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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
NASA NTRS1992

A trace-driven analysis of name and attribute caching in a distributed system

This paper presents the results of simulating file name and attribute caching on client machines in a distributed file system. The simulation used trace data gathered on a network of about 40 workstations. Caching was found to be advantageous: a cache on each client containing just 10 directories had a 91 percent hit rate on name look ups. Entry-based name caches (holding individual directory entries) had poorer performance for several reasons, resulting in a maximum hit rate of about 83 percent. File attribute caching obtained a 90 percent hit rate with a cache on each machine of the attributes for 30 files. The simulations show that maintaining cache consistency between machines is not a significant problem; only 1 in 400 name component look ups required invalidation of a remotely cached entry. Process migration to remote machines had little effect on caching. Caching was less successful in heavily shared and modified directories such as /tmp, but there weren't enough references to /tmp overall to affect the results significantly. We estimate that adding name and attribute caching to the Sprite operating system could reduce server load by 36 percent and the number of network packets by 30 percent.

Shirriff, Ken W.↗
NASA NTRS2015

0.625" FPPW Abstract

Friction Pull Plug Welding (FPPW) is a solid‐state process that is the primary close out method for Self‐ Reacting Friction Stir Welding (SR‐FSW). This process uses a servo hydraulic machine to spin an aluminum plug to several thousand revolutions per minute and pull the plug with several thousand pound force into an aluminum piece of material. This process, which has been around for approximately a decade, has proven to be a very difficult process to develop. There are large number of variables with interactions and correlations that are difficult to detect. Historically this method only provided good results on aluminum material up to 0.327" thick. The SLS rocket required weld land configurations of up to 0.625" thick. This not only pushed the limits of the process but also of the tools procured for materials 1/2 as thick. Ultimate Tensile Results was typically the response used for FPPW input variables. The problem was there were multiple processes including, welding, post weld machining, Non Destructive Evaluation, specimen fabrication and mechanical testing between the FPPW inputs and the mechanical test results. This only compiled the list of variables and made the process of FPPW even more difficult to develop. This presentation and paper describes the new process development methodology, which uses the FPPW tool's feedback to observe the process and develop it systematically. It captures 6 months and 600 plugs worth of work using only the tool's feedback as a response to the process. This presentation describes the solution to the issue, a solution whose methodology could apply to a variety of other processes.

Littell, Justin↗
NASA NTRS1971

Rapid method for sampling metals for materials identification

Nondamaging process similar to electrochemical machining is useful in obtaining metal samples from places inaccessible to conventional sampling methods or where methods would be hazardous or contaminating to specimens. Process applies to industries where metals or metal alloys play a vital role.

Higgins, L. E.↗
NASA NTRS1967

Machining heavy plastic sections

Machining technique produces consistently satisfactory plane-parallel optical surfaces for pressure windows, made of plexiglass, required to support a photographic study of liquid rocket combustion processes. The surfaces are machined and polished to the required tolerances and show no degradation from stress relaxation over periods as long as 6 months.

Stalkup, O. M.↗
NASA NTRS1972

Computers formed by the problems rather than problems deformed by the computers.

Description of an approach to computer programming which tries to minimize the time required for retranslation from the computer language into the language of the original process. A notion of a programmable network is introduced which allows the abstract machines that are a model of the processes in the user's mind to be put into a rigorous and simple form. Each process is then modeled as a particular finite-state machine, a circulating page loose system being employed as an architecture for implementing these finite-state machines. An experiment is discussed in which the use of abstract machines as a language for modeling processes, in conjunction with the use of a self-organizing computer, decreases user effort, eliminates the need for compilation, facilitates debugging, and decreases computer time.

Schaffner, M. R.↗
NASA NTRS2010

Integration Methodology For Oil-Free Shaft Support Systems: Four Steps to Success

Commercial applications for Oil-Free turbomachinery are slowly becoming a reality. Micro-turbine generators, highspeed electric motors, and electrically driven centrifugal blowers are a few examples of products available in today's commercial marketplace. Gas foil bearing technology makes most of these applications possible. A significant volume of component level research has led to recent acceptance of gas foil bearings in several specialized applications, including those mentioned above. Component tests identifying such characteristics as load carrying capacity, power loss, thermal behavior, rotordynamic coefficients, etc. all help the engineer design foil bearing machines, but the development process can be just as important. As the technology gains momentum and acceptance in a wider array of machinery, the complexity and variety of applications will grow beyond the current class of machines. Following a robust integration methodology will help improve the probability of successful development of future Oil-Free turbomachinery. This paper describes a previously successful four-step integration methodology used in the development of several Oil-Free turbomachines. Proper application of the methods put forward here enable successful design of Oil-Free turbomachinery. In addition when significant design changes or unique machinery are developed, this four-step process must be considered.

Howard, Samuel A.↗
NASA NTRS2010

Economical Fabrication of Thick-Section Ceramic Matrix Composites

A method was developed for producing thick-section [>2 in. (approx.5 cm)], continuous fiber-reinforced ceramic matrix composites (CMCs). Ultramet-modified fiber interface coating and melt infiltration processing, developed previously for thin-section components, were used for the fabrication of CMCs that were an order of magnitude greater in thickness [up to 2.5 in. (approx.6.4 cm)]. Melt processing first involves infiltration of a fiber preform with the desired interface coating, and then with carbon to partially densify the preform. A molten refractory metal is then infiltrated and reacts with the excess carbon to form the carbide matrix without damaging the fiber reinforcement. Infiltration occurs from the inside out as the molten metal fills virtually all the available void space. Densification to <5 vol% porosity is a one-step process requiring no intermediate machining steps. The melt infiltration method requires no external pressure. This prevents over-infiltration of the outer surface plies, which can lead to excessive residual porosity in the center of the part. However, processing of thick-section components required modification of the conventional process conditions, and the means by which the large amount of molten metal is introduced into the fiber preform. Modification of the low-temperature, ultraviolet-enhanced chemical vapor deposition process used to apply interface coatings to the fiber preform was also required to accommodate the high preform thickness. The thick-section CMC processing developed in this work proved to be invaluable for component development, fabrication, and testing in two complementary efforts. In a project for the Army, involving SiC/SiC blisk development, nominally 0.8 in. thick x 8 in. diameter (approx. 2 cm thick x 20 cm diameter) components were successfully infiltrated. Blisk hubs were machined using diamond-embedded cutting tools and successfully spin-tested. Good ply uniformity and extremely low residual porosity (<2 percent) were achieved, the latter being far lower than that achieved with SiC matrix composites fabricated via CVI or PIP. The pyrolytic carbon/zirconium nitride interface coating optimized in this work for use on carbon fibers was incorporated in the SiC/SiC composites and yielded a >41 ksi (approx. 283 MPa) flexural strength.

Babcock, Jason↗
NASA NTRS1986

Automated Rotating-Machinery Analysis

Computer-controlled automatic system processes accelerometer data from rotating machines, producing mathematical description and graphical display of shaft motion. Program saves processing time, readily identifies type of motion (circular, looped, or elliptical), provides annotated assessments to assist in failure analysis, alerts user to look for distinctive characteristics of machinery, and creates informative plots.

Clark, J.↗
NASA NTRS1991

Advanced fiber placement of composite fuselage structures

The Hercules/NASA Advanced Composite Technology (ACT) program will demonstrate the low cost potential of the automated fiber placement process. The Hercules fiber placement machine was developed for cost effective production of composite aircraft structures. The process uses a low cost prepreg tow material form and achieves equivalent laminate properties to structures fabricated with prepreg tape layup. Fiber placement demonstrations planned for the Hercules/NASA program include fabrication of stiffened test panels which represent crown, keel, and window belt segments of a typical transport aircraft fuselage.

Anderson, Robert L.↗
NASA NTRSDate not supplied

Collaborative Communications Between a Human and a Resilient Safety Support System

Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACC to which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.

Advanced Air Mobility,↗
NASA NTRS2021

Collaborative Communications Between A Human and A Resilient Safety Support System

Successful introductory UAM integration into the NAS will be contingent on resilient safety systems that support reduced-crew flight operations. In this paper, we present a system that performs three functions: 1) monitors an operator’s physiological state; 2) assesses when the operator is experiencing anomalous states; and 3) mitigates risks by a combination of dynamic, context-based unilateral or collaborative dynamic function allocation of operational tasks. The monitoring process receives high data-rate sensor values from eye-tracking and electrocardiogram sensors. The assessment process takes these values and performs a classification that was developed using machine learning algorithms. The mitigation process invokes a collaboration protocol called DFACCto which, based on context, performs vehicle operations that the operator would otherwise routinely execute. This system has been demonstrated in a UAM flight simulator for an operator incapacitation scenario. The methods and initial results as well as relevant UAM and AAM scenarios will be described.

Advanced air mobility↗
NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗
NASA NTRSDate not supplied

Feasibility Study of Distributed Decision-Making on the Edge for Urban Air Mobility

The Concept of Operations for Urban Air Mobility (UAM) put forward by FAA, NASA, and several industry stakeholders acknowledges the diversity and complexity in UAM operations and, thereby, envisions a federated architecture for UAM management. In this architecture, the decision-making is distributed to a set of service providers who collectively manage the shared airspace usage by different stakeholders. This notionally brings autonomy closer to the UAM businesses and encourages to explore the feasibility of decision making on the very edge, which is the topic of the presented research. This paper reports research conducted on the hypothesis based on which the residual compute capability onboard smart unmanned aerial systems (UASs) is utilized to build situational awareness and resolve conflicts by passive and active coordination among multiple UASs, thereby implementing a layer of distributed autonomy in UAM. Key features of the edge-computing approach involve inter-UAS information exchange, independent assessment of own flight and environmental conditions, and estimation of other UASs’ flight preferences, incorporating machine learning techniques in the last two. Parallel computing on portable graphics processing unit (GPU) enables the machine learning workflow on the edge. A custom-built 3D simulator is used to evaluate the efficacy of the distributed decision-making on the edge. Each edge node, representing a smart UAS, connects to the simulator from a remote location and independently controls the behavior of the corresponding virtual asset in the simulator, analogous to participants in an online multi-player game. The presented edge-computing-based distributed decision-making framework is envisioned to pave the way for collective mobility of autonomous air vehicles in the future shared airspace, while allowing the inclusion of the business preferences of the UAS operators within allowed regulatory limits.

Edge computing↗
NASA NTRS2015

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human‐rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30‐sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post‐processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one‐way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Prater, Tracie↗
NASA NTRS2018

Introduction to Analysis Methods for Big Earth Data

Big Earth Data are too big to be tractable to simple data inspection and require models to make sense of all the data. Useful models for Big Earth Data may be physical, statistical, or machine learning based. In many cases, hybrid models combine attributes of two or more of these types.

parallel processing (computers)↗
NASA NTRS2015

Characterization of Machine Variability and Progressive Heat Treatment in Selective Laser Melting of Inconel 718

The absence of an economy of scale in spaceflight hardware makes additive manufacturing an immensely attractive option for propulsion components. As additive manufacturing techniques are increasingly adopted by government and industry to produce propulsion hardware in human-rated systems, significant development efforts are needed to establish these methods as reliable alternatives to conventional subtractive manufacturing. One of the critical challenges facing powder bed fusion techniques in this application is variability between machines used to perform builds. Even with implementation of robust process controls, it is possible for two machines operating at identical parameters with equivalent base materials to produce specimens with slightly different material properties. The machine variability study presented here evaluates 60 specimens of identical geometry built using the same parameters. 30 samples were produced on machine 1 (M1) and the other 30 samples were built on machine 2 (M2). Each of the 30-sample sets were further subdivided into three subsets (with 10 specimens in each subset) to assess the effect of progressive heat treatment on machine variability. The three categories for post-processing were: stress relief, stress relief followed by hot isostatic press (HIP), and stress relief followed by HIP followed by heat treatment per AMS 5664. Each specimen (a round, smooth tensile) was mechanically tested per ASTM E8. Two formal statistical techniques, hypothesis testing for equivalency of means and one-way analysis of variance (ANOVA), were applied to characterize the impact of machine variability and heat treatment on six material properties: tensile stress, yield stress, modulus of elasticity, fracture elongation, and reduction of area. This work represents the type of development effort that is critical as NASA, academia, and the industrial base work collaboratively to establish a path to certification for additively manufactured parts. For future flight programs, NASA and its commercial partners will procure parts from vendors who will use a diverse range of machines to produce parts and, as such, it is essential that the AM community develop a sound understanding of the degree to which machine variability impacts material properties.

Prater, T.↗
NASA NTRSDate not supplied

The TOLNet 2.0 Website: How an API Can Promote Open Science and FAIR Principles

The Tropospheric Ozone Lidar Network (TOLNet) has generated over a decade of ozone vertical profile data products over North America. The science value of the TOLNet data has been demonstrated in numerous peer-reviewed publications on air quality and other ozone relevant research. To support the broad spectrum of data use, the TOLNet team launched a major effort to upgrade the web-based data repository aiming to enhance the data discoverability and to enable machine-to-machine data upload and download processes. Specifically, the TOLNet website included an application programming interface (API), which supports machine-to-machine data search and data download. The API also extracts selected variables from the files, which can be retrieved as JSON objects and used to create data displays without having to download or open the underlying files. The TOLNet science team members can also use the API for automated data upload, including a data file scanning feature to ensure data product integrity. To be presented will include a summary of key features of data repositories, an actual use case of machine-to-machine data access/use, as well as our journey to make TOLNet data more FAIR, i.e., more findable, accessible, interoperable, and (re)usable.

Crystal Gummo↗