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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 109 records · Page 6

Model-Based GN and C Simulation and Flight Software Development for Orion Missions beyond LEO

For Orion missions beyond low Earth orbit (LEO), the Guidance, Navigation, and Control (GN&C) system is being developed using a model-based approach for simulation and flight software. Lessons learned from the development of GN&C algorithms and flight software for the Orion Exploration Flight Test One (EFT-1) vehicle have been applied to the development of further capabilities for Orion GN&C beyond EFT-1. Continuing the use of a Model-Based Development (MBD) approach with the Matlab®/Simulink® tool suite, the process for GN&C development and analysis has been largely improved. Furthermore, a model-based simulation environment in Simulink, rather than an external C-based simulation, greatly eases the process for development of flight algorithms. The benefits seen by employing lessons learned from EFT-1 are described, as well as the approach for implementing additional MBD techniques. Also detailed are the key enablers for improvements to the MBD process, including enhanced configuration management techniques for model-based software systems, automated code and artifact generation, and automated testing and integration.

Odegard, Ryan↗

Application of the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) for Dynamic Systems Analysis

Systems analysis involves steady-state simulations of combined components to evaluate the steady-state performance, weight, and cost of a system; dynamic considerations are not included until later in the design process. The Dynamic Systems Analysis task, under NASAs Fixed Wing project, is developing the capability for assessing dynamic issues at earlier stages during systems analysis. To provide this capability the Tool for Turbine Engine Closed-loop Transient Analysis (TTECTrA) has been developed to design a single flight condition controller (defined as altitude and Mach number) and, ultimately, provide an estimate of the closed-loop performance of the engine model. This tool has been integrated with the Commercial Modular Aero-Propulsion System Simulation 40,000 (CMAPSS 40k) engine model to demonstrate the additional information TTECTrA makes available for dynamic systems analysis. This dynamic data can be used to evaluate the trade-off between performance and safety, which could not be done with steady-state systems analysis data. TTECTrA has been designed to integrate with any turbine engine model that is compatible with the MATLAB Simulink (The MathWorks, Inc.) environment.

control↗

Modeling of Solid Waste Processing Options in BIO-Plex

BIO-Plex is a ground-based test bed currently under development by NASA for testing technologies and practices that may be utilized in future long-term life support missions. All aspects of such an Advanced Life Support (ALS) System must be considered to confidently construct a reliable system, which will not only allow the crew to survive in harsh environments, but allow the crew time to perform meaningful research. Effective handling of solid wastes is a critical aspect of the system, especially when recovery of resources contained in the waste is required. This is particularly important for ALS Systems configurations that include a Biomass Production Chamber. In these cases, significant amounts of inedible biomass waste may be produced, which can ultimately serve as a repository of necessary resources for sustaining life, notably carbon, water, and plant nutrients. Numerous biological and physicochemical solid waste processing options have been considered. Biological options include composting, aerobic digestion, and anaerobic digestion. Physicochemical options include pyrolysis, SCWO (supercritical water oxidation), various incineration configurations, microwave incineration, magnetically assisted gasification, and low temperature plasma reaction. Modeling of these options is a necessary step to assist in the design process. A previously developed top-level model of BIO-Plex implemented in MATLAB Simulink (r) for the use of systems analysis and design has been adopted for this analysis. Presently, this model only considered incineration for solid waste processing. Present work, reported here, includes the expansion of this model to include a wider array of solid waste processing options selected from the above options, bearing in mind potential, near term solid waste treatment systems. Furthermore, a trade study has also been performed among these solid waste processing technologies in an effort to determine the ideal technology for long-term life support missions.

Rodriguez, Luis F.↗

Test Generator for MATLAB Simulations

MATLAB Automated Test Tool, version 3.0 (MATT 3.0) is a software package that provides automated tools that reduce the time needed for extensive testing of simulation models that have been constructed in the MATLAB programming language by use of the Simulink and Real-Time Workshop programs. MATT 3.0 runs on top of the MATLAB engine application-program interface to communicate with the Simulink engine. MATT 3.0 automatically generates source code from the models, generates custom input data for testing both the models and the source code, and generates graphs and other presentations that facilitate comparison of the outputs of the models and the source code for the same input data. Context-sensitive and fully searchable help is provided in HyperText Markup Language (HTML) format.

Henry, Joel↗

Genetic Adaptive Control for PZT Actuators

A piezoelectric transducer (PZT) is capable of providing linear motion if controlled correctly and could provide a replacement for traditional heavy and large servo systems using motors. This paper focuses on a genetic model reference adaptive control technique (GMRAC) for a PZT which is moving a mirror where the goal is to keep the mirror velocity constant. Genetic Algorithms (GAs) are an integral part of the GMRAC technique acting as the search engine for an optimal PID controller. Two methods are suggested to control the actuator in this research. The first one is to change the PID parameters and the other is to add an additional reference input in the system. The simulation results of these two methods are compared. Simulated Annealing (SA) is also used to solve the problem. Simulation results of GAs and SA are compared after simulation. GAs show the best result according to the simulation results. The entire model is designed using the Mathworks' Simulink tool.

Kim, Jeongwook↗

Closed-Loop Simulation Study of the Ares I Upper Stage Thrust Vector Control Subsystem for Nominal and Failure Scenarios

As a replacement to the current Shuttle, the Ares I rocket and Orion crew module are currently under development by the National Aeronautics and Space Administration (NASA). This new launch vehicle is segmented into major elements, one of which is the Upper Stage (US). The US is further broken down into subsystems, one of which is the Thrust Vector Control (TVC) subsystem which gimbals the US rocket nozzle. Nominal and off-nominal simulations for the US TVC subsystem are needed in order to support the development of software used for control systems and diagnostics. In addition, a clear and complete understanding of the effect of off-nominal conditions on the vehicle flight dynamics is desired. To achieve these goals, a simulation of the US TVC subsystem combined with the Ares I vehicle as developed. This closed-loop dynamic model was created using Matlab s Simulink and a modified version of a vehicle simulation, MAVERIC, which is currently used in the Ares I project and was developed by the Marshall Space Flight Center (MSFC). For this report, the effects on the flight trajectory of the Ares I vehicle are investigated after failures are injected into the US TVC subsystem. The comparisons of the off-nominal conditions observed in the US TVC subsystem with those of the Ares I vehicle flight dynamics are of particular interest.

Chicatelli, Amy↗

Developing a Model Component

The Spaceport Command and Control System (SCCS) Simulation Computer Software Configuration Item (CSCI) is,. responsible for providing simulations to support test and verification of SCCS hardware and software. The Universal Coolant Transporter System (UCTS) is a Space Shuttle Orbiter support piece of the Ground Servicing Equipment (GSE). The purpose of the UCTS is to provide two support services to the Space Shuttle Orbiter immediately after landing at the Shuttle Landing Facility. The Simulation uses GSE Models to stand in for the actual systems to support testing of SCCS systems s:luring their development. As an intern at KSC, my assignment was to develop a model component for the UCTS. I was given a fluid component (drier) to model in Matlab. The drier was a Catch All replaceable core type filter-drier. The filter-drier provides maximum protection for the thermostatic expansion valve and solenoid valve from dirt that may be in the system. The filter-drier also protects the valves from freezing up. I researched fluid dynamics to understand the function of my component. I completed training for UNIX and Simulink to help aid in my assignment. The filter-drier was modeled by determining affects it has on the pressure, velocity and temperature of the system. I used Bernoulli's Equation to calculate the pressure and velocity differential through the dryer. I created my model filter-drier in Simulink and wrote the test script to test the component. I completed component testing and captured test data. The finalized model was sent for peer review for any improvements.

Fields, Christina M.↗

LADEE Multi-Domain Simulation

The Lunar Atmosphere Dust Environment Explorer (LADEE) was a small explorer class spacecraft that was launched on Sept 7, 2013 and that was de-orbited and successfully impacted the Moons surface on April 17, 2014 after completing all of the mission objectives. The low-cost rapidly prototyped hardware design used for the spacecraft was extend to the development of the software base. To achieve this goal, a Model Based Design approach was utilized to develop the onboard flight software, and out of this development a model based multipurpose simulator was created of the LADEE spacecraft and its mission environment. This simulator extended the traditional function of propagating the vehicle's kinematic and rotational states and included the electrical and thermal states propagation. Traditionally, these domains are handled by domain specific high fidelity simulations that use the states histories from other domains as input. By reducing the fidelity and abstracting the relevant features being monitored and controlled by the flight software, it was possible to model the coupling across these domains resulting in more accurate overall system behavior. A faster than real-time workstation (WSIM) version of the LADEE simulator was used to develop and test the software control algorithms in the Simulink environment. To maximize the performance of the simulation, modeling knobs were introduced to reduce the resolution of the some of the domains models when the effects of that domain were not significant for the scope of that simulation. The automatic code generation feature in Simulink was used to port the simulation to several real-time environments to support Processor-in-the-Loop (PIL) and Hardware-in-the-Loop (HIL) testing, verification and validation. The real-time environment required that the design of each of the domain models be deterministic as possible in the time required to perform all of the calculations to update its states. The simulation interface was designed to be compatible with the command interface employed by the LADEE mission operation team. The WSIM, PIL, and HIL simulators thus used a common interface and thus were used for flight software testing, for mission operations personnel training (nominal and off-nominal operations) prior to the mission and to perform command sequence verification during the mission. This presentation will look at the modeling strategies used to create a common interface to the simulator and to model and couple multiple domains within the simulation, the results of those strategies, and the lessons learned.

Multi-Domain↗

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↗

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↗

Dynamic Modeling of Off-Nominal Operation in Advanced Life Support Systems

System failures, off-nominal operation, or unexpected interruptions in processing capability can cause unanticipated instabilities in Advanced Life Support (ALS) systems, even long after they are repaired. Much current modeling assumes ALS systems are static and linear, but ALS systems are actually dynamic and nonlinear, especially when failures and off nominal operation are considered. Modeling and simulation provide a way to study the stability and time behavior of nonlinear dynamic ALS systems under changed system configurations or operational scenarios. The dynamic behavior of a nonlinear system can be fully explored only by computer simulation over the full range of inputs and initial conditions. Previous simulations of BIO-Plex in SIMULINK, a toolbox of Matlab, were extended to model the off-nominal operation and long-term dynamics of partially closed physical/chemical and bioregenerative life support systems. System nonlinearity has many interesting potential consequences. Different equilibrium points may be reached for different initial conditions. The system stability can depend on the exact system inputs and initial conditions. The system may oscillate or even in rare cases behave chaotically. Temporary internal hardware failures or external perturbations in ALS systems can lead to dynamic instability and total ALS system failure. Appropriate control techniques can restore reliable operation and minimize the effects of dynamic instabilities due to anomalies or perturbations in a life support system.

Jones, Harry↗

Certifying Auto-Generated Flight Code

Model-based design and automated code generation are being used increasingly at NASA. Many NASA projects now use MathWorks Simulink and Real-Time Workshop for at least some of their modeling and code development. However, there are substantial obstacles to more widespread adoption of code generators in safety-critical domains. Since code generators are typically not qualified, there is no guarantee that their output is correct, and consequently the generated code still needs to be fully tested and certified. Moreover, the regeneration of code can require complete recertification, which offsets many of the advantages of using a generator. Indeed, manual review of autocode can be more challenging than for hand-written code. Since the direct V&V of code generators is too laborious and complicated due to their complex (and often proprietary) nature, we have developed a generator plug-in to support the certification of the auto-generated code. Specifically, the AutoCert tool supports certification by formally verifying that the generated code is free of different safety violations, by constructing an independently verifiable certificate, and by explaining its analysis in a textual form suitable for code reviews. The generated documentation also contains substantial tracing information, allowing users to trace between model, code, documentation, and V&V artifacts. This enables missions to obtain assurance about the safety and reliability of the code without excessive manual V&V effort and, as a consequence, eases the acceptance of code generators in safety-critical contexts. The generation of explicit certificates and textual reports is particularly well-suited to supporting independent V&V. The primary contribution of this approach is the combination of human-friendly documentation with formal analysis. The key technical idea is to exploit the idiomatic nature of auto-generated code in order to automatically infer logical annotations. The annotation inference algorithm itself is generic, and parametrized with respect to a library of coding patterns that depend on the safety policies and the code generator. The patterns characterize the notions of definitions and uses that are specific to the given safety property. For example, for initialization safety, definitions correspond to variable initializations while uses are statements which read a variable, whereas for array bounds safety, definitions are the array declarations, while uses are statements which access an array variable. The inferred annotations are thus highly dependent on the actual program and the properties being proven. The annotations, themselves, need not be trusted, but are crucial to obtain the automatic formal verification of the safety properties without requiring access to the internals of the code generator. The approach has been applied to both in-house and commercial code generators, but is independent of the particular generator used. It is currently being adapted to flight code generated using MathWorks Real-Time Workshop, an automatic code generator that translates from Simulink/Stateflow models into embedded C code.

Denney, Ewen↗

Proceedings of the Second NASA Formal Methods Symposium

This publication contains the proceedings of the Second NASA Formal Methods Symposium sponsored by the National Aeronautics and Space Administration and held in Washington D.C. April 13-15, 2010. Topics covered include: Decision Engines for Software Analysis using Satisfiability Modulo Theories Solvers; Verification and Validation of Flight-Critical Systems; Formal Methods at Intel -- An Overview; Automatic Review of Abstract State Machines by Meta Property Verification; Hardware-independent Proofs of Numerical Programs; Slice-based Formal Specification Measures -- Mapping Coupling and Cohesion Measures to Formal Z; How Formal Methods Impels Discovery: A Short History of an Air Traffic Management Project; A Machine-Checked Proof of A State-Space Construction Algorithm; Automated Assume-Guarantee Reasoning for Omega-Regular Systems and Specifications; Modeling Regular Replacement for String Constraint Solving; Using Integer Clocks to Verify the Timing-Sync Sensor Network Protocol; Can Regulatory Bodies Expect Efficient Help from Formal Methods?; Synthesis of Greedy Algorithms Using Dominance Relations; A New Method for Incremental Testing of Finite State Machines; Verification of Faulty Message Passing Systems with Continuous State Space in PVS; Phase Two Feasibility Study for Software Safety Requirements Analysis Using Model Checking; A Prototype Embedding of Bluespec System Verilog in the PVS Theorem Prover; SimCheck: An Expressive Type System for Simulink; Coverage Metrics for Requirements-Based Testing: Evaluation of Effectiveness; Software Model Checking of ARINC-653 Flight Code with MCP; Evaluation of a Guideline by Formal Modelling of Cruise Control System in Event-B; Formal Verification of Large Software Systems; Symbolic Computation of Strongly Connected Components Using Saturation; Towards the Formal Verification of a Distributed Real-Time Automotive System; Slicing AADL Specifications for Model Checking; Model Checking with Edge-valued Decision Diagrams; and Data-flow based Model Analysis.

Munoz, Cesar↗

Simulink-Based Simulation Architecture for Evaluating Controls for Aerospace Vehicles (SAREC-ASV)

The Simulation Architecture for Evaluating Controls for Aerospace Vehicles (SAREC-ASV) is a Simulink-based approach to providing an engineering quality desktop simulation capability for finding trim solutions, extracting linear models for vehicle analysis and control law development, and generating open-loop and closed-loop time history responses for control system evaluation. It represents a useful level of maturity rather than a finished product. The layout is hierarchical and supports concurrent component development and validation, with support from the Concurrent Versions System (CVS) software management tool. Real Time Workshop (RTW) is used to generate pre-compiled code for substantial component modules, and templates permit switching seamlessly between original Simulink and code compiled for various platforms. Two previous limitations are addressed. Turn around time for incorporating tabular model components was improved through auto-generation of required Simulink diagrams based on data received in XML format. The layout was modified to exploit a Simulink "compile once, evaluate multiple times" capability for zero elapsed time for use in trimming and linearizing. Trim is achieved through a Graphical User Interface (GUI) with a narrow, script definable interface to the vehicle model which facilitates incorporating new models.

Christhilf, David m.↗

A Multibody Slosh Analysis for the Lunar Reconnaissance Orbiter

The Lunar Reconnaissance Orbiter (LRO) undergoes a series of thruster maneuvers to attain lunar orbit. The first of the series of lunar orbit insertion (LOI) maneuvers is crucial to the success of the mission. Therefore, it is important to characterize the disturbances acting on the spacecraft during this phase of the mission. This paper focuses on the internal disturbance force caused by fuel slosh and its impact on attitude control. During the first LOI maneuver (LOI-1), approximately 50% of the total fuel mass is used or roughly 25% of the spacecraft s wet mass, during the 38-minute burn. The forces imparted on the spacecraft from the fuel are dependent on the fill level of the two fuel tanks. During LOI-1, the fill level in both tanks varies greatly and thus so does the disturbance level caused by the fuel. It is therefore necessary to account for the time-varying mass properties of the spacecraft and the effects of the varying fuel levels during the entire 38-minute maneuver. Two simulations are developed in Mathworks s Simulink to analyze the fuel slosh effect. The first model, a baseline model, is a rigid body dynamics model where the fuel slosh is not modeled. The second is a multibody model, developed using a multibody dynamics toolbox, where each of the two fuel tanks and the remaining spacecraft body are treated as separate rigid bodies. The simulations are executed in a piece-wise fashion to account for the time-varying mass properties, and to accommodate the multibody toolbox. Disturbances caused by fuel slosh during both lunar and mission orbit insertions will be analyzed through simulation of different dynamics models. Results of the analysis will show the effects of the slosh disturbance on the spacecraft s attitude.

Shah, Neerav↗

Dynamical Modeling and Control Simulation of a Large Flexible Launch Vehicle

This paper presents dynamical models of a large flexible launch vehicle. A complete set of coupled dynamical models of propulsion, aerodynamics, guidance and control, structural dynamics, fuel sloshing, and thrust vector control dynamics are described. Such dynamical models are used to validate NASA s SAVANT Simulink-based program which is being used for the preliminary flight control systems analysis and design of NASA s Ares-1 Crew Launch Vehicle. SAVANT simulation results for validating the performance and stability of an ascent phase autopilot system of Ares-1 are also presented.

Du, Wei↗

An Introduction to Transient Engine Applications Using the Numerical Propulsion System Simulation (NPSS) and MATLAB

This document outlines methodologies designed to improve the interface between the Numerical Propulsion System Simulation framework and various control and dynamic analyses developed in the Matlab and Simulink environment. Although NPSS is most commonly used for steady-state modeling, this paper is intended to supplement the relatively sparse documentation on it's transient analysis functionality. Matlab has become an extremely popular engineering environment, and better methodologies are necessary to develop tools that leverage the benefits of these disparate frameworks. Transient analysis is not a new feature of the Numerical Propulsion System Simulation (NPSS), but transient considerations are becoming more pertinent as multidisciplinary trade-offs begin to play a larger role in advanced engine designs. This paper serves to supplement the relatively sparse documentation on transient modeling and cover the budding convergence between NPSS and Matlab based modeling toolsets. The following sections explore various design patterns to rapidly develop transient models. Each approach starts with a base model built with NPSS, and assumes the reader already has a basic understanding of how to construct a steady-state model. The second half of the paper focuses on further enhancements required to subsequently interface NPSS with Matlab codes. The first method being the simplest and most straightforward but performance constrained, and the last being the most abstract. These methods aren't mutually exclusive and the specific implementation details could vary greatly based on the designer's discretion. Basic recommendations are provided to organize model logic in a format most easily amenable to integration with existing Matlab control toolsets.

Matlab↗