Lecture Notes Ppt Top | Modeling And Simulation
Building a model is meaningless if it fails to accurately simulate the intended system behavior.
(Dr. Imtiaz Hussain): These lecture notes focus on physical systems, including transfer functions, state-space models, and the simulation of mechanical and electrical systems.
The backbone of any DES program relies on two primary data structures:
┌───────────────────────────────────────────────────┐ │ Real-World System │ └─────────────────────────┬─────────────────────────┘ │ Validation (Am I building the right thing?) │ ▼ ┌──────────────────────┐ Verification ┌──────────────────────┐ │ Conceptual Model ├───────────────>│ Computational Model │ │ (Logic / Equations) │ (Am I building │ (Code / Software) │ └──────────────────────┘ the thing right?) └───────────────────┘ Verification (Code Accuracy)
Slide 8 — Modeling Process (Lifecycle)
Slide 23 — Ethical & Practical Considerations modeling and simulation lecture notes ppt top
This tracks a system as a chronological sequence of events. Each event occurs at a specific point in time and marks a change of state in the system. Example: Customers arriving at a bank teller. B. Continuous Simulation
: Triggered when a continuous variable crosses a defined threshold (e.g., a thermostat turning off a heater when temperature hits 22°C).
Step 1: Fetch the most imminent event from the FEL. Step 2: Advance the Simulation Clock to that event's time. Step 3: Execute the logic associated with that event type. Step 4: Update system states and statistics. Step 5: Schedule future events and insert them into the FEL. Step 6: Repeat until the termination condition is met. 3. Continuous and Hybrid Simulation
Simulating years of behavior in minutes, or slowing down high-speed events.
X=−1λln(1−U)cap X equals negative the fraction with numerator 1 and denominator lambda end-fraction l n open paren 1 minus cap U close paren is statistically identical to , this simplifies to: Building a model is meaningless if it fails
: The process of creating a simplified representation of a real-world system or entity to facilitate study. It relies on abstraction to focus only on relevant variables. Simulation
There are several types of models, including:
Standard lecture materials typically distinguish between the two terms:
Balancing loops (which stabilize systems) and reinforcing loops (which cause exponential growth or collapse). 8. Summary: Choosing the Right Framework Simulation Paradigm System Perspective Primary Component Time Advance Mechanism Typical Applications Discrete-Event (DES) Process-oriented / Operational Entities, Queues, Resources Next-Event / Variable Step Supply chains, manufacturing plants, call centers Continuous (SD/ODE) State-oriented / Aggregate Stocks, Flows, Integrators Fixed-Step / Variable-Step Numerical Fluid dynamics, macroeconomics, chemical reactions Agent-Based (ABM) Behavior-oriented / Decentralized Autonomous Agents, Rules Fixed Tick / Event-driven Crowd mechanics, market ecology, epidemiology
Simulates the actions and interactions of autonomous "agents" to assess their effects on the system as a whole. Introduction to Modeling and Simulation Techniques The backbone of any DES program relies on
" textbook, these slides define the nature of simulation, discrete-event simulation, and single-server queueing systems . Key Concepts Typically Covered Simulation Modeling - Lecture Notes
, these techniques enable a "learn-before-doing" approach that is essential for modern innovation. Core Concepts and Definitions
Modeling and simulation have a wide range of applications, including:
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