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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 1,369 records · Page 76
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

The Role of Snowmelt and Subsurface Heterogeneity in Headwater Hydrology of a Mountainous Catchment in Colorado: A Model‐Data Integration Approach

Mountainous headwater streams are sustained by both snowmelt‐driven streamflow and groundwater discharge in the Upper Colorado River Basin. However, predicting headwater stream discharge magnitude and peak flow timing is challenging in mountainous terrains, where snowmelt rates vary with vegetation type and elevation, and heterogeneous subsurface physical properties influence groundwater storage and its release. We used a model‐data integration approach to investigate the roles of snowmelt and subsurface structure in stream discharge and groundwater level. We ran an ensemble of 100 integrated surface‐subsurface hydrologic models for a mountainous headwater catchment near Crested Butte, Colorado, USA. We also evaluated and calibrated these models against observed data sets, including snow depth measurements using distributed temperature probes, stream discharge, and groundwater levels. Calibration with multiple data sources using neural density estimators has further constrained uncertainty in subsurface properties and snowmelt rates. Results indicated that observed slower snowmelt rates in evergreen forests delayed the peak flow and baseflow onset. In upstream areas with lower subsurface permeability, water was stored within the subsurface but was not released as interflow or shallow groundwater flow, and thereby not contributing to downstream streamflow during recession limb periods. Double peaks in groundwater occurred in areas with spatial subsurface heterogeneity, in our case due to the contrast between granodiorite and Mancos shale. These process‐based insights into groundwater and snowmelt dynamics in mountainous headwaters will help improve predictions of headwater hydrology.

Wang, Lijing [University of Connecticut, Storrs, C↗
DOE OSTI2022

Real-time streaming tomographic reconstruction with on-demand data capturing and 3D zooming to regions of interest

Complex dynamic tomographic experiments at brilliant X-ray light sources require real-time feedback on the sample changes with respect to environmental conditions, selecting representative regions of interest for high-resolution scanning, and on-demand data saving mechanisms for storing only relevant projections acquired by fast area detectors and reducing data volumes. Here the implementation details of a 3D real-time imaging monitoring instrument, with zooming to a volume of interest with easy-to-use visualization via ImageJ , a tool familiar to most beamline users, is presented. The instrument relies on optimized data flow between the detector and processing machines and is implemented on commodity computers. The instrument has been developed at beamline 2-BM of the Advanced Photon Source, where the automatic lens changing mechanism for zooming is implemented with an Optique Peter microscope. Performance tests demonstrate the ability to process more than 3 GB of projection data per second and generate real-time 3D zooming with different magnification. These new capabilities are essential for new APS Upgrade instruments such as the projection microscope under development at beamline 32-ID. The efficacy of the proposed instrument was demonstrated during an in situ tomographic experiment on ice and gas hydrate formation in porous samples.

3D zooming↗
NASA NTRS2010

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

Earlier onset of springtime weather including earlier snowmelt has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for streamflow management. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud- gap-filled (CGF) map products and 30 years of discharge and meteorological station data are studied. Streamflow data from six streams in the WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed using MODIS snow-cover maps within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period. MODIS-derived snow cover (percent of basin covered) measured on 30 April explains over 89% of the variance in discharge for maximum monthly streamflow in the decade of the 2000s using Spearman rank correlation analysis. We also investigated stream power for Bull Lake Creek Above Bull Lake from 1970 to 2009; a statistically-significant end toward reduced stream power was found (significant at the 90% confidence level). Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period. The strong relationship between percent of basin covered and streamflow indicates that MODIS data is useful for predicting streamflow, leading to improved reservoir management

Hall, Dorothy K.↗
NASA NTRS2008

Wireless Sensor Network Handles Image Data

To relay data from remote locations for NASA s Earth sciences research, Goddard Space Flight Center contributed to the development of "microservers" (wireless sensor network nodes), which are now used commercially as a quick and affordable means to capture and distribute geographical information, including rich sets of aerial and street-level imagery. NASA began this work out of a necessity for real-time recovery of remote sensor data. These microservers work much like a wireless office network, relaying information between devices. The key difference, however, is that instead of linking workstations within one office, the interconnected microservers operate miles away from one another. This attribute traces back to the technology s original use: The microservers were originally designed for seismology on remote glaciers and ice streams in Alaska, Greenland, and Antarctica-acquiring, storing, and relaying data wirelessly between ground sensors. The microservers boast three key attributes. First, a researcher in the field can establish a "managed network" of microservers and rapidly see the data streams (recovered wirelessly) on a field computer. This rapid feedback permits the researcher to reconfigure the network for different purposes over the course of a field campaign. Second, through careful power management, the microservers can dwell unsupervised in the field for up to 2 years, collecting tremendous amounts of data at a research location. The third attribute is the exciting potential to deploy a microserver network that works in synchrony with robotic explorers (e.g., providing ground truth validation for satellites, supporting rovers as they traverse the local environment). Managed networks of remote microservers that relay data unsupervised for up to 2 years can drastically reduce the costs of field instrumentation and data rec

Source record↗
NASA NTRS2011

Feature Acquisition with Imbalanced Training Data

This work considers cost-sensitive feature acquisition that attempts to classify a candidate datapoint from incomplete information. In this task, an agent acquires features of the datapoint using one or more costly diagnostic tests, and eventually ascribes a classification label. A cost function describes both the penalties for feature acquisition, as well as misclassification errors. A common solution is a Cost Sensitive Decision Tree (CSDT), a branching sequence of tests with features acquired at interior decision points and class assignment at the leaves. CSDT's can incorporate a wide range of diagnostic tests and can reflect arbitrary cost structures. They are particularly useful for online applications due to their low computational overhead. In this innovation, CSDT's are applied to cost-sensitive feature acquisition where the goal is to recognize very rare or unique phenomena in real time. Example applications from this domain include four areas. In stream processing, one seeks unique events in a real time data stream that is too large to store. In fault protection, a system must adapt quickly to react to anticipated errors by triggering repair activities or follow- up diagnostics. With real-time sensor networks, one seeks to classify unique, new events as they occur. With observational sciences, a new generation of instrumentation seeks unique events through online analysis of large observational datasets. This work presents a solution based on transfer learning principles that permits principled CSDT learning while exploiting any prior knowledge of the designer to correct both between-class and withinclass imbalance. Training examples are adaptively reweighted based on a decomposition of the data attributes. The result is a new, nonparametric representation that matches the anticipated attribute distribution for the target events.

Thompson, David R.↗
NASA NTRS2010

Relationship Between Satellite-Derived Snow Cover and Snowmelt-Runoff Timing and Stream Power in the Wind River Range, Wyoming

Earlier onset of springtime weather including earlier snowmelt has been documented in the western United States over at least the last 50 years. Because the majority (>70%) of the water supply in the western U.S. comes from snowmelt, analysis of the declining spring snowpack (and shrinking glaciers) has important implications for streamflow management. The amount of water in a snowpack influences stream discharge which can also influence erosion and sediment transport by changing stream power, or the rate at which a stream can do work such as move sediment and erode the stream bed. The focus of this work is the Wind River Range (WRR) in west-central Wyoming. Ten years of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow-cover, cloud- gap-filled (CGF) map products and 30 years of discharge and meteorological station a are studied. Streamflow data from six streams in the WRR drainage basins show lower annual discharge and earlier snowmelt in the decade of the 2000s than in the previous three decades, though no trend of either lower streamflow or earlier snowmelt was observed using MODIS snow-cover maps within the decade of the 2000s. Results show a statistically-significant trend at the 95% confidence level (or higher) of increasing weekly maximum air temperature (for three out of the five meteorological stations studied) in the decade of the 1970s, and also for the 40-year study period. MODIS- derived snow cover (percent of basin covered) measured on 30 April explains over 89% of the variance in discharge for maximum monthly streamflow in the decade of the 2000s using Spearman rank correlation analysis. We also investigated stream power for Bull Lake Creek Above Bull Lake from 1970 to 2009; a statistically-significant trend toward reduced stream power was found (significant at the 90% confidence level). Observed changes in streamflow and stream power may be related to increasing weekly maximum air temperature measured during the 40-year study period. The strong relationship between percent of basin covered and streamflow indicates that MODIS data is useful for predicting streamflow, leading to improved reservoir management.

Hall, Dorothy K.↗
NASA NTRS1976

The acceleration of energetic particles in the interplanetary medium by transit-time damping

Transit time damping is examined as a possible means for accelerating low energy particles in co-rotating streams and interstellar ions. Data show that: the protons in co-rotating streams may be accelerated by transient-time damping the small-scale variations in the field magnitude that are observed at a low level in the inner solar system. The interstellar ions may be accelerated by transit time damping large-scale field variations in the outer solar system.

Fisk, L. A.↗
NASA NTRS1998

Improving Acoustic Models by Watching Television

Obtaining sufficient labelled training data is a persistent difficulty for speech recognition research. Although well transcribed data is expensive to produce, there is a constant stream of challenging speech data and poor transcription broadcast as closed-captioned television. We describe a reliable unsupervised method for identifying accurately transcribed sections of these broadcasts, and show how these segments can be used to train a recognition system. Starting from acoustic models trained on the Wall Street Journal database, a single iteration of our training method reduced the word error rate on an independent broadcast television news test set from 62.2% to 59.5%.

Witbrock, Michael J.↗
NASA NTRS2003

Possible Stick-Slip Mechanism for Whillans Ice Stream

Tidally-induced stick-slip motion in the mouth of Whillans Ice Stream provides a unique natural experiment in ice-stream response behavior and fiom which we might learn a great deal about subglacial till properties and sub-ice-stream conditions. At the IGS Symposium on Fast Glacier Flow (Yakutat, 2002), we reported our observations of stick- slip motion and demonstrated its synchronicity with tidal forcing. Recently, we have completed additional processing of our GPS data in differential mode. It reveals more details of the stick-slip events and illustrates that within 30 seconds, the temporal interval of our data, the ice stream accelerates to a speed corresponding to a completely lubricated bed. While details of individual events vary, there seems to be strong evidence of an elastic rebound on the time scale of one hour following most events. This suggests the event involves the release of stored elastic strain energy in the ice. The similar displacements of events suggest further that till or subglacial hydrologic properties limit the amount of elastic strain released in any single event. We follow a line of reasoning that dilatant strengthening limits the slip displacement and present model of the stick-slip process. To match the observed delay between the peak ocean tide and stick-slip events, our model includes a propagating pressure wave in the subglacial hydrologic system between the grounding line, where the rising tide first increases the subglacial water pressure and regions upstream where stored elastic strain increases the basal shear stress. This high-tide event is released when the increased water pressure reaches the region of increased shear stress. Dilatant strengthening stops the event by increasing pore volume and lowering the water pressure. Following this event, falling tide increases the normal forces, compresses the till and increases pore pressure again, leading to the second falling-tide event we observe every tidal cycle.

Bindschadler, Robert↗
NASA NTRS2003

Possible Stick-Slip Mechanism for Whillans Ice Stream

Tidally-induced stick-slip motion in the mouth of Whillans Ice Stream provides a unique natural experiment in ice-stream response behavior and from which we might learn a great deal about subglacial till properties and sub-ice-stream conditions. At the IGS Symposium on Fast Glacier Flow (Yakutat, 2002), we reported our observations of stick- slip motion and demonstrated its synchronicity with tidal forcing. Recently, we have completed additional processing of our GPS data in differential mode. It reveals more details of the stick-slip events and illustrates that within 30 seconds, the temporal interval of our data, the ice stream accelerates to a speed corresponding to a completely lubricated bed. While details of individual events vary, there seems to be strong evidence of an elastic rebound on the time scale of one hour following most events. This suggests the event involves the release of stored elastic strain energy in the ice. The similar displacements of events suggest further that till or subglacial hydrologic properties limit the amount of elastic strain released in any single event. We follow a line of reasoning that dilatant strengthening limits the slip displacement and present model of the stick-slip process. To match the observed delay between the peak ocean tide and stick-slip events, our model includes a propagating pressure wave in the subglacial hydrologic system between the grounding line, where the rising tide first increases the subglacial water pressure and regions upstream where stored elastic strain increases the basal shear stress. This high-tide event is released when the increased water pressure reaches the region of increased shear stress. Dilatant strengthening stops the event by increasing pore volume and lowering the water pressure. Following this event, falling tide increases the normal forces, compresses the till and increases pore pressure again, leading to the second falling-tide event we observe every tidal cycle.

Bindschadler, Robert↗
NASA NTRS2018

Space-to-Ground Interactions While Conducting Scientific Fieldwork Under Mars Mission Constraints

The Biologic Analog Science Associated with Lava Terrains (BASALT) project is a 4-year program dedicated to iteratively designing, implementing, and evaluating concepts of operations (ConOps) and supporting capabilities to enable and enhance scientific exploration for future human Mars missions. BASALT incorporates three field deployments during which real (non-simulated) biological and geochemical field science is conducted at two high-fidelity Mars analog locations under simulated Mars mission conditions, including communication de-lays and data transmission limitations. BASALT’s primary science objective is to investigate how the redox conditions of altered basaltic environments affect the development of microbial communities in these Mars-relevant settings. Field sites include the active East Rift Zone on the Big Island of Hawaii, reminiscent of early Mars when basaltic volcanism and interaction with water were widespread, and the dormant eastern Snake River Plain in Idaho, similar to present-day Mars where basaltic volcanism is rare and most evidence for volcano-driven hydrothermal activity is relict. BASALT’s primary science operations objective is to investigate exploration ConOps and capabilities that facilitate scientific return during human-robotic exploration under Mars mission constraints. Each field deployment consists of ten extravehicular activities (EVAs) on the volcanic flows in which two extravehicular and two intravehicular (IV) crew-members conduct the science while communicating across time delay and under bandwidth constraints with an Earth-based Mission Support Center (MSC) comprised of expert scientists and operators. Communication latencies of 5 and 15-minute one-way light time and low (0.512 Mb/s uplink, 1.54 Mb/s down-link) and high (5.0 Mb/s uplink, 10.0 Mb/s downlink) bandwidth conditions are being evaluated. EVA crewmembers communicate with the MSC via voice and text messaging and provide scientific instrument data, still imagery, video streams, and GPS tracking information. The MSC reviews this data across delay and provides recommendations for presampling and sampling tasks. The scientists used dynamic leaderboards (priority rank-ing lists), to track and rank candidate samples relative to one another and against the science objectives for the current EVA and the overall mission. Updates to the dynamic leaderboards are relayed regularly to the IV crewmembers to provide scientific feedback from Earth and to help minimize crew idle time (time spent waiting for Earth input during which no productive tasks are performed). EVA timelines are strategically designed to enable continuous (delayed) feedback from an Earth-based science team while simultaneously minimizing crew idle time. Such timelines are operationally advantageous, reducing transport costs by eliminating the need for crews to return to the same locations on multiple EVAs while still providing opportunities for recommendations from science experts on Earth, and scientifically advantageous by minimizing the potential for cross-contamination across sites. This paper will highlight the space-to-ground interaction results from the three BASALT field deployments, including planned versus actual EVA time-line data, ground assimilation times (the amount of time available to the MSC to provide input to the crew), and idle time. Furthermore, we describe how these results vary under the different communication latency and bandwidth conditions. Together, these data will provide a basis for guiding and prioritizing capability development for future human exploration missions.

Beaton, Kara H.↗
DOE OSTI2017

Analysis in Motion Initiative – Summarization Capability

Analysts are tasked with integrating information from multiple data sources for important and timely decision making. What if sense making and overall situation awareness could be improved through visualization techniques? The Analysis in Motion initiative is advancing the ability to summarize and abstract multiple streams and static data sources over time.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Quantification of Hydrogen Isotopes Utilizing Raman Spectroscopy Paired with Chemometric Analysis for Application across Multiple Systems

On-line and real-time analysis of a chemical process is a major analytical challenge that can drastically change the way the chemical industry or chemical research operates. With in situ analyses, new and powerful understanding of chemistry can be gained; however, building robust tools for long-term monitoring faces many challenges that include compensating for instrument drift, instrument replacement, and sensor or probe replacement. Accounting for these changes by recollecting calibration data and rebuilding quantification models can be costly and time consuming. Here, in this study, methods to overcome these challenges are demonstrated with an application of Raman spectroscopy to monitoring hydrogen isotopes with varied speciation within dynamic gas streams. Specifically, chemical data science tools such as chemometric modeling are leveraged along with several examples of calibration transfer approaches. Furthermore, the optimization of instrument and sensors cell parameters for targeted gas phase analyses is discussed. While the particular focus on hydrogen is highly beneficial within the nuclear energy sector, mechanisms built and demonstrated here are widely applicable to optical spectroscopy monitoring in numerous other chemical systems that can be leveraged in other hazardous processes.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

Sensor enabled data-driven predictive analytics for modeling and control with high penetration of DERs in distribution systems

The electric power grid is undergoing a tremendous transformation due to the increasing penetration of renewable energy resources beginning with wind and more recently with the distributed energy resources (DERs) such as solar and battery storage. DERs have dramatically changed the role of the distribution systems in the overall power grid, and they are expected to contribute a significant portion of power generation in the future. If current trends for DERs continue, system operation and control will need to change dramatically for improved grid reliability and resiliency. As renewable resources increase in penetration, new and challenging operational, planning, and design problems are expected to emerge. Some of the key challenges that arise in the planning and operation of the future grid are: 1) Quantifying the impact of high DER penetration in distribution systems on bulk grid behavior over multiple time scales. 2) Identifying whether a particular DER configuration/settings have a large impact on the overall grid behavior. These challenges can be addressed in an offline manner using detailed T&D grid models and they can also be addressed in an online manner using sensor measurements. In particular, the advancement and planned growth in sensor technology in power grid over various voltage levels provide us with a unique opportunity to tackle these challenges from a data analytic perspective without needing detailed T&D grid models. A few questions that naturally arise when addressing the challenges from DERs using sensor data are: 1) How can we use limited sensor measurements to monitor & control voltage stability and small signal stability of the bulk system? 2) How can we ensure that the developed data analytic methods are robust to data availability and quality issues? 3) How can we compute the developed analytics in a scalable manner using streaming measurements? In this project, we addressed the aforementioned challenges arising from DERs and answered the questions raised above on how to effectively use the sensor measurements to enhance the reliability and performance of the electric grid. Thus, the overarching goal of this project is to develop effective reduced/representative system models from data that make the computational complexity sufficiently manageable so as to be useful to simulate, analyze, and even control complex non-linear power systems dynamics with large penetrations of DERs. In order to achieve the objective, the project team established a four-fold technical approach 1) Formulated a combined transmission-distribution co-simulation framework for data generation and validation, 2) Derived reduced/representative models of power systems based on data-driven methods for efficient computation and appropriate representation of system behavior, 3) Developed data driven characterization of power system behavior based on transfer operator theory, machine learning and optimization for model estimation, 4) Incorporated a scalable data management and processing architecture using distributed Kafka streaming applications that coordinate input data streams to the developed data analytics. The key accomplishments of the project are: 1) Development of a scalable multi-timescale T&D co-simulation framework (both for steady state and for dynamic co-simulation) using commercial solvers (PSSE and GridLAB-D). The steady-state T&D co-simulation interface is shared with our industry partner (PJM). 2) A structured reduced order dynamic model of distribution systems that can represent partial motor stalling along with a systematic procedure to derive the model parameters. 3) A PMU based online method to monitor, localize and mitigate fault-induced delayed voltage recovery using DER reactive support and load control in distribution systems. 4) Development of linear operator based robust methodologies for dynamic state estimation, uncertainty quantification, system identification and trajectory prediction for power system dynamics. 5) An adaptive damping control for utilizing wind energy resources to provide oscillation damping and system stability. 6) Implementation of Kafka-based framework for efficient processing of streaming data using Linux-based local virtual environment.

DER integration↗
NASA NTRS1986

Gulf stream velocity structure through combined inversion of hydrographic and acoustic Doppler data

Near-surface velocities from an acoustic Doppler instrument are used in conjunction with CTD/O2 data to produce estimates of the absolute flow field off Cape Hatteras. The data set consists of two transects across the Gulf Stream made by the R/V Endeavor cruise EN88 in August 1982. An inverse procedure is applied which makes use of both the acoustic Doppler data and property conservation constraints. Velocity sections at approximately 73 deg. W and 71 deg. W are presented with formal errors of 1-2 cm/s. The net Gulf Stream transports are estimated to be 116 + or - 2 Sv across the south leg and 161 + or - 4 Sv across the north. A Deep Western Boundary Current transport of 4 + or - 1 Sv is also estimated. While these values do not necessarily represent the mean, they are accurate estimates of the synoptic flow field in the region.

Pierce, S. D.↗
NASA NTRS1985

On boundary layer transition in high-subsonic and transonic flow under the influence of acoustic disturbances and free-stream turbulence

The existing data base which quantifies the roles played by the Mach number, turbulence level, and acoustic noise in the flow quality of wind tunnels is reviewed. Attention is given to the effects on end (ET) and beginning (BT) transitions in flows over a 10 deg cone in transonic channels. The Re of both ET and BT flows were significantly affected by the Mach number, acoustic noise level and the noise frequency content. A unit increment in the Mach number increased the Re beyond 3,000,000, while noise below the 1 percent level in the rms pressure coefficient did not alter the transition phenomenon. More data are required on the effects of turbulence, which was a significant factor, and in the settling chamber, test section, plenum and diffuser to trace the locations and magnitudes of the acoustic sources.

Murthy, S. V.↗