Outline. Calculus for the Life Sciences. What is a Differential Equation? Introduction. Lecture Notes Introduction to Differential Equa

Similar documents
Outline. Calculus for the Life Sciences. Malthusian Growth Model. Introduction. Lecture Notes Separable Differential Equations

Math 266: Ordinary Differential Equations

Calculus for the Life Sciences

Calculus for the Life Sciences

Outline Calculus for the Life Sciences II. Pollution in a Lake 1. Introduction. Lecture Notes Numerical Methods for Differential Equations

Mathematical Models. MATH 365 Ordinary Differential Equations. J. Robert Buchanan. Fall Department of Mathematics

Mathematical Models. MATH 365 Ordinary Differential Equations. J. Robert Buchanan. Spring Department of Mathematics

Outline. Formic Acid

2.1 Exponential Growth

Calculus for the Life Sciences

EAD 115. Numerical Solution of Engineering and Scientific Problems. David M. Rocke Department of Applied Science

Modeling with Differential Equations

XXIX Applications of Differential Equations

Section 3.7: Mechanical and Electrical Vibrations

Elementary Differential Equations

Unforced Mechanical Vibrations

Motivation and Goals. Modelling with ODEs. Continuous Processes. Ordinary Differential Equations. dy = dt

Honors Differential Equations

Forced Mechanical Vibrations

DIFFERENTIATION RULES

CHAPTER 7: OSCILLATORY MOTION REQUIRES A SET OF CONDITIONS

Chapters 8.1 & 8.2 Practice Problems

MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. D) u = - x15 cos (x15) + C

Differential Equations

M A : Ordinary Differential Equations

Differential Equations & Separation of Variables

Math 308 Exam I Practice Problems

PHYSICS. Chapter 15 Lecture FOR SCIENTISTS AND ENGINEERS A STRATEGIC APPROACH 4/E RANDALL D. KNIGHT Pearson Education, Inc.

MATH 251 Week 6 Not collected, however you are encouraged to approach all problems to prepare for exam

Modelling biological oscillations

First order differential equations

Outline. Calculus for the Life Sciences. Falling Cat 1. Introduction. Lecture Notes Differential Equations and Integr

Chapter 12 Vibrations and Waves Simple Harmonic Motion page

Chapter 14: Periodic motion

APPLICATIONS OF SECOND-ORDER DIFFERENTIAL EQUATIONS

Physics General Physics. Lecture 24 Oscillating Systems. Fall 2016 Semester Prof. Matthew Jones

Exponential Growth (Doubling Time)

2nd-Order Linear Equations

Applications of Second-Order Differential Equations

Topic 5 Notes Jeremy Orloff. 5 Homogeneous, linear, constant coefficient differential equations

Calculus II. George Voutsadakis 1. LSSU Math 152. Lake Superior State University. 1 Mathematics and Computer Science

Systems of Ordinary Differential Equations

A Level. A Level Physics. Oscillations (Answers) AQA, Edexcel. Name: Total Marks: /30

MAT01B1: Separable Differential Equations

=================~ NONHOMOGENEOUS LINEAR EQUATIONS. rn y" - y' - 6y = 0. lid y" + 2y' + 2y = 0, y(o) = 2, y'(0) = I

Chapter 14 Oscillations

Solutions to Homework 1, Introduction to Differential Equations, 3450: , Dr. Montero, Spring y(x) = ce 2x + e x

MODELS ONE ORDINARY DIFFERENTIAL EQUATION:

28. Pendulum phase portrait Draw the phase portrait for the pendulum (supported by an inextensible rod)

ODE Math 3331 (Summer 2014) June 16, 2014

Section 11.1 What is a Differential Equation?

Lecture 6: Differential Equations Describing Vibrations

M A : Ordinary Differential Equations

Homogeneous Equations with Constant Coefficients

2 Growth, Decay, and Oscillation

Introduction to Differential Equations

Math Applied Differential Equations

Chapter 1, Section 1.2, Example 9 (page 13) and Exercise 29 (page 15). Use the Uniqueness Tool. Select the option ẋ = x

Math 266 Midterm Exam 2

Outline. Calculus for the Life Sciences. Crow Predation on Whelks. Introduction. Lecture Notes Optimization. Joseph M. Mahaffy,

Chapter 11 Vibrations and Waves

Ordinary Di erential Equations Lecture notes for Math 133A. Slobodan N. Simić

sections June 11, 2009

Oscillations. Simple Harmonic Motion (SHM) Position, Velocity, Acceleration SHM Forces SHM Energy Period of oscillation Damping and Resonance

First and Second Order Differential Equations Lecture 4

Second order linear equations

Math 128A Spring 2003 Week 12 Solutions

Boyce/DiPrima/Meade 11 th ed, Ch 1.1: Basic Mathematical Models; Direction Fields

Vibrations and Waves MP205, Assignment 4 Solutions

Chapter 4. Systems of ODEs. Phase Plane. Qualitative Methods

9.1 Solving Differential Equations

F = ma, F R + F S = mx.

Systems of Differential Equations: General Introduction and Basics

First Order Systems of Linear Equations. or ODEs of Arbitrary Order

CHAPTER Let x(t) be the position (displacement) of the particle at time t. The force on the particle is given to be

ENGI 3424 First Order ODEs Page 1-01

SMA 208: Ordinary differential equations I

School of Engineering Faculty of Built Environment, Engineering, Technology & Design

Differential Equations and Linear Algebra Exercises. Department of Mathematics, Heriot-Watt University, Edinburgh EH14 4AS

Physics Mechanics. Lecture 32 Oscillations II

The acceleration of gravity is constant (near the surface of the earth). So, for falling objects:

4.9 Free Mechanical Vibrations

Ch 3.7: Mechanical & Electrical Vibrations

SIMPLE HARMONIC MOTION

Predicting the future with Newton s Second Law

Differential Equations

2.4 Harmonic Oscillator Models

MATH 1014 N 3.0 W2015 APPLIED CALCULUS II - SECTION P. Perhaps the most important of all the applications of calculus is to differential equations.

DIFFERENTIAL EQUATIONS

ENGI 2422 First Order ODEs - Separable Page 3-01

Applied Mathematics B Study Guide

Chapter 6. Second order differential equations

Linear algebra and differential equations (Math 54): Lecture 19

Applications of First Order Differential Equation

Math 308 Exam I Practice Problems

Example (#1) Example (#1) Example (#2) Example (#2) dv dt

Chapter 14 Oscillations. Copyright 2009 Pearson Education, Inc.

2.4 Models of Oscillation

Chapter1. Ordinary Differential Equations

Note: Unless otherwise specified, the domain of a function f is assumed to be the set of all real numbers x for which f (x) is a real number.

Transcription:

Outline Calculus for the Life Sciences Lecture Notes to Differential Equations Joseph M. Mahaffy, jmahaffy@mail.sdsu.edu 1 Department of Mathematics and Statistics Dynamical Systems Group Computational Sciences Research Center San Diego State University San Diego, CA 92182-7720 http://www-rohan.sdsu.edu/ jmahaffy 2 Spring 2017 Lecture Notes to Differential Equations (1/34) Lecture Notes to Differential Equa (2/34) Differential equations frequently arise in modeling situations They describe population growth, chemical reactions, heat exchange, motion, and many other applications Differential equations are continuous analogs of discrete dynamical systems A differential equation is any equation of some unknown function that involves some derivative of the unknown function The classical example is Newton s Law of motion The mass of an object times its acceleration is equal to the sum of the forces acting on that object Acceleration is the first derivative of velocity or the second derivative of position This is an example of a differential equation In biology, a differential equation describes a growth rate, a reaction rate, or the change in some physiological state Lecture Notes to Differential Equations (3/34) Lecture Notes to Differential Equa (4/34)

Discrete Population, P n, at time n with growth rate, r P n+1 = P n +rp n Rearrange the discrete Malthusian growth model P n+1 P n = rp n The change in population between (n+1) st time and the n th time is proportional to the population at the n th time Lecture Notes to Differential Equations (5/34) (cont) Let P(t) be the population at time t Assume that r is the rate of change of the population per unit time per animal in the population Let t be a small interval of time, then the change in population between t and t+ t, satisfies P(t+ t) P(t) = t rp(t) Biologically, this equation says that the change (difference) in the population over a small period of time is found by taking the rate of growth times the population times the interval of time t The equation above can be rearranged to give P(t+ t) P(t) = rp(t) t Lecture Notes to Differential Equa (6/34) Continuous Continuous The discrete model was given by P(t+ t) P(t) = rp(t) t The right hand side of the equation should remind you of the definition of the derivative Take the limit of t 0, so P(t+ t) P(t) lim = dp(t) t 0 t = rp(t) This is the continuous Malthusian growth model Continuous Solution of Model The Malthusian growth model dp(t) = rp(t) The rate of change of a population is proportional to the population Let c be an arbitrary constant, so try a solution of the form P(t) = ce rt Differentiating dp(t) = cre rt, which is rp(t), so satisfies the differential equation Lecture Notes to Differential Equations (7/34) Lecture Notes to Differential Equa (8/34)

Continuous : 1 Solution of Model (cont) The Malthusian growth model satisfies P(t) = ce rt With the initial condition, P(0) = P 0, then the unique solution is P(t) = P 0 e rt Malthusian growth is often called exponential growth : Consider the Malthusian growth model Skip dp(t) Find the solution = 0.02P(t) with P(0) = 100 Determine how long it takes for this population to double Lecture Notes to Differential Equations (9/34) Lecture Notes to Differential Equa (10/34) : 2 2: 1 Solution: The solution is given by P(t) = 100e 0.02t We can confirm this by computing dp = 0.02(100e0.02t ) = 0.02P(t), so this solution satisfies the differential equation and the initial condition The population doubles when 200 = 100e 0.02t 0.02t = ln(2) or t = 50ln(2) 34.66 2: Suppose that a culture of Escherichia coli is growing according to the Malthusian growth model Skip dp(t) = rp(t) with P(0) = 100,000 Assume the population doubles in 25 minutes Find the growth rate constant and the solution to this differential equation Compute the population after one hour Lecture Notes to Differential Equations (11/34) Lecture Notes to Differential Equa (12/34)

2: 2 Solution: The general solution satisfies P(t) = 100,000e rt If the population doubles in 25 minutes, then P(25) = 200,000 = 100,000e 25r Dividing by 100,000 and taking the logarithm of both sides ln(2) = 25r The growth rate constant is r = 0.0277 The specific solution is given by P(t) = 100,000e 0.0277t The population after one hour is P(60) = 100,000e 0.0277(60) = 527,803 1 Radioactive Decay: Let R(t) be the amount of a radioactive substance Radioactive materials are often used in biological experiments and for medical applications Radioactive elements transition through decay into another state at a rate proportional to the amount of radioactive material present The differential equation is dr(t) = kr(t) with R(0) = R 0 Like the Malthusian growth model, this has an exponential solution R(t) = R 0 e kt Lecture Notes to Differential Equations (13/34) Lecture Notes to Differential Equa (14/34) 2 Harmonic Oscillator: A Hooke s law spring exerts a force that is proportional to the displacement of the spring Newton s law of motion: Mass times the acceleration equals the force acting on the mass Applied to biological phenomena Vibrating cilia in ears Stretching of actin filaments in muscle fibers The simplest spring-mass problem is The general solution is my = cy or y +k 2 y = 0 y(t) = c 1 cos(kt)+c 2 sin(kt), 3 Swinging Pendulum: A pendulum is a mass attached at one point so that it swings freely under the influence of gravity Newton s law of motion (ignoring resistance) gives the differential equation my +gsin(y) = 0, where y is the angle of the pendulum, m is the mass of the bob of the pendulum, and g is the gravitational constant This problem does not have an easily expressible solution where c 1 and c 2 are arbitrary constants Lecture Notes to Differential Equations (15/34) Lecture Notes to Differential Equa (16/34)

4 5 Logistic Growth: Most populations are limited by food, space, or waste build-up, thus, cannot continue to grow according to Malthusian growth The Logistic growth model has a Malthusian growth term and a term limiting growth due to crowding The differential equation is dp = rp ( 1 P ) M P is the population, r is the Malthusian rate of growth, and M is the carrying capacity of the population We solve this problem later in the semester The van der Pol Oscillator: In electrical circuits, diodes show a rapid rise in current, leveling of the current, then a steep decline Biological applications include a similar approximation for nerve impulses The van der Pol Oscillator satisfies the differential equation v +a(v 2 1)v +v = b v is the voltage of the system, and a and b are constants Lecture Notes to Differential Equations (17/34) Lecture Notes to Differential Equa (18/34) 6 Lotka-Volterra Predator and Prey Model: Model for studying the dynamics of predator and prey interacting populations Model for the population dynamics when one predator species and one prey species are tightly interconnected in an ecosystem System of differential equations 7 Forced Spring-Mass Problem with Damping: An extension of the spring-mass problem that includes viscous-damping caused by resistance to the motion and an external forcing function that is applied to the mass The model is given by my +cy +ky = F(t) x = ax bxy y = cy +dxy x is the prey species, and y is the predator species No explicit solution, but will study its behavior Lecture Notes to Differential Equations (19/34) y is the position of the mass m is the mass of the object c is the damping coefficient k is the spring constant F(t) is an externally applied force There are techniques for solving this Lecture Notes to Differential Equa (20/34)

8 9 Classification for Types of Differential Equations: Order of a Differential Equation The order of a differential equation is determined by the highest derivative in the differential equation Harmonic oscillator, swinging-pendulum, van der Pol oscillator, and forced spring mass problem are 2 nd order differential equations Malthusian and logistic growth and radioactive decay are 1 st order differential equations Lotka-Volterra model is a 1 st order system of differential equations Classification for Types of Differential Equations: Linear and Nonlinear Differential Equations A differential equation is linear if the unknown dependent variable and its derivatives only appear in a linear manner The Malthusian growth, radioactive decay, harmonic oscillator, and forced spring mass problem are linear differential equations The swinging pendulum, van der Pol oscillator, logistic growth, and Lotka-Volterra model are nonlinear differential equations Lecture Notes to Differential Equations (21/34) Lecture Notes to Differential Equa (22/34) Spring-Mass Problem 1 Spring-Mass Problem: Assume a mass attached to a spring without resistance satisfies the second order linear differential equation y (t)+5y(t) = 0 Skip Show that two of the solutions to this differential equation are given by ( ) ( ) y 1 (t) = 3sin 5t and y 2 (t) = 2cos 5t Spring-Mass Problem 2 Solution: Undamped spring-mass problem Take two derivatives of y 1 (t) = 3sin ( 5t ) y 1(t) = 3 ( ) ( ) 5cos 5t and y 1(t) = 15sin 5t Substituting into the differential equation ( ) ( ( )) y 1 +5y 1 = 15sin 5t +5 3sin 5t = 0 Take two derivatives of y 2 (t) = 2cos ( 5t ) y 2(t) = 2 ( ) ( ) 5sin 5t and y 2(t) = 10cos 5t Substituting into the differential equation ( ) ( ( )) y 2 +5y 2 = 10cos 5t +5 2cos 5t = 0 Lecture Notes to Differential Equations (23/34) Lecture Notes to Differential Equa (24/34)

Damped Spring-Mass Problem 1 Damped Spring-Mass Problem: Assume a mass attached to a spring with resistance satisfies the second order linear differential equation Skip y (t)+2y (t)+5y(t) = 0 Show that one solution to this differential equation is y 1 (t) = 2e t sin(2t) Damped Spring-Mass Problem 2 Solution: Damped spring-mass problem The 1 st derivative of y 1 (t) = 2e t sin(2t) y 1(t) = 2e t (2cos(2t)) 2e t sin(2t) = 2e t (2cos(2t) sin(2t)) The 2 nd derivative of y 1 (t) = 2e t sin(2t) y 1(t) = 2e t ( 4sin(2t) 2cos(2t)) 2e t (2cos(2t) sin(2t)) = 2e t (4cos(2t)+3sin(2t)) Substitute into the spring-mass problem y 1 +2y 1 +5y = 2e t (4cos(2t)+3sin(2t)) +2(2e t (2cos(2t) sin(2t)))+5(2e t sin(2t)) = 0 Lecture Notes to Differential Equations (25/34) Lecture Notes to Differential Equa (26/34) Damped Spring-Mass Problem 3 1 Graph of Damped Oscillator y(t) 1 0.8 0.6 0.4 0.2 0 Damped Spring y(t) = 2 e t sin(2t) 0.2 0 π/2 π 3π/2 2π t Lecture Notes to Differential Equations (27/34) : Animals lose moisture proportional to their surface area Skip If V(t) is the volume of water in the animal, then the moisture loss satisfies the differential equation dv = 0.03V 2/3, V(0) = 8 cm 3 The initial amount of water is 8 cm 3 with t in days Verify the solution is V(t) = (2 0.01t) 3 Determine when the animal becomes totally dessicated according to this model Graph the solution Lecture Notes to Differential Equa (28/34)

2 3 Solution: Show V(t) = (2 0.01t) 3 satisfies dv = 0.03V 2/3, V(0) = 8 cm 3 V(0) = (2 0.01(0)) 3 = 8, so satisfies the initial condition Differentiate V(t), dv = 3(2 0.01t)2 ( 0.01) = 0.03(2 0.01t) 2 But V 2/3 (t) = (2 0.01t) 2, so Solution (cont): Find the time of total dessication Must solve V(t) = (2 0.01t) 3 = 0 Thus, 2 0.01t = 0 or t = 200 It takes 200 days for complete dessication dv = 0.03V 2/3 Lecture Notes to Differential Equations (29/34) Lecture Notes to Differential Equa (30/34) 4 1 Graph of Dessication Volume of Water V(t) = (2 0.01t) 3 8 6 : Consider the nonautonomous differential equation with initial condition (Initial Value Problem): dy = ty2, y(0) = 2 V(t) 4 Show that the solution to this differential equation, including the initial condition, is 2 0 0 50 100 150 200 t (days) Graph of the solution y(t) = 2 t 2 +1 Lecture Notes to Differential Equations (31/34) Lecture Notes to Differential Equa (32/34)

2 3 Solution: Consider the solution y(t) = 2 t 2 +1 = 2(t2 +1) 1 The initial condition is Differentiate y(t), However, y(0) = 2 0 2 +1 = 2 dy = 2(t2 +1) 2 (2t) = 4t(t 2 +1) 2 ty 2 = t(2(t 2 +1) 1 ) 2 = 4t(t 2 +1) 2 Thus, the differential equation is satisfied Lecture Notes to Differential Equations (33/34) Solution of Nonautonomous Differentiation Equation y(t) 2 1.5 1 0.5 y = 2(t 2 + 1) 1 0 1 2 3 4 5 t Lecture Notes to Differential Equa (34/34)