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control loading, instructor station, motion system,
visual system, instrument displays either provide
inputs to these models or present their results to the
pilot as cues (Allerton, 2009).
Research simulators have been used as the test
beds for flight simulator, flight systems and human
factors research. So, while the models that are used
in training simulators and even in engineering
simulators are more mature and stable, the models in
research simulators are subject to a constant change.
Recent advances in Model Based Design and
Software Development (MBDSD) have brought
aeronautics community agile model development
workflows. So that model development is integrated
to product development employing mature code
generation practices (Ruff et al., 2012). Models
developed to design the products now became the
bases for code generation to be deployed in the
product.
For research flight simulators with MBDSD, the
models that are built to study overall systems (e.g.
Flight Dynamics Model) and subsystem (e.g. Flight
Warning Computer Model) behaviour became the
bases for generating code to be deployed in real time
flight simulators. These models serve for researchers
that exercise various aspects of aircraft in their
desktop environments, and for simulator developers
to simulate aircraft system and sub systems.
Research simulator developers need to establish
mechanisms to tackle frequent behaviour and
interface changes in models. And constant model
changes in a research habitat can only be enabled
with a model integration workflow in the systems
development. But flight simulator literature lacks in
reporting any efforts.
There are some recommended practices from the
aerospace industry for model based flight systems
design and development. Estrada et al. introduce
best practices for developing DO-178 compliant
software using Model-Based Design and
Development (Estrada, R.G. et al., 2013). Miller
presents automatic flight code generation practices
in Northrop Grumman (Miller, 2007) and introduces
a use case from desktop simulation to Hardware in
the Loop testing. BAE Systems has a model based
flight control systems development process
(Fielding, 2010). Fielding presents a process
starting from aerodynamic dataset generation to
flight clearance of the aircraft. In this process he
mentions the use of engineering simulators for
model based flight control system design. Nixon
states that in F-35 project MBDSD forced them to
reinterpret traditional software development process
for flight control systems (Nixon, 2004). He
introduces Lockheed Martin Aeronautics practices
of MBDSD.
On the other hand, there exists a vast amount of
effort to develop integration workflows for their
model based developed software component. In one
of them (Guido and Thompson, 2008) from Math-
works, authors propose a workflow to develop
software components to be integrated to Automotive
Open System Architecture (AUTOSAR).
AUTOSAR specifies the architecture to integrate
functional applications over a hardware abstracting
runtime environment in automotive electronic
control units. The presented workflow enables
modellers to develop an infrastructure compliant
model development and seamless integration over a
standard architecture.
Figure 1: DLR AVES.
DLR’s Institute of Flight Systems (FT) has a
long tradition in flight research and simulation of
various flight vehicles. Currently AVES, a modern
research simulator facility is being operated at DLR
Braunschweig. AVES is designed such that
interchangeable cockpits of rotorcraft (EC135) and
airplanes (A320) can be operated on motion and
fixed-base platforms according to the particular
needs. 2Simulate is the enabling real-time simulation
infrastructure of AVES. All simulator software
components are integrated over this infrastructure.
This effort adopts best practices from both aerospace
and automotive industries. It tackles the model
integration problem of research flight simulators by
developing a model integration workflow for the
indigenous simulator infrastructure, namely
2Simulate. The motivation is to contribute to flight
simulator development by introducing a model
integration workflow for institutionalizing MBDSD.
The paper presents the Mathwork’s Simulink
Coder based model integration workflow of
2Simulate infrastructure in AVES facility. This
workflow provides the users of AVES a shortened
time to simulator after they updated their models.
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