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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 37 records · Page 2

Monitoring space shuttle air quality using the Jet Propulsion Laboratory electronic nose

A miniature electronic nose (ENose) has been designed and built at the Jet Propulsion Laboratory (JPL), Pasadena, CA, and was designed to detect, identify, and quantify ten common contaminants and relative humidity changes. The sensing array includes 32 sensing films made from polymer carbon-black composites. Event identification and quantification were done using the Levenberg-Marquart nonlinear least squares method. After successful ground training, this ENose was used in a demonstration experiment aboard STS-95 (October-November, 1998), in which the ENose was operated continuously for six days and recorded the sensors' response to the air in the mid-deck. Air samples were collected daily and analyzed independently after the flight. Changes in shuttle-cabin humidity were detected and quantified by the JPL ENose; neither the ENose nor the air samples detected any of the contaminants on the target list. The device is microgravity insensitive.

manned↗

Daily evaluation of 26 precipitation datasets using Stage-IV gauge-radar data for the CONUS

New precipitation (P) datasets are released regularly, following innovations in weather forecasting models, satellite retrieval methods, and multi-source merging techniques. Using the conterminous US as a case study, we evaluated the performance of 26 gridded (sub-)daily P datasets to obtain insight into the merit of these innovations. The evaluation was performed at a daily timescale for the period 2008–2017 using the Kling–Gupta efficiency (KGE), a performance metric combining correlation, bias, and variability. As a reference, we used the high-resolution (4 km) Stage-IV gauge-radar P dataset. Among the three KGE components, the P datasets performed worst overall in terms of correlation (related to event identification). In terms of improving KGE scores for these datasets, improved P totals (affecting the bias score) and improved distribution of P intensity (affecting the variability score) are of secondary importance. Among the 11 gauge-corrected P datasets, the best overall performance was obtained by MSWEP V2.2, underscoring the importance of applying daily gauge corrections and accounting for gauge reporting times. Several uncorrected P datasets outperformed gauge-corrected ones. Among the 15 uncorrected P datasets, the best performance was obtained by the ERA5-HRES fourth-generation reanalysis, reflecting the significant advances in earth system modeling during the last decade. The (re)analyses generally performed better in winter than in summer, while the opposite was the case for the satellite-based datasets. IMERGHH V05 performed substantially better than TMPA-3B42RT V7, attributable to the many improvements implemented in the IMERG satellite P retrieval algorithm. IMERGHH V05 outperformed ERA5-HRES in regions dominated by convective storms, while the opposite was observed in regions of complex terrain. The ERA5-EDA ensemble average exhibited higher correlations than the ERA5-HRES deterministic run, highlighting the value of ensemble modeling. The WRF regional convection-permitting climate model showed considerably more accurate P totals over the mountainous west and performed best among the uncorrected datasets in terms of variability, suggesting there is merit in using high-resolution models to obtain climatological P statistics. Our findings provide some guidance to choose the most suitable P dataset for a particular application.

Hylke E. Beck↗

Land Surfaces at the Tipping-Point for Water and Energy Balance Coupling

The surface water and energy balances can be coupled or uncoupled depending on whether the evaporation regime is water-limited or energy-limited. As the landscape loses soil moisture during drydowns, a transition between the regimes may occur, which signifies a nonlinear change in water-energy-carbon coupling. Regions that switch often between these two regimes, that is, are dominated by neither regime, are particularly vulnerable to climate variability and change. To robustly identify these tipping points, we identify drydown events based on global soil moisture data sets from remote sensing. The event identification does not rely on precipitation information and is robust with respect to measurement noise. Then, the soil moisture thresholds delineating the evaporation regime transitions are determined by Sequential Monte Carlo Sampling and a two-stage parametrization strategy. Based on the estimated soil moisture thresholds across the globe, we estimate observation-based water availability indices which quantify the nonlinear controls of soil moisture on evaporation. This framework is tested and applied globally using Soil Moisture Active Passive soil moisture retrievals. Combined with a new tippling-point metric that describes the frequency of evaporation regime transitions, we identify regions that switch often between different evaporation regimes at the global scale. Given unit shifts in soil moisture, these regions will experience the most change in how their surface water and energy are coupled.

Jianzhi Dong↗

Development of a Korotkov sound processor for automatic identification of auscultatory events. I - Specification of preprocessing bandpass filters

Frequency bands that best discriminate the Korotkov sounds at systole and at diastole from the sounds immediately preceding these events are defined. Korotkov sound data were recorded from five normotensive subjects during orthostatic stress (lower body negative pressure) and bicycle ergometry. A spectral analysis of the seven Korotkov sounds centered about the systolic and diastolic auscultatory events revealed that a maximum increase in amplitude at the systolic transition occurred in the 18-26-Hz band, while a maximum decrease in amplitude at the diastolic transition occurred in the 40-60-Hz band. These findings were remarkably consistent across subjects and test conditions. These passbands are included in the design specifications for an automatic blood pressure measuring system used in conjuction with medical experiments during NASA's Skylab program.

Golden, D. P., Jr.↗

Identification of Health Events in Astronaut Missions Using Longitudinal Molecular Signature Detection

Individualized health monitoring can now incorporate a precision medicine approach, profiling multiple molecular and physiological measures of health (generalized omics) longitudinally to enable the timely diagnosis and treatment of disease. Such measurements can include blood chemistries, gene expression data, metabolite measurements, and digital device data. We will present our work on extending such an approach to monitoring individual astronaut health for deep space missions. We have developed and implemented novel algorithms to monitor and detect physiolgical state departures from individualized healthy astronaut baselines , utilizing and biologically annotating generalized omics. Our new methods can detect baseline deviations across omics corresponding to potentially adverse medical events. Events pointing to changes in individual health are then compared across individuals to identify common responses and detect changes affecting multiple crewmembers. We show the utility of our methods in detecting temporal health changes across subjects using retrospective Earth and astronaut mission data (metabolite and immune marker data across multiple missions), in order for this technique t o be applicable for future missions.

G I Mias↗

Evidence for an episode of crater obliteration intermediate in Martian history

It is shown that Mars experienced a brief episode of an increased obliteration rate contemporaneous with the formation of the cratered plains units. The obliteration rate during this episode was at least an order of magnitude greater than the preexisting rate. The obliteration rates prior to and after the event were identical within a factor of 3. Regional variations in the observed densities of degraded craters on the cratered terrain are shown to result from differences in the intensity of the obliteration rate during the event. The identification and characterization of the event are accomplished by using crater diameter-frequency distributions, not only for the total crater population but also for four morphological classes. Distributions are selected from 38 regions within the Martian equatorial latitudes.

Jones, K. L.↗

Wireless event-recording device with identification codes

A wireless recording device can be interrogated to determine its identity and its state. The state indicates whether a particular physical or chemical event has taken place. In effect, the physical or chemical event is recorded by the device. The identity of the device allows it to be distinguished from a number of similar devices. Thus the sensor device may be used in an array of devices that can be probed by a wireless interrogation unit. The device tells the interrogator who it is and what state it is in. The interrogator can thus easily identify particular items in an array that have reached a particular condition.

Watters, David G.↗

Event-recording devices with identification codes

A recording device allows wireless interrogation to determine its identity and its state. The state indicates whether one or more physical or chemical events have taken place. In effect, the one or more physical or chemical events are recorded by the device. The identity of the device allows it to be distinguished from a number of similar devices. The recording device may be used in an array of devices that allows wireless probing by an interrogation unit. When probed, each device tells the interrogator who it is and what state it is in. The devices allow multiple use and the interrogator may use a logical reset to determine the state of each device. The interrogator can thus easily identify particular items in an array that have reached a particular condition. The device may record the status of each device in a database to maintain a history for each.

Watters, David G.↗

The Frasnian-Famennian mass killing event(s), methods of identification and evaluation

The absence of an abnormally high number of earlier Devonian taxa from Famennian sediments was repeatedly documented and can hardly be questioned. Primary recognition of the event(s) was based on paleontological data, especially common macrofossils. Most paleontologists place the disappearance of these common forms at the gigas/triangularis contact and this boundary was recently proposed as the Frasnian-Famennian (F-F) boundary. Not unexpectedly, alternate F-F positions were suggested caused by temporary Frasnian survivors or sudden post-event radiations of new forms. Secondary supporting evidence for mass killing event(s) is supplied by trace element and stable isotope geochemistry but not with the same success as for the K/T boundary, probably due to additional 300 ma of tectonic and diagenetic overprinting. Another tool is microfacies analysis which is surprisingly rarely used even though it can explain geochemical anomalies or paleontological overlap not detectable by conventional macrofacies analysis. The combination of microfacies analysis and geochemistry was applied at two F-F sections in western Canada and showed how interdependent the two methods are. Additional F-F sections from western Canada, western United States, France, Germany and Australia were sampled or re-sampled and await geochemical/microfacies evaluation.

Geldsetzer, H. H. J.↗

High Energy Physics Network Requirements Review: Final Report, July 2024–December 2024

The world-class research infrastructure at the US Department of Energy (DOE) Office of Science (SC) provides the research community with premier observational, experimental, computational, and network capabilities. Each user facility is designed to provide unique capabilities to advance the core DOE mission in science and technology for its SC program to stimulate rich scientific discoveries and enhance its innovation ecosystem. Research communities gather and flourish around each user facility, bringing together new and enhanced perspectives. The continual reinvention of the practice of science — as users and staff forge novel approaches expressed in research workflows — unlocks new discoveries and propels scientific progress. Within this research ecosystem, the high-performance computing (HPC) and networking user facilities stewarded by the SC’s Advanced Scientific Computing Research (ASCR) program play a dynamic cross-cutting role, enabling complex workflows demanding high-performance data, networking, and computing solutions. The ASCR facilities enterprise seeks to understand and meet the needs and requirements across SC and DOE domain science programs and priority efforts, highlighted by the formal requirements review methodology. Between July and December 2024, the Energy Sciences Network (ESnet) and the Office of High Energy Physics (HEP) of the DOE-SC organized an ESnet requirements review of HEP-supported program activities. Preparation for these events included identification of key stakeholders: program and facility management, research groups, and technology providers. Each stakeholder group was asked to prepare formal case study documents about its relationship to the HEP program to build a complete understanding of the current, near-term, and long-term status, expectations, and processes that will support the science going forward.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Alternative Datasets for Identification of Earth Science Events and Data

Alternative, or non-traditional, data sources can be used to generate datasets which can in turn be analyzed for temporal, spatial and climatological patterns. Events and case studies inferred from the analysis of these patterns can be used by the remote sensing community to more effectively search for Earth observation data. In this paper, we present a new alternative Earth science dataset created from the National Weather Service’s Area Forecast Discussion (AFD) documents. We then present an exploratory methodology for identifying interesting climatological patterns within the AFD data and a corresponding motivating example as to how these data and patterns can be used to search for relevant events or case studies.

Bugbee, Kaylin↗

Neutrino Physics with Deep Learning on NOvA

The NOvA experiment has made both νμ \nu_\mu disappearance and νe \nu_e appearance measurements in Fermilab's NuMI beam, and is working on cross section measurements using near detector data. At the core of NOvA's measurements is the use of deep learning algorithms for identification and reconstruction of the neutrino flavor and energy. These algorithms, used for the first time on NOvA in 2016, yielded large improvements in selection efficiency, and will be applied to our first anti-neutrino results to be released this year. Presented here is the extension of our deep learning efforts for identification of neutrino signal events, final state identification, single particle tagging, and reconstruction using instance segmentation techniques. We will describe the new implementations of modified Convolutional Neural Networks for anti-neutrino events, single particles and their performance for analysis final states selection, standard candle measurements, and reconstruction.

Psihas, Fernanda [Indiana U.]↗

Search for Electromagnetic Counterparts to LIGO-Virgo Candidates: Expanded Very Large Array Observations

This paper summarizes a search for radio wavelength counterparts to candidate gravitational wave events. The identification of an electromagnetic counterpart could provide a more complete understanding of a gravitational wave event, including such characteristics as the location and the nature of the progenitor. We used the Expanded Very Large Array (EVLA) to search six galaxies which were identified as potential hosts for two candidate gravitational wave events. We summarize our procedures and discuss preliminary results.

methods↗

The Impact of Early Design Phase Risk Identification Biases on Space System Project Performance

Risk identification during the early design phases of complex systems is commonly implemented but often fails to result in the identification of events and circumstances that truly challenge project performance. Inefficiencies in cost and schedule estimation are usually held accountable for cost and schedule overruns, but the true root cause is often the realization of programmatic risks. A deeper understanding of frequent risk identification trends and biases pervasive during space system design and development is needed, for it would lead to improved execution of existing identification processes and methods.

Reeves, John D., Jr.↗

Simultaneous Probe of the Charm and Bottom Quark Yukawa Couplings Using $t\bar{t}$𝐻 Events

A search for the standard model Higgs boson decaying to a charm quark-antiquark pair, 𝐻→$c\bar{c}$, produced in association with a top quark-antiquark pair ($t\bar{t}$𝐻) is presented. The search is performed with data from proton-proton collisions at √𝑠 =13 TeV, corresponding to an integrated luminosity of 138 fb−1. Advanced machine learning techniques are employed for jet flavor identification and event classification. The Higgs boson decay to a bottom quark-antiquark pair is measured simultaneously and the observed $t\bar{t}$𝐻(𝐻→$b\bar{b}$) event rate relative to the standard model expectation is 0.91$^{+0.26}_{−0.22}$. The observed (expected) upper limit on the product of production cross section and branching fraction 𝜎⁡($t\bar{t}$𝐻)⁢ℬ⁡(𝐻→$c\bar{c}$) is 0.11 (0.13) pb at 95% confidence level, corresponding to 7.8 (8.7) times the standard model prediction. When combined with the previous search for 𝐻 →$c\bar{c}$ via associated production with a 𝑊 or 𝑍 boson, the observed (expected) 95% confidence interval on the Higgs-charm Yukawa coupling modifier, 𝜅 𝑐 , is |𝜅 𝑐 | < 3.5 (2.7), the most stringent constraint to date.

Bottom quark↗

Real-time charged track reconstruction for CLAS12

Abstract This paper presents the results of charged particle track reconstruction in CLAS12 using artificial intelligence. In our approach, we use machine learning algorithms to reconstruct tracks, including their momentum and direction, with high accuracy from raw hits of the CLAS12 drift chambers. The reconstruction is performed in real-time, with the rate of data acquisition, and allows for the identification of event topologies in real-time. This approach revolutionizes the Nuclear Physics experiments' data processing, allowing us to identify and categorize the experimental data on the fly, and will lead to a significant reduction in experiment data processing. It can also be used in streaming readout applications leading to more efficient data acquisition and post-processing.

Instruments & Instrumentation↗