Transcript Tracking the Purity of Non-GM Grain at a Local Elevator Using Modeling

AE 503 TERM PROJECT
TRACKING THE PURITY OF NON-GM GRAIN
AT THE LOCAL ELEVATOR USING DYNAMIC
MODELLING
Maureen Suryaatmadja
Graduate Research Assistant
Agricultural Engineering
Iowa State University
April 29, 2005
Introduction


Traceability is the ability to trace the
history, application or location of an entity
by means of recorded identifications
(Hurburgh, 2004)
Traceability has become a major concern
for food manufacturers and commodity
handlers
Introduction

The issue of GMO has been closely associated
with traceability. In reality, product tracking
serves much wider such as:
1.
2.
3.
4.
5.
To document a chain of custody of a product.
To document how a product was produced or handled.
To meet consumer desire for connection with the earth and
production and the environment and/or some other socioreligious need.
To provide due diligence for buyer safety/quality assurance
To respond to the security needs or regulations.
(Hurburgh, 2004)
Problem Statement


The bulk grain production and marketing system
has not been considered adaptable to identity
tracking, but there have been programs to
produce special grains for individual users that
require some form of purity maintenance.
More recently, EU customers had begun asking
for assurances that certain GM materials were
kept out of commodity grain, to an 0.9% or less
mixing level.
Flow Chart

Grain Flow Chart
Production
Farm Sales
Local
Elevators
Grain
Processor
Food and
Industry
Local Elevator Flow Chart
Truck
Pit and
Conveyor
Bucket
Elevators
Bin
(storage)
Problem Statement

The key areas in an elevator that provide
challenges for Identity Preservation (IP):
Receiving pits
 Conveyors
 Legs
 Storage Bins
(Thelen, 1999)


This project will analyze the mixing process in
the pit and conveyor, and bucket elevator (legs)
Objective

To build a dynamic simulation model that
tracks the grain purity at the local elevator
with the respect to the purity of non-GM
grain from GM grain contamination.
Assumptions





The grain is checked for the initial purity
before it unloads from the truck (GM/nonGM grain).
The system only use one pit.
There will be no cleaning activity in the
pit, conveyor and bucket elevator.
There will be some grain left in the pit and
the bucket.
The process is perfect mixing.
Assumptions


The final purity is the grain purity after
exiting the bucket.
After exiting the bucket elevator, the nonGM grain will be stored at non GM bin and
the GM grain will be stored at GM bin.
Differential Equations Development

Mass balance equation:
dM/dt = qin – qout (1)
M = accumulated mass of the
grain (kg)
dM/dt = mass flow rate of the
grain (kg/s)
qin = grain flow rate entering the
tank (kg/s)
qout = grain flow rate exiting the
tank (kg/s)
Differential Equations Development

Mass balance of the contaminant:
dmc/dt = qin Cin – qout Cout
(2)
Cout = mc/M (dimensionless)
(3)
Equation (3) is divided by M become:
dCout/dt = 1/M (qin Cin – qout Cout) (4)
mc = mass of the contaminant grain (kg)
dmc/dt = mass flow rate of the contaminant grain (kg/s)
qin = grain flow rate entering the tank (kg/s)
qout = grain flow rate exiting the tank (kg/s)
C in = grain concentration entering the tank (%)
C out = grain concentration exiting the tank (%)
Differential equation application of
grain mixing process in the local
elevator

At the pit and conveyor
dMpit/dt = qpiti - qpite
(5)
dCconve /dt = 1/(dMpit/dt) (qconvi Cconvi - qconve Cconve) (6)
dMpit/dt = the grain mass rate of change of left in the pit
dCconve/dt = the grain purity rate of change exiting the conveyor
qpiti = grain flow rate entering the pit
qpite = grain flow rate exiting the pit
Cconvi = the purity of grain entering the pit and conveyor (initial purity
of grain)
Cconve = the purity of grain exiting the conveyor
q truck out = q pit in
q pit out = q conveyor in = q conveyor out
Differential equation application of
grain mixing process in the local
elevator

At the bucket elevator
dMbucket/dt = qbucketi - qbuckete
(7)
dCbuckete/dt = 1/(dMbucket/dt) (qbucketi Cbucketi - qe Cbuckete) (8)
dM/dt = the grain mass rate of change in the bucket
dCbuckete /dt = the grain purity rate of change exiting the bucket
qbucketi = grain flow rate entering the bucket elevator
qbuckete = grain flow rate exiting the bucket elevator
Cbucketi = the purity of grain entering the bucket elevator
Cbuckete = the purity of grain exiting the bucket elevator (final purity of
grain)
q conveyor out = q bucket in
Cbucketin = Cconve
Simulink Model

The simulink model consist of four subsystems:
The first subsystem describes the changing of the grain
mass in the pit
dMpit/dt = qpiti - qpite , qpit e = A (Mpit –C)
2. The second subsystem describes the changing of the grain
purity after exiting the conveyor
dCconve /dt = 1/(dMpit/dt) (qconvi Cconvi - qconve
Cconve)
3. The third subsystem describes the changing of the grain
mass in the bucket
dMbucket/dt = qbucketi – qbuckete
4.
The fourth subsystem describes the changing of the grain
purity after exiting the bucket elevator
dCbuckete/dt = 1/(dMbucket/dt) (qbucketi Cbucketi - qe
Cbuckete)
1.
mpi t
Qpi t i n=Qtruckout
1
s
Step
Integrator
Step1
Q pi t out
Scope4
-K-
0
Swi tch
0.5
-Csi mout
Current Load puri ty
T o Workspace
C conv i n
1
u
1/mpi t
Q conv i n
1
s
Scope1
Product
C conv out
Q conv out
Q bucket i n
mbucket
1
s
Scope2
Q bucket out
1.5
Swi tch1
7
0
1
u
1/mbucket
Cbucket i n
Qbucket i n
1
s
C bucket out
Q bucket out
Scope3
MATLAB INPUT
close all % Close all open figures
clear all % Clears all the variables in the workspace
Con = [0 100 0 100 ];
simsave = [];
for load = 1:4
disp(load);
currentloadpurity = Con(load);
if load == 1
mpit = 0.0001;
cpit = 0;
mbucket = 0.0001;
cbucket = 0;
else
mpit = simout.signals.values(size(simout.signals.values,1),1);
cpit = simout.signals.values(size(simout.signals.values,1),2);
mbucket = simout.signals.values(size(simout.signals.values,1),3);
cbucket = simout.signals.values(size(simout.signals.values,1),4);
end
[T,X,Y]= sim('impurity',[0 8000]);
disp(simout.signals.values(size(simout.signals.values,1),1:4));
simsave = [simsave; simout.signals.values];
end
Input Value


First Step
step time = 12.5
initial value = 0
final value = 17.5
sample time = 0
Second Step
step time = 367.5
initial value = 0
final value = -17.5
sample time = 0
Input Value




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
Mpit initial before the first load flow = 0.0001 kg
Cpit initial before the first load flow = 0
Mbucket initial before the first load flow = 0.0001 kg
Cbucket initial before the first load flow = 0
Switch function in the pit: qpite = A(Mpit – C)
A = 0.001
C = 0.5
Treshold = 7, 15
Switch function in the bucket elevator: qbuckete = A(Mbucket – C)
A = 1.5
C = 7, 15
Treshold =7,15
T = 8000 s
Result

First Combination Load:
1.
2.
3.
4.
GM load = 0% non-GM load
Non-GM load = 100% non-GM load
GM load = 0% non-GM load
Non-GM load = 100% non-GM load
Result
Load
Initial
Purity
M grain left in
C exiting
M grain left in
C exiting
the pit
conveyor
the bucket
Bucket
(%)
(kg)
(%)
(kg)
(%)
1
0
7.0000
0.0000
7.0018
0.0000
2
100
7.0000
99.9062
7.0003
99.6890
3
0
7.0000
0.0937
7.0025
0.1873
4
100
7.0000
99.9063
7.0004
99.6904
Result
Load
Initial
Purity
M grain left in
C exiting
M grain left in
C exiting
the pit
Conveyor
the bucket
Bucket
(%)
(kg)
(%)
(kg)
(%)
1
0
15.0000
0.0000
15.0176
0.0000
2
100
15.0000
99.7993
15.0010
99.4745
3
0
15.0000
0.2003
15.0007
0.4003
4
100
15.0000
99.7997
15.0008
99.4742
Result

The second combination load:
1.
2.
3.
GM load = 0% non-GM load
GM load = 0% non-GM load
Non-GM load = 100% non-GM load
Result
Load
Initial
Purity
M grain left in
C exiting
M grain left in
C exiting
the pit
Conveyor
the bucket
Bucket
(%)
(kg)
(%)
(kg)
(%)
1
0
7.0000
0.0000
7.0018
0.0000
2
0
7.0000
0.0000
7.0043
0.0000
3
100
7.0000
99.9062
7.0015
99.7060
Result
The Changing of Grain Purity After Exiting Bucket
120
100
Purity (%)
80
60
40
20
0
1
1144 2287 3430 4573 5716 6859 8002 9145 10288 11431 12574 13717 14860
Time (s)
Result
The Changing Mass in the Pit
6000
Grain Mass (kg)
5000
4000
3000
2000
1000
0
0
500
1000
1500
2000
Time (s)
2500
3000
3500
4000
Result
The Changing Grain Purity After Exiting The Conveyor
100
90
80
70
Purity (%)
60
50
40
30
20
10
0
0
500
1000
1500
2000
Time (s)
2500
3000
3500
4000
Result
The Changing Mass in the Bucket
10.5
10
Grain Mass (kg)
9.5
9
8.5
8
7.5
7
6.5
0
500
1000
1500
2000
Time (s)
2500
3000
3500
4000
Result
The Changing Grain Purity After Exiting The Bucket
100
90
80
Grain Purity (%)
70
60
50
40
30
20
10
0
0
500
1000
1500
2000
Time (s)
2500
3000
3500
4000
Conclusion
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
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
The model is not able to describe all the processes
that happen in the local elevator; however it can be
used to track the purity of the grain.
The final purity level depends on the amount of grain
that left in the pit and the bucket.
When the amount of grain left in the pit and the
bucket increase, the final purity level will decrease.
It is important to keep grain left in the pit and bucket
as least as possible.
The future development should improve the accuracy
of the model and describe all the processes happen in
the local elevator.
SPECIAL THANKS TO:
DR. BRIAN STEWARD for his
valuable advises and helps in
developing the simulation model