SEARCH · Engineering Papers

Results for “data shift”

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.

SourceResearch connectionFrom yearThrough year

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

At least 235 records · Page 13

All sources NASA NTRS DOE OSTI

DOE OSTI2020

Geomancy: Automated Performance Enhancement through Data Layout Optimization

Large distributed storage systems such as high- performance computing (HPC) systems used by national or international laboratories require sufficient performance and scale for demanding scientific workloads and must handle shifting workloads with ease. Ideally, data is placed in locations to optimize performance, but the size and complexity of large storage systems inhibit rapid effective restructuring of data layouts to maintain performance as workloads shift. To address these issues, we have developed Geomancy, a tool that models the placement of data within a distributed storage system and reacts to drops in performance. Using a combination of machine learning techniques suitable for temporal modeling, Geomancy determines when and where a bottleneck may happen due to changing workloads and suggests changes in the layout that mitigate or prevent them. Our approach to optimizing throughput offers benefits for storage systems such as avoiding potential bottlenecks and increasing overall I/O throughput from 11% to 30%.

Bel, Oceane M.↗

NASA NTRS1972

Frequency shifts of ionospheric nfH resonances.

New observational data are analyzed to interpret mechanisms responsible for large positive frequency shifts of Alouette II plasma resonances (corresponding to the first and second electron cyclotron harmonics) relative to frequency values expected from model magnetic field calculations. It is shown that the frequency shifts can be consistently explained by plasma wave dispersion effects combined with sounder transmitter frequency deviation (positive offset of several kilohertz) and a negative offset (several tens of gammas) in the geomagnetic field relative to the model field. Plasma wave dispersion effects are observed on the electron cyclotron second harmonic resonance when it is in the vicinity of the resonance observed near the upper hybrid frequency. The observations suggest that an oblique echo model may be required for interpretation of the electron cyclotron second harmonic resonance.

Benson, R. F.↗

NASA NTRS1995

SSME Post Test Diagnostic System: Systems Section

An assessment of engine and component health is routinely made after each test firing or flight firing of a Space Shuttle Main Engine (SSME). Currently, this health assessment is done by teams of engineers who manually review sensor data, performance data, and engine and component operating histories. Based on review of information from these various sources, an evaluation is made as to the health of each component of the SSME and the preparedness of the engine for another test or flight. The objective of this project - the SSME Post Test Diagnostic System (PTDS) - is to develop a computer program which automates the analysis of test data from the SSME in order to detect and diagnose anomalies. This report primarily covers work on the Systems Section of the PTDS, which automates the analyses performed by the systems/performance group at the Propulsion Branch of NASA Marshall Space Flight Center (MSFC). This group is responsible for assessing the overall health and performance of the engine, and detecting and diagnosing anomalies which involve multiple components (other groups are responsible for analyzing the behavior of specific components). The PTDS utilizes several advanced software technologies to perform its analyses. Raw test data is analyzed using signal processing routines which detect features in the data, such as spikes, shifts, peaks, and drifts. Component analyses are performed by expert systems, which use 'rules-of-thumb' obtained from interviews with the MSFC data analysts to detect and diagnose anomalies. The systems analysis is performed using case-based reasoning. Results of all analyses are stored in a relational database and displayed via an X-window-based graphical user interface which provides ranked lists of anomalies and observations by engine component, along with supporting data plots for each.

Bickmore, Timothy↗

NASA NTRS2005

Data Format Classification for Autonomous Software Defined Radios

We present maximum-likelihood (ML) coherent and noncoherent classifiers for discriminating between NRZ and Manchester coded (biphase-L) data formats for binary phase-shift-keying (BPSK) modulation. Such classification of the data format is an essential element of so-called autonomous software defined radio (SDR) receivers (similar to so-called cognitive SDR receivers in the military application) where it is desired that the receiver perform each of its functions by extracting the appropriate knowledge from the received signal and, if possible, with as little information of the other signal parameters as possible. Small and large SNR approximations to the ML classifiers are also proposed that lead to simpler implementation with comparable performance in their respective SNR regions. Numerical performance results obtained by a combination of computer simulation and, wherever possible, theoretical analyses, are presented and comparisons are made among the various configurations based on the probability of misclassification as a performance criterion. Extensions to other modulations such as QPSK are readily accomplished using the same methods described in the paper.

classification↗

NASA NTRS2007

Mars-Approach Navigation Using In Situ Orbiters

A document discusses the continuing development of a navigation system that would enable a spacecraft to approach Mars on a trajectory precise enough to enable the spacecraft to land within 1 km of a specified location on the Martian surface. This degree of accuracy would represent an order-of-magnitude improvement over that now obtained in radiometric tracking by use of the Deep Space Network. The navigation system would be implemented largely in software running in digital processors in the Electra transceiver, the Mars Network s standard radio transceiver, that would be in both the approaching spacecraft and Mars Network orbiter. The Mars Network is an ad hoc constellation of existing and future Mars science orbiters and dedicated telecommunication orbiters that has been established as a communication and navigation infrastructure to support the exploration of Mars. The software would exploit the sensory and data-processing capabilities of the Electra transceivers to gather Doppler-shift and other radiometric tracking data and process those data into trajectories data that would be accurate to within 0.3 km at the point of entry into the Martian atmosphere (as needed to land within 1 km of a target surface location).

Duncan, Courtney↗

NASA NTRS1980

Determination of spacecraft attitude using synthetic aperture radar data

A method has been developed for precise sensor platform attitude determination which exploits the availability of synthetic aperture radar (SAR) sensors on future planned NASA earth orbiting spacecraft. Using the ephemeris along with data on planet shape and rotation, the relative motion between sensor and target area and therefore the Doppler frequency shift in the returned echo data is determined. Equations have been developed that relate the Doppler shift to the antenna attitude. The method is tested by comparing attitude predictions from SEASAT SAR digital echo data with available conventionally determined SEASAT attitude information.

Wu, C.↗

NASA NTRS2019

Past and Future Operations Concepts of NASA's Earth Science Data and Information System

NASA committed to support the collection and distribution of Earth science data to study global change in the 1990's. A series of Earth science remote sensing satellites, the Earth Observing System (EOS), was to be the centerpiece. The concept for the science data system, the EOS Data and Information System (EOSDIS), created new challenges in the data processing of multiple satellite instrument observations for climate research and in the distribution of global-coverage remote sensor products to a large and growing science research community. EOSDIS was conceived to facilitate easy access to EOS science data for a wide heterogeneous national and international community of users. EOSDIS was to provide a spectrum of services designed for research scientists working on NASA focus areas but open to the general public and international science community. EOSDIS would give researchers tools and assistance in searching, selecting and acquiring data, allowing them to focus on Earth science climate research rather than complex product generation. Goals were to promote exchange of data and research results and expedite development of new geophysical algorithms. The system architecture had to accommodate a diversity of data types, data acquisition and product generation operations, data access requirements and different centers of science discipline expertise. Steps were taken early to make EOSDIS flexible by distributing responsibility for basic services. Many of the system operations concept decisions made in the 90s continued to this day. Once implemented, concepts such as the EOSDIS data model played a critical role developing effective data services, now a hallmark of EOSDIS. In other cases, EOSDIS architecture has evolved to enable more efficient operations, taking advantage of new technology and thereby shifting more resources on data services and less on operating and maintaining infrastructure. In looking to the future, EOSDIS may be able to take advantage of commercial compute environments for infrastructure and further enable large scale climate research. In this presentation, we will discuss key EOSDIS operations concepts from the 1990's, how they were implemented and evolved in the architecture, and look at concepts and architectural challenges for EOSDIS operations utilizing commercial cloud services.

Moses, John F.↗

NASA NTRS2017

Relationship Between Carbon Dioxide Levels and Reported Congestion and Headaches on the International Space Station

Congestion is commonly reported during spaceflight, and most crewmembers have reported using medications for congestion during International Space Station (ISS) missions. Although congestion has been attributed to fluid shifts during spaceflight, fluid status reaches equilibrium during the first week after launch while congestion continues to be reported throughout long duration missions. Congestion complaints have anecdotally been reported in relation to ISS CO2 levels; this evaluation was undertaken to determine whether or not an association exists. METHODS: Reported headaches, congestion symptoms, and CO2 levels were obtained for ISS expeditions 2-31, and time-weighted means and single-point maxima were determined for 24-hour (24hr) and 7-day (7d) periods prior to each weekly private medical conference. Multiple imputation addressed missing data, and logistic regression modeled the relationship between probability of reported event of congestion or headache and CO2 levels, adjusted for possible confounding covariates. The first seven days of spaceflight were not included to control for fluid shifts. Data were evaluated to determine the concentration of CO2 required to maintain the risk of congestion below 1% to allow for direct comparison with a previously published evaluation of CO2 concentrations and headache. RESULTS: This study confirmed a previously identified significant association between CO2 and headache and also found a significant association between CO2 and congestion. For each 1-mm Hg increase in CO2, the odds of a crew member reporting congestion doubled. The average 7-day CO2 would need to be maintained below 1.5 mmHg to keep the risk of congestion below 1%. The predicted probability curves of ISS headache and congestion curves appear parallel when plotted against ppCO2 levels with congestion occurring at approximately 1mmHg lower than a headache would be reported. DISCUSSION: While the cause of congestion is multifactorial, this study showed congestion is associated with CO2 levels on ISS. Data from additional expeditions could be incorporated to further assess this finding. CO2 levels are also associated with reports of headaches on ISS. While it may be expected for astronauts with congestion to also complain of headaches, these two symptoms are commonly mutually exclusive. Furthermore, it is unknown if a temporal CO2 relationship exists between congestion and headache on ISS. CO2 levels were time-weighted for 24hr and 7d, and thus the time course of congestion leading to headache was not assessed; however, congestion could be an early CO2-related symptom when compared to headache. Future studies evaluating the association of CO2-related congestion leading to headache would be difficult due to the relatively stable daily CO2 levels on ISS currently, but a systematic study could be implemented on-orbit if desired.

Cole, Robert↗

DOE OSTI2025

The Importance of Being Adaptable: An Exploration of the Power and Limitations of Domain Adaptation for Simulation-Based Inference with Galaxy Clusters

The application of deep machine learning methods in astronomy has exploded in the last decade, with new models showing remarkably improved performance on benchmark tasks. Not nearly enough attention is given to understanding the models' robustness, especially when the test data are systematically different from the training data, or "out of domain." Domain shift poses a significant challenge for simulation-based inference, where models are trained on simulated data but applied to real observational data. In this paper, we explore domain shift and test domain adaptation methods for a specific scientific case: simulation-based inference for estimating galaxy cluster masses from X-ray profiles. We build datasets to mimic simulation-based inference: a training set from the Magneticum simulation, a scatter-augmented training set to capture uncertainties in scaling relations, and a test set derived from the IllustrisTNG simulation. We demonstrate that the Test Set is out of domain in subtle ways that would be difficult to detect without careful analysis. We apply three deep learning methods: a standard neural network (NN), a neural network trained on the scatter-augmented input catalogs, and a Deep Reconstruction-Regression Network (DRRN), a semi-supervised deep model engineered to address domain shift. Although the NN improves results by 17% in the Training Data, it performs 40% worse on the out-of-domain Test Set. Surprisingly, the Scatter-Augmented Neural Network (SANN) performs similarly. While the DRRN is successful in mapping the training and Test Data onto the same latent space, it consistently underperforms compared to a straightforward Yx scaling relation. These results serve as a warning that simulation-based inference must be handled with extreme care, as subtle differences between training simulations and observational data can lead to unforeseen biases creeping into the results.

Ntampaka, Michelle [Baltimore, Space Telescope Sci↗

DOE OSTI2024

Roadmap on data-centric materials science

Science is and always has been based on data, but the terms ‘data-centric’ and the ‘4th paradigm’ of materials research indicate a radical change in how information is retrieved, handled and research is performed. It signifies a transformative shift towards managing vast data collections, digital repositories, and innovative data analytics methods. The integration of artificial intelligence and its subset machine learning, has become pivotal in addressing all these challenges. This Roadmap on Data-Centric Materials Science explores fundamental concepts and methodologies, illustrating diverse applications in electronic-structure theory, soft matter theory, microstructure research, and experimental techniques like photoemission, atom probe tomography, and electron microscopy. While the roadmap delves into specific areas within the broad interdisciplinary field of materials science, the provided examples elucidate key concepts applicable to a wider range of topics. The discussed instances offer insights into addressing the multifaceted challenges encountered in contemporary materials research.

36 MATERIALS SCIENCE↗

DOE OSTI2020

An Adaptive Reference Scheme to Extend the Functional Range of Optical Backscatter Reflectometry in Extreme Environments

Optical frequency domain reflectometry (OFDR) measurements are performed by recording the interference pattern of light backscattered by density fluctuations or Bragg gratings along the length of an optical fiber. Changes in local temperature or strain in the fiber cause shifts in the backscattered light spectrum, which can be calibrated to the applied temperature or strain. Comparing the backscattered optical spectra from each reflection site with a reference (unstrained) spectrum allows for quantification of local spectral shifts. While mature OFDR-based technologies can provide high-precision spatially distributed measurements over kilometer lengths, the post-processing approaches used to recover spectral shifts from raw optical intensity data can limit the use of OFDR in harsh environments. This paper presents a novel approach to post-processing OFDR data which extends the usability of optical fibers exposed to harsh environments. This approach is the first to use the spectral shift quality, calculated for two OFDR measurements, to identify an appropriate reference scan from which the spectral shift can be determined. Here, three experimental data sets are used to test the algorithm: (1) an optical fiber heated to >950°C, (2) an aluminum-embedded optical fiber under strain from differential thermal expansion, and (3) an optical fiber exposed to a total neutron flux of 2×10 13 n/cm 2 /s over 40 hours in a nuclear test reactor. Results show that using a metric of quality to select an appropriate reference measurement extends the functional range of OFDR strain and temperature sensors. Furthermore, this algorithm can be applied to existing OFDR data.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

AI Data Quality Monitoring with Hydra

Hydra is an extensible framework for training and managing AI for near real time monitoring that aims to replace the tedious and repetitive data quality monitoring activities the shift crew and online monitoring coordinator typically perform. It continuously scans incoming data in the form of monitoring plots for signs of problems, flagging them for human review. A web app was developed such that experts can efficiently label images for training. Labels are stored in a database for use in training and model validation. Backed up by a comprehensive database, it utilizes an additional web based front-end for viewing the current monitoring status from anywhere in the world. The system has been in production use for the GlueX experiment at Jefferson Lab for more than 2 years with new features still under active development.

Britton, Thomas↗

DOE OSTI2023

Propagating Uncertainties in the SALT3 Model-training Process to Cosmological Constraints

Type Ia supernovae (SNe Ia) are standardizable candles that must be modeled empirically to yield cosmological constraints. To understand the robustness of this modeling to variations in the model-training procedure, we build an end-to-end pipeline to test the recently developed SALT3 model. We explore the consequences of removing pre-2000s low-z or poorly calibrated U-band data, adjusting the amount and fidelity of SN Ia spectra, and using a model-independent framework to simulate the training data. We find that the SALT3 model surfaces are improved by having additional spectra and U-band data, and can be shifted by ~5% if host-galaxy contamination is not sufficiently removed from SN spectra. We find that resulting measurements of w are consistent to within 2.5% for all of the training variants explored in this work, with the largest shifts coming from variants that add color-dependent calibration offsets or host-galaxy contamination to the training spectra and those that remove pre-2000s low-z data. These results demonstrate that the SALT3 model-training procedure is largely robust to reasonable variations in the training data, but that additional attention must be paid to the treatment of spectroscopic data in the training process. We also find that the training procedure is sensitive to the color distributions of the input data—the resulting w measurement can be biased by ~2% if the color distribution is not sufficiently wide. Future low-z data, particularly u-band observations and high signal-to-noise ratio SN Ia spectra, will help to significantly improve SN Ia modeling in the coming years.

79 ASTRONOMY AND ASTROPHYSICS↗

NASA NTRS1990

Bit-error-rate testing of fiber optic data links for MMIC-based phased array antennas

The measured bit-error-rate (BER) performance of a fiber optic data link to be used in satellite communications systems is presented and discussed. In the testing, the link was measured for its ability to carry high burst rate, serial-minimum shift keyed (SMSK) digital data similar to those used in actual space communications systems. The fiber optic data link, as part of a dual-segment injection-locked RF fiber optic link system, offers a means to distribute these signals to the many radiating elements of a phased array antenna. Test procedures, experimental arrangements, and test results are presented.

Shalkhauser, K. A.↗

NASA NTRS1990

Bit error rate testing of fiber optic data links for MMIC-based phased array antennas

Shalkhauser, K. A.↗

NASA NTRSDate not supplied

OCO-2 Satellite-imposed Constraints on Terrestrial Biospheric CO2 Flux over South Asia

The spatiotemporal variability of terrestrial biospheric carbon dioxide (CO2) flux over South Asia is poorly understood. The inverse model “top-down” CO2 flux estimates which rely on atmospheric CO2 observational data are impeded by sparse in situ measurements over this region. The Orbiting Carbon Observatory 2 (OCO-2) provides much needed global retrievals of column-average CO2 dry-air mole fraction (XCO2) with the finest spatial and temporal resolution and highest sensitivity to surface fluxes available to-date. This study conducted global inverse model simulations as part of the second OCO-2 Multi-model Intercomparison Project assimilating version 9 of the OCO-2 XCO2 retrievals in land nadir (LN) and land glint (LG) observing modes and global in situ (IS) measurements. The four-dimensional variational assimilation system with the GEOS-Chem global chemical transport model was used to estimate CO2 fluxes from 2015 to 2018. We then assessed the spatiotemporal variability of optimized CO2 Net ecosystem Exchange (NEE) fluxes aggregated over the South Asia region. The most robust result found by assimilating OCO-2 observations was the constraints imposed on the seasonal cycle of terrestrial biospheric fluxes over South Asia. The seasonality of South Asian NEE estimated by assimilating OCO-2 or global IS data showed a larger seasonal cycle compared to the current understanding of NEE in this region (represented by the prior NEE used in the model). The satellite-in situ joint inversion (IS + LN + LG) led to land flux seasonal amplitude (absolute magnitude of the difference between peak and trough of monthly mean values over a year) of 4.0 PgC yr-1, compared to the prior model (1.5 PgC yr-1). Moreover, OCO-2 data imposed a phase shift in the seasonal cycle, resulting in a large CO2 source in April and a large uptake in September. Most of the features in the seasonal cycle imposed by OCO-2 data are in agreement with previous “top-down” studies assimilating regional aircraft observations. Nevertheless, we recommend a closer examination of the novel features highlighted by the OCO-2 column data over South Asia in future studies by conducting regional inverse modelling with denser in situ and vertically-resolved regional observations along with satellite data.

OCO-2↗

NASA NTRSDate not supplied

Mars Science Laboratory Mastcam Multispectral Investigation of Drill Targets From the Beginning of the Clay Sulfate Transition to Marker Band Valley

In March, 2021 the Mars Science Laboratory Curiosity rover officially started exploring the Clay Sulfate Transition (CST). This area of Mt. Sharp has been interpreted to have hydrated Mg-sulfate spectral signatures in CRISM orbital data, and it no longer has the strong phyllosilicate spectral signature as the previous Glen Torridon region. Recently, the Curiosity rover has also encountered the marker band that was also identified in orbital data [1,3]. This shift from phyllosilicates to hydrated Mg-sulfates suggests a major change in the environmental conditions during which these rocks were deposited. This abstract focuses on changes seen in the Mastcam multispectral data between the CST drill targets.

S R Jacob↗

NASA NTRS1976

A generalization of MSK-type signaling based upon input data symbol pulse shaping

Minimum-shift-keying (MSK), which is a special case of continuous phase frequency-shift-keying (CPFSK) with frequency deviation ratio equal to 0.5, is known to be spectrally equivalent to a form of offset quadrature phase-shift-keying (OQPSK) in which the symbol pulse shape is a half-cycle sinusoid rather than the usual rectangular form. Appropriate shaping of the input data symbols allows one to generate an entire class of constant envelope, MSK-type signals, whose spectral properties are in some applications more desirable than those of MSK or OQPSK. The present study derives and presents a set of conditions on the input pulse shaping which in turn describes the class of envelope shapes allowable. The autocorrelation function and power spectral density of this class of signals are then derived, and specific examples are given to illustrate the desirable spectral properties. Such properties are important considerations in system design where interchannel and intersymbol interference degradations must be kept to a minimum.

Simon, M. K.↗