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At least 487 records · Page 27

A New Time-Space Accurate Scheme for Hyperbolic Problems: Quasi-Explicit Case - 1

This paper presents a new discretization scheme for hyperbolic systems of conservations laws. It satisfies the TVD property and relies on the new high-resolution mechanism which is compatible with the genuinely multidimensional approach proposed recently. This work can be regarded as a first step towards extending the genuinely multidimensional approach to unsteady problems. Discontinuity capturing capabilities and accuracy of the scheme are verified by a set of numerical tests.

Sidilkover, David↗

Near-Limit Flamelet Phenomena in Buoyant Low Stretch Diffusion Flames Beneath a Solid Fuel

A unique near-limit low stretch multidimensional stable flamelet phenomena has been observed for the first time which extends the material flammability limit beyond the one-dimensional low stretch flammability limit to lower burning rates and higher relative heat losses than is possible with uniform flame coverage. During low stretch experiments burning the underside of very large radii (greater than or = 75 cm stretch rate less than or = 3/s) cylindrical cast PMMA samples, multidimensional flamelets were observed, in contrast with a one-dimensional flame that was found to blanket the surface for smaller radii samples ( higher stretch rate). Flamelets were observed by decreasing the stretch rate or by increasing the conductive heat loss from the flame. Flamelets are defined as flames that cover only part of the burning sample at any given time, but persist for many minutes. Flamelet phenomena is viewed as the flame's method of enhancing oxygen flow to the flame, through oxygen transport into the edges of the flamelet. Flamelets form as heat losses (surface radiation and solid-phase conduction) become large relative to the weakened heat release of the low stretch flame. While heat loss rates remain fairly constant, the limiting factor in the heat release of the flame is hypothesized to be the oxygen transport to the flame in this low stretch (low convective) environment. Flamelet extinction is frequently caused by encroachment of an adjacent flamelet. Large-scale whole-body flamelet oscillations at 1.2 - 1.95 Hz are noted prior to extinction of a flamelet. This oscillation is believed to be due a repeated process of excess fuel leakage through the dark channels between the flamelets, fuel premixing with slow incoming oxidizer, and subsequent rapid flame spread and retreat of the flamelet through the premixed layer. The oscillation frequency is driven by gas-phase diffusive time scales.

Olson, S. L.↗

Axisymmetric Numerical Modeling of Pulse Detonation Rocket Engines

Pulse detonation rocket engines (PDREs) have generated research interest in recent years as a chemical propulsion system potentially offering improved performance and reduced complexity compared to conventional rocket engines. The detonative mode of combustion employed by these devices offers a thermodynamic advantage over the constant-pressure deflagrative combustion mode used in conventional rocket engines and gas turbines. However, while this theoretical advantage has spurred considerable interest in building PDRE devices, the unsteady blowdown process intrinsic to the PDRE has made realistic estimates of the actual propulsive performance problematic. The recent review article by Kailasanath highlights some of the progress that has been made in comparing the available experimental measurements with analytical and numerical models. In recent work by the author, a quasi-one-dimensional, finite rate chemistry CFD model was utilized to study the gasdynamics and performance characteristics of PDREs over a range of blowdown pressure ratios from 1-1000. Models of this type are computationally inexpensive, and enable first-order parametric studies of the effect of several nozzle and extension geometries on PDRE performance over a wide range of conditions. However, the quasi-one-dimensional approach is limited in that it cannot properly capture the multidimensional blast wave and flow expansion downstream of the PDRE, nor can it resolve nozzle flow separation if present. Moreover, the previous work was limited to single-pulse calculations. In this paper, an axisymmetric finite rate chemistry model is described and utilized to study these issues in greater detail. Example Mach number contour plots showing the multidimensional blast wave and nozzle exhaust plume are shown. The performance results are compared with the quasi-one-dimensional results from the previous paper. Both Euler and Navier-Stokes solutions are calculated in order to determine the effect of viscous effects in the nozzle flowfield. Additionally, comparisons of the model results to performance data from CalTech, as well as experimental flowfield measurements from Stanford University, are also reported.

Morris, Christopher I.↗

Decision-Tree Formulation With Order-1 Lateral Execution

A compact symbolic formulation enables mapping of an arbitrarily complex decision tree of a certain type into a highly computationally efficient multidimensional software object. The type of decision trees to which this formulation applies is that known in the art as the Boolean class of balanced decision trees. Parallel lateral slices of an object created by means of this formulation can be executed in constant time considerably less time than would otherwise be required. Decision trees of various forms are incorporated into almost all large software systems. A decision tree is a way of hierarchically solving a problem, proceeding through a set of true/false responses to a conclusion. By definition, a decision tree has a tree-like structure, wherein each internal node denotes a test on an attribute, each branch from an internal node represents an outcome of a test, and leaf nodes represent classes or class distributions that, in turn represent possible conclusions. The drawback of decision trees is that execution of them can be computationally expensive (and, hence, time-consuming) because each non-leaf node must be examined to determine whether to progress deeper into a tree structure or to examine an alternative. The present formulation was conceived as an efficient means of representing a decision tree and executing it in as little time as possible. The formulation involves the use of a set of symbolic algorithms to transform a decision tree into a multi-dimensional object, the rank of which equals the number of lateral non-leaf nodes. The tree can then be executed in constant time by means of an order-one table lookup. The sequence of operations performed by the algorithms is summarized as follows: 1. Determination of whether the tree under consideration can be encoded by means of this formulation. 2. Extraction of decision variables. 3. Symbolic optimization of the decision tree to minimize its form. 4. Expansion and transformation of all nested conjunctive-disjunctive paths to a flattened conjunctive form composed only of equality checks when possible. If each reduced conjunctive form contains only equality checks and all of these forms use the same variables, then the decision tree can be reduced to an order-one operation through a table lookup. The speedup to order one is accomplished by distributing each decision variable over a surface of a multidimensional object by mapping the equality constant to an index

James, Mark↗

Stochastic Evolutionary Algorithms for Planning Robot Paths

A computer program implements stochastic evolutionary algorithms for planning and optimizing collision-free paths for robots and their jointed limbs. Stochastic evolutionary algorithms can be made to produce acceptably close approximations to exact, optimal solutions for path-planning problems while often demanding much less computation than do exhaustive-search and deterministic inverse-kinematics algorithms that have been used previously for this purpose. Hence, the present software is better suited for application aboard robots having limited computing capabilities (see figure). The stochastic aspect lies in the use of simulated annealing to (1) prevent trapping of an optimization algorithm in local minima of an energy-like error measure by which the fitness of a trial solution is evaluated while (2) ensuring that the entire multidimensional configuration and parameter space of the path-planning problem is sampled efficiently with respect to both robot joint angles and computation time. Simulated annealing is an established technique for avoiding local minima in multidimensional optimization problems, but has not, until now, been applied to planning collision-free robot paths by use of low-power computers.

Fink, Wolfgang↗

Self-Organizing-Map Program for Analyzing Multivariate Data

SOM_VIS is a computer program for analysis and display of multidimensional sets of Earth-image data typified by the data acquired by the Multi-angle Imaging Spectro-Radiometer [MISR (a spaceborne instrument)]. In SOM_VIS, an enhanced self-organizing-map (SOM) algorithm is first used to project a multidimensional set of data into a nonuniform three-dimensional lattice structure. The lattice structure is mapped to a color space to obtain a color map for an image. The Voronoi cell-refinement algorithm is used to map the SOM lattice structure to various levels of color resolution. The final result is a false-color image in which similar colors represent similar characteristics across all its data dimensions. SOM_VIS provides a control panel for selection of a subset of suitably preprocessed MISR radiance data, and a control panel for choosing parameters to run SOM training. SOM_VIS also includes a component for displaying the false-color SOM image, a color map for the trained SOM lattice, a plot showing an original input vector in 36 dimensions of a selected pixel from the SOM image, the SOM vector that represents the input vector, and the Euclidean distance between the two vectors.

Li, P. Peggy↗

Overview of Heat Addition and Efficiency Predictions for an Advanced Stirling Convertor

The U.S. Department of Energy (DOE) and Lockheed Martin Space Systems Company (LMSSC) have been developing the Advanced Stirling Radioisotope Generator (ASRG) for use as a power system for space science missions. This generator would use two high-efficiency Advanced Stirling Convertors (ASCs), developed by Sunpower Inc. and NASA Glenn Research Center (GRC). The ASCs convert thermal energy from a radioisotope heat source into electricity. As part of ground testing of these ASCs, different operating conditions are used to simulate expected mission conditions. These conditions require achieving a particular operating frequency, hot end and cold end temperatures, and specified electrical power output for a given net heat input. Microporous bulk insulation is used in the ground support test hardware to minimize the loss of thermal energy from the electric heat source to the environment. The insulation package is characterized before operation to predict how much heat will be absorbed by the convertor and how much will be lost to the environment during operation. In an effort to validate these predictions, numerous tasks have been performed, which provided a more accurate value for net heat input into the ASCs. This test and modeling effort included: (a) making thermophysical property measurements of test setup materials to provide inputs to the numerical models, (b) acquiring additional test data that was collected during convertor tests to provide numerical models with temperature profiles of the test setup via thermocouple and infrared measurements, (c) using multidimensional numerical models (computational fluid dynamics code) to predict net heat input of an operating convertor, and (d) using validation test hardware to provide direct comparison of numerical results and validate the multidimensional numerical models used to predict convertor net heat input. This effort produced high fidelity ASC net heat input predictions, which were successfully validated using specially designed test hardware enabling measurement of heat transferred through a simulated Stirling cycle. The overall effort and results are discussed.

Wilson, Scott D.↗

Constructing an Efficient Self-Tuning Aircraft Engine Model for Control and Health Management Applications

Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulations.Self-tuning aircraft engine models can be applied for control and health management applications. The self-tuning feature of these models minimizes the mismatch between any given engine and the underlying engineering model describing an engine family. This paper provides details of the construction of a self-tuning engine model centered on a piecewise linear Kalman filter design. Starting from a nonlinear transient aerothermal model, a piecewise linear representation is first extracted. The linearization procedure creates a database of trim vectors and state-space matrices that are subsequently scheduled for interpolation based on engine operating point. A series of steady-state Kalman gains can next be constructed from a reduced-order form of the piecewise linear model. Reduction of the piecewise linear model to an observable dimension with respect to available sensed engine measurements can be achieved using either a subset or an optimal linear combination of "health" parameters, which describe engine performance. The resulting piecewise linear Kalman filter is then implemented for faster-than-real-time processing of sensed engine measurements, generating outputs appropriate for trending engine performance, estimating both measured and unmeasured parameters for control purposes, and performing on-board gas-path fault diagnostics. Computational efficiency is achieved by designing multidimensional interpolation algorithms that exploit the shared scheduling of multiple trim vectors and system matrices. An example application illustrates the accuracy of a self-tuning piecewise linear Kalman filter model when applied to a nonlinear turbofan engine simulation. Additional discussions focus on the issue of transient response accuracy and the advantages of a piecewise linear Kalman filter in the context of validation and verification. The techniques described provide a framework for constructing efficient self-tuning aircraft engine models from complex nonlinear simulatns.

Armstrong, Jeffrey B.↗

Improving the Accessibility and Use of NASA Earth Science Data

Many of the NASA Langley Atmospheric Science Data Center (ASDC) Distributed Active Archive Center (DAAC) multidimensional tropospheric and atmospheric chemistry data products are stored in HDF4, HDF5 or NetCDF format, which traditionally have been difficult to analyze and visualize with geospatial tools. With the rising demand from the diverse end‐user communities for geospatial tools to handle multidimensional products, several applications, such as ArcGIS, have refined their software. Many geospatial applications now have new functionalities that enable the end user to: Store, serve, and perform analysis on each individual variable, its time dimension, and vertical dimension. Use NetCDF, GRIB, and HDF raster data formats across applications directly. Publish output within REST image services or WMS for time and space enabled web application development. During this webinar, participants will learn how to leverage geospatial applications such as ArcGIS, OPeNDAP and ncWMS in the production of Earth science information, and in increasing data accessibility and usability.

Tisdale, Matthew↗

Polarbrdf: A General Purpose Python Package for Visualization Quantitative Analysis of Multi-Angular Remote Sensing Measurements

The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR). Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wild fire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

CAR↗

Systems and Methods for Data Visualization Using Three-Dimensional Displays

Data visualization systems and methods for generating 3D visualizations of a multidimensional data space are described. In one embodiment a 3D data visualization application directs a processing system to: load a set of multidimensional data points into a visualization table; create representations of a set of 3D objects corresponding to the set of data points; receive mappings of data dimensions to visualization attributes; determine the visualization attributes of the set of 3D objects based upon the selected mappings of data dimensions to 3D object attributes; update a visibility dimension in the visualization table for each of the plurality of 3D object to reflect the visibility of each 3D object based upon the selected mappings of data dimensions to visualization attributes; and interactively render 3D data visualizations of the 3D objects within the virtual space from viewpoints determined based upon received user input.

Djorgovski, Stanislav G.↗

Effects of Repeated Fire on Florida Oak-Saw Palmetto Scrub

Background: The dominant species of Florida oak-saw palmetto scrub sprout after burning from belowground rhizomes or fire-resistant aboveground buds with rapid reestablishment of cover. Responses to single fires are well documented; however, responses to repeated fires may differ. Fire return intervals, differences among sites, and species may influence responses. We used transect data from four sites on Kennedy Space Center/Merritt Island National Wildlife Refuge to test whether growth differed through repeated fires. Two sites burned five times in 36 years, one site burned five times in 25 years, and one burned four times in 18 years. We used linear mixed models that account for repeated measures to determine if the number of fires affected height, total cover ≥ 0.5 m and < 0.5 m, bare ground, and cover of the dominant oak (Quercus) ≥ 0.5 m and of saw palmetto (Serenoa repens) ≥ 0.5 m. We compared community composition through repeated fires using nonmetric multidimensional scaling ordination. Results: Height, total cover ≥ 0.5 m, and cover of the dominant oak ≥ 0.5 m and of saw palmetto ≥ 0.5 m increased with time since burn; total cover < 0.5 m and bare ground decreased. A quadratic term in the growth model was significant except for total cover < 0.5 m. There were site differences for all variables except bare ground. The number of fires decreased height, total cover ≥ 0.5 m, and cover of the dominant oak ≥ 0.5 and increased total cover < 0.5 m and bare ground but had no effect on cover of Serenoa repens ≥ 0.5 m. Community changes after repeated fires were similar in nonmetric multidimensional ordinations with time since burn correlated to the first or second axis. Conclusions: Scrub recovered from repeated fires at a range of intervals and seasons, but short return intervals reduced growth with responses differing among species.

Florida↗

Making NASA GES DISC Level 2 Data GIS Analysis Ready

There are many valuable data hosted by NASA Goddard Earth Sciences Data and Information Services Center (GES DISC) for GIS applications in the areas of extreme weather events, climatic anomaly, and public health. However, using NASA Earth Science Data poses some challenges for GIS users. Many of these users are not experts in Earth Observation and have little knowledge about NASA's Earth science data. In the GIS community, GeoTiff is the most widely used raster format, whereas NASA's data is primarily in complex multidimensional netCDF and HDF formats. This complexity makes it difficult for GIS users, especially those who are unfamiliar with these formats. Although GIS software like ArcGIS has made progress in processing multidimensional netCDF data, certain issues still remain, particularly with level 2 data. In this study, we use TROPSpheric Monitoring instrument (TROPOMI) level 2 data as an example to demonstrate how to make such data GIS analysis ready. The process involves: 1. Creating a feature layer from the TROPOMI level 2 data. 2. Converting the feature layer to a gridded raster dataset. 3. Mosaicking gridded raster datasets into a raster dataset covering the entire desired extent. 4. Generating a symbology with a GIBS-specific style that aligns with the visual standards and requirements of GIBS. 5. Publishing image services. By performing these preprocessing and transformation steps, NASA level 2 data can be made compatible and ready for use within GIS software for various spatial analysis and visualization tasks.

Geographic Information System↗

Electrochemical force microscopy

A system and method for electrochemical force microscopy are provided. The system and method are based on a multidimensional detection scheme that is sensitive to forces experienced by a biased electrode in a solution. The multidimensional approach allows separation of fast processes, such as double layer charging, and charge relaxation, and slow processes, such as diffusion and faradaic reactions, as well as capturing the bias dependence of the response. The time-resolved and bias measurements can also allow probing both linear (small bias range) and non-linear (large bias range) electrochemical regimes and potentially the de-convolution of charge dynamics and diffusion processes from steric effects and electrochemical reactivity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

MultiDimChemImaging v1.30

The purpose of this software is to correlate and visualize multidimensional chemical images where the different modalities were collected with different resolution and/or offset. List of features: - change dimension of data stored in XYZ (XYcoordinate, value) or Comma Separated Values (CSV) formats via bipolar or bicubic interpolation - determine and apply offset between different modalities - create a multimodal image file from multiple single modalities in Tab Separate Values (TSV) or TissueViewTM (industry standard for chemical image visualization) formats - visualize and save (whole or partial) composite chemical images made of multiple (up to 3 at once) modalities Specific application: correlated multidimensional chemical imaging by AFM-based nano-thermal (nano-TA) analysis coupled to spectroscopy and mass spectrometry for spatially resolved surface analysis. In case of a phase separated polymer film, the modalities were: 1. topography image 203. IR images collected at two different wavelengths 4-5. mass spectral chemical images of two different m/z values.

Kertesz, Vilmos↗

A Metaheuristic Optimization Tool for High Flux Isotope Reactor Low-Enriched Uranium Core Design

A metaheuristic optimization tool was developed for design optimization studies of a High Flux Isotope Reactor low-enriched uranium core. Low-enriched uranium core design presents a multidimensional, multi-objective optimization problem that requires a systematic approach to avoid arbitrary design decisions. This tool searches this multidimensional design space to generate an optimum design, considering a weighted design performance metric that includes several parameters. The search methods are discussed herein, and the tool is applied to uranium silicide fuel designs.

Variansyah, I.↗

Release on the Virtual Test Bed of an MSRE thermal hydraulics model

The nuclear industry is taking leaps in innovations with companies seeking a sustainable energy future through advanced nuclear reactors. The \gls{DOE}’s \gls{neams} program seeks to substantiate and bolster the deployment of advanced reactors through flexible multifidelity, multiphysics simulations of advanced nuclear reactors. Applications like SAM for one-dimensional systems thermal-hydraulics, and Pronghorn for multidimensional coarse mesh thermal-hydraulics, are geared to support innovations in industry by facilitating design, optimization, and licensing of advanced nuclear reactors. Coupling systems thermal-hydraulics and computational fluid dynamics codes can be difficult as the pressure coupling converges slowly; however, it is important to obtain the desired accuracy in each part of the primary loop. The authors of this model created an \gls{odc}~\cite{Mau23} approach to coupling SAM and Pronghorn. Leveraging this coupling technique, a \gls{msre} model was developed and released to the \gls{neams}/\gls{nric} \gls{vtb}. The \gls{msre} was chosen to be modeled because of the wealth of experimental data available and because of the strong physics coupling between the core and primary circuit \cite{doi:10.13182/NT8-2-118}. This document contextualizes the history of the \gls{msre}, describes the thermal hydraulics models used, and detail the implementation of multidimensional thermal-hydraulics and system codes based on the \gls{odc} method~\cite{Penn} for the \gls{msre} model. Finally, this document presents how other modelers could apply the SAM-Pronghorn \gls{odc} for other advanced reactor models. Current item is the set of slides for ANS Winter 23. The release of the model and the ANS summary have already been approved

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Release on the Virtual Test Bed of an MSRE thermal hydraulics model

The nuclear industry is taking leaps in innovations with companies seeking a sustainable energy future through advanced nuclear reactors. The \gls{DOE}’s \gls{neams} program seeks to substantiate and bolster the deployment of advanced reactors through flexible multifidelity, multiphysics simulations of advanced nuclear reactors. Applications like SAM for one-dimensional systems thermal-hydraulics, and Pronghorn for multidimensional coarse mesh thermal-hydraulics, are geared to support innovations in industry by facilitating design, optimization, and licensing of advanced nuclear reactors. Coupling systems thermal-hydraulics and computational fluid dynamics codes can be difficult as the pressure coupling converges slowly; however, it is important to obtain the desired accuracy in each part of the primary loop. The authors of this model created an \gls{odc}~\cite{Mau23} approach to coupling SAM and Pronghorn. Leveraging this coupling technique, a \gls{msre} model was developed and released to the \gls{neams}/\gls{nric} \gls{vtb}. The \gls{msre} was chosen to be modeled because of the wealth of experimental data available and because of the strong physics coupling between the core and primary circuit \cite{doi:10.13182/NT8-2-118}. This document contextualizes the history of the \gls{msre}, describes the thermal hydraulics models used, and detail the implementation of multidimensional thermal-hydraulics and system codes based on the \gls{odc} method~\cite{Penn} for the \gls{msre} model. Finally, this document presents how other modelers could apply the SAM-Pronghorn \gls{odc} for other advanced reactor models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗