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At least 199 records · Page 11

Microwave reflector characterization using simple instruments in EVA

An antenna with rigid panels which can be measured under ground conditions, carried to space in a packaged condition, deployed into a form similar to the Earth-measured one, measured under space conditions, restowed, and brought back to Earth so that the original measurements can be verified is the type being proposed for this experiment. The antenna chosen will be measured under ground conditions, carried aloft, deployed into its antenna shape, lifted by the remote manipulator system to a position where it can be sighted by two astronauts at the two theodolites, and held there until the surface characterization can be completed. An alternate method would be to use photogrammetry and take pictures of the surface from the payload handling station. After the surface characterization is completed, the antenna will be folded and restowed into the Shuttle bay for return to Earth. The surface characterization will be repeated on Earth after its return for verification both of the original measurement taken on Earth and the measurement taken in space.

Goslee, J. W.↗

Characterizing the Non-linear Interactions Between Tide, Storm Surge, and River Flow in the Delaware Bay Estuary, United States

Low-lying coastal areas in the mid-Atlantic region are prone to compound flooding resulting from the co-occurrence of river floods and coastal storm surges. To better understand the contribution of non-linear tide-surge-river interactions to compound flooding, the unstructured-grid Finite Volume Community Ocean Model was applied to simulate coastal storm surge and flooding in the Delaware Bay Estuary in the United States. The model was validated with tide gauge data in the estuary for selected hurricane events. Non-linear interactions between tide-surge-river were investigated using a non-stationary tidal analysis method, which decomposes the interactions’ components at the frequency domain. Model results indicated that tide-river interactions damped semidiurnal tides, while the tide-surge interactions mainly influenced diurnal tides. Tide-river interactions suppressed the water level upstream while tide-surge interaction increased the water level downstream, which resulted in a transition zone of damping and enhancing effects where the tide-surge-river interaction was prominent. Evident compound flooding was observed as a result of non-linear tide-surge-river interactions. Furthermore, sensitivity analysis was carried out to evaluate the effect of river flooding on the non-linear interactions. The transition zone of damping and enhancing effects shifted downstream as the river flow rate increased.

54 ENVIRONMENTAL SCIENCES↗

Combining RNA-SEQ Datasets from NASA GENELAB: An Evaluation of Correction Methods

Background: Conducting space biology experiments aboard the International Space Station, particularly those utilizing complex model organisms like mice, is expensive and difficult due to limited crew availability, hardware, and space. As a result, sample numbers from these studies are low, reducing the statistical power of any one experiment. Aggregating spaceflight datasets serves as a method to increase sample numbers, allowing for novel insights through bioinformatic analysis of ‘omics data from merged datasets. However, aggregating datasets can introduce unwanted variation including 1) differences in sample handling, processing, and sequencing platforms between datasets (technical variation) as well as 2) differences in experimental design between datasets. Methods: In the present study, NASA GeneLab-hosted RNAseq datasets from mouse liver tissues were used to evaluate several statistical methods to correct for this unwanted variation through two approaches, reference-based and standard. The following correction algorithms were applied with (reference-based) and/or without (standard) considering Universal Mouse RNA Reference samples: ComBat and ComBat_seq from the SVA package, the median polish, empirical Bayes, and ANOVA-based algorithms from the MBatch package, and negative binomial regression normalization in the DESeq2 package. For each approach, after the correction algorithm was applied, differential gene expression (DGE) analysis of flight and ground control samples was performed with the combined data. The robustness of each tool was evaluated using BatchQC to determine statistical differences between datasets before and after correction, Principal Component Analysis to evaluate global gene expression in samples before and after correction, and by comparing DGE analysis of individual datasets and combined datasets before and after correction. Results: The results showed that the reference-based approach introduced several additional (and likely artificial) differentially expressed genes when compared with the respective standard approach. Conclusions: Of the methods tested, standard ComBat_seq and DESeq2 were identified as the most robust correction methods for combining spaceflight mouse liver RNAseq datasets hosted on GeneLab.

Finsam Samson↗

Investigation of Stiffening and Curvature Effects on the Residual Strength of Composite Stiffened Panels with Large Transverse Notches

Design of robust aircraft structure requires consideration of the load-carrying capability with large damage. Large notches, typically introduced as machined cracks (aka "notches") severing a single skin bay and a central stiffening member, are often used to conservatively address the wide range of possible large damage scenarios. The objective of the current effort was to develop more generalized and rapid analysis methods addressing large-notch residual strength of stiffened panels to support preliminary design activities..

Enjuto, Patrick↗

Study Methods to Characterize and Implement Thermography Nondestructive Evaluation (NDE)

The limits and conditions under which an infrared thermographic nondestructive evaluation can be utilized to assess the quality of aerospace hardware is demonstrated in this research effort. The primary focus of this work is on applying thermography to the inspection of advanced composite structures such as would be found in the International Space Station Instrumentation Racks, Space Shuttle Cargo Bay Doors, Bantam RP-1 tank or RSRM Nose Cone. Here, the detection of delamination, disbond, inclusion and porosity type defects are of primary interest. In addition to composites, an extensive research effort has been initiated to determine how well a thermographic evaluation can detect leaks and disbonds in pressurized metallic systems "i.e. the Space Shuttle Main Engine Nozzles". In either case, research into developing practical inspection procedures was conducted and thermographic inspections were performed on a myriad of test samples, subscale demonstration articles and "simulated" flight hardware. All test samples were fabricated as close to their respective structural counterparts as possible except with intentional defects for NDE qualification. As an added benefit of this effort to create simulated defects, methods were devised for defect fabrication that may be useful in future NDE qualification ventures.

Walker, James L.↗

Application of a data-mining method based on Bayesian networks to lesion-deficit analysis

Although lesion-deficit analysis (LDA) has provided extensive information about structure-function associations in the human brain, LDA has suffered from the difficulties inherent to the analysis of spatial data, i.e., there are many more variables than subjects, and data may be difficult to model using standard distributions, such as the normal distribution. We herein describe a Bayesian method for LDA; this method is based on data-mining techniques that employ Bayesian networks to represent structure-function associations. These methods are computationally tractable, and can represent complex, nonlinear structure-function associations. When applied to the evaluation of data obtained from a study of the psychiatric sequelae of traumatic brain injury in children, this method generates a Bayesian network that demonstrates complex, nonlinear associations among lesions in the left caudate, right globus pallidus, right side of the corpus callosum, right caudate, and left thalamus, and subsequent development of attention-deficit hyperactivity disorder, confirming and extending our previous statistical analysis of these data. Furthermore, analysis of simulated data indicates that methods based on Bayesian networks may be more sensitive and specific for detecting associations among categorical variables than methods based on chi-square and Fisher exact statistics.

NASA Discipline Neuroscience↗

Rapid wavefield forecasting for earthquake early warning via deep sequence to sequence learning

We propose a deep learning model, WaveCastNet, to forecast high-dimensional wavefields. WaveCastNet integrates a convolutional long expressive memory architecture into a sequence-to-sequence forecasting framework, enabling it to model long-term dependencies and multiscale patterns in both space and time. By sharing weights across spatial and temporal dimensions, WaveCastNet requires significantly fewer parameters than more resource-intensive models such as transformers, resulting in faster inference times. Crucially, WaveCastNet also generalizes better than transformers to rare and critical seismic scenarios, such as high-magnitude earthquakes. Here, we show the ability of the model to predict the intensity and timing of destructive ground motions in real time, using simulated data from the San Francisco Bay Area. Furthermore, we demonstrate its zero-shot capabilities by evaluating WaveCastNet on real earthquake data. Our approach does not require estimating earthquake magnitudes and epicenters, steps that are prone to error in conventional methods, nor does it rely on empirical ground-motion models, which often fail to capture strongly heterogeneous wave propagation effects.

Geophysics↗

Correlation of coastal water turbidity and current circulation with ERTS-1 and Skylab imagery

The article reviews investigations of current circulation patterns, suspended sediment concentration, coastal frontal systems, and waste disposal plumes based on visual interpretation and digital analysis of ERTS-1 and Skylab/EREP imagery. Data on conditions in the Delaware Bay area were obtained from 10 ERTS-1 passes and one Skylab pass, with simultaneous surface and airborne sensing. The current patterns and sediments observed by ERTS-1 correlated well with ground-based observations. Methods are suggested which would make it possible to identify certain pollutants and sediment types from multispectral scanner data.

Klemas, V.↗

Learning with imperfectly labeled patterns

The problem of learning in pattern recognition using imperfectly labeled patterns is considered. The performance of the Bayes and nearest neighbor classifiers with imperfect labels is discussed using a probabilistic model for the mislabeling of the training patterns. Schemes for training the classifier using both parametric and non parametric techniques are presented. Methods for the correction of imperfect labels were developed. To gain an understanding of the learning process, expressions are derived for success probability as a function of training time for a one dimensional increment error correction classifier with imperfect labels. Feature selection with imperfectly labeled patterns is described.

Chittineni, C. B.↗

Tangential, semisubmerged, and internal store carriage and separation

Accounts are presented of tangential, semisubmerged, and internal store carriage drag, as well as of the results to date of stores-separation investigations employing both computational and experimental methods. It is demonstrated that CFD can contribute to the data base needed for internal stores carriage design and trade studies. Attention is given to the case of an internally carried store separating from its bay at supersonic speeds, where various kinds of interference are encountered. A code is developed for the simulation of these unsteady flows through time-accurate computations; computation results are noted to closely reproduce experiment data.

Wilcox, Floyd J., Jr.↗

Modeling ozone episodes in the Baltimore-Washington region

Surface ozone (O3) concentrations in excess of the National Ambient Air Quality Standard (NAAQS) continue to occur in metropolitan areas in the United States despite efforts to control emissions of O3 precursors. Future O3 control strategies will be based on results from modeling efforts that have just begun in many areas. Two initial questions that arise are model sensitivity to domain-specific conditions and the selection of episodes for model evaluation and control strategy development. For the Baltimore-Washington region (B-W), the presence of the Chesapeake Bay introduces a number of issues relevant to model sensitivity. In this paper, the specific questions of the determination of model volume (mixing height) for the Urban Airshed Model (UAM) is discussed and various alternative methods compared. For the latter question, several analytic approaches, Cluster Analysis and classification and Regression Tree (CART) analysis are undertaken to determine meteorological conditions associated with severe O3 events in the B-W domain.

Ryan, William F.↗

Analysis of the Planetary Boundary Layer Height During DISCOVER-AQ Baltimore–Washington, D.C., with Lidar and High-Resolution WRF Modeling

The daytime planetary boundary layer (PBL) was examined for the Deriving Information on Surface Conditions from Column and Vertically Resolved Observations Relevant to Air Quality (DISCOVER-AQ) Baltimore (Maryland)–Washington, D.C., campaign of July 2011 using PBL height (PBLH) retrievals from aerosol backscatter measurements from ground-based micropulse lidar (MPL), the NASA Langley Research Center airborne High Spectral Resolution Lidar-1 (HSRL-1), and the Cloud–Aerosol Lidar with Orthogonal Polarization (CALIOP) on the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) satellite. High-resolution Weather Research and Forecasting (WRF) Model simulations with horizontal grid spacing of 1 km and different combinations of PBL schemes, urban parameterization, and sea surface temperature inputs were evaluated against PBLHs derived from lidars, ozonesondes, and radiosondes. MPL and WRF PBLHs depicted a growing PBL in the morning that reached a peak height by midafternoon. WRF PBLHs calculated from gridded output profiles generally showed more rapid growth and higher peak heights than did the MPLs, and all WRF–lidar differences were dependent on model configuration, PBLH calculation method, and synoptic conditions. At inland locations, WRF simulated an earlier descent of the PBL top in the afternoon relative to the MPL retrievals and radiosonde PBLHs. At Edgewood, Maryland, the influence of the Chesapeake Bay breeze on the PBLH was captured by both the ozonesonde and WRF data but generally not by the MPL PBLH retrievals because of generally weaker gradients in the aerosol backscatter profile and limited normalized relative backscatter data near the top height of the marine layer.

Hegarty, Jennifer D.↗

California coast nearshore processes study

The author has identified the following significant results. This report contains the techniques used for enhancing and analyzing nearshore processes from ERTS-1 and aircraft data. Four California nearshore sites are used as test cells including the San Francisco area, Monterey Bay, Santa Barbara Channel, and Los Angeles area. Techniques used for analyzing the test cells included direct photographic processing, computer compatible tape gain change enhancement, discrete point density analysis and plotting, and densitometer enhancement. Using these methods, it is possible to measure the seaward extent of the suspended sediment transport and to differentiate sediment levels within the individual sediment lobes. The movement of riverine discharged suspensates and coastal sediments by currents was an intricate part of the sediment transport analysis. The larger estuaries in the test cell areas were also studied for flushing characteristics.

Pirie, D. M.↗

Processing multispectral data obtained by orbital platforms of the LANDSAT series for studies of water quality in Guanabara Bay

The relationship existing between Guanabara Bay water quality ground truth parameters and LANDSAT MSS video data was investigated. The parameters considered were: chorophyll content, water transparency usng the Secchi disk, salinity, and dissolved ammonia. Data from two overflights was used, and methods of processing digital data were compared. Linear and nonlinear regression analyses were utilized, comparing original data with processed data by using the correlation coefficient and the estimation mean error. It was determined that better quality data are obtained by using radiometric correction programs with a physical basis, contrast ratio, and normalization. Incidental locations of floating vegetation, changes in bottom depth, oil slicks, and ships at anchor were made.

Dejesusparada, N.↗

Visible-infrared remote-sensing model and applications for ocean waters

Remote sensing has become important in the ocean sciences, especially for research involving large spatial scales. To estimate the in-water constituents through remote sensing, whether carried out by satellite or airplane, the signal emitted from beneath the sea surface, the so called water-leaving radiance (L(w)), is of prime importance. The magnitude of L(w) depends on two terms: one is the intensity of the solar input, and the other is the reflectance of the in-water constituents. The ratio of the water-leaving radiance to the downwelling irradiance (E(d)) above the sear surface (remote-sensing reflectance, R(sub rs)) is independent of the intensity of the irradiance input, and is largely a function of the optical properties of the in-water constituents. In this work, a model is developed to interpret r(sub rs) for ocean water in the visible-infrared range. In addition to terms for the radiance scattered from molecules and particles, the model includes terms that describe contributions from bottom reflectance, fluorescence of gelbstoff or colored dissolved organic matter (CDOM), and water Raman scattering. By using this model, the measured R(sub rs) of waters from the West Florida Shelf to the Mississippi River plume, which covered a (concentration of chlorophyll a) range of 0.07 - 50 mg/cu m, were well interpreted. The average percentage difference (a.p.d.) between the measured and modeled R(sub rs) is 3.4%, and, for the shallow waters, the model-required water depth is within 10% of the chart depth. Simple mathematical simulations for the phytoplankton pigment absorption coefficient (a(sub theta)) are suggested for using the R(sub rs) model. The inverse problem of R(sub rs), which is to analytically derive the in-water constituents from R(sub rs) data alone, can be solved using the a(sub theta) functions without prior knowledge of the in-water optical properties. More importantly, this method avoids problems associated with a need for knowledge of the shape and value of the chlorophyll-specific absorption coefficient. The simulation was tested for a wide range of water types, including waters from Monterey Bay, the West Florida Shelf, and the Mississippi River plume. Using the simulation, the R(sub rs)-derived in-water absorption coefficients were consistent with the values from in-water measurements (r(exp 2) greater than 0.94, slope approximately 1.0). In the remote-sensing applications, a new approach is suggested for the estimation of primary production based on remote sensing. Using this approach, the calculated primary production (PP) values based upon remotely sensed data were very close to the measured values for the euphotic zone (r(exp 2) = 0.95, slope 1.26, and 32% average difference), while traditional, pigment-based PP model provided values only one-third the size of the measured data. This indicates a potential to significantly improve the accuracy of the estimation of primary production based upon remote sensing.

Lee, Zhongping↗

Prediction of R-curves from small coupon tests

R-curves were predicted for Alclad 2024-T3 and C188-T3 sheet using the results of small-coupon Kahn tear tests in combination with two-dimensional elastic-plastic finite element stress analyses. The predictions were compared to experimental R-curves from 6.3, 16 and 60-inch wide M(T) specimens and good agreement was obtained. The method is an inexpensive alternative to wide panel testing for characterizing the fracture toughness of damage-tolerant sheet alloys. The usefulness of this approach was demonstrated by performing residual strength calculations for a two-bay crack in a representative fuselage structure. C188-T3 was predicted to have a 24 percent higher load carrying capability than 2024-T3 in this application as a result of its superior fracture toughness.

Yeh, J. R.↗

Investigation of Stiffening Effects on Notch Growth Trajectory of Composite Stiffened Panels with Large Transverse Notches

Design of robust aircraft structure requires consideration of the load-carrying capability with large damage. Large notches, typically introduced as machined cracks (aka “notches”) severing a single skin bay and a central stiffening member, are often used to conservatively address the wide range of possible large damage scenarios. The objective of current effort was to explore the viability of developing preliminary laminate-based methods for predicting crack turning at the adjacent stiffener using traditional fracture mechanics concepts.

Enjuto, Patrick↗

A procedure for combining acoustically induced and mechanically induced loads (first passage failure design criterion)

The combined load statistics are developed by taking the acoustically induced load to be a random population, assumed to be stationary. Each element of this ensemble of acoustically induced loads is assumed to have the same power spectral density (PSD), obtained previously from a random response analysis employing the given acoustic field in the STS cargo bay as a stationary random excitation. The mechanically induced load is treated as either (1) a known deterministic transient, or (2) a nonstationary random variable of known first and second statistical moments which vary with time. A method is then shown for determining the probability that the combined load would, at any time, have a value equal to or less than a certain level. Having obtained a statistical representation of how the acoustic and mechanical loads are expected to combine, an analytical approximation for defining design levels for these loads is presented using the First Passage failure criterion.

Crowe, D. R.↗