Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “mapping variables”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,027 records · Page 57

Reveal, A General Reverse Engineering Algorithm for Inference of Genetic Network Architectures

Given the immanent gene expression mapping covering whole genomes during development, health and disease, we seek computational methods to maximize functional inference from such large data sets. Is it possible, in principle, to completely infer a complex regulatory network architecture from input/output patterns of its variables? We investigated this possibility using binary models of genetic networks. Trajectories, or state transition tables of Boolean nets, resemble time series of gene expression. By systematically analyzing the mutual information between input states and output states, one is able to infer the sets of input elements controlling each element or gene in the network. This process is unequivocal and exact for complete state transition tables. We implemented this REVerse Engineering ALgorithm (REVEAL) in a C program, and found the problem to be tractable within the conditions tested so far. For n = 50 (elements) and k = 3 (inputs per element), the analysis of incomplete state transition tables (100 state transition pairs out of a possible 10(exp 15)) reliably produced the original rule and wiring sets. While this study is limited to synchronous Boolean networks, the algorithm is generalizable to include multi-state models, essentially allowing direct application to realistic biological data sets. The ability to adequately solve the inverse problem may enable in-depth analysis of complex dynamic systems in biology and other fields.

Liang, Shoudan↗

Development of the Sasquatch Drop Test Footprint Tool

The Crew Exploration Vehicle Parachute Assembly System (CPAS) is the parachute system for NASA s Orion spacecraft. CPAS is currently in the design and testing phase of development. The test program consists of numerous drop tests, wherein a test article rigged with parachutes is extracted or released from an aircraft. During such tests, range safety is paramount, as is the recoverability of the parachutes and test article. It is crucial to establish an aircraft release point that will ensure that the article and all items released from it will land in safe locations. Early in the CPAS project, a legacy tool (previously used on the X-38 project) was used to determine a safe release point and to predict the landing locations (the footprint) of the payload and all released objects. Due to increasing test complexity and the need for a more flexible tool, a new footprint predictor tool, called Sasquatch, was created in MATLAB. This tool takes in a simulated trajectory for the test article, information about all released objects, and atmospheric wind data (simulated or actual) to calculate the trajectories of the released objects. Dispersions are applied to the landing locations of those objects, taking into account the variability of winds, aircraft release point, and object descent rate. A safe aircraft release point is determined based on the landing locations of the payload and released objects. The release point, landing locations, and dispersions are plotted on a simple map of the drop zone for easy reference. To date, Sasquatch has been used for thirteen drop tests. Comparing the predictions with actual test results has allowed for significant improvements in the tool s predictive capabilities, especially the incorporation of a well-correlated horizontal throw model. Intended future improvements to the tool include tighter dispersions on the landing locations, Monte Carlo capability, direct input from trajectory simulations, and a graphical user interface.

Bledsoe, Kristin J.↗

Groundwater and Terrestrial Water Storage

Most people think of groundwater as a resource, but it is also a useful indicator of climate variability and human impacts on the environment. Groundwater storage varies slowly relative to other non-frozen components of the water cycle, encapsulating long period variations and trends in surface meteorology. On seasonal to interannual timescales, groundwater is as dynamic as soil moisture, and it has been shown that groundwater storage changes have contributed to sea level variations. Groundwater monitoring well measurements are too sporadic and poorly assembled outside of the United States and a few other nations to permit direct global assessment of groundwater variability. However, observational estimates of terrestrial water storage (TWS) variations from the GRACE satellites largely represent groundwater storage variations on an interannual basis, save for high latitude/altitude (dominated by snow and ice) and wet tropical (surface water) regions. A figure maps changes in mean annual TWS from 2009 to 2010, based on GRACE, reflecting hydroclimatic conditions in 2010. Severe droughts impacted Russia and the Amazon, and drier than normal weather also affected the Indochinese peninsula, parts of central and southern Africa, and western Australia. Groundwater depletion continued in northern India, while heavy rains in California helped to replenish aquifers that have been depleted by drought and withdrawals for irrigation, though they are still below normal levels. Droughts in northern Argentina and western China similarly abated. Wet weather raised aquifer levels broadly across western Europe. Rains in eastern Australia caused flooding to the north and helped to mitigate a decade long drought in the south. Significant reductions in TWS seen in the coast of Alaska and the Patagonian Andes represent ongoing glacier melt, not groundwater depletion. Figures plot time series of zonal mean and global GRACE derived non-seasonal TWS anomalies (deviation from the mean of each month of the year) excluding Greenland and Antarctica. The two figures show that 2010 was the driest year since 2003. The drought in the Amazon was largely responsible, but an excess of water in 2009 seems to have buffered that drought to some extent. The drying trend in the 25-55 deg S zone is a combination of Patagonian glacier melt and drought in parts of Australia.

Rodell, Matthew↗

Understanding the Water Cycle Above the North Polar Cap on Mars Using MRO CRISM Retrievals of Water Vapor

The north polar cap (NPC) on Mars is the major reservoir of atmospheric water (H2O) currently on Mars. The retrieval and monitoring of atmospheric water vapor abundance are crucial for tracking the cycle of water above the NPC. The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter (MRO) has provided a wealth of data that extend over 5 + Martian years, covering the time period between 2006 and 2016. CRISM is ideally suited for spring and summer observations of the north polar region (latitudes poleward of 60 °N). The retrievals of water vapor column abundances over this extended period of time were performed over both ice-free and water ice covered surfaces, extending the coverage of the water vapor maps to include the permanent cap, where a maximum value of 90 precipitable micrometers (pr–µm) is retrieved, as compared to 60 pr–µm over ice-free regions in the North Polar Region. Away from summertime maximum, modest interannual variability in the water vapor abundance is observed. Zonal averages over all the observed Martian years combined show a developing water front that shifts northward towards summer, before dissipating over the permanent cap during mid-summer. A prominent feature at latitudes around 75 °N shows large abundances of water vapor, indicating a water vapor annulus encircling the retreating edge of the seasonal polar cap during late spring. Meridional transport of water modeled here show that the annulus may be a result of the convergence of water vapor from both south and north along the retreating edge of the NPC.

Khayat, Alain S. J.↗

Classifying planetary cloudiness with an updated set of MODIS Cloud Regimes

We present an updated Cloud Regime (CR) dataset based on Moderate resolution Imaging Spectroradiometer (MODIS) Collection 6.1 cloud products, specifically joint histograms that partition cloud fraction within distinct combinations of cloud top pressure and cloud optical thickness ranges. The paper focuses on an edition of the CR dataset derived from our own aggregation of MODIS pixel-level cloud retrievals on an equal area grid and pre-specified 3-hour UTC intervals that spatiotemporally match International Satellite Cloud Climatology Project (ISCCP) gridded cloud data. The other edition comes from the 1-degree daily aggregation provided by standard MODIS Level-3 data, as in previous versions of the MODIS CRs, for easier use with datasets mapped on equal angle grids. Both editions consist of 11 clusters whose centroids are nearly identical.We provide a physical interpretation of the new CRs and aspects of their climatology that have not been previously examined, such as seasonal and interannual variability of CR frequency of occurrence. We also examine the makeup and precipitation properties of the CRs assisted by independent datasets originating from active observations, and provide a first glimpse of how MODIS CRs relate to clouds as seen by ISCCP.

MODIS↗

Aeroacoustic Computations of a Generic Low Boom Concept in Landing Configuration: Part 3 - Aerodynamic Validation and Noise Source Identification

Wind tunnel test data were used to validate the predicted aerodynamic behavior of a 15%-scale version of a generic, low-boom aircraft. The test was conducted in the NASA Langley 14- by 22-Foot Subsonic Tunnel to determine the low-speed aerodynamic characteristics of the model. Measured steady surface pressures and global forces were used to validate predicted aerodynamic results obtained from high-fidelity simulations of the model as installed in the tunnel. Very good agreement between predicted and measured aerodynamic trends was demonstrated, providing the impetus to proceed with companion airframe noise simulations that were conducted in a free-air setting. Computed near-field flow variables acquired on a permeable data surface were used to generate synthetic pressure records for two 800-element phased microphone arrays positioned overhead and to the side of the model. The array data were beamformed to generate noise source localization maps for the clean model and several landing configurations. Primary and secondary airframe sources were identified and their relative strengths were determined. Far-field integrated noise spectra for the full aircraft, as well as individual components, were obtained from the source maps via integration of tailored regions. The analysis showed that noise produced by the landing gear was the dominant contributor to the far-field acoustic signature of the model, followed by flap noise. The effects of permeable data surface end caps, spatial resolution, array orientation, angle of attack, component interaction, velocity scaling, and numerical precision on synthetic far-field spectra were also evaluated.

low boom↗

Mapping Aerosol Lidar Ratios Over Ocean for CALIPSO Using Modis AOD-Constrained Retrievals and A Global Aerosol Model

The CALIPSO aerosol algorithms currently assign one lidar ratio value for each of the seven tropospheric aerosol types. In a future data products release, the CALIPSO project aims to improve these algorithms by developing regional and seasonal lidar ratio climatologies. In this study, aerosol lidar ratios are inferred through Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) backscatter profiles constrained by collocated aerosol optical depth from Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) datasets. The analysis is subsampled for only those profiles that are cloud-free and contain one aerosol type (based on CALIOP feature classification). In addition, the CALIOP profiles are collocated with aerosol volume fractions simulated by the Goddard Chemistry Aerosol Radiation and Transport (GOCART) model. In this talk, the twelve-year (2006-2017) mean spatial distributions of inferred aerosol lidar ratios for CALIOP-classified marine aerosols and the corresponding modeled sea salt volume fractions (SSVF) will be shown. Model-assisted climatological lidar ratio maps on a seasonal scale will also be presented, developed from the empirical relationship found between the modeled SSVF and lidar ratios. A comparison with past studies will be provided as well as results of a sensitivity study regarding the variability of retrieved lidar ratios as a function of horizontal averaging resolution. While the majority of this talk will focus on lidar ratios for CALIOP-classified marine aerosols, preliminary results will be shown for other aerosol types over ocean, such as dust and elevated smoke.

Travis Toth↗

Construction of Polarimetric Radar-Based Reference Rain Maps for the Iowa Flood Studies Campaign

The Global Precipitation Measurement (GPM) Mission Iowa Flood Studies (IFloodS) campaign was conducted in central and northeastern Iowa during the months of April-June, 2013. Specific science objectives for IFloodS included quantification of uncertainties in satellite and ground-based estimates of precipitation, 4-D characterization of precipitation physical processes and associated parameters (e.g., size distributions, water contents, types, structure etc.), assessment of the impact of precipitation estimation uncertainty and physical processes on hydrologic predictive skill, and refinement of field observations and data analysis approaches as they pertain to future GPM integrated hydrologic validation and related field studies. In addition to field campaign archival of raw and processed satellite data (including precipitation products), key ground-based platforms such as the NASA NPOL S-band and D3R Ka/Ku-band dual-polarimetric radars, University of Iowa X-band dual-polarimetric radars, a large network of paired rain gauge platforms, and a large network of 2D Video and Parsivel disdrometers were deployed. In something of a canonical approach, the radar (NPOL in particular), gauge and disdrometer observational assets were deployed to create a consistent high-quality distributed (time and space sampling) radar-based ground "reference" rainfall dataset, with known uncertainties, that could be used for assessing the satellite-based precipitation products at a range of space/time scales. Subsequently, the impact of uncertainties in the satellite products could be evaluated relative to the ground-benchmark in coupled weather, land-surface and distributed hydrologic modeling frameworks as related to flood prediction. Relative to establishing the ground-based "benchmark", numerous avenues were pursued in the making and verification of IFloodS "reference" dual-polarimetric radar-based rain maps, and this study documents the process and results as they pertain specifically to efforts using the NPOL radar dataset. The initial portions of the "process" involved dual-polarimetric quality control procedures which employed standard phase and correlation-based approaches to removal of clutter and non-meteorological echo. Calculation of a scale-adaptive KDP was accomplished using the method of Wang and Chandrasekar (2009; J. Atmos. Oceanic Tech.). A dual-polarimetric blockage algorithm based on Lang et al. (2009; J. Atmos. Oceanic Tech.) was then implemented to correct radar reflectivity and differential reflectivity at low elevation angles. Next, hydrometeor identification algorithms were run to identify liquid and ice hydrometeors. After the quality control and data preparation steps were completed several different dual-polarimetric rain estimation algorithms were employed to estimate rainfall rates using rainfall scans collected approximately every two to three minutes throughout the campaign. These algorithms included a polarimetrically-tuned Z-R algorithm that adjusts for drop oscillations (via Bringi et al., 2004, J. Atmos. Oceanic Tech.), and several different hybrid polarimetric variable approaches, including one that made use of parameters tuned to IFloodS 2D Video Disdrometer measurements. Finally, a hybrid scan algorithm was designed to merge the rain rate estimates from multiple low level elevation angle scans (where blockages could not be appropriately corrected) in order to create individual low-level rain maps. Individual rain maps at each time step were subsequently accumulated over multiple time scales for comparison to gauge network data. The comparison results and overall error character depended strongly on rain event type, polarimetric estimator applied, and range from the radar. We will present the outcome of these comparisons and their impact on constructing composited "reference" rainfall maps at select time and space scales.

Radar↗

Kentucky Disasters: Multi-Hazard Approach to Mapping Flood Susceptibility and Vulnerability in Kentucky

Flooding is the most common and costly natural disaster in Kentucky, with major flood events in 2022 and 2023 highlighting the need for flood risk assessment. In partnership with the National Weather Service Jackson and Paducah Forecast Offices and the Kentucky Climate Center, we mapped flood risk in Kentucky using a multi-hazard approach that considered two dimensions of risk: flood susceptibility based on a weighted combination of seven physical factors and flood vulnerability based on 13 socioeconomic and infrastructure factors. We additionally analyzed NASA Soil Moisture Active Passive (SMAP) observations of surface soil moisture to explore the utility of SMAP observations for future analysis of flood risk. By analyzing flood susceptibility, we found that with equal rainfall, western Kentucky generally displays a higher propensity to flood than eastern Kentucky. In contrast, our flood vulnerability analysis indicated that more vulnerable areas were generally concentrated in the eastern part of the state. Through a combined perspective, our flood risk analysis identified much of the state as having moderate degrees of flood susceptibility and vulnerability. Our parallel analysis of antecedent soil moisture found that SMAP soil moisture levels were variable in the months leading up to each flood event but were drier than normal in the month prior to the 2023 event, as shown by negative soil moisture anomalies. These results were limited by challenges with weighting input parameters and a lack of validation but overall demonstrate the feasibility of using GIS and Earth observations for mapping flood risk and soil moisture.

analytic hierarchy process↗

Fully synthetic platform to rapidly generate tetravalent bispecific nanobody–based immunoglobulins

Nanobodies bind a target antigen with a kinetic profile similar to a conventional antibody, but exist as a single heavy chain domain that can be readily multimerized to engage antigen via multiple interactions. Presently, most nanobodies are produced by immunizing camelids; however, platforms for animal-free production are growing in popularity. Here, we describe the development of a fully synthetic nanobody library based on an engineered human V H 3-23 variable gene and a multispecific antibody-like format designed for biparatopic target engagement. To validate our library, we selected nanobodies against the SARS-CoV-2 receptor–binding domain and employed an on-yeast epitope binning strategy to rapidly map the specificities of the selected nanobodies. We then generated antibody-like molecules by replacing the V H and V L domains of a conventional antibody with two different nanobodies, designed as a molecular clamp to engage the receptor-binding domain biparatopically. The resulting bispecific tetra-nanobody immunoglobulins neutralized diverse SARS-CoV-2 variants with potencies similar to antibodies isolated from convalescent donors. Subsequent biochemical analyses confirmed the accuracy of the on-yeast epitope binning and structures of both individual nanobodies, and a tetra-nanobody immunoglobulin revealed that the intended mode of interaction had been achieved. This overall workflow is applicable to nearly any protein target and provides a blueprint for a modular workflow for the development of multispecific molecules.

60 APPLIED LIFE SCIENCES↗

Mapping of flumioxazin tolerance in a snap bean diversity panel leads to the discovery of a master genomic region controlling multiple stress resistance genes

Effective weed management tools are crucial for maintaining the profitable production of snap bean (Phaseolus vulgaris L.). Preemergence herbicides help the crop to gain a size advantage over the weeds, but the few preemergence herbicides registered in snap bean have poor waterhemp (Amaranthus tuberculatus) control, a major pest in snap bean production. Waterhemp and other difficult-to-control weeds can be managed by flumioxazin, an herbicide that inhibits protoporphyrinogen oxidase (PPO). However, there is limited knowledge about crop tolerance to this herbicide. We aimed to quantify the degree of snap bean tolerance to flumioxazin and explore the underlying mechanisms. We investigated the genetic basis of herbicide tolerance using genome-wide association mapping approach utilizing field-collected data from a snap bean diversity panel, combined with gene expression data of cultivars with contrasting response. The response to a preemergence application of flumioxazin was measured by assessing plant population density and shoot biomass variables. Snap bean tolerance to flumioxazin is associated with a single genomic location in chromosome 02. Tolerance is influenced by several factors, including those that are indirectly affected by seed size/weight and those that directly impact the herbicide's metabolism and protect the cell from reactive oxygen species-induced damage. Transcriptional profiling and co-expression network analysis identified biological pathways likely involved in flumioxazin tolerance, including oxidoreductase processes and programmed cell death. Transcriptional regulation of genes involved in those processes is possibly orchestrated by a transcription factor located in the region identified in the GWAS analysis. Several entries belonging to the Romano class, including Bush Romano 350, Roma II, and Romano Purpiat presented high levels of tolerance in this study. The alleles identified in the diversity panel that condition snap bean tolerance to flumioxazin shed light on a novel mechanism of herbicide tolerance and can be used in crop improvement.

60 APPLIED LIFE SCIENCES↗

The diminiode: A research and development tool for nuclear thermionics

Diminiodes are fixed-or variable-gap cesium diodes with plane miniature emitters and guarded collectors. In addition to smallness, their relative advantages are simplicity, precision, ease of fabrication, interchangeability of parts, cleanliness, full instrumentation, ruggedness, and economy. With diminiodes and computers used in thermionic performance mapping, a thorough electrode screening program becomes practical.

Morris, J. F.↗

OSO-7 observations of high galactic latitude X-ray sources

Six hundred days of observations by the X-ray detectors aboard OSO-7 have been analyzed. All-sky maps of X-ray intensity have been constructed from these data. A sample map is displayed. Seven sources with galactic latitude greater than 10 deg, discovered during the mapping process, are reported, and upper limits are set on other high-latitude sources. The OSO-7 results are compared with those of Uhuru, and an implication of this comparison, that many of the high-latitude sources may be variable, is discussed.

Markert, T. H.↗

Characterization of LANDSAT-4 TM and MSS Image Quality for the Interpretation of California's Agricultural Resources

The quality of LANDSAT-4 MSS and TM data was determined by analyzing TM spectral and spatial performance in terms of spectral variability of natural targets and the TM-ground instantaneous field-of-view (IFOV) variability in level and mountainous terrain; and by assessing the suitability of TM and MSS image products for characterizing renewable resourse features. The TM data should be extremelly valuable for crop type and area proportion estimation; undating agricultural land use survey maps at 1:24,000 scale and smaller, field boundary definition; and determining the size and location of individual farmsteads. Ongoing research activities are focused on making spectral and spatial analyses of both MSS and TM analytical film products. The improved spectral, spatial, and radiometric quality of the TM data, should promote a renewed emphasis and interest in direct visual interpretation of these image products, both for updating and improving land stratification in support of resource inventory and for enhancing the image analyst's contribution to computer-assisted analysis procedures.

Degloria, S. D.↗

Global three-dimensional constituent fields derived from profile data

The success of three-dimensional simulations of stratospheric constituent variability depends critically on the initialization of the constituent fields within the global model. This paper describes a technique for generating global three-dimensional fields from vertical constituent proflies. The technique uses potential vorticity (q) and potential temperature (theta) to map the profiles onto the global domain. The profiles used here are obtained from a two-dimensional model calculation that reproduces the relationship between theta, q, N2O and O3 observed during the Airborne Arctic Stratospheric Expedition. The method is verified by comparison with satellite data, aircraft data, and model simulations.

Douglass, Anne R.↗

Visualizing Flow Over Parametric Surfaces Using Line Integral Convolution

Line Integral Convolution (LIC) is a powerful technique for imaging and animating vector fields. We extend the LIC paradigm in three ways: (1) The existing technique is limited to vector fields over a regular Cartesian grid. We extend it to vector fields over parametric surfaces, such as those found in curvilinear grids, used in computational fluid dynamics simulations; (2) Periodic motion filters can be used to animate the flow visualization. When the flow lies on a parametric surface, however, the motion appears misleading. We explain why this problem arises and show how to adjust the LIC algorithm to handle it; (3) We introduce a technique to visualize vector magnitudes as well as vector direction. Cabral and Leedom have suggested a method for variable-speed animation, which is based on varying the frequency of the filter function. We develop a different technique based on kernel phase shifts which we have found to show substantially better results. Our implementation of these algorithms utilizes texture-mapping hardware to run in real time, which allows them to be included in interactive applications.

Forssell, Lisa↗

NASA GES DISC support of CO2 Data from OCO-2, ACOS, and AIRS

NASA Goddard Earth Sciences Data and Information Services Centers (GES DISC) is the data center assigned to archive and distribute current AIRS, ACOS data and data from the upcoming OCO-2 mission. The GES DISC archives and supports data containing information on CO2 as well as other atmospheric composition, atmospheric dynamics, modeling and precipitation. Along with the data stewardship, an important mission of GES DISC is to facilitate access to and enhance the usability of data as well as to broaden the user base. GES DISC strives to promote the awareness of science content and novelty of the data by working with Science Team members and releasing news articles as appropriate. Analysis of events that are of interest to the general public, and that help in understanding the goals of NASA Earth Observing missions, have been among most popular practices.Users have unrestricted access to a user-friendly search interface, Mirador, that allows temporal, spatial, keyword and event searches, as well as an ontology-driven drill down. Variable subsetting, format conversion, quality screening, and quick browse, are among the services available in Mirador. The majority of the GES DISC data are also accessible through OPeNDAP (Open-source Project for a Network Data Access Protocol) and WMS (Web Map Service). These services add more options for specialized subsetting, format conversion, image viewing and contributing to data interoperability.

Wei, Jennifer C↗

Bringing Analysis Closer to Data: Developing a Visualization Tool for L2 Earth Science Satellite Data

Earth Science satellite missions provide a unique opportunity for scientists to visualize complex and multifaceted observations projected geospatially across maps of the Earth. While visualization tools can help scientists comprehend, analyze, and share data, visualizing Level-2 Earth Sciences data poses its own specific set of challenges. Since the geospatial information in Level-2 data files is stored as independent variables, the plotting process involves matching dimensional information from latitude and longitude with a desired variable. Variables are stored in different ways across various Earth Science data file formats, which complicates the process of extracting data and plotting variables from a given file without requiring extensive user input and prerequisite familiarity with the file type variable structure. In coordination with NASA’s Goddard Earth Sciences Data Information Services Center (GES DISC), the team developed a Level-2 Earth Science data visualization tool that aims to address some of the complexities associated with plotting Level-2 data. This tool offers command-line and user interface support for file and variable selection to accommodate varying use cases and degrees of user familiarity with the structure of a given file. The visualization tool is written in Python 3 and utilizes a modular approach to facilitate continued expansion and reuse. In addressing some common complications involved in plotting Level-2 Earth Sciences data, the tool aims to help to link the process of analysis more directly with data acquisition and visualization, bringing analysis closer to data across levels of processing.

Li, Angela W.↗