Mathematics for Mechanics
Code  Completion  Credits  Range  Language 

2013054  Z  4  3P+1C  Czech 
 Lecturer:
 Petr Sváček (guarantor)
 Tutor:
 Petr Sváček (guarantor)
 Supervisor:
 Department of Technical Mathematics
 Synopsis:

Summary: Tensor calculus. Introduction to functional analysis. Calculus of variations.
• Orthogonal transformation of coordinate systems.
• Afinne orthogonal tensors and tensor operations.
• Tensor as linear operator and bilinear form.
• Metrics and metric spaces. Convergence. Completness.
• Linear normed space. Banach space.
• Linear space with scalar product (unitary space). Hilbert space.
• Contractive operators and Banach fixed point theorem.
• Function spaces in examples.
• Operators and functionals. Linear, continuous and bounded operator/functional.
• Derivative of a functional in the given direction. Gateaux differential and derivative.
• Necessary and sufficient conditions for extremes of a functional.
• Convex set and convex functional. Minimum of convex functional.
• Extremes of functional of different types. Euler equation. Necessary and sufficient conditions for extrema.
• Discrete methods for approximation of the minima of an functional. Ritz method.
 Requirements:
 Syllabus of lectures:

Summary: Tensor calculus. Introduction to functional analysis. Calculus of variations.
• Orthogonal transformation of coordinate systems.
• Afinne orthogonal tensors and tensor operations.
• Tensor as linear operator and bilinear form.
• Metrics and metric spaces. Convergence. Completness.
• Linear normed space. Banach space.
• Linear space with scalar product (unitary space). Hilbert space.
• Contractive operators and Banach fixed point theorem.
• Function spaces in examples.
• Operators and functionals. Linear, continuous and bounded operator/functional.
• Derivative of a functional in the given direction. Gateaux differential and derivative.
• Necessary and sufficient conditions for extremes of a functional.
• Convex set and convex functional. Minimum of convex functional.
• Extremes of functional of different types. Euler equation. Necessary and sufficient conditions for extrema.
• Discrete methods for approximation of the minima of an functional. Ritz method.
 Syllabus of tutorials:

Summary: Tensor calculus. Introduction to functional analysis. Calculus of variations.
• Orthogonal transformation of coordinate systems.
• Afinne orthogonal tensors and tensor operations.
• Tensor as linear operator and bilinear form.
• Metrics and metric spaces. Convergence. Completness.
• Linear normed space. Banach space.
• Linear space with scalar product (unitary space). Hilbert space.
• Contractive operators and Banach fixed point theorem.
• Function spaces in examples.
• Operators and functionals. Linear, continuous and bounded operator/functional.
• Derivative of a functional in the given direction. Gateaux differential and derivative.
• Necessary and sufficient conditions for extremes of a functional.
• Convex set and convex functional. Minimum of convex functional.
• Extremes of functional of different types. Euler equation. Necessary and sufficient conditions for extrema.
• Discrete methods for approximation of the minima of an functional. Ritz method.
 Study Objective:

Summary: Tensor calculus. Introduction to functional analysis. Calculus of variations.
• Orthogonal transformation of coordinate systems.
• Afinne orthogonal tensors and tensor operations.
• Tensor as linear operator and bilinear form.
• Metrics and metric spaces. Convergence. Completness.
• Linear normed space. Banach space.
• Linear space with scalar product (unitary space). Hilbert space.
• Contractive operators and Banach fixed point theorem.
• Function spaces in examples.
• Operators and functionals. Linear, continuous and bounded operator/functional.
• Derivative of a functional in the given direction. Gateaux differential and derivative.
• Necessary and sufficient conditions for extremes of a functional.
• Convex set and convex functional. Minimum of convex functional.
• Extremes of functional of different types. Euler equation. Necessary and sufficient conditions for extrema.
• Discrete methods for approximation of the minima of an functional. Ritz method.
 Study materials:
 Note:
 Further information:
 No timetable has been prepared for this course
 The course is a part of the following study plans:

 13 136 NSTI MMT 2012 základ (compulsory course in the program)
 14 141 NSTI AME 2012 základ (compulsory course in the program)
 15 141 NSTI MCH 2012 základ (compulsory course in the program)
 16 151 NSTI BLP 2012 základ (compulsory course in the program)