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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 883 records · Page 49
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

High-performance mass storage system for workstations

Reduced Instruction Set Computer (RISC) workstations and Personnel Computers (PC) are very popular tools for office automation, command and control, scientific analysis, database management, and many other applications. However, when using Input/Output (I/O) intensive applications, the RISC workstations and PC's are often overburdened with the tasks of collecting, staging, storing, and distributing data. Also, by using standard high-performance peripherals and storage devices, the I/O function can still be a common bottleneck process. Therefore, the high-performance mass storage system, developed by Loral AeroSys' Independent Research and Development (IR&D) engineers, can offload a RISC workstation of I/O related functions and provide high-performance I/O functions and external interfaces. The high-performance mass storage system has the capabilities to ingest high-speed real-time data, perform signal or image processing, and stage, archive, and distribute the data. This mass storage system uses a hierarchical storage structure, thus reducing the total data storage cost, while maintaining high-I/O performance. The high-performance mass storage system is a network of low-cost parallel processors and storage devices. The nodes in the network have special I/O functions such as: SCSI controller, Ethernet controller, gateway controller, RS232 controller, IEEE488 controller, and digital/analog converter. The nodes are interconnected through high-speed direct memory access links to form a network. The topology of the network is easily reconfigurable to maximize system throughput for various applications. This high-performance mass storage system takes advantage of a 'busless' architecture for maximum expandability. The mass storage system consists of magnetic disks, a WORM optical disk jukebox, and an 8mm helical scan tape to form a hierarchical storage structure. Commonly used files are kept in the magnetic disk for fast retrieval. The optical disks are used as archive media, and the tapes are used as backup media. The storage system is managed by the IEEE mass storage reference model-based UniTree software package. UniTree software will keep track of all files in the system, will automatically migrate the lesser used files to archive media, and will stage the files when needed by the system. The user can access the files without knowledge of their physical location. The high-performance mass storage system developed by Loral AeroSys will significantly boost the system I/O performance and reduce the overall data storage cost. This storage system provides a highly flexible and cost-effective architecture for a variety of applications (e.g., realtime data acquisition with a signal and image processing requirement, long-term data archiving and distribution, and image analysis and enhancement).

Chiang, T.↗
NASA NTRS1988

Design of an optical PPM communication link in the presence of component tolerances

A systematic approach is described for estimating the performance of an optical direct detection pulse position modulation (PPM) communication link in the presence of parameter tolerances. This approach was incorporated into the JPL optical link analysis program to provide a useful tool for optical link design. Given a set of system parameters and their tolerance specifications, the program will calculate the nominal performance margin and its standard deviation. Through use of these values, the optical link can be designed to perform adequately even under adverse operating conditions.

Chen, C.-C.↗
NASA NTRS1994

Data Analysis with Graphical Models: Software Tools

Probabilistic graphical models (directed and undirected Markov fields, and combined in chain graphs) are used widely in expert systems, image processing and other areas as a framework for representing and reasoning with probabilities. They come with corresponding algorithms for performing probabilistic inference. This paper discusses an extension to these models by Spiegelhalter and Gilks, plates, used to graphically model the notion of a sample. This offers a graphical specification language for representing data analysis problems. When combined with general methods for statistical inference, this also offers a unifying framework for prototyping and/or generating data analysis algorithms from graphical specifications. This paper outlines the framework and then presents some basic tools for the task: a graphical version of the Pitman-Koopman Theorem for the exponential family, problem decomposition, and the calculation of exact Bayes factors. Other tools already developed, such as automatic differentiation, Gibbs sampling, and use of the EM algorithm, make this a broad basis for the generation of data analysis software.

Buntine, Wray L.↗
DOE OSTI2021

PBjam: A Python Package for Automating Asteroseismology of Solar-like Oscillators

Asteroseismology is an exceptional tool for studying stars using the properties of observed modes of oscillation. So far the process of performing an asteroseismic analysis of a star has remained somewhat esoteric and inaccessible to nonexperts. In this software paper we describe PBjam, an open-source Python package for analyzing the frequency spectra of solar-like oscillators in a simple but principled and automated way. The aim of PBjam is to provide a set of easy-to-use tools to extract information about the radial and quadropole oscillations in stars that oscillate like the Sun, which may then be used to infer bulk properties such as stellar mass, radius, age, or even structure. Asteroseismology and its data analysis methods are becoming increasingly important as space-based photometric observatories are producing a wealth of new data, allowing asteroseismology to be applied in a wide range of contexts such as exoplanet, stellar structure and evolution, and Galactic population studies.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS2008

Solar Tower Experiments for Radiometric Calibration and Validation of Infrared Imaging Assets and Analysis Tools for Entry Aero-Heating Measurements

The NASA Engineering and Safety Center sponsored Hypersonic Thermodynamic Infrared Measurements assessment team has a task to perform radiometric calibration and validation of land-based and airborne infrared imaging assets and tools for remote thermographic imaging. The IR assets and tools will be used for thermographic imaging of the Space Shuttle Orbiter during entry aero-heating to provide flight boundary layer transition thermography data that could be utilized for calibration and validation of empirical and theoretical aero-heating tools. A series of tests at the Sandia National Laboratories National Solar Thermal Test Facility were designed for this task where reflected solar radiation from a field of heliostats was used to heat a 4 foot by 4 foot test panel consisting of LI 900 ceramic tiles located on top of the 200 foot tall Solar Tower. The test panel provided an Orbiter-like entry temperature for the purposes of radiometric calibration and validation. The Solar Tower provided an ideal test bed for this series of radiometric calibration and validation tests because it had the potential to rapidly heat the large test panel to spatially uniform and non-uniform elevated temperatures. Also, the unsheltered-open-air environment of the Solar Tower was conducive to obtaining unobstructed radiometric data by land-based and airborne IR imaging assets. Various thermocouples installed on the test panel and an infrared imager located in close proximity to the test panel were used to obtain surface temperature measurements for evaluation and calibration of the radiometric data from the infrared imaging assets. The overall test environment, test article, test approach, and typical test results are discussed.

Splinter, Scott C.↗
NASA NTRS1996

An Exercise in Ion Beam Analysis

Scattering phenomena are taught in introductory physics classes, and concepts such as conservation of energy and momentum are used at all levels of physics. However, applications of scattering are often not included as part of an education. Rutherford scattering, a topic of any modern physics course, is now used as a tool for materials science applications. In the absence of lab equipment for students to perform such experiments, an exercise in the analysis of scattering data may accent the useful concepts given in lectures. The objective of this exercise is to analyze data from Rutherford backscattering experiments in order to determine elemental composition.

Kern, Kristen T.↗
NASA NTRS1989

New multivariable capabilities of the INCA program

The INteractive Controls Analysis (INCA) program was developed at NASA's Goddard Space Flight Center to provide a user friendly, efficient environment for the design and analysis of control systems, specifically spacecraft control systems. Since its inception, INCA has found extensive use in the design, development, and analysis of control systems for spacecraft, instruments, robotics, and pointing systems. The (INCA) program was initially developed as a comprehensive classical design analysis tool for small and large order control systems. The latest version of INCA, expected to be released in February of 1990, was expanded to include the capability to perform multivariable controls analysis and design.

Bauer, Frank H.↗
DOE OSTI2018

Trial Implementation of a Multihazard Risk Assessment Framework for High-Impact Low-Frequency Power Grid Events

The Pacific Northwest National Laboratory developed a risk framework for modeling high-impact, low-frequency power grid events to support risk-informed decisions. In this research article, we briefly recap the framework and demonstrate its implementation for seismic and geomagnetic hazards using a benchmark reliability test system. We describe integration of a collection of models implemented to perform hazard analysis, fragility evaluation, consequence estimation and post-event restoration. We demonstrate the value of the framework as a multi-hazard power grid risk assessment and management tool. The research will benefit transmission planners and emergency planners by improving their ability to maintain a resilient grid infrastructure against impacts from major events.

power grid, risk assessment, seismic hazard, dynam↗
NASA NTRS2011

Impact of Vehicle Flexibility on IRVE-II Flight Dynamics

The Inflatable Re-entry Vehicle Experiment II (IRVE-II) successfully launched from Wallops Flight Facility (WFF) on August 17, 2009. The primary objectives of this flight test were to demonstrate inflation and re-entry survivability, assess the thermal and drag performance of the reentry vehicle, and to collect flight data for refining pre-flight design and analysis tools. Post-flight analysis including trajectory reconstruction outlined in O Keefe3 demonstrated that the IRVE-II Research Vehicle (RV) met mission objectives but also identified a few anomalies of interest to flight dynamics engineers. Most notable of these anomalies was high normal acceleration during the re-entry pressure pulse. Deflection of the inflatable aeroshell during the pressure pulse was evident in flight video and identified as the likely cause of the anomaly. This paper provides a summary of further post-flight analysis with particular attention to the impact of aeroshell flexibility on flight dynamics and the reconciliation of flight performance with pre-flight models. Independent methods for estimating the magnitude of the deflection of the aeroshell experienced on IRVE-II are discussed. The use of the results to refine models for pre-flight prediction of vehicle performance is then described.

Bose, David M.↗
NASA NTRS2006

On Certain Theoretical Developments Underlying the Hilbert-Huang Transform

One of the main traditional tools used in scientific and engineering data spectral analysis is the Fourier Integral Transform and its high performance digital equivalent - the Fast Fourier Transform (FFT). Both carry strong a-priori assumptions about the source data, such as being linear and stationary, and of satisfying the Dirichlet conditions. A recent development at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), known as the Hilbert-Huang Transform (HHT), proposes a novel approach to the solution for the nonlinear class of spectral analysis problems. Using a-posteriori data processing based on the Empirical Mode Decomposition (EMD) sifting process (algorithm), followed by the normalized Hilbert Transform of the decomposed data, the HHT allows spectral analysis of nonlinear and nonstationary data. The EMD sifting process results in a non-constrained decomposition of a source real-value data vector into a finite set of Intrinsic Mode Functions (IMF). These functions form a nearly orthogonal derived from the data (adaptive) basis. The IMFs can be further analyzed for spectrum content by using the classical Hilbert Transform. A new engineering spectral analysis tool using HHT has been developed at NASA GSFC, the HHT Data Processing System (HHT-DPS). As the HHT-DPS has been successfully used and commercialized, new applications pose additional questions about the theoretical basis behind the HHT and EMD algorithms. Why is the fastest changing component of a composite signal being sifted out first in the EMD sifting process? Why does the EMD sifting process seemingly converge and why does it converge rapidly? Does an IMF have a distinctive structure? Why are the IMFs nearly orthogonal? We address these questions and develop the initial theoretical background for the HHT. This will contribute to the development of new HHT processing options, such as real-time and 2-D processing using Field Programmable Gate Array (FPGA) computational resources,

Kizhner, Semion↗
NASA NTRS2005

On the Hilbert-Huang Transform Theoretical Developments

One of the main heritage tools used in scientific and engineering data spectrum analysis is the Fourier Integral Transform and its high performance digital equivalent - the Fast Fourier Transform (FFT). Both carry strong a-priori assumptions about the source data, such as linearity, of being stationary, and of satisfying the Dirichlet conditions. A recent development at the National Aeronautics and Space Administration (NASA) Goddard Space Flight Center (GSFC), known as the Hilbert-Huang Transform (HHT), proposes a novel approach to the solution for the nonlinear class of spectrum analysis problems. Using a-posteriori data processing based on the Empirical Mode Decomposition (EMD) sifting process (algorithm), followed by the normalized Hilbert Transform of the decomposition data, the HHT allows spectrum analysis of nonlinear and nonstationary data. The EMD sifting process results in a non-constrained decomposition of a source real value data vector into a finite set of Intrinsic Mode Functions (IMF). These functions form a near orthogonal adaptive basis, a basis that is derived from the data. The IMFs can be further analyzed for spectrum interpretation by the classical Hilbert Transform. A new engineering spectrum analysis tool using HHT has been developed at NASA GSFC, the HHT Data Processing System (HHT-DPS). As the HHT-DPS has been successfully used and commercialized, new applications post additional questions about the theoretical basis behind the HHT and EMD algorithms. Why is the fastest changing component of a composite signal being sifted out first in the EMD sifting process? Why does the EMD sifting process seemingly converge and why does it converge rapidly? Does an IMF have a distinctive structure? Why are the IMFs near orthogonal? We address these questions and develop the initial theoretical background for the HHT. This will contribute to the developments of new HHT processing options, such as real-time and 2-D processing using Field Programmable Array (FPGA) computational resources, enhanced HHT synthesis, and broaden the scope of HHT applications for signal processing.

Kizhner, Semion↗
DOE OSTI2022

Network Uncertainty Quantification for Analysis of Multi-Component Systems

To impact physical mechanical system design decisions and realize the full promise of high-fidelity computational tools, simulation results must be integrated at the earliest stages of the design process. This is particularly challenging when dealing with uncertainty and optimizing for system-level performance metrics, as full-system models (often notoriously expensive and time-consuming to develop) are generally required to propagate uncertainties to system-level quantities of interest. Methods for propagating parameter and boundary condition uncertainty in networks of interconnected components hold promise for enabling design under uncertainty in real-world applications. These methods avoid the need for time consuming mesh generation of full-system geometries when changes are made to components or subassemblies. Additionally, they explicitly tie full-system model predictions to component/subassembly validation data which is valuable for qualification. These methods work by leveraging the fact that many engineered systems are inherently modular, being comprised of a hierarchy of components and subassemblies that are individually modified or replaced to define new system designs. By doing so, these methods enable rapid model development and the incorporation of uncertainty quantification earlier in the design process. The resulting formulation of the uncertainty propagation problem is iterative. We express the system model as a network of interconnected component models, which exchange solution information at component boundaries. We present a pair of approaches for propagating uncertainty in this type of decomposed system and provide implementations in the form of an open-source software library. We demonstrate these tools on a variety of applications and demonstrate the impact of problem-specific details on the performance and accuracy of the resulting UQ analysis. This work represents the most comprehensive investigation of these network uncertainty propagation methods to date.

42 ENGINEERING↗
NASA NTRS1992

OCAM - A CELSS modeling tool: Description and results

Controlled Ecological Life Support System (CELSS) technology is critical to the Space Exploration Initiative. NASA's Kennedy Space Center has been performing CELSS research for several years, developing data related to CELSS design. We have developed OCAM (Object-oriented CELSS Analysis and Modeling), a CELSS modeling tool, and have used this tool to evaluate CELSS concepts, using this data. In using OCAM, a CELSS is broken down into components, and each component is modeled as a combination of containers, converters, and gates which store, process, and exchange carbon, hydrogen, and oxygen on a daily basis. Multiple crops and plant types can be simulated. Resource recovery options modeled include combustion, leaching, enzyme treatment, aerobic or anaerobic digestion, and mushroom and fish growth. Results include printouts and time-history graphs of total system mass, biomass, carbon dioxide, and oxygen quantities; energy consumption; and manpower requirements. The contributions of mass, energy, and manpower to system cost have been analyzed to compare configurations and determine appropriate research directions.

Drysdale, Alan↗
DOE OSTI2022

The Evolution of Volatile Memory Forensics

The collection and analysis of volatile memory is a vibrant area of research in the cybersecurity community. The ever-evolving and growing threat landscape is trending towards fileless malware, which avoids traditional detection but can be found by examining a system’s random access memory (RAM). Additionally, volatile memory analysis offers great insight into other malicious vectors. It contains fragments of encrypted files’ contents, as well as lists of running processes, imported modules, and network connections, all of which are difficult or impossible to extract from the file system. For these compelling reasons, recent research efforts have focused on the collection of memory snapshots and methods to analyze them for the presence of malware. However, to the best of our knowledge, no current reviews or surveys exist that systematize the research on both memory acquisition and analysis. We fill that gap with this novel survey by exploring the state-of-the-art tools and techniques for volatile memory acquisition and analysis for malware identification. For memory acquisition methods, we explore the trade-offs many techniques make between snapshot quality, performance overhead, and security. For memory analysis, we examined the traditional forensic methods used, including signature-based methods, dynamic methods performed in a sandbox environment, as well as machine learning-based approaches. We summarize the currently available tools, and suggest areas for more research.

Nyholm, Hannah↗
NASA NTRS2017

Automated Sensitivity Analysis of Interplanetary Trajectories for Optimal Mission Design

This work describes a suite of Python tools known as the Python EMTG Automated Trade Study Application (PEATSA). PEATSA was written to automate the operation of trajectory optimization software, simplify the process of performing sensitivity analysis, and was ultimately found to out-perform a human trajectory designer in unexpected ways. These benefits will be discussed and demonstrated on sample mission designs.

trajectory design↗
DOE OSTI2017

Assembling Multiple Models Within the RAVEN Framework

RAVEN (Risk Analysis Virtual Environment) is an INL-developed software tool that can be used to identify and increase the safety margin in complex systems. As a generic software framework, RAVEN is designed to perform parametric and probabilistic analysis based on the response of complex system codes. RAVEN is capable of investigating the system response as well as the input space using Monte Carlo, Grid, or Latin Hyper Cube sampling schemes, but its strength is focused toward system feature discovery, such as limit surfaces, separating regions of the input space leading to system failure, using dynamic supervised learning techniques. RAVEN is currently able to construct multi-targets Reduced Order Models (ROMs), which are aimed to represent the response of a system (in a fixed configuration) for multiple Figures of Merits (FOMs) and time-dependent ROMs. These capabilities represent the initial steps for a larger implementation about the interaction of multiple models. In fact, in several cases, multiple models need to interface with each other since the initial conditions of one are dependent on the outcomes of another. To better understand the problem that here is solved, it is useful to consider a simple example: The following problem is considered: a weather forecast simulation code 'a' is used to compute the external (i.e. ambient) temperature in a certain location. A second model 'b' is inquired to compute the average temperature in a room having as boundary condition, among several others, the external ambient temperature. The response of the model 'b' depends on the outcome of the model 'a'. The reported example is only aimed to illustrate the reason why the creation of a framework to make interact different models is a key development for the advancement of RAVEN as a comprehensive calculation flow driver. Before reporting how the ensemble-models have been implemented, it is necessary to briefly describe the representative Model 'entities' that are available in RAVEN.

42 ENGINEERING↗
DOE OSTI2025

Gas-Cooled High-Temperature Pebble-Bed Reactor Reference Plant Model Updates

This work presents the latest improvements to, and investigations performed with, the pebble-bed high-temperature gas-cooled reactor (PB-HTGR) reference plant models for the United States Nuclear Regulatory Commission. These models serve as the foundation for the future development of detailed design evaluation models based on license applications. The reference plant models have been developed with the Comprehensive Reactor Analysis Bundle, or BlueCRAB, which is the code suite proposed for non-light-water reactor systems safety analysis. It incorporates various simulation tools developed by the Nuclear Energy Advanced Modeling and Simulation program, including the Griffin code for reactor physics, the Pronghorn and SAM codes for core thermal fluids, the BISON code for solid conduction and fuel performance, and the SAM code for system analysis. The primary objective of the work that was performed was to assess BlueCRAB’s level of readiness for modeling a PB-HTGR. To do so, we first developed numerical models in BlueCRAB that include the key physics for this technology to ensure an adequate level of fidelity for modeling PB-HTGR core performance and for performing multiphysics simulations for equilibrium core conditions and different accident scenarios. Then we simulated transient scenarios, including depressurized and pressurized loss of forced cooling accidents, over-cooling, and control rod withdrawal events with delayed and prompt supercritical reactivity insertions. The analysis in this report includes comparisons of the 2D thermal fluid porous media models in Pronghorn and SAM, and comparisons of coupled SAM/Griffin/SAM and coupled Pronghorn/Griffin for depressurized and pressurized loss of forced cooling, over-cooling, and control rod withdrawal events. In addition, we compare 3D, 2D, and 0D/PKE neutronic models for the two control rod withdrawal scenarios with coupled Pronghorn/Griffin. The comparisons show that the BlueCRAB models lead to physically intuitive solutions for the scenarios examined. The changes in the various scalar and vector fields, such as neutron flux, power, temperature, density, pressure, and velocity, are within the expected ranges, and their distributions can be explained by the system response of the transients and the geometric and material variations. Several comparisons suggest that the porous media models in Pronghorn and SAM can lead to similar solutions, even though they are based on different methodologies. This work further highlights the need for flexible tools with various levels of fidelity to cover the breadth and depth of needs that may arise in future technical evaluations of the PB-HTGR. We believe that the BlueCRAB capabilities will be a significant asset for confirmatory analyses in order to resolve important safety questions.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
NASA NTRS2015

SARDA HITL #6 Simulation: System Performance Analysis (Initial Results)

This presentation discusses the results of the 6th human-in-the-loop simulation of the Spot and Runway Departure Advisor (SARDA). SARDA is a research prototype decision support tool for both Air Traffic Control Tower controllers and airlines ramp controllers to assit in controlling surface traffic of a busy airport. Data was collected during the human-in-the-loop simulations of SARDA for ramp operatoins at Charlotte International Airport (Oct-Nov 2014). The performance results include taxi time, taxi delay, total delay, and runway usage.

surface management↗