Search NASA⌕ Search

SEARCH · Search NASA

Results for “data rate”

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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Emulation Framework for Distributed Large-Scale Systems Integration

Recent trends in systems engineering include integration of very large-scale systems, which entails significant challenges when they are geographically dispersed. In these scenarios, intelligent integration of distributed large-scale systems requires significant coordination among hardware elements as well as all software components. The approach of integrated systems (both computing platform and experimental equipment) for end-to-end orchestration is called federation. Virtual frameworks can aid in the testing, assessment, and implementation of a functional system of interconnected resources. We present an emulation framework that replicates the software environments of multi-site federations of computing systems and instruments. Our emulation framework allows systems engineers to reduce developmentcost and avoid disruptions to production infrastructure. Our framework was effectively used to develop and test software modules for various tasks including container orchestration and instrument access. For performance assessment, however, the emulated framework is severely limited in providing accurate network and IO measurements at 10 Gbps and higher data rates. The data transfer performance profiles estimated using these emulated measurements are usually inaccurate for high bandwidth and high latency connections, since emulation does not accurately reflect the critical network transport dynamics.We utilize measurements from a physical testbed with hardware network emulators to obtain data transfer profiles that closely match the expected profiles for the emulated federations. We show the effectiveness of our approach by an illustrative example of integrated (federated) multi-site ultra large-scale systems that are connected via high speed wide area networks.

Imam, Neena↗
DOE OSTI2022

Decoding Golden Eagle Movement Behavior from High-Resolution, Variable-Rate Telemetry Data Through Bayesian Filtering

The recent advances in animal tracking technology have enabled the collection of a vast amount of in situ data regarding the movement of wildlife at high spatiotemporal resolution. These data are usually available at variable time resolutions and contains noise (error) originating from GPS fixes. Decoding movement characteristics, particularly of flying animals, from telemetry data while handling these factors is a challenging yet important task for conservation purposes. Typically, this task is broken into two subtasks: resampling, and model calibration. The resampling subtask converts the variable rate positional data into a constant time interval data, while the model calibration subtask uses the resampled data to tune time-invariant parameters of the proposed models. For telemetry data at high temporal resolutions (order of 1 second), it is very challenging to decouple noise from actual movements using interpolation-based resampling techniques. Any errors introduced during resampling can significantly alter the the calibration and prediction attributes of the movement model. We address this problem through a unified Bayesian state-space framework that can handle both the resampling and calibration tasks in a single step. In addition, we use the speed and heading of the bird from telemetry data to regularize the position information of the bird. We use a Kalman filtering approach to include these nonlinearly related motion parameters within the state space framework. We cross-validated to quantify how this inclusion affects the model performance in estimating true bird movements. The relationship between the true state of the bird and environmental and topographical covariates is then represented parametrically. These parameters are then tuned using stochastic sampling strategies like Markov Chain Monte Carlo (MCMC). We use the telemetry data collected from golden eagles in the western USA to demonstrate the applicability of this approach to build a predictive, probabilistic movement model. Our preliminary results show that this approach provides improved predictive performance in terms of capturing higher-order motion parameters such as angular and horizontal accelerations, which may have simpler and more direct relationships with environmental covariates than corresponding speeds. In this talk, we will demonstrate how this state-space approach benefits the prediction capabilities of a movement model in simulating golden eagle paths through a wind power plant in Wyoming given certain atmospheric conditions. The model outcomes are aimed at informing mitigation strategies that can minimize the potential for collisions of golden eagles with wind turbines.

Bayesian methods↗
DOE OSTI2020

Cryogenic C-band wavelength division multiplexing system using an AIM Photonics Foundry process design kit

Cryogenic environments make superconducting computing possible by reducing thermal noise, electrical resistance and heat dissipation. Heat generated by the electronics and thermal conductivity of electrical transmission lines to the outside world constitute two main sources of thermal load in such systems. As a result, higher data rates require additional transmission lines which come at an increasingly higher cooling power cost. Hybrid or monolithic integration of silicon photonics with the electronics can be the key to higher data rates and lower power costs in these systems. We present a 4-channel wavelength division multiplexing photonic integrated circuit (PIC) built from modulators in the AIM Photonics process development kit (PDK) that operate at 25 Gbps at room temperature and 10 Gbps at 40 K. We further demonstrate 2-channel operation for 20 Gbps aggregate data rate at 40 K using two different modulators/wavelengths, with the potential for higher aggregate bit rates by utilizing additional channels.

42 ENGINEERING↗
DOE OSTI2024

Anticipating Optical Availability in Hybrid RF/FSO Links Using RF Beacons and Deep Learning

Radiofrequency (RF) communications offer reliable but low data rates and energy-inefficient satellite links, while free-space optical (FSO) promises high bandwidth but struggles with disturbances imposed by atmospheric effects. A hybrid RF/FSO architecture aims to achieve optimal reliability along with high data rates for space communications. Accurate prediction of dynamic ground-to-satellite FSO link availability is critical for routing decisions in low-earth orbit constellations. In this paper, we propose a system leveraging ubiquitous RF links to proactively forecast FSO link degradation prior to signal drops below threshold levels. This enables pre-calculation of rerouting to maximally maintain high data rate FSO links throughout the duration of weather effects. We implement a supervised learning model to anticipate FSO attenuation based on the analysis of RF patterns. Through the simulation of a dense lower earth orbit (LEO) satellite constellation, we demonstrate the efficacy of our approach in a simulated satellite network, highlighting the balance between predictive accuracy and prediction duration. An emulated cloud attenuation model is proposed to provide insight into the temporal profiles of RF signals and their correlation to FSO channel dynamics. Our investigation sheds light on the trade-offs between prediction horizon and accuracy arising from RF beacon numbers and proximity.

FSO availability↗
DOE OSTI2023

High-throughput, dynamic, multi-dimensional: an expanding repertoire of plant respiration measurements

A recent burst of technological innovation and adaptation has greatly improved our ability to capture respiration rate data from plant sources. At the tissue level, several independent respiration measurement options are now available, each with distinct advantages and suitability, including high-throughput sampling capacity. These advancements facilitate the inclusion of respiration rate data into large-scale biological studies such as genetic screens, ecological surveys, crop breeding trials, and multi-omics molecular studies. As a result, our understanding of the correlations of respiration with other biological and biochemical measurements is rapidly increasing. Difficult questions persist concerning the interpretation and utilization of respiration data; concepts such as allocation of respiration to growth versus maintenance, the unnecessary or inefficient use of carbon and energy by respiration, and predictions of future respiration rates in response to environmental change are all insufficiently grounded in empirical data. However, we emphasize that new experimental designs involving novel combinations of respiration rate data with other measurements will flesh-out our current theories of respiration. Furthermore, dynamic recordings of respiration rate, which have long been used at the scale of mitochondria, are increasingly being used at larger scales of size and time to reflect processes of cellular signal transduction and physiological response to the environment. Herein, we also highlight how respiratory methods are being better adapted to different plant tissues including roots and seeds, which have been somewhat neglected historically.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Characterization of throughput on the AXI DMA bus for burst data transfer over Ethernet

cThe Xilinx AXI Direct Memory Access (AXI DMA) module is an efficient solution for medium-speed data transfer in Xilinx SoC FPGAs, supporting data rates greater than 1000 Gbps even in very suboptimal operating modes. It facilitates direct transfer of AXI stream data into processor memory without constant software intervention, which reduces overhead and ensures consistent data logging. By utilizing the FPGA's available memory, large circular buffers (1-5 GiB) are used to buffer data and accommodate network limitations, enabling high-rate data bursts. In this study, we measured the performance of AXI DMA under conditions simulating its lowest practical data transfer speeds. The Arbitrary Length Data Sender was used to transmit AXI stream packets at 32-bit width and 100 MHz frequency, a narrow width and slow speed. Results show that the AXI DMA can transfer up to 3192.76 Mbps with large packet sizes but experiences reduced performance for smaller packets, as low as 2.6 Mbps for 4-byte packets. For Ethernet-limited applications, packet sizes between 8,000 and 16,000 bytes provided optimal transfer speeds of 874 to 1600 Mbps. These findings suggest that the AXI DMA is not the limiting factor in systems where packet sizes exceed 8,000 bytes.

43 PARTICLE ACCELERATORS↗
DOE OSTI2021

A Synoptic VLBI Technique for Localizing Nonrepeating Fast Radio Bursts with CHIME/FRB

We demonstrate the blind interferometric detection and localization of two fast radio bursts (FRBs) with subarcminute precision on the 400 m baseline between the Canadian Hydrogen Intensity Mapping Experiment (CHIME) and the CHIME Pathfinder. In the same spirit as Very Long Baseline Interferometry (VLBI), the telescopes were synchronized to separate clocks, and the channelized voltage (herein referred to as baseband) data were saved to a disk with correlation performed offline. The simultaneous wide field of view and high sensitivity required for blind FRB searches implies a high data rate—6.5 terabits per second (Tb/s) for CHIME and 0.8 Tb s{sup −1} for the Pathfinder. Since such high data rates cannot be continuously saved, we buffer data from both telescopes locally in memory for ≈40 s, and write to the disk upon receipt of a low-latency trigger from the CHIME Fast Radio Burst Instrument (CHIME/FRB). The ≈200 deg{sup 2} field of view of the two telescopes allows us to use in-field calibrators to synchronize the two telescopes without needing either separate calibrator observations or an atomic timing standard. In addition to our FRB observations, we analyze bright single pulses from the pulsars B0329+54 and B0355+54 to characterize systematic localization errors. Our results demonstrate the successful implementation of key software, triggering, and calibration challenges for CHIME/FRB Outriggers: cylindrical VLBI outrigger telescopes which, along with the CHIME telescope, will localize thousands of single FRB events with sufficient precision to unambiguously associate a host galaxy with each burst.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Real-time data reduction at 100 Tbps: Challenge and opportunity for AI-based data reduction for next-generation large-scale nuclear physics collider experiment

The modern large-scale nuclear physics (NP) experiments in high-energy particle colliders utilize streaming-readout electronics to digitize detector response at O(100) Tbps bandwidth. Prominent examples at Brookhaven National Lab (BNL) include the sPHENIX experiment at Relativistic Heavy Ion Collider (RHIC), which is under construction, and the experiments proposed for the Electron-Ion Collider (EIC), planned for the 2030s . One of the main challenges for these streaming readout systems is to manage the data rate with sufficient data reduction in real time so the end-data fit persistent storage for offline analysis, which is typically at O(1000) times smaller and O(100) Gbps. Such data reduction traditionally is achieved via real-time high level triggers, which select and save a small subset of collisions of interest. Although triggering is applicable to high energy collider experiments such as those at the Large Hardron Collider at CERN, it is insufficient for these nuclear physics experiments which study diverse collision topologies. And traditional triggering approach is inefficient to preserve the max information harvested from the operation of colliders that costs O(100)M per year to DOE. Meanwhile, in recent years, ML-based high-throughput data reduction has emerged as a promising approach to efficiently preserve max information for a given space of persistent storage, e.g. via AI data compression, feature extraction, and noise filtering.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2025

WHONDRS River Corridor Sediment and Water Geochemistry and In Situ Sensor Data from 7 Perennial and 7 Intermittent Streams across San Antonio, Texas (v3)

This dataset supports a broader study examining the effects of intermittency on sediment respiration. The dataset provides sediment and surface water geochemistry and in situ sensor data from 7 perennial and 7 intermittent streams in San Antonio, Texas. Each stream/site was visited both in summer during base flow (July-September 2023) and winter during peak flow (January-February 2024). Related data were collected and will be published separately in collaboration with A. Veach. The data package was originally published in April 2025. It was updated in June 2025 (v2; modified and new files) and September 2025 (v3; modified files). See the change history section in the readme for more details. For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. This dataset is comprised of two folders of field photos and videos, one folder of raw Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS) data and one main data folder containing (1) file-level metadata; (2) data dictionary; (3) field metadata; (4) readme; (5) international generic sample number (IGSN) mapping file; (6) field protocol; (7) a subfolder with sample data; and (8) a subfolder with sensor data. The sample data subfolder contains (1) surface water and sediment dissolved organic carbon (DOC, measured as non-purgeable organic carbon, NPOC) data and averages; (2) surface water and sediment total nitrogen data and averages; (3) sediment grain size data; (4) sediment iron (II) data and averages; (5) wet sediment mass, dry sediment mass, water mass, and wet sediment volume in incubation and sediment ICR vials; (7) sediment incubation respiration rate data and averages; (8) normalized respiration rate data and averages; (9) methods codes; (10) sediment percent carbon and nitrogen; (11) sediment X-ray diffraction (XRD) data; (12) gravimetric moisture and averages; (13) a subfolder with sediment incubation respiration data, scripts, and plots; (14) surface water and sediment FTICR methods; and (15) a subfolder of 9.4 Tesla (9.4T) FTICR-MS data. This folder contains five subfolders, one containing the sediment .xml data files, one containing the water .xml files, one containing the sediment CoreMS output 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). The sensor data subfolder contains (1) a subfolder with miniDOT dissolved oxygen and temperature data and plots; (2) miniDOT dissolved oxygen and temperature summary data; and (3) miniDOT installation methods. All files are .csv, .pdf, .R, .xml, .d, .html, .Rmd, .py, .cal, .json, .jpg, .jpeg, .png, .mov, or .mp4. CORRECTION: The data processing methods for FTICR described in “v3_WHONDRS_AV1_Methods_Codes.csv” mistakenly indicate that users should process the data in Formultitude. The corrected description should read: “Both unprocessed and processed data are provided to allow users flexibility in data processing. Instructions and scripts for processing the data using CoreMS are included.” CORRECTION: Carbon and nitrogen content are reported as percentages. The current column headers "01395_C_percent_per_mg" and "01397_N_percent_per_mg" are incorrect. These should read "01395_C_percent" and "01397_N_percent" and will be corrected in the next version of this data package.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Selecting Appropriate Model Complexity: An Example of Tracer Inversion for Thermal Prediction in Enhanced Geothermal Systems

Abstract A major challenge in the inversion of subsurface parameters is the ill‐posedness issue caused by the inherent subsurface complexities and the generally spatially sparse data. Appropriate simplifications of inversion models are thus necessary to make the inversion process tractable and meanwhile preserve the predictive ability of the inversion results. In this study, we investigate the effect of model complexity on fracture aperture inversion and thermal performance prediction in a field‐scale EGS model. Principal component analysis was used to map the aperture field to a low‐dimensional latent space. The complexity of the inversion model was quantitatively represented by the percentage of total variance in the original aperture fields preserved by the latent space. Tracer, pressure and flow rate data were used to invert for fracture aperture through an ensemble‐based inversion method, and the inferred aperture field was used to predict thermal performance. With an over‐simplified aperture model, ensemble collapse occurred. The inverted aperture models failed to resolve necessary flow and transport features, leading to a biased thermal performance prediction. A complex aperture model involved excessive features and was prone to overinterpreting the inversion data. Both the tracer/pressure/flow rate data reproduction and thermal prediction showed significant uncertainties, making it difficult to properly estimate long‐term thermal performance. Fortunately, our results indicate that there exists an appropriate model complexity which can simultaneously match inversion data and predict thermal performance with an acceptable uncertainty. The quality of the fit of tracer data appears to be a useful indicator of such an appropriate model complexity.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Variational autoencoders for at-source data reduction and anomaly detection in high energy particle detectors

Detectors in next-generation high-energy physics experiments face several daunting requirements, such as high data rates, damaging radiation exposure, and stringent constraints on power, space, and latency. To address these challenges, machine learning in readout electronics can be leveraged for smart detector designs, enabling intelligent inference and data reduction at-source. Variational autoencoders (VAEs) offer a variety of benefits for front-end readout; an on-sensor encoder can perform efficient lossy data compression while simultaneously providing a latent space representation that can be used for anomaly detection. Results are presented from low-latency and resource-efficient VAEs for front-end data processing in a futuristic silicon pixel detector. Encoder-based data compression is found to preserve good performance of off-detector analysis while significantly reducing the off-detector data rate as compared to a similarly sized data filtering approach. Furthermore, the latent space information is found to be a useful discriminator in the context of real-time sensor defect monitoring. Together, these results highlight the multifaceted utility of autoencoder-based front-end readout schemes and motivate their consideration in future detector designs.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Experience with Rucio in the wider HEP community

Managing the data of scientific projects is an increasingly complicated challenge, which was historically met by developing experiment-specific solutions. However, the ever-growing data rates and requirements of even small experiments make this approach very difficult, if not prohibitive. In recent years, the scientific data management system Rucio has evolved into a successful open-source project that is now being used by many scientific communities and organisations. Rucio is incorporating the contributions and expertise of many scientific projects and is offering common features useful to a diverse re-search community. This article describes the recent experiences in operating Rucio, as well as contributions to the project, by ATLAS, Belle II, CMS, ES-CAPE, IGWN, LDMX, Folding@Home, and the UK's Science and Technology Facilities Council (STFC).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

June 2022 Permeability Measurements in P-Tunnel, Nevada National Security Site

This document describes gas permeability measurements made in June 2022 in P-Tunnel at the Nevada National Security Site (NNSS). Four boreholes (AC-1, GI-5, GI-6, and HF-1) were tested with a dual packer system. The pressure versus flow rate data that were collected are analyzed using a numerical simulation method that captures compressible gas flow in partially saturated porous media using a close approximation to the geometry of the test setup. The first part of this document begins with data collection and a description of the packer assembly followed by details on data acquisition, measurement instrumentation, and equipment followed by a description of pre-test system verification. Next, the implementation of testing in the field is described, including how specific locations were chosen for testing. The second part of this document describes the numerical simulations used to back-out permeability from the pressure versus flow rate data. First, the numerical model is described, including assumptions. Next the details of the mesh that represents the experiment are described. A method for generating type curves in pressure versus flow rate space is presented and finally the data are mapped to permeability. We conclude with a discussion of the results.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Free-space optical communication system and methods for efficient data delivery

Communication systems and methods for high-data-rate, high-efficiency, free-space communications are described. High-speed optical modems and automatic repeat request can be employed to transmit large data files without data errors between remote devices, such as an earth-orbiting satellite and ground station. Data rates over 100 Gb/s can be achieved.

Boroson, Don M.↗
DOE OSTI2024

Region of Interest Filter in DUNE DAQ

The Deep Underground Neutrino Experiment (DUNE) is the next generation neutrino experiment currently under construction. It consists of a broadband neutrino beam at Fermilab, a high precision near detector, and the largest liquid argon time projection chamber far detector ever designed at the Sanford Underground Research Facility (SURF). The Region of Interest (ROI) filter is designed for DUNE’s online Data Acquisition (DAQ) system to address data rate constraints and enable low energy physics in the <10 MeV range. The filter employs zero suppression on the detector signal, and by tuning the readout window and threshold the data rates can be reduced by >90%. Performance of the ROI is analyzed in LArsoft on MARLEY generated low energy MC events propagated through the detector simulation. Notably, the optimized ROI filter enables a lower trigger threshold for readout at ~5-10 MeV, allowing DUNE to explore low-energy physics, specifically focusing on solar boron 8 neutrinos which are relevant in this energy range. This advancement enhances DUNE's scientific capabilities, opening avenues for detailed analyses of previously inaccessible low-energy neutrino interactions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2022

Peak Prediction Using Multi Layer Perceptron (MLP) for Edge Computing ASICs Targeting Scientific Applications

High data rate detectors play an integral part in scientific research and their development is actively pursued at High Energy Physics (HEP) facilities around the world. Edge Machine Learning (ML) offers the ability to reduce data rates by integrating ML algorithms into Application Specific Integrated Circuits (ASICs) on the front end electronics. In this work, we explore a set of neural network architectures for predicting the peak amplitudes in the detector's sensor response. We have designed and synthesized several MLP based neural networks comparing their inference accuracy, power consumption, and area targeting for minimal latency. The neural networks are synthesized in a commercial 65nm process. The effect of quantizing the network's weights and biases on hardware performance and area is reported. We also conduct design space exploration to compare between design alternatives

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

As-Run Thermal Analysis for the AGC-4 Experiment Irradiated in the ATR

The Advanced Graphite Capsule (AGC) irradiation experiment will provide irradiation creep rate data for the new graphite proposed for the Next Generation Nuclear Plant (NGNP) program. The fourth experiment in the series (AGC-4) was designed to irradiate various types of graphite specimens at a temperature of 900 ºC and targeted displacements per atom (DPA) of 6. This experiment has been irradiated in the east flux trap of the Advanced Test Reactor (ATR) during the cycles of 157D, 158A, 162A, 162B, 164A, 164B, 166A, and 166B. Temperatures were monitored using twelve thermocouples (TC) located at various elevations in the reactor core, and variable helium-argon gas mixtures were used for gas gap temperature control of the specimens. The purpose of this Engineering Calculation and Analysis Report (ECAR) is to calculate the specimen temperature after the model is calibrated by the measured TC data with the as-run heating rates of the components, DPA of the graphite, and the gas mixture compositions during the experiment. As-run specimen mean temperature and the tolerance will be obtained.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2021

Melting rate correlation with batch properties and melter operating conditions during conversion of nuclear waste melter feeds to glasses

The rate of conversion of nuclear waste melter feed to glass is affected by the selection of melter feed materials and by melter design and operation. The melting rate correlation (MRC) is an equation that relates the glass production rate with two types of variables: (1) feed and melt properties: conversion heat, cold-cap bottom temperature, and glass melt viscosity; and (2) melter design and operation parameters: melter geometry, melter operating temperature, and gas bubbling rate. The MRC shows good agreement for an extended melting-rate data set of high-level waste (HLW) melter feeds and a data set generated for low-activity waste (LAW) melter feeds. Laboratory observation of heated melter feed samples is often used to assess the cold-cap bottom temperature of HLW melter feeds (moderately foaming feeds), but this technique appears inadequate for LAW melter feeds (vigorously foaming feeds). For LAW feeds, an adequate assessment of the cold-cap bottom temperature was achieved using evolved gas analysis, which allows identification of the collapse of primary foam for oxidized feeds. This assessment shows that the cold-cap bottom temperature for vigorously foaming LAW feeds is higher than that for moderately foaming HLW feeds. When the results of MRC are compared, LAW feeds are generally less sensitive to the bubbling rate and melt viscosity, and more sensitive to the cold-cap bottom temperature than HLW feeds. The MRC qualifies as a promising tool to support the selection of melter feed materials and melter operating conditions, which is determined from expensive independent scaled melter experiments, and sophisticated mathematical models.

Lee, Seung Min↗