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How to code a certain part of this equation?

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Angshuman Podder
Angshuman Podder am 17 Mai 2022
Bearbeitet: Angshuman Podder am 18 Mai 2022
I am trying to write a code for solving population based equations (PBEs) using cell average technique (CAT) by Kumar et al. (2006). Link to the paper: PAPER
However, I am stucking with interpreting a certain part of the whole formulation (mathematical notation) which I have circled in red in the figure. Can anyone help me in correcting me or explaining it? My attempt is somewhat as follows:
clear
close all;
clc;
% ======== User handle starts ==================
%% Initializing
v_max = 100.0; % Maximum size/volume
v_min = 1e-5; % Minimum size/volume
r = 2; % Geometric ratio
% v0 = 0.01; % Initial average size
% N0 = 1; % Initial total number
% tspan = [0 20]; % time span for integration
%% Generating discretized grid
disp('Creating the geometric grid..')
m = ceil(log(v_max/v_min)/log(r)); % Number of pivots
mv = m + 1; % Number of volume boundaries
vi = zeros(mv,1);
vi(1) = v_min;
for i = 2:mv
vi(i) = vi(i-1)*r; %cell edges
end
x = zeros(m,1); % Creating pivots
w = zeros(m,1); % Bin width
for i = 1:m
x(i) = (vi(i) + vi(i+1))/2; %cell centers/pivots
w(i) = vi(i+1) - vi(i); % width
end
p = 1; %fixed pivot
for j = 1: m
for k = 1:j
v = x(j) + x(k) ;
for i = 1:m-1
if v < x(i+1) && v >= x(i)
itvl(p,:) = [x(j), x(k)] ;
Z(i,j,k) = 1;
p = p +1;
break;
end
end
end
end
p = 1; %CAT
for j = 1: m
for k = 1:j
v = x(j) + x(k) ;
for i = 1:mv-1
if v < vi(i+1) && v >= vi(i)
itvl(p,:) = [x(j), x(k)] ;
Z(i,j,k) = 1;
p = p +1;
end
end
end
end
return
%%%%%%%% i-th equation %%%%%%%%%%%%
for i = 1:m
for j = 1:m
for k = 1:j
B(i) = (1 - (1/2)*Z(i,j,k)*dirac_delta(i,j))*beta(j,k)*N(j)*N(k) ;
end
end
end

Akzeptierte Antwort

Torsten
Torsten am 17 Mai 2022
for i = 1:m-1
xmhalf = x(i);
xphalf = x(i+1);
B_agg(i) = 0.0;
for k=1:m
for j=k:m
if vi(j) + vi(k) < xphalf && vi(j) + vi(k) >= xmhalf
B_agg(i) = B_agg(i) + (1-0.5*dirac_delta(j,k))*beta(j,k)*N(j)*N(k);
end
end
end
end
Not sure about the loop limits - recheck !
  1 Kommentar
Angshuman Podder
Angshuman Podder am 18 Mai 2022
Bearbeitet: Angshuman Podder am 18 Mai 2022
Thank you for your solution. Really appreciate it! I think it makes sense now. I modified your code a little and tried to implement it in the overall code. However, I am still running into a solution not matching the published results. I have outlined the entire algorithm here in the figure:
Can you please have a look at my attempt and point out errors which is as follows. Thanks in advance.
function [dNdt] = aggregation_CA(t,y,rcenter,redge)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Function to calculate aggregation rate
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
N = y;
% Initialize
n = length(rcenter) ; %no. of cell centers %one less than edge
B = zeros(n,1) ;
M = zeros(n,1) ;
abar = zeros(n,1) ;
D = zeros(n,1) ;
x = rcenter;%(4/3)*pi*r.^3;
vi = redge;
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Step 1: Calculate birth rates
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% a. Calculation of kernels
for i = 1: n
for j = 1:n
beta(i,j) = 1; %constant kernel %test problem 1
end
end
% b. Calculation of the net rate of addition of particles to cell i by
% coagulation of particles in lower cells
p=1;
for i = 1:n
xmhalf = vi(i);
xphalf = vi(i+1);
B_agg(i) = 0.0;
for k=1:n
for j=k:n
if x(j) + x(k) < xphalf && x(j) + x(k) >= xmhalf
B_agg(i) = B_agg(i) + (1-0.5*dirac_delta(j,k))*beta(j,k)*N(j)*N(k);
%interval(p,:) = [x(k), x(j)] ;
%del(p,:) = x(j) - x(k);
p = p +1;
end
end
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Step 2: Calculate volume averages
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% a. Calculation of fluxes into cell i as a result of coagulations
for i = 1:n
xmhalf = vi(i);
xphalf = vi(i+1);
M(i) = 0.0;
for k=1:n
for j=k:n
if x(j) + x(k) < xphalf && x(j) + x(k) >= xmhalf
M(i) = M(i) + (1-0.5*dirac_delta(j,k))*beta(j,k)*N(j)*N(k)*(x(j)+x(k));
end
end
end
end
% b. Average volume of newborn particles in the ith cell
for i = 1:n
abar(i) = M(i)/B(i);
end
for i = 1:n
if B(i) == 0 % if no particles is there in a bin, avoid NaN error
abar(i) = 1;
end
end
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Step 3: Calculate of birth modification
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
Bmod = B;
Bzero = 0 ; %zero boundary at first cell
Bmod(1) = Bzero...%B(1)*lambdaminus(1,abar(1),xcenter)*heaviSide(xcenter(1)-abar(1)) ...
+ B(1)*lambdaplus(1,abar(1),x)*heaviSide(abar(1)-x(1));
Bmod(n) = B(n-1)*lambdaminus(n,abar(n-1),x)*heaviSide(x(n-1)-abar(n-1)) ...
+ Bzero;%B(n-1)*lambdaplus(n,abar(n-1),xcenter)*heaviSide(abar(n-1)-xcenter(n-1)) ;
for i = 2:n-1
Bmod(i) = B(i-1)*lambdaminus(i,abar(i-1),x)*heaviSide(abar(i-1)-x(i-1)) + ...
B(i)*lambdaminus(i,abar(i),x)*heaviSide(x(i)-abar(i)) ...
+ B(i)*lambdaplus(i,abar(i),x)*heaviSide(abar(i)-x(i)) +...
B(i+1)*lambdaplus(i,abar(i+1),x)*heaviSide(x(i+1)-abar(i+1)) ;
end
%Bmod(n) = Bmod(n-1) ; %zero flux at last cell
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%Step 4: Calculate of death terms
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
for i = 1:n
sum = 0;
for k = 1: n
sum = sum + beta(i,k)*N(k) ;
end
D(i) = N(i)*sum;
end
%dNdt = Bmod - D; %Birth-Death
for i =1:n
dNdt(i,1) = Bmod(i) - D(i);
end
fprintf('t= %2.2e; maxN = %2.2e ; minN = %2.2e \n',t,max(N),min(N))
end
%% Auxillary math functions
function y = dirac_delta(i,j)
if i == j
y = 1;
else
y = 0;
end
end
function y = heaviSide(x)
if x > 0
y = 1;
elseif x == 0
y = 1/2;
else
y = 0;
end
end
function y = lambdaplus(i,x,xcenter)
y = (x - xcenter(i+1))/(xcenter(i) - xcenter(i+1));
end
function y = lambdaminus(i,x,xcenter)
y = (x - xcenter(i-1))/(xcenter(i) - xcenter(i-1));
end

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