Modelica and Functional Mock-Up Interface: Open Standards for Gas Turbine Simulation

• Lightweight CH4/air gas turbine simulator. • System identification, cycle, and sensitivity analyses CH4/air gas turbines. • Developing and calibrating a CH4/air gas turbine controller. • The potential of utilizing waste heat utilization mechanisms. • Control measures to eliminate turbine overheating. Due to the uncertainties of determining stable, efficient, and safe operating conditions of methane-air gas turbines and the complexity of involving multivariable parameters, the task of controlling and analyzing methane-gas turbines remains a challenge despite the existing methods of control and analyses in the literature. In fact, as far as the methane-air gas turbines are concerned, there is still much room for improvement within the criterion of (computation effort, settle time, its capacity to adjust with a variable range of set-points, as well as its stable, steady, and dynamic outputs can all be enhanced). Furthermore, an accurate system-identification phase has been adopted in this paper to initiate the process of advancing an efficient gas turbine controller by determining the system's sensitivities towards the involved multivariable parameters. Therefore, this paper presents a control and analysis tool for methane-air gas turbines. This tool is a ‘light code (the time to reach the desired set-point (i.e., settle period reaches 1 s)) to serve as a methane-air gas turbine controller that can be used for experimentation or applied on an industrial scale. Moreover, the code is designed with a user interface that enables the simulations and system identification for the methane-fueled gas turbine, thus; ensuring that the governing parameters are calibrated precisely. The code was created using LabVIEW and GASEQ and is driven by conventional gas turbine cycle assessments. A simulation case study has been utilized as a system identification phase to determine the system's sensitivity of temperatures and works at the three primary stages of a simple cycle methane-air gas turbine (compressor, combustion chamber, and turbine) toward the multivariable input parameters of the compression stage (compressor pressure ratio, efficiency, inlet pressure, and temperature), the combustion phase (methane, airflow rates) and the expansion phase (turbine ratio of pressures and isentropic efficiency). Based on the sensitivity analysis performed through the developed code, the turbine output temperature is shown to be very sensitive to the turbine's parameters ( P 04 / P 03 and ε t ). This essentially emphasizes the possibility of including waste heat utilization mechanisms (i.e., heat exchangers, combined cycles) for turbines with high P 04 / P 03 or/and low ε t , resulting in a high turbine outlet temperature. Based on the performed system identification phase and sensitivity analyses, the intervals of the Proportional controller gain ( K c ) , Integral time ( t i ) , and Derivative time ( t d ) have been identified to guarantee a settling period ( T s ) within [1 s-60 s] to achieve the desired temperature set-point which eliminates turbine overheating.

Multi-tool modeling and co-simulation of complex systems is a difficult problem. The missile power distribution system is a typical multidisciplinary combination of electrical, mechanical, dynamic, magnetic and cybernetics. Traditional professional software can only simulate a specific domain model. In order to study the coupling characteristics of the missile system and verify the rationality of the system model design, a multi-domain model simulation tool is needed. This paper proposes a multi-domain simulation method based on FMI (Functional Mock-up Interface) to simulate complex systems. It can use the advantages of different software and its professional model library, and overcome the difficulty of multi-source model co-simulation in the process of complex system development. This paper makes study in two aspects. On the one hand, the missile electrical characteristics are taken as the research object, the missile system is analyzed and decoupled according to the function. The missile subsystem models are established by using different professional software, and then the original model of the subsystem is converted into an FMU (Functional Mock-up Unit) model that conforms to the FMI standard. On the other hand, a simulation platform supporting the FMI standard was developed for co-simulation of the entire missile power distribution system. Finally, the simulation results show the correctness of the FMI based simulation scheme and the effectiveness of the simulation platform.

The aircraft power distribution system is a combination of electrical, mechanical, magnetics, and control system. Traditional professional software can only simulate one specific domain, in order to study the coupling characteristics of aircraft power distribution system, a multi-domain simulation tool is needed. A FMI (Functional Mock-up Interface) based multi-domain simulation method is proposed in this paper to utilize the advantages of different software and their professional model libraries. As a case study, this paper built the controllers of aircraft power distribution by Simulink, and then exported as the FMU (Functional Mock-up Unit) model to Dymola platform according to the FMI standard for the modeling and simulation of whole systems. Those models which exported according FMI standard can be independent from the original simulator and applied to other platforms corresponded FMI standard, which realize multi-domain modeling and simulation.

The development of Cyber Physical Systems (CPS) requires to model both the cyber (i.e., digital) parts, the physical parts and the interaction between them. The state of the practice in such domain usually involves different stakeholders, which use dedicated modeling languages tailored syntactically and semantically to their domain. Functional Mock-up Interface (FMI) is a recent standard, which provides technical facilities to enable the co-simulation among the different dedicated modeling languages. In this context, this paper investigates how discrete-event models of the cyber part are supported by FMI standard for co-simulation. Two main results are presented: 1) how SystemC models can be integrated into the FMI environment and 2) FMI limitations for the efficient use of discrete-event models in co-simulation. Both results are illustrated by using a simple but illustrative use case mixing models in SystemC (for the cyber part) and Modelica (for the physical part).

Ecos is a cross-platform framework for running co-simulations adhering to the Functional Mockup Interface (FMI) standard (Blochwitz et al., 2012); an open standard for model exchange and co-simulation of dynamic systems.The FMI Standard provides three interface types for difference aspects of models, namely: FMI for Model Exchange (ME), FMI for Co-simulation (CS), and FMI for Scheduled execution (Since FMI 3.0).Ecos supports the co-simulation mode, which is the most widely used interface type.An FMU (Functional Mock-up Unit) is a self-contained component that implements the FMI standard.It is packaged as a zip archive containing:

Reconciling interoperability with efficient Verification and Validation within open source simulation environments

This research introduces a simulation framework for aircraft ground roll, integrating a dynamic model developed in Simcenter Amesim with a control system implemented in MATLAB/Simulink through the Functional Mock-up Interface (FMI). The study aims to provide a robust environment for analysing and validating advanced ground control strategies under realistic runway roll conditions. The aircraft model, based on a 6DOF tricycle configuration, includes steering and differential braking features adapted from a validated Amesim taxi model, using representative data of a commercial turboprop aircraft. The framework enables bidirectional communication between Amesim and MATLAB through FMI and Co-Simulation, allowing performance evaluation of the control system. The controller employs a structured H-Infinity approach combined with a control allocator to coordinate rudder, nose wheel, and differential braking actions, ensuring runway centerline tracking and stability even in the presence of crosswind and for different runway conditions. The FMI integration process includes interface remapping, FMI export from Simulink, and closed-loop coupling with the Amesim model. Additional simulations were performed using a reverse configuration, with Amesim running as a co-simulation module within MATLAB via an S-function interface, to validate interoperability and numerical consistency. Comparative analysis between FMI and Co-Simulation confirm consistent data exchange and equivalent dynamic responses across platforms. The developed framework demonstrates the feasibility, flexibility, and accuracy of hybrid Amesim–MATLAB environments for studying complex aircraft ground dynamics configurations and provides a foundation for future work.

One primary objective of drone simulation is to evaluate diverse drone configurations and contexts aligned with specific user objectives. The initial challenge for simulator designers involves managing the heterogeneity of drone components, encompassing both software and hardware systems, as well as the drone’s behavior. To facilitate the integration of these diverse models, the Functional Mock-Up Interface (FMI) for co-simulation proposes a generic data-oriented interface. However, an additional challenge lies in simplifying the configuration of co-simulation, necessitating an approach to guide the modeling of parametric features and operational conditions such as failures or environment changes. The article addresses this challenge by introducing CARES, a model-driven engineering and component-based approach for designing drone simulators, integrating the FMI for co-simulation. The proposed models incorporate concepts from component-based software engineering and FMI. The NAVIDRO architectural style is presented for designing and configuring drone co-simulation. CARES utilizes a code generator to produce structural glue code (Java or C++), facilitating the integration of FMI-based domain-specific code. The approach is evaluated through the development of a simulator for navigation functions in an autonomous underwater vehicle, demonstrating its effectiveness in assessing various autonomous underwater vehicle configurations and contexts.

This paper describes how models from different simulation tools can be connected and simulated on different processors by using the Functional Mockup Interface (FMI) and the transmission line eleme ...

This paper describes how models from different simulation tools can be connected and simulated on different processors by using the Functional Mockup Interface (FMI) and the transmission line element method (TLM).Interconnectivity between programs makes it possible to model each part of a complex system with the best suited tool, which will shorten the modelling time and increase the accuracy of the results.Because the system will be naturally partitioned, it is possible to identify weak links and replace them with transmission line elements, thereby introducing a controlled time delay.This makes the different parts of the system naturally independent, making it possible to simulate large aggregated system models with good performance on multi-core processors.The proposed method is demonstrated on an example model.A suggestion of an XML extension to the FMI standard for describing TLM ports is also presented.

District heating grids (DHG) face the problem of seasonal variability and peak demands, e.g., there is a high demand for heat in winter and a low demand in summer. Operators of district heating networks and energy suppliers are therefore seeking solutions to store heat and access it at peak times, thus reducing the use of carbon-emitting heat sources. Aquifers are well suited for heat storage because of high storage capacity relative to the surface occupancy and reasonably high recovery efficiency, if geological suitable. In this study, the potential of Aquifer Thermal Energy Storages (ATES) contribution in decreasing seasonal peak heat loads is investigated by numerical modelling. Each part of the overall system (surface and subsurface) is modelled in their corresponding simulation environment. They are numerically coupled with a novel approach, allowing for highest accuracy in both subsystems. The District Heating Grid is modelled in the object-oriented modelling language Modelica including the Open-Source library MoSDH. Using the Functional Mock-Up Interface (FMI) the Modelica models are exported to executable Functional Mock-Up Units (FMU). The groundwater flow and heat transport processes are modelled in the finite-element software FEFLOW. By developing a C++ Plug-In for FEFLOW the FMU is imported and dynamically co-simulated. This approach allows for easier adjustments in both subsystems and more coupling options to existing models and softwares.  Through numerical analysis different hydrological and geological scenarios of the ATES and different operational cycles are investigated to determine the long-term efficiency and capacity of the storage. This modelling approach can be used to develop strategies for the operation of the ATES as well as to evaluate in advance whether geological conditions are suitable for the particular network situation.

This paper describes the results of an evaluation of vehicle power network modeling using Functional Mock-up Interface (FMI). FMI, developed by the Modelica Association, is a tool-independent standard for a model interface. This study compared simulation results between the vehicle power network model with Functional Mock-up Units (FMUs) connected and the model without FMUs. Conversion adaptors were inserted to generate and connect each FMU because it was necessary to convert physical connections from acausal connections to causal inputs and outputs. Using FMI for Model Exchange, it was confirmed that the results for both simulations showed good matches, without any time delays although algebraic loops which would often occur in electrical circuit modeling were included. This method possesses significant potential to reduce the validation effort using models created by other departments or suppliers.

The main objective of virtual commissioning is to help design and validate the control systems of entire production plants. Therefore, simulations on a logical and kinematic level are performed, typically in a Software- or Hardware-in-the-Loop configuration using the original control software and controller [1].However, the lack of level of detail means that this type of simulation is insufficient for an integrated system dynamics and control algorithms design. These engineering tasks are currently performed in separate tools, e.g. by finite element analysis, multibody simulations or by a combination, i.e. elastic multibody systems (EMBS) [2]. However, the designed components are only considered individually and not in the context of the control technology used. Therefore, primarily synthetic inputs are used and not the original control behavior. With a higher level of simulation detail, further questions about the system, such as the effect of control algorithms on the dynamic processes, can be virtually validated.Therefore, this paper explores hybrid component-based digital twins to combine the advantages of both VC and EMBS. Hybrid components allow the simulation of the interactions between process, machine and control system with a high level of detail where this is beneficial. Such integration is achieved using the Functional Mock-up Interface (FMI) to couple different simulation models in a co-simulation environment [3]. This is demonstrated in a simulation use case of an inverted pendulum. The level of detail of individual components in the virtual commissioning tool ISG-virtuos [4] is increased by the modular integration of elastic multibody simulations via FMI so that the swing-up controller can be designed in the simulation.

The Functional Mock-up Interface (FMI) is an industry standard which enables co-simulation of complex heterogeneous systems using multiple simulation engines. In this paper, we show how to use FMI in order to co-simulate hybrid systems modeled in the model checkers SPACEEX and UPPAAL. We show how FMI components can be automatically generated from SPACEEX and UPPAAL models. We also validate the cosimulation approach by comparing the simulations of a room heating benchmark in two cases: first, when a single model is simulated in SPACEEX; and second, when the model is split in two submodels, and co-simulated using SPACEEX and UPPAAL. Finally, we perform a measurement experiment on a composite model to show a potential for statistical model checking using stochastic co-simulations.

The Electro-Hydrostatic Actuation (EHA) nose landing gear system is a complex multi-domain system. in order to study the coupling characteristics of EHA system, a multi-domain simulation tool is needed. In this paper, a EHA block diagram based on extraction and retraction of nose landing gear is described and established from the mathematic model, and then completed the modeling and simulation of EHA system in Dymola. A controller of EHA system is exported as the Functional Mock-up Unit (FMU) model from Simulink to Dymola according to the Functional Mock-up Interface (FMI) standard.