From Pi to Omega: Constants in Mathematics
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Calculating Numerical Roots = = 1.37480222744
#10 in Fundamentals of Applied Math Series Calculating Numerical Roots Richard J. Nelson Introduction – What is a root? Do you recognize this number(1)? 1.41421 35623 73095 04880 16887 24209 69807 85696 71875 37694 80731 76679 73799 07324 78462 10703 88503 87534 32764 15727 35013 84623 09122 97024 92483 60558 50737 21264 41214 97099 93583 14132 22665 92750 55927 55799 95050 11527 82060 57147 01095 59971 60597 02745 34596 86201 47285 17418 64088 91986 09552 32923 04843 08714 32145 08397 62603 62799 52514 07989 68725 33965 46331 80882 96406 20615 25835 Fig. 1 - HP35s √ key. 23950 54745 75028 77599 61729 83557 52203 37531 85701 13543 74603 40849 … If you have had any math classes you have probably run into this number and you should recognize it as the square root of two, . The square root of a number, n, is that value when multiplied by itself equals n. 2 x 2 = 4 and = 2. Calculating the square root of the number is the inverse operation of squaring that number = n. The "√" symbol is called the "radical" symbol or "check mark." MS Word has the radical symbol, √, but we often use it with a line across the top. This is called the "vinculum" circa 12th century. The expression " (2)" is read as "root n", "radical n", or "the square root of n". The vinculum extends over the number to make it inclusive e.g. Most HP calculators have the square root key as a primary key as shown in Fig. 1 because it is used so much. Roots and Powers Numbers may be raised to any power (y, multiplied by itself x times) and the inverse operation, taking the root, may be expressed as shown below. -
An Introduction to Mathematical Modelling
An Introduction to Mathematical Modelling Glenn Marion, Bioinformatics and Statistics Scotland Given 2008 by Daniel Lawson and Glenn Marion 2008 Contents 1 Introduction 1 1.1 Whatismathematicalmodelling?. .......... 1 1.2 Whatobjectivescanmodellingachieve? . ............ 1 1.3 Classificationsofmodels . ......... 1 1.4 Stagesofmodelling............................... ....... 2 2 Building models 4 2.1 Gettingstarted .................................. ...... 4 2.2 Systemsanalysis ................................. ...... 4 2.2.1 Makingassumptions ............................. .... 4 2.2.2 Flowdiagrams .................................. 6 2.3 Choosingmathematicalequations. ........... 7 2.3.1 Equationsfromtheliterature . ........ 7 2.3.2 Analogiesfromphysics. ...... 8 2.3.3 Dataexploration ............................... .... 8 2.4 Solvingequations................................ ....... 9 2.4.1 Analytically.................................. .... 9 2.4.2 Numerically................................... 10 3 Studying models 12 3.1 Dimensionlessform............................... ....... 12 3.2 Asymptoticbehaviour ............................. ....... 12 3.3 Sensitivityanalysis . ......... 14 3.4 Modellingmodeloutput . ....... 16 4 Testing models 18 4.1 Testingtheassumptions . ........ 18 4.2 Modelstructure.................................. ...... 18 i 4.3 Predictionofpreviouslyunuseddata . ............ 18 4.3.1 Reasonsforpredictionerrors . ........ 20 4.4 Estimatingmodelparameters . ......... 20 4.5 Comparingtwomodelsforthesamesystem . ......... -
Example 10.8 Testing the Steady-State Approximation. ⊕ a B C C a B C P + → → + → D Dt K K K K K K [ ]
Example 10.8 Testing the steady-state approximation. Å The steady-state approximation contains an apparent contradiction: we set the time derivative of the concentration of some species (a reaction intermediate) equal to zero — implying that it is a constant — and then derive a formula showing how it changes with time. Actually, there is no contradiction since all that is required it that the rate of change of the "steady" species be small compared to the rate of reaction (as measured by the rate of disappearance of the reactant or appearance of the product). But exactly when (in a practical sense) is this approximation appropriate? It is often applied as a matter of convenience and justified ex post facto — that is, if the resulting rate law fits the data then the approximation is considered justified. But as this example demonstrates, such reasoning is dangerous and possible erroneous. We examine the mechanism A + B ¾¾1® C C ¾¾2® A + B (10.12) 3 C® P (Note that the second reaction is the reverse of the first, so we have a reversible second-order reaction followed by an irreversible first-order reaction.) The rate constants are k1 for the forward reaction of the first step, k2 for the reverse of the first step, and k3 for the second step. This mechanism is readily solved for with the steady-state approximation to give d[A] k1k3 = - ke[A][B] with ke = (10.13) dt k2 + k3 (TEXT Eq. (10.38)). With initial concentrations of A and B equal, hence [A] = [B] for all times, this equation integrates to 1 1 = + ket (10.14) [A] A0 where A0 is the initial concentration (equal to 1 in work to follow). -
Finding Pi Project
Name: ________________________ Finding Pi - Activity Objective: You may already know that pi (π) is a number that is approximately equal to 3.14. But do you know where the number comes from? Let's measure some round objects and find out. Materials: • 6 circular objects Some examples include a bicycle wheel, kiddie pool, trash can lid, DVD, steering wheel, or clock face. Be sure each object you choose is shaped like a perfect circle. • metric tape measure Be sure your tape measure has centimeters on it. • calculator It will save you some time because dividing with decimals can be tricky. • “Finding Pi - Table” worksheet It may be attached to this page, or on the back. What to do: Step 1: Choose one of your circular objects. Write the name of the object on the “Finding Pi” table. Step 2: With the centimeter side of your tape measure, accurately measure the distance around the outside of the circle (the circumference). Record your measurement on the table. Step 3: Next, measure the distance across the middle of the object (the diameter). Record your measurement on the table. Step 4: Use your calculator to divide the circumference by the diameter. Write the answer on the table. If you measured carefully, the answer should be about 3.14, or π. Repeat steps 1 through 4 for each object. Super Teacher Worksheets - www.superteacherworksheets.com Name: ________________________ “Finding Pi” Table Measure circular objects and complete the table below. If your measurements are accurate, you should be able to calculate the number pi (3.14). Is your answer name of circumference diameter circumference ÷ approximately circular object measurement (cm) measurement (cm) diameter equal to π? 1. -
UNDERSTANDING MATHEMATICS to UNDERSTAND PLATO -THEAETEUS (147D-148B Salomon Ofman
UNDERSTANDING MATHEMATICS TO UNDERSTAND PLATO -THEAETEUS (147d-148b Salomon Ofman To cite this version: Salomon Ofman. UNDERSTANDING MATHEMATICS TO UNDERSTAND PLATO -THEAETEUS (147d-148b. Lato Sensu, revue de la Société de philosophie des sciences, Société de philosophie des sciences, 2014, 1 (1). hal-01305361 HAL Id: hal-01305361 https://hal.archives-ouvertes.fr/hal-01305361 Submitted on 20 Apr 2016 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. UNDERSTANDING MATHEMATICS TO UNDERSTAND PLATO - THEAETEUS (147d-148b) COMPRENDRE LES MATHÉMATIQUES POUR COMPRENDRE PLATON - THÉÉTÈTE (147d-148b) Salomon OFMAN Institut mathématique de Jussieu-PRG Histoire des Sciences mathématiques 4 Place Jussieu 75005 Paris [email protected] Abstract. This paper is an updated translation of an article published in French in the Journal Lato Sensu (I, 2014, p. 70-80). We study here the so- called ‘Mathematical part’ of Plato’s Theaetetus. Its subject concerns the incommensurability of certain magnitudes, in modern terms the question of the rationality or irrationality of the square roots of integers. As the most ancient text on the subject, and on Greek mathematics and mathematicians as well, its historical importance is enormous. -
Proofs by Cases, Square Root of 2 Is Irrational, Operations on Sets
COMP 1002 Intro to Logic for Computer Scientists Lecture 16 B 5 2 J Puzzle: Caesar cipher • The Roman dictator Julius Caesar encrypted his personal correspondence using the following code. – Number letters of the alphabet: A=0, B=1,… Z=25. – To encode a message, replace every letter by a letter three positions before that (wrapping). • A letter numbered x by a letter numbered x-3 mod 26. • For example, F would be replaced by C, and A by X • Suppose he sent the following message. – QOBXPROB FK QEB ZXSB • What does it say? Proof by cases • Use the tautology • If is ( ) ( ), 1 2 1 2 • prove 푝 ∨ 푝( ∧ 푝 → 푞 ∧). 푝 → 푞 → 푞 1 2 • Proof:∀푥 퐹 푥 ∀푥 퐺 푥 ∨ 퐺 푥 → 퐻 푥 1 2 – Universal퐺 푥 instantiation:→ 퐻 푥 ∧ 퐺“let푥 n be→ an퐻 arbitrary푥 element of the domain of ” – Case 1: ( ) – Case 2: 푆 ∀푥 ( ) 1 – Therefore,퐺 (푛 → 퐻 푛 ) ( ), 2 – Now use퐺 universal푛 → 퐻 generalization푛 to conclude that is true. 퐺1 푛 ∨ 퐺2 푛 → 퐻 푛 • This generalizes for any number of cases 2. ∀ 푥 퐹 푥 푘 ≥ (Done). □ Proof by cases. • Definition (of odd integers): – An integer n is odd iff , = 2 + 1. • Theorem: Sum of an integer with a consecutive integer is odd. ∃푘 ∈ ℤ 푛 ⋅ 푘 – ( + + 1 ). • Proof: – Suppose∀푥 ∈ ℤ 푂푂푂n is an푥 arbitrary푥 integer. – Case 1: n is even. • So n=2k for some k (by definition). • Its consecutive integer is n+1 = 2k+1. Their sum is (n+(n+1))= 2k + (2k+1) = 4k+1. (axioms). -
Differentiation Rules (Differential Calculus)
Differentiation Rules (Differential Calculus) 1. Notation The derivative of a function f with respect to one independent variable (usually x or t) is a function that will be denoted by D f . Note that f (x) and (D f )(x) are the values of these functions at x. 2. Alternate Notations for (D f )(x) d d f (x) d f 0 (1) For functions f in one variable, x, alternate notations are: Dx f (x), dx f (x), dx , dx (x), f (x), f (x). The “(x)” part might be dropped although technically this changes the meaning: f is the name of a function, dy 0 whereas f (x) is the value of it at x. If y = f (x), then Dxy, dx , y , etc. can be used. If the variable t represents time then Dt f can be written f˙. The differential, “d f ”, and the change in f ,“D f ”, are related to the derivative but have special meanings and are never used to indicate ordinary differentiation. dy 0 Historical note: Newton used y,˙ while Leibniz used dx . About a century later Lagrange introduced y and Arbogast introduced the operator notation D. 3. Domains The domain of D f is always a subset of the domain of f . The conventional domain of f , if f (x) is given by an algebraic expression, is all values of x for which the expression is defined and results in a real number. If f has the conventional domain, then D f usually, but not always, has conventional domain. Exceptions are noted below. -
Optimization of the Manufacturing Process for Sheet Metal Panels Considering Shape, Tessellation and Structural Stability Optimi
Institute of Construction Informatics, Faculty of Civil Engineering Optimization of the manufacturing process for sheet metal panels considering shape, tessellation and structural stability Optimierung des Herstellungsprozesses von dünnwandigen, profilierten Aussenwandpaneelen by Fasih Mohiuddin Syed from Mysore, India A Master thesis submitted to the Institute of Construction Informatics, Faculty of Civil Engineering, University of Technology Dresden in partial fulfilment of the requirements for the degree of Master of Science Responsible Professor : Prof. Dr.-Ing. habil. Karsten Menzel Second Examiner : Prof. Dr.-Ing. Raimar Scherer Advisor : Dipl.-Ing. Johannes Frank Schüler Dresden, 14th April, 2020 Task Sheet II Task Sheet Declaration III Declaration I confirm that this assignment is my own work and that I have not sought or used the inadmissible help of third parties to produce this work. I have fully referenced and used inverted commas for all text directly quoted from a source. Any indirect quotations have been duly marked as such. This work has not yet been submitted to another examination institution – neither in Germany nor outside Germany – neither in the same nor in a similar way and has not yet been published. Dresden, Place, Date (Signature) Acknowledgement IV Acknowledgement First, I would like to express my sincere gratitude to Prof. Dr.-Ing. habil. Karsten Menzel, Chair of the "Institute of Construction Informatics" for giving me this opportunity to work on my master thesis and believing in my work. I am very grateful to Dipl.-Ing. Johannes Frank Schüler for his encouragement, guidance and support during the course of work. I would like to thank all the staff from "Institute of Construction Informatics " for their valuable support. -
Evaluating Fourier Transforms with MATLAB
ECE 460 – Introduction to Communication Systems MATLAB Tutorial #2 Evaluating Fourier Transforms with MATLAB In class we study the analytic approach for determining the Fourier transform of a continuous time signal. In this tutorial numerical methods are used for finding the Fourier transform of continuous time signals with MATLAB are presented. Using MATLAB to Plot the Fourier Transform of a Time Function The aperiodic pulse shown below: x(t) 1 t -2 2 has a Fourier transform: X ( jf ) = 4sinc(4π f ) This can be found using the Table of Fourier Transforms. We can use MATLAB to plot this transform. MATLAB has a built-in sinc function. However, the definition of the MATLAB sinc function is slightly different than the one used in class and on the Fourier transform table. In MATLAB: sin(π x) sinc(x) = π x Thus, in MATLAB we write the transform, X, using sinc(4f), since the π factor is built in to the function. The following MATLAB commands will plot this Fourier Transform: >> f=-5:.01:5; >> X=4*sinc(4*f); >> plot(f,X) In this case, the Fourier transform is a purely real function. Thus, we can plot it as shown above. In general, Fourier transforms are complex functions and we need to plot the amplitude and phase spectrum separately. This can be done using the following commands: >> plot(f,abs(X)) >> plot(f,angle(X)) Note that the angle is either zero or π. This reflects the positive and negative values of the transform function. Performing the Fourier Integral Numerically For the pulse presented above, the Fourier transform can be found easily using the table. -
The Catenary
The Catenary Daniel Gent December 10, 2008 Daniel Gent The Catenary I The shape of the catenary was originally thought to be a parabola by Galileo, but this was proved false by the German mathmatitian Jungius in 1663. It was not until 1691 that the true shape of the catenary was discovered to be the hyperbolic cosine in a joint work by Leibnez, Huygens, and Bernoulli. History of the catenary. I The catenary is defined by the shape formed by a hanging chain under normal conditions. The name catenary comes from the latin word for chain catena. Daniel Gent The Catenary History of the catenary. I The catenary is defined by the shape formed by a hanging chain under normal conditions. The name catenary comes from the latin word for chain catena. I The shape of the catenary was originally thought to be a parabola by Galileo, but this was proved false by the German mathmatitian Jungius in 1663. It was not until 1691 that the true shape of the catenary was discovered to be the hyperbolic cosine in a joint work by Leibnez, Huygens, and Bernoulli. Daniel Gent The Catenary I The forces on the chain at the point (x,y) will be the tension in the chain (T) which is tangent to the chain, the weight of the chain (W), and the horizontal pull (H) at the origin. Now the magnitude of the weight is proportional to the distance (s) from the origin to the point (x,y). I Thus the sum of the forces W and H must be equal to −T , but since T is tangent to the chain the slope of H + W must equal f 0(x). -
PLEASANTON UNIFIED SCHOOL DISTRICT Math 8/Algebra I Course Outline Form Course Title
PLEASANTON UNIFIED SCHOOL DISTRICT Math 8/Algebra I Course Outline Form Course Title: Math 8/Algebra I Course Number/CBED Number: Grade Level: 8 Length of Course: 1 year Credit: 10 Meets Graduation Requirements: n/a Required for Graduation: Prerequisite: Math 6/7 or Math 7 Course Description: Main concepts from the CCSS 8th grade content standards include: knowing that there are numbers that are not rational, and approximate them by rational numbers; working with radicals and integer exponents; understanding the connections between proportional relationships, lines, and linear equations; analyzing and solving linear equations and pairs of simultaneous linear equations; defining, evaluating, and comparing functions; using functions to model relationships between quantities; understanding congruence and similarity using physical models, transparencies, or geometry software; understanding and applying the Pythagorean Theorem; investigating patterns of association in bivariate data. Algebra (CCSS Algebra) main concepts include: reason quantitatively and use units to solve problems; create equations that describe numbers or relationships; understanding solving equations as a process of reasoning and explain reasoning; solve equations and inequalities in one variable; solve systems of equations; represent and solve equations and inequalities graphically; extend the properties of exponents to rational exponents; use properties of rational and irrational numbers; analyze and solve linear equations and pairs of simultaneous linear equations; define, -
Length of a Hanging Cable
Undergraduate Journal of Mathematical Modeling: One + Two Volume 4 | 2011 Fall Article 4 2011 Length of a Hanging Cable Eric Costello University of South Florida Advisors: Arcadii Grinshpan, Mathematics and Statistics Frank Smith, White Oak Technologies Problem Suggested By: Frank Smith Follow this and additional works at: https://scholarcommons.usf.edu/ujmm Part of the Mathematics Commons UJMM is an open access journal, free to authors and readers, and relies on your support: Donate Now Recommended Citation Costello, Eric (2011) "Length of a Hanging Cable," Undergraduate Journal of Mathematical Modeling: One + Two: Vol. 4: Iss. 1, Article 4. DOI: http://dx.doi.org/10.5038/2326-3652.4.1.4 Available at: https://scholarcommons.usf.edu/ujmm/vol4/iss1/4 Length of a Hanging Cable Abstract The shape of a cable hanging under its own weight and uniform horizontal tension between two power poles is a catenary. The catenary is a curve which has an equation defined yb a hyperbolic cosine function and a scaling factor. The scaling factor for power cables hanging under their own weight is equal to the horizontal tension on the cable divided by the weight of the cable. Both of these values are unknown for this problem. Newton's method was used to approximate the scaling factor and the arc length function to determine the length of the cable. A script was written using the Python programming language in order to quickly perform several iterations of Newton's method to get a good approximation for the scaling factor. Keywords Hanging Cable, Newton’s Method, Catenary Creative Commons License This work is licensed under a Creative Commons Attribution-Noncommercial-Share Alike 4.0 License.