Combining performance and numerical stability is a key issue in co-simulation. The Transmission Line Modeling method uses physically motivated communication delays to ensure numerical stability for stiff connections. However, using a fixed communication delay may limit performance for some models. This paper proposes Steady-State Identifcation for enabling variable communication delays. Three algorithms for online Steady-State Identification are evaluated in three different co-simulation models. All algorithms are able to identify steady-state and can thereby determine when communication delays can be allowed to increase without compromising accuracy and stability. The results show a reduction in number of the solver derivative evaluations by roughly 40-60% depending on the model. The proposed method additionally supports connections with asymmetric communication delays, which allows each sub-model to independently control the delay of its input variables. Models supporting delay-size control can thereby be connected to those that do not so that the step length of each individual sub-model is maximized. Controlling the delay-size in sub-models also makes the method independent of the master co-simulation algorithm. 

New technologies and innovations to reduce carbon dioxide emissions in the aeronautics industry are essential. The morphing wing concept is an excellent method to increase aircraft performance and reduce fuel consumption and may now become re-applied using a new actuation technology. Nevertheless, for the moment, several showstoppers inhibit the commercial introduction of morphing systems. A morphing wing design's structural skeleton, actuator and sensor network are characterized by an extensive and multi-branched network of actuators and sensors and many mechanical and electrical components that reduce reliability, availability, flight safety and maintainability. It also dramatically impacts weight, volume, complexity and costs. Therefore, less complex and more robust solutions are desired for the morphing wing technology to become a realistic alternative for the aeronautics industry.  Future morphing wing systems in aircraft can be improved significantly by utilizing a new type of hydraulic linear actuator invention, the Hydraulic Infinite Linear Actuator with Multiple Rods (HILA MR). A single HILA MR actuator has the potential to replace the whole actuator and sensor network in a morphing wing, enabling substantial rationalization in several ways and facilitating certification and commercial introduction.  Furthermore, compared to conventional actuating technologies, a HILA MR architecture allows for controlling the morphing structure using reduced mass and volume, enabling a power consumption reduction. With HILA MR, the mechanical actuation of the control surfaces may be embedded into the aircraft's fuselage in a bio-mimicking fashion similar to the human hand, where the muscles that control the fingers of the hand are located in the forearm. Light Dyneema fibre cables with high tensile strength are used to distribute actuator motions in the fuselage to the control surface, similar to how they are used in cable robots. In addition, the location of the actuator facilitates a slender wing design.  The HILA MR technology enables a novel way to generate and distribute linear mechanical movement for flight control and wing morphing. It mimics the characteristics of hydraulic servo cylinders, but the piston actuates several multiple rods in a switching fashion, using clamping elements. The HILA technology acts according to a timing-controlled shifting of operating modes between continuous and discrete incremental actuator positioning steps. Each rod actuates one part of the wings morphing mechanical structure. The application of this technology in aviation is also characterized by the following: a reduced number of servo valves, well-known clamping technology used for both stepping and locking functionality, a reduced number of position feedback sensors and a local hydraulic system in the fuselage or situated in the wing box with a small oil reservoir volume.  This paper aims to evaluate different aspects and design issues of the HILA MR system in a morphing wing application (actuator, sensor, control system and structural skeleton) and compare the technology against present electromechanical solutions. In addition, a simplified morphing wing system simulation model based on HILA MR is presented. Results from initial simulations show that the concept is attainable and will have the required response timings. 

Two different metrics quantifying model and simulator predictive capability are formulated and evaluated; both metrics exploit results from conducted validation experiments where simulation results are compared to the corresponding measured quantities. The first metric is inspired by the modified nearest neighbor coverage metric and the second by the Kullback?Liebler divergence. The two different metrics are implemented in Python and in a here-developed general metamodel designed to be applicable for most physics-based simulation models. These two implementations together facilitate both offline and online metric evaluation. Additionally, a connection between the two, here separated, concepts of predictive capability and credibility is established and realized in the metamodel. The two implementations are, finally, evaluated in an aeronautical domain context.

Modeling and simulation are important tools for efficient product development. There is a growing need for collaboration, interdisciplinary simulation, and re-usability of simulation models. This usually requires simulation tools to be coupled together for co-simulation. However, the usefulness of co-simulation is often limited by poor performance and numerical instability. Achieving stability is especially hard for stiff mechanical couplings. A suitable method is to use transmission line modeling (TLM), which separates submodels using physically motivated time delays. The most established standard for tool coupling today is the Functional Mock-up Interface (FMI). Two example models in one dimension and three dimensions are used to demonstrate how the next version of FMI for co-simulation can be used in conjunction with TLM. The stability properties of TLM are also proven by numerical analysis. Results show that numerical stability can be ensured without compromising on performance. With the current FMI standard, this requires tailor-made models and custom solutions for the interpolation of input variables. Without using custom solutions, variables must be exchanged using sampled communication and extrapolation. In this case, stability properties can be improved by reducing communication step size. However, it is shown that stability cannot be achieved even when using unacceptably small communication steps. This motivates the need for the next version of FMI to include an intermediate update mode, where variables can be interchanged in between communication points. It is suggested that the FMI standard should be extended with optional callback functions for providing intermediate output variables and requesting intermediate input variables.

Establishing interoperability is an essential aspect in the often pursued shift towards Model Based System Engineering (MBSE) of, for example, aircraft. If models are to be the primary information carriers during development, the applied methods to enable interaction between engineering domains need to be modular, reusable, and scalable. One possible solution is to rely on available open-source tools and standards. In this paper, the standards Functional Mock-up Interface (FMI) and System Structure and Parameterization (SSP) are exploited to exchange data between the disciplines of systems simulation and geometry modeling. A method to export data from the 3D Computer Aided Design (CAD) Software (SW) CATIA in the SSP format is developed and presented. Analogously, FMI support of the Modeling & Simulation (M&S) tools OMSimulator, OpenModelica, and Dymola are utilized along with the SSP support of OMSimulator. The developed technology is put into context by means of integration with M&S methodology for aircraft vehicle system development deployed at Saab Aeronautics. Finally, the established interoperability is demonstrated in an industrially relevant use-case. A primary goal of the research is to prototype and demonstrate functionality, enabled by the SSP and FMI standards, that could improve on MBSE methodology implemented in industry and academia.

Modeling and Simulation (M&S) is seen as a means to mitigate the difficulties associated with increased system complexity, integration, and cross-couplings effects encountered during development of aircraft subsystems. As a consequence, knowledge of model validity is necessary for taking robust and justified design decisions. This paper presents a method for using coverage metrics to formulate an optimal model validation strategy. Three fundamentally different and industrially relevant use-cases are presented. The first use-case entails the successive identification of validation settings, and the second considers the simultaneous identification of n validation settings. The latter of these two use-cases is finally expanded to incorporate a secondary model-based objective to the optimization problem in a third use-case. The approach presented is designed to be scalable and generic to models of industrially relevant complexity. As a result, selecting experiments for validation is done objectively with little required manual effort.

Hopsan is an open-source simulation package developed as a collaboration project between industry and academia. The simulation methodology is based on transmission line modelling, which provides several benefits such as linear model scalability, numerical robustness and parallel simulation. All sub-models are pre-compiled, so that no compilation is required prior to starting a simulation. Default component libraries are available for hydraulic, mechanic, pneumatic, electric and signal domains. Custom components can be written in C++ or generated from Modelica and Mathematica. Support for simulation-based optimization is provided using population-based, evolutionary or direct-search algorithms. Recent research has largely focused on co-simulation with other simulation tools. This is achieved either by using the Functional Mock-up Interface standard, or by tool-to-tool communications. This paper provides a description of the program and its features, the current status of the project, and an overview of recent and ongoing use cases from industry and academia.

OpenModelica is a unique large-scale integrated open-source Modelica- and FMI-based modeling, simulation, optimization, model-based analysis and development environment. Moreover, the OpenModelica environment provides a number of facilities such as debugging; optimization; visualization and 3D animation; web-based model editing and simulation; scripting from Modelica, Python, Julia, and Matlab; efficient simulation and co-simulation of FMI-based models; compilation for embedded systems; Modelica-UML integration; requirement verification; and generation of parallel code for multi-core architectures. The environment is based on the equation-based object-oriented Modelica language and currently uses the MetaModelica extended version of Modelica for its model compiler implementation. This overview paper gives an up-to-date description of the capabilities of the system, short overviews of used open source symbolic and numeric algorithms with pointers to published literature, tool integration aspects, some lessons learned, and the main vision behind its development.

Numerical stability is a key aspect in co-simulation of physical systems. Decoupling a system into independent sub-models will introduce time delays on interface variables. By utilizing physical time delays for decoupling, affecting the numerical stability can be avoided. This requires interpolation, to allow solvers to request input variables for the time slot where they are needed. The FMI for co-simulation standard does not support fine-grained interpolation using interpolation tables. Here, various modifications to the FMI standard are suggested for improved handling of interpolation. Mechanical and thermodynamic models are used to demonstrate the need for interpolation, as well as to provide an industrial context. It is shown that the suggested improvements are able to stabilize the otherwise unstable connections.

Modern aircraft can be seen as heterogeneous systems, containing multiple embedded subsystems which are in today’s simulations split into different domain-specific models based on different modelling methods and tools. This paper addresses typical workflow-driven model integration problems with respect to model fidelity, accuracy in combination with the selected abstraction methods and the target system characteristics. A short overview of integration strategies with the help of co-simulation frameworks including an analysis of the inherent problems that emerge because of different domain-specific modelling methods is being given. It is shown that huge benefits can be reached with the help of a smart system break-up. In detail, the discrepancy between the cyber-physical system simulations and human-machine interaction (HMI) models are being analysed. Therefore, a close look at the typical shortcomings of behavioural models is being discussed, too. To enable an effort-less human-in-the-loop integration into a cyber-physical system simulation, the usage of flight simulation software, offering real-time capability and a graphical user interface is suggested. This approach is applied to overcome today’s complexity and shortcomings in human psychological models. An example implementation based on a commercial flight simulator software (X-Plane) together with a high-performance system simulation tool (Hopsan) via UDP communication is presented and analysed.