Ontology-assisted system modeling combines classic system-theoretical modeling with an ontological system specification. Different dynamic system behavior is modeled in configurable basic models with defined input and output interfaces. Basic models are organized in a model base (MB). The ontology is used to specify a set of modular, hierarchical system structures using references to basic models in the MB. Moreover, the ontological model defines possible parameter settings of referenced basic models. Thus, the ontology describes a set of different system configurations for a specific domain. A base ontology for mapping such problems is the System Entity Structure (SES). A combination of SES ontology with a MB for system modeling and goal-oriented model generation was introduced with the SES/MB framework. Starting with the basics of SES ontology and SES/MB framework as well as the discussion of some extensions, a new SES toolbox for ontological modeling within the MATLAB/Simulink environment is presented. The toolbox architecture is then discussed. The main focus in this regard is on the graphical SES editor, the toolbox methods and the seamless integration with MATLAB/Simulink. The latter is described by means of deriving a specific system model from the formal specification and the automatic generation of a corresponding executable MATLAB/ Simulink model.

The increasing complexity of systems entails an increasing complexity of simulation models. Likewise, heterogeneity in system components corresponds to heterogeneous simulation models. Cyber physical systems (CPS) represent an emerging class of technical systems characterized by their complexity and heterogeneity. Developing simulation models for CPS brings various challenges, one of which is determining the simulation fidelity. Fidelity evaluation can be introduced as the degree to which a simulation model matches the characteristics of the system it represents. Due to the growth of system complexity in CPS, the number of test cases required to reach admissible coverage to assure adequate simulation fidelity is very high. Along with that, heterogeneity in system components comes on top as another challenge. Therefore, adaptability, flexibility and automation can be identified as the key characteristics of a fidelity evaluation approach that determines its success. Model-based testing (MBT) advocates the use of models for the specification of test cases and proposes workflows for automatic test case generation. This paper presents an MBT approach for objective fidelity evaluation of complex, modular simulation models. The methodology implies that appropriate data for fidelity evaluation are available. Each test model is represented according to the formal structure of experimental frame (EF). For generating an executable EF for a model under test (MUT), configurable basic models are provided by a model base (MB). In the same manner, configurable basic models for composing various MUTs are stored in the MB. The system entity structure (SES) ontology is used for the specification of a family of MUT and test model designs on an abstract level. This means that the SES describes a set of various MUT and test model structures and parameter settings. Using the SES and MB, a specific executable model consisting of an MUT and a test model can be generated. Based on these ideas an infrastructure implementation for automated fidelity evaluation of complex, modular simulation models within MATLAB/Simulink is proposed in this paper.

The term simulator fidelity has become enormously important in the scope of simulation research, when assessing training efficiency and the transfer of training to real flight. It is defined as the degree to which a flight simulator matches the characteristics of the real aircraft. Objective simulator fidelity provides an engineering standard, by attacking the fidelity problem with comparison of simulator and the actual flight over some quantitative cues. Research flight simulation encompasses some differences from commercial flight simulation. It requires high flexibility and versatility concerning the cockpit layout and visual and motion systems, as well as flight simulation models. It shoud be easy to modify the flight simulation model or other soft-and hardware components of the simulator. By this, there is a need for an automatic test method, in order to determine the fidelity of the most relevant simulator subsystems, since they are often modified during the life cycle of the simulator. The Institute of Flight Systems (FT) at the German Aerospace Center (DLR) has a reconfigurable flight simulator, the Air Vehicle Simulator (AVES), for research of rotorcraft and fixed-wing aircraft. The study reported in this paper targets a model based testing approach designed to tackle the high flexibility requirement of AVES. This paper presents a metamodel for objective flight simulator evaluation. Metamodeling has been carried out in two levels. An Experimental Frame Ontology (EFO) has been developed adopting experimental frames from Discrete Event System Specification (DEVS), and as an upper ontology to specify a formal structure for simulation test. Then in Objective Fidelity Evaluation Ontology (OFEO) that builds upon EFO, domain specific meta-test definitions are captured.

No abstract

Simulator fidelity has been defined as the conformance of a flight simulator to the characteristics of the real aircraft. Objective fidelity evaluation is an engineering approach that attacks the fidelity problem with comparison of simulator and the actual system behavior over some quantitative measures. Testing can be pronounced as the fundamental mean for this comparison. From the utilization perspective, flight simulators are classified as research, engineering and training simulators. Research simulators are both test beds for flight simulator research and computational tools for flight systems and human factors research. Engineering simulators are used for systems development and training simulators are utilized for flight training. While training simulators are subject to rare or few upgrades or modifications in their lifespan, engineering simulators are under occasional and research simulators are under frequent change. The test cases to evaluate the fidelity of training simulators are guided by standards whereas for engineering and research simulators, test cases may present a great variation depending on the scope of change and the use case. These two characteristics of engineering and research simulators, combined with the complexity of today's aircrafts necessitate new methodologies for efficient and effective testing. Model-Based Testing (MBT) targets flexibility and adaptability via utilization of models for specification of test cases and proposes workflows for automatic test case generation. The paper presents an MBT approach for objective fidelity evaluation of engineering and research simulators. The proposed approach is exercised with an infrastructure implementation and an example case study. Thus, evidences are collected that indicate increased efficiency and an effective test process.