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    Modeling Scenario
    383

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    652

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    1-155-CruiseControl-ModelingScenario
    In this project we illustrate the design of a proportional-integral-derivative (PID) cruise control algorithm for an automobile. PID control is one of the most common techniques in control engineering.
    PID controllerfeedback controlControl theorycruise controlautomobileclosed-loop controlinput-ouputblock diagram
    Potential Scenario
    172

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    51

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    2017-Sim-EtAl-Optimal control of a coupled tanks system with model-reality differences
    In this paper, an efficient computational approach is proposed to optimize and control a coupled tanks system.
    optimal controlflowtankscoupled tanks
    Potential Scenario
    115

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    45

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    1994-S_S_Everingham-C_Peter_Rydell-Modeling the Demand for Cocaine
    This is a report prepared for the Office of National Drug Control Policy of the United States Army by the Rand Corporation. The report contains lots of data and builds a two compartment difference equation model.
    drugstwo compartmentcocainedemand
    Modeling Scenario
    442

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    263

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    7-011-CoupledSystemLaplace-ModelingScenario
    Differential equations and Laplace transforms are an integral part of control problems in engineering systems. We consider a baby warming device.
    transfer functionpolycarbonatebaby heatercoupled systemheating
    Modeling Scenario
    259

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    263

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    1-079-HomeHeating-ModelingScenario
    This project concerns using Newton's Law of Cooling to model the heating of a house. In particular, if one is going away for awhile, is it more economical to leave a house at a desired temperature or reheat it upon return?
    Optimal Control TheorytemperatureheatfurnaceNewton's Law of Coolinghome heatingspecific heat
    Modeling Scenario
    221

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    166

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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
    Potential Scenario
    294

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    47

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    2018-Robert_Phair-Differential_equation_methods_for_simulation_of_GFP_kinetics_in_non–steady_state_experiments
    Here, we derive new tracer kinetic analytical methods for non–steady state biological systems by constructing mechanistic nonlinear differential equation models of the underlying cell biological processes.
    protein quality controlkineticsCellssteady statechemical kineticsfluouresencephotoactivationinytracellular
    Article or Presentation
    127

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    64

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    1992-Emelie_Kenney-Differential_equations_and_the_AIDS_epidemic
    This paper describes a lecture for Calculus II students in which the Acquired Immune Deficiency Syndrome was used to motivate study of first-order linear differential equations and the derivative as a rate of change.
    datafirst orderparameterAIDS
    Modeling Scenario
    332

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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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    1390

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    5-040-TunedMassDamper-Part-I-Modeling Scenario
    We offer an opportunity to build mathematical models to mitigate dangerous displacements in structures using structural improvements called Tuned Mass Dampers. We model the motion of the original structure as a spring-mass-dashpot system.
    structurespring-mass-dashpotspring massearthquakevibrationtuned mass tunerrestoring forcecontroldampe