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NASA NTRS1989

Correlative visualization techniques for multidimensional data

Critical to the understanding of data is the ability to provide pictorial or visual representation of those data, particularly in support of correlative data analysis. Despite the advancement of visualization techniques for scientific data over the last several years, there are still significant problems in bringing today's hardware and software technology into the hands of the typical scientist. For example, there are other computer science domains outside of computer graphics that are required to make visualization effective such as data management. Well-defined, flexible mechanisms for data access and management must be combined with rendering algorithms, data transformation, etc. to form a generic visualization pipeline. A generalized approach to data visualization is critical for the correlative analysis of distinct, complex, multidimensional data sets in the space and Earth sciences. Different classes of data representation techniques must be used within such a framework, which can range from simple, static two- and three-dimensional line plots to animation, surface rendering, and volumetric imaging. Static examples of actual data analyses will illustrate the importance of an effective pipeline in data visualization system.

Treinish, Lloyd A.↗

NASA NTRS1989

Globally convergent techniques in nonlinear Newton-Krylov

Some convergence theory is presented for nonlinear Krylov subspace methods. The basic idea of these methods is to use variants of Newton's iteration in conjunction with a Krylov subspace method for solving the Jacobian linear systems. These methods are variants of inexact Newton methods where the approximate Newton direction is taken from a subspace of small dimensions. The main focus is to analyze these methods when they are combined with global strategies such as linesearch techniques and model trust region algorithms. Most of the convergence results are formulated for projection onto general subspaces rather than just Krylov subspaces.

Brown, Peter N.↗

NASA NTRS1991

Spatial operator approach to under-actuated manipulator kinematics and dynamics

A study is made of the kinematics and dynamics of under-actuated manipulators. The presence of passive hinges causes the kinematics and dynamics of these manipulators to be considerably more complex when compared with fully actuated manipulators. Techniques from the spatial operator algebra are used to develop expressions for the generalized Jacobian, the mass matrix, and an efficient inverse dynamics computational algorithm.

Jain, A.↗

NASA NTRS1993

Accuracy control in Monte Carlo radiative calculations

The general accuracy law that rules the Monte Carlo, ray-tracing algorithms used commonly for the calculation of the radiative entities in the thermal analysis of spacecraft are presented. These entities involve transfer of radiative energy either from a single source to a target (e.g., the configuration factors). or from several sources to a target (e.g., the absorbed heat fluxes). In fact, the former is just a particular case of the latter. The accuracy model is later applied to the calculation of some specific radiative entities. Furthermore, some issues related to the implementation of such a model in a software tool are discussed. Although only the relative error is considered through the discussion, similar results can be derived for the absolute error.

Almazan, P. Planas↗

NASA NTRS1993

Code Validation Study for Base Flows

New and old rocket launch concepts recommend the clustering of motors for improved lift capability. The flowfield of the base region of the rocket is very complex and can contain high temperature plume gases. These hot gases can cause catastrophic problems if not adequately designed for. To assess the base region characteristics, advanced computational fluid dynamics (CFD) is being used. As a precursor to these calculations the CFD code requires validation on base flows. The primary objective of this code validation study was to establish a high level of confidence in predicting base flows with the USA CFD code. USA has been extensively validated for fundamental flows and other applications. However, base heating flows have a number of unique characteristics so it was necessary to extend the existing validation for this class of problems. In preparation for the planned NLS 1.5 Stage base heating analysis, six case sets were studied to extend the USA code validation data base. This presentation gives a cursive review of three of these cases. The cases presented include a 2D axi-symmetric study, a 3D real nozzle study, and a 3D multi-species study. The results of all the studies show good general agreement with data with no adjustments to the base numerical algorithms or physical models in the code. The study proved the capability of the USA code for modeling base flows within the accuracy of available data.

Ascoli, Edward P.↗

NASA NTRS1990

High spatial resolution restoration of IRAS images

A general technique to improve the spatial resolution of the IRAS AO data was developed at The Aerospace Corporation using the Maximum Entropy algorithm of Skilling and Gull. The technique has been applied to a variety of fields and several individual AO MACROS. With this general technique, resolutions of 15 arcsec were achieved in 12 and 25 micron images and 30 arcsec in 60 and 100 micron images. Results on galactic plane fields show that both photometric and positional accuracy achieved in the general IRAS survey are also achieved in the reconstructed images.

Grasdalen, Gary L.↗

NASA NTRS1997

Error Analysis System for Spacecraft Navigation Using the Global Positioning System (GPS)

The Flight Dynamics Division (FDD) at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC) is currently developing improved space-navigation filtering algorithms to use the Global Positioning System (GPS) for autonomous real-time onboard orbit determination. In connection with a GPS technology demonstration on the Small Satellite Technology Initiative (SSTI)/Lewis spacecraft, FDD analysts and programmers have teamed with the GSFC Guidance, Navigation, and Control Branch to develop the GPS Enhanced Orbit Determination Experiment (GEODE) system. The GEODE system consists of a Kalman filter operating as a navigation tool for estimating the position, velocity, and additional states required to accurately navigate the orbiting Lewis spacecraft by using astrodynamic modeling and GPS measurements from the receiver. A parallel effort at the FDD is the development of a GPS Error Analysis System (GEAS) that will be used to analyze and improve navigation filtering algorithms during development phases and during in-flight calibration. For GEAS, the Kalman filter theory is extended to estimate the errors in position, velocity, and other error states of interest. The estimation of errors in physical variables at regular intervals will allow the time, cause, and effect of navigation system weaknesses to be identified. In addition, by modeling a sufficient set of navigation system errors, a system failure that causes an observed error anomaly can be traced and accounted for. The GEAS software is formulated using Object Oriented Design (OOD) techniques implemented in the C++ programming language on a Sun SPARC workstation. The Phase 1 of this effort is the development of a basic system to be used to evaluate navigation algorithms implemented in the GEODE system. This paper presents the GEAS mathematical methodology, systems and operations concepts, and software design and implementation. Results from the use of the basic system to evaluate navigation algorithms implemented on GEODE are also discussed. In addition, recommendations for generalization of GEAS functions and for new techniques to optimize the accuracy and control of the GPS autonomous onboard navigation are presented.

Truong, S. H.↗

NASA NTRS1992

On the Retrieval and Analysis of Multilevel Clouds

An accurate satellite retrieval of cloud properties depends upon the detection and analysis of multilayered, overlapping cloud systems that surface observations show to be common. Multiple cloud layers are often found, for instance, in frontal situations, where cirrus overlays boundary layer convective cloud or low-to mid-level stratus cloud. Surface observers (Hahan et al., 1982) indicate that over ocean in the Northern Hemisphere between 30 deg. N and 60 deg. N, 51 percent of observations are of multilevel clouds. A satellite analysis by Coakley (1983) over the Pacific Ocean finds that more than 50 percent of 500 (250 sq km) frames exhibit evidence of multilayered cloud systems. The questions addressed in this study are the following: What error is introduced when inferring the cloud pressure from a Field-Of-View (FOV) that contains some arbitrary amount of transparent cloud overlaying a lower-level black cloud, such as stratus, by making the assumption that there is only a single cloud layer in the FOV, and what may be done to improve the cloud retrieval? The CO2 slicing methods (e.g. McCleese and Wilson, 1976; Smith and Platt, 1978; Chahine, 1974) have been shown to provide accurate means of inferring cirrus cloud altitude from passive infrared radiance measurements. The CO2 techniques have been applied to radiometric data from several instruments, notably the High Resolution Infrared Radiometric Sounder (HIRS/2, hereafter referred to as HIRS), the VISSR Atmospheric Sounder (VAS) (e.g., Menzel et al., 1983; Wylie and Menzel, 1989), and most recently to the High Resolution Interferometer Sounder (HIS) (Smith and Frey, 1990). The methods take advantage of the fact that infrared CO2 sounding channels spaced closely in wavenumber each have varying opacity to CO2, thereby causing each channel to be sensitive to a different level in the atmosphere. The techniques have been shown to be effective for single-layered, nonblack, mid- to high-level clouds such as cirrus, but are generally applied operationally to any given cloud occurrence. The CO2 slicing algorithms are most accurate for clouds than occur in a single, well-defined layer, or for multi-layered cloud cases in which the uppermost cloud layer is nearly black. Significant cloud height retrieval errors may ensue if the HIRS Field-Of-View (FOV) is cotaminated with low cloud. McCleese and Wilson (1976) have shown that the retrieved cloud height for the case of multiple cloud layers is a weighted average of the cloud heights actually present. The weight is approximately proportional to the product of the cloud heigt and the effective cloud amount. The effect of their result is that the uppermost cloud layer dominates the cloud pressure retrieval. Beyond stating that the higher cloud dominates the cloud pressure retrieval, there is no quantitative information to provide a way of estimating the errors in cloud pressure retrieval one should expect for certain common multilevel cloud situations or any suggestions on how to reduce the errors. In this paper we estimate the magnitude of the errors and use a simple algorithm to reduce the errors in optically thin cloud height retrival.

Baum, Bryan A.↗

NASA NTRS1997

Comparison of N2O Emissions from Soils at Three Temperate Agricultural Sites

Nitrous oxide (N2O) flux simulations by four models were compared with year-round field measurements from five temperate agricultural sites in three countries. The field sites included an unfertilized, semi-arid rangeland with low N2O fluxes in eastern Colorado, USA; two fertilizer treatments (urea and nitrate) on a fertilized grass ley cut for silage in Scotland; and two fertilized, cultivated crop fields in Germany where N2O loss during the winter was quite high. The models used were daily trace gas versions of the CENTURY model, DNDC, ExpertN, and the NASA-Ames version of the CASA model. These models included similar components (soil physics, decomposition, plant growth, and nitrogen transformations), but in some cases used very different algorithms for these processes. All models generated similar results for the general cycling of nitrogen through the agro-ecosystems, but simulated nitrogen trace gas fluxes were quite different. In most cases the simulated N20 fluxes were within a factor of about 2 of the observed annual fluxes, but even when models produced similar N2O fluxes they often produced very different estimates of gaseous N loss as nitric oxide (NO), dinitrogen (N2), and ammonia (NH3). Accurate simulation of soil moisture appears to be a key requirement for reliable simulation of N2O emissions. All models simulated the general pattern of low background fluxes with high fluxes following fertilization at the Scottish sites, but they could not (or were not designed to) accurately capture the observed effects of different fertilizer types on N2O flux. None of the models were able to reliably generate large pulses of N2O during brief winter thaws that were observed at the two German sites. All models except DNDC simulated very low N2O fluxes for the dry site in Colorado. The US Trace Gas Network (TRAGNET) has provided a mechanism for this model and site intercomparison. Additional intercomparisons are needed with these and other models and additional data sets; these should include both tropical agro-ecosystems and new agricultural management techniques designed for sustainability.

Frolking, S. E.↗

NASA NTRS2004

Latent Heating from TRMM Satellite Measurements

Rainfall production is the fundamental variable within the Earth's hydrological cycle because it is both the principal forcing term in surface water budgets and its energetics corollary, latent heating, is the principal source of atmospheric diabatic heating. Latent heat release itself is a consequence of phase changes between the vapor, liquid, and frozen states of water. The properties of the vertical distribution of latent heat release modulate large-scale meridional and zonal circulations within the tropics - as well as modifying the energetic efficiencies of midlatitude weather systems. This paper focuses on the retrieval of latent heat release from satellite measurements generated by the Tropical Rainfall Measuring Mission (TRMM) satellite observatory, which was launched in November 1997 as a joint American-Japanese space endeavor. Since then, TRMM measurements have been providing an accurate four-dimensional account of rainfall over the global tropics and sub-tropics, information which can be used to estimate the space-time structure of latent heating across the Earth's low latitudes. The paper examines how the observed TRMM distribution of rainfall has advanced an understanding of the global water and energy cycle and its consequent relationship to the atmospheric general circulation and climate via latent heat release. A set of algorithm methodologies that are being used to estimate latent heating based on rain rate retrievals from the TRMM observations are described. The characteristics of these algorithms and the latent heating products that can be generated from them are also described, along with validation analyses of the heating products themselves. Finally, the investigation provides an overview of how TRMM-derived latent heating information is currently being used in conjunction with global weather and climate models, concluding with remarks intended to stimulate further research on latent heating retrieval from satellites.

Tao, Wei-Kuo↗

NASA NTRS2008

Analysis of Effectiveness of Phoenix Entry Reaction Control System

Interaction between the external flowfield and the reaction control system (RCS) thruster plumes of the Phoenix capsule during entry has been investigated. The analysis covered rarefied, transitional, hypersonic and supersonic flight regimes. Performance of pitch, yaw and roll control authority channels was evaluated, with specific emphasis on the yaw channel due to its low nominal yaw control authority. Because Phoenix had already been constructed and its RCS could not be modified before flight, an assessment of RCS efficacy along the trajectory was needed to determine possible issues and to make necessary software changes. Effectiveness of the system at various regimes was evaluated using a hybrid DSMC-CFD technique, based on DSMC Analysis Code (DAC) code and General Aerodynamic Simulation Program (GASP), the LAURA (Langley Aerothermal Upwind Relaxation Algorithm) code, and the FUN3D (Fully Unstructured 3D) code. Results of the analysis at hypersonic and supersonic conditions suggest a significant aero-RCS interference which reduced the efficacy of the thrusters and could likely produce control reversal. Very little aero-RCS interference was predicted in rarefied and transitional regimes. A recommendation was made to the project to widen controller system deadbands to minimize (if not eliminate) the use of RCS thrusters through hypersonic and supersonic flight regimes, where their performance would be uncertain.

Dyakonov, Artem A.↗

NASA NTRS2015

Spin-Up and Tuning of the Global Carbon Cycle Model Inside the GISS ModelE2 GCM

Planetary carbon cycle involves multiple phenomena, acting at variety of temporal and spacial scales. The typical times range from minutes for leaf stomata physiology to centuries for passive soil carbon pools and deep ocean layers. So, finding a satisfactory equilibrium state becomes a challenging and computationally expensive task. Here we present the spin-up processes for different configurations of the GISS Carbon Cycle model from the model forced with MODIS observed Leaf Area Index (LAI) and prescribed ocean to the prognostic LAI and to the model fully coupled to the dynamic ocean and ocean biology. We investigate the time it takes the model to reach the equilibrium and discuss the ways to speed up this process. NASA Goddard Institute for Space Studies General Circulation Model (GISS ModelE2) is currently equipped with all major algorithms necessary for the simulation of the Global Carbon Cycle. The terrestrial part is presented by Ent Terrestrial Biosphere Model (Ent TBM), which includes leaf biophysics, prognostic phenology and soil biogeochemistry module (based on Carnegie-Ames-Stanford model). The ocean part is based on the NASA Ocean Biogeochemistry Model (NOBM). The transport of atmospheric CO2 is performed by the atmospheric part of ModelE2, which employs quadratic upstream algorithm for this purpose.

Climate model↗

NASA NTRS2016

Recent Progresses in Incorporating Human Land-Water Management into Global Land Surface Models Toward Their Integration into Earth System Models

The global water cycle has been profoundly affected by human land-water management. As the changes in the water cycle on land can affect the functioning of a wide range of biophysical and biogeochemical processes of the Earth system, it is essential to represent human land-water management in Earth system models (ESMs). During the recent past, noteworthy progress has been made in large-scale modeling of human impacts on the water cycle but sufficient advancements have not yet been made in integrating the newly developed schemes into ESMs. This study reviews the progresses made in incorporating human factors in large-scale hydrological models and their integration into ESMs. The study focuses primarily on the recent advancements and existing challenges in incorporating human impacts in global land surface models (LSMs) as a way forward to the development of ESMs with humans as integral components, but a brief review of global hydrological models (GHMs) is also provided. The study begins with the general overview of human impacts on the water cycle. Then, the algorithms currently employed to represent irrigation, reservoir operation, and groundwater pumping are discussed. Next, methodological deficiencies in current modeling approaches and existing challenges are identified. Furthermore, light is shed on the sources of uncertainties associated with model parameterizations, grid resolution, and datasets used for forcing and validation. Finally, representing human land-water management in LSMs is highlighted as an important research direction toward developing integrated models using ESM frameworks for the holistic study of human-water interactions within the Earths system.

biogeochemistry↗

NASA NTRS2019

A Learning-Based Guidance Selection Mechanism for a Formally Verified Sense and Avoid Algorithm

This paper describes a learning-based strategy for selecting conflict avoidance maneuvers for autonomous unmanned aircraft systems. The selected maneuvers are provided by a formally verified algorithm and they are guaranteed to solve any impending conflict under general assumptions about aircraft dynamics. The decision-making logic that selects the appropriate maneuvers is encoded in a stochastic policy encapsulated as a neural network. The network’s parameters are optimized to maximize a reward function. The reward function penalizes loss of separation with other aircraft while rewarding resolutions that result in minimum excursions from the nominal flight plan. This paper provides a description of the technique and presents preliminary simulation results.

Balachandran, Swee↗

DOE OSTI2022

Fiber Bundle Morphisms as a Framework for Modeling Many-to-Many Maps

While it is not generally reflected in the `nice' datasets used for benchmarking machine learning algorithms, the real-world is full of processes that would be best described as many-to-many. That is, a single input can potentially yield many different outputs (whether due to noise, imperfect measurement, or intrinsic stochasticity in the process) and many different inputs can yield the same output (that is, the map is not injective). For example, imagine a sentiment analysis task where, due to linguistic ambiguity, a single statement can have a range of different sentiment interpretations while at the same time many distinct statements can represent the same sentiment. When modeling such a multivalued function $f: X \rightarrow Y$, it is frequently useful to be able to model the distribution on $f(x)$ for specific input $x$ as well as the distribution on fiber $f^{-1}(y)$ for specific output $y$. Such an analysis helps the user (i) better understand the variance intrinsic to the process they are studying and (ii) understand the range of specific input $x$ that can be used to achieve output $y$. Following existing work which used a fiber bundle framework to better model many-to-one processes we describe how morphisms of fiber bundles provide a template for building models which naturally capture the structure of many-to-many processes.

Coda, Elizabeth D.↗

NASA NTRS2004

A Study of Penalty Function Methods for Constraint Handling with Genetic Algorithm

COMETBOARDS (Comparative Evaluation Testbed of Optimization and Analysis Routines for Design of Structures) is a design optimization test bed that can evaluate the performance of several different optimization algorithms. A few of these optimization algorithms are the sequence of unconstrained minimization techniques (SUMT), sequential linear programming (SLP) and the sequential quadratic programming techniques (SQP). A genetic algorithm (GA) is a search technique that is based on the principles of natural selection or "survival of the fittest". Instead of using gradient information, the GA uses the objective function directly in the search. The GA searches the solution space by maintaining a population of potential solutions. Then, using evolving operations such as recombination, mutation and selection, the GA creates successive generations of solutions that will evolve and take on the positive characteristics of their parents and thus gradually approach optimal or near-optimal solutions. By using the objective function directly in the search, genetic algorithms can be effectively applied in non-convex, highly nonlinear, complex problems. The genetic algorithm is not guaranteed to find the global optimum, but it is less likely to get trapped at a local optimum than traditional gradient-based search methods when the objective function is not smooth and generally well behaved. The purpose of this research is to assist in the integration of genetic algorithm (GA) into COMETBOARDS. COMETBOARDS cast the design of structures as a constrained nonlinear optimization problem. One method used to solve constrained optimization problem with a GA to convert the constrained optimization problem into an unconstrained optimization problem by developing a penalty function that penalizes infeasible solutions. There have been several suggested penalty function in the literature each with there own strengths and weaknesses. A statistical analysis of some suggested penalty functions is performed in this study. Also, a response surface approach to robust design is used to develop a new penalty function approach. This new penalty function approach is then compared with the other existing penalty functions.

Ortiz, Francisco↗

DOE OSTI2024

Multi deep learning-based stochastic microstructure reconstruction and high-fidelity micromechanics simulation of time-dependent ceramic matrix composite response

A multi deep learning-based framework is developed for efficient, automated microstructure reconstruction and generation of stochastic representative volume elements (SRVEs) with periodic boundary conditions (PBCs) for accurate modeling of ceramic matrix composite (CMC) response. The methodology comprises a convolutional neural network coupled with regression layers to act as a vanilla regression network for semantic segmentation of the microstructure, allowing accurate characterization of the phases and their distributions at the microscale. Scanning electron microscope and confocal microscope are used to obtain C/SiNC and SiC/SiNC CMCs micrographs for vanilla regression testing. Microstructure variability in terms of fiber volume fraction and porosity are quantified through the output regression layer, ensuring accurate representation of material variability in SRVE construction. Generative adversarial network (GAN) and its variants are designed to produce high-fidelity SRVE, spanning CMCs microstructure variability space. A circular padding algorithm is developed to generate SRVEs with PBCs during training of GANs. The accuracy of the generated SRVEs is established through micromechanics simulations, where an efficient formulation of the high-fidelity generalized methods of cells (HFGMC) approach is used to compute the effective mechanical properties. Furthermore, an iterative algorithm is implemented in the HFGMC solver to simulate time-dependent deformation of SiC/SiNC subjected to creep loading conditions.

36 MATERIALS SCIENCE↗

NASA NTRS2022

Low-Level Jets and the Convergence of Mars Data Assimilation Algorithms

Data assimilation is an increasingly popular technique in Mars atmospheric science, but its effect on the mean states of the underlying atmosphere models has not been thoroughly examined. The robustness of results to the choice of model and assimilation algorithm also warrants further study. We investigate these issues using two Mars general circulation models (MGCMs), with particular emphasis on zonal wind and temperature fields. When temperature retrievals from the Mars Global Surveyor Thermal Emission Spectrometer (TES) are assimilated into the U.K.-Laboratoire de M ́et ́eorologie Dynamique (UK-LMD) MGCM to create the Mars Analysis Correction Data Assimilation (MACDA) reanalysis, low-level zonal jets in the winter northern hemisphere shift equatorward and weaken relative to a free-running control simulation from the same MGCM. The Ensemble Mars Atmosphere Reanalysis System (EMARS) reanalysis, which is also based on TES temperature retrievals, also shows jet weakening (but less if any shifting) relative to a control simulation performed with the underlying Geophysical Fluid Dynamics Laboratory (GFDL) MGCM. Examining higher levels of the atmosphere, monthly mean three-dimensional temperature and zonal wind fields are in generally better agreement between the two reanalyses than between the two control simulations. In conjunction with information about the MGCMs’ physical parametrizations, intercomparisons between the various reanalyses and control simulations suggest that overall the EMARS control run is plausibly less biased (relative to the true state of the Martian atmosphere) than the MACDA control run. Implications for future observational studies are discussed. Plain Language Summary An increasingly popular way to study Martian weather and climate is to combine atmospheric temperature observations with a computer model (specifically, a global climate model). The process of combining model and observations is called “data assimilation”, and the resulting merged data set is called a “reanalysis”. One advantage of reanalyses is that they include variables (such as wind) that are not directly observed. For scientific and practical applications we want these variables to be reasonably accurate— however, it is not clear how well data assimilation algorithms compute them. Our study investigates this issue using two Mars reanalyses and two model simulations that do not assimilate temperature data. We focus on slowly-varying atmospheric phenomena (timescales from 10 Mars days to a season). Assimilating temperature data into two different global climate models changes the strength and/or spatial pattern of east-west winds at low altitudes. Furthermore, monthly mean three-dimensional temperature and east-west wind fields agree better between reanalyses than between non-assimilating model simulations. This suggests that the data assimilation process is basically successful. One non-assimilating model simulation has less realistic representations of atmospheric physical processes than the other—we argue that this plausibly gives it larger biases relative to the true state of the atmosphere.

Todd A Mooring↗