Modeling is a way of thinking and reasoning about systems. It is a process that moves in evolutionary fashion from simple to more elaborate to reflect the complexity of the system being modeled. Examine the intuitive process by which scientists and engineers develop and use models for problem solving. The course will focus on modeling fundamentals; architecture and data; and systems, behavior, and execution.

• Engineers
• Scientists
• Technical managers

• Describe the simulation life cycle and where modeling fits in this process
• Understand the different model representations and how they are used to describe the problem domain
• Describe the relationship between systems and theory, and how assumptions are critical to forming valid models
• Explore how fidelity, resolution and accuracy are related to modeling
• Understand the difference between data, information and knowledge
• Learn about conceptual models and their relationship to reference architectures
• Explore systems thinking and how that supports conceptual modeling
• Hands-on experience developing a conceptual model
• Explore how models are used in everyday problem solving

• Modeling & Simulation Life Cycle
• Model Representations and Uses
• Problem Formulation, Assumptions and Theory
• Fidelity, Resolution, and Accuracy
• Model Validation
• Data, Information and Knowledge
• Conceptual Models, Techniques and Tools
• Model-Base Problem Solving
• Model Execution, Interoperability, Reusability and Composability

Participants receive a notebook with slides and copies of conference papers discussed in the course.

There are no prerequisites, though some technical background or training is beneficial.