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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 739 records · Page 41
All sourcesNASA NTRSDOE OSTI
NASA NTRS1996

Performance of the NASA Airborne Radar with the Windshear Database for Forward-Looking Systems

This document describes the simulation approach used to test the performance of the NASA airborne windshear radar. An explanation of the actual radar hardware and processing algorithms provides an understanding of the parameters used in the simulation program. This report also contains a brief overview of the NASA airborne windshear radar experimental flight test results. A description of the radar simulation program shows the capabilities of the program and the techniques used for certification evaluation. Simulation of the NASA radar is comprised of three steps. First, the choice of the ground clutter data must be made. The ground clutter is the return from objects in or nearby an airport facility. The choice of the ground clutter also dictates the aircraft flight path since ground clutter is gathered while in flight. The second step is the choice of the radar parameters and the running of the simulation program which properly combines the ground clutter data with simulated windshear weather data. The simulated windshear weather data is comprised of a number of Terminal Area Simulation System (TASS) model results. The final step is the comparison of the radar simulation results to the known windshear data base. The final evaluation of the radar simulation is based on the ability to detect hazardous windshear with the aircraft at a safe distance while at the same time not displaying false alerts.

Switzer, George F.↗
NASA NTRS2011

Theory and Simulations of Solar System Plasmas

"Theory and simulations of solar system plasmas" aims to highlight results from microscopic to global scales, achieved by theoretical investigations and numerical simulations of the plasma dynamics in the solar system. The theoretical approach must allow evidencing the universality of the phenomena being considered, whatever the region is where their role is studied; at the Sun, in the solar corona, in the interplanetary space or in planetary magnetospheres. All possible theoretical issues concerning plasma dynamics are welcome, especially those using numerical models and simulations, since these tools are mandatory whenever analytical treatments fail, in particular when complex nonlinear phenomena are at work. Comparative studies for ongoing missions like Cassini, Cluster, Demeter, Stereo, Wind, SDO, Hinode, as well as those preparing future missions and proposals, like, e.g., MMS and Solar Orbiter, are especially encouraged.

Goldstein, Melvyn L.↗
DOE OSTI2025

Data Assimilation for Robust UQ Within Agent-Based Simulation on HPC Systems

Agent-based simulation provides a powerful tool for in silico system modeling. However, these simulations do not provide built-in methods for uncertainty quantification (UQ). Within these types of models a typical approach to UQ is to run multiple realizations of the model then compute aggregate statistics. This approach is limited due to the compute time required for a solution. When faced with an emerging biothreat, public health decisions need to be made quickly and solutions for integrating near real-time data with analytic tools are needed. We propose an integrated Bayesian UQ framework for agent-based models based on sequential Monte Carlo sampling. Given streaming or static data about the evolution of an emerging pathogen this Bayesian framework provides a distribution over the parameters governing the spread of a disease through a population. These estimates of the spread of a disease may be provided to public health agencies seeking to abate the spread. By coupling agent-based simulations with Bayesian modeling in a data assimilation, our proposed framework provides a powerful tool for modeling dynamical systems in silico. We propose a method which reduces model error and provides a range of realistic possible outcomes. Moreover, our method addresses two primary limitations of ABMs: the lack of UQ and an inability to assimilate data. Our proposed framework combines the flexibility of an agent-based model with UQ provided by the Bayesian paradigm in a workflow which scales well to HPC systems. We provide algorithmic details and results on a simulated outbreak with both static and streaming data.

Spannaus, Adam [ORNL] (ORCID:0000000225213657)↗
NASA NTRS2001

NPARC Alliance

The NPARC Alliance is a cooperative effort between the United States Air Force's Arnold Engineering Development Center, NASA's Glenn Research Center and The Boeing Company. The mission of the Alliance is to develop, validate, and support an integrated, general purpose computational flow simulator for the U.S. aerospace community. The Alliance provides a state of the art simulation system that includes geometry manipulation, flow solution, and post-processing capabilities. The system is centered around the WIND flow solver. This presentation provides an overview of the Alliance and the flowfield simulation system. Several example computations are provided.

DeBonis, James R.↗
NASA NTRS1988

Quadruplex digital flight control system assessment

Described are the development and validation of a double fail-operational digital flight control system architecture for critical pitch axis functions. Architectural tradeoffs are assessed, system simulator modifications are described, and demonstration testing results are critiqued. Assessment tools and their application are also illustrated. Ultimately, the vital role of system simulation, tailored to digital mechanization attributes, is shown to be essential to validating the airworthiness of full-time critical functions such as augmented fly-by-wire systems for relaxed static stability airplanes.

Mulcare, D. B.↗
NASA NTRS2008

Architecture Modeling and Performance Characterization of Space Communications and Navigation (SCaN) Network Using MACHETE

As future space exploration missions will involve larger number of spacecraft and more complex systems, theoretical analysis alone may have limitations on characterizing system performance and interactions among the systems. Simulation tools can be useful for system performance characterization through detailed modeling and simulation of the systems and its environment...This paper reports the simulation of the Orion (Crew Exploration Vehicle) to the International Space Station (ISS) mission where Orion is launched by Ares into orbit on a 14-day mission to rendezvous with the ISS. Communications services for the mission are provided by the Space Communication and Navigation (SCaN) network infrastructure which includes the NASA Space Network (SN), Ground Network (GN) and NASA Integrated Services Network (NISN). The objectives of the simulation are to determine whether SCaN can meet the communications needs of the mission, to demonstrate the benefit of using QoS prioritization, and to evaluate network-key parameters of interest such as delay and throughout.

space based networking↗
NASA NTRS1981

Solar Power Satellite antenna phase control system hardware simulation, phase 4. Volume 3: SOLARSIM users manual

Documentation of the interactive software package designed to predict the effect of certain electrical and mechanical imperfections on the performance of the SPS system is presented. The capabilities of the SOLARSIM program to quantify the spacetenna performance parameter values are described. The SOLARSIM package can compute the RMS pointing error, title effects, MPTX code tracking loop performance, MPTX carrier tracking loop performance, averaged power pattern, and the power transfer efficiency.

Lindsey, W. C.↗
NASA NTRS1992

Domain modeling and grid generation for multi-block structured grids with application to aerodynamic and hydrodynamic configurations

About five years ago, a joint development was started of a flow simulation system for engine-airframe integration studies on propeller as well as jet aircraft. The initial system was based on the Euler equations and made operational for industrial aerodynamic design work. The system consists of three major components: a domain modeller, for the graphical interactive subdivision of flow domains into an unstructured collection of blocks; a grid generator, for the graphical interactive computation of structured grids in blocks; and a flow solver, for the computation of flows on multi-block grids. The industrial partners of the collaboration and NLR have demonstrated that the domain modeller, grid generator and flow solver can be applied to simulate Euler flows around complete aircraft, including propulsion system simulation. Extension to Navier-Stokes flows is in progress. Delft Hydraulics has shown that both the domain modeller and grid generator can also be applied successfully for hydrodynamic configurations. An overview is given about the main aspects of both domain modelling and grid generation.

Spekreijse, S. P.↗
NASA NTRS2006

Crew Launch Vehicle (CLV) Avionics and Software Integration Overview

On January 14, 2004, the President of the United States announced a new plan to explore space and extend a human presence across our solar system. The National Aeronautics and Space Administration (NASA) established the Exploration Systems Mission Directorate (ESMD) to develop and field a Constellation Architecture that will bring the Space Exploration vision to fruition. The Constellation Architecture includes a human-rated Crew Launch Vehicle (CLV) segment, managed by the Marshall Space Flight Center (MSFC), comprised of the First Stage (FS), Upper Stage (US), and Upper Stage Engine (USE) elements. The CLV s purpose is to provide safe and reliable crew and cargo transportation into Low Earth Orbit (LEO), as well as insertion into trans-lunar trajectories. The architecture's Spacecraft segment includes, among other elements, the Crew Exploration Vehicle (CEV), managed by the Johnson Space Flight Center (JSC), which is launched atop the CLV. MSFC is also responsible for CLV and CEV stack integration. This paper provides an overview of the Avionics and Software integration approach (which includes the Integrated System Health Management (ISHM) functions), both within the CLV, and across the CEV interface; it addresses the requirements to be met, logistics of meeting those requirements, and the roles of the various groups. The Avionics Integration and Vehicle Systems Test (ANST) Office was established at the MSFC with system engineering responsibilities for defining and developing the integrated CLV Avionics and Software system. The AIVST Office has defined two Groups, the Avionics and Software Integration Group (AVSIG), and the Integrated System Simulation and Test Integration Group (ISSTIG), and four Panels which will direct trade studies and analyses to ensure the CLV avionics and software meet CLV system and CEV interface requirements. The four panels are: 1) Avionics Integration Panel (AIP), 2) Software Integration Panel, 3) EEE Panel, and 4) Systems Simulation and Test Panel. Membership on the groups and panels includes the MSFC representatives from the requisite engineering disciplines, the First Stage, the Upper Stage, the Upper Stage Engine projects, and key personnel from other NASA centers. The four panels will take the results of trade studies and analyses and develop documentation in support of Design Analysis Cycle Reviews and ultimately the System Requirements Review.

Monell, Donald W.↗
DOE OSTI2023

Constructing Neural Network Based Models for Simulating Dynamical Systems

Dynamical systems see widespread use in natural sciences like physics, biology, and chemistry, as well as engineering disciplines such as circuit analysis, computational fluid dynamics, and control. For simple systems, the differential equations governing the dynamics can be derived by applying fundamental physical laws. However, for more complex systems, this approach becomes exceedingly difficult. Data-driven modeling is an alternative paradigm that seeks to learn an approximation of the dynamics of a system using observations of the true system. In recent years, there has been an increased interest in applying data-driven modeling techniques to solve a wide range of problems in physics and engineering. Here this article provides a survey of the different ways to construct models of dynamical systems using neural networks. In addition to the basic overview, we review the related literature and outline the most significant challenges from numerical simulations that this modeling paradigm must overcome. Based on the reviewed literature and identified challenges, we provide a discussion on promising research areas.

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1981

Model aerodynamic test results for two variable cycle engine coannular exhaust systems at simulated takeoff and cruise conditions. Comprehensive data report. Volume 2: Tabulated aeroynamic data book 1

Tabulated data from wind tunnel tests conducted to evaluate the aerodynamic performance of an advanced coannular exhaust nozzle for a future supersonic propulsion system are presented. Tests were conducted with two test configurations: (1) a short flap mechanism for fan stream control with an isentropic contoured flow splitter, and (2) an iris fan nozzle with a conical flow splitter. Both designs feature a translating primary plug and an auxiliary inlet ejector. Tests were conducted at takeoff and simulated cruise conditions. Data were acquired at Mach numbers of 0, 0.36, 0.9, and 2.0 for a wide range of nozzle operating conditions. At simulated supersonic cruise, both configurations demonstrated good performance, comparable to levels assumed in earlier advanced supersonic propulsion studies. However, at subsonic cruise, both configurations exhibited performance that was 6 to 7.5 percent less than the study assumptions. At takeoff conditions, the iris configuration performance approached the assumed levels, while the short flap design was 4 to 6 percent less. Data are provided through test run 25.

Nelson, D. P.↗
NASA NTRSDate not supplied

Autonomous Science: Simulated Solar System Mission to Enceladus, Icy Ocean Moon of Saturn

Future NASA missions to icy ocean worlds such as Europa, Titan, or Enceladus will collect mass spectrometry (MS) data from exospheres, atmospheres, and plume volatiles to assess their geochemistry and potential for microbial life1. These remote missions face challenges related to limited bandwidth, communication, and power, highlighting the need for science autonomy2 to prioritize data for timely downlink. We extend our previous work on machine learning (ML) biosignature detection from isotope ratio mass spectrometry (IRMS) data to distributed systems missions (DSM) by incorporating the ML and autonomous data quality control and prioritization code into an onboard decision-making platform. We use simulated orbital telemetry for eight orbiters around Enceladus with a mothership to illustrate an automated biosignature and novel seawater chemistry detection with data prioritization from MS analyses of volatile CO2.

Conor Williams↗
NASA NTRS1973

Shuttle mission simulator baseline definition report, volume 1

A baseline definition of the space shuttle mission simulator is presented. The subjects discussed are: (1) physical arrangement of the complete simulator system in the appropriate facility, with a definition of the required facility modifications, (2) functional descriptions of all hardware units, including the operational features, data demands, and facility interfaces, (3) hardware features necessary to integrate the items into a baseline simulator system to include the rationale for selecting the chosen implementation, and (4) operating, maintenance, and configuration updating characteristics of the simulator hardware.

Burke, J. F.↗
NASA NTRS2002

NPSS Overview to TAFW Multidisciplinary Simulation Capabilities

The Numerical Propulsion System Simulation (NPSS) is a concerted effort by NASA Glenn Research Center, the aerospace industry, and academia to develop an advanced engineering environment or integrated collection of software programs for the analysis and design of aircraft engines and, eventually, space transportation components. NPSS is now being applied by GE ground power to ground power generation with the view of expanding the capability to nontraditional power plant applications (example: fuel cells) and NPSS has an interest in in-space power and will be developing those simulation capabilities.

Owen, Karl↗