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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 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

Analysis of EIT/LASCO Observations Using Available MHD Models: Investigation of CME Initiation Propagation and Geoeffectiveness

The Sun's activity drives the variability of geospace (i.e., near-earth environment). Observations show that the ejection of plasma from the sun, called coronal mass ejections (CMEs), are the major cause of geomagnetic storms. This global-scale solar dynamical feature of coronal mass ejection was discovered almost three decades ago by the use of space-borne coronagraphs (OSO-7, Skylab/ATM and P78-1). Significant progress has been made in understanding the physical nature of the CMEs. Observations show that these global-scale CMEs have size in the order of a solar radius (approximately 6.7 x 10(exp 5) km) near the sun, and each event involves a mass of about 10(exp 15) g and an energy comparable to that of a large flare on the order of 10(exp 32) ergs. The radial propagation speeds of CMEs have a wide range from tens to thousands of kilometers per second. Thus, the transit time to near earth's environment [i.e., 1 AU (astronomical unit)] can be as fast as 40 hours to 100 hours. The typical transit time for geoeffective events is approximately 60-80 h. This paper consists of two parts: 1) A summary of the observed CMEs from Skylab to the present SOHO will be presented. Special attention will be made to SOHO/ LASCO/ EIT observations and their characteristics leading to a geoeffectiv a CME 2) The chronological development of theory and models to interpret the physical nature of this fascinating phenomenon will be reviewed. Finally, an example will be presented to illustrate the geoeffectiveness of the CMEs by using both observation and model.

Wu, S. T.↗
DOE OSTI2023

SULI Oral Presentation

Furthering our understanding of the prevalence and severity of issues that customers face when charging their electric vehicles (EVs) is crucial in order to improve the charging experience across the United States. This project utilizes web-scraping, machine leaning (ML), and natural language processing (NLP) techniques to analyze and categorize user-generated reviews. Selenium was used to build a data collection tool that can scrape vast amounts of user review data from the PlugShare website. Sentiment analysis was employed on this dataset in order to filter out negative reviews for further analysis. NLP techniques such as tokenization and word embedding were then used to convert user-written comments into a numerical format that a ML model can interpret. Multiple ML approaches are currently being explored in order to identify and categorize the charging issues being talked about in each review. Ultimately, the results from the ML model will be visualized and explained in a report on customer pain points to be delivered to the ChargeX Consortium, therefore revealing specific areas for improvement in the customer charging experience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2023

SULI Oral Presentation

Furthering our understanding of the prevalence and severity of issues that customers face when charging their electric vehicles (EVs) is crucial in order to improve the charging experience across the United States. This project utilizes web-scraping, machine leaning (ML), and natural language processing (NLP) techniques to analyze and categorize user-generated reviews. Selenium was used to build a data collection tool that can scrape vast amounts of user review data from the PlugShare website. Sentiment analysis was employed on this dataset in order to filter out negative reviews for further analysis. NLP techniques such as tokenization and word embedding were then used to convert user-written comments into a numerical format that a ML model can interpret. Multiple ML approaches are currently being explored in order to identify and categorize the charging issues being talked about in each review. Ultimately, the results from the ML model will be visualized and explained in a report on customer pain points to be delivered to the ChargeX Consortium, therefore revealing specific areas for improvement in the customer charging experience.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2018

Incorporating Suborganismal Processes into Dynamic Energy Budget Models for Ecological Risk Assessment

Here, a working group at the National Institute for Mathematical and Biological Synthesis (NIMBioS) explored the feasibility of integrating 2 complementary approaches relevant to ecological risk assessment. Adverse outcome pathway (AOP) models provide “bottom-up” mechanisms to predict specific toxicological effects that could affect an individual's ability to grow, reproduce, and/or survive from a molecular initiating event. Dynamic energy budget (DEB) models offer a “top-down” approach that reverse engineers stressor effects on growth, reproduction, and/or survival into modular characterizations related to the acquisition and processing of energy resources. Thus, AOP models quantify linkages between measurable molecular, cellular, or organ-level events, but they do not offer an explicit route to integratively characterize stressor effects at higher levels of organization. While DEB models provide the inherent basis to link effects on individuals to those at the population and ecosystem levels, their use of abstract variables obscures mechanistic connections to suborganismal biology. To take advantage of both approaches, we developed a conceptual model to link DEB and AOP models by interpreting AOP key events as measures of damage-inducing processes affecting DEB variables and rates. We report on the type and structure of data that are generated for AOP models that may also be useful for DEB models. We also report on case studies under development that merge information collected for AOPs with DEB models and highlight some of the challenges. Finally, we discuss how the linkage of these 2 approaches can improve ecological risk assessment, with possibilities for progress in predicting population responses to toxicant exposures within realistic environments.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Data-driven high-dimensional statistical inference with generative models

Crucial to many measurements at the LHC is the use of correlated multi-dimensional information to distinguish rare processes from large backgrounds, which is complicated by the poor modeling of many of the crucial backgrounds in Monte Carlo simulations. In this work, we introduce HI-SIGMA, a method to perform unbinned high-dimensional statistical inference with data-driven background distributions. In contradistinction to many applications of Simulation Based Inference in High Energy Physics, HI-SIGMA relies on generative ML models, rather than classifiers, to learn the signal and background distributions in the high-dimensional space. These ML models allow for interpretable inference while also incorporating model errors and other sources of systematic uncertainties. We showcase this methodology on a simplified version of a di-Higgs measurement in the bbγγ final state, where the di-photon resonance allows for background interpolation from sidebands into the signal region. We demonstrate that HI-SIGMA provides improved sensitivity as compared to standard classifier-based methods, and that systematic uncertainties can be straightforwardly incorporated by extending methods which have been used for histogram based analyses.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2024

Search for supersymmetry using vector boson fusion signatures and missing transverse momentum in pp collisions at $\sqrt{s}$ = 13 TeV with the ATLAS detector

This paper presents a search for supersymmetric particles in models with highly compressed mass spectra, in events consistent with being produced through vector boson fusion. The search uses 140 fb −1 of proton-proton collision data at $\sqrt{s}$ = 13 TeV collected by the ATLAS experiment at the Large Hadron Collider. Events containing at least two jets with a large gap in pseudorapidity, large missing transverse momentum, and no reconstructed leptons are selected. A boosted decision tree is used to separate events consistent with the production of supersymmetric particles from those due to Standard Model backgrounds. The data are found to be consistent with Standard Model predictions. The results are interpreted using simplified models of R-parity-conserving supersymmetry in which the lightest supersymmetric partner is a bino-like neutralino with a mass similar to that of the lightest chargino and second-to-lightest neutralino, both of which are wino-like. Lower limits at 95% confidence level on the masses of next-to-lightest supersymmetric partners in this simplified model are established between 117 and 120 GeV when the lightest supersymmetric partners are within 1 GeV in mass.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2019

Long live the Higgs factory: Higgs decays to long-lived particles at future lepton colliders

We initiate the study of exotic Higgs decays to long-lived particles (LLPs) at proposed future lepton colliders, focusing on scenarios with displaced hadronic final states. Our analysis entails a realistic tracker-based search strategy involving the reconstruction of displaced secondary vertices and the imposition of selection cuts appropriate for eliminating the largest irreducible backgrounds. The projected sensitivity is broadly competitive with that of the LHC and potentially superior at lower LLP masses. In addition to forecasting branching ratio limits, which may be freely interpreted in a variety of model frameworks, we interpret our results in the parameter space of a Higgs portal Hidden Valley and various incarnations of neutral naturalness, illustrating the complementarity between direct searches for LLPs and precision Higgs coupling measurements at future lepton colliders.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2023

Time-dependent SOLPS-ITER simulations of the tokamak plasma boundary for model predictive control using SINDy *

Abstract Time-dependent SOLPS-ITER simulations have been used to identify reduced models with the sparse identification of nonlinear dynamics (SINDy) method and develop model-predictive control of the boundary plasma state using main ion gas puff actuation. A series of gas actuation sequences are input into SOLPS-ITER to produce a dynamic response in upstream and divertor plasma quantities. The SINDy method is applied to identify reduced linear and nonlinear models for the electron density at the outboard midplane n e , s e p O M P and the electron temperature at the outer divertor T e , s e p d i v . Note that T e , s e p d i v is not necessarily the peak value of T e along the divertor. The identified reduced models are interpretable by construction (i.e. not black box), and have the form of coupled ordinary differential equations. Despite significant noise in T e , s e p d i v , the reduced models can be used to predict the response over a range of actuation levels to a maximum deviation of 0.5% in n e , s e p O M P and 5%–10% in T e , s e p d i v for the cases considered. Model retraining using time history data triggered by a preset error threshold is also demonstrated. A model predictive control strategy for nonlinear models is developed and used to perform feedback control of a SOLPS-ITER simulation to produce a setpoint trajectory in n e , s e p O M P using the integrated plasma simulator framework. The developed techniques are general and can be applied to time-dependent data from other boundary simulations or experimental data. Ongoing work is extending the approach to model identification and control for divertor detachment, which will present transient nonlinear behavior from impurity seeding, including realistic latency and synthetic diagnostic signals derived from the full SOLPS-ITER output.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2022

Benchmark eA generator for leptoproduction in high-energy lepton-nucleus collisions

The upcoming electron-ion collider (EIC) will address several outstanding puzzles in modern nuclear physics. Topics such as the partonic structure of nucleons and nuclei, the origin of their mass and spin, among others, can be understood via the study of high-energy electron-proton (ep) and electron-nucleus (eA) collisions. Achieving the scientific goals of the EIC will require a novel electron-hadron collider and detectors capable to perform high-precision measurements but also dedicated tools to model and interpret the data. To aid in the latter, we present a general-purpose e A Monte Carlo generator—BeAGLE. In this paper, we provide a general description of the models integrated into BeAGLE, applications of BeAGLE in eA physics, implications for detector requirements at the EIC, and the tuning of the parameters in BeAGLE based on available experimental data. Specifically, we focus on a selection of model and data comparisons in particle production in both ep and eA collisions, where baseline particle distributions provide essential information to characterize the event. In addition, we investigate the collision geometry determination in eA collisions, which could be used as an experimental tool for varying the nuclear density.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Search for new phenomena using the invariant mass distribution of same-flavour opposite-sign dilepton pairs in events with missing transverse momentum in $\sqrt{s}=13$ TeV pp collisions with the ATLAS detector

A search for new phenomena in final states containing an e + e - or μ + μ - pair, jets, and large missing transverse momentum is presented. This analysis makes use of proton–proton collision data with an integrated luminosity of 36.1 fb -1 , collected during 2015 and 2016 at a centre-of-mass energy s√=13 TeV with the ATLAS detector at the Large Hadron Collider. The search targets the pair production of supersymmetric coloured particles (squarks or gluinos) and their decays into final states containing an e + e - or μ + μ - pair and the lightest neutralino ($\sim\atop{χ}$ $0\atop{1}$) via one of two next-to-lightest neutralino ($\sim\atop{χ}$ $0\atop{2}$) decay mechanisms: $\sim\atop{χ}$ $0\atop{2}$→Z$\sim\atop{χ}$ $0\atop{1}$, where the Z boson decays leptonically leading to a peak in the dilepton invariant mass distribution around the Z boson mass; and $\sim\atop{χ}$ $0\atop{2}$→ℓ + ℓ - $\sim\atop{χ}$ $0\atop{1}$ with no intermediate ℓ + ℓ - resonance, yielding a kinematic endpoint in the dilepton invariant mass spectrum. The data are found to be consistent with the Standard Model expectation. Finally, results are interpreted using simplified models, and exclude gluinos and squarks with masses as large as 1.85 and 1.3 TeV at 95% confidence level, respectively.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2020

Search for top squarks in events with a Higgs or Z boson using 139 fb -1 of pp collision data at $\sqrt{s}=13$ TeV with the ATLAS detector

This paper presents a search for direct top squark pair production in events with missing transverse momentum plus either a pair of jets consistent with Standard Model Higgs boson decay into b-quarks or a same-flavour opposite-sign dilepton pair with an invariant mass consistent with a Z boson. The analysis is performed using the proton–proton collision data at √s=13 TeV collected with the ATLAS detector during the LHC Run-2, corresponding to an integrated luminosity of 139 fb -1 . No excess is observed in the data above the Standard Model predictions. The results are interpreted in simplified models featuring direct production of pairs of either the lighter top squark ($\tilde{t}_1$) or the heavier top squark ($\tilde{t}_2$), excluding at 95% confidence level $\tilde{t}_1$ and $\tilde{t}_2$ masses up to about 1220 and 875 GeV, respectively.

42 ENGINEERING↗
NASA NTRS1984

Analysis of head-down tilt as an analog of weightlessness using a methematical simulation model

Antiorthostasis or head down tilt of a moderate degree was used as a ground based analog of weightless space flight to study headward fluid shifts, decreased plasma volume, orthostatic intolerance and muscular skeletal degradation. A mathematical model was used to help interpret these observations. The model proved most valuable for these studies was originally developed as a description of the major circulatory, fluid and electrolyte control systems. Two different experimental studies are employed to validate the model. The first is a 24 hour head down tilt study and the second is a 7 day head down bed rest study. The major issues addressed include the reduction in plasma volume, the dynamic changes of venous pressure and cardiac output, the extent of central hypervolemia during long term zero g exposure, the existence of an early diuresis, the mechanisms which alter the renal regulating hormones during the short term and long term periods, the significance of potassium loss on other zero g responses, and the role of transcapillary filtration in adjusting fluid shifts. The use of mathematical models as an interpretive and analysis technique for experimental research for space life science is illustrated.

Leonard, J. I.↗
NASA NTRS2017

Impact of Evolving Isoprene Mechanisms on Simulated Formaldehyde: An Inter-comparison Supported by in Situ Observations from SENEX

Isoprene oxidation schemes vary greatly among gas-phase chemical mechanisms, with potentially significant ramifications for air quality modeling and interpretation of satellite observations in biogenic-rich regions. In this study, in situ observations from the 2013 SENEX mission are combined with a constrained O-D photochemical box model to evaluate isoprene chemistry among five commonly used gas-phase chemical mechanisms: CBO5, CB6r2, MCMv3.2, MCMv3.3.1, and a recent version of GEOS-Chem. Mechanisms are evaluated and inter-compared with respect to formaldehyde (HCHO), a high-yield product of isoprene oxidation. Though underestimated by all considered mechanisms, observed HCHO mixing ratios are best reproduced by MCMv3.3.1 (normalized mean bias = -15%), followed by GEOS-Chem (-17%), MCMv3.2 (-25%), CB6r2 (-32%) and CB05 (-33%). Inter-comparison of HCHO production rates reveals that major restructuring of the isoprene oxidation scheme in the Carbon Bond mechanism increases HCHO production by only approx. 5% in CB6r2 relative to CBO5, while further refinement of the complex isoprene scheme in the Master Chemical Mechanism increases HCHO production by approx. 16% in MCMv3.3.1 relative to MCMv3.2. The GEOS-Chem mechanism provides a good approximation of the explicit isoprene chemistry in MCMv3.3.1 and generally reproduces the magnitude and source distribution of HCHO production rates. We analytically derive improvements to the isoprene scheme in CB6r2 and incorporate these changes into a new mechanism called CB6r2-UMD, which is designed to preserve computational efficiency. The CB6r2-UMD mechanism mimics production of HCHO in MCMv3.3.1 and demonstrates good agreement with observed mixing ratios from SENEX (-14%). Improved simulation of HCHO also impacts modeled ozone: at approx. 0.3 ppb NO, the ozone production rate increases approx. 3% between CB6r2 and CB6r2-UMD, and rises another approx. 4% when HCHO is constrained to match observations.

isoprene↗
NASA NTRS1970

Computer discrimination procedures applicable to aerial and ERTS multispectral data

Two statistical models are compared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

Richardson, A. J.↗
NASA NTRS1971

Computer identification of ground pattern from aerial photographs.

Two statistical models are comapared in the classification of crops recorded on color aerial photographs. A theory of error ellipses is applied to the pattern recognition problem. An elliptical boundary condition classification model (EBC), useful for recognition of candidate patterns, evolves out of error ellipse theory. The EBC model is compared with the minimum distance to the mean (MDM) classification model in terms of pattern recognition ability. The pattern recognition results of both models are interpreted graphically using scatter diagrams to represent measurement space. Measurement space, for this report, is determined by optical density measurements collected from Kodak Ektachrome Infrared Aero Film 8443 (EIR). The EBC model is shown to be a significant improvement over the MDM model.

Richardson, A. J.↗
NASA NTRS2003

Role of the Polar Oceans in Global Climate

The project focused on ice-ocean model development and in particular on the assimilation of ice motion data and ice concentration data into both regional and global models. Many of the resulting publications below deal with improvements made in the physics treated by the model and the procedures for assimilating data. Several papers examine how the ability of the model to simulate the past behavior of the ice cover, especially to represent the ice thickness and ice deformation, is improved by data assimilation. A second aspect of the work involved interpretation of modeled behavior. Resulting papers treat the decline of arctic ice thickness over the last thirty years, and how that decline was caused by a slight warming of the near-surface atmosphere, and also how large variation in ice thickness are due to changes in wind patterns associated with a well- known oscillation of the atmospheric circulation. The research resulted in over 20 published papers on these topics.

Rothrock, D. A.↗
NASA NTRS1976

The period-pulse-width distribution of pulsars and their division into three classes

The period-pulse-width (P-W) distribution of sample of 41 pulsars has been reanalyzed under two versions of a model where radiation is beamed from magnetic polar caps which are isotropically oriented with respect to the rotation axis of the neutron stars (IOPC models). It is found that neither IOPC model can explain the P-W distribution of the entire sample. Pulsars with simple unimodal (U) or complicated multimodal (M) pulse shapes show significantly different P-W distributions. Class M pulsars have a narrower P-W distribution than do class U pulsars and, taken separately, are compatible with either IOPC model. Class U pulsars divide into two subgroups, those with relatively narrower pulses (UN) and those with relatively wider pulses (UW), each of which is compatible with either IOPC model. One interpretation of these results is that the pulsars in classes UN, M, and UW have different intrinsic beam sizes, roughly in the ratios 1:2:4, respectively. The possible origins of the three classes are discussed in terms of the force-balance magnetosphere model (Roberts et al., 1972, 1973), where the differences may be attributed to different-mass neutron stars and the structure of the polar caps. An alternative interpretation is that the angle between the rotation and emission axes is not isotropically distributed, but can take only certain preferred values.

Roberts, D. H.↗