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Institution

Langley Research Center

FacilityHampton, Virginia, United States
About: Langley Research Center is a facility organization based out in Hampton, Virginia, United States. It is known for research contribution in the topics: Mach number & Wind tunnel. The organization has 15945 authors who have published 37602 publications receiving 821623 citations. The organization is also known as: NASA Langley & NASA Langley Research Center.


Papers
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Journal ArticleDOI
TL;DR: This paper supplies a presentation of experiments on a commercial robot that demonstrate the effectiveness of iterative learning control, improving the tracking accuracy of the robot performing a high speed maneuver by a factor of 100 in six repetitions.
Abstract: Iterative learning control (ILC) applies to control systems that perform the same finite-time tracking command repeatedly. It iteratively adjusts the command from one repetition to the next in order to reduce the tracking error. This creates a two-dimensional (2-D) system, with time step and repetition number as independent variables. The simplest form of ILC uses only one gain times one error in the previous repetition, and can be shown to converge to the zero-tracking error independent of the system dynamics. Hence, it appears very effective from a mathematical perspective. However, in practice, there are unacceptable learning transients. A zero-phase low-pass filter is introduced here to eliminate the worst transients. The main purpose of this paper is to supply a presentation of experiments on a commercial robot that demonstrate the effectiveness of this approach, improving the tracking accuracy of the robot performing a high speed maneuver by a factor of 100 in six repetitions. Experiments using a two-gain ILC reaches this error level in only three iterations. It is suggested that these two simple ILC laws are the equivalent for learning control of proportional and PD control in classical control system design. Thus, what was an impractical approach, becomes practical, easy to apply, and effective.

156 citations

01 Jul 2003
TL;DR: The electron beam freeform fabrication (EBF) as discussed by the authors was developed at NASA Langley REsearch Center to add structural details to simpler cast or forged structures rather than the conventional approach of machining large volumes of chips to produce a monolithic metallic structure.
Abstract: Manufacturing of structural metal parts directly from computer aided design (CAD) data has been investigated by numerous researchers over the past decade. Researchers at NASA Langley REsearch Center are developing a new solid freeform fabrication process, electron beam freeform fabrication (EBF), as a rapid metal deposition process that works efficiently with a variety of weldable alloys. The EBF process introduces metal wire feedstock into a molten pool that is created and sustained using a focused electron beam in a vacuum environment. Thus far, this technique has been demonstrated on aluminum and titanium alloys of interest for aerospace structural applications nickel and ferrous based alloys are also planned. Deposits resulting from 2219 aluminum demonstrations have exhibited a range of grain morphologies depending upon the deposition parameters. These materials ave exhibited excellent tensile properties comparable to typical handbook data for wrought plate product after post-processing heat treatments. The EBF process is capable of bulk metal deposition at deposition rated in excess of 2500 cubic centimeters per hour (150 cubic inches per our) or finer detail at lower deposition rates, depending upon the desired application. This process offers the potential for rapidly adding structural details to simpler cast or forged structures rather than the conventional approach of machining large volumes of chips to produce a monolithic metallic structure. Selective addition of metal onto simpler blanks of material can have a significant effect on lead time reduction and lower material and machining costs.

156 citations

Journal ArticleDOI
TL;DR: This work proposes a scalable energy-efficient training protocol for nodes that are initially anonymous, asynchronous and unaware of their location that imposes a flexible and intuitive coordinate system onto the deployment area and partitions the anonymous nodes into clusters where data can be gathered from the environment and synthesized under local control.
Abstract: The networks considered in this paper consist of tiny energy-constrained commodity sensors massively deployed, along with one or more sink nodes providing interface to the outside world. Our contribution is to propose a scalable energy-efficient training protocol for nodes that are initially anonymous, asynchronous and unaware of their location. Our training protocol imposes a flexible and intuitive coordinate system onto the deployment area and partitions the anonymous nodes into clusters where data can be gathered from the environment and synthesized under local control. An important by-product of the training protocol is a simple and natural data fusion protocol as well as an energy-efficient protocol for routing data from clusters to the sink node. Being energy-efficient, our training protocol can be run on either a scheduled or ad-hoc basis to provide robustness and dynamic reconfiguration. We also outline a way of making the training protocol secure by using a parameterized variant of frequency hopping.

156 citations

Proceedings ArticleDOI
01 Jan 1991
TL;DR: In this paper, the ability of adaptive methods to obtain accurate results was examined using two different Euler solvers for a near-sonic flow containing several important flow features, and it was shown that the accuracy obtained can be greatly affected by the lack of resolution of smooth portions of the flow caused by adapting only to the more prevalent flow features such as discontinuities.
Abstract: The ability of adaptive methods to obtain accurate results is examined using two different Euler solvers for a near-sonic flow containing several important flow features. It is shown that the accuracy obtained can be greatly affected by the lack of resolution of smooth portions of the flow caused by adapting only to the more prevalent flow features such as discontinuities. In particular, common methods of adaptation can lead to results in which shocks are well resolved but whose locations are highly inaccurate due to the lack of resolution of the smoother regions. An explanation for this behavior is given and a correction is proposed.

156 citations

Journal ArticleDOI
TL;DR: In this article, a study of instabilities in incompressible boundary-layer flow on a flat plate is conducted by spatial direct numerical simulation (DNS) of the Navier-Stokes equations.
Abstract: A study of instabilities in incompressible boundary-layer flow on a flat plate is conducted by spatial direct numerical simulation (DNS) of the Navier-Stokes equations. Here, the DNS results are used to evaluate critically the results obtained using parabolized stability equations (PSE) theory and to study mechanisms associated with breakdown from laminar to turbulent flow. Three test cases are considered: two-dimensional Tollmien-Schlichting wave propagation, subharmonic instability breakdown, and oblique-wave breakdown. The instability modes predicted by PSE theory are in good quantitative agreement with the DNS results, except a small discrepancy is evident in the mean-flow distortion component of the two-dimensional test problem. This discrepancy is attributed to far-field boundary-condition differences. Both DNS and PSE theory results show several modal discrepancies when compared with the experiments of subharmonic breakdown. Computations that allow for a small adverse pressure gradient in the basic flow and a variation of the disturbance frequency result in better agreement with the experiments.

156 citations


Authors

Showing all 16015 results

NameH-indexPapersCitations
Daniel J. Jacob16265676530
Donald R. Blake11872749697
Veerabhadran Ramanathan10030147561
Raja Parasuraman9140241455
Robert W. Platt8863831918
James M. Russell8769129383
Daniel J. Inman8391837920
Antony Jameson7947431518
Ya-Ping Sun7927728722
Patrick M. Crill7922820850
Richard B. Miles7875925239
Patrick Minnis7749023403
Robert W. Talbot7729719783
Raphael T. Haftka7677328111
Jack E. Dibb7534418399
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202335
202286
2021571
2020540
2019669
2018797