Midterm Flashcards
(34 cards)
modeling real world scenario
- e.g. traffic congestion, weather forecast, real-time laws
Modeling and Simulation
- done inside a confined/isolated environment which does not affect any production system
- In IT and CS, LAB Simulations are usually utilized
LAB SIMULATION
is used to ready your workers
LAB SIMULATION
- crucial tool in various fields of works
- FOCUS: Stepped Time Simulation, Event-based Simulation
SIMULATION TIME HANDLING
are in fixed term intervals
- e.g. weather - temperature, wind speed, precipitation, time
- details for reportings
- for continuous development
- e.g. every two weeks, there will be a report
STEPPED TIME SIMULATION
- determine the behavior based on given time
- ease of implementation
- suitability for continuous system
Advantages of Stepped time simulation
- computational inefficiency: too slow to compute big data
- difficulty in handling rare events - abnormalities in the linear progression
- accuracy trade off
LIMITATIONS of stepped time simulation
has an event trigger
- e.g. earthquake, stock market
EVENT-BASED SIMULATION
- computational efficiency
- higher accuracy
- scalability
Advantages of event-based
- complex implementation
- not suitable for continuous system
LIMITATIONS of event based
- not applicable at the current time
- combination of stepped-time and event-based
HYBRID SIMULATION
- creation of mathematical representation of real world problems/systems
- to study a behavior
- predict future states of the thing you are representing
MODELING
- use of models to study the behavior of a system over time
- e.g. crash - we need to evaluate the timing, precision, activation of the system (e.g. airbags)
- e.g. in it - creating bugs before publicly engaging in the implementation of the project
SIMULATION
similar to stepped time
: changes occur at a specific interval
: e.g. queuing system (depends on the amount of customers), cellular automata (spatially and
temporally finite-state discrete computational systems composed of a finite set of cells evolving
in parallel at discrete time steps.), digital circuits (uses binary signals to process data)
DISCRETE MODEL
changing smoothly and continuously overtime
: e.g. physics based simulation (e.g. boiling point), fluid dynamics (weather prediction),
population growth (predict how much population will grow)
: should not be bothered by intervals
CONTINUOUS MODEL
- countable = discrete
- evolution or changes coming smoothly = continuous
understand the nature of the system
- event-driven data = discrete
- precise measurements available that changes overtime = continuous
data availability
- logical computation = discrete
- based on the availability of data
- complex computation using numerical method = continuous
computational resources
- some studies need d+c approach = HYBRID MODEL
- e.g. heat transfer (continuous), 3 stoves (discrete), capacity of the stoves to heat water faster
from point a to point b (0 to boiling point)
accuracy
solves scientific problem
- whenever analytical methods are not feasible
NUMERICAL METHODS
based on differential methodologies
- get first the center
e.g. heat conduction
FINITE DIFFERENCE METHOD
- complex engineering equations
- CUT THROUGH ONE SEGMENT
- find out the strength of the material/product
FINITE ELEMENT Method
a mathematical technique that uses random numbers to
simulate possible outcomes of an uncertain event
MONTECARLO SIMULATION
approximating the roots of an equation through repetitive
numerical methods
ROOT FINDING SIMULATIONS
