Lecture

Kinematics: Deformation and Expansion

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In course

ME-331: Solid mechanics III

Fundamental understanding and analysis of the mechanical behavior of engineering materials and their use in mechanical design based on the continuum mechanics of solids. ...

Description

This lecture covers the concepts of kinematics related to deformation and expansion, focusing on the radial expansion of a sphere and linear expansion. The instructor explains the principles behind the deformation of circular arcs and the changes in thickness and centerline length. The lecture also delves into the torsion of a cylinder and the rotation by an angle around different axes. The content includes the mapping of vectors, radial displacement, and the gradient operator. The examples provided illustrate the application of these concepts in various scenarios.

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Instructors (3)

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.

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.

Official source

Related concepts (32)

Type system

In computer programming, a type system is a logical system comprising a set of rules that assigns a property called a type (for example, integer, floating point, string) to every "term" (a word, phrase, or other set of symbols). Usually the terms are various constructs of a computer program, such as variables, expressions, functions, or modules. A type system dictates the operations that can be performed on a term. For variables, the type system determines the allowed values of that term.

Type theory

In mathematics, logic, and computer science, a type theory is the formal presentation of a specific type system, and in general, type theory is the academic study of type systems. Some type theories serve as alternatives to set theory as a foundation of mathematics. Two influential type theories that were proposed as foundations are Alonzo Church's typed λ-calculus and Per Martin-Löf's intuitionistic type theory. Most computerized proof-writing systems use a type theory for their foundation, a common one is Thierry Coquand's Calculus of Inductive Constructions.

Type safety

In computer science, type safety and type soundness are the extent to which a programming language discourages or prevents type errors. Type safety is sometimes alternatively considered to be a property of facilities of a computer language; that is, some facilities are type-safe and their usage will not result in type errors, while other facilities in the same language may be type-unsafe and a program using them may encounter type errors.

Type inference

Type inference refers to the automatic detection of the type of an expression in a formal language. These include programming languages and mathematical type systems, but also natural languages in some branches of computer science and linguistics. Types in a most general view can be associated to a designated use suggesting and restricting the activities possible for an object of that type. Many nouns in language specify such uses. For instance, the word leash indicates a different use than the word line.

Data type

In computer science and computer programming, a data type (or simply type) is a collection or grouping of data values, usually specified by a set of possible values, a set of allowed operations on these values, and/or a representation of these values as machine types. A data type specification in a program constrains the possible values that an expression, such as a variable or a function call, might take. On literal data, it tells the compiler or interpreter how the programmer intends to use the data.

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