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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 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
NASA NTRS1979

Development of a beam builder for automatic fabrication of large composite space structures

The composite material beam builder which will produce triangular beams from pre-consolidated graphite/glass/thermoplastic composite material through automated mechanical processes is presented, side member storage, feed and positioning, ultrasonic welding, and beam cutoff are formed. Each process lends itself to modular subsystem development. Initial development is concentrated on the key processes for roll forming and ultrasonic welding composite thermoplastic materials. The construction and test of an experimental roll forming machine and ultrasonic welding process control techniques are described.

Bodle, J. G.↗
NASA NTRS1989

Automated assembly in space

The installation of robots and their use of assembly in space will create an exciting and promising future for the U.S. Space Program. The concept of assembly in space is very complicated and error prone and it is not possible unless the various parts and modules are suitably designed for automation. Certain guidelines are developed for part designing and for an easy precision assembly. Major design problems associated with automated assembly are considered and solutions to resolve these problems are evaluated in the guidelines format. Methods for gripping and methods for part feeding are developed with regard to the absence of gravity in space. The guidelines for part orientation, adjustments, compliances and various assembly construction are discussed. Design modifications of various fasteners and fastening methods are also investigated.

Srivastava, Sandanand↗
NASA NTRS2006

Dynamic Aperture-based Solar Loop Segmentation

A new method to automatically segment arc-like loop structures from intensity images of the Sun's corona is introduced. The method constructively segments credible loop structures by exploiting the Gaussian-like shape of loop cross-sectional intensity profiles. The experimental results show that the method reasonably segments most of the well-defined loops in coronal images. The method is only the second published automated solar loop segmentation method. Its advantage over the other published method is that it operates independently of supplemental time specific data.

Lee, Jon Kwan↗
DOE OSTI2022

A Systems Engineering Analysis of National Ignition Facility Industrial Controls Systems and Safety Interlock Systems Remote Input/Output Networking Migration from ControlNet to EtherNet/IP

The ControlNet industrial communications protocol and modules used in the Industrial Control System (ICS) and Safety Interlock System (SIS) at the National Ignition Facility (NIF) are no longer necessary and the ICS and SIS would be better served by migrating the communications structure to use EtherNet/Industrial Protocol (IP) and EtherNet bridge modules instead. By the admission of the vendor of ControlNet hardware, Rockwell Automation, in literature by Bill Petro [1], “Moving forward, customers will be able to optimize their asset utilization better using EtherNet/IP protocol than with ControlNet.” The NIF is one of the key elements of the Inertial Confinement Fusion (ICF) program at Lawrence Livermore National Laboratory (LLNL), a federally funded research and development center (FFRDC). The NIF contains the systems and provides the operational capacity to perform ICF, high energy density (HED), and discovery science experiments utilizing 192 individual beamlines, a host of diagnostics, and all the industrial systems required to facilitate these beamlines and diagnostics. The industrial systems are governed by the ICS and SIS, with the ICS providing control and the SIS providing monitoring and permissives. Construction on the NIF began in 1997 and was certified complete in 2009 and, as a result, the ICS and SIS were developed during this time using the tools that were available then. This includes the communications structure and protocols for these systems, much of which was, and still is, ControlNet. ControlNet, particularly during the time that the ICS and SIS were being built, has several attractive features. ControlNet hardware is exclusive to Rockwell Automation, which was the automation hardware chosen for the ICS and SIS. One feature that could be considered an advantage or a disadvantage depending on the communication needs of the system is that ControlNet also utilizes no active network components, excluding repeaters which are not always necessary. According to the architect of the ICS system at the NIF, Gordon Lau, one of the most attractive features of the ControlNet protocol during development of the ICS and SIS was that it is deterministic, providing timing of data transfer that is executed exactly as it is defined by the developer.

42 ENGINEERING↗
NASA NTRS1991

Contact dynamics testing of automated three point docking mechanism

TRW has conducted an extensive Contact Dynamics Test Program (CDTP) of the Three Point Docking Mechanism (TPDM). The CDTP tested the ability of the TPDM latches to capture and automatically dock to target spacecraft. The target selected was the Hubble Space Telescope (HST). Mock ups of the TPDM with its three latches and the docking interface of the HST were constructed at the Marshall Space Flight Center (MSFC) in Huntsville, Alabama for use in the tests. The tests were performed at the Flat Floor and Six Degree of Freedom (6-DOF) facilities at MSFC.

Spitzer, Christopher J.↗
NASA NTRS1984

JPL Robotics Laboratory computer vision software library

The past ten years of research on computer vision have matured into a powerful real time system comprised of standardized commercial hardware, computers, and pipeline processing laboratory prototypes, supported by anextensive set of image processing algorithms. The software system was constructed to be transportable via the choice of a popular high level language (PASCAL) and a widely used computer (VAX-11/750), it comprises a whole realm of low level and high level processing software that has proven to be versatile for applications ranging from factory automation to space satellite tracking and grappling.

Cunningham, R.↗
NASA NTRS1999

Benefit Estimates of Terminal Area Productivity Program Technologies

This report documents benefit analyses for the NASA Terminal Area Technology (TAP) technology programs. Benefits are based on reductions in arrival delays at ten major airports over the 10 years from 2006 through 2015. Detailed analytic airport capacity and delay models were constructed to produce the estimates. The goal of TAP is enable good weather operations tempos in all weather conditions. The TAP program includes technologies to measure and predict runway occupancy times, reduce runway occupancy times in bad weather, accurately predict wake vortex hazards, and couple controller automation with aircraft flight management systems. The report presents and discusses the estimate results and describes the models. Three appendixes document the model algorithms and discuss the input parameters selected for the TAP technologies. The fourth appendix is the user's guide for the models. The results indicate that the combined benefits for all TAP technologies at all 10 airports range from $550 to $650 million per year (in constant 1997 dollars). Additional benefits will accrue from reductions in departure delays. Departure delay benefits are calculated by the current models.

Hemm, Robert↗
NASA NTRS2003

Automation and Robotics for Human Mars Exploration (AROMA)

Automation and Robotics (A&R) systems are a key technology for Mars exploration. All over the world initiatives in this field aim at developing new A&R systems and technologies for planetary surface exploration. From December 2000 to February 2002 Kayser-Threde GmbH, Munich, Germany lead a study called AROMA (Automation and Robotics for Human Mars Exploration) under ESA contract in order to define a reference architecture of A&R elements in support of a human Mars exploration program. One of the goals of this effort is to initiate new developments and to maintain the competitiveness of European industry within this field. c2003 Published by Elsevier Science Ltd.

Space Flight/instrumentation↗
NASA NTRS2008

Novel Process Revolutionizes Welding Industry

Glenn Research Center, Delphi Corporation, and the Michigan Research Institute entered into a research project to study the use of Deformation Resistance Welding (DRW) in the construction and repair of stationary structures with multiple geometries and dissimilar materials, such as those NASA might use on the Moon or Mars. Traditional welding technologies are burdened by significant business and engineering challenges, including high costs of equipment and labor, heat-affected zones, limited automation, and inconsistent quality. DRW addresses each of those issues, while drastically reducing welding, manufacturing, and maintenance costs.

Source record↗
NASA NTRS2014

Assessing V and V Processes for Automation with Respect to Vulnerabilities to Loss of Airplane State Awareness

Automation has contributed substantially to the sustained improvement of aviation safety by minimizing the physical workload of the pilot and increasing operational efficiency. Nevertheless, in complex and highly automated aircraft, automation also has unintended consequences. As systems become more complex and the authority and autonomy (A&A) of the automation increases, human operators become relegated to the role of a system supervisor or administrator, a passive role not conducive to maintaining engagement and airplane state awareness (ASA). The consequence is that flight crews can often come to over rely on the automation, become less engaged in the human-machine interaction, and lose awareness of the automation mode under which the aircraft is operating. Likewise, the complexity of the system and automation modes may lead to poor understanding of the interaction between a mode of automation and a particular system configuration or phase of flight. These and other examples of mode confusion often lead to mismanaging the aircraftâ€"TM"s energy state or the aircraft deviating from the intended flight path. This report examines methods for assessing whether, and how, operational constructs properly assign authority and autonomy in a safe and coordinated manner, with particular emphasis on assuring adequate airplane state awareness by the flight crew and air traffic controllers in off-nominal and/or complex situations.

Whitlow, Stephen↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learningautonomous systems; flight simulat↗
NASA NTRSDate not supplied

Tradeoffs When Considering Deep Reinforcement Learning for Contingency Management in Advanced Air Mobility

Air transportation is undergoing a rapid evolution globally with the introduction of Advanced Air Mobility (AAM) and with it comes novel challenges and opportunities for transforming aviation. As AAM operations introduce increasing heterogeneity in vehicle capabilities and density, increased levels of automation are likely necessary to achieve operational safety and efficiency goals. This paper focuses on one example where increased automation has been suggested. Autonomous operations will need contingency management systems that can monitor evolving risk across a span of interrelated (or interdependent) hazards and, if necessary, execute appropriate control interventions via supervised or automated decision making. Accommodating this complex environment may require automated functions (autonomy) that apply artificial intelligence (AI) techniques that can adapt and respond to a quickly changing environment. This paper explores the use of Deep Reinforcement Learning (DRL) which has shown promising performance in complex and high-dimensional environments where the objective can be constructed as a sequential decision-making problem. An extension of a prior formulation of the contingency management problem as a Markov Decision Process (MDP) is presented and uses a DRL framework to train agents that mitigate hazards present in the simulation environment. A comparison of these learning-based agents and classical techniques is presented in terms of their performance, verification difficulties, and development process.

machine learning↗
NASA NTRS1981

To Produce Nutrients for Plant Growth

On July 1, 1979 a new research program entitled "Development of a Prototype Experiment for Treating CELSS and PCELSS Wastes to Produce Nutrients for Plant Growth" was undertaken by the Massachusetts Institute of Technology and the Georgia Institute of Technology under grant from the National Aeronautics and Space Administration's Ames Research Center. The program was designed to be completed over a five-year period, with the work divided into two phases. Phase I covers approximately two years and involves the development of necessary facilities, chemical methodologies and models to allow meaningful experiments during Phase II, which will involve interfacing waste oxidation with plant growth. Homogeneous samples of freeze-dried human feces and urine have been prepared to assure comparability of results among various CELSS waste treatment research groups. A model of food processing wastes within a PCELSS was developed, and an initial batch of waste was prepared. An automated gas chromatographic system to analyze oxidizer effluents was designed and is operational. A state-of-the-art quantitative elemental analysis capability, built around inductively coupled plasma emission spectroscopy and atomic absorption spectroscopy using electrothermal atomization, has been demonstrated. A continuous flow wet oxidation system was constructed and is now operational.

Michael Modell↗
NASA NTRS1991

Lunar outpost agriculture

The development of a CELSS for a lunar outpost is discussed. It is estimated that a lunar outpost life support system with a crew of four that produces food would break even in terms of mass and cost to deliver the system to the lunar surface after 2.5 years when compared to the cost of resupply from earth. A brief review is made of research on life support systems and NASA projects for evaluating CELSS components. The use of on-site materials for propellants, construction materials, and agriculture is evaluated, and the use of microbes for waste decomposition and stabilization of ecological balance is touched upon. Areas for further investigation include the behavior of organisms in microgravity, genetic alteration, gas exchange capabilities of organisms, integration of biological and physicochemical components, and automation. The development stages leading to lunar deployment are outlined.

Hossner, Lloyd R.↗
DOE OSTI2023

Automated extraction of interfacial dislocations and disconnections from atomistic data

Here we introduce Interfacial Line Defect Analysis (ILDA), a method for identifying and extracting interfacial dislocations and disconnections with little-to-no input from the user on the nature of the interface. By simply providing the orientations and coherency strains for the crystals in a coherent reference state of the interface, ILDA provides exact Burgers vectors. Alternatively, these orientations and strains can be estimated using local atomic deformation gradients, making ILDA fully automated and providing estimated Burgers vectors. ILDA also determines the step height associated with each defect line segment, in case the associated defect is a disconnection. The heart of the method is the identification of atoms residing at co-incidence sites between the two crystals and the construction of a surface mesh connecting these sites that is used to compose Burgers circuits and insert defect line segments. We demonstrate the performance of ILDA in two test cases: a twist grain boundary and a phase boundary.

36 MATERIALS SCIENCE↗
DOE OSTI2020

A scoping review of non-destructive testing (NDT) techniques in building performance diagnostic inspections

Understanding building envelope thermodynamics is an essential foundation of building sciences, mainly due to the envelope’s role as a boundary layer for exterior environments, as well as a container and regulator of internal microclimates. This paper presents a scoping literature review of select Non-destructive Testing (NDT) techniques for building envelope scanning and surveying for thermodynamic diagnostics. The investigation focuses specifically on reviewing six NDT techniques: Ground Penetrating Radar (GPR), Light Detection and Ranging (LiDAR)/Laser Scanning, Thermography, Ultrasound, Close-Range Photogrammetry and Through Wall Imaging Radar (TWIR). The aim is to identify knowledge gaps in terms of their use in accurately characterizing envelope compositions for further integration in Building Energy Modeling (BEM). Each technique was evaluated according to set categories imbibed from the American Society of Heating, Refrigerating, and Air Conditioning Engineering (ASHRAE) Standard 211P that showcase the technique’s ability to extract various relevant information. A framework is then developed to inform users on how to use hybrid NDT-based workflows applied in building envelope energy audits. The study concludes by discussing possibilities of utilizing NDT in large-scale audit automation, BEM integration, and developing built environment policies focusing on increasing existing building performance through retrofitting design.

36 MATERIALS SCIENCE↗
DOE OSTI2023

VDiSC: An Open Source Framework for Distributed Smart City Vision and Biometric Surveillance Networks

Recent global growth in the interest of smart cities has led to trillions of dollars of investment toward research and development. These connected cities have the potential to create a symbiosis of technology and society and revolutionize the cost of living, safety, ecological sustainability, and quality of life of societies on a world-wide scale. Some key components of the smart city construct are connected smart grids, self-driving cars, federated learning systems, smart utilities, large-scale public transit, and proactive surveillance systems. While exciting in prospect, these technologies and their subsequent integration cannot be attempted without addressing the potential societal impacts of such a high degree of automation and data sharing. Additionally, the feasibility of coordinating so many disparate tasks will require a fast, extensible, unifying framework. To that end, we propose the Distributed Smart City framework for Vision, or VDiSC. VDiSC serves as a unified biometric API harness that allows for seamless evaluation, deployment, and simple pipeline creation for heterogeneous biometric software. VDiSC additionally provides a fully declarative capability for defining and coordinating custom machine learning and sensor pipelines, allowing the distribution of processes across otherwise incompatible hardware and networks. VDiSC ultimately provides a way to quickly configure, hot-swap, and expand large coordinated or federated systems online without interruptions for maintenance. Because much of the data collected in a smart city contains Personally Identifying Information (PII), VDiSC also provides built-in tools and layers to ensure secure and encrypted streaming, storage, and access of PII data across distributed systems.

Brogan, Joel↗
NASA NTRS1990

A flight expert system for on-board fault monitoring and diagnosis

An architecture for a flight expert system (FLES) to assist pilots in monitoring, diagnosing, and recovering from inflight faults is described. A prototype was implemented and an attempt was made to automate the knowledge acquisition process by employing a learning by being told methodology. The scope of acquired knowledge ranges from domain knowledge, including the information about objects and their relationships, to the procedural knowledge associated with the functionality of the mechanisms. AKAS (automatic knowledge acquisition system) is the constructed prototype for demonstration proof of concept, in which the expert directly interfaces with the knowledge acquisition system to ultimately construct the knowledge base for the particular application. The expert talks directly to the system using a natural language restricted only by the extent of the definitions in an analyzer dictionary, i.e., the interface understands a subset of concepts related to a given domain. In this case, the domain is the electrical system of the Boeing 737. Efforts were made to define and employ heuristics as well as algorithmic rules to conceptualize data produced by normal and faulty jet engine behavior examples. These rules were employed in developing the machine learning system (MLS). The input to MLS is examples which contain data of normal and faulty engine behavior and which are obtained from an engine simulation program. MLS first transforms the data into discrete selectors. Partial descriptions formed by those selectors are then generalized or specialized to generate concept descriptions about faults. The concepts are represented in the form of characteristic and discriminant descriptions, which are stored in the knowledge base and are employed to diagnose faults. MLS was successfully tested on jet engine examples.

Ali, Moonis↗