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    Modeling Scenario
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    5-077-MandMAttritionWarfare-ModelingScenario
    Students model attrition between two opposing forces using M&M candies and discover a system of linear differential equations of order one, often called the Lanchester equations.
    attritionLanchester modelpredator-predatorN-square Law
    Modeling Scenario
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    5-080-SpaceFlightRecolonize-ModelingScenario
    This project is a combination of differential equations, multi-variable calculus, and vector calculus with use of technology to model colonization of a new planet. Students solve a system of second order differential equations to model a planet
    optimizationsum of square errorsvector calculusLagrange multipliersline integrals
    Modeling Scenario
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    5-090-SolidParticleErosion-ModelingScenario
    By applying Newton's second law, and making a collection of reasonable assumptions, students will derive a system of differential equations that model the path of a rigid particle as it gouges material from a more ductile surface.
    classical mechanicssolid mechanicsNewton's Laws of Motionrigid bodyplasticitypittingductile surface
    Modeling Scenario
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    6-002-EulerCromerPendulum-ModelingScenario
    This activity introduces students to the concept of numerical stability. While modeling a simple pendulum, students compare performance of the semi-implicit Euler-Cromer method with Euler's method and the higher-order Improved Euleror algorithm.
    pendulumsemi-implicit methodsEuler-Cromernumerical solvers
    Modeling Scenario
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    6-006-ZombieGameHvZ-ModelingScenario
    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.
    zombiesSIR modelsGame
    Modeling Scenario
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    6-007-FunctionsAndDerivativesInSIRModels-ModelingScenario
    Given a system of differential equations, how do the solution graphs compare with the graphs of the differential equations? Students tackle this question using SIR models for well-known infectious diseases.
    epidemiologyspecies interactionsderivativesvisualizationinfectionSIR modelsLaw of Mass Action
    Modeling Scenario
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    6-010-SocialCampaign-ModelingScenario
    The epidemic modeling problem is formulated as a system of three nonlinear, first order differential equations in which three compartments (S, I, and R) of the population are linked.
    diseasegrowth rateJudgment and Decision MakingSIR modelinfections diseasesocial campaignrecovery ratedelay timejoining processquitting processexponential distribution
    Modeling Scenario
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    6-011-HumansVsZombies-ModelingScenario
    Students analyze the SIR differential equations model in the context of a zombie invasion of a human population. Students analyze a two equation system representing only two populations, humans and zombies and then recovered zombies.
    zombiesinfectionSIR models
    Modeling Scenario
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    6-012-RiverCrossing-ModelingScenario
    Students develop a model of a river crossing in a boat with thrust using Newton's Second Law of Motion from a Free Body Diagram they construct. The model is thence a system of one second order linear and a second order nonlinear differential...
    dragonNewton's Second Law of Motionriver crossinriver currentvelocity profilethrustFree Body Diagram
    Modeling Scenario
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    6-015-CombatingEbolaEpidemic-ModelingScenario
    This project offers students a chance to make a policy recommendation based on analysis of a nonlinear system of differential equations (disease model). The scenario is taken from the fall of 2014 when the Ebola outbreak in West Africa.
    diseaseEbolaAnalysisPolicydecision
    Modeling Scenario
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    6-016-PandemicModeling-ModelingScenario
    The recent coronavirus outbreak has infected millions of people worldwide and spread to over 200 countries. How can we use differential equations to study the spread of coronavirus?
    population dynamicsinfectious diseasediseaseEbolaeSIR modelsCOVID19pandemicepidemicreproduction number
    Modeling Scenario
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    6-018-ExploringSIRModel-ModelingScenario
    Students will transform, solve, and interpret Susceptible Infected Recovered (SIR) models using systems of differential equation models. The project is progressively divided into three parts to understand, to apply, and to develop SIR models.
    population dynamicssensitivitydiseaseSIR modelsepidemicrumors
    Modeling Scenario
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    6-019-EnablingEpidemicExploration-ModelingScenario
    We became aware of several interesting possibilities for a modeling opportunity with data and we invited you to explore the several routes to parameter estimation in a SIR model with respect to the data offered.
    Akaike Information CriterionMichaelis-Mentenepidemicsaturationgradientleast sum of square errors
    Modeling Scenario
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    6-020-AlgaePopulationSelf-Replenishment-ModelingScenario
    This modeling scenario investigates the massive algal blooms that struck Lake Chapala, Mexico, in 1994. A
    algaepopulationMexicoqualitativecompartmentlinearizationJacobianlaknondimensionalizationpplane
    Modeling Scenario
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    6-023-DroneHeadingHome-ModelingScenario
    We describe a comprehensive project in modeling through a two dimensional system of equations and a first order system of differential equations a drone heading home.
    dronesoursuitflight pathchange of variables
    Modeling Scenario
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    6-024-DronePackageDelivery-ModelingScenario
    Students will derive a system of first order differential equations which describe the flight path of a drone delivering a package.
    VectorsTrigonometryFlightdronesparametric curveImproved Euler MethodRunge-Kutta
    Modeling Scenario
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    6-026-IsleRoyaleModeling-ModelingScenario
    The primary aim of this project is to draw a connection between differential equations and vector calculus, using population ecology modeling as a vehicle.
    ecologyoptimizationpredator-preypopulationvector calculusLagrange multipliersleast squaresIslel Royale
    Modeling Scenario
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    6-029-TumorGrowth-ModelingScenario
    This modeling scenario guides a student familiar with single ordinary differential equation (ODE) models towards the development of a more complex system of two ODEs for describing the evolution of tumor growth over time.
    Pop_Growth Pilotlogisticcomparmenttumorsynthetic datasum of squares error
    Modeling Scenario
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    6-030-SaltAndTorricelli-ModelingScenario
    We build on a model for the height of a falling column of water with a small hole in the container at the bottom of the column of water. We use data from one video of a falling column of water.
    whole picturetankmixingflowcolumn of watersalt mixinggraduated cylinderapertureTorricelli's Law
    Modeling Scenario
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    6-035-Shampoo-ModelingScenario
    We ask students to model the amount of shampoo in a bottle if when we shower we do not cover the opening at the top of the bottle while in the shower.
    shampoodiluationshower