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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 667 records · Page 37
All sourcesNASA NTRSDOE OSTI
NASA NTRS1993

Computer simulation of a resonant dc link for advanced launch systems

The performance of a resonant dc link based actuator power system being built for an advanced launch system application is evaluated for a typical launch scenario using two end-to-end system simulations, one using a digital computer and the other using a hybrid computer. Aspects of system performance from the switching of the power electronic devices to the vehicle aerodynamics are addressed. Using these simulations, it is shown that the resonance dc link actuator adequately stabilize the vehicle against a wind gust during a launch.

Sudhoff, S. D.↗
NASA NTRS2014

A Modular Framework for Modeling Hardware Elements in Distributed Engine Control Systems

Progress toward the implementation of distributed engine control in an aerospace application may be accelerated through the development of a hardware-in-the-loop (HIL) system for testing new control architectures and hardware outside of a physical test cell environment. One component required in an HIL simulation system is a high-fidelity model of the control platform: sensors, actuators, and the control law. The control system developed for the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) provides a verifiable baseline for development of a model for simulating a distributed control architecture. This distributed controller model will contain enhanced hardware models, capturing the dynamics of the transducer and the effects of data processing, and a model of the controller network. A multilevel framework is presented that establishes three sets of interfaces in the control platform: communication with the engine (through sensors and actuators), communication between hardware and controller (over a network), and the physical connections within individual pieces of hardware. This introduces modularity at each level of the model, encouraging collaboration in the development and testing of various control schemes or hardware designs. At the hardware level, this modularity is leveraged through the creation of a Simulink(R) library containing blocks for constructing smart transducer models complying with the IEEE 1451 specification. These hardware models were incorporated in a distributed version of the baseline C-MAPSS40k controller and simulations were run to compare the performance of the two models. The overall tracking ability differed only due to quantization effects in the feedback measurements in the distributed controller. Additionally, it was also found that the added complexity of the smart transducer models did not prevent real-time operation of the distributed controller model, a requirement of an HIL system.

numerical simulation↗
NASA NTRS2014

A Modular Framework for Modeling Hardware Elements in Distributed Engine Control Systems

Progress toward the implementation of distributed engine control in an aerospace application may be accelerated through the development of a hardware-in-the-loop (HIL) system for testing new control architectures and hardware outside of a physical test cell environment. One component required in an HIL simulation system is a high-fidelity model of the control platform: sensors, actuators, and the control law. The control system developed for the Commercial Modular Aero-Propulsion System Simulation 40k (40,000 pound force thrust) (C-MAPSS40k) provides a verifiable baseline for development of a model for simulating a distributed control architecture. This distributed controller model will contain enhanced hardware models, capturing the dynamics of the transducer and the effects of data processing, and a model of the controller network. A multilevel framework is presented that establishes three sets of interfaces in the control platform: communication with the engine (through sensors and actuators), communication between hardware and controller (over a network), and the physical connections within individual pieces of hardware. This introduces modularity at each level of the model, encouraging collaboration in the development and testing of various control schemes or hardware designs. At the hardware level, this modularity is leveraged through the creation of a Simulink (R) library containing blocks for constructing smart transducer models complying with the IEEE 1451 specification. These hardware models were incorporated in a distributed version of the baseline C-MAPSS40k controller and simulations were run to compare the performance of the two models. The overall tracking ability differed only due to quantization effects in the feedback measurements in the distributed controller. Additionally, it was also found that the added complexity of the smart transducer models did not prevent real-time operation of the distributed controller model, a requirement of an HIL system.

numerical simulation↗
NASA NTRS2015

A Modular Framework for Modeling Hardware Elements in Distributed Engine Control Systems

Progress toward the implementation of distributed engine control in an aerospace application may be accelerated through the development of a hardware-in-the-loop (HIL) system for testing new control architectures and hardware outside of a physical test cell environment. One component required in an HIL simulation system is a high-fidelity model of the control platform: sensors, actuators, and the control law. The control system developed for the Commercial Modular Aero-Propulsion System Simulation 40k (C-MAPSS40k) provides a verifiable baseline for development of a model for simulating a distributed control architecture. This distributed controller model will contain enhanced hardware models, capturing the dynamics of the transducer and the effects of data processing, and a model of the controller network. A multilevel framework is presented that establishes three sets of interfaces in the control platform: communication with the engine (through sensors and actuators), communication between hardware and controller (over a network), and the physical connections within individual pieces of hardware. This introduces modularity at each level of the model, encouraging collaboration in the development and testing of various control schemes or hardware designs. At the hardware level, this modularity is leveraged through the creation of a SimulinkR library containing blocks for constructing smart transducer models complying with the IEEE 1451 specification. These hardware models were incorporated in a distributed version of the baseline C-MAPSS40k controller and simulations were run to compare the performance of the two models. The overall tracking ability differed only due to quantization effects in the feedback measurements in the distributed controller. Additionally, it was also found that the added complexity of the smart transducer models did not prevent real-time operation of the distributed controller model, a requirement of an HIL system.

propulsion simulation↗
NASA NTRS1991

Control system software, simulation, and robotic applications

All essential existing capabilities needed to create a man-machine interaction dynamics and performance (MMIDAP) capability are reviewed. The multibody system dynamics software program Order N DISCOS will be used for machine and musculo-skeletal dynamics modeling. The program JACK will be used for estimating and animating whole body human response to given loading situations and motion constraints. The basic elements of performance (BEP) task decomposition methodologies associated with the Human Performance Institute database will be used for performance assessment. Techniques for resolving the statically indeterminant muscular load sharing problem will be used for a detailed understanding of potential musculotendon or ligamentous fatigue, pain, discomfort, and trauma. The envisioned capacity is to be used for mechanical system design, human performance assessment, extrapolation of man/machine interaction test data, biomedical engineering, and soft prototyping within a concurrent engineering (CE) system.

Frisch, Harold P.↗
NASA NTRS1985

Zero-gravity movement studies

The use of computer graphics to simulate the movement of articulated animals and mechanisms has a number of uses ranging over many fields. Human motion simulation systems can be useful in education, medicine, anatomy, physiology, and dance. In biomechanics, computer displays help to understand and analyze performance. Simulations can be used to help understand the effect of external or internal forces. Similarly, zero-gravity simulation systems should provide a means of designing and exploring the capabilities of hypothetical zero-gravity situations before actually carrying out such actions. The advantage of using a simulation of the motion is that one can experiment with variations of a maneuver before attempting to teach it to an individual. The zero-gravity motion simulation problem can be divided into two broad areas: human movement and behavior in zero-gravity, and simulation of articulated mechanisms.

Badler, N. I.↗
NASA NTRSDate not supplied

Introducing The Lunar Autonomous PNT System(LAPS) Simulator

In this paper we introduce a software simulator that has been used to develop an architecture for a low-cost Lunar Autonomous Position, Navigation and Time (PNT) System, LAPS. LAPS is a conceptual architecture for providing autonomous PNT services on and around the Moon using non-dedicated low-cost orbital and ground assets. The simulation tool has been developed to be flexible and is capable of modeling and analyzing the many different capabilities and configurations that the non-dedicated assets could support. The tool models the creation of an ad hoc swarm, the localization of this swarm and the subsequent provision of PNT services from this swarm. We present results from several studies of select configurations chosen to reflect existing and future real-world needs and capabilities.

Benjamin Hagenau↗
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.↗