Modeling and Simulation (H1)

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Modeling and Simulation Quiz

Test your knowledge on Modeling and Simulation with our comprehensive quiz! Dive deep into the foundations and classifications of systems, their components, and methodologies.

This quiz is designed for those interested in:

  • Understanding core concepts in system modeling
  • Exploring the historical context of numerical simulation
  • Differentiating between various types of systems
32 Questions8 MinutesCreated by AnalyzingData42
Originated from the concept of numerical simulation in 1940, which was also marked as the beginning year of computer science
Electronic Numerical Integrator and Computer (ENIAC)
Three-phase method
Computer-Aided Design (CAD) w
Modeling and simulation
Was the first electronic programmable computer that could solve a large class of numerical problems.
Electronic Numerical Integrator and Computer (ENIAC)
Three-phase method
Computer-Aided Design (CAD) w
Modeling and simulation
In the mid-1950s, Keith Douglas Tocher established the
Electronic Numerical Integrator and Computer (ENIAC)
Three-phase method
Computer-Aided Design (CAD) w
Modeling and simulation
Widely used for discrete simulation.
Electronic Numerical Integrator and Computer (ENIAC)
Three-phase method
Computer-Aided Design (CAD) w
Modeling and simulation
In the late 1950s, it was developed
Electronic Numerical Integrator and Computer (ENIAC)
Three-phase method
Computer-Aided Design (CAD) w
Modeling and simulation
This allowed engineers to convert drawn designs into numerical designs and visualize in 2D and 3D.
Electronic Numerical Integrator and Computer (ENIAC)
Three-phase method
Computer-Aided Design (CAD) w
Modeling and simulation
Basic System Components: It refers to an object of interest in a system
Entity
Attribute
Event
System State
System Progress
System environment
System Analysis
Basic System Components: It is an instantaneous occurrence that may change the state of the system.
Entity
Attribute
Event
System State
System Progress
System environment
System Analysis
Basic System Components: It refers to the property of an entity
Entity
Attribute
Event
System State
System Progress
System environment
System Analysis
Basic System Components: It is a collection of variables necessary to describe a system at a given point in time, relative to the study's objectives.
Entity
Attribute
Event
System State
System Progress
System environment
System Analysis
Basic System Components: The gradual development of a system can be analyzed by monitoring the changes in a system's state.
Entity
Attribute
Event
System State
System Progress
System environment
System Analysis
Basic System Components: Is the "supersystem" within which a smaller system or organization operates.
Entity
Attribute
Event
System State
System Progress
System environment
System Analysis
Basic System Components: Is the process of collecting and interpreting facts and identifying problems and possible solutions, possibly through system decomposition.
Entity
Attribute
Event
System State
System Progress
System environment
System Analysis
Are the fundamental parts of a system having an organized relationship with each other or the environment.
System
System limitations
System components
Must always be clearly identified. These basically defines the composition of a system, inside and out.
System
System limitations
System components
Is an organized collection of entities linked together according to a plan to accomplish a specific goal
System
System limitations
System components
Classifications of Systems: (According to Time Frame) The state variables change instantaneously at separated points in time.
Discrete system
Continuous system
Hybrid system
Classifications of Systems: (According to Time Frame) The state variables change continuously with respect to time.
Discrete system
Continuous system
Hybrid system
Classifications of Systems: (According to Time Frame) It is a combination of a continuous and discrete system that has the benefit of encompassing a larger class of systems within its structure, allowing more flexibility in terms of modeling.
Discrete system
Continuous system
Hybrid system
Classifications of Systems: (According to Complexity) This system is intended to be understood by a small number of people with specialized knowledge or interest.
Physical system
Conceptual system
Esoteric system
Classifications of Systems: (According to Complexity) The components or variables of this system are theoretical and in qualitative form
Physical system
Conceptual system
Esoteric system
Classifications of Systems: (According to Complexity) The components or variables of this system are quantitative and measured through physical devices
Physical system
Conceptual system
Esoteric system
Classifications of Systems: (According to Degree of Interactions) The events within the system do not affect each other (i.e., event A does not affect event B and vice versa).
Independent systems
Cascaded systems
Coupled systems
Is an examinable representation of a system. It may represent an event and/or an entity, which can be real or contrived.
Model
Simulation
Aleatory Variable
Epistemic Uncertainty
Is an applied methodology that can describe the behavior of a system using either a mathematical model or a symbolic model
Model
Simulation
Aleatory Variable
Epistemic Uncertainty
These are specific phenomena and events in any environment which are considered random, simply because there is no better way of characterizing them
Model
Simulation
Aleatory Variable
Epistemic Uncertainty
These are the scientific uncertainties in the simulation model, commonly caused by limited data and knowledge.
Model
Simulation
Aleatory Variable
Epistemic Uncertainty
Classifications of Systems: (According to Degree of Interactions) The events mutually affect each other (i.e., event A affects event B and vice versa).
Independent systems
Cascaded systems
Coupled systems
Classifications of Systems: (According to Degree of Interactions) The effects of the events are unilateral (i.e., event A affects event B, B affects C, C affects D, and not in reverse).
Independent systems
Cascaded systems
Coupled systems
Classifications of Systems: (According to Degree of Interactions) The events within the system do not affect each other (i.e., event A does not affect event B and vice versa).
Independent systems
Cascaded systems
Coupled systems
Advantages of Modeling and Simulation:
Safer, more efficient, and effective than an actual or real-life simulation
Used to identify unexpected problems.
Allow stakeholders to test a product or a system before building it.
Used to explore and evaluate possibilities
Results are generally not accurate
Disadvantages of Modeling and Simulation:
Possible to commit errors in setting-up
A higher initial investment cost is required
Requires some time to articulate results
Results are generally not accurate
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