EECE.5492 Systems, Modeling and Simulations for Digital Eng (3cr)
This course provides a high-level view of systems thinking, systems engineering, physical system modeling and model-based systems engineering (MBSE) in the context of digital transformation initiatives taking place in government and industry. Examples of systems engineering practice are drawn from government acquisition processes. State-space models of system dynamics are introduced considering deterministic and random effects. Security primitives and threat modeling tools are reviewed and their integration during the design phased discussed. System dynamics will be simulated using MATLAB, Simulink and Python programming platforms Students will learn to implement MBSE using the systems modeling language (SySML) and supporting commercial or open-source software platforms In team-based project work, students will emulate a digital transformation of stakeholder requirements examine design trade-offs by integrating the MBSE representation with dynamic system simulations.
EECE.5494 Model-Based Systems Engineering (3cr)
This course provides experiential learning in implementing Model-Based Systems Engineering (MBSE) from an applications perspective. Principles of systems thinking and practices in design of engineered systems are discussed. The mapping of systems engineering stages to a model-based graphical representation in undertaken with the systems modeling (SysML) language and supporting programming platforms. Model-based representation of stakeholder requirement, use-cases and scenarios, system and interface architecture will be learnt through case studies drawn from mission operations. MBSE practitioners will present their best practices for integrating respective models for verification, validation, traceability and presentation to teams with differing backgrounds and expertise.
Requirements:
EECE.5492 Systems, Modeling and Simulation for Digital Eng.
EECE.5496 Cyber-Physical Systems Modeling and Simulation (3cr)
Physical systems and their interactions with embedded digital sub-systems and communication networks are analyzed by representing them in the context of cyber-physical systems (CPS). Related concepts of system control, hybrid dynamical systems and state estimation are presented. The application of the CPS model as a digital twin and approaches for representing the model across it's lifecycle are explored. The specification of functional, behavioral and security requirements for CPS using a model-based systems engineering framework is undertaken. The performance verification with multiphysics models and simulation experiments are conducted. Particular focus will be on the verifying correctness of algorithms that control the CPS and challenges in bridging continuous and discrete event based systems that comprise a CPS.
Requirements:
EECE.5492 Systems, Modeling and Simulation for Digital Eng.
EECE.5498 Data-Driven Models, Decision Making, and Risk Mgmt (3cr)
This course addresses the application of data recorded from models, simulation or measurements for prediction, inference of estimation of system behavior. Students are introduced to AI/machine learning algorithms, data visualization and data analytics. The focus will be on the analysis of decisions driven by data and models using concepts of decision trees, multi-objective models and game theory. Methods for estimating costs and managing risks across the lifecycle of the system will be discussed. Case studies will be drawn from the government and industry that highlight mission statements with proposed strategy, tactics and operations. Optimization methods that address these directives with associated uncertainty parameters will be explored in team-based projects.
Requirements:
EECE.5492 Systems, Modeling and Simulation for Digital Eng.