MBSE WITHIN THE ENGINEERING DESIGN COMMUNITY – AN EXPLORATORY STUDY

One approach to tackle the complexity in the development of cyber-physical systems is system decomposition and modelling in a central system model with model-based system engineering (MBSE). However, MBSE also requires increased development effort due to the high degree of formalisation of the development results using the Systems Modelling Language (SysML). One solution is reusing system elements from model libraries, which requires formalization that allows them to be networked into consistent models. Due to the abstract nature of SysML, the options for formalizing system elements are extremely diverse, meaning that even identical technical system elements are modelled with a different structure by engineers. As a consequence, no standardized structure is maintained and the reuse of system elements from model libraries is very unlikely. This leads to high, redundant modelling efforts as well as a considerable error potential and significantly hinders the economic application of MBSE in mechanical engineering. A standardized structure of the system elements can be ensured through MBSE methodology specific modelling guidelines. Current modelling guidelines for MBSE are based on the SysMLv1 language standard and cannot be used unchanged in SysML v2. Nevertheless, SysML v2 offers great potential for modelling reusable system elements, especially with its synonymous textual and graphical modelling capabilities, enabling the easy linkage of knowledge from various domain-specific tools. Consequently, modelling guidelines based on SysML v2, which guarantee a standardized structure, are required to fully exploit the potential of model libraries in MBSE. To solve this deficit, this paper presents modelling guidelines based on SysML v2 and their application for building reusable system elements.

As Model-Based Systems Engineering (MBSE) was applied to the Electric Multiple Unit (EMU) braking system control logic, a preliminary exploration was conducted for bullet train braking system control logic research using an MBSE practice framework. The framework mainly includes the requirement analysis phase, functional analysis phase, and design phase. Systems Modeling Language (SysML) was used as the modeling language, and Cameo Systems Modeler (CSM) was employed as the modeling tool. By integrating the EMU braking system control logic and utilizing a top-down design approach, the implementation of MBSE in the bullet train braking system was analyzed and studied. The results show that, according to the MBSE practice framework, a unified description of the requirement analysis, functional analysis, and design synthesis of the EMU braking system control logic can be achieved. Additionally, the correlation and traceability between models can be established.

Integrating Analytical Models with Descriptive System Models: Implementation of the OMG SyML Standard for the Tool-specific Case of MapleSim and MagicDraw

An Integrated Intelligent Modeling and Simulation Language for Model-based Systems Engineering

Many of today‟s advanced simulation tools are suitable for modeling specific systems; however, they provide rather limited support for model building and management. Setting up a detailed vehicle simulation model requires more than writing down state equations and running them on a computer. In this paper, we describe how modern software techniques can be used to support modeling and design activities, with the objective of providing better system models more quickly by assembling these system models in a “plug-and-play” architecture. Instead of developing detailed models specifically for Argonne National Laboratory‟s Autonomie modeling tool, we have chosen to place emphasis on integrating and re-using the system models, regardless of the environment in which they were initially developed. By way of example, this paper describes a vehicle model composed of a detailed engine model from GT Power, a transmission from AMESim, and with vehicle dynamics from CarSim. The paper will explain the different options available for the interface and how each of these options can be implemented. It will use a simple case study to show how the detailed expert simulation models can be used with simpler Simulink models to address different vehicle design issues. INTRODUCTION One of the basic capabilities that an enterprise-wide modeling and simulation tool needs is to provide a framework for integrating models developed in different languages/tools. Because different expert tools have distinct advantages for modeling specific phenomena, numerous tools are used across companies, such as automotive original equipment manufacturers (OEMs). When these models are available, nevertheless the attempt to integrate them into a single environment to build an accurate system model is very onerous. As a result, most vehicle models used for analysis are usually based on steady-state look-up tables. The lack of a common framework to link such expert models results in isolated pockets of model-rich design groups. The open architecture of Autonomie [1, 2], a modeling tool developed by Argonne National Laboratory (Argonne) over the past four years in collaboration with General Motors (GM), supports the rapid integration and analysis of powertrain/propulsion systems and technologies for rapid technology sorting and evaluation of fuel economy improvement under dynamic/transient testing conditions. The tool, developed in the MathWorks environment, is based on a forward-looking model architecture. Its plug-and-play architecture provides a common framework in which expert tools can be linked to build detailed vehicle models. In this paper, we will explain how Autonomie is used to act as the interface between models developed with expert tool by taking the GT-Power engine model, AMESim transmission model, and CarSim vehicle dynamics models as examples. THE NEED FOR DETAILED SYSTEM MODELS Each type of model has its own advantages and disadvantages. While Simulink models based on simple look-up tables are easy to develop and use, they lack the ability to simulate the details of the plant‟s physical interactions. As a result, simple plant models cannot support control systems development. More detailed models are also needed to evaluate the effect of new technology. Different expert tools are available to meet such needs. It is far more practical to use those tools than to build and validate an equally detailed model in Simulink. While the detailed models add accuracy, the input data needed for those models are difficult to obtain, and the models run slower. Hence, engineers must switch between the detailed and simpler models depending on the analysis and what level of accuracy in the simulation results is desired. As shown in Fig. 1, Autonomie provides a convenient way to use models of appropriate fidelity by enabling a plug-and-play function with the models and by interfacing with expert system tools.

Systems modeling tools such as STELLA Research 7 for Windows are used in economics and ecosystem management, but their application to the tourism system at the local destination level has been little explored. This article uses STELLA Research 7 for Windows to examine the potential of dynamic systems modeling as a community destination planning tool. The conceptual and theoretical basis of systems modeling is explained, followed by an application of STELLA modeling in an undergraduate tourism impacts class. A basic model of Hardin's (1968) Tragedy of the Commons was developed as an example to illustrate how the systems-based software helps to address interrelationships between various components. This was then followed by a collaborative class project to develop aspects of a Tourism Management System (TMS) model with the help of STELLA. Student responses to a questionnaire administered subsequent to project completion indicates that systems-based modeling exhibits strong potential to be applied as a visual and process-based tool to facilitate (a) joint learning of the nature of tourism impacts at the destination level and (b) collaborative decision making on issues related to destination planning and management. Other benefits and limitations of this participatory modeling approach are provided in the article.

A Lift Dispatching System (LDS) is a typical real-time system that is highly complicated in design and implementation. This article presents the formal design, specification, and modeling of the LDS system using a denotational mathematics known as Real-Time Process Algebra (RTPA). The conceptual model of the LDS system is introduced as the initial requirements for the system. The architectural model of the LDS system is created using RTPA architectural modeling methodologies and refined by a set of Unified Data Models (UDMs). The static behaviors of the LDS system are specified and refined by a set of Unified Process Models (UPMs) for the lift dispatching and serving processes. The dynamic behaviors of the LDS system are specified and refined by process priority allocation and process deployment models. Based on the formal design models of the LDS system, code can be automatically generated using the RTPA Code Generator (RTPA-CG), or be seamlessly transferred into programs by programmers. The formal models of LDS may not only serve as a formal design paradigm of real-time software systems, but also a test bench of the expressive power and modeling capability of exiting formal methods in software engineering.

Making explicit domain knowledge in formal system development

Recent advances in high-throughput biotechnologies have led to the rapid growing research interest in reverse engineering of biomolecular systems (REBMS). 'Data-driven' approaches, i.e. data mining, can be used to extract patterns from large volumes of biochemical data at molecular-level resolution while 'design-driven' approaches, i.e. systems modeling, can be used to simulate emergent system properties. Consequently, both data- and design-driven approaches applied to -omic data may lead to novel insights in reverse engineering biological systems that could not be expected before using low-throughput platforms. However, there exist several challenges in this fast growing field of reverse engineering biomolecular systems: (i) to integrate heterogeneous biochemical data for data mining, (ii) to combine top-down and bottom-up approaches for systems modeling and (iii) to validate system models experimentally. In addition to reviewing progress made by the community and opportunities encountered in addressing these challenges, we explore the emerging field of synthetic biology, which is an exciting approach to validate and analyze theoretical system models directly through experimental synthesis, i.e. analysis-by-synthesis. The ultimate goal is to address the present and future challenges in reverse engineering biomolecular systems (REBMS) using integrated workflow of data mining, systems modeling and synthetic biology.

PurposeScience of systems requires a specific and constructive mathematical model and language, which describe jointly such systemic categories as adaptation, self‐organization, complexity, evolution, and bring the applied tools for building a system model for each specific object of a diverse nature. This formalism should be connected directly with a world of information and computer applications of systemic model, developed for a particular object. The considered information systems theory (IST) is aimed at building a bridge between the mathematical systemic formalism and information technologies to develop a constructive systemic model of revealing information regularities and specific information code for each object.Design/methodology/approachTo fulfill this goal and the considered systems' definition, the IST joins two main concepts: unified information description of interacted flows, initiated by the sources of different nature, with common information language and systems modeling methodology, applied to distinct interdisciplinary objects; general system's information formalism for building the model, which allows expressing mathematically the system's regularities and main systemic mechanisms.FindingsThe formalism of informational macrodynamics (IMD), based of the minimax variational principle, reveals the system model's main layers: microlevel stochastics, macrolevel dynamics, hierarchical dynamic network (IN) of information structures, its minimal logic, and optimal code of communication language, generated by the IN hierarchy, dynamics, and geometry. The system's complex dynamics originate information geometry and evolution with the functional information mechanisms of ordering, cooperation, mutation, stability, diversity, adaptation, self‐organization, and the double helix's genetic code.Practical implicationsThe developed IMD's theoretical computer‐based methodology and the software has been applied to such areas as technology, communications, computer science, intelligent processes, biology, economy, management, and other nonphysical and physical subjects.Originality/valueThe IMD's macrodynamics of uncertainties connect randomness and regularities, stochastic and determinism, reversibility and irreversibility, symmetry and asymmetry, stability and instability, structurization and stochastization, order and disorder, as a result of micro‐macrolevel's interactions for an open system, when the external environment can change the model's structure.

This paper is a further step towards application of the Model-Based Systems Engineering (MBSE) paradigm, using standardized, graphical, and executable system modeling languages. It presents further development of Modelica graphical Modeling Language (ModelicaML), a UML Profile for Modelica, which enables an integrated modeling and simulation of system requirements and design (for systems including both hardware and software). This approach combines the power of the OMG UML/SysML standardized graphical notation for system and software modeling, and the modeling and simulation power of Modelica. It facilitates the creation of executable system-specification and analysis models that can simulate time-discrete (or eventbased) and time-continuous system behavior.

Systems engineering is a transdisciplinary scientific and applied direction that combines the principles of a systems approach, methods, tools and standards that provide an integrated methodology and relevant technologies for the design and development of complex systems, their comprehensive analysis and verification, efficient and safe use. The modern approach to systems engineering is characterized by an accentuated modeling of systems throughout their life cycle with the ultimate goal of creating their digital twins. It is called model-based systems engineering (MBSE). Consistent integration of MBSE with software engineering leads to the formation of the MBSSE (Model-Based Systems and Software Engineering) direction. This textbook is devoted to this area, the main objective of which is to study the conceptual and scientific-methodological foundations of MBSE and MBSSE, models and methods of life cycle management of systems and software, basic standards of systems engineering, study and mastery of the UML and SysML systems modeling languages and the corresponding modeling tools, study of requirements engineering methods and development of a description of the system architecture, familiarization with the concept of digital twins and their role in MBSE, study of the MBSSE reference model and its relationship with the process standards of systems engineering, study of the methodological aspects of the system and software integration process. The final chapter of the textbook is devoted to the study of the mathematical foundations of systems engineering. The main aspects of the mathematical theory of systems by A. Wayne Wymore, which became an important stimulus for the development of the model-oriented approach in systems engineering, and modern research, including the apparatus of finite automata by David Harel, the formalism of modeling of discrete systems DEVS, research into category theory as a formal mathematical basis for model-based system design are considered. The authors recommend this course as a basic course for training IT professionals.

The monograph provides a detailed presentation of the main approaches to the creation of formalized descriptions of various objects, processes, and systems based on visual modeling tools. The evolution of visual models based on graph representations is examined. A classification of visual information modeling tools is presented. Information is provided on the principles of applying domain modeling methods based on formal visual modeling languages. The monograph may be useful to a wide range of readers, including experienced specialists in the field of information modeling of various processes, systems, and technologies.

This study deals with the formal modeling and verification of reconfigurable discrete event control systems (RDECSs). The behavior of an RDECS is represented by that of control components (CCs) and the communication among them. A new formalism, called Reconfigurable Timed Net Condition/Event Systems (TNCES) (R-TNCES), is proposed for the optimal functional and temporal specification of RDECS, which is defined by a behavior module and a control module. The former is a union of various superposed TNCESs, where TNCES-based CC modules are basic units. The latter is a set of reconfiguration functions dealing with the automatic transformations of these TNCESs in response to errors or user requirements by enabling or disabling CC modules, changing condition signals and/or event signals among them, and also treating the state feasibility before and after reconfigurations. To control the verification complexity of R-TNCES, a layer-by-layer verification method is developed, where the similarities of different TNCESs in the behavior module are considered. The contribution of this original paper is applied to a benchmark production system.

To cope with large data sets, distributed data stores partition their data across servers. However, real-world systems usually do not provide useful transactional semantics for operations accessing multiple partitions due to the delays involved in achieving multi-partition consistency. Read Atomic Multi-Partition (RAMP) transactions have recently been proposed as efficient light-weight multi-partition transactions that guarantee read atomicity: either all updates or no updates of a transaction are visible to other transactions. In this paper we formalize RAMP transactions in rewriting logic and perform model checking verification of key properties using the Maude tool. In particular, we develop detailed formal models---and formally analyze---a number of extensions and optimizations of RAMP that are only briefly mentioned by the RAMP developers.