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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 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

KAZRARSCL-CLOUDSAT Value Added Product Data Stream

The KAZRARSCL-CLOUDSAT Value-Added Product (VAP) is based on the KAZR-ARSCL VAP, which provides cloud boundaries and best-estimate time-height fields of radar moments. The KAZRARSCL-CLOUDSAT VAP applies a statistically-derived calibration offset to reflectivity fields in order to align them with observations from the spaceborne CloudSat Cloud Profiling Radar. For details on the offset values applied, please refer to "Kollias, P., Puigdomènech Treserras, B., and Protat, A.: Calibration of the 2007–2017 record of ARM Cloud Radar Observations using CloudSat, Atmos. Meas. Tech. Discuss., https://doi.org/10.5194/amt-2019-34, 2019."

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1975

Results of an aerodynamic investigation of a space shuttle orbiter/747 carrier vehicle configuration to establish a free-stream data base for ALT separation investigations, utilizing a 0.0125-scale model (48-0/AX1318I-1) in the ARC 14-foot wind tunnel (CA23A)

Force and moment data are presented which were obtained for each vehicle separately at a Mach number of 0.6, and for the mated orbiter/747 configuration at Mach numbers of 0.3, 0.5, 0.6, and 0.7. Orbiter angles of attack from 0 degrees to +12 degrees and 747/Carrier angles of attack from -3 degrees to +7 degrees were investigated at angles of sideslip of 0 degrees and -5 degrees. Model variables include orbiter elevon and rudder deflections, orbiter tail cone-on and off, various orbiter/747 attach structure configurations, 747 stabilizer and rudder deflections, and 747 CAM modification components-on and off. Photographs of test configurations are included.

Gillins, R. L.↗
DOE OSTI2024

ML Classifier Fusion for Three Data Streams with Quality Inversely Proportional to Time Resolution

We consider a monitoring scenario of phenomenon using three different streams of measurements whose quality is proportional to their constant inter-arrival times. Each measurement of a stream needs to be binary-classified to reflect the state of interest of the phenomenon. A set of classifiers is separately trained and fused for each stream at its time resolution using measurements collected under known states. We present a machine learning method to fuse the outputs of these fusers to provide a final classification at the finest time resolution. We show that this fused-fusers method provides decisions with likely superior classification probability compared to the best individual classifiers and fused-classifiers. We derive generalization equations that guarantee a superior classification probability of fused-fusers with a confidence probability specified by the classifiers’ generalization equations. We apply these results to study a practical problem of classifying Pu/Np target dissolution events at a radiochemical processing facility using gamma spectral measurements of effluent flows.

Rao, Nageswara↗
DOE OSTI2023

Toward Statistical Real-Time Power Fault Detection

We propose statistical fault detection methodology based on high-frequency data streams that are becoming available in modern power grids. Our approach can be treated as an online (sequential) change point monitoring methodology. However, due to the mostly unexplored and very nonstandard structure of high-frequency power grid streaming data, substantial new statistical development is required to make this methodology practically applicable. The paper includes development of scalar detectors based on multichannel data streams, determination of data-driven alarm thresholds and investigation of the performance and robustness of the new tools. Due to a reasonably large database of faults, we can calculate frequencies of false and correct fault signals, and recommend implementations that optimize these empirical success rates.

bolted faults↗
DOE OSTI2023

A Three-Tier Incremental Approach for Development of Smart Corridor Digital Twins

Development of an arterial smart corridor digital twin requires the integration of real time data streams, data storage, and simulation model execution. This process may be complex, time consuming, and susceptible to errors. To aid in smart corridor digital twin development this paper seeks to provide a framework, best practices, and development guidance. As such, a three-tier incremental approach to smart corridor digital twin development is presented. The paper highlights practical issues in digital twin construction along with key data challenges based on experiences from the development of digital twins for two large Smart Corridor deployments, one in Chattanooga, Tennessee, and the other in Atlanta, Georgia. The presented three-tier incremental approach includes: 1) development of a prepopulated offline simulation, 2) development of a pseudo digital twin that is driven by archived data, and 3) integration of real time data streams to create the online digital twin model. The three-tiered approach facilitates conducting multiple trials and scenarios with increasing complexity, allowing for incremental error processing and updating of the digital twin.

Saroj, Abhilasha↗
NASA NTRS1995

Simulation Results for PCM/PM/NRZ Receivers in Non-Ideal Channels

This paper studies, by computer simulations, the performance of deep space telemetry signals that employ PCM/PM/NRZ modulation technique under the separate and combined effects of an unbalanced data stream, data asymmetry, and band-limited channel. The study is based on measuring the Symbol Error Rate (SER) performance and comparing the results to the theoretical results presented in previous reports [1,2]. Only the effects of imperfect carrier tracking due to an imperfect data stream are considered.

PCM/PM/NRS Receivers↗
DOE OSTI2021

Evolutionary NAS in Light of Model Stability for Accurate Continual Learning

Continual learning, the capability to learn new knowledge from streaming data without forgetting the previous knowledge, is a critical requirement for dynamic learning systems, especially for emerging edge devices such as self-driving cars and drones. However, continual learning is still facing the catastrophic forgetting problem. Previous work illustrate that model performance on continual learning is not only related to the learning algorithms but also strongly dependent on the inherited model, i.e., the model where continual learning starts. The better stability of the inherited model, the less catastrophic forgetting and thus, the inherited model should be elaborately selected. Inspired by this finding, we develop an evolutionary neural architecture search (ENAS) algorithm that emphasizes the Stability of the inherited model, namely ENAS-S. ENAS-S aims to find optimal architectures for accurate continual learning on edge devices. On CIFAR-10 and CIFAR-100, we present that ENAS-S achieves competitive architectures with lower catastrophic forgetting and smaller model size when learning from a data stream, as compared with handcrafted DNNs.

Du, Xiaocong↗
DOE OSTI2026

Characterizing the GD-1 Stream with DESI DR2 Data: Thin Stream and Hot Cocoon

GD-1 is among the longest, coldest stellar streams in the Milky Way, making it an ideal target for probing dark matter substructure through dynamical heating. We present a catalog of 608 spectroscopically confirmed GD-1 members from the first three years of Dark Energy Spectroscopic Instrument (DESI) observations. This constitutes the largest homogeneous spectroscopic sample of GD-1, doubling the number of members previously available only through heterogeneous compilations combining multiple surveys with different systematics. Using these data, we derive updated stream tracks in sky position, proper motion, and radial velocity that extend over $100^\circ$ of the stream. We apply a Gaussian mixture model to decompose the stream into a dynamically cold thin component ($σ_V = 2.49\pm 0.28$ km s$^{-1}$, width $= 0.23\pm0.01^\circ$) and a kinematically hot cocoon ($σ_V = 6.13\pm0.75$ km s$^{-1}$, width $= 2.18\pm0.17^\circ$). The cocoon contains $\sim30\%$ of members and its velocity dispersion is consistent with $\sim11$ Gyr of heating by cold dark matter subhalos. We also detect a large proper motion dispersion ($41.36\pm4.98$ km s$^{-1}$) along the stream direction in the cocoon component. This feature indicates a significant line-of-sight distance spread in the cocoon, and its origin will be further explored in a forthcoming paper. These measurements demonstrate the power of DESI spectroscopy for characterizing the multi-component phase-space structure of stellar streams and constraining small-scale dark matter substructure.

Jarvis, Emma [Toronto U.] (ORCID:0009000656127336)↗
NASA NTRS1993

Data Systems Dynamic Simulator

The Data System Dynamic Simulator (DSDS) is a discrete event simulation tool. It was developed for NASA for the specific purpose of evaluating candidate architectures for data systems of the Space Station era. DSDS provides three methods for meeting this requirement. First, the user has access to a library of standard pre-programmed elements. These elements represent tailorable components of NASA data systems and can be connected in any logical manner. Secondly, DSDS supports the development of additional elements. This allows the more sophisticated DSDS user the option of extending the standard element set. Thirdly, DSDS supports the use of data streams simulation. Data streams is the name given to a technique that ignores packet boundaries, but is sensitive to rate changes. Because rate changes are rare compared to packet arrivals in a typical NASA data system, data stream simulations require a fraction of the CPU run time. Additionally, the data stream technique is considerably more accurate than another commonly-used optimization technique.

Rouff, Christopher↗
DOE OSTI2022

Electronic device and method for compressing video data

A computer-implemented method for compressing video data comprises receiving a sequence of video data values, each video data value being a digital value from a successive one of a plurality of pixels that form a video sensor, the sequence of video data values resulting from successive frames of video captured by the video sensor; extracting the video data values for each pixel in turn to create a plurality of pixel data streams, each pixel data stream including the video data value for each frame of captured video for the pixel; and applying data compression to each pixel data stream to create compressed data for each pixel data stream.

Tohlen, Michael Aaron↗
DOE OSTI2023

Electronic device and method for compressing video data

A computer-implemented method for compressing video data comprises receiving a sequence of video data values, each video data value being a digital value from a successive one of a plurality of pixels that form a video sensor, the sequence of video data values resulting from successive frames of video captured by the video sensor; extracting the video data values for each pixel in turn to create a plurality of pixel data streams, each pixel data stream including the video data value for each frame of captured video for the pixel; and applying data compression to each pixel data stream to create compressed data for each pixel data stream.

Tohlen, Michael Aaron↗
DOE OSTI2021

Transmitter with fully re-assignable segments for reconfigurable FFE taps

Methods and systems of performing feed forward equalization (FFE) on data streams are described. A circuitry may generate staggered data streams from data streams of an input signal. The staggered data streams may include data in staggered unit intervals. The circuitry may include a plurality of segments. A segment may define a specific unit interval to carve the staggered data streams into one unit interval pulses positioned at the specific unit interval. The specific unit interval to carve the staggered data streams may indicate an assignment of the segment as one of a FFE pre tap, a FFE main tap, and a FFE post tap. The plurality of segments may be assigned to different FFE taps based on different clock signal selection defining different unit intervals to perform the carving. The plurality of segments may output respective one unit interval pulses to reproduce the input signal.

Toprak-Deniz, Zeynep↗