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Modeling Scenarios feed

  1. 1-062-S-BacterialGrowth

    15 Sep 2018 | Modeling Scenarios | Contributor(s):: Arati Nanda Pati

    We offer students a simulation experience or data from a simulation and ask them to model the simulation using several approaches andusing EXCEL spreadsheet. In this particular modeling scenario, we know the exact solution and want to see how various models predict our expectations. We have used...

  2. 6-006-S-ZombieGameHvZ

    09 Sep 2018 | Modeling Scenarios | Contributor(s):: Jue Wang

    Invented in 2005, Humans vs. Zombies, or HvZ, is a game of tag, predominantly played at US college campuses. In this activity, students use systems of non-linear differential equations to model the HvZ game. Many alternate rule sets provide options to formulate different models. Students solve...

  3. 1-053-S-SlimeSpread

    30 Aug 2018 | Modeling Scenarios | Contributor(s):: Brian Winkel

    We offer a video showing real time spread of a cylinder of slime and challenge students to build a mathematical model for this phenomenon.

  4. 6-003-S-SchoolFluEpidemic

    28 Aug 2018 | Modeling Scenarios | Contributor(s):: Darrell Weldon Pepper

    We offer a model of the spread of flu in a school dormitory and are asked to find when the flu levels reach their peak and explain long term behavior of the spread of the flu.

  5. 1-141-S-M&MGameRevisited

    27 Aug 2018 | Modeling Scenarios | Contributor(s):: Mehdi Hakim-Hashemi

    In this project students will learn to find a probability distribution using the classical M&M game in SIMIODE.

  6. 1-108-S-PoissonProcess

    27 Aug 2018 | Modeling Scenarios | Contributor(s):: Mehdi Hakim-Hashemi

    In this project students learn to derive the probability density function (pdf) of the Poisson distribution and the cumulative distribution (cdf) of the waiting time. They will use them to solve problems in stochastic processes.

  7. 1-118-S-SolowEconomicGrowth

    22 Aug 2018 | Modeling Scenarios | Contributor(s):: Yuri Yatsenko

  8. 7-040-S-TankInterruptMixing

    22 Aug 2018 | Modeling Scenarios | Contributor(s):: Norman Loney

    We present a differential equation model for the interrupted mixing of a tank with salt water. We offer two solution strategies (1) two step approach and (2) Laplace Transforms.

  9. 7-020-S-ThermometerInVaryingTempStream

    22 Aug 2018 | Modeling Scenarios | Contributor(s):: Norman Loney

    We present a differential equation model for the temperature of a mercury thermometer which is sitting in a stream of water whose temperature oscillates. We suggest a solving strategy which uses Laplace Transforms.

  10. 1-138-S-InnerEarDrugDelivery

    20 Aug 2018 | Modeling Scenarios | Contributor(s):: Jue Wang

    Hearing loss is difficult to treat due to the inner ear location and structure. Drawing from this challenging case, this scenario guides students to transform a treatment protocol into a mathematical model. Students engage in pre-clinical studies to examine local drug delivery to the cochlea. The...

  11. 4-055-S-ShatterWineGlass

    20 Aug 2018 | Modeling Scenarios | Contributor(s):: Jue Wang

    This module takes students through real life scenarios to examine resonance and its destructive power using differential equation models. What is resonance? How does it happen? Why is it important? Three cases are presented: shattering a wine glass, collapse of a suspension bridge, and crash of...

  12. 1-067-S-ModelingWithSigmoidCurves

    18 Aug 2018 | Modeling Scenarios | Contributor(s):: Natali Hritonenko

    The assignment considers two well-known models of population growth, Verhulst-Pearl and Gompertz models, for which qualitative and quantitative analyses are provided. The graphs of the corresponding functions have a sigmoidal or S-shape. The assignment contains two opposite, but related tasks:...

  13. 1-032-S-DigoxinElimination

    17 Aug 2018 | Modeling Scenarios | Contributor(s):: Therese Shelton

    We model the concentration of digoxin eliminated from the human body at a rate proportional to the concentration. This is a ``first-order reaction'' in the language of pharmacokinetics -- the study of how drugs move in the body. This activity can be used to introduce compartmentalized...

  14. 1-131-S-CaffeineElimination

    15 Aug 2018 | Modeling Scenarios | Contributor(s):: Therese Shelton

    We model the concentration of caffeine eliminated from the human body at a rate proportional to the concentration. This is a reaction in the language of pharmacokinetics -- the study of how drugs move in the body. This simple activity can be used to introduce differential equations, and it can be...

  15. 1-130-S-AspirinAbsorption

    15 Aug 2018 | Modeling Scenarios | Contributor(s):: Therese Shelton

    We model the amount of aspirin absorbed by the human body at a constant rate. This is a ``zero-order reaction'' in the language of pharmacokinetics -- the study of how drugs move in the body. This simple activity can be used to introduce differential equations and it can be used to...

  16. 1-089-S-SpreadOfDisease

    15 Aug 2018 | Modeling Scenarios | Contributor(s):: Shinemin Lin

    In this project we use the algebra based concept “difference quotient” to solve differential equations models with the help of Excel.

  17. 1-054-S-GrowthInFarmland

    14 Aug 2018 | Modeling Scenarios | Contributor(s):: Richard Spindler

    An enriching project developing a model from data with missing temporal information is described. Students fit functions to the data that leads to the creation of a differential equations model, which they then are required to analyze in multiple ways. Different fits, modeling approaches, and...

  18. 6-007-S-FunctionsAndDerivativesInSIRModels

    12 Aug 2018 | Modeling Scenarios | Contributor(s):: Meredith L. Greer

  19. 5-026-S-Evictions

    12 Aug 2018 | Modeling Scenarios | Contributor(s):: Mary Vanderschoot

  20. 1-102-S-CancerGrowth

    29 Jul 2018 | Modeling Scenarios | Contributor(s):: Jue Wang

    This scenario guides students in the use of differential equation models to predict cancer growth and optimize treatment outcomes. Several classical models for cancer growth are studied, including exponential, power law, Bertalanffy, logistic, and Gompertz. They examine the behaviors of the...