QUENCHING A THIRST WITH DIFFERENTIAL EQUATIONS By: Emily Clerc, Abigail Martinez, Daniel Mashal.

Slides:



Advertisements
Similar presentations
Partial Differential Equations
Advertisements

Derivatives - Equation of the Tangent Line Now that we can find the slope of the tangent line of a function at a given point, we need to find the equation.
Small Coupled Oscillations. Types of motion Each multi-particle body has different types of degrees of freedom: translational, rotational and oscillatory.
Kliah Soto Jorge Munoz Francisco Hernandez. and.
Principal Component Analysis
Chapter 4. Numerical Interpretation of Eigenvalues In terms of matrix arithmetic eigenvalues turn matrix multiplication into scalar multiplication. Numerically.
example: four masses on springs
5. Topic Method of Powers Stable Populations Linear Recurrences.
AppxA_01fig_PChem.jpg Complex Numbers i. AppxA_02fig_PChem.jpg Complex Conjugate.
Linearization. Fixed Point  A map f is defined on a metric space X.  Points are mapped to other points in the space.  A fixed point for the map is.
Dynamical Systems Analysis II: Evaluating Stability, Eigenvalues By Peter Woolf University of Michigan Michigan Chemical Process Dynamics.
Ch 7.5: Homogeneous Linear Systems with Constant Coefficients
Rotations. Space and Body  Space coordinates are an inertial system. Fixed in spaceFixed in space  Body coordinates are a non- inertial system. Move.
Schrödinger We already know how to find the momentum eigenvalues of a system. How about the energy and the evolution of a system? Schrödinger Representation:
Partial Differential Equation (PDE) An ordinary differential equation is a differential equation that has only one independent variable. For example, the.
8/27/2014PHY 711 Fall Lecture 11 PHY 711 Classical Mechanics and Mathematical Methods 10-10:50 AM MWF Olin 103 Plan for Lecture 1: 1. Welcome &
Eigensystems - IntroJacob Y. Kazakia © Eigensystems 1.
Analysis of the Rossler system Chiara Mocenni. Considering only the first two equations and ssuming small z The Rossler equations.
Dynamical Systems 2 Topological classification
Newton's Method for Functions of Several Variables Joe Castle & Megan Grywalski.
AppxA_01fig_PChem.jpg Complex Numbers i. AppxA_02fig_PChem.jpg Complex Conjugate * - z* =(a, -b)
1 In this lecture we will compare two linearizing controller for a single-link robot: Linearization via Taylor Series Expansion Feedback Linearization.
Analyzing the Edwards- Buckmire Model for Movie Sales Mike Lopez & P.J. Maresca.
Dynamical Systems 2 Topological classification
AP Calculus 2005: 240,000 Currently growing at ~13,000/year.
CEE162/262c Lecture 2: Nonlinear ODEs and phase diagrams1 CEE162 Lecture 2: Nonlinear ODEs and phase diagrams; predator-prey Overview Nonlinear chaotic.
Solve by using the ELIMINATION method The goal is to eliminate one of the variables by performing multiplication on the equations. Multiplication is not.
Homogeneous Linear Systems with Constant Coefficients Solutions of Systems of ODEs.
MULTIPLE INTEGRALS 2.2 Iterated Integrals In this section, we will learn how to: Express double integrals as iterated integrals.
Linear Algebra Diyako Ghaderyan 1 Contents:  Linear Equations in Linear Algebra  Matrix Algebra  Determinants  Vector Spaces  Eigenvalues.
Review of Matrix Operations Vector: a sequence of elements (the order is important) e.g., x = (2, 1) denotes a vector length = sqrt(2*2+1*1) orientation.
Linear Algebra Diyako Ghaderyan 1 Contents:  Linear Equations in Linear Algebra  Matrix Algebra  Determinants  Vector Spaces  Eigenvalues.
6- Comparative Statics Analysis Comparative-Static Analysis - The Nature of Comparative Statics - Rate of Change and the Derivative - The Derivative and.
Complex Eigenvalues and Phase Portraits. Fundamental Set of Solutions For Linear System of ODEs With Eigenvalues and Eigenvectors and The General Solution.
Quasi Random Sequences Fields of use Author: Stefan Ilijevski.
Derivation of the 2D Rotation Matrix Changing View from Global to Local X Y X’ Y’  P Y Sin  X Cos  X’ = X Cos  + Y Sin  Y Cos  X Sin  Y’ = Y Cos.
Pamela Leutwyler. Find the eigenvalues and eigenvectors next.
Matrices.
ΜΕΤΑΣΥΛΛΕΚΤΙΚΗ ΦΥΣΙΟΛΟΓΙΑ ΕΡΓΑΣΤΗΡΙΟ 3. Μετασυλλεκτική Εργ3-Λιοσάτου Γ.2 ΒΙΟΛΟΓΙΚΟΙ ΠΑΡΑΓΟΝΤΕΣ ΠΟΥ ΕΠΗΡΕΑΖΟΥΝ ΤΗ ΦΘΟΡΑ ΤΩΝ ΟΠΩΡΟΚΗΠΕΥΤΙΚΩΝ Αναπνοή Η λειτουργία.
Introduction to Differential Equations
Lecture 4 Complex numbers, matrix algebra, and partial derivatives
Rules Of Differentiation And Their Use In Comparative Statics
DIFFERENTIAL EQUATIONS
Review of Matrix Operations
9.3 Filtered delay embeddings
Linear Algebra Lecture 34.
CHAPTER 3 NUMERICAL METHODS.
Blair Ebeling MATH441: Spring 2017
Elementary Linear Algebra
Multiple Regression.
Eigenvalues and Eigenvectors
Topics in Phase-Space Jeffrey Eldred
Systems of Differential Equations Nonhomogeneous Systems
Boyce/DiPrima 10th ed, Ch 7.5: Homogeneous Linear Systems with Constant Coefficients Elementary Differential Equations and Boundary Value Problems, 10th.
اثرات گرمايش جهاني تغييرات آب و هوا، تأثيرات عميق و شديدي بر بسياري از عوامل اساسي موثر بر سلامت از جمله : آب، غذا، هوا و محيط زيست دارد كه اين مورد خود.
Implicit Differentiation
Copyright © Cengage Learning. All rights reserved.
Equation Review Given in class 10/4/13.
Differentiate. f (x) = x 3e x
Factor Analysis Development
Eigenvalues and Eigenvectors
Warmup Open Loop System Closed Loop System
Hour 33 Coupled Oscillators I
Boundary Value Problems
Equation Review.
Linear Algebra Lecture 30.
Poincare Maps and Hoft Bifurcations
Copyright © Cengage Learning. All rights reserved.
Linear Algebra Lecture 28.
Ch 7.5: Homogeneous Linear Systems with Constant Coefficients
Presentation transcript:

QUENCHING A THIRST WITH DIFFERENTIAL EQUATIONS By: Emily Clerc, Abigail Martinez, Daniel Mashal

TOPIC OVERVIEW Modelling the behavior of CO 2 bubbles as they grow and rise from the bottom of a glass of beer.

MAJOR RESULTS Created a three dimensional model for the growing and rising of bubbles. But, through experimentation, model does not hold.

PHYSICS EQUATIONS USED TO MAKE OUR MODEL

OUR MODEL

THE JACOBIAN MATRIX

OUR JACOBIAN We took a Jacobian in order to find a fixed point, eigenvalues, and eigenvectors for our system. There is not a fixed point since the Jacobian shows that in our first equation the partial derivative is coupled, so it can never be 0. Since there can never be a fixed point, we cannot find the eigenvalues and eigenvectors at that point in our system.