CCSDS application profiles for the Mars environment
An application profile addresses the five layers of the CCSDS protocol stack applicable to space missions: physical, data link, network, transport, and application.
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An application profile addresses the five layers of the CCSDS protocol stack applicable to space missions: physical, data link, network, transport, and application.
An application profile addresses the five layers of the CCSDS protocol stacking applicable to space missions: physical, data link, network, transport, and application.
Described herein is a method and system for training nonlinear adaptive filters (or neural networks) which have embedded memory. Such memory can arise in a multi-layer finite impulse response (FIR) architecture, or an infinite impulse response (IIR) architecture. We focus on filter architectures with separate linear dynamic components and static nonlinear components. Such filters can be structured so as to restrict their degrees of computational freedom based on a priori knowledge about the dynamic operation to be emulated. The method is detailed for an FIR architecture which consists of linear FIR filters together with nonlinear generalized single layer subnets. For the IIR case, we extend the methodology to a general nonlinear architecture which uses feedback. For these dynamic architectures, we describe how one can apply optimization techniques which make updates closer to the Newton direction than those of a steepest descent method, such as backpropagation. We detail a novel adaptive modified Gauss-Newton optimization technique, which uses an adaptive learning rate to determine both the magnitude and direction of update steps. For a wide range of adaptive filtering applications, the new training algorithm converges faster and to a smaller value of cost than both steepest-descent methods such as backpropagation-through-time, and standard quasi-Newton methods. We apply the algorithm to modeling the inverse of a nonlinear dynamic tracking system 5, as well as a nonlinear amplifier 6.
The high performance computing (HPC) community has shown tremendous interest in exploring cloud computing as it promises high potential. In this paper, we examine the feasibility, performance, and scalability of production quality scientific and engineering applications of interest to NASA on NASA's cloud computing platform, called Nebula, hosted at Ames Research Center. This work represents the comprehensive evaluation of Nebula using NUTTCP, HPCC, NPB, I/O, and MPI function benchmarks as well as four applications representative of the NASA HPC workload. Specifically, we compare Nebula performance on some of these benchmarks and applications to that of NASA s Pleiades supercomputer, a traditional HPC system. We also investigate the impact of virtIO and jumbo frames on interconnect performance. Overall results indicate that on Nebula (i) virtIO and jumbo frames improve network bandwidth by a factor of 5x, (ii) there is a significant virtualization layer overhead of about 10% to 25%, (iii) write performance is lower by a factor of 25x, (iv) latency for short MPI messages is very high, and (v) overall performance is 15% to 48% lower than that on Pleiades for NASA HPC applications. We also comment on the usability of the cloud platform.
Heightened occurrence of severe wildfires in the Western United States is increasing the need to better understand regions of high potential wildfire severity and develop methodologies for identifying the best locations for fuels reduction and active wildfire suppression, especially in populated regions such as Marin County, California. Marin County, located in the San Francisco Bay Area, has had significant development in the wildland-urban interface and periods of highly wildfire-prone conditions. The NASA DEVELOP team collaborated with Fire Foundry (a Marin-based fire service workforce development program) and the Marin County Fire Department to develop models to assist with fire management. Using data from Sentinel-2A, PlanetScope, ECOSTRESS, a county-wide LiDAR mapping effort, Landsat 7 Enhanced Thematic Mapper (ETM+), and Landsat 8 Operational Land Imager (OLI), our team developed a number of input data layers for three different models to evaluate wildfire severity. One model performed a suitability analysis with weights based on scientific literature; another model utilized a U-Net Convolutional Neural Network trained on previous fires in Marin and neighboring Sonoma County to predict the difference normalized burn severity; and the third inputted data layers into the FlamMap tool that outputs risk categories. We compared model outputs and performed a weighted overlay analysis to identify specific locations where a fireline could be constructed to interrupt the progress of an active fire. These tools will assist partners in preparing for and managing active wildfire situations.
The 1997 Mars Pathfinder mission provided information on a site in the Ares Vallis floodplain. Initial analysis of multispectral data from the Imager for Mars Pathfinder (IMP) indicated the presence of only a single rock type, the 'gray rock' spectral class and various coated variants thereof (e.g., 'maroon rock'). Continued analysis of the IMP 'SuperPan' mosaic has confirmed multiple examples of a second 'black rock' spectral class existing as small cobbles in the near field and as boulders in the far field. These results are consistent with recent analysis of MGS Thermal Emission Spectrometer (TES) data which indicates that there is likely a mix of both 'Surface Type 1' (ST1) and 'Surface Type 2' (ST2) spectral classes at the MPF landing site. Nominally, the black rock spectral class would correspond to ST1 (basalts) and 'gray rock' would correspond to ST2 (andesites). Orbital remote sensing has also revealed the pervasive presence of layering on Mars. Recently it was suggested that there are extensive outcrops of the black rock spectral class in the SuperPan far field on the flanks of the Twin Peaks and on the rim of Big Crater. These authors suggested that these exposures represented outcrops of black rock from beneath a surficial, flood deposited layer. In this work, we have reexamined the MPF IMP SuperPan mosaic using an artificial neural network self organizing map (SOM) processing architecture in order to classify the distribution of spectral classes within the SuperPan. In this paper, we present initial results from that work and draw specific attention to a subset of the identified spectral classes in order to address questions relating to whether there are extensive exposures of black rock in the IMP far field, what other materials might be exposed in the far field, and what evidence there is for subsurface layering at the MPF landing site.
The interfacial structure of silicon/dielectric and silicon/metal systems is particularly amenable to analysis using a combination of surface spectroscopies together with a variety of chemical structures of Si/SiO2, Si/SiO2Si3N4, Si/Si2N2O, Si/SiO2/Al, and Si/Native Oxide interfaces using high resolution (0.350 eV FWHM) X ray photoelectron spectroscopy. The general structure of these dielectric interfaces entails a monolayer chemical transition layer at the Si/dielectric boundary. Amorphous Si substrates show a wide variety of hydrogenated Si and Si(OH) sub x states that are not observed in thermal oxidation of single crystal material. Extended SiO2 layers greater than 8 A in thickness are shown to be stoichiometric SiO2, but to exhibit a wide variety of local network structures. In the nitrogen containing systems, an approach to stoichiometric oxynitride compounds with interesting impurity and electron trapping properties are seen. In native oxides, substantial topographical nonuniformity in oxide thickness and composition are found. Analysis of metal/oxide interfacial layers is accomplished by analytical removal of the Si substrate by UHV XeF2 dry etching methods.
The thermal shock resistance of a ceramic layer is improved. The invention is particularly directed to an improved abradable lining that is deposited on shroud forming a gas path in turbomachinery. Improved thermal shock resistance of a shroud is effected through the deliberate introduction of benign cracks. These are microcracks which will not propagate appreciably upon exposure to the thermal shock environment in which a turbine seal must function. Laser surface fusion treatment is used to introduce these microcracks. The ceramic surface is laser scanned to form a continuous dense layer. As this layer cools and solidifies, shrinkage results in the formation of a very fine crack network. The presence of this deliberately introduced fine crack network precludes the formation of a catastrophic crack during thermal shock exposure.
The integrity of the metal-poly oxide and the gate oxide was evaluated for several 5-micron CMOS-bulk processes. The pinhole array capacitor consists of diffused and poly fingers that form a network of MOS transistors (elements), which are capped by a deposited oxide and metal layer. The smallest structure used in this study contained about 15,000 elements and the largest structure contained about 68,000 elements. Each structure was divided into several subarrays. The structures are placed a number of times on each wafer. From a yield analysis of the subarrays, the elements per defect were found to be typically in excess of 50,000 elements/defect for the metal-poly oxide and 100,000 elements/defect for the gate oxide. From the switching behavior of the transistors, the gate oxide defects were tentatively identified as gate-to-body shorts rather than gate-to-diffusion shorts.
The integrity of the metal-poly oxide and the gate oxide was evaluated for several 5-micron CMOS-bulk process. The pinhole array capacitor consists of diffused and poly fingers that form a network of MOS transistors (elements), which are capped by a deposited oxide and metal layer. The smallest structure used contained about 15,000 elements and the largest structure contained about 68,000 elements. Each structure was divided into several subarrays. The structures are placed a number of times on each wafer. From a yield analysis of the subarrays, the elements per defect were found to be typically in excess of 50,000 elements/defect for the metal-poly oxide and 100,000 elements/defect for the gate oxide. From the switching behavior of the transistors, the gate oxide defects were tentatively identified as gate-to-body shorts rather than gate-to-diffusion shorts.
Like two enormous steam engines, throttles wide-open, bells clanging and whistles screeching, careening toward each other down the same track, two powerful forces are about to collide and the point of collision will be smack in the middle of the white-collar workplace. Moreover, once the dust has settled, it is quite likely that we will never be able to think about the white-collar workplace in quite the same way again. The forces couldn't be more different. One force, the theory of complex adaptive systems, has its roots in the radical new sciences of chaos and complexity. The other force, the notion of organizations being learning systems, more like living organisms than 'information factories,' is an outgrowth of the new management thinking of leading organizational theorists like the Claremont Graduate School's Peter Drucker, MIT's Peter Senge, and Hitotsubashi University's Ikujiro Nonaka. Nevertheless, both the new science and the new management thinking seem to point to a similar and perhaps even startling conclusion: the business organization of the 21st century will look nothing like the bureaucratic organizational model that prevails in most companies today, a model that has remained largely unchanged since the manufacturing heydays of 1950s. While the details of the new organization remain sketchy, its rough outline is already beginning to take shape. Rather than simply being flatter through the elimination of layer upon layer of 'middle management,' the new organization is likely to be made up of networks of specialists who will be, for all practical purposes, self-managing. Rather than focusing on issues like re-engineering business processes, a holdover from Taylorism, the focus will be on supporting the continuous learning of an organization's specialists, the sharing of this learning with other specialists, and the embedding of this learning in the organization's physical structure. Finally, rather than viewing themselves as going through relatively long periods of stability punctuated by shorts bursts of 'reorganization,' business enterprises will come to realize that their very survival depends upon their being in a state of continuous organization. The implications of the new organization with respect to how companies approach the planning, design, and management of the technology infrastructure that enables individual learning, self-management, and continuous orgsnization, are both numerous and far-reaching. As part of this technology infrastructure, the white-collar workplace exists in the form it does today as a direct result of management's beliefs about how time, space, and tools ought to be organized and managed in order to accomplish useful intellectual work. Obviously, if these beliefs change radically, as both the new science and the new management thinking suggest is about to happen, then it is almost inevitable that the form and function of the white-collar workplace will change radically, as well. Will there even be a white-collar workplace in the 21st century, in the sense of purpose-built facilities designed to support the co-location of large numbers of white-collar workers? Only time will tell. However, the leading indicators seem to suggest that, as the old saying goes, 'We ain't seen nothin' yet!'
The Proximity-1 Space Link Interleaved Time Synchronization (PITS) protocol provides time distribution and synchronization services for space systems. A software prototype implementation of the PITS algorithm has been developed that also provides the test harness to evaluate the key functionalities of PITS with simulated data source and sink. PITS integrates time synchronization functionality into the link layer of the CCSDS Proximity-1 Space Link Protocol. The software prototype implements the network packet format, data structures, and transmit- and receive-timestamp function for a time server and a client. The software also simulates the transmit and receive-time stamp exchanges via UDP (User Datagram Protocol) socket between a time server and a time client, and produces relative time offsets and delay estimates.
The fidelity of flux estimates from an atmospheric inversion depends on the ability of atmospheric transport models to simulate the measured quantity. For species such as CO2, with surface fluxes and a large network of surface measurements, this means correctly simulating the dynamics of the planetary boundary layer (PBL), which is one of the most uncertain aspects of atmospheric transport modeling. In contrast, the simulated total column average mole fraction of CO2 (XCO2) is largely insensitive to simulated PBL dynamics. Therefore, measurements of XCO2 provided by current and future short wave infrared (SWIR) greenhouse gas (GHG) satellites such as GOSAT and the OCO family would seem to be more appropriate to flux inversions, as far as minimizing transport model errors (the "noise") is concerned. Unfortunately, the flux-induced variation of CO2 (the "signal") is the largest within the PBL and smallest in XCO2. Therefore, assimilating XCO2 as opposed to PBL CO2 need not give us the strongest "signal to noise" in flux inversions. Recent work on GOSAT and OCO2 retrievals suggest that SWIR satellite spectra may be used to estimate a lower partial column CO2, which could be assimilated in a flux inversion, instead of XCO2.Here we report on a study to assess whether there is an optimal partial column average CO2, intermediate between PBL CO2 and XCO2, whose assimilation might yield the best signal to noise in flux inversions, where (as before) "signal" is the flux-induced variation and "noise" is the error in transport modeling. We simulate atmospheric CO2 with five different global transport models and a common surface CO2 flux over ten years. We consider the spread across the five models to be a proxy for transport model error (the "noise"), and the common variation of CO2 in all five models to be a proxy for the "signal". We compare these signals and noises at different spatiotemporal scales for different partial column specifications to investigate whether there exists an optimal partial column that has large surface flux-driven variations and yet is relatively insensitive to errors in transport models. Finally, we comment on the feasibility of estimating such a partial column from current and future SWIR GHG satellites in the light of recent work on vertically resolved CO2 from current SWIR GHG satellites.
Space-borne soil moisture (SM) satellite products such as those available from Soil Moisture Active Passive (SMAP) offer unique opportunities for global and frequent monitoring of SM and also to understand its spatiotemporal variability. The present study investigates the performance of the SMAP L4 SM product at selected experimental sites across four continents, namely North America, Europe, Asia and Australia. This product provides global scale SM estimates at 9 km × 9 km spatial resolution at daily intervals. For the product evaluation, co-orbital in situ SM measurements were used, acquired at 14 test sites in North America, Europe, and Australia belonging to the International Soil Moisture Network (ISMN) and local networks in India. The satellite SM estimates of up to 0–5 cm soil layer were compared against collocated ground measurements using a series of statistical scores. Overall, the best performance of the SMAP product was found in North America (RMSE = 0.05 m(exp 3)/m(exp 3)) followed by Australia (RMSE = 0.08 m(exp 3)/m(exp 3)), Asia (RMSE = 0.09 m(exp 3)/m(exp 3)) and Europe (RMSE = 0.14 m(exp 3)/m(exp 3)). Our findings provide important insights into the spatiotemporal variability of the specific operational SM product in different ecosystems and environments. This study also furnishes an independent verification of this global product, which is of international interest given its suitability for a wide range of practical and research applications.
Predicting transition locations over a vehicle surface is of fundamental importance for many engineering applications. With the transition information, the Reynolds-averaged Navier-Stokes (RANS) computations can turn on the turbulence model at the right locations so that drag, lift and other aerodynamic quantities can be accurately predicted. In contrast to the popularity of RANS-based transition modeling in which transition onset is governed by the turbulence equations, physics-based transition models that account for instability waves within the boundary layer, thus more compliant to flow physics, only gained more attention in recent years. This paper describes the development of a new physics-based transition model based on either the linear stability theory (LST) or parabolized stability equations (PSE). The model is designed to communicate with a structured or unstructured-mesh RANS solver back and forth in order to more accurately compute transition fronts over a three-dimensional body. In the developed model, the Python suite of interface codes in conjunction with the LASTRAC software can be executed autonomously to produce transition onset locations for a given laminar or RANS-computed transitional state. In addition, as a proof of concept, the tool set consists of a deep learning neural network model that has been designed and trained to predict instability wave evolutions inside the boundary layer for various instability wave mechanisms across a selected speed range. A machine-learned intelligent profile interpolation model has also been devised to enable reliable instability-wave spectra predictions with just a few points in the mean flow profiles.
We present the first network analysis of interplanetary magnetic field (IMF) clock angle dependent, high-latitude, hemispheric-specific total electron content (TEC) data. We examine network parameters to describe spatio-temporal correlations in the TEC data for January 2016. We find that significant network structure exists distinguishing the dayside and nightside ionosphere, and specific features in the high-latitudes (cusp/ionospheric footpoints of magnetospheric boundary layers, polar cap, and auroral zone), and that these features vary with IMF clock angle. In this brief summary paper, we provide proof of concept results and identify important areas of future research, providing a basis for the discussion of network analysis and machine learning approaches for space weather applications.
The relationship between the dispersion and concentration of sediment in the superficial layers of the Tres Marias reservoir and the dynamics of the drainage basins of its tributaries was verified using LANDSAT MSS imagery. The drainage network, dissection patterns, and land use of each watershed were considered in an analysis of multispectral images, corresponding to bands 4,5, and 7, of dry and rainy seasons in 1973, 1975, 1977, and 1978. The superficial layer water layers of the reservoir were also divided according to the grey level pattern of each image. Two field trips were made to collect Secchi depths and in situ water reflectance. It is concluded that it is possible to determine the main factors that act in the dynamics of the drainage basins of a reservoir by simultaneous control of the physical variables and the antropic action of each basin.
As the neutrino fluxes can bring information from the internal layers of the collapsing star, the problem of the neutrino burst detection is of importance for both the direct registering of the collapse itself and the investigation of its dynamics. The main characteristics of the neutrino fluxes have been obtained by simulations. The total neutrino flux energy is estimated as 2.5 x 10 to the 53 to 1.4 x 10 to the 54 erg, the energy of NU sub E flux being 10 to the 53 erg. Predictions on neutrino energy spectra are quite different. Two models of the collapse will be used: the model by Bowers and Wilson, hereafter BW, and the model by Nadyozhin and Otroschenko (NO). The NU sub e spectrum in the BW-model reaches the maximum at E max sub NU = 8 MeV. Average energy of NU sub E E sub nu approx. = 10 MeV. The NO-model gives E max sub Nu = 10.5 MeV and E sub nu = 12.6 MeV. The NU sub E-burst duration is DELTA tau sub NU = 20s for the NO-model. As the black hole formation is the result of the star collapse in the BW-model, DELTA tau sub nu is taken to be 5s.