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At least 127 records · Page 7
All sourcesNASA NTRSDOE OSTI
NASA NTRS2012

A Multiscale Computational Model of the Response of Swine Epidermis After Acute Irradiation

Radiation exposure from Solar Particle Events can lead to very high skin dose for astronauts on exploration missions outside the protection of the Earth s magnetic field [1]. Assessing the detrimental effects to human skin under such adverse conditions could be predicted by conducting territorial experiments on animal models. In this study we apply a computational approach to simulate the experimental data of the radiation response of swine epidermis, which is closely similar to human epidermis [2]. Incorporating experimentally measured histological and cell kinetic parameters into a multiscale tissue modeling framework, we obtain results of population kinetics and proliferation index comparable to unirradiated and acutely irradiated swine experiments [3]. It is noted the basal cell doubling time is 10 to 16 days in the intact population, but drops to 13.6 hr in the regenerating populations surviving irradiation. This complex 30-fold variation is proposed to be attributed to the shortening of the G1 phase duration. We investigate this radiation induced effect by considering at the sub-cellular level the expression and signaling of TGF-beta, as it is recognized as a key regulatory factor of tissue formation and wound healing [4]. This integrated model will allow us to test the validity of various basic biological rules at the cellular level and sub-cellular mechanisms by qualitatively comparing simulation results with published research, and should lead to a fuller understanding of the pathophysiological effects of ionizing radiation on the skin.

FROM↗
NASA NTRS2013

The Role of Model and Initial Condition Error in Numerical Weather Forecasting Investigated with an Observing System Simulation Experiment

A series of experiments that explore the roles of model and initial condition error in numerical weather prediction are performed using an observing system simulation experiment (OSSE) framework developed at the National Aeronautics and Space Administration Global Modeling and Assimilation Office (NASA/GMAO). The use of an OSSE allows the analysis and forecast errors to be explicitly calculated, and different hypothetical observing networks can be tested with ease. In these experiments, both a full global OSSE framework and an 'identical twin' OSSE setup are utilized to compare the behavior of the data assimilation system and evolution of forecast skill with and without model error. The initial condition error is manipulated by varying the distribution and quality of the observing network and the magnitude of observation errors. The results show that model error has a strong impact on both the quality of the analysis field and the evolution of forecast skill, including both systematic and unsystematic model error components. With a realistic observing network, the analysis state retains a significant quantity of error due to systematic model error. If errors of the analysis state are minimized, model error acts to rapidly degrade forecast skill during the first 24-48 hours of forward integration. In the presence of model error, the impact of observation errors on forecast skill is small, but in the absence of model error, observation errors cause a substantial degradation of the skill of medium range forecasts.

Model Error↗
NASA NTRS2019

A Joint NICER and XMM-Newton View of the "Magnificent" Thermally Emitting X-ray Isolated Neutron Star RX J1605.3+3249

Thermally emitting X-ray isolated neutron stars (NSs) represent excellent targets for testing cooling surface emission and atmosphere models, which are used to infer the physical parameters of the NS. Among the seven known members of this class, RXJ1605.3+3249 is the only one that still lacks confirmation of its spin period. Here we analyze NICER and XMM-Newton observations of RXJ1605.3+3249, in order to address its timing and spectral behavior. Contrary to a previous tentative detection, but in agreement with the recent work by Pires et al., we find no significant pulsation with a pulsed fraction higher than 1.3% (3σ) for periods above 150 ms. We also find a limit of 2.6% for periods above 2 ms, despite searches in different energy bands. The X-ray spectrum can be fit by either a double-blackbody model or by a single-temperature magnetized atmosphere model, both modified by a Gaussian absorption line at ∼0.44 keV. The origin of the absorption feature as a proton cyclotron line or as an atomic transition in the NS atmosphere is discussed. The predictions of the best-fit X-ray models extended to IR, optical, and UV bands, are compared with archival data. Our results are interpreted in the framework of a fallback disk scenario.

Christian Malacaria↗
NASA NTRS2005

A Comparative Study of Probability Collectives Based Multi-agent Systems and Genetic Algorithms

We compare Genetic Algorithms (GA's) with Probability Collectives (PC), a new framework for distributed optimization and control. In contrast to GA's, PC-based methods do not update populations of solutions. Instead they update an explicitly parameterized probability distribution p over the space of solutions. That updating of p arises as the optimization of a functional of p. The functional is chosen so that any p that optimizes it should be p peaked about good solutions. The PC approach works in both continuous and discrete problems. It does not suffer from the resolution limitation of the finite bit length encoding of parameters into GA alleles. It also has deep connections with both game theory and statistical physics. We review the PC approach using its motivation as the information theoretic formulation of bounded rationality for multi-agent systems. It is then compared with GA's on a diverse set of problems. To handle high dimensional surfaces, in the PC method investigated here p is restricted to a product distribution. Each distribution in that product is controlled by a separate agent. The test functions were selected for their difficulty using either traditional gradient descent or genetic algorithms. On those functions the PC-based approach significantly outperforms traditional GA's in both rate of descent, trapping in false minima, and long term optimization.

Huang, Chien-Feng↗
NASA NTRS1998

Efficient Methods to Assimilate Satellite Retrievals Based on Information Content: Suboptimal Retrieval Assimilation - Part 2

One of the outstanding problems in data assimilation has been and continues to be how best to utilize satellite data while balancing the tradeoff between accuracy and computational cost. A number of weather prediction centers have recently achieved remarkable success in improving their forecast skill by changing the method by which satellite data are assimilated into the forecast model from the traditional approach of assimilating retrievals to the direct assimilation of radiances in a variational framework. The operational implementation of such a substantial change in methodology involves a great number of technical details, e.g., pertaining to quality control procedures, systematic error correction techniques, and tuning of the statistical parameters in the analysis algorithm. Although there are clear theoretical advantages to the direct radiance assimilation approach, it is not obvious at all to what extent the improvements that have been obtained so far can be attributed to the change in methodology, or to various technical aspects of the implementation. The issue is of interest because retrieval assimilation retains many practical and logistical advantages which may become even more significant in the near future when increasingly high-volume data sources become available. The central question we address here is: how much improvement can we expect from assimilating radiances rather than retrievals, all other things being equal? We compare the two approaches in a simplified one-dimensional theoretical framework, in which problems related to quality control and systematic error correction are conveniently absent. By assuming a perfect radiative transfer model and perfect knowledge of radiance and background error covariances, we are able to formulate a nonlinear local error analysis for each assimilation method. Direct radiance assimilation is optimal in this idealized context, while the traditional method of assimilating retrievals is suboptimal because it ignores the cross-covariances between background errors and retrieval errors. We show that interactive retrieval assimilation (where the same background used for assimilation is also used in the retrieval step) is equivalent to direct assimilation of radiances with suboptimal analysis weights. We illustrate and extend these theoretical arguments with several one-dimensional assimilation experiments, where we estimate vertical atmospheric profiles using simulated data from both the High-resolution InfraRed Sounder 2 (HIRS2) and the future Atmospheric InfraRed Sounder (AIRS).

Joiner, J.↗
NASA NTRS1996

A Comparison of Structurally Connected and Multiple Spacecraft Interferometers

Structurally connected and multiple spacecraft interferometers are compared in an attempt to establish the maximum baseline (referred to as the "cross-over baseline") for which it is preferable to operate a single-structure interferometer in space rather than an interferometer composed of numerous, smaller spacecraft. This comparison is made using the total launched mass of each configuration as the comparison metric. A framework of study within which structurally connected and multiple spacecraft interferometers can be compared is presented in block diagram form. This methodology is then applied to twenty-two different combinations of trade space parameters to investigate the effects of different orbits, orientations, truss materials, propellants, attitude control actuators, onboard disturbance sources, and performance requirements on the cross-over baseline. Rotating interferometers and the potential advantages of adding active structural control to the connected truss of the structurally connected interferometer are also examined. The minimum mass design of the structurally connected interferometer that meets all performance-requirements and satisfies all imposed constraints is determined as a function of baseline. This minimum mass design is then compared to the design of the multiple spacecraft interferometer. It is discovered that the design of the minimum mass structurally connected interferometer that meets all performance requirements and constraints in solar orbit is limited by the minimum allowable aspect ratio, areal density, and gage of the struts. In the formulation of the problem used in this study, there is no advantage to adding active structural control to the truss for interferometers in solar orbit. The cross-over baseline for missions of practical duration (ranging from one week to thirty years) in solar orbit is approximately 400 m for non-rotating interferometers and 650 m for rotating interferometers.

Surka, Derek M.↗
NASA NTRS1983

Structural optimization by multilevel decomposition

A method is described for decomposing an optimization problem into a set of subproblems and a coordination problem which preserves coupling between the subproblems. The method is introduced as a special case of multilevel, multidisciplinary system optimization and its algorithm is fully described for two level optimization for structures assembled of finite elements of arbitrary type. Numerical results are given for an example of a framework to show that the decomposition method converges and yields results comparable to those obtained without decomposition. It is pointed out that optimization by decomposition should reduce the design time by allowing groups of engineers, using different computers to work concurrently on the same large problem.

Sobieszczanski-Sobieski, J.↗
NASA NTRS2001

Biogeochemical Response to Mesoscale Physical Forcing in the California Current System

In the first part of the project, we investigated the local response of the coastal ocean ecosystems (changes in chlorophyll, concentration and chlorophyll, fluorescence quantum yield) to physical forcing by developing and deploying Autonomous Drifting Ocean Stations (ADOS) within several mesoscale features along the U.S. west coast. Also, we compared the temporal and spatial variability registered by sensors mounted in the drifters to that registered by the sensors mounted in the satellites in order to assess the scales of variability that are not resolved by the ocean color satellite. The second part of the project used the existing WOCE SVP Surface Lagrangian drifters to track individual water parcels through time. The individual drifter tracks were used to generate multivariate time series by interpolating/extracting the biological and physical data fields retrieved by remote sensors (ocean color, SST, wind speed and direction, wind stress curl, and sea level topography). The individual time series of the physical data (AVHRR, TOPEX, NCEP) were analyzed against the ocean color (SeaWiFS) time-series to determine the time scale of biological response to the physical forcing. The results from this part of the research is being used to compare the decorrelation scales of chlorophyll from a Lagrangian and Eulerian framework. The results from both parts of this research augmented the necessary time series data needed to investigate the interactions between the ocean mesoscale features, wind, and the biogeochemical processes. Using the historical Lagrangian data sets, we have completed a comparison of the decorrelation scales in both the Eulerian and Lagrangian reference frame for the SeaWiFS data set. We are continuing to investigate how these results might be used in objective mapping efforts.

Niiler, Pearn P.↗
NASA NTRS2006

A Test of Sensitivity to Convective Transport in a Global Atmospheric CO2 Simulation

Two approximations to convective transport have been implemented in an offline chemistry transport model (CTM) to explore the impact on calculated atmospheric CO2 distributions. GlobalCO2 in the year 2000 is simulated using theCTM driven by assimilated meteorological fields from the NASA s Goddard Earth Observation System Data Assimilation System, Version 4 (GEOS-4). The model simulates atmospheric CO2 by adopting the same CO2 emission inventory and dynamical modules as described in Kawa et al. (convective transport scheme denoted as Conv1). Conv1 approximates the convective transport by using the bulk convective mass fluxes to redistribute trace gases. The alternate approximation, Conv2, partitions fluxes into updraft and downdraft, as well as into entrainment and detrainment, and has potential to yield a more realistic simulation of vertical redistribution through deep convection. Replacing Conv1 by Conv2 results in an overestimate of CO2 over biospheric sink regions. The largest discrepancies result in a CO2 difference of about 7.8 ppm in the July NH boreal forest, which is about 30% of the CO2 seasonality for that area. These differences are compared to those produced by emission scenario variations constrained by the framework of Intergovernmental Panel on Climate Change (IPCC) to account for possible land use change and residual terrestrial CO2 sink. It is shown that the overestimated CO2 driven by Conv2 can be offset by introducing these supplemental emissions.

Bian, H.↗
NASA NTRS2021

Changes in TOA SW Fluxes over Marine Clouds When Estimated via Semiphysical Angular Distribution Models

Top-of-atmosphere (TOA) shortwave (SW) angular distribution models (ADMs) approximate—per angular direction of an imagined upward hemisphere—the intensity of sunlight scattered back from a specific Earth–atmosphere scene. ADMs are, thus, critical when converting satellite-borne broadband radiometry into estimated radiative fluxes. This paper applies a set of newly developed ADMs with a more refined scene definition and demonstrates tenable changes in estimated fluxes compared to currently operational ADMs. Newly developed ADMs use a semiphysical framework to consider cloud-top effective radius (¯¯R_e) and above-cloud water vapor (ACWV), in addition to accounting for surface wind speed and clouds’ phase, fraction, and optical depth. In effect, instantaneous TOA SW fluxes for marine liquid-phase clouds had the largest flux differences (of up to 25 W m−2) for lower solar zenith angles and cloud optical depth greater than 10 due to extremes in ¯¯R_e or ACWV. In regions where clouds had persistently extreme levels of ¯¯R_e (here mostly for ¯¯R_e < 7μm and ¯¯R_e > 15μm) or ACWV, instantaneous fluxes estimated from Aqua, Terra, Meteosat-8, and Meteosat-9 satellites using the two ADMs differed systematically, resulting in significant deviations in daily mean fluxes (up to ±10 W m^(−2)) and monthly mean fluxes (up to ±5 W m^(−2)). Flux estimates using newly developed, semiphysical ADMs may contribute to a better understanding of solar fluxes over low-level clouds. It remains to be seen whether aerosol indirect effects are impacted by these updates.

angular distribution models (ADMs)↗
NASA NTRS2021

NASA SpaceCube Edge TPU SmallSat Card for Autonomous Operations and Onboard Science-Data Analysis

Using state-of-the-art artificial intelligence (AI)frameworks onboard spacecraft is challenging because common spacecraft processors cannot provide comparable performance to datacenters with server-grade CPUs and GPUs available for terrestrial applications and advanced deep-learning networks. This limitation makes small, lo w-p o we r AI microchip architectures, such as the Google Coral Edge Tensor Processing Unit (TPU), attractive for space missions where the application-specific design enables both high-performance and power-efficient computing for AI applications. To address these challenging considerations for space deployment, this research introduces the design and capabilities of a CubeSat-sized Edge TPU-based co-processor card, known as the SpaceCube Low-power Ed g e Artificial Intelligence Resilient Node (SC-LEARN). This design conforms to NASA’s CubeSat Card Specification (CS2) for integration into next-generation SmallSat and CubeSat systems. This paper describes the overarching architecture and design of the SC-LEARN, as well as, the supporting test card designed for rapid prototyping and evaluation. The SC-LEARN was developed with three operational modes: (1) a high-performance parallel-processing mode,(2)a fault-tolerant mode for onboard resilience, and (3) a power-saving mode with cold spares. Importantly, this research also elaborates on both training and quantization of Tensor Flow models for the SC-LEARN for use onboard with representative, open-source datasets. Lastly, we describe future research plans, including radiation-beam testing and flight demonstration.

Advanced avionics↗
NASA NTRS2007

GVIPS Models and Software

Two reports discuss, respectively, (1) the generalized viscoplasticity with potential structure (GVIPS) class of mathematical models and (2) the Constitutive Material Parameter Estimator (COMPARE) computer program. GVIPS models are constructed within a thermodynamics- and potential-based theoretical framework, wherein one uses internal state variables and derives constitutive equations for both the reversible (elastic) and the irreversible (viscoplastic) behaviors of materials. Because of the underlying potential structure, GVIPS models not only capture a variety of material behaviors but also are very computationally efficient. COMPARE comprises (1) an analysis core and (2) a C++-language subprogram that implements a Windows-based graphical user interface (GUI) for controlling the core. The GUI relieves the user of the sometimes tedious task of preparing data for the analysis core, freeing the user to concentrate on the task of fitting experimental data and ultimately obtaining a set of material parameters. The analysis core consists of three modules: one for GVIPS material models, an analysis module containing a specialized finite-element solution algorithm, and an optimization module. COMPARE solves the problem of finding GVIPS material parameters in the manner of a design-optimization problem in which the parameters are the design variables.

Arnold, Steven M.↗
NASA NTRS2014

Development Context Driven Change Awareness and Analysis Framework

Recent work on workspace monitoring allows conflict prediction early in the development process, however, these approaches mostly use syntactic differencing techniques to compare different program versions. In contrast, traditional change-impact analysis techniques analyze related versions of the program only after the code has been checked into the master repository. We propose a novel approach, DeCAF (Development Context Analysis Framework), that leverages the development context to scope a change impact analysis technique. The goal is to characterize the impact of each developer on other developers in the team. There are various client applications such as task prioritization, early conflict detection, and providing advice on testing that can benefit from such a characterization. The DeCAF framework leverages information from the development context to bound the iDiSE change impact analysis technique to analyze only the parts of the code base that are of interest. Bounding the analysis can enable DeCAF to efficiently compute the impact of changes using a combination of program dependence and symbolic execution based approaches.

Sarma, Anita↗
NASA NTRS2014

Development Context Driven Change Awareness and Analysis Framework

Recent work on workspace monitoring allows conflict prediction early in the development process, however, these approaches mostly use syntactic differencing techniques to compare different program versions. In contrast, traditional change-impact analysis techniques analyze related versions of the program only after the code has been checked into the master repository. We propose a novel approach, De- CAF (Development Context Analysis Framework), that leverages the development context to scope a change impact analysis technique. The goal is to characterize the impact of each developer on other developers in the team. There are various client applications such as task prioritization, early conflict detection, and providing advice on testing that can benefit from such a characterization. The DeCAF framework leverages information from the development context to bound the iDiSE change impact analysis technique to analyze only the parts of the code base that are of interest. Bounding the analysis can enable DeCAF to efficiently compute the impact of changes using a combination of program dependence and symbolic execution based approaches.

Change Awareness↗
NASA NTRS2020

Computational Design of Eutectic Molten Salt Mixtures: What Can Thermodynamic Models Do?

In the search for efficient energy storage battery technologies, designing stable electrolytes has been a long-standing challenge. Electrolytes based on molten salt eutectics are known for their stability with minimum parasitic reactions when compared to their widely used organic counterparts. However, the operating temperatures of these molten salt electrolyte-based batteries are dictated by the melting point of the eutectic mixtures. Design and high throughput screening of low melting temperature eutectic molten salt mixtures have been hindered by the lack of computational models. In this work, we develop thermodynamic models to predict the eutectic points of several molten salt mixtures. The framework of the COSMO-SAC model is used for the predictions and is compared with experimental data and other thermodynamic approaches. Rapid thermodynamics-based approaches, as shown in this study, can accelerate the discovery of new materials, complementing experimental techniques.

Ashwin Ravichandran↗
NASA NTRSDate not supplied

SAGE III/ISS Rapid Data Analysis Through Dashboarding with Jupyter Notebooks

Spaceborne remote sensing observations of Earth’s atmosphere produce significant quantities of data over the life of each mission. In the case of the Stratospheric Aerosol and Gas Experiment III on the International Space Station (SAGE III/ISS) nearly four years of vertical profiles of atmospheric ozone, water vapor, and nitrogen dioxide concentrations as well as aerosol extinction coefficients have been released. The dichotomy of the desire for both long-term trends in the atmospheric state alongside the assessment of short-term impacts of major disruptive events such as volcanic eruptions and pyrocumulus injections requires agile tools to handle these cases in near real-time as new data are produced. The analysis landscape is further complicated by the desire to compare results between the numerous contemporary observations available for a given dataset. The SAGE III/ISS team has developed a suite of tools leveraging modern web-based frameworks allowing members to interact with a dashboard-style interface to load the data record, assess new profiles as they are generated and in ensemble, compare between species, and additionally add in measurements observed by other platforms as necessary. Leveraging a commonly packaged data format of NetCDF alongside the Python Jupyter Notebook framework, the data can be served to interested parties from an analysis server while still runnable on personal systems if required. This presentation illustrates the ecosystem developed by the SAGE III/ISS team, the applicability to measurements made by any limb-observing platform, and the benefit to transforming routine analyses into readily accessible dynamic plots. Frameworks currently exist at larger scales with projects such as GIOVANNI, and this illustration seeks to show that similar frameworks are accessible and possible within the local research environment while simultaneously unloading human processing cycles for more specialized analysis tasks.

Dashboarding↗
NASA NTRS2013

Center-TRACON Automation System (CTAS) En Route Trajectory Predictor Requirements and Capabilities

This requirements framework document is designed to support the capture of requirements and capabilities for state-of-the-art trajectory predictors (TPs). This framework has been developed to assist TP experts in capturing a clear, consistent, and cross-comparable set of requirements and capabilities. The goal is to capture capabilities (types of trajectories that can be built), functional requirements (including inputs and outputs), non-functional requirements (including prediction accuracy and computational performance), approaches for constraint relaxation, and input uncertainties. The sections of this framework are based on the Common Trajectory Predictor structure developed by the FAA/Eurocontrol Cooperative R&D Action Plan 16 Committee on Common Trajectory Prediction. It is assumed that the reader is familiar with the Common TP Structure.1 This initial draft is intended as a first cut capture of the En Route TS Capabilities and Requirements. As such, it contains many annotations indicating possible logic errors in the CTAS code or in the description provided. It is intended to work out the details of the annotations with NASA and to update this document at a later time.

framework↗
NASA NTRS1972

Random response of rectangular panels to the pressure field beneath a turbulent boundary layer in subsonic flows

The response of a rectangular panel under the excitation of a turbulent boundary layer with a zero longitudinal mean pressure gradient in a subsonic flow was studied in detail. The method of normal mode was used together with the technique of spectral analysis. Both simply supported and clamped edge conditions of a panel were considered, and the displacement power spectral density of the panel response was computed. The results for the clamped edge panel compare favorably with existing data. Charts of structural acceptance, which provide a framework for estimating the response of other rectangular panels, are presented, and the physical significances of structural acceptances discussed.

Chyu, W. J.↗