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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 469 records · Page 26

All sources NASA NTRS DOE OSTI

NASA NTRS1994

Operations automation

This is truly the era of 'faster-better-cheaper' at the National Aeronautics and Space Administration/Jet Propulsion Laboratory (NASA/JPL). To continue JPL's primary mission of building and operating interplanetary spacecraft, all possible avenues are being explored in the search for better value for each dollar spent. A significant cost factor in any mission is the amount of manpower required to receive, decode, decommutate, and distribute spacecraft engineering and experiment data. The replacement of the many mission-unique data systems with the single Advanced Multimission Operations System (AMMOS) has already allowed for some manpower reduction. Now, we find that further economies are made possible by drastically reducing the number of human interventions required to perform the setup, data saving, station handover, processed data loading, and tear down activities that are associated with each spacecraft tracking pass. We have recently adapted three public domain tools to the AMMOS system which allow common elements to be scheduled and initialized without the normal human intervention. This is accomplished with a stored weekly event schedule. The manual entries and specialized scripts which had to be provided just prior to and during a pass are now triggered by the schedule to perform the functions unique to the upcoming pass. This combination of public domain software and the AMMOS system has been run in parallel with the flight operation in an online testing phase for six months. With this methodology, a savings of 11 man-years per year is projected with no increase in data loss or project risk. There are even greater savings to be gained as we learn other uses for this configuration.

Boreham, Charles Thomas↗

NASA NTRSDate not supplied

Automated Management of Small Unmanned Aircraft System Communications and Navigation Contingency

The number of small Unmanned Aircraft System (sUAS) operating in the low-altitude of the National Airspace System (NAS) has been rapidly increasing in the past few years and this number is expected to grow in the future. However, aside from a few special cases, all sUAS must fly within visual line-of-sight (VLOS) of their operators and this limitation is blocking highly anticipated beyond visual line-of-sight (BVLOS) sUAS applications such as package delivery from practice. To enable routine low-altitude BVLOS operations, there needs to be a traffic management ecosystem that complements the FAA’s Air Traffic Management (ATM) system, which does not provide air traffic services under 400 feet above ground level (AGL). NASA has been pioneering research and development of this ecosystem under UAS Traffic Management (UTM) project since 2015 in a series of Technical Capability Levels (TCL) activities that are increasingly complex. In TCL1, completed in 2015, visual line-of-sight operations such as agriculture, firefighting, and infrastructure monitoring were addressed with a focus on geofencing and operations scheduling. Technologies and requirements needed for BVLOS operations in sparsely populated areas were examined in TCL2 in 2016, and those for operations over moderately populated areas in TCL3 in 2017 and 2018. TCL4 is building on the earlier TCLs and focuses on technologies and requirements for operations in higher-density urban areas for tasks such as newsgathering and package delivery and for managing large-scale contingencies. To coordinate and facilitate the incremental implementation of the UTM ecosystem in the NAS, a Research Transition Team (RTT) has been formed between the FAA, NASA, and industry. The RTT is divided into four subgroups, concept and use case development, data exchange and information architecture, sense and avoid, and communications and navigation (C&N). This paper focuses on C&N subgroup activities, in particular about the development of automated sUAS communications and navigation contingency management. The goal of this development is to prepare sUAS to display predictable behavior while handling C&N off-nominal events. It is expected that the adoption of the presented automated contingency management by the sUAS community will accommodate and inform rulemaking towards governing low-altitude BVLOS operations.

Unmanned Aviation System (UAS) Traffic Management↗

NASA NTRS1982

Development of the structural technology of a large deployable antenna

The current NASA-sponsored Antenna Technology Development Program of the offset wrap-rib antenna concept is based on a ground test program of 'proof of concept' hardware whose potential on-orbit performance is based on analytical estimates. The ground demonstration hardware represents a partial 55-meter diameter reflector and feed support structure. Testing will include automated deployment, reflector surface quality evaluation and validation of analytical performance models. Test results and hardware fabrication costs will be used to refine the models that will be the basis for the preliminary design of a 100-meter diameter wrap-rib antenna system. Additionally, the design, processes, tooling, fabrication techniques, fixturing and assembly approaches used for the 'proof of concept' hardware are directly applicable to building flight systems up to 100 meters in diameter.

Wada, B. K.↗

NASA NTRS2009

Programs Automate Complex Operations Monitoring

Kennedy Space Center, just off the east coast of Florida on Merritt Island, has been the starting place of every human space flight in NASA s history. It is where the first Americans left Earth during Project Mercury, the terrestrial departure point of the lunar-bound Apollo astronauts, as well as the last solid ground many astronauts step foot on before beginning their long stays aboard the International Space Station. It will also be the starting point for future NASA missions to the Moon and Mars and temporary host of the new Ares series rockets designed to take us there. Since the first days of the early NASA missions, in order to keep up with the demands of the intricate and critical Space Program, the launch complex - host to the large Vehicle Assembly Building, two launch pads, and myriad support facilities - has grown increasingly complex to accommodate the sophisticated technologies needed to manage today s space missions. To handle the complicated launch coordination safely, NASA found ways to automate mission-critical applications, resulting in streamlined decision-making. One of these methods, management software called the Control Monitor Unit (CMU), created in conjunction with McDonnell Douglas Space & Defense Systems, has since left NASA, and is finding its way into additional applications.

Source record↗

NASA NTRSDate not supplied

Automated Management of Small Unmanned Aircraft System (UAS) Communications and Navigation Contingency

Unmanned Aviation Systems (UAS) Traffic Management↗

NASA NTRS1996

A Mission Operations Architecture for the 21st Century

A new operations architecture for low cost missions is proposed, to build a framework to enable NASA to face its major challenges beond 2000. This architecture is composed of three elements: Service Based Architecture, Demand Access Automation, Distributed Science Hubs.

operations↗

NASA NTRS1992

Knowledge-intensive software design systems: Can too much knowledge be a burden?

While acknowledging the considerable benefits of domain-specific, knowledge-intensive approaches to automated software engineering, it is prudent to carefully examine the costs of such approaches, as well. In adding domain knowledge to a system, a developer makes a commitment to understanding, representing, maintaining, and communicating that knowledge. This substantial overhead is not generally associated with domain-independent approaches. In this paper, I examine the downside of incorporating additional knowledge, and illustrate with examples based on our experiences building the SIGMA system. I also offer some guidelines for developers building domain-specific systems.

Keller, Richard M.↗

NASA NTRSDate not supplied

AMO-EXPRESS-2.5: Crew Autonomy Onboard the International Space Station

NASA is committed to landing American astronauts, including the first woman and the next man, on the Moon by 2024. Currently, the crew cannot take on all functions performed by the ground today, so the future crews will need more automation to reduce the crew workload for future missions. Of significant importance for these missions is the balance between crew autonomy and vehicle automation. The Advanced Exploration Systems (AES) Autonomous Systems and Operations (ASO) Project has been investigating the ability to evaluate crew self-scheduling and activity monitoring for future space missions. The ASO project designed the Autonomous Mission and Operations- EXpedite the PRocessing of Experiments to Space Station Rack-2.5 (AMO-EXPRESS-2.5) payload to evaluate crew self-scheduling and activity monitoring. The AMO-EXPRESS-2.5 builds on the previous AMO-EXPRESS and AMO-EXPRESS-2.0 demonstrations on ISS. The AMO-EXPRESS-2.5 demonstration goals are to prove crew self-scheduling by planning through diagnosing systems expertise, failure detection, procedure recommendation and situational awareness. This paper will describe the development, test and execution results of the AMO-EXPRESS-2.5 demonstration, and will also outline the future planned development and operational efforts to enable autonomy for future deep space manned missions.

Brooke C. Allen↗

DOE OSTI2023

Automated methods for scalable, parallelized enzymatic biopolymer synthesis and modification using microfluidic devices

Methods for the automated template-free synthesis of user-defined sequence controlled biopolymers using microfluidic devices are described. The methods facilitate simultaneous synthesis of up to thousands of uniquely addressed biopolymers from the controlled movement and combination of regents as fluid droplets using microfluidic and EWOD-based systems. In some forms, biopolymers including nucleic acids, peptides, carbohydrates, and lipids are synthesized from step-wise assembly of building blocks based on a user-defined sequence of droplet movements. In some forms, the methods synthesize uniquely addressed nucleic acids of up to 1,000 nucleotides in length. Methods for adding, removing and changing barcodes on biopolymers are also provided. Biopolymers synthesized according to the methods, and libraries and databases thereof are also described. Modified biopolymers, including chemically modified nucleotides and biopolymers conjugated to other molecules are described.

Banal, James↗

NASA NTRS2014

Use of Semantic Technology to Create Curated Data Albums

One of the continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available online. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the data sets they need can obtain the specific files using these systems. However, in cases where researchers are interested in studying an event of research interest, they must manually assemble a variety of relevant data sets by searching the different distributed data systems. Consequently, there is a need to design and build specialized search and discover tools in Earth science that can filter through large volumes of distributed online data and information and only aggregate the relevant resources needed to support climatology and case studies. This paper presents a specialized search and discovery tool that automatically creates curated Data Albums. The tool was designed to enable key elements of the search process such as dynamic interaction and sense-making. The tool supports dynamic interaction via different modes of interactivity and visual presentation of information. The compilation of information and data into a Data Album is analogous to a shoebox within the sense-making framework. This tool automates most of the tedious information/data gathering tasks for researchers. Data curation by the tool is achieved via an ontology-based, relevancy ranking algorithm that filters out nonrelevant information and data. The curation enables better search results as compared to the simple keyword searches provided by existing data systems in Earth science.

Ramachandran, Rahul↗

NASA NTRS2014

Use of Semantic Technology to Create Curated Data Albums

One of the continuing challenges in any Earth science investigation is the discovery and access of useful science content from the increasingly large volumes of Earth science data and related information available online. Current Earth science data systems are designed with the assumption that researchers access data primarily by instrument or geophysical parameter. Those who know exactly the data sets they need can obtain the specific files using these systems. However, in cases where researchers are interested in studying an event of research interest, they must manually assemble a variety of relevant data sets by searching the different distributed data systems. Consequently, there is a need to design and build specialized search and discovery tools in Earth science that can filter through large volumes of distributed online data and information and only aggregate the relevant resources needed to support climatology and case studies. This paper presents a specialized search and discovery tool that automatically creates curated Data Albums. The tool was designed to enable key elements of the search process such as dynamic interaction and sense-making. The tool supports dynamic interaction via different modes of interactivity and visual presentation of information. The compilation of information and data into a Data Album is analogous to a shoebox within the sense-making framework. This tool automates most of the tedious information/data gathering tasks for researchers. Data curation by the tool is achieved via an ontology-based, relevancy ranking algorithm that filters out non-relevant information and data. The curation enables better search results as compared to the simple keyword searches provided by existing data systems in Earth science.

Ramachandran, Rahul↗

DOE OSTI2025

Framework and Tool for Artificial Intelligence & Machine Learning (AI/ML) Enabled Automated Non-Destructive Inspection of Composites Aerostructures Manufacturing

Vehicles and systems in the field of aerospace have two major requirements: a high demand for a large quantity and an expectation to perform for their lifetime with little to no failures. Thus, there is a need for a fast production rate of aerospace products with high quality. Improvements to production rate have many benefits, including a reduction in energy consumption per unit manufactured. This would be from factory energy usage, which is required to build and verify a product. Manufacturing process specifications require inspection of parts to determine if any flaws are present. Depending on factory planning and product quality, especially at higher rates, the evaluation process can pose a production rate bottleneck. This project was comprised of using artificial intelligence and machine learning (AI/ML) methods on inspection evaluations with the objective of reducing the required time to produce an aerospace structure or product and without reducing the final quality.

42 ENGINEERING↗

NASA NTRS1992

Automating the design of scientific computing software

SINAPSE is a domain-specific software design system that generates code from specifications of equations and algorithm methods. This paper describes the system's design techniques (planning in a space of knowledge-based refinement and optimization rules), user interaction style (user has option to control decision making), and representation of knowledge (rules and objects). It also summarizes how the system knowledge has evolved over time and suggests some issues in building software design systems to facilitate reuse.

Kant, Elaine↗

NASA NTRS1987

Space shuttle main engine anomaly data and inductive knowledge based systems: Automated corporate expertise

Progress is reported on the development of SCOTTY, an expert knowledge-based system to automate the analysis procedure following test firings of the Space Shuttle Main Engine (SSME). The integration of a large-scale relational data base system, a computer graphics interface for experts and end-user engineers, potential extension of the system to flight engines, application of the system for training of newly-hired engineers, technology transfer to other engines, and the essential qualities of good software engineering practices for building expert knowledge-based systems are among the topics discussed.

Modesitt, Kenneth L.↗

NASA NTRS1992

Knowledge-intensive software design systems: Can too much knowledge be a burden?

While acknowledging the considerable benefits of domain-specific, knowledge-intensive approaches to automated software engineering, it is prudent to carefully examine the costs of such approaches, as well. In adding domain knowledge to a system, a developer makes a commitment to understanding, representing, maintaining, and communicating that knowledge. This substantial overhead is not generally associated with domain-independent approaches. In this paper, I examine the downside of incorporating additional knowledge, and illustrate with examples based on our experience in building the SIGMA system. I also offer some guidelines for developers building domain-specific systems.

Keller, Richard M.↗

DOE OSTI2021

Building an AI-enhanced modeling framework to address multiscale predictability challenges

Focal Area(s): Build an AI-enhanced modeling framework that integrates the three focus areas in the solicitation. Science Challenge: The 4M-2N complexities (Multiscale, Multiphysics, Multibody, Multidimension, Non-linearity, and Non-Gaussianality) of atmospheric aerosol-cloud-precipitation-turbulence-radiation system poses physical and computational challenges to further advance predictive models; We plan to address the challenges by developing an AI-enhanced modeling framework that facilitates automated calibration and improvement of subgrid parameterizations, enhance data assimilation of measurements to improve initial and boundary conditions used to drive the physical model, and optimally blends data-driven and physics-based forecasting models.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1993

A strip chart recorder pattern recognition tool kit for Shuttle operations

During Space Shuttle operations, Mission Control personnel monitor numerous mission-critical systems such as electrical power; guidance, navigation, and control; and propulsion by means of paper strip chart recorders. For example, electrical power controllers monitor strip chart recorder pen traces to identify onboard electrical equipment activations and deactivations. Recent developments in pattern recognition technologies coupled with new capabilities that distribute real-time Shuttle telemetry data to engineering workstations make it possible to develop computer applications that perform some of the low-level monitoring now performed by controllers. The number of opportunities for such applications suggests a need to build a pattern recognition tool kit to reduce software development effort through software reuse. We are building pattern recognition applications while keeping such a tool kit in mind. We demonstrated the initial prototype application, which identifies electrical equipment activations, during three recent Shuttle flights. This prototype was developed to test the viability of the basic system architecture, to evaluate the performance of several pattern recognition techniques including those based on cross-correlation, neural networks, and statistical methods, to understand the interplay between an advanced automation application and human controllers to enhance utility, and to identify capabilities needed in a more general-purpose tool kit.

Hammen, David G.↗

DOE OSTI2021

BETO 2021 Peer Review - Inverse Bioproduct Design Through Machine Learning and Molecular Simulation

This work aims to identify performance advantaged bioproducts (PABPs) through property prediction, which will guide experimental synthesis. The impact of this work will be faster market adoption of bioproducts with greater performance relative to incumbent products. We have identified >106 bioproduct candidates, but only some will have superior performance to create a market pull. High-throughput property prediction, enabled by machine learning, and elucidation of structure-function relationships, enabled by molecular simulation, provide a hypothesis driven approach for down selection of candidate biomolecules to pursue experimentally. To enable machine learning and molecular simulation for bioproduct discovery, automated structure generation and embedding must capture relevant features for prediction, databases must cover domains applicable to biobased products, and best practices for simulation of polymer systems must be developed. To address these challenges, we have established bioproduct relevant datasets, developed high-throughput polymer structure generation, and built end-to-end neural networks that have predicted 8 properties for >1.4 x 106 biopolymers. A molecular simulation pipeline for building, running, and analyzing polymers and polymer additives is being used to predict performance and develop design principles of biobased products. In collaboration with the PABP synthesis project, these computational tools are guiding synthesis and informing design of PABPs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗