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At least 1,495 records · Page 83
All sourcesNASA NTRSDOE OSTI
NASA NTRS2007

Algorithm Plans Collision-Free Path for Robotic Manipulator

An algorithm has been developed to enable a computer aboard a robot to autonomously plan the path of the manipulator arm of the robot to avoid collisions between the arm and any obstacle, which could be another part of the robot or an external object in the vicinity of the robot. In simplified terms, the algorithm generates trial path segments and tests each segment for potential collisions in an iterative process that ends when a sequence of collision-free segments reaches from the starting point to the destination. The main advantage of this algorithm, relative to prior such algorithms, is computational efficiency: the algorithm is designed to make minimal demands upon the limited computational resources available aboard a robot. This path-planning algorithm utilizes a modified version of the collision-detection method described in "Improved Collision-Detection Method for Robotic Manipulator" (NPO-30356), NASA Tech Briefs, Vol. 27, No. 3 (June 2003), page 72. The method involves utilization of mathematical models of the robot constructed prior to operation and similar models of external objects constructed automatically from sensory data acquired during operation. This method incorporates a previously developed method, known in the art as the method of oriented bounding boxes (OBBs), in which an object is represented approximately, for computational purposes, by a box that encloses its outer boundary. Because many parts of a robotic manipulator are cylindrical, the OBB method has been extended in this method to enable the approximate representation of cylindrical parts by use of octagonal or other multiple-OBB assemblies denoted oriented bounding prisms (OBPs). A multiresolution OBB/OBP representation of the robot and its manipulator arm and a multiresolution OBB representation of external objects (including terrain) are constructed and used in a process in which collisions at successively finer resolutions are detected through computational detection of overlaps between the corresponding OBB and OBP models. For computational efficiency, the process is started at the coarsest resolution and stopped as soon as possible, preferably before reaching the finest resolution. At the coarsest resolution, there is a single OBB enclosing all relevant external objects and a single OBB enclosing the entire robot. At the next finer level of resolution, the coarsest-resolution OBB is divided into two OBBs, and so forth. If no collision is detected at the coarsest resolution, then there is no need for further computation to detect collisions. If a collision is detected at the coarsest resolution, then tests for collisions are performed at the next finer level of resolution. This process is continued to successively finer resolutions until either no more collisions are detected or the finest resolution is reached.

Backes, Paul↗
NASA NTRS2009

Towards a Framework for Evaluating and Comparing Diagnosis Algorithms

Diagnostic inference involves the detection of anomalous system behavior and the identification of its cause, possibly down to a failed unit or to a parameter of a failed unit. Traditional approaches to solving this problem include expert/rule-based, model-based, and data-driven methods. Each approach (and various techniques within each approach) use different representations of the knowledge required to perform the diagnosis. The sensor data is expected to be combined with these internal representations to produce the diagnosis result. In spite of the availability of various diagnosis technologies, there have been only minimal efforts to develop a standardized software framework to run, evaluate, and compare different diagnosis technologies on the same system. This paper presents a framework that defines a standardized representation of the system knowledge, the sensor data, and the form of the diagnosis results and provides a run-time architecture that can execute diagnosis algorithms, send sensor data to the algorithms at appropriate time steps from a variety of sources (including the actual physical system), and collect resulting diagnoses. We also define a set of metrics that can be used to evaluate and compare the performance of the algorithms, and provide software to calculate the metrics.

Kurtoglu, Tolga↗
NASA NTRS2010

Project M: Scale Model of Lunar Landing Site of Apollo 17: Focus on Lighting Conditions and Analysis

This document captures the research and development of a scale model representation of the Apollo 17 landing site on the moon as part of the NASA INSPIRE program. Several key elements in this model were surface slope characteristics, crater sizes and locations, prominent rocks, and lighting conditions. This model supports development of Autonomous Landing and Hazard Avoidance Technology (ALHAT) and Project M for the GN&C Autonomous Flight Systems Branch. It will help project engineers visualize the landing site, and is housed in the building 16 Navigation Systems Technology Lab. The lead mentor was Dr. Timothy P. Crain. The purpose of this project was to develop an accurate scale representation of the Apollo 17 landing site on the moon. This was done on an 8'2.5"X10'1.375" reduced friction granite table, which can be restored to its previous condition if needed. The first step in this project was to research the best way to model and recreate the Apollo 17 landing site for the mockup. The project required a thorough plan, budget, and schedule, which was presented to the EG6 Branch for build approval. The final phase was to build the model. The project also required thorough research on the Apollo 17 landing site and the topography of the moon. This research was done on the internet and in person with Dean Eppler, a space scientist, from JSC KX. This data was used to analyze and calculate the scale of the mockup and the ratio of the sizes of the craters, ridges, etc. The final goal was to effectively communicate project status and demonstrate the multiple advantages of using our model. The conclusion of this project was that the mockup was completed as accurately as possible, and it successfully enables the Project M specialists to visualize and plan their goal on an accurate three dimensional surface representation.

Vanik, Christopher S.↗
NASA NTRS2000

Patterns of Transfer of Adaptation Among Body Segments

Two experiments were conducted in order to determine the patterns of transfer of visuomotor adaptation between arm and head pointing. An altered gain of display of pointing movements was used to induce a conflict between visual and somatosensory representations. Two subject groups participated in Experiment One: group 1 adapted shoulder pointing movements, and group 2 adapted wrist pointing movements to a 0.5 gain of display. Following the adaptation regimen, subjects performed a transfer test in which the shoulder group performed wrist movements and the wrist group performed shoulder movements. The results demonstrated that both groups displayed typical adaptation curves, initially undershooting the target followed by a return to baseline performance. Transfer tests revealed that both groups had high transfer of the acquired adaptation to the other joint. Experiment Two followed a similar design except that group 1 adapted head pointing movements and group 2 adapted arm pointing movements. The arm adaptation had high transfer to head pointing while the head adaptation had very little transfer to arm pointing. These results imply that, while the arm segments may share a common target representation for goal-directed actions, individual but functionally dependent target representations may exist for the control of head and arm movements.

Seidler, R. D.↗
NASA NTRS2011

Hyperresolution Global Land Surface Modeling: Meeting a Grand Challenge for Monitoring Earth's Terrestrial Water

Monitoring Earth's terrestrial water conditions is critically important to many hydrological applications such as global food production; assessing water resources sustainability; and flood, drought, and climate change prediction. These needs have motivated the development of pilot monitoring and prediction systems for terrestrial hydrologic and vegetative states, but to date only at the rather coarse spatial resolutions (approx.10-100 km) over continental to global domains. Adequately addressing critical water cycle science questions and applications requires systems that are implemented globally at much higher resolutions, on the order of 1 km, resolutions referred to as hyperresolution in the context of global land surface models. This opinion paper sets forth the needs and benefits for a system that would monitor and predict the Earth's terrestrial water, energy, and biogeochemical cycles. We discuss six major challenges in developing a system: improved representation of surface-subsurface interactions due to fine-scale topography and vegetation; improved representation of land-atmospheric interactions and resulting spatial information on soil moisture and evapotranspiration; inclusion of water quality as part of the biogeochemical cycle; representation of human impacts from water management; utilizing massively parallel computer systems and recent computational advances in solving hyperresolution models that will have up to 10(exp 9) unknowns; and developing the required in situ and remote sensing global data sets. We deem the development of a global hyperresolution model for monitoring the terrestrial water, energy, and biogeochemical cycles a grand challenge to the community, and we call upon the international hydrologic community and the hydrological science support infrastructure to endorse the effort.

Wood, Eric F.↗
NASA NTRS2003

Improved Collision-Detection Method for Robotic Manipulator

An improved method has been devised for the computational prediction of a collision between (1) a robotic manipulator and (2) another part of the robot or an external object in the vicinity of the robot. The method is intended to be used to test commanded manipulator trajectories in advance so that execution of the commands can be stopped before damage is done. The method involves utilization of both (1) mathematical models of the robot and its environment constructed manually prior to operation and (2) similar models constructed automatically from sensory data acquired during operation. The representation of objects in this method is simpler and more efficient (with respect to both computation time and computer memory), relative to the representations used in most prior methods. The present method was developed especially for use on a robotic land vehicle (rover) equipped with a manipulator arm and a vision system that includes stereoscopic electronic cameras. In this method, objects are represented and collisions detected by use of a previously developed technique known in the art as the method of oriented bounding boxes (OBBs). As the name of this technique indicates, an object is represented approximately, for computational purposes, by a box that encloses its outer boundary. Because many parts of a robotic manipulator are cylindrical, the OBB method has been extended in this method to enable the approximate representation of cylindrical parts by use of octagonal or other multiple-OBB assemblies denoted oriented bounding prisms (OBPs), as in the example of Figure 1. Unlike prior methods, the OBB/OBP method does not require any divisions or transcendental functions; this feature leads to greater robustness and numerical accuracy. The OBB/OBP method was selected for incorporation into the present method because it offers the best compromise between accuracy on the one hand and computational efficiency (and thus computational speed) on the other hand.

Leger, Chris↗
NASA NTRS2011

Graphical Language for Data Processing

A graphical language for processing data allows processing elements to be connected with virtual wires that represent data flows between processing modules. The processing of complex data, such as lidar data, requires many different algorithms to be applied. The purpose of this innovation is to automate the processing of complex data, such as LIDAR, without the need for complex scripting and programming languages. The system consists of a set of user-interface components that allow the user to drag and drop various algorithmic and processing components onto a process graph. By working graphically, the user can completely visualize the process flow and create complex diagrams. This innovation supports the nesting of graphs, such that a graph can be included in another graph as a single step for processing. In addition to the user interface components, the system includes a set of .NET classes that represent the graph internally. These classes provide the internal system representation of the graphical user interface. The system includes a graph execution component that reads the internal representation of the graph (as described above) and executes that graph. The execution of the graph follows the interpreted model of execution in that each node is traversed and executed from the original internal representation. In addition, there are components that allow external code elements, such as algorithms, to be easily integrated into the system, thus making the system infinitely expandable.

Alphonso, Keith↗
NASA NTRS2004

Microscopic and Metallurgical Aspects of the Space Shuttle Columbia Accident Investigation and Reconstruction

The Space Shuttle Columbia was descending for a landing at the Kennedy Space Center (KSC) on February 1, 2003. Approximately 20 minutes prior to touchdown, the Columbia began disintegrating over the western United States; the majority of debris eventually impacted in eastern Texas and western Louisiana. A monumental effort eventually recovered approximately 84,000 pieces of debris, approximately 38% of the Orbiter's original dry weight. The debris was transported to KSC, where the items were catalogued and evaluated. Critical areas of interest, such as the left and right leading edge surfaces and the underside of the ship, were placed upon a grid to aid in the reconstruction. Items of interest included metallic structures, reinforced carbon-carbon composites, and ceramic heat insulation tiles. Many of the leading edge elements had re-solidified metallic deposits spattered on them. These deposits became known as slag and were one of the main focuses of the investigation. In order to help determine the sequence of events inside the left wing during the accident, the slag's composition, layering order, and directionality of deposition were studied. A myriad of analytical tests were performed in an attempt to ascertain the compositional and depositional characteristics of selected slag deposits, including the ordering of deposited layers within each individual slag deposit harvested. Initially, Scanning Electron Microscopy and Energy Dispersive X-Ray Spectroscopy (SEM/EDX) were performed to quickly characterize the overall composition of individual slag deposits: SEM utilizes a narrowlyfocused high-energy electron beam impinging upon a specimen. The incident beam excites and liberates lower energy secondary electrons, which are detected and analyzed, providing a visual representation of the sample's surface topography. EDX also relies on an incident electron beam, except an EDX unit measures X-ray energies generated by the impinging beam. Each element generates a unique X-ray signature; the EDX detector measures these discreet energies. EDX actually penetrates approximately 2 microns into the bulk of the sample. However, random examination of various portions of slag, coupled with the semiquantitative nature of the SEM/EDX analysis, did not yield convincingly pertinent data. Therefore, X-ray dot mapping was conducted, which provided more understandable data, both in terms of slag layering and composition. An X-ray dot map is generated by performing numerous EDX scans for individual elements, then compiling the scans in a visual representation. Eventually, specimens consisting of not only the slag, but of the adjacent RCC substrate as well were cross-sectioned. X-Ray dot mapping of the materialographicallymounted and -polished cross- sections provided a visual representation of both the layering sequence and compositional characteristics of the slag. Contemporaneously, Electron Spectroscopy for Chemical Analysis/X-Ray Photoelectron Spectroscopy (ESCA/XPS) and powdered X-Ray Diffraction (XRD) were performed to further characterize the deposits and to attempt to identify what, if any, compounds were present. The ESCA/XPS analysis allowed the analyst to "sputter" into the sample with an electron gun, aiding in the identification of the layering sequence. XPS uses photons, rather than electrons, which impinge upon the surface of the sample. XPS measures the electrons emitted from within the first 5 nm of the sample's surface. The XRD measures the scatter angles of incident X-rays; the angle and intensity of scatter depend upon the crystalline structure of the pulverized sample. XRD is considered a qualitative rather than quantitative technique. ESCA/XPS revealed that the final layer to deposit was predominantly carbonaceous. XRD was successful in identifying specific compounds, such as Al 2O3, Al and/or Al3 21SiO47, mullite (3(Al2)O3 -SiO2), and nickel-aluminides. Eventually, Electron MicroProbe Analysis (EMPA) was conducted on the marialographically-prepared cross- sections of selected slag deposits. Microprobe combines SEM and Wavelength Dispersive X-Ray Spectroscopy (WDS), and, like EDX, uses a narrowly-focused high-energy electron beam impinging upon a specimen to elicit, in the case of EPMA, characteristic X-rays with specific wavelengths. This quantitative, analytical tool proved the most useful in determining depositional layering and composition of the slag deposits. This information was utilized in verifying the location of the breach in the left leading edge of the wing of the Columbia.

McDaniels, Steven J.↗
NASA NTRS2012

Statistical Orbit Determination using the Particle Filter for Incorporating Non-Gaussian Uncertainties

The tracking of space objects requires frequent and accurate monitoring for collision avoidance. As even collision events with very low probability are important, accurate prediction of collisions require the representation of the full probability density function (PDF) of the random orbit state. Through representing the full PDF of the orbit state for orbit maintenance and collision avoidance, we can take advantage of the statistical information present in the heavy tailed distributions, more accurately representing the orbit states with low probability. The classical methods of orbit determination (i.e. Kalman Filter and its derivatives) provide state estimates based on only the second moments of the state and measurement errors that are captured by assuming a Gaussian distribution. Although the measurement errors can be accurately assumed to have a Gaussian distribution, errors with a non-Gaussian distribution could arise during propagation between observations. Moreover, unmodeled dynamics in the orbit model could introduce non-Gaussian errors into the process noise. A Particle Filter (PF) is proposed as a nonlinear filtering technique that is capable of propagating and estimating a more complete representation of the state distribution as an accurate approximation of a full PDF. The PF uses Monte Carlo runs to generate particles that approximate the full PDF representation. The PF is applied in the estimation and propagation of a highly eccentric orbit and the results are compared to the Extended Kalman Filter and Splitting Gaussian Mixture algorithms to demonstrate its proficiency.

Mashiku, Alinda↗
NASA NTRS2016

Hybrid Reality Lab Capabilities - Video 2

Our Hybrid Reality and Advanced Operations Lab is developing incredibly realistic and immersive systems that could be used to provide training, support engineering analysis, and augment data collection for various human performance metrics at NASA. To get a better understanding of what Hybrid Reality is, let's go through the two most commonly known types of immersive realities: Virtual Reality, and Augmented Reality. Virtual Reality creates immersive scenes that are completely made up of digital information. This technology has been used to train astronauts at NASA, used during teleoperation of remote assets (arms, rovers, robots, etc.) and other activities. One challenge with Virtual Reality is that if you are using it for real time-applications (like landing an airplane) then the information used to create the virtual scenes can be old (i.e. visualized long after physical objects moved in the scene) and not accurate enough to land the airplane safely. This is where Augmented Reality comes in. Augmented Reality takes real-time environment information (from a camera, or see through window, and places digitally created information into the scene so that it matches with the video/glass information). Augmented Reality enhances real environment information collected with a live sensor or viewport (e.g. camera, window, etc.) with the information-rich visualization provided by Virtual Reality. Hybrid Reality takes Augmented Reality even further, by creating a higher level of immersion where interactivity can take place. Hybrid Reality takes Virtual Reality objects and a trackable, physical representation of those objects, places them in the same coordinate system, and allows people to interact with both objects' representations (virtual and physical) simultaneously. After a short period of adjustment, the individuals begin to interact with all the objects in the scene as if they were real-life objects. The ability to physically touch and interact with digitally created objects that have the same shape, size, location to their physical object counterpart in virtual reality environment can be a game changer when it comes to training, planning, engineering analysis, science, entertainment, etc. Our Project is developing such capabilities for various types of environments. The video outlined with this abstract is a representation of an ISS Hybrid Reality experience. In the video you can see various Hybrid Reality elements that provide immersion beyond just standard Virtual Reality or Augmented Reality.

Delgado, Francisco J.↗
NASA NTRS2018

GeneLab Analysis Working Group Kick-Off Meeting

Goals to achieve for GeneLab AWG - GL vision - Review of GeneLab AWG charter Timeline and milestones for 2018 Logistics - Monthly Meeting - Workshop - Internship - ASGSR Introduction of team leads and goals of each group Introduction of all members Q/A Three-tier Client Strategy to Democratize Data Physiological changes, pathway enrichment, differential expression, normalization, processing metadata, reproducibility, Data federation/integration with heterogeneous bioinformatics external databases The GLDS currently serves over 100 omics investigations to the biomedical community via open access. In order to expand the scope of metadata record searches via the GLDS, we designed a metadata warehouse that collects and updates metadata records from external systems housing similar data. To demonstrate the capabilities of federated search and retrieval of these data, we imported metadata records from three open-access data systems into the GLDS metadata warehouse: NCBI's Gene Expression Omnibus (GEO), EBI's PRoteomics IDEntifications (PRIDE) repository, and the Metagenomics Analysis server (MG-RAST). Each of these systems defines metadata for omics data sets differently. One solution to bridge such differences is to employ a common object model (COM) to which each systems' representation of metadata can be mapped. Warehoused metadata records are then transformed at ETL to this single, common representation. Queries generated via the GLDS are then executed against the warehouse, and matching records are shown in the COM representation (Fig. 1). While this approach is relatively straightforward to implement, the volume of the data in the omics domain presents challenges in dealing with latency and currency of records. Furthermore, the lack of a coordinated has been federated data search for and retrieval of these kinds of data across other open-access systems, so that users are able to conduct biological meta-investigations using data from a variety of sources. Such meta-investigations are key to corroborating findings from many kinds of assays and translating them into systems biology knowledge and, eventually, therapeutics.

GeneLab↗
NASA NTRS2016

Evaluation of Methods for Molecular Dynamics Simulation of Ionic Liquid Electric Double Layers

We investigate how systematically increasing the accuracy of various molecular dynamics modeling techniques influences the structure and capacitance of ionic liquid electric double layers (EDLs). The techniques probed concern long-range electrostatic interactions, electrode charging (constant charge versus constant potential conditions), and electrolyte polarizability. Our simulations are performed on a quasi-two-dimensional, or slab-like, model capacitor, which is composed of a polarizable ionic liquid electrolyte, [EMIM][BF4], interfaced between two graphite electrodes. To ensure an accurate representation of EDL differential capacitance, we derive new fluctuation formulas that resolve the differential capacitance as a function of electrode charge or electrode potential. The magnitude of differential capacitance shows sensitivity to different long-range electrostatic summation techniques, while the shape of differential capacitance is affected by charging technique and the polarizability of the electrolyte. For long-range summation techniques, errors in magnitude can be mitigated by employing two-dimensional or corrected three dimensional electrostatic summations, which lead to electric fields that conform to those of a classical electrostatic parallel plate capacitor. With respect to charging, the changes in shape are a result of ions in the Stern layer (i.e. ions at the electrode surface) having a higher electrostatic affinity to constant potential electrodes than to constant charge electrodes. For electrolyte polarizability, shape changes originate from induced dipoles that soften the interaction of Stern layer ions with the electrode. The softening is traced to ion correlations vertical to the electrode surface that induce dipoles that oppose double layer formation. In general, our analysis indicates an accuracy dependent differential capacitance profile that transitions from the characteristic camel shape with coarser representations to a more diffuse profile with finer representations.

Haskins, Justin B.↗
NASA NTRS2019

Impact of Assimilating Adaptively Thinned AIRS Cloud-Cleared Radiances in the GEOS

This work examines the assimilation of AIRS (Atmospheric Infrared Sounder) radiances from two points of view: the thinning strategy and the use of cloud-cleared radiances as opposed to clear-sky. Previous published work by this team, based on a very large set of Observing System Experiments performed with a 2014 3DVAR version of the GEOS (Goddard Earth Observing System), has shown that the assimilation of adaptively thinned AIRS cloud-cleared radiances (CCRs) improves the representation of tropical cyclones (TCs) without damaging the global forecast skill. The simple adaptive methodology is based on denser AIRS coverage in moving domains centered on TCs, and sparser coverage everywhere else. Subsequent experiments showed that the adaptive methodology produces good results also when applied to clear-sky CrIS (Cross-track Infrared Sounder) and IASI (Infrared Atmospheric Sounding Interferometer) radiances. In addition, the results indicate that the density of all hyperspectral data assimilated over meteorologically inactive areas is excessive, probably because of horizontal error correlation, suggesting that the global thinning should be more aggressive. More recent work focused on the polar regions has shown another positive impact of assimilating cloud-cleared AIRS radiances instead of clear-sky. The results show that high latitude atmospheric dynamics is very sensitive to the representation of the lower tropospheric temperature structure over the Arctic region. Specifically, assimilation of CCRs over areas that are data poor and also affected by broken stratus clouds, and as such minimally observed by AIRS clear-sky radiances, changes substantially the temperature structure over the Arctic low troposphere. Ingestion of CCRs over the region propagates, through hydrostatic adjustments, to mid-tropospheric geopotential height, allowing for better prediction of mid-latitude waves. In addition, adaptively thinned CCRs also improve the representation of mesoscale convective cyclones at high latitudes. An example of an Antarctic low is provided. Finally, recent ongoing work with the hybrid 4DenVAR GEOS, investigating the 2017 boreal TC season, has confirmed the previous results: namely that aggressively thinned cloud-cleared radiances improve TC structure with no loss of global skill.

CCR↗
NASA NTRS2020

Influence of Dynamic Ozone Dry Deposition on Ozone Pollution

Identifying the contributions of chemistry and transport to observed ozone pollution using regional‐to‐global models relies on accurate representation of ozone dry deposition. We use a recently developed configuration of the NOAA GFDL chemistry‐climate model – in which the atmosphere and land are coupled through dry deposition—to investigate the influence of ozone dry deposition on ozone pollution over northern midlatitudes. In our model, deposition pathways are tied to dynamic terrestrial processes, such as photosynthesis and water cycling through the canopy and soil. Small increases in winter deposition due to more process‐based representation of snow and deposition to surfaces reduce hemispheric‐scale ozone throughout the lower troposphere by 5–12 ppb, improving agreement with observations relative to a simulation with the standard configuration for ozone dry deposition. Declining snow cover by the end of the 21st‐century tempers the previously identified influence of rising methane on winter ozone. Dynamic dry deposition changes summer surface ozone by −4 to +7 ppb. While previous studies emphasize the importance of uptake by plant stomata, new diagnostic tracking of depositional pathways reveals a widespread impact of nonstomatal deposition on ozone pollution. Daily variability in both stomatal and nonstomatal deposition contribute to daily variability in ozone pollution. Twenty‐first century changes in summer deposition result from a balance among changes in individual pathways, reflecting differing responses to both high carbon dioxide (through plant physiology versus biomass accumulation) and water availability. Our findings highlight a need for constraints on the processes driving ozone dry deposition to test representation in regional‐to‐global models.

dry deposition↗
NASA NTRSDate not supplied

Developing Procedures to Implement Geometric Imperfections Beyond Right Circular Cylindrical Shells in Finite Element Method Models

Analysis of aerospace structures is frequently conducted using nominal dimensions and frequently assumes ideal conditions in loading, contact, constraints, et cetera. Off-nominal dimensions and nonideal conditions, however, are present in all structures. These are the result of widely ranging causes from coefficient of thermal expansion mismatches, manufacturing tooling anomalies, to assembly procedures that inadvertently alter the structure. Specifically, geometric imperfections can have potentially significant influence on the response of a structural test article observed in an experiment versus the response given by a numerical simulation. The Python Tool for Implementing Geometric Imperfections in Reduced Structures (Py_TIGIRS) was previously presented as a set of Python scripts to calculate and implement as-manufactured geometric midsurface and thickness imperfections into finite element method (FEM) shell models of nominally right circular cylinders. By taking advantage of the simple shape of a right circular cylinder, interpolations of the measured data points were able to be performed along directions that aligned to the cylindrical coordinate system axes of the entire structure. By taking advantage of the shell representation of the real structure as opposed to modeling using a continuum representation, the thickness variation was able to be implemented by shell section definitions instead of having to modify the position of multiple nodes in the thickness direction. Py_TIGIRS is a useful tool that established a procedural example on how to implement geometric imperfections in right circular cylindrical shell structures. Three new procedures, each expanded from concepts established in Py_TIGIRS, are proposed for various test-article designs and are intended to broaden the range of structures that can be modeled with measured geometric imperfections in the structural analysis community. Each test-article design introduces new challenges to successfully implement geometric imperfections into a FEM model. The first test-article design consists of a carbon fiber reinforced polymer square plate with a hat-shaped stiffener co-cured on one side. This test-article design was for a novel seven-point bend test that was also previously presented. Manufacturing and cure-cycle imperfections are observed using digital image correlation (DIC) techniques. As thermal expansion coefficient mismatches between the plate and stiffener materials were anticipated, a thermal analysis study with continuum shell and solid elements was conducted to capture the global shape observed prior to testing. The second test-article design is of a similar hat-stiffened plate configuration, but with a side length ratio near 3:1 with elongation in the stiffener direction. The test article was used to characterize the response to uniaxial compressive loading in the direction of the stiffener. Due to differing manufacturing steps, a thermal analysis like the one developed for the seven-point bend configuration was unable to mimic the observed geometric imperfections. Instead, a strategy based on applying deformations directly to the structure during analysis was developed for continuum shell and solid element representation of a stiffened panel.

Geometric imperfections↗
NASA NTRS2021

Drought Variability over the Conterminous United States for the past century

We examine the drought variability over the Conterminous United States (CONUS) for 1915-2018 using the Noah-MP land-surface model. We examine different model options on drought reconstruction including optional representation of groundwater and dynamic vegetation phenology. Over our 104-year reconstruction period, we identify 12 great droughts that each covered at least 36% of CONUS and lasted for at least 5 months. The great droughts tend to have smaller areas when groundwater and/or dynamic vegetation are included in the model configuration. We detect a small decreasing trend in dry area coverage over CONUS in all configurations. We identify 45 major droughts in the baseline (with a dry area coverage greater than 23.6% of CONUS) that are, on average, somewhat less severe than great droughts. We find that representation of groundwater tends to increase drought duration for both great and major droughts, primarily by leading to earlier drought onset (some due to short-lived recovery from a previous drought) or later demise (groundwater anomalies lag precipitation anomalies). In contrast, representation of dynamic vegetation tends to shorten major droughts duration, primarily due to earlier drought demise ( closed stoma or dead vegetation reduces ET loss during droughts). On a regional basis, the U.S. Southwest (Southeast) has the longest (shortest) major drought durations. Consistent with earlier work, dry area coverage in all subregions except the Southwest has decreased. The effects of groundwater and dynamic vegetation vary regionally due to differences in groundwater depths (hence connectivity with the surface) and vegetation types.

drought↗
NASA NTRSDate not supplied

Exploring Semantic Search Capability of Graph Convolutions Over a Knowledge Graph Built Using Earth Science Corpora

Traditional knowledge graphs tend to be too generic, and often perform poorly on complex scientific queries. Often times, precedence is given to pop culture over scientific knowledge for queries. This is predominantly due to the use of internet sources for building the knowledge graph. With this work, we aim to explore the effectiveness of combining a knowledge graph generated from earth science corpora with a language model and graph convolutions for the purpose of surfacing latent and related sentences given a natural language query. In this model, sentences are conceptualized in the graph as nodes which are connected through entities—words and phrases of interest found in the text—extracted using Google Cloud’s entity extraction model. The language model we used for this is Bidirectional Encoder Representations from Transformers (BERT).The sentences are given a numeric representation by the BERT model. Graph convolutions are then applied to sentence embeddings in order to obtain a vector representation of the sentence as well as the surrounding graph structure, thereby leveraging the power of adjacency inherently encoded in graph structures. With this presentation, we demonstrate the ability of graph convolutions and their improved ability to surface relevant, latent information based on the subject of the input query.

Muthukumaran Ramasubramanian↗
NASA NTRS2021

Evaluation and Intercomparison of Wildfire Smoke Forecasts from Multiple Modeling Systems for the 2019 Williams Flats Fire

Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from 12 state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, US, August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within 1 d are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models, with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by fire radiative power (FRP)-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019, mainly over the transported smoke plumes, owing to the underestimated emissions on 7 August. In contrast, the surface smoke PM2.5 (sPM2.5) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM2.5. Overpredictions of sPM2.5 are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center's Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 3–8 August, the plume height became deeper, with a day-to-day range of about 2–9 km a.g.l. However, narrower ranges are found for all models, with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported smoke that is 1 d old. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated for by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.

AOD↗