MultiPEM Toolbox
Supports characterization of explosive events by providing estimates of device parameters such as yield, height of burst/depth of burial, geolocation, and event time with uncertainty quantification.
Williams, Brian↗
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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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Designing Critical Experiments Using Gaussian Process Optimization
New nuclear applications may lack similarity between the application and existing ICSBEP benchmarks. Without accurate benchmark data, predictive simulations will have high uncertainty in the estimate of a parameter of interest (such as k eff ). The design of critical experiments tuned for specific applications of interest is one solution to reducing uncertainty in the necessarily nuclear data. We propose an optimization technique to design critical experiments that match the cross-section sensitivities of an application model while minimizing the number of simulation runs in the optimization. The optimization of a critical experiment is slow because the potential design space covers many qualitative variables (types of material and geometries) and corresponding quantitative variables (e.g., material dimensions) and the evaluation of any specific design requires running an expensive code like MCNP1 and Whisper. The optimization of expensive black-box computer codes with quantitative variables has been extensively explored in the literature of design of computer experiments. We propose a modified version of standard Gaussian process (GP) optimization that optimizes over multiple discrete configurations of qualitative variables in parallel which reduces the computational cost of the entire optimization. The goal of this work is to minimize the number of MCNP evaluations while still exploring many different design configurations in parallel.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
XCal: model-based approach to X-ray CT spectral calibration
Transmission X-ray computed tomography (CT) is widely used to quantitatively reconstruct 3D objects composed of multiple materials. However, accurate CT reconstruction requires the system to be calibrated to account for the effective X-ray spectrum. Unfortunately, measurement of the effective spectrum is ill-posed, and existing calibration methods require that the system be recalibrated when the system parameters are changed. In this paper, we propose XCal, a multi-energy model-based spectral calibration approach for X-ray CT. The XCal approach models the effective spectrum using a separable physics-based model of the CT system. The model parameters are then estimated by fitting calibration data with known objects at multiple energies. An important advantage of XCal is that it allows the user to change scanner settings, such as the source voltage or X-ray filters, without the need for recalibration. Evaluations on simulated and measured datasets demonstrate that XCal significantly improves the accuracy of the estimated spectrum as compared to existing calibration methods.
Li, Wenrui [Purdue Univ., West Lafayette, IN (Unit↗
Models of SIV rebound after treatment interruption that involve multiple reactivation events
In order to assess the efficacy of novel HIV-1 treatments leading to a functional cure, the time to viral rebound is frequently used as a surrogate endpoint. The longer the time to viral rebound, the more efficacious the therapy. In support of such an approach, mathematical models serve as a connection between the size of the latent reservoir and the time to HIV-1 rebound after treatment interruption. The simplest of such models assumes that a single successful latent cell reactivation event leads to observable viremia after a period of exponential viral growth. Here we consider a generalization developed by Pinkevych et al. and Hill et al. of this simple model in which multiple reactivation events can occur, each contributing to the exponential growth of the viral load. We formalize and improve the previous derivation of the dynamics predicted by this model, and use the model to estimate relevant biological parameters from SIV rebound data. We confirm a previously described effect of very early antiretroviral therapy (ART) initiation on the rate of recrudescence and the viral load growth rate after treatment interruption. We find that every day ART initiation is delayed results in a 39% increase in the recrudescence rate (95% credible interval: [18%, 62%]), and a 11% decrease of the viral growth rate (95% credible interval: [4%, 20%]). We show that when viral rebound occurs early relative to the viral load doubling time, a model with multiple successful reactivation events fits the data better than a model with only a single successful reactivation event.
59 BASIC BIOLOGICAL SCIENCES↗
Towards a Validation Protocol for Satellite-Based Solar Resource Data
Satellite-based solar resource data are valued for their spatial extensiveness and long temporal record. Validation of such data, including accurate assessment of their uncertainties against reference datasets, is essential to give users confidence in and maximum benefit from the data. More broadly, the international Earth observation from space community estimates many geophysical parameters from satellite data, such as, to name just a few, precipitation, sea surface temperature and atmospheric aerosol amount. This community has made considerable progress in developing standard validation protocols for numerous satellite-derived parameters, protocols that recommend best practices to support benchmarking and comparison of satellite datasets. This paper explores some of the elements that could be included in a validation protocol for satellite solar resource data. The elements are illustrated using satellite and surface based solar data over Australia. Keywords: solar resource, satellite, validation, protocol
POWER TRANSMISSION AND DISTRIBUTION,SOLAR ENERGY↗
Simulation of Transparent Spin Experiment in RHIC
The transparent spin mode has been proposed as a new technique for preservation and control of the spin polarization of an ion beam in a synchrotron. The ion rings of the proposed Jefferson Lab Electron-Ion Collider adopted this technique in their figure-8 design. The transparent spin mode can also be setup in a racetrack with two identical Siberian snakes. There is a proposal to test the predicted features of the spin transparent mode in RHIC, which already has all of the necessary hardware capabilities. We have earlier analytically estimated the setup parameters and developed a preliminary experimental plan. In this paper we describe simulations of the proposed experiment using a Zgoubi model of RHIC. We present simulation of the polarization preservation during acceleration in the transparent spin mode. We also demonstrate polarization control by simulating an adiabatic polarization adjustment. A procedure to measure the strength of the spin transparent resonance is illustrated.
Morozov, Vasiliy↗
Characterizing Shielded Special Nuclear Material by Neutron Capture Gamma-Ray Multiplicity Counting
We present a new neutron multiplicity counting analysis and measurement method for neutron-shielded fissile material using neutron-capture gamma rays. Neutrons absorbed in shielding produce characteristic gamma rays that preserve the otherwise lost neutron multiplicity signature. Neutron multiplicity counting provides estimates of fission parameters, such as neutron leakage multiplication, spontaneous fissioner (e.g. Pu-240) mass, and (α,n) ratio. Standard neutron multiplicity counting can incorporate the new neutron-capture gamma-ray multiplicity counting technique to characterize previously degenerate or intractable source configurations by maximizing the multiplicity signature. The new method decouples neutron source-detector interferences, such as reflection and thermalization time in the detector, that could improve measurements of the mean neutron lifetime. We also develop a detector prototype for the multiplicity counting of neutron-capture gamma rays and present detector design considerations, such as detection material and shielding, to optimize the detection of the 2.2 MeV hydrogen capture gamma ray. We simulate the prototype neutron- capture gamma-ray multiplicity counter against the BeRP ball in polyethylene shells to inform future measurements.
73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
Vibration-Based Sensor Design: A Grey-Box Approach
Knowledge of the internal structure of an object or device under investigation proceeds from the basic idea of constructing its dynamic behavioral relations governed by a set of differential/algebraic equations that characterize its response. These equations can be partial differential equations leading to finite element or finite difference relations requiring a complex numerical solution on a super computer or ordinary differential equations requiring sophisticated numerical integration techniques to obtain the desired solution. Discrete dynamic systems evolving from digitized data acquisition are typically captured by sampled-data (continuous-to-discrete) representations characterized by a set of difference equations specifying the underlying system dynamics. In any case, with a mathematical description in hand, Grey-Box modeling techniques have evolved, concerned with the estimation of model parameters embedded in a prescribed set of equations (the system) governing its behavior, while capturing the underlying physical phenomenology of the problem at hand.
97 MATHEMATICS AND COMPUTING↗
Deep Learning Based Approach to Integrate MyShake's Trigger Data with ShakeAlert for Faster and Robust EEW Alerts
Earthquake Early Warning (EEW) systems depend on the dense seismic network to make fast and accurate earthquake detections to issue useful early alerts. The recent development and implementation of the ShakeAlert system is relying on the west coast seismic network to detect and estimate the earthquake parameters in real-time. While working on making improvements on the current system, one potential approach is to include more seismic recordings from various sources, such as the low-cost smartphone seismic network, such as the MyShake network, or the Google Android smartphones, since these smartphone seismic networks have much more portable stations (phones) to potentially provide useful data to the system. This report summarizes the initial exploration of using a deep learning approach to combine the data from both traditional seismic stations and the smartphone data in California. Due to the heterogeneity nature of the data, we aggregate data from the phones (using simulation data), as well as that from traditional seismic stations to grid cells. By generating real-time triggering ratio grid cell maps, the designed deep learning algorithm can process the data from multiple sources and detect the earthquake faster than only using that from a traditional seismic network.
58 GEOSCIENCES↗
Processing, structure, and thermal properties of ZrW 2 O 8 , HfW 2 O 8 , HfMgW 3 O 12 , Al(HfMg) 0.5 W 3 O 12 , and Al 0.5 Sc 1.5 W 3 O 12 negative and zero thermal expansion coefficient ceramics
Negative and zero coefficient of thermal expansion (CTE) materials are of interest for developing polymer composites in electronic circuits that match the expansion of Si and in zero CTE supports for optical components, e.g., mirrors. In this work, the processing challenges and stability of ZrW 2 O 8 , HfW 2 O 8 , HfMgW 3 O 12 , Al(HfMg) 0.5 W 3 O 12 , and Al 0.5 Sc 1.5 W 3 O 12 negative and zero thermal expansion coefficient ceramics are discussed. Al 0.5 Sc 1.5 W 3 O 12 is demonstrated to be a relatively simple oxide to fabricate in large quantity and is shown to exhibit single phase up to 1300 °C in air and inert N 2 environments. The negative and zero CTE behavior was confirmed with dilatometry. Thermal conductivity and heat capacity were reported for the first time for HfMgW 3 O 12 and Al 0.5 Sc 1.5 W 3 O 12 and thermal conductivity was found to be very low (~0.5 W/mK). Grüneisen parameter is also estimated. Methods for integration of Al 0.5 Sc 1.5 W 3 O 12 with other materials was examined and embedding 50 vol% of the ceramic powder in flexible epoxy was demonstrated with a commercial vendor.
36 MATERIALS SCIENCE↗
Geophysical Signatures of Crack Network Coalescence in Rocks at Multiple Length Scales
The main goal of the research project was to identify the geophysical signatures of fracture growth in natural rocks by utilizing novel geophysical techniques. The research objectives were to (a) investigate the potential for geophysical methods to determine when cracks initiate, the types and locations of propagated cracks, and the coalescence of networks of cracks in natural rocks at multiple scales, (b) determine how damage at the microscale evolved into damage at the macroscale and then link the microscopic and macroscopic observations, (c) quantify crack coalescence in rocks under realistic stress conditions using coupled mechanical-geophysical-optical visualization, and (d) identify the precursors in geophysical signals to crack coalescence. The following research thrusts were explored to achieve the research objectives: (1) uniaxial compression testing of rock specimens with and without a set of pre‐existing flaws and (2) triaxial compression testing of natural rock specimens. These thrusts allowed for exploring fracturing in rocks under realistic in situ environments and at multiple scales. This project provided educational opportunities for nine graduate and undergraduate students and resulted in 27 peer-reviewed publications. This first research thrust focused on investigating the micromechanics of fractures in rocks through uniaxial compression testing combined with advanced geophysical and imaging techniques, specifically acoustic emission (AE) monitoring, ultrasonic imaging, and 2-dimensional Digital Image Correlation (2D-DIC). By examining damage processes under time-independent and time-dependent loading conditions, insights into damage localization, crack initiation, and fracturing mechanisms were gained. It was observed that the AE signals and the strain-based measurements directly reflect the state of damage in the rock specimen and could be used to identify the cracking levels, such as the crack initiation (CI) and crack damage (CD), and the mode of deformation. A novel calibration apparatus was developed to enhance the accuracy of AE sensors, allowing for the estimation of key parameters such as magnitude, source dimension, stress drop, and radiated seismic energy associated with the fractures. The findings highlighted significant variations in the temporal evolution of AE source parameters during the primary, secondary, and tertiary stages of creep, identifying tensile cracking as the primary deformation mode. The second research thrust focused on enhancing the understanding of fracturing processes in natural rocks through triaxial compression testing, real-time AE monitoring, and ultrasonic monitoring. We investigated the impact of various factors such as fracture propagation regimes, injection parameters, rock types, and pre-existing conditions on the hydraulic fracture (HF) behavior using scaled true-triaxially loaded specimens of Barre granite and Lyons sandstone. Custom sensor housing facilitated concurrent active and passive monitoring to analyze hydro-mechanical responses and microseismicity associated with different HF scenarios. A coupled investigation of passive microseismicity and active signal attributes permitted a detailed comprehension of the various HF processes (aseismic deformation, fracture initiation and propagation, fluid permeation, and leak-off) and their dependence on the specific rock type. The findings of this research demonstrated the effectiveness of AE monitoring techniques in providing valuable insights into the impact of various factors on the behavior and dynamics of HF processes. The advancements in monitoring techniques, offering a more thorough and precise approach, represent a significant step towards optimizing HF practices and ensuring sustainable resource extraction.
58 GEOSCIENCES↗
Design Methods, Tools, and Data for Ceramic Solar Receivers
This report presents the development of tools and methods for evaluating the reliability and performance of ceramic materials in high temperature solar receivers. As Concentrating Solar Power (CSP) technologies aim for higher operating temperatures to enhance efficiency and meet industrial process heat requirements, current high temperature metallic materials face challenges in maintaining structural integrity. This report explores advanced ceramics as a promising alternative, given their superior high temperature strength and lower thermal expansion, compared to metals. To address the need for effective ceramic receiver design tools, this report integrates statistical failure models of ceramics into the existing srlife tool: an open-source software package designed to estimate the life of high temperature CSP components. These failure models account for the inherent variability and flaw distribution in ceramics, as well as the impact of subcritical crack growth under high temperature cyclic loads. The report also presents experimental data collected for a commercially available ceramic material, SiC, and details the process of estimating reliability model parameters from these data. A comparative design analysis is then performed between ceramic (SiC) and metallic (current nickel-based superalloys A740H and A282) receiver. This comparison demonstrates that SiC receivers can achieve service life exceeding 30 years under high incident heat flux conditions, compared to just a few years for metallic receivers.
14 SOLAR ENERGY↗
Discovery of 15 A-F Main Sequence Pulsating Star Candidates
Delta Scuti stars, spanning spectral types A to F with masses between 1.5 and 2.5 solar masses, exhibit a complex mix of radial and non-radial pressure modes. This study focuses on 15 Delta Scuti, Gamma Doradus, and Hybrid candidate stars using TESS satellite photometry data with a time series of exposures ranging from 20 to 600 seconds across different sky regions. Employing the prewhitening technique via fast Fourier transforms, significant frequencies are extracted from light curves. Three approximation methods are used to estimate critical stellar parameters such as density, radius, and mass. This research also verifies the variability of these stars, which are currently not classified as variable in databases like SIMBAD.
79 ASTRONOMY AND ASTROPHYSICS↗
Geometric Measures of Trustworthiness for Machine Learning Predictions
his report details the findings from the research and investigation of Geometric Measures of Trustworthiness for Machine Learning Predictions. We explored the trustworthiness of machine learning (ML) models’ predictions using geometric measures to quantify the similarity of a query point with the training data. Predictive uncertainty in ML can originate from at least three sources: (1) Model uncertainty, which represents the uncertainty in model form (e.g. decision tree, vs neural network) and estimating the model parameters from the training data, (2) Data uncertainty, which represents the natural complexities of the data such as class overlap and inherent noise, and (3) Distributional uncertainty, which represents the mismatch between the training and operational distributions. The proposed measures focus on measuring and explaining the data and distributional uncertainties by measuring the relationships of operational data with the training data.
97 MATHEMATICS AND COMPUTING↗
Provably accurate simulation of gauge theories and bosonic systems
Quantum many-body systems involving bosonic modes or gauge fields have infinite-dimensional local Hilbert spaces which must be truncated to perform simulations of real-time dynamics on classical or quantum computers. To analyze the truncation error, we develop methods for bounding the rate of growth of local quantum numbers such as the occupation number of a mode at a lattice site, or the electric field at a lattice link. Our approach applies to various models of bosons interacting with spins or fermions, and also to both abelian and non-abelian gauge theories. We show that if states in these models are truncated by imposing an upper limit Λ on each local quantum number, and if the initial state has low local quantum numbers, then an error at most ϵ can be achieved by choosing Λ to scale polylogarithmically with ϵ − 1 , an exponential improvement over previous bounds based on energy conservation. For the Hubbard-Holstein model, we numerically compute a bound on Λ that achieves accuracy ϵ , obtaining significantly improved estimates in various parameter regimes. We also establish a criterion for truncating the Hamiltonian with a provable guarantee on the accuracy of time evolution. Building on that result, we formulate quantum algorithms for dynamical simulation of lattice gauge theories and of models with bosonic modes; the gate complexity depends almost linearly on spacetime volume in the former case, and almost quadratically on time in the latter case. We establish a lower bound showing that there are systems involving bosons for which this quadratic scaling with time cannot be improved. By applying our result on the truncation error in time evolution, we also prove that spectrally isolated energy eigenstates can be approximated with accuracy ϵ by truncating local quantum numbers at Λ = polylog ( ϵ − 1 ) .
Tong, Yu↗
Methods and Comparisons Between Computer Vision and Radar Based Vehicle Location
Measuring vehicle locations relative to a driver's vehicle is a critical component in the analysis of driving data from both postanalysis (such as in naturalistic driving studies) or in autonomous vehicle navigation. In this work we describe a method to estimate vehicle positions from a forward-looking video camera using intrinsic camera calibration, estimates of extrinsic parameters, and a convolutional neural network trained to detect and locate vehicles in video data. We compare the measurements we achieve with this method with ground truth and with radar data available from a naturalistic driving study. We identify regions where video is preferred, where radar is preferred, and explore trade-offs between the two methods in regions where the preference is more ambiguous. We describe applications of these measurements for transportation analysis.
Aykac, Deniz↗
High Contagiousness and Rapid Spread of Severe Acute Respiratory Syndrome Coronavirus 2
Severe acute respiratory syndrome coronavirus 2 is the causative agent of the ongoing coronavirus disease pandemic. Initial estimates of the early dynamics of the outbreak in Wuhan, China, suggested a doubling time of the number of infected persons of 6–7 days and a basic reproductive number (R 0 ) of 2.2–2.7. We collected extensive individual case reports across China and estimated key epidemiologic parameters, including the incubation period (4.2 days). We then designed 2 mathematical modeling approaches to infer the outbreak dynamics in Wuhan by using high-resolution domestic travel and infection data. Results show that the doubling time early in the epidemic in Wuhan was 2.3–3.3 days. Assuming a serial interval of 6–9 days, we calculated a median R0 value of 5.7 (95% CI 3.8–8.9). Here, we further show that active surveillance, contact tracing, quarantine, and early strong social distancing efforts are needed to stop transmission of the virus.
60 APPLIED LIFE SCIENCES↗
Sporophyte Stage Genes Exhibit Stronger Selection Than Gametophyte Stage Genes in Haplodiplontic Giant Kelp
Macrocystis pyrifera (giant kelp), a haplodiplontic brown macroalga that alternates between a macroscopic diploid (sporophyte) and a microscopic haploid (gametophyte) phase, provides an ideal system to investigate how ploidy background affects the evolutionary history of a gene. In M. pyrifera , the same genome is subjected to different selective pressures and environments as it alternates between haploid and diploid life stages. We assembled M. pyrifera gene models using available expression data and validated 8,292 genes models using the model alga Ectocarpus siliculosus . Differential expression analysis identified gene models expressed in either or both the haploid and diploid life stages while functional annotation identified processes enriched in each stage. Genes expressed preferentially or exclusively in the gametophyte stage were found to have higher nucleotide diversity (π = 2.3 × 10 –3 and 2.8 × 10 –3 , respectively) than those for sporophytes (π = 1.1 × 10 –3 and 1 × 10 –3 , respectively). While gametophyte-biased genes show faster sequence evolution, the sequence evolution exhibits less signatures of adaptations when compared to sporophyte-biased genes. Our findings contrast the standing masking hypothesis, which predicts higher standing genetic variation at the sporophyte stage, and support the strength of expression theory, which posits that genes expressed more strongly are expected to evolve slower. We argue that the sporophyte stage undergoes more stringent selection compared with the gametophyte stage, which carries a heavy genetic load associated with broadcast spawning. Furthermore, using whole-genome sequencing, we confirm the strong population structure in wild M. pyrifera populations previously established using microsatellite markers, and estimate population genetic parameters, such as pairwise genetic diversity and Tajima’s D , important for conservation and domestication of M. pyrifera .
Molano, Gary↗