Atilla Ozgur Cakmak, PhD

Slides:



Advertisements
Similar presentations
Courant and all that Consistency, Convergence Stability Numerical Dispersion Computational grids and numerical anisotropy The goal of this lecture is to.
Advertisements

P. Venkataraman Mechanical Engineering P. Venkataraman Rochester Institute of Technology DETC2013 – 12269: Continuous Solution for Boundary Value Problems.
2010 SKA Africa Bursary Conference Chalmers University of Technology Jian Yang, Associate Professor Chalmers University of Technology Sweden.
Modelling techniques and applications Qing Tan EPFL-STI-IMT-OPTLab
5/4/2015rew Accuracy increase in FDTD using two sets of staggered grids E. Shcherbakov May 9, 2006.
Finite Difference Time Domain Method (FDTD)
Consortium for Metrology of Semiconductor Nanodefects Mechanical Engineering An Introduction to Computational Electromagnetics using FDTD R. E. Diaz.
III Solution of pde’s using variational principles
Pseudospectral Methods
Implementation of 2D FDTD
Ch 8.1 Numerical Methods: The Euler or Tangent Line Method
Tutorial 5: Numerical methods - buildings Q1. Identify three principal differences between a response function method and a numerical method when both.
Finite Differences Finite Difference Approximations  Simple geophysical partial differential equations  Finite differences - definitions  Finite-difference.
Introduction to Numerical Methods for ODEs and PDEs Methods of Approximation Lecture 3: finite differences Lecture 4: finite elements.
Lecture 6.
Simulating Electron Dynamics in 1D
Grating reconstruction forward modeling part Mark van Kraaij CASA PhD-day Tuesday 13 November 2007.
Finite Element Method.
Modeling Plasmonic Effects in the Nanoscale Brendan McNamara, Andrei Nemilentsau and Slava V. Rotkin Department of Physics, Lehigh University Methodology.
EEE 431 Computational methods in Electrodynamics Lecture 1 By Rasime Uyguroglu.
Coupling Heterogeneous Models with Non-matching Meshes by Localized Lagrange Multipliers Modeling for Matching Meshes with Existing Staggered Methods and.
Antenna Modeling Using FDTD SURE Program 2004 Clemson University Michael Frye Faculty Advisor: Dr. Anthony Martin.
1 EEE 431 Computational Methods in Electrodynamics Lecture 4 By Dr. Rasime Uyguroglu
1 EEE 431 Computational Methods in Electrodynamics Lecture 9 By Dr. Rasime Uyguroglu
Periodic Boundary Conditions in Comsol
Acoustic diffraction by an Oscillating strip. This problem is basically solved by a technique called Wiener Hopf technique.
HOT PLATE CONDUCTION NUMERICAL SOLVER AND VISUALIZER Kurt Hinkle and Ivan Yorgason.
Introduction to CST MWS
EMLAB 1 3D Update Equations with Perfectly Matched Layers.
Lai-Ching Ma & Raj Mittra Electromagnetic Communication Laboratory
1 EEE 431 Computational Methods in Electrodynamics Lecture 8 By Dr. Rasime Uyguroglu
Discretization for PDEs Chunfang Chen,Danny Thorne Adam Zornes, Deng Li CS 521 Feb., 9,2006.
Dipole Driving Point Impedance Comparison  Dipole antenna modeled: length = 2m, radius = 0.005m  Frequency range of interest: 25MHz=500MHz  Comparison.
Mengyu Wang1, Christian Engström1,2,
Partial Derivatives Example: Find If solution: Partial Derivatives Example: Find If solution: gradient grad(u) = gradient.
1 EEE 431 Computational Methods in Electrodynamics Lecture 7 By Dr. Rasime Uyguroglu
Predicting the behaviour of a finite phased array from an infinite one Jacki van der Merwe MScEng University of Stellenbosch.
ECE 576 – Power System Dynamics and Stability Prof. Tom Overbye Dept. of Electrical and Computer Engineering University of Illinois at Urbana-Champaign.
Formulation of 2D‐FDTD without a PML.
2003 SURE Program Basic Applications of Integral Equations in Electromagnetics Nathaniel Burt Kansas State University Advisor: Professor Chalmers M. Butler.
In this work, we propose a novel local mesh refinement algorithm based on the use of transformation optics. The new algorithm is an alternative way to.
UT-BATTELLE New method for modeling acoustic waves in plates A powerful boundary element method is developed for plate geometry The new method achieves.
1 EEE 431 Computational Methods in Electrodynamics Lecture 13 By Dr. Rasime Uyguroglu
FDTD Simulation of Diffraction Grating Displacement Noise 1 Daniel Brown University of Birmingham AEI, Hanover - 14/12/2010.
Agenda for today Today we will use Lumerical FDTD to simulate the scattering of light from a ‘pit’ used to encode data on a DVD. The size of the pit will.
Fang Liu and Arthur Weglein Houston, Texas May 12th, 2006
Agenda for today Today we will do another tutorial example together to continue introduction to Lumerical FDTD software. Task #1: Tune the resonance frequency.
EEE 431 Computational Methods in Electrodynamics
Lecture 4: Numerical Stability
FDTD 1D-MAP Plane Wave TFSF Simulation for Lossy and Stratified Media
FDTD Modeling of FID Signal in Chirped-Pulse Millimeter Wave Spectroscopy Alexander Heifetz1, Sasan Bakhtiari1, Hual-Teh Chien1, Stephen Gray1, Kirill.
ELEC 401 MICROWAVE ELECTRONICS Lecture 3
ECE 576 – Power System Dynamics and Stability
THE METHOD OF LINES ANALYSIS OF ASYMMETRIC OPTICAL WAVEGUIDES Ary Syahriar.
Prof: Ming Wu GSI: Kevin Han Discussion 1/17/18
Agenda for today Today we will do another tutorial example to continue introduction to Lumerical FDTD software. Task #1: Tune the resonance frequency of.
Convergence in Computational Science
ELEC 401 MICROWAVE ELECTRONICS Lecture 3
Prof: Ming Wu GSI: Kevin Han Discussion 1/17/18
Chapter 23.
Analytical Tools in ME Course Objectives
Accuracy of the Finite Element Method for Directivity of Horn Antennas
EE 534 Numerical Methods in Electromagnetics
PHYS 408 Applied Optics (Lecture 18)
Diyu Yang Mentor: Xu Chen Advisor: José E. Schutt-Ainé Abstract
The Method of Moments Lf = g where L is a linear operator
Akram Bitar and Larry Manevitz Department of Computer Science
Atilla Ozgur Cakmak, PhD
Atilla Ozgur Cakmak, PhD
Atilla Ozgur Cakmak, PhD
Presentation transcript:

Atilla Ozgur Cakmak, PhD Nanophotonics Atilla Ozgur Cakmak, PhD

Lecture 23: An Exemplary Modeling Method-Introduction to FDTD Unit 3 Lecture 23: An Exemplary Modeling Method-Introduction to FDTD

Outline Introduction to Modeling in EM Finite Difference Approximation Finite Difference Time Domain Absorbing Boundary Stability and Discretization Conclusion 1-D FDTD Problem

A couple of words… This lecture aims to give the reader a feeling about the numerical solutions like we have employed using HFSS. Many of the problems in electromagnetics (EM) will not have exact analytical expressions. A lot of numerical methods are developed to handle such problems. Finite Difference Time Domain is only of those. It is heavily employed in the field of nanophotonics, though in order to model the nanostructures’ responses to light. Suggested readings: Computational Electrodynamics: The Finite-Difference Time- Domain Method, 3rd Edition is a great book in the field by Allen Taflove. However, it is very much beyond the scope of this discussion. A quick review is suggested if possible rather than a detailed analysis.

Introduction to Modeling in EM Exact solutions Separation of variables Series expansion Numerical Methods Finite Difference Time Domain Finite Element Method (eg. HFSS) Method of Moments Transmission line matrix method Only certain shapes will allow exact solutions like spheres, discs, wedges, cylinders. EM (electromagnetic) problems are classified to be differential, integral and integrodifferential. We will only touch finite difference time domain in 1-D just as an introduction.

Finite Difference Approximation

Finite Difference Time Domain

Finite Difference Time Domain

Finite Difference Time Domain z Step 1: Model the leapfrog scheme

Finite Difference Time Domain z Step 2: Initialize the fields, such that for t<0 both E and H are zero

Finite Difference Time Domain z Step 3: Define the boundaries such that Ex(-1/2,t)=f1(t) and Ex(5/2,t)=f2(t)

Finite Difference Time Domain z Step 4: Run the exemplary leap form solely storing the previous time steps. Do not store more!

Absorbing Boundary How should we terminate the boundaries to minimize the reflection back into the simulation domain? Special care must be given to minimize such artificial reflections such that the simulation domain will act as if the waves are continuing to progress into free space. Here, we will discuss 1-D Absorbing Boundary Conditions (ABC)

Absorbing Boundary

Absorbing Boundary Backward Waves Forward Waves t Black arrows show ABC … Initialization z

Absorbing Boundary (problem) Discretize for the backward waves at z=-L and attain a formula similar to the forward waves.

Absorbing Boundary (solution) Discretize for the backward waves at z=-L and attain a formula similar to the forward waves.

Stability and Discretization

Stability and Discretization

Stability and Discretization As it can be seen, people would want to work with a better mesh (smaller ∆z) and larger p value. But large p value makes FDTD unstable! Plane wave in free space

Conclusions So, we have discussed the stability and dispersion errors due to discretization. We are ready to apply our knowledge to a simple 1-D case with ABC. But are we done with FDTD? Far from it. There are 2-D and 3-D adaptations that we never touched. The main essence of this lecture has been to give a feeling of how the numerical tools are working and how multi purpose solvers are working for different geometries. There are also Perfectly Matched Layers (PMLs) employed after mid-90s which work very well with different problems while introducing minimum errors (reflections) back into the simulation domain. For a radiation problem that I had solved before, the figure below shows the enhancement coming with PMLs for 2-D problems compared to ABCs to show how powerful PMLS are . Errors introduced in linear scale Errors introduced in log scale: 60 dB gain!

1-D FDTD problem Let us try to solve the same transmission problem through a slab that we had formulized for our TMM in the previous lecture with FDTD. ε1=1 and tslab=500nm with ε2=9. The slab is sandwiched between free space semi infinite layers. Please watch the video here.

1-D FDTD problem Let us try to solve the same transmission problem through a slab that we had formulized for our TMM in the previous lecture with FDTD. ε1=1 and tslab=500nm with ε2=9. The slab is sandwiched between free space semi infinite layers. Please watch the video here. We will illuminate the slab with a pulse to get the whole frequency information. We will discuss how we will retrieve the data from the present excitation method with the help of fourier analysis.

1-D FDTD problem Let us try to solve the same transmission problem through a slab that we had formulized for our TMM in the previous lecture with FDTD. ε1=1 and tslab=500nm with ε2=9. The slab is sandwiched between free space semi infinite layers. Please watch the video here.

1-D FDTD problem Let us try to solve the same transmission problem through a slab that we had formulized for our TMM in the previous lecture with FDTD. ε1=1 and tslab=500nm with ε2=9. The slab is sandwiched between free space semi infinite layers. Please watch the video here.

1-D FDTD problem Let us try to solve the same transmission problem through a slab that we had formulized for our TMM in the previous lecture with FDTD. ε1=1 and tslab=500nm with ε2=9. The slab is sandwiched between free space semi infinite layers. Please watch the video here.

1-D FDTD problem Let us try to solve the same transmission problem through a slab that we had formulized for our TMM in the previous lecture with FDTD. ε1=1 and tslab=500nm with ε2=9. The slab is sandwiched between free space semi infinite layers. Please watch the video here. Exact position is -250.5nm Exact position is -250.1nm source monitor

1-D FDTD problem Let us try to solve the same transmission problem through a slab that we had formulized for our TMM in the previous lecture with FDTD. ε1=1 and tslab=500nm with ε2=9. The slab is sandwiched between free space semi infinite layers. Please watch the video here.