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The paper presents a novel approach for reducing the co‐simulation interface representation between multiple large‐scale models. The methodology leverages model order reduction through component mode synthesis in some specific small deformation flexible multibody formulations that yield a constant transformation matrix between Cartesian coordinates and general multibody coordinates, such as the flexible natural coordinates formulation or the generalized component mode synthesis. The constant transformation matrix stemming from these techniques is further modified using modified Gram–Schmidt orthonormalization and the effective independence methodology to create a constant interface model reduction matrix. This matrix effectively connects a minimal set of interface nodes to the entire nodal domain, while simultaneously projecting the forces acting on the entire nodal domain onto the interface nodes. Notably, the proposed methodology scales the size of the required co‐simulation interface representation with the considered set of mode shapes rather than the size of the numerical finite element mesh. This co‐simulation interface model reduction strategy not only renders large distributed load models compatible with the Functional Mock‐Up Interface but also extends its applicability to any structural model beyond the flexible multibody scope, provided that deformations remain relatively small. Numerical validation with a simply supported beam, connected to springs at each node, demonstrates that the interface model reduction error is significantly smaller than the co‐simulation error. This suggests that substantial interface model reduction can be achieved without compromising accuracy. Moreover, additional numerical validation performed with a rotor‐drum model showcases the versatility and scalability of the proposed approach, particularly in addressing dynamic structural systems. [ABSTRACT FROM AUTHOR]

This article describes recent co-simulation advances for the simultaneous modeling of detailed building electrical distribution systems and whole-building energy performance. The co-simulation architecture combines the EnergyPlus® engine for whole-building energy modeling with a new Modelica library for building an electrical distribution system model that is based on harmonic power flow. This new library allows for a higher-fidelity modeling of electrical power flows and losses within buildings than is available with current building electrical modeling software. We demonstrate the feasibility of the architecture by modeling a simple, two-zone thermal chamber with internal power electronics converters and resistive loads, and we validate the model using experimental data. The proposed co-simulation capability significantly expands the capabilities of building electrical distribution system models in the context of whole-building energy modeling, thus enabling more complex analyses than would have been possible with individual building performance simulation tools that are used to date.

Currently, innovations in mechatronic products often occur at the system level, requiring consideration of component interactions throughout the entire development process. In the earlier phases of development, this is accomplished by coupling virtual prototypes such as simulation models. As the development progresses and real prototypes of certain system components become available, real-virtual prototypes (RVPs) are established with the help of network communication. However, network effects—all of which can be interpreted as latencies in simplified terms—distort the system behavior of RVPs. To reduce these distortions, we propose a coupling method for RVPs that compensates for latencies. We present an easily applicable approach by introducing a generic coupling algorithm based on error space extrapolation. Furthermore, we enable online learning by transforming coupling algorithms into feedforward neural networks. Additionally, we conduct a frequency domain analysis to assess the impact of coupling faults and algorithms on the system behavior of RVPs and derive a method for optimally designing coupling algorithms. To demonstrate the effectiveness of the coupling method, we apply it to a hybrid vehicle that is productively used as an RVP in the industry. We show that the optimally designed and trained coupling algorithm significantly improves the credibility of the RVP. [ABSTRACT FROM AUTHOR]

This paper presents the development of a wind energy conversion system co-simulation based on the Functional Mock-up Interface standard aiming at contributing to the development of co-simulation of large electrical power systems by means of open-source and standardized computational tools. Co-simulation enables the computational burden of a monolithic simulation to be shared among several processing units, significantly reducing processing time. Through the Functional Mock-up Interface standard, developed models are encapsulated into Functional Mock-up Unit, providing an extra means for the protection of intellectual property, a very appealing feature for end users, both in industry and academia. To achieve the decoupling of the subsystems, the Bergeron ideal transmission line model will be used, with travel time equal to the simulation time-step. The computational performance and effectiveness of the proposed co-simulation technique was evaluated with a wind power plant with 50 wind turbines. The system digital models were developed into Modelica language, while co-simulation was implemented in Python. [ABSTRACT FROM AUTHOR]

In this work, we introduce a novel approach to model the rain and fog effect on the light detection and ranging (LiDAR) sensor performance for the simulation-based testing of LiDAR systems. The proposed methodology allows for the simulation of the rain and fog effect using the rigorous applications of the Mie scattering theory on the time domain for transient and point cloud levels for spatial analyses. The time domain analysis permits us to benchmark the virtual LiDAR signal attenuation and signal-to-noise ratio (SNR) caused by rain and fog droplets. In addition, the detection rate (DR), false detection rate (FDR), and distance error  d e r r o r  of the virtual LiDAR sensor due to rain and fog droplets are evaluated on the point cloud level. The mean absolute percentage error (MAPE) is used to quantify the simulation and real measurement results on the time domain and point cloud levels for the rain and fog droplets. The results of the simulation and real measurements match well on the time domain and point cloud levels if the simulated and real rain distributions are the same. The real and virtual LiDAR sensor performance degrades more under the influence of fog droplets than in rain. [ABSTRACT FROM AUTHOR]

The increased integration of distributed energy resources (DERs) is bringing a number of challenges to the power grid. These include reverse power flows in distribution systems and potentially transmission systems and grid stability. So far, specialized tools have been developed to capture some of the impact of DERs at the distribution level. However, distribution system operators lack visibility into the overall system conditions. Furthermore, the impact of increasing DERs is not limited to the distribution level but also influences the transmission grid. To support the planning and operation of the grid, we developed a co-simulation platform called CyDER (A Cyber Physical Co-simulation Platform for Distributed Energy Resources in Smart Grids) that integrates various domain-specific simulation tools. CyDER is based on the functional mock-up interface standard. This paper gives an overview of CyDER and demonstrates its use based on two applications.

Measurement performance evaluation of real and virtual automotive light detection and ranging (LiDAR) sensors is an active area of research. However, no commonly accepted automotive standards, metrics, or criteria exist to evaluate their measurement performance. ASTM International released the ASTM E3125-17 standard for the operational performance evaluation of 3D imaging systems commonly referred to as terrestrial laser scanners (TLS). This standard defines the specifications and static test procedures to evaluate the 3D imaging and point-to-point distance measurement performance of TLS. In this work, we have assessed the 3D imaging and point-to-point distance estimation performance of a commercial micro-electro-mechanical system (MEMS)-based automotive LiDAR sensor and its simulation model according to the test procedures defined in this standard. The static tests were performed in a laboratory environment. In addition, a subset of static tests was also performed at the proving ground in natural environmental conditions to determine the 3D imaging and point-to-point distance measurement performance of the real LiDAR sensor. In addition, real scenarios and environmental conditions were replicated in the virtual environment of a commercial software to verify the LiDAR model's working performance. The evaluation results show that the LiDAR sensor and its simulation model under analysis pass all the tests specified in the ASTM E3125-17 standard. This standard helps to understand whether sensor measurement errors are due to internal or external influences. We have also shown that the 3D imaging and point-to-point distance estimation performance of LiDAR sensors significantly impacts the working performance of the object recognition algorithm. That is why this standard can be beneficial in validating automotive real and virtual LiDAR sensors, at least in the early stage of development. Furthermore, the simulation and real measurements show good agreement on the point cloud and object recognition levels. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

This paper presents an overview and formalization of the Functional Mock-up Interface (FMI) 3.0. The formalization captures the new FMI 3.0 standard and is intended to be used as an introduction for conceptualizing the use of clocks in the FMI standard to support the simulation of event-based cyber-physical systems. The FMI 3.0 standard supports two kinds of clock-based simulations: Synchronous Clocked Simulation to ensure predictable systems scheduling with multiple simultaneous events and scheduled execution to facilitate real-time simulations comprising multiple black-box models by allowing fine-grained control over the computation time of submodels. The formalization is a basis for developing tools for orchestrating, verifying and validating the composition of multiple FMUs. The formalization is provided as an accessible VDM-SL specification. [ABSTRACT FROM AUTHOR]

This work introduces a process to develop a tool-independent, high-fidelity, ray tracing-based light detection and ranging (LiDAR) model. This virtual LiDAR sensor includes accurate modeling of the scan pattern and a complete signal processing toolchain of a LiDAR sensor. It is developed as a functional mock-up unit (FMU) by using the standardized open simulation interface (OSI) 3.0.2, and functional mock-up interface (FMI) 2.0. Subsequently, it was integrated into two commercial software virtual environment frameworks to demonstrate its exchangeability. Furthermore, the accuracy of the LiDAR sensor model is validated by comparing the simulation and real measurement data on the time domain and on the point cloud level. The validation results show that the mean absolute percentage error (M A P E) of simulated and measured time domain signal amplitude is 1.7 % . In addition, the M A P E of the number of points N p o i n t s and mean intensity I m e a n values received from the virtual and real targets are 8.5 % and 9.3 % , respectively. To the author's knowledge, these are the smallest errors reported for the number of received points N p o i n t s and mean intensity I m e a n values up until now. Moreover, the distance error d e r r o r is below the range accuracy of the actual LiDAR sensor, which is 2 cm for this use case. In addition, the proving ground measurement results are compared with the state-of-the-art LiDAR model provided by commercial software and the proposed LiDAR model to measure the presented model fidelity. The results show that the complete signal processing steps and imperfections of real LiDAR sensors need to be considered in the virtual LiDAR to obtain simulation results close to the actual sensor. Such considerable imperfections are optical losses, inherent detector effects, effects generated by the electrical amplification, and noise produced by the sunlight. [ABSTRACT FROM AUTHOR]

Simulation is an important tool to support rail decarbonisation but can be challenging due to heterogeneous models, simulation tools and skill sets, and concerns around intellectual property. Multi-modelling, a proven methodology in sectors such as aerospace and automotive, uses Functional Mock-up Interface (FMI) and co-simulation to potentially overcome these problems. This paper presents a feasibility study of multi-modelling for rail decarbonisation, using a combination of audit of current state of the art, technical implementation and stakeholder consultation. The audit showed that while current uptake of FMI in rail is low, there is potential to repurpose models from pre-existing tools and apply them within multi-modelling. The technical feasibility assessment demonstrated how multi-modelling could generate flexible simulation outputs to identify decarbonisation systems effects both for urban and mainline rail, including rapid integration of pre-existing MATLAB Simulink models. Work with industry stakeholders identified use cases where multi-modelling would benefit rail decarbonisation, as well as barriers and enablers to adoption. Overall, the study demonstrates the feasibility and considerations for multi-modelling to support rail decarbonisation efforts, and the future developments necessary for wider rollout. [ABSTRACT FROM AUTHOR]

Digital twin is a technology that facilitates a real-time coupling of a cyber–physical system and its virtual representation. The technology is applicable to a variety of domains and facilitates more intelligent and dependable system design and operation, but it relies heavily on the existence of digital models that can be depended upon. In realistic systems, there is no single monolithic digital model of the system. Instead, the system is broken into subsystems, with models exported from different tools corresponding to each subsystem. In this paper, we focus on techniques that can be used for a black-box model, such as the ones implementing the Functional Mock-up Interface (FMI) standard, formal analysis, and verification. We propose two techniques for simulation-based reachability analysis of models. The first one is based on system dynamics, while the second one utilizes dynamic sensitivity analysis to improve the quality of the results. Our techniques employ simulations to obtain the model’s sensitivity with respect to the initial state (or model’s Lipschitz constant) which is then used to compute reachable states of the system. The approaches also provide probabilistic guarantees on the accuracy of the computed reachable sets that are based on simulations. Each technique requires different levels of information about the black-box system, allowing the readers to select the best technique according to the capabilities of the models. The validation experiments have demonstrated that our proposed algorithms compute accurate reachable sets of stable and unstable linear systems. The approach based on dynamic sensitivity provides an accurate and, with respect to system dimensions, more scalable approach, while the sampling-based method allows a flexible trade-off between accuracy and runtime cost. The validation results also show that our approaches are promising even when applied to nonlinear systems, especially, when applied to larger and more complex systems. The reproducibility package with code and data can be found at https://github.com/twright/FMI-Reachability-Reproducibility. [ABSTRACT FROM AUTHOR]

Increasing system complexity requires adapted methodologies to tackle the challenges that come along with multi-domain systems development. Model-Based Systems Engineering (MBSE) provides significant support by using models to describe different aspects of an examined system already in the early stages of the development process. The Systems Modeling Language (SysML) can be utilized to establish a common system information basis on a comparatively abstract level for all participating stakeholders. Although SysML models are able to encompass system information like requirements, structure, behaviour and parametrics, in many cases additional specialized simulation or computation models are needed, especially for early design decision-making and verification activities. Ideally, the input data and the calculated results are automatically exchanged between the SysML modelling editor and the involved simulation tools. Hence, tool chain integration is a crucial factor to provide the necessary interconnectivity to achieve multi-domain simulation. In general, the integration of simulation environments with SysML tools is mainly limited by two factors. First, as the tools available for modelling with SysML are legion, interface solutions are usually developed for a specific tool and therefore, their usage is restricted to that particular software. Second, evolving standards like the Functional Mock-up Interface (FMI) provide capabilities to ease model data exchange and co-simulation, but the implementation of different versions of various standards in the tools causes incompatibilities. In this work a state of the art of the integration between simulation environments and available SysML modelling tools with respect to utilized standards and their implementation maturity is presented. Additionally, the capabilities of the reviewed tools to support co-simulation are evaluated. Furthermore, existing challenges are highlighted, and potential improvements are discussed. [ABSTRACT FROM AUTHOR]

Various development and validation methods for cyber-physical systems such as Controller-Hardware-in-the-Loop (C-HIL) testing strongly benefit from a seamless integration of (hardware) prototypes and simulation models. It has been often demonstrated that linking discrete event-based control systems and hybrid plant models can advance the quality of control implementations. Nevertheless, high manual coupling efforts and sometimes spurious simulation artifacts such as glitches and deviations are observed frequently. This work specifically addresses these two issues by presenting a generic, standard-based infrastructure referred to as virtual component, which enables the efficient coupling of simulation models and automation systems. A novel soft real-time coupling algorithm featuring event-accurate synchronization by extrapolating future model states is outlined. Based on considered standards for model exchange (FMI) and controls (IEC 61499), important properties such as real-time capabilities are derived and experimentally validated. Evaluation demonstrates that virtual components support engineers in efficiently creating C-HIL setups and that the novel algorithm can feature accurate synchronization when conventional approaches fail. [ABSTRACT FROM AUTHOR]

This paper investigates the use of the Functional Mock-up Interface (FMI) for code coupling in nuclear engineering. The FMI is a standard that defines a container and an interface to exchange dynamic simulation models. It has been developed and refined by several actors over the past two decades. This coupling standard allows seamless integrations of independent objects called Functional Mock-up Units (FMU). Since communication among FMUs is standardized, encapsulating a simulation tool and model within an FMU allows this tool and model to be coupled with any other FMU. This approach is opposed to creating dedicated code-to-code coupling interfaces and enables a more sustainable approach to code coupling in nuclear engineering. The paper showcases the utilization of the FMI standard for the simulation of an operational load-follow scenario in a Lead-cooled Fast Reactor. The primary circuit and balance of the plant are modeled using higher and lower-fidelity codes, respectively, with a third tool employed to model a simplified control system. The paper investigates the pros and cons of the proposed approach by exercising it throughout the following workflow: incorporation of the FMI standard into an existing code; setting up of models using different codes; coupling of these codes based on different architectures; simulation and post-processing of results. As an outcome, implementing an FMI interface presents itself as a judicious long-term investment for simulation software. However, users and developers should be aware of the limited FMI capabilities for the coupling of partial differential equations. In addition, a coupling standard by itself cannot address some difficulties, such as simulation restart, that are associated with the handling of a heterogeneous set of tools. [ABSTRACT FROM AUTHOR]

State-of-the-art Modelica tools for modelling and simulating multi-physical systems have reached certain maturity among the building physics community. Hence, simulation is widely used for control, sizing and performance assessment of energy systems. However, serious efficiency issues arise for large-scale models. This article proposes a practical application of co-simulation methods on detailed district energy systems. The aim of this study is to assess performance and scalability of co-simulation through functional mock-up interfaces on a detailed and multi-physical district model. In particular, we propose a comparative analysis between classical simulation and co-simulation methods and a scalability analysis on a growing number of buildings. The models have been implemented using Modelica language and the OpenIDEAS library. A decomposition approach is taken for modelling the entire system, while stochasticity in the inputs is taken into account. Results are presented for various integration scenarios, including a classical integrated simulation for reference and co-simulations involving different master-algorithms within Dymola and DACCOSIM 2017. Scenarios are compared in terms of speed-up and accuracy of principal physical quantities representing key performance indicators such as indoor temperature, current and voltage at building's connection. The analysis shows that co-simulation can run up to 90 times faster than the integrated simulation for 24 buildings, while ensuring acceptable accuracy. [ABSTRACT FROM AUTHOR]

Model-based design methodologies are commonly used in industry for the development of complex cyber-physical systems (CPSs). There are many different languages, tools, and formalisms for model-based design, each with its strengths and weaknesses. Instead of accepting some weaknesses of a particular tool, an alternative is to embrace heterogeneity, and to develop tool integration platforms and protocols to leverage the strengths from different environments. A fairly recent attempt in this direction is the functional mock-up interface (FMI) standard that includes support for co-simulation. Although this standard has reached acceptance in industry, it provides only limited support for simulating systems that mix continuous and discrete behavior, which are typical of CPS. This paper identifies the representation of time as a key problem, because the FMI representation does not support well the discrete events that typically occur at the cyber-physical boundary. We analyze alternatives for representing time in hybrid co-simulation and conclude that a superdense model of time using integers only solves many of these problems. We show how an execution engine can pick an adequate time resolution, and how disparities between time representations internal to co-simulated components and the resulting effects of time quantization can be managed. We propose a concrete extension to the FMI standard for supporting hybrid co-simulation that includes integer time, automatic choice of time resolution, and the use of absent signals. We explain how these extensions can be implemented modularly within the frameworks of existing simulation environments. [ABSTRACT FROM AUTHOR]

Abstract Cyber-Physical Systems (CPSs) often operate in a critical context where it is crucial that they behave as intended. However, the heterogeneous nature of CPSs makes them inherently challenging to develop. To assist in the development process, one can perform co-simulation, where models of constituents of a CPS are coupled to jointly simulate the full system. The challenge herein is to combine heterogeneous formalisms in a sound fashion and address practical needs such as stability, performance, platform compatibility and so forth. To address this, Maestro is a tool for co-simulation using models adhering to the Functional Mock-up Interface standard for co-simulation. Its development was driven by needs from different industry domains such as railways, agriculture, building automation and automotive. It supports both a fixed and variable constraint-based iteration scheme along with platform distribution capabilities. The tool is open-source as an attempt to increase adoption of co-simulation and encourage researchers to collaborate. Maestro has been validated by industry through application in the aforementioned domains. It is a step in the direction of the two-folded long-term goals: ensure trustworthy co-simulation results and make co-simulation a technology taken for granted. [ABSTRACT FROM AUTHOR]

Abstract The conventional design methods for tracked walking systems of large hydraulic excavators based on empirical formulas, does not take into account the dynamic load of the track. As such, a safety margin factor has to be adopted to ensure adequate working strength. However, the machine weight will be increased, and the hydraulic system will be overmatched. To address this design issue, an electromechanical–hydraulic design approach based on co-simulation is proposed in this study. The proposed design approach consists of four parts, namely, 1) a terramechanics model of the track that considers the pressure–sinkage relationship and soil shear stress of the individual tracked plate, 2) a tracked multibody dynamics (MBD) model that considers the intermittent transmission between the sprocket and the tracks, 3) the hydraulic systems model, and 4) the data communication interface. To demonstrate the proposed approach, it was used to design a large hydraulic excavator with a bucket capacity of 15 m3. Experimental results from the prototype showed that the proposed design principle can accurately reflect the impact load and periodic torque fluctuations on the track. The maximum error between the simulated and experimental results is 5.4% in forward walking and 12.7% in backward walking, thus demonstrating the effectiveness and accuracy of the proposed design approach. Graphical abstract Unlabelled Image Highlights • A co-simulation design method for ultra-large tracked walking systems is proposed. • Dynamic intermittent transmission pair and terramechanics are considered. • Interactions among track, excavator structure and hydraulic system are considered. • Dynamic load and periodical fluctuation are reflected accurately in the method. • The test verifies the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

This Paper introduces a mission profile-based and simulation-driven framework for creating digital twins, by combining different modeling techniques into an integrated model of a complex electronic system used in automotive and railway applications. It envisages monitoring, diagnostics and prognostic of the condition, degradation or abnormalities in the electronic system's behaviour in the field. Furthermore, this work contributes towards the development of digital twins by adding black-box modules to the main simulation models, which can be achieved by employing the functional mock-up interface toolbox. The key features and functionalities of this approach for the simulation of digital twins will be also highlighted in this work. This approach is applied on a common example circuit, a full wave bridge rectifier, whose model is implemented and simulated in Modelica 1 1 Modelica® and Python® are registered trademarks. Modelica®, Matlab/Simulink® and Ansys Twin Builder® are registered trademarks.. Moreover, the functionality of the investigated circuit, as well as the degradation behaviour under variable external thermal as well as electrical loads, is demonstrated with the help of automated parametric studies performed within Python+. Finally, the framework is verified using the functional test structure of the full wave diode bridge rectifier. • Open source Mission profile-based digital twin framework • Multi-domain system level modeling for assessing system's degradation behaviour • Functional mock-up interface and mission profile-based simulation [ABSTRACT FROM AUTHOR]

Various development and validation methods for cyber-physical systems such as Controller-Hardware-in-the-Loop (C-HIL) testing strongly benefit from a seamless integration of (hardware) prototypes and simulation models. It has been often demonstrated that linking discrete event-based control systems and hybrid plant models can advance the quality of control implementations. Nevertheless, high manual coupling efforts and sometimes spurious simulation artifacts such as glitches and deviations are observed frequently. This work specifically addresses these two issues by presenting a generic, standard-based infrastructure referred to as virtual component, which enables the efficient coupling of simulation models and automation systems. A novel soft real-time coupling algorithm featuring event-accurate synchronization by extrapolating future model states is outlined. Based on considered standards for model exchange (FMI) and controls (IEC 61499), important properties such as real-time capabilities are derived and experimentally validated. Evaluation demonstrates that virtual components support engineers in efficiently creating C-HIL setups and that the novel algorithm can feature accurate synchronization when conventional approaches fail.

A cyber physical system (CPS) is a distributed control system in which the cyber part and physical part are tightly interconnected. A representative CPS is an electric vehicle (EV) composed of a complex system and information and communication technology (ICT), preliminary verified through simulations for performance prediction and a quantitative analysis is essential because an EV comprises a complex CPS. This paper proposes an FMI-based distributed CPS simulation framework (F-DCS) adopting a redundancy reduction algorithm (RRA) for the validation of EV simulation. Furthermore, the proposed algorithm was enhanced to ensure an efficient simulation time and accuracy by predicting and reducing repetition patterns involved during the simulation progress through advances in the distributed CPS simulation. The proposed RRA improves the simulation speed and efficiency by avoiding the repeated portions of a given driving cycle while still maintaining accuracy. To evaluate the performance of the proposed F-DCS, an EV model was simulated by adopting the RRA. The results confirm that the F-DCS with RRA efficiently reduced the simulation time (over 30%) while maintaining a conventional accuracy. Furthermore, the proposed F-DCS was applied to the RRA, which provided results reflecting real-time sensor information.

Maximizing energy conservation, improving energy efficiency and integration and control of renewable energy sources are critical in order to achieve a low carbon future. An integrated modelling system is needed to evaluate and improve energy performance of urban energy systems’ design and operation, from both financial and environmental perspectives. To this end, this paper presents an urban energy co-simulation framework. It is based on co-simulation standard Functional Mock-up Interface (FMI) and CityGML-based semantic 3D city model and utilized programing packages, like PyFMI, FMILibrary, and mosaik, which is capable of orchestrating the execution of dynamic simulation models supporting the for co-simulation. To demonstrate the proof of concept, two simulation tools are coupled in the first instance: EnergyPlus and No-MASS. Based on the two use cases, the principles and workflow of the framework and results from its application are described. Results from use cases show that synchronization and interaction between our urban energy co-simulation framework and coupled co-simulation components works as intended. The paper concludes by discussing strategies to tackle more complex and multiscale energy systems. [ABSTRACT FROM AUTHOR]

This paper addresses a co-simulation method for fluid power driven machinery equipment, i.e. oil hydraulic machinery. In these types of machinery, the fluid-structure interaction affects the end-product performance to a large extent, hence an efficient co-simulation method is of high importance. The proposed method is based on a 1D system model representing the fluid components of the hydraulic machinery, within which structural 3D Finite Element (FE) models can be incorporated for detailed simulation of specific sub-models or complete structural assemblies. This means that the fluid system simulation will get a more accurate structural response, and that the structural simulation will get more correct fluid loads at every time step, compared to decoupled analysis. Global system parameters such as fluid flow, performance and efficiency can be evaluated from the 1D system model simulation results. From the 3D FE-models, it is possible to evaluate displacements, stresses and strains to be used in stress analysis, fatigue evaluation, acoustic analysis, etc. The method has been implemented using two well-known simulation tools for fluid power system simulations and FE-simulations, respectively, where the interface between the tools is realised by use of the Functional Mock-up Interface standard. A simple but relevant model is used to validate the method. [ABSTRACT FROM AUTHOR]

Hybrid systems such as Cyber Physical Systems (CPS) are becoming more important with time. Apart from CPS there are many hybrid systems in nature. To perform a simulation based analysis of a hybrid system, a simulation framework is presented, named SAHISim. It is based on the most popular simulation interoperability standards, i.e. High Level Architecture (HLA) and Functional Mock-up Interface (FMI). Being a distributed architecture it is able to execute on cluster, cloud and other distributed topologies. Moreover, as it is based on standards so it allows many different simulation packages to interoperate, making it a flexible and robust solution for simulation based analysis. The underlying algorithm which enables the synchronization of different simulation components is discussed in detail. A test example is presented, whose results are compared to a monolithic simulation of the same model for verification of results.

Today's increasing use of Virtual Commissioning during the development process of automated manufacturing plants paired with the increasing request towards better control quality leads to the need of improved virtual plants with more effortless set ups. The common techniques of simulating the plant within Virtual Commissioning do no longer fulfil these needs, new approaches have to be developed. This paper examines ways to standardize Functional Mock-Up Unit based behaviour models of mechatronic components of such automated manufacturing plants. It is argued how such components can be classified to reach a distinction between different types to be able to develop standardized interfaces for every type. Therefore a standardized framework of how these interfaces can look like is proposed. Based on this framework as well as the classification of the components two examples, a pneumatic valve cylinder combination and an industrial robot are exemplarily implemented. Besides the standard interfaces to the control program and the visualisation of the simulation a special effort to implement energetically considerations were made. Therefore the presented work shows a way of how to standardize the interfaces of behaviour models of different classes of mechatronic components while increasing the quality of these behaviour models for more complex and accurate behaviour simulation of production plants for Virtual Commissioning as well as related applications. [ABSTRACT FROM AUTHOR]