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Modeling and Simulation in Graphics, Gaming, and Biology

Explore the world of modeling and simulation in graphics, gaming, and computational biology. Learn about complex systems, discrete and continuous simulation, queuing systems, meteorological models, and computational biomodeling. Understand the importance of simulation in predicting outcomes and analyzing complex systems.

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Modeling and Simulation in Graphics, Gaming, and Biology

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  1. Chapter 14 Simulation, Graphics, GamingandOtherApplications

  2. Chapter Goals – THE BIG SLICES • Models and Simulation • Computational Biology • (Complex) Computer Graphics • Computer Gaming

  3. Chapter Goals • Models and Simulation • Complex Systems • Continuous and Discrete simulation • Object-oriented design and building models • Queuing systems • Weather and Seismic models

  4. Chapter Goals • Computational Biology • Bioinformatics • Computational Biomodeling • Protein Modeling • Molecular Modeling

  5. Chapter Goals • Computer Graphics • The CREATION of complex images • CAD • Fractal and Other Techniques • Light and Rendering • Movement

  6. Chapter Goals • Computer Gaming • The LAYERS • Design and Development • Game Programming

  7. Complexity! • Some real-world systems are complicated • We want to model complex systems to: • better understand them • predict the future

  8. What is a Model? • An Abstraction of a Real World System • A representation of the objects or quantities within the system (Noun, the Data) • and the rules that govern the interactions between them (Verb, the Code & Algorithms) • Systems that are best suited to being simulated are dynamic, interactive, and complicated

  9. What Is Simulation? • Simulation is RUNNING a model to PREDICT the results of experimental CHANGES in the system • Doing “What If” analysis “What happens if I change this? “What happens if I don’t?”

  10. Kinds of Models

  11. Kinds of Models • There are 2 Big Slices: • Discrete Models • Continuous Models

  12. Kinds of Models • Discrete event simulation • Made up of entities, attributes, and events • Entity The representation of some object in the real system • Attribute Some characteristic of a particular entity • Event An interaction between entities

  13. Air Traffic – A Discrete Model • Air Traffic in USA • Planes are objects • Attributes include speed • Events are planes entering and leaving airspace

  14. Kinds of Models • Continuous simulation • Treats time as continuous • Expresses changes in terms of a set of differential equations that reflect the relationships among the quantities in the model • Meteorological models falls into this category

  15. Hurricanes – A Continuous Model

  16. A Continuous Models and FEA • Finite Element Analysis (FEA): Dividing a volume of space into small cubes, which contain our quantities of interest • Many Continuous Models Use FEA

  17. Queuing Systems

  18. Queuing Systems Queuing system: A particular kind of discrete-event model The system is made up of • Server objects • Clients objects • Queues of clients to be served Please Wait….

  19. Queuing Systems • Can you name at least three queuing systems that you interact with every day? Please wait!

  20. Queuing Systems • To construct a queuing model, we must know • The number of events and how they affect the system in order to determine the rules of entity interaction • The number of servers • The distribution of arrival times in order to determine if an entity enters the system • The expected service time in order to determine the duration of an event

  21. Queuing Systems • Given a hypothetical service station, what are • the events? • the number of servers? • How can you determine • distribution of arrival time? • expected service time?

  22. Meteorological Models

  23. Weather – A Continuous Model

  24. Meteorological Models Meteorological models • Models based on the time-dependent partial differential equations of fluid mechanics and thermodynamics • Initial values for the variables are entered from observation, and the equations are solved to define the values of the variables at some later time

  25. Meteorological Models How much math does it take to be a meteorologist?

  26. Weather – A Continuous Model

  27. Hurricane Tracking (GFDL) Geophysical and Fluid Dynamics Laboratory Figure 14.2 Improvements in hurricane models

  28. Computational Biology

  29. Computational Biology • The application of computer science to problems in biology • (or is it the other way around??  ) • Encompasses: • bioinformatics • computational biomodeling • molecular modeling • protein structure prediction 29

  30. Computational Biology • Bioinformatics • Discovering and Processing DNA sequences • Human Genome Project and Others 30

  31. Computational Biology • Computational Biomodeling • The simulation of biological systems Knees Cell Wall Protein Cell Metabolism 31

  32. Computational Biology • Protein Structure Modeling • Simulating 3-Dimensional Structure and Function of Protein Molecules 32

  33. Computational Biology • Molecular Modeling • Simulating Structure and Function of Chemical Molecules (usually drug discovery) 33

  34. Graphics

  35. “Traditional” Graphics • Technical or Engineering Graphics • Originally a language of communication for engineers, designers, and architects • Computer-Aided Design (CAD) • A system that uses computers with advanced graphics hardware and software to create precision drawings or technical illustrations

  36. Graphics for Computer Aided Design Figure 14.3 Geometric modeling techniques

  37. Simulating Light Ray Tracing The projection of a 3-Dimensional model onto a 2-Dimensional computer screen

  38. Simulating Light Illumination model Used to simulate the interaction of light with objects Objects are Shaded Rendered

  39. Fractal Techniques

  40. Modeling Complex Objects What graphics challenges are inherent in natural landscapes ? Figure 14.5 A natural computer generated landscape

  41. Fractal Terrain Fractal terrains via Midpoint subdivision (Fractal Mountains)

  42. “Cell” Models

  43. Earth, Wind, Fire and Water • Cell-Based Models • Like continuous FEA models • Uses quantities and laws from physics • “How is a hurricane like a glass of water?” • Or a Cloud? • Or Fire? • Or Smoke?

  44. Cell Models Figure 14.7 Water pouring into a glass

  45. Cell Models Figure 14.8 Cellular automata-based clouds

  46. Modeling Complex Objects Cell Models What do clouds, smoke and fire have in common? Figure 14.9 A campfire

  47. Gaming

  48. ComputerGaming • A simulation of a virtual world • Usually based on the rules of our real world • Some rules can be bent • Some rules can be broken • 

  49. ComputerGaming • Game designers need to know the LAYERS: • Computer graphics • Artificial intelligence • Human-computer interactions and simulation • Software engineering (management of large complex projects) • Computer security • Laws of physics relating to gravity, elasticity, light & sound

  50. Creating the Virtual World • Game engine: • A software system within which games can be created (A tool to create games) • Analogous to a compiler (A tool to create programs) • (Similarly, some people write engines, some people write games)

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