Communication of Simulation and Modelling Activities in Early Systems Engineering

In this paper we present a framework that aids and supports communication of modeling and simulation activities in early systems engineering. We do this by analyzing existing simulation and modelling frameworks, both in systems engineering as well as more generic frameworks. For each framework, we discuss its purpose, main outcomes and the tools and methods used in the framework. Using this overview, we argue that in order to apply simulation and modeling techniques fully in conceptual systems design, it is necessary to use a framework focused on communication and aimed at four key issues. We extract a generic process from the discussed frameworks and discuss for each step of this process how these issues should be addressed. We also explain how this framework should be supported with tooling. Finally we discuss a simulation study of a medical imaging system that gave us initial experiences on the approach presented here. We conclude that this framework shows promise in supporting the communication of a modeling and simulation study in a multidisciplinary settin

Relational oriented systems engineering framework for flight training

The integration of systems of systems (SoS) associated with a flight training mission directly reflects the problem of developing a system engineering process for the design of live, virtual and constructive (LVC) experiments. Due to the complexity and disparity of the technology in a flight training SoS (FTSoS), modeling and analysis of architecture is becoming increasingly important. Relational Oriented Systems Engineering (ROSE) methodology is used to develop a framework for simulation and analysis of a navigational SoS for a typical aircraft. The framework can be used for both the prescription of navigation systems entering and exiting the SoS and for the analysis of pilot behavior as navigation quality of service (QoS) changes. ROSE offers a novel approach to developing a model-based systems engineering (MBSE) process for simulation and analysis of a complex SoS problem

A Framework for Executable Systems Modeling

Systems Modeling Language (SysML), like its parent language, the Unified Modeling Language (UML), consists of a number of independently derived model languages (i.e. state charts, activity models etc.) which have been co-opted into a single modeling framework. This, together with the lack of an overarching meta-model that supports uniform semantics across the various diagram types, has resulted in a large unwieldy and informal language schema. Additionally, SysML does not offer a built in framework for managing time and the scheduling of time based events in a simulation. In response to these challenges, a number of auxiliary standards have been offered by the Object Management Group (OMG); most pertinent here are the foundational UML subset (fUML), Action language for fUML (Alf), and the UML profile for Modeling and Analysis of Real Time and Embedded Systems (MARTE). However, there remains a lack of a similar treatment of SysML tailored towards precise and formal modeling in the systems engineering domain. This work addresses this gap by offering refined semantics for SysML akin to fUML and MARTE standards, aimed at primarily supporting the development of time based simulation models typically applied for model verification and validation in systems engineering. The result of this work offers an Executable Systems Modeling Language (ESysML) and a prototype modeling tool that serves as an implementation test bed for the ESysML language. Additionally a model development process is offered to guide user appropriation of the provided framework for model building

An integrated modeling framework for infrastructure system-of-systems simulation

Design of future hard infrastructure must consider emergent behaviors from cross-system interdependencies. Understanding these interdependencies is challenging due to high levels of integration in high-performance systems and their operation as a collaborative system-of-systems managed by multiple organizations. Existing modeling frameworks have limitations for strategic planning either because important spatial structure attributes have been abstracted out or behavioral models are oriented to shorter-term analysis with a static network structure. This paper presents a formal modeling framework as a first step to integrating infrastructure system models in a system-of-systems simulation addressing these concerns. First, a graph-theoretic structural framework captures the spatial dimension of physical infrastructure. An element's simulation state includes location, parent, resource contents, and operational state properties. Second, a functional behavioral framework captures the temporal dimension of infrastructure operations at a level suitable for strategic analysis. Resource behaviors determine the flow of resources into or out of nodes and element behaviors modify other state including the network structure. Two application use cases illustrate the usefulness of the modeling framework in varying contexts. The first case applies the framework to future space exploration infrastructure with an emphasis on mobile system elements and discrete resource flows. The second case applies the framework to infrastructure investment in Saudi Arabia with an emphasis on immobile system elements aggregated at the city level and continuous resource flows. Finally, conclusions present future work planned for implementing the framework in a simulation software tool.American Society for Engineering Education. National Defense Science and Engineering Graduate Fellowshi

Executable system architecting using systems modeling language in conjunction with Colored Petri Nets - a demonstration using the GEOSS network centric system

Models and simulation furnish abstractions to manage complexities allowing engineers to visualize the proposed system and to analyze and validate system behavior before constructing it. Unified Modeling Language (UML) and its systems engineering extension, Systems Modeling Language (SysML), provide a rich set of diagrams for systems specification. However, the lack of executable semantics of such notations limits the capability of analyzing and verifying defined specifications. This research has developed an executable system architecting framework based on SysML-CPN transformation, which introduces dynamic model analysis into SysML modeling by mapping SysML notations to Colored Petri Net (CPN), a graphical language for system design, specification, simulation, and verification. A graphic user interface was also integrated into the CPN model to enhance the model-based simulation. A set of methodologies has been developed to achieve this framework. The aim is to investigate system wide properties of the proposed system, which in turn provides a basis for system reconfiguration --Abstract, page iii

A Framework To Model Complex Systems Via Distributed Simulation: A Case Study Of The Virtual Test Bed Simulation System Using the High Level Architecture

As the size, complexity, and functionality of systems we need to model and simulate con-tinue to increase, benefits such as interoperability and reusability enabled by distributed discrete-event simulation are becoming extremely important in many disciplines, not only military but also many engineering disciplines such as distributed manufacturing, supply chain management, and enterprise engineering, etc. In this dissertation we propose a distributed simulation framework for the development of modeling and the simulation of complex systems. The framework is based on the interoperability of a simulation system enabled by distributed simulation and the gateways which enable Com-mercial Off-the-Shelf (COTS) simulation packages to interconnect to the distributed simulation engine. In the case study of modeling Virtual Test Bed (VTB), the framework has been designed as a distributed simulation to facilitate the integrated execution of different simulations, (shuttle process model, Monte Carlo model, Delay and Scrub Model) each of which is addressing differ-ent mission components as well as other non-simulation applications (Weather Expert System and Virtual Range). Although these models were developed independently and at various times, the original purposes have been seamlessly integrated, and interact with each other through Run-time Infrastructure (RTI) to simulate shuttle launch related processes. This study found that with the framework the defining properties of complex systems - interaction and emergence are realized and that the software life cycle models (including the spiral model and prototyping) can be used as metaphors to manage the complexity of modeling and simulation of the system. The system of systems (a complex system is intrinsically a system of systems ) continuously evolves to accomplish its goals, during the evolution subsystems co-ordinate with one another and adapt with environmental factors such as policies, requirements, and objectives. In the case study we first demonstrate how the legacy models developed in COTS simulation languages/packages and non-simulation tools can be integrated to address a compli-cated system of systems. We then describe the techniques that can be used to display the state of remote federates in a local federate in the High Level Architecture (HLA) based distributed simulation using COTS simulation packages

Model-Based Systems Engineering Approach to Distributed and Hybrid Simulation Systems

INCOSE defines Model-Based Systems Engineering (MBSE) as the formalized application of modeling to support system requirements, design, analysis, verification, and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases. One very important development is the utilization of MBSE to develop distributed and hybrid (discrete-continuous) simulation modeling systems. MBSE can help to describe the systems to be modeled and help make the right decisions and partitions to tame complexity. The ability to embrace conceptual modeling and interoperability techniques during systems specification and design presents a great advantage in distributed and hybrid simulation systems development efforts. Our research is aimed at the definition of a methodological framework that uses MBSE languages, methods and tools for the development of these simulation systems. A model-based composition approach is defined at the initial steps to identify distributed systems interoperability requirements and hybrid simulation systems characteristics. Guidelines are developed to adopt simulation interoperability standards and conceptual modeling techniques using MBSE methods and tools. Domain specific system complexity and behavior can be captured with model-based approaches during the system architecture and functional design requirements definition. MBSE can allow simulation engineers to formally model different aspects of a problem ranging from architectures to corresponding behavioral analysis, to functional decompositions and user requirements (Jobe, 2008)

Physics-Informed Learning Using Hamiltonian Neural Networks with Output Error Noise Models

In order to make data-driven models of physical systems interpretable and reliable, it is essential to include prior physical knowledge in the modeling framework. Hamiltonian Neural Networks (HNNs) implement Hamiltonian theory in deep learning and form a comprehensive framework for modeling autonomous energy-conservative systems. Despite being suitable to estimate a wide range of physical system behavior from data, classical HNNs are restricted to systems without inputs and require noiseless state measurements and information on the derivative of the state to be available. To address these challenges, this paper introduces an Output Error Hamiltonian Neural Network (OE-HNN) modeling approach to address the modeling of physical systems with inputs and noisy state measurements. Furthermore, it does not require the state derivatives to be known. Instead, the OE-HNN utilizes an ODE-solver embedded in the training process, which enables the OE-HNN to learn the dynamics from noisy state measurements. In addition, extending HNNs based on the generalized Hamiltonian theory enables to include external inputs into the framework which are important for engineering applications. We demonstrate via simulation examples that the proposed OE-HNNs results in superior modeling performance compared to classical HNNs.Comment: Preprint submitted to IFAC 202

MS2G as pillar for developing strategic engineering as a new discipline for complex problem solving

Simulation science is a strategic resource to address most challenging problems; in this paper, it is provided an overview about how new simulation capabilities, such as that ones based on MS2G (Modeling, interoperable Simulation and Serious Games), could enable to address complex systems and to support decision making; in addition, the new Strategic Engineering Discipline is proposed as framework where to combine all these new approaches for Problem Solving and Strategic Planning nowadays; several real examples are proposed as case studies to confirm the validity of these innovative concepts