Engineering Mathematics: New Applications
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en-us2017 Maplesoft, A Division of Waterloo Maple Inc.Maplesoft Document SystemWed, 18 Jan 2017 05:55:00 GMTWed, 18 Jan 2017 05:55:00 GMTNew applications in the Engineering Mathematics categoryhttp://www.mapleprimes.com/images/mapleapps.gifEngineering Mathematics: New Applications
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Pulsdruckwerte aus Langzeitmessung
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During a period of nearly 24 hours the blood pressure of a patient at a Hospital in Aachen has been measured. Thus, we have a lot of Systole-, Diastole-, Pulse Pressure-, and Pulse-Values important for a medical doctor treating sick patients. This worksheet is concerned with the mathematical analysis of this data.<img src="/view.aspx?si=154144/pressure.PNG" alt="Pulsdruckwerte aus Langzeitmessung" align="left"/>During a period of nearly 24 hours the blood pressure of a patient at a Hospital in Aachen has been measured. Thus, we have a lot of Systole-, Diastole-, Pulse Pressure-, and Pulse-Values important for a medical doctor treating sick patients. This worksheet is concerned with the mathematical analysis of this data.154144Tue, 06 Sep 2016 04:00:00 ZProf. Josef BettenProf. Josef BettenPulse Values from Long Term Measurement
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Long term measurement of heart rate furnishes important information of cardiac anomalies. During a period of about 24 hours pulse rate of a patient at the University Hospital Aachen has been measured. Thus, we have a lots of pulse values, which are important for a medical doctor treating sick patients. We use Maple to analyze this data. At first the given data have been interpolated by cubic spline functions. Then, these functions have been approximated by nonlinear regression and also by Fourier series.<img src="/view.aspx?si=154087/pulsevalues.png" alt="Pulse Values from Long Term Measurement" align="left"/>Long term measurement of heart rate furnishes important information of cardiac anomalies. During a period of about 24 hours pulse rate of a patient at the University Hospital Aachen has been measured. Thus, we have a lots of pulse values, which are important for a medical doctor treating sick patients. We use Maple to analyze this data. At first the given data have been interpolated by cubic spline functions. Then, these functions have been approximated by nonlinear regression and also by Fourier series.154087Wed, 20 Apr 2016 04:00:00 ZProf. Josef BettenProf. Josef BettenVectors in the plane.
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If an object is subjected to several forces having different magnitudes and act in different directions, how can determine the magnitude and direction of the resultant total force on the object? Forces are vectors and should be added according to the definition of the vector sum. Engineering dealing with many quantities that have both magnitude and direction and can be expressed and analyzed as vectors.
<BR><BR>
In Spanish.<img src="/view.aspx?si=154071/vpThumb.jpg" alt="Vectors in the plane." align="left"/>If an object is subjected to several forces having different magnitudes and act in different directions, how can determine the magnitude and direction of the resultant total force on the object? Forces are vectors and should be added according to the definition of the vector sum. Engineering dealing with many quantities that have both magnitude and direction and can be expressed and analyzed as vectors.
<BR><BR>
In Spanish.154071Fri, 01 Apr 2016 04:00:00 ZProf. Lenin Araujo CastilloProf. Lenin Araujo CastilloGlobal Population from 1804 to 2015
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This worksheet is concerned with the development of the global population during the period of 1804 – 2015, where the population rose from 10^9 to 7.4*10^9. The given data has been interpolated by the cubic spline function. Several nonlinear model functions to data have been suggested and tested by using error norms.<img src="/view.aspx?si=153967/population.png" alt="Global Population from 1804 to 2015" align="left"/>This worksheet is concerned with the development of the global population during the period of 1804 – 2015, where the population rose from 10^9 to 7.4*10^9. The given data has been interpolated by the cubic spline function. Several nonlinear model functions to data have been suggested and tested by using error norms.153967Tue, 09 Feb 2016 05:00:00 ZProf. Josef BettenProf. Josef BettenDemo Worksheet for Numerical Delay Differential Equation Solution
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<P>This application shows several examples of modeling using delay differential equations in Maple. These examples are from the webinar <A HREF="http://www.maplesoft.com/products/maple/demo/player/2015/solvingdelaydiffeq.aspx">Solving Delay Differential Equations</A>.</P>
<P>Note: Requires Maple 2015.2 or later.</P><img src="/view.aspx?si=153939/dde.PNG" alt="Demo Worksheet for Numerical Delay Differential Equation Solution" align="left"/><P>This application shows several examples of modeling using delay differential equations in Maple. These examples are from the webinar <A HREF="http://www.maplesoft.com/products/maple/demo/player/2015/solvingdelaydiffeq.aspx">Solving Delay Differential Equations</A>.</P>
<P>Note: Requires Maple 2015.2 or later.</P>153939Wed, 16 Dec 2015 05:00:00 ZAllan WittkopfAllan WittkopfNonlinear Viscoelastic Behaviour of Brain Tissue
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In this worksheet the relaxation of Brain Tissue has been calculated to experimental data by two nonlinear model functions:
a five parameters PRONY-Series and compared with a three parameters Sqrt(t)-Law due to BETTEN, Creep Mechanics, 3rd edtion, 2008 Springer-Verlag Berlin / Heidelberg.<img src="/applications/images/app_image_blank_lg.jpg" alt="Nonlinear Viscoelastic Behaviour of Brain Tissue" align="left"/>In this worksheet the relaxation of Brain Tissue has been calculated to experimental data by two nonlinear model functions:
a five parameters PRONY-Series and compared with a three parameters Sqrt(t)-Law due to BETTEN, Creep Mechanics, 3rd edtion, 2008 Springer-Verlag Berlin / Heidelberg.153923Tue, 01 Dec 2015 05:00:00 ZProf. Josef BettenProf. Josef BettenNonlinear Regression with Maple
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Many Authors have discussed Nonlinear Regression based upon the LEVENBERG-MARQUART algorithm. Often the SIGMAPLOT Program is very useful, too.
In this worksheet the Maple routine NonlinearFit [Statistics] has been preferred, to fit nonlinear model functions to given data. This routine is very effective and simple to use. Examples in this document include the envelopes of FRENEL's integrals and the hardening of an aluminium alloy.<img src="/applications/images/app_image_blank_lg.jpg" alt="Nonlinear Regression with Maple" align="left"/>Many Authors have discussed Nonlinear Regression based upon the LEVENBERG-MARQUART algorithm. Often the SIGMAPLOT Program is very useful, too.
In this worksheet the Maple routine NonlinearFit [Statistics] has been preferred, to fit nonlinear model functions to given data. This routine is very effective and simple to use. Examples in this document include the envelopes of FRENEL's integrals and the hardening of an aluminium alloy.153895Wed, 14 Oct 2015 04:00:00 ZProf. Josef BettenProf. Josef BettenPacking Circles into a Triangle
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<p>This application finds the best packing and largest radius of equal-sized circles, such that they fit in a pre-defined triangle. One solution, as visualized by this application, is given below.</p>
<p>This is a difficult global optimization problem and demands strong solvers. This application uses Maple's <a href="http://www.maplesoft.com/products/toolboxes/globaloptimization/">Global Optimization Toolbox</a>.</p>
<p>Circle packing (and packing optimization in general) is characterized by a large optimization space and many constraints; for this application, 20 circles generates 310 constraint equations.</p>
<p>The number of circles can be increased to create an increasingly complex problem; Maple automatically generates the symbolic constraint equations. The vertices of the triangle can also be modified</p>
<p>Applications like this are used to stress-test global optimizers.</p><img src="/view.aspx?si=153596/2ac6ca1378717b3d939f3d8107616b35.gif" alt="Packing Circles into a Triangle" align="left"/><p>This application finds the best packing and largest radius of equal-sized circles, such that they fit in a pre-defined triangle. One solution, as visualized by this application, is given below.</p>
<p>This is a difficult global optimization problem and demands strong solvers. This application uses Maple's <a href="http://www.maplesoft.com/products/toolboxes/globaloptimization/">Global Optimization Toolbox</a>.</p>
<p>Circle packing (and packing optimization in general) is characterized by a large optimization space and many constraints; for this application, 20 circles generates 310 constraint equations.</p>
<p>The number of circles can be increased to create an increasingly complex problem; Maple automatically generates the symbolic constraint equations. The vertices of the triangle can also be modified</p>
<p>Applications like this are used to stress-test global optimizers.</p>153596Wed, 04 Jun 2014 04:00:00 ZSamir KhanSamir KhanCircle Packing in an Ellipse
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<p>This application optimizes the packing of circles in an ellipse, such that the area of the ellipse is minimized. A typical solution is visualized here.</p>
<p>This is a difficult global optimization problem and demands strong solvers. This application uses Maple's <a href="/products/toolboxes/globaloptimization/">Global Optimization Toolbox</a>.</p>
<p>Circle packing (and packing optimization in general) is characterized by a large optimization space and many constraints; for this application, 35 circles generates 666 constraint equations.</p>
<p>The number of circles can be increased to create an increasingly complex problem; Maple automatically generates the symbolic constraint equations.</p>
<p>Applications like this are used to stress-test global optimizers.</p>
<p>The constraints and ellipse parameterization are taken from "Packing circles within ellipses", Birgin et al., International Transactions in Operational Research , Volume 20, Issue 3, pages 365–389, May 2013.</p><img src="/view.aspx?si=153598/5f52383daddaeb53aec548d14ebd6ce0.gif" alt="Circle Packing in an Ellipse" align="left"/><p>This application optimizes the packing of circles in an ellipse, such that the area of the ellipse is minimized. A typical solution is visualized here.</p>
<p>This is a difficult global optimization problem and demands strong solvers. This application uses Maple's <a href="/products/toolboxes/globaloptimization/">Global Optimization Toolbox</a>.</p>
<p>Circle packing (and packing optimization in general) is characterized by a large optimization space and many constraints; for this application, 35 circles generates 666 constraint equations.</p>
<p>The number of circles can be increased to create an increasingly complex problem; Maple automatically generates the symbolic constraint equations.</p>
<p>Applications like this are used to stress-test global optimizers.</p>
<p>The constraints and ellipse parameterization are taken from "Packing circles within ellipses", Birgin et al., International Transactions in Operational Research , Volume 20, Issue 3, pages 365–389, May 2013.</p>153598Wed, 04 Jun 2014 04:00:00 ZSamir KhanSamir KhanCircle Packing in a Square
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<p>This application optimizes the packing of circles (of varying radii) in a square, such that the side-length of the square is minimized. One solution for 20 circles (with integer radii of 1 to 20) is visualized here.</p>
<p>This is a difficult global optimization problem and demands strong solvers. This application uses Maple's <a href="/products/toolboxes/globaloptimization/">Global Optimization Toolbox</a>.</p>
<p>Circle packing (and packing optimization in general) is characterized by a large optimization space and many constraints; for this application, 20 circles generates 230 constraint equations.</p>
<p>The number of circles can be increased to create an increasingly complex problem; Maple automatically generates the symbolic constraint equations.</p>
<p>Applications like this are used to stress-test global optimizers.</p><img src="/view.aspx?si=153599/071f7b81258c5cad651a5030370d824f.gif" alt="Circle Packing in a Square" align="left"/><p>This application optimizes the packing of circles (of varying radii) in a square, such that the side-length of the square is minimized. One solution for 20 circles (with integer radii of 1 to 20) is visualized here.</p>
<p>This is a difficult global optimization problem and demands strong solvers. This application uses Maple's <a href="/products/toolboxes/globaloptimization/">Global Optimization Toolbox</a>.</p>
<p>Circle packing (and packing optimization in general) is characterized by a large optimization space and many constraints; for this application, 20 circles generates 230 constraint equations.</p>
<p>The number of circles can be increased to create an increasingly complex problem; Maple automatically generates the symbolic constraint equations.</p>
<p>Applications like this are used to stress-test global optimizers.</p>153599Wed, 04 Jun 2014 04:00:00 ZSamir KhanSamir KhanPacking Disks into a Circle
http://www.maplesoft.com/applications/view.aspx?SID=153600&ref=Feed
<p>This application finds the best packing of unequal non-overlapping disks in a circular container, such that the radius of the container is minimized. This is a tough global optimization problem that demands strong solvers; this application uses Maple's <a href="/products/toolboxes/globaloptimization/">Global Optimization Toolbox</a>. You must have the Global Optimization Toolbox installed to use this application.</p>
<p>One solution for the packing of 50 disks with the integer radii 1 to 50 (as found by this application) is visualized here.</p>
<p>Other solutions for similar packing problems are documented at <a href="http://www.packomania.com">http://www.packomania.com</a>.</p>
<p>Packing optimization is industrially important, with applications in pallet loading, the arrangement of fiber optic cables in a tube, or the placing of components on a circuit board.</p><img src="/view.aspx?si=153600/32183b61c1bca332d0c71924ae09f73a.gif" alt="Packing Disks into a Circle" align="left"/><p>This application finds the best packing of unequal non-overlapping disks in a circular container, such that the radius of the container is minimized. This is a tough global optimization problem that demands strong solvers; this application uses Maple's <a href="/products/toolboxes/globaloptimization/">Global Optimization Toolbox</a>. You must have the Global Optimization Toolbox installed to use this application.</p>
<p>One solution for the packing of 50 disks with the integer radii 1 to 50 (as found by this application) is visualized here.</p>
<p>Other solutions for similar packing problems are documented at <a href="http://www.packomania.com">http://www.packomania.com</a>.</p>
<p>Packing optimization is industrially important, with applications in pallet loading, the arrangement of fiber optic cables in a tube, or the placing of components on a circuit board.</p>153600Wed, 04 Jun 2014 04:00:00 ZSamir KhanSamir KhanAutomatic Speech Segmentation
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<p>This worksheet demonstrates the use of the Forward-Backward Divergence model (FBD) in Automatic Speech Segmentation, and how it detects discontinuities in the voice signal. It illustrates in the example below how it is possible to enlarge some segments of the speech (vowels enlargement for instance). To realize this result, it is possible to visually and acoustically perceive the stationary segments of the speech signal.</p><img src="/view.aspx?si=153553/speech.png" alt="Automatic Speech Segmentation" align="left"/><p>This worksheet demonstrates the use of the Forward-Backward Divergence model (FBD) in Automatic Speech Segmentation, and how it detects discontinuities in the voice signal. It illustrates in the example below how it is possible to enlarge some segments of the speech (vowels enlargement for instance). To realize this result, it is possible to visually and acoustically perceive the stationary segments of the speech signal.</p>153553Thu, 17 Apr 2014 04:00:00 ZJocelyn MagneJocelyn MagneWavelet analysis of the blood pressure and pulse frequency measurements with Maple
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<p>A significant part of medical signals, or observations, is non-stationary, discrete time sequences. Thus, the computer methods analysis, as well as refinement and compression, are very helpful as for the problems of recognition and detection of their key diagnostic features. We are going to illustrate here this statement with examples of very common, and even routine medical measurements of blood pressure as well as pulse rate and with possibilities of Maple.<br />The package of Discrete Wavelet transforms (DWT) within Maple 16 [1] was recently added as new research software just for such tasks. The practical testing of this package was additional goal of present study.</p><img src="/view.aspx?si=149420/4b9024ee653d2c7be8febb717b1df52a.gif" alt="Wavelet analysis of the blood pressure and pulse frequency measurements with Maple" align="left"/><p>A significant part of medical signals, or observations, is non-stationary, discrete time sequences. Thus, the computer methods analysis, as well as refinement and compression, are very helpful as for the problems of recognition and detection of their key diagnostic features. We are going to illustrate here this statement with examples of very common, and even routine medical measurements of blood pressure as well as pulse rate and with possibilities of Maple.<br />The package of Discrete Wavelet transforms (DWT) within Maple 16 [1] was recently added as new research software just for such tasks. The practical testing of this package was additional goal of present study.</p>149420Sun, 14 Jul 2013 04:00:00 ZIrina A. DanishewskaIrina A. DanishewskaHardening of Aluminium Alloy AA 7075 T 7351
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<p><span id="ctl00_mainContent__documentViewer"><span><span class="body summary">This worksheet is concerned with the hardening of aluminium alloy, the behaviour of which can be expressed by a simple power law with two hardening parameters. Based upon experimental data these parameters have been determined by both a linear regrssion and the nonlinear <em>MARQUARDT-LEVENBERG algorithm.</em></span></span></span></p><img src="/applications/images/app_image_blank_lg.jpg" alt="Hardening of Aluminium Alloy AA 7075 T 7351" align="left"/><p><span id="ctl00_mainContent__documentViewer"><span><span class="body summary">This worksheet is concerned with the hardening of aluminium alloy, the behaviour of which can be expressed by a simple power law with two hardening parameters. Based upon experimental data these parameters have been determined by both a linear regrssion and the nonlinear <em>MARQUARDT-LEVENBERG algorithm.</em></span></span></span></p>140361Wed, 14 Nov 2012 05:00:00 ZJosef BettenJosef BettenClassroom Tips and Techniques: Fourier Series and an Orthogonal Expansions Package
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The OrthogonalExpansions package contributed to the Maple Application Center by Dr. Sergey Moiseev is considered as a tool for generating a Fourier series and its partial sums. This package provides commands for expansions in 17 other bases of orthogonal functions. In addition to looking at the Fourier series option, this article also considers the Bessel series expansion.<img src="/view.aspx?si=134198/thumb.jpg" alt="Classroom Tips and Techniques: Fourier Series and an Orthogonal Expansions Package" align="left"/>The OrthogonalExpansions package contributed to the Maple Application Center by Dr. Sergey Moiseev is considered as a tool for generating a Fourier series and its partial sums. This package provides commands for expansions in 17 other bases of orthogonal functions. In addition to looking at the Fourier series option, this article also considers the Bessel series expansion.134198Mon, 14 May 2012 04:00:00 ZDr. Robert LopezDr. Robert LopezSolving Equations with Maple
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<p>This worksheet is concerned with methods implemented in Maple to solve some equations of several types.</p>
<p> For instance, the procedures <strong>fsolve </strong>and <strong>RootOf </strong>are very effective and should be used in the following examples.</p>
<p> </p>
<p><em>Keywords: </em>fsolve, RootOf, polynomials of degree n > 3, orthopoly, <em>HERMITE, LEGENDRE, </em></p>
<p><em> LAGUERRE, CHEBYSHEV, </em>transcendental equations</p>
<p> </p>
<p><em><br /></em></p><img src="/applications/images/app_image_blank_lg.jpg" alt="Solving Equations with Maple" align="left"/><p>This worksheet is concerned with methods implemented in Maple to solve some equations of several types.</p>
<p> For instance, the procedures <strong>fsolve </strong>and <strong>RootOf </strong>are very effective and should be used in the following examples.</p>
<p> </p>
<p><em>Keywords: </em>fsolve, RootOf, polynomials of degree n > 3, orthopoly, <em>HERMITE, LEGENDRE, </em></p>
<p><em> LAGUERRE, CHEBYSHEV, </em>transcendental equations</p>
<p> </p>
<p><em><br /></em></p>130644Mon, 13 Feb 2012 05:00:00 ZProf. Josef BettenProf. Josef BettenClassroom Tips and Techniques: An Undamped Coupled Oscillator
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<p>Even for just three degrees of freedom, an undamped coupled oscillator modeled by the ODE system <em>M</em> ü + <em>K</em> u = 0 is difficult to solve analytically because, ultimately, a cubic characteristic equation has to be solve exactly. Instead, we simultaneously diagonalize <em>M</em> and <em>K</em>, the mass and stiffness matrices, thereby uncoupling the equations, and obtaining an explicit solution.</p><img src="/view.aspx?si=129521/thumb.jpg" alt="Classroom Tips and Techniques: An Undamped Coupled Oscillator" align="left"/><p>Even for just three degrees of freedom, an undamped coupled oscillator modeled by the ODE system <em>M</em> ü + <em>K</em> u = 0 is difficult to solve analytically because, ultimately, a cubic characteristic equation has to be solve exactly. Instead, we simultaneously diagonalize <em>M</em> and <em>K</em>, the mass and stiffness matrices, thereby uncoupling the equations, and obtaining an explicit solution.</p>129521Tue, 10 Jan 2012 05:00:00 ZDr. Robert LopezDr. Robert LopezClassroom Tips and Techniques: Simultaneous Diagonalization and the Generalized Eigenvalue Problem
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<p>This article explores the connections between the generalized eigenvalue problem and the problem of simultaneously diagonalizing a pair of <em>n × n</em> matrices.</p>
<p>Given the <em>n × n</em> matrices <em>A</em> and <em>B</em>, the <em>generalized eigenvalue problem</em> seeks the eigenpairs <em>(lambda<sub>k</sub>, x<sub>k</sub>)</em>, solutions of the equation <em>Ax = lambda Bx</em>, or <em>(A - lambda B) x = 0</em>. If <em>B</em> is nonsingular, the eigenpairs of <em>B<sup>-1</sup> A</em> are solutions. If a matrix <em>S</em> exists for which<em> S<sup>T</sup> A S = Lambda</em>, and <em>S<sup>T</sup> B S = I</em>, where <em>Lambda</em> is a diagonal matrix and <em>I</em> is the <em>n × n</em> identity, then <em>A</em> and <em>B</em> are said to be <em>diagonalized simultaneously</em>, in which case the diagonal entries of <em>Lambda</em> are the generalized eigenvalues for <em>A</em> and <em>B</em>. Such a matrix <em>S</em> exists if <em>A</em> is symmetric and <em>B</em> is positive definite. (Our definition of positive definite includes symmetry.)</p><img src="/view.aspx?si=128444/thumb.jpg" alt="Classroom Tips and Techniques: Simultaneous Diagonalization and the Generalized Eigenvalue Problem" align="left"/><p>This article explores the connections between the generalized eigenvalue problem and the problem of simultaneously diagonalizing a pair of <em>n × n</em> matrices.</p>
<p>Given the <em>n × n</em> matrices <em>A</em> and <em>B</em>, the <em>generalized eigenvalue problem</em> seeks the eigenpairs <em>(lambda<sub>k</sub>, x<sub>k</sub>)</em>, solutions of the equation <em>Ax = lambda Bx</em>, or <em>(A - lambda B) x = 0</em>. If <em>B</em> is nonsingular, the eigenpairs of <em>B<sup>-1</sup> A</em> are solutions. If a matrix <em>S</em> exists for which<em> S<sup>T</sup> A S = Lambda</em>, and <em>S<sup>T</sup> B S = I</em>, where <em>Lambda</em> is a diagonal matrix and <em>I</em> is the <em>n × n</em> identity, then <em>A</em> and <em>B</em> are said to be <em>diagonalized simultaneously</em>, in which case the diagonal entries of <em>Lambda</em> are the generalized eigenvalues for <em>A</em> and <em>B</em>. Such a matrix <em>S</em> exists if <em>A</em> is symmetric and <em>B</em> is positive definite. (Our definition of positive definite includes symmetry.)</p>128444Tue, 06 Dec 2011 05:00:00 ZDr. Robert LopezDr. Robert LopezShock Response Spectrum
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<p>This worksheet calculates the shock response spectrum based on some input data.</p><img src="/view.aspx?si=125009/SRS.jpg" alt="Shock Response Spectrum" align="left"/><p>This worksheet calculates the shock response spectrum based on some input data.</p>125009Mon, 22 Aug 2011 04:00:00 ZSurak PereraSurak PereraSignal Processing in Maple
http://www.maplesoft.com/applications/view.aspx?SID=102646&ref=Feed
Consider the problem of evaluating the impact of a structure against a hard surface. The resulting acceleration will typically consist of the actual physical transient acceleration signal plus high frequency sensor resonance. Below we define a few simple analytical functions to model these responses. The effect of adjusting the sampling rate will be explored.<img src="/view.aspx?si=102646/thumb.jpg" alt="Signal Processing in Maple" align="left"/>Consider the problem of evaluating the impact of a structure against a hard surface. The resulting acceleration will typically consist of the actual physical transient acceleration signal plus high frequency sensor resonance. Below we define a few simple analytical functions to model these responses. The effect of adjusting the sampling rate will be explored.102646Fri, 18 Mar 2011 04:00:00 ZMaplesoftMaplesoft