Handbook of Model-Based Systems Engineering (Springer Nature Reference)

✍ Scribed by Azad M. Madni (editor), Norman Augustine (editor), Michael Sievers (editor)

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 1362
• Category: Library

✦ Synopsis

This handbook brings together diverse domains and technical competences of Model Based Systems Engineering (MBSE) into a single, comprehensive publication. It is intended for researchers, practitioners, and students/educators who require a wide-ranging and authoritative reference on MBSE with a multidisciplinary, global perspective. It is also meant for those who want to develop a sound understanding of the practice of systems engineering and MBSE, and/or who wish to teach both introductory and advanced graduate courses in systems engineering. It is specifically focused on individuals who want to understand what MBSE is, the deficiencies in current practice that MBSE overcomes, where and how it has been successfully applied, its benefits and payoffs, and how it is being deployed in different industries and across multiple applications. MBSE engineering practitioners and educators with expertise in different domains have contributed chapters that address various uses of MBSE and related technologies such as simulation and digital twin in the systems lifecycle. The introductory chapter reviews the current state of practice, discusses the genesis of MBSE and makes the business case. Subsequent chapters present the role of ontologies and meta-models in capturing system interdependencies, reasoning about system behavior with design and operational constraints; the use of formal modeling in system (model) verification and validation; ontology-enabled integration of systems and system-of-systems; digital twin-enabled model-based testing; system model design synthesis; model-based tradespace exploration; design for reuse; human-system integration; and role of simulation and Internet-of-Things (IoT) within MBSE.

✦ Table of Contents

Foreword
Preface
Acknowledgment
Contents
About the Editors-in-Chief
About the Associate Editor
Section Editors
Contributors
Part I: Introduction
1 Introduction to the Handbook
Introduction
What New Developments in Systems Engineering Are Important to Meeting Twenty-First-Century Challenges?
What Is Unique About MBSE?
What Kinds of Models Can Be Created Using MBSE?
How Can MBSE Be Applied to AI-Driven Systems?
How Does MBSE Deal with Complexity?
How Should Humans Be Modeled in Complex Systems?
How Should Nonlinearities, Including Discontinuities, Be Addressed When Modeling Complex Systems?
How Can Complex Systems Be Protected Against Active Human-Initiated Interference?
How Can Digital Twin and Digital Thread from Digital Engineering Be Leveraged in Model-Based Systems Engineering?
How Can Simulation Benefit Systems Engineering?
How Can MBSE Be Used to Protect Against Unintended Consequence Produced by Changes?
What Is MBSE´s Contribution to Risk Analysis?
Is There a Return on Investment from MBSE?
Part II: MBSE Foundations
2 Semantics, Metamodels, and Ontologies
Introduction
Problem Statement
Key Concepts and Terminology
Semantics and Semantic Domain
Metamodels
Ontologies
State-of-the-Practice
Best Practice Approach
What Is the Ontology Structure and Ownership?
How Much Commonality Is There?
What Is the Process for Developing an Ontology?
Step 1: Determine the Domain and Scope
Step 2: Look for Existing Ontologies
Step 3: Enumerate Key Terms
Steps 4 and 5: Define Concepts, Concept Hierarchy, and Concept Properties
Step 6: Define Slot Facets
Step 7: Create Instances
Ontology Development and Analysis Tools
Illustrative Example
Competency Questions
Existing Ontologies
Key Terms
Concepts, Concept Hierarchy, Slots, and Facets
Instances
Chapter Summary
Cross-References
References
3 MBSE Methodologies
Introduction
Key Concepts and Definition
Best Practice Approach
Object-Oriented Systems Engineering Method (OOSEM)
Overview
Tool Support
Offering/Availability
Selected Resources
Object-Process Methodology (OPM)
Tool Support
Offering/Availability
Selected Resources
Integrated Systems Engineering and Pipelines of Processes in Object-Oriented Architectures (ISE&PPOOA)
Overview
Tool Support
Offering/Availability
Selected Resources
Illustrative Example/Case
The Systems Modeling Toolbox (SYSMOD) in Review
A Few Examples of SYMOD Core Concepts in Greater Detail
SYSMOD Method: Tailor the MBSE Methodology
Purpose
Description
SYSMOD Method: Analyze the Problem
Purpose
Description
Example of SYSMOD Product: FFDS Problem Statement
Document
Model
SYSMOD Method: Identify System Use Cases
Purpose
Description
Example of SYSMOD Product: FFDS System Use Cases
Document
Model
SYSMOD Method: Model the Logical Architecture
Purpose
Description
Example of SYSMOD Product: FFDS Logical Architecture
Document
Model
Challenges and Gaps
Evaluating and Comparing Methodologies
Methodology Adoption and Tailoring
Expected Advances in the Future
Chapter Summary
Systems Modeling Toolbox (SYSMOD)
Overview
Tool Support
Offering/Availability
Selected Resources
Cross-References
References
General Refences
MBSE Methodology References
Object-Oriented Systems Engineering Method (OOSEM)
Object-Process Methodology (OPM)
Systems Modeling Toolbox (SYSMOD)
Integrated Systems Engineering and Process Pipelines in OO Architectures (ISE&PPOOA)
4 SysML State of the Art
Introduction (Problem Statement, Key Concepts, Terms, and Definitions)
Decision-Making, Surrogate Modeling, and Parametric Requirements
An Example of Multifidelity Multiphase Tool Integration Through SysML
Design, Operate, and Manage Digital Ecosystems Using SysML and MBSE
Additional Project Examples
Chapter Summary
Cross-References
References
5 Role of Decision Analysis in MBSE
Introduction
Key Concepts and Definitions
Current State of Practice/Current State of the Art
MBSE Capabilities to Enable Trade-Off Analyses
Illustrative Example/Case Study
Case Study Background
Case Study Motivation
Modeling Requirements for Enabling Decision-Making in System Design
Implementing the Integrated System Model
Best Practice Approach: Creating a Custom MODA Model for Use in Integrated Trade-Off Analysis
Using the Model-Based Integrated Decision Support Tool to Inform Design Decisions
Discussion of Case Study Observations
Challenges and Gaps
Chapter Contribution
Expected Advances in the Future
Summary
Cross-References
Appendix: List of Acronyms and Their Meaning
References
6 Pattern-Based Methods and MBSE
Introduction
MBSE Pattern Concept
Expanded Perspective and Organization of Chapter
State-of-the-Art
The Most Important Pattern: What Is the Smallest Model of a System?
Introduction to the SMetamodel
Interactions, Requirements, and States
Selectable System Features and Stakeholder Value
Failure Modes and Effects
Attributes and Attribute Couplings
SModels and S*Patterns
Architectural Frameworks, Ontologies, Reference Models, Platforms, Families, Product Lines
Patterns, Configurations, Compression, Specialization
Distillation and Representation of Learning; Accessibility and Impact of Learning
Tooling and Language Issues for MBSE Patterns
Modeling Languages and MBSE Patterns
Automated Tooling and MBSE Patterns
Best Practice Approach
INCOSE Innovation Ecosystem Reference Pattern
Effective Ecosystem-Level Learning: More than Lessons Learned´´ Reports Model Characterization Pattern: Universal Model Metadata Reference Pattern Intended Uses and Origins of the Model Characterization Pattern Summary of the MCP Model Stakeholder Feature Groups Detailed Reference on the MCP Model Stakeholder Features Illustrative Examples Chapter Summary Impact on Practice, Education, and Research Impact on the Theoretical Foundations of Systems Engineering Cross-References References 7 Overarching Process for Systems Engineering and Design Introduction to Modeling Uncertainty Is Ubiquitous Model-Based System Engineering Purpose of Models Kinds of Models Types of Models Tasks in the Modeling Process Model for a Baseball-Bat Collision Checklist for Tasks Necessary in a Modeling Project Sensitivity Analysis of a Bat-Ball Collision Model Requirements Discovery Process Where Do Requirements Come From? A Use Case Template A Use Case Example from a Chocolate Chip Cookie-Making System A Test Plan for This System Tradeoff Study Process Tradeoff Study Example from a Chocolate Chip Cookie Acquisition System Risk Analysis Process Risk Analysis Example from a Chocolate Chip Cookie Making System Comparing the Requirements, Tradeoff, and Risk Processes Comparing the Activities of the Requirements, Tradeoff, and Risk Processes Comparing the Products of the Requirements, Tradeoff, and Risk Processes A Requirement from the Chocolate Chip Cookie Acquisition System An Evaluation Criterion from the Chocolate Chip Cookie Acquisition System A Risk from the Chocolate Chip Cookie Acquisition System Comparing a Requirement, an Evaluation Criterion, and a Risk The similar Process State the Problem Investigate Alternatives Model the System Integrate Launch the System Assess Performance Reevaluate The Overarching Process Effects of Human Decision-Making on the Overarching Process Confirmation Bias Severity Amplifiers Framing The Overarching Process Uncertainty in Stating the Problem for the Overarching Process A System for Handling Uncertainty in Models and Documentation Chapter Summary Cross-References References 8 Problem Framing: Identifying the Right Models for the Job Introduction Background Why Use a Model-Based Approach? Architecture Frameworks The Nature of Frameworks NATO Architecture Framework (NAF) DOD Architecture Framework (DODAF) OMG Unified Architecture Framework (UAF) Modeling Methodology Model Development Six-Step Method for Model Development Example Using the Method Step 1: Problem Framing Step 2: Metamodel Development Step 3: Data Collection Step 4: Model Creation Step 5: Architecture Deployment Step 6: Architecture Utilization Agile Development of Models Using Sprints Evolution of the Model Development Method Problem Framing Overview of the Problem Framing Approach Problem Framing Steps Step 1.1: Intended Users and Uses of the Models Step 1.2: Scope and Context of the Models Step 1.3: Information and Data Needs Step 1.4: Model Views and Products Problem Framing Execution Summary References Part III: Technical and Management Aspects of MBSE 9 Model-Based System Architecting and Decision-Making Introduction Model-Based System Architecting: Crossing a Mental Grand Canyon A Tango of Conceptualizations and Decisions Model-Based Concept Representation System Architecture Framework The Stakeholder Domain (D1) The Solution-Neutral Environment (D2) The Solution-Specific Environment (D3) The Integrated Concept (D4) The Concept of Operations (D5) The Scope of an MBSA Application MBSA and Architectural Decision-Making What is a Decision and Which Decisions are Architectural? Concept Attributes, Metrics, and Decision-Supporting Criteria Capturing Stakeholder Needs Capturing and Discovering Possible Architectures Capturing the Architectural Decision-Making Process Alongside the Resulting Architecture Solution-Specific Architecture Decisions Conclusion References 10 Adoption of MBSE in an Organization Introduction Related Work Change, Resistance, and Bad Practices Aimless Modeling Fast False Start Overmodeling Model Island Ivory Tower Fly Out of the Learning Curve Developing the MBSE Methodology Selection of the Modeling Languages Selection of the Modeling Tools Verification and Validation Running the MBSE Infrastructure Summary Cross-References References 11 Model-Based Requirements Introduction Theoretical Framework Dedicated Classes and Flagged Models Requirements As a Specific Class of Element System Models As Requirements Math-Based Models of Requirements Wymorian Models of Requirements Property-Model Methodology (PMM) Semantic Extensions to Model the Problem Space Elicitation, Derivation, and Trade-Off Analysis Better Problem Formulation Due to Automated Enforcement of Syntactic Rules More Comprehensive Requirements Derivation Due to Increased Semantic Precision Early Verification and Validation Cognitive Assistance to Increase Completeness Chapter Summary Cross-References References 12 Modeling Hardware and Software Integration by an Advanced Digital Twin for Cyber-physical Systems: Applied to the Automotiv... Introduction State of the Art Systems Engineering: Overcoming the Differences? Different Skills and Knowledge Different Handling in Complexity Model-Based: Unite Engineering Solutions? Related Work Best Practice Approach Systems Engineering: Merging Engineering Disciplines Decomposition Abstraction The Advanced System Model The Advanced Digital Twin Model-Based: More than a Description Illustrative Examples Level A: Customer Value Level B: Operating Principle Level C: Technical Solution Level D: Realization Chapter Summary and Expected Advances Cross-References References 13 Integrating Heterogenous Models Introduction Key Concepts and Definitions Ontologies and Models Preserving Model Correspondence Causes of Ontological Differences among Models The Levels of Conceptual Interoperability Model Best Practice Approaches Model Integration Standards and Tools - Levels 1 and 2 Addressing Levels 3 Through 6 Semantic Ontologies Bridging Mechanisms Illustrative Example Expected Advances in the Future Chapter Summary Disclaimer References 14 Improving System Architecture Decisions by Integrating Human System Integration Extensions into Model-Based Systems Enginee... Introduction State of the Art Human System Integration Ontology HSI Ontology - Mechanisms HSI Ontology - Requirements HSI Ontology - Human Agent HSI Ontology - Behavior HSI Ontology - Structure HSI Ontology - Parametrics Best Practice Approach Develop or Extend a Human System Ontology Stand Up a Model-Based Environment Create System Diagrams and Export Task Allocation and Workflow for Analysis Evaluate Results, Build Alternatives, and Evaluate Alternatives Illustrative Examples Case Study System Overview Ontology Extension or Modifications Architecture and Analysis The Human System Integration Analysis Results of Analysis Evaluate Architecture and Its Impact Evaluate Alternative Architecture and Its Impact Chapter Summary Cross-References References 15 Model-Based Human Systems Integration Introduction State of the Art: History and Evolution Task and Activity Evolution of Engineering and Associated Human Factors System Knowledge Impacts Design Flexibility and Resource Management Use of Digital Twins During System´s Whole Life Cycle Key Concepts and Definitions for a Human-Centered Systemic Approach What DoesSystem´´ Really Mean?
Emergent Functions and Structures
Looking for Separability, Emergence, and Maturity
Domain Experience Integration and Artificial Intelligence Solutions
What Does Experience´´ Mean? Toward Model-Based Experience Integration: Human-AI-SE Cross-fertilization Coordinating Technology, Organization, and People (TOP) Concrete Chapter Contribution: The PRODEC Method Procedural and Declarative Knowledge An Instance of PRODEC An Illustrative Example of PRODEC Use Discussion: Challenges, Gaps, and Possible Futures Departing from Technology-Centered MBSE Human-Centered Modeling Limitations and Perspectives HCD Based on Virtual Environments as Digital Twins Summary References 16 Model-Based Hardware-Software Integration Introduction (Problem Statement, Key Concepts, Terms, and Definitions) State-of-the-Art (Review of the Literature) Hardware-Software Integration Modeling Methodologies Functional Allocation Instance Specifications for Data Intensive Applications Capturing Data as Properties Typing Ports Item Flows Allocation Relationships Illustrative Example Chapter Summary References Part IV: Quality Attributes Tradeoffs in MBSE 17 Exploiting Digital Twins in MBSE to Enhance System Modeling and Life Cycle Coverage Introduction MBSE and Digital Twin Technology: State of the Art Model-Based Systems Engineering Digital Twin Technology Best Practice Approach Methodology Process Ontology Use in Digital Twin Definition Illustrative Example Experiments Implementation Digital Twin and Machine Learning Quantitative Analysis Chapter Summary Cross-References References 18 Model-Based Mission Assurance/Model-Based Reliability, Availability, Maintainability, and Safety (RAMS) Introduction From Document-Based to Model-Based Reliability and Safety Assessment Model-Based Reliability and Safety Assessment: A Literature Review Functional Hazard Analysis (FHA) Fault Tree Analysis (FTA) Failure Model and Effects Analysis (FMEA) Reliability Analysis Summary Table A Recommended Approach for Model-Based Reliability and Safety Assessment Model-Based Functional Hazard Analysis Model-Based Fault Tree Analysis Model-Based Failure Modes and Effects Analysis Model-Based Reliability Block Diagram Advantages of the Model-Based Reliability and Safety Assessment Examples of Application of the Recommended Model-Based Reliability and Safety Assessment Model-Based Functional Hazard Analysis: Aileron Command Model-Based Fault Tree Analysis: Aileron Command Model-Based Failure Modes and Effects Analysis: Aileron Command Model-Based Reliability Block Diagram: Aileron Command Chapter Summary Cross-References References 19 MBSE in Architecture Design Space Exploration Introduction The Need for Quantitative Evaluation in the Early Design Stage System Architecting in the Systems Engineering Process Challenges Developments at the DLR Institute of System Architectures in Aeronautics State of the Art Architecture Modeling and Tightly Coupled Evaluation Generating Architectures by Morphological Matrix Enumeration and Reasoning Domain-Specific Systematic Architecting Methods Dynamic Mapping of Function to Form Summary Table Proposed Best Practice Approach for Systematic Architecture Design Space Exploration Modeling the Architecture Design Space Design Space Elements The Architecture Design Space Graph (ADSG) Generating Architecture Instances Formalizing the Architecture Optimization Problem Decision Hierarchy: Architecture Generation In the Loop Performance Metrics as Objectives and Constraints Properties of System Architecture Optimization Problems Evaluating the Performance of Generated Architectures Illustrative Examples NASA Apollo Mission Design Hybrid-Electric Propulsion System Architecture Chapter Summary Cross-References References Part V: Digital Engineering and MBSE 20 Digital Twin: Key Enabler and Complement to Model-Based Systems Engineering Introduction Digital Twin Rationale and Potential Uses Exploiting Synergy Between Digital Twins and MBSE Level 1: Pre-digital Twin Level 2: Digital Twin Level 3: Adaptive Digital Twin Level 4: Intelligent Digital Twin Integration of Digital Twins with Related Technologies Digital Twin and Simulation Digital Twin and Machine Learning Digital Twin and Internet of Things (IoT) Digital Twin and Cost Chapter Summary and Future Prospects Cross-References References 21 Developing Industry 4 Systems with OPM ISO 19450 Augmented with MAXIM Introduction Model-Based Systems Engineering The Digital Transformation Digital Engineering: The Ultimate Blend of Hardware and Software High-Level DoD Acquisition Community Goals for the DE Transformation INCOSE Model-Based Capabilities Matrix The System-Software Engineering Gap Why Is MBSE Not Picking Up Momentum in the Expected Pace? The UML/SysML Dominance of the MBSE Landscape The UML/SysML Software/System Focus Difference OPM ISO 19450 and Its MAXIM Extension OPM ISO 19450 MAXIM: Methodical Approach to Executable Integrative Modeling OPM Cyber-physical System Applications Chapter Summary Cross-References References 22 MBSE Testbed for Unmanned Vehicles Introduction MBSE State-of-the-Art MBSE Testbed for Unmanned Vehicles: A Best Practice Approach Testbed Ontology MBSE Testbed Concept Key Features Predefined Scenarios Dashboard Tool System Modeling Scenario Elements Human-Computer Cooperation Extensible Architecture Current Testbed Components Software Programming Environment Optimization, Control, and Learning Algorithms Graphical User Interface Exemplar Repositories, Packages, Libraries (Not Fixed) Simulation Platforms Hardware and Connectors Logical Architecture Testbed Benefits Distributed Hardware Environment Prototype Testbed Implementation System Modeling and Verification Model and Scenario Refinement Testbed Repository Experimentation Support Rapid Scenario Authoring Multi-perspective Visualization Smart Dashboard Preliminary Experiments Lessons Learned Summary Cross-References References 23 Transitioning from Observation to Patterns: A Real-World Example Introduction and Context State of the Art Background Best Practice Approach Energy Storage System Pattern Mining Using Patterns Chapter Summary Cross-References References Part VI: MBSE for System Acquisition and Management 24 MBSE for Acquisition Introduction Introducing Model-Based Systems Engineering The Unique Nature of Acquisition The Acquisition Life Cycle Enterprise Gap Assessment Materiel Solution Analysis Contracting and Procurement Technology Maturation and Risk Reduction Development Production and Deployment Operations and Support MBSE Needs of the Acquisition Environment The Digital Engineering (DE) Construct and Its Implications for MBSE in Acquisition MBSE State of the Art and Best Practices for Acquisition MBSE for Enterprise Gap Analysis MBSE for Materiel Solution Analysis MBSE for Contracting and Procurement MBSE for the Remainder of the Acquisition Life Cycle Chapter Summary References 25 Managing Model-Based Systems Engineering Efforts Introduction Project Management Project Management for MBSE Projects State-of-the-Art Best Practice Approach Initiation and Scope Definition Planning Measurement Execution Review and Evaluation Closure Management Tools Illustrative Example Chapter Summary Cross-References References 26 MBSE Methods for Inheritance and Design Reuse Introduction Design Reuse in Complex Engineering Systems Taxonomy of Reuse in the Space Industry Hardware Reuse Design Knowledge Reuse Work Effort Reuse Reuse Taxonomy Reuse Trends in the Space Industry Planned and Unplanned Reuse Structured and Unstructured Methods MBSE as a Facilitator of Improved Design Reuse Practices Hierarchy of MBSE Methods for Reuse Conditions Conducive to MBSE Adoption and Reuse Best Practice Methodology for MBSE Design Reuse Design Reuse Logical Process Step 1: Reuse Context Definition Process Step 2: Technical Inheritance Process Step 3: Reuse Value Assessment Process MBSE Implementation of Reuse Process SysML as the Basis for a Canonical MBSE Environment Key Decisions in MBSE Implementation Reuse Profile Methodology: Summary and Visualization Methodology Demonstration on Sample Problem Problem Selection and Description Methodology Walkthrough and Sample Output Chapter Summary References 27 Model Interoperability Introduction MBSE Interoperability Concepts Scenario #0: No Interoperability Scenario #1: Connected Information Between Two Repositories Scenario #1a: Interoperability by Import/Export Scenario #1b: Interoperability by Linked Data Scenario #1c: Interoperability by Proprietary Adapters Scenario #2: Interoperability by Link Management Scenario #3: Central Repository Scenario #4: Interoperability by Using Services Conclusion Cross-References References 28 A Reuse Framework for Mode-Based Systems Engineering Introduction Reuse in Research and Literature The Generalized Reuse Framework Reusable Resources The Reuse Process Development with Reuse Development for Reuse GRF Usage Scenarios Case 1: Reuse of System Definition Case 2: Reuse of System Design Case 3: Reuse of System Implementation Case 4: Reuse of Validated System Component Summary of the GRF Scenarios An Illustrative Example – Application of the Generalized Reuse Framework to Cost Estimating and Analysis Parametric Cost Estimating for System Development COSYSMO The GRF-Based Cost Estimating Relationship The DWR and DFR Weights The DWR Weights The DFR Weights Chapter Summary Appendix A A1. DWR Detailed Weight Table A2. DFR Detailed Weight Table Cross-References References 29 MBSE Mission Assurance Introduction (Problem Statement, Key Concepts, Terms and Definitions) Definitions Challenges State-of-the-Art (Review of the Literature) Best Practice Approach (What´s New and Different, Benefits and Payoffs) Program Assurance Core MA Process Best Practices Requirements Analysis and Validation Core MA Process Best Practices Design Assurance Core MA Practice Best Practices Manufacturing Assurance Core MA Process Integration, Test, and Evaluation Core MA Process Operations Readiness Assurance (ORA) Core MA Process Operations, Maintenance, and Sustainment Core MA Process MA Reviews and Audits Illustrative Examples (A Couple to Show Uses of Approach) Program Assurance Example Design Assurance Example IT&E Assurance Example Chapter Summary Cross-References References 30 Conceptual Design Support by MBSE: Established Best Practices Introduction State-of-the-Art Survey MBCD Objectives Conceptual-Design Methodology and Methods MBCD Implementation Issues SysML for MBCD MBCD Best Practices Defining the Process Addressing MBCD Needs and Objectives Problem Definition, Operational Aspects, and Stakeholders´ Needs Performance-Based Specification and System Characteristics Abstraction Designing Alternative Solutions Selecting Candidate Solution(s) Addressing MBCD Issues Model Interoperability and Data Management Organizational Support for MBCD Solutioneering Lack ofStopping Criteria´´ for Modeling
Low Stakeholder Engagement
Return on Investment (ROI) Concerns
Requirements´ Uncertainty
Lack of Common Taxonomy
Methodology Elaborated
Reports
MBCD Methodology Discussion and Future Direction
Chapter Summary
Cross-References
References
Part VII: Case Studies
31 Ontological Metamodeling and Analysis Using openCAESAR
Introduction
Language
Abstraction
Automation
The Meaning of Modeling
The Meaning of Metamodeling
Combining Modeling Languages and Semantics
Ontological Metamodeling
State of the Art
Vocabularies and Ontological Reasoning
Ontological Modelling Language
Vocabulary
Vocabulary Bundle
Description
Description Bundle
OML Analysis Workflows
openCAESAR Tools
OML Workbenches
Analysis Services (https://langserver.org/) (https://theia-ide.org/)
OML Bikeshed
OML Merge
OML to OWL Adapter
OML Reason
OML Load
OWL SPARQL
OWL SHACL
OWL Start/Stop Fuseki
Tool Adapters
Example Ontologies
Core Vocabularies
IMCE Vocabularies
FireSat Example
Chapter Summary
References
32 MBSE Validation and Verification
Introduction
State of the Art
Best Practice Approach
Software Overview
Prototyping the Process
Development Cycle
Requirements
Simulation Hardware
Test Infrastructure and Traceability
Model-Based Unit Testing
GOTS Components
Command and Telemetry Dictionary
ConOps-Driven Testing Methodology
Test Patterns for Verification of Level-4 Requirements
Guidance, Navigation, and Control
Commanding Modes and Transitions
Fault Management
Commands and Telemetry
Testing Cadence During Development
Formal Inspection
Illustrative Examples
Training and Mission Operations
Ambiguous ICDs
Heater Tanks
Reaction Wheels
Star Tracker System
Emergent Behavior
System Reboot
Final Load
Conclusions
Cross-References
References
33 MBSE for System-of-Systems
Introduction: System-of-Systems and Imperative for Model-Based Approach
Systems and System-of-Systems
Implications for a Model-Based Approach for System-of-Systems
State of Art: Three Model-Based Functions Supporting SoSE
Sharing of Information via Models
Discovery of Information via Models
Risk Detection and Response via Models
Best Practice Approach: Structured Approach to Modeling System-of-Systems
Overview
Preliminary Phase for SoS Problem Scoping
Purpose of SoS Analysis and Time Horizon
SoS Stakeholder Control and Organizational Structure
Definition Phase
Abstraction Phase
Implementation Phase
Illustrative Examples: Research Vignettes in System-of-Systems
The Past
Lunar C3I
The Present
SysML Diagrams to Help Characterize System-of-Systems
MBSE for Modeling and Analysis of Space Exploration SoS
MBSE as an Enabler for System-of-Systems Integration
The Future
MBSE as Enablers for Better SoSE Analysis and Synthesis Activities
Artificial Intelligence as Enabler for SoS MBSE Model Definition
Chapter Summary
Cross-References
References
34 NSOSA: A Case Study in Early Phase Architecting
Introduction
Concept Exploration
Concept Development and Development Strategy
System Development and Production
Concept Exploration Phase Goals
NSOSA Background and Goals
Models Relevant to the Problem
A 42010 and National Academies Guide to Model Selection
Functional Description
Physical Descriptions: Models Versus Design Vectors
Performance and Value Modeling
Choosing the NSOSA Value Model
NSOSA Design Vector Models
NSOSA Modeling Processes
NSOSA Results
From Early Phase to Acquisition
Chapter Summary
References
35 Cybersecurity Systems Modeling: An Automotive System Case Study
Introduction and Terminology
Origins of Cybersecurity
State of the Art
Threat Modeling with Attack Trees
State-Based Security Modeling Approaches
Simulation-Based Security Modeling
Security Viewpoints in Unified Architecture Framework
Chassis
SysML-Sec
MB3SE
MBSEsec
Best Practice Approach
Illustrative Example
HSUV Security Issues
Instantiating the MBSEsec Security Domain and Profile
Applying the Best Practice Approach
Chapter Summary
Cross-References
References
36 Assistive Technologies for Disabled and Older Adults
Introduction
Population of Interest
Assistive Technologies
Mobility
Sensory Disabilities
Older Adults
Social Inclusion
Summary
Wearable Coach
Accessible Driverless Cars
Model-Based Approach
Model Integration
Models of Use Cases
Economic Modeling
Market Economics Model
Economic Projections
Investment Strategies
Models of Business Cases
Discussion
Conclusions
Cross-References
References
37 Multi-model-Based Decision Support in Pandemic Management
Introduction
State of the Art
Ontologies
SIR Model and Pandemics
Simulations
Best Practice Approach
Multi-model Approach
Illustrative Examples
Chapter Summary
References
38 Semantic Modeling for Power Management Using CAESAR
Introduction
Problem Statement
JPL, IMCE, and CAESAR
Case Study
Europa Clipper Introduction
Modeling Scenarios
Modeling Waste Heat
CAESAR PEL Application
CAESAR PEL Application
Advantages of the CAESAR PEL Vocabulary
Implementing the CAESAR PEL
CAESAR Authoring Workbench
Power Analysis Workflow
Chapter Summary and Future Updates
Cross-References
References
39 Modeling Trust and Reputation in Multiagent Systems
Introduction
Problem Statement
Key Concepts and Terminology
State-of-the-Practice
Ontologies
Trust Evaluation
Bayesian Belief Network
Markov Decision Processes
Partially Observable Markov Decision Process
MDP and POMDP Trust Evaluation
Evaluating Agent Health
Conventional Error Detection
Health Evaluation Using Models and Machine Learning
Model-Based Health Assessment
ML-Health Evaluations
Additional Resources
Best Practice Approach
Illustrative Example
JPL´s Deep Space Network
Trust and Reputation Study and Results
Chapter Summary and Future Work
Cross-References
References
40 Modeling and Simulation Through the Metamodeling Perspective: The Case of the Discrete Event System Specification
Introduction
What Is Modeling and Simulation?
State of the Art
Computational Representation: The DEVS Metamodel
The Basic Layer: Mathematical Function´´ andSet Theory Utility´´ Packages
The DEVS-General Purpose Layer: DEVS Model Core,´´DEVS Structural Model,´´ and DEVS Coupling Definition´´ Packages The DEVS-Specific Layer:DEVS Atomic Structural Model,´´ DEVS Atomic Behavioral Model,´´DEVS Atomic Interaction Definit...
Best Practice Approach
Defining a DEVS Simulation Model Through the DEVS Computational Representation: Software Tool and Illustrative Examples
Limitations of the DEVS Community That Metamodeling Overcomes
Chapter Summary and Conclusion
Cross-References
Appendix
References
Part VIII: Future Outlook
41 Exploiting Transdisciplinarity in MBSE to Enhance Stakeholder Participation and Increase System Life Cycle Coverage
Introduction
MBSE and Decision Analysis
Preferences, Values, and Utility
Quantifying Uncertainty
Updating Belief
Valuing Information and Experimentation
Biases in Human Decision-Making
Institutional Barriers
MBSE and Digital Engineering
MBSE and Digital Twins
MBSE and Digital Thread
Industry 4.0
Internet of Things
MBSE and AI/ML
MBSE and Social Networks
Crowdsourcing
MBSE and Entertainment Arts
Transdisciplinarity: Key to Exploiting Convergence
Implications for MBSE Curriculum
Conclusions
Cross-References
References
42 Toward an Engineering 3.0
Introduction
Complex Systems Challenges
Two Complications for Engineering 3.0
Further Challenges
Limitations of Modeling and Simulation
Beyond Established Equations
Chapter Summary
References
43 Category Theory
Introduction
Composition and Context
A Model Is a Mapping
Isomorphism and Identity
Picturing Processes
Nondeterminism
Possibility
Probability
State
Visual Reasoning
Duality
Further Study
Conclusion
References
44 Perspectives on SE, MBSE, and Digital Engineering: Road to a Digital Enterprise
Introducing the Digital Enterprise (DE)
Historical Perspective on Systems Engineering (SE)
The Broader Context of Today´s Systems
Implications of a Circular Economy on SE
State of the Practice
System Boundaries
End-to-End Approach and SE Focus
System Architecting
Assumption and Sensitivity Analyses
SE and Project Management Overlap
Engineering Simplicity
System Engineering Failures
Risk Management
Model-Based Systems Engineering
Concurrent System Design Facilities
Lessons from CAD/CAE
Current SE Issues Affecting MBSE
From Fixed to Living Systems
Project Handovers
Models Needed for MBSE
Relationship of MBSE to MBE
US DoD Digital Engineering Strategy
The MBSE Landscape
Implications of the Emerging Digital World for SE
The DT Building Block for SE and Digital Enterprises
The Advancing Simulation and ``Virtualization´´ World
Best Practice Approach for Combining MBSE and DE
Toward a System-Driven Digital Enterprise (DE)
Interrelationships Between SE Tools and Their DE Contributions
MBSE Can Help Shape the Digital Enterprise
How Does MBSE Support Digital Enterprises?
Chapter Summary
References
Index