Numerical control

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You Never Thought You Had to Think to Count It was after taking the 2nd MOEMS (Math Olympiad Elementary and Middle School) that I heard this phrase from my school’s math coach. We had sat and taken this test for 26 minutes, and then afterwards ALWAYS talked about the problems. It came up when looking at a problem that went somewhat like this: ‘Each student in an art class is given 48 cubes that measure 1cm x 1cm x 1cm. No students make the same design. What is the largest possible amount of students

support system, and stiffness of the support required etc. This project has proven to very beneficial to me as I came to know about the power of Final Element Analysis because of use of a powerful 2D finitef element software called RS2 (Phase2) for numerical analysis. During my Undergraduate studies, as a part of the course, I also interned at Upper Tamakoshi Hydro-Electric Project. This internship actually boosted my desire to choose my career path to Structural Engineering when I studied the plans

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Solution of Algebraic & Transcendental Equation Introduction When mathematically modeling real life situations we often come across equations in the form of f(x)=0. These equations can either be in the form of algebraic or transcendental equations. In certain cases, these equations may prove to be difficult to solve, as the equation may not have an exact answer. A problem of great importance in science and engineering is that of determining the roots/zeros of an equation of the form

In numerical analysis, explicit and implicit approaches are used to obtain numerical approximations of time dependent ordinary and partial differential equations. Fractional order differential equations are used widely for finance market analysis. Implicit solution methods require more computational efforts and are complex to program. In order to overcome these difficulties, explicit method for fractional order differential equation has been introduced which is one of the most recently developed

SpMV is the significant importance of the solution of sparse linear systems which involved on many numerical methods such as finite difference method, finite element method, and other engineering and scientific problems. The widespread importance of sparse matrix computation has resulted in significant research efforts poured into implementations based

\subsection{NIPG DGFEM Superconvergence 2011} Now that the continuous standard Galerkin solution over a quasi-uniform mesh may oscillate as $\epsilon \to 0$. An alternative tool will be a discontinuous Galerkin (DG) method where the oscillation can be avoided provided that an appropriate mesh refinement is applied, to capture the boundary layer behavior. The origins of the DG methods can be traced back to the seventies where they had been proposed as variational methods for numerically solving initial-value

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From Fig.2, it shows that the inner surface temperature against time and tile thickness. On the right hand side, it is shown that the Forward and the Dufort-Frankel method are very unstable. Both methods had an infinite inner surface temperature at start, which is not ideal. For Backward and Crank Nicolson methods, both of them had a smooth curve and did not have much fluctuation. On the left hand side, it shows the temperature at the inner surface against time. Forward and Dufort-Frankel deviated