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At least 343 records · Page 19

The X-43A Flush Airdata Sensing System Flight Test Results

The National Aeronautics and Space Administration (NASA) has flight-tested a flush airdata sensing (FADS) system on the Hyper-X Research Vehicle (X-43A) at hypersonic speeds during the course of two successful flights. For this series of tests, the FADS system was calibrated to operate between Mach 3 and Mach 8, and flight test data was collected between Mach 1 and Mach 10. The FADS system acquired pressure data from surface-mounted ports and generated a real-time angle-of-attack (alpha) estimate on board the X-43A. The collected data were primarily intended to evaluate the FADS system performance, and the estimated alpha was used by the flight control algorithms on the X-43A for only a portion of the first successful flight. This paper provides an overview of the FADS system and alpha estimation algorithms, presents the in-flight alpha estimation algorithm performance, and provides comparisons to wind tunnel results and theory. Results indicate that the FADS system adequately estimated the alpha of the vehicle during the hypersonic portions of the two flights.

Baumann, Ethan↗

A Photographic Atlas of Rock Breakdown Features in Geomorphic Environments

A primary goal of geomorphological enquiry is to make genetic associations between process and form. In rock breakdown studies, the links between process, inheritance and lithology are not well constrained. In particular, there is a need to establish an understanding of feature persistence. That is, to determine the extent to which in situ rock breakdown (e.g., aeolian abrasion or salt weathering) masks signatures of earlier geomorphic transport processes (e.g., fluvial transport or crater ejecta). Equally important is the extent to which breakdown during geomorphic transport masks the imprint of past weathering. The use of rock features in this way raises the important question: Can features on the surface of a rock reliably indicate its geomorphic history? This has not been determined for rock surfaces on Earth or other planets. A first step towards constraining the links between process, inheritance, and morphology is to identify pristine features produced by different process regimes. The purpose of this atlas is to provide a comprehensive image collection of breakdown features commonly observed on boulders in different geomorphic environments. The atlas is intended as a tool for planetary geoscientists and their students to assist in identifying features found on rocks on planetary surfaces. In compiling this atlas, we have attempted to include features that have formed 'recently' and where the potential for modification by another geomorphic process is low. However, we acknowledge that this is, in fact, difficult to achieve when selecting rocks in their natural environment. We group breakdown features according to their formative environment and process. In selecting images for inclusion in the atlas we were mindful to cover a wide range of climatic zones. For example, in the weathering chapter, clast features are shown from locations such as the hyper-arid polar desert of Antarctica and the semi-arid canyons of central Australia. This is important as some features (e.g., alveoli) occur across climate regimes. We have drawn on the published geomorphological literature and our own field experience. We use, where possible, images of extrusive igneous rocks as the data returned from Mars, Venus and the Moon indicates that this is the predominant rock type. One of the purposes of this atlas is to expand the range of surface features that are known to indicate a particular geomorphic environment or process history. The surface features on boulders in some environments such as aeolian and weathering are well understood. In contrast, those in fluvial or ejecta environments are not. Therefore we have presented a comprehensive assemblage of features that are likely to be produced in each of the geomorphic environments. We hope that this atlas will trigger more research on diagnostic features, particularly their morphometry and detailed morphology, their persistence and rates of formation. In this first edition of the atlas we detail the features found on clasts in three geomorphic environments: aeolian, fluvial and weathering. Future editions of the atlas will include chapters on ejecta, micro-impacts, coastal, colluvial, glacial and structural features.

Bourke, Mary C.↗

Multidisciplinary Design, Analysis, and Optimization Tool Development using a Genetic Algorithm

Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space A dministration Dryden Flight Research Center to automate analysis and design process by leveraging existing tools such as NASTRAN, ZAERO a nd CFD codes to enable true multidisciplinary optimization in the pr eliminary design stage of subsonic, transonic, supersonic, and hypers onic aircraft. This is a promising technology, but faces many challe nges in large-scale, real-world application. This paper describes cur rent approaches, recent results, and challenges for MDAO as demonstr ated by our experience with the Ikhana fire pod design.

Pak, Chan-gi↗

Flight Test Determined Aerodynamics Force and Moment Characteristics of the X-43A Research Vehicle at Mach 7.0

The second flight of the HYPER-X Program afforded a unique opportunity to determine the aerodynamic force and moment characteristics of an airframe integrated scramjet powered aircraft in hypersonic flight. These data were gathered via a repeated series of pitch, yaw, and roll doublets, frequency sweeps, and pull-up/push-over maneuvers performed throughout the X-43A cowl-closed descent phase. The subject flight research maneuvers were conducted in a Mach number range of 6.8 to 0.95 at altitudes from 92,000 ft to sea level. In this flight regime, the dynamic pressure varied from 1300 psf to 400 psf with angle-of-attack ranging from 0 deg to 14 deg. The flight-extracted aerodynamics were compared with pre-flight predictions based on wind tunnel test data. The X-43A flight-derived axial force was found to be 10 to 15 percent higher than prediction. Under-predictions of similar magnitude were observed for the normal force. For Mach numbers greater than 4, the X-43A flight-derived stability and control characteristics resulted in larger than predicted static margins, with the largest discrepancy approximately 5-inches forward along the X(CG) at Mach 6. This would result in less static margin in pitch. The X-43A predicted lateral-directional stability and control characteristics matched well with flight data when allowance was made for the high uncertainty in angle-of-sideslip.

Davis, Mark C.↗

Heating Augmentation for Short Hypersonic Protuberances

Computational aeroheating analyses of the Space Shuttle Orbiter plug repair models are validated against data collected in the Calspan University of Buffalo Research Center (CUBRC) 48 inch shock tunnel. The comparison shows that the average difference between computed heat transfer results and the data is about 9:5%. Using CFD and Wind Tunnel (WT) data, an empirical correlation for estimating heating augmentation on short hyper- sonic protuberances (k/delta < 0.33) is proposed. This proposed correlation is compared with several computed flight simulation cases and good agreement is achieved. Accordingly, this correlation is proposed for further investigation on other short hypersonic protuberances for estimating heating augmentation.

Mazaheri, Alireza R.↗

Super-convergence of Discontinuous Galerkin Method Applied to the Navier-Stokes Equations

The practical benefits of the hyper-accuracy properties of the discontinuous Galerkin method are examined. In particular, we demonstrate that some flow attributes exhibit super-convergence even in the absence of any post-processing technique. Theoretical analysis suggest that flow features that are dominated by global propagation speeds and decay or growth rates should be super-convergent. Several discrete forms of the discontinuous Galerkin method are applied to the simulation of unsteady viscous flow over a two-dimensional cylinder. Convergence of the period of the naturally occurring oscillation is examined and shown to converge at 2p+1, where p is the polynomial degree of the discontinuous Galerkin basis. Comparisons are made between the different discretizations and with theoretical analysis.

Atkins, Harold L.↗

Long Duration Hot Hydrogen Exposure of Nuclear Thermal Rocket Materials

An arc-heater driven hyper-thermal convective environments simulator was recently developed and commissioned for long duration hot hydrogen exposure of nuclear thermal rocket materials. This newly established non-nuclear testing capability uses a high-power, multi-gas, wall-stabilized constricted arc-heater to .produce high-temperature pressurized hydrogen flows representative of nuclear reactor core environments, excepting radiation effects, and is intended to serve as a low cost test facility for the purpose of investigating and characterizing candidate fuel/structural materials and improving associated processing/fabrication techniques. Design and engineering development efforts are fully summarized, and facility operating characteristics are reported as determined from a series of baseline performance mapping runs and long duration capability demonstration tests.

Litchford, Ron J.↗

Possible Deficiencies in Predicting Transonic Aerodynamics on the X-43A

The initial X-43A flight test, June 2, 2001, resulted in a mishap and loss of the vehicle. A mishap investigation board (MIB) report and findings, including the established root cause, were publicly released on July, 23, 2003. The X-43A Flight 1 Hyper-X Launch Vehicle (HXLV) failed because the vehicle control system design was deficient for the trajectory flown due to inaccurate analytical models (Pegasus heritage and HXLV specific), which overestimated the (control) system margin ? X-43A Mishap Investigation Report, Vol. I. ? included as Reference 1. Several specific errors were noted, 1) HXLV aerodynamics ? failure to model changes to wing, fin and rudder airfoil shapes due to addition of thermal protection system (TPS); 2) Fin actuation system (FAS) modeling ? under prediction of the control surface hinge moments and FAS compliance; and 3) Parametric uncertainties ? insufficient variation in the aerodynamic, FAS and control system models. In response to the MIB findings, the X-43A program has been working RTF through an approved Corrective Action Plan (CAP) over the last two years.

Labbe, Steven G.↗

Adjoint-Based Diagnostics in Atmospheric Data Assimilation

With the adjoint of a data assimilation system, the impact of any or all assimilated observations on measures of forecast or analysis skill can be estimated accurately and efficiently. The approach is especially well-suited for assessing the impact of hyper-spectral satellite instruments on numerical weather forecasts because it easily allows aggregation of results in terms of individual data types, channels or locations, all computed simultaneously based on a single pass of the Adjoint- system. This talk 'provides a general overview of the use of Adjoint-based diagnostic tools in data assimilation. We will focus on the theoretical basis and practical implementation of these tools, as well as their application to specific problems. Adjoint-based Impact calculations will be compared with results from standard observing system experiments (OSEs) and their application to related problems, such as the calibration of Observing System Simulation Experiments (OSSEs) will be discussed.

Gelaro, Ronald↗

Automated Knowledge Discovery From Simulators

A computational method, SimLearn, has been devised to facilitate efficient knowledge discovery from simulators. Simulators are complex computer programs used in science and engineering to model diverse phenomena such as fluid flow, gravitational interactions, coupled mechanical systems, and nuclear, chemical, and biological processes. SimLearn uses active-learning techniques to efficiently address the "landscape characterization problem." In particular, SimLearn tries to determine which regions in "input space" lead to a given output from the simulator, where "input space" refers to an abstraction of all the variables going into the simulator, e.g., initial conditions, parameters, and interaction equations. Landscape characterization can be viewed as an attempt to invert the forward mapping of the simulator and recover the inputs that produce a particular output. Given that a single simulation run can take days or weeks to complete even on a large computing cluster, SimLearn attempts to reduce costs by reducing the number of simulations needed to effect discoveries. Unlike conventional data-mining methods that are applied to static predefined datasets, SimLearn involves an iterative process in which a most informative dataset is constructed dynamically by using the simulator as an oracle. On each iteration, the algorithm models the knowledge it has gained through previous simulation trials and then chooses which simulation trials to run next. Running these trials through the simulator produces new data in the form of input-output pairs. The overall process is embodied in an algorithm that combines support vector machines (SVMs) with active learning. SVMs use learning from examples (the examples are the input-output pairs generated by running the simulator) and a principle called maximum margin to derive predictors that generalize well to new inputs. In SimLearn, the SVM plays the role of modeling the knowledge that has been gained through previous simulation trials. Active learning is used to determine which new input points would be most informative if their output were known. The selected input points are run through the simulator to generate new information that can be used to refine the SVM. The process is then repeated. SimLearn carefully balances exploration (semi-randomly searching around the input space) versus exploitation (using the current state of knowledge to conduct a tightly focused search). During each iteration, SimLearn uses not one, but an ensemble of SVMs. Each SVM in the ensemble is characterized by different hyper-parameters that control various aspects of the learned predictor - for example, whether the predictor is constrained to be very smooth (nearby points in input space lead to similar output predictions) or whether the predictor is allowed to be "bumpy." The various SVMs will have different preferences about which input points they would like to run through the simulator next. SimLearn includes a formal mechanism for balancing the ensemble SVM preferences so that a single choice can be made for the next set of trials.

Burl, Michael↗

Online Remote Sensing Interface

BasinTools Module 1 processes remotely sensed raster data, including multi- and hyper-spectral data products, via a Web site with no downloads and no plug-ins required. The interface provides standardized algorithms designed so that a user with little or no remote-sensing experience can use the site. This Web-based approach reduces the amount of software, hardware, and computing power necessary to perform the specified analyses. Access to imagery and derived products is enterprise-level and controlled. Because the user never takes possession of the imagery, the licensing of the data is greatly simplified. BasinTools takes the "just-in-time" inventory control model from commercial manufacturing and applies it to remotely-sensed data. Products are created and delivered on-the-fly with no human intervention, even for casual users. Well-defined procedures can be combined in different ways to extend verified and validated methods in order to derive new remote-sensing products, which improves efficiency in any well-defined geospatial domain. Remote-sensing products produced in BasinTools are self-documenting, allowing procedures to be independently verified or peer-reviewed. The software can be used enterprise-wide to conduct low-level remote sensing, viewing, sharing, and manipulating of image data without the need for desktop applications.

Lawhead, Joel↗

Generating Code Review Documentation for Auto-Generated Mission-Critical Software

Model-based design and automated code generation are increasingly used at NASA to produce actual flight code, particularly in the Guidance, Navigation, and Control domain. However, since code generators are typically not qualified, there is no guarantee that their output is correct, and consequently auto-generated code still needs to be fully tested and certified. We have thus developed AUTOCERT, a generator-independent plug-in that supports the certification of auto-generated code. AUTOCERT takes a set of mission safety requirements, and formally verifies that the autogenerated code satisfies these requirements. It generates a natural language report that explains why and how the code complies with the specified requirements. The report is hyper-linked to both the program and the verification conditions and thus provides a high-level structured argument containing tracing information for use in code reviews.

Denney, Ewen↗

A Cloud Hydrology and Albedo Synthesis Mission (CHASM)

This slide presentation reviews the Cloud Hydrology and Albedo Synthesis Mission (CHASM). The interaction of clouds with radiation and the hydrological cycle represents a huge uncertainty in our understanding of climate science and the modeling of climate system feedbacks. Despite the recognized need for a unified treatment of cloud processes, the present global average values of remotely sensed cloud liquid water and theoretically accepted values used for cloud physics and precipitation modeling differ by an order of magnitude. This is due in part to sampling and saturation effects, as well as to threedimensional cloud structure effects. In recent work with the Multiangle Imaging SpectroRadiometer (MISR) on Terra, we have gained new insights as to how the remote sensing approach could be significantly improved using a new instrument that combines passive optical (visible and near infrared) and microwave measurements, both as pushbroom scanners with multiple viewing angles, to the degree that measurements of liquid water path over deep convective clouds over land also become possible. This instrument would also have the ability of measuring height-resolved cloud-tracked winds using a hyper stereo retrieval technique. Deployment into a precessing low earth orbit would be optimal for measuring diurnal cloud activity. We have explored an instrument design concept for this that looks promising if we can establish partnerships that provide launch and bus capabilities.

hydrology↗

The Lagrange Points in a Binary Black Hole System: Applications to Electromagnetic Signatures

We study the stability and evolution of the Lagrange points L_4 and L-5 in a black hole (BH) binary system, including gravitational radiation. We find that gas and stars can be shepherded in with the BH system until the final moments before merger, providing the fuel for a bright electromagnetic counterpart to a gravitational wave signal. Other astrophysical signatures include the ejection of hyper-velocity stars, gravitational collapse of globular clusters, and the periodic shift of narrow emission lines in AGN.

Schnittman, Jeremy↗

Visible and Near-IR Reflectance Spectra of Mars Analogue Materials Under Arid Conditions for Interpretation of Martian Surface Mineralogy

Visible and near-IR (VNIR) spectra from the hyper-spectral imagers MRO-CRISM and Mars Express OMEGA in martian orbit have signatures from Fe-bearing phases (e.g., olivine, pyroxene, and jarosite), H2O/OH-bearing phases (e.g., smectites and other phyllosilicates, sulfates, and high-SiO2 phases), and carbonate [e.g., 1-5]. Mineralogical assignments of martian spectral features are made on the basis of VNIR spectra acquired in the laboratory under appropriate environmental conditions on samples whose mineralogical composition is known. We report here additional results for our ongoing project [6] to acquire VNIR spectra under arid conditions.

Morris, R. V.↗

Assessing the Impact of Advanced Satellite Observations in the NASA GEOS-5 Forecast System Using the Adjoint Method

The adjoint of a data assimilation system provides a flexible and efficient tool for estimating observation impacts on short-range weather forecasts. The impacts of any or all observations can be estimated simultaneously based on a single execution of the adjoint system. The results can be easily aggregated according to data type, location, channel, etc., making this technique especially attractive for examining the impacts of new hyper-spectral satellite instruments and for conducting regular, even near-real time, monitoring of the entire observing system. In this talk, we present results from the adjoint-based observation impact monitoring tool in NASA's GEOS-5 global atmospheric data assimilation and forecast system. The tool has been running in various off-line configurations for some time, and is scheduled to run as a regular part of the real-time forecast suite beginning in autumn 20 I O. We focus on the impacts of the newest components of the satellite observing system, including AIRS, IASI and GPS. For AIRS and IASI, it is shown that the vast majority of the channels assimilated have systematic positive impacts (of varying magnitudes), although some channels degrade the forecast. Of the latter, most are moisture-sensitive or near-surface channels. The impact of GPS observations in the southern hemisphere is found to be a considerable overall benefit to the system. In addition, the spatial variability of observation impacts reveals coherent patterns of positive and negative impacts that may point to deficiencies in the use of certain observations over, for example, specific surface types. When performed in conjunction with selected observing system experiments (OSEs), the adjoint results reveal both redundancies and dependencies between observing system impacts as observations are added or removed from the assimilation system. Understanding these dependencies appears to pose a major challenge for optimizing the use of the current observational network and defining requirements for future observing systems.

Gelaro, Ron↗

Desert Varnish - Preservation of Biofabrics/Implcations for Mars

Desert varnish is the orange to dark brown rind that accumulates on exposed rock surfaces in many arid environments. Samples from the Sonoran Desert of Arizona are composed predominantly of clays (illite, smectite) and Mn- and Fe- oxides (birnessite, hematite). Features that appear to be single organisms are found within the varnish and at the rock-varnish interface. Many of these features are embedded in films that strongly resemble the water-rich extracellular polysaccharides produced by diverse microorganisms. Most common are rod-shaped celllike objects, 0.5-2 microns in the longest dimension, located within the varnish coatings. Some of these objects are shown to contain amines by fluorescence microscopy. The rod-shaped objects are observed in various states of degradation, as indicated by C and S abundances. Rods with higher C and S abundances appear less degraded than those with lower concentrations of these two elements. Regions rich in apparent microbes are present, while other regions display Mn- and Fe-rich mineral fabrics with microbe-sized voids and no obvious cells. These textures are interpreted as biofabrics, preserved by the precipitation of Mn and Fe minerals. We are researching the preservation of biofabrics by desert varnish in Earth's geological record. Rock coatings may similarly preserve evidence of microbial life on the hyper-arid surface of Mars.

Probst, Luke W.↗

Markov Chain Monte Carlo Bayesian Learning for Neural Networks

Conventional training methods for neural networks involve starting al a random location in the solution space of the network weights, navigating an error hyper surface to reach a minimum, and sometime stochastic based techniques (e.g., genetic algorithms) to avoid entrapment in a local minimum. It is further typically necessary to preprocess the data (e.g., normalization) to keep the training algorithm on course. Conversely, Bayesian based learning is an epistemological approach concerned with formally updating the plausibility of competing candidate hypotheses thereby obtaining a posterior distribution for the network weights conditioned on the available data and a prior distribution. In this paper, we developed a powerful methodology for estimating the full residual uncertainty in network weights and therefore network predictions by using a modified Jeffery's prior combined with a Metropolis Markov Chain Monte Carlo method.

Goodrich, Michael S.↗