Exploring the Jezero Crater Floor: The Mars 2020 Perseverance Rover’s First Science Campaign
No abstract provided
Engineering topics
Publications and source records attributed to Bell, James.
No abstract provided
Infra-red thermography can visualize surface flow features including boundary layer transition, shock impingement, streamwise vortex impingement, flow separation, and buffet. The Infra-red thermography system at the NASA ARC Unitary Plan Wind Tunnel allows for continuous monitoring of wind tunnel models with up to four cameras simultaneously. For best results the models should be covered with a high emissivity coating, and the images processed to enhance contrast. However image processing algorithms allow some flow information to be recovered even from uncoated models.
The National Partnership for Aeronautical Testing is a cooperative agreement between NASA and the DoD which serves as a framework for cooperation on individual projects related to aeronautical test facilities, particularly wind tunnels and engine test facilities. The Aeronautics Evaluation and Test Capability is a NASA portfolio which provides resources and coordination for the large wind tunnels and engine test cells at NASA Ames, Glenn, and Langley. This presentation describes the history, organization, and activities of the NPAT, as well as the AETC.
Funds directed to improve measurement capabilities (pressure, force, flow, and temperature), test techniques and processes, and develop technologies critical to meeting NASA research needs and applicable to a multitude of facilities. Primarily works by funding small ($40K - $400K) tasks which result in a demonstration or initial capability of a new technology in an AETC facility.TT research and development tasks are generally TRL 3-6; they should be things which work in small scale or lab environments but need further development for use in production facilities.TT differs from CA in its focus on smaller-scale tasks and on instrumentation. Technologies developed by TT may become CA projects in order be fully realized within a facility.
NASA maintains twelve major wind tunnels at three field centers capable of providing flows at 0.1 M 10 and unit Reynolds numbers up to 45106m. The maintenance and enhancement of these facilities is handled through a unified management structure under NASAs Aeronautics and Evaluation and Test Capability (AETC) project. The AETC facilities are; the 11x11 transonic and 9x7 supersonic wind tunnels at NASA Ames; the 10x10 and 8x6 supersonic wind tunnels, 9x15 low speed tunnel, Icing Research Tunnel, and Propulsion Simulator Laboratory, all at NASA Glenn; and the National Transonic Facility, Transonic Dynamics Tunnel, LAL aerothermodynamics laboratory, 8 High Temperature Tunnel, and 14x22 low speed tunnel, all at NASA Langley. This presentation describes the primary AETC facilities and their current capabilities, as well as improvements which are planned over the next five years. These improvements fall into three categories. The first are operations and maintenance improvements designed to increase the efficiency and reliability of the wind tunnels. These include new (possibly composite) fan blades at several facilities, new temperature control systems, and new and much more capable facility data systems. The second category of improvements are facility capability advancements. These include significant improvements to optical access in wind tunnel test sections at Ames, improvements to test section acoustics at Glenn and Langley, the development of a Supercooled Large Droplet capability for icing research, and the development of an icing capability for large engine testing. The final category of improvements consists of test technology enhancements which provide value across multiple facilities. These include projects to increase balance accuracy, provide NIST-traceable calibration characterization for wind tunnels, and to advance optical instruments for Computational Fluid Dynamics (CFD) validation. Taken as a whole, these individual projects provide significant enhancements to NASA capabilities in ground-based testing. They ensure that these wind tunnels will provide accurate and relevant experimental data for years to come, supporting both NASAs mission and the missions of our government and industry customers.
The brightness signal from a pressure-sensitive paint varies inversely with absolute pressure. Consequently high signal-to-noise ratios are required to resolve aerodynamic pressure fields at low speeds, where the pressure variation around an object might only be a few percent of the mean pressure. This requirement is unavoidable, and implies that care must be taken to minimize noise sources present in the measurement. This paper discusses and compares the main noise sources in low speed PSP testing using the "classical" intensity-based single-luminophore technique. These are: temperature variation, model deformation, and lamp drift/paint degradation. Minimization of these error sources from the point of view of operation in production wind tunnels is discussed, with some examples from recent tests in NASA Ames facilities.
Registration of test and reference images is a key component of nearly all PSP data reduction techniques. This is done to ensure that a test image pixel viewing a particular point on the model is ratioed by the reference image pixel which views the same point. Typically registration is needed to account for model motion due to differing airloads when the wind-off and wind-on images are taken. Registration is also necessary when two cameras are used for simultaneous acquisition of data from a dual-frequency paint. This presentation will discuss the advantages and disadvantages of several different image registration techniques. In order to do so, it is necessary to propose both an accuracy requirement for image registration and a means for measuring the accuracy of a particular technique. High contrast regions in the unregistered images are most sensitive to registration errors, and it is proposed that these regions be used to establish the error limits for registration. Once this is done, the actual registration error can be determined by locating corresponding points on the test and reference images, and determining how well a particular registration technique matches them. An example of this procedure is shown for three transforms used to register images of a semispan model. Thirty control points were located on the model. A subset of the points were used to determine the coefficients of each registration transform, and the error with which each transform aligned the remaining points was determined. The results indicate the general superiority of a third-order polynomial over other candidate transforms, as well as showing how registration accuracy varies with number of control points. Finally, it is proposed that image registration may eventually be done away with completely. As more accurate image resection techniques and more detailed model surface grids become available, it will be possible to map raw image data onto the model surface accurately. Intensity ratio data can then be obtained by a "model surface ratio," rather than an image ratio. The problems and advantages of this technique will be discussed.