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NASA NTRS1989

Secular change in chert distribution: a reflection of evolving biological participation in the silica cycle

In the modern oceans, the removal of dissolved silica from sea water is principally a biological process carried out by diatoms, with lesser contributions from radiolaria, silicoflagellates, and sponges. Because such silica in sediments is often redistributed locally during diagenesis to from nodular or bedded chert, stratigraphic changes in the facies distribution of early diagenetic chert provide important insights into the development of biological participation in the silica cycle. The abundance of chert in upper Proterozoic peritidal carbonates suggests that at this time silica was removed from seawater principally by abiological processes operating in part of the margins of the oceans. With the evolution of demosponges near the beginning of the Cambrian Period, subtidal biogenetic cherts became increasingly common, and with the Ordovician rise of radiolaria to ecological and biogeochemical prominence, sedimented skeletons became a principal sink for oceanic silica. Cherts of Silurian to Cretaceous age share many features of facies distribution and petrography but they differ from Cenozoic siliceous deposits. These differences are interpreted to reflect the mid-Cretaceous radiation of diatoms and their subsequent rise to domination of the silica cycle. Biogeochemical cycles provide an important framework for the paleobiological interpretation of the organisms that participate in them.

Non-NASA Center↗

NASA NTRS2004

An Empirical Cumulus Parameterization Scheme for a Global Spectral Model

Realistic vertical heating and drying profiles in a cumulus scheme is important for obtaining accurate weather forecasts. A new empirical cumulus parameterization scheme based on a procedure to improve the vertical distribution of heating and moistening over the tropics is developed. The empirical cumulus parameterization scheme (ECPS) utilizes profiles of Tropical Rainfall Measuring Mission (TRMM) based heating and moistening derived from the European Centre for Medium- Range Weather Forecasts (ECMWF) analysis. A dimension reduction technique through rotated principal component analysis (RPCA) is performed on the vertical profiles of heating (Q1) and drying (Q2) over the convective regions of the tropics, to obtain the dominant modes of variability. Analysis suggests that most of the variance associated with the observed profiles can be explained by retaining the first three modes. The ECPS then applies a statistical approach in which Q1 and Q2 are expressed as a linear combination of the first three dominant principal components which distinctly explain variance in the troposphere as a function of the prevalent large-scale dynamics. The principal component (PC) score which quantifies the contribution of each PC to the corresponding loading profile is estimated through a multiple screening regression method which yields the PC score as a function of the large-scale variables. The profiles of Q1 and Q2 thus obtained are found to match well with the observed profiles. The impact of the ECPS is investigated in a series of short range (1-3 day) prediction experiments using the Florida State University global spectral model (FSUGSM, T126L14). Comparisons between short range ECPS forecasts and those with the modified Kuo scheme show a very marked improvement in the skill in ECPS forecasts. This improvement in the forecast skill with ECPS emphasizes the importance of incorporating realistic vertical distributions of heating and drying in the model cumulus scheme. This also suggests that in the absence of explicit models for convection, the proposed statistical scheme improves the modeling of the vertical distribution of heating and moistening in areas of deep convection.

Rajendran, K.↗

NASA NTRS1997

Mechanical signals in plant development: a new method for single cell studies

Cell division, which is critical to plant development and morphology, requires the orchestration of hundreds of intracellular processes. In the end, however, cells must make critical decisions, based on a discrete set of mechanical signals such as stress, strain, and shear, to divide in such a way that they will survive the mechanical loads generated by turgor pressure and cell enlargement within the growing tissues. Here we report on a method whereby tobacco protoplasts swirled into a 1.5% agarose entrapment medium will survive and divide. The application of a controlled mechanical load to agarose blocks containing protoplasts orients the primary division plane of the embedded cells. Photoelastic analysis of the agarose entrapment medium can identify the lines of principal stress within the agarose, confirming the hypothesis that cells divide either parallel or perpendicular to the principal stress tensors. The coincidence between the orientation of the new division wall and the orientation of the principal stress tensors suggests that the perception of mechanical stress is a characteristic of individual plant cells. The ability of a cell to determine a shear-free orientation for a new partition wall may be related to the applied load through the deformation of the matrix material. In an isotropic matrix a uniaxial load will produce a rotationally symmetric strain field, which will define a shear-free plane. Where high stress intensities combine with the loading geometry to produce multiaxial loads there will be no axis of rotational symmetry and hence no shear free plane. This suggests that two mechanisms may be orienting the division plane, one a mechanism that works in rotationally symmetrical fields, yielding divisions perpendicular to the compressive tensor, parallel to the long axis of the cell, and one in asymmetric fields, yielding divisions parallel to the short axis of the cell and the compressive tensor.

NASA Discipline Number 40-50↗

NASA NTRS1949

On the Theory of the Laval Nozzle

In the present paper, the motion of a gas in a plane-parallel Laval nozzle in the neighborhood of the transition from subsonic to supersonic velocities is studied. In a recently published paper, F. I. Frankl, applying the holograph method of Chaplygin, undertook a detailed investigation of the character of the flow near the line of transition from subsonic to supersonic velocities. From the results of Tricomi's investigation on the theory of differential equations of the mixed elliptic-hyperbolic type, Frankl introduced as one of the independent variables in place of the modulus of the velocity, a certain specially chosen function of this modulus. He thereby succeeded in explaining the character of the flow at the point of intersection of the transition line and the axis of symmetry (center of the nozzle) and in studying the behavior of the stream function in the neighborhood of this point by separating out the principal term having, together with its derivatives, the maximum value as compared with the corresponding corrections. This principal term is represented in Frankl's paper in the form of a linear combination of two hypergeometric functions. In order to find this linear combination, it is necessary to solve a number of boundary problems, which results in a complex analysis. In the investigation of the flow with which this paper is concerned, a second method is applied. This method is based on the transformation of the equations of motion to a form that may be called canonical for the system of differential equations of the mixed elliptic-hyperbolic type to which the system of equations of the motion of an ideal compressible fluid refers. By studying the behavior of the integrals of this system in the neighborhood of the parabolic line, the principal term of the solution is easily separated out in the form of a polynomial of the third degree. As a result, the computation of the transitional part of the nozzle is considerably simplified.

Falkovich, S. V.↗

NASA NTRS2005

Interpreting the International Space Station Microgravity Environment

The International Space Station (ISS) serves as a platform for microgravity research for the foreseeable future. A microgravity environment is one in which the effects of gravity are drastically reduced which then allows physical experiments to be conducted without the overpowering effects of gravity. A physical environment with very low-levels of acceleration and vibration has been accomplished by both the free fall associated with orbital flight and the design of the International Space Station. The International Space Station design has been driven by a long-standing, high-level requirement for a microgravity mode of operation. The Space Acceleration Measurement System has been in operation for nearly four years on the ISS measuring the microgravity environment in support of principal investigators and to characterize the ISS microgravity environment. The Principal Investigator Microgravity Services project functions as a detective to ascertain the source of disturbances seen in the ISS microgravity environment to allow correlation between that environment and experimental data. Payload developers need to predict the microgravity environment that will be imposed upon an experiment and ensure that the science and engineering requirements will be met. The Principal Investigator Microgravity Services project is developing n interactive tool to predict the microgravity environment at science payloads based on user defined operational scenarios. These operations (predictions and post-analyses) allow a researcher to examine the microgravity acceleration levels expected to exist when their experiment is operated and then receive an analysis of the environment which existed during their experiment operations. Presented in this paper will be descriptions of the environment predictive tool and an investigation into a previously unknown disturbance in the ISS microgravity environment.

DeLombard, Richard↗

NASA NTRS2004

Global variability of precipitation according to the Tropical Rainfall Measuring Mission

Numerous studies have documented the effect of El Nino-Southern Oscillation (ENSO) on rainfall in many regions of the globe. The question of whether ENSO is the single most important factor in interannual rainfall variability has received less attention, mostly because the kind of data that would be required to make such an assessment were simply not available. Until 1979 the evidence linking El Nino with changes in rainfall around the world came from rain gauges measuring precipitation over land masses and a handful of islands. From 1980 until the launch of the Tropical Rainfall Measuring Mission (TRMM) in November 1997 the remote sensing evidence was confined to ocean rainfall because of the very poor sensitivity of the instruments over land. In this paper we summarize the results of a principal component analysis of TRMM's 60-month (January 1998 to December 2002) global land and ocean remote-sensing record of monthly rainfall accumulations. Contrary to the first principal component of the rainfall itself, the first three indices of the anomaly are most sensitive to precipitation over the ocean rather than over the land. With the help of archived surface station data the first TRMM rain anomaly index is extended back several decades. Comparison of the extended index with the Southern Oscillation Index confirms that the first principal component of the rainfall anomaly is strongly correlated with the ENSO indices.

rainfall↗

NASA NTRS2006

Real Time On-line Space Research Laboratory Environment Monitoring with Off-line Trend and Prediction Analysis

One of the responsibilities of the NASA Glenn Principal Investigator Microgravity Services is to support NASA sponsored investigators in the area of reduced-gravity acceleration data analysis, interpretation and the monitoring of the reduced-gravity environment on-board various carriers. With the International Space Station currently operational, a significant amount of acceleration data is being down-linked and processed on ground for both the space station onboard environment characterization (and verification) and scientific experiments. Therefore, to help principal investigator teams monitor the acceleration level on-board the International Space Station to avoid undesirable impact on their experiment, when possible, the NASA Glenn Principal Investigator Microgravity Services developed an artificial intelligence monitoring system, which detects in near real time any change in the environment susceptible to affect onboard experiments. The main objective of the monitoring system is to help research teams identify the vibratory disturbances that are active at any instant of time onboard the International Space Station that might impact the environment in which their experiment is being conducted. The monitoring system allows any space research scientist, at any location and at any time, to see the current acceleration level on-board the Space Station via the World Wide Web. From the NASA Glenn s Exploration Systems Division web site, research scientists can see in near real time the active disturbances, such as pumps, fans, compressor, crew exercise, re-boost, extra-vehicular activity, etc., and decide whether or not to continue operating or stopping (or making note of such activity for later correlation with science results) their experiments based on the g-level associated with that specific event. A dynamic graphical display accessible via the World Wide Web shows the status of all the vibratory disturbance activities with their degree of confidence as well as their g-level contribution to the environment. The system can detect both known and unknown vibratory disturbance activities. It can also perform trend analysis and prediction by analyzing past data over many Increments of the space station for selected disturbance activities. This feature can be used to monitor the health of onboard mechanical systems to detect and prevent potential system failure as well as for use by research scientists during their science results analysis. Examples of both real time on-line vibratory disturbance detection and off-line trend analysis are presented in this paper. Several soft computing techniques such as Kohonen s Self-Organizing Feature Map, Learning Vector Quantization, Back-Propagation Neural Networks, and Fuzzy Logic were used to design the system.

Jules, Kenol↗

NASA NTRS2004

Three dimensional empirical mode decomposition analysis apparatus, method and article manufacture

An apparatus and method of analysis for three-dimensional (3D) physical phenomena. The physical phenomena may include any varying 3D phenomena such as time varying polar ice flows. A repesentation of the 3D phenomena is passed through a Hilbert transform to convert the data into complex form. A spatial variable is separated from the complex representation by producing a time based covariance matrix. The temporal parts of the principal components are produced by applying Singular Value Decomposition (SVD). Based on the rapidity with which the eigenvalues decay, the first 3-10 complex principal components (CPC) are selected for Empirical Mode Decomposition into intrinsic modes. The intrinsic modes produced are filtered in order to reconstruct the spatial part of the CPC. Finally, a filtered time series may be reconstructed from the first 3-10 filtered complex principal components.

Gloersen, Per↗

NASA NTRS2010

Project Management Using Modern Guidance, Navigation and Control Theory

The idea of control theory and its application to project management is not new, however literature on the topic and real-world applications is not as readily available and comprehensive in how all the principals of Guidance, Navigation and Control (GN&C) apply. This paper will address how the fundamental principals of modern GN&C Theory have been applied to NASA's Constellation Space Suit project and the results in the ability to manage the project within cost, schedule and budget. A s with physical systems, projects can be modeled and managed with the same guiding principles of GN&C as if it were a complex vehicle, system or software with time-varying processes, at times non-linear responses, multiple data inputs of varying accuracy and a range of operating points. With such systems the classic approach could be applied to small and well-defined projects; however with larger, multi-year projects involving multiple organizational structures, external influences and a multitude of diverse resources, then modern control theory is required to model and control the project. The fundamental principals of G N&C stated that a system is comprised of these basic core concepts: State, Behavior, Control system, Navigation system, Guidance and Planning Logic, Feedback systems. The state of a system is a definition of the aspects of the dynamics of the system that can change, such as position, velocity, acceleration, coordinate-based attitude, temperature, etc. The behavior of the system is more of what changes are possible rather than what can change, which is captured in the state of the system. The behavior of a system is captured in the system modeling and if properly done, will aid in accurate system performance prediction in the future. The Control system understands the state and behavior of the system and feedback systems to adjust the control inputs into the system. The Navigation system takes the multiple data inputs and based upon a priori knowledge of the input, will develop a statistical-based weighting of the input to determine where the system currently is located. Guidance and Planning logic of the system with the understanding of where it is (provided by the navigation system) will in turn determine where it needs to be and how to get there. Lastly, the system Feedback system is the right arm of the control system to allow it to affect change in the overall system and therefore it is critical to not only correctly identify the system feedback inputs but also the system response to the feedback inputs. And with any systems project it is critical that the objective of the system be clearly defined for not only planning but to be used to measure performance and to aid in the guidance of the system or project.

Hill, Terry↗

NASA NTRS2011

Scanning and Defocusing Properties of Microstrip Reflectarray Antennas

A symmetric reflectarray, consisting of variable-size square patch elements with a commonly used mathematical model for the horn in the form of a cosine function, has been designed using the transmit mode technique for different f/D ratios with 10 dB edge taper. Subsequently, the antennas were analyzed for the radiation pattern and gain. The infinite array model was used to determine the reflection phase of each patch element in the design and analysis codes. By displacing the feed laterally, the scan characteristics were obtained, such as the beam deviation factor, gain loss, and pattern degradation. The properties of reflect arrays were compared to those of the conventional paraboloidal reflectors. The same procedure was used to study the scan properties of offset reflectarrays. There is no cross-polarized radiation in the principal planes for a symmetric system. Cross-polarized radiation exists in non-principal planes off broadside in symmetric systems, with greater levels for larger values of subtended angles. Such cross-polarized radiation level increases with subtended angle just as cross-polarization level increases with decreasing values of f/D ratios for symmetric paraboloids in non-principal planes. Pattern distortions and gain loss were found to be more severe in the case of a microstrip reflectarray compared to the conventional parabolic reflector. The scan performance of the reflect arrays was found to improve with f/D ratios as is true for paraboloids. In general, scanning by means of displaced feed is limited to a few beam - widths in reflectarrays. Feed displacement in the axial direction of a symmetric reflectarray was investigated and compared to that of paraboloids. The gain loss due to the defocused feed of a reflectarray was found to be nearly the same as that of a paraboloid of the same subtended angle for larger values of f/D, and for displacements away from the antenna. The gain loss of an axially defocused reflectarray was found to be greater than that of a paraboloid for displacements closer to the antenna, especially for smaller values of f/D. In general, the performance of a defocused reflectarray was found to be poorer than that of a comparable paraboloid reflector.

Rengarajan, Sembiam↗

NASA NTRS1974

Apollo 17 Index: 70 mm, 35 mm, and 16 mm Photographs

This index lists and provides supplemental data for all Apollo 17 70 mm, 35 mm, and 16 mm photographs. The 70 mm and 35 mm photographs are indexed in three ways: (1) all photographs are listed in numerical sequence according to NASA photograph number, (2) photographs exposed in lunar orbit are listed according to longitude in 10deg increments, and (3) all photographs exposed on the lunar surface are listed in chronological order. In indexing the 70 mm and 35 mm orbital photographs, individual frames were matched to imagery on the 1:2,750,000 scale Lunar Planning Charts (LOC). Each frame was outlined on the LOC base map, and the principal point determined. The latitude and longitude of each principal point, to the nearest 0.1 degree, is recorded in this index, If the principal point of a photograph is in space or its location obscured by shadow, an approximate longitude was recorded so that the photograph would not be excluded from the computer-generated listing by longitude. Each frame is described in terms of a named lunar surface feature within the boundaries of the frame or, if no named features are within the frame boundaries, a major nearby feature.

Wells, Ronald A.↗

NASA NTRS2017

Integrated Model of the Eye/Optic Nerve Head Biomechanical Environment

Visual Impairment and Intracranial Pressure (VIIP) syndrome is a concern for long-duration space flight. Previously, it has been suggested that ocular changes observed in VIIP syndrome are related to the cephalad fluid shift that results in altered fluid pressures [1]. We are investigating the impact of changes in intracranial pressure (ICP) using a combination of numerical models, which simulate the effects of various environment conditions, including finite element (FE) models of the posterior eye. The specific interest is to understand how altered pressures due to gravitational changes affect the biomechanical environment of tissues of the posterior eye and optic nerve sheath. METHODS: Additional description of the numerical modeling is provided in the IWS abstract by Nelson et al. In brief, to simulate the effects of a cephalad fluid shift on the cardiovascular and ocular systems, we utilized a lumped-parameter compartment model of these systems. The outputs of this lumped-parameter model then inform boundary conditions (pressures) for a finite element model of the optic nerve head (Figure 1). As an example, we show here a simulation of postural change from supine to 15 degree head-down tilt (HDT), with primary outcomes being the predicted change in strains at the optic nerve head (ONH) region, specifically in the lamina cribrosa (LC), retrolaminar optic nerve, and prelaminar neural tissue (PLNT). The strain field can be decomposed into three orthogonal components, denoted as the first, second and third principal strains. We compare the peak tensile (first principal) and compressive (third principal) strains, since elevated strain alters cell phenotype and induces tissue remodeling. RESULTS AND CONCLUSIONS: Our lumped-parameter model predicted an IOP increase of c. 7 mmHg after 21 minutes of 15 degree HDT, which agreed with previous reports of IOP in HDT [1]. The corresponding FEM simulations predicted a relative increase in the magnitudes of the peak tensile and compressive strains in the lamina cribrosa of 42 and 43, respectively (Fig. 2). The corresponding changes in the optic nerve strains were 17 and 39, while in the PLNT they were 47 and 43. These magnitudes of relative elevations in peak strains may induce a phenotypic response in resident mechano-responsive resident cells [2]. This approach may be expanded to investigate other environmental changes (e.g. parabolic flight). Through our VIIP SCHOLAR project, we will validate and improve these integrated models by measuring patient-specific changes in optic nerve sheath geometry in patients with idiopathic intracranial hypertension before and after lumbar puncture and CSF removal.

biomechanics↗

NASA NTRS2017

Development of an Input Suite for an Orthotropic Composite Material Model

An orthotropic three-dimensional material model suitable for use in modeling impact tests has been developed that has three major components elastic and inelastic deformations, damage and failure. The material model has been implemented as MAT213 into a special version of LS-DYNA and uses tabulated data obtained from experiments. The prominent features of the constitutive model are illustrated using a widely-used aerospace composite the T800S3900-2B[P2352W-19] BMS8-276 Rev-H-Unitape fiber resin unidirectional composite. The input for the deformation model consists of experimental data from 12 distinct experiments at a known temperature and strain rate: tension and compression along all three principal directions, shear in all three principal planes, and off axis tension or compression tests in all three principal planes, along with other material constants. There are additional input associated with the damage and failure models. The steps in using this model are illustrated composite characterization tests, verification tests and a validation test. The results show that the developed and implemented model is stable and yields acceptably accurate results.

finite element method↗

NASA NTRSDate not supplied

NO2 Anomalies - Economy Attribution and Rapid Climate Response

Using principal component (PC) analysis of 16 years of monthly series of NO2 from OMI/Aura, we show that it is the third PC (PC3) from the full hierarchy of principal modes that is best coupled with the economic indicators. This coupling is positive, i.e. PC3 and economic indicators manifest positive covariance. However, the economic variability can explain only 40% of the information in PC3. Furthermore, this mode by itself explains only 3% of the total deseasonalized NO2 variability. We thus conclude that, while having an unambiguous impact, the economy can be awarded at best third order of importance in driving the deseasonalized NO2 series, i.e. after seasonal variability is removed from the series. Once we identified PC3 as the NO2 mode that is coupled with economic variability, we use this mode as an indicator and look for rapid climate adjustments to that part of NO2 variability that we are confident is coupled with the economic variability. We focus on observational data from the Atmospheric Infrared Sounder (AIRS) on board of NASA Aqua satellite, decompose series of surface skin temperature and clear-sky outgoing longwave radiances (OLR) into principal components, and identify potential impacts of NO2 PC3 on these climate variables.

NO2↗

NASA NTRSDate not supplied

NO2 Anomalies - Economy Attribution and Rapid Climate Response

Using principal component (PC) analysis of 16 years of monthly series of NO2 from OMI/Aura, we show that it is the third PC (PC3) from the full hierarchy of principal modes that is best coupled with the economic indicators. This coupling is positive, i.e. PC3 and economic indicators manifest positive covariance. However, the economic variability can explain only 40%of the information in PC3. Furthermore, this mode by itself explains only 3% of the total deseasonalized NO2 variability. We thus conclude that, while having an unambiguous impact, the economy can be awarded at best third order of importance in driving the deseasonalized NO2 series, i.e. after seasonal variability is removed from the series. Once we identified PC3 as the NO2 mode that is coupled with economic variability, we use this mode as an indicator and look for rapid climate adjustments to that part of NO2 variability that we are confident is coupled with the economic variability. We focus on observational data from the Atmospheric Infrared Sounder (AIRS) on board of NASA Aqua satellite, decompose series of surface skin temperature and clear-sky outgoing longwave radiances (OLR) into principal components, and identify potential impacts of NO2 PC3 on these climate variables.

NO2↗

DOE OSTI2020

System and method for automated extraction of high resolution structural dynamics from video

A method for extracting vibrational modes of a structure includes: receiving a plurality of video frames, each of the video frames including a plurality of pixels; decomposing each of the video frames on a plurality of spatial scales in accordance with complex steerable pyramid filters to obtain a filter response for each of the spatial scales; computing a plurality of local phases of the pixels of each frame; removing a temporal mean from each frame to obtain a plurality of factored vibration motion functions; performing principal component analysis on the factored vibration motion functions to obtain principal components; blind source separating the principal components to compute a plurality of modal coordinates; computing frequency and damping ratios in accordance with the modal coordinates; and outputting the computed frequency and damping ratios.

42 ENGINEERING↗

DOE OSTI2020

Machine Learning Approaches for Nuclear Material Accounting Data from Irradiation and Reprocessing

We are currently exploring data analysis methods for their ability to strengthen the synthesis and evaluation of information generated within domestic and international safeguard regimes. Safeguard data typically includes rich heterogenous datasets amenable to advanced data analytics methods, such as machine learning. We have converted transactional data containing both numerical and categorical attributes from a domestic nuclear material control and accountability (NMC&A) system into a low-dimensional numerical structure via linear principal component analysis. This data representation allows for global structure discovery via cluster analysis, which can characterize the typical behavior of each of the primary types of transaction events. Furthermore, the structure of the top principal components captures the “typical behavior” of the data and is thus amenable to anomaly detection through statistical hypothesis testing. We explored this capability by generating erroneous permutations of the data and computing the Q-residual quantity increase associated with the information loss when these data are projected into the low-dimensional principal component analysis space representative of typical transactions.Future work will focus on identifying data transformations (e.g., graph networks) that more closely align with the inherent structure of these transactions to explain more salient information and disambiguate the underlying nuclear process—in this case, irradiation and reprocessing—from artifacts of NMC&A system transactional record keeping data.

Drescher, Adam↗

DOE OSTI2021

Incorporating historical data and past analyses for improved tensile property prediction of 9% Cr steel

Data-driven analytical clustering and visualization techniques were applied to the dataset of 9% Cr experimental alloy data generated through the eXtremeMAT project. Techniques and results were compared with the resulting clusters obtained through similar analytical techniques on previous and reduced versions of the dataset. The principal components were generated in order to reduce the dimensionality of the complex dataset and to visualize the underlying trends in the data. Partitioning around medoids was performed on the resulting principal components to determine relevant clusters. Domain knowledge labels were further applied to the principal components to compare the labels with the trends identified through the clustering methods. The resulting clusters show the addition of the new data into the dataset, and show where alignment between the domain knowledge labels and partitioning around medoids (PAM) clusters show where the labels are appropriate. The clusters can be used to compare the tensile properties of the alloys, and to reduce the variation in the dataset.

Alloy design, Mechanical Properties, data analysis↗