MBSE with/out Simulation: State of the Art and Way Forward

Zeigler, Bernard P.; Mittal, Saurabh; Traoré, Mamadou Kaba

doi:10.3390/systems6040040

Cited by 46 publications

(40 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Reconciling the MBSE paradigm with the Discrete Event Simulation (DEVS) paradigm is a recent ongoing effort [73]. Ongoing collaboration between the MBSE and DEVS communities has been institutionalized in a joint workgroup for the International Council on Systems Engineering (INCOSE) and International Association for Engineering Modeling and Simulation (NAFEMS) [74].…”

Section: Resultsmentioning

confidence: 99%

Category-Theoretic Formulation of Model-Based Systems Architecting: The Concept-Model-Graph-View-Concept Transformation Cycle

Mordecai¹,

Fairbanks²,

Crawley³

2021

Preprint

View full text Add to dashboard Cite

We introduce the Concept-Model-Graph-View-Concept (CMGVC) transformation cycle. The CMGVC cycle facilitates coherent architecture analysis, reasoning, insight, and decision-making based on conceptual models that are transformed into a common, robust graph data structure (GDS). The GDS is then transformed into multiple views on the model, which inform stakeholders in various ways. This GDS-based approach decouples the view from the model and constitutes a powerful enhancement of model-based systems engineering (MBSE). CMGVC applies the rigorous foundations of Category Theory, a mathematical framework of representations and transformations. The CMGVC architecture is superior to direct transformations and language-coupled common representations. We demonstrate the CMGVC cycle to transform a conceptual system architecture model built with the Object Process Modeling Language (OPM) into dual graphs and a decision support matrix (DSM) that stimulates system architecture insight.

show abstract

Section: Resultsmentioning

confidence: 99%

Category-Theoretic Formulation of Model-Based Systems Architecting: The Concept-Model-Graph-View-Concept Transformation Cycle

Mordecai¹,

Fairbanks²,

Crawley³

2021

Preprint

View full text Add to dashboard Cite

show abstract

“…S.O.B. method also contributes to the Model-Based Engineering, which together with its related methods, have been recognized for the SoS development [Graciano Neto et al 2018b, Zeigler et al 2018. Model-Based Engineering (MBE) is the practice of systematically using models during an engineering activity [Agner et al 2013].…”

Section: Discussionmentioning

confidence: 99%

S.O.B (Save Our Budget) - A Simulation-Based Method for Prediction of Acquisition Costs of Constituents of a System-of-Systems

Neto

Horita

Santos

et al. 2019

iSys

View full text Add to dashboard Cite

Software economics, acquisition, and pricing are important con- cerns for Systems-of-Systems (SoS). SoS are alliances of independent software- intensive systems combined to offer holistic functionalities as a result of the con- stituents interoperability. SoS engineering involves separately acquiring con- stituents and combining them to form the SoS. Despite the existence of cost pre- diction techniques, predicting SoS acquisition costs at design-time should also include the analysis of different suppliers of constituents, their respective prices and quality. However, known methods cover only two out of these three param- eters. The main contribution of this article is to present the S.O.B. (Save Our Budget) method, a novel simulation-based method to predict, at design-time, the acquisition cost of constituents, while still considering quality attributes and different suppliers. Results of a case study in the Smart Building domain re- vealed that S.O.B. method supports a precise prediction of acquisition cost of constituents to build a SoS for that domain. Furthermore, it also contributes to estimate the cost based on a pre-established quality attribute (functional suit- ability), as well as to support the selection of coalition that exhibits better results through the analysis of cost-benefit ratio.

show abstract

“…The Automated Scenario Construction (ASC) architecture envisions a collaboration between human and AI agents while offering a generic workflow for SoS model development (Zeigler et al 2018b). The human modeler develops the System Entity Structure (SES) (Zeigler and Sarjoughian 2017) and the DEVS model base to span the configuration space that encompasses the model family of interest.…”

Section: Automated Search Through Architectural Alternativesmentioning

confidence: 99%

Multi-resolution Modeling for Adaptive UAV Service Systems

2019

Annual Simulation Symposium (ANSS 2019)

View full text Add to dashboard Cite

With the advent of Unmanned Autonomous Vehicles (UAV), new kinds of systems of systems (SoS) that provide specific services may be on the horizon. We recognize that beyond basic technology requirements, such UAV-based service systems may be subject to a multiplicity of system engineering objectives. An allinclusive model would be able to provide the basis for decision making in each of such categories as payload requirements, on-board-energy constraints, locations of depots/launch sites, and so on. Multiresolution modeling helps us to construct a collection of partial models, each oriented to one or more objectives. In this paper, we discuss a Modeling and Simulation methodology that is based on Discrete Event System Specification (DEVS) and System Entity Structure (SES). As implemented in the MS4 Me integrated development environment, it provides a practical approach to multiresolution model-based system design of UAV-based service systems.

show abstract

MBSE with/out Simulation: State of the Art and Way Forward

Cited by 46 publications

References 32 publications

Category-Theoretic Formulation of Model-Based Systems Architecting: The Concept-Model-Graph-View-Concept Transformation Cycle

Category-Theoretic Formulation of Model-Based Systems Architecting: The Concept-Model-Graph-View-Concept Transformation Cycle

S.O.B (Save Our Budget) - A Simulation-Based Method for Prediction of Acquisition Costs of Constituents of a System-of-Systems

Multi-resolution Modeling for Adaptive UAV Service Systems

Contact Info

Product

Resources

About