Search NASA⌕ Search

SEARCH · Search NASA

Results for “streaming data”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2014

AGR-3/4 Data Qualification Report for ATR Cycles 151A, 151B, 152A, 152B, 154A, and 154B

This data report provides the qualification status of Advanced Gas Reactor-3/4 (AGR-3/4) fuel irradiation experimental data from Advanced Test Reactor (ATR) Cycles 151A, 151B, 152A, 152B, 154A, and 154B, as recorded in the Nuclear Data Management and Analysis System (NDMAS). Of these cycles, ATR Cycle 152A is a low power cycle that occurred when the ATR core was briefly at low power. The irradiation data are not used for physics and thermal calculation, but the qualification status of these cycle data is still covered in this report. On the other hand, during ATR Cycles 153A (unplanned Outage cycle) and 153B (Power Axial Locator Mechanism [PALM] cycle), the AGR-3/4 was pulled out from the ATR core and stored in the canal to avoid being overheated. Therefore, qualification of the AGR-3/4 irradiation data from these 2 cycles was excluded in this report. By the end of ATR Cycle 154B, AGR-3/4 was irradiated for a total of 264.1 effective full power days. The AGR-3/4 data streams addressed in this report include thermocouple (TC) temperatures, sweep gas data (flow rates, pressure, and moisture content), and Fission Product Monitoring System (FPMS) data (release rates and release-to-birth rate ratios [R/Bs]) for each of the twelve capsules in the AGR-3/4 experiment. The final data qualification status for these data streams is determined by a Data Review Committee (DRC) composed of AGR technical leads, Sitewide Quality Assurance (QA), and NDMAS analysts. The DRC convened on February 12, 2014, reviewed the data acquisition process, and considered whether the data met the requirements for data collection as specified in QA-approved Very High Temperature Reactor (VHTR) Technology Development Office (TDO) data collection plans. The DRC also examined the results of NDMAS data testing and statistical analyses, and confirmed the qualification status of the data as given in this report.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2015

AGR-3/4 Final Data Qualification Report for ATR Cycles 151A through 155B-1

This report provides the qualification status of experimental data for the entire Advanced Gas Reactor 3/4 (AGR 3/4) fuel irradiation. AGR-3/4 is the third in a series of planned irradiation experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL) for the AGR Fuel Development and Qualification Program, which supports development of the advanced reactor technology under the INL ART Technology Development Office (TDO). The main objective of AGR-3/4 irradiation is to provide a known source of fission products for subsequent transport through compact matrix and structural graphite materials due to the presence of designed-to-fail fuel particles. Full power irradiation of the AGR 3/4 test began on December 14, 2011 (ATR Cycle 151A), and was completed on April 12, 2014 (end of ATR Cycle 155B) after 369.1 effective full power days of irradiation. The AGR-3/4 test was in the reactor core for eight of the ten ATR cycles between 151A and 155B. During the unplanned outage cycle, 153A, the experiment was removed from the ATR northeast flux trap (NEFT) location and stored in the ATR canal. This was to prevent overheating of fuel compacts due to higher than normal ATR power during the subsequent Powered Axial Locator Mechanism cycle, 153B. The AGR 3/4 test was inserted back into the ATR NEFT location during the outage of ATR Cycle 154A on April 26, 2013. Therefore, the AGR-3/4 irradiation data received during these 2 cycles (153A and 153B) are irrelevant and their qualification status isnot included in this report. Additionally, during ATR Cycle 152A the ATR core ran at low power for a short enough duration that the irradiation data are not used for physics and thermal calculations. However, the qualification status of irradiation data for this cycle is still covered in this report. As a result, this report includes data from 8 ATR Cycles: 151A, 151B, 152A, 152B, 154A, 154B, 155A, and 155B, as recorded in the Nuclear Data Management and Analysis System (NDMAS). The AGR 3/4 data streams addressed in this report include thermocouple (TC) temperatures, sweep gas data (flow rates, pressure, and moisture content), and Fission Product Monitoring System (FPMS) data (release rates, release to birth rate ratios [R/Bs], and particle failure counts) for each of the twelve capsules in the AGR 3/4 experiment. During Outage Cycle 155A, fourteen flow meters were installed downstream from fourteen FPMS monitors to measure flows from the monitors; qualification status of these data are also included in the report. The final data qualification status for these data streams is determined by a Data Review Committee (DRC) composed of AGR technical leads, Sitewide Quality Assurance (QA), and NDMAS analysts. For ATR Cycles 151A through 154B, the DRC convened on February 12, 2014, reviewed the data acquisition process, and considered whether the data met the requirements for data collection as specified in QA approved INL ART TDO data collection plans. The DRC also examined the results of NDMAS data testing and statistical analyses, and confirmed the qualification status of the data as given in this report. The qualification status of AGR-3/4 irradiation data during the first six cycles were previously reported in INL/EXT-14-31186 document. This report presents data qualification status for the entire AGR-3/4 irradiation.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
NASA NTRS2019

Alternative Vegetation States in Tropical Forests and Savannas: The Search for Consistent Signals in Diverse Remote Sensing Data

Globally, the spatial distribution of vegetation is governed primarily by climatological factors (rainfall and temperature, seasonality, and inter-annual variability). The local distribution of vegetation, however, depends on local edaphic conditions (soils and topography) and disturbances (fire, herbivory, and anthropogenic activities). Abrupt spatial or temporal changes in vegetation distribution can occur if there are positive (i.e., amplifying) feedbacks favoring certain vegetation states under otherwise similar climatic and edaphic conditions. Previous studies in the tropical savannas of Africa and other continents using the MODerate Resolution Imaging Spectroradiometer (MODIS) vegetation continuous fields (VCF) satellite data product have focused on discontinuities in the distribution of tree cover at different rainfall levels, with bimodal distributions (e.g., concentrations of high and low tree cover) interpreted as alternative vegetation states. Such observed bimodalities over large spatial extents may not be evidence for alternate states, as they may include regions that have different edaphic conditions and disturbance histories. In this study, we conduct a systematic multi-scale analysis of diverse MODIS data streams to quantify the presence and spatial consistency of alternative vegetation states in Sub-Saharan Africa. The analysis is based on the premise that major discontinuities in vegetation structure should also manifest as consistent spatial patterns in a range of remote sensing data streams, including, for example, albedo and land surface temperature (LST). Our results confirm previous observations of bimodal and multimodal distributions of estimated tree cover in the MODIS VCF. However, strong disagreements in the location of multimodality between VCF and other data streams were observed at 1 km scale. Results suggest that the observed distribution of VCF over vast spatial extents are multimodal, not because of local-scale feedbacks and emergent bifurcations (the definition of alternative states), but likely because of other factors including regional scale differences in woody dynamics associated with edaphic, disturbance, and/or anthropogenic processes. These results suggest the need for more in-depth consideration of bifurcation mechanisms and thus the likely spatial and temporal scales at which alternative states driven by different positive feedback processes should manifest.

Savanna↗
NASA NTRS2005

Portable Airborne Laser System Measures Forest-Canopy Height

(PALS) is a combination of laser ranging, video imaging, positioning, and data-processing subsystems designed for measuring the heights of forest canopies along linear transects from tens to thousands of kilometers long. Unlike prior laser ranging systems designed to serve the same purpose, the PALS is not restricted to use aboard a single aircraft of a specific type: the PALS fits into two large suitcases that can be carried to any convenient location, and the PALS can be installed in almost any local aircraft for hire, thereby making it possible to sample remote forests at relatively low cost. The initial cost and the cost of repairing the PALS are also lower because the PALS hardware consists mostly of commercial off-the-shelf (COTS) units that can easily be replaced in the field. The COTS units include a laser ranging transceiver, a charge-coupled-device camera that images the laser-illuminated targets, a differential Global Positioning System (dGPS) receiver capable of operation within the Wide Area Augmentation System, a video titler, a video cassette recorder (VCR), and a laptop computer equipped with two serial ports. The VCR and computer are powered by batteries; the other units are powered at 12 VDC from the 28-VDC aircraft power system via a low-pass filter and a voltage converter. The dGPS receiver feeds location and time data, at an update rate of 0.5 Hz, to the video titler and the computer. The laser ranging transceiver, operating at a sampling rate of 2 kHz, feeds its serial range and amplitude data stream to the computer. The analog video signal from the CCD camera is fed into the video titler wherein the signal is annotated with position and time information. The titler then forwards the annotated signal to the VCR for recording on 8-mm tapes. The dGPS and laser range and amplitude serial data streams are processed by software that displays the laser trace and the dGPS information as they are fed into the computer, subsamples the laser range and amplitude data, interleaves the subsampled data with the dGPS information, and records the resulting interleaved data stream.

Nelson, Ross↗
DOE OSTI2022

Learning Global Proliferation Expertise Evolution Using AI-Driven Analytics and Public Information

Detecting and anticipating global proliferation expertise and capability evolution from unstructured, noisy, and incomplete public data streams is a highly desired, but extremely challenging task. Here, in this article, we present our pioneering data-driven approach to support the non-proliferation mission to detect and explain the evolution of proliferation expertise and capability development globally from terabytes of publicly available information (PAI), focusing on our knowledge extraction pipeline and descriptive analytics. We first discuss how we fuse nine open-source data streams, including multilingual data, to convert 4 TB of unstructured data to structured knowledge and encode dynamically evolving proliferation expertise representations—content and context graphs. For this, we rely on natural language processing (NLP) and deep learning (DL) models to perform information extraction, topic modeling, and distributed text representation (aka embedding) learning. We then present interactive, usable, and explainable descriptive analytics to refine domain knowledge and present it in a human-understandable form. Finally, we introduce future work avenues that will leverage our dynamic knowledge representations and descriptive analytics to enable predictive and prescriptive inferences to achieve real-time domain understanding and contextual reasoning about global proliferation expertise and capability evolution.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗
DOE OSTI2016

SPRUCE S1 Bog Porewater, Groundwater, and Stream Chemistry Data: 2011-2013

This data set reports the chemistry of S1 bog porewater, outlet stream water, and groundwater from upland wells from 2011 through 2013. These data provide information for studies of the biogeochemical status of the bog and surrounding groundwater aquifer. Porewater samples were collected from one nest of 6 piezometers installed in a hollow in the south end of the S1 bog to characterize solute chemistry depth profiles. Peat porewater was collected from piezometers that opened at 0, 0.3, 0.5, 1, 2, and 3 m depths below hollow surfaces. Samples were collected weekly (2011) or monthly (2012 & 2013) when the samplers were not frozen (typically June – November). Stream water was sampled weekly (2011-2013) from the outlet of the S1 bog (located on the southern edge of the bog). Four groundwater wells located in the uplands of the S1 watershed were sampled monthly in 2013. Bog water level data are also reported for the S1 bog. Water samples were analyzed for pH, specific conductivity, nutrient concentrations (ammonium, nitrate, soluble reactive phosphorus, total nitrogen, total phosphorus), cation concentrations (calcium, potassium, magnesium, sodium, aluminum, iron, manganese, silicon, strontium), anion concentrations (chloride, sulfate), and total organic carbon concentrations. The experimental work is to be conducted in a Picea mariana [black spruce] – Sphagnum spp. bog forest in northern Minnesota, 40 km north of Grand Rapids, in the USDA Forest Service Marcell Experimental Forest (MEF).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1995

Computer simulation results for PCM/PM/NRZ receivers in nonideal channels

This article studies, by computer simulations, the performance of deep-space telemetry signals that employ the pulse code modulation/phase modulation (PCM/PM) technique, using nonreturn-to-zero data, under the separate and combined effects of unbalanced data, data asymmetry, and a band-limited channel. The study is based on measuring the symbol error rate performance and comparing the results to the theoretical results presented in previous articles. Only the effects of imperfect carrier tracking due to an imperfect data stream are considered. The presence of an imperfect data stream (unbalanced and/or asymmetric) produces undesirable spectral components at the carrier frequency, creating an imperfect carrier reference that will degrade the performance of the telemetry system. Further disturbance to the carrier reference is caused by the intersymbol interference created by the band-limited channel.

Anabtawi, A.↗
DOE OSTI2014

Accelerating Data Acquisition, Reduction, and Analysis at the Spallation Neutron Source

ORNL operates the world's brightest neutron source, the Spallation Neutron Source (SNS). Funded by the US DOE Office of Basic Energy Science, this national user facility hosts hundreds of scientists from around the world, providing a platform to enable break-through research in materials science, sustainable energy, and basic science. While the SNS provides scientists with advanced experimental instruments, the deluge of data generated from these instruments represents both a big data challenge and a big data opportunity. For example, instruments at the SNS can now generate multiple millions of neutron events per second providing unprecedented experiment fidelity but leaving the user with a dataset that cannot be processed and analyzed in a timely fashion using legacy techniques. To address this big data challenge, ORNL has developed a near real-time streaming data reduction and analysis infrastructure. The Accelerating Data Acquisition, Reduction, and Analysis (ADARA) system provides a live streaming data infrastructure based on a high-performance publish subscribe system, in situ data reduction, visualization, and analysis tools, and integration with a high-performance computing and data storage infrastructure. ADARA allows users of the SNS instruments to analyze their experiment as it is run and make changes to the experiment in real-time and visualize the results of these changes. In this paper we describe ADARA, provide a high-level architectural overview of the system, and present a set of use-cases and real-world demonstrations of the technology.

Campbell, Stuart I↗
DOE OSTI2017

Why wait? Let's start computing while data is still on the wire

In this era of Big Data, computing useful information from data is becoming increasingly complicated, particularly due to the ever increasing volumes of data that need to travel over the network to data centers to be stored and processed, all highly expensive operations in the long haul. In this paper we suggest that we can do computing and analysis of data "on the wire," i.e., while data is still in transit. The nature of these computations include analysis, visualization, pattern recognition, and prediction, or forecasting, on the streaming data. We follow a service function chaining architecture to implement this, assuming that the data packets arrive within a single network administrative domain. As a demonstration of this new computing paradigm, we present three examples. Firstly, we demonstrate pattern recognition and data visualization on streaming forex data, which can be used for lucrative trading in the forex market. In our second example, we analyze and learn user buying patterns from clickstream data streaming from multiple websites. Finally, we monitor solar sensors for a zero reading while the packets are still on their way to the data center, to schedule any maintenance and requisite repairs with no time delay.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

LHC physics dataset for unsupervised New Physics detection at 40 MHz

In the particle detectors at the Large Hadron Collider, hundreds of millions of proton-proton collisions are produced every second. If one could store the whole data stream produced in these collisions, tens of terabytes of data would be written to disk every second. The general-purpose experiments ATLAS and CMS reduce this overwhelming data volume to a sustainable level, by deciding in real-time whether each collision event should be kept for further analysis or be discarded. We introduce a dataset of proton collision events that emulates a typical data stream collected by such a real-time processing system, pre-filtered by requiring the presence of at least one electron or muon. This dataset could be used to develop novel event selection strategies and assess their sensitivity to new phenomena. In particular, we intend to stimulate a community-based effort towards the design of novel algorithms for performing unsupervised new physics detection, customized to fit the bandwidth, latency and computational resource constraints of the real-time event selection system of a typical particle detector.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2014

Selecting Essential Information for Biosurveillance - A Multi-Criteria Decision Analysis

This paper proposes the use of Multi-Attribute Utility Theory to address the issue of identifying and selecting essential information for inclusion into a biosurveillance system or process. Additionally, we developed a decision support framework that can facilitate identifying data streams for use in biosurveillance systems or processes and demonstrated utility by applying the framework to the problem of evaluating data streams for use in an global infectious disease surveillance system.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2009

Transitioning NPOESS Data to Weather Offices: The SPoRT Paradigm with EOS Data

Real-time satellite information provides one of many data sources used by NWS weather forecast offices (WFOs) to diagnose current weather conditions and to assist in short-term forecast preparation. While GOES satellite data provides relatively coarse spatial resolution coverage of the continental U.S. on a 10-15 minute repeat cycle, polar orbiting imagery has the potential to provide snapshots of weather conditions at high-resolution in many spectral channels. Additionally, polar orbiting sounding data can provide additional information on the thermodynamic structure of the atmosphere in data sparse regions of at asynoptic observation times. The NASA Short-term Prediction Research and Transition (SPoRT) project has demonstrated the utility of polar orbiting MODIS and AIRS data on the Terra and Aqua satellites to improve weather diagnostics and short-term forecasting on the regional and local scales. SPoRT scientists work directly forecasters at selected WFOS in the Southern Region (SR) to help them ingest these unique data streams into their AWIPS system, understand how to use the data (through on-site and distance learn techniques), and demonstrate the utility of these products to address significant forecast problems. This process also prepares forecasters for the use of similar observational capabilities from NPOESS operational sensors. NPOESS environmental data records (EDRs) from the Visible 1 Infrared Imager I Radiometer Suite (VIIRS), the Cross-track Infrared Sounder (CrlS) and Advanced Technology Microwave Sounder (ATMS) instruments and additional value-added products produced by NESDIS will be available in near real-time and made available to WFOs to extend their use of NASA EOS data into the NPOESS era. These new data streams will be integrated into the NWs's new AWIPS II decision support tools. The AWIPS I1 system to be unveiled in WFOs in 2009 will be a JAVA-based decision support system which preserves the functionality of the existing systems and offers unique development opportunities for new data sources and applications in the Service Orientated Architecture ISOA) environment. This paper will highlight some of the SPoRT activities leading to the integration of VllRS and CrIS/ATMS data into the display capabilities of these new systems to support short-term forecasting problems at WFOs.

Jedlovec, Gary↗
DOE OSTI2019

Stream splitting moving target defense

Systems and methods for utilizing stream splitting Moving Target Defense (MTD) to provide enhanced computer system communication system security by splitting a data stream in to a plurality of paths is described. In some implementations, Stream splitting MTD, involves splitting a single data stream (e.g., TCP stream) into a plurality of discrete units, then sending and receiving those discrete units from and to different (ideally geographically disparate) receiving servers, with the stream being reassembled on the receiving end. The plurality of discrete units of data include resequencing data. The size of each discrete unit may vary depending on the specific implementation, even down to small unit sizes (e.g., a single packet).

Evans, Nathaniel↗
NASA NTRS1978

High data volume and transfer rate techniques used at NASA's image processing facility

Data storage and transfer operations at a new image processing facility are described. The equipment includes high density digital magnetic tape drives and specially designed controllers to provide an interface between the tape drives and computerized image processing systems. The controller performs the functions necessary to convert the continuous serial data stream from the tape drive to a word-parallel blocked data stream which then goes to the computer-based system. With regard to the tape packing density, 1.8 times 10 to the tenth data bits are stored on a reel of one-inch tape. System components and their operation are surveyed, and studies on advanced storage techniques are summarized.

Heffner, P.↗
NASA NTRS2000

The Life Cycle Application of Intelligent Software Modeling for the First Materials Science Research Rack

Marshall Space Flight Center (MSFC) has been funding development of intelligent software models to benefit payload ground operations for nearly a decade. Experience gained from simulator development and real-time monitoring and control is being applied to engineering design, testing, and operation of the First Material Science Research Rack (MSRR-1). MSRR-1 is the first rack in a suite of three racks comprising the Materials Science Research Facility (MSRF) which will operate on the International Space Station (ISS). The MSRF will accommodate advanced microgravity investigations in areas such as the fields of solidification of metals and alloys, thermo-physical properties of polymers, crystal growth studies of semiconductor materials, and research in ceramics and glasses. The MSRR-1 is a joint venture between NASA and the European Space Agency (ESA) to study the behavior of different materials during high temperature processing in a low gravity environment. The planned MSRR-1 mission duration is five (5) years on-orbit and the total design life is ten (IO) years. The MSRR-1 launch is scheduled on the third Utilization Flight (UF-3) to ISS, currently in February of 2003). The objective of MSRR-1 is to provide an early capability on the ISS to conduct material science, materials technology, and space product research investigations in microgravity. It will provide a modular, multi-user facility for microgravity research in materials crystal growth and solidification. An intelligent software model of MSRR-1 is under development and will serve multiple purposes to support the engineering analysis, testing, training, and operational phases of the MSRR-1 life cycle development. The G2 real-time expert system software environment developed by Gensym Corporation was selected as the intelligent system shell for this development work based on past experience gained and the effectiveness of the programming environment. Our approach of multi- uses of the simulation model and its intuitive graphics capabilities is providing a concurrent engineering environment for rapid prototyping and development. Operational schematics of the MSRR-1 electrical, thermal control, vacuum access, and gas supply systems, and furnace inserts are represented graphically in the environment. Logic to represent first order engineering calculations is coded into the knowledge base to simulate the operational behavior of the MSRR-1 systems. An example of engineering data provided includes electrical currents, voltages, operational power, temperatures, thermal fluid flow rates. pressures, and component status indications. These type of data are calculated and displayed at appropriate instrumentation points, and the schematics are animated to reflect the simulated operational status of the MSRR-1. The software control functions are also simulated to represent appropriate operational behavior based on automated control and response to commands received by the crew or ground controllers. The first benefit of this simulation environment is being realized in the high fidelity engineering analysis results from the electrical power system G2 model. Secondly, the MSRR-1 simulation model will be embedded with a hardware mock-up of the MSRR-1 to provide crew training on MSRR-1 integrated payload operations. G2 gateway code will output the simulated instrumentation values, termed as telemetry, in a flight-like data stream so that the crew has realistic and accurate simulated MSRR-1 data on the flight displays which will be designed for crew use. The simulation will also respond appropriately to crew or ground initiated commands, which will be part of normal facility operations. A third use of the G2 model is being planned; the MSRR-1 simulation will be integrated with additional software code as part of the test configuration of the primary onboard computer, or Master Controller, for MSRR-1. We will take advantage of the G2 capability to simulate the flight like data stream to test flight software responses and behavior. A fourth use of the G2 model will be to train the Ground Support Personnel that will monitor the MSRR-1 systems and payloads while they are operating aboard the ISS. The intuitive, schematic based environment will provide an excellent foundation for personnel to understand the integrated configuration and operation of the MSRR-1, and the anticipated telemetry feedback based on operational modes of the equipment. Expert monitoring features will be enhanced to provide a smart monitoring environment for the operators. These features include: (1) Animated, intuitive schematic-based displays which reflect telemetry values, (1) Real-time plotting of simulated or incoming sensor values, (3) High/Low exception monitoring for analog data, (4) Expected state monitoring for discrete data, (5) Data trending, (6) Automated malfunction procedure execution to diagnose problems, (7) Look ahead capability to planned MSRR-1 activities in the onboard timeline. And finally, the logic to calculate telemetry values will be deactivated, and the same environment will interface to the incoming data for the real-time telemetry stream to schematically represent the onboard hardware configuration. G2 will be the foundation for the real-time monitoring and control environment. In summary, our MSRR-1 simulation model spans many elements of the life cycle development of this project: Engineering Analysis, Test and Checkout, Training of Crew and Ground Personnel, and Real-time monitoring and control. By utilizing the unique features afforded by an expert system development environment, we have been able to synergize a powerful tool capable of addressing our project needs at every phase of project development.

Rice, Amanda↗
NASA NTRS1985

Evaluation of existing and proposed computer architectures for future ground-based systems

Parallel processing architectures and techniques used in current supercomputers are described and projections are made of future advances. Presently, the von Neumann sequential processing pattern has been accelerated by having separate I/O processors, interleaved memories, wide memories, independent functional units and pipelining. Recent supercomputers have featured single-input, multiple data stream architectures, which have different processors for performing various operations (vector or pipeline processors). Multiple input, multiple data stream machines have also been developed. Data flow techniques, wherein program instructions are activated only when data are available, are expected to play a large role in future supercomputers, along with increased parallel processor arrays. The enhanced operational speeds are essential for adequately treating data from future spacecraft remote sensing instruments such as the Thematic Mapper.

Schulbach, C.↗
DOE OSTI2026

WHONDRS Surface Water Geochemistry and Organic Matter Characterization Data from Streams Distributed across Latin America

This dataset supports a broader study examining global transferability of stream biogeochemistry and was generated in collaboration with the MicroSudAqua (µSudAqua) network (https://microsudaqua.netlify.app/en/). The dataset provides surface water geochemistry (dissolved organic carbon, total dissolved nitrogen, cations) and organic matter characterization (FTICR-MS) from streams in Argentina, Brazil, Chile, and Colombia. Samples were collected across stream orders (1st to 6th order) within five basins. Related data were collected and will be published separately in collaboration with the µSudAqua network. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. In addition to this readme, this data package also includes a file-level metadata (FLMD) file that describes each file and a data dictionary (DD) that describes all column/row headers and variable definitions. This dataset is comprised of (1) a folder of field photos; (2) a folder of surface water sample data, (3) a folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data; (4) file-level metadata; (5) data dictionary; (6) field metadata; (7) readme; (8) international generic sample number (IGSN) mapping file; and (9) field protocol. The sample data subfolder contains (1) dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) total dissolved nitrogen data and averages; (3) anions and averages; (4) methods codes; (5) FTICR-MS methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains the processed data and three subfolders, one containing the .xml files, one containing the water CoreMS output files, and the other containing instructions and scripts for processing the files in CoreMS (https://github.com/EMSL-Computing/CoreMS). All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4.

Anions↗
DOE OSTI2026

Machine Learning Digital Twin for Lithium Ion Battery State of Health Predictions

A digital twin system has been established to model the long term degradation of the state of health of lithium ion batteries. Two data streams result from the computational model of the system and from the physical experiment measurements. A machine learning pipeline has been developed at the nexus of these data streams. Leveraging the unique data sources in multiple transfer learning approaches has lead to the development of multiple cell specific machine learning digital twins. Our discussion on this first of its kind technology will cover challenges in data ingestion, scalability, architecture and orchestration, and research findings.

25 - ENERGY STORAGE↗