Digital Engineering

This two-day short course, based on segments of three semester-long graduate-level systems engineering courses, provides an overview the Digital Engineering (DE) of systems, and how models, simulations, and data enable its implementation.  The course begins with an introduction focusing on the U.S. Department of Defense (DoD) DE Strategy, key competencies for DE, and key Modeling and Simulation (M&S) terms and processes.  The course then presents an overview of the types of models and simulations that are used across the phases of the Systems Engineering life cycle, from system needs analysis through system sustainment.  Examples are given for several types of systems, including systems developed under the U.S. DoD acquisition process.

The course then provides information on several M&S topics, including Model Based Systems Engineering, along with the Systems Modeling Language; simulation interoperability standards, architectures, and techniques; and modeling of the natural and man-made environments.  The course culminates by putting the aforementioned topics together in an architecture for a collaborative environment to support DE that includes models, simulations, data, processes, and standards, including a repository to implement what the U.S. DoD DE Strategy calls the Authoritative Source of Truth.  Finally, the course explains how the collaborative environment can be applied to implement Digital Threads and Digital Twins.

• Name the five strategic goals of the U.S. Department of Defense Digital Engineering initiative
• Define and distinguish key Modeling and Simulation (M&S) terms
• Describe how M&S tools are used in each phase of the Systems Engineering process
• Explain Unified Modeling Language (UML) and Systems Modeling Language (SysML) diagrams
• Describe the use of simulation interoperability standards and Live-Virtual-Constructive (LVC) simulation techniques
• Compare and contrast modeling of the natural and man-made environment
• Construct a top-level architectural view of a collaborative environment for Digital Engineering

Course Outline:

1. Introduction to Digital Engineering and Modeling and Simulation
   1. The U.S. DoD Digital Engineering Strategy. U.S. DoD Definition of Digital Engineering; Goals of the Digital Engineering Strategy
   2. Key Competencies for Digital Engineering. The Digital Engineering Competency Framework and its five competency groups
   3. Overview of Modeling and Simulation. Definitions and Distinguishing Characteristics; Views and Categories of Models and Simulations; Resolution, Aggregation, and Fidelity; Overview of the Model/Simulation Development Process; Important M&S-Related Processes; M&S as a Professional Discipline
2. Use of Models and Simulations in the Phases of the Systems Engineering Process
   1. a.      M&S in System Needs and Opportunities Analysis. Needs/Opportunities for New/ Improved Systems; U.S. Defense vs. Commercial System Processes; M&S Use in Operational Analysis, Functional Analysis, and Feasibility Determination
   2. b.      M&S in Concept Exploration and Evaluation. Effectiveness Simulations and Their Components; Analyses of Alternatives; Ensuring a “Level Playing Field”; System Effectiveness Simulation Examples
   3. c.       M&S in Design and Development. Range of Engineering Disciplines Needed for System Design and Development Simulations; Simulating Interactions between System Components; Time Management in Simulations Interacting at Run-Time; Examples of Interacting Simulations for Design and Development
   4. d.      M&S in Integration and Test & Evaluation. Simulation Use During Integration; Planning for Use of Models and Simulations During T&E; Simulation Use During Testing; Post-Test Evaluation Using Models and Simulations
   5. e.      M&S in Production and Sustainment. Planning for Use of Models and Simulations During Production; Model and Simulation Use During Production; Systems Operation Simulations; Reliability Modeling, Logistics Simulations, and Ownership Cost Modeling
3. 3.      Modeling Languages, Simulation Interoperability, and Environmental Modeling
   1. a.      Model Based Systems Engineering (MBSE). History of Graphical Modeling Languages; the Unified Modeling Language (UML); MBSE Concepts; the Systems Modeling Language (SysML)
   2. Simulation Interoperability – Standards, Architectures, and Techniques. The History of Interoperable Simulation; Why the High Level Architecture (HLA) is Important for Systems Engineering; Components of the HLA Standard; Live-Virtual-Constructive (LVC) Simulations; Why LVC Simulation Federations Are Important for Systems Engineering; Interoperability Architectures for LVC Simulations; Issues in LVC Simulation Federations; The Distributed Simulation Engineering and Execution Process (DSEEP); The DSEEP Multi-Architecture Overlay and the Federation Execution Agreements Template
   3. Modeling the Natural Environment. Definition of the Natural Environment; Overview of the Air, Ground, Maritime, and Space Environments; Separating the Natural Environment from Sources and Sensors; Issues in Aggregation of Natural Environment Representations; Environmental Modeling Standards
   4. Modeling the Man-Made Environment. Definition of the Man-Made Environment; Distinguishing the Man-Made Environment from the Natural Environment and Friendly/Threat Systems; Some Man-Made Environment Modeling Examples; Man-Made Environment Modeling Standard Example: Shapefiles
4. 4.      Putting It All Together: A Digital Engineering Collaborative Environment
   1. Historical Background on Collaborative Environments. Background: Studies on M&S for System Acquisition; Definition of a Collaborative Environment (CE); Characteristics and a Reference Model for a CE; Examples of CE Architectures
   2. A Collaborative Environment for Digital Engineering. Top-Level Architecture Diagram; the Three Layers; the Two Overlays
   3. Repositories, Metadata, and Their Application to the Authoritative Source of Truth (AST). Definitions: Repository, Catalog, and Registry; Issues in the Discovery and Reuse of M&S Assets; Desired Features for Repositories; Metadata (Data About the Data), with an Example; Applying a Metadata Standard to the AST; A Digital Engineering CE Hypothetical Use Case
   4. Application to Digital Threads and Digital Twins.  Digital Thread Definitions; Creating a Digital Thread in the CE; Digital Twins – Definitions and AST Instantiation

This short course is intended for systems engineers who are seeking a broad understanding of Digital Engineering of systems, and how models, simulations, and data enable its implementation.  A basic knowledge of the systems engineering process is helpful, but detailed knowledge of models and simulation is not necessary, as the short course will explain how models and simulations are used across all phases of the systems engineering process.  The short course is not intended to provide a “deep dive” into any specific modeling or simulation language, but will provide for a basic understanding of diagrams used in the Unified Modeling Language and the Systems Modeling Language.  As an adjunct to the presentation slides, an extensive list of references will be provided, so that participants can access resources to obtain more detailed information on the topics presented.

James E. Coolahan, Ph.D., is the Chief Technology Officer of Coolahan
Associates, LLC, having retired from full-time employment at the Johns
Hopkins University Applied Physics Laboratory (JHU/APL) in December 2012
after 40 years of service. He chaired the M&S Committee of the Systems
Engineering Division of the National Defense Industrial Association for seven
years, and currently teaches three courses in M&S and Digital Engineering in
the M.S. in Systems Engineering program of the JHU Engineering for
Professionals. He holds B.S. and M.S. degrees in aerospace engineering