April 2011 

NASA/TM-2011-217085/Volume I 

NESC-RP-09-00598 

 

Flight Simulation Model Exchange 

Daniel G. Murri/NESC 

Langley Research Center, Hampton, Virginia 

E. Bruce Jackson 

Langley Research Center, Hampton, Virginia 
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April 2011 

NASA/TM-2011-217085/Volume I 

NESC-RP-09-00598 

 

Flight Simulation Model Exchange 

Daniel G. Murri/NESC 

Langley Research Center, Hampton, Virginia 

E. Bruce Jackson 

Langley Research Center, Hampton, Virginia 
Available from: 

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7115 Standard Drive 

Hanover, MD 21076-1320 

443-757-5802 

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constitute an official endorsement, either expressed or implied, of such products or manufacturers by the 

National Aeronautics and Space Administration. 
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Flight Simulation Model Exchange

Volume I

NRB Review Date: February 17, 2011
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Report Approval and Revision History 

Approval and Document Revision History 

NOTE: This document was approved at the February 17, 2011, NRB. This document was 

submitted to the NESC Director on March 7, 2011

, for configuration control.

Approved

Version:

Original Signature on File 3/8/11

1.0 NESC Director Date

Version Description of Revision Office of Primary 

Responsibility Effective Date

1.0 Initial Version Mr. Daniel Murri, 

NASA Technical 

Fellow for Flight 

Mechanics

02/17/11
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Table of Contents

Volume I: Technical Assessment Report

1.0 Notification and Authorization........................................................................................ 5

2.0 Signature Page................................................................................................................... 6

3.0 Team List........................................................................................................................... 7

3.1 Acknowledgements............................................................................................................. 7

4.0 Executive Summary .......................................................................................................... 8

5.0 Assessment Plan .............................................................................................................. 10

6.0 Problem Description, Proposed Solution, and Known Risks...................................... 11

6.1 Problem Description ......................................................................................................... 11

6.2 Proposed Solution ............................................................................................................. 11

6.2.1 History..................................................................................................................... 11

6.2.2 Overview of Proposed Solution.............................................................................. 11

6.3 Known Risks and Mitigations........................................................................................... 14

6.3.1 Loss of Cross-checks from Independently Coded Models..................................... 14

6.3.2 Reliance on a Standard Format Developed and Maintained by a Third Party........ 14

6.3.3 Insufficient Flexibility for Modeling Special Use Cases........................................ 14

6.3.4 Incompatibility with Standards Developed by Other Agency Partners.................. 15

6.3.5 Lack of Export Capability for Existing Models...................................................... 15

7.0 Assessment Results.......................................................................................................... 15

7.1 Ames Research Center...................................................................................................... 15

7.2 Dryden Flight Research Center......................................................................................... 16

7.3 Glenn Research Center ..................................................................................................... 17

7.4 Johnson Space Center ....................................................................................................... 17

7.4.1 Software Integration................................................................................................ 17

7.4.2 Execution Time Study of DAVE-ML Interpreters ................................................. 18

7.4.3 Non-aerodynamics Models Implemented in DAVE-ML ....................................... 18

7.4.4 DAVE-ML Specification Comments/Suggestions................................................. 19

7.4.5 Conclusions and Suggestions for Future Work ...................................................... 19

7.5 Marshall Space Flight Center............................................................................................ 19

7.6 Summary of Results.......................................................................................................... 20
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8.0 Findings, Observations, and NESC Recommendations .............................................. 21

8.1 Findings............................................................................................................................. 21

8.2 Observations ..................................................................................................................... 21

8.3 NESC Recommendations.................................................................................................. 22

9.0 Definition of Terms......................................................................................................... 22

10.0 Acronyms List ................................................................................................................. 23

11.0 References........................................................................................................................ 24

Volume II: Appendices 

Appendix A. NESC Flight Simulation Model Exchange Assessment Report from Johnson 

Space Center

Appendix B. American National Standard: Flight Dynamics Model Exchange Standard (draft 

BSR/AIAA S-119-201x)

Appendix C. XML Document Type Definition file for S-119 markup: DAVEfunc.dtd

Appendix D. Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) 

Reference Manual
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Volume I: Technical Assessment Report

1.0 Notification and Authorization 

Mr. Dan Murri, NASA Technical Fellow for Flight Mechanics at Langley Research Center 

(LaRC), requested the NASA Engineering and Safety Center (NESC) to test the implementation 

of a draft American Institute of Aeronautics and Astronautics (AIAA) flight-dynamics 

simulation model exchange Standard by developing and exercising import tools at several NASA 

Centers with two representative high-fidelity aerospace vehicle aerodynamics models. This 

implementation will serve as a pathfinder for more rapid vehicle model exchanges in the future, 

increasing productivity and cross-Agency collaboration.

An NESC out-of-board activity was approved by NESC Director Ralph Roe on November 4, 

2009. Mr. Murri was selected to lead this assessment. The assessment plan was approved by the 

NESC Review Board (NRB) on December 10, 2009. 

The key stakeholders for this assessment are the NASA Office of Chief Engineer and the NASA 

Technical Fellows for Guidance, Navigation, and Control (GN&C); Aerosciences; and Flight 

Mechanics.
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2.0 Signature Page

Submitted by:

//Team Signature Page on File//

Mr. Daniel G. Murri Date Mr. E. Bruce Jackson Date

Significant Contributors: 

Mr. Edwin Z. Crues Date Mr. Robert D. Falck Date

Mr. David A. Hasan Date Ms. Melissa A. Hill Date

Mr. Matthew V. Jessick Date Mr. Thomas G. McCarthy Date

Mr. William L. Othon Date Mr. John M. Penn Date

Mr. Nghia D. Vuong Date Mr. Curtis J. Zimmerman Date

Signatories declare the findings and observations compiled in the report are factually based from 

data extracted from Program/Project documents, contractor reports, and open literature, and/or 

generated from independently conducted tests, analysis, and inspections.
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3.0 Team List

Name Discipline Organization

Core Team

Dan Murri NESC Assessment Lead LaRC

Bruce Jackson NESC Team Lead LaRC

Neil Dennehy Assessment Team Co-Lead GSFC

Zack Crues Simulation Representative JSC

Rob Falck Simulation Representative GRC

David Hasan Simulation Representative JSC

Missy Hill Simulation Representative LaRC

Matt Jessick Simulation Representative JSC

Greg McCarthy Simulation Representative DFRC

Bill Othon GN&C Representative JSC

John Penn Simulation Representative JSC

Nghia Vuong Simulation Representative ARC

Curt Zimmerman Simulation Representative MSFC

Laura Leybold MTSO Program Analyst LaRC

Administrative Support

Diane Sarrazin Project Coordinator LaRC/ATK

Linda Burgess Planning and Control Analyst LaRC/ATK

Carolyn Snare Technical Writer LaRC/ATK

3.1 Acknowledgements 

The assessment team would like to express appreciation to Mr. Bruce Hildreth of J. F. Taylor, 

Inc. and Mr. Geoffery Brian of the Australian Department of Defence for their support and 

initiative in bringing this technology to simulation model exchange. They would also like to 

thank Mr. Mike Red of the Simulation and Graphics Division at Johnson Space Center (JSC) for 

supporting the effort and hosting the final meeting; Ms. Linda Burgess, Ms. Laura Leybold, 

Ms. Diane Sarrazin, and Ms. Carolyn Snare for their unflagging efforts; the NESC for supporting 

this worthwhile assessment; and Mr. Neil Dennehy and Dr. David Schuster of the NESC for their 

support.
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4.0 Executive Summary

The American Institute of Aeronautics and Astronautics (AIAA) has, through its Modeling and 

Simulation Technical Committee (MSTC), developed a draft Board of Standards Review (BSR) / 

American National Standards Institute (ANSI) Standard that establishes a convention for

variable names, axis systems, units-of-measure and sign convention abbreviations, and an 

Extensible Markup Language (XML) grammar. AIAA is using this Standard to encode most of 

the details for a high-fidelity flight vehicle dynamics model. The draft Standard, Flight 

Dynamics Model Exchange Standard, BSR/ANSI-S-119-201x, hereafter ―S-119,‖ has recently 

completed a second round of public comments. Several NASA engineers from the flight

mechanics; aerosciences; and guidance, navigation, and control (GN&C) disciplines collectively 

contributed to the development of S-119.

The NASA Engineering and Safety Center (NESC) Review Board (NRB) sponsored an 

assessment of S-119 that was conducted by simulation and GN&C engineers from several NASA 

Centers, including Ames Research Center (ARC), Dryden Flight Research Center (DFRC), 

Glenn Research Center (GRC), Johnson Space Center (JSC), Langley Research Center (LaRC), 

and Marshall Space Flight Center (MSFC). The assessment team reviewed the conventions and 

formats spelled out in the draft Standard and the actual implementation of two example 

aerodynamic models (a subsonic F-16 and the HL-20 lifting body) encoded in the XML 

grammar. During the implementation, the team kept records of lessons learned and provided

feedback to the AIAA MSTC representative. 

The team judged the implementation successful if the two example models, which contained 

internal static check cases, generated outputs to specified inputs that matched the check cases 

within the specified tolerance. (This self-verification capability is a benefit of S-119.) Each site 

reported success in verifying the examples in their respective simulation frameworks. A further, 

optional, exercise was to implement a complete HL-20 simulation with guidance and control 

law, mass-and-inertia, and landing-gear models to demonstrate the imported model in real-time. 

This exercise was successful at each Center that attempted to fly a complete HL-20 simulation.

An assessment kick-off was held at LaRC on January 13, 2010, with several introductory 

presentations and discussions on expectations and existing tools. At the end of a 9-month 

assessment period, a second face-to-face meeting was held at JSC on October 21, 2010, and 

included representatives from each Center (one Center’s representative attended via 

teleconference). 

Based on the relative ease of importing the example models by each participating Center, the 

assessment team recommended the adoption of Flight Dynamic Model Exchange Standard, 

BSR/AIAA-S-119-201x, with some suggested changes, as a recommended practice for both 

developing new simulation aerodynamic models and for exchange of such models, when such 

models involve significant numbers of function tables. 
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In addition to providing a practical test of the S-119 format, the assessment resulted in having the 

ability to share a single flight simulation model format across most NASA Centers, feedback to 

the AIAA, and identification and correction of several errors in existing S-119 tools.
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5.0 Assessment Plan

The AIAA MSTC worked for several years to develop a programming-language-neutral method 

of encoding a mathematical model, model function data, and verification data using XML, a textfile, data-encoding method adopted as a standard web data-exchange method. Using XML, a 

specialized grammar was developed to encode aero models in a human- and machine-readable 

format that captures most of the elements of a high-fidelity engineering math model (including 

documentation, modification history, data references, uncertainty, and verification check cases). 

S-119 includes standard variable names, sign conventions, axis systems, and units-of-measure 

encoding that achieve an unambiguous representation of the data, suitable for automated import 

to or export from an existing simulation framework.

This assessment focused on the shared implementation of two existing aerospacecraft models, 

specifically the F-16 subsonic aero and the HL-20 lifting body aero databases. With an 

accompanying fixed inertia model and Simulink®control law, an autolanding-capable, flyable 

HL-20 real-time simulation was realized within the duration of this assessment at three 

participating Centers. 

Most of the effort by each participating Center involved developing import scripts or linking 

existing application programming interface (API) tools to allow their simulation framework to 

accept S-119 models. Some additional software development was necessary to implement the 

existing autocoded HL-20 control laws, landing gear, and inertia models in the simulation, if a 

complete simulation was desired, as these elements were not available in S-119 format.

This assessment allowed team members from ARC, DFRC, GRC, JSC, and MSFC to implement 

and evaluate S-119 by adopting existing or developing and exercising new import tools and

importing existing aerodynamic models into each Center’s real-time simulation or analysis tool 

framework. One of these import tools was developed and exercised at LaRC prior to this 

assessment and took approximately 6 staff-months of effort [ref. 1]. LaRC’s results and 

experiences were used as a starting point for the other Centers, and the LaRC team members had 

the opportunity to update their tool, assist the other Centers with their implementations, and 

participate in the development of findings, observations, and NESC recommendations. 

For all Centers, once an import tool existed, importing new models became much easier. If there 

were no changes to the model inputs or outputs, an updated aero model of arbitrary size and 

complexity could be imported in a matter of minutes. A byproduct of adopting S-119 was the 

automatic verification of the newly realized model via included check case data.

The adoption of a flight simulation model exchange Standard benefits existing cross-Center 

Programs, such as Exploration and Fundamental Aeronautics, almost immediately. Lessons 

learned are available for the potential development of a NASA Standard in this area and to help 

the AIAA MSTC publish the new S-119. (As of February 2011, S-119 had successfully 

completed two rounds of public comments and was being referred to ANSI for publication.)
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6.0 Problem Description, Proposed Solution, and Known Risks

6.1 Problem Description

This assessment targeted one of the factors that paces the research and development of new 

aerospacecraft: the development and distribution of a high-fidelity flight simulation dynamics 

model. At the time of this report, each NASA Center uses mostly incompatible simulation 

frameworks for both real-time and analytical simulation studies. The incompatibility arises from 

the separate growth of simulation capability within each Center, dating back to the 1970s or 

earlier [ref. 2]. Adopting a common framework at this stage, however, would be 

counterproductive for several reasons, including significant retooling and retraining costs, loss of 

unique capabilities that exist at each Center, and potential loss of valuable cross-checking of 

results. Nevertheless, such incompatibility has served as a pacing item for collaborative research 

(e.g., the 1990s High Speed Civil Transport (HSCT) [ref. 3]) and accident board/return-to-flight 

activities (e.g., the X-43A first mission booster failure). Due to the complexity of developing, 

sharing, and verifying the HSCT Industry Reference H aero database, the Program took 

approximately 12 months to prepare for a new release of the simulation database. The problem 

extends beyond NASA as well: a 2002 paper showed that the United States (US) Department of 

Defense (DoD) loses approximately $6 million in opportunity cost and negative training per 

year, due to incompatible simulation formats, for one aircraft type [ref. 4].

6.2 Proposed Solution

6.2.1 History

For many years, various organizations have tried to resolve this incompatibility by proposing 

standards on simulation software and hardware implementations. In 2002, members of the 

AIAA MSTC, including a co-author of this report, proposed a standards-based approach that 

focused on standardizing the exchange of simulation models, not their actual hosting and 

execution [ref. 4]. As the idea caught on, tools began to appear that assisted in the 

implementation and use of standard models. Both Australia’s Defence Science Technology 

Organisation (DSTO) and LaRC’s simulation branches developed code libraries or APIs that 

made using these S-119 models much easier. Other organizations began to develop tools and 

scripts that would convert S-119 models into analysis source formats (such as Simulink®).

6.2.2 Overview of Proposed Solution

The proposed S-119 Standard for dynamic model exchange is composed of three elements: a 

written document that gives standard identifiers (text-based names or abbreviations) for axis 

systems, units of measure, sign convention, and variable names; an XML markup specification

for encoding vehicle model data, equations, provenance, and check-cases; and a reference 

manual for the XML markup grammar.
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The written document, known as BSR/ANSI-S-119-201x, Flight Dynamic Model Exchange 

Standard, contains conventions for unique identifiers (text-based names) for axis systems, units

of measure, sign convention, and variable name structure and core names. It is found in 

Appendix B in Volume II of this report. It required use of a NASA-developed XML markup 

specification.

The XML markup specification (more specifically, a document type definition (DTD)) is known 

as the Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML), and is in 

Appendix C in Volume II of this report. A reference manual for the DAVE-ML DTD is given in 

Appendix D. These three documents form the basis for encoding flight dynamic models in XML 

and are herein referred to as ―S-119.‖

The identifiers defined in the written Standard are used with the DAVE-ML DTD to create 

stand-alone XML files that encode a large portion of a flight vehicle’s dynamics. Separate XML 

files would be required for each subsystem thus encoded (e.g., aerodynamics, inertia, landing 

gear, propulsion, reaction control, etc.).

Each XML file contains a fixed sequence of elements, beginning with a file header that describes 

the encoded model and (typically) gives information about the origins of the model 

(i.e., provenance). Following the header is a definition of all the variables used within the model 

(including calculations to generate intermediate and output variables) followed by definitions of 

any non-linear function tables used by the model. The last part of the XML file contains any 

check cases for verification of proper implementation of the model, with allowable tolerances.

An excerpt of an aerodynamic DAVE-ML model (see Figure 6.2-1 below) shows how variable 

definitions, breakpoint and function table definitions, and functions combine to map input 

variables like Mach number and control surface deflections to an aerodynamic coefficient output 

variable. Not shown are the calculations and check-case sets that such a model would employ 

for complete definition and verification of the model implementation.
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Figure 6.2-1. Excerpt from an Example DAVE-ML Model
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6.3 Known Risks and Mitigations

Potential risks associated with adopting a standard model exchange format, and their mitigations, 

are briefly discussed below.

6.3.1 Loss of Cross-checks from Independently Coded Models

Risk: A benefit of the existing state-of-the-art (where each model has to be rehosted, usually by 

hand re-coding the subsystem models) is that tracking down the inevitable differences in model 

behavior generally leads to discovery and resolution of programming errors in the original 

model. The risk of adopting a common model source format is that this ―implicit‖ validation and 

verification would be lost.

Mitigation: It is true that independently developed simulations serve as informal cross-checks to 

the primary simulation. Each program should decide if an independent simulation is warranted.

However, often the differences between simulation trajectories arise from different atmospheric 

models and/or integration of the equations of motion; these are not usually exchanged and thus 

sharing common vehicle dynamic models would have no effect, good or bad, on these 

differences.

6.3.2 Reliance on a Standard Format Developed and Maintained by a Third Party

Risk: Another risk of adoption of a third-party standard (in this case, the proposed S-119 AIAA 

Standard, if adopted) would be the loss of control over changes to that Standard.

Mitigation: In mitigation of this risk, the author and current maintainer of the DAVE-ML format

(technically an XML DTD) is a NASA employee. The idea of a formal consortium to oversee 

changes to the DTD should be pursued to provide longevity and consensus to mitigate this risk.

6.3.3 Insufficient Flexibility for Modeling Special Use Cases

Risk: Being locked into one model format that may include unforeseen limitations, which could 

prevent efficient or reasonable representation of the physical behavior of the modeled system.

Mitigation: S-119 is extensible and can be adapted to handle common-use cases; it is anticipated 

that such changes should be backwards-compatible for the growing library of existing models. It 

is possible that the format may not lend itself to future special modeling techniques which are not 

presently foreseen. However, given the diversity of models that have been successfully encoded 

in S-119 (e.g., F-16 subsonic aero, HL-20 full envelope aero, blended-wing-body multi-control 

surface aero, Constellation Program models including the Ares I aerodynamics, the Orion 

Launch Abort Vehicle common aerodynamics, and various aero and inertia models for military 

aircraft ―libraries‖), the S-119 format is believed sufficient to handle typical flight dynamics 

model applications.
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6.3.4 Incompatibility with Standards Developed by Other Agency Partners

Risk: If NASA were to adopt one standard while another Agency partner adopted a different 

standard, the competing standards might obviate any benefit of adoption, placing mission success 

at risk.

Mitigation: The S-119 document is proposed to become an ANSI and eventually an International 

Organization for Standardization (ISO) Standard, which may minimize the potential emergence 

of another standard. As part of this assessment, several emerging modeling Standards were 

reviewed. One in particular, Modelica [ref. 5], is an emerging European academic Standard that 

has some merit. However, at the time of this report, it does not have sufficient treatment of 

multidimensional interpolated function tables, which are the core of most high-fidelity aerospace 

vehicle dynamic models, to be useful.

6.3.5 Lack of Export Capability for Existing Models

Risk: While the assessment focused on importing and reusing existing models written in the 

standard format, only two Centers have explored exporting existing model data into the format. 

Such exports will require extensive manual intervention to complete the model. 

Mitigation: This risk may be mitigated by adoption of the standard format by aerodynamicists 

who define the original model, if tools can be developed to assist them. The format lends itself 

to archival status (simple text-based file with sufficient metadata to interpret as a stand-alone 

document). 

7.0 Assessment Results

A summary of the efforts of ARC, DFRC, GRC, JSC, and MSFC is given below. A report from 

the team at JSC on their extensive investigation of S-119 may be found in Appendix A. As 

mentioned previously, LaRC developed and exercised their import tool prior to this assessment. 

LaRC’s results and experiences were used as a starting point for other Centers, and the LaRC 

team members had the opportunity to update their tool, assist the other Centers with their 

implementation, and participate in the development of findings, observations, and NESC 

recommendations.

7.1 Ames Research Center

ARC’s Simulation Laboratories (Simlabs) participated in an early (2004) exercise at accepting 

models encoded in what became the S-119 format [ref. 6]. The extent of participation in this 

assessment was to revisit the Perl scripts developed for that 2004 effort and to revise them as 

necessary to accommodate changes that had transpired in the underlying DAVE-ML format 

since that initial exercise.
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The approach was to convert the S-119 models into the equivalent Formula Translator 

(FORTRAN) algorithm and the data tables into the equivalent, ARC-unique, function table 

processor (FTP) input files for subsequent compilation. 

This assessment was pursued on a part-time basis as time allowed; as a result, approximately 

10 months were required to successfully update the import scripts. However, the test cases for 

both the HL-20 lifting body aero model and other simple models were matched within the 

specified tolerance. Importing a new S-119 model at ARC’s SimLabs with these scripts should 

take no more than a few minutes.

7.2 Dryden Flight Research Center

At DFRC, an HL-20 simulation was constructed from the example S-119 model using the 

following components:

 Dryden Core Software v 4.0—March 2010 

 Janus API version 1.10, Copyright © 2006, DSTO, Commonwealth of Australia [ref. 7]

 Xerces-c library 3.0.1—sparc-solaris-cc-5.7, Copyright © 1999, IBM Corporation [ref. 8]

 Qhull library 2009.1, Copyright © 1993–2003, Free Software Foundation, Inc. [ref. 9]

The Janus API was chosen to provide access to the DAVE-ML dataset structure. Xerces and 

Qhull are supporting libraries required by the Janus API.

Examples for loading, testing, and running Janus models were found in sample code provided 

with its release and proved to be easy to implement. The development platform was a Sun-Sparc 

V890 computer hosting the Sun OS 5.10 (Solaris 10). The Sun C++ compiler 5.9 was used to 

generate a simulation executable.

The aero model initialization was accomplished by dynamically loading the HL20_aero.dml

file using Janus during simulation startup. The test cases were executed and checked to verify 

the integrity of the aero model. Other HL-20 vehicle models were provided "as is" from LaRC. 

These models were assumed to be correct.

The simulation was successfully flown in real-time at 200 Hz (5-ms frame time). It was 

demonstrated to be functional by exercising the control system in each of its major modes 

(Direct, SAS, and Automatic). Flight path and trajectory plots were compared against data 

provided in Reference 10 and deemed satisfactory.

As a result of this assessment, re-hosting simulations provided in the S-119 format should be 

relatively straightforward at DFRC.
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7.3 Glenn Research Center

For this assessment, a means to import S-119 models into the Optimal Trajectory by Implicit 

Simulation, version 4 (OTIS4) non-real-time simulation analysis tool was developed. OTIS4 is a 

3 degrees of freedom (DOF)/6DOF trajectory optimization program based on collocation 

methods originally developed by Mr. Steve Paris and Mr. Charles Hargraves of Boeing. OTIS4 

is now maintained by GRC and used by several industry partners, academia, NASA, and the US 

Air Force.

OTIS4 is primarily used for atmospheric flight optimization, although it is also capable of 

optimizing in-space trajectories. 

GRC chose to develop Perl scripts to convert from the standard model format into OTIS4 input 

tables. The scripts provided a means to import S-119 tabular data into OTIS4 via the Graphical 

Otis Dataset Interpolator and Editor (GRODIE) tool. Updates to GRODIE to load S-119 models 

took only a few days. This capability has been added to the OTIS4 distribution package.

Work is ongoing to provide an export capability (to convert OTIS4 models into S-119 models).

7.4 Johnson Space Center

At JSC, a team of analysts undertook several areas of assessment of S-119, including: 

1. Integration of two S-119 APIs with the JSC Trick simulation framework, and 

development of a novel S-119 to C-code generator.

2. Analysis of S-119 interpreter performance.

3. Investigation of some non-aerodynamic S-119 models, including implied dynamic 

models.

4. Analysis of the S-119 and DAVE-ML XML draft specifications.

Each activity is summarized below; Appendix A contains full details.

7.4.1 Software Integration

The JSC team’s effort to integrate S-119 models into JSC simulation software involved two 

activities: API integration and code generation. The integration activity focused on integrating 

the two available S-119 interpreter systems (Janus and LaSRS++/DAVE-ML Translator) into 

Trick. The code generation activity involved the development of an XML-to-C/C++ code 

generator to create compilable code from an S-119 model.

The code generator addressed, in a novel fashion, the desire of some to convert directly from 

S-119 model to C source code. It used a new technology, Extensible Style Sheet Language 

Transformation (XSLT) to convert an XML file into C source code whose input-output mapping 

matched that described in the S-119 model. Prior to this assessment, such capability was not 
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immediately available; instead, autocode had to be generated from an intermediate (and 

compute-intensive) translation from S-119 into Simulink® models.

For both activities (integration and code generation), the JSC team focused primarily on an 

HL-20 lifting body simulation, incorporating the HL-20 S-119 aerodynamic model with the 

Trick simulation framework and a JSC dynamics package (JSC Engineering Orbital Dynamics) 

to provide a planet model, coordinate systems, vehicle dynamics, and vehicle trajectory. They

implemented a single "generic" software model that integrated their Trick-based simulations with 

either the Janus or the LaSRS++ DAVE-ML interpreters. Details of this generic design are 

provided in Appendix A. The JSC team also used the XML-to-C/C++ code generator to 

generate equivalent C-code. The team found this generated code useful as a baseline against 

which to compare the runtime performance of the interpreted approach. It could also be used to 

compare against a hand-coded equivalent C-based HL-20 aero model during development.

7.4.2 Execution Time Study of DAVE-ML Interpreters

The JSC team’s performance analysis of S-119 models involved the investigation of a Trickbased HL-20 auto-landing simulation integrated with (1) the Janus DAVE-ML interpreters, 

(2) the LaSRS++ DAVE-ML interpreter, (3) the C code auto-coded from our XML-to-C/C++ 

code generator, and (4) some pre-existing hand-written HL-20 source code. In all four cases, the 

simulations generated the same trajectory. The JSC team found that interpreted DAVE-ML was 

of comparable speed to auto-generated compiled C-code and hand-tuned code for the limited 

testing they performed. Detailed results are available in Appendix A, including some of the 

limitations of the method used for performance analysis.

7.4.3 Non-aerodynamics Models Implemented in DAVE-ML

In addition to the JSC team’s work with the HL-20 aerodynamics model, the JSC team looked at 

two non-aerodynamic S-119 models: (1) an HL-20 reaction control system (RCS) algorithm and 

(2) a pneumatic tire force model. The investigation of the RCS algorithm, in particular the

successful representation of it in DAVE-ML and subsequent execution of the model using the 

Janus and LaSRS++ interpreters and their XML-to-C/C++ code generator, offers some evidence 

that models beyond the aerodynamics niche can indeed be represented through the current 

DAVE-ML specification. In particular, dynamic models with saved states can be created in 

DAVE-ML without direct support in the specification, by the caller providing external storage 

and integration of the state variables. This worked reasonably well when aided by a convenient 

method of hooking together corresponding simulation and internal DAVE-ML interpreter 

variables. The JSC team’s investigation of a pneumatic tire data compression model showed that

the self-documenting properties of DAVE-ML can be used to record provenance, modification, 

and accuracy data for static data sets; sophisticated models can be created entirely in MathML 

without recourse to table look-ups; and models can be created in a hierarchy where the outputs 

from one are then fed into the next in DAVE-ML, even though this feature is not supported 

directly in the specification. Further details are available in Appendix A.
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7.4.4 DAVE-ML Specification Comments/Suggestions

In the course of their assessment, the JSC team made some observations about the S-119

specification, in particular the DAVE-ML DTD. These observations are primarily the result of 

(1) the C-code generation work, and (2) a detailed look into the DAVE-ML uncertainty element. 

Generally it was found that in a few places, the DAVE-ML DTD is insufficiently precise to 

support automatic code generation (e.g., certain XML element attributes are optional leading to 

the possibility that an S-119-compliant XML model might not allow code generation without 

some manual intervention). The JSC team also found that the documentation of the uncertainty 

element in the reference manual could be improved, and they drafted a proposed replacement for 

the relevant section of the reference manual to fix some (but not all) of the weaknesses found. 

These detailed observations are available in Appendix A.

7.4.5 Conclusions and Suggestions for Future Work

The JSC team suggested several clarifications and changes to the DAVE-ML DTD specification 

that are described in more detail and summarized in Appendix A. They believe these changes 

will improve the rigor and clarity of the specification, making it easier to develop interpreters

and code generators for S-119 and helping to transfer models without ambiguity. The feasibility 

of an S-119 to C-code generation capability was demonstrated during this assessment. Although 

incomplete, the system prototyped during this assessment is useful at present and shows 

considerable potential for future expansion. The utility of the S-119 model format for use by 

non-aerodynamics models was shown by two test cases. The first case investigated hierarchical 

models; the second case was a pseudo-dynamic model with saved states implemented via callerprovided memory storage. This second case also demonstrated two ways to use ―macros‖ 

(essentially) to ease MathML authoring for complex algorithms. The JSC team suggested 

several areas where future work would be useful. These areas included further exploration of the 

S-119 and DAVE-ML specifications, continued development of the XSLT code generator 

toward an operational capability, and testing of the DAVE-ML <uncertainty> element by 

exercising it to specify dispersion test cases for the Trick Monte-Carlo capability. 

7.5 Marshall Space Flight Center

The Flight Mechanics and Analysis division (EV40) of MSFC’s Spacecraft and Vehicle Systems 

Department performs vehicle control system design and analysis as well as guidance, navigation, 

trajectory design, and mission analysis for launch vehicles and spacecraft. One of the primary 

tools used by EV40 in these analyses is the Marshall Aerospace Vehicle Representation in C 

(MAVERIC) simulation. At the time of this report, the efforts of EV40 as a part of this

assessment have been focused on incorporating the ability in MAVERIC to read and use S-119 

models. 

Following a brief evaluation, LaRC’s C++-based DAVE-ML Translator was chosen to be 

included in MAVERIC. The DAVE-ML Translator software was relatively easy to add to 
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MAVERIC but necessitated development of an intermediate ―wrapper‖ function. The wrapper 

was required to send data from MAVERIC into DAVE-ML translator objects and return data 

from translator objects into MAVERIC. The development of the DAVE-ML Translator wrapper 

and use of S-119 in MAVERIC have so far been exclusively for aerodynamics modeling. 

Testing of the DAVE-ML Translator software and the S-119/MAVERIC wrapper was performed 

by re-constituting aerodynamic data and models already used by MAVERIC into the DAVE-ML

format and using a DAVE-ML translator object to provide aerodynamic forces and moments. 

Initially, the aerodynamic buildup equations were encoded in the wrapper function and the 

DAVE-ML translator was just used for table lookups. Eventually, the entire aerodynamic 

buildup equations were encoded into the S-119 format and the wrapper was used only as an 

interface function. Tests were successful and conclusive. The simulation fed by S-119

aerodynamic data exactly matched the simulation using the standard MAVERIC aero model.

Of particular note is that the initial implementation of the HL-20 S-119 aero model into 

MAVERIC was completed with less than 1 week of effort.

7.6 Summary of Results

In general, most Centers found developing the means to import S-119 models into their existing 

simulation frameworks straightforward, taking as little as less than a week (if an existing API 

were used) to a few weeks (if a custom import tool was developed). Exporting from an existing 

simulation framework to the S-119 format was not tested.

Performance of the two existing APIs, which accept S-119 models at run-time, compared 

favorably with import scripts that convert S-119 models into compilation units and with handwritten C-code equivalent models.

Several limitations to the proposed S-119 format were uncovered and were provided as feedback 

to the AIAA standards subcommittee. In addition, some errors in one existing API and one 

existing import script were discovered and fixed during the assessment. Finally, a new import 

tool was developed that allows direct conversion of S-119 models into C-code.

The assessment was completed on time and well within budget (less than 40 percent of the 

allocated NESC funds were expended), indicating the burden of adapting an existing flight 

simulation framework to work with an S-119 model was much less than anticipated.

As a result of the assessment, the real-time flight simulation labs at ARC (SimLabs), DFRC

(Dryden Sim), JSC (Trick), and LaRC (LaSRS++) can now accept models written using S-119, 

as can the analysis simulations at MSFC (MAVERIC) and GRC (OTIS4). Collaboration 

between these facilities and tools will become much easier if the S-119 model format becomes 

more common in the US aerospace industry.
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8.0 Findings, Observations, and NESC Recommendations

8.1 Findings

The following findings were identified:

F-1. Current flight simulation frameworks utilized at each Center are mutually incompatible.

F-2. A common model format to exchange data would be beneficial to NASA for crossAgency teams involving flight simulation.

F-3. Implementation of necessary import scripts from the S-119 format to individual Center 

frameworks can be readily achieved (and has been accomplished to a large degree during 

this assessment).

F-4. Several limitations of the format were found that somewhat limit the usefulness of S-119 

for NASA. 

These limitations include: not specifying the valid range attributes for input 

variables and not requiring identifiers on all table definitions.

F-5. Lack of native editing tools for the S-119 model format is a hindrance to the usefulness of 

S-119.

F-6. The author and current maintainer of the custom XML grammar is a NASA employee, 

giving NASA considerable leverage in maintaining an essential part of the proposed 

standard.

8.2 Observations

The following observations were identified:

O-1. The AIAA draft Standard appears better tailored for aerospace applications than other 

available modeling formats.

O-2. Adoption of an existing API can typically be accomplished in less than a week.

O-3. Errors in the existing APIs were identified and corrected.

O-4. During the assessment, JSC developed a novel C language generation tool to convert 

from the standard format into C-code that performed almost as well as hand-generated 

code.
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8.3 NESC Recommendations

The following NESC recommendations were identified and directed toward the Office of Chief 

Engineer and all NASA organizations that conduct flight dynamic analyses and simulations:

R-1. Adopt the Flight Dynamic Model Exchange Standard, BSR/AIAA-S-119-201x, with 

suggested changes, as a recommended practice both for developing new simulation 

aerodynamic models and model exchange, when such models involve significant 

numbers of function tables. (F-1, F-2, F-3, F-4, O-1)

Suggested changes to S-119 for AIAA consideration include: add optional valid 

range attributes for input variables; require identifiers on all table definitions; and 

consider adopting National Institutes of Standards and Technology’s UnitsML 

encoding for units of measure. 

The first and second items have been adopted by AIAA MSTC with the third 

item undergoing evaluation.

R-2. In concert with other users of the AIAA S-119 Standard, support development and 

refinement of the necessary tools to make the format more useful and mutually beneficial. 

(F-5)

R-3. NASA should, through continued representation on the AIAA Modeling Standards 

subcommittee, remain cognizant of changes to the S-119 Standard and the associated 

DAVE-ML DTD to mitigate the risk of unilateral changes to S-119. (F-6)

9.0 Definition of Terms 

Finding A conclusion based on facts established by the investigating authority. 

Janus A specialized computer library (API) that understands and manipulates 

DAVE-ML model files.

Observation A factor, event, or circumstance identified during the assessment that did 

not contribute to the problem, but if left uncorrected has the potential to 

cause a mishap, injury, or increase the severity should a mishap occur. 

Alternatively, an observation could be a positive acknowledgement of a 

Center/Program/Project/Organization’s operational structure, tools, and/or 

support provided.

Parsing The act of reading and interpreting an encoded data file.

Perl An interpreted script programming language.
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Qhull A programming library (API) that deals with ungridded tabular data 

interpolation.

Recommendation An action identified by the NESC to correct a root cause or deficiency 

identified during the investigation. The recommendations may be used by 

the responsible Center/Program/Project/Organization in the preparation of 

a corrective action plan.

RT3D A graphics package for simulation visualization, used at DFRC.

S-119 AIAA draft standard for Flight Dynamic Model Exchange.

Simlabs ARC Simulation Laboratories.

Simulink® A dynamic system analysis and programming tool. It is a commercial 

product of The Mathworks, Inc. of Natick, MA.

UnitsML A markup language for units-of-measure encoding.

Xerces A programming library (API) that understands and manipulates data files 

encoded in XML.

10.0 Acronyms List

AIAA American Institute of Aeronautics and Astronautics

ANSI American National Standards Institute

API Application Programming Interface

ARC Ames Research Center

ATK Alliant Techsystems, Inc.

BSR ANSI Board of Standards Review

DAVE-ML Dynamic Aerospace Vehicle Exchange Markup Language

DFRC Dryden Flight Research Center

DMLT DAVE-ML Translator 

DoD Department of Defense

DOF Degree of Freedom

DSTO Australian DoD Defence Science Technology Organisation

DTD Document Type Definition

FORTRAN Formula Translation programming language

FTP Function Table Processor

GN&C Guidance, Navigation, and Control

GRC Glenn Research Center
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GRODIE GRaphical Otis Dataset Interpolator and Editor

GSFC Goddard Space Flight Center

HDD Heads Down Display

HSCT High Speed Civil Transport

ISO International Organization for Standardization

JSC Johnson Space Center

LaRC Langley Research Center

MAVERIC Marshall Aerospace Vehicle Representation in C

MSFC Marshall Space Flight Center

MSTC AIAA Modeling and Simulation Technical Committee

MTSO Management and Technical Support Office

NESC NASA Engineering and Safety Center

NRB NESC Review Board

OTIS4 Optimal Trajectory by Implicit Simulation, version 4

RCS Reaction Control System

SAS Stability Augmentation System

Simlabs Simulation Laboratories

US United States

XML Extensible Markup Language

XSLT Extensible Style Sheet Language Transformation

11.0 References

1. Hill, Melissa A.; and Jackson, E. Bruce; The Dave-MLTranslator: An Interface for DAVEML Aerodynamic Models, AIAA Paper 2007-6890. Presented at the AIAA Flight Simulation 

Technologies Conference, Hilton Head, SC, August 2007.

2. Jackson, E. Bruce; Results of a Flight Simulation Software Methods Survey, AIAA Paper 93-

3414. Presented at the AIAA Flight Simulation Technologies Conference, Baltimore, MD, 

August 1995.

3. Jackson, E. Bruce; Raney, David L.; Glaab, Louis J.; and Derry, Stephen D.; Piloted 

Simulation Assessment of a High-Speed Civil Transport Configuration, NASA/TP-2002-

211441, March 2002.

4. Jackson, E. Bruce and Hildreth, Bruce L.; Flight Dynamic Model Exchange using XML,

AIAA Paper 2002-4482. Presented at the AIAA Modeling and Simulation Technology 

Conference, Monterey, CA, August 2002.

5. The Modelica Association website: http://www.modelica.org (accessed November 6, 2010).

6. Jackson, E. Bruce; Hildreth, Bruce L.; York, Brent W.; and Cleveland, William; Evaluation 

of a Candidate Flight Dynamics Model Simulation Standard Exchange Format, AIAA Paper 
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2004-5038. Presented at the AIAA Modeling and Simulation Technologies Conference and 

Exhibit, Providence, RI, August 2004.

7. Janus Dynamic Aerospace Vehicle Exchange Mark-up Language (DAVE-ML) C++ 

Interpreter website: http://www.dsto.defence.gov.au/research/4675 (accessed November 6,

2010).

8. Xerces C++ XML Parser website: http://xerces.apache.org/xerces-c (accessed November 6,

2010).

9. Qhull Convex Hull Library website: http://www.qhull.org (accessed November 6, 2010).

10. Jackson, E. Bruce; Cruz, Christopher I.; and Ragsdale, W. A.; Real-Time Simulation Model 

of the HL-20 Lifting Body. NASA TM-107580, July 1992.
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Volume II: Appendices

Appendix A. NESC Flight Simulation Model Exchange Assessment Report from Johnson 

Space Center

Appendix B. American National Standard: Flight Dynamics Model Exchange Standard (draft 

BSR/AIAA S-119-201x)

Appendix C. XML Document Type Definition file for S-119 markup: DAVEfunc.dtd

Appendix D. Dynamic Aerospace Vehicle Exchange Markup Language (DAVE-ML) 

Reference Manual
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Flight Simulation Model Exchange

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14. ABSTRACT

The NASA Engineering and Safety Center Review Board sponsored an assessment of the draft Standard, Flight Dynamics 

Model Exchange Standard, BSR/ANSI-S-119-201x (S-119) that was conducted by simulation and guidance, navigation, and 

control engineers from several NASA Centers. The assessment team reviewed the conventions and formats spelled out in the 

draft Standard and the actual implementation of two example aerodynamic models (a subsonic F-16 and the HL-20 lifting 

body) encoded in the Extensible Markup Language grammar. During the implementation, the team kept records of lessons 

learned and provided feedback to the American Institute of Aeronautics and Astronautics Modeling and Simulation Technical 

Committee representative. This document contains the results of the assessment.

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