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All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Evaluation of precipitation indices in suites of dynamically and statistically downscaled regional climate models over Florida

Abstract The present work evaluates historical precipitation and its indices defined by the Expert Team on Climate Change Detection and Indices (ETCCDI) in suites of dynamically and statistically downscaled regional climate models (RCMs) against NOAA’s Global Historical Climatology Network Daily (GHCN-Daily) dataset over Florida. The models examined here are: (1) nested RCMs involved in the North American CORDEX (NA-CORDEX) program, (2) variable resolution Community Earth System Models (VR-CESM), (3) Coupled Model Intercomparison Project phase 5 (CMIP5) models statistically downscaled using localized constructed analogs (LOCA) technique. To quantify observational uncertainty, three in situ-based (PRISM, Livneh, CPC) and three reanalysis (ERA5, MERRA2, NARR) datasets are also evaluated against the station data. The reanalyses and dynamically downscaled RCMs generally underestimate the magnitude of the monthly precipitation and the frequency of the extreme rainfall in summer. The models forced with CanESM2 miss the phase of the seasonality of extreme precipitation. All models and reanalyses severely underestimate both the mean and interannual variability of mean wet-day precipitation (SDII), consecutive dry days (CDD), and overestimate consecutive wet days (CWD). Metric analysis suggests large uncertainty across NA-CORDEX models. Both the LOCA and VR-CESM models perform better than the majority of models. Overall, RegCM4 and WRF models perform poorer than the median model performance. The performance uncertainty across models is comparable to that in the reanalyses. Specifically, NARR performs poorer than the median model performance in simulating the mean indices and MERRA2 performs worse than the majority of models in capturing the interannual variability of the indices.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2019

Bacterial communities protect the alga Microchloropsis salina from grazing by the rotifer Brachionus plicatilis

Open algal ponds are likely to succumb to unpredictable, devastating crashes by one or several deleterious species. Developing methodology to mitigate or prevent pond crashes will increase algal biomass production, drive down costs for algae farmers, and reduce the risk involved with algae cultivation, making it more favorable for investment by entrepreneurs and biotechnology companies. In this work, we postulate that specific algal-bacterial co-cultures grown with the green alga Microchloropsis salina prevented grazing by the marine rotifer, Brachionus plicatilis. We obtained seven algal-bacterial co-cultures from crashed rotifer cultures, maintained them in co-culture with Microchloropsis salina , and used a microalgal survival assay to determine that algae present in each co-culture were protected from rotifer grazing and culture crash. After months of routinely diluting and maintaining these seven algal-bacterial co-cultures, we repeated the assay and found the opposite result: none of the seven bacterial communities protected the microalgae from rotifer grazing. We performed 16S rRNA gene amplicon sequencing on the protective and nonprotective co-culture samples and identified substantial differences in the makeup of the bacterial communities. Protective bacterial communities consisted primarily of Alphaproteobacteria (Rhodobacteraceae) and Gammaproteobacteria ( Marinobacter , Pseudomonas, Methylophaga ) while nonprotective bacterial communities were less diverse and missing many putatively crucial members. We compared the seven protective communities with the seven nonprotective communities and we correlated specific bacterial amplicon sequence variants with algal protection. With these data, our future research will aim to define and develop an engineered-microbiome that can stabilize industrial Microchloropsis salina cultures by protecting against grazer-induced pond crashes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2023

Evaluation of the excitation spectra with diffusion Monte Carlo on an auxiliary bosonic ground state

We aim to improve upon the variational Monte Carlo (VMC) approach for excitations replacing the Jastrow factor by an auxiliary bosonic (AB) ground state and multiplying it by a fermionic component factor. The instantaneous change in imaginary time of an arbitrary excitation in the original interacting fermionic system is obtained by measuring observables via the ground-state distribution of walkers of an AB system that is subject to an auxiliary effective potential. The effective potential is used to (i) drive the AB system’s ground-state configuration space toward the configuration space of the excitations of the original fermionic system and (ii) subtract from a diffusion Monte Carlo (DMC) calculation contributions that can be included in conventional approximations, such as mean-field and configuration interaction (CI) methods. In this novel approach, the AB ground state is treated statistically in DMC, whereas the fermionic component of the original system is expanded in a basis. The excitation energies of the fermionic eigenstates are obtained by sampling a fermion–boson coupling term on the AB ground state. We show that this approach can take advantage of and correct for approximate eigenstates obtained via mean-field calculations or truncated interactions. We demonstrate that the AB ground-state factor incorporates the correlations missed by standard Jastrow factors, further reducing basis truncation errors. Relevant parts of the theory have been tested in soluble model systems and exhibit excellent agreement with exact analytical data and CI and VMC approaches. In particular, for limited basis set expansions and sufficient statistics, AB approaches outperform CI and VMC in terms of basis size for the same systems. The implementation of this method in current codes, despite being demanding, will be facilitated by reusing procedures already developed for calculating ground-state properties with DMC and excitations with VMC.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Investigation of plastic yielding in near-micrometer grain size aluminum using synchrotron microdiffraction

The onset of plastic yielding has been studied in samples of aluminum with nearmicrometer average grain size using in situ tensile loading combined with synchrotron radiation. A white-beam Laue 3D micro-diffraction technique was used allowing the collection of diffraction signal from a volume with a resolution of 1 μm in all three dimensions. The orientation data obtained from the micro-diffraction are used to estimate the local variation in geometrically necessary dislocation density, and correction factors are suggested for voxels where neighbors are missing in either one or two dimensions. The results demonstrate a considerable heterogeneity in deformation in the early stages of plastic deformation.

Zhang, C L↗
DOE OSTI2018

Search for long-lived, massive particles in events with displaced vertices and missing transverse momentum in s = 13 TeV p p collisions with the ATLAS detector

A search for long-lived, massive particles predicted by many theories beyond the Standard Model is presented. Here, the search targets final states with large missing transverse momentum and at least one high-mass displaced vertex with five or more tracks, and uses 32.8 fb -1 of $\sqrt s = 13$ TeV pp collision data collected by the ATLAS detector at the LHC. The observed yield is consistent with the expected background. The results are used to extract 95% C.L. exclusion limits on the production of long-lived gluinos with masses up to 2.37 TeV and lifetimes of O (10 - 2 ) - O (10) ns in a simplified model inspired by split supersymmetry.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Polarization observables in three-nucleon systems

In the past two decades, several laboratories have produced a large amount of data for cross sections, analyzing powers, and other spin observables from various reactions in the three-nucleon system. The results allow one to arrive at a moderately good description of the data by only using the two-nucleon potentials in Faddeev-type calculations. The remaining discrepancies should, in principle, and aside from Coulomb and relativistic effects, be removed once the effects of three-nucleon forces are implemented. High precision data on elastic and break-up reactions show, however, that even after the inclusion of these effects, the picture is not complete yet and some ingredients are still missing in the calculations.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2015

Search for invisible particles produced in association with single-top-quarks in proton–proton collisions at √s = 8 TeV with the ATLAS detector

A search for the production of single-top-quarks in association with missing energy is performed in proton–proton collisions at a centre-of-mass energy of √s=8 TeV with the ATLAS experiment at the large hadron collider using data collected in 2012, corresponding to an integrated luminosity of 20.3 fb -1 . In this study, the W boson from the top quark is required to decay into an electron or a muon and a neutrino. No deviation from the standard model prediction is observed, and upper limits are set on the production cross-section for resonant and non-resonant production of an invisible exotic state in association with a right-handed top quark. In the case of resonant production, for a spin-0 resonance with a mass of 500 GeV, an effective coupling strength above 0.15 is excluded at 95% confidence level for the top quark and an invisible spin-1/2 state with mass between 0 and 100 GeV. In the case of non-resonant production, an effective coupling strength above 0.2 is excluded at 95% confidence level for the top quark and an invisible spin-1 state with mass between 0 and 657 GeV.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

A search for new physics in central exclusive production using the missing mass technique with the CMS detector and the CMS-TOTEM precision proton spectrometer

A generic search is presented for the associated production of a Z boson or a photon with an additional unspecified massive particle X, pp → pp + Z/γ + X, in proton-tagged events from proton–proton collisions at $\sqrt{s}$ = 13 TeV, recorded in 2017 with the CMS detector and the CMS-TOTEM precision proton spectrometer. The missing mass spectrum is analysed in the 600–1600 GeV range and a fit is performed to search for possible deviations from the background expectation. No significant excess in data with respect to the background predictions has been observed. Model-independent upper limits on the visible pro duction cross section of pp → pp + Z/γ + X are set

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2013

Search for third generation scalar leptoquarks in pp collisions at s = 7 TeV with the ATLAS detector

CERN-LHC. Study of events with final states consisting of one electron or muon with large PT, one high-PT hadronically decaying tau, missing ET from the tau decays, and two high-PT jets, produced in proton-proton collisions at a centre-of-lass enegy of 7 TeV. The data sample used has an integraterd luminosity of 4.7 fb-1 collected during 2011. The data are used to set limits on the production of pairs of 3rd generation leptoquarks which decay in a tau plus b-quark with an assumed branching ratio of 100% with only the specific lepton-hadron decay mode of the tau being sought after here. The limits are shown separately for the electron and muon decay modes of the tau and for the combined two modes combined.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Development and Validation of a Non-Invasive, Chairside Oral Cavity Cancer Risk Assessment Prototype Using Machine Learning Approach

Oral cavity cancer (OCC) is associated with high morbidity and mortality rates when diagnosed at late stages. Early detection of increased risk provides an opportunity for implementing prevention strategies surrounding modifiable risk factors and screening to promote early detection and intervention. Historical evidence identified a gap in the training of primary care providers (PCPs) surrounding the examination of the oral cavity. The absence of clinically applicable analytical tools to identify patients with high-risk OCC phenotypes at point-of-care (POC) causes missed opportunities for implementing patient-specific interventional strategies. This study developed an OCC risk assessment tool prototype by applying machine learning (ML) approaches to a rich retrospectively collected data set abstracted from a clinical enterprise data warehouse. We compared the performance of six ML classifiers by applying the 10-fold cross-validation approach. Accuracy, recall, precision, specificity, area under the receiver operating characteristic curve, and recall–precision curves for the derived voting algorithm were: 78%, 64%, 88%, 92%, 0.83, and 0.81, respectively. The performance of two classifiers, multilayer perceptron and AdaBoost, closely mirrored the voting algorithm. Integration of the OCC risk assessment tool developed by clinical informatics application into an electronic health record as a clinical decision support tool can assist PCPs in targeting at-risk patients for personalized interventional care.

60 APPLIED LIFE SCIENCES↗
NASA NTRS1990

Bar-Code System Tracks Test Equipment

Administration of complicated system speeded and simplified. Computer system uses bar codes to keep track of more than 2,200 items of test equipment. BETUS (Barcode Equipment Tracking and Utilization System), maintains data base on what items borrowed, who is using them and where, and when calibrated. Keeps records on tools and small electronic components. Saves on equipment purchases and recovers missing equipment more quickly. Cuts check-in and checkout time by 90 percent.

Rogers, Jacob R.↗
NASA NTRS1992

Experimental evaluation of candidate graphical microburst alert displays

A piloted flight simulator experiment was conducted to evaluate issues related to the display of microburst alerts on electronic cockpit instrumentation. Issues addressed include display clarity, usefulness of multilevel microburst intensity information, and whether information from multiple sensors should be presented separately or 'fused' into combined alerts. Nine active airline pilots of 'glass cockpit' aircraft participated in the study. Microburst alerts presented on a moving map display were found to be visually clear and useful to pilots. Also, multilevel intensity information coded by colors or patterns was found to be important for decision making purposes. Pilot opinion was mixed on whether to 'fuse' data from multiple sensors, and some resulting design tradeoffs were identified. The positional information included in the graphical alert presentation was found useful by the pilots for planning lateral missed approach maneuvers, but may result in deviations which could interfere with normal airport operations. A number of flight crew training issues were also identified.

Wanke, Craig R.↗
NASA NTRS2006

Optical Coatings and Surfaces in Space: MISSE

The space environment presents some unique problems for optics. Components must be designed to survive variations in temperature, exposure to ultraviolet, particle radiation, atomic oxygen and contamination from the immediate environment. To determine the importance of these phenomena, a series of passive exposure experiments have been conducted which included, among others, the Long Duration Exposure Facility (LDEF, 1985- 1990), the Passive Optical Sample Assembly (POSA, 1996- 1997) and most recently, the Materials on the International Space Station Experiment (MISSE, 2001 - 2005). The MISSE program benefited greatly from past experience so that at the conclusion of this 4 year mission, samples which remained intact were in remarkable condition. This study will review data from different aspects of this experiment with emphasis on optical properties and performance.

Stewart, Alan F.↗
NASA NTRS2006

Autonomous Detection of Dust Devils and Clouds on Mars

Acquisition of science in space applications is shifting from teleoperated gathering to an automated on-board analysis with improvements in the use of on-board memory, CPU, bandwidth and data quality. In this paper, we describe algorithms to autonomously detect dust devils and clouds from a rover and summarize the results. These algorithms meet high hit-to-miss ratios and satisfy strict requirements of CPU, memory usage and bandwidth. The detectors have been scheduled for upload to the Mars Exploration Rovers (MER) in 2006. These are the first autonomous science processes in the rovers.

onboard science↗
NASA NTRS2010

MG Isotopic Measurement of FIB-Isolated Presolar Silicate Grains

The majority of presolar oxide and silicate grains are ascribed to origins in low-mass red giant and asymptotic giant branch (AGB) stars based on their O isotopic ratios. However, a minor population of these grains (< 10%) has O isotopic ratios incompatible with these sources. Two principle alternative sources are higher-than-solar metallicity (Z) stars or, more likely, supernovae (SN) [1-3]. These rare (Group 4) grains [3] are characterized by enrichments in O-18, and typically also enrichments in O-17. An even rarer subset of grains with extremely large enrichments in O-17 and smaller depletions in O-18 were suggested to come from binary star systems [2]. To establish the origins of these isotopically unusual grains, it is necessary to examine isotopic systems in addition to O. Presolar silicates offer several elements diagnostic of their stellar sources and nuclear processes, including O, Si, Mg, Fe and Ca. However, the database for minor element isotopic compositions in silicates is seriously lacking. To date only two silicate grains have been analyzed for Mg [4] or Fe [5]. One major complicating factor is their small size (average ~230 nm), which greatly limits the number of measurements that can be performed on any one grain and makes it more difficult to obtain statistically relevant data. This problem is compounded because the grains are identified among isotopically solar silicates, which contribute a diluting signal in isotopic measurements [1]. Thus, relatively small isotopic anomalies are missed due to this dilution effect. By applying focused ion beam (FIB) milling, we obtain undiluted Mg isotopic ratios of isolated rare presolar silicate grains to investigate their sources.

Messenger, Scott R.↗
DOE OSTI2012

Search for pair-produced heavy quarks decaying to Wq in the two-lepton channel at root(s)=7 TeV with the ATLAS detector

A search is presented for heavy-quark pair production (QQ{sup -}) under the decay hypothesis QQ{sup -} {yields} W{sup +}qW{sup -}q{sup -} with q=d, s, b for up-type Q or q=u, c for down-type Q. The search is performed with 1.04 fb{sup -1} of integrated luminosity from pp collisions at {radical}s = 7 TeV collected by the ATLAS detector at the CERN LHC. Dilepton final states are selected, requiring large missing transverse momentum and at least two jets. Mass reconstruction of heavy-quark candidates is performed by assuming that the W boson decay products are nearly collinear. The data are in agreement with standard model expectations; a heavy quark with mass less than 350 GeV is excluded at 95% confidence level.

43 PARTICLE ACCELERATORS↗
DOE OSTI2024

Physics-Based Machine Learning Methods for U-235 Forensics Signatures

Signatures of low-intensity U-235 sources have been recently studied by utilizing a variety of machine learning (ML) classifiers using features derived from gamma spectral measurements collectedunder structured campaigns. Several ML classifiers, such as ensemble of tress and classification trees, revealed misleadingly-optimistic training error due to over-fitting, and furthermore,their performance is not directly relatable to the physical properties due to their data-driven, opaque designs. We present a regression-based ML method that first estimates the inverse distanceto the source and then utilizes a threshold to infer its presence, by representing the background as a source located at an infinite distance. For the inverse distance estimation, we study the ensembleof trees and Gaussian process regression methods, and a hyper parameter auto-tuning and selection method that employs five regression estimators. These methods avoid the over-fittingobserved in several ML classifiers, while providing the classification error nearly comparable to them based on independent test data. Their error is directly related to estimates of the inversephysical distance to source, and the precision of error determines the seperability property that determines the false alarm and missed detection rates. The property of monotonic decrease of thesource strength with increasing detector distance combined with Poisson distribution of measurements is utilized to analytically validate these methods by deriving the generalization equations ofunderlying regression methods.

Rao, Nageswara↗
DOE OSTI2022

Correlation Calculations for the Russian Pu Metal Fast Experiments

Nuclear criticality experiments are often conducted in campaigns with multiple variations. These experiments reuse the same basic components, like the fuel, moderator, or positioning machines. The components have uncertainties in their geometry and composition that propagate to models of the experiments. Shared components create shared uncertainty between the $k_{eff}$ of benchmarks. The shared uncertainty is commonly quantified with a covariance, or correlation coefficient. These covariances can impact criticality safety and nuclear data validation applications. While benchmark evaluations tabulate an experiment’s uncertainty, they often lack a detailed calculation of correlations between experiments. Even some very commonly used benchmarks, like the Russian Pu Metal Fast (PMF) experiments, have missing correlations. This paper presents our approach to calculate the correlations for five of the Russian PMF experiments. The experiments share hemispherical Pu shells that induce a correlation between modeled $k_{eff}$ values. We estimated the correlations with simplified and detailed models of the experiments through linear-perturbation theory. The correlations between the experiments vary significantly between the detailed vs. simplified models. We also investigate how the correlations affect validation metrics of the experiments.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗