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Lecture

2D Conduction: Method of Separation of Variables

In course

ME-341: Heat and mass transfer

This course covers fundamentals of heat transfer and applications to practical problems. Emphasis will be on developing a physical and analytical understanding of conductive, convective, and radiative heat transfer. ...

Description

This lecture covers the method of separation of variables for 2D conduction problems, including the heat diffusion equation, shape factor, and exercises on thermal circuits. It explains the limitations of the electrical analogy in layers with heat sources and the symmetry of temperature profiles in different geometries.

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Instructor

Giulia Tagliabue

Dr. Giulia Tagliabue is an Assistant Professor at the Institute of Mechanical Engineering (IGM). She obtained her B.S. and M.S degrees cum laude in Mechanical Engineering from the University of Udine in Italy. Concurrently she also obtained the diploma from the Scuola Normale Superiore of Udine. In 2015 she obtained her PhD in Mechanical Engineering from ETH Zurich with a thesis on nanophotonic design for light-to-heat and light-to-charge conversion devices. In 2015 Dr. Tagliabue was awarded the Early Mobility Fellowship from the Swiss National Science Foundation and moved to Caltech as a PostDoctoral fellow. In 2017, thanks to the award of an Advanced Mobility Fellowship, she prolonged her stay at Caltech. Here, in collaboration with the Joint Center for Artificial Photosynthesis (JCAP) she investigated coupled light, heat and charge transfer processes in nanophotonic structures and low-dimensional materials for photoelectrochemical and photovoltaic sustainable energy conversion.

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Related concepts (32)

Heat equation

In mathematics and physics, the heat equation is a certain partial differential equation. Solutions of the heat equation are sometimes known as caloric functions. The theory of the heat equation was first developed by Joseph Fourier in 1822 for the purpose of modeling how a quantity such as heat diffuses through a given region. As the prototypical parabolic partial differential equation, the heat equation is among the most widely studied topics in pure mathematics, and its analysis is regarded as fundamental to the broader field of partial differential equations.

Symmetry

Symmetry () in everyday language refers to a sense of harmonious and beautiful proportion and balance. In mathematics, the term has a more precise definition and is usually used to refer to an object that is invariant under some transformations, such as translation, reflection, rotation, or scaling. Although these two meanings of the word can sometimes be told apart, they are intricately related, and hence are discussed together in this article.

Symmetry group

In group theory, the symmetry group of a geometric object is the group of all transformations under which the object is invariant, endowed with the group operation of composition. Such a transformation is an invertible mapping of the ambient space which takes the object to itself, and which preserves all the relevant structure of the object. A frequent notation for the symmetry group of an object X is G = Sym(X). For an object in a metric space, its symmetries form a subgroup of the isometry group of the ambient space.

Rotational symmetry

Rotational symmetry, also known as radial symmetry in geometry, is the property a shape has when it looks the same after some rotation by a partial turn. An object's degree of rotational symmetry is the number of distinct orientations in which it looks exactly the same for each rotation. Certain geometric objects are partially symmetrical when rotated at certain angles such as squares rotated 90°, however the only geometric objects that are fully rotationally symmetric at any angle are spheres, circles and other spheroids.

Diffusion equation

The diffusion equation is a parabolic partial differential equation. In physics, it describes the macroscopic behavior of many micro-particles in Brownian motion, resulting from the random movements and collisions of the particles (see Fick's laws of diffusion). In mathematics, it is related to Markov processes, such as random walks, and applied in many other fields, such as materials science, information theory, and biophysics. The diffusion equation is a special case of the convection–diffusion equation, when bulk velocity is zero.

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