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    Modeling Scenario
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    4-035-ParEstSteadyState-ModelingScenario
    Students estimate parameters in a second order, linear, ordinary differential equations through analysis of the steady state solution. By applying a driver we can collect data in terms of the parameters and estimate these parameters
    driversteady statesum of square errors
    Modeling Scenario
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    3-105-FrequencyResponse-ModelingScenario
    We describe the frequency response to a second order differential equation with a driving function as the maximum steady state solution amplitude and perform some analyses in this regard.
    transient dynamicscircuitspring massdriverfrequency responseamplitudesteady state
    Modeling Scenario
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    152

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    1-001c-PopulationDecayThenSome-ModelingScenario
    You will be modeling the following situation: 100 people are in a hotel. Each day, each person has a random chance of 50% of leaving the hotel. No new people enter the hotel.
    simulationoccupancypopulationhotel
    Modeling Scenario
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    1-001d-HotelPopulationDecay-ModelingScenario
    You will be modeling the following situation: 100 people are in a hotel. Each day, each person has a random chance of 50% of leaving the hotel. No new people enter the hotel. Before you run the simulation in MATLAB, answer some questions.
    simulationlogisticexponential decayfitting
    Modeling Scenario
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    243

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    3-069-HeatInBar-ModelingScenario
    The temperature distribution along a uniform slender bar due to conduction and convection is investigated through experimental, analytical, and numerical approaches.
    heat transferexperimentconductionconvectionboundary conditionsfinite volume method
    Modeling Scenario
    250

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    499

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    3-004-VanderPol-ModelingScenario
    This paper presents an electronic spreadsheet model of the Van der Pol oscillator, a well-known nonlinear second-order ordinary differential equation.
    phase planeVan der Pol oscillatorlimit cycleRunge-Kutta methodLienard equation
    Modeling Scenario
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    395

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    5-040-TunedMassDampers-PartII-ModelingScenario
    Studentsbuild mathematical models to mitigate dangerous swaying in structures using structural improvements called Tuned Mass Dampers (TMD). We model the motion of the original structure as a spring-mass-dashpot with stiffness replacing spring...
    structureresistancespring-mass-dashpotearthquakevibrationcontroldampingtuned mass damperstiffnessreduction of vibration
    Modeling Scenario
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    210

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    1-005A-ChemDataCollection-ModelingScenario
    A student is assigned the task of collecting data on a chemical reaction and does a poor job of collecting data. She only collects data at the start and end of a number of ten minute intervals and does not keep track of when the observations are...
    linear regressionkineticschemistryorder of reactionchemical reactionchemical datainfusiondifferencing
    Modeling Scenario
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    1-006-Financing-ModelingScenario
    We describe two situations, one in which we are saving for a purpose and one in which we are borrowing for a purpose. In the first case we ask for discrete and continuous model of the situation and in the second case we ask that the results of...
    financesavingsloaninterest ratepayment
    Modeling Scenario
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    6-040-StruggleForExistence-ModelingScenario
    We use historical data from the 1930's in the Soviet Union and model competition between two species of yeast after modeling each species separately and estimate parameters
    competitionlogisticcarrying capacityparamecium
    Article or Presentation
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    89

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    SIMIODE Spring 2024 Webinars - WikiModel
    WikiModel is cloud-based application and requires no installation and is run via a web-browser to facilitate rapid implementation. Equations are typed in as they appear in a textbook. ODEs are automatically integrated via Runge-Kutta methods.
    modelingSoftwaretoolapplicationWikiModelmodeling cycle
    Modeling Scenario
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    1-046-GoingViral-ModelingScenario
    Students participate in a simulation of the spread of a viral disease in the classroom and model the process with a logistic differential equation. The simulation uses random numbers and the entire class participates.
    simulationmathematical modeldatalogisticrandom number generatorfittingrandom process
    Modeling Scenario
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    1-012-Sublimation-Modeling Scenario
    We offer data on the sublimation of dry ice (carbon dioxide) collected in a classroom setting so that students can model the rate of change in the mass of a small solid carbon dioxide block with a differential equation model, solve the...
    sublimationdry ice