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Description of an optical pattern recognition system employing a laser-diode lensless MSF correlator based on the use of holographic optical elements (HOE). The system has size, cost, and weight advantages over conventional optical processors, and it is believed to be the first unification of MSF correlation, laser diode, and HOE technologies.
The Microgravity Simulator Facility (MSF) at Kennedy Space Center (KSC) was established to support visiting scientists for short duration studies utilizing a variety of microgravity simulator devices that negate the directional influence of the "g" vector (providing simulated conditions of micro or partial gravity). KSC gravity simulators can be accommodated within controlled environment chambers allowing investigators to customize and monitor environmental conditions such as temperature, humidity, CO2, and light exposure.
An experimental investigation was conducted in the MSFC 14 inch TWT to study the roll characteristics of a 0.00548 scale model of the 146 inch shuttle solid rocket booster to obtain more accurate rolling moment data on the solid rocket booster. A sensitive single component roll balance was utilized. Data were obtained for a single nose mounted sting. The angle of attack range consisted of angles from 150 deg to 190 deg; roll angles consisted of angles from 0 deg to 337 1/2 deg in increments of 22 1/2 deg; and Mach numbers were 1.46, 1.96, 2.74 and 2.48.
Symmetrical phase-only filtering (SPOF) can be exploited to obtain substantial improvements in the results of data processing in particle-image velocimetry (PIV). In comparison with traditional PIV data processing, SPOF PIV data processing yields narrower and larger amplitude correlation peaks, thereby providing more-accurate velocity estimates. The higher signal-to-noise ratios associated with the higher amplitude correlation peaks afford greater robustness and reliability of processing. SPOF also affords superior performance in the presence of surface flare light and/or background light. SPOF algorithms can readily be incorporated into pre-existing algorithms used to process digitized image data in PIV, without significantly increasing processing times. A summary of PIV and traditional PIV data processing is prerequisite to a meaningful description of SPOF PIV processing. In PIV, a pulsed laser is used to illuminate a substantially planar region of a flowing fluid in which particles are entrained. An electronic camera records digital images of the particles at two instants of time. The components of velocity of the fluid in the illuminated plane can be obtained by determining the displacements of particles between the two illumination pulses. The objective in PIV data processing is to compute the particle displacements from the digital image data. In traditional PIV data processing, to which the present innovation applies, the two images are divided into a grid of subregions and the displacements determined from cross-correlations between the corresponding sub-regions in the first and second images. The cross-correlation process begins with the calculation of the Fourier transforms (or fast Fourier transforms) of the subregion portions of the images. The Fourier transforms from the corresponding subregions are multiplied, and this product is inverse Fourier transformed, yielding the cross-correlation intensity distribution. The average displacement of the particles across a subregion results in a displacement of the correlation peak from the center of the correlation plane. The velocity is then computed from the displacement of the correlation peak and the time between the recording of the two images. The process as described thus far is performed for all the subregions. The resulting set of velocities in grid cells amounts to a velocity vector map of the flow field recorded on the image plane. In traditional PIV processing, surface flare light and bright background light give rise to a large, broad correlation peak, at the center of the correlation plane, that can overwhelm the true particle- displacement correlation peak. This has made it necessary to resort to tedious image-masking and background-subtraction procedures to recover the relatively small amplitude particle-displacement correlation peak. SPOF is a variant of phase-only filtering (POF), which, in turn, is a variant of matched spatial filtering (MSF). In MSF, one projects a first image (denoted the input image) onto a second image (denoted the filter) as part of a computation to determine how much and what part of the filter is present in the input image. MSF is equivalent to cross-correlation. In POF, the frequency-domain content of the MSF filter is modified to produce a unitamplitude (phase-only) object. POF is implemented by normalizing the Fourier transform of the filter by its magnitude. The advantage of POFs is that they yield correlation peaks that are sharper and have higher signal-to-noise ratios than those obtained through traditional MSF. In the SPOF, these benefits of POF can be extended to PIV data processing. The SPOF yields even better performance than the POF approach, which is uniquely applicable to PIV type image data. In SPOF as now applied to PIV data processing, a subregion of the first image is treated as the input image and the corresponding subregion of the second image is treated as the filter. The Fourier transforms from both the firs and second- image subregions are normalized by the square roots of their respective magnitudes. This scheme yields optimal performance because the amounts of normalization applied to the spatial-frequency contents of the input and filter scenes are just enough to enhance their high-spatial-frequency contents while reducing their spurious low-spatial-frequency content. As a result, in SPOF PIV processing, particle-displacement correlation peaks can readily be detected above spurious background peaks, without need for masking or background subtraction.
The area of the Asian summer monsoon anticyclone (ASMA), as defined by contours of Montgomery stream function (MSF) on isentropic surfaces, has been increasing over at least the last four decades. Here we analyze the relationship of the trend in ASMA area to trends in dynamical diagnostics in the ASM region, both inside and outside the ASMA, for 1979 through 2020 in the MERRA-2, JRA-55, and ERA5 reanalyses. Trends in geopotential height (GPH) and temperature (from which MSF is calculated) indicate that MSF increases are dominated by increasing temperature (GPH) at levels that are primarily in the troposphere (stratosphere). Trends in MSF, GPH, and temperature are much less clear within the ASMA circulation than those for the entire ASM region, suggesting that other mechanisms, besides the direct effects of increasing tropospheric temperatures, are at play. To further explore these results, we present trends in lapse rate and dynamical tropopause altitudes, easterly and westerly windspeeds bounding the ASMA, and potential vorticity. Overall, weak or inconsistent trends inside the ASMA in most diagnostics likely arise from a complex interplay of mechanisms in this region (which spans tropospheric/stratospheric and tropical/midlatitude conditions), and suggest that the previously reported area trends do not necessarily indicate an increase in “intensity" of the ASMA. In regions both with and without robust trends in dynamical diagnostics, trend results are typically consistent between the three reanalyses studied even when there are biases in the magnitudes of those diagnostics. This generally good agreement indicates that these reanalyses are suitable for more detailed studies needed to fully understand the mechanisms for trends in the ASMA.
The Mission Simulation Facility (MSF) supports research in autonomy technology for planetary exploration vehicles. Using HLA (High Level Architecture) across distributed computers, the MSF connects users autonomy algorithms with provided or third-party simulations of robotic vehicles and planetary surface environments, including onboard components and scientific instruments. Simulation fidelity is variable to meet changing needs as autonomy technology advances in Technical Readiness Level (TRL). A virtual robot operating in a virtual environment offers numerous advantages over actual hardware, including availability, simplicity, and risk mitigation. The MSF is in use by researchers at NASA Ames Research Center (ARC) and has demonstrated basic functionality. Continuing work will support the needs of a broader user base.
An achromatic optical correlator using spatially multiplexed achromatic matched spatial filters (MSFs) for white light optical pattern recognition is presented. The MSF array is synthesizd using a monochromatic laser and its achromaticity is achieved by adjusting the scale and spatial carrier frequency of each MSF to accommodate the wavelength variations in white light correlation detections. Systems analysis and several experimental results showing the correlation peak intensity using white-light illumination are presented.
Autonomy is a key factor in remote robotic exploration and there is significant activity addressing the application of autonomy to remote robots. It has become increasingly important to have simulation tools available to test the autonomy algorithms. While indus1;rial robotics benefits from a variety of high quality simulation tools, researchers developing autonomous software are still dependent primarily on block-world simulations. The Mission Simulation Facility I(MSF) project addresses this shortcoming with a simulation toolkit that will enable developers of autonomous control systems to test their system s performance against a set of integrated, standardized simulations of NASA mission scenarios. MSF provides a distributed architecture that connects the autonomous system to a set of simulated components replacing the robot hardware and its environment.
Some impact-melt glasses in shergottite meteorites contain large abundances of martian atmospheric noble gases with high (129)Xe/(132)Xe ratios, accompanied by varying (87)Sr/(86)Sr (initial) ratios. These glasses contain Martian Soil Fines (MSF) probably from young volcanic terrains such as Tharsis or Elysium Mons. The composition of the MSF bearing samples is different from the average bulk composition of the host rock. These samples show the following charecteristics: a) simultaeneous enrichment of the felsic component and depletion of the mafic component relative to the host phase and b) significant secondary sulfur/sulfate excesses over the host material. The degree of enrichment and associated depletion varies from one sample to another. Earlier, we found large enrichments of felsic (Al, Ca, Na and K) component and depletion of mafic (Fe, Mg, Mn and Ti) component in several impact melt glass veins and pods of samples ,77 ,78 , 18, and ,20A in EET79001 accompanied by large sulfur/sulfate excesses. Based on these results, we proposed a model where the comminution of basaltic rocks takes place by meteoroid bombardment on the martian surface, leading to the generation of fine-grained soil near the impact sites. This fine-grained soil material is subsequently mobilized by saltation and deflation processes on Mars surface due to pervasive aeolian activity. This movement results in mechanical fractionation leading to the felsic enrichment and mafic depletion in the martian dust. We report, here, new data on an impact-melt inclusion ,507 (PAPA) from EET79001, Lith B and ,506 (ALPHA) from EET79001, Lith A and compare the results with those obtained on Shergotty impact melt glass (DBS).
Impact-melt glasses, rich in Martian atmospheric gases, contain Martian soil fines (MSF) mixed with other coarse-grained regolith fractions which are produced during impact bombardment on Mars surface. An important characteristic of the MSF fraction is the simultaneous enrichment of felsic component accompanied by the depletion of mafic component relative to the host phase in these glasses. In addition, these glasses yield large sulfur abundances due to the occurrence of secondary mineral phases such as sulfates produced during acid-sulfate weathering of the regolith material near the Martian surface. Sulfurous gases released into atmosphere by volcanoes on Mars are oxidized to H2SO4 which deposit back on the surface of Mars as aerosol particles. Depending on the water availability, sulfuric acids dissolve into solutions which aggressively decompose the Fe-Mg silicates in the Martian regolith. During chemical weathering, structural elements such as Fe, Mg and Ca (among others) are released into the transgressing solutions. These solutions leach away the soluble components of Mg, Ca and Na, leaving behind insoluble iron as Fe3(+) hydroxysulfate mixed with poorly crystalline hydroxide- precipitates under oxidizing conditions. In this study, we focus on the elemental distribution of FeO and SO3 in the glass veins of EET79001, 507 sample, determined by Electron Microprobe and FE SEM measurements at JSC. This glass sample is an aliquot of a bigger glass inclusion ,104 analysed by where large concentrations of Martian atmospheric noble gases are found.
The Mission Simulation Toolkit (MST) is a flexible software system for autonomy research. It was developed as part of the Mission Simulation Facility (MSF) project that was started in 2001 to facilitate the development of autonomous planetary robotic missions. Autonomy is a key enabling factor for robotic exploration. There has been a large gap between autonomy software (at the research level), and software that is ready for insertion into near-term space missions. The MST bridges this gap by providing a simulation framework and a suite of tools for supporting research and maturation of autonomy. MST uses a distributed framework based on the High Level Architecture (HLA) standard. A key feature of the MST framework is the ability to plug in new models to replace existing ones with the same services. This enables significant simulation flexibility, particularly the mixing and control of fidelity level. In addition, the MST provides automatic code generation from robot interfaces defined with the Unified Modeling Language (UML), methods for maintaining synchronization across distributed simulation systems, XML-based robot description, and an environment server. Finally, the MSF supports a number of third-party products including dynamic models and terrain databases. Although the communication objects and some of the simulation components that are provided with this toolkit are specifically designed for terrestrial surface rovers, the MST can be applied to any other domain, such as aerial, aquatic, or space.
NASA has increasingly relied on high-performance computing (HPC) re- sources for computational modeling, simulation, and data analysis to meet the science and engineering goals of its missions in space exploration, aeronautics, and Earth and space science. The NASA Advanced Supercomputing (NAS) Division at Ames Research Center in Silicon Valley, Calif., hosts NASA’s premier supercomputing resources, integral to achieving and enhancing the success of the agency’s missions. NAS provides a balanced environment, funded under the High-End Computing Capability (HECC) project, comprised of world-class supercomputers, including its flagship distributed-memory cluster, Pleiades; high-speed networking; and massive data storage facilities, along with multi-disciplinary support teams for user support, code porting and optimization, and large-scale data analysis and scientific visualization. However, as scientists have increased the fidelity of their simulations and engineers are conducting larger parameter-space studies, the requirements for supercomputing resources have been growing by leaps and bounds. With the facility housing the HECC systems reaching its power and cooling capacity, NAS undertook a prototype project to investigate an alternative approach for housing supercomputers. Modular supercomputing, or container-based computing, is an innovative concept for expanding NASA’s HPC capabilities. With modular supercomputing, additional containers—similar to portable storage pods—can be connected together as needed to accommodate the agency’s ever-increasing demand for computing resources. In addition, taking advantage of the local weather permits the use of cooling technologies that would additionally save energy and reduce annual water usage. The first stage of NASA’s Modular Supercomputing Facility (MSF) prototype, which resulted in a 1,000 square-foot module on a concrete pad with room for 16 compute racks, was completed in Fall 2016 and an SGI (now HPE) computer system, named Electra, was deployed there in early 2017. Cooling is performed via an evaporative system built into the module, and preliminary experience shows a Power Usage Effectiveness (PUE) measurement of 1.03. Electra achieved over a petaflop on the LINPACK benchmark, sufficient to rank number 96 on the November 2016 TOP500 list [14]. The system consists of 1,152 InfiniBand-connected Intel Xeon Broadwell-based nodes. Its users access their files on a facility-wide file system shared by all HECC compute assets via Mellanox MetroX InfiniBand extenders, which connect the Electra fabric to Lustre routers in the primary facility over fiber-optic links about 900 feet long. The MSF prototype has exceeded expectations and is serving as a blueprint for future expansions. In the remainder of this chapter, we detail how modular data center technology can be used to expand an existing compute resource. We begin by describing NASA’s requirements for supercomputing and how resources were provided prior to the integration of the Electra module-based system.
The basic requirements for a standard test and checkout language applicable to all phases of the space shuttle test and ground operations are determined. The general characteristics outlined here represent the integration of selected ideas and concepts from operational elements within Kennedy Space Center (KSC) that represent diverse disciplines associated with space vehicle testing and launching operations. Special reference is made to two studies conducted in this area for KSC as authorized by the Advanced Development Element of the Office of Manned Space Flight (MSF). Information contained in reports from these studies have contributed significantly to the final selection of language features depicted in this technical report.
Pulsed laser sheet velocimetry yields nonintrusive measurements of velocity vectors across an extended 2-dimensional region of the flow field. The application of optical correlation techniques to the analysis of multiple exposure laser light sheet photographs can reduce and/or simplify the data reduction time and hardware. Here, Matched Spatial Filters (MSF) are used in a pattern recognition system. Usually MSFs are used to identify the assembly line parts. In this application, the MSFs are used to identify the iso-velocity vector contours in the flow. The patterns to be recognized are the recorded particle images in a pulsed laser light sheet photograph. Measurement of the direction of the partical image displacements between exposures yields the velocity vector. The particle image exposure sequence is designed such that the velocity vector direction is determined unambiguously. A global analysis technique is used in comparison to the more common particle tracking algorithms and Young's fringe analysis technique.
Pulsed laser sheet velocimetry yields noninstrusive measurements of velocity vectors across an extended 2-dimensional region of the flow field. The application of optical correlation techniques to the analysis of multiple exposure laser light sheet photographs can reduce and/or simplify the data reduction time and hardware. Here, Matched Spatial Filters (MSF) are used in a pattern recognition system. Usuallay MSFs are used to identify the assembly line parts. In this application, the MSFs are used to identify the iso-velocity vector contours in the flow. The patterns to be recognized are the recorded particle images in a pulsed laser light sheet photograph. Measurement of the direction of the particle image displacements between exposures yields the velocity vector. The particle image exposure sequence is designed such that the velocity vector direction is determined unambiguously. A global analysis technique is used in comparison to the more common particle tracking algorithms and Young's fringe analysis technique.
A spaceflight-compatible flow cytometer would be useful for the diagnosis of astronaut illness during long duration spaceflight and for conducting in-flight research to evaluate the effects of microgravity on human physiology. Until recently, the primary limitations preventing the development of a spaceflight compatible flow cytometer have been largely mechanical. Standard commercially available flow cytometers are large, complex instruments that use high-energy lasers and require significant training to operate. Standard flow cytometers function by suspending the particles to be analyzed inside a sheath fluid for analysis. This requires the presence of several liters of sheath fluid for operation, and generates a corresponding amount of liquid hazardous waste. The particles are then passed through a flow cell which uses the fluid mechanical property of hydrodynamic focusing to place the cells in single-file (laminar flow) as they pass through a laser beam for scanning and evaluation. Many spaceflight experiments have demonstrated that fluid physics is dramatically altered in microgravity (MSF [Manned Space Flight] Fluid Physics Data Sheet-August 1997) and previous studies have shown that sheath-fluid based hydrodynamic focusing may also be altered during microgravity (Crucian et al, 2000). For these reasons it is likely that any spaceflight compatible design for a flow cytometer would abandon the sheath fluid requirement. The elimination of sheath fluid would remove both the problems of weight associated with large volumes of liquids as well as the large volume of liquid waste generated. It would also create the need for a method to create laminar particle flow distinct from the standard sheath-fluid based method. The spaceflight prototype instrument is based on a recently developed commercial flow cytometer possessing a novel flow cell design that creates single-particle laser scanning and evaluation without the need for sheath-fluid based hydrodynamic focusing. This instrument also possesses a number of design advances that make it conditionally microgravity compatible: it is highly miniaturized and lightweight, uses a low energy diode laser, has a small number of moving parts, does not use sheath fluid and does not generate significant liquid waste. Although possessing certain limitations, the commercial cytometer functions operationally like a standard bench top laboratory flow cytometer, aspirating liquid particle samples and generating histogram or dot-plot data in standard FCS file format. In its current configuration however, the cytometer is limited to three parameter/two-color capability (two color PMTs + forward scatter), does not allow compensation between colors, does not allow linear analysis and is operated by rather inflexible software with limited capabilities. This is due to the fact that the cytometer has been designed and marketed as an instrument specific to a few particular assays, not as a multipurpose cytometer.
In the Technology 2006 Case Studies/Success Stories presentation, we will describe and demonstrate a prototype of a compact optical pattern recognition system as an example of a successful technology transfer and continuuing development of state-of-the-art know-how by the close collaboration among government, academia, and small business via the NASA SBIR program. The prototype consists of a complete set of optical pattern recognition hardware with multi-channel storage and retrieval capability that is compactly configured inside a portable 1'X 2'X 3' aluminum case.