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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.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2002

Nonlinear Propagation of Planet-Generated Tidal Waves

The propagation and evolution of planet-generated density waves in protoplanetary disks is considered. The evolution of waves, leading to shock formation and wake dissipation, is followed in the weakly nonlinear regime. The 2001 local approach of Goodman and Rafikov is extended to include the effects of surface density and temperature variations in the disk as well as the disk cylindrical geometry and nonuniform shear. Wave damping due to shocks is demonstrated to be a nonlocal process spanning a significant fraction of the disk. Torques induced by the planet could be significant drivers of disk evolution on timescales of approx. 10(exp 6)-10(exp 7) yr, even in the absence of strong background viscosity. A global prescription for angular momentum deposition is developed that could be incorporated into the study of gap formation in a gaseous disk around the planet.

Rafikov, R. R.↗
NASA NTRS2004

Implicit and Explicit Spacecraft Gyro Calibration

This paper presents a comparison between two approaches to sensor calibration. According to one approach, called explicit, an estimator compares the sensor readings to reference readings, and uses the difference between the two to estimate the calibration parameters. According to the other approach, called implicit, the sensor error is integrated to form a different entity, which is then compared with a reference quantity of this entity, and the calibration parameters are inferred from the difference. In particular this paper presents the comparison between these approaches when applied to in-flight spacecraft gyro calibration. Reference spacecraft rate is needed for gyro calibration when using the explicit approach; however, such reference rates are not readily available for in-flight calibration. Therefore the calibration parameter-estimator is expanded to include the estimation of that reference rate, which is based on attitude measurements in the form of attitude-quaternion. A comparison between the two approaches is made using simulated data. It is concluded that the performances of the two approaches are basically comparable. Sensitivity tests indicate that the explicit filter results are essentially insensitive to variations in given spacecraft dynamics model parameters.

Bar-Itzhack, Itzhack Y.↗
NASA NTRS2009

Estimating Accurate Relative Spacecraft Angular Position from DSN VLBI Phases Using X-Band Telemetry or DOR Tones

At present spacecraft angular position with Deep Space Network (DSN) is determined using group delay estimates from very long baseline interferometer (VLBI) phase measurements employing differential one way ranging (DOR) tones. As an alternative to this approach, we propose estimating position of a spacecraft to half a fringe cycle accuracy using time variations between measured and calculated phases as the Earth rotates using DSN VLBI baseline(s). Combining fringe location of the target with the phase allows high accuracy for spacecraft angular position estimate. This can be achieved using telemetry signals of at least 4-8 MSamples/sec data rate or DOR tones.

x-band telemetry↗
NASA NTRS2018

Implementation of J-A Methodology Elastic-Plastic Crack Instability Analysis Capability into the WARP-3D Code

Characterization of the near crack-tip stress/strain fields is the foundation of fracture mechanics. The description of the near tip stress field and the prediction of when fracture occurs is well established for brittle materials that exhibit linear elastic behavior. However, in ductile materials or conditions that violate linear elastic assumptions (Aluminum alloys, Al 2024-T3, Al 2024- T351 etc.), the elastic-plastic crack-tip stress fields are characterized by the Hutchison-Rice-Rosengren (HRR) field. The J-integral is commonly used to characterize amplitude of the HRR field under elastic-plastic conditions. The J-integral has been demonstrated for crack-tip fields that are under high constraint conditions (i.e., small-scale plasticity where the J-dominance is maintained). However, as the external load increases, yielding changes from small- to largescale plasticity and usually a loss of constraint (i.e., reduction in the triaxial stress field along the crack front). The loss of constraint leads to the deviation of the crack-tip stress fields from that given by the HRR field. Hence, the J-dominance will be gradually lost and additional parameter(s) are required to quantify the crack-tip stress fields and predict fracture behavior. The assessment objectives were to: 1) implement a two-parameter (i.e., J-A) fracture criterion into an elastic-plastic three-dimensional (3D) finite element analysis (FEA), 2) validate the implementation by comparison with the A parameter from literature data, 3) conduct material characterization tests to quantify the material behavior and provide fracture data for validation of the J-A fracture criteria, and (4) perform evaluations to establish if the J-A criteria can be used to predict fracture in a ductile metallic material (e.g., aluminum alloys). The A parameter in these criteria is the second parameter in a three-term elastic-plastic asymptotic expansion of the neartip stress behavior. A series of extensive FEAs were performed using WARP3D software package to obtain solutions for the A parameter for different specimen configurations. The methodology needed for the estimation of the A parameter in the asymptotic expansion was developed and implemented using Matlab®. A user material (UMAT) routine was used to model the material stress-strain response using a Ramberg-Osgood power law with a hardening exponent (n) and a material coefficient (alpha). This UMAT routine was successfully implemented in WARP3D software and validated through comparison with the experimental data. Three configurations were extracted from published results: 1) center cracked plate (CCP), 2) single edge-cracked plate (SECP), and 3) double edge-cracked plate (DECP). These configurations and four other configurations (three-hole tension (THT)), three-point bend (3PTB), three-hole compact tension (3PCT), and compact tension (CT)) were analyzed to verify the methodology that was developed and implemented into WARP3D. Solutions of the A parameter were obtained for remote tension loading conditions that started with small-scale yielding and continued into the large-scale plasticity regime. The results indicate that the methodology developed can be used to calculate the elastic-plastic J-A parameters for test specimens with a range of crack geometries, material strain hardening behaviors, and loading conditions. The J-A parameters were implemented as fracture criteria and used to predict the test results. For comparison, other fracture criteria were used to predict the same test results. Major findings include: The A constraint parameter A varies with specimen type and applied load thus accurate determination is crucial in predicting the failure load, and the A parameter is asymptotic as the failure load is approached, making an accurate determination difficult (i.e., small differences in the A parameter can cause large variations in failure load) for materials exhibiting elastic-plastic behavior. The failure predictions from J-A methodology were more accurate than the traditionally used KC and J methods, and have comparable scatter to that observed when using the crack-tip opening angle (CTOA) method. However, the J-A methodology requires considerable effort (expertise level and labor) to implement and to evaluate the A parameter for different specimen types and materials, or to apply this methodology to part-through crack (e.g., 3D problems) structural applications.

Hamm, Kenneth R., Jr.↗
NASA NTRSDate not supplied

Simulating a Low-Weight Encoding of the Fermi-Hubbard Model Feedback and Support with QAOA

Recent work [1] has proposed a compact fermion-to-qubit mapping for the Fermi-Hubbard model (FHM), potentially lowering the overhead needed to simulate such a system on quantum hardware. In prior work [2], we numerically investigated how well a quantum annealer could prepare ground states of the FHM encoded using the resource-efficient mapping. In order to compare these results to gate-model systems, we turn to a QAOA-style approach and replace the annealing schedule with both Trotterizations thereof and also more general Hamiltonian-variational ansatze based on the terms of the mapped FH Hamiltonian. We investigate the achievable ground state fidelities of these gate sequences, consider various optimizations of the ansatze structure, and offer resource estimations of the optimized QAOA protocols for near-term hardware.

quantum computing↗
DOE OSTI2020

PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction

Understanding protein structure-function relationships is a key challenge in computational biology, with applications across the biotechnology and pharmaceutical industries. While it is known that protein structure directly impacts protein function, many functional prediction tasks use only protein sequence. In this work, we isolate protein structure to make functional annotations for proteins in the Protein Data Bank in order to study the expressiveness of different structure-based prediction schemes. We present PersGNN - an end-to-end trainable deep learning model that combines graph representation learning with topological data analysis to capture a complex set of both local and global structural features. While variations of these techniques have been successfully applied to proteins before, we demonstrate that our hybridized approach, PersGNN, outperforms either method on its own as well as a baseline neural network that learns from the same information. PersGNN achieves a 9.3% boost in area under the precision recall curve (AUPR) compared to the best individual model, as well as high F1 scores across different gene ontology categories, indicating the transferability of this approach.

Swenson, Nicolas↗
DOE OSTI2022

Arctic Shrub Expansion, Plant Functional Trait Variation, and Effects on Belowground Carbon Cycling (Final Technical Report)

Terrestrial ecosystems are undergoing dramatic changes in response to climate warming, and these changes are expected to feedback to the atmosphere, potentially altering the trajectory of future climate change. Feedbacks from Arctic ecosystems are a major concern because the Arctic is projected to warm significantly in the 21 st century and because >50% of global belowground organic carbon is stored in permafrost and overlying soils. Warming-driven release of this carbon could drastically increase atmospheric greenhouse gas concentrations and accelerate climate warming. Plant communities are also responding to warming, as evidenced by the widely documented increase in woody-shrub growth and “greening” across much of the Arctic tundra biome. This vegetation shift may offset or amplify warming by altering carbon cycling. The direction and magnitude of shrub effects remain highly uncertain, however, due to limited understanding of the consequences of shrub expansion for belowground carbon cycling and simplification of these relationships in models. The major shrubs expanding in the Arctic (Betula, Salix, and Alnus) vary widely with respect to aboveground and belowground traits (e.g., tissue production and chemistry, rooting depth, microbial symbionts), and may also exhibit substantial intraspecific variation in these traits in response to environmental conditions. Such variation is likely to have profound implications for soil carbon cycling. The overarching goal of this project was to improve process-based understanding of the influence of shrub expansion on carbon cycling to enable improved representation of carbon dynamics in ecosystem and Earth system models. We investigated how plant functional traits vary among shrub genera, respond to environmental conditions, and affect belowground carbon and nutrient cycling by quantifying relationships among functional traits and biogeochemical cycling along edaphic gradients nested within a climate gradient in the Alaskan tundra. We found consistent differences in leaf and root traits among shrub genera and between shrubs and a widespread sedge species, indicating diverse nutrient acquisition strategies and belowground impacts among different arctic shrubs. We also found striking differences in trait values among individuals within the same species or genera within sites. Soil parameters were more important than climate parameters for predicting size and leaf trait variation, and root trait responses were less dependent on climate overall. For all but one root trait, including parameters representing aboveground traits improved the predictive ability of models. These results demonstrate that tundra shrub traits vary considerably at local scales and soil factors drive this variation, especially belowground. Furthermore, leveraging information about aboveground traits and soil conditions can improve predictions of how belowground traits will respond to climate change. Despite these differences, soil carbon and nitrogen pools in the active layer did not vary among plots dominated by different shrub or sedge genera. Instead, pool sizes generally decreased from warmer to colder sites, consistent with a productivity gradient. Patterns of isotopic N composition indicate that shrubs tighten nitrogen cycling via nitrogen resorption or immobilization of shrub litter. Overall, these results suggest that further identifying the specific shrub genera in the tundra landscape will ultimately provide better predictions of belowground dynamics across the changing arctic. We also performed simulation experiments with the Terrestrial Ecosystem Model (TEM) incorporated in the Predictive Ecosystem Analyzer (PEcAn) framework, treats model parameters as probability distributions, estimates parameters based on a synthesis of available field data, and then quantifies both model sensitivity and uncertainty to a given parameter or suite of parameters. We performed simulations across different types of tundra, including shrub tundra. One key finding was that both model sensitivity and uncertainty to a given parameter could vary within the same type of tundra, but in a different geographical location, such as over the climate gradient of shrub tundra described above. We organized a special session at the annual meeting of the Ecological Society of America in August 2019 to disseminate our results, refine recommendations for model improvement, and initiate collaborations to implement these recommendations in existing models of tundra carbon dynamics at ecosystem to Earth system scales. Our results support DOE near-term priorities by providing mechanistic insights into the role of vegetation change in the terrestrial carbon cycle in a region that is inadequately represented in Earth system models. Current models reduce the complexity of Arctic vegetation to a small number of plant functional types (PFTs). This approach implicitly assumes that each PFT represents the average ecological function of its constituent species, thus ignoring the effects of trait variation on biogeochemical cycling and potentially leading to large uncertainty in the sign and magnitude of ecosystem feedbacks to climate. By quantifying variation of plant functional traits across broad gradients of climatic and edaphic conditions and elucidating the linkages of such variation with carbon and nutrient cycling, our results illustrate the need and create a foundation for further developing trait-based modeling approaches that allow the traits of PFTs to vary as a function of environmental conditions. These approaches should improve the capacity of simulation models to offer insights into ecosystem carbon dynamics associated with novel plant communities in a rapidly changing Arctic.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1999

Ultrasound Thermal Field Imaging of Opaque Fluids

We have initiated an experimental program to develop an ultrasound system for non-intrusively imaging the thermal field in opaque fluids under an externally imposed temperature gradient. Many industrial processes involve opaque fluids, such as molten metals, semiconductors, and polymers, often in situations in which thermal gradients are important. For example, one may wish to understand semiconductor crystal growth dynamics in a Bridgman apparatus. Destructive testing of the crystal after the process is completed gives only indirect information about the fluid dynamics of the formation process. Knowledge of the coupled thermal and velocity fields during the growth process is then essential. Most techniques for non-intrusive velocity and temperature measurement in fluids are optical in nature, and hence the fluids studied must be transparent. In some cases (for example, LDV (laser Doppler velocimetry) and PIV (particle imaging velocimetry)) the velocities of small neutrally buoyant seed particles suspended in the fluid, are measured. Without particle seeding one can use the variation of the index of refraction of the fluid with temperature to visualize, through interferometric, Schlieren or shadowgraph techniques, the thermal field. The thermal field in turn gives a picture of the pattern existing in the fluid. If the object of study is opaque, non-optical techniques must be used. In this project we focus on the use of ultrasound, which propagates easily through opaque liquids and solids. To date ultrasound measurements have almost exclusively relied on the detection of sound scattered from density discontinuities inside the opaque material of interest. In most cases it has been used to visualize structural properties, but more recently the ultrasound Doppler velocimeter has become available. As in the optical case, it relies on seed particles that scatter Doppler shifted sound back to the detector. Doppler ultrasound techniques are, however, not useful for studying convective fluid flow in crystal growth, because particle seeding is unacceptable and flow velocities are typically too low to be resolved, and may be even lower in microgravity conditions where buoyancy forces are negligible. We will investigate a different use of ultrasound to probe the flows of opaque fluids non-intrusively and without the use of seed particles: our goal is to ultrasonically visualize the thermal field of opaque fluids with relatively high spatial resolution. The proposed technique relies upon the variation of sound speed with temperature of the fluid. A high frequency ultra-sound pulse passing through a fluid-filled chamber will traverse the chamber in a time determined by the relevant chamber dimension and the temperature of the fluid through which the pulse passes. With high time-resolution instrumentation that compares the excitation signal with the received pulse we can detect the influence of the fluid temperature on the pulse travel time. This is effectively an interferometric system, which in its optical form is an extremely sensitive approach to measuring thermal fields in fluids. Moreover, the temperature dependence of sound velocity in liquid metals is comparable to the temperature dependence of the speed of light required for accurate interferometric thermal images in transparent fluids. With an array of transducers scanned electronically a map of the thermal field over the chamber could be produced. An alternative approach would be to use the ultrasound analog of the shadowgraph technique. In the optical version, collimated light passes through the fluid, where it is focused or defocused locally by temperature field induced variations of the index of refraction. The resulting image reveals the thermal field through the spatial pattern of light intensity variations. By analogy, an ultrasound plane wave traversing an opaque fluid sample would be also locally focused or defocused depending on the speed of sound variations, giving rise to spatial variations in sound intensity that will reveal the thermal field pattern. These approaches could be applied to any situation in which temperature differences are expected to occur, and will rapidly provide information about the flow that simply cannot be obtained by any current intrusive or non-intrusive diagnostic technique. As materials processing in microgravity matures it will become increasingly important to have available simple and versatile diagnostic tools, such as we will develop, for studying the flows of opaque fluids under thermal forcing.

Andereck, C. David↗
DOE OSTI2020

Characterizing Peatland Microtopography Using Gradient and Microform-Based Approaches

Abstract Peatlands represent an important component of the global carbon cycle, storing 180–621 Gt of carbon (C). Small-scale spatial variations in elevation, frequently referred to as microtopography, influence ecological processes associated with the peatland C cycle, including Sphagnum photosynthesis and methane flux. Microtopography can be characterized with measures of topographic variability and by using conceptual classes (microforms) linked to function: most commonly hummocks and hollows. However, the criteria used to define these conceptual classes are often poorly described, if at all, and vary between studies. Such inconsistencies compel development of explicit quantitative methods to classify microforms. Furthermore, gradient-based characterizations that describe spatial variability without the use of microforms are lacking in the literature. Therefore, the objectives of this study were to (1) calculate peatland microtopographical elevation gradients and measures of spatial variability, (2) develop three microform classification methods intended for specific purposes, and (3) evaluate and contrast classification methods. Our results suggest that at spatial scales much larger than microforms, elevation distributions are unimodal and are well approximated with parametric probability density functions. Results from classifications were variable between methods and years and exhibited significant differences in mean hollow areal coverages of a raised ombrotrophic bog. Our results suggest that the conceptualization and classification of microforms can significantly influence microtopographic structural metrics. The three explicit methods for microform classification described here may be used and built upon for future applications.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Atomic Ordering-Induced Ensemble Variation in Alloys Governs Electrocatalyst On/Off States

The catalytic behavior of a material is influenced by ensembles—the geometric configuration of atoms. Traditional approaches, mainly utilizing solid-solution alloys in electrocatalysis, have often overlooked the challenges posed by concurrent changes in the electronic structure (i.e. d-band center) when the composition is altered. Here, this study introduces a methodology that distinctly separates the geometric effects (i.e. ensembles) from the electronic structure. We compare the reactivity of compositionally identical, but structurally different Pd 3 Bi ordered intermetallic and solid-solution alloys. Remarkably, we find that Pd 3 Bi intermetallics display nearly no reactivity for the methanol oxidation (MOR), while their solid-solution counterparts have significant reactivity. This highlights a unique case where materials with identical chemical compositions demonstrate drastically different catalytic behavior underscoring the critical importance of ensembles in electrocatalysis. Specifically, Pd 3 Bi intermetallics form smaller ensembles (average coordination number: 4.5 ± 1.6) with almost no measurable MOR activity at room temperature, in contrast to the solid-solution Pd 3 Bi that exhibit larger ensembles (average coordination number: 6.8 ± 0.9) and considerable MOR reactivity (0.5 mA cm −2 Pd ). An ordered Pd 3 Bi alloy, with an intermediate ensemble size (average coordination number: 5.3 ± 1.2), displays moderate MOR activity (0.1 mA cm −2 Pd ), further confirming the direct correlation between ensemble size and catalytic activity. Notably, all Pd 3 Bi alloys maintain similar electronic structures, because the chemical composition of the alloys is fixed, indicating that the differences in reactivity are predominantly from changes to the ensemble size. Our findings offer an approach for precisely controlling catalytic activity through manipulating the geometric configuration of the atoms within an alloy, paving the way for more efficient catalyst design.

alloys↗
NASA NTRS1994

Northern middle-latitude ozone profile features and trends observed by SBUV and Umkehr, 1979-1990

A comparison of Umkehr ozone profile data with the reprocessed solar backscatter ultraviolet (SBUV) ozone data in the northern middle-latitude region, 30 deg to 50 deg N, is reported. Although significant biases exist between the two types of observations, the long-term variations and least squares linear regression trends agree remarkably well over the comparison period of 1979 to 1990. The ozone trend in the upper stratosphere is of the order of -0.9%/yr. Near 25 km, little if any trend appears, but a larger negative trend is seen in the lower stratosphere near 15 km. Comparisons show that the average annual ozone cycles in the profiles also agree well. The upper stratospheric ozone results are consistent with photochemical model predictions of ozone depletion near 40 km that are due to the release of anthropogenically produced chlorofluorocarbons. The lower stratospheric ozone trend results are in reasonable agreement with published ozonesonde data trends. It is shown that the ozone trends in the lower stratospheric layers impact significantly on the total ozone trend of the order of -0.47%/yr. The good agreement now seen between the two types of observations suggest that the combined ground-based and satellite approach could provide a valuable database for long-term monitoring of stratospheric ozone for trends and extraordinary variations.

Deluisi, J. J.↗
NASA NTRS2004

Laser Sounder for Global Measurement of CO2 Concentrations in the Troposphere from Space: Progress

We describe progress toward developing a laser-based technique for the remote measurement of the tropospheric CO2 concentrations from orbit. Our goal is to demonstrate a lidar technique and instrument technology that will permit measurements of the CO2 column abundance in the lower troposphere from aircraft at the few ppm level, with a capability of scaling to permit global CO2 measurements from orbit. Accurate measurements of the tropospheric CO2 mixing ratio from space are challenging due to the many potential error sources. These include possible interference from other trace gas species, the effects of temperature, clouds, aerosols & turbulence in the path, changes in surface reflectivity, and variability in dry air density caused by changes in atmospheric pressure, water vapor and topographic height. Some potential instrumental errors include frequency drifts in the transmitter, small transmission and sensitivity drifts in the instrument. High signal-to-noise ratios and measurement stability are needed for mixing ratio estimates at the few ppm level. We have been developing a laser sounder approach as a candidate for a future space mission. It utilizes multiple different laser transmitters to permit simultaneous measurement of CO2 and O2 extinction, and aerosol backscatter in the same measurement path. It directs the narrow co-aligned laser beams from the instrument's fiber lasers toward nadir, and measures the energy of the strong laser echoes reflected from the Earth's land and water surfaces. During the measurement its narrow linewidth lasers are rapidly tuned on- and off- selected CO2 line near 1572 nm and an O2 absorption line near 770 nm. The receiver measures the energies of the laser echoes from the surface and any clouds and aerosols in the path with photon counting detectors. Ratioing the on- to off-line echo pulse energies for each gas permits the column extinction and column densities of CO2 and O2 to be estimated simultaneously via the differential absorption lidar technique. For the on-line wavelengths, the side of the selected absorption lines are used, which due to pressure broadening, weights the measurements to the lower troposphere, where CO2 variations caused by surface sources and sinks are largest. Simultaneous measurements of O2 column abundance are made using an identical approach using an O2 line. The laser backscatter profiles from clouds and aerosols are measured with other lidar channels, which permits identifying measurements influenced by clouds and/or aerosol scattering in the path. For space use, our lidar would continuously measure at nadir in near polar circular orbit. Using dawn and dusk measurements made over the same region will make it possible to sample the diurnal variations in CO2 mixing ratios. A 1-m diameter telescope is used for the receiver for all wavelengths. When averaging over 50 seconds, our calculations show a SNR of approximately 1500 is achievable for each gas at each on- and off-line measurement. Measurements from such a mission can be used to generate monthly global maps of the lower tropospheric CO2 column abundance. Our calculations show global coverage with an accuracy of a few ppm with a spatial resolution of approximately 50,000 sq. km are achievable each month. We have demonstrated some key elements of the laser, detector and receiver approaches in the laboratory and with measurements over a 206 m horizontal path. These include stable measurements of CO2 line shapes in an absorption cell using a fiber laser amplifier seeded by a tunable diode laser, measurement of small amplitude changes at low optical signal levels with the PMT receiver, and comparison of the horizontal path measurements of CO2 against those from an in-situ instrument.

Abshire, J. B.↗
DOE OSTI2025

Genomic Analysis of the Natural Variation of Fatty Acid Composition in Seed Oils of Camelina sativa

Camelina sativa is an oilseed crop that has shown strong promise as a biofuel feedstock. The profile of fatty acids greatly influences the oil quality; however, genetic mechanisms that determine the natural variation of fatty acid composition in camelina are not fully understood. A genome wide association study (GWAS) was performed to uncover genetic loci that may contribute to the contents of major fatty acids such as oleic and linolenic acids in camelina seed. Two approaches were taken to improve the GWAS efficiency. First, growing a diversity panel of 212 accessions in four locations and two nitrogen fertilization conditions revealed great variation in fatty acid contents in seeds. Second, using an improved reference genome, abundant markers, including 203,320 single nucleotide polymorphisms (SNPs) and 99,067 insertions/deletions (indels), were developed, which refined the population structure of the diversity panel. GWAS resulted in 118 genetic markers across 31 trait/treatment conditions. Closely linked markers were determined based on linkage decay and by comparing secondarily associated markers when highly associated ones were removed. Candidate genes were examined by comparing the pangenomes of 12 high-quality reference genomes. This study provides new resources to understand seed lipid metabolism and improve camelina oils through molecular breeding.

Life Sciences & Biomedicine - Other Topics↗
DOE OSTI2024

Weak boundary conditions for Lagrangian shock hydrodynamics: A high-order finite element implementation on curved boundaries

Here, we propose a new Nitsche-type approach for weak enforcement of normal velocity boundary conditions for a Lagrangian discretization of the compressible shock-hydrodynamics equations using high-order finite elements on curved boundaries. Specifically, the variational formulation is appropriately modified to enforce free-slip wall boundary conditions, without perturbing the structure of the function spaces used to represent the solution, with a considerable simplification with respect to traditional approaches. Total energy is conserved and the resulting mass matrices are constant in time. The robustness and accuracy of the proposed method are validated with an extensive set of tests involving nontrivial curved boundaries.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS2010

Architecture-Based Unit Testing of the Flight Software Product Line

This paper presents an analysis of the unit testing approach developed and used by the Core Flight Software (CFS) product line team at the NASA GSFC. The goal of the analysis is to understand, review, and reconunend strategies for improving the existing unit testing infrastructure as well as to capture lessons learned and best practices that can be used by other product line teams for their unit testing. The CFS unit testing framework is designed and implemented as a set of variation points, and thus testing support is built into the product line architecture. The analysis found that the CFS unit testing approach has many practical and good solutions that are worth considering when deciding how to design the testing architecture for a product line, which are documented in this paper along with some suggested innprovennents.

Ganesan, Dharmalingam↗
NASA NTRS1975

Time-dependent hydrodynamic phenomena in the envelopes of the Be stars

Temporal and angular variations in the motion and distribution of circumstellar material about Be stars are studied by means of a simple hydrodynamical approach. The flow variables are each written as the sum of a known, steady-state axisymmetric term and a smaller component which contains both temporal and angular dependence. Substitution of these dichotomous expressions for the flow variables into Euler's equation and the continuity equation leads to a set of linearized equations for the terms which depend on time and angle. Solutions can be found to a somewhat approximated version of the linearized equations, and these solutions explain the qualitative features of the observed short-time variations.

Morgan, T. H.↗
NASA NTRS2004

Human-Induced Climate Variations Linked to Urbanization: From Observations to Modeling

The goal of this session is to bring together scientists from interdisciplinary backgrounds to discuss the data, scientific approaches and recent results focusing on the impact of urbanization on the climate. The discussion will highlight current observational and modeling capabilities being employed for investigating the urban environment and its linkage to the change in the Earth's climate system. The goal of the session is to identify our current stand and the future direction on the topic. Urbanization is one of the extreme cases of land use change. Most of population of the world has moved to urban areas. By 1995, more than 70% of population of North America and Europe were living in cities. By 2025, the United Nations estimates that 60% of the worlds population will live in cities. Although currently only 1.2% of the land is urban, better understanding of how the atmosphere-ocean-land-biosphere components interact as a coupled system and the influence of human activities on this system is critical. Our understanding of urbanization effect is incomplete, partly because human activities induce new changes on climate in addition to the original natural variations, and partly because previously few data available for study urban effect globally. Urban construction changes surface roughness, albedo, heat capacity and vegetation coverage. Traffic and industry increase atmospheric aerosol. It is suggested that urbanization may modify rainfall processes through aerosol-cloud interactions or dynamic feedbacks. Because urbanization effect on climate is determined by many factors including land cover, the city's microscale features, population density, and human lifestyle patterns, it is necessary to study urban areas over globe.

Shepherd, J. Marshall↗
DOE OSTI2020

Kensor: Coordinated Intelligence from Co-Located Sensors

Internet of Things (IoT) is becoming more pervasive in many installations, including homes, manufacturing plants, and industrial facilities of all kinds. The data that IoT produces is a reflection of usual behavior such as daily routines and scheduled tasks, but also from unexpected behavior due to unintentional or undesirable abnormalities. Here, we focus on achieving coordinated intelligence about normal and abnormal phenomena from multiple sensors that are geographically colocated in close proximity, monitoring and controlling a set of co-located devices. Given a set of co-located sensors, we seek an intelligent approach that would automatically determine the “normal” patterns of behaviors among the correlated sensors. After normal behavior is extracted, later monitoring should detect any deviant variations over time. An example application is an entry monitoring and alert system for facilities such as nuclear reactors, where badge readers, door locks, lights, weight trackers and other co-located sensors at the entry point are collectively tracked. To address this problem, we identify the possible solution approach that can be used to solve its different variants. The implemented model is developed as a combination of rules and Markov Chain methods.

Kotevska, Olivera↗