Engineering topics

Henry, Joel

Publications and source records attributed to Henry, Joel.

5 records

NASA NTRS2014

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↗

NASA NTRS2011

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↗

NASA NTRS2010

Accelerating NASA GN&C Flight Software Development

When the guidance, navigation, and control (GN&C) system for the Orion crew vehicle undergoes Critical Design Review (CDR), more than 90% of the flight software will already be developed - a first for NASA on a project of this scope and complexity. This achievement is due in large part to a new development approach using Model-Based Design.

Tamblyn, Scott↗

NASA NTRS1998

Testing and Troubleshooting Automatically Generated Source Code

Tools allowing engineers to model the real-time behavior of systems that control many types of NASA systems have become widespread. These tools automatically generate source code that is compiled, linked, then downloaded into computers controlling everything from wind tunnels to space flight systems. These tools save hundreds of hours of software development time and allow engineers with thorough application area knowledge but little software development experience to generate software to control the systems they use daily. These systems are verified and validated by simulating the real-time models, and by other techniques that focus on the model or the hardware. The automatically generated source code is typically not subjected to rigorous testing using conventional software testing techniques. Given the criticality and safety issues surrounding these systems, the application of conventional and new software testing and troubleshooting techniques to the automatically generated will improve the reliability of the resulting systems.

Henry, Joel↗

NASA NTRS1994

A quantitative comparison of corrective and perfective maintenance

This paper presents a quantitative comparison of corrective and perfective software maintenance activities. The comparison utilizes basic data collected throughout the maintenance process. The data collected are extensive and allow the impact of both types of maintenance to be quantitatively evaluated and compared. Basic statistical techniques test relationships between and among process and product data. The results show interesting similarities and important differences in both process and product characteristics.

Henry, Joel↗