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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 91 records · Page 5
All sourcesNASA NTRSDOE OSTI
NASA NTRS1990

Unique failure behavior of metal/composite aircraft structural components under crash type loads

Failure behavior results are presented on some of the crash dynamics research conducted with concepts of aircraft elements and substructure which have not necessarily been designed or optimized for energy absorption or crash loading considerations. To achieve desired new designs which incorporate improved energy absorption capabilities often requires an understanding of how more conventional designs behave under crash type loadings. Experimental and analytical data are presented which indicate some general trends in the failure behavior of a class of composite structures which include individual fuselage frames, skeleton subfloors with stringers and floor beams but without skin covering, and subfloors with skin added to the frame-stringer arrangement. Although the behavior is complex, a strong similarity in the static/dynamic failure behavior among these structures is illustrated through photographs of the experimental results and through analytical data of generic composite structural models. It is believed that the thread of similarity in behavior is telling the designer and dynamists a great deal about what to expect in the crash behavior of these structures and can guide designs for improving the energy absorption and crash behavior of such structures.

Carden, Huey D.↗
NASA NTRS1990

Behavior of composite/metal aircraft structural elements and components under crash type loads: What are they telling us

Failure behavior results are presented from crash dynamics research using concepts of aircraft elements and substructure not necessarily designed or optimized for energy absorption or crash loading considerations. To achieve desired new designs which incorporate improved energy absorption capabilities often requires an understanding of how more conventional designs behave under crash loadings. Experimental and analytical data are presented which indicate some general trends in the failure behavior of a class of composite structures which include individual fuselage frames, skeleton subfloors with stringers and floor beams but without skin covering, and subfloors with skin added to the frame-stringer arrangement. Although the behavior is complex, a strong similarity in the static and dynamic failure behavior among these structures is illustrated through photographs of the experimental results and through analytical data of generic composite structural models. It is believed that the similarity in behavior is giving the designer and dynamists much information about what to expect in the crash behavior of these structures and can guide designs for improving the energy absorption and crash behavior of such structures.

Carden, Huey D.↗
NASA NTRS1990

Behavior of composite/metal aircraft structural elements and components under crash type loads - What are they telling us?

Failure behavior results are presented from crash dynamics research using concepts of aircraft elements and substructure not necessarily designed or optimized for energy absorption or crash loading considerations. To achieve desired new designs which incorporate improved energy absorption capabilities often requires an understanding of how more conventional designs behave under crash loadings. Experimental and analytical data are presented which indicate some general trends in the failure behavior of a class of composite structures which include individual fuselage frames, skeleton subfloors with stringers and floor beams but without skin covering, and subfloors with skin added to the frame-stringer arrangement. Although the behavior is complex, a strong similarity in the static and dynamic failure behavior among these structures is illustrated through photographs of the experimental results and through analytical data of generic composite structural models. It is believed that the similarity in behavior is giving the designer and dynamists much information about what to expect in the crash behavior of these structures and can guide designs for improving the energy absorption and crash behavior of such structures.

Carden, Huey D.↗
NASA NTRS1991

An overview of the crash dynamics failure behavior of metal and composite aircraft structures

An overview of failure behavior results is presented from some of the crash dynamics research conducted with concepts of aircraft elements and substructure not necessarily designed or optimized for energy absorption or crash loading considerations. Experimental and analytical data are presented that indicate some general trends in the failure behavior of a class of composite structures that includes fuselage panels, individual fuselage sections, fuselage frames, skeleton subfloors with stringers and floor beams without skin covering, and subfloors with skin added to the frame stringer structure. Although the behavior is complex, a strong similarity in the static/dynamic failure behavior among these structures is illustrated through photographs of the experimental results and through analytical data of generic composite structural models.

Carden, Huey D.↗
NASA NTRS1974

Experiments with a four-bladed cyclic pitch stirring model rotor, part 3

The experimental work with the 2-bladed 16-inch diameter model rotor has been continued with a 4-bladed 16.5 inch diameter rotor capable of progressing and regressing cyclic pitch excitation (cyclic pitch stirring). Advance ratios of 0, .19 and .38 were tested at rotor speeds corresponding to non-dimensional blade natural frequencies of 1:14 and 1.19. The results are presented in the form of the first 5 Fourier components of the periodic response modulating function which for a periodic system takes the place of the complex response amplitude ratio of a constant system. In addition, the first and second harmonics of the trim response are presented. The test data are compared to analytical data without rotor wake and to the test data obtained earlier with the two-bladed rotor model of half the blade solidity ratio.

Hohenemser, K. H.↗
NASA NTRS1981

Voyager 1 encounter with the Saturnian system

The Voyager 1 Saturn flyby mission of March 1979 is reviewed, with brief discussions of its flight, trajectory, science plan formulation and telemetered data. Analytical results of such data with respect to Saturn's atmosphere, rings, icy satellites, Titan satellite atmosphere and the Saturn magnetosphere, are summarized. The Voyager science investigations comprise imaging science (ISS), infrared radiation (IRIS), photopolarimetry (PPS), ultraviolet spectroscopy (UVS), radio science (RSS), magnetic fields (MAG), plasma particles (PLS), plasma waves (PWS), planetary radio astronomy (PRA), low energy charged particles (LECP), and cosmic-ray particles (CRS).

Stone, E. C.↗
NASA NTRS1991

Water droplet impingement on airfoils and aircraft engine inlets for icing analysis

This paper includes the results of a significant research program for verification of computer trajectory codes used in aircraft icing analysis. Experimental water droplet impingement data have been obtained in the NASA Lewis Research Center Icing Research Tunnel for a wide range of aircraft geometries and test conditions. The body whose impingement characteristics are required is covered at strategic locations by thin strips of moisture absorbing (blotter) paper and then exposed to an airstream containing a dyed-water spray cloud. Water droplet impingement data are extracted from the dyed blotter strips by measuring the optical reflectance of the dye deposit on the strips with an automated reflectometer. Impingement characteristics for all test geometries have also been calculated using two recently developed trajectory computer codes. Good agreement is obtained with experimental data. The experimental and analytical data show that maximum impingement efficiency and impingement limits increase with mean volumetric diameter for all geometries tested. For all inlet geometries tested, as the inlet mass flow is reduced, the maximum impingement efficiency is reduced and the location of the maximum impingement shifts toward the inlet inner cowl.

Papadakis, Michael↗
NASA NTRS2002

Comparison of ISS Power System Telemetry with Analytically Derived Data for Shadowed Cases

Accurate International Space Station (ISS) power prediction requires the quantification of solar array shadowing. Prior papers have discussed the NASA Glenn Research Center (GRC) ISS power system tool SPACE (System Power Analysis for Capability Evaluation) and its integrated shadowing algorithms. On-orbit telemetry has become available that permits the correlation of theoretical shadowing predictions with actual data. This paper documents the comparison of a shadowing metric (total solar array current) as derived from SPACE predictions and on-orbit flight telemetry data for representative significant shadowing cases. Images from flight video recordings and the SPACE computer program graphical output are used to illustrate the comparison. The accuracy of the SPACE shadowing capability is demonstrated for the cases examined.

Fincannon, H. James↗
NASA NTRS2002

Simulation of an Impact Test of the All-Composite Lear Fan Aircraft

An MSC.Dytran model of an all-composite Lear Fan aircraft fuselage was developed to simulate an impact test conducted at the NASA Langley Research Center Impact Dynamics Research Facility (IDRF). The test was the second of two Lear Fan impact tests. The purpose of the second test was to evaluate the performance of retrofitted composite energy-absorbing floor beams. A computerized photogrammetric survey was performed to provide airframe geometric coordinates, and over 5000 points were processed and imported into MSC.Patran via an IGES file. MSC.Patran was then used to develop the curves and surfaces and to mesh the finite element model. A model of the energy-absorbing floor beams was developed separately and then integrated into the Lear Fan model. Structural responses of components such as the wings were compared with experimental data or previously published analytical data wherever possible. Comparisons with experimental results were used to guide structural model modifications to improve the simulation performance. This process was based largely on qualitative (video and still camera images and post-test inspections) rather than quantitative results due to the relatively few accelerometers attached to the structure.

Stockwell, Alan E.↗
NASA NTRS2003

International Space Station Power System Telemetry Compared With Analytically Derived Data for Shadowed Cases

This article highlights fiscal year 2002 work performed by NASA Glenn Research Center personnel to validate algorithms and data developed in-house to predict shadowing effects on the International Space Station (ISS) solar arrays power generation. The validation effort utilized video footage and on-orbit telemetry for cases spanning a 1-yr period. Validation was required because of the uncertainty of various aspects involved in shadowing analysis. Results show that a good comparison exists between actual and predicted shadowed power system performance for solar array front and backside shadowing.

Fincannon, H. James↗
NASA NTRSDate not supplied

An Introduction to Data Visualization

Data visualization can be used to present findings, explore data, and use the human eye to find patterns that a computer would struggle to locate. Borrowing tools from art, storytelling, data analytics and software development, data visualization is an indispensable part of the analysis process. While data visualization usage spans across multiple disciplines and sectors, most never receive formal training in the subject. As such, this tutorial will introduce key data visualization building blocks and how to best use those building blocks for different scenarios and audiences. We will also go over tips on accessibility, design and interactive elements. While this will by no means be a complete overview of the data visualization field, by building a foundation and introducing some rules of thumb, attendees will be better equipped for communicating their findings to their audience.

data visualization↗
NASA NTRS2020

Machine Learning-Based Predictive Analytics for Aircraft Engine Conceptual Design

Big data and artificial intelligence/machine learning are transforming the global business environment. Data is now the most valuable asset for enterprises in every industry. Companies are using data-driven insights for competitive advantage. With that, the adoption of machine learning-based data analytics is rapidly taking hold across various industries, producing autonomous systems that support human decision-making. This work explored the application of machine learning to aircraft engine conceptual design. Supervised machine-learning algorithms for regression and classification were employed to study patterns in an existing, open-source database of production and research turbofan engines, and resulting in predictive analytics for use in predicting performance of new turbofan designs. Specifically, the author developed machine learning-based analytics to predict cruise thrust specific fuel consumption (TSFC) and core sizes of high-efficiency turbofan engines, using engine design parameters as the input. The predictive analytics were trained and deployed in Keras, an open-source neural networks application program interface (API) written in Python, with Google’s TensorFlow (an open source library for numerical computation) serving as the backend engine. The promising results of the predictive analytics show that machine-learning techniques merit further exploration for application in aircraft engine conceptual design.

deep-learning↗
NASA NTRS2014

Cultivating an Emergent Earth Observation Analytics Ecosystem in the Cloud

A diverse set of data analytics systems for Earth Observations are sprouting up in the Earth Science community, with a wealth of processing algorithms and analysis methods. There is a similar wealth of data resources available via myriad data providers and clearinghouses, including large institutional systems like the Earth Observing System Data and Information System, Comprehensive Large Scale Array-data Stewardship System, and Federated Earth Observation Missions gateway. With Earth system science driving a need to work with more datasets together, and the community developing more analysis tools (some of them dataset-specific), how can we develop analysis workflows that incorporate far-flung datasets and leverage analysis resources from multiple organizations? Cloud computing points the way toward a solution in two different respects. Firstly, the access to and abstraction of virtually unlimited storage and computing power provides an environment that enables more straightforward means of pulling datasets and analysis resources together. Just as importantly, however, cloud computing serves as an example of an "ecosystem" of interoperating services, since the essence of cloud computing is the presentation of all resources as a service, from hardware to infrastructure to platform to software. This enables the combination of off-the-shelf, diverse services to construct entire systems that emerge out of an equally diverse community of architects and developers. This approach can be similarly applied to the data and analysis resources in the Earth Observation community. By exposing these resources via well understood services, and consuming resources in the same way, different organizations can construct bespoke analysis workflows and systems for their own purposes. The key leap the community needs to make is to develop analysis systems in components that interact with other components via services. The result would be a rich ecosystem of analytics components that can be combined to analyze datasets at scale and in conjunction with other datasets from other sources.

chaos↗
NASA NTRS1977

Outline of the survey on the development of earth observation satellites

An independent earth observation system with land and sea satellites to be developed by Japan is described. Visible and infrared radiometers, microwave radiometers, microwave scattermeters, synthetic aperture radar, and laser sensors are among the instrumentation discussed. Triaxial attitude control, basic technology common to sea and land observation satellites as well as land data analytical technology developed for U.S. LANDSAT data are reviewed.

Source record↗
NASA NTRSDate not supplied

Natural Language Processing Analysis of Notices to Airmen for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized.

Natural Language Processing↗
NASA NTRSDate not supplied

Natural Language Processing (NLP) Analysis of NOTAMs for Air Traffic Management Optimization

With new emerging technologies in the field of NLP, we explore their applications to digitize and analyze heritage Air Traffic Management (ATM) documents for planning and optimizing airspace operations. Specifically, this research focuses on harvesting semi-structured or un-structured information contained in Notices to Airmen (NOTAMs). Using NLP and other advanced data analytics, we will construct a data-driven framework which facilitates finding language patterns and the use of pretrained language models for classification and extraction of useful airspace constraints and restrictions. These may lead to tools that assist airspace users in understanding the constraints more efficiently, contributing to better route planning and safer execution. This paper explores three workflows entailing different NLP tasks. First, unsupervised techniques like word embedding and topic modeling are used for pattern finding and document classification. Second, a dataset is created by extracting information from the semi-structured NOTAM format as metadata for categorizing, visualizing, and extracting key entities driving NOTAM content. Third, modern pre-built deep learning based transformer models such as BERT, RoBERTa, and XLNet are evaluated on the question answering task, an even more robust approach to information extraction, as well as their respective fine-tuning tasks. In this work we include various performance metrics for the trained models to evaluate both accuracy and precision and we show that the models can be generalized for their respective tasks. The research work developed shows promise in uncovering trends in digital NOTAMs in the NAS and also offers a new framework for digitizing and inferring insights from free-form legacy NOTAMs, that are yet to be digitized. Video is an mp4 download, with a play time of 9 min 35 secs.

Natural Language Processing↗