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At least 127 records · Page 7

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NASA NTRSDate not supplied

Modeling of a Stewart Platform for Analyzing One Directional Dynamics for Spacecraft Docking Operations

A one-directional dynamic model of a Stewart Platform was developed to assist NASA in analyzing the dynamic response in spacecraft docking operations. A simplified mechanical drawing was created, capturing the physical structure's main features. A simplified schematic diagram was developed in a lumped mass model from the mechanical drawing. Three differential equations were derived according to the schematic diagram. A Simulink diagram was created using MATLAB to represent the three equations. System parameters, including spring constants and masses, are derived in detail from the physical system. The model can be used for further analysis via computer simulation in predicting dynamic response in its main docking direction, i.e., up-and-down motion.

Stewart Platform↗

NASA NTRSDate not supplied

Developing a Multi-Lingual Autocoding Interface for the MAVERIC-II Dynamics Simulator

Simulation model development in certain high-level languages such as Python, MATLAB, or Simulink are unparalleled by their convenience and rapid turnover time. However, legacy simulation engines often depend on more traditional languages such as FORTRAN or C/C++. The NASA Marshall Aerospace Vehicle Representation in C version II (MAVERIC-II) is a modular, legacy-derived computer program used for high-fidelity, 6 degree-of-freedom (6dof) simulation for aerospace vehicle flights and analyses of guidance and control performance with built-in mathematical modeling of environmental effects such as wind, atmosphere, and gravity as well as dispersion capability for Monte Carlo analysis. MAVERIC-II is modular in the sense that each component software element of the simulation engine may be supplanted for a higher or lower fidelity version. The design flow of the development of these models is often performed in high-level languages as mentioned previously, which must then be translated into C or C++ code to be integrated into MAVERIC-II. We propose a unified method of autocoding and interfacing between several languages and MAVERIC-II, which may be generalized further to any type of 6dof simulation engine.

Mason Nixon↗

NASA NTRSDate not supplied

Developing a Multilingual Auto-coding Interface Control for the MAVERIC-II Dynamics Simulator

Simulation model development in certain high-level languages such as Python, MATLAB, or Simulink are unparalleled by their convenience and rapid turnover time. However, legacy simulation engines often depend on more traditional languages such as FORTRAN or C/C++. The NASA Marshall Aerospace Vehicle Representation in C version II (MAVERIC-II) is a modular, legacy-derived computer program used for high-fidelity, 6 degree-of-freedom (6DOF) simulation for aerospace vehicle flights and analyses of guidance and control performance with built-in mathematical modeling of environmental effects such as wind, atmosphere, and gravity as well as dispersion capability for Monte Carlo analysis. MAVERIC-II is modular in the sense that each component software element of the simulation engine may be supplanted for a higher or lower fidelity version. The design flow of the development of these models is often performed in high-level languages as mentioned previously, which must then be translated into C or C++ code to be integrated into MAVERIC-II. Using principles of model-based design, we propose a unified method of auto-coding and interfacing between several languages and MAVERIC-II, which may be generalized further to any type of 6DOF simulation engine.

Mason Nixon↗

NASA NTRSDate not supplied

Runtime Monitoring with R2U2 for Aircraft Systems with Neural Networks

R2U2 (Realizable, Responsive, Unobtrusive Unit) is a hardware-supported tool and framework for real-time system monitoring and software health management of cyber-physical systems. During system operation, R2U2 continuously monitors properties about safety, performance, and security of the vehicle and its vital components and can perform diagnostic reasoning. Efficient observers for past-time and future-time Metric Temporal Logic, fast reasoners for Bayesian Networks, and model-based prognostics algorithms are key components of R2U2 and designed for minimal computational footprint. R2U2 has been implemented in software supporting ROS, NASA's cFS/cFE, and Simulink and as an FPGA configuration. The synergistic combination of monitors and observers in R2U2 makes it possible to design powerful models for system runtime monitoring, diagnostics, software health management, prognostics, and security monitoring. In this presentation, I will give a detailed overview of the R2U2 architecture and its features and will discuss the application of R2U2 for safety-monitoring of a neural-network based autonomous centerline tracking system (ACT) for autonomous aircraft.

Runtime Monitoring↗

NASA NTRS2005

Propellant Slosh Analysis for the Solar Dynamics Observatory

The Solar Dynamics Observatory (SDO) mission, part of the Living With a Star program, is a geosynchronous satellite with tight pointing requirements. Due to a large amount of liquid propellant, a detailed slosh analysis is required to ensure the tight pointing budget can be satisfied. Much of the high fidelity slosh analysis and simulation has been performed via computational fluid dynamics. Even though this method of simulation is very accurate, it requires significant computational effort and specialized knowledge, limiting the ability of the SDO project to access fluid dynamics simulations at will. Furthermore, it is very difficult to incorporate most of these models into simulations of the overall spacecraft and its environment. Ultimately, the effects of the propellant slosh on the attitude stability and pointing performance of the entire spacecraft are of great interest to attitude control engineers. Equivalent mechanical models, such as models that approximate the fluid slosh effects by analogy to the movements of a point-mass pendulum, are important tools in simulating propellant slosh dynamics as part of the entire attitude determination and control system. This paper describes some of the current methods used to analyze and model slosh. It focuses on equivalent mechanical models and their incorporation into control-based analysis tools such as Simulink. The SDO mission is used as the case study for this work.

Mason, Paul A. C.↗

NASA NTRSDate not supplied

Developing A Dependable Multi-Agent Rover Swarm Using cFS

The future of space exploration lies in cooperative autonomous systems. Ensuring their high integrity remains a challenge. The Robust Software Engineering group at NASA Ames Research Center has been developing the Troupe project to explore the challenges with developing and assuring high integrity of cooperative autonomous robotic systems. In particular, Troupe aims to develop a swarm of autonomous rovers capable of mapping unknown terrain and assure their high integrity using the advanced V&V tools developed in the group. In this paper, we present the evolution of the design of Troupe. We focus on the lessons learned in developing and assuring the rover swarm using core Flight System (cFS). In particular, we discuss the benefits and challenges in applying model-based development to develop the rover swarm.

space systems↗

NASA NTRSDate not supplied

Developing A Dependable Multi-Agent Rover Swarm Using cFS

space systems↗

NASA NTRS1995

Simulating the dynamic interaction of a robotic arm and the Space Shuttle remote manipulator system

Industrial robots are usually attached to a rigid base. Placing the robot on a compliant base introduces dynamic coupling between the two systems. The Vehicle Emulation System (VES) is a six DOF platform that is capable of modeling this interaction. The VES employs a force-torque sensor as the interface between robot and base. A computer simulation of the VES is presented. Each of the hardware and software components is described and Simulink is used as the programming environment. The simulation performance is compared with experimental results to validate accuracy. A second simulation which models the dynamic interaction of a robot and a flexible base acts as a comparison to the simulated motion of the VES. Results are presented that compare the simulated VES motion with the motion of the VES hardware using the same admittance model. The two computer simulations are compared to determine how well the VES is expected to emulate the desired motion. Simulation results are given for robots mounted to the end effector of the Space Shuttle Remote Manipulator System (SRMS). It is shown that for fast motions of the two robots studied, the SRMS experiences disturbances on the order of centimeters. Larger disturbances are possible if different manipulators are used.

Garrahan, Steven L.↗

NASA NTRSDate not supplied

Verification of the Generalized Aerospace Simulation in Simulink (R)

NASA uses six-degrees-of-freedom (6-DOF) simulations tools to design, test, develop Guidance Navigation and Control (GN&C) software, and certify vehicle performance prior to flight. Therefore, it is critical that the 6-DOF tools used for vehicle design and certification are validated. The focus of this work is the vali-dation of the NASA Marshall Space Flight Center 6-DOF “GeneraLized Aero-space Simulation in Simulink” (GLASS) framework tool. The GLASS tool framework is currently used to support NASA GN&C insight for the Human Landing System (HLS) project, simulating vehicle dynamics during lunar descent and as-cent. The GLASS framework utilizes the off-the-shelf Mathworks ® Simscape Multibody® toolbox to model vehicle multi-body dynamics. NASA’s Engineering and Safety Center (NESC) provides a set of 6-DOF simulation verification “check cases” that are available to any user needing to verify 6-DOF tools. The check cases contain seventeen atmospheric and twenty-six orbital test scenarios are provided to validate equations of motion, environmental models (e.g., atmosphere, gravitation, and geodesy) and tool propagators. This paper compares GLASS 6-DOF simulation results against the NESC check cases’ results via simulation-to-simulation comparisons. The comparisons demonstrate that GLASS simulation results are “in family” with the outputs of the applicable NASA NESC check cases and verifies the GLASS core framework dynamics and the correct implementation of the check case scenario models.

6-Dof↗

NASA NTRSDate not supplied

Verification of the Generalized Aerospace Simulation in Simulink

NASA uses six-degrees-of-freedom (6-DOF) simulations tools to design, test, develop Guidance Navigation and Control (GN&C) software, and certify vehicle performance prior to flight. Therefore, it is critical that the 6-DOF tools used for vehicle design and certification are validated. The focus of this work is the validation of the NASA Marshall Space Flight Center 6-DOF “GeneraLized Aerospace Simulation in Simulink” (GLASS) framework tool. The GLASS tool framework is currently used to support NASA GN&C insight for the Human Landing System (HLS) project, simulating vehicle dynamics during lunar descent and ascent. The GLASS framework utilizes the off-the-shelf Mathworks (R) Simscape (TM) Multibody (TM) toolbox to model vehicle multi-body dynamics. NASA’s Engineering and Safety Center (NESC) provides a set of 6-DOF simulation verification “check cases” that are available to any user needing to verify 6-DOF tools. The check cases contain seventeen atmospheric and twenty-six orbital test scenarios are provided to validate equations of motion, environmental models (e.g., atmosphere, gravitation, and geodesy) and tool propagators. This paper compares GLASS 6-DOF simulation results against the NESC check cases’ results via simulation-to-simulation comparisons. The comparison demonstrates that GLASS simulation results are “in family” with the outputs of the applicable NASA NESC check-cases and verify the GLASS core framework dynamics and the implementation of the check case scenario models.

6-Dof↗

NASA NTRS2014

Cantera Integration with the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS)

NASA Glenn Research Center (GRC) has recently developed a software package for modeling generic thermodynamic systems called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a library of building blocks that can be assembled to represent any thermodynamic system in the Simulink (The MathWorks, Inc.) environment. These elements, along with a Newton Raphson solver (also provided as part of the T-MATS package), enable users to create models of a wide variety of systems. The current version of T-MATS (v1.0.1) uses tabular data for providing information about a specific mixture of air, water (humidity), and hydrocarbon fuel in calculations of thermodynamic properties. The capabilities of T-MATS can be expanded by integrating it with the Cantera thermodynamic package. Cantera is an object-oriented analysis package that calculates thermodynamic solutions for any mixture defined by the user. Integration of Cantera with T-MATS extends the range of systems that may be modeled using the toolbox. In addition, the library of elements released with Cantera were developed using MATLAB native M-files, allowing for quicker prototyping of elements. This paper discusses how the new Cantera-based elements are created and provides examples for using T-MATS integrated with Cantera.

Thermodynamics↗

NASA NTRS2014

Cantera Integration with the Toolbox for Modeling and Analysis of Thermodynamic Systems (T-MATS)

NASA Glenn Research Center (GRC) has recently developed a software package for modeling generic thermodynamic systems called the Toolbox for the Modeling and Analysis of Thermodynamic Systems (T-MATS). T-MATS is a library of building blocks that can be assembled to represent any thermodynamic system in the Simulink(Registered TradeMark) (The MathWorks, Inc.) environment. These elements, along with a Newton Raphson solver (also provided as part of the T-MATS package), enable users to create models of a wide variety of systems. The current version of T-MATS (v1.0.1) uses tabular data for providing information about a specific mixture of air, water (humidity), and hydrocarbon fuel in calculations of thermodynamic properties. The capabilities of T-MATS can be expanded by integrating it with the Cantera thermodynamic package. Cantera is an object-oriented analysis package that calculates thermodynamic solutions for any mixture defined by the user. Integration of Cantera with T-MATS extends the range of systems that may be modeled using the toolbox. In addition, the library of elements released with Cantera were developed using MATLAB native M-files, allowing for quicker prototyping of elements. This paper discusses how the new Cantera-based elements are created and provides examples for using T-MATS integrated with Cantera.

Systems Analysis↗

NASA NTRS2012

A Novel Technique for Running the NASA Legacy Code LAPIN Synchronously With Simulations Developed Using Simulink

This report presents a method for running a dynamic legacy inlet simulation in concert with another dynamic simulation that uses a graphical interface. The legacy code, NASA's LArge Perturbation INlet (LAPIN) model, was coded using the FORTRAN 77 (The Portland Group, Lake Oswego, OR) programming language to run in a command shell similar to other applications that used the Microsoft Disk Operating System (MS-DOS) (Microsoft Corporation, Redmond, WA). Simulink (MathWorks, Natick, MA) is a dynamic simulation that runs on a modern graphical operating system. The product of this work has both simulations, LAPIN and Simulink, running synchronously on the same computer with periodic data exchanges. Implementing the method described in this paper avoided extensive changes to the legacy code and preserved its basic operating procedure. This paper presents a novel method that promotes inter-task data communication between the synchronously running processes.

Vrnak, Daniel R.↗

NASA NTRS2006

ADGS-2100 Adaptive Display and Guidance System Window Manager Analysis

Recent advances in modeling languages have made it feasible to formally specify and analyze the behavior of large system components. Synchronous data flow languages, such as Lustre, SCR, and RSML-e are particularly well suited to this task, and commercial versions of these tools such as SCADE and Simulink are growing in popularity among designers of safety critical systems, largely due to their ability to automatically generate code from the models. At the same time, advances in formal analysis tools have made it practical to formally verify important properties of these models to ensure that design defects are identified and corrected early in the lifecycle. This report describes how these tools have been applied to the ADGS-2100 Adaptive Display and Guidance Window Manager being developed by Rockwell Collins Inc. This work demonstrates how formal methods can be easily and cost-efficiently used to remove defects early in the design cycle.

Whalen, Mike W.↗

NASA NTRS2014

Visualizing Flutter Mechanism as Traveling Wave Through Animation of Simulation Results for the Semi-Span Super-Sonic Transport Wind-Tunnel Model

It has long been recognized that frequency and phasing of structural modes in the presence of airflow play a fundamental role in the occurrence of flutter. Animation of simulation results for the long, slender Semi-Span Super-Sonic Transport (S4T) wind-tunnel model demonstrates that, for the case of mass-ballasted nacelles, the flutter mode can be described as a traveling wave propagating downstream. Such a characterization provides certain insights, such as (1) describing the means by which energy is transferred from the airflow to the structure, (2) identifying airspeed as an upper limit for speed of wave propagation, (3) providing an interpretation for a companion mode that coalesces in frequency with the flutter mode but becomes very well damped, (4) providing an explanation for bursts of response to uniform turbulence, and (5) providing an explanation for loss of low frequency (lead) phase margin with increases in dynamic pressure (at constant Mach number) for feedback systems that use sensors located upstream from active control surfaces. Results from simulation animation, simplified modeling, and wind-tunnel testing are presented for comparison. The simulation animation was generated using double time-integration in Simulink of vertical accelerometer signals distributed over wing and fuselage, along with time histories for actuated control surfaces. Crossing points for a zero-elevation reference plane were tracked along a network of lines connecting the accelerometer locations. Accelerometer signals were used in preference to modal displacement state variables in anticipation that the technique could be used to animate motion of the actual wind-tunnel model using data acquired during testing. Double integration of wind-tunnel accelerometer signals introduced severe drift even with removal of both position and rate biases such that the technique does not currently work. Using wind-tunnel data to drive a Kalman filter based upon fitting coefficients to analytical mode shapes might provide a better means to animate the wind tunnel data.

Christhilf, David M.↗

NASA NTRS2018

Investigation of a Verification and Validation Tool with a Turbofan Aircraft Engine Application

The development of more advanced control architectures for turbofan aircraft engines can yield gains in performance and efficiency over the lifetime of an engine. However, the implementation of these increasingly complex controllers is contingent on their ability to provide safe, reliable engine operation. Therefore, having the means to verify the safety of new control algorithms is crucial. As a step towards this goal, CoCoSim, a publicly available verification tool for Simulink, is used to analyze C-MAPSS40k, a 40,000 lbf class turbo-fan engine model developed at NASA for testing new control algorithms. Due to current limitations of the verification software, several modifications are made to C-MAPSS40k to achieve compatibility with CoCoSim. Some of these modifications sacrifice fidelity to the original model. Several safety and performance requirements typical for turbofan engines are identified and constructed into a verification framework. Preliminary results using an industry standard baseline controller for these requirements are presented. While verification capabilities are demonstrated, a truly comprehensive analysis will require further development of the verification tool.

V&↗

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(Trademark) 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 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(Registered TradeMark) 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↗