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1/30/2016 http://numericalmethods.eng.usf.edu 1 Elliptic Partial Differential Equations – Lieberman Method – Part 1 of 2 Elliptic Partial Differential Equations – Lieberman Method – Part 1 of 2 http://numericalmethods.eng.usf.edu Transforming Numerical Methods Education for STEM Undergraduates
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For more details on this topic Go to http://numericalmethods.eng.usf.eduhttp://numericalmethods.eng.usf.edu Click on Keyword Click on Elliptic Partial Differential Equations
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You are free to Share – to copy, distribute, display and perform the work to Remix – to make derivative works
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Under the following conditions Attribution — You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). Noncommercial — You may not use this work for commercial purposes. Share Alike — If you alter, transform, or build upon this work, you may distribute the resulting work only under the same or similar license to this one.
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Physical Example of an Elliptic PDE
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Discretizing the Elliptic PDE
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The Gauss-Seidel Method Recall the discretized equation This can be rewritten as For the Gauss-Seidel Method, this equation is solved iteratively for all interior nodes until a pre-specified tolerance is met.
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The Lieberman Method Recall the equation used in the Gauss- Siedel Method If the Guass-Siedel Method is guaranteed to converge, we can accelerate the process by using over- relaxation. In this case,
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THE END http://numericalmethods.eng.usf.edu
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This instructional power point brought to you by Numerical Methods for STEM undergraduate http://numericalmethods.eng.usf.edu Committed to bringing numerical methods to the undergraduate Acknowledgement
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For instructional videos on other topics, go to http://numericalmethods.eng.usf.edu/videos/ This material is based upon work supported by the National Science Foundation under Grant # 0717624. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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The End - Really
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1/30/2016 http://numericalmethods.eng.usf.edu 13 Elliptic Partial Differential Equations – Lieberman Method – Part 2 of 2 Elliptic Partial Differential Equations – Lieberman Method – Part 2 of 2 http://numericalmethods.eng.usf.edu Transforming Numerical Methods Education for STEM Undergraduates
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For more details on this topic Go to http://numericalmethods.eng.usf.eduhttp://numericalmethods.eng.usf.edu Click on Keyword Click on Elliptic Partial Differential Equations
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You are free to Share – to copy, distribute, display and perform the work to Remix – to make derivative works
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Under the following conditions Attribution — You must attribute the work in the manner specified by the author or licensor (but not in any way that suggests that they endorse you or your use of the work). Noncommercial — You may not use this work for commercial purposes. Share Alike — If you alter, transform, or build upon this work, you may distribute the resulting work only under the same or similar license to this one.
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Example: Lieberman Method Consider a plate that is subjected to the boundary conditions shown below. Find the temperature at the interior nodes using a square grid with a length of. Use a weighting factor of 1.4 in the Lieberman method. Assume the initial temperature guess at all interior nodes to be 0 o C.
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Example: Lieberman Method We can discretize the plate by taking
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Example: Lieberman Method We can also develop equations for the boundary conditions to define the temperature of the exterior nodes.
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Example: Lieberman Method Solve for the temperature at each interior node using the rewritten discretized Laplace equation from the Gauss-Siedel method. Apply the over relaxation equation using temperatures from previous iteration. i=1 and j=1 Iteration #1
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Example: Lieberman Method Iteration #1 i=1 and j=2
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Example: Lieberman Method After the first iteration the temperatures are as follows. These will be used as the nodal temperatures during the second iteration.
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Example: Lieberman Method i=1 and j=1 Iteration #2
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Example: Lieberman Method Iteration #2 i=1 and j=2
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Example: Lieberman Method The figures below show the temperature distribution and absolute relative error distribution in the plate after two iterations: Temperature Distribution Absolute Relative Approximate Error Distribution
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Example: Lieberman Method Node Temperature Distribution in the Plate (°C) Number of Iterations 129 43.750052.2813 73.7832 41.562551.313392.9758 40.796987.0125119.9378 145.5289160.9353173.3937 32.812554.178977.5449 26.031357.9731103.3285 23.3898122.0937138.3236 164.1216215.6582198.5498 63.984469.145882.9805 66.505576.1516104.3815 66.4634155.0472131.2525 220.7047181.4650182.4230
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THE END http://numericalmethods.eng.usf.edu
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This instructional power point brought to you by Numerical Methods for STEM undergraduate http://numericalmethods.eng.usf.edu Committed to bringing numerical methods to the undergraduate Acknowledgement
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For instructional videos on other topics, go to http://numericalmethods.eng.usf.edu/videos/ This material is based upon work supported by the National Science Foundation under Grant # 0717624. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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The End - Really
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