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Lecture

Vectors and Tensors

Description

This lecture introduces vectors as physical measures in 3 dimensions specifying magnitude and spatial direction, using Cartesian basis vectors and inner product definitions. It covers vector representation, unit vectors, vector products, and basis vector transformations.

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Instructors (3)

William Curtin

John Martin Kolinski

Dr. Kolinski studied Applied Mathematics (Sc.M.) and Applied Physics (Ph.D.) at Harvard University, completing a PhD under the supervision of L. Mahadevan and Shmuel Rubinstein on the role of air in droplet impact. John did his post-doc at the Hebrew University of Jerusalem in Israel supported by the Fulbright post-doctoral fellowship. At HUJI, he worked on interfacial instabilities in soft matter in the labs of Eran Sharon and Jay Fineberg. John continues his research into interfacial mechanics at EPFL in EMSI, his newly founded laboratory for the study of Engineering Mechanics of Soft Interfaces.

John Botsis

John (Ioannis) Botsis obtained his diplôme in civil engineering at the University of Patras, Greece in 1979. He continued his education at Case Institute of Technology in Cleveland Ohio/USA, where he received his MS and Ph.D. in 1984. After two years at the research center for national defense in Athens he was nominated assistant professor at the University of Illinois in Chicago, associate in 1991 and full professor in 1995. In 1996, he was nominated professor of solids and structural mechanics at the EPFL. At EPFL he teaches mechanics of structures and mechanics of continuous media´ at the bachelors level and Fracture mechanics at the masters and doctoral levels. His research covers the mechanics of solids and structures, fracture mechanics and micromechanics of polymers, metals and their composites as well as biomechanics. He is also actively involved in full-filed optical methods for surface strain measurements as well as internal strain measurements using fiber Bragg grating sensors, aimed at characterizing micromechanics of fracture, residual strains and strain distribution in composite laminates for structural monitoring. Funding for his research comes from the Swiss National Science Foundation, State Secretariat for Education and Research and Swiss industry. He retired on February 28, 2020.

Official source

Ontological neighbourhood

Mathematics

Algebra: Linear algebra

Analysis: Tensor analysis

Related concepts (32)

Euclidean vector

In mathematics, physics, and engineering, a Euclidean vector or simply a vector (sometimes called a geometric vector or spatial vector) is a geometric object that has magnitude (or length) and direction. Vectors can be added to other vectors according to vector algebra. A Euclidean vector is frequently represented by a directed line segment, or graphically as an arrow connecting an initial point A with a terminal point B, and denoted by . A vector is what is needed to "carry" the point A to the point B; the Latin word vector means "carrier".

Vector space

In mathematics and physics, a vector space (also called a linear space) is a set whose elements, often called vectors, may be added together and multiplied ("scaled") by numbers called scalars. Scalars are often real numbers, but can be complex numbers or, more generally, elements of any field. The operations of vector addition and scalar multiplication must satisfy certain requirements, called vector axioms. The terms real vector space and complex vector space are often used to specify the nature of the scalars: real coordinate space or complex coordinate space.

Cartesian coordinate system

In geometry, a Cartesian coordinate system (UKkɑːrˈtiːzjən, USkɑːrˈtiʒən) in a plane is a coordinate system that specifies each point uniquely by a pair of real numbers called coordinates, which are the signed distances to the point from two fixed perpendicular oriented lines, called coordinate lines, coordinate axes or just axes (plural of axis) of the system. The point where they meet is called the origin and has (0, 0) as coordinates.

Tensor product

In mathematics, the tensor product of two vector spaces V and W (over the same field) is a vector space to which is associated a bilinear map that maps a pair to an element of denoted An element of the form is called the tensor product of v and w. An element of is a tensor, and the tensor product of two vectors is sometimes called an elementary tensor or a decomposable tensor. The elementary tensors span in the sense that every element of is a sum of elementary tensors.

Unit vector

In mathematics, a unit vector in a normed vector space is a vector (often a spatial vector) of length 1. A unit vector is often denoted by a lowercase letter with a circumflex, or "hat", as in (pronounced "v-hat"). The term direction vector, commonly denoted as d, is used to describe a unit vector being used to represent spatial direction and relative direction. 2D spatial directions are numerically equivalent to points on the unit circle and spatial directions in 3D are equivalent to a point on the unit sphere.

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