Technical note | Vector and Matrix Variable Definitions in DAVE-ML

Abstract

The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) is a syntactical language for exchanging flight vehicle dynamic model data. It has been developed in conjunction with the ANSI/AIAA S-119-2011 Flight Dynamics Model Exchange Standard prepared by the American Institute of Astronautics and Aeronautics (AIAA) Modeling and Simulation Technical Committee (MSTC). The purpose of DAVE-ML is to provide a framework to encode entire flight vehicle simulation data packages for exchange between simulation applications and the long-term archiving of model data. This report documents an extension to DAVE-ML for managing data as vectors or n-dimensional matrices. The attributes and dependencies of the additional DAVE-ML elements are discussed, and examples of encapsulating data as vectors and matrices are provided.

Executive Summary

The Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) is a syntactical language for exchanging flight vehicle dynamic model data. It has been developed in conjunction with the ANSI/AIAA S-119-2011 Flight Dynamics Model Exchange Standard, prepared by the American Institute of Astronautics and Aeronautics (AIAA) Modeling and Simulation Technical Committee (MSTC). The intended purpose of DAVE-ML is to provide a framework for encoding entire flight vehicle simulation data packages for exchange between simulation applications and the long-term archiving of model data. Such data packages are commonly used in research, engineering development, and flight training simulations. DAVE-ML is designed to provide a programming-language-independent representation of aerospace vehicle characteristics, such as the aerodynamics, mass, propulsion, navigation and control properties.

Version 2.0.1 of DAVE-ML supports the storage of static aerospace vehicle characteristic data in human-readable text form, together with directives for automating the conversion of data into a form suitable for use in vehicle simulations. It provides a capability to include statistical properties for embedded data, such as confidence bounds and uncertainty ranges; along with references to reports, contact information and data provenance. However, additional functionality is required to support the exchange of entire flight vehicle simulation models. This includes supporting vector and matrix data, abstracting sub-system models, detailing dynamics system models (both discrete and continuous), and defining a dynamic data format (such as time-history data) for validating dynamics system models and the overall simulation package.

This report documents a DAVE-ML consistent syntax for managing data as vectors and n-dimensional matrices, including syntax for computing vectors and matrices using equations, and examples of encoding data using the syntax. The syntax offers an approach to improve the clarity of encoding aerospace vehicle dynamic model data, and thereby enhance the ability of DAVE-ML to encode entire flight vehicle dynamic simulation models and their validation data. This, in turn, will simplify the exchange of vehicle model data between simulation applications.