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Electronics
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Tools and Languages for Object-Oriented Modeling and Simulation
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Tools and Languages for Object-Oriented Modeling and Simulation

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: closed (21 March 2021) | Viewed by 18735

Special Issue Editor

Prof. Dr. Peter Fritzson

E-Mail Website
Guest Editor
Department of Computer and Information Science, Linköpings University, SE-581 83 Linköping, Sweden
Interests: software engineering, especially programming languages; high-level specification and modeling languages; programming and debugging tools and environments; parallel and multicore computing, compilers and compiler generators; tools and languages for object-oriented equation-based modeling and simulation; Modelica language
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

During the past two decades, object-oriented model-based design of complex cyberphysical systems (which mix physical dynamics with software and networks) has gained significant attention. Hybrid modeling languages based on equations, supporting both continuous-time and event-based aspects (e.g., Modelica, SysML, VHDL-AMS, and Simulink/ Simscape) enable high-level reuse and integrated modeling capabilities of both the physically surrounding system and software for embedded systems.

This Special Issue on Tools and Languages for object-oriented modeling and simulation solicits papers in this area, including but not limited to the following subtopics: object-oriented modeling and simulation languages and tools, cyberphysical and multidomain system modeling and development, Industry 4.0, hardware modeling (electrical, hydraulic, multi-body systems, etc.), integrated hardware–software modeling, metamodeling (Modelica, UML, SysML, etc.), methods and standards for co-modeling and co-simulation (e.g. FMI, SSP, DCP), design optimization and sensitivity analysis, numeric and symbolic methods for simulation, parallel and distributed simulation, verification and validation, requirement modeling,  real-time and hardware-in-the-loop simulation, Internet of Things and embedded systems modeling, experiences of application of model-based product development, integration of machine learning models, and object-oriented systems modeling.

Prof. Dr. Peter Fritzson
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • object-oriented
  • equation-based
  • modeling
  • simulation
  • Industry 4.0
  • optimization
  • compilation
  • requirement validation and verification

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Published Papers (6 papers)

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Research

17 pages, 666 KiB  
Article
An Open-Source Many-Scenario Approach for Power System Dynamic Simulation on HPC Clusters
by Junjie Zhang, Lukas Razik, Sigurd Hofsmo Jakobsen, Salvatore D’Arco and Andrea Benigni
Electronics 2021, 10(11), 1330; https://doi.org/10.3390/electronics10111330 - 1 Jun 2021
Cited by 3 | Viewed by 2988
Abstract
In this paper we introduce an approach to accelerate many-scenario (i.e., hundreds to thousands) power system simulations which is based on a highly scalable and flexible open-source software environment. In this approach, the parallel execution of simulations follows the single program, multiple data [...] Read more.
In this paper we introduce an approach to accelerate many-scenario (i.e., hundreds to thousands) power system simulations which is based on a highly scalable and flexible open-source software environment. In this approach, the parallel execution of simulations follows the single program, multiple data (SPMD) paradigm, where the dynamic simulation program is executed in parallel and takes different inputs to generate different scenarios. The power system is modeled using an existing Modelica library and compiled to a simulation executable using the OpenModelica Compiler. Furthermore, the parallel simulation is performed with the aid of a message-passing interface (MPI) and the approach includes dynamic workload balancing. Finally, benchmarks with the simulation environment are performed on high-performance computing (HPC) clusters with four test cases. The results show high scalability and a considerable parallel speedup of the proposed approach in the simulation of all scenarios. Full article
(This article belongs to the Special Issue Tools and Languages for Object-Oriented Modeling and Simulation)
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21 pages, 1409 KiB  
Article
An Integrated Framework for Traceability and Impact Analysis in Requirements Verification of Cyber–Physical Systems
by Alachew Mengist, Lena Buffoni and Adrian Pop
Electronics 2021, 10(8), 983; https://doi.org/10.3390/electronics10080983 - 20 Apr 2021
Cited by 8 | Viewed by 3420
Abstract
In the field of model-based design of Cyber–Physical Systems (CPS), seamless traceability of the process, from requirements to models to simulation results, is becoming increasingly important. It can be used to support several activities such as variant handling, impact analysis, component reuse, software [...] Read more.
In the field of model-based design of Cyber–Physical Systems (CPS), seamless traceability of the process, from requirements to models to simulation results, is becoming increasingly important. It can be used to support several activities such as variant handling, impact analysis, component reuse, software maintenance and evolution, verification, and validation. Despite the fact that the relevance of traceability in the model-based design of CPSs is well known, current tools that support traceability management are inadequate in practice. The lack of comprehensive whole-lifecycle systems engineering support in a single tool is one of the main causes of such ineffective traceability management, where traceability relationships between artifacts are still manually generated and maintained. This paper aims at presenting an approach and a prototype for automatically generating and maintaining the appropriate traceability links between heterogeneous artifacts ranging from requirement models, through design models, down to simulation and verification results throughout the product life cycle in model-based design of CPSs. A use case study is presented to validate and illustrate the proposed method and prototype. Full article
(This article belongs to the Special Issue Tools and Languages for Object-Oriented Modeling and Simulation)
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30 pages, 3101 KiB  
Article
Open Source Languages and Methods for Cyber-Physical System Development: Overview and Case Studies
by Lena Buffoni, Lennart Ochel, Adrian Pop, Peter Fritzson, Niklas Fors, Görel Hedin, Walid Taha and Martin Sjölund
Electronics 2021, 10(8), 902; https://doi.org/10.3390/electronics10080902 - 10 Apr 2021
Cited by 8 | Viewed by 4816
Abstract
Industrial cyber-physical system products interleave hardware, software, and communication components. System complexity is increasing simultaneously with increased demands on quality and shortened time-to-market. To effectively support the development of such systems, we present languages and tools for comprehensive integrated model-based development that cover [...] Read more.
Industrial cyber-physical system products interleave hardware, software, and communication components. System complexity is increasing simultaneously with increased demands on quality and shortened time-to-market. To effectively support the development of such systems, we present languages and tools for comprehensive integrated model-based development that cover major phases such as requirement analysis, design, implementation, and maintenance. The model-based approach raises the level of abstraction and allows to perform virtual prototyping by simulating and optimizing system models before building physical products. Moreover, open standards and open source implementations enable model portability, tool reuse and a broader deployment. In this paper we present a general overview of the available solutions with focus on Modelica/OpenModelica, Bloqqi, and Acumen. The paper presents contributions to these languages and environments, including symbolic-numeric modeling, requirement verification, code generation, model debugging, design optimization, graphical modeling, and variant handling with traceability, as well a general discussion and conclusions. Full article
(This article belongs to the Special Issue Tools and Languages for Object-Oriented Modeling and Simulation)
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24 pages, 411 KiB  
Article
Modular Compilation for a Hybrid Non-Causal Modelling Language
by Guerric Chupin and Henrik Nilsson
Electronics 2021, 10(7), 814; https://doi.org/10.3390/electronics10070814 - 30 Mar 2021
Viewed by 1799
Abstract
Non-causal modelling is a powerful approach to modelling physical systems in a variety of domains from science and engineering. Non-causal modelling languages enable a high-level and modular approach to modelling. However, it is hard to compile non-causal languages modularly (in the sense of [...] Read more.
Non-causal modelling is a powerful approach to modelling physical systems in a variety of domains from science and engineering. Non-causal modelling languages enable a high-level and modular approach to modelling. However, it is hard to compile non-causal languages modularly (in the sense of separate compilation). This causes difficulties when simulating large models for which code generation takes a long time, or structurally singular models in which parts of the model are allowed to change at runtime. In this work, we introduce a technique we call order-parametric differentiation to allow truly modular compilation. The idea is to generate (machine) code that can compute derivatives of any order of an expression as needed, thus allowing for ahead-of-time modular compilation of a hybrid non-causal language. We also develop a compilation scheme that enables using partial models as first-class objects in a seamless way and simulating them without the need for just-in-time compilation, even in the presence of structural dynamism. We present a performance evaluation of the scheme we used and study its shortcomings and possible improvements, demonstrating that it is a feasible complement to existing implementation techniques for cases where true modular compilation is a primary objective. Full article
(This article belongs to the Special Issue Tools and Languages for Object-Oriented Modeling and Simulation)
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26 pages, 1036 KiB  
Article
ProMECoS: A Process Model for Efficient Standard-Driven Distributed Co-Simulation
by Martin Krammer, Clemens Schiffer and Martin Benedikt
Electronics 2021, 10(5), 633; https://doi.org/10.3390/electronics10050633 - 9 Mar 2021
Cited by 6 | Viewed by 2622
Abstract
Co-simulation techniques have evolved significantly over the last 10 years. System simulation and hardware-in-the-loop testing are used to develop innovative products in many industrial sectors. Despite the success of these simulation techniques, their efficient application requires a systematic approach. In practice the integration [...] Read more.
Co-simulation techniques have evolved significantly over the last 10 years. System simulation and hardware-in-the-loop testing are used to develop innovative products in many industrial sectors. Despite the success of these simulation techniques, their efficient application requires a systematic approach. In practice the integration and coupling of heterogeneous systems still require enormous efforts. At this point in time no unified process for integration and simulation of DCP-based co-simulation scenarios is available. In this article we present ProMECoS, a process model for efficient, standard-driven distributed co-simulation. It defines the necessary tasks required to prepare, instantiate and execute distributed co-simulations according to the DCP standard. Furthermore, it enables the exploitation of front-loading benefits, thus reducing the overall system development effort. ProMECoS is based on the IEEE 1730 standard for Distributed Simulation Engineering and Execution Process. It adopts the artefacts of the DCP specification, and defines additional process artefacts. The DCP specification and its associated default integration methodology were developed by a balanced consortium in context of the ITEA 3 project ACOSAR. The DCP is compatible to the well-adopted FMI standard. Therefore both standards can be used together for seamless development using models, software, and real components. ProMECoS provides the necessary guidance for efficient product development and testing. Full article
(This article belongs to the Special Issue Tools and Languages for Object-Oriented Modeling and Simulation)
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14 pages, 4165 KiB  
Article
Provision of Data to Use in Artificial Intelligence Algorithms for Single Room Heating
by Kristin Majetta, Christoph Clauß and Christoph Nytsch-Geusen
Electronics 2021, 10(4), 523; https://doi.org/10.3390/electronics10040523 - 23 Feb 2021
Cited by 1 | Viewed by 1852
Abstract
This paper describes a way to generate a great amount of data and to use it to find a relation between a room controller and a certain room. Therefore, simulation scenarios are defined and developed that contain different room, location, usage and controller [...] Read more.
This paper describes a way to generate a great amount of data and to use it to find a relation between a room controller and a certain room. Therefore, simulation scenarios are defined and developed that contain different room, location, usage and controller models. With parameter variation and optimization of the corresponding controller parameters a data basis is created with about 5300 entries. On the basis of this data, machine learning algorithms like artificial neural networks can be used to investigate the relation between rooms and their best suited controllers. Full article
(This article belongs to the Special Issue Tools and Languages for Object-Oriented Modeling and Simulation)
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