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New uses found for correlation functions in analyses of spectra. In approach combining elements of both pattern-recognition and traditional spectral-analysis techniques, spectral lines identified in data appear useless at first glance because they are dominated by noise. New approach particularly useful in measurement of concentrations of rare species of molecules in atmosphere.
The purpose of this manual is to document the standard high level command language procedures of the Computational Structural Mechanics (CSM) Testbed software system. A description of each procedure including its function, commands, data interface, and use is presented. This manual is designed to assist users in defining and using command procedures to perform structural analysis in the CSM Testbed User's Manual and the CSM Testbed Data Library Description.
A theory has been developed at the University of Virginia which explains the effects of including an ideal predictor in the forward loop of a linear error-sampled system. It has been shown that the presence of this ideal predictor tends to stabilize the class of systems considered. A prediction controller is merely a system which anticipates a signal or part of a signal before it actually occurs. It is understood that an exact prediction controller is physically unrealizable. However, in systems where the input tends to be repetitive or limited, (i.e., not random) near ideal prediction is possible. In order for the controller to act as a stability compensator, the predictor must be designed in a way that allows it to learn the expected error response of the system. In this way, an unstable system will become stable by including the predicted error in the system transfer function. Previous and current prediction controller include pattern recognition developments and fast-time simulation which are applicable to the analysis of linear sampled data type systems. The use of pattern recognition techniques, along with a template matching scheme, has been proposed as one realizable type of near-ideal prediction. Since many, if not most, systems are repeatedly subjected to similar inputs, it was proposed that an adaptive mechanism be used to 'learn' the correct predicted error response. Once the system has learned the response of all the expected inputs, it is necessary only to recognize the type of input with a template matching mechanism and then to use the correct predicted error to drive the system. Suggested here is an alternate approach to the realization of a near-ideal error prediction controller, one designed using Neural Networks. Neural Networks are good at recognizing patterns such as system responses, and the back-propagation architecture makes use of a template matching scheme. In using this type of error prediction, it is assumed that the system error responses be known for a particular input and modeled plant. These responses are used in the error prediction controller. An analysis was done on the general dynamic behavior that results from including a digital error predictor in a control loop and these were compared to those including the near-ideal Neural Network error predictor. This analysis was done for a second and third order system.
In the present work, we use three-dimensional Direct Numerical Simulation (DNS) of premixed flames in turbulent shear flow to characterize the effect of a mean shear motion on flame surface production. The shear is uniform in the unburnt gas, and simulations are performed for different values of the mean shear rate, S. The data base is then used to estimate and compare the different terms appearing in the Sigma-equation as a function of S. The analysis gives in particular the relative weights f the turbulent flow and mean flow components, a(sub T) and A(sub T), of the flame surface production term. This comparison indicates whether the dominant effects of a mean flow velocity gradient on flame surface area are implicit and scale with the modified turbulent flow parameters, kappa and epsilon, or explicit and scale directly with the rate of deformation.
The real atomic structure of nanocrystals determines unique, key properties of the materials. Determination of the structure presents a challenge due to inherent limitations of standard powder diffraction techniques when applied to nanocrystals. Alternate methodology of the structural analysis of nanocrystals (several nanometers in size) based on Bragg-like scattering and called the "apparent lattice parameter" (alp) is proposed. Application of the alp methodology to examination of the core-shell model of nanocrystals will be presented. The results of application of the alp method to structural analysis of several nanopowders were complemented by those obtained by determination of the Atomic Pair Distribution Function, PDF. Based on synchrotron and neutron diffraction data measured in a large diffraction vector of up to Q = 25 Angstroms(exp -1), the surface stresses in nanocrystalline diamond and SiC were evaluated.
The authors describe and illustrate an integrated trio of software programs for carrying out surface-based analyses of cerebral cortex. The first component of this trio, SureFit (Surface Reconstruction by Filtering and Intensity Transformations), is used primarily for cortical segmentation, volume visualization, surface generation, and the mapping of functional neuroimaging data onto surfaces. The second component, Caret (Computerized Anatomical Reconstruction and Editing Tool Kit), provides a wide range of surface visualization and analysis options as well as capabilities for surface flattening, surface-based deformation, and other surface manipulations. The third component, SuMS (Surface Management System), is a database and associated user interface for surface-related data. It provides for efficient insertion, searching, and extraction of surface and volume data from the database.
Source code level software defect detection has gone from state of the art to a software engineering best practice. Automated code analysis tools streamline many of the aspects of formal code inspections but have the drawback of being difficult to construct and either prone to false positives or severely limited in the set of defects that can be detected. Machine learning technology provides the promise of learning software defects by example, easing construction of detectors and broadening the range of defects that can be found. Pinpointing software defects with the same level of granularity as prominent source code analysis tools distinguishes this research from past efforts, which focused on analyzing software engineering metrics data with granularity limited to that of a particular function rather than a line of code.
Experimental results describing the hydraulic dynamic pump transfer matrix (Yp) for a cavitating J-2X oxidizer turbopump inducer+impeller tested in subscale waterflow are presented. The transfer function is required for integrated vehicle pogo stability analysis as well as optimization of local inducer pumping stability. Dynamic transfer functions across widely varying pump hydrodynamic inlet conditions are extracted from measured data in conjunction with 1D-model based corrections. Derived Dynamic transfer functions are initially interpreted relative to traditional Pogo pump equations. Water-to-liquid oxygen scaling of measured cavitation characteristics are discussed. Comparison of key dynamic transfer matrix terms derived from waterflow testing are made with those implemented in preliminary Ares Upper Stage Pogo stability modeling. Alternate cavitating pump hydraulic dynamic equations are suggested which better reflect frequency dependencies of measured transfer matrices.
Experimental results describing the hydraulic dynamic pump transfer matrix (Yp) for a cavitating J-2X oxidizer turbopump inducer+impeller tested in subscale waterflow are presented. The transfer function is required for integrated vehicle pogo stability analysis as well as optimization of local inducer pumping stability. Dynamic transfer functions across widely varying pump hydrodynamic inlet conditions are extracted from measured data in conjunction with 1D-model based corrections. Derived Dynamic transfer functions are initially interpreted relative to traditional Pogo pump equations. Water-to-liquid oxygen scaling of measured cavitation characteristics are discussed. Comparison of key dynamic transfer matrix terms derived from waterflow testing are made with those implemented in preliminary Ares Upper Stage Pogo stability modeling. Alternate cavitating pump hydraulic dynamic equations are suggested which better reflect frequency dependencies of measured transfer matrices.
Quantifying above-cloud aerosols can help improve the assessment of aerosol intercontinental transport and climate impacts. Large-scale measurements of aerosol above low-level clouds had been generally unexplored until very recently when CALIPSO lidar started to acquire aerosol and cloud profiles in June 2006. Despite CALIPSO s unique capability of measuring above-cloud aerosol optical depth (AOD), such observations are substantially limited in spatial coverage because of the lidar s near-zero swath. We developed an approach that integrates measurements from A-Train satellite sensors (including CALIPSO lidar, OMI, and MODIS) to extend CALIPSO above-cloud AOD observations to substantially larger areas. We first examine relationships between collocated CALIPSO above-cloud AOD and OMI absorbing aerosol index (AI, a qualitative measure of AOD for elevated dust and smoke aerosol) as a function of MODIS cloud optical depth (COD) by using 8-month data in the Saharan dust outflow and southwest African smoke outflow regions. The analysis shows that for a given cloud albedo, above-cloud AOD correlates positively with AI in a linear manner. We then apply the derived relationships with MODIS COD and OMI AI measurements to derive above-cloud AOD over the whole outflow regions. In this talk, we will present spatial and day-to-day variations of the above-cloud AOD and the estimated direct radiative forcing by the above-cloud aerosols.
ROBoT is an on-orbit version of the ground-based Dynamics Skills Trainer (DST) that astronauts use for training on a frequent basis. This software consists of two primary software groups. The first series of components is responsible for displaying the graphical scenes. The remaining components are responsible for simulating the Mobile Servicing System (MSS), the Japanese Experiment Module Remote Manipulator System (JEMRMS), and the H-II Transfer Vehicle (HTV) Free Flyer Robotics Operations. The MSS simulation software includes: Robotic Workstation (RWS) simulation, a simulation of the Space Station Remote Manipulator System (SSRMS), a simulation of the ISS Command and Control System (CCS), and a portion of the Portable Computer System (PCS) software necessary for MSS operations. These components all run under the CentOS4.5 Linux operating system. The JEMRMS simulation software includes real-time, HIL, dynamics, manipulator multi-body dynamics, and a moving object contact model with Tricks discrete time scheduling. The JEMRMS DST will be used as a functional proficiency and skills trainer for flight crews. The HTV Free Flyer Robotics Operations simulation software adds a functional simulation of HTV vehicle controllers, sensors, and data to the MSS simulation software. These components are intended to support HTV ISS visiting vehicle analysis and training. The scene generation software will use DOUG (Dynamic On-orbit Ubiquitous Graphics) to render the graphical scenes. DOUG runs on a laptop running the CentOS4.5 Linux operating system. DOUG is an Open GL-based 3D computer graphics rendering package. It uses pre-built three-dimensional models of on-orbit ISS and space shuttle systems elements, and provides realtime views of various station and shuttle configurations.
We report evidence from epithermal neutron flux observations that show that the Moon's high latitude surfaces are being actively hydrated, dehydrated and rehydrated in a diurnal cycle. The near-surface hydration is indicated by an enhanced suppression of the lunar epithermal neutron leakage flux on the dayside of the dawn terminator on poleward-facing slopes (PFS). At 0600 to 0800 local-time, hydrogen concentrations within the upper 1 meter of PFS are observed to be maximized relative to equivalent equator-facing slopes (EFS). During the lunar day surface hydrogen concentrations diminish towards dusk and then rebuild overnight. Surface hydration is determined by differential comparison of the averaged EFS to PFS epithermal neutron count rates above +/- 75 deg latitude. At dawn the contrast bias towards PFS is consistent with at least 15 to 25 parts-per-million (ppm) hydrogen that dissipates by dusk. We review several lines of evidence derived from temperature and epithermal neutron data by a correlated analysis of observations from the Lunar Reconnaissance Orbiter's (LRO) Lunar Exploration Neutron Detector (LEND) that were mapped as a function of lunar local-time, Lunar Observing Laser Altimeter (LOLA) topography and Diviner (DLRE) surface temperature.
Approaches to optimize the adhesive joint strength between shape memory alloy ribbons and carbon fiber-reinforced epoxy composites were investigated for potential use as either an actuating structure or a dampening composite for structural applications. The interfacial bond strength between nickel-titanium (NiTi) and a polymer matrix composite (PMC) was measured by double lap shear testing as a function of NiTi surface treatment and adhesive material. The effect of NiTi surface treatment on damping was investigated using dynamic mechanical analysis. Lap shear data show that treating the surfaces of NiTi ribbons by light sandblasting and primer application increased the interfacial bond strength by 20 percent over the baseline composite structure. Lap shear data also reveal that out of three different film adhesives investigated, samples bonded with AF 191U and Hysol® 9696U display the highest adhesive joint strengths. Optical microscopy reveals that most samples failed by either cohesive failure within the adhesive or by adhesive failure at either the adhesive/PMC or NiTi/adhesive interface. Adhering NiTi to the PMC did not appear to negatively impact damping performance; however, a more thorough examination into NiTi's role on vibration damping should be investigated.
In space, astronauts are more susceptible to pathogens, viral reactivation and immunosuppression, which poses limits to their health and the mission. Interestingly, during space flight, stress-inducible heat shock proteins (HSP) are robustly induced, and the overexpression of HSPs have been implicated in immune dysregulation, therefore HSPs may be critically involved in regulating immune homeostasis. HSP40/DNAJ1 plays a major role in proper protein translation and folding. Its loss of function has been implicated in susceptibility to microbial infection, while its overexpression has been implicated in autoimmunity, collectively suggesting its complicated, but necessary, role in maintaining immunological function. To determine the role of HSP40 during stress-induced altered gravity conditions, wild-type and Hsp40 mutant Drosophila melanogaster were exposed to ground-based chronic hypergravity conditions, followed by quantitative PCR (qPCR) analysis of immune gene expression. In addition, larval hemocytes were collected to determine the functional output in response to E. coli bioparticle phagocytosis. Preliminary data indicates a required role for Hsp40 in strengthening immune function during stress-induced spaceflight in flies. In short, a critical need to evaluate the relationship between HSPs and immune suppression during space flight is necessary. Since space travel may become available to the general public in the not too distant future, and for the possibility of long-term space missions, a more comprehensive evaluation of the molecules responsible for immune dysfunction observed during space flight is required.
The Subsonic Ultra Green Aircraft Research (SUGAR) Phase III was led by Dr. Rakesh K. Kapania and Dr. Joseph A. Schetz at the Multidisciplinary Analysis and Design Center for Advanced Vehicles, Department of Aerospace and Ocean Engineering, Virginia Tech, Blacksburg VA. The research was performed from December 2014 to December 2015. Three major areas were investigated: Multidisciplinary Design Optimization (MDO) studies of truss braced wing (TBW) and strut braced wing (SBW) vehicles at cruise Mach numbers of 0.7 and 0.8 for a flight mission similar to current market single aisle configurations. The performance and the characteristics of the optimized vehicles were compared to the SUGAR Phase II TBW vehicle. These results were obtained without applying any of the extended transonic aerodynamic and aeroelastic tools that will be discussed later. It was found that the cruise Mach number has a large effect on the best “truss” configuration. At Mach 0.7, an SBW has a better fuel consumption and better take-off gross weight (TOGW). However, at Mach 0.8, the TBW is superior because the jury strut aids in satisfying the flutter constraint; Two-dimensional, steady, transonic aerodynamic analysis of the Boeing Airfoil J (BACJ) airfoil was performed for a range of thickness ratios, Mach numbers and lift coefficients. Reynolds-averaged Navier-Stokes (RANS) equations were solved to obtain the lift-curve slope, wave drag coefficient, the location of the center of pressure and to predict the separation at the trailing edge, which may lead to buffeting. One of the goals was to develop a database of lift-curve slope and the location of center of pressure, which could be used in a transonic aeroelastic analysis. Another goal was to compare the wave drag coefficients to those predicted by Lock’s fourth-power law and also to compare the transonic effects obtained from RANS simulations to those predicted by the Korn equations. A third goal was to develop a buffet boundary, which can be integrated into the MDO framework to prevent the optimized designs from probable buffeting; A state-space transonic aeroelastic analysis tool was developed, which can incorporate the nonlinear transonic effects in the unsteady aerodynamics but is yet computationally cheap when used within the VT MDO framework. The aeroelastic analysis uses Leishman- Beddoes (LB) indicial functions, which generated a state-space representation of the aeroelastic system. The indicial functions allow the incorporation of data for steady lift-curve slope and location of the center of pressure. Thus, the steady transonic effects are included, and the unsteady aerodynamic responses are a linearization about the steady results. The aeroelastic approach discretizes the wing into numerous strips, which results in a large eigenvalue problem as each strip has eight augmented aerodynamic states as per the LB theory. Thus, to reduce the computation expense, a reduced order model (ROM) was developed. The approach was validated using a few examples.
In space, astronauts are more susceptible to pathogens, viral reactivation and immunosuppression, which poses limits to their health and the mission. Interestingly, during space flight, stress-inducible heat shock proteins (HSP) are robustly induced, and the overexpression of HSPs have been implicated in immune dysregulation, therefore HSPs may be critically involved in regulating immune homeostasis. HSP40/DNAJ1 plays a major role in proper protein translation and folding. Its loss of function has been implicated in susceptibility to microbial infection, while its overexpression has been implicated in autoimmunity, collectively suggesting its complicated, but necessary, role in maintaining immunological function. To determine the role of HSP40 during stress-induced altered gravity conditions, wild-type and Hsp40 mutant Drosophila melanogaster were exposed to ground-based chronic hypergravity conditions, followed by quantitative PCR (qPCR) analysis of immune gene expression. In addition, larval hemocytes were collected to determine the functional output in response to E. coli bioparticle phagocytosis. Preliminary data indicates a required role for Hsp40 in strengthening immune function during stress-induced spaceflight in flies. In short, a critical need to evaluate the relationship between HSPs and immune suppression during space flight is necessary. Since space travel may become available to the general public in the not too distant future, and for the possibility of long-term space missions, a more comprehensive evaluation of the molecules responsible for immune dysfunction observed during space flight is required.
Prokaryotic lifeforms can be observed to demonstrate many keen adaptive advantages, perhaps facilitated by a nature simplistic relative to divergent domains of life. In particular, decompartmentalized gene expression facilitates adaptation by allowing free exchange of genetic material, albeit at the cost of increased susceptibility to genetic damage. Thus, these lifeforms must compensate by embracing diverse investment strategies in an attempt to “brute force” the evolvability equation through precipitous genesis, lean metabolic efficiency, and sheer population. This prokaryotic archetype also enables symbiotic relationships with secondary mobile genetic elements known as plasmids, which have been shown to drive evolution on rapid temporal scales through processes such as conjugation and transformation. This study attempts to decipher whether these mechanisms of horizontal gene transfer (HGT) are major factors in determining prokaryote fitness within a unique isolated environment, the International Space Station (ISS). The ISS Microbial Tracking (MT) project has generated a wealth of data concerning the successive reigns of microbial genera that appear to thrive amidst harsh conditions for life. Despite relatively higher doses of ionizing radiation as compared to Earth, complications associated with microgravity, and the anti-microbial mélange deployed, microbial life still persists in this environment. The NASA GeneLab serves as a data repository and analysis platform to enable researchers to access space flight factor related data. With the use of GeneLab’s modern computational suites (computomics), phylogenetic and functional genomic investigations of HGT events were conducted on the data generated from the MT-1 project. The putative data concerning the plasmid population (plasmidome) of the ISS was algorithmically derived and compared to those of habitats with similar environmental dynamics- such as living quarters and hospitals- to investigate whether these HGT elements may play crucial role(s) in shaping the microbiome of this closed habitat that serves as the only inhabited structure in space.
NASA’s priorities for Earth Science are informed by the 2017-2027 Decadal Survey for Earth Science and Applications from Space of the National Academies of Sciences, Engineering and Medicine. In that document, five Designated Observables are identified as priorities for research, two of which are Aerosols, and Clouds, Convection, and Precipitation. NASA is addressing these two Designated Observables by a combined study (the Aerosols, Clouds, Convection, and Precipitation, or ACCP, study). In this context of the ACCP study’s multiple objectives and multiple stakeholders, heuristic-based approaches are insufficient to assess candidate observing system concepts due to the complexity of the decision problem. For the ACCP study, this complexity in assessment is such that absent a structured approach that permits understanding of the steps leading to a decision, the decision risks being made on an incomplete basis. While prose and numeric data both have their place in effective communication, visualizations play an important part not only in presenting information, but also in structuring conversations around that information. Each of the visualizations developed for the ACCP Value Framework serve at least one of several functions: it structures communication about a method or process, it facilitates the elicitation and aggregation of data, or it summarizes complex information to enable analysis. Thus, these visualizations can present information, structure conversations, or do both.