1

THE SCALING OF TUBES IN MSF EVAPORATORS: THE HISTORY, THE WEAPONS AGAINST IT AND THE NEW TRENDS Author:

E. Ghiazza (Fisia Italimpianti)

ABSTRACT: The accumulation of heat resistive deposits inside MSF evaporator tube bundles, deriving from scaling and fouling, significantly reduces plant thermal efficiency up to 25% and more, thus resulting in increased steam requirements to maintain the same distillate production rate. Furthermore fouling contributes to tube corrosion and failure, badly affecting maintenance costs and overall plant life. Weapons against scaling and fouling are of chemical or physical type, both on-line and off-line. The optimum combination of them should minimise costs, time and environmental impacts, whilst being not labour intensive or hazardous to workers. The paper presents an extensive overview of the results of scale control through 20 years of MSF evaporators operational experience with different combination of the above mentioned methods. On the basis of a long experience, it is shown how best results have been achieved by the regular application of sponge ball cleaning as an integral part of the overall chemical dosing and process control system to maintain condenser tubes status near optimum. A final discussion about new accurate fouling factor evaluation algorithms on the basis of plants feedback data is also presented, together with possible future influences on MSF design optimisation.

INDEX 1. INTRODUCTION 2 2. SCALING PHENOMENA 2

2.1. Nature and causes 2 2.2. Problems caused by the fouling 3

3. WEAPONS AGAINST IT 3 3.1. Measures for prevention of solid deposits 3 3.2. Measures to remove solid deposits 3 3.3. The optimal combination 4

4. THE FOULING BEHAVIOUR 4 4.1. Methods for fouling factor evaluation 4 4.2. Time based fouling recording 6

5. NEW TRENDS AND CONCLUSIONS 7 6. Appendix A 9

FIGURES INDEX Figure 1: Typical Performance Ratio decline with fouling 4 Figure 2: Relationship between performance ratio and recovery section fouling factor 5 Figure 3: Fouling behaviour vs. time 6 Figure 4 Actual fouling factor from plants feedback data 7

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1. INTRODUCTION

The accumulation of any heat resistive deposits within the heat transfer tube bundles of an MSF evaporator system will readily reduce plant thermal efficiency and result in increased steam requirements to maintain a set distillate production rate. Scale formation, hindering heat transfer process, increases operating costs and causes frequent shut down of the plant for cleaning.

At present time the most widely used method to control scale is by the addition of chemicals additives (antiscalants) combined with a continuous application of sponge ball cleaning system.

These combined actions allow reaching very satisfactory results and feed back data from plants running since long times are very comforting. This leads to the firm belief that future improvements on MSF design are possible through a heat transfer surface optimisation.

2. SCALING PHENOMENA

2.1. Nature and causes

In most of the cases, scale process starts from a super saturation situation, proceeds with a nucleation and a crystal growth up to the final phase of scale precipitation or crystallisation. The rate of scale formation is usually influenced by temperature, pH, concentration of ions (e.g. HCO3

-,

Ca2+, Mg2+), rate of CO2 release, total dissolved solids.

Fouling occurring in desalination units may have different origin (from scale, from corrosion, biological), and can consist in chemical reaction products deposits (alkaline scales, and non-alkaline scale), or in particulate deposits (silt).

The main kinds of scales taking place can be summarised as follows:

Alkaline scales: Calcium carbonate is the major scale formed in seawater at temperatures up to 90°C, whereas magnesium hydroxide is formed at temperatures above 95-100°C. Both compounds have an inverse solubility, decreasing with increasing temperature, and are almost inevitable in seawater thermal evaporators. They generate during periods of chemicals under dosing and/or over-concentration of brine. Since the surface of heat exchangers normally has a higher temperature that the surrounding liquid it is preferentially sought out by deposits.

Non-alkaline scales: Calcium sulphate forms hard, tenacious deposits. Being this compound significantly more soluble than calcium carbonate, deposits will form only in supersaturated sea water, when its solubility is exceeded at high concentration factors (1.8-2.0) and temperatures above 110-120°C.

Particulate deposits: fouling by fine silt can occur especially when the seabed is disturbed during rough sea condition, dredging activities, and generally when suspended solids content increases. The silt can also combine with calcium carbonate and/or magnesium hydroxides forming mixed scales and can absorb antiscalant additives, hence reducing the concentration of the additive in the bulk solution.

Other: chemical compounds (iron oxides and hydroxides) taking origin from corrosion of unprotected steel flash chamber floors, walls or piping as consequence of over-acidification, deposits related to high pollution levels (calcium phosphate), plus trapped, or agglomerated suspended matter such as silica and an infinitive variety of biological organism, sludge (calcium orthophosphate) generating in case of over-dosing of polyphosphate-based additives.

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2.2. Problems caused by the fouling

The presence of scaling directly involves the following effects:

formation of insulating film, that constitutes an additional resistance to heat transfer, thus resulting in a reduction of plant thermal efficiency;

narrowing of passageways, that means either a flow rate reduction for the higher head loss in the tubes or an increasing in energy consumption to keep the same flow rate;

risk of corrosion under deposits, with the consequent risk of pitting priming.

3. WEAPONS AGAINST IT

Efforts to fight with fouling may be aimed to prevent all the possible scaling phenomena from taking place or to remove the scales once they are formed.

In the first case the weapons used are chemistry based (namely acid treatment or antiscalants dosing), while in the second one they may be chemistry based (acid cleaning) or mechanical (physical removal by means of sponge ball).

3.1. Measures for prevention of solid deposits

To prevent the formation of solid deposits when seawater is heated, the following measures can be adopted:

Avoidance of temperature and concentration ranges in which solid phase can form.

Partial or complete removal of solution components which may form solid deposits (acid treatment). This method is effective, but has many drawbacks, since involves the addition of acid, which is hazardous and can give rise to corrosion problems. Moreover an additional equipment (decarbonator) is required to remove the large volumes of CO2 released.

Inhibition of crystal growth by means of specific chemical additives. The first ones used in MSF plants are polyphosphates, abandoned later on since polyphosphates thermal stability declines rapidly above 90°C. Nowadays the most used antiscalants are polymeric compounds.

3.2. Measures to remove solid deposits

Once scaling is formed actions must be taken to remove it, and the methods employed are the following:

Mechanical cleaning, (sponge ball cleaning system): this on-line method removes any soft scales, even formed in presence of additives, deposited on the heat transfer surface.

Chemical cleaning (acid cleaning): this off-line method consists in circulating an acid solution inside the heat exchangers tubes. The solution flow is selected to maintain a proper velocity inside the tubes, and the acid dosing keeps an appropriate pH value of the solution. The acid consumption accounts for the quantity necessary to dissolve scales and to neutralise sea water alkalinity.

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3.3. The optimal combination

After a very long experience on several desalination plants, coming to an end, the best possible operation is the use of high temperature improved antiscalants together with the use of ball cleaning system at a relatively high cycle frequency. This way of operating definitely prevents from tube sheet and tubes clogging, allows to reduce additive dosage, lowers heat consumption and substantially reduces tubes corrosion. Moreover, allowing an almost complete elimination of manual and /or off line cleaning, it leads to very high plants availability.

In fig. 1 the advantages achieved by means of the continuous use of improved antiscale plus sponge ball cleaning system in terms of both plant availability and energy saving are summarised.

In fact, typical performance ratio very quick decline (curve C) causes the need for acid cleaning after very short periods of plant operation (about 4 months), to bring back the performance ratio (curve D) above the design figure. The continuous use of improved antiscale + sponge ball cleaning system (curve E) allows, on the contrary, an extended operation keeping the performance ratio near to the one characteristic of the clean plant (curve A) and usually far above the design figure (curve B).

Figure 1: Typical Performance Ratio decline with fouling

4. THE FOULING BEHAVIOUR

4.1. Methods for fouling factor evaluation

Unfortunately, fouling is not a directly measurable variable, hence in order to estimate tubes scaling in a running plant it is necessary to infer it in some way from field data. Since measurements are

PERFORMANCE RATIO DECLINE WITH FOULING

A

B

C

E

D

332,3

244,8

258,4

273,6

290,8

310,1

7

7,5

8

8,5

9

9,5

0 2 4 6 8 10 12Operating Time [Months]

Perf

orm

ance

ratio

[kgd

ist/2

326k

J]

Spec

ific

Hea

t Con

sum

p. [k

J/kg

dis

t]

A: Completely clean plant B: Design performance ratio C: Typical decline by tube fouling E: P.R. with continuous spongeball cleaning D: Off load acid cleaning

5

often unreliable, we have to choose a stable and valid reference parameter to rely on. The plant performance ratio, easily deducible from distillate production, condensate extraction flow and temperature measurements, seems to be a suitable figure for this purpose due to the higher accuracy of the measurements involved in its calculation and to the remarkable effect fouling has on it. In this respect, all heat exchange surfaces (brine heater, heat reject, heat recovery) are in principle involved, but not all of them can be related to plant performance ratio.

As brine heater tubes fouling increases, equilibrium condition in the exchanger will become different to account for a reduced heat transfer coefficient, leading, to keep the same brine temperature increase, to an increase of LMTD, and thus of condensation temperature. This effect only slightly affects steam consumption, and the influence on plant performance ratio is negligible.

This concept also applies to the heat reject section, since the fouling increase in this section would result only in a blow down temperature increase, again only slightly influencing distillate production rate or steam consumption.

On the contrary, as the fouling in heat recovery stages increases, exchange phenomena in this section will worsen leading to a brine temperature at brine heater inlet reduction. This would cause a top brine temperature (and consequently distillate production) quick decline. To keep the same top brine temperature (since this is the controlled variable fixed by distillate production demand) it follows that a larger amount of steam will be required, thus directly bad affecting performance ratio.

For what above said, only heat recovery section fouling factor significantly affects plant performance, so our efforts will concentrate on it as a representative index for plant performance monitoring.

To calculate the recovery fouling from performance ratio data, it is possible to build up a set of curves of fouling versus performance ratio for several different plants, as shown in fig. 2.

These curves, based on plant heat & mass balances data, are built up by means of several computer runs carried at nominal condition (the same used during plants performance tests), with different percentages of design fouling factor. The resulting data are then interpolated to obtain the best fitting continuous curve describing the plants behaviour, with lower fouling corresponding to higher performance ratio, at the same reference running condition.

Figure 2: Relationship between performance ratio and recovery section fouling factor

Plant 1

Plant 2

Plant 3

Plant 4

0,00

0,02

0,04

0,06

0,08

0,10

0,12

0,14

0,16

0,18

0,207,0 7,5 8,0 8,5 9,0 9,5 10,0

performance ratio [kg/2326kJ]

reco

very

sec

tion

foul

ing

[m2 °C

/kW

]

6

4.2. Time based fouling recording

The curves in fig. 2 allow only to evaluate punctually plant fouling from the feedback data of a running plant. In addition to that it is necessary to build up a couple of curves describing the fouling assessment with time (see fig. 3). The first of these curves, built to cross 0 at the beginning and to cross the design figure for fouling factor after a given time, represents the theoretical trend of fouling vs. time. In addition to the theoretical curve it is possible to build up a curve from feed back data after a certain number of running hours. This second curve, crossing again 0 at the beginning and interpolating the feed back data at the various measurement times, represents the expected trend of fouling vs. time, allowing a prediction of plant behaviour after a certain running time, knowing the plant behaviour at present time.

Both curves have a typical quick initial increase and will be later flat, considering the continuous use of sponge ball cleaning system. The main highlight arising from the comparison of these two curves, describing the actual expected plant behaviour as time goes by, is that the expected trend is always considerably lower than the theoretical one, as shown in the following chapter.

For more details about these curves see Appendix A.

Figure 3: Fouling behaviour vs. time

Desalination Unit fouling condition assessment curve

800070006000500040003000200010000 9000 10000 11000 12000 13000 14000 15000 16000 17000 18000 19000 20000

b

a

0,00

0,05

0,10

0,15

0,20

0,25

time [hours]

reco

very

foul

ing

fact

or [m

2 °C/k

W]

6,8 7,0 7,2 7,4 7,6 7,8 8,0 8,2 8,4 8,6 8,8 9,0 9,2 9,4 9,6 9,8 10,0 10,2 10,4 10,6 10,8

evaporator unit performance ratio [kg/2326kJ]

c

theoretical fouling (design) after running hoursforeseen before acid cleaning

expected fouling after running hours foreseen before acid cleaning

a. actual P.R. valueb. actual plant running hoursc. actual fouling factor value-----------------------------------------------e. plant running hours before a.c.f. expected P.R. value before a.c.

e

f

7

5. NEW TRENDS AND CONCLUSIONS

From the review of different plants feedback data, a rich data base has been created in order to better understand the plants behaviour through their whole operating life.

Extracting from this data base the figures necessary to calculate the desalination units performance ratio, and applying the procedure written above, it has been possible to plot the fouling trend for several plants in the periods between two subsequent acid cleanings.

The results for three units, quite different as far as capacity, materials, design performance ratio, ambient conditions are concerned, are shown in fig. 4.

From the diagram, as a matter of fact, the following two basic issues clearly appear:

1. not depending on the specific plant, the fouling behaviour is the same, settling to an approximately constant value after a relatively short number of running hours.

2. The asymptotic value of the fouling is always remarkably lower than the corresponding design value.

It must be noted that all the reported data refer to desalination units where the ball cleaning system was kept in almost continuous operation, coupled with a proper dosage of improved chemicals for scale prevention, which is, according to our experience, the best way to operate desalination plants

.

Figure 4 Actual fouling factor from plants feedback data

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 2000 4000 6000 8000 10000 12000

Plant running hours

% o

f sta

ndar

d de

sign

foul

ing

8

This leads to the following conclusions:

• The common fouling factor values still used nowadays in the design of desalination units date back to several years ago, when antiscalants were poorly effective and the ball cleaning systems were still not available, or used at very low frequencies. Today these values appear to be extremely overestimated with respect to the real ones.

• As a consequence, the design of desalination plants is far from being optimised, since the actual steam and condensate flows result to be in the reality much lower than the expected ones. This leads to the over sizing of several parts of the desalination units (piping, equipment, etc.), and to a non-optimised link between the water production and power production plants.

It would be advisable to take into consideration these new trends for the design of the future plants, since the confidence in reaching the desired performances together with the best possible knowledge of the margins you keep when carrying out a design are among the key parameters for a real design optimisation.

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6. Appendix A

A good agreement has been found interpolating the fouling data vs. time with curves corresponding to the following equations:

21θθθ

+⋅

= ∞ffff

where:

ff actual fouling [m2°C/kW]

ff∝ asymptotic fouling [m2°C/kW]

θ actual time [h]

θ1/ 2 characteristic time [h]

The asymptotic fouling represents the settling value of this variable, while the characteristic time represents the number of hours necessary to reach 50% of the fouling asymptotic value.

The shape of this curve fits both the theoretical and the expected one.

For the theoretical curve the value of ff∝ is fixed by the constraint that after the number of hours theoretically foreseen before an acid cleaning the fouling must reach the design value, while the value of θ1/ 2 is chosen according to experience.

For the expected curve the value of ff∝ and θ1/ 2 are fixed by the two values of fouling measured at the actual time and expected after the number of hours theoretically foreseen before an acid cleaning. This last value can be estimated from the actual one according to the following formula:

−⋅

+⋅+= 11

1

exp ηη

θθ

ηT

n

ACD

baff

where:

a,b parameters of fouling vs. performance ratio curves in fig. 2 (ff = a+b/η)

ffexp expected fouling before acid cleaning [m2°C/kW]

θ actual time [h]

θAC time before acid cleaning [h]

ηD design performance ratio [kg/2326kJ]

ηT theoretical performance ratio [kg/2326kJ]

η actual performance ratio [kg/2326kJ]

n empirical exponent [-]

EUROPEAN SCIENCE FOUNDATION

“Scaling in Sea Water Desalination:

Is molecular modeling the tool to overcome the

problem ?” Lutherstadt Wittenberg, Germany

April 26th –27th, 2001

1

THE SCALING OF TUBES IN

MSF EVAPORATORS:

the history, the weapons against it

and the new trends

E. Ghiazza - Fisia Italimpianti

2

Types of fouling in

desalination plants

FOULING

BIOLOGICAL CORROSION SCALE

PARTICULATE CHEMICAL

•Silt •Calcium carbonate

•Magnesium hydroxide

•Calcium sulphate

3

Problems caused by scale

SCALING

Possibility of

corrosion

under deposits

Narrowing of

passageways Insulating film

Flow rate reduction

Energy consumption increasing

Heat transfer

reduction Pitting

4

Prevention of solid deposits

Avoidance of risky

temperature and

concentration ranges

Removal of risky components

(acid treatment)

Inhibition of crystal growth

(chemical additives)

hazardous

corrosion risk

high CO2 release

ok non-alkaline

costly

n.a. for alkaline

5

Removal of solid deposits

• Mechanical cleaning

SPONGEBALL CLEANING

SYSTEM

(on line)

• Chemical cleaning

ACID CLEANING SYSTEM

(off line)

6

The optimal combination

PERFORMANCE RATIO DECLINE WITH FOULING

A

B

C

E

D

332,3

244,8

258,4

273,6

290,8

310,1

7

7,5

8

8,5

9

9,5

0 2 4 6 8 10 12

Operating Time [Months]

Perf

orm

an

ce r

ati

o [

kg

dis

t/2326kJ]

Sp

ecif

ic H

eat

Co

nsu

mp

. [k

J/k

g d

ist]

A: Completely clean plant B: Design performance ratio

C: Typical decline by tube fouling E: P.R. with continuous spongeball cleaning

D: Off load acid cleaning

7

Experience Results

high temperature improved antiscalants +

continuous ball cleaning system

• clogging prevention

• additive dosage reduction

• heat consumption lowering

• tube corrosion reduction

•high plants availability

8

Fouling Evaluation

Heat Recovery Section Fouling

Factor =

Monitoring Index

Set of Fouling factor Curves vs.

Performance Ratio by fitting the results of different computer runs

Performance Ratio =

Reliable Indirect Parameter

9

Fouling vs Performance Ratio

Plant 1

Plant 2

Plant 3

Plant 4

0,00

0,02

0,04

0,06

0,08

0,10

0,12

0,14

0,16

0,18

0,20

7,0 7,5 8,0 8,5 9,0 9,5 10,0

performance ratio [kg/2326kJ]re

co

ve

ry s

ec

tio

n f

ou

lin

g [

m2°C

/kW

]

10

Fouling Assessment

curves describing fouling trend vs. time

together with fouling evaluation

from feedback data

Theoretical (design figure)

Expected (feed back data fitting)

11

Time Based Fouling Recording Desalination Unit fouling condition assessment curve

800070006000500040003000200010000 9000 10000 11000 12000 13000 14000 15000 16000 17000 18000 19000 20000

b

a

0,00

0,05

0,10

0,15

0,20

0,25

time [hours]

reco

ve

ry f

ou

ling

fa

cto

r [m

2°C

/kW

]

6,8 7,0 7,2 7,4 7,6 7,8 8,0 8,2 8,4 8,6 8,8 9,0 9,2 9,4 9,6 9,8 10,0 10,2 10,4 10,6 10,8

evaporator unit performance ratio [kg/2326kJ]

c

theoretical fouling (design)

after running hours

foreseen before acid cleaning

expected fouling

after running hours

foreseen before acid

cleaning

a. actual P.R. value

b. actual plant running hours

c. actual fouling factor value

-----------------------------------------------

e. plant running hours before a.c.

f. expected P.R. value before a.c.

e

f

12

Different Plants Review

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0 2000 4000 6000 8000 10000 12000

Plant running hours

% o

f sta

nd

ard

desig

n f

ou

lin

g

(based on Fisia Italimpianti experience in MSF Deaslination since 1970)

13

CONCLUSIONS

Fouling behavior :

• not depending on the specific

plant (capacity, p.r., ..)

• settling to almost constant value

after relative short number of

running hours

• asymptotic value always

remarkably lower than the

design

14

New Trends

Standard f.f. values

(overestimated)

Actual f.f. values

Optimized Desalination Plant

Design