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Sand erosion experiments and model
development for UNS N06625 cladding
and UNS S32750
BY GURUPRASAD KULKARNI, RAVINDRA DEVI, BIJU DASAN, PAUL MATHEW /
GE GLOBAL RESEARCH
YONGLI ZHANG, EMAD GHARAIBAH, JOHN DANIEL FRIEDEMANN /
SUBSEA SYSTEMS, GE OIL & GAS
Copyright 2012, Offshore Technology Conference
This paper was prepared for presentation at the Offshore Technology Conference held on 30 April – 3 May
2012, Houston, Texas.
Abstract
Material loss due to sand erosion can cause severe damage to oil and gas production facilities and
lead to leaks and ruptures if left undetected. The design of oil and gas production equipment to
safely withstand sand erosion and simultaneously optimize production requires a reliable erosion
prediction tool. One of the key requirements for such a tool is that it correctly models both the
erosion resistance of the exposed materials and the effects of the particle impact trajectories and
velocities.
Key to this is a full understanding of the individual materials and their impact resistance. This is
because the impact behavior varies very much between materials and models cannot be simplified to two approaches: ductile or brittle. Model validity must be questioned as the oil industry begins to
implement hardened and high chrome content materials.
UNS N06625 and UNS S32750 are two of the popular alloys in the subsea industry. Despite the popularity of these materials, little erosion data or validated models for either application are found in
the literature. Another significant gap is related to experimental studies aimed at understanding the erosion caused by fines.
To fill this gap and provide verification of the existing models, a series of experiments were conducted and analyzed. Direct impact erosion experiments for UNS N06625 cladding and UNS S32750
were conducted using sand particles carried by air at ambient temperature and pressure. The sand particle sizes ranged from 27 µm to 619 µm, sand particle velocities from about 25 m/s to 160
m/s, and impact angles from 15° to 90°. An erosion correlation for each material was derived from these experimental data. The erosion correlations were then applied within a CFD (Computational
Fluid Dynamics) model for a typical subsea assembly to demonstrate the applications. A significant contribution is that these experiments and correlations provide an input to the understanding of
erosion for the full range of particle size, impact angles and velocities, and how these are related to erosion in modern corrosion resistant alloys (CRAs).
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Introduction
Sand erosion is commonly encountered in the oil and gas industry. Severe damage to the production facilities can occur if the sand is not handled properly. The sand
produced with oil and gas is normally filtered down hole and monitored at various critical locations in the pipeline. The down hole sand screen limits the size and amount of
sand that can move through it. The material of the pipeline and other components is also important for mitigating the sand erosion damage. UNS N06625 and UNS S32750
are two of the popular alloys in the subsea industry. Sometimes, the oil and gas production rate has to be limited due to excessive sand erosion. The design of the oil and gas
production systems to safely withstand sand erosion and simultaneously optimize production requires a reliable sand erosion prediction tool. Tulsa SPPS [1] and DNV RP
O501 [2] are the two methods widely applied in the oil and gas industry for predicting sand erosion. One of the key ingredients of these methods is the erosion correlation,
which calculates the erosion rate from the parameters that are believed to affect the erosion rate the most. The accuracy of the erosion correlation is thus very important
for the erosion rate prediction.
A wide variety of erosion correlations have been developed by many investigators. Meng and Ludema [3] examined various erosion correlations in the literature. They
concluded that no single erosion correlation is accurate for practical use across the the range of parameters affecting erosion. Based on the literature survey, they
concluded that there are four primary mechanisms by which solid particle erosion occurs. These mechanisms are:
Cuttings wear (which is defined as indentation of a material surface by a sharp solid particle followed by fracture of the material) and plastic
deformation (perhaps referring to deformation beyond the elastic deformation and followed by fracture of the material)
Cyclic fatigue
Brittle fracture ("non-cyclic failure")
Melting of the materials
These mechanisms were proposed by various investigators to explain the erosion, or in general, the wear process. The real erosion process is much more complex than
what can be explained by these mechanisms. Many parameters were investigated and incorporated into the erosion correlations found in the literature. For the sand erosion
encountered in the oil and gas industry, the important contributing factors are believed to be the sand particle impact velocity and angle, the pipeline material hardness, and
the sand particle size and sharpness [1, 2, 4, 5].
As discussed above, the existing erosion models do not correctly describe the materials currently in use by the subsea industry. UNS N06625 and UNS S32750 are widely
used in subsea oil and gas pipelines but there is little erosion data in the literature. Another challenge is that there is little erosion data for very small sand particle size (< 50
µm). Fine sand was believed to cause insignificant erosion damage. However, some recent evidence shows that these fines can cause severe erosion damage under certain
conditions [6]. Fines are almost inevitable in oil and gas production since they can escape through most sand screens.
There are two major objectives of this work. The first one is to generate erosion data using both fine and coarse sand grain sizes. The second is to develop erosion
correlations for UNS N06625 and UNS S32750 from these data. The ultimate goal is to implement these erosion correlations into various sand erosion prediction tools and
provide more accurate sand erosion prediction for oil and gas production systems.

2. Figure 1
Schematic of the test facility
UNS N06625 UNS S32750
Sample Length 76.2 mm 76.2 mm
Sample Width 25.4 mm 25.4 mm
Sample Thickness 10 mm 5 mm
Sample Weight 200 g 80 g
Surface Roughness Ra = 0.2 µm Ra = 0.2 µm
Vickers Hardness 2.26 GPa 2.69 GPa
Sample Cleaning Using acetone in an ultrasonic cleaner for 5 minutes
Table 2
Key parameters of the erosion samples
Figure 2
Erosion sample and the sample holding assembly
Figure 2a
Erosion sample before (top) and after (bottom) the test
Description of the experiments
A direct impact test rig has been designed. The experiments were conducted in air-under-room conditions (1 atm,
24°C). Figure 1 shows a schematic of the test rig. It consists of the compressor, the sand feeding system, the venturi
device for mixing the sand and air, and the test section. The test section is a transparent acrylic cabin with two of
the walls made of borosilicate glass to enable velocity measurement using LDV (Laser Doppler Velocimetry). A
double-disk device can also be put in the test section for measuring the sand particle velocity. The sand feeding
system consists of a hopper with a pneumatic vibrator that feeds the sand particles onto a slowly rotating disk that
drops the sand particles into the venturi device. The sand feeding rate is maintained at about 10 g/min for all cases.
The volumetric sand concentration varies depending on the airflow rate, with the highest value of about 0.014%.
The test duration ranges from about 9 to 16 minutes, depending on the particle velocity. Lower velocities were
tested for longer times to achieve measurable erosion. The venturi device creates a relatively low pressure region
and draws the sand particles in. The mixture of sand and air is then accelerated through the nozzle to the required
velocities. The erosion samples are mounted at the exit of the nozzle which is designed according to ASTM guideline
G76 [7]. The nozzle is made of stainless steel and has an ID of 5 mm and length of 125 mm. The distance between
the nozzle exit and the surface of the erosion samples along the nozzle centerline is maintained at 10 mm. After
impacting the erosion sample, the sand particles fall into a collecting hopper that is connected to a dust collector at
the bottom of the test section. The dust collector is filled with water to prevent the fine particles from flying out to
the atmosphere. The airflow is controlled and monitored with a pressure gage that can regulate air pressures to a
maximum of 6 bars. The velocity of air and particles is controlled using the pressure gage. The key parameters are
summarized in Table 1.
Carrier Fluid Air under room conditions (1 atm, 24°C)
Line Pressure 6 bars
Sand Feed Rate 10 g/min
Volumetric Sand Concentration < 0.014%
Test Duration 9 to 16 min
Nozzle ID 5 mm
Nozzle Length 125 mm
Nozzle-Coupon Distance 10 mm along the nozzle centerline
Table 1
Key parameters of the test rig
Erosion samples
Two types of materials were tested in this work, the Ni-based alloy UNS N06625 and the high
chrome alloy UNS S32750. UNS N06625 is normally used for cladding due to its excellent
weldability and erosion/corrosion resistance. UNS S32750 is also widely used in the harsh
offshore environment due to its great mechanical strength and corrosion resistance. In this
work, the erosion samples are rectangular shaped (1 inch by 3 inches). The thickness of the
UNS S32750 samples is about 5 mm, with a weight of about 80 g per sample. The UNS
N06625 samples are thicker (about 10 mm) since they are a combination of an AISI 4130
substrate and the UNS N06625 cladding. The weight of a UNS N06625 sample is about 200 g.
The sample surfaces subject to sand impact are polished to Ra = 0.2 µm. The average Vickers
hardness (Hv) is about 2.26 GPa for the UNS N06625 samples and 2.69 GPa for the UNS
S32750 samples. The samples are cleaned in acetone in an ultrasonic cleaner for 5 minutes
and weighed. Weight measurements are made before and after each test. Figure 2 shows pictures of a typical erosion sample before and after the test, and the erosion
sample holding arrangement. The key parameters of the erosion samples are summarized in Table 2.
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Sand erosion experiments and model development for UNS N06625 cladding and UNS S32750 Download
Figure 3
Sand particle size distribution.
Figure 4
Sand sample SEM pictures
Case No. dP (µm)
θ
(degree) VP (m/s)
1 27 15 69.2
2 27 15 161.6
3 78 15 25.7
4 211 15 110.7
5 619 15 44.3
6 619 15 161.3
7 78 25 110.7
8 211 25 41.0
9 211 25 157.2
10 619 25 22.7
11 619 25 71.5
12 619 25 161.3
13 27 35 24.8
14 27 35 161.6
15 211 35 26.3
16 211 35 72.4
17 211 35 157.2
18 619 35 44.3
19 619 35 108.1
20 27 45 24.8
21 211 45 157.2
22 619 45 22.7
23 619 45 108.1
24 27 60 161.6
25 619 60 161.3
26 27 90 69.2
27 211 90 26.3
28 211 90 157.2
29 619 90 22.7
30 619 90 108.1
31 27 60 24.8
32 211 60 72.4
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Sand used for the erosion test
Four different size ranges of sand were used in this work. These are naturally occurring sand (Silica, SiO2) from mines (Tumkur mines in Karnataka state, India), washed,
crushed and sieved to the required sizes. The D50 sizes of these four types of sand are 27 µm, 78 µm, 211 µm, and 619 µm (). Due to the mechanical crushing, the sand
particles have an angular shape, as seen in the Scanning Electron Microscopy (SEM) pictures ().
Measurement equipment
The weight of sand and erosion samples is obtained using a high resolution digital balance (Sartorius model CPA 225D). This
digital balance has an upper limit of 220 g and a resolution of 0.1 mg.
The air flow is regulated using a digital pressure gauge which has a resolution of 0.1 bar. In addition, a pitot tube is used to
measure the air velocity at the nozzle exit to ensure consistency of the air flow rate. An anemometer is also used to measure
the air velocity for a lower range, up to 30 m/s.
The sand particle velocity was measured using a double-disk device. The distance is 10 mm between the nozzle exit and the
top disk, and 24 mm from the top to the bottom disk. The width of the four slits on the top disk is 1.5 mm each. For
measurements, the double-disk device is set at 1000 rpm for the 619 µm sand and about 3000 rpm for the other sand sizes
to ensure that a measurable scar is formed on the bottom disk. The double-disk is considered acceptable for measuring
particle velocity in erosion tests according to ASTM G76 [7]. However, the accuracy of the double-disk measurements may be
questionable due to the errors induced due to manual measurement of the scar and also the wide range of sand particle
sizes and velocities explored in this work. Laser Doppler Velocimetry (LDV) is scheduled for measuring the sand particle
velocity to achieve better accuracy in the next stage of this work. The sand particle velocities reported in this paper are based
on double-disk measurements.
Design of experiments (DOE)
DOE is a systematic way of evaluating the variables within a design space and analyzing the resulting responses in order to
quantify the effects of inputs on the responses while using a minimum number of experimental runs. In this work, the
experiments for evaluating the erosion behavior were designed using an optimal DOE method [8, 9] that maximizes the
amount of information from a fixed number of experiments.
The experiments were planned for the following three parameters, angle of impact (θ), particle size (dP) and particle velocity
(VP). These three parameters define the basic design space for the DOE (Table 3). The hardness of the materials is used in
some erosion correlations [1, 4, 5]. However, using the hardness to characterize the material’s erosion resistance is
questionable. In this work, the hardness is not included in the DOE because it is kept constant for each of the two materials
and an erosion correlation will be developed for each of the two materials. The full test matrix, based on a full factorial DOE,
would consist of 120 cases for each test material. The number of actual test cases was reduced to 36 by applying the Q-
optimal criterion during the DOE. Table 4 lists the tested cases along with the corresponding parameters.
dP (µm, measured D50 values) 27, 78, 211, 619
θ (degree) 15, 25, 35, 45, 60, 90
VP (m/s, nominal values) 25, 40, 70, 110, 160
Table 3
Basic Design Space for the DOE

4. 33 78 60 41.2
34 78 15 158.2
35 78 35 75.5
36 78 45 158.2
Table 4
Q-Optimal DOE – Tested Cases and Parameters
Figure 5
Experimental results of UNS 06625
Figure 6
Experimental results of UNS S32750.
Experimental results
There are 36 test cases conducted for each of the two materials. Each test case was repeated three times. Figure 5 and Figure 6 plot the results for all tested cases in the
order of increasing percentage of the standard deviation with respect to the mean erosion rate. The repeatability of the measurements is considered good for most cases.
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Sand erosion experiments and model development for UNS N06625 cladding and UNS S32750 Download
Figure 7
Effects of impact angle and impact velocity on the erosion rate, according to equations (1) and
(2)
Equation 3
Tulsa correlation for steels [10]
Equation 4
DNV correlation for steels [2]
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Sand erosion correlations and discussion
The erosion correlations for UNS N06625 and UNS 32750
The collected erosion data were analyzed and a correlation was developed for each of the two materials, Equation (1) for UNS N06625 and Equation (2) for UNS S32750, as
shown below:
– UNS N06625 Correlation (15° ≤ θ ≤ 90°) (1)
– UNS S32750 Correlation (15° ≤ θ ≤ 90°) (2)
where,
E – Erosion rate in micrograms of target mass loss per gram of sand (µg/g of sand)
θ – Sand particle impact angle (radian, refer to Figure 2)
d – Sand particle diameter (µm)
V – Sand particle impact velocity (m/s)
a to k – parameters derived from experimental results to best model the erosion, all positive values
Note that these two equations are applicable in the design space that is defined
by the tested parameters, namely, the sand particle diameter, impact angle and
impact velocity. It must be recognized that these two equations are not valid for
an impact angle less than 15°.
The format of the equations is pre-assumed based on a review of published
sand erosion correlations and on the trend of the experimental data collected in
this work. The R-square value of these two equations is about 97%, which
suggests that these two equations are a good fit to the experimental data. d and
j are the largest parameters in these two equations, indicating that the impact
velocity is the most important parameter affecting the erosion rate. The positive
value in the exponent indicates that the erosion rate increases with an increase
of the impact velocity. The erosion rate decreases with increasing sand particle
size. The number of small sand particles is greater than that of large sand
particles for the same amount (in terms of mass) of sand. Therefore, the small
sand particles may erode more efficiently. Notice that this trend is opposite to
that observed by some investigators, such as Oka et. al. [4, 5]. This is an
indication that some other sand particle properties, such as sharpness and size
distribution, need to be considered in a more accurate correlation. Designers
should apply caution while assuming that smaller sand causes less erosion, or
vice versa. The effect of the impact angle is slightly more complicated since it is
coupled with the impact velocity in these two equations. Figure 7 includes a few
graphs to show the trend dependence of particle impact angle and impact velocity, according to equations (1) and (2). The erosion rate trends vary as a function of angle and
velocity. Noticeably, the maximum rate of erosion occurs at varying angles with an increase in velocity for the same particle size. One can also find that the erosion
resistance of these two tested materials is not vastly different. The erosion rate, especially for UNS S32750, becomes increasingly independent of angle from low to high
velocities.
Comparison with other erosion correlations
The most-used erosion correlations in the oil and gas industry are the Tulsa correlation [10] and the DNV correlation [2]. These two correlations are cited here for the
purpose of comparison. The Tulsa correlation is shown in Equation (3) and the DNV correlation is shown in Equation (4). In the Tulsa correlation, HB is the Brinell hardness
number of the pipeline material; FS is the sand particle sharpness factor and is set to 1.0 since all sand utilized in this work has sharp edges. Other variables are the same as
in Equations (1) and (2). Both correlations are applied to common steels, and sometimes to modern CRAs with caution. Notice that the unit of erosion rate had been
converted to µg/g of sand. Therefore, the constant coefficients in Equations (3) and (4) are different than in the original forms.
Figure 8 shows the comparison of these erosion correlations for several sets of conditions. The comparison is done for only one particle size since the erosion rate is
independent of the particle size in Equations (3) and (4), and is a weak function of particle size in Equations (1) and (2). For low impact velocity (V1) and an impact angle greater
P
P

6. Figure 8
Comparison with other erosion correlations.
than about 25°, the UNS N06625 and UNS S32750 correlations lie between the
Tulsa and DNV correlations for impact angle greater than about 25°. For high
impact velocity (V4), the UNS N06625 and UNS S32750 correlations give a lower
erosion rate, close to the DNV correlation but much lower than the Tulsa
correlation. The impact angle of the maximum erosion rate is about 35° for the
DNV correlation and 50° for the Tulsa correlation, but varies for the UNS
N06625 and UNS S32750 correlations depending on the impact velocity.
All four erosion correlations are purely derived from experimental data after
making some assumptions about the format of the correlations. For instance,
the Tulsa and the DNV correlations assume that the erosion rate is a function of
the impact velocity raised to a constant power and is independent of the particle
size, and that the impact velocity and impact angle dependence are not coupled.
Each set of experimental data for deriving these correlations has its own testing
conditions. Therefore, each correlation should be applied with caution, ensuring
that the applied conditions of interest are not too far off from the testing
conditions. Compared to the Tulsa and the DNV correlations, the correlations
derived in this paper cover a relatively larger range of impact velocity and a
broader sand particle size.
Equations (1) and (2) do not cover impact angles less than 15°. These angles can
be included by assuming that the erosion rate is zero at the impact angle of
zero, and then fitting a curve based on the trend at larger impact angles. This
was also done when the Tulsa and the DNV correlations were derived. There
were no sound erosion data for impact angles shallower than 10~15° when
deriving all of these four correlations. The challenge for the UNS N06625 and UNS S32750 correlations is that the maximum erosion rate occurs at 15° under certain
conditions, which makes it hard to tell where the maximum erosion rate would be for the full range (0~90°) of the impact angle.
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Sand erosion experiments and model development for UNS N06625 cladding and UNS S32750 Download
Figure 9
The direct impact geometry and dimensions.
Figure 10
Boundary conditions and hexahedral mesh.
Figure 11
CFD prediction results in comparison with the UNS 06625 correlation.
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Predicting sand erosion using the correlations
Approximate method: bulk particle impact information
The simplest way of applying the correlations is to use them directly, without calculating the true particle impact angle and impact velocity. Instead, the bulk flow velocity and
the angle estimated from the flow geometry can be used under certain conditions. For instance, the impact angle can be assumed as 45° and the impact velocity as the fluid
velocity in a standard elbow. This approach is best applied when the inertia of the sand particles is much greater than that of the carrier fluid. The sand particles are
therefore expected to retain their direction and velocity towards the wall. This is also the main reason for conducting the erosion experiments in air rather than in liquid, if
the final purpose is to derive a correlation through experiments in which the impact angle and impact velocity are well controlled. The DNV RP O501 [2] uses this approach,
with a little more adjustment depending on the type of flow geometry. The correlations derived in this work can be used along with the method described in the DNV RP
O501, simply by replacing the DNV correlation. This method is easy to apply but can only be used in very limited applications.
Accurate method: CFD with detailed particle impact information
The most accurate way of applying the erosion correlations is to use them along with CFD. CFD is able to provide detailed information for the whole flow domain, including
the motion of the sand particles. By modeling the dynamics of a large number of sand particles, the particle impact angles and velocities are calculated and then used in the
erosion correlations. This approach can provide a very detailed erosion distribution and help identify erosion hot spots. It is useful when the flow geometry is complex. The
main disadvantages of this approach are that it normally takes much more time and requires CFD expertise.
In this work, the UNS N06625 and UNS S32750 correlations are implemented into ANSYS CFX v12.1. CFD simulations were performed to evaluate the implementation and
the CFD setup. The simulations were carried out to replicate the direct impact experiment setup as shown in Figure 9. The geometry has a nozzle with 5mm diameter and its
length is 25 times the nozzle diameter, 125mm, as per the ASTM [6] recommendation. The length of the nozzle makes the particles injected at the inlet flow through a
sufficient length to have a fully developed flow at the outlet of the nozzle. The distance from the nozzle center at the exit to the target coupon, along the nozzle axis, is 10 mm
away from the target coupons. The target coupon dimensions were 1 x 3 inch. All flow condition parameters are chosen to reflect the experiments.
The upper nozzle opening was treated as an inlet with uniform velocity/mass flow and the bottom of the chamber as an outlet with constant pressure. A no-slip wall
boundary condition was imposed for all other boundaries (Figure 10). A hexahedral mesh was generated and a mesh sensitivity study was carried out. The boundary layer at
the wall is well captured with y+ values less than 5 and an elemental growth ratio of around 1.2 from wall to volume zone. Steady state fluid flow was computed, under the
assumption of a smooth wall boundary condition. The SST k-ω turbulence model with automatic wall function was used. The sand particle path was then solved assuming
one way coupling, i.e., the sand particles are transported by the fluid but are not affecting the fluid. This is a reasonable assumption for low volume flow rates of particles
(volume fraction less than 10 percent) [11]. The perpendicular and parallel restitution coefficients describing the wall-rebound action of the particles are set to 0.8 and 1.0,
respectively. The effects of drag (calculated using the Schiller Naumann drag model), pressure, added mass, buoyancy, and the particle dispersion due to turbulence are
considered in calculating the particle trajectories. For each impact on the wall, the UNS N06625 or the UNS S32750 correlations was applied to calculate the corresponding
erosion rate at the impacted location. Figure 11 shows the comparison between the CFD prediction results and the UNS N06625 correlation. The CFD prediction matches the
correlation.
Practical method: mechanistic model with representative particle impact information
This approach aims to provide a quick solution like the approximate method, but still captures the most important dynamics of the sand particles like the CFD approach. The
Tulsa SPPS tool [1] belongs to this category. The 1D version of SPPS calculates the impact information of one representative sand particle and uses this to estimate the

8. Nomenclature
d Sand particle size, µm
D50 Median sand particle size, µm
E Erosion rate, µg/g of sand
F Particle sharpness factor
HB Brinell hardness
Hv Vickers hardness, GPa
Ra Absolute roughness, µm
V Impact velocity, m/s
θ Impact angle, radian or degree
maximum erosion rate for the given set of conditions. By calculating the representative impact information, it takes into account the effects of fluid properties, sand particle
properties, geometry, and other flow field information. The 2D version of SPPS is just like a 2D CFD, calculating the impact information of a large number of sand particles. It
takes significantly more time than the 1D version but much less time than a true CFD simulation.
Concluding remarks
The main conclusions drawn from this work are,
1. Direct impact erosion experiments were performed and data was collected, especially for fines.
2. Sand erosion correlations were derived for UNS N06625 and UNS S32750.
According to these correlations, the impact velocity is the dominant parameter; the effect of the
impact angle varies depending on the impact velocity; the erosion rate decreases slightly with
increasing sand particle size; and the UNS N06625 and UNS S32750 have comparable erosion
resistance.
3. The UNS N06625 and UNS S32750 correlations lie between the Tulsa and the DNV correlations for
relatively low impact velocity. For relatively high impact velocity, however, they give much lower
erosion rates in comparison with the Tulsa and the DNV correlations.
4. A revision of the UNS N06625 and UNS S32750 correlations is necessary using more accurate
particle velocity measurements that are scheduled for the next phase of this work.
5. The derived erosion correlations are successfully implemented into ANSYS CFX and can be applied in
complex geometries.
References
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374.
[7] ASTM, 2007, "Standard Test Method for Conducting Erosion Tests by Solid Particle Impingement Using Gas Jets," G76-07.
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