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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 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
NASA NTRS2014

A Process for the Creation of T-MATS Propulsion System Models from NPSS data

A modular thermodynamic simulation package called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS) has been developed for the creation of dynamic simulations. The T-MATS software is designed as a plug-in for Simulink (Math Works, Inc.) and allows a developer to create system simulations of thermodynamic plants (such as gas turbines) and controllers in a single tool. Creation of such simulations can be accomplished by matching data from actual systems, or by matching data from steady state models and inserting appropriate dynamics, such as the rotor and actuator dynamics for an aircraft engine. This paper summarizes the process for creating T-MATS turbo-machinery simulations using data and input files obtained from a steady state model created in the Numerical Propulsion System Simulation (NPSS). The NPSS is a thermodynamic simulation environment that is commonly used for steady state gas turbine performance analysis. Completion of all the steps involved in the process results in a good match between T-MATS and NPSS at several steady state operating points. Additionally, the T-MATS model extended to run dynamically provides the possibility of simulating and evaluating closed loop responses.

gas path dynamics↗
NASA NTRS2004

Turbofan Engine Simulated in a Graphical Simulation Environment

Recently, there has been an increase in the development of intelligent engine technology with advanced active component control. The computer engine models used in these control studies are component-level models (CLM), models that link individual component models of state space and nonlinear algebraic equations, written in a computer language such as Fortran. The difficulty faced in performing control studies on Fortran-based models is that Fortran is not supported with control design and analysis tools, so there is no means for implementing real-time control. It is desirable to have a simulation environment that is straightforward, has modular graphical components, and allows easy access to health, control, and engine parameters through a graphical user interface. Such a tool should also provide the ability to convert a control design into real-time code, helping to make it an extremely powerful tool in control and diagnostic system development. Simulation time management is shown: Mach number versus time, power level angle versus time, altitude versus time, ambient temperature change versus time, afterburner fuel flow versus time, controller and actuator dynamics, collect initial conditions, CAD output, and component-level model: CLM sensor, CAD input, and model output. The Controls and Dynamics Technologies Branch at the NASA Glenn Research Center has developed and demonstrated a flexible, generic turbofan engine simulation platform that can meet these objectives, known as the Modular Aero-Propulsion System Simulation (MAPSS). MAPSS is a Simulink-based implementation of a Fortran-based, modern high pressure ratio, dual-spool, low-bypass, military-type variable-cycle engine with a digital controller. Simulink (The Mathworks, Natick, MA) is a computer-aided control design and simulation package allows the graphical representation of dynamic systems in a block diagram form. MAPSS is a nonlinear, non-real-time system composed of controller and actuator dynamics (CAD) and component-level model (CLM) modules. The controller in the CAD module emulates the functionality of a digital controller, which has a typical update rate of 50 Hz. The CLM module simulates the dynamics of the engine components and uses an update rate of 2500 Hz, which is needed to iterate to balance mass and energy among system components. The actuators in the CAD module use the same sampling rate as those in the CLM. Two graphs of normalized spool speed versus time in seconds and one graph of normalized average metal temperature versus time in seconds is shown. MAPSS was validated via open-loop and closed-loop comparisons with the Fortran simulation. The preceding plots show the normalized results of a closed-loop comparison looking at three states of the model: low-pressure spool speed, high-pressure spool speed, and the average metal temperature measured from the combustor to the high-pressure turbine. In steady state, the error between the simulations is less than 1 percent. During a transient, the difference between the simulations is due to a correction in MAPSS that prevents the gas flow in the bypass duct inlet from flowing forward instead of toward the aft end, which occurs in the Fortran simulation. A comparison between MAPSS and the Fortran model of the bypass duct inlet flow for power lever angles greater than 35 degrees is shown.

Parker, Khary I.↗
NASA NTRS2013

Sample Analysis at Mars Instrument Simulator

The Sample Analysis at Mars Instrument Simulator (SAMSIM) is a numerical model dedicated to plan and validate operations of the Sample Analysis at Mars (SAM) instrument on the surface of Mars. The SAM instrument suite, currently operating on the Mars Science Laboratory (MSL), is an analytical laboratory designed to investigate the chemical and isotopic composition of the atmosphere and volatiles extracted from solid samples. SAMSIM was developed using Matlab and Simulink libraries of MathWorks Inc. to provide MSL mission planners with accurate predictions of the instrument electrical, thermal, mechanical, and fluid responses to scripted commands. This tool is a first example of a multi-purpose, full-scale numerical modeling of a flight instrument with the purpose of supplementing or even eliminating entirely the need for a hardware engineer model during instrument development and operation. SAMSIM simulates the complex interactions that occur between the instrument Command and Data Handling unit (C&DH) and all subsystems during the execution of experiment sequences. A typical SAM experiment takes many hours to complete and involves hundreds of components. During the simulation, the electrical, mechanical, thermal, and gas dynamics states of each hardware component are accurately modeled and propagated within the simulation environment at faster than real time. This allows the simulation, in just a few minutes, of experiment sequences that takes many hours to execute on the real instrument. The SAMSIM model is divided into five distinct but interacting modules: software, mechanical, thermal, gas flow, and electrical modules. The software module simulates the instrument C&DH by executing a customized version of the instrument flight software in a Matlab environment. The inputs and outputs to this synthetic C&DH are mapped to virtual sensors and command lines that mimic in their structure and connectivity the layout of the instrument harnesses. This module executes, and thus validates, complex command scripts prior to their up-linking to the SAM instrument. As an output, this module generates synthetic data and message logs at a rate that is similar to the actual instrument.

Benna, Mehdi↗
NASA NTRS2019

Software and System Health Management with R2U2

R2U2 (Realizable, Responsive, Unobtrusive Unit) is a hardware-supported tool and framework for the real-time system and software health management of cyber-physical systems. R2U2 continuously monitors properties about safety, performance, and security of the vehicle and can perform diagnostic reasoning. Efficient observers for past-time and future-time Metric Temporal Logic, reasoners for Bayesian Networks, and model-based prognostics algorithms are major components of R2U2. Their combination makes it possible to design powerful models for system runtime monitoring, diagnostics, software health management, prognostics, and security monitoring. The R2U2 monitoring engine is designed for minimal runtime overhead and is available as Simulink block or as a software component for integration into the flight software stack, and enables R2U2 to monitor complex cyber-physical systems without any instrumentation of the flight software. In this presentation, we give an overview of R2U2 architecture and reasoning algorithms, present its features, and give a life demo of the tool.

Schumann, Johann↗
NASA NTRS2011

A Data System for a Rapid Evaluation Class of Subscale Aerial Vehicle

A low cost, rapid evaluation, test aircraft is used to develop and test airframe damage diagnosis algorithms at Langley Research Center as part of NASA's Aviation Safety Program. The remotely operated subscale aircraft is instrumented with sensors to monitor structural response during flight. Data is collected for good and compromised airframe configurations to develop data driven models for diagnosing airframe state. This paper describes the data acquisition system (DAS) of the rapid evaluation test aircraft. A PC/104 form factor DAS was developed to allow use of Matlab, Simulink simulation code in Langley's existing subscale aircraft flight test infrastructure. The small scale of the test aircraft permitted laboratory testing of the actual flight article under controlled conditions. The low cost and modularity of the DAS permitted adaptation to various flight experiment requirements.

Hogge, Edward F.↗
NASA NTRS1994

Controls design with crossfeeds for hovering rotorcraft using quantitative feedback theory

This work is extending the research accomplished on project NCC2-751. A newly implemented helicopter model has been used to simulate 25 flight configurations near hover for the UH-60 RASCAL aircraft. A new engine model has been installed in the FORECAST simulation (alias UMGENHEL) for the better prediction of the yaw and heave responses. By applying the decoupling metric from project NCC 751 it was determined that the aileron to pitch and the elevator to yaw responses do not indicate the need for crossfeeds since both of them have a decoupling metric value over 20 dB (less than 10 percent coupling). In the case of the aileron to heave and the elevator to heave responses, the large size and the overlapping of the templates indicate that a low-order dynamic crossfeed cannot be found. The low-order dynamic crossfeed selection is proceeding, however, for the remaining eight crossfeeds. Note that most of them have successfully decoupled the system by 20 dB or more, except for the rudder to heave crossfeed (18.2 dB). It is probable that the engine model needs more accuracy to further improve the heave to yaw crossfeed decoupling metric value. To see how the new low-order dynamic crossfeeds perform, a simulation was accomplished using MATLAB SIMULINK.

Biezad, Daniel J.↗
NASA NTRS2012

Getting a Cohesive Answer from a Common Start: Scalable Multidisciplinary Analysis through Transformation of a Systems Model

One of the challenges of systems engineering is in working multidisciplinary problems in a cohesive manner. When planning analysis of these problems, system engineers must trade between time and cost for analysis quality and quantity. The quality often correlates with greater run time in multidisciplinary models and the quantity is associated with the number of alternatives that can be analyzed. The trade-off is due to the resource intensive process of creating a cohesive multidisciplinary systems model and analysis. Furthermore, reuse or extension of the models used in one stage of a product life cycle for another is a major challenge. Recent developments have enabled a much less resource-intensive and more rigorous approach than hand-written translation scripts between multi-disciplinary models and their analyses. The key is to work from a core systems model defined in a MOF-based language such as SysML and in leveraging the emerging tool ecosystem, such as Query/View/Transformation (QVT), from the OMG community. SysML was designed to model multidisciplinary systems. The QVT standard was designed to transform SysML models into other models, including those leveraged by engineering analyses. The Europa Habitability Mission (EHM) team has begun to exploit these capabilities. In one case, a Matlab/Simulink model is generated on the fly from a system description for power analysis written in SysML. In a more general case, symbolic analysis (supported by Wolfram Mathematica) is coordinated by data objects transformed from the systems model, enabling extremely flexible and powerful design exploration and analytical investigations of expected system performance.

Operational QVT↗
NASA NTRS2011

LADEE Satellite Modeling and Simulation Development

As human activity on and around the Moon increases, so does the likelihood that our actions will have an impact on its atmosphere. The Lunar Atmosphere and Dust Environment Explorer (LADEE), a NASA satellite scheduled to launch in 2013, will orbit the Moon collecting composition, density, and time variability data to characterize the current state of the lunar atmosphere. LADEE will also test the concept of the "Modular Common Bus" spacecraft architecture, an effort to reduce both development time and cost by designing reusable, modular components for use in multiple missions with similar requirements. An important aspect of this design strategy is to both simulate the spacecraft and develop the flight code in Simulink, a block diagram-style programming language that allows easy algorithm visualization and performance testing. Before flight code can be tested, however, a realistic simulation of the satellite and its dynamics must be generated and validated. This includes all of the satellite control system components such as actuators used for force and torque generation and sensors used for inertial orientation reference. My primary responsibilities have included designing, integrating, and testing models for the LADEE thrusters, reaction wheels, star trackers, and rate gyroscopes.

Adams, Michael↗
NASA NTRS2024

Inexpensive Multirotor Platform for Advanced Controls Testing (IMPACT): Development, Integration, and Experimentation

A comprehensive framework was explored and validated for rapid deployment and testing of custom flight control logic using the Inexpensive Multirotor Platform for Advanced Controls Testing (IMPACT). This vehicle facilitated the efficient validation and refinement of a custom flight control algorithm, which was designed using Simulink and deployed onto a Pixhawk flight computer running PX4 firmware through the utilization of the MathWorks UAV Toolbox. The robust and cost-effective design of IMPACT provides the groundwork for future flight testing of flight controls and model development research for electric vertical takeoff and landing (eVTOL) aircraft.

flight testing↗
NASA NTRS2013

Session 6: Dynamic Modeling and Systems Analysis

These presentations cover some of the ongoing work in dynamic modeling and dynamic systems analysis. The first presentation discusses dynamic systems analysis and how to integrate dynamic performance information into the systems analysis. The ability to evaluate the dynamic performance of an engine design may allow tradeoffs between the dynamic performance and operability of a design resulting in a more efficient engine design. The second presentation discusses the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a Simulation system with a library containing the basic building blocks that can be used to create dynamic Thermodynamic Systems. Some of the key features include Turbo machinery components, such as turbines, compressors, etc., and basic control system blocks. T-MAT is written in the Matlab-Simulink environment and is open source software. The third presentation focuses on getting additional performance from the engine by allowing the limit regulators only to be active when a limit is danger of being violated. Typical aircraft engine control architecture is based on MINMAX scheme, which is designed to keep engine operating within prescribed mechanical/operational safety limits. Using a conditionally active min-max limit regulator scheme, additional performance can be gained by disabling non-relevant limit regulators

control↗
NASA NTRS2022

Rapid Flight Control Law Deployment and Testing Framework for Subscale VTOL Aircraft

A set of procedures was developed to enable rapid flight control law deployment and testing on subscale vertical takeoff and landing (VTOL) aircraft. Low-cost, subscale flight vehicles have become well-suited testbeds for rapid flight dynamics and controls research progression; however, integration of custom flight control laws onto flight hardware has historically been an arduous task. The toolchain described in this report leverages Simulink with the UAV Toolbox, a Pixhawk flight computer running PX4 firmware, and QGroundControl to efficiently design and flight test custom control algorithms. A subscale CL-84 VTOL aircraft was used as a testbed in this investigation to exercise the hardware integration process on a physical model. Implementation of custom attitude stabilization control laws and programmed test input excitations for aircraft system identification were demonstrated using the expeditious hardware integration process. The detailed procedures given in this report are expected to be used in future flight test efforts.

flight testing↗
NASA NTRS1998

Simulation-Based Analysis of Reentry Dynamics for the Sharp Atmospheric Entry Vehicle

This thesis describes the analysis of the reentry dynamics of a high-performance lifting atmospheric entry vehicle through numerical simulation tools. The vehicle, named SHARP, is currently being developed by the Thermal Protection Materials and Systems branch of NASA Ames Research Center, Moffett Field, California. The goal of this project is to provide insight into trajectory tradeoffs and vehicle dynamics using simulation tools that are powerful, flexible, user-friendly and inexpensive. Implemented Using MATLAB and SIMULINK, these tools are developed with an eye towards further use in the conceptual design of the SHARP vehicle's trajectory and flight control systems. A trajectory simulator is used to quantify the entry capabilities of the vehicle subject to various operational constraints. Using an aerodynamic database computed by NASA and a model of the earth, the simulator generates the vehicle trajectory in three-dimensional space based on aerodynamic angle inputs. Requirements for entry along the SHARP aerothermal performance constraint are evaluated for different control strategies. Effect of vehicle mass on entry parameters is investigated, and the cross range capability of the vehicle is evaluated. Trajectory results are presented and interpreted. A six degree of freedom simulator builds on the trajectory simulator and provides attitude simulation for future entry controls development. A Newtonian aerodynamic model including control surfaces and a mass model are developed. A visualization tool for interpreting simulation results is described. Control surfaces are roughly sized. A simple controller is developed to fly the vehicle along its aerothermal performance constraint using aerodynamic flaps for control. This end-to-end demonstration proves the suitability of the 6-DOF simulator for future flight control system development. Finally, issues surrounding real-time simulation with hardware in the loop are discussed.

Tillier, Clemens Emmanuel↗
NASA NTRS1997

SPASIM: A Spacecraft Simulator

The SPAcecraft SIMulator (SPASIM) simulates the functions and resources of a spacecraft to quickly perform conceptual design (Phase A) trade-off and sensitivity analyses and uncover any operational bottlenecks during any part of the mission. Failure modes and operational contingencies can be evaluated allowing operational planning (what-if scenarios) and optimization for a range of mission scenarios. The payloads and subsystems are simulated, using a hierarchy of graphical models, in terms of how their functions affect resources such as propellant, power, and data. Any of the inputs and outputs of the payloads and subsystems can be plotted during the simulation or stored in a file so they can be used by other programs. Most trade-off analyses, including those that compare current versus advanced technology, can be performed by changing values in the parameter menus. However, when a component is replaced by one with a different functional architecture, its graphical model can also be modified or replaced by drawing from a component library. SPASIM has been validated using several spacecraft designs that were at least at the Critical Design Review level. The user and programmer guide, including figures, is available on line as a hypertext document. This is an easy-to-use and expandable tool which is based on MATLAB(R) and SIMULINK(R). It runs on Silicon Graphics Inc. workstations and personal computers with Windows 95(TM) or NT(TM).

Liceaga, Carlos A.↗
NASA NTRS1997

A Functional Simulator of Spacecraft Resources

The SPAcecraft SIMulator (SPASIM) simulates the functions and resources of a spacecraft to quickly perform Phase A trade-off analyses and uncover any operational bottlenecks during any part of the mission. Failure modes and operational contingencies can be evaluated allowing optimization for a range of mission scenarios. The payloads and subsystems are simulated, using a hierarchy of graphical models, in terms of how their functions affect resources such as propellant, power, and data. Any of the inputs and outputs of the payloads and subsystems can be plotted during the simulation. Most trade-off analyses, including those that compare current versus advanced technology, can be performed by changing values in the parameter menus. However, when a component is replaced by one with a different functional architecture, its graphical model can also be modified or replaced by drawing from a component library. SPASIM has been validated using several spacecraft designs which were at least at the Critical Design Review level. The user and programmer guide, including figures, is available on line as a hyper text document. This is an easy-to-use and expand tool which is based on MATLAB and SIMULINK. It runs on SGI workstations and PCs under Windows 95 or NT.

Liceaga, Carlos A.↗
NASA NTRS1993

Development of a non-linear simulation for generic hypersonic vehicles - ASUHS1

A nonlinear simulation is developed to model the longitudinal motion of a vehicle in hypersonic flight. The equations of motion pertinent to this study are presented. Analytic expressions for the aerodynamic forces acting on a hypersonic vehicle which were obtained from Newtonian Impact Theory are further developed. The control surface forces are further examined to incorporate vehicle elastic motion. The purpose is to establish feasible equations of motion which combine rigid body, elastic, and aeropropulsive dynamics for use in nonlinear simulations. The software package SIMULINK is used to implement the simulation. Also discussed are issues needing additional attention and potential problems associated with the implementation (with proposed solutions).

Salas, Juan↗
NASA NTRS2020

Multi-Objective Gust Load Alleviation Control Designs for an Aeroelastic Wind Tunnel Demonstration Wing

This paper presents several control and gust disturbance estimation techniques applied to a mathematical model of a physical flexible wing wind tunnel model used in ongoing tests at the University of Washington Aeronautical Laboratory's Kirsten Wind Tunnel. Three methods of gust disturbance estimation are presented, followed by three control methods: LQG, Basic Multi-Objective (BMO), and a novel Multi-Objective Prediction Correction (MOPC) controller. The latter of which augments a multi-objective controller, and attempts to correct for errors in the disturbance estimate. A simplified linear simulation of the three controllers is performed and a simple MIMO stability and robustness assessment is performed. Then, the same controllers are simulated in a higher fidelity Simulink environment that captures sampling, saturation and noise effects. This preliminary analysis indicates that the BMO controller provides the best performance and largest stability margins.

Drew, Michael C.↗