Keyframing can be tedious - especially to get realism Using physics to define the animation, Subset of procedural animation Provide the physical
|
|
|
- Βαρ-ιησούς Δυοβουνιώτης
- 7 χρόνια πριν
- Προβολές:
Transcript
1 Dynamics-Physics based animation Keyframing can be tedious - especially to get realism Using physics to define the animation, Subset of procedural animation Provide the physical rules-laws that govern the motion, let the system evaluate the positions/shape Animator gives up control, gets realistic motion automatically. Can use augmented laws of physics Reusable code, autonomous agents, automatically captures compleity Ice skater, child on a swing
2 Dynamics-Physics based animation Point masses (particle systems, rigid bodies, deformable bodies, articulated objects One should specify forces, material properties, initial conditions, constraints Solving ordinary differential equations, inclusion of constraints Collision detection and handling
3 A Canonical Differential Equation 1 f(,t = f(,t (t: a moving point. f(,t: 's velocity. 2 SIGGRAPH 97 COURSE NOTES SB2 PHYSICALLY BASED MODELING
4 Vector Field The differential equation = f (,t defines a vector field over. SIGGRAPH 97 COURSE NOTES SB3 PHYSICALLY BASED MODELING
5 Integral Curves Start Here Pick any starting point, and follow the vectors. SIGGRAPH 97 COURSE NOTES SB4 PHYSICALLY BASED MODELING
6 Initial Value Problems Given the starting point, follow the integral curve. SIGGRAPH 97 COURSE NOTES SB5 PHYSICALLY BASED MODELING
7 Solving ODE &( t = f (, t Given the differential equations and a starting point ( t i (known as an initial value problem find (t Interest in numerical solutions (discrete time steps (t 0, (t 0 +h, (t 0 +2h not analytical ones. We need to integrate to find the new position t+ h t+ h t '( τ dτ = ( t+ h ( t = f(, τ dτ t
8 Euler method Assumes that the derivative f is constant over the timestep ( t+ h ( t + hf( ( t, t First order approimation given Taylor epansion gives ( t ( t ( t i i i + dt + dt + dt &( t = f (, t and t = ( t ( t ( t i i i + & ( t i + & ( t i + f ( ( t dt dt i, t i dt ( i + O( dt 2
9 Euler's Method Simplest numerical solution method Discrete time steps Bigger steps, bigger errors. (t + t = (t + t f(,t SIGGRAPH 97 COURSE NOTES SB6 PHYSICALLY BASED MODELING
10 Euler method Inaccurate smaller timesteps only slow the problems down Unstable f (, t = k reasonable if dt <1/ k
11 Method performance Performance depends on the number of calculations per time step. However performance is also related to the number of time steps required to obtain a certain accuracy and stability Sophisticated methods: more evaluations per step but they allow bigger steps
12 Midpoint Method Second order approimation 2 dt ( ti + dt = ( ti + & ( ti dt + & ( ti + with f ( dt 2 2 f d &&(t i = = f dt f 2 O( dt 2 f ( f ( f i + = i + ( i + O( dt dt + f ( ( ( ( ( 2 i = f i + f 2 i f i O dt 3 dt && + O dt = dt ( f ( + f ( f ( i + ( i 2 i i 2 3 dt ( ti + dt = ( ti + dt ( f ( i + f ( 2 i
13 Midpoint Method Requires 2 derivative evaluations per step Geometric Interpretation dt ( ti + dt = ( ti + dt ( f ( i + f ( 2 i Euler result + i i f ( dt 2 i dt f ( i + f ( 2 i Midpoint result we can use higher orders (e: runge-kutta 4
14 Adaptive Timestepping Fied timestep: proceed only as fast as worst section of (t allows. Allow the timestep to change over the course of the solution e = a b 1 timestep 2 timesteps Scale the timestep based on the error s e e desired = current integrationorder See: Numerical recipes in C
15 ODE solver For(time=t0; time<t1; time+=delta{ derivative=derivative_function(time, ; =ode(derivative, time,, delta; } The user should provide derivative_function. Alternatively, derivative_function is fed to ode.
16 Particles Particles are objects modeled as point masses Particle systems are collections of particles Particle systems can represent: fire smoke/clouds flow of fluids debris/shrapnel soft bodies flocks/crowds etc.
17 Particles Particles respond to forces (Newtonian particles We represent this using differential equations Newton s second law && = f m & v& = = v f m 2 nd order ODE 1 st order ODEs
18 Particle Systems The state of the system is fully determined by, v. Phase space Particle properties: mass position velocity total forces age, lifespan rendering properties etc.
19 Newtonian συστήµατα σωµατιδίων Η συµπεριφορά του συστήµατος προσδιορίζεται από τις χρονοµεταβλητές δυνάµεις που ασκούνται. Εσωτερικές δυνάµεις (σύστηµα ελατηρίων ή/και εξωτερικές δυνάµεις (βαρύτητα Καθορίζοντας κατάλληλα τις δυνάµεις πετυχαίνουµε να µοντελοποιήσουµε την επιθυµητή συµπεριφορά.
20 Particle Systems Separate the data structures and integration Particle System particles time state send data as 6n vectors state/derivatives Solver state derivatives Particle v f m v f m v f m L v f m
21 Particle Motion (t v(t SIGGRAPH 97 COURSE NOTES SD2 PHYSICALLY BASED MODELING
22 Particle State Y = (t v(t (t v(t Y = SIGGRAPH 97 COURSE NOTES SD3 PHYSICALLY BASED MODELING
23 Particle Dynamics (t v(t F(t SIGGRAPH 97 COURSE NOTES SD4 PHYSICALLY BASED MODELING
24 State Derivative d dt Y = d dt (t = v(t v(t F(t/m d dt Y = v(t F(t/m SIGGRAPH 97 COURSE NOTES SD5 PHYSICALLY BASED MODELING
25 Multiple Particles SIGGRAPH 97 COURSE NOTES SD6 PHYSICALLY BASED MODELING
26 State Derivative d dt Y = d dt 1 (t v 1 (t M n (t v n (t = v 1 (t F 1 (t/m 1 M v n (t F n (t/m n d dt Y = n elements SIGGRAPH 97 COURSE NOTES SD7 PHYSICALLY BASED MODELING
27 ODE solution d dt Y(t 0 + t... Y(t 1 d dt Y(t 0 Y(t 0 + t Y(t 0 SIGGRAPH 97 COURSE NOTES SD8 PHYSICALLY BASED MODELING
28 Y(t 0 len t 0 t 1 dydt ODE solver Y(t 1 void dydt(double t, double y[], double ydot[] SIGGRAPH 97 COURSE NOTES SD9 PHYSICALLY BASED MODELING
29 Y(t = 1 (t v 1 (t n (t v n (t dydt d dt Y(t = v 1 (t F 1 (t/ m 1 v n (t F n (t/m n SIGGRAPH 97 COURSE NOTES SD10 PHYSICALLY BASED MODELING
30 v f m v f m v f m Clear Force Accumulators 1 2 Deriv Eval Loop F F F F Invoke apply_force functions v f m v f m v f m 3 Return [v, f/m, ] to solver. SIGGRAPH 97 COURSE NOTES SC17 PHYSICALLY BASED MODELING
31 Forces Unary forces :forces that only depend on 1 particle. O(n compleity f drag v Gravity Dampening Wind Fields f mg f = k = drag d f = k v wind v
32 Forces Binary forces - forces that only depend on 2 particles Springs ( 0 b a b a b a s a l k f = f a f b ( ( b a b a b a b a b a k d v v Generalizes to n-ary forces f b =- f a direction: a - b
33 υνάµεις από σύστηµα ελατηρίων Χρήση σωµατιδίων για µοντελοποίηση επιφάνειας που µεταβάλλεται µε το χρόνο: ύφασµα στον άνεµο Κάθε σωµατίδιο κόµβος σε πλέγµα Εξωτερικές δυνάµεις (βαρύτητα, άνεµος υνάµεις µεταξύ σωµατιδίων που τα καθιστούν συνεκτική επιφάνεια
34 υνάµεις από σύστηµα ελατηρίων Θεώρηση ότι τα σωµατίδια συνδέονται µε ελατήρια. Πολυπλοκότητα O(n (επίδραση µόνο από γειτονικά σωµατίδια
35 Ελκτικές-απωθητικές δυνάµεις Spatial interaction forces Οι δυνάµεις σε σύστηµα ελατηρίων κρατούν τα σωµατίδια στην ίδια τοπολογική διάταξη, Επιδρούν πάντα στο ίδιο ζεύγος. Οι ελκτικές ή απωθητικές δυνάµεις τα φέρνουν κοντά ή τα αποµακρύνουν. Απωθητικές δυνάµεις για να κατανείµουµε σωµατίδια σε επιφάνεια ή να τα αποτρέψουµε να συγκρουστούν Ελκτικές δυνάµεις: µοντέλο ηλιακού
36 Ελκτικές-απωθητικές δυνάµεις ρουν στην κατεύθυνση d = p -q και είναι αντιστρόφως ανάλογες της απόστασης Απωθητική αντίστροφου τετράγωνου f = k r d d 3 Στη γενική περίπτωση ο υπολογισµός των δυνάµεων είναι O(n 2.
37 Ελκτικές-απωθητικές δυνάµεις Χωρισµός του χώρου σε υποχώρους και υπόθεση ότι δυνάµεις από σωµατίδια σε γειτονικούς υποχώρους αµελητέες. Κόστος για αρχική διαµοίραση των σωµατιδίων και υπολογισµό µετάβασης σωµατιδίων σε άλλο υποχώρο για κάθε
38 Usually just use springs Forces Controlled particles: motion not controlled by forces Fied particles (anchors and pivots Procedurally controlled particles User Interaction forces (for interactive animation : forces applied to particles by the user f user
39 Soft Constraints Forces: provided by the user to specify the desired behavior (e.g. spring forces keep particles together It is often easier to specify a condition that we want to be true rather than a force to make it true Constraint (or behavior functions: specify a condition that we wish to have fulfilled C (, = 0 a b = a b or C(, = r = a b a Constraint functions But how do we make it true? Convert constraints to force laws b 0 C: vector
40 Energy Functions Minimize the energy of the constraint The smaller the energy the more the constraint is satisfied ks E = C C 2 Force the particle towards the constraint E C fi = = ks C i i Add damping in order to avoid oscillations around the constraint dampening C f = k C& i d i Jacobian matri
41 Energy Functions Eample b a C = I C = a I C = b v a v b C = & a derivative b derivative time derivative Plug into the force equation C C C C f & i d i s i k k = ( ( b a d b a s a k k v v f = Just a damped spring
42 Collision Detection Determine when a particle has collided (simple case N N ( p < 0 N ( p = 0 Particle has collided iff N ( p < p: point on the surface 0
43 Collisions and Contact What should we do when there is a collision? ( t 0 ( t 1 ( t 2 ( t 3
44 Rolling Back the Simulation Restart the simulation at the time of the collision ( t 0 ( t 1 ( t 2 ( t c ( t 3 Collision time can be found by bisection, etc.
45 Collision Response What should we do when a particle has collided? The correct thing to do is rollback the simulation to the eact point of contact Easier to just modify positions and velocities v n v t v N new v After the collision: new v = ε vn + v t ε=1 elastic collision coefficient of restitution
46 Contact Forces Contact: the particle is on the collision surface with zero normal velocity A contact force resists penetration c ( N f < 0 f = ( N f N Contact forces do not resist leaving the surface f c = 0 Simple friction can be modeled f f f t ( N f > = k ( N f v ( N f < 0 0
Keyframing can be tedious - especially to get realism Using physics to define the animation, Subset of procedural animation Provide the physical
Dynamics-Physics based animation Keyframing can be tedious - especially to get realism Using physics to define the animation, Subset of procedural animation Provide the physical rules-laws that govern
Απόκριση σε Μοναδιαία Ωστική Δύναμη (Unit Impulse) Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο. Απόστολος Σ.
Απόκριση σε Δυνάμεις Αυθαίρετα Μεταβαλλόμενες με το Χρόνο The time integral of a force is referred to as impulse, is determined by and is obtained from: Newton s 2 nd Law of motion states that the action
Phys460.nb Solution for the t-dependent Schrodinger s equation How did we find the solution? (not required)
Phys460.nb 81 ψ n (t) is still the (same) eigenstate of H But for tdependent H. The answer is NO. 5.5.5. Solution for the tdependent Schrodinger s equation If we assume that at time t 0, the electron starts
CHAPTER 25 SOLVING EQUATIONS BY ITERATIVE METHODS
CHAPTER 5 SOLVING EQUATIONS BY ITERATIVE METHODS EXERCISE 104 Page 8 1. Find the positive root of the equation x + 3x 5 = 0, correct to 3 significant figures, using the method of bisection. Let f(x) =
Section 8.3 Trigonometric Equations
99 Section 8. Trigonometric Equations Objective 1: Solve Equations Involving One Trigonometric Function. In this section and the next, we will exple how to solving equations involving trigonometric functions.
Forced Pendulum Numerical approach
Numerical approach UiO April 8, 2014 Physical problem and equation We have a pendulum of length l, with mass m. The pendulum is subject to gravitation as well as both a forcing and linear resistance force.
The Simply Typed Lambda Calculus
Type Inference Instead of writing type annotations, can we use an algorithm to infer what the type annotations should be? That depends on the type system. For simple type systems the answer is yes, and
EE512: Error Control Coding
EE512: Error Control Coding Solution for Assignment on Finite Fields February 16, 2007 1. (a) Addition and Multiplication tables for GF (5) and GF (7) are shown in Tables 1 and 2. + 0 1 2 3 4 0 0 1 2 3
HOMEWORK 4 = G. In order to plot the stress versus the stretch we define a normalized stretch:
HOMEWORK 4 Problem a For the fast loading case, we want to derive the relationship between P zz and λ z. We know that the nominal stress is expressed as: P zz = ψ λ z where λ z = λ λ z. Therefore, applying
Exercises 10. Find a fundamental matrix of the given system of equations. Also find the fundamental matrix Φ(t) satisfying Φ(0) = I. 1.
Exercises 0 More exercises are available in Elementary Differential Equations. If you have a problem to solve any of them, feel free to come to office hour. Problem Find a fundamental matrix of the given
Second Order RLC Filters
ECEN 60 Circuits/Electronics Spring 007-0-07 P. Mathys Second Order RLC Filters RLC Lowpass Filter A passive RLC lowpass filter (LPF) circuit is shown in the following schematic. R L C v O (t) Using phasor
ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 19/5/2007
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Αν κάπου κάνετε κάποιες υποθέσεις να αναφερθούν στη σχετική ερώτηση. Όλα τα αρχεία που αναφέρονται στα προβλήματα βρίσκονται στον ίδιο φάκελο με το εκτελέσιμο
Second Order Partial Differential Equations
Chapter 7 Second Order Partial Differential Equations 7.1 Introduction A second order linear PDE in two independent variables (x, y Ω can be written as A(x, y u x + B(x, y u xy + C(x, y u u u + D(x, y
Μονοβάθμια Συστήματα: Εξίσωση Κίνησης, Διατύπωση του Προβλήματος και Μέθοδοι Επίλυσης. Απόστολος Σ. Παπαγεωργίου
Μονοβάθμια Συστήματα: Εξίσωση Κίνησης, Διατύπωση του Προβλήματος και Μέθοδοι Επίλυσης VISCOUSLY DAMPED 1-DOF SYSTEM Μονοβάθμια Συστήματα με Ιξώδη Απόσβεση Equation of Motion (Εξίσωση Κίνησης): Complete
( y) Partial Differential Equations
Partial Dierential Equations Linear P.D.Es. contains no owers roducts o the deendent variables / an o its derivatives can occasionall be solved. Consider eamle ( ) a (sometimes written as a ) we can integrate
Chapter 6: Systems of Linear Differential. be continuous functions on the interval
Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations
9.09. # 1. Area inside the oval limaçon r = cos θ. To graph, start with θ = 0 so r = 6. Compute dr
9.9 #. Area inside the oval limaçon r = + cos. To graph, start with = so r =. Compute d = sin. Interesting points are where d vanishes, or at =,,, etc. For these values of we compute r:,,, and the values
Exercises to Statistics of Material Fatigue No. 5
Prof. Dr. Christine Müller Dipl.-Math. Christoph Kustosz Eercises to Statistics of Material Fatigue No. 5 E. 9 (5 a Show, that a Fisher information matri for a two dimensional parameter θ (θ,θ 2 R 2, can
Finite Field Problems: Solutions
Finite Field Problems: Solutions 1. Let f = x 2 +1 Z 11 [x] and let F = Z 11 [x]/(f), a field. Let Solution: F =11 2 = 121, so F = 121 1 = 120. The possible orders are the divisors of 120. Solution: The
CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS
CHAPTER 48 APPLICATIONS OF MATRICES AND DETERMINANTS EXERCISE 01 Page 545 1. Use matrices to solve: 3x + 4y x + 5y + 7 3x + 4y x + 5y 7 Hence, 3 4 x 0 5 y 7 The inverse of 3 4 5 is: 1 5 4 1 5 4 15 8 3
Higher Derivative Gravity Theories
Higher Derivative Gravity Theories Black Holes in AdS space-times James Mashiyane Supervisor: Prof Kevin Goldstein University of the Witwatersrand Second Mandelstam, 20 January 2018 James Mashiyane WITS)
Eulerian Simulation of Large Deformations
Eulerian Simulation of Large Deformations Shayan Hoshyari April, 2018 Some Applications 1 Biomechanical Engineering 2 / 11 Some Applications 1 Biomechanical Engineering 2 Muscle Animation 2 / 11 Some Applications
Partial Differential Equations in Biology The boundary element method. March 26, 2013
The boundary element method March 26, 203 Introduction and notation The problem: u = f in D R d u = ϕ in Γ D u n = g on Γ N, where D = Γ D Γ N, Γ D Γ N = (possibly, Γ D = [Neumann problem] or Γ N = [Dirichlet
ΗΜΥ 220: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ Ι Ακαδημαϊκό έτος Εαρινό Εξάμηνο Κατ οίκον εργασία αρ. 2
ΤΜΗΜΑ ΗΛΕΚΤΡΟΛΟΓΩΝ ΜΗΧΑΝΙΚΩΝ ΚΑΙ ΜΗΧΑΝΙΚΩΝ ΥΠΟΛΟΓΙΣΤΩΝ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΥΠΡΟΥ ΗΜΥ 220: ΣΗΜΑΤΑ ΚΑΙ ΣΥΣΤΗΜΑΤΑ Ι Ακαδημαϊκό έτος 2007-08 -- Εαρινό Εξάμηνο Κατ οίκον εργασία αρ. 2 Ημερομηνία Παραδόσεως: Παρασκευή
Chapter 6: Systems of Linear Differential. be continuous functions on the interval
Chapter 6: Systems of Linear Differential Equations Let a (t), a 2 (t),..., a nn (t), b (t), b 2 (t),..., b n (t) be continuous functions on the interval I. The system of n first-order differential equations
ANSWERSHEET (TOPIC = DIFFERENTIAL CALCULUS) COLLECTION #2. h 0 h h 0 h h 0 ( ) g k = g 0 + g 1 + g g 2009 =?
Teko Classes IITJEE/AIEEE Maths by SUHAAG SIR, Bhopal, Ph (0755) 3 00 000 www.tekoclasses.com ANSWERSHEET (TOPIC DIFFERENTIAL CALCULUS) COLLECTION # Question Type A.Single Correct Type Q. (A) Sol least
Homework 8 Model Solution Section
MATH 004 Homework Solution Homework 8 Model Solution Section 14.5 14.6. 14.5. Use the Chain Rule to find dz where z cosx + 4y), x 5t 4, y 1 t. dz dx + dy y sinx + 4y)0t + 4) sinx + 4y) 1t ) 0t + 4t ) sinx
Matrices and Determinants
Matrices and Determinants SUBJECTIVE PROBLEMS: Q 1. For what value of k do the following system of equations possess a non-trivial (i.e., not all zero) solution over the set of rationals Q? x + ky + 3z
Appendix to On the stability of a compressible axisymmetric rotating flow in a pipe. By Z. Rusak & J. H. Lee
Appendi to On the stability of a compressible aisymmetric rotating flow in a pipe By Z. Rusak & J. H. Lee Journal of Fluid Mechanics, vol. 5 4, pp. 5 4 This material has not been copy-edited or typeset
ΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ
ΕΙΣΑΓΩΓΗ ΣΤΗ ΣΤΑΤΙΣΤΙΚΗ ΑΝΑΛΥΣΗ ΕΛΕΝΑ ΦΛΟΚΑ Επίκουρος Καθηγήτρια Τµήµα Φυσικής, Τοµέας Φυσικής Περιβάλλοντος- Μετεωρολογίας ΓΕΝΙΚΟΙ ΟΡΙΣΜΟΙ Πληθυσµός Σύνολο ατόµων ή αντικειµένων στα οποία αναφέρονται
TMA4115 Matematikk 3
TMA4115 Matematikk 3 Andrew Stacey Norges Teknisk-Naturvitenskapelige Universitet Trondheim Spring 2010 Lecture 12: Mathematics Marvellous Matrices Andrew Stacey Norges Teknisk-Naturvitenskapelige Universitet
Srednicki Chapter 55
Srednicki Chapter 55 QFT Problems & Solutions A. George August 3, 03 Srednicki 55.. Use equations 55.3-55.0 and A i, A j ] = Π i, Π j ] = 0 (at equal times) to verify equations 55.-55.3. This is our third
Numerical Analysis FMN011
Numerical Analysis FMN011 Carmen Arévalo Lund University carmen@maths.lth.se Lecture 12 Periodic data A function g has period P if g(x + P ) = g(x) Model: Trigonometric polynomial of order M T M (x) =
derivation of the Laplacian from rectangular to spherical coordinates
derivation of the Laplacian from rectangular to spherical coordinates swapnizzle 03-03- :5:43 We begin by recognizing the familiar conversion from rectangular to spherical coordinates (note that φ is used
2 Composition. Invertible Mappings
Arkansas Tech University MATH 4033: Elementary Modern Algebra Dr. Marcel B. Finan Composition. Invertible Mappings In this section we discuss two procedures for creating new mappings from old ones, namely,
2. Μηχανικό Μαύρο Κουτί: κύλινδρος με μια μπάλα μέσα σε αυτόν.
Experiental Copetition: 14 July 011 Proble Page 1 of. Μηχανικό Μαύρο Κουτί: κύλινδρος με μια μπάλα μέσα σε αυτόν. Ένα μικρό σωματίδιο μάζας (μπάλα) βρίσκεται σε σταθερή απόσταση z από το πάνω μέρος ενός
Jesse Maassen and Mark Lundstrom Purdue University November 25, 2013
Notes on Average Scattering imes and Hall Factors Jesse Maassen and Mar Lundstrom Purdue University November 5, 13 I. Introduction 1 II. Solution of the BE 1 III. Exercises: Woring out average scattering
Example Sheet 3 Solutions
Example Sheet 3 Solutions. i Regular Sturm-Liouville. ii Singular Sturm-Liouville mixed boundary conditions. iii Not Sturm-Liouville ODE is not in Sturm-Liouville form. iv Regular Sturm-Liouville note
1 String with massive end-points
1 String with massive end-points Πρόβλημα 5.11:Θεωρείστε μια χορδή μήκους, τάσης T, με δύο σημειακά σωματίδια στα άκρα της, το ένα μάζας m, και το άλλο μάζας m. α) Μελετώντας την κίνηση των άκρων βρείτε
Areas and Lengths in Polar Coordinates
Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the
Approximation of distance between locations on earth given by latitude and longitude
Approximation of distance between locations on earth given by latitude and longitude Jan Behrens 2012-12-31 In this paper we shall provide a method to approximate distances between two points on earth
Other Test Constructions: Likelihood Ratio & Bayes Tests
Other Test Constructions: Likelihood Ratio & Bayes Tests Side-Note: So far we have seen a few approaches for creating tests such as Neyman-Pearson Lemma ( most powerful tests of H 0 : θ = θ 0 vs H 1 :
Lifting Entry (continued)
ifting Entry (continued) Basic planar dynamics of motion, again Yet another equilibrium glide Hypersonic phugoid motion Planar state equations MARYAN 1 01 avid. Akin - All rights reserved http://spacecraft.ssl.umd.edu
Homework 3 Solutions
Homework 3 Solutions Igor Yanovsky (Math 151A TA) Problem 1: Compute the absolute error and relative error in approximations of p by p. (Use calculator!) a) p π, p 22/7; b) p π, p 3.141. Solution: For
PARTIAL NOTES for 6.1 Trigonometric Identities
PARTIAL NOTES for 6.1 Trigonometric Identities tanθ = sinθ cosθ cotθ = cosθ sinθ BASIC IDENTITIES cscθ = 1 sinθ secθ = 1 cosθ cotθ = 1 tanθ PYTHAGOREAN IDENTITIES sin θ + cos θ =1 tan θ +1= sec θ 1 + cot
Problem Set 9 Solutions. θ + 1. θ 2 + cotθ ( ) sinθ e iφ is an eigenfunction of the ˆ L 2 operator. / θ 2. φ 2. sin 2 θ φ 2. ( ) = e iφ. = e iφ cosθ.
Chemistry 362 Dr Jean M Standard Problem Set 9 Solutions The ˆ L 2 operator is defined as Verify that the angular wavefunction Y θ,φ) Also verify that the eigenvalue is given by 2! 2 & L ˆ 2! 2 2 θ 2 +
Variational Wavefunction for the Helium Atom
Technische Universität Graz Institut für Festkörperphysik Student project Variational Wavefunction for the Helium Atom Molecular and Solid State Physics 53. submitted on: 3. November 9 by: Markus Krammer
forms This gives Remark 1. How to remember the above formulas: Substituting these into the equation we obtain with
Week 03: C lassification of S econd- Order L inear Equations In last week s lectures we have illustrated how to obtain the general solutions of first order PDEs using the method of characteristics. We
MATH423 String Theory Solutions 4. = 0 τ = f(s). (1) dτ ds = dxµ dτ f (s) (2) dτ 2 [f (s)] 2 + dxµ. dτ f (s) (3)
![MATH423 String Theory Solutions 4. = 0 τ = f(s). (1) dτ ds = dxµ dτ f (s) (2) dτ 2 [f (s)] 2 + dxµ. dτ f (s) (3)](/thumbs/81/84712331.jpg "MATH423 String Theory Solutions 4. = 0 τ = f(s). (1) dτ ds = dxµ dτ f (s) (2) dτ 2 [f (s)] 2 + dxµ. dτ f (s) (3)")
1. MATH43 String Theory Solutions 4 x = 0 τ = fs). 1) = = f s) ) x = x [f s)] + f s) 3) equation of motion is x = 0 if an only if f s) = 0 i.e. fs) = As + B with A, B constants. i.e. allowe reparametrisations
Finite difference method for 2-D heat equation
Finite difference method for 2-D heat equation Praveen. C praveen@math.tifrbng.res.in Tata Institute of Fundamental Research Center for Applicable Mathematics Bangalore 560065 http://math.tifrbng.res.in/~praveen
Areas and Lengths in Polar Coordinates
Kiryl Tsishchanka Areas and Lengths in Polar Coordinates In this section we develop the formula for the area of a region whose boundary is given by a polar equation. We need to use the formula for the
SCHOOL OF MATHEMATICAL SCIENCES G11LMA Linear Mathematics Examination Solutions
SCHOOL OF MATHEMATICAL SCIENCES GLMA Linear Mathematics 00- Examination Solutions. (a) i. ( + 5i)( i) = (6 + 5) + (5 )i = + i. Real part is, imaginary part is. (b) ii. + 5i i ( + 5i)( + i) = ( i)( + i)
b. Use the parametrization from (a) to compute the area of S a as S a ds. Be sure to substitute for ds!
MTH U341 urface Integrals, tokes theorem, the divergence theorem To be turned in Wed., Dec. 1. 1. Let be the sphere of radius a, x 2 + y 2 + z 2 a 2. a. Use spherical coordinates (with ρ a) to parametrize.
the total number of electrons passing through the lamp.
1. A 12 V 36 W lamp is lit to normal brightness using a 12 V car battery of negligible internal resistance. The lamp is switched on for one hour (3600 s). For the time of 1 hour, calculate (i) the energy
3.4 SUM AND DIFFERENCE FORMULAS. NOTE: cos(α+β) cos α + cos β cos(α-β) cos α -cos β
3.4 SUM AND DIFFERENCE FORMULAS Page Theorem cos(αβ cos α cos β -sin α cos(α-β cos α cos β sin α NOTE: cos(αβ cos α cos β cos(α-β cos α -cos β Proof of cos(α-β cos α cos β sin α Let s use a unit circle
Instruction Execution Times
1 C Execution Times InThisAppendix... Introduction DL330 Execution Times DL330P Execution Times DL340 Execution Times C-2 Execution Times Introduction Data Registers This appendix contains several tables
Οδηγίες Αγοράς Ηλεκτρονικού Βιβλίου Instructions for Buying an ebook
Οδηγίες Αγοράς Ηλεκτρονικού Βιβλίου Instructions for Buying an ebook Βήμα 1: Step 1: Βρείτε το βιβλίο που θα θέλατε να αγοράσετε και πατήστε Add to Cart, για να το προσθέσετε στο καλάθι σας. Αυτόματα θα
D Alembert s Solution to the Wave Equation
D Alembert s Solution to the Wave Equation MATH 467 Partial Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Objectives In this lesson we will learn: a change of variable technique
Problem Set 3: Solutions
CMPSCI 69GG Applied Information Theory Fall 006 Problem Set 3: Solutions. [Cover and Thomas 7.] a Define the following notation, C I p xx; Y max X; Y C I p xx; Ỹ max I X; Ỹ We would like to show that C
Written Examination. Antennas and Propagation (AA ) April 26, 2017.
Written Examination Antennas and Propagation (AA. 6-7) April 6, 7. Problem ( points) Let us consider a wire antenna as in Fig. characterized by a z-oriented linear filamentary current I(z) = I cos(kz)ẑ
DESIGN OF MACHINERY SOLUTION MANUAL h in h 4 0.
DESIGN OF MACHINERY SOLUTION MANUAL -7-1! PROBLEM -7 Statement: Design a double-dwell cam to move a follower from to 25 6, dwell for 12, fall 25 and dwell for the remader The total cycle must take 4 sec
Section 7.6 Double and Half Angle Formulas
09 Section 7. Double and Half Angle Fmulas To derive the double-angles fmulas, we will use the sum of two angles fmulas that we developed in the last section. We will let α θ and β θ: cos(θ) cos(θ + θ)
ECE Spring Prof. David R. Jackson ECE Dept. Notes 2
ECE 634 Spring 6 Prof. David R. Jackson ECE Dept. Notes Fields in a Source-Free Region Example: Radiation from an aperture y PEC E t x Aperture Assume the following choice of vector potentials: A F = =
ES440/ES911: CFD. Chapter 5. Solution of Linear Equation Systems
ES440/ES911: CFD Chapter 5. Solution of Linear Equation Systems Dr Yongmann M. Chung http://www.eng.warwick.ac.uk/staff/ymc/es440.html Y.M.Chung@warwick.ac.uk School of Engineering & Centre for Scientific
Introduction to Theory of. Elasticity. Kengo Nakajima Summer
Introduction to Theor of lasticit Summer Kengo Nakajima Technical & Scientific Computing I (48-7) Seminar on Computer Science (48-4) elast Theor of lasticit Target Stress Governing quations elast 3 Theor
[1] P Q. Fig. 3.1
![[1] P Q. Fig. 3.1](/thumbs/79/80362156.jpg "[1] P Q. Fig. 3.1")
1 (a) Define resistance....... [1] (b) The smallest conductor within a computer processing chip can be represented as a rectangular block that is one atom high, four atoms wide and twenty atoms long. One
Solutions to Exercise Sheet 5
Solutions to Eercise Sheet 5 jacques@ucsd.edu. Let X and Y be random variables with joint pdf f(, y) = 3y( + y) where and y. Determine each of the following probabilities. Solutions. a. P (X ). b. P (X
Mock Exam 7. 1 Hong Kong Educational Publishing Company. Section A 1. Reference: HKDSE Math M Q2 (a) (1 + kx) n 1M + 1A = (1) =
Mock Eam 7 Mock Eam 7 Section A. Reference: HKDSE Math M 0 Q (a) ( + k) n nn ( )( k) + nk ( ) + + nn ( ) k + nk + + + A nk... () nn ( ) k... () From (), k...() n Substituting () into (), nn ( ) n 76n 76n
( ) 2 and compare to M.
Problems and Solutions for Section 4.2 4.9 through 4.33) 4.9 Calculate the square root of the matrix 3!0 M!0 8 Hint: Let M / 2 a!b ; calculate M / 2!b c ) 2 and compare to M. Solution: Given: 3!0 M!0 8
Strain gauge and rosettes
Strain gauge and rosettes Introduction A strain gauge is a device which is used to measure strain (deformation) on an object subjected to forces. Strain can be measured using various types of devices classified
Fourier Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics
Fourier Series MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Introduction Not all functions can be represented by Taylor series. f (k) (c) A Taylor series f (x) = (x c)
Example of the Baum-Welch Algorithm
Example of the Baum-Welch Algorithm Larry Moss Q520, Spring 2008 1 Our corpus c We start with a very simple corpus. We take the set Y of unanalyzed words to be {ABBA, BAB}, and c to be given by c(abba)
6.3 Forecasting ARMA processes
122 CHAPTER 6. ARMA MODELS 6.3 Forecasting ARMA processes The purpose of forecasting is to predict future values of a TS based on the data collected to the present. In this section we will discuss a linear
C.S. 430 Assignment 6, Sample Solutions
C.S. 430 Assignment 6, Sample Solutions Paul Liu November 15, 2007 Note that these are sample solutions only; in many cases there were many acceptable answers. 1 Reynolds Problem 10.1 1.1 Normal-order
Math 6 SL Probability Distributions Practice Test Mark Scheme
Math 6 SL Probability Distributions Practice Test Mark Scheme. (a) Note: Award A for vertical line to right of mean, A for shading to right of their vertical line. AA N (b) evidence of recognizing symmetry
Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3
Lecture 2: Dirac notation and a review of linear algebra Read Sakurai chapter 1, Baym chatper 3 1 State vector space and the dual space Space of wavefunctions The space of wavefunctions is the set of all
Numerical Methods for Civil Engineers. Lecture 10 Ordinary Differential Equations. Ordinary Differential Equations. d x dx.
Numerical Metods for Civil Engineers Lecture Ordinar Differential Equations -Basic Ideas -Euler s Metod -Higer Order One-step Metods -Predictor-Corrector Approac -Runge-Kutta Metods -Adaptive Stepsize
Differential equations
Differential equations Differential equations: An equation inoling one dependent ariable and its deriaties w. r. t one or more independent ariables is called a differential equation. Order of differential
DERIVATION OF MILES EQUATION FOR AN APPLIED FORCE Revision C
DERIVATION OF MILES EQUATION FOR AN APPLIED FORCE Revision C By Tom Irvine Email: tomirvine@aol.com August 6, 8 Introduction The obective is to derive a Miles equation which gives the overall response
Figure A.2: MPC and MPCP Age Profiles (estimating ρ, ρ = 2, φ = 0.03)..
Supplemental Material (not for publication) Persistent vs. Permanent Income Shocks in the Buffer-Stock Model Jeppe Druedahl Thomas H. Jørgensen May, A Additional Figures and Tables Figure A.: Wealth and
ΚΥΠΡΙΑΚΗ ΕΤΑΙΡΕΙΑ ΠΛΗΡΟΦΟΡΙΚΗΣ CYPRUS COMPUTER SOCIETY ΠΑΓΚΥΠΡΙΟΣ ΜΑΘΗΤΙΚΟΣ ΔΙΑΓΩΝΙΣΜΟΣ ΠΛΗΡΟΦΟΡΙΚΗΣ 6/5/2006
Οδηγίες: Να απαντηθούν όλες οι ερωτήσεις. Ολοι οι αριθμοί που αναφέρονται σε όλα τα ερωτήματα είναι μικρότεροι το 1000 εκτός αν ορίζεται διαφορετικά στη διατύπωση του προβλήματος. Διάρκεια: 3,5 ώρες Καλή
CE 530 Molecular Simulation
C 53 olecular Siulation Lecture Histogra Reweighting ethods David. Kofke Departent of Cheical ngineering SUNY uffalo kofke@eng.buffalo.edu Histogra Reweighting ethod to cobine results taken at different
Assalamu `alaikum wr. wb.
LUMP SUM Assalamu `alaikum wr. wb. LUMP SUM Wassalamu alaikum wr. wb. Assalamu `alaikum wr. wb. LUMP SUM Wassalamu alaikum wr. wb. LUMP SUM Lump sum lump sum lump sum. lump sum fixed price lump sum lump
Lecture 2. Soundness and completeness of propositional logic
Lecture 2 Soundness and completeness of propositional logic February 9, 2004 1 Overview Review of natural deduction. Soundness and completeness. Semantics of propositional formulas. Soundness proof. Completeness
Advanced Subsidiary Unit 1: Understanding and Written Response
Write your name here Surname Other names Edexcel GE entre Number andidate Number Greek dvanced Subsidiary Unit 1: Understanding and Written Response Thursday 16 May 2013 Morning Time: 2 hours 45 minutes
What happens when two or more waves overlap in a certain region of space at the same time?
Wave Superposition What happens when two or more waves overlap in a certain region of space at the same time? To find the resulting wave according to the principle of superposition we should sum the fields
2. THEORY OF EQUATIONS. PREVIOUS EAMCET Bits.
EAMCET-. THEORY OF EQUATIONS PREVIOUS EAMCET Bits. Each of the roots of the equation x 6x + 6x 5= are increased by k so that the new transformed equation does not contain term. Then k =... - 4. - Sol.
The kinetic and potential energies as T = 1 2. (m i η2 i k(η i+1 η i ) 2 ). (3) The Hooke s law F = Y ξ, (6) with a discrete analog
Lecture 12: Introduction to Analytical Mechanics of Continuous Systems Lagrangian Density for Continuous Systems The kinetic and potential energies as T = 1 2 i η2 i (1 and V = 1 2 i+1 η i 2, i (2 where
Parametrized Surfaces
Parametrized Surfaces Recall from our unit on vector-valued functions at the beginning of the semester that an R 3 -valued function c(t) in one parameter is a mapping of the form c : I R 3 where I is some
ΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ. Ψηφιακή Οικονομία. Διάλεξη 7η: Consumer Behavior Mαρίνα Μπιτσάκη Τμήμα Επιστήμης Υπολογιστών
ΕΛΛΗΝΙΚΗ ΔΗΜΟΚΡΑΤΙΑ ΠΑΝΕΠΙΣΤΗΜΙΟ ΚΡΗΤΗΣ Ψηφιακή Οικονομία Διάλεξη 7η: Consumer Behavior Mαρίνα Μπιτσάκη Τμήμα Επιστήμης Υπολογιστών Τέλος Ενότητας Χρηματοδότηση Το παρόν εκπαιδευτικό υλικό έχει αναπτυχθεί
상대론적고에너지중이온충돌에서 제트입자와관련된제동복사 박가영 인하대학교 윤진희교수님, 권민정교수님
상대론적고에너지중이온충돌에서 제트입자와관련된제동복사 박가영 인하대학교 윤진희교수님, 권민정교수님 Motivation Bremsstrahlung is a major rocess losing energies while jet articles get through the medium. BUT it should be quite different from low energy
1) Formulation of the Problem as a Linear Programming Model
1) Formulation of the Problem as a Linear Programming Model Let xi = the amount of money invested in each of the potential investments in, where (i=1,2, ) x1 = the amount of money invested in Savings Account
Inverse trigonometric functions & General Solution of Trigonometric Equations. ------------------ ----------------------------- -----------------
Inverse trigonometric functions & General Solution of Trigonometric Equations. 1. Sin ( ) = a) b) c) d) Ans b. Solution : Method 1. Ans a: 17 > 1 a) is rejected. w.k.t Sin ( sin ) = d is rejected. If sin
Bayesian statistics. DS GA 1002 Probability and Statistics for Data Science.
Bayesian statistics DS GA 1002 Probability and Statistics for Data Science http://www.cims.nyu.edu/~cfgranda/pages/dsga1002_fall17 Carlos Fernandez-Granda Frequentist vs Bayesian statistics In frequentist
Concrete Mathematics Exercises from 30 September 2016
Concrete Mathematics Exercises from 30 September 2016 Silvio Capobianco Exercise 1.7 Let H(n) = J(n + 1) J(n). Equation (1.8) tells us that H(2n) = 2, and H(2n+1) = J(2n+2) J(2n+1) = (2J(n+1) 1) (2J(n)+1)
Calculating the propagation delay of coaxial cable
Your source for quality GNSS Networking Solutions and Design Services! Page 1 of 5 Calculating the propagation delay of coaxial cable The delay of a cable or velocity factor is determined by the dielectric
Section 9.2 Polar Equations and Graphs
180 Section 9. Polar Equations and Graphs In this section, we will be graphing polar equations on a polar grid. In the first few examples, we will write the polar equation in rectangular form to help identify
Reminders: linear functions
Reminders: linear functions Let U and V be vector spaces over the same field F. Definition A function f : U V is linear if for every u 1, u 2 U, f (u 1 + u 2 ) = f (u 1 ) + f (u 2 ), and for every u U
Math221: HW# 1 solutions
Math: HW# solutions Andy Royston October, 5 7.5.7, 3 rd Ed. We have a n = b n = a = fxdx = xdx =, x cos nxdx = x sin nx n sin nxdx n = cos nx n = n n, x sin nxdx = x cos nx n + cos nxdx n cos n = + sin
ΜΕΤΑΠΤΥΧΙΑΚΗ ΔΙΠΛΩΜΑΤΙΚΗ ΕΡΓΑΣΙΑ «ΘΕΜΑ»
ΠΑΝΕΠΙΣΤΗΜΙΟ ΑΙΓΑΙΟΥ ΣΧΟΛΗ ΑΝΘΡΩΠΙΣΤΙΚΩΝ ΕΠΙΣΤΗΜΩΝ ΤΜΗΜΑ ΕΠΙΣΤΗΜΩΝ ΤΗΣ ΠΡΟΣΧΟΛΙΚΗΣ ΑΓΩΓΗΣ ΚΑΙ ΤΟΥ ΕΚΠΑΙΔΕΥΤΙΚΟΥ ΣΧΕΔΙΑΣΜΟΥ Π.Μ.Σ. «ΠΕΡΙΒΑΛΛΟΝΤΙΚΗ ΕΚΠΑΙΔΕΥΣΗ» ΜΕΤΑΠΤΥΧΙΑΚΗ ΔΙΠΛΩΜΑΤΙΚΗ ΕΡΓΑΣΙΑ «ΘΕΜΑ» «Εφαρμογή