Pavel Sumets
Computational Framework for the Finite Element Method in MATLAB® and Python (eBook, PDF)
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Pavel Sumets
Computational Framework for the Finite Element Method in MATLAB® and Python (eBook, PDF)
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This book aims to provide a programming framework for coding linear FEM using matrix-based MATLAB language and Python scripting language. It describes FEM algorithm implementation in the most generic formulation so that it is possible to apply this algorithm to as many application problems as possible.
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- Größe: 6.9MB
This book aims to provide a programming framework for coding linear FEM using matrix-based MATLAB language and Python scripting language. It describes FEM algorithm implementation in the most generic formulation so that it is possible to apply this algorithm to as many application problems as possible.
Dieser Download kann aus rechtlichen Gründen nur mit Rechnungsadresse in A, B, BG, CY, CZ, D, DK, EW, E, FIN, F, GR, HR, H, IRL, I, LT, L, LR, M, NL, PL, P, R, S, SLO, SK ausgeliefert werden.
Produktdetails
- Produktdetails
- Verlag: Taylor & Francis
- Seitenzahl: 182
- Erscheinungstermin: 11. August 2022
- Englisch
- ISBN-13: 9781000609998
- Artikelnr.: 64314078
- Verlag: Taylor & Francis
- Seitenzahl: 182
- Erscheinungstermin: 11. August 2022
- Englisch
- ISBN-13: 9781000609998
- Artikelnr.: 64314078
- Herstellerkennzeichnung Die Herstellerinformationen sind derzeit nicht verfügbar.
Pavel Sumets is a research and development software engineer from New Zealand whose main interest and expertise are biomechanics, numerical methods, and scientific programming.
He received his master's degree in applied mathematics and worked as a university lecturer teaching courses on mathematical modelling, numerical methods and programming. In 2017, he graduated from the University of Auckland with a PhD degree in engineering science. His PhD research revolved around building and solving mathematical models for multiphasic flow using boundary and finite element methods. He has published several scientific works on mathematical modelling biomechanical systems.
Currently, Pavel is working for a software development company on developing computational models in the area of computer-human interactions. His work involves creating software for digital character animation and implementing character physics simulator. Pavel holds a patent in the technology of processing three dimensional shapes.
Having background in applied mathematics along with both academic and industrial experience allows him to approach research task with solution implementation suitable for practical utilization. Pavel is passionate about magic tricks and in his spare time does magic shows.
He received his master's degree in applied mathematics and worked as a university lecturer teaching courses on mathematical modelling, numerical methods and programming. In 2017, he graduated from the University of Auckland with a PhD degree in engineering science. His PhD research revolved around building and solving mathematical models for multiphasic flow using boundary and finite element methods. He has published several scientific works on mathematical modelling biomechanical systems.
Currently, Pavel is working for a software development company on developing computational models in the area of computer-human interactions. His work involves creating software for digital character animation and implementing character physics simulator. Pavel holds a patent in the technology of processing three dimensional shapes.
Having background in applied mathematics along with both academic and industrial experience allows him to approach research task with solution implementation suitable for practical utilization. Pavel is passionate about magic tricks and in his spare time does magic shows.
1. Finite Element Method for the One-Dimensional Boundary Value Problem. 1.1 Formulation of the Problem. 1.2 Integral Equation. 1.3 Lagrange Interpolating Polynomials. 1.4 Illustrative Problem. 1.5 Algorithms of The Finite Element Method. 1.6. Quadrature Rules. 1.7. Defining Parameters of the FEM. 2. Programming One-Dimensional Finite Element Method. 2.1 Sparse Matrices in MATLAB. 2.2 Input Data Structures. 2.3 Coding Quadrature Rules. 2.4 Interpolating and Differentiating Matrices. 2.5. Calculating and Assembling Fem Matrices. 2.6 Python Implementation. 3. Finite Element Method for the Two-Dimensional Boundary Value Problem. 3.1 Model Problem. 3.2 Finite Elements Definition. 3.3. Triangulation Examples. 3.4. Linear System of the FEM. 3.5 Stiffness Matrix and Forcing Vector. 3.6. Algorithm of Solving Problem. 4. Building Two-Dimensional Meshes. 4.1. Defining Geometry. 4.2. Representing Meshes in Matrix Form for Linear Interpolation Functions. 4.3. Complementary Mesh. 4.4. Building Meshes in MATLAB. 4.5. Building Meshes in Python. 5. Programming Two-Dimensional Finite Element Method. 5.1. Assembling Global Stiffness Matrix. 5.2. Assembling Global Forcing Vector. 5.3. Calculating Local Stiffness Matrices. 5.4. Calculating Equation Coefficients. 5.5. Calculating Global Matrices. 5.6. Calculating Boundary Conditions. 5.7. Assembling Boundary Conditions 5.8. Solving Example Problem. 6. Nonlinear Basis Functions. 6.1. Linear Triangular Elements. 6.2. Curvilinear Triangular Elements. 6.3. Stiffness Matrix with Quadratic Basis. Conclusion Appendix A. Variational Formulation of a BVP. Appendix B. Discussion of Global Interpolation. Appendix C. Interpolatory Quadrature Formulas. Appendix D. Quadrature Rules and Orthogonal Polynomials. Appendix E. Computational Framework in Python.
1. Finite Element Method for the One-Dimensional Boundary Value Problem.
1.1 Formulation of the Problem. 1.2 Integral Equation. 1.3 Lagrange
Interpolating Polynomials. 1.4 Illustrative Problem. 1.5 Algorithms of The
Finite Element Method. 1.6. Quadrature Rules. 1.7. Defining Parameters of
the FEM. 2. Programming One-Dimensional Finite Element Method. 2.1 Sparse
Matrices in MATLAB. 2.2 Input Data Structures. 2.3 Coding Quadrature Rules.
2.4 Interpolating and Differentiating Matrices. 2.5. Calculating and
Assembling Fem Matrices. 2.6 Python Implementation. 3. Finite Element
Method for the Two-Dimensional Boundary Value Problem. 3.1 Model Problem.
3.2 Finite Elements Definition. 3.3. Triangulation Examples. 3.4. Linear
System of the FEM. 3.5 Stiffness Matrix and Forcing Vector. 3.6. Algorithm
of Solving Problem. 4. Building Two-Dimensional Meshes. 4.1. Defining
Geometry. 4.2. Representing Meshes in Matrix Form for Linear Interpolation
Functions. 4.3. Complementary Mesh. 4.4. Building Meshes in MATLAB. 4.5.
Building Meshes in Python. 5. Programming Two-Dimensional Finite Element
Method. 5.1. Assembling Global Stiffness Matrix. 5.2. Assembling Global
Forcing Vector. 5.3. Calculating Local Stiffness Matrices. 5.4. Calculating
Equation Coefficients. 5.5. Calculating Global Matrices. 5.6. Calculating
Boundary Conditions. 5.7. Assembling Boundary Conditions 5.8. Solving
Example Problem. 6. Nonlinear Basis Functions. 6.1. Linear Triangular
Elements. 6.2. Curvilinear Triangular Elements. 6.3. Stiffness Matrix with
Quadratic Basis. Conclusion Appendix A. Variational Formulation of a BVP.
Appendix B. Discussion of Global Interpolation. Appendix C. Interpolatory
Quadrature Formulas. Appendix D. Quadrature Rules and Orthogonal
Polynomials. Appendix E. Computational Framework in Python.
1.1 Formulation of the Problem. 1.2 Integral Equation. 1.3 Lagrange
Interpolating Polynomials. 1.4 Illustrative Problem. 1.5 Algorithms of The
Finite Element Method. 1.6. Quadrature Rules. 1.7. Defining Parameters of
the FEM. 2. Programming One-Dimensional Finite Element Method. 2.1 Sparse
Matrices in MATLAB. 2.2 Input Data Structures. 2.3 Coding Quadrature Rules.
2.4 Interpolating and Differentiating Matrices. 2.5. Calculating and
Assembling Fem Matrices. 2.6 Python Implementation. 3. Finite Element
Method for the Two-Dimensional Boundary Value Problem. 3.1 Model Problem.
3.2 Finite Elements Definition. 3.3. Triangulation Examples. 3.4. Linear
System of the FEM. 3.5 Stiffness Matrix and Forcing Vector. 3.6. Algorithm
of Solving Problem. 4. Building Two-Dimensional Meshes. 4.1. Defining
Geometry. 4.2. Representing Meshes in Matrix Form for Linear Interpolation
Functions. 4.3. Complementary Mesh. 4.4. Building Meshes in MATLAB. 4.5.
Building Meshes in Python. 5. Programming Two-Dimensional Finite Element
Method. 5.1. Assembling Global Stiffness Matrix. 5.2. Assembling Global
Forcing Vector. 5.3. Calculating Local Stiffness Matrices. 5.4. Calculating
Equation Coefficients. 5.5. Calculating Global Matrices. 5.6. Calculating
Boundary Conditions. 5.7. Assembling Boundary Conditions 5.8. Solving
Example Problem. 6. Nonlinear Basis Functions. 6.1. Linear Triangular
Elements. 6.2. Curvilinear Triangular Elements. 6.3. Stiffness Matrix with
Quadratic Basis. Conclusion Appendix A. Variational Formulation of a BVP.
Appendix B. Discussion of Global Interpolation. Appendix C. Interpolatory
Quadrature Formulas. Appendix D. Quadrature Rules and Orthogonal
Polynomials. Appendix E. Computational Framework in Python.
1. Finite Element Method for the One-Dimensional Boundary Value Problem. 1.1 Formulation of the Problem. 1.2 Integral Equation. 1.3 Lagrange Interpolating Polynomials. 1.4 Illustrative Problem. 1.5 Algorithms of The Finite Element Method. 1.6. Quadrature Rules. 1.7. Defining Parameters of the FEM. 2. Programming One-Dimensional Finite Element Method. 2.1 Sparse Matrices in MATLAB. 2.2 Input Data Structures. 2.3 Coding Quadrature Rules. 2.4 Interpolating and Differentiating Matrices. 2.5. Calculating and Assembling Fem Matrices. 2.6 Python Implementation. 3. Finite Element Method for the Two-Dimensional Boundary Value Problem. 3.1 Model Problem. 3.2 Finite Elements Definition. 3.3. Triangulation Examples. 3.4. Linear System of the FEM. 3.5 Stiffness Matrix and Forcing Vector. 3.6. Algorithm of Solving Problem. 4. Building Two-Dimensional Meshes. 4.1. Defining Geometry. 4.2. Representing Meshes in Matrix Form for Linear Interpolation Functions. 4.3. Complementary Mesh. 4.4. Building Meshes in MATLAB. 4.5. Building Meshes in Python. 5. Programming Two-Dimensional Finite Element Method. 5.1. Assembling Global Stiffness Matrix. 5.2. Assembling Global Forcing Vector. 5.3. Calculating Local Stiffness Matrices. 5.4. Calculating Equation Coefficients. 5.5. Calculating Global Matrices. 5.6. Calculating Boundary Conditions. 5.7. Assembling Boundary Conditions 5.8. Solving Example Problem. 6. Nonlinear Basis Functions. 6.1. Linear Triangular Elements. 6.2. Curvilinear Triangular Elements. 6.3. Stiffness Matrix with Quadratic Basis. Conclusion Appendix A. Variational Formulation of a BVP. Appendix B. Discussion of Global Interpolation. Appendix C. Interpolatory Quadrature Formulas. Appendix D. Quadrature Rules and Orthogonal Polynomials. Appendix E. Computational Framework in Python.
1. Finite Element Method for the One-Dimensional Boundary Value Problem.
1.1 Formulation of the Problem. 1.2 Integral Equation. 1.3 Lagrange
Interpolating Polynomials. 1.4 Illustrative Problem. 1.5 Algorithms of The
Finite Element Method. 1.6. Quadrature Rules. 1.7. Defining Parameters of
the FEM. 2. Programming One-Dimensional Finite Element Method. 2.1 Sparse
Matrices in MATLAB. 2.2 Input Data Structures. 2.3 Coding Quadrature Rules.
2.4 Interpolating and Differentiating Matrices. 2.5. Calculating and
Assembling Fem Matrices. 2.6 Python Implementation. 3. Finite Element
Method for the Two-Dimensional Boundary Value Problem. 3.1 Model Problem.
3.2 Finite Elements Definition. 3.3. Triangulation Examples. 3.4. Linear
System of the FEM. 3.5 Stiffness Matrix and Forcing Vector. 3.6. Algorithm
of Solving Problem. 4. Building Two-Dimensional Meshes. 4.1. Defining
Geometry. 4.2. Representing Meshes in Matrix Form for Linear Interpolation
Functions. 4.3. Complementary Mesh. 4.4. Building Meshes in MATLAB. 4.5.
Building Meshes in Python. 5. Programming Two-Dimensional Finite Element
Method. 5.1. Assembling Global Stiffness Matrix. 5.2. Assembling Global
Forcing Vector. 5.3. Calculating Local Stiffness Matrices. 5.4. Calculating
Equation Coefficients. 5.5. Calculating Global Matrices. 5.6. Calculating
Boundary Conditions. 5.7. Assembling Boundary Conditions 5.8. Solving
Example Problem. 6. Nonlinear Basis Functions. 6.1. Linear Triangular
Elements. 6.2. Curvilinear Triangular Elements. 6.3. Stiffness Matrix with
Quadratic Basis. Conclusion Appendix A. Variational Formulation of a BVP.
Appendix B. Discussion of Global Interpolation. Appendix C. Interpolatory
Quadrature Formulas. Appendix D. Quadrature Rules and Orthogonal
Polynomials. Appendix E. Computational Framework in Python.
1.1 Formulation of the Problem. 1.2 Integral Equation. 1.3 Lagrange
Interpolating Polynomials. 1.4 Illustrative Problem. 1.5 Algorithms of The
Finite Element Method. 1.6. Quadrature Rules. 1.7. Defining Parameters of
the FEM. 2. Programming One-Dimensional Finite Element Method. 2.1 Sparse
Matrices in MATLAB. 2.2 Input Data Structures. 2.3 Coding Quadrature Rules.
2.4 Interpolating and Differentiating Matrices. 2.5. Calculating and
Assembling Fem Matrices. 2.6 Python Implementation. 3. Finite Element
Method for the Two-Dimensional Boundary Value Problem. 3.1 Model Problem.
3.2 Finite Elements Definition. 3.3. Triangulation Examples. 3.4. Linear
System of the FEM. 3.5 Stiffness Matrix and Forcing Vector. 3.6. Algorithm
of Solving Problem. 4. Building Two-Dimensional Meshes. 4.1. Defining
Geometry. 4.2. Representing Meshes in Matrix Form for Linear Interpolation
Functions. 4.3. Complementary Mesh. 4.4. Building Meshes in MATLAB. 4.5.
Building Meshes in Python. 5. Programming Two-Dimensional Finite Element
Method. 5.1. Assembling Global Stiffness Matrix. 5.2. Assembling Global
Forcing Vector. 5.3. Calculating Local Stiffness Matrices. 5.4. Calculating
Equation Coefficients. 5.5. Calculating Global Matrices. 5.6. Calculating
Boundary Conditions. 5.7. Assembling Boundary Conditions 5.8. Solving
Example Problem. 6. Nonlinear Basis Functions. 6.1. Linear Triangular
Elements. 6.2. Curvilinear Triangular Elements. 6.3. Stiffness Matrix with
Quadratic Basis. Conclusion Appendix A. Variational Formulation of a BVP.
Appendix B. Discussion of Global Interpolation. Appendix C. Interpolatory
Quadrature Formulas. Appendix D. Quadrature Rules and Orthogonal
Polynomials. Appendix E. Computational Framework in Python.