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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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At least 685 records · Page 38
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Facilitating Staging-based Unstructured Mesh Processing to Support Hybrid In-Situ Workflows

In-situ and in-transit processing alleviate the gap between the computing and I/O capabilities by scheduling data analytics close to the data source. Hybrid in-situ processing splits data analytics into two stages: the data processing that runs in-situ aims to extract regions of interest, which are then transferred to staging services for further in-transit analytics. To facilitate this type of hybrid in-situ processing, the data staging service needs to support complex intermediate data representations generated/consumed by the in-situ tasks. Unstructured (or irregular) mesh is one such derived data representation that is typically used and bridges simulation data and analytics. However, how staging services efficiently support unstructured mesh transfer and processing remains to be explored. This paper investigates design options for transferring and processing unstructured mesh data using staging services. Using polygonal mesh data as an example, we show that hybrid in-situ workflows with staging-based unstructured mesh processing can effectively support hybrid in-situ workflows, and can significantly decrease data movement overheads.

data-driven↗
NASA NTRS1981

Multistage classification of multispectral Earth observational data: The design approach

An algorithm is proposed which predicts the optimal features at every node in a binary tree procedure. The algorithm estimates the probability of error by approximating the area under the likelihood ratio function for two classes and taking into account the number of training samples used in estimating each of these two classes. Some results on feature selection techniques, particularly in the presence of a very limited set of training samples, are presented. Results comparing probabilities of error predicted by the proposed algorithm as a function of dimensionality as compared to experimental observations are shown for aircraft and LANDSAT data. Results are obtained for both real and simulated data. Finally, two binary tree examples which use the algorithm are presented to illustrate the usefulness of the procedure.

Bauer, M. E.↗
NASA NTRS1981

Data base management system analysis and performance testing with respect to NASA requirements

Several candidate Data Base Management Systems (DBM's) that could support the NASA End-to-End Data System's Integrated Data Base Management System (IDBMS) Project, later rescoped and renamed the Packet Management System (PMS) were evaluated. The candidate DBMS systems which had to run on the Digital Equipment Corporation VAX 11/780 computer system were ORACLE, SEED and RIM. Oracle and RIM are both based on the relational data base model while SEED employs a CODASYL network approach. A single data base application which managed stratospheric temperature profiles was studied. The primary reasons for using this application were an insufficient volume of available PMS-like data, a mandate to use actual rather than simulated data, and the abundance of available temperature profile data.

Martin, E. A.↗
NASA NTRS1993

A normal stress subgrid-scale eddy viscosity model in large eddy simulation

The Smagorinsky subgrid-scale eddy viscosity model (SGS-EVM) is commonly used in large eddy simulations (LES) to represent the effects of the unresolved scales on the resolved scales. This model is known to be limited because its constant must be optimized in different flows, and it must be modified with a damping function to account for near-wall effects. The recent dynamic model is designed to overcome these limitations but is compositionally intensive as compared to the traditional SGS-EVM. In a recent study using direct numerical simulation data, Horiuti has shown that these drawbacks are due mainly to the use of an improper velocity scale in the SGS-EVM. He also proposed the use of the subgrid-scale normal stress as a new velocity scale that was inspired by a high-order anisotropic representation model. The testing of Horiuti, however, was conducted using DNS data from a low Reynolds number channel flow simulation. It was felt that further testing at higher Reynolds numbers and also using different flows (other than wall-bounded shear flows) were necessary steps needed to establish the validity of the new model. This is the primary motivation of the present study. The objective is to test the new model using DNS databases of high Reynolds number channel and fully developed turbulent mixing layer flows. The use of both channel (wall-bounded) and mixing layer flows is important for the development of accurate LES models because these two flows encompass many characteristic features of complex turbulent flows.

Horiuti, K.↗
NASA NTRS2020

The GGCMI Phase 2 Experiment: Global Gridded Crop Model Simulations Under Uniform Changes in CO2, Temperature, Water, and Nitrogen Levels (Protocol Version 1.0)

Concerns about food security under climate change motivate efforts to better understand future changes in crop yields. Process-based crop models, which represent plant physiological and soil processes, are necessary tools for this purpose since they allow representing future climate and management conditions not sampled in the historical record and new locations to which cultivation may shift. However, process-based crop models differ in many critical details, and their responses to different interacting factors remain only poorly understood. The Global Gridded Crop Model Intercomparison (GGCMI) Phase 2 experiment, an activity of the Agricultural Model Intercomparison and Improvement Project (AgMIP), is designed to provide a systematic parameter sweep focused on climate change factors and their interaction with overall soil fertility, to allow both evaluating model behavior and emulating model responses in impact assessment tools. In this paper we describe the GGCMI Phase 2 experimental protocol and its simulation data archive. A total of 12 crop models simulate five crops with systematic uniform perturbations of historical climate, varying CO2, temperature, water supply, and applied nitrogen (“CTWN”) for rainfed and irrigated agriculture, and a second set of simulations represents a type of adaptation by allowing the adjustment of growing season length. We present some crop yield results to illustrate general characteristics of the simulations and potential uses of the GGCMI Phase 2 archive. For example, in cases without adaptation, modeled yields show robust decreases to warmer temperatures in almost all regions, with a nonlinear dependence that means yields in warmer baseline locations have greater temperature sensitivity. Inter-model uncertainty is qualitatively similar across all the four input dimensions but is largest in high-latitude regions where crops may be grown in the future.

GGCMI↗
DOE OSTI2014

A high-performance workflow system for subsurface simulation

Subsurface modeling applications typically neglect uncertainty in the conceptual models, past or future scenarios, and attribute most or all uncertainty to errors in model parameters. In this contribution, uncertainty in technetium-99 transport in a heterogeneous, deep vadose zone is explored with respect to the conceptual model using a next generation user environment called Akuna. Akuna provides a range of tools to manage environmental modeling projects, from managing simulation data to visualizing results from high-performance computational simulators. Core toolsets accessible through the user interface include model setup, grid generation, parameter estimation, and uncertainty quantification. The BC Cribs site at Hanford in southeastern Washington State is used to demonstrate Akuna capabilities. At the BC Cribs site, conceptualization of the system is highly uncertain because only sparse information is available for the geologic conceptual model, the physical and chemical properties of the sediments, and the history of waste disposal operations. Using the Akuna toolset to perform an analysis of conservative solute transport, significant prediction uncertainty in simulated concentrations is demonstrated by conceptual model variation. This demonstrates that conceptual model uncertainty is an important consideration in sparse data environments such as BC Cribs. It is also demonstrated that Akuna and the underlying toolset provides an integrated modeling environment that streamlines model setup, parameter optimization, and uncertainty analyses for high-performance computing applications.

Akuna↗
DOE OSTI2018

The F-t-Pj-RG method: An adjacent-rolling-windows based steady-state detection technique for application to kinetic Monte Carlo simulations

A window-based steady-state detection algorithm has been developed for application to kinetic Monte Carlo simulation data. The algorithm, termed F-t-Pj-RG sequentially applies an F-test, a t-test, and a projection test on adjacent windows of the data while rolling (or shifting) and growing the windows when any of the tests fail. In aggregate, the algorithm is able to (a) automatically reject the warm-up period as not being at steady-state, as well as (b) determine an appropriate window size for converged statistics when sampling the data, which is necessary for detection of steady-state, and (c) detect steady-state within a particular tolerance. The last step, the projection test, is actually an oscillating-slope projection test, and is performed on j sequential data windows (i.e., more than two adjacent windows). It requires more than simply being within the user defined tolerance: the oscillating-slope projection test includes a condition that the slope must oscillate around zero when 2, which is an additional indication of steady-state. When all three tests are passed, the F-t-Pj test is passed, indicating that the prerequisites of steady-state detection have been met and also that conditions consistent with the definition of steady-state have been realized. This algorithm is applied to a variety of data sets that correspond to the diverse type of data trends that can be produced by kinetic Monte Carlo simulations. The algorithm is shown to be robust in its ability to handle differing functional forms, and is able to detect steady-state with low computational cost. Finally, the low computational cost of this method and its robustness towards varied data trends make it suitable for on-the-fly use in kinetic Monte Carlo simulations.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

HERO WEC V1.0 - WEC-Sim Detailed Simulation Runs and Summary Data

Data sets from simulation runs include 144 wave cases that were run based on the WEC-Sim model (https://mhkdr.openei.org/submissions/483). The 144 wave cases represent waves with the following wave height and wave period ranges: - Significant Wave Height: 0.25 - 4.0m in 0.25m increments - Wave Period: 5 - 13 sec in 1 sec increments Each run was simulated using a Pierson-Moskowitz irregular wave spectrum with a 200 second ramp time and a total simulation time of 2,200 seconds. Summary data set includes a spreadsheet and image files with matrices that are associated with data from simulation runs. All matrices cover the same significant wave height and wave periods from the sim runs, in the same increments. The following matrices are included: - Mechanical Power Input: Absorbed power calculated using linear input velocity at PTO (power take-off) multiplied by winch tension. - Mechanical Power Output: The hydraulic power calculated at the pump output prior to the pressure relief valve dump. - Feed Pressure: Average pressure at RO (reverse osmosis) input prior to pre-filters - RO Power Input: The hydraulic power calculated at the RO system inlet, accounts for flow loss due to pressure relief valve - Water Production: Average clean water flow at RO output

16 TIDAL AND WAVE POWER↗
NASA NTRS2006

Airborne Turbulence Detection System Certification Tool Set

A methodology and a corresponding set of simulation tools for testing and evaluating turbulence detection sensors has been presented. The tool set is available to industry and the FAA for certification of radar based airborne turbulence detection systems. The tool set consists of simulated data sets representing convectively induced turbulence, an airborne radar simulation system, hazard tables to convert the radar observable to an aircraft load, documentation, a hazard metric "truth" algorithm, and criteria for scoring the predictions. Analysis indicates that flight test data supports spatial buffers for scoring detections. Also, flight data and demonstrations with the tool set suggest the need for a magnitude buffer.

Hamilton, David W.↗
NASA NTRS1981

A stochastic-dynamical approach to the study of the natural variability of the climate

A method, suggested by Leith (1975), which employed stochastic-dynamic forecasts obtained from a general circulation model in such a way as to satisfy the definition of climatic noise, was used to validate assumptions accounting for the effects of external influences in estimating the climatic noise. Two assumptions were investigated: (1) that the weather fluctuations can be represented as a Markov process, and (2) that changing external conditions do not influence the atmosphere's statistical properties on short time scales. The general circulation model's simulation of the daily weather fluctuations was generated by performing integrations with prescribed climatological boundary conditions for random initial atmospheric states, with resulting dynamical forecasts providing an ensemble of simulated data for the autoregressive modeling of weather fluctuations. To estimate the climatic noise from the observational data (consisting of hourly values of sea level pressure and surface temperature at 54 U.S. stations for the month of January for the years 1949-1975) use of the short time-scale assumption is made. The simulated and observed data were found not to be consistent with either white noise or a Markov process of weather fluctuations. Good agreement was found between the results of the hypothetical testing of the simulated and the observed surface temperatures; and only partial support was found for the short time-scale assumption, i.e., for sea level pressure.

Straus, D. M.↗
DOE OSTI2022

Expanded analysis of machine learning models for nuclear transient identification using TPOT

Industries around the world are becoming more and more data driven. The nuclear field is no exception with several different applications being proposed. One popular area of research is the use of machine learning in transient detection. This paper seeks to build upon a previous study which made use of the AutoML package TPOT to train traditional machine learning models to classify transient events occurring with a reactor. Synthetic data was once again collected using a GPWR reactor simulator. Data on 12 different events was collected using 15 different initial conditions. Here, a dataset consisting of over 100,000 data points was compiled and used to train 7 different machine learning models using a pre-defined TPOT dictionary with 12 different preprocessing techniques. Three of the trained models were able to produce validation results in the 90s with the expanded dataset. Once the models were trained, it was possible to look into where during the simulation, misclassifications occurred. Using these three models, analysis was done to determine if TPOT could be used to train models that were effective if important features were missing. The results from this were positive with the newly trained models scoring close to the original models. Finally, to conclude this study, the three high performing models were retrained using different random states to see if there was any major variation when different states were used.

42 ENGINEERING↗
NASA NTRS2009

Data Processing for Atmospheric Phase Interferometers

This paper presents a detailed discussion of calibration procedures used to analyze data recorded from a two-element atmospheric phase interferometer (API) deployed at Goldstone, California. In addition, we describe the data products derived from those measurements that can be used for site intercomparison and atmospheric modeling. Simulated data is used to demonstrate the effectiveness of the proposed algorithm and as a means for validating our procedure. A study of the effect of block size filtering is presented to justify our process for isolating atmospheric fluctuation phenomena from other system-induced effects (e.g., satellite motion, thermal drift). A simulated 24 hr interferometer phase data time series is analyzed to illustrate the step-by-step calibration procedure and desired data products.

Acosta, Roberto J.↗
DOE OSTI2015

Detecting vortices in superconductors: Extracting one-dimensional topological singularities from a discretized complex scalar field

In type II superconductors, the dynamics of superconducting vortices determine their transport properties. In the Ginzburg-Landau theory, vortices correspond to topological defects in the complex order parameter. Extracting their precise positions and motion from discretized numerical simulation data is an important, but challenging, task. In the past, vortices have mostly been detected by analyzing the magnitude of the complex scalar field representing the order parameter and visualized by corresponding contour plots and isosurfaces. However, these methods, primarily used for small-scale simulations, blur the fine details of the vortices, scale poorly to large-scale simulations, and do not easily enable isolating and tracking individual vortices. In this paper, we present a method for exactly finding the vortex core lines from a complex order parameter field. With this method, vortices can be easily described at a resolution even finer than the mesh itself. The precise determination of the vortex cores allows the interplay of the vortices inside a model superconductor to be visualized in higher resolution than has previously been possible. Finally, by representing the field as the set of vortices, this method also massively reduces the data footprint of the simulations and provides the data structures for further analysis and feature tracking.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2015

Recasting a model atomistic glassformer as a system of icosahedra

We consider a binary Lennard-Jones glassformer whose super-Arrhenius dynamics are correlated with the formation of icosahedral structures. Upon cooling, these icosahedra organize into mesoclusters. We recast this glassformer as an effective system of icosahedra which we describe with a population dynamics model. This model we parameterize with data from the temperature regime accessible to molecular dynamics simulations. We then use the model to determine the population of icosahedra in mesoclusters at arbitrary temperature. Using simulation data to incorporate dynamics into the model, we predict relaxation behavior at temperatures inaccessible to conventional approaches. Our model predicts super-Arrhenius dynamics whose relaxation time remains finite for non-zero temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Liquid-state polaron theory of the hydrated electron revisited

The quantum path integral/classical liquid-state theory of Chandler and co-workers, created to describe an excess electron in solvent, is re-examined for the hydrated electron. The portion that models electron-water density correlations is replaced by two equations: the range optimized random phase approximation (RO-RPA), and the Donley, Rajasekaran, and Liu (DRL) approximation to the “two-chain” equation, both shown previously to describe accurately the static structure and thermodynamics of strongly charged polyelectrolyte solutions. The static equilibrium properties of the hydrated electron are analyzed using five different electron-water pseudopotentials. The theory is then compared with data from mixed quantum/classical Monte Carlo and molecular dynamics simulations using these same pseudopotentials. It is found that the predictions of the RO-RPA and DRL-based polaron theories are similar and improve upon previous theory, with values for almost all properties analyzed in reasonable quantitative agreement with the available simulation data. Also, it is found using the Larsen, Glover, and Schwartz pseudopotential that the theories give values for the solvation free energy that are at least three times larger than that from experiment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2014

Testing local anisotropy using the method of smoothed residuals I — methodology

We discuss some details regarding the method of smoothed residuals, which has recently been used to search for anisotropic signals in low-redshift distance measurements (Supernovae). In this short note we focus on some details regarding the implementation of the method, particularly the issue of effectively detecting signals in data that are inhomogeneously distributed on the sky. Using simulated data, we argue that the original method proposed in Colin et al. [1] will not detect spurious signals due to incomplete sky coverage, and that introducing additional Gaussian weighting to the statistic as in [2] can hinder its ability to detect a signal. Issues related to the width of the Gaussian smoothing are also discussed.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2025

Validation of a Global Geospace Model With a Systems Science Approach Based on Canonical Correlation Analysis

A systems science approach based on canonical correlation analysis (CCA) is applied as a new, behavioral way to validate global geospace models. The biggest novelty of the technique is that it validates models at a system level, whereby a side‐by‐side comparison is performed of CCA applied to a 30‐day observational and the corresponding simulation data sets comprising quiet, moderate and active times. The simulation used the Multiscale Atmosphere‐Geospace Environment (MAGE) model. It is shown that (a) CCA must be combined with sensitivity analysis to be effective, (b) the MAGE model generally reproduces the observed behavior (more so for quieter time intervals), quantified by the intercorrelations between different variables and (c) the technique identifies the SuperMAG SML index as a quantity for which refinements of the model are needed.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2019

Impact and mitigation of angular uncertainties in Bragg coherent x-ray diffraction imaging

Bragg coherent diffraction imaging (BCDI) is a powerful technique to explore the local strain state and morphology of microscale crystals. The method can potentially reach nanometer-scale spatial resolution thanks to the advances in synchrotron design that dramatically increase coherent flux. However, there are experimental bottlenecks that may limit the image reconstruction quality from future high signal-to-noise ratio measurements. In this work we show that angular uncertainty of the sample orientation with respect to a fixed incoming beam is one example of such a factor, and we present a method to mitigate the resulting artifacts. On the basis of an alternative formulation of the forward problem, we design a phase retrieval algorithm which enables the simultaneous reconstruction of the object and determination of the exact angular position corresponding to each diffraction pattern in the data set. We have tested the algorithm performance on simulated data for different degrees of angular uncertainty and signal-to-noise ratio.

36 MATERIALS SCIENCE↗