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Лекции John B. Schneider - Numerical Solutions to EM Problems
Electromagnetic ?elds and waves, vector calculus, differential equations, distributed.
parameter systems (transmission lines, waveguides, and antennas), high-level programming.
language (e.g., FORTRAN, C, or C++). Familiarity with Matlab or Mathematica helpful but.
not essential.
Ensure students:
Understand why numerical methods are needed to solve realistic or practical problems in.
electromagnetics and why this need will increase.
Understand the inherent limits of numerical methods as well as the constraints placed on.
solutions due to current technology.
Can translate a textual or mathematical descriptions of a solution into a well-written com-.
puter program.
Can choose between the various numerical methods to use the right method for a particular.
Can effectively use computer tools, including hardware, and commercial and open-source.
software, that are typically employed to solve problems in electromagnetics.
Can effectively communicate their work via an oral and written project report (as well as on.
the homework assignments).
Understand the mathematical concepts upon which computational electromagnetics relies.
Topics (with approximate number of 75-minute lectures):
Review of electromagnetic theory. (1).
Constraints of numeric modeling (e.g., consequence of ?nite precision). (1).
Fundamentals of ?nite differences. (1).
Construction of leap-frog schemes for modeling wave propagation in one dimension. (1).
Hard and soft source. The Higdon absorbing boundary condition. (2).
Frequency-domain data from time-domain simulations. (2).
Generalization to two- and three-dimensional propagation. The Yee cube. (2).
Rendering of data. (1).
Total-?eld/scattered-?eld boundary. (2).
The FDTD dispersion relation and its rami?cations. (2).
Discrete scatterers and PEC boundaries. (1).
Penetrable dielectrics. (1).
Dispersive materials. (3).
The perfectly matched layer absorbing boundary condition. (3).
Modeling printed circuits. (3).
Antennas and near- to far-?eld transformations. (3).
Parallelization. (1).
Higher-order FDTD algorithm and the pseudospectral time-domain technique. (2).
Приведено множество алгоритмов, включая исходные коды программ.
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