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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 1,081 records · Page 60

An application of the MPP to the interactive manipulation of stereo images of digital terrain models

Massively Parallel Processor algorithms were developed for the interactive manipulation of flat shaded digital terrain models defined over grids. The emphasis is on real time manipulation of stereo images. Standard graphics transformations are applied to a 128 x 128 grid of elevations followed by shading and a perspective projection to produce the right eye image. The surface is then rendered using a simple painter's algorithm for hidden surface removal. The left eye image is produced by rotating the surface 6 degs about the viewer's y axis followed by a perspective projection and rendering of the image as described above. The left and right eye images are then presented on a graphics device using standard stereo technology. Performance evaluations and comparisons are presented.

Pol, Sanjay↗

Using an instrumented manikin for Space Station Freedom analysis

One of the most intriguing and complex areas of current computer graphics research is animating human figures to behave in a realistic manner. Believable, accurate human models are desirable for many everyday uses including industrial and architectural design, medical applications, and human factors evaluations. For zero-gravity (0-g) spacecraft design and mission planning scenarios, they are particularly valuable since 0-g conditions are difficult to simulate in a one-gravity Earth environment. At NASA/JSC, an in-house human modeling package called PLAID is currently being used to produce animations for human factors evaluation of Space Station Freedom design issues. Presented here is an introductory background discussion of problems encountered in existing techniques for animating human models and how an instrumented manikin can help improve the realism of these models.

Orr, Linda↗

Interplanetary proton fluence model - JPL 1991

We describe an updated predictive engineering model for the interplanetary fluence of protons with energies respectively greater than 1, 4, 10, 30, and 60 MeV. This has been the first opportunity to derive a model from a data set that has been collected in space over a long enough period of time to produce a valid sample of solar proton events. The model provides a quantitative basis for estimating the exposures to solar protons of spacecraft during missions of varying length and of surfaces and atmospheres of solar system objects. The data sets contain several major proton events comparable to the 1972 event. For the cases of the over 10 and over 30 MeV particles, the fluences are somewhat lower than in our earlier model No over 1, over 4, and over 60 MeV proton fluence models have been published in the literature previously. We present our results in a convenient graphical form which may be used to calculate the 1 AU fluence expected at a given confidence level as a function of the length of the exposure. A method of extending this estimate to other heliocentric distances is described.

Feynman, J.↗

Airport surveillance using a solid state coherent lidar

The utility of solid state coherent LIDAR was assessed in the following application areas: (1) wake vortices; (2) dry and wet microburst windshear; (3) gusts; (4) vertical and general wind profiling; and (5) cloud ceiling. The system performance model described was based on a concept definition, system sizing, measurement planning, and algorithm and graphics display development. Data were collected at the Kennedy Space Center and the National Weather Service site adjacent to Denver's Stapleton Airport.

Huffaker, R. Milton↗

Implementation of Flow Tripping Capability in the USM3D Unstructured Flow Solver

A flow tripping capability is added to an established NASA tetrahedral unstructured parallel Navier-Stokes flow solver, USM3D. The capability is based on prescribing an appropriate profile of turbulence model variables to energize the boundary layer in a plane normal to a specified trip region on the body surface. We demonstrate this approach using the k-e two-equation turbulence model of USM3D. Modification to the solution procedure primarily consists of developing a data structure to identify all unstructured tetrahedral grid cells located in the plane normal to a specified surface trip region and computing a function based on the mean flow solution to specify the modified profile of the turbulence model variables. We leverage this data structure and also show an adjunct approach that is based on enforcing a laminar flow condition on the otherwise fully turbulent flow solution in user specified region. The latter approach is applied for the solutions obtained using other one- and two-equation turbulence models of USM3D. A key ingredient of the present capability is the use of a graphical user-interface tool PREDISC to define a trip region on the body surface in an existing grid. Verification of the present modifications is demonstrated on three cases, namely, a flat plate, the RAE2822 airfoil, and the DLR F6 wing-fuselage configuration.

Pandya, Mohagna J.↗

A Prototype System for Ground Control Space Telerobotics

A telerobotics system is described which provides supervised autonomous control capability for time-delayed ground-remote control applications. The system includes a local site operator interface for interactive task description and a remote site task execution system. Interactive stereo graphics overlay on video is provided at the local site to update the remote environmental model. The remote site system is capable of nominal task execution as well as monitoring and reflex action. Execution utilizes multiple control modules which execute based upon command parameterization.

robotics autonomous control telerobotics manipulat↗

Implementation of Flow Tripping Capability in the USM3D Unstructured Flow Solver

A flow tripping capability is added to an established NASA tetrahedral unstructured parallel Navier-Stokes flow solver, USM3D. The capability is based on prescribing an appropriate profile of turbulence model variables to energize the boundary layer in a plane normal to a specified trip region on the body surface. We demonstrate this approach using the k-epsilon two-equation turbulence model of USM3D. Modification to the solution procedure primarily consists of developing a data structure to identify all unstructured tetrahedral grid cells located in the plane normal to a specified surface trip region and computing a function based on the mean flow solution to specify the modified profile of the turbulence model variables. We leverage this data structure and also show an adjunct approach that is based on enforcing a laminar flow condition on the otherwise fully turbulent flow solution in user-specified region. The latter approach is applied for the solutions obtained using other one-and two-equation turbulence models of USM3D. A key ingredient of the present capability is the use of a graphical user-interface tool PREDISC to define a trip region on the body surface in an existing grid. Verification of the present modifications is demonstrated on three cases, namely, a flat plate, the RAE2822 airfoil, and the DLR F6 wing-fuselage configuration.

Pandya, Mohagna J.↗

Distributed Visualization Project

Distributed Visualization allows anyone, anywhere to see any simulation at any time. Development focuses on algorithms, software, data formats, data systems and processes to enable sharing simulation-based information across temporal and spatial boundaries without requiring stakeholders to possess highly-specialized and very expensive display systems. It also introduces abstraction between the native and shared data, which allows teams to share results without giving away proprietary or sensitive data. The initial implementation of this capability is the Distributed Observer Network (DON) version 3.1. DON 3.1 is available for public release in the NASA Software Store (https://software.nasa.gov/software/KSC-13775) and works with version 3.0 of the Model Process Control specification (an XML Simulation Data Representation and Communication Language) to display complex graphical information and associated Meta-Data.

Tech Port↗

OverFlight: Graphical Flight Operations Planning

OverFlight is an in-development graphical user interface (GUI) that implements a state-of-the-art rotorcraft maneuvering noise model using a source noise hemisphere approach coupled with the Aircraft NOise Prediction Program 2 (ANOPP2). This GUI stems from a demand for easy-to-use mission planning and community impact acoustic tools that can model the maneuvering flight of a rotary-wing vehicle. This paper covers the models used for the development of OverFlight and model validation efforts. Data from a joint NASA/Army flight test of an MD530F aircraft are used both for source noise hemispheres as well as maneuvering flight data. Analysis of the predicted maneuvering noise shows better agreement that traditional methods currently employed, while also demonstrating maneuvers where the underlying assumptions fail to hold.

rotorcraft↗

Demonstrating solarpilot ’s Python Application Programmable Interface Through Heliostat Optimal Aimpoint Strategy Use Case

solarpilot is a software package that generates solar field layouts and characterizes the optical performance of concentrating solar power (CSP) tower systems. solarpilot was developed by the National Renewable Energy Laboratory (NREL) as a stand-alone desktop application but has also been incorporated into NREL’s System Advisor Model (SAM) in a simplified format. Prior means for user interaction with solarpilot have included the application’s graphical interface, the SAM routines with limited configurability, and through a built-in scripting language called “LK.” This article presents a new, full-featured, python-based application programmable interface (API) for solarpilot, which we hereafter refer to as CoPylot. CoPylot enables python users to perform detailed CSP tower analysis utilizing either the Hermite expansion technique (analytical) or the SolTrace ray-tracing engine. CoPylot’s enables CSP researchers to perform analysis that was previously not possible through solarpilot’s existing interfaces. This article discusses the capabilities of CoPylot and presents a use case wherein we populate a model that obtains optimal solar field aiming strategies.

14 SOLAR ENERGY↗

Desktop computer graphics for RMS/payload handling flight design

A computer program, the Multi-Adaptive Drawings, Renderings and Similitudes (MADRAS) program, is discussed. The modeling program, written for a desktop computer system (the Hewlett-Packard 9845/C), is written in BASIC and uses modular construction of objects while generating both wire-frame and hidden-line drawings from any viewpoint. The dimensions and placement of objects are user definable. Once the hidden-line calculations are made for a particular viewpoint, the viewpoint may be rotated in pan, tilt, and roll without further hidden-line calculations. The use and results of this program are discussed.

Homan, D. J.↗

Design of a graphical user interface for few-shot machine learning classification of electron microscopy data

The recent growth in data generation by modern electron microscopes requires rapid, scalable, and flexible approaches to image segmentation and analysis. Few-shot machine learning, which can richly classify images from a handful of user-provided examples, is a promising route to high-throughput analysis. However, current command-line implementations of such approaches can be slow and unintuitive to use, lacking the real-time feedback necessary to perform effective classification. Here we report on the development of a Python-based graphical user interface that enables end users to easily conduct and visualize the output of few-shot learning models. This interface is portable and can be hosted locally or on the web, providing the opportunity to reproducibly conduct, share, and crowd-source few-shot analyses.

97 MATHEMATICS AND COMPUTING↗

Enabling real-time adaptation of machine learning models at x-ray Free Electron Laser facilities with high-speed training optimized computational hardware

The emergence of novel computational hardware is enabling a new paradigm for rapid machine learning model training. For the Department of Energy’s major research facilities, this developing technology will enable a highly adaptive approach to experimental sciences. In this manuscript we present the per-epoch and end-to-end training times for an example of a streaming diagnostic that is planned for the upcoming high-repetition rate x-ray Free Electron Laser, the Linac Coherent Light Source-II. We explore the parameter space of batch size and data parallel training across multiple Graphics Processing Units and Reconfigurable Dataflow Units. We show the landscape of training times with a goal of full model retraining in under 15 min. Although a full from scratch retraining of a model may not be required in all cases, we nevertheless present an example of the application of emerging computational hardware for adapting machine learning models to changing environments in real-time, during streaming data acquisition, at the rates expected for the data fire hoses of accelerator-based user facilities.

97 MATHEMATICS AND COMPUTING↗

Development of a Phasor Diagram Creator to Visualize the Piston and Displacer Forces in an Advanced Stirling Convertor

The steady state, nearly sinusoidal behavior of the components in a Free Piston Stirling Engine allows for visualization of the forces in the system using phasor diagrams. Based on Newton's second law, F=ma, any phasor diagrams modeling a given component in a system should close if all of the acting forces have been considered. Since the Advanced Stirling Radioisotope Generator (ASRG), currently being developed for future NASA deep space missions, is made up of such nearly sinusoidally oscillating components, its phasor diagrams would also be expected to close. A graphical user interface (GUI) has been written in MATLAB by taking user input data, passing it to Sage, a 1-D thermodynamic modeling program used to model the Stirling convertor, running Sage and then automatically plotting the phasor diagrams. Using this software tool, the effect of varying different Sage inputs on the phasor diagrams was determined. The parameters varied were piston amplitude, hot end temperature, cold end temperature, operating frequency, and displacer spring constant. By using these phasor diagrams, better insight can be gained as to why the convertor operates the way that it does.

Saha, Dipanjan↗

Graph-based featurization methods for classifying small molecule compounds

For over a decade, drug-induced liver injury (DILI) has posed significant drawbacks in the synthesis and development of drugs and remains a consequential concern. With finite success within the existing preclinical models, DILI is one of the main causes of drug withdrawal or termination from the market. Particularly, this withdrawal occurs during the late stages of drug development (Kullak-Ublick, 2017). Since DILI is difficult to diagnose and treat, it has become an obstacle in the drug production market that in turn affects clinicians, pharmaceutical companies, and consumers. We propose a method for learning features of DILI-positive drugs based on the graphical relationships and patterns they possess within a network of biological databases. We also train various statistical and machine learning models on these learned features in order to classify the drugs as DILI-positive or negative. Our methods include Random Forest, Neural networks, and logistic regression classification. We utilize labeled DILI-positive and DILI-negative datasets, which were developed by the FDA and the National center for toxicological research, as well as additional literature datasets (Thakkar, 2020) in order to validate our results and assess our featurization and model accuracy.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Building complex simulations rapidly using MATRIX(x): The Space Station redesign

MSFC's quick response to the Space Station redesign effort last year required the development of a computer simulation to model the attitude and station-keeping dynamics of a complex body with rotating solar arrays in orbit around the Earth. The simulation was written using a rapid-prototyping graphical simulation and design tool called MATRIX(x) and provided the capability to quickly remodel complex configuration changes by icon manipulation using a mouse. The simulation determines time-dependent inertia properties, and models forces and torques from gravity-gradient, solar radiation, and aerodynamic disturbances. Surface models are easily built from a selection of beams, plates, tetrahedrons, and cylinders. An optimization scheme was written to determine the torque equilibrium attitudes that balance gravity-gradient and aerodynamic torques over an orbit, and propellant-usage estimates were determined. The simulation has been adapted to model the attitude dynamics for small spacecraft.

Carrington, C. K.↗

Testing the stability of magnetic iron oxides/kaolinite nanocomposite under various pH conditions

Magnetically modified clays containing iron oxides nanoparticles (Fe{sub x}O{sub y} NPs) are low-cost and environmentally harmless materials suitable for sorption of pollutants from wastewaters. Stability of this smart material was evaluated both experimentally and theoretically using molecular modelling. Original kaolinite and prepared Fe{sub x}O{sub y}/kaolinite nanocomposite were characterized using X-ray fluorescence spectroscopy, X-ray powder diffraction, infrared spectroscopy, and transmission electron microscopy, and the stability was studied using leaching tests performed according to the European technical standard EN 12457-2 in deionized water and extraction agents with varying pH (2, 4, 9, and 11). The influence of pH on amount of Fe{sub x}O{sub y} NPs released from the composite and amount of the basic elements released from the kaolinite structure was studied using inductively coupled plasma atomic emission spectroscopy. All experiments proved that the magnetic properties of the nanocomposite will not change even after leaching in extraction agents with various pH. - Graphical abstract: The stability of magnetic Fe{sub x}O{sub y}/kaolinite nanocomposite was studied using molecular modelling and leaching tests under various pH conditions. Display Omitted - Highlights: • Magnetization by Fe{sub x}O{sub y} nanoparticles did not influenced the structure of the kaolinite. • Maghemite (γ-Fe{sub 2}O{sub 3}) and mainly magnetite (Fe{sub 3}O{sub 4}) phases were detected. • Leaching test confirmed good adhesion of Fe{sub x}O{sub y} nanoparticles on kaolinite. • Molecular modelling of kaolinite/Fe{sub x}O{sub y} nanocomposite agrees well with experiments. • Nanocomposite can be considered stable in the wide range of pH.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adaptive Fault Detection Based on Neural Networks and Multiple Sampling Points for Distribution Networks and Microgrids

Smart networks such as microgrid (MG) and active distribution networks (ADN) have been recently playing an important role in power system operation. The design and implementation of appropriate protection systems for such networks must be addressed, which imposes new technical challenges. This paper presents the implementation and validation aspects of an adaptive fault detection strategy based on neural networks (NNs) and multiple sampling points for ADN and MG. The solution is implemented on an edge device. Artificial NNs are used to derive a data-driven model that uses only local measurements to detect fault states of the network without the need for communication infrastructure. Multiple sampling points are used to derive a data-driven model, which allows the generalization considering the implementation in physical systems. The adaptive fault detector model is implemented on a Jetson Nano system, which is a single-board computer (SBC) with a small Graphic Processing Unit (GPU) intended to run machine learning loads at the edge. The proposed method is tested in a physical, real-life, low-voltage network located at Universidad del Norte, Colombia. This testing network is based on the IEEE-13 Node Test Feeder scaled down to 220 V. The validation in a simulation environment shows the accuracy and dependability above 99.6%, while the real-time tests show the accuracy and dependability of 95.5% and 100%, respectively. Without hard-to-derive parameters, the easy-to-implement embedded model highlights the potential for real-life applications.

42 ENGINEERING↗