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Published byAngelica Baily Modified over 2 years ago

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Course Introduction BIOE 4200

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Class Website Click on Scott Molitor > Courses > BIOE 4200 Contains all information you need Syllabus includes grading policies, office hours, lecture schedule Assignments describes assigned problems and project sections, shows due dates Announcements for cancellations, revised due dates, class in computer room, etc. Lecture notes as provided

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Grading Policies Three exams and one final (60%) – Each exam is 20%, lowest score dropped – All exams open book & open note Group project (25%) – Model and analyze biological or medical system – Various stages due throughout the semester – Group members receive same grade Homework assignments (15%) – Receive full credit if you gave reasonable effort – I will hand out solutions, wont correct answers – You are encouraged to work together

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Course Objectives To learn how to create and analyze mathematical models of physical systems Includes mechanical, electrical and chemical systems – Dont view this as electrical engineering type course Emphasize biological, physiologic and medical applications

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Mathematical Models Sets of equations that approximate the function of a physical system Variables represent physical quantities Equations are applications of physical laws or empirical data that represent transformations between the relevant physical quantities Employ analytical or computational solutions of equations to approximate system behavior You have spent much time in your previous engineering courses learning this process!

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Why Mathematical Modeling? Low cost – All you need a brain and a computer – Much cheaper than building physical equivalents Accessibility – Can sometimes use models to answer questions that cannot be addressed experimentally – May not be ethical to obtain data from humans or animals Starting point for any new design – Models can indicate whether an idea will work – Can suggest tests/experiments you need to perform once the physical system is constructed

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Course Outline Schematic representations of physical systems Modeling behavior of physical processes with differential equations Simulation and analysis of differential equations Methods to control and improve system performance

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