DOI: 10.3303/CET2290015 
 

 
 

 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 

 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 

Paper Received: 20 November 2021; Revised: 17 March 2022; Accepted: 22 April 2022 
Please cite this article as: Fuchino T., Kitajima T., Shimada Y., Miyazawa M., 2022, Development for Prediction Model for Environmental Condition 
of Deterioration Phenomena for Asset Integrity Management, Chemical Engineering Transactions, 90, 85-90  DOI:10.3303/CET2290015 

CHEMICAL ENGINEERING TRANSACTIONS 

VOL. 90, 2022

A publication of 

The Italian Association 
of Chemical Engineering 
Online at www.cetjournal.it 

Guest Editors: Aleš Bernatík, Bruno Fabiano
Copyright © 2022, AIDIC Servizi S.r.l.
ISBN 978-88-95608-88-4; ISSN 2283-9216 

Development for Prediction Model for Environmental 
Condition of Deterioration Phenomena for Asset Integrity 

Management 
Tetsuo Fuchinoa,*, Teiji Kitajimab, Yukiyasu Shimadac, Masazumi Miyazawad
a Tokyo Institute of Technology, 2-12-1 O-okayama, Meguro, Tokyo, Japan
b Tokyo University of Agriculture and Technology, 2-24-16 Naka-cho, Koganei-shi, Tokyo, Japan 
c National Institute of Occupational Safety and Health, Japana, 1-4-6, Umezono, Kiyose, Tokyo Japan 
d Best Materia Corporation, 2-43-15, Misawa, Hino-shi, Tokyo, Japan 
fuchino@chemeng.titech.ac.jp

The occurrence and progress of a deterioration phenomenon in a chemical plant is determined by the 
construction material, the plant physical structure and the physical and chemical environmental condition. In
order to ensure and maintain the reliability of the facility during operation, the environmental condition such as
the concentration of the deterioration substances at the deterioration site should be managed. In this study, we 
propose an approach to develop a prediction model for physical and chemical environmental condition of
deterioration phenomena consistent with the plant operation. The prediction model is composed of the three 
layers; the process information management layer, the process bulk simulation layer, and the microscopic 
environmental condition prediction layer. By integrating abovementioned three layers based on the observability
and measurable nature of the interfacial variables, it becomes possible to synthesize multi-scale simulation- 
based environment to predict the environmental condition of deterioration phenomena.

1. Introduction
In these days, once a serious incident occurs, it may affect the sustainability of the business, so it is required to 
ensure and maintain the reliability of facilities in the chemical industry. The reliability of a facility is influenced by 
the deteriorations accompanying the operation. In order to ensure and maintain the reliability of the facility, the 
physical and chemical environmental condition such as the concentration of the deterioration substances at the 
deterioration site is to be managed. The environmental condition has been monitored by a limited number of 
sampling, so far. Originally, monitoring the environmental condition by sampling is an observation method for
trend management on the assumption that the process operating condition does not change greatly. However,
the operation is often forced to be changed greatly according to the market situation under the today’s mega
competitive situation. Thus, the sampling-based condition monitoring up to now is insufficient to manage asset 
integrity under today’s change environment.
To overcome the above-mentioned problem, the prediction model for physical and chemical environmental 
condition of deterioration phenomena consistent with the plant operation is indispensable. In general, a 
deterioration phenomenon of a chemical plant occurs in a microscopic region, and the chemical and physical 
environmental condition is behaved within such a microscopic region. This microscopic behaviour is governed
by the overall bulk fluid condition of the corresponding deteriorated equipment module and the bulk fluid
condition are dominated by the process overall operation. Therefore, the prediction model for physical and
chemical environmental condition should be composed of the three layers; the process information management 
layer correcting and providing the operation data, the process bulk simulation layer estimating the unmeasurable 
bulk fluid conditions in the corresponding equipment module from the operating data, and the microscopic 
environmental condition prediction layer. In this study, the phenomena leading to microscopic corrosion 
environmental conditions and their causal events are expressed as hierarchical causal relationships. By 
integrating abovementioned three layers based on the observability and measurable nature of these causal 

85



events, it becomes possible to synthesize multi-scale environment to predict the environmental condition of 
deterioration phenomena. 

2. Example of NH4HS Corrosion in HDS process 
In this study, development of an environmental condition prediction model is considered by using a case study 
of the ammonium bisulfide (NH4HS) corrosion in the hydrodesulphurization (HDS) process. 

2.1 HDS Process 

Figure 1 shows a block flow diagram of the HDS process, which represents the HDS plant providing the 
operation data, here. The diesel fraction containing nitrogen and sulphur components from the battery limit is 
fed through the “D-201: Feed Surge Drum” and pressurized by the “P-201A/B: Feed Pump”. After mixed with 
hydrogen, it is preheated by the E-201, E-203: Reactor Feed/Effluent Exchangers” and further heated up to the 
predetermined temperature by the “H-201: Reactor Charge Heater”. In the “R-201: Reactor”, the sulphur hydro-
desulphurization reaction (e.g.; RS-R+H2=2R+H2S(g)), nitrogen hydro-denitrogenation reaction (e.g.; 
R’N=R’+3/2H2=R+R’+NH3(g)) and decomposition reactions occur. The reactor effluent containing H2S and NH3 
equivalent to sulphur and nitrogen in the “Feed Diesel Fraction” is heat recovered by the “E-203, E-201: Reactor 
Feed/Effluent Exchangers” and “E-202: Stripper Reboiler”, and furthermore is cooled to about 40 C in “C-204: 
Reactor Effluent Condenser (Air Fin Cooler)”. In the low temperature section of “C-204”, H2S(g) and NH3(g) 
react to form NH4SH(s), which can cause under-deposit corrosion and blockage. To prevent forming of 
NH4SH(s), sour condensate is injected at inlet of “C-204” to decreasing partial pressure of H2S(g) and NH3(g). 
this blockage, the reactor effluent is quenched before sent to the “C-204” by using vaporization heat of injection 
water. The sufficiently cooled reactor effluent is sent to the “D-202: High Pressure Separator”. In the “D-202”, a 
vapour containing H2S and H2, an oil, and an aqueous phase are separated. The oil is further decompressed, 
and vapour liquid is separated by the “D-203: Low Pressure Separator”, and then purified by the “T-202: 
Stripper”. The gas containing H2S and H2 is sent to T-201 Amine Scrubber” to separate H2S, and the remaining 
gas is recycled after being partially purged.  

 

Figure 1: Block flow diagram of hydro desulphurization process. 

2.2 NH4HS Corrosion 

The reactor effluent is supplied to the “C-204” at around 160C near the dew point of water by the latent heat of 
vaporization of injected water on the “C-204” inlet line, and cooled to about 40C by air. With cooling, the amount 
of condensate of light hydrocarbons and water in the vapor phase increases. Hydrocarbons in the diesel fraction 
and water are immiscible, and NH3(g) and H2S(g) are dissolved in the aqueous phase. The dissolved NH3(aq) 
and H2S(aq) form NH4HS(aq), and it is known that NH4HS corrosion is caused by NH4HS(aq) dissolved in the 
aqueous phase, and that if its equivalent concentration in aqueous phase exceeds 35wt% (Scherrer et al. 
(1980)), severe corrosion will occur. Therefore, it is important to monitor or predict the weight concentration of 
NH4HS in an aqueous phase as a corrosive environment, in order to ensure and maintain the reliability of 
facilities. In this study, we focus on the NH4HS corrosion environment of C-204 tube. 
The amount of NH4HS dissolved in the aqueous phase increases with the amount of water condensed, and the 
NH4HS corrosive environment becomes more severe as the outlet of “C-204” is approached. Near the outlet of 
“C-204”, considerable amounts of light hydrocarbons and water in the vapor phase are condensed. For this 
reason, it is expected that the volume velocity of the fluid falls and becomes a laminar flow region, and the vapor 
phase and the liquid phase flow separately in the tube. In such a case, the upper surface of the tube on the 
vapor phase side has a lower film heat transfer coefficient, and the tube surface temperature becomes 
substantially equal to the air temperature. Figure 2 shows an image of the flow inside the tube near the outlet of 
“C-204”. The water component of the tube vapor phase is under vapor pressure at the process bulk temperature 

D-201
Feed Surge Drum

P-201A/B
Feed Pump

H-201
Reactor 
Charge 
Furnace

K-205
Recycle Gas 
Compressor

H2 Make-up from BL

R-201
Reactor

E-203
E-202
E-201

P-204
Water 
Injection 
Pump

C-204
Reactor 
Effluent 
Condenser

D-202
High　
Pressure 
Separatoｒ

Diesel

Sour Condensate

D-203
Low　
Pressure 
Separatoｒ

To T-202

T-201
Amine 
Scrubber

Rich Amine

Purge

Lean Amine

5201

FIC

5202

FIC
5203

PIA

E-201
E-203

5227

TIC

5228

TIC

5205

PdI

5229

TR

FI
5218

5212

TI

5231

TIC

5206

PIC

BL

S

520９

PIC

86



TBulk K. On the other hand, when the tube surface temperature TSurface K reaches air temperature TAir K (<TBulk 
K), water droplets or film-like condensation occurs on the tube surface. Near the outlet of “C-204”, NH4HS is 
absorbed by process bulk condensate and tube surface condensate. Therefore, as the corrosive environment, 
it is necessary to predict the NH4HS concentration in these two aqueous phases at the same site. 

 
 

Figure 2 An image of the flow inside the tube  Figure 3 NH3-H2S-H2O system outline 

3. Dissolution Model of NH4HS in Aqueous Phase  
In recent years, there have been many reports of the use of thermodynamic simulators using electrolyte 
properties to predict the corrosive environment (Toba 2013). NH4HS corrosion is caused by NH4HS dissolved 
in the aqueous phase as in other corrosive environments. Therefore, in order to accurately estimate the 
corrosion environment, the use of electrolyte properties is desired. However, utilization of electrolyte properties 
requires input of pH and electric potential. The NH4HS corrosion target site in this study is inside the “Air Fin 
Cooler Tube”, and it is difficult to measure the pH and the electric potential of the surface condensate on the 
tube even if it is dissolved in the process bulk condensate. 
In order to estimate the corrosive environment, the dissolution process of NH4HS in the aqueous phase is not a 
major problem. In other words, there is no significant difference between estimating the dissolution equilibrium 
with an electrochemical equilibrium model nor with the overall equilibrium solubility model. It is said that 
hydrogen sulphide hardly dissolves in water, but it dissolves in an aqueous ammonia solution to form an 
apparent ammonium bisulfide (NH4SH(aq)) aqua. Assuming that this dissolution of H2S in the aqueous ammonia 
solution is a neutralization reaction, it can be interpreted that H2S equivalent to the ammonia dissolved in the 
aqueous phase at the maximum is dissolved in the aqueous phase to become an NH4HS aqueous solution. The 
general style guidelines are first given, followed by specific cases. First of all, avoid lower-level heading 
immediately following the higher-level one. It is recommended to have at least one sentence in-between. 

3.1 Ammonia Solubility Model 

Sherwood (1925) published data on the solubility of ammonia in water, for each temperature. This data shows 
the partial pressure of ammonia in vapor phase and the mole fraction of liquid phase ammonia at different 
temperatures, and a solubility model of ammonia in aqua can be expressed by estimating the parameters of the 
general equilibrium equation as shown in Eq. (1). Where xaqNH3 is ammonia mole fraction in aqua, TBulk is bulk 
fluid temperature and pNH3 is ammonia partial pressure.  

𝑥𝑥𝑁𝑁𝑁𝑁3
𝑎𝑎𝑎𝑎 = 𝑒𝑒𝑥𝑥𝑒𝑒�

2061
𝑇𝑇Bulk

− 10.279� ∙ 𝑒𝑒NH3
0.5 − exp �

5556.6
𝑇𝑇Bulk

− 26.793� ∙ 𝑒𝑒NH3 (1) 

3.2 Dissolution Model in Bulk Condensed Aqueous Phase  

As described with reference to Figure 2, the NH4HS corrosion occurs at the tube metal regions contacting with 
the bulk condensed water and with the tube upper surface condensed water. In this section, a prediction model 
for the NH4HS mass concentration in bulk aqueous condensate in the NH3-H2S-H2O system as shown in Figure 
3 is considered. When rDSNH3; ammonia dissolved fraction to the input NH3 flow rate (FNH3), and rCDH2O; water 
condensate fraction to the input H2O flow rate (FH2O) are set as internal variables, then the material balance 
equations between the input component molar flow rates and vapour/liquid phase output component molar flow 
rates as shown in Eqs. (2) to (4) are obtained. 
 

𝑉𝑉NH3 = 𝐹𝐹NH3 ∙ �1 − 𝑟𝑟DSNH3�  (2) 𝑉𝑉H2S = 𝐹𝐹H2S − 𝐹𝐹NH3 ∙ 𝑟𝑟DSNH3  (3) 

TBulk[K]
Bulk Liquid 

Phase 
(Oil・H2O)

Tube Surface 
TSurface[K]

Psystem[kPa]
Vapor Phase  

Condensed Water in 
Vapor Phase

Air TAir[K]

Bulk Liquid 
Temp.=TBulk [K]

Psystem [bar]
System Input

FN H3 [kmol/h]
FH2S [kmol/h]
FH2O  [kmol/h]

Vapor Phase Output
VN H3 [kmol/h]
VH2S [kmol/h]
VH2O  [kmol/h]

Liquid Phase Output
LN H3 [kmol/h]
LH2S [kmol/h]
LH2O  [kmol/h]

Surface Temp.=TSurface [K]
pNH3

87



𝑉𝑉H2S = 𝐹𝐹H2S − 𝐹𝐹NH3 ∙ 𝑟𝑟DSNH3  (4)   

Furthermore, Eqs. (5) to (7) show the material balance equations between the input component molar flow rates 
and liquid phase output component molar flow rates.  

𝐿𝐿H2S = 𝐹𝐹NH3 ∙ 𝑟𝑟DSNH3  (5) 𝐿𝐿H2S = 𝐹𝐹NH3 ∙ 𝑟𝑟DSNH3  (6) 

𝐿𝐿H2S = 𝐹𝐹NH3 ∙ 𝑟𝑟DSNH3𝐿𝐿H2O = 𝐹𝐹H2O ∙ 𝑟𝑟CDH2O (7)   

The total vapor and liquid flow rates (Vsystem and Lsystem) of this system can be described as shown in Eq. (8) and 
(9). The component molar fractions of vapor (ycomp) and liquid (xcomp) phases for each component can be 
described as shown in Eqs. (10) and (11), where the subscript comp indicates the composition element of NH3, 
H2S and H2O.  

𝑉𝑉system = 𝑉𝑉NH3 + 𝑉𝑉H2S + 𝑉𝑉H2O  (8) 𝐿𝐿system = 𝐿𝐿NH3 + 𝐿𝐿H2S + 𝐿𝐿H2O (9) 

𝑦𝑦comp = 𝑉𝑉comp 𝑉𝑉system⁄  (10) 𝑥𝑥comp = 𝐿𝐿comp 𝐿𝐿system⁄  (11) 

The partial pressure (pcomp bar) of each component is described as shown in Eq. (12) based on the material 
balance. The vapor pressure of water is a function of the temperature of the field and can be expressed with 
Eq. (13) by applying the modified Antoine’s equation, where pvH2O is vapor pressure of water in bar. 

𝑒𝑒comp = 𝑃𝑃system ∙ 𝑉𝑉comp 𝑉𝑉system⁄  (12) 

ln(𝑒𝑒H2O
v ) = 61.323 − 7.2275 × 103 𝑇𝑇Bulk⁄ − 7.177 ln(𝑇𝑇Bulk) + 4.0313 × 10−6𝑇𝑇Bulk

2  (13) 

In this system, if a sufficient low pressure and an ideal solution could be assumed, then the molar fraction of 
water in the vapor phase (ycalcH2O) as shown in Eq. (14) can be obtained by applying Raoult's law.  

𝑦𝑦H2O
calc = 𝑒𝑒H2O

v 𝑃𝑃system� ∙ 𝑥𝑥H2O   (14) 

The internal variables rCDH2O and rDSNH3 are to be searched iteratively within a region of zero to one so that Eqs. 
(15) and (16) are sufficiently equal to zero to make consistent the material balance calculations shown in Eqs. 
(2) through (12) with the equilibrium calculations shown in Eqs. (1), (13), and (14).  

. �𝑦𝑦H2O − 𝑦𝑦H2O
calc�  ≤ ε (15) �𝑥𝑥NH3 − 𝑥𝑥NH3

aq �  ≤ ε  (16) 

The mass percent of ammonium bisulfide in the aqueous phase, which is a corrosive environmental parameter 
to be managed, can be estimated by equation (17). 

51.111 ∙ 𝑥𝑥NH3
  17.031 ∙ 𝑥𝑥NH3 + 34.082 ∙ 𝑥𝑥H2S + 18.02 ∙ 𝑥𝑥H2O

 (17) 

3.3 Dissolution Model in Tube Upper Surface Condensed Aqueous Phase 

Solving the dissolution model in the bulk aqueous condensed water explained in the previous section, the 
ammonia partial pressure in the vapor phase at the bulk liquid temperature TBulk can be obtained. As mentioned 
before with Figure 2, in some cases, the tube upper surface temperature TSurface becomes lower than the bulk 
temperature, and at that time, a surface condensate drop or film at TSurface appears. When NH3 dissolves there 
and an equal amount of H2S dissolves as a neutralization reaction, then the concentration of NH4HS becomes 
extremely high from the equilibrium absorption phenomena, and severe corrosion occurs. Therefore, estimating 
the mass concentration of NH4HS in the tube upper surface condensed aqueous phase is much important for 
managing the reliability of the facility during operation. The amount of condensed water as drops or film on the 
tube upper surface is negligibly small, so that the dissolved NH3 and H2S molar fractions (xsNH3, xsH2S) in the 
tube upper surface condensed water can be interpreted as expressed in Eq. (18).  

𝑥𝑥NH3
𝑠𝑠 = 𝑥𝑥H2S

s = 𝑒𝑒𝑥𝑥𝑒𝑒�
2061
𝑇𝑇Surface

− 10.279� ∙ 𝑒𝑒NH3
0.5 − exp �

5556.6
𝑇𝑇Surface

− 26.793� ∙ 𝑒𝑒NH3 (18) 

The mass percent of NH4HS in the aqueous phase, which is a corrosion environmental parameter to be 
managed, can be estimated by equation (19). 

88



51.111 ∙ 𝑥𝑥NH3
𝑠𝑠

 51.111 ∙ 𝑥𝑥NH3
s + 18.02 ∙ �1 − 2 ∙ 𝑥𝑥NH3

s �
 (19) 

4. Three Layers Model for Predicting Corrosion Environmental Condition  
Figure 4 shows the corrosion environmental condition prediction layer which describes the hierarchical 
input/output relations between the above mentioned dissolution models. The pale green boxes represent 
functional sub-models indicated by equation numbers, and light blue boxes represent internal variables. The 
pink boxes represent the interface for indicating the NH4HS corrosion environmental conditions, and the white 
boxes represent the required input parameters.  

 

Figure 4 Equilibrium solubility based hierarchical model to predict NH4HS concentration in aqueous phase 

On the other hand, Figure 5 shows process simulation scheme for the process bulk simulation layer correcting 
the operation data and providing the process parameters which are necessary for the corrosion environmental 
condition prediction layer. In this scheme, the heat transfer tube of “C-204: Reactor Effluent Condenser” is 
represented by a series of plural number of decanter unit with cooler. Performing flow sheet simulation, the 
Peng Robinson thermodynamic model is used, and the necessary process parameters (Psystem, pcomp, Fcomp and 
TBulk) for predicting corrosion environmental conditions can be retrieved from the aqueous liquid and vapour 
flows of the decanters. Unfortunately, TSurface: tube surface temperature should be estimated form the 
temperature difference between “C-204” outlet temperature and TAir: ambient one.  
 

 

Figure 5 Process simulation scheme for process bulk simulation layer 

Furthermore the process bulk simulation layer receives operating conditions including the raw material oil, 
hydrogen and injected water flow rates, their compositions and the other process parameters of TPFLC 
(Temperature, Pressure, Flow, Composition) process parameters, from the process information management 
system, which will be implemented on the upper level than the operating system. The required information may 
be retrieved via the item number as shown in the flow diagram in Figure 1. 

5. Case Study 
For the HDS plant shown in Figure 1, a case study is performed using the developed NH4HS corrosion 
environmental condition prediction model using design data instead of the normal plant operation data. In this 

NH4SH
Mass Fraction  in 
Bulk  Condensate 
Aqueous Phase

Eq. (17)

NH3-H2S-H2O System
Input Molar Flow Rate: 

Fcomp [kmol/h]

Bulk Process 
Fluid Temp.

: TBulk[K]

NH4SH
Mass Fraction in 

Tube Upper Surface   
Condensate 

Aqueous Phase
Eq. (19)

Material 
Balance

Eqs. (2) to (11)

NH3-H2S-H2O System 
Press : PSystem [kPa] 

Tube Upper 
Surface Temp.

: TSurface [K]

Internal 
Variable: 
rDSNH3

St Eq (16)

Partial 
Pressure 

Calculation
Eqs. (12)

Internal 
Variable: 
rCDH2O

St. Eq.(15)

Fcomp

H2O VLE
Eqs. (13), (14) 

NH3 Solubility
Eqs. (1) to (5) 

xaqNH3

xNH3

ycalcH2O

yH2O

rDSNH3

rCDH2O

TBulk

xH2O

ycomp
TBulk

T

PSystem

PSystem

PSystem

pNH3

xNH3, xH2S, xH2O

NH3 Solubility
Eq. (18)pNH3

TSurface

xsNH3

xNH3
xH2S
xH2O

#1 #2

#3

#4

Mixer

Nitrogen 
Concen-
tration

Sulphur 
Concen-
tration

Hydrogen Flow 
Rate

Oil Flow 
Rate

Oil 
Composi

-tion

Water Injection 
Amount

Mixer

Mixer Mixer Psystem, pcomp
Fcomp, TBulk 

#1, 
#2, 
#3,

89



study, DWSim 6.7.1 (https://dwsim.fossee.in/) was used as a process bulk simulator, and an off-line external 
program was implemented for the corrosion environment condition prediction layer. Table 1 shows the outline 
of oil, hydrogen and injection water. These are based on the design values, but the physical properties that can 
be used with the simulator are limited, so that the average molecular weight of the oil components was only 
adjusted. As shown in Table 2, sulphur and nitrogen components are assumed to be “Thiophene” and “Aniline”. 
Changes in the corrosion environment were investigated when the feedstock oil was changed from the current 
operating conditions of 1.8 wt% sulfur and 150 wt ppm nitrogen to 350 wt ppm nitrogen as shown in Figure 6. 
Where, the temperature difference between the bulk fluid and tube upper surface is assumed to be 40 K. 
 

  

Figure 6 Comparison of corrosion environments with different concentrations of N2 in feedstock  

Table 1: Oil, gas, injected water condition for design basis  

 Feed Oil Make up Gas Recycle Gas Injected Water 
Flow Rate (kg/h) 91,100 1,402 5,579 912 
MW 250.0 4.80 6.80 18.02 
Temperature (C) 138 40 64 43 
Pressure (MPa) 7,823 8,927 7,810 6,810 
S (wt%) 1.8    
N (wt ppm) 150 - - - 

6. Conclusions 
The purpose of this research is to predict how changes, such as changing raw materials, which are performed 
by the operation to increase productivity and reduce cost, will affect the deterioration of plant assets, and to 
conduct production planning in consideration of asset management. And a system for enabling a maintenance 
plan to be made consistent with the production plan. Insufficient change management has been pointed out as 
the cause of many incidents, and the realization of this corrosion environmental condition prediction directly 
leads to a reduction in incidents due to inconsistencies between operation and equipment conditions, and 
contribute to the sustainable of the chemical industry. 

Acknowledgments 

The authors are grateful to the following plant maintenance experts for their cooperation; Mr. Iuchi, Kensuke 
(Safety Case Research Lab.), Mr. Hosoda, Kazutaka (Fuji Oil), Mr. Kumazawa, Nobumitsu (Kumazawa 
Consultant Office), Mr. Shigekuni, Eiji (Tokuyama), Mr. Shinohara, Hitoshi (Tokuyama), Mr. Tsuyoshi Takehara 
(NUC).. 

References 

Scherrer, C., M. Durrieu, and G. Jarno (1980). Distillate and reside hydroprocessing coping with corrosion with 
high concentration of ammonium bisulfide in the process water. Material Performance 19, 11-25. 

Sherwood, T. K. (1925). Solubilities of Sulfur Dioxide and Ammonia in Water, Ind. Eng. Chem 17, 745-747. 
Toba, K. (2013). Application of Simulation Technique on Studies of Ammonium Salts Corrosion in Oil Refining 

Plants, Zairyo-to-Kankyo 62, 352-358 (Japanese).  
 
 

0

0.05

0.1

0.15

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0.4

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N
H

4H
S 

co
nc

en
tr

at
io

n 
[w

t F
ra

c.
]

Bulk Fluid Temperature [C]

N2 Concentration in Feedstick=150 wt PPM Case

Bukl Aqueous Phase Tube Upper Surface Water

0

0.05

0.1

0.15

0.2

0.25

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0.35

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405060708090100110120130140150160

N
H

4H
S 

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Bulk Fluid Temperature [C]

N2 Concentration in Feedstock=350 wt PPM Case

Bulk Aqueous Phase Tube Upper Surface Water

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	Development for Prediction Model for Environmental Condition of Deterioration Phenomena for Asset Integrity Management