Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Data processing and standardization”

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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS2001

The Paperless Solution

REI Systems, Inc. developed a software solution that uses the Internet to eliminate the paperwork typically required to document and manage complex business processes. The data management solution, called Electronic Handbooks (EHBs), is presently used for the entire SBIR program processes at NASA. The EHB-based system is ideal for programs and projects whose users are geographically distributed and are involved in complex management processes and procedures. EHBs provide flexible access control and increased communications while maintaining security for systems of all sizes. Through Internet Protocol- based access, user authentication and user-based access restrictions, role-based access control, and encryption/decryption, EHBs provide the level of security required for confidential data transfer. EHBs contain electronic forms and menus, which can be used in real time to execute the described processes. EHBs use standard word processors that generate ASCII HTML code to set up electronic forms that are viewed within a web browser. EHBs require no end-user software distribution, significantly reducing operating costs. Each interactive handbook simulates a hard-copy version containing chapters with descriptions of participants' roles in the online process.

Source record↗
NASA NTRS2015

Update on CMH-17 Volume 5: Ceramic Matrix Composites

CMC components are projected to enter service in commercial aircraft in 2016. A wide range of issues must be addressed prior to certification of this hardware. The Composite Materials Handbook-17, Volume 5 on ceramic matrix composites is being revised to support FAA certification of CMCs for hot structure and other elevated temperature applications. The handbook supports the development and use of CMCs through publishing and maintaining proven, reliable engineering information and standards that have been thoroughly reviewed. Volume 5 will contain detailed sections describing CMC materials processing, design analysis guidelines, testing procedures, and data analysis and acceptance. A review of the status of and plans for two of these areas, which are being addressed by the M and P Working Group and the Testing Working Group, will be presented along with a timeline for the preparation of CMH-17, Volume 5.

design↗
NASA NTRSDate not supplied

A Brief Introduction to AI/ML Applications of Air Traffic Management Data at NASA Ames

This presentation will give a brief overview of several AI/ML This presentation will give a brief overview of several AI/ML projects that NASA Ames interns are exploring in partnership with NASA Aeronautic Research Institute (NARI) and the FAA. NASA is interested in Natural Language Processing (NLP) of various legacy text and speech data within air traffic management e.g., Notices To Airmen (NOTAMs), Letters of Agreement (LoAs), Standard Operating Procedures (SOPs), and Air Traffic Control Center audio briefings. Since our focus is on applying state of the art AI/ML tools to legacy air traffic management data, we first showcase the different data sources of interest followed by a brief introduction to the techniques and language models used. We present some exciting preliminary results on each topic including both unsupervised learning techniques (e.g., clustering) and other modern language models (e.g., BERT) that help extract useful information from these data sources that are interpretable by both man and machine.

Air Traffic Management↗
NASA NTRS2023

Establishing Standardized Test Methods for Evaluating Space Suit Gloves

The Artemis space suit glove environmental protection garment (EPG) will be the first line of protection used to protect the crewmember’s hands from the environments encountered during extravehicular activity (EVA). As the Artemis missions will include more extreme environments, it is necessary to define tests to evaluate if gloves can meet new, challenging requirements. The NASA Engineering and Safety Center (NESC)has funded an effort with the goal to help vendors to produce a space suit glove that is sufficiently durable to meet the needs of the Artemis missions. Three problems were identified in meeting that goal. First, there are no standardized tests defined to evaluate the durability of space suit gloves for the extreme lunar environments. Second, there is insufficient data on glove performance in a lunar environment from which to compare new designs. And third, current ISS glove TMG fabrics are unlikely to be sufficient to meet Lunar requirements. Four tasks were established to answer different aspects of these three problems. Task 1 focused on the characterization of potential glove fabrics using ASTM standardized test methods when possible. When one did not exist, new standardized test procedures were devised. Task 2 focused on developing a procedure for characterizing the thermal performance of a glove assembly. Task 3 focused on devising a standard procedure for characterizing the dust/abrasion resistance of a space suit glove. Task 4 focused on devising a standard procedure for characterizing the cut resistance of a space suit glove while at cryogenic temperatures. The new procedures created in Tasks 2, 3 and 4 were then validated by testing the Phase VI glove to collect baseline data. This paper will summarize the approach used to establish standardized test methods for each task and will expound on the ASTM process to publish the new standards.

spacesuit↗
NASA NTRS2010

The Landsat Data Continuity Mission Operational Land Imager (OLI) Radiometric Calibration

The Operational Land Imager (OLI) on the Landsat Data Continuity Mission (LDCM) has a comprehensive radiometric characterization and calibration program beginning with the instrument design, and extending through integration and test, on-orbit operations and science data processing. Key instrument design features for radiometric calibration include dual solar diffusers and multi-lamped on-board calibrators. The radiometric calibration transfer procedure from NIST standards has multiple checks on the radiometric scale throughout the process and uses a heliostat as part of the transfer to orbit of the radiometric calibration. On-orbit lunar imaging will be used to track the instruments stability and side slither maneuvers will be used in addition to the solar diffuser to flat field across the thousands of detectors per band. A Calibration Validation Team is continuously involved in the process from design to operations. This team uses an Image Assessment System (IAS), part of the ground system to characterize and calibrate the on-orbit data.

Markham, Brian L.↗
NASA NTRS2011

The Modeling and Simulation Catalog for Discovery, Knowledge and Reuse

The DoD M&S Steering Committee has noted that the current DoD and Service's modeling and simulation resource repository (MSRR) services are not up-to-date limiting their value to the using communities. However, M&S leaders and managers also determined that the Department needs a functional M&S registry card catalog to facilitate M&S tool and data visibility to support M&S activities across the DoD. The M&S Catalog will discover and access M&S metadata maintained at nodes distributed across DoD networks in a centrally managed, decentralized process that employs metadata collection and management. The intent is to link information stores, precluding redundant location updating. The M&S Catalog uses a standard metadata schemas based on the DoD's Net-Centric Data Strategy Community of Interest metadata specification. The Air Force, Navy and OSD (CAPE) have provided initial information to participating DoD nodes, but plans on the horizon are being made to bring in hundreds of source providers.

Stone, George F. III↗
NASA NTRS1996

Calibration improvements to electronically scanned pressure systems and preliminary statistical assessment

Orifice-to-orifice inconsistencies in data acquired with an electronically-scanned pressure system at the beginning of a wind tunnel experiment forced modifications to the standard, instrument calibration procedures. These modifications included a large increase in the number of calibration points which would allow a critical examination of the calibration curve-fit process, and a subsequent post-test reduction of the pressure data. Evaluation of these data has resulted in an improved functional representation of the pressure-voltage signature for electronically-scanned pressures sensors, which can reduce the errors due to calibration curve fit to under 0.10 percent of reading compared to the manufacturer specified 0.10 percent of full scale. Application of the improved calibration function allows a more rational selection of the calibration set-point pressures. These pressures should be adjusted to achieve a voltage output which matches the physical shape of the pressure-voltage signature of the sensor. This process is conducted in lieu of the more traditional approach where a calibration pressure is specified and the resulting sensor voltage is recorded. The fifteen calibrations acquired over the two-week duration of the wind tunnel test were further used to perform a preliminary, statistical assessment of the variation in the calibration process. The results allowed the estimation of the bias uncertainty for a single instrument calibration; and, they form the precursor for more extensive and more controlled studies in the laboratory.

Everhart, Joel L.↗
NASA NTRS1993

Radar backscattering from snow facies of the Greenland ice sheet: Results from the AIRSAR 1991 campaign

In June 1991, the NASA/JPL airborne SAR (AIRSAR) acquired C- (lambda = 5.6cm), L- (lambda = 24cm), and P- (lambda = 68m) band polarimetric SAR data over the Greenland ice sheet. These data are processed using version 3.55 of the AIRSAR processor which provides radiometrically and polarimetrically calibrated images. The internal calibration of the AIRSAR data is cross-checked using the radar response from corner reflectors deployed prior to flight in one of the scenes. In addition, a quantitative assessment of the noise power level at various frequencies and polarizations is made in all the scenes. Synoptic SAR data corresponding to a swath width of about 12 by 50 km in length (compared to the standard 12 x 12 km size of high-resolution scenes) are also processed and calibrated to study transitions in radar backscatter as a function of snow facies at selected frequencies and polarizations. The snow facies on the Greenland ice sheet are traditionally categorized based on differences in melting regime during the summer months. The interior of Greenland corresponds to the dry snow zone where terrain elevation is the highest and no snow melt occurs. The lowest elevation boundary of the dry snow zone is known traditionally as the dry snow line. Beneath it is the percolation zone where melting occurs in the summer and water percolates through the snow freezing at depth to form massive ice lenses and ice pipes. At the downslope margin of this zone is the wet snow line. Below it, the wet snow zone corresponds to the lowest elevations where snow remains at the end of the summer. Ablation produces enough meltwater to create areas of snow saturated with water, together with ponds and lakes. The lowest altitude zone of ablation sees enough summer melt to remove all traces of seasonal snow accumulation, such that the surface comprises bare glacier ice.

Rignot, Eric↗
DOE OSTI2025

Toward Drilling the Perfect Geothermal Well: An International Research Coordination Network for Geothermal Drilling Optimization Supported by Deep Machine Learning and Cloud Based Data Aggregation

The EDGE project, supported by the U.S. Department of Energy Geothermal Technologies Office under award DE-EE0008793, established a data-driven framework for improving the efficiency, cost-effectiveness, and reliability of geothermal well drilling. The project focused on developing scalable data infrastructure, advanced machine learning and probabilistic models, and integrated analytics tools to support continuous drilling optimization. A central objective was to reduce geothermal drilling costs by up to seventy percent while minimizing the risk of well failure through predictive diagnostics and adaptive planning. Over the project period, a comprehensive data repository was designed and deployed, incorporating records from over one hundred geothermal wells across varied geological settings. This repository supported both structured and unstructured data and adhered to FAIR data principles, enabling provenance tracking, quality control, and standardized metadata. The project introduced automated ingestion pipelines and a cloud-hosted platform that facilitated access to raw, processed, and derived datasets. This infrastructure served as the foundation for model development and analysis. Machine learning workflows were developed to predict key drilling metrics including rate of penetration, non-productive time, and total drilling costs. Self-organizing maps and dimensionality reduction methods were used to uncover operational patterns and outliers, while supervised learning algorithms such as random forests and deep neural networks were applied to forecast performance outcomes. The models were validated on heterogeneous datasets from both U.S. and Icelandic fields, demonstrating variable but significant predictive accuracy. The results indicated that finer temporal resolution, inclusion of lithological data, and consistency in operational annotations could substantially improve model performance. The project also implemented process mining techniques to reconstruct state-transition models from drilling event logs. These models enabled the identification of deviations from optimal workflows and provided insights into recurring failure modes. Analysis of non-productive time highlighted the impact of equipment failures, geological challenges, and human factors, offering opportunities for targeted mitigation strategies. The EDGE Dashboard was developed as a web-based expert system integrating data visualization, model outputs, and user-driven queries. It provided an accessible interface for operators to explore historical data, evaluate predicted outcomes, and compare drilling scenarios. Initial feedback from project partners suggested that the dashboard could serve as a foundation for more advanced advisory and optimization tools. Overall, the EDGE project demonstrated the feasibility and value of applying modern data science techniques to geothermal drilling. It delivered a set of interoperable tools and models that can support more efficient, lower-risk well development. The findings point toward a viable path for transitioning from advisory analytics to semi-autonomous drilling systems, contingent on continued collaboration, expanded datasets, and field validation. The project results have immediate relevance for drilling operations, data management practices, and future geothermal R&D efforts aimed at achieving reliable, cost-competitive geothermal energy at scale.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Using GANs with adaptive training data to search for new molecules

The process of drug discovery involves a search over the space of all possible chemical compounds. Generative Adversarial Networks (GANs) provide a valuable tool towards exploring chemical space and optimizing known compounds for a desired functionality. Standard approaches to training GANs, however, can result in mode collapse, in which the generator primarily produces samples closely related to a small subset of the training data. In contrast, the search for novel compounds necessitates exploration beyond the original data. In this work, we present an approach to training GANs that promotes incremental exploration and limits the impacts of mode collapse using concepts from Genetic Algorithms. In our approach, valid samples from the generator are used to replace samples from the training data. We consider both random and guided selection along with recombination during replacement. By tracking the number of novel compounds produced during training, we show that updates to the training data drastically outperform the traditional approach, increasing potential applications for GANs in drug discovery.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

Towards in-situ certification of additively manufactured parts: the vital roles of physics-based and data-driven models

Certifying additively manufactured (AM) parts in-situ at the completion of a build is an enticing prospect, as it can help reduce the high costs associated with post-build testing and evaluation. However, achieving this goal presents significant challenges that may keep it aspirational for the foreseeable future. Nonetheless, incremental progress can pave the way forward. A critical aspect of in-situ certification involves continuous quality checking due to the random nature of the AM process and the difficulties in detecting defects or anomalies once layers are built over. While real-time in-situ monitoring strategies assisted by machine learning (ML) play a pivotal role in auditing part quality, they must ideally be supported by real-time (or near real-time) adaptive process control enabled by ML-assisted decision-making. By analyzing in-situ monitoring data in real-time (or near real- time) to dynamically adjust manufacturing parameters, such intervention can ensure AM parts are built to meet stringent certification standards. This can be achieved virtually by using high-fidelity performance models for the physical testing and evaluation tasks. In this short editorial, we discuss the key contributions made by data-driven and physics-based models in providing intelligence to the monitoring and process control tasks underpinning in-situ certification and in the simulation of the build’s performance under test and service conditions. While our focus lies in metal AM, the concepts discussed here are also relevant to other AM processes.

: In-situ monitoring↗
NASA NTRS1975

The effects of correlation on goodness of fit

Autocorrelated normal random variates were generated via computer and the effects of various levels of correlation on goodness of fit problems were studied. The results are useful in determining the distribution or estimating the parameters of populations that correlate observations such as wind speeds and temperature. The model used to generate the autocorrelated data is an autoregressive process of order 1. The Kolmogorov-Smirnov and chi-square statistics are used in the analysis. It was observed in the simulation that high positive correlations tend to shift the sample mean away from the population mean and negative correlations tend to shift the sample mean towards the population mean. In many cases, it was observed that positive and negative correlations tend to decrease the standard deviation. However, since this did not occur in all cases, no definite conclusion can be made regarding the standard deviation. Since the autoregressive process is a linear transformation, it is not surprising that normality was preserved. However, a possible extension of this problem could be to generate non-normal data and observe how the distribution is affected by correlation. Another extension might utilize another model such as autoregressive of order k or a moving average process of order k.

Kitchens, L. J.↗
DOE OSTI2023

A genomic data archive from the Network for Pancreatic Organ donors with Diabetes

The Network for Pancreatic Organ donors with Diabetes (nPOD) is the largest biorepository of human pancreata and associated immune organs from donors with type 1 diabetes (T1D), maturity-onset diabetes of the young (MODY), cystic fibrosis-related diabetes (CFRD), type 2 diabetes (T2D), gestational diabetes, islet autoantibody positivity (AAb+), and without diabetes. nPOD recovers, processes, analyzes, and distributes high-quality biospecimens, collected using optimized standard operating procedures, and associated de-identified data/metadata to researchers around the world. Herein describes the release of high-parameter genotyping data from this collection. 372 donors were genotyped using a custom precision medicine single nucleotide polymorphism (SNP) microarray. Data were technically validated using published algorithms to evaluate donor relatedness, ancestry, imputed HLA, and T1D genetic risk score. Additionally, 207 donors were assessed for rare known and novel coding region variants via whole exome sequencing (WES). These data are publicly-available to enable genotype-specific sample requests and the study of novel genotype:phenotype associations, aiding in the mission of nPOD to enhance understanding of diabetes pathogenesis to promote the development of novel therapies.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2020

Detector Channel Combining Results from a High Photon Efficiency Optical Communications Link Test Bed

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is developing a low cost, scalable, photon-counting receiver prototype for space-to-ground optical communications links. The receiver is being tested in a test bed that emulates photon-starved space-to-ground optical communication links. The receiver uses an array of single-pixel fiber-coupled superconducting nanowire single-photon detectors. The receiver is designed to receive the high photon efficiency serially concatenated pulse position modulation (SCPPM) waveform specified in the Consultative Committee for Space Data Systems (CCSDS) Optical Communications Coding and Synchronization Blue Book Standard. The optical receiver consists of an array of single-pixel superconducting nanowire detectors, analog phase shifters for channel alignment, digitizers for each detector channel, and digital processing of the received signal. An overview of the test bed and arrayed receiver system is given. Simulation and system characterization results are presented. The data rate increase of using a four-channel arrayed detector system over using one single pixel nanowire detector is characterized. Results indicate that a single-pixel detector is capable of receiving data at a rate of 40 Mbps and a four-channel arrayed detector system is capable of receiving data at a rate of 130 Mbps.

Downey, Jennifer N.↗
NASA NTRS2020

Detector Channel Combining Results from a High Photon Efficiency Optical Communications Link Test Bed

The National Aeronautics and Space Administration (NASA) Glenn Research Center (GRC) is developing a low cost, scalable, photon counting receiver prototype for space-to-ground optical communications links. The receiver is being tested in a test bed that emulates photon-starved space-to-ground optical communication links. The receiver uses an array of single-pixel fiber-coupled superconducting nanowire single-photon detectors. The receiver is designed to receive the high photon efficiency serially concatenated pulse position modulation (SCPPM) waveform specified in the Consultative Committee for Space Data Systems (CCSDS) Optical Communications Coding and Synchronization Blue Book Standard. The optical receiver consists of an array of single-pixel superconducting nanowire detectors, analog phase shifters for channel alignment, digitizers for each detector channel, and digital processing of the received signal. An overview of the test bed and arrayed receiver system is given. Simulation and system characterization results are presented. The data rate increase of using a four-channel arrayed detector system over using one single pixel nanowire detector is characterized. Results indicate that a single-pixel detector is capable of receiving data at a rate of 40 Mbps and a four-channel arrayed detector system is capable of receiving data at a rate of 130 Mbps.

Downey, Jennifer N.↗
NASA NTRS1993

Goddard Conference on Mass Storage Systems and Technologies, Volume 1

Copies of nearly all of the technical papers and viewgraphs presented at the Goddard Conference on Mass Storage Systems and Technologies held in Sep. 1992 are included. The conference served as an informational exchange forum for topics primarily relating to the ingestion and management of massive amounts of data and the attendant problems (data ingestion rates now approach the order of terabytes per day). Discussion topics include the IEEE Mass Storage System Reference Model, data archiving standards, high-performance storage devices, magnetic and magneto-optic storage systems, magnetic and optical recording technologies, high-performance helical scan recording systems, and low end helical scan tape drives. Additional topics addressed the evolution of the identifiable unit for processing purposes as data ingestion rates increase dramatically, and the present state of the art in mass storage technology.

Kobler, Ben↗
DOE OSTI2022

Techno-economic analysis of the use of atomic layer deposited transition metal oxides in silicon heterojunction solar cells

The industry for producing silicon solar cells and modules has grown remarkably over the past decades, with more than a 100-fold reduction in price over the past 45?years. The main solar cell fabrication technology has shifted over that time and is currently dominated by the passivated emitter and rear cell (PERC). Other technologies are expected to increase in market share, including tunnel-oxide passivated contact (TOPCon) and heterojunction technology (HJT). In this paper, we examine the cost potential for using atomic layer deposition (ALD) to form transition metal oxide (TMO) layers (MoO x , TiO x and aluminium-doped zinc oxide [AZO]) to use as lower cost alternatives of the p-doped, n-doped and indium tin oxide (ITO) layers, respectively, the layers normally used in HJT solar cells. Using a bottom-up cost and uncertainty model with equipment cost data and process experience in the lab, we find that the production cost of these variations will likely be lower per wafer than standard HJT, with the main cost drivers being the cost of the ALD precursors at high-volume production. We then considered what efficiency is required for these sequences to be cost effective in $/W and discuss whether these targets are technically feasible. This work motivates further work in developing these ALD TMO processes to increase their efficiency towards their theoretical limits to take advantage of the processing cost advantage.

14 SOLAR ENERGY↗
DOE OSTI2023

Characterizing the performance of node-aware strategies for irregular point-to-point communication on heterogeneous architectures

Supercomputer architectures are trending toward higher computational throughput due to the inclusion of heterogeneous compute nodes. These multi-GPU nodes increase on-node computational efficiency, while also increasing the amount of data to be communicated and the number of potential data flow paths. In this work, we characterize the performance of irregular point-to-point communication with MPI on heterogeneous compute environments through performance modeling, demonstrating the limitations of standard communication strategies for both device-aware and staging-through-host communication techniques. Presented models suggest staging communicated data through host processes then using node-aware communication strategies for high inter-node message counts. Notably, the models also predict that node-aware communication utilizing all available CPU cores to communicate inter-node data leads to the most performant strategy when communicating with a high number of nodes. Furthermore, model validation is provided via a case study of irregular point-to-point communication patterns in distributed sparse matrix–vector products. Importantly, we include a discussion on the implications model predictions have on communication strategy design for emerging supercomputer architectures.

97 MATHEMATICS AND COMPUTING↗