- Email: [email protected]
Simulation of M.S.F. desalination plants
Desalination, 45 (1983) 65-76 ElsevierScience PublishersB.V.,Amsterdan-Printed in The Netherlands
65
SIMULATION OF M.S.F. DESALINATION PLANTS ADEL M. OMAR Chief Operations Engineer, WCC Al-Khobar Desalination Plant, P.D. Box 262, Al-Khobar (Saudi Arabia).
ABSTRACT A simulation program on the modeling of MSF desalination plants has been developed by the author (ref.1). The program can be used to accurately either design or simulate plants in actual operation. Proprietory computer programs have been originated by a number of desalination designers for their own use. A few general ones have been published (refs. 2 & 3). The paper describes the design and modeling philosophy utilized in developing the said program. A typical application on Al-Khobar (Phase-I) MSF desalination plant is briefly illustrated as an example for the use of simulation mode of the code. INTRODUCTION The analysis summarized in this paper is oriented towards developing a design code requiring a mathematical model for the MSF distillation process which is schematically illustrated in Fig. 1.
.------_-______ ___-__-__________--_______ -~ ,~--------------_-_--_--------________ ..____- _._.._. _-I,
E;
&=__
Fig. 1.
=$$,ygg x-
TzE=-q
:a
gzfz,EEy (N4
_______ _ ____ ____________________ ______ _--___-______-____-__-_-___-_--__-__--___ .f'wm -*ncr-L&r
Schematic Diagram
OOll-9164/63/$03.00
for
the
ii
JJ
MSF distillation process.
CD1963 Elsevier 6cience! PubliaberclB.V.
66 The development of simulation program for this system requires analysis of the various components shown in the figure to obtain the desired information for the basic process streams. The system consists of N stages of which M are rejection stages and (N-M) are recovery stages, a mixing stage (N+l), a recycling pump (N+2), a splitter (N+3), feed water, brine recycle, flashing brine, blow down, distilled water and the heater (N+4) streams etc. FORMULATION OF MATHEMATICAL MODEL The desired model relationships consist of standard chemical These are: Material balances, Energy
engineering relationships.
balances, Momentum balances, Kinetic relationships, Equilibrium relationships and Control relationships (ref. 4). Typical Stage Analysis Typical stage variables and parameters are indicated on the actual stage as shown in Fig. 2. A set of mathematical relationships for each stage may be represented in a box manner
Fig. 2
as
Typical MSF Stage Variables
follows:INPUT STREAM VARIABLES
MODEL OF PROCESS STAGE b I STAGE PARAMETERS
OUTPUT STREAM VARIABLES
67 in mathematical
Input
Stream
stream
Each
stream
= f (output stream variables, stage parameters)
is defined
we have
Mass
(dependent)
variable
As shown
on several
condenser
bundle
(
A”i)
-
A’i
= Ti' - BPEi
The experimental the major
use a certain
losses
losses
losses,
(tl) can
which
cause
are the non-equilibrium
through
the demisters
boiling
point
and elevation
losses
stage
there
of four independent
twelve
independent
stage.
The basic
are three
equations
(top), the distilled stream
designers for the
for the
on the results.
will
it can be seen
streams three
each consisting
streams
variables.
be needed
to fully
leave the Therefore describe
are the tube side cooling
water
stream
(middle)
that
a
brine
and the flashing
(bottom).
The formulated which
incoming Another
streams
to account influence
and Fig.2,
of four independent
stage
to account
Equations
analysis
variables.
each consisting
used
are of prime
(ref. 5) indi-
Some MSF plant
allowance
The methods
losses
of researches
Ali.
affecting
and Subsidiary
the typical stage,
(1)
correction
(ref. 6).
Fundamental
for each
A’li from a number
temperature
thermodynamic
From
-
data
various
tities
side temperature
and the classical
parameters
various
brine
One desired
; thus:-
(BPEji
stream
vapour
thermodynamic
(i), these
stage
the pressure
stage
(T or t)OF,
(P or p)psia.
effects.
( ki),
Staqe
Temperature
for
these
(H or h) BTU/lb.
2, the stage
based
For typical
cates
where
variables:
Relationship
allowance
ti
variables
(independent)
and Pressure
is enthalpy
in Fig.
be calculated
of the basic
(M or m) lb/hr,
(C)% solid
Equilibrium
subcooling
in terms
four fundamental
flow rate
Concentration
Stage
variables
as:-
Definition
each stream are:
this can be expressed
terms;
basic
twelve
are dependent
equations
on the stage
(ref.1) include variables
some quan-
and these quanti-
ties can be expressed'by means of set of independent (subsidiary) equations.
Variables other than fundamental variables previously
defined must be specified or fixed in order to achieve consistent solution to the problem. Brine Heater Analysis Similar analysis can be done to the brine heater model (Fig. 3) (ref.1) resulting in another eight basic equations describing the brine heater and its related streams.
STAGE
(1)
BRINE
HEATER
4
CONDENSATE
mC.tC.c~,pc,hC
co.
P. Ii.
Fig. 3.
-
Brine Heater and First Stage Variables.
GENERAL SYSTEM ANALYSIS When the overall system has been synthesized into a set of mathematical relationships, the consistent solution to the design problem of the system can only be obtained if the total number of variables match the number of developed equations. Total Streams Counting the total number of streams in Figs. 1 & 2 can be summarized in Table l:-
69
Table 1 Counting Total No. of System Streams VP=
Inter-stage st*eams
0.
0
Identification
stre*ms 3(N-2)
3 streams
for
inter-stage Stage
terminals
stream 6,
Mixer
(N*l)
Pump (N*Z)
Splitter Heater
(N+3) (N+4)
7,
Total
1,
2,
12 and
nos. 9 and
stream
11 and
already
included
strellm
nos.
stream
nos.
addition
already
i.e.
nos. 10,
stream
in
Total
(N-2)
partition 3,
4,
5
13 11
4
8 14 and to
15
12 and
13
included
3N+9
Total Number of Streams
=
3N+9
(2)
Variables
Once the total number of streams is known, the number of variables can be calculated.
We have four independent variables for each stream and in addition an arbitrary chosen number of heat rejection stages (M) and total number of stages (N) as two independ-
ent variables.
Therefore:-
Total Number of Variables
=
(3N+9).(4)+2
=
12N + 38
(3)
TotalEquations Based on the desired fundamental equations for the various system components, the total number of independent equations is given in Table 2:-
70
Table 2 Counting Total No. of
0.
Component
Equations
0
comment
equations
N stages
We have 12 fundamental equations/stage
Mixer (N+l)
4
Pump (N+Z)
4
Splitter (N+3)
8
Brine heater (N+4)
8
Total
i.e.
Previously derived
ltN+24
Total no. of equations
=
12N + 24
(4)
Check for consistency Comparing equations
(3) and (4), it can be seen that the number
of variables exceeds the number of equations by fourteen.
This difference implies specification of fourteen variables to permit consistent solution of the problem.
Variables to be specified The fourteen variables to be specified are chosen based on the analysis of the system guided by Fig. 1 as follows:Feed. variables 1.
F
:
fresh sea water cooling water flow
2.
TF
:
fresh sea water inlet temperature
3. 4.
cs : PF or VF :
lb/hr OF
sea water salt concentration
% salt
sea water inlet pressure (or velocity)
psia
71 General boundary conditions D
:
plant distillate production
lb/hr
6.
CD
:
distillate production purity
% salt
7.
CR
:
(recycle concentration ratio). This fixed the overall salt balance in the system by fixing the maximum allowable salt concentration into the brine heater (CO) as
5.
CO = CS. CR and since CS is also specified, therefore CO is fixed. 8.
:
To
maximum brine temperature OF. this is bound by the total enthalpy balance for the system or the control relationship at the brine heater.
Brine heater boundary conditions 9.
:
Ts
10.
Ps
11.
cs
12.
or C
MS
C
steam temperature to brine heater
OF
:
steam pressure to brine heater
psia
:
purity of steam or condensate
% salt
:
steam flow to brine heater
lb/hr
:
heat input to brine heater (fixed by performance ratio)
BTU/hr
or 'B.H.
Number of stages 13.
M
:
number of heat rejection stages
14.
N
:
total number of stages
Thus by specifying these parameters and the additional specific variables, appearing in the subsidiary equations or needed for physical property calculation, a consistent solution can be achieved. For example, parameters such as fouling factors, tube diameter, thickness and material etc. can be arbitrarily fixed by designer.
SALINE WATER EVAPORATOR DESIGN CODE "SWEDC" The mathematical model is translated into a Fortran IV computer code "SWEDC" for the design or simulation of MSF desalination plants with the aid of an IBM 370 machine.
72 The problem solved by this code is basically the calculation of heat and mass balance in the MSF evaporator by a stage-to-stage method, in addition to the design of the process equipment.
The
design is based upon the specified basic information referred to as input parameters.
The program results or output will consist of
the various calculated process parameters including condenser surface area of the various plant sections, process pump heads, basic stream flow rates etc. information is also provided.
Comprehensive stage-by-stage process The general algorithm that is used
in the program is shown in Fig. 4.
Fig. 4
General flow process diagram for "SWEDC"
Convergence of solution is based upon a thermodynamically feasible solution.
No cost bases are involved in this study.
The
specific design information and initializing values are read in with the input data to obtain the first or approximate solution. Adjustment of variables is then made and calculations are repeated until the convergent solution is reached. The code application to various desalination plant designs showed excellent results (ref.1). The original plant specifications as contracted between purchaser and consultant were considered as
73 inputs, while the outputs were compared with the detailed design information as supplied by the desalination project contractor. SIMULATION OF ACTUAL MSF PLANTS Four actual plant designs are simulated: Al-Jubail Phase-I and Al-Khobar Phase-II which are low temp. (90°C maximum) and Al-Khobar Phase-I and Fichtner Reference Plant (ref. 6) which are high temp. (Note that Al-Khobar Phase-II has also been (12OOC maximum). specified for high temperature operation). In terms of production capacity the low temperature plants are approximately twice that of the high temperature ones, the former having a production capacity of 5 MIGD. Prediction of thermodynamic losses criteria As the original designers consider the information on thermodynamic losses particularly proprietory, to circumvent this problem the program was run for the several known correlations (ref.5), and the design obtained closest to the original chosen as most priate.
appro-
The accuracy comparison indicated that the agreement is
within 2% and is in general much better than that.
It is not
intended in this paper to discuss these simulations with their lengthy input-output details, however a typical application of the code can be shown for the simulation of Al-Khobar Phase-I Operation,
Al-Khobar Phase-I plant operation simulation From the simulation calculations for Al-Khobar Phase-I operating since 1974, it is concluded that the original plant production 2.5 MGD/Unit cannot be obtained for the following reasons:The first reason is that the difference between the actual sea water salinity (56,000 ppm) and that reported by the project consultant (50,000 ppm) limits the plant production to only 87% of the original capacity due to the accompanying limitations on the maximum brine temperature to avoid CaS04 scaling. The second reason is the influence of the design sea water temperature on the plant productivity.
A sea water temperature of 35OC (95OF) is considered more practical assumption for design purpose reflecting the updated trends in the newly built desalination plants on the Arabian Gulf shores.
It is predicted that this assumption causes a further drop in the expected production for the
74
desalination units of Al-Khobar Phase-I plant (plant designer's assumption is 29.4'C) as shown in Table 3.
Table
3
Effect of Sea Water Temperature on Production for Original Desiqn
Al-Khobar (I) Plant Original Design Conditions TSEA
TFBO -
244’F
CSEA
50.0
30.0
1 wd
PRODI
% age
GPD(U.S)
lb/hr
i
00
icTION
I
29.4
-
output
100%
85.0
865,867
2.50
86.0
858.632
2.479
99.16%
87.8
852,662
2.462
98.47%
89.6
846,736
2.445
97.80%
836,305
2.415
96.59%
830,492
2.398
95.91%
824,720
2.381
95.25%
I
The net effect of these two reasons when combined together indicates that the predicted evaporator unit production will be approximately 83.72% of the original capacity for plant operating at 56,000 ppm sea water salinity and at the severe summer condition sea water temperature of 35OC (95OF) (Table 4). Table
4
Effect of Sea Water Temperature on Production for Modified Conditions ’ Al-Khobsr (I) Modified Conditions
I
TSEA L
f
Plant
Design -I-
PRODUCTION
0,
lb/hr
85.0
767,187
86.0 87.8
1 I
GPD(U.S)
1
% age
output
2.2077
85.31%
760,415
2.1882
87.53%
755,129
2.1730
86.921
89.6
742,709
2.1373
a5.49a
91.4
737,546
2.1224
89.90%
93.2
732,419
2.1077
84.31%
95.0
727.328
2.0930
83.72%
76
These are represented in Fig. 5.
Fig.
5.
Al-Khobar-I Production as Function of Sea Water Temperature
REFERENCES A.M. Omar, 'Simulation of MSF Desalination Plants', M.Sc.Thesis, D.P.M., Dhahran, Saudi Arabia (1981). R.J. Easterday, 'FLASH : An IBM-7000 Code for Computing MSF Plant Designs for the Desalination of Sea Water', ORNL TM-124 (1965). C.T. Mothershed, 'OROSEF : A Fortran Code for Overall Design of the MSF Desalination Plant', ORNL TM-1627 (1966). K.F. Loughlin, 'Mathematical Model and Simulation of a Chemical Process' ,Lecture notes prepared for the Course on Separation Processes : Theory and Practice, presented at U.P.M. Dhahran, Saudi Arabia (1980). N. Lior, 'A Review of'Equations Used to Calculate Non-Equilibrium Allowance in Flash Evaporators', University of Pennsylvania, Mech. Eng. Dept. (1979). H.E. Homig, 'Sea Water and Sea Water Distillation', Fichtner Handbook, Vulkan Verlay, Essen (1978).
'76 RESUME Ein simulation program fiirMSF entsalzung anlagen model ist beschrieben (ref.1). Dieser program kann man benutzen sum design order simulate anlagen die sind schon in betrieb. Komputer programmen fiir eigene benutzung sind bei entsalzungsanlagen designers gemacht von dieser programme sind nur wentage veroffentlicht (refs.2 & 3). In dieser arbeit ist die design u modeling philosophy fiirdie program beschrieben. Als beispiel zum benutzung die simulation mode von code, Phase-I MSF Alkhobar (Saudi Arabia) entsalzungsanlage ist ausgewahlt.
EXTRAIT
Un programnede simulationD'une installation de dessalement"Multiflash" a ete mis au point par auteur ( Ref.1 ). Le progranmepeut etre utilise,soit pour calculer,soit pouk simulerle fonctionnement D'une installation. De nombreuxprogranmesont ete treespar les bureauxD'etudesconcevant de tellesusines,et sont leur proprietereservea leur propreusage. Quelquesun seulement,D'orpregeneral,ont ete publies (ref2 et 3) Le rapportdecrit la philosophieDu model de calculutilisedans la mise au point du progranme. Conne example,une applicationa l'usinede dessalement D'al Khobar (PhaseI) illustre/brievenent l'utilisation de la methodede simulation.
65
SIMULATION OF M.S.F. DESALINATION PLANTS ADEL M. OMAR Chief Operations Engineer, WCC Al-Khobar Desalination Plant, P.D. Box 262, Al-Khobar (Saudi Arabia).
ABSTRACT A simulation program on the modeling of MSF desalination plants has been developed by the author (ref.1). The program can be used to accurately either design or simulate plants in actual operation. Proprietory computer programs have been originated by a number of desalination designers for their own use. A few general ones have been published (refs. 2 & 3). The paper describes the design and modeling philosophy utilized in developing the said program. A typical application on Al-Khobar (Phase-I) MSF desalination plant is briefly illustrated as an example for the use of simulation mode of the code. INTRODUCTION The analysis summarized in this paper is oriented towards developing a design code requiring a mathematical model for the MSF distillation process which is schematically illustrated in Fig. 1.
.------_-______ ___-__-__________--_______ -~ ,~--------------_-_--_--------________ ..____- _._.._. _-I,
E;
&=__
Fig. 1.
=$$,ygg x-
TzE=-q
:a
gzfz,EEy (N4
_______ _ ____ ____________________ ______ _--___-______-____-__-_-___-_--__-__--___ .f'wm -*ncr-L&r
Schematic Diagram
OOll-9164/63/$03.00
for
the
ii
JJ
MSF distillation process.
CD1963 Elsevier 6cience! PubliaberclB.V.
66 The development of simulation program for this system requires analysis of the various components shown in the figure to obtain the desired information for the basic process streams. The system consists of N stages of which M are rejection stages and (N-M) are recovery stages, a mixing stage (N+l), a recycling pump (N+2), a splitter (N+3), feed water, brine recycle, flashing brine, blow down, distilled water and the heater (N+4) streams etc. FORMULATION OF MATHEMATICAL MODEL The desired model relationships consist of standard chemical These are: Material balances, Energy
engineering relationships.
balances, Momentum balances, Kinetic relationships, Equilibrium relationships and Control relationships (ref. 4). Typical Stage Analysis Typical stage variables and parameters are indicated on the actual stage as shown in Fig. 2. A set of mathematical relationships for each stage may be represented in a box manner
Fig. 2
as
Typical MSF Stage Variables
follows:INPUT STREAM VARIABLES
MODEL OF PROCESS STAGE b I STAGE PARAMETERS
OUTPUT STREAM VARIABLES
67 in mathematical
Input
Stream
stream
Each
stream
= f (output stream variables, stage parameters)
is defined
we have
Mass
(dependent)
variable
As shown
on several
condenser
bundle
(
A”i)
-
A’i
= Ti' - BPEi
The experimental the major
use a certain
losses
losses
losses,
(tl) can
which
cause
are the non-equilibrium
through
the demisters
boiling
point
and elevation
losses
stage
there
of four independent
twelve
independent
stage.
The basic
are three
equations
(top), the distilled stream
designers for the
for the
on the results.
will
it can be seen
streams three
each consisting
streams
variables.
be needed
to fully
leave the Therefore describe
are the tube side cooling
water
stream
(middle)
that
a
brine
and the flashing
(bottom).
The formulated which
incoming Another
streams
to account influence
and Fig.2,
of four independent
stage
to account
Equations
analysis
variables.
each consisting
used
are of prime
(ref. 5) indi-
Some MSF plant
allowance
The methods
losses
of researches
Ali.
affecting
and Subsidiary
the typical stage,
(1)
correction
(ref. 6).
Fundamental
for each
A’li from a number
temperature
thermodynamic
From
-
data
various
tities
side temperature
and the classical
parameters
various
brine
One desired
; thus:-
(BPEji
stream
vapour
thermodynamic
(i), these
stage
the pressure
stage
(T or t)OF,
(P or p)psia.
effects.
( ki),
Staqe
Temperature
for
these
(H or h) BTU/lb.
2, the stage
based
For typical
cates
where
variables:
Relationship
allowance
ti
variables
(independent)
and Pressure
is enthalpy
in Fig.
be calculated
of the basic
(M or m) lb/hr,
(C)% solid
Equilibrium
subcooling
in terms
four fundamental
flow rate
Concentration
Stage
variables
as:-
Definition
each stream are:
this can be expressed
terms;
basic
twelve
are dependent
equations
on the stage
(ref.1) include variables
some quan-
and these quanti-
ties can be expressed'by means of set of independent (subsidiary) equations.
Variables other than fundamental variables previously
defined must be specified or fixed in order to achieve consistent solution to the problem. Brine Heater Analysis Similar analysis can be done to the brine heater model (Fig. 3) (ref.1) resulting in another eight basic equations describing the brine heater and its related streams.
STAGE
(1)
BRINE
HEATER
4
CONDENSATE
mC.tC.c~,pc,hC
co.
P. Ii.
Fig. 3.
-
Brine Heater and First Stage Variables.
GENERAL SYSTEM ANALYSIS When the overall system has been synthesized into a set of mathematical relationships, the consistent solution to the design problem of the system can only be obtained if the total number of variables match the number of developed equations. Total Streams Counting the total number of streams in Figs. 1 & 2 can be summarized in Table l:-
69
Table 1 Counting Total No. of System Streams VP=
Inter-stage st*eams
0.
0
Identification
stre*ms 3(N-2)
3 streams
for
inter-stage Stage
terminals
stream 6,
Mixer
(N*l)
Pump (N*Z)
Splitter Heater
(N+3) (N+4)
7,
Total
1,
2,
12 and
nos. 9 and
stream
11 and
already
included
strellm
nos.
stream
nos.
addition
already
i.e.
nos. 10,
stream
in
Total
(N-2)
partition 3,
4,
5
13 11
4
8 14 and to
15
12 and
13
included
3N+9
Total Number of Streams
=
3N+9
(2)
Variables
Once the total number of streams is known, the number of variables can be calculated.
We have four independent variables for each stream and in addition an arbitrary chosen number of heat rejection stages (M) and total number of stages (N) as two independ-
ent variables.
Therefore:-
Total Number of Variables
=
(3N+9).(4)+2
=
12N + 38
(3)
TotalEquations Based on the desired fundamental equations for the various system components, the total number of independent equations is given in Table 2:-
70
Table 2 Counting Total No. of
0.
Component
Equations
0
comment
equations
N stages
We have 12 fundamental equations/stage
Mixer (N+l)
4
Pump (N+Z)
4
Splitter (N+3)
8
Brine heater (N+4)
8
Total
i.e.
Previously derived
ltN+24
Total no. of equations
=
12N + 24
(4)
Check for consistency Comparing equations
(3) and (4), it can be seen that the number
of variables exceeds the number of equations by fourteen.
This difference implies specification of fourteen variables to permit consistent solution of the problem.
Variables to be specified The fourteen variables to be specified are chosen based on the analysis of the system guided by Fig. 1 as follows:Feed. variables 1.
F
:
fresh sea water cooling water flow
2.
TF
:
fresh sea water inlet temperature
3. 4.
cs : PF or VF :
lb/hr OF
sea water salt concentration
% salt
sea water inlet pressure (or velocity)
psia
71 General boundary conditions D
:
plant distillate production
lb/hr
6.
CD
:
distillate production purity
% salt
7.
CR
:
(recycle concentration ratio). This fixed the overall salt balance in the system by fixing the maximum allowable salt concentration into the brine heater (CO) as
5.
CO = CS. CR and since CS is also specified, therefore CO is fixed. 8.
:
To
maximum brine temperature OF. this is bound by the total enthalpy balance for the system or the control relationship at the brine heater.
Brine heater boundary conditions 9.
:
Ts
10.
Ps
11.
cs
12.
or C
MS
C
steam temperature to brine heater
OF
:
steam pressure to brine heater
psia
:
purity of steam or condensate
% salt
:
steam flow to brine heater
lb/hr
:
heat input to brine heater (fixed by performance ratio)
BTU/hr
or 'B.H.
Number of stages 13.
M
:
number of heat rejection stages
14.
N
:
total number of stages
Thus by specifying these parameters and the additional specific variables, appearing in the subsidiary equations or needed for physical property calculation, a consistent solution can be achieved. For example, parameters such as fouling factors, tube diameter, thickness and material etc. can be arbitrarily fixed by designer.
SALINE WATER EVAPORATOR DESIGN CODE "SWEDC" The mathematical model is translated into a Fortran IV computer code "SWEDC" for the design or simulation of MSF desalination plants with the aid of an IBM 370 machine.
72 The problem solved by this code is basically the calculation of heat and mass balance in the MSF evaporator by a stage-to-stage method, in addition to the design of the process equipment.
The
design is based upon the specified basic information referred to as input parameters.
The program results or output will consist of
the various calculated process parameters including condenser surface area of the various plant sections, process pump heads, basic stream flow rates etc. information is also provided.
Comprehensive stage-by-stage process The general algorithm that is used
in the program is shown in Fig. 4.
Fig. 4
General flow process diagram for "SWEDC"
Convergence of solution is based upon a thermodynamically feasible solution.
No cost bases are involved in this study.
The
specific design information and initializing values are read in with the input data to obtain the first or approximate solution. Adjustment of variables is then made and calculations are repeated until the convergent solution is reached. The code application to various desalination plant designs showed excellent results (ref.1). The original plant specifications as contracted between purchaser and consultant were considered as
73 inputs, while the outputs were compared with the detailed design information as supplied by the desalination project contractor. SIMULATION OF ACTUAL MSF PLANTS Four actual plant designs are simulated: Al-Jubail Phase-I and Al-Khobar Phase-II which are low temp. (90°C maximum) and Al-Khobar Phase-I and Fichtner Reference Plant (ref. 6) which are high temp. (Note that Al-Khobar Phase-II has also been (12OOC maximum). specified for high temperature operation). In terms of production capacity the low temperature plants are approximately twice that of the high temperature ones, the former having a production capacity of 5 MIGD. Prediction of thermodynamic losses criteria As the original designers consider the information on thermodynamic losses particularly proprietory, to circumvent this problem the program was run for the several known correlations (ref.5), and the design obtained closest to the original chosen as most priate.
appro-
The accuracy comparison indicated that the agreement is
within 2% and is in general much better than that.
It is not
intended in this paper to discuss these simulations with their lengthy input-output details, however a typical application of the code can be shown for the simulation of Al-Khobar Phase-I Operation,
Al-Khobar Phase-I plant operation simulation From the simulation calculations for Al-Khobar Phase-I operating since 1974, it is concluded that the original plant production 2.5 MGD/Unit cannot be obtained for the following reasons:The first reason is that the difference between the actual sea water salinity (56,000 ppm) and that reported by the project consultant (50,000 ppm) limits the plant production to only 87% of the original capacity due to the accompanying limitations on the maximum brine temperature to avoid CaS04 scaling. The second reason is the influence of the design sea water temperature on the plant productivity.
A sea water temperature of 35OC (95OF) is considered more practical assumption for design purpose reflecting the updated trends in the newly built desalination plants on the Arabian Gulf shores.
It is predicted that this assumption causes a further drop in the expected production for the
74
desalination units of Al-Khobar Phase-I plant (plant designer's assumption is 29.4'C) as shown in Table 3.
Table
3
Effect of Sea Water Temperature on Production for Original Desiqn
Al-Khobar (I) Plant Original Design Conditions TSEA
TFBO -
244’F
CSEA
50.0
30.0
1 wd
PRODI
% age
GPD(U.S)
lb/hr
i
00
icTION
I
29.4
-
output
100%
85.0
865,867
2.50
86.0
858.632
2.479
99.16%
87.8
852,662
2.462
98.47%
89.6
846,736
2.445
97.80%
836,305
2.415
96.59%
830,492
2.398
95.91%
824,720
2.381
95.25%
I
The net effect of these two reasons when combined together indicates that the predicted evaporator unit production will be approximately 83.72% of the original capacity for plant operating at 56,000 ppm sea water salinity and at the severe summer condition sea water temperature of 35OC (95OF) (Table 4). Table
4
Effect of Sea Water Temperature on Production for Modified Conditions ’ Al-Khobsr (I) Modified Conditions
I
TSEA L
f
Plant
Design -I-
PRODUCTION
0,
lb/hr
85.0
767,187
86.0 87.8
1 I
GPD(U.S)
1
% age
output
2.2077
85.31%
760,415
2.1882
87.53%
755,129
2.1730
86.921
89.6
742,709
2.1373
a5.49a
91.4
737,546
2.1224
89.90%
93.2
732,419
2.1077
84.31%
95.0
727.328
2.0930
83.72%
76
These are represented in Fig. 5.
Fig.
5.
Al-Khobar-I Production as Function of Sea Water Temperature
REFERENCES A.M. Omar, 'Simulation of MSF Desalination Plants', M.Sc.Thesis, D.P.M., Dhahran, Saudi Arabia (1981). R.J. Easterday, 'FLASH : An IBM-7000 Code for Computing MSF Plant Designs for the Desalination of Sea Water', ORNL TM-124 (1965). C.T. Mothershed, 'OROSEF : A Fortran Code for Overall Design of the MSF Desalination Plant', ORNL TM-1627 (1966). K.F. Loughlin, 'Mathematical Model and Simulation of a Chemical Process' ,Lecture notes prepared for the Course on Separation Processes : Theory and Practice, presented at U.P.M. Dhahran, Saudi Arabia (1980). N. Lior, 'A Review of'Equations Used to Calculate Non-Equilibrium Allowance in Flash Evaporators', University of Pennsylvania, Mech. Eng. Dept. (1979). H.E. Homig, 'Sea Water and Sea Water Distillation', Fichtner Handbook, Vulkan Verlay, Essen (1978).
'76 RESUME Ein simulation program fiirMSF entsalzung anlagen model ist beschrieben (ref.1). Dieser program kann man benutzen sum design order simulate anlagen die sind schon in betrieb. Komputer programmen fiir eigene benutzung sind bei entsalzungsanlagen designers gemacht von dieser programme sind nur wentage veroffentlicht (refs.2 & 3). In dieser arbeit ist die design u modeling philosophy fiirdie program beschrieben. Als beispiel zum benutzung die simulation mode von code, Phase-I MSF Alkhobar (Saudi Arabia) entsalzungsanlage ist ausgewahlt.
EXTRAIT
Un programnede simulationD'une installation de dessalement"Multiflash" a ete mis au point par auteur ( Ref.1 ). Le progranmepeut etre utilise,soit pour calculer,soit pouk simulerle fonctionnement D'une installation. De nombreuxprogranmesont ete treespar les bureauxD'etudesconcevant de tellesusines,et sont leur proprietereservea leur propreusage. Quelquesun seulement,D'orpregeneral,ont ete publies (ref2 et 3) Le rapportdecrit la philosophieDu model de calculutilisedans la mise au point du progranme. Conne example,une applicationa l'usinede dessalement D'al Khobar (PhaseI) illustre/brievenent l'utilisation de la methodede simulation.