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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 325 records · Page 18
All sourcesNASA NTRSDOE OSTI
NASA NTRS2003

Advanced Signal Processing for Integrated LES-RANS Simulations: Anti-aliasing Filters

Currently, a wide variety of flow phenomena are addressed with numerical simulations. Many flow solvers are optimized to simulate a limited spectrum of flow effects effectively, such as single parts of a flow system, but are either inadequate or too expensive to be applied to a very complex problem. As an example, the flow through a gas turbine can be considered. In the compressor and the turbine section, the flow solver has to be able to handle the moving blades, model the wall turbulence, and predict the pressure and density distribution properly. This can be done by a flow solver based on the Reynolds-Averaged Navier-Stokes (RANS) approach. On the other hand, the flow in the combustion chamber is governed by large scale turbulence, chemical reactions, and the presence of fuel spray. Experience shows that these phenomena require an unsteady approach. Hence, for the combustor, the use of a Large Eddy Simulation (LES) flow solver is desirable. While many design problems of a single flow passage can be addressed by separate computations, only the simultaneous computation of all parts can guarantee the proper prediction of multi-component phenomena, such as compressor/combustor instability and combustor/turbine hot-streak migration. Therefore, a promising strategy to perform full aero-thermal simulations of gas-turbine engines is the use of a RANS flow solver for the compressor sections, an LES flow solver for the combustor, and again a RANS flow solver for the turbine section.

Schlueter, J. U.↗
NASA NTRS2002

INTEGRITY - Integrated Human Exploration Mission Simulation Facility

It is proposed to develop a high-fidelity ground facility to carry out long-duration human exploration mission simulations. These would not be merely computer simulations - they would in fact comprise a series of actual missions that just happen to stay on earth. These missions would include all elements of an actual mission, using actual technologies that would be used for the real mission. These missions would also include such elements as extravehicular activities, robotic systems, telepresence and teleoperation, surface drilling technology-all using a simulated planetary landscape. A sequence of missions would be defined that get progressively longer and more robust, perhaps a series of five or six missions over a span of 10 to 15 years ranging in duration from 180 days up to 1000 days. This high-fidelity ground facility would operate hand-in-hand with a host of other terrestrial analog sites such as the Antarctic, Haughton Crater, and the Arizona desert. Of course, all of these analog mission simulations will be conducted here on earth in 1-g, and NASA will still need the Shuttle and ISS to carry out all the microgravity and hypogravity science experiments and technology validations. The proposed missions would have sufficient definition such that definitive requirements could be derived from them to serve as direction for all the program elements of the mission. Additionally, specific milestones would be established for the "launch" date of each mission so that R&D programs would have both good requirements and solid milestones from which to .build their implementation plans. Mission aspects that could not be directly incorporated into the ground facility would be simulated via software. New management techniques would be developed for evaluation in this ground test facility program. These new techniques would have embedded metrics which would allow them to be continuously evaluated and adjusted so that by the time the sequence of missions is completed, the best management techniques will have been developed, implemented, and validated. A trained cadre of managers experienced with a large, complex program would then be available.

Henninger, Donald L.↗
NASA NTRS1972

Simulation of a steady-state integrated human thermal system.

The mathematical model of an integrated human thermal system is formulated. The system consists of an external thermal regulation device on the human body. The purpose of the device (a network of cooling tubes held in contact with the surface of the skin) is to maintain the human body in a state of thermoneutrality. The device is controlled by varying the inlet coolant temperature and coolant mass flow rate. The differential equations of the model are approximated by a set of algebraic equations which result from the application of the explicit forward finite difference method to the differential equations. The integrated human thermal system is simulated for a variety of combinations of the inlet coolant temperature, coolant mass flow rate, and metabolic rates. Two specific cases are considered: (1) the external thermal regulation device is placed only on the head and (2) the devices are placed on the head and the torso. The results of the simulation indicate that when the human body is exposed to hot environment, thermoneutrality can be attained by localized cooling if the operating variables of the external regulation device(s) are properly controlled.

Hsu, F. T.↗
NASA NTRS1972

Simulation of a steady-state integrated human thermal system.

The mathematical model of an integrated human thermal system is formulated. The system consists of an external thermal regulation device on the human body. The purpose of the device (a network of cooling tubes held in contact with the surface of the skin) is to maintain the human body in a state of thermoneutrality. The device is controlled by varying the inlet coolant temperature and coolant mass flow rate. The differential equations of the model are approximated by a set of algebraic equations which result from the application of the explicit forward finite difference method to the differential equations. The integrated human thermal system is simulated for a variety of combinations of the inlet coolant temperature, coolant mass flow rate, and metabolic rates.

Hsu, F. T.↗
NASA NTRS1984

Autonomous Integrated Receive System (AIRS) requirements definition. Volume 3: Performance and simulation

The autonomous and integrated aspects of the operation of the AIRS (Autonomous Integrated Receive System) are discussed from a system operation point of view. The advantages of AIRS compared to the existing SSA receive chain equipment are highlighted. The three modes of AIRS operation are addressed in detail. The configurations of the AIRS are defined as a function of the operating modes and the user signal characteristics. Each AIRS configuration selection is made up of three components: the hardware, the software algorithms and the parameters used by these algorithms. A comparison between AIRS and the wide dynamics demodulation (WDD) is provided. The organization of the AIRS analytical/simulation software is described. The modeling and analysis is for simulating the performance of the PN subsystem is documented. The frequence acquisition technique using a frequency-locked loop is also documented. Doppler compensation implementation is described. The technological aspects of employing CCD's for PN acquisition are addressed.

Chie, C. M.↗
NASA NTRS1998

X-33 Integrated Test facility, Extended Range Simulation

In support of the X-33 Single Stage To Orbit program, NASA Dryden Flight Research Center was selected to provide continuous communications coverage of the X-33 vehicle from launch, through landing at Malmstrom Air Force Base, Montana and Michaels Army Air Field, Utah. An extensive real-time range simulation capability is being developed to ensure successful communications with the autonomous X-33 vehicle. This paper will provide an overview of the various levels of simulation being developed to support the X-33 extended range subsystems. These subsystems include the Flight Termination System, L-Band command uplink subsystem and the S-Band telemetry downlink subsystem. In addition, the radar model developed provides continuous azimuth, elevation and range information based on the flight trajectory. The Dynamic Ground Station Analysis model developed by NASA Goddard Space Flight Center, calculate the received signal strength at each ground station. This model takes into consideration Radio Frequency (RF) link parameters such as frequency, antenna gain, space loss, plasma effects and the vehicle's position and attitude at any point in time during the flight path. All three RF links are then attenuated based on this calculated level and the RF signals are sent into telemetry receivers to emulate remote sites, or the power incident on the vehicle from uplinked signals. The best source received telemetry data is then passed back to the Launch and Mission Control Monitoring System (LMCMS) resident in the Operations Control Center. The LMCMS also provides the range simulation system the uplink command combined with differential GPS corrections. Later stages will require the progressive integration of actual range hardware with this simulation effort, leading to communication between telemetry, uplink and FTS antennas at NASA Dryden Flight Research Center, with vehicle antennas mounted on the Walter C. Williams Research Aircraft Integration Facility (RAIF). Decommutated Pulse Code Modulated (PCM) data is displayed on one of the four monitors that comprise the Range Safety Officer's (RSO) station. Also displayed are instantaneous impact prediction models, and Federal Aviation Administration (FAA) data for notification of other traffic in the area. Aside from initiating the flight termination command and validating communication links, the RSO station with the range simulation will be used to provide both range control and range safety officers training. The training is necessary to perform their respective functions with greater levels of confidence prior to first flight.

Sharma, Ashley↗
NASA NTRS1982

Nozzle performance calibration and turbomachinery operational analysis of Turbo-Powered Simulators (TPS) for the NASA-Langley EET propulsion airframe integration investigation

The Boeing flight simulator chamber facility energy efficient transport (EET) propulsion/airframe integration investigation was tested. Two turbopowered simulators (TPS) were calibrated with four different nacelle configurations. Two nacelle configurations were calibrated on each TPS, each calibration simulating the full nozzle pressure ratio range encountered in a one atmosphere total pressure wind tunnel operating over a Mach number range from 0.70 to 0.90 Mach. The results of the calibration test are in the form of velocity and discharge coefficient which is used in determining the simulator thrust while the TPS is operating in the wind tunnel.

Rowe, R. K.↗
DOE OSTI2025

Hydrologic Model Data for the East Fork Poplar Creek Watershed Simulated with the Advanced Terrestrial Simulator (ATS): Streamflow and Network Expansion–Contraction Dynamics

This dataset supports hydrologic modeling and stream network expansion–contraction analysis for the East Fork Poplar Creek (EFPC) Watershed in Tennessee. It includes a Jupyter notebook for model setup, model configuration files, simulation outputs, and derived products used to evaluate model performance and investigate stream dynamics under varying hydrologic conditions. The dataset was generated using the Watershed Workflow Python package and the Advanced Terrestrial Simulator (ATS), enabling integrated surface–subsurface hydrologic simulations using a stream-aligned mesh. Outputs include high-resolution time series of streamflow, active network length, water table depth, and related hydrologic variables. Also included are spatially explicit stream persistency indices and classifications of reaches as perennial or non-perennial. These data facilitate reproducibility and support further research on stream intermittency and variability in network extent.The model data archive is organized in following directories:1) model_setup_inputsContains the Watershed Workflow Jupyter notebooks (accessed through any open source code editor), selected input datasets, and resulting ATS input files, including XML files (access through any open source code editor), computational mesh (.exo files can be viewed using Paraview), and meteorological forcing files (.h5 files can be accessed through h5py python package and HDFView open source software). 2) model_outputsIncludes ATS simulation outputs relevant to this study. Time series of spatially integrated or averaged variables (e.g., streamflow, water table depth) are provided as CSV files. Select spatial fields (e.g., ponded depth and water table depth) are saved as pickled Python objects to reduce file size, and can be accessed through pickle package in Python. Key geometry objects from Watershed Workflow—such as the surface mesh and river tree—are also included to support analysis of streamflow persistency and expansion–contraction dynamics. These files can also be accessed through Watershed Workflow Python package.3) model_evaluationProvides observed streamflow time series and field survey-based flow regime classifications used to evaluate model performance. Jupyter notebooks for processing ATS outputs and comparing model predictions with observations to build confidence in the model prior to scientific analysis are also included.4) Q_L_relationshipsContains workflows for generating time series of discharge, active network length, and related hydrologic variables used in the stream network expansion–contraction analysis. Includes routines for delineating baseflow-dominated periods. For each catchment, notebooks and processed data (as pickled DataFrames accessed through Pandas Python package) are provided. 5) figure_scriptsProvides the Jupyter notebooks used to generate the figures presented in the paper.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1985

Statistical magnetic anomalies from satellite measurements for geologic analysis

The errors of numerically averaging satellite magnetic anomaly data for geologic analysis are investigated using orbital anomaly simulations of crustal magnetic sources by Gauss-Legendre quadrature integration. These simulations suggest that numerical averaging errors constitute small and relatively minor contributions to the total error-budget of higher orbital estimates (approx. 400 km), whereas for lower orbital estimates the error of averaging may increase substantially. Least-squares collocation is also investigated as an alternative to numerical averaging and found to produce substantially more accurate anomaly estimates as the elevation of prediction is decreased towards the crustal sources.

Goyal, H. K.↗
NASA NTRS1987

Integrated restructurable flight control system demonstration results

The purpose of this study was to examine the complementary capabilities of several restructurable flight control system (RFCS) concepts through the integration of these technologies into a complete system. Performance issues were addressed through a re-examination of RFCS functional requirements, and through a qualitative analysis of the design issues that, if properly addressed during integration, will lead to the highest possible degree of fault-tolerant performance. Software developed under previous phases of this contract and under NAS1-18004 was modified and integrated into a complete RFCS subroutine for NASA's B-737 simulation. The integration of these modules involved the development of methods for dealing with the mismatch between the outputs of the failure detection module and the input requirements of the automatic control system redesign module. The performance of this demonstration system was examined through extensive simulation trials.

Weiss, Jerold L.↗
NASA NTRS2010

The Application of Modeling and Simulation in Capacity Management within the ITIL Framework

Tightly integrating modeling and simulation techniques into Information Technology Infrastructure Library (ITIL) practices can be one of the driving factors behind a successful and cost-effective capacity management effort for any Information Technology (IT) system. ITIL is a best practices framework for managing IT infrastructure, development and operations. Translating ITIL theory into operational reality can be a challenge. This paper aims to highlight how to best integrate modeling and simulation into an ITIL implementation. For cases where the project team initially has difficulty gaining consensus on investing in modeling and simulation resources, a clear definition for M&S implementation into the ITIL framework, specifically its role in supporting Capacity Management, is critical to gaining the support required to garner these resources. This implementation should also help to clearly define M&S support to the overall system mission. This paper will describe the development of an integrated modeling approach and how best to tie M&S to definitive goals for evaluating system capacity and performance requirements. Specifically the paper will discuss best practices for implementing modeling and simulation into ITIL. These practices hinge on implementing integrated M&S methods that 1) encompass at least two or more predictive modeling techniques, 2) complement each one's respective strengths and weaknesses to support the validation of predicted results, and 3) are tied to the system's performance and workload monitoring efforts. How to structure two forms of modeling: statistical and simUlation in the development of "As Is" and "To Be" efforts will be used to exemplify the integrated M&S methods. The paper will show how these methods can better support the project's overall capacity management efforts.

Rahmani, Sonya↗
NASA NTRS1988

Simulation of proton-induced energy deposition in integrated circuits

A time-efficient simulation technique was developed for modeling the energy deposition by incident protons in modern integrated circuits. To avoid the excessive computer time required by many proton-effects simulators, a stochastic method was chosen to model the various physical effects responsible for energy deposition by incident protons. Using probability density functions to describe the nuclear reactions responsible for most proton-induced memory upsets, the simulator determines the probability of a proton hit depositing the energy necessary for circuit destabilization. This factor is combined with various circuit parameters to determine the expected error-rate in a given proton environment. An analysis of transient or dose-rate effects is also performed. A comparison to experimental energy-disposition data proves the simulator to be quite accurate for predicting the expected number of events in certain integrated circuits.

Fernald, Kenneth W.↗
NASA NTRS2012

Integration of MATLAB Simulink(Registered Trademark) Models with the Vertical Motion Simulator

This paper describes the integration of MATLAB Simulink(Registered TradeMark) models into the Vertical Motion Simulator (VMS) at NASA Ames Research Center. The VMS is a high-fidelity, large motion flight simulator that is capable of simulating a variety of aerospace vehicles. Integrating MATLAB Simulink models into the VMS needed to retain the development flexibility of the MATLAB environment and allow rapid deployment of model changes. The process developed at the VMS was used successfully in a number of recent simulation experiments. This accomplishment demonstrated that the model integrity was preserved, while working within the hard real-time run environment of the VMS architecture, and maintaining the unique flexibility of the VMS to meet diverse research requirements.

Lewis, Emily K.↗
NASA NTRS2012

Simulation and Flight Test Capability for Testing Prototype Sense and Avoid System Elements

NASA Langley Research Center (LaRC) and The MITRE Corporation (MITRE) have developed, and successfully demonstrated, an integrated simulation-to-flight capability for evaluating sense and avoid (SAA) system elements. This integrated capability consists of a MITRE developed fast-time computer simulation for evaluating SAA algorithms, and a NASA LaRC surrogate unmanned aircraft system (UAS) equipped to support hardware and software in-the-loop evaluation of SAA system elements (e.g., algorithms, sensors, architecture, communications, autonomous systems), concepts, and procedures. The fast-time computer simulation subjects algorithms to simulated flight encounters/ conditions and generates a fitness report that records strengths, weaknesses, and overall performance. Reviewed algorithms (and their fitness report) are then transferred to NASA LaRC where additional (joint) airworthiness evaluations are performed on the candidate SAA system-element configurations, concepts, and/or procedures of interest; software and hardware components are integrated into the Surrogate UAS research systems; and flight safety and mission planning activities are completed. Onboard the Surrogate UAS, candidate SAA system element configurations, concepts, and/or procedures are subjected to flight evaluations and in-flight performance is monitored. The Surrogate UAS, which can be controlled remotely via generic Ground Station uplink or automatically via onboard systems, operates with a NASA Safety Pilot/Pilot in Command onboard to permit safe operations in mixed airspace with manned aircraft. An end-to-end demonstration of a typical application of the capability was performed in non-exclusionary airspace in October 2011; additional research, development, flight testing, and evaluation efforts using this integrated capability are planned throughout fiscal year 2012 and 2013.

Howell, Charles T.↗
DOE OSTI2024

Spatio–Temporal Machine Learning for Regional to Continental Scale Terrestrial Hydrology

Integrated hydrologic models can simulate coupled surface and subsurface processes but are computationally expensive to run at high resolutions over large domains. Here we develop a novel deep learning model to emulate subsurface flows simulated by the integrated ParFlow–CLM model across the contiguous US. We compare convolutional neural networks like ResNet and UNet run autoregressively against our novel architecture called the Forced SpatioTemporal RNN (FSTR). The FSTR model incorporates separate encoding of initial conditions, static parameters, and meteorological forcings, which are fused in a recurrent loop to produce spatiotemporal predictions of groundwater. We evaluate the model architectures on their ability to reproduce 4D pressure heads, water table depths, and surface soil moisture over the contiguous US at 1 km resolution and daily time steps over the course of a full water year. The FSTR model shows superior performance to the baseline models, producing stable simulations that capture both seasonal and event–scale dynamics across a wide array of hydroclimatic regimes. The emulators provide over 1,000× speedup compared to the original physical model, which will enable new capabilities like uncertainty quantification and data assimilation for integrated hydrologic modeling that were not previously possible. Our results demonstrate the promise of using specialized deep learning architectures like FSTR for emulating complex process–based models without sacrificing fidelity.

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2002

A Facility and Architecture for Autonomy Research

Autonomy is a key enabling factor in the advancement of the remote robotic exploration. There is currently a large gap between autonomy software at the research level and software that is ready for insertion into near-term space missions. The Mission Simulation Facility (MST) will bridge this gap by providing a simulation framework and suite of simulation tools to support research in autonomy for remote exploration. This system will allow developers of autonomy software to test their models in a high-fidelity simulation and evaluate their system's performance against a set of integrated, standardized simulations. The Mission Simulation ToolKit (MST) uses a distributed architecture with a communication layer that is built on top of the standardized High Level Architecture (HLA). This architecture enables the use of existing high fidelity models, allows mixing simulation components from various computing platforms and enforces the use of a standardized high-level interface among components. The components needed to achieve a realistic simulation can be grouped into four categories: environment generation (terrain, environmental features), robotic platform behavior (robot dynamics), instrument models (camera/spectrometer/etc.), and data analysis. The MST will provide basic components in these areas but allows users to plug-in easily any refined model by means of a communication protocol. Finally, a description file defines the robot and environment parameters for easy configuration and ensures that all the simulation models share the same information.

Pisanich, Greg↗