Part I: Modeling and Simulation Fundamentals -- Introduction to Modeling and Simulation -- The Modeling and Simulation Lifecycle Process -- Fidelity, Resolution, Accuracy and Uncertainty -- Conceptual Modeling -- Types of Models -- Model Verification and Validation -- Part II: Methods and Methodologies -- Modeling the Environment -- Modeling Behavior -- Modeling Time -- Discrete Event Simulation -- Continuous Time Simulation -- Agent Based Simulation -- System Dynamics Simulation -- Hardware-in-the-Loop Simulation -- Human-in-the-Loop Simulation -- Part III: Experimentation, Execution and Results -- Design of Experiments -- Surrogate Modeling -- Monte Carlo Analysis -- Wargames -- Distributed Simulation and Architectures -- Part IV: Introduction to Systems Engineering -- Systems Engineering Fundamentals -- Introduction to Systems Thinking -- Model Based Systems Engineering -- Part V: M&S in Systems Engineering Life Cycle -- Real-time Data Driven Arterial Simulation for Performance Measure Estimation -- Rotorcraft Pilot's Associate -- Framework Assessing Cost and Technology -- Model Based Systems Engineering: Extracorporeal Membrane Oxygenation (ECMO) Therapy -- Computational Modeling of Complex Enterprise Systems: A Multi-Level Approach -- Real Time Simulation of a Nuclear Power Plant with Embedded Hardware -- Return on Investment Metrics for Funding Modeling and Simulation. This easy to read text provides a broad introduction to the fundamental concepts of modeling and simulation (M&S) and systems engineering, highlighting how M&S is used across the entire systems engineering lifecycle. Features: reviews the full breadth of technologies, methodologies and uses of M&S, rather than just focusing on a specific aspect of the field; presents contributions from specialists in each topic covered; introduces the foundational elements and processes that serve as the groundwork for understanding M&S; explores common methods and methodologies used in M&S; discusses how best to design and execute experiments, covering the use of Monte Carlo techniques, surrogate modeling and distributed simulation; explores the use of M&S throughout the systems development lifecycle, describing a number of methods, techniques, and tools available to support systems engineering processes; provides a selection of case studies illustrating the use of M&S in systems engineering across a variety of domains.