIVE folder for further details. Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration under contract DE-NA0003525. SAND Number: SAND2021-3407 O.

mercury injection capillary pressure↗
DOE OSTI2020

Optimization of Geometric Perturbations on a Rod Moving Through a High Explosive Target

After completing a study to ensure the simulation results were converged, several high resolution 3D Smoothed Particle Hydrodynamic (SPH) simulations of copper rods impacting a high explosive (LX14) target were performed. This was then formulated into an optimization problem: I wanted to find the optimum shape and location of a perturbation on the rod that would maximize its erosion after it left the target. The shape of the perturbation was modeled as a 2D Gaussian bump and parameterized by its location along the rod axis (z 0 ) and amplitude (A). The final mass of the coherent part of the rod as it leaves the target was used as a metric to represent the erosion of the rod, and the optimization was formulated to maximize this metric with respect to the aforementioned design variables. Due to the expensive nature of the high-fidelity 3D SPH simulations, a surrogate model needed to be chosen so that many function calls to the optimizer would be feasible. Thus, a strategic full factorial sampling plan was chosen to build a dataset, which consisted of 24 high-fidelity simulations. Two surrogate models, a third order polynomial regression model and a Gaussian Process Model, were analyzed using a 14%/86% test/train holdout technique. The root mean square and R2 score of the test set was used to determine the best model, and the third order polynomial regression model was chosen as the surrogate model. Finally, the Nelder-Mead Simplex and Basin-hopping optimization algorithms were implemented, and it was found that the two algorithms gave slightly different optimum values. Nelder-Mead gave an optimum point of [z* 0 ;A*] = [9:9;0:4] and Basin-Hopping gave an optimum value of x* = [z* 0 ;A*] = [9:2;0:1].

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Report on the recovery of legacy 1997-1998 Depth-of-Burial / Tunnel-and-Hole-Closure explosion data from the Kazakhstan former Soviet nuclear test site, Semipalatinsk.

In 1996, negotiations between the National Nuclear Center of the Republic of Kazakhstan (NNC), the U.S. Defense Special Weapons Administration (DSWA) and the U.S. Department of Energy led to an agreement for a joint series of experiments at the former Soviet nuclear test site Semipalatinsk (STS). These experiments had a dual purpose: to close holes and tunnels originally created for the purpose of testing nuclear weapons, and to characterize explosive sources at a former nuclear test site. This report covers the recovery of legacy data from the experiments conduct in 1997 and 1998. Two teams collected data. Los Alamos National Laboratory (LANL), in collaboration with the NNC, collected the near-source (local) data out to approximately 20 km. Lamont-Doherty Earth Observatory (LDEO), with funding from Lawrence Livermore Laboratory (LLNL), also in collaboration with NNC, collected regional data, 200 – 1000 km distant, leveraging the KZ regional seismic network that LDEO had recently installed in collaboration with NNC. The two teams also worked together to some extent, regarding instrumentation and planning. This report primarily addresses the near-source data collected by the LANL/NNC team.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2020

Verification and Validation of High Explosive Reactive Burn Models Implemented in LANL's EAP and LAP Code Base

Reactive burn models represent a significant leap in high explosive (HE) modeling capability. The first generation of engineering models of HE detonation are called programmed burn models and they are largely based on the distance between a prescribed detonation point and each zone in a simulation. There have been many advancements to programmed burn models over the years and when the assumptions upon which they are based are met, a properly tuned programmed burn model can be highly accurate but if any of their assumptions is not met, as is the case for corner turning or weakly initiated HE burn, they will give the wrong answer. Reactive burn models represent an entirely new way of modeling HE burn. They use the local conditions of a zone – e.g. temperature, pressure or density – as calculated by a hydrocode to determine if and when the zone is going to detonate and if so, how rapidly. This difference opens up an entirely new set of capabilities for HE modeling. It makes it possible to accurately and predictively model phenomena like the effect of confinement and the formation of dead zones. Reactive burn models have seen sustained development effort at LANL for at least the last decade but several recent developments make it timely to transition reactive burn models from a research topic to a production tool. The main goal of this milestone is to facilitate and accelerate the adoption of reactive burn as a commonly available modeling option, with recommendations on the resolution that will be required and uncertainties associated with their modeling choices. To achieve this, we have performed verification, validation, and uncertainty quantification (UQ) assessments of AWSD and SURF/SURFplus in xRage and FLAG on a variety of different problems.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Applying Compression-Based Metrics to Seismic Data in Support of Global Nuclear Explosion Monitoring

The analysis of seismic data for evidence of possible nuclear explosion testing is a critical global security mission that relies heavily on human expertise to identify and mark seismic signals embedded in background noise. To assist analysts in making these determinations, we adapted two compression distance metrics for use with seismic data. First, we demonstrated that the Normalized Compression Distance (NCD) metric can be adapted for use with waveform data and can identify the arrival times of seismic signals. Then we tested an approximation for the NCD called Sliding Information Distance (SLID), which can be computed much faster than NCD. We assessed the accuracy of the SLID output by comparing it to both the Akaike Information Criterion (AIC) and the judgments of expert seismic analysts. Our results indicate that SLID effectively identifies arrival times and provides analysts with useful information that can aid their analysis process.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2020

Aerial Crosspolarized NQR-NMR: Buried Explosive Detection From a Safe Distance

Nuclear quadrupole resonance is a non-destructive detection and inspection technique with potential as a non-destructive test (NDT) tool. Establishment of the capability opens the door to its use in furthering the mission of the labs. There are many possible uses of the capability: explosive detection and stress/strain detection in epoxies are two of the more obvious and are the main results of this work. Enhancement of the signal-to-noise ratio (SNR) and improvements in the acquisition time of the experiment were key focuses of this work. These were achieved by combing special spin-lock pulse sequences with cross-polarization (CP) schemes to improve the signals with shorter acquisition times. A novel rotating magnetic field device was created to facilitate CP in the field. Implementation of these schemes provided a significant reduction in SNR/time.

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2021

Modeling Explosive Dispersal of Radiological Material: A Nonparametric Analysis

The National Atmospheric Release Advisory Center (NARAC) is a Department of Energy (DOE) asset that provides guidance on the potential effects of atmospherically released hazards based on dispersion simulation results. Numerical simulation results are compared to well-characterized experimental measurements whenever possible to validate and refine the model predictions. In 2012, such measurements were obtained by Defence Research and Development Canada (DRDC) and collaborating organizations for the case of explosively released 140 La – a radioactive isotope with a half-life of 1.6781 days.

42 ENGINEERING↗