Lampiran 1. Diagram alir penelitian

Ukuran: px

Mulai penontonan dengan halaman:

Download "Lampiran 1. Diagram alir penelitian"

Liani Dharmawijaya
8 tahun lalu
Tontonan:

1 LAMPIRAN 41

2 42

3 43 Lampiran 1. Diagram alir penelitian Penelusuran Literatur Sudah Siap Penguasaan Software Penentuan Parameter Pembuatan dan Pengujian Program Analisis Output Penyusunan Laporan

4 44

5 45 Lampiran 2. Program coding untuk mensimulasikan proses perambatan gelombang elektromagnetik di dalam struktur sensor dengan menggunakan metode FDTD % FDTD 2D dengan PML % % optical biosensor kuasi kristal fotonik 1D dengan DUA ROD DEFEK % Bahan penelitian Tesis % Sumber berupa gelombang sinusoidal % Dani clear all; close all; clc; %-- % Kondisi Inisial. %-- Imax = 200; % Jumlah grid. Jmax = 400; Ez = zeros(imax,jmax); Dz = zeros(imax,jmax); Dz_hat = zeros(imax,jmax); Hy = zeros(imax,jmax); sumbu-y Hx = zeros(imax,jmax); sumbu-x % vektor medan listrik % vektor flux listrik % vektor parameter % vektor medan magnet arah % vektor medan magnet arah fi1 = zeros(imax,1); fi2 = ones(imax,1); fi3 = ones(imax,1); gi2 = ones(imax,1); gi3 = ones(imax,1); fj1 = zeros(jmax,1); fj2 = ones(jmax,1); fj3 = ones(jmax,1); gj2 = ones(jmax,1); gj3 = ones(jmax,1); ihx = zeros(imax,jmax); ihy = zeros(imax,jmax); c0 = 3e8; lambda=560e-9; freq=c0/lambda; excitation omega=2.0*pi*freq; k=2*pi/lambda; time=0; t0=50; spread=15; %center wavelength of source excitation %center frequency of source % inisial kondisi waktu

6 46 %-- % vektor konstanta dielektrik input. %-- e0 = 8.85e-12; er = ones(imax,jmax); %-- % konduktivitas input. konduktivity ohmik: J = sigma*e. %-- sigma = zeros(imax,jmax); %-- % parameter PML. %-- npml = 8; for i= 0:npml xnum = npml - i; % Dz xxn = xnum/npml; xn =.333*xxn^3; gi2(i+1) = 1/(1+xn); gi2(imax-i) = 1/(1+xn); gi3(i+1) = (1-xn)/(1+xn); gi3(imax-i) = (1-xn)/(1+xn); % for H_x dan H_y xxn = (xnum -.5)/npml; xn =.333*xxn^3; fi1(i+1) = xn; fi1(imax-i) = xn; fi2(i+1) = 1/(1+xn); fi2(imax-i) = 1/(1+xn); fi3(i+1) = (1-xn)/(1+xn); fi3(imax-i) = (1-xn)/(1+xn); for j= 0:npml xnum = npml-j; % Dz xxn = xnum/npml; xn =.333*xxn^3; gj2(j+1) = 1/(1+xn); gj2(jmax-j) = 1/(1+xn); gj3(j+1) = (1-xn)/(1+xn); gj3(jmax-j) = (1-xn)/(1+xn); % for H_x dan H_y xxn = (xnum -.5)/npml; xn =.333*xxn^3; fj1(j+1) = xn; fj1(jmax-j) = xn; fj2(j+1) = 1/(1+xn); fj2(jmax-j) = 1/(1+xn); fj3(j+1) = (1-xn)/(1+xn);

7 47 fj3(jmax-j) = (1-xn)/(1+xn); %-- % penentuan ukuran ddx dan dt. %-- ddx = 5.0e-8; % space increment dt = ddx/6e8; % time step % % Variasi indeks bias pada struktur sensor % er_a=(3.48)^2; % Si er_b=(1.44)^2; % SiO2 er_c= (1.7)^2; % Al2O3 for i=1:80 for j=30:380 sigma(i,j)=0.0; for i=81:120 for j=30:380 sigma(i,j)=0.0; A1=zeros(i,j); A2=zeros(i,j); A3=zeros(i,j); A4=zeros(i,j); A5=zeros(i,j); A6=zeros(i,j); A7=zeros(i,j); A8=zeros(i,j); A9=zeros(i,j); A10=zeros(i,j); A11=zeros(i,j); radius = 10; radius2 = 12; xc=100; yc1=60; yc2=90; yc3=120; yc4=150; yc5=180; yc6=210; yc7=240; yc8=270; yc9=300; yc10=330; yc11=360; A1(i,j)=sqrt((i-xc)^2 + (j-yc1)^2); A2(i,j)=sqrt((i-xc)^2 + (j-yc2)^2); A3(i,j)=sqrt((i-xc)^2 + (j-yc3)^2); A4(i,j)=sqrt((i-xc)^2 + (j-yc4)^2); A5(i,j)=sqrt((i-xc)^2 + (j-yc5)^2); A6(i,j)=sqrt((i-xc)^2 + (j-yc6)^2); A7(i,j)=sqrt((i-xc)^2 + (j-yc7)^2); A8(i,j)=sqrt((i-xc)^2 + (j-yc8)^2); A9(i,j)=sqrt((i-xc)^2 + (j-yc9)^2); A10(i,j)=sqrt((i-xc)^2 + (j-yc10)^2); A11(i,j)=sqrt((i-xc)^2 + (j-yc11)^2); if A1(i,j)<=radius

8 48 elseif A2(i,j)<=radius elseif A3(i,j)<=radius elseif A4(i,j)<=radius2 er(i,j)=er_c; % Defek ke-1 (rod 4) elseif A5(i,j)<=radius elseif A6(i,j)<=radius elseif A7(i,j)<=radius elseif A8(i,j)<=16 er(i,j)=1.45^2; % Defek ke-2 (rod 8) elseif A9(i,j)<=radius elseif A10(i,j)<=radius elseif A11(i,j)<=radius else er(i,j)=er_a; for i=120:200 for j=30:380 sigma(i,j)=0.0; %-- % Penentuan vektor dan konstanta. %-- gb = (dt*sigma)./e0; gbc = zeros(imax,jmax); ga = 1./(er + gb + gbc); %-- % variabel awal. %-- T = 0; NSTEPS =2500; %-- % MAIN FDTD LOOP. %--

9 49 for n = 1:NSTEPS time= time+n*dt; t(n)=time; T = T + 1; % % Penentuan Dz dari Hy and Hx. % for i = 2:Imax for j = 2:Jmax Dz_hat_temp = gi3(i)*dz_hat(i,j) + gi2(i)*.5*(hy(i,j)-hy(i- 1,j)-Hx(i,j)+Hx(i,j-1)); Dz(i,j) = gj3(j)*dz(i,j) + gj2(j)*(dz_hat_temp - Dz_hat(i,j)); Dz_hat(i,j) = Dz_hat_temp; % % Pembentukan pulsa listrik. % Ic = 150; % domain komputasi Jc = 50; rtau=160.0e-12; tau=rtau/dt; delay=3*tau; for i = 1:Imax for j = 1:Jmax pulse = 50*sin(2*pi*(freq*dt*T-(freq/3e8)*ddx)); Dz(i,10) = Dz(i,10) + pulse; % source = 50*sin(2*pi*1500*1e6*dt*T); % Dz(Ic,Jc) = Dz(Ic,Jc) + source; % source = 50*sin(2*pi*(1500*1e6*dt*T-(1500*1e6/3e8)*ddx)); % Dz(Ic,Jc) = Dz(Ic,Jc) + source; % source = exp(-.5*((t0-t)/spread)^2 ); % Dz(Ic,Jc) = Dz(Ic,Jc) + source; % % Penentuan Ez dari Dz. % Ez = ga.*dz; Ez(1,:) = 0; Ez(Imax,:) = 0; Ez(:,1) = 0; Ez(:,Jmax) = 0;

10 50 % % penentuan Hx dan Hy dari Ez. % for i = 1:Imax-1 for j = 1:Jmax-1 % Hy. de = Ez(i+1,j) - Ez(i,j); ihy(i,j) = ihy(i,j) + fj1(j)*de; Hy(i,j) = fi3(i)*hy(i,j) + fi2(i)*.5*de + fi2(i)*ihy(i,j); % Hx. de = Ez(i,j) - Ez(i,j+1); ihx(i,j) = ihx(i,j) + fi1(i)*de; Hx(i,j) = fj3(j)*hx(i,j) + fj2(j)*.5*de + fj2(j)*ihx(i,j); % %Perhitungan input dan output % for i=81:120 Q1=abs(Ez(i,28)); Q2=abs(Ez(i,382)); for a=1:40 p(a)=a; Z1(a)=e0*Q1; Z2(a)=e0*Q2; Az1(n)=trapz(p,Z1); Az2(n)=trapz(p,Z2); timestep=int2str(n); figure(1) surf(real(ez)); caxis([-3e4 3e4]); title(['ez at time step = ',timestep]); xlabel('x-direction (*5E-2 µm)'); ylabel('y direction (*5E-2 µm)'); zlabel('ez Field'); view(0,90) shading interp hold on hold off; pause(0.1)

11 51 Energi_In=trapz(t,Az1) Energi_Out=trapz(t,Az2) figure(2) surf(abs(er)); title('struktur Berdasarkan Nilai Permitivitas') xlabel('x-direction (*5E-2 µm)'); ylabel('y direction (*5E-2 µm)'); zlabel('relative permitivity') view(0,90) shading interp figure(3) title('power input'); plot(t,az1); xlabel('time(second)'); ylabel('power Input(watt)'); figure(4) plot(t,az2); title('power Output er=11.00') xlabel('time(second)'); ylabel('power Output(watt)');

12 52

13 53 Lampiran 3. Proses pengukuran nilai rapat energi rata-rata W Incident wave defek 1 st defect 2 nd defect z y x h Q t E t dy = ε ( ) ( ) t 0 ( ) W = Q t dt t Simulasi dilakukan beberapa kali dengan memvariasikan nilai indeks bias defek kedua Grafik hubungan rapat energi rata-rata terhadap indeks bias

14 54

15 PUBLIKASI 55

16 56

17 PROCEEDING The 4 th Asian Physics Symposium 2010 (APS 2010), Bandung 57

18 58

19 59

dokumen-dokumen yang mirip

BAB IV HASIL DAN PEMBAHASAN

23 BAB IV HASIL DAN PEMBAHASAN 4.1 Visualisasi Gelombang di Dalam Domain Komputasi Teknis penelitian yang dilakukan dalam menguji disain sensor ini adalah dengan cara menembakkan struktur sensor yang telah