Modeling and Simulation Flashcards

Flashcards based on lecture notes covering the history, components, classifications, applications, and best practices of modeling and simulation.

What is the origin of modeling and simulation?

Numerical simulation, spurred by World War II research (1940s).

What were key developments in early modeling and simulation?

ENIAC (first electronic programmable computer) and the Manhattan Project's nuclear detonation models.

What significant advancements occurred in modeling and simulation through the 1950s and beyond?

CAD, the establishment of the Winter Simulation Conference (1967), and increased accessibility of computers (1980-present).

What are the advantages of modeling and simulation?

Safer, more efficient, effective than real-life simulations; helps identify unexpected problems; allows testing before implementation; provides accurate results; explores possibilities.

What are the disadvantages of modeling and simulation?

Errors in model setup/programming, higher initial investment, and time to articulate/analyze results.

What is a system?

An organized collection of entities linked together according to a plan to accomplish a specific goal.

What are system limitations?

Must always be clearly identified.

What are system components?

Fundamental parts of a system that have organized relationships with each other or the environment.

What is an entity?

Object of interest in a system.

What is an attribute?

Property of an entity.

What is an event?

Instantaneous occurrence that may change the state of the system.

What is system state?

A collection of variables necessary to describe a system at a given point in time, relative to the study's objectives.

What is system progress?

The gradual development of a system analyzed by monitoring changes in a system's state.

What is the system environment?

The “supersystem” within which a smaller system or organization operates.

What is system analysis?

Process of collecting and interpreting facts, identifying problems, and possible solutions, possibly through system decomposition.

What is a model?

An examinable representation of a system.

What is simulation?

An applied methodology that can describe the behavior of a system using either a mathematical or symbolic model.

What is an aleatory variable?

Refers to random phenomena and events in an environment that exhibit natural randomness.

What is epistemic uncertainty?

Pertains to scientific uncertainties in a simulation model caused by limited data and knowledge.

What is a discrete system?

State variables change instantaneously at separated points in time (e.g., queuing systems).

What is a continuous system?

State variables change continuously with respect to time (e.g., movement of an airplane).

What is a hybrid system?

A combination of continuous and discrete systems, allowing more flexibility in modeling (e.g., continuous traffic with multiple traffic lights).

What is a physical system?

Composed of quantitative components or variables that can be measured through physical devices (e.g., electrical, mechanical, and computer systems).

What is a conceptual system?

Consists of theoretical and qualitative components or variables that cannot be measured (e.g., psychological and economic systems).

What is an esoteric system?

Designed for understanding by a small group with specialized knowledge, exhibiting the highest level of complexity.

What are independent systems?

Events within the system do not affect each other.

What are cascaded systems?

Effects of events are unilateral, where one event affects the next in a sequence.

What are coupled systems?

Events mutually affect each other, meaning one event influences another and vice versa.

What is a deterministic system?

No uncertainties exist in any variable involved in the system.

What is a stochastic system?

Some variables in the system are arbitrary or inconsistent, introducing uncertainty.

What is a fuzzy system?

Variables are difficult to understand and explain clearly, leading to ambiguity in the system's behavior.

What are the basic applications of simulation?

Gathering insights, validation of experiments, simulation-based training, supporting different statistical analyses, computer animation, controlling real-time processes, predicting outcomes, evaluating new systems, enhanced education.

What are the best practices in modeling and simulation?

Always define a set of objectives, include sufficient physical phenomena, focus on converting the actual problem into an equation, carefully configure the model, select appropriate software, be mindful of possible errors, closely monitor validity, and identify proper maintenance frequency.

What is systems modeling?

The process of creating abstract representations of a system to depict its internal processes and behaviors.

What is a logical model?

A model that represents all the plausible requirements of a system.

What is a mathematical model?

A mathematical description of properties and interactions in a system.

What is a white-box model?

Encompasses systems where all necessary information is available.

What is a black-box model?

Associated with systems without prior information available.

What are the characteristics of a model described by English text?

Good descriptive capabilities, very ambiguous, no manipulation capabilities, limited implementation capabilities.

What are the characteristics of a model using drawings and block diagrams?

Good descriptive capabilities, not ambiguous, no manipulation capabilities, good implementation capabilities.

What are the characteristics of a model using logical flowcharts and decision tables?

Fair descriptive capabilities, not ambiguous, no manipulation capabilities, good implementation capabilities.

What are the characteristics of a model using curves, tables, and monographs?

Fair descriptive capabilities, not ambiguous, good manipulation capabilities, no implementation capabilities.

What are the characteristics of a mathematical model?

Poor descriptive capabilities, not ambiguous, excellent manipulation capabilities, good implementation capabilities.

What are physical models?

Tangible replicas (tabletop scale models).

What are abstract models?

Models that represent systems through logical or quantitative relationships (flowcharts).

What are mathematical models?

Mathematical symbols that describe systems (Pythagorean theorem).

What are descriptive models?

Models that provide practical descriptions of systems and their relationships (model for profiling Google play).

What are static models?

Models that represent systems at a specific time (floor plans).

What are dynamic models?

Models that depict systems as they evolve over time (conveyor system model of a factory).

What are steady state models?

Models that exhibit consistent behavior over time.

What are transient models?

Models that reflect changing behavior, often during one-time phenomena or growth.

What are deterministic models?

Models that have predictable outputs based on inputs (complex differential equations describing a chemical reaction).

What are stochastic models?

Models that produce random outputs that are estimates of true characteristics (inventory systems model).

What are continuous models?

Models that represent smooth changes in a system.

What are discrete models?

Models that involve abrupt changes in system states.

Where does the term 'simulation' originate?

Comes from the Latin word "simulare," meaning "to pretend."

What is simulation?

A safe and powerful method for experimenting with system models, but the accuracy of results relies on the quality of the model.

What are the advantages of simulation?

Provides deeper understanding of complex systems, offers better insights into resource performance, allows exploration of multiple alternatives, saves time and money through virtual experimentation, improves quality of analysis and decision-making, enhances existing processes and aids in planning new facilities.

What is physical simulation?

Experimentation with a physical prototype of a real system, comparing outputs with actual system results.

What is numerical simulation?

Utilizes mathematical models for sequential calculations, making it easy to develop and modify.

What is digital (computer) simulation?

Employs digital computers to simulate equations of a system, characterized by clarity of representation and high automation.

What is efficiency in simulation?

Higher mission and operational system availability, transportation avoidance, and reduced costs.

What is effectiveness in simulation?

Improves proficiency, simplifies complex activities, and enhances observation and analysis capabilities.

What is risk reduction in simulation?

Ensures stakeholder safety, minimizes environmental impact, and facilitates machinery handling.

What is Monte Carlo simulation?

A mathematical technique that generates random sample data for risk quantitative analysis and decision-making.

What is agent-based modeling?

Simulates interactions of autonomous agents to understand complex behaviors and dynamics within a system.

What is discrete event simulation?

Models complex systems as a sequence of well-defined events, tracking changes in system states over time.

What is system dynamics simulation?

A modeling technique that analyzes complex systems' overall behavior, emphasizing feedback loops and time delays for long-term strategic insights.

What are queuing systems?

Found in any context where multiple entities compete for limited resources.

What is queuing theory?

Mathematically analyzes congestion and delays, focusing on components like the arrival process, service process, number of servers, system capacity, and customer population.

What are the strengths of queuing models?

Increased efficiency, productivity, reduced customer walkaways, better trend analysis, and higher customer lifetime value.

What are the weaknesses of queuing models?

Potential for long wait times, queue jumping, reneging (customers leaving the queue), and crowd management challenges.

What is a customer in a queuing model?

Any entity requiring service.

What is a server in a queuing model?

The resource providing service.

What is a calling population in a queuing model?

Can be finite (arrival rate depends on current system state) or infinite (arrival rate is independent).

What is system capacity in a queuing model?

Maximum number of customers allowed in the system.

What is the arrival process in a queuing model?

Describes how customers arrive (random or scheduled).

What is queue behavior in a queuing model?

How customers act while waiting (e.g., leaving if the queue is too long).

What is queue discipline in a queuing model?

The rule for selecting the next customer (e.g., FIFO, LIFO, priority).

What is service time in a queuing model?

Duration of service, often modeled as a random variable.

What is the service mechanism in a queuing model?

Number and arrangement of service centers and servers.

What is Kendall’s Notation?

Standard notation for queuing models: (A/B/c), where A is the interarrival time distribution, B is the service time distribution, and c is the number of servers. System capacity (N) and population size (K) are included if finite.

What is Queuing Simulation?

Simulations are used to analyze system performance and test models, often using assumptions and simplifications.

What are common performance metrics in queuing simulations?

Average waiting time, probability a customer must wait, proportion of server idle time, average service time, average time between arrivals, and average time spent in the system.

What are Pseudorandom Number Generators (PRNGs)?

Algorithms that generate sequences of numbers that mimic randomness, crucial for simulations and cryptographic applications.

What are the characteristics of PRNGs?

Efficient, deterministic (repeatable with the same seed), and periodic (sequence eventually repeats).

What is input data modeling?

Involves collecting and analyzing input data to improve the accuracy of simulations, especially in discrete event simulations like queuing systems.

What are good practices in data collection?

Plan ahead, analyze data during collection, use scatter diagrams to check relationships, and check for autocorrelation.

What is a histogram?

A graphical representation that groups data into ranges (bins) to show frequency distributions.

Name some families of distributions.

Exponential (time between events), Normal (bell-shaped, symmetric about the mean), and Poisson (count of events in a time period).

What is parameter estimation?

After selecting a distribution, estimate its parameters (mean, variance) using formulas based on whether the data is raw, grouped by frequency, or grouped into intervals.

Name some Goodness-of-Fit Tests.

Chi-Square Test (for large samples) and Kolmogorov-Smirnov Test (for small samples).

What is output analysis for simulation models?

Examines data from simulation runs to predict or compare the performance of different system designs.

What is the purpose of output analysis?

To estimate the mean and variance of random variables, or determine how many observations are needed for a desired precision.

What is a trace?

The basic output data from a simulation run.

What is the mean in output analysis?

Shows the main characteristic of output data.

What is standard deviation in output analysis?

Summarizes variability.

What is a histogram in output analysis?

Shows data distribution.

What is point estimation?

Produces a single value estimate of a population parameter.

What is interval estimation?

Estimates a parameter within a range (confidence interval) with a given probability.