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At least 1,261 records · Page 70

Enhancing accessibility and usability of Algorithm Theoretical Basis Documents through the Algorithm Publication Tool

Effective communication of scientific theories is crucial for transforming raw instrument data into valuable Earth observation products. The NASA Earth science data community disseminates this knowledge through Algorithm Theoretical Basis Documents (ATBDs). Historically, these documents lacked a standardized format, were designed for human readability rather than machine interpretation, and were challenging to locate due to the absence of a centralized repository. The Algorithm Publication Tool (APT) transforms how ATBD content is presented, simplifying the processes of creating, updating, and locating these documents. APT offers authors the option to use its user-friendly cloud-based interface or standardized templates for ATBD development. The primary advantage of the interface is its capability to manage the entire ATBD creation process within a single environment, ensuring comprehensive tracking of all activities and facilitating user tasks. Conversely, the use of standardized ATBD templates allows users to create documents using familiar tools like Google Docs, Microsoft Word, or Overleaf for LaTeX. APT also provides a centralized repository, enabling easy search and discovery of published ATBDs. This presentation showcases APT's functionalities, illustrates its contributions to advancing open science, and highlights potential benefits for broader community adoption.

Bradley Baker↗

Resin transfer molding of textile preforms for aircraft structural applications

The NASA LaRC is conducting and supporting research to develop cost-effective fabrication methods that are applicable to primary composite aircraft structures. One of the most promising fabrication methods that has evolved is resin transfer molding (RTM) of dry textile material forms. RTM has been used for many years for secondary structures, but has received increased emphasis because it is an excellent method for applying resin to damage-tolerant textile preforms at low cost. Textile preforms based on processes such as weaving, braiding, knitting, stitching, and combinations of these have been shown to offer significant improvements in damage tolerance compared to laminated tape composites. The use of low-cost resins combined with textile preforms could provide a major breakthrough in achieving cost-effective composite aircraft structures. RTM uses resin in its lowest cost form, and storage and spoilage costs are minimal. Near net shape textile preforms are expected to be cost-effective because automated machines can be used to produce the preforms, post-cure operations such as machining and fastening are minimized, and material scrap rate may be reduced in comparison with traditional prepreg molding. The purpose of this paper is to discuss experimental and analytical techniques that are under development at NASA Langley to aid the engineer in developing RTM processes for airframe structural elements. Included are experimental techniques to characterize preform and resin behavior and analytical methods that were developed to predict resin flow and cure kinetics.

Hasko, Gregory H.↗

Using Docker Containers to Extend Reproducibility Architecture for the NASA Earth Exchange (NEX)

NASA Earth Exchange (NEX) is a data, supercomputing and knowledge collaboratory that houses NASA satellite, climate and ancillary data where a focused community can come together to address large-scale challenges in Earth sciences. As NEX has been growing into a petabyte-size platform for analysis, experiments and data production, it has been increasingly important to enable users to easily retrace their steps, identify what datasets were produced by which process chains, and give them ability to readily reproduce their results. This can be a tedious and difficult task even for a small project, but is almost impossible on large processing pipelines. We have developed an initial reproducibility and knowledge capture solution for the NEX, however, if users want to move the code to another system, whether it is their home institution cluster, laptop or the cloud, they have to find, build and install all the required dependencies that would run their code. This can be a very tedious and tricky process and is a big impediment to moving code to data and reproducibility outside the original system. The NEX team has tried to assist users who wanted to move their code into OpenNEX on Amazon cloud by creating custom virtual machines with all the software and dependencies installed, but this, while solving some of the issues, creates a new bottleneck that requires the NEX team to be involved with any new request, updates to virtual machines and general maintenance support. In this presentation, we will describe a solution that integrates NEX and Docker to bridge the gap in code-to-data migration. The core of the solution is saemi-automatic conversion of science codes, tools and services that are already tracked and described in the NEX provenance system, to Docker - an open-source Linux container software. Docker is available on most computer platforms, easy to install and capable of seamlessly creating and/or executing any application packaged in the appropriate format. We believe this is an important step towards seamless process deployment in heterogeneous environments that will enhance community access to NASA data and tools in a scalable way, promote software reuse, and improve reproducibility of scientific results.

earth exchange↗

Computing with Beowulf

Parallel computers built out of mass-market parts are cost-effectively performing data processing and simulation tasks. The Supercomputing (now known as "SC") series of conferences celebrated its 10th anniversary last November. While vendors have come and gone, the dominant paradigm for tackling big problems still is a shared-resource, commercial supercomputer. Growing numbers of users needing a cheaper or dedicated-access alternative are building their own supercomputers out of mass-market parts. Such machines are generally called Beowulf-class systems after the 11th century epic. This modern-day Beowulf story began in 1994 at NASA's Goddard Space Flight Center. A laboratory for the Earth and space sciences, computing managers there threw down a gauntlet to develop a $50,000 gigaFLOPS workstation for processing satellite data sets. Soon, Thomas Sterling and Don Becker were working on the Beowulf concept at the University Space Research Association (USRA)-run Center of Excellence in Space Data and Information Sciences (CESDIS). Beowulf clusters mix three primary ingredients: commodity personal computers or workstations, low-cost Ethernet networks, and the open-source Linux operating system. One of the larger Beowulfs is Goddard's Highly-parallel Integrated Virtual Environment, or HIVE for short.

Cohen, Jarrett↗

Film Processing Module for Automated Fiber Placement

This viewgraph presentation describes fiber placement technology which was originally developed by Marshall Space Flight Center (MSFC) for the fabrication of fiber composite propellant tanks. The presentation includes an image of the MSFC Fiber Placement Machine, which is a prototype test bed, and images of some of the machine's parts. Some possible applications for the machines are listed.

Hulcher, A. Bruce↗

Towards an Aviation Large Language Model by Fine-tuning and Evaluating Transformers

In the aviation domain, there are many applications for machine learning and artificial intelligence tools that utilize natural language. For example, there is a desire to know the commonalities in written safety reports such as voluntary post incidents reports or aerial wildfire operations reports to better understand the risks present. Another use-case is the possibility of extracting airspace procedures and constraints currently written in documents such as Letters of Agreement. These applications can benefit from the use of state-of-the-art natural language processing techniques when adapted to the language/phraseology specific to the aviation domain. This paper evaluates the viability of adaptation of NLP tools to the aviation domain by fine-tuning transformer based models using aviation data sets. In 2018, a novel language model based on neural units (also called transformers) was created and became known as “Bidirectional Encoder Representations from Transformers” or BERT. This architecture combined with large amounts of English training data and innovative semi-supervised training tasks set the standard for what would later emerge as Large Language Models. The performance of these models was further improved by hyperparameter tuning and refinement of the semi-supervised training task and resulted in “Robustly Optimized BERT Pre-training Approach through hyperparameter tuning” or RoBERTa models. These pre-trained Large Language Models proved to be useful for a wide variety of natural language processing tasks such as text classification and question answering through a process called fine-tuning. The transformer architecture with pre-trained weights served as the basis with the last few layers replaced with layers fine-tuned to perform a new task e.g., a layer that provides a label for the entire input text. This process of fine-tuning can also be used to adapt the models to new domains; e.g., BioBERT started with the pre-trained BERT model and was completed by additional fine-tuning and training on biomedical documents. Transformer-based architectures can also be used to create rich representations of text called embeddings which can serve as the input to other machine learning models. This allows simpler algorithms such as logistic regression to use context-rich representations of the text while still remaining quick to train and evaluate. In the world of aviation, there is a growing demand for natural language processing and understanding but the domain presents unique challenges. Due to the technical content (and specialized language) of most aviation documents, fine-tuning pre-trained Large Language Models to specific tasks has not met the benchmark on natural language processing tasks set by simpler models trained from scratch on the data. To address this deficiency, this paper evaluates the improvements from fine-tuning a Large Language Model on a large set of aviation documents using the original semi-supervised training tasks before performing specific natural language tasks. In fine-tuning, a domain-specific dataset is used on the original training task but with the pre-trained Large Language Model instead of starting from a random initialization. This approach allows the model to be adapted to the specific domain language without discarding the information gained from training on general English data. This paper utilized two major dataset types to train and assess the RoBERTa fine-tuning performance. The first are 7,057 Letters of Agreement which are Federal Aviation Administration (FAA) documents that formalize airspace operations across the national airspace system. They contain many examples of ‘aviation English’ using domain specific terminology and phrasing which serves as a representative basis to perform the semi-supervised fine-tuning. The second type is the 494 document classification labels to be used for evaluation. This down-stream evaluation aims to show the performance of the fine-tuned model, better understand how much data is needed for an effective fine-tuning, and how fine-tuning can be adapted for different applications in-the domain. After semi-supervised training, evaluation begins by encoding the documents for classification using the fine-tuned RoBERTa model. Then a logistic regression classifier is trained to label the document type and compared against our ground truth labels. This currently leads to a 82.8% accuracy on 10-fold cross validation showing improvement over baseline RoBERTa which achieved 81.0%. We plan to measure the improvements on additional tasks and it is expected that these improvements will lead to more robust models that can tackle the natural language processing challenges present in aviation datasets.

ATM↗

Using Coordinated, Multi-Agent Platforms for Dynamic Ocean Worlds Science

Planetary science missions have the opportunity to enhance science return through deployment of autonomous capabilities designed to dynamically respond to new information. Future outer solar system missions to ocean worlds in particular would benefit from this technology - intelligent science payloads (ISP) - because it would allow for a coordinated, near real-time response to ephemeral ‘events’ such as plumes, tectonism, surface implantation, volatile releases, thermal and magnetic anomalies, or radiation, as well as increasing the cadence and coverage of data collection. Prioritization and decision-making frameworks from ISP could be deployed at various scales - from analysis onboard a spacecraft with multiple instruments – to coordinated analyses among separate spacecraft in an e.g., distributed systems mission (DSM) composed of multiple SmallSats. Goddard’s Intelligent Science Payload team is developing an agile autonomous architecture for an icy ocean worlds DSM concept. Our goals are to coordinate data collection and onboard data analysis, and to make autonomous decisions for new data collection and analysis based on science priorities between multiple spacecraft with variable instrumentation and orbits. We use a range of data analysis tools to coordinate the DSM response, spanning from observations of data over a specified threshold to more computationally intensive machine learning algorithms (ML). ML algorithms here currently focus on determining the composition of an ocean world using mass spectrometry, and specifically methods for understanding ‘novelties’ and potential biosignatures. These algorithms could be used to quickly process and analyze onboard data that would be significantly delayed in downlink due to long communication delays for outer solar system missions in order to make dynamic science observations. Our ocean worlds case study ISP architecture is intended as an ‘agile’ and modular framework that could be used as a whole or as particular modules based on mission needs.

Distributed Systems↗

Economic analysis of materials processing in space: Introduction

Space processing concepts investigated included an unmanned space factory, and a permanently launched factory. Product lines chosen for analysis were: (1) turbine blades, (2) tungsten targets for X-ray machines, (3) 1 sub G subclass separation by electrophoresis, and (4) high-price exotic crystals. The turbine blade, and 1 sub G products are considered promising candidates.

Source record↗

Numerical aerodynamic simulation facility preliminary study, volume 2 and appendices

Data to support results obtained in technology assessment studies are presented. Objectives, starting points, and future study tasks are outlined. Key design issues discussed in appendices include: data allocation, transposition network design, fault tolerance and trustworthiness, logic design, processing element of existing components, number of processors, the host system, alternate data base memory designs, number representation, fast div 521 instruction, architectures, and lockstep array versus synchronizable array machine comparison.

Source record↗

Documentation for the machine-readable version of the general catalogue of trigonometric stellar parallaxes and supplement

The machine-readable version of the General Catalog of Trigonometric Stellar parallaxes as distributed by the Astronomical Data Center is described. It is intended to enable users to read and process the data without problems and guesswork. The source reference should be consulted for details concerning the compilation of the main catalogue and supplement, the probable errors, and the weighting system used to combine determinations from different observatories.

Warren, W. H., Jr.↗

A new measuring machine in Paris

A new photographic measuring machine is under construction at the Paris Observatory. The amount of transmitted light is measured by a linear array of 1024 photodiodes. Carriage control, data acquisition and on line processing are performed by microprocessors, a S.E.L. 32/27 computer, and an AP 120-B Array Processor. It is expected that a Schmidt telescope plate of size 360 mm square will be scanned in one hour with pixel size of ten microns.

Guibert, J.↗

Organic materials for ceramic molding processes

Ceramic molding processes are examined. Binders, wetting agents, lubricants, plasticizers, surface active agents, dispersants, etc., for pressing, rubber pressing, sip casting, injection casting, taping, extrusion, etc., are described, together with forming machines.

Saito, K.↗

Vacuum plasma coatings for turbine blades

Turbine blades, vacuum plasma spray coated with NiCrAlY, CoCrAlY or NiCrAlY/Cr2O3, were evaluated and rated superior to standard space shuttle main engine (SSME) coated blades. Ratings were based primarily on 25 thermal cycles in the MSFC Burner Rig Tester, cycling between 1700 F (gaseous H2) and -423 F (liquid H2). These tests showed no spalling on blades with improved vacuum plasma coatings, while standard blades spalled. Thermal barrier coatings of ZrO2, while superior to standard coatings, lacked the overall performance desired. Fatigue and tensile specimens, machined from MAR-M-246(Hf) test bars identical to the blades were vacuum plasma spray coated, diffusion bond treated, and tested to qualify the vacuum plasma spray process for flight hardware testing and application. While NiCrAlY/Cr2O3 offers significant improvement over standard coatings in durability and thermal protection, studies continue with an objective to develop coatings offering even greater improvements.

Holmes, R. R.↗

Comparison of the MPP with other supercomputers for LANDSAT data processing

The massively parallel processor is compared to the CRAY X-MP and the CYBER-205 for LANDSAT data processing. The maximum likelihood classification algorithm is the basis for comparison since this algorithm is simple to implement and vectorizes very well. The algorithm was implemented on all three machines and tested by classifying the same full scene of LANDSAT multispectral scan data. Timings are compared as well as features of the machines and available software.

Ozga, Martin↗

Intelligent laser soldering inspection and process control

Component assembly on printed circuitry keeps making giant strides toward denser packaging and smaller dimensions. From a single layer to multilayer, from through holes to surface mounted components and tape applied bonds, unrelenting progress results in new, difficult problems in assembling, soldering, inspecting and controlling the manufacturing process of the new electronics. Among the major problems are the variables introduced by human operators. The small dimensions and the tight assembly tolerances are now successfully met by machines which are faster and more precise than the human hand. The same is true for soldering. But visual inspection of the solder joints is now so severely limited by the ever shrinking area accessible to the human eye that the inspector's diagnosis cannot be trusted any longer. Solutions to correcting these problems are discussed.

Vanzetti, Riccardo↗

Space Station data management system architecture

Within the Space Station program, the Data Management System (DMS) functions in a dual role. First, it provides the hardware resources and software services which support the data processing, data communications, and data storage functions of the onboard subsystems and payloads. Second, it functions as an integrating entity which provides a common operating environment and human-machine interface for the operation and control of the orbiting Space Station systems and payloads by both the crew and the ground operators. This paper discusses the evolution and derivation of the requirements and issues which have had significant effect on the design of the Space Station DMS, describes the DMS components and services which support system and payload operations, and presents the current architectural view of the system as it exists in October 1986; one-and-a-half years into the Space Station Phase B Definition and Preliminary Design Study.

Mallary, William E.↗

Real-time model-based vision system for object acquisition and tracking

A machine vision system is described which is designed to acquire and track polyhedral objects moving and rotating in space by means of two or more cameras, programmable image-processing hardware, and a general-purpose computer for high-level functions. The image-processing hardware is capable of performing a large variety of operations on images and on image-like arrays of data. Acquisition utilizes image locations and velocities of the features extracted by the image-processing hardware to determine the three-dimensional position, orientation, velocity, and angular velocity of the object. Tracking correlates edges detected in the current image with edge locations predicted from an internal model of the object and its motion, continually updating velocity information to predict where edges should appear in future frames. With some 10 frames processed per second, real-time tracking is possible.

Wilcox, Brian↗

Structural mechanics of 3-D braided preforms for composites. IV - The 4-step tubular braiding

This paper presents the fundamentals of the 4-step 3D tubular braiding process and the structure of the preforms produced. Based on an idealized structural model, geometric relations between the structural parameters of the preform are analytically established. The effects of machine arrangement and operating conditions are discussed. Yarn retraction, yarn surface angle, outside diameter, and yarn volume fraction of the preform in terms of the pitch length, the inner diameter, and the machine arrangement are theoretically predicted and experimentally verified.

Hammad, M.↗