EFFECT OF DESERT PARTICULATE COMPOSITION ON HELICOPTER ENGINE DEGRADATION RATE

Abstract

Abrasive, short-term damage to helicopter engines by quartz particles can be mitigated by the use of an inlet particle separator. However, such devices fail to remove the finest particles that havesignificantly different mineralogy to quartz. If these particles reach the hot end components, they may form deposits on the vane surfaces, or clog cooling holes. In the former case, a choking effect is created leading to a reduction in the surge margin; in the latter, an increase in heat transfer to the blade thence reduction in life may result.Prediction of this is limited by the myriad of contributory factors: the likelihood of a particle adhering to a surface depends on its phase and viscosity which changes along its path; the rate of change of state depends on the physical and chemical properties of the particle, which vary according to global location and inlet separator effectiveness. This contribution summarises the process of turbine degradation in desert-based helicopters, and proposes a novel approach to its prediction.

Full text

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European Rotorcraft Forum, Southampton, Sept. 2014
EFFECT OF DESERT PARTICULATE COMPOSITION ON HELICOPTER ENGINE DEGRADATION RATE
Nicholas Bojdo
*
& Antonio Filippone
The University of Manchester
Manchester M13 9PL
United Kingdom
ABSTRACT
Abrasive, short-term damage to helicopter engines by quartz particles can be mitigated by the use of an inlet
particle separator. However, such devices fail to remove the finest particles that havesignificantly different
mineralogy to quartz. If these particles reach the hot end components, they may form deposits on the vane
surfaces, or clog cooling holes. In the former case, a choking effect is created leading to a reduction in the
surge margin; in the latter, an increase in heat transfer to the blade thence reduction in life may
result.Prediction of this is limited by the myriad of contributory factors: the likelihood of a particle adhering to
a surface depends on its phase and viscosity which changes along its path; the rate of change of state
depends on the physical and chemical properties of the particle, which vary according to global location and
inlet separator effectiveness. This contribution summarises the process of turbine degradation in desert-
based helicopters, and proposes a novel approach to its prediction.
1 INTRODUCTION
*
Modern day rotorcraft are often required to
operate to and from unprepared landing sites. In
desert environments this can lead to the disturbance
of loose sediment from the ground, creating a cloud
of dust that soon envelopes the whole aircraft in a
situation known as brownout (see Fig. 1). In such an
event, particulate is drawn into the engine inlets.
Almost all rotorcraft operating in such environments
are fitted with engine air particle separators, or
EAPS, which remove the majority of the particulate
with varying degrees of success, depending on the
type of device employed
[1]
.
Fig. 1: RAF Merlin Helicopter Creates a 'Brownout'
Dust Cloud Landing in Afghanistan. (Images: © Sgt.
Steve Blake, UK Ministry of Defence.
[2]
).
A recent study by Barone et al.
[3]
demonstrated
that an inertial particle separator (based on patent
Ref.
[4]
) could achieve an efficiency of 92% removal
*
Honorary Lecturer & Research Associate. School of
MACE, Pariser Building. Corresponding Author.
Email: Nicholas.Bojdo@manchester.ac.uk
of AC Coarse test dust (diameter range 0-200µm;
mean diameter 36.8µm), although similar studies on
IPS in the literature report lower efficiencies
[5]–[7]
.
However, samples taken from typical locations of
operation have shown AC Coarse test dust to be an
inaccurate representation of the typical size
distribution likely to be ingested by helicopter
engines in desert environments. Furthermore, of the
finer particles that avoid capture, samples taken
from typical regions of operation are found to have
mineral compositions much different to that found in
test dust
[8]
.
The importance of mineral composition should
not be underestimated. While diameter, shape and
density all influence the trajectory through the fluid,
the mineralogy of the particle – that is, the way in
which the constituent elements combine to make a
mineral –is the key to predicting the likelihood of
adhesion to a surface in the hot section of a gas
turbine engine. Furthermore, when several minerals
are combined in molten form, their product may
exhibit radically different chemical properties to the
original influent particulate that could lead to
corrosion of component surfaces.
The damage to component surfaces is wide-
ranging and affects each stage of the gas turbine. A
comprehensive review of the research into erosion
and deposition in turbomachinery is presented by
Hamed & Tabakoff
[9]
. During the first Gulf War, the
severity of damage to unprotected Chinook engines
led to rejection rates of 20 to 40 engines per 1000
flight hours. Compressor blades bear the brunt of
the damage from hard quartz particles, suffering
blunted leading and trailing edges, and pitted
pressure surfaces, while turbine blades experience
considerable build-up of molten deposits as
impurities solidify on film cooled surfaces. Such
damage is pictured in Fig. 2. Combustor walls may
also become glazed, reducing the flow path area.
Cooled turbine blades suffer a secondary

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problem too, in that cooling holes can become
blocked by particulate entering compressor bleed
line, heating as they pass through internal cooling
ducts, and sticking to hole surfaces through inertia
as the cooling air navigates the labyrinth-like
passages. Smialek et al.
[8]
report that inspection of
Gulf War engines revealed crusty deposits on
leading edges of vane platforms and a talc-like
powdery substance in the cooling passages of
turbine discs. The process is non-linear and
exponential by nature: as particulate builds up, it
acts as an insulating layer thus reducing the heat
transfer from coolant to blade. The subsequent
elevated blade temperature leads to acceleration
offurther sticking and thickening of the insulating
layer
[10]
.Clogging of cooling holes in turbine blades
and vanes can have a short term positive effect on
engine performance as compressor bleed is
reduced. This reduces the surge margin but
increases the overall engine efficiency. However, the
overheating of the nozzles and blades significantly
reduces their lifetime from thousands to hundreds of
hours
[11]
.
Fig. 2: Effects of particle ingestion on key turboshaft
engine components, illustrating: a. leading and
trailing edge erosion of compressor blades; b.
agglomeration of molten impurities on turbine
blades. (Images © Crown Copyright.)
Fortunately, since the first Gulf War there has
been a great progress made in limiting this kind of
damage, through the use of EAPS. For example,
one study purports to achieve a hundredfold
increase in mean time between overhaul as a result
of using an inlet barrier filter
[12]
.However, as a
particle’s size diminishes, it becomes more difficult
to remove.Van der Walt & Nurick studied
degradation of an engine fitted with an array of
vortex tube separators,focusing on efficiency of
removal and subsequent fate of the unfiltered
particulate
[13]
.Using a macroscale approach to the
effects of erosion, they were able to predict engine
lifetime by relating the resulting unfiltered particle
size to the rate of metal erosion. Crucially, however,
the interaction of unfiltered particulateon hot section
components and the consequent effect on
degradation was not considered.
The work presented herein reports the authors’
progress in predicting engine performance loss and
through life costs due to the degradation of turbine
nozzle guide vanes and rotor blades by desert
particulate. The blockage of cooling holes, one of
the two main effects leading to turbine
degradation,is predicted as part of the methodology.
2 BACKGROUND
Research on particle deposition in the hot
section of turbomachinery has received more
attention since the turn of the century. Initial
motivation has been prompted by the deposition
found on the surface of turbines of combined-cycle
power plants using ‘new’ alternative fuels. In lieu of
natural gas, these power plants use a filtered syngas
generated from ‘dirty fuels’ such as coal, biomass
and oil residue petcoke that contain trace amounts
of uncaptured particulate. When this combines with
the hot combustion products, the result is a gradual
building up of deposits on the turbine vanes and
blades. This has proven to be detrimental to
component life, and authors are continuing research
into mechanisms of deposition (Ref.
[10], [14]
). More
recent attention on turbine degradationarose
following the Eyjafjallajokull eruption of 2010, which
highlighted the insufficiency of experimental data on
accretion and sintering rates of ingested volcanic
ash in the prediction of engine performance
loss.This has prompted recent studies into the effect
of ash ingestion on engine performance (Refs.
[15],
[16]
); Davison & Rutke
[11]
provide a comprehensive
review of much of the literature to date on the threat
of volcanic ash to aircraft engines.
While ash composition is typically different to
that found in desert dust, there is plenty of overlap in
the techniques used to characterize and predict
degradation, particularly concerning mechanisms of
particle capture and locations of deposition.Volcanic
ash typically contains compounds that transition to
glass at relatively low temperatures (approximately ≤
900°C). This exacerbates the deposition of ash
particles by producing a sticky glass substrate on
the blades into which higher inertia particles that

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would otherwise bounce may stick. While desert
sand is mainly composed of high melting-point
quartz, optical micrographs of leading edge deposits
from four turbines operating in the Persian gulf
[17]
revealed similar deposition morphology: a glassy
matrix containing second phase precipitates and
even bright metallic by-products of upstream
erosion. This suggests that the prediction of
degradation by sand should carry a greater
emphasis on contaminant mineralogy, as well as
physical properties such as size and density as
tends to be the case
[18]
.
Particle deposition in hot section
turbomachinery is a complex, multi-disciplinary
process involving three-phase, time-variant flow.
While little is still known about the effects of
deposition, the literature on this subject is growing.
2.1 Particle Melting and Sticking Potential
As the ash or dust passes through the core of
the engine, it can melt. The melting point for volcanic
ash depends on silicate content and can be as low
as 960 °C but is usually closer to 1100 °C
[11]
. The
sticking potential of material at high temperatures
has been recognized as a useful parameter to
describe the likelihood of capture by hot gas turbine
components
[19]
. According to Song et al.
[16]
, a
sticking-potential criterion requires consideration of:
a) The onset temperature at which the material
is capable of sticking to a hot surface.
b) The time-dependent rheology of the ash as
it evolves into a liquid.
The aim of these authors’ work was to quantitatively
characterize the fusion and sintering dynamics of
volcanic ash with a view to determining the
temperature at which a given sample gained the
ability to stick to a surface. From the literature, they
suggest that there are four characteristic
temperatures in the phase transition of a material
that describe sticking potential: the shrinkage
temperature (ST), the deformation temperature (DT),
the hemisphere temperature (HT), and the flow
temperature (FT). They determined these
temperatures by heating a cylindrically shaped
volcanic ash compact (CSVAC) sample ash from
Santaguito Volcano, Guatemala, from 50°C to
1400°C at a rate of 10°Cmin
-1
and quantified the
change in height, area and shape factor of the
samples’ silhouettes.The results depict an initially
quadrilateral silhouette that begins to shrink at
around 1100°C, becomes rounded at 1300°C
resembling a liquid droplet attached under surface
tension, then flows out to a half-dome at 1400°C.
The shrinking can be attributed to sintering, and
each of the temperatures above can be clearly
recognised. The sintering phase is described as the
temperature at which the area reduces by 1.5%, in
this case determined as 1115°C; however, the
samples only began to stick to the substrate once
the sample had reached the deformation
temperature (DT) (signified by the onset of sample
edge rounding) at around 1250°C. The authors thus
conclude that the sticking potential of volcanic ash
becomes important once the temperature reaches
the deformation temperature, which can be used as
a temperature limit in assessing jet engine operation
safety.
Whilstthe sintering of many particles provides
useful set of temperature markers for the
agglomeration of deposits, it does not cater for the
sticking ability of individual particles whose
mineralogy will be distinct. Tafti et al.
[20]
developed a
probabilistic sticking model based on particle
viscosity, a property that changes with temperature
and can be predicted from the properties of the
material. Their work concerns deposition of coal ash
on turbine nozzle guide vanes. They define a critical
sticking temperature at which the material softens,
and prescribe a probability of 1 for any particle of a
given composition above this temperature. Particles
with a temperature much below this have a
probability of 0 whilst any other particle is assigned a
probability of between 0 and 1 based on its
temperature-dependent viscosity, and the viscosity
at the critical sticking temperature of the material.
The temperature-viscosity relationship is
determined using a series of empirical formulae that
take the chemical composition (compound % by
weight), as summarized by Barker
[21]
. Generally, a
particulate melt will contain a balance of cationsthat
act either as glass formers, which promote the
formation of a glass structure, as modifiers that
terminate chains in the structure, or as amphoterics,
which can act as modifiers or formers. Modifier ions,
such as Ca
2+
or Mg
2+
, disrupt the glass structure and
tend to lower the viscosity.The temperature-viscosity
relationship is reported in the same study for a
number of different samples of ash, and appears to
be linear. If one can ascertain the particle
temperature, for example by knowing its heat
transfer properties and residence time in the flow
domain, then aprobability of adhesion can be found
from the calculated viscosity.
2.2 Particulate Composition and
Concentration
From the above it should be fairly evident that
the chemical composition of the ingested dust is as
important as the physical properties for the
prediction of erosion and deposition in
turbomachinery. A study by Walsh et
al.
[22]
investigated the effects of desert sand blockage
in the cooling holes of a kiln-heated leading edge
coupon. A reduction in coolant flow due to blockage
by deposited materials was quantified using a flow
parameter that is the ratio of momentum force to

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pressure force, as discussed by Hill
[23]
. They
investigated the reduction in flow parameter for a
range of parameters, including sand diameter and
metal temperature. They found the latter to be the
most significant parameter: as metal temperature
increased beyond 1000°C, those particles not
already molten either melted on impact or shortly
after impact.
Walsh et al. used three test dusts as
surrogates for real desert sand in the study. The
samples were analysed to determine their chemical
composition and size distribution, and heated to
determine melting point. A bulk powder spectrum
revealed that the test dusts were crushed granite,
containing: 68-76%wt quartz (SiO
2
) of varying
phase; between 10-15% aluminium oxide (Fe
2
O
3
);
and traces of iron oxide (Fe
2
O
3
), sodium silicate
(Na
2
O), lime (CaO), magnesium oxide (MgO),
titanium dioxide (TiO
2
), and potassium oxide (K
2
O).
While this gives an impression of the elements
present in the sample, the mineralogy (i.e. crystalline
structure) of the particle would be required to directly
infer melting points. Instead, by baking a small
sample of the test dust from 930°C to 1090°C, the
sample began to show signs of melting by
agglomerating at 980°C. By 1040°C a significant
colour change was observed, and by 1090°C the
now darker sample had become a solid block. Using
this result and assuming adiabatic heating solely by
radiation, the authors calculated that over a period of
just 0.01s – a conservative residence time for a
particle in the heated coupon – the particle would
increase from 675°C to 820°C, based on ametal
temperature of 1010°C. Given that the internal blade
cooling channels are serpentine by nature, the
particles may bounce and take a lot longer to exit
the blade through the cooling holes than the air, by
which time they may have reached melting point.
The proximity of the sand melting point to the
typical turbine inlet temperature was thus one of the
main causes of the substantial damage suffered by
desert-operating helicopters in the past, as reported
earlier. The investigation by Walsh et al.
[22]
was
prompted by evidence of large quantities of sand
being entrained into the compressor of C-17engines.
Unlike C-17 aircraft, helicopters can be protected by
one of a range of EAPS devices
[24]
. Their use
substantially changes the composition of the
particulate that does happen to evade capture and
reach the engine components. Physically, the
uncaptured particulate has a much smaller mean
diameter: in the aforementioned study by Van der
Walt & Nurick
[25]
, the mean diameter of the AC
Coarse test dust that evaded removal by vortex
tubes was found to be 4.9µm (from an original mean
diameter of 38µm). Chemically, the uncaptured
particulate has a much different mineralogy too: in
the aforementioned study by Smialek et al.
[8]
,
powders and deposits found within Blackhawk T700
engines were found to resemble a fine dust silicate-
based dust with much higher amounts of calcium,
aluminium, iron, magnesium and carbon oxide
species than ordinary dune sand from the same
region. It is significant to note that these T700
engines are fitted with an inertial particle separator,
which is effective at removing most particulate
above 20µm.
The same study by Smialek et al.
[8]
referenceda
prior study by Bessee & Kohl
[17]
conducted for the
US Army in 1993, in which a number of soil samples
were collected from various geographical areas on
the Continental United States (CONUS) and Saudi
Arabia. Their aim was to characterize each sample
using particle size distributions, elemental analysis,
mineral composition, and particle angularity, to
determine whether new test dusts used to evaluate
fuel filters for land-based vehicles were
representative of naturally occurring soils. 22
samples were examined and generally fell into three
families: a. high calcium, no silicate; b. magnesium
silicate; and c. high silica. Only a limited amount of
the sand samples matched standardized test dust
compositions (including AC Coarse and AC Fine test
dusts, used respectively in the studies by Walsh et
al.
[22]
andVan der Walt & Nurick
[25]
). In a separate
contribution but using the same samples from the
fouled Gulf War T700, Smialek et al. compared the
chemical composition of one such Saudi sample
with deposits found in cooling holes and nozzle
guide vanes, as shown in Fig. 3
[26]
. While it is not
known just how much quartz passes right through
the engine, these results indicate a vast difference in
composition between the dust on the ground and the
dust reaching the engine components.
Fig. 3: Analysed composition of Saudi Arabian sand
and helicopter engine deposits. (Presented as oxide
species normalized to 100% total.) Averages of
cooling passage powders and vane deposits from 4
engines). Major components.
[17]
As well as differing in chemical composition, the
22 samples analysed by Bessee & Kohl exhibited
different particle size distributions (PSD) from one
location to the next. This is expected, given the great
variability of geology across the globe. However, the

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study also found variation in PSD of airborne
particulate with height above the ground. To test
this, a light armoured vehicle (LAV) was driven along
a dirt road past a 3-metre pole with an array of
sampling containers. As can be imagined, there was
a greater abundance of sub-10µm particles in the
highest placed containers due to their lower terminal
descent speed. In addition, a spike in total mass
collected was found in the container at 1.5m,
assumed to be the result of air currents generated
by the vehicles.
A similar experiment was performed as part of
the Sandblaster 2 study by Cowherd et al.
[27]
in 2007,
which aimed to develop quantitative field information
for rotary wing and tilt rotor aircraft dust clouds to
help evaluate new ‘see-through technologies’ for use
in brownout operations. Using a similar approach to
that described by Bessee & Kohl, their report
gathered data relating to: a. dust cloud densities and
particle size distributions; b. spatial distributions
(heights, distances from rotors); and c. relationship
of dust cloud densities to downward rotor force. No
data on the chemical composition of the samples
taken are available in the open literature. A number
of vertical lift aircraft with intentionally contrasting
downwash signatures were tested.In addition to
illustrating a variation in particle size with height, the
results showed that each aircraft creates a unique
brownout cloud exhibiting differences in dust
concentration and size distribution. The results are
shown in Fig. 4.
Fig. 4: Mass concentrations by particle size band at
the rotor tip location for sixrotorcraft, as taken from
Sandblaster 2 tests
[27]
.
In Fig. 4 one can see that from the data
pertaining to the HH-60 there is an almost equal
mass concentration of particles in the 0-10µm range
as all other size bands, while the CH-53 produces a
relatively low concentration of 10-62µm particles but
a high concentration of larger particles in the 125-
250µm range. The differences are related to the
unique upwash mechanisms created by each main
rotordownwash – a complex mix of merging
detached tip vortices and strong groundwash jets.
Attempts have been made to at least qualitatively
relate the brownout signature to the rotor design
parameters (Refs.
[28], [29]
), but quantitative results are
limited. Nevertheless, the Sandblaster 2results
suggest that consequent degradation rates may be a
function of the aircraft within which the engine is
installed. Incidentally, the Sikorsky HH-60 uses a GE
T700 turboshaft to provide power to the rotor
system.
The above should begin to highlight the
complexity of developing a suitable methodology for
predicting engine degradation that encapsulates all
the contributory parameters.
2.3 Particle Transportand Deposition
If a particle evades removal by the EAPS
system, its journey through the engine will depend
upon its diameter, shape, density, as well as
properties of the carrier fluid, all of which can vary
due to temperature and pressure changes.
Once beyond the EAPS system, an ingested
particle will continue with the main flow to the
compressor stages, which it will most likely pass
through and reach the combustor. A very small
percentage may become attached to surfaces of the
compressor through van der Waals force (the
dominant sticking force for non-molten particles)
while a larger percentage may enter the bleed line
and head towards the turbine blade cooling
passages. The mass of bleed air for turbine cooling
varies, but is typically 3-5% of the inlet mass flow
[30]
.
As mentioned in Hill et al.
[23]
, even small gas
turbines such as the General Electric T700 are
amenable to internal blade cooling. The cooling air is
split between the nozzle guide vanes and rotor
blades of the high pressure turbine, initially following
serpentine multi-pass channels within the blades
before exiting through a number of small holes to re-
join the core flow. The exit holes vary in their
orientation to the oncoming core flow, but are
designed to create a thin layer of cooler air around
the blade to absorb some of the heat from the core
flow and permit the blades to operate in
temperatures beyond their stress limit. For more
details of typical internal cooling channel and film-
cooling hole arrangement, see Han et al.
[30]
.
Such a tortuous path in an increasingly hot
environment presents many opportunities for the
particle to become attached to a surface. If the
viscosity of the particle dictates a high probability of
sticking, the particle may do so on the exit of a bend
of an internal cooling passage, or as it negotiates a
sharp change in direction to pass through a hole in

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the turbine wall. This capture mechanism is known
as inertial impaction. Several investigators have
devised experiments to simulate the effects of
particulate deposition within cooling passages; a
recent review is given by Singh et al.
[18]
.Walsh et
al.
[22]
subjected a 60-hole and a 36-hole coupon, kiln-
heated, to cooling flow containing concentrations of
ISO Coarse and ISO fine test dusts, under different
operating conditions. They found that the rate of
deposition was proportional to the coupon casing
temperature, particulate concentration, and particle
size, and found to be inversely proportional to the
pressure ratio.
The problem is complicated by the inherently
turbulent nature of the flow, which may be added to
by the additionof channel ribs designed to augment
heat transfer. These secondary flows create rotating
eddies that can entrain low Stokes number particles
outside of the wall boundary layer and deposit them
on the channel wall
[18]
. This capture mechanism is
known as eddy impaction.Two other capture
mechanisms present as described by Hamed &
Tabakoff
[9]
are: turbulent diffusion, whereby particles
within the turbulent boundary layer can be swept
towards the wall by turbulent eddies; and
thermophoresis, whereby sub-micron particles are
bombarded by thermally agitated gas molecules and
transported to the wall by impact force. Brownian
motion is a similar mechanism that may cause a
particle to change direction and impact a wall.
Thermophoresis is more applicable to
deposition from the core flow or film coolant to the
blade surface, which is cooler. Surface deposition is
found to be much more prevalent a problem, in
some cases resulting in thick amorphous
agglomerations up to 6 mm thick
[26]
.Almost all of the
recent experimental and numerical investigations in
the open literature on this subject are based
onsynthetic-fuel powered gas turbines for power
generation (Refs.
[10], [14], [20], [31], [32]
).In research by
Bons et al.
[33]
, the increase in surface roughness due
to deposition was found to increase heat transfer by
up to 50% skin friction by up to 300%
[33], [34]
. The
effectiveness of the film cooling is also adversely
affected as it is influenced by the morphology of the
deposit in the vicinity of the cooling holes.
The deterioration process is almost always non-
linear, since the reduction in cooling effectiveness
leads to a hotter blade that accelerates the sticking
process. Furthermore, studies of deposit growth
behavior suggests that entrained particles more
readily adhere to surfaces that have some initial
deposit coverage, as opposed to clean surfaces
[10]
.
In all cases the deposition was seen to increase with
surface temperature, growing faster in between
cooling holes and not in the cooler surface
temperature region in the cooling flow channels. In
some cases the cooling hole may become
completely blocked, which can have disastrous
consequences. Surfaces coated with a thermal
barrier coating generally encourage more sticking
due to their outer surface running hotter, although
the blade itself is cooler.The relationship between
parameters such as hole spacing, hole shape,
coolant blowing ratio, and vane/blade geometry on
deposition mechanics represents the most recent
developments in the literature, as researchers look
for ways to mitigate damage and prolong component
life.
3 PROPOSED METHODOLOGY
From the evidence presented in the preceding
section, a picture emerges of the complexity of
modelling engine degradation due to sand ingestion.
Even characterizing the dust that enters the
helicopter engine is a multi-variable problem. Once
ingested, the likelihood of particle deposition is
dependent on its own mineralogy and Stokes
number, while the morphology of the resulting
surface agglomerate depends on the overall
physical and chemical properties of the adhered
particulate and surrounding flow conditions. The
consequence of deposition is a blocking of cooling
holes and reduction in core flow area.
While separate research has been reported on
desert sand characterization, on particle heating,
and on the effects of deposition on heat transfer at
the blade, all with respect to turbine degradation, to
the authors’ knowledge no studies on predicting the
macro-scale consequences on engine performance
have yet been reported in the literature. To deal with
the multitude of contributory parameters, a
methodology is proposed that takes a multi-block,
gas-particle path analysis approach to modelling the
effect of sand ingestion on helicopter engine
performance. This is depicted in Fig. 5.
3.1 Ingestion Model
The first objective is to ascertain the properties
of the particulate reaching the engine during a
brownout landing, and the rate at which those
particles are ingested.
3.5 Particulate Mass Flow Rate
The Sandblaster 2 study revealed a variation in
the size distribution and concentration of particulate
surrounding the airframe
[27]
and intimated a link
between dust concentration and disk loading but
provided no empirical relationship. The sediment
uplift is thought to be a combination of two
mechanisms created by the rotor wake. A
groundwash jet creates a surface boundary layer
that liberates particles form the surface, while
impinging detached tip vortices loft the particles
higher into the air. Assuming the groundwash jet is

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always large enough to release particles, it follows
that a higher and stronger vortex impingement rate
will result in a fast-forming, dense dust cloud.
However, a large downwash resulting from a high
disk loading may push airborne particulate away
from the helicopter before it can be lifted into the air
by tip vortices.
Fig. 5: Multi-block approach to macroscale modelling
of engine degradation by sand ingestion.
In quantifying these features, Milluzzo &
Leishman
[28]
attempted to relate the brownout
severity level to:a. Total Wake Strength;b. Wake
Vortex Impingement Rapidity. The wake strength
gives a measure of the intensity of the brownout
cloud, and is defined quantitatively as a product of
the tip vortex strength

and the total number of
blades

, normalized with 



. The tip vortex
strength can be approximated as a product of the
blade loading coefficient 


, tip speed 



, and
blade chord 

. Hence, the normalized total wake
strength, 


can be written:
(1) 





















 











Where 

is the rotational frequency,

is the rotor
disk radius,

is the number of rotors, 

is the thrust
coefficient, and is the rotor solidity. is an empirical
constant equal to 2 in hover (from vortex theory).The
rate of production is related to the frequency of
vortex impingement on the ground, and is called the
wake convection frequency,

given by:
(2) 







From this relationship one can see that a helicopter
with a greater number of blades and/or higher rotor
rotational speeds may tend to uplift more sediment
from the ground per unit time, all other factors being
equal. This can be used to establish a quantitative
brownout metric by establishing a reduced
frequency, defined as:
(3) 










And comparing it with the normalized total wake
strength 


and the normalized downwash, defined
as:
(4) 







Where  is the slipstream flow velocity. When
calculated, these values allow a particular helicopter
to be rated in terms of its brownout characteristics.
Based in its rotor design, a helicopter is assigned a
level of 1 to 3 for each of the above metrics. These
levels are based on anecdotal (videographic)
evidence of large set of existing helicopters entering
a brownout landing.
While it is acknowledged that this approach is
macroscale and does not account for many other
contributory factors such as blade tip shape, blade
twist, and local dust type, it can be crudely used to
suggest a dust concentration based on experimental
data. For example, from the Sandblaster 2
experiment (Ref.
[27]
), the V-22 was found to create a
mean volume concentration of 1.62 gm
-3
at the rotor
tip. As a Level 3 rotorcraft according to Milluzzo &
Leishman, this could be used as a benchmark
concentration for all other Level 3 rotorcraft.
However, the concentration at the rotor tip does not
necessarily correlate to the concentration at the
intake; more work is required in this area.
If the concentration is at least estimated (other
technologies exist to directly measure dust cloud
density), the particulate mass flow rate into the
engine, 

is a simple calculation:
Ingestion
Model
• Particulate mass flow rate
• Particle Size Distribution
• Textural Characteristics
• Mineral Composition
Separation
Model
• EAPS Efficiency
• EAPS Pressure drop
• Unseparated Properties
Engine
Model
• Surge Margin
• Power Performance Index
Deposition
Model
• Particle Stokes Number
• Capture Mechanisms
• Accumulation Rate
Deterioration
Model
• Reduction in Flow Parameter
• Cooling Effectiveness
• Blade Lifetime
Rheology
Model
• Particle Sticking Probability
• Particulate Fusibility
• Particle Residence Time

40
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European Rotorcraft Forum, Southampton, Sept. 2014
(5) 





Where 

is the engine mass flow rate and 

is the
particulate concentration by mass. With reference to
the Sandblaster 2 study, dust cloud densities are
usually quoted as a volume concentration, i.e. mass
of particulate per unit volume of carrier fluid. The
conversion to mass concentration is found by
considering each phase’s density and volume, and
is expressed as:
(6) 












Where 

is the gas density, 

is the particle
density, and 

is the volume concentration.
3.1.2 Particle Size Distribution
Particle size distribution (PSD) is one of the
more difficult variables to determine. By performing
a variety of sieving techniques on a sample, one can
establish the PSD of a given area of operation as a
starting point. To determine what proportion of the
size distribution reaches the engine inlet is more
difficult, as the upwash mechanisms may not be
powerful enough to loft all sizes of particles to a
height at height they can be intercepted by the
engine. Since most engines are located directly
below the rotor disk, any particulate that reaches the
engine has probably been re-ingested by the rotor
disk. The recirculatory mode is one of the stages of
a brownout landing identified by Phillips et al.
[35]
,
which happens at low forward speeds and can result
in the formation of a large vortex at the rotor disk
leading edge, causing an appreciable portion of the
flow near to the ground to be re-ingested through the
forward portion of the rotor.Only particles with a low
enough Stokes number will remain entrained in this
vortex, hence through this process, the ground
sediment undergoes a rather rudimentary form of
centrifugal separation.
Characterising that separation is simplified here
by assuming that the mean vortical flow has a
tangential velocity equal to the average induced
velocity

, which through classic momentum theory
for a hovering rotor can be found from rotor design
parameters as:
(7) 











Where  is the rotor thrust (approximately equal to
rotorcraft weight), 

is the rotor disk area, and  is
the disk loading.
The particle size distribution is most usefully
presented as a percentage by mass of a number of
representative sizes. Typically, some form of sieving
(the exact technique depends on the size; smaller
sizes for example can be susceptible to inter-particle
forces that influence results) will be used to
determine the mass of particulate ‘no smaller than’ a
given mesh size. Occasionally the size distribution
may be expressed as number of particles per size
band. In that case, a simple calculation can convert
to mass fraction:
(8) 





















Where 

is the characteristic diameter of the 
size band range (usually the mid-point), 

is the
mean density of the  size band, 

is the number
of particles in the  size band, and 

is the mean
volume shape coefficient of the  size band.
The size distribution can be represented by
an arithmetic mass mean diameter, 

, and an
arithmetic standard deviation, 

:
(9) 









(10) 












Where 

is the number of size bands. This
information allows a more generalized distribution to
be found. Dust sample in nature are commonly
found to exhibit a log-normal distribution that can be
represented by a probability density function of the
form:
(11) 

















This is a well-known distribution, whose
characteristics are given in several mathematics
textbooks.
3.5 Textural Characteristics
The textural characteristics essentially encompass
the angularity and sphericity of the particle, which
influence the particle drag coefficient. The sphericity
is a measure of how compact the volume of an
object is. It is defined as the surface area of a
sphere with the same volume as the particle, divided
by the actual surface area of the particle:
(12)  















Where

is the surface area of the particle,

is the
surface area of a sphere of equivalent volume to the
particle, and 

is the volume of the particle.
Angularity is more qualitative by nature, and is used
as an indicator of a particle’s abrasion history, hence

40
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European Rotorcraft Forum, Southampton, Sept. 2014
is more a measure of the particle’s roundness.
However, it can be used to infer the skin friction
coefficient of a particle.
The two characteristics are not the same, as a
rounded particle may be flat thus have low
sphericity, while a dodecahedron-shaped particle
may have high sphericity but may be considered
angular. The sphericity is used to define a volume
shape coefficient, 

, as featured in Eq. (8) as
follows:
(13) 






A derivation is provided in Bojdo, Ch. 3.2.3
[36]
. For
example an angular particle with   
(qualitatively termed ‘flaky’) will have a volume
shape coefficient of 

 . Similarly, a spherical
particle with    yields a shape coefficient of  
,
as expected for the calculation sphere volume.
3.1.4 Mineral Composition
The chemical composition has been classified
via a number of techniques: atomic emission and
absorption spectroscopy, x-ray crystallography
(commonly known as XRD), scanning electron
microscope, differential thermal analysis,
metallography. Atomic emission and absorption
spectroscopy can be used to determine the minerals
present in a given sample and determine the
elemental composition of given particle. Using XRD,
one can infer the crystallographic structure of the
mineral to inform how the elements are chemically
bonded. For example, high levels of silicon and
oxygen from the elemental analysis indicate that the
material is a silicate mineral, while a three-
dimensional tetrahedral crystal framework may
indicate the silicate family, such as quartz. Within
the silicate family, there can be several forms of the
same mineral. Each of these branches can result in
a different melting point, hence it is important to
determine the mineralogy of the sample as well as
the physical properties.
3.2 Separation Model
Once at the engine inlet, the particles are met
by an EAPS system, as is common on all rotorcraft
operating in the desert nowadays. The EAPS
systems differ by the removal mechanisms they
employ: Inlet Barrier Filters arrest particles on their
surface; Vortex Tubes swirl the flow to centrifuge
particles to an annular scavenge chamber; while a
hump attached to the engine works as the vortex
tubes but axially, in an Integrated Inertial Particle
Separator. The latter two inertia-based separators
require extra mass flow to operate.
3.2.1 EAPS Efficiency
The efficiency of an EAPS system depends on
a number of parameters, including particle Stokes
number, device geometry, scavenge mass flow rate.
For a comprehensive discussion see Ref.
[36]
.
Assuming the device is working at a design point, it
will have agrade efficiency expressed as a function
of particle size, 

. For the present work,
however, it is the particulate that evades capture
that is of interest. The PSD of the ingested
particulate is related to the size distribution
calculated in Eq. (11):
(14)   






Where  is the ingested (unseparated) particle
diameter.
3.2.2 EAPS Pressure Drop
The pressure drop, similar to the efficiency, is a
function of the device geometry and flow conditions.
Analytical expressions exist to predict the pressure
loss across vortex tubes and barrier filters, but it is
more difficult to similarly predict for integrated
particle separators. Inlet barrier filters typically begin
with a pressure loss of around 0.54%, rising to
2.97% as dust accumulates. An analytical study by
the authors revealed a low pressure loss across a
typical vortex tube of around 0.42%, although this
only considered skin friction drag; a more realistic
approximation would be double this. A CFD
simulation of an integrated particle separator by
Taslim & Spring revealed pressure losses of up
0.96%
[7]
. A study by Bojdo & Filippone revealed that
in all cases the pressure loss was a function of the
mass flow rate, with the integrated separator rising
steepest with mass flow rate
[1]
.
3.2.3 Unseparated Particulate Properties
To enable the prediction of engine damage by
ingested particulate, the size distribution calculated
in Eq. (14) can be used. As this represents a
probability density function, the mean diameter of
the contaminant is simply:
(15) 



Smialek et al.
[8]
found that the unseparated
particulate not only had a narrower and smaller size
distribution than the ground sediment PSD, but also
a different chemical composition (see Fig. 3). A
significant reduction in quartz content was found.
This suggests that the smaller sized particles in the
sample are dominated by other minerals, which may
decrease the overall deformation temperature (DT)
discussed in Section 2.1, at which the particulate
begins to stick. It would be useful therefore to

40
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European Rotorcraft Forum, Southampton, Sept. 2014
explore further the change in particulate mineralogy
as the particle size distribution is modified post-
filtration.
The mass flow rate of unseparated particles is
calculated in a similar way, by calculating the mean
separation efficiency, 


 and multiplying it by
the particulate mass flow rate given in Eq. (5):
(16) 






 




This is useful as it gives the true rate at which
particulate enters the engine, in spite of an EAPS
system being in place.
3.3 Rheology Model
The rheology model determines the likelihood
of a single particle adhering if it comes into contact
with a surface. It also determines the temperature at
which the particulate as a whole begins to
agglomerate and potentially glaze.
3.3.1 Particle Sticking Probability
The sticking probability of a single particle is
related back to its mineralogy. It bridges the gap
between the particle melting point, and the solid, as
there exists a small range of temperatures during
which the particle may be soft enough to stick on
impact.This is more common in ash, which has more
particles that undergo glass transition, but is applied
here to create a general case.
A viscosity sticking model is proposed by
Barker
[21]
which draws on a number of authors’ work.
First, a critical softening temperature is defined, 

.
Particles above this have a sticking probability of 1.
Particles much below this have a probability of zero.
For particles in between, the probability function is:
(17) 






Where 

is the current particle temperature, 

is
the viscosity at the critical sticking temperature, and



is the viscosity at the current particle
temperature. The temperature dependence of
viscosity of silicate and aluminosilicate melts can be
described by the following empirical relationship:
(18) 




   





Where  and  are constants that depend on the
chemical composition, or more specifically the
balance of amphoterics and modifiers as described
in Section 2.1. The ratio of non-bridging oxygens to
tetrahedral oxygens,  
  is:
(19)





























Where the terms on the right hand side represent
the chemical formulas of the minerals present. The
constant varies with  
  while both  and 
are determined for two temperature regions (low and
high) and are determined by curve fitting
experimental results. The product is a relationship
between temperature and viscosity in the two
regions; the higher of the two is adopted by Barker.
3.3.2 Particle Residence Time
In order to apply the previous relationship, an
estimate of the particle temperature is required. As it
travels through the compressor, the particle’s
temperature can be assumed to rise in proportion to
the gas temperature. A small portion of the
particulate-laden flow is bled off the compressor to
the internal cooling channels of the compressor
blades, at which point the flow experiences a
sudden increase in temperature, especially within
the wall boundary layer. Conversely, particles that
pass all the way through the combustor and arrive at
the turbine blades may interact with a region of film
cooling and undergo a sudden decrease in
temperature.
To model sudden changes in heat transfer to a
particle, a simple lumped mass approximation is
adopted. Consider the case of particles in the
cooling holes. Initially particles are at the
temperature of the compressor stage at which the
coolant was bled, 

. The ambient gas temperature
is 

. The particle temperature as a function of time
is given as:
(20) 

 







Where  represents residence time and  is the time
constant. The time constant is dependent on
properties of the particle and the heat transfer
coefficient, :
(21)  








Where 

is the particle surface area, 

is the
particle volume, and 

is the specific heat capacity
at constant pressure of the particle. The heat
transfer coefficient, , can be approximated from the
analytic solution for conduction from a sphere.
The specific heat capacity at constant pressure
is assumed to be equal to the value at constant
volume, and can be found by looking again at the
chemical composition of the particle. The specific
heat capacity is estimated by adding the Kopp value
heat capacities of the constituent atoms. For
example, silicon has a heat capacity of 15.9 Jmol
-

40
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European Rotorcraft Forum, Southampton, Sept. 2014
1
°C
-1
, while oxygen has a heat capacity of 16.7 Jmol
-
1
°C
-1
,
which means the heat capacity of quartz (SiO
2
)
is estimated as 49.3 Jmol
-1
°C
-1
. Magnetite, a mineral
also found in desert samples, by comparison has a
heat capacity of 143.5 Jmol
-1
°C
-1
.
3.3.3 Particle Fusibility
The tendency for deposited particulate to fuse
is also included in the rheology model. As single
molten particles stick to turbine surfaces and form a
deposit, the surface temperature can rise due to
inefficient cooling. The individual particles may begin
to agglomerate and form a coherent mass that may
stick more solidly to the turbine blade and insulate
the blade more thoroughly. Davison & Rutke
[11]
predicted the deformation temperature (DT) to be
the critical point at which particles under pressure
begin to sinter and exhibit more fluid-like properties.
A number of other key temperatures were identified
in the heating process that could help to define the
evolution of the deposited material, although more
work is required in this area. An initial step would be
to follow the procedure set by Davison & Rutke.
3.4 Deposition Model
The rheology model and deposition model are
interdependent: the particle trajectory through the
complex domain dictates the residence time hence
particle temperature, and ultimately where the
particle will stick if it meets the sticking criteria.
Likewise, as particles buildup, the flowfield and heat
transfer between the fluid and the blade are
affected, which then influences the particle trajectory
and rheology, and so on.
3.4.1 Particle Stokes Number
The Stokes number can be used to determine
how the fluid and inertial forces will influence the
motion of a particle. The Stokes number is a non-
dimensional parameter that represents the ratio of
particle response time to domain fluid response
time. The particle response time, or how fast the a
particle reacts to the fluid forces imposed upon it,
can be determined by the ratio of the effective
particle momentum to the acting fluid forces:
(22)  










 


Where 

is the particle response time, 

is the fluid
response time, 

is the fluid bulk velocity, and 

is
the characteristic domain length, e.g. hydraulic
diameter. If a particle’s response to the fluid is
dominated by its own momentum forces, its
response time to a change in direction, for example,
will be longer than the fluid response time, resulting
in a Stokes number greater than 1, and vice versa. A
particle whose Stokes number is around unity is
likely to have its motion affected by both bouncing
and fluid forces
[3]
.
The particle shape in a given sample will vary
considerably, which means each has a unique drag
coefficient. It would be impossible to model this, so
without lack of generality the characteristic particle
diameter is that also implemented into Eq. (11).
The typical forces acting on a particle are drag,
gravitational forces, the Saffman lift force due to
shear of the surrounding fluid, added mass,
pressure and viscous forces, Bassett forces due to
fluid acceleration, Magnus lift force due to particle
rotation, forces due to particle rotation, and if the
particle is sub-micron in size, thermophoretic forces
and Brownian motion. For the size range of particles
that are likely to enter the engine i.e. 0.5-25 µm,
(see Ref.
[8]
), and considering the high density ratio of
dispersed to carrier phase, the only significant forces
are drag and gravitational forces
[18]
. Under these
assumptions, the simplified equation of motion of a
particle is given as:
(23)






















Where 

is the particle velocity, 

is the carrier
(gas) velocity, 

is the particle diameter, 

and 

are the gas and particle densities, and 

is the drag
coefficient.
Accurate models exist to predict the drag
coefficient, including those for non-spherical
particles that employ a shape factor as calculated in
Eq. (13), such as the model by Haider &
Levenspiel
[37]
:
(24) 




















Where the coefficients 

are a function of shape
factor, and

is the particle Reynolds number,
defined as:
(25) 











Eq. (24) is valid for Reynolds numbers below 

.
3.4.2 Capture Mechanisms
When the particle is in the vicinity of the wall, it
may experience forces that attract it closer to the
wall and retain it there. Of the four mechanisms
described by Hamed & Tabakoff
[9]
described in
Section 2.3, inertial impaction is the most important
for particles in the range of 0.5-25µm, whereby a
particle impingesa surface by virtue of its
momentum. If a particle’s trajectory takes it close to

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European Rotorcraft Forum, Southampton, Sept. 2014
the wall, it may impinge the surface by virtue of its
bulk; this is known as direct interception and like
inertial impaction, depends on the particle Stokes
number.
In most recent CFD studies on particle transport
in blade cooling holes and turbine nozzles, particles
are tracked in a Lagrangian framework (Refs.
[18], [21],
[38]
). If a particle trajectory impinges a wall, its
collision is assigned as either perfectly elastic
(bounces) or perfectly inelastic (adheres). The
sticking probability model outlined in Section 3.3.1
aims to create an intermediate condition, but
ultimately the process of deposition depends on
many factors and may require a case-specific
empirical model, such as in Ref.
[38]
.
3.4.3 Accumulation Rate
It follows that if deposition can be modelled,
then it may be possible to predictthe gradual
accumulation of a surface deposit that is large
enough to significantly influence the flowfield. An
accumulation model is difficult to derive analytically,
as the location of particle build-up may vary with flow
conditions, pressure ratio, particle properties and so
on. The situation is more conducive to a numerical
solution, as has been attempted in the literature
[18],
[21], [38]
. However, these authors did not model the
effect of accumulation on the flow. Modifying a
computational mesh in such small increments as to
capture individual particle deposition is likely to be
extremely computationally heavy.
A novel Computational Fluid Dynamics (CFD)
simulation is proposed that models turbine cooling
hole blockage. The cooling hole geometry is initially
discretised with a structured mesh, with high cell
density at the wall. A quasi-steady state solution is
solved, whereby particles are tracked in a
Lagrangian framework, then updates to the flow
domain are made based on any particle interactions
with the wall and thermal boundary layer. The
particle’s temperature is updated along the trajectory
and its subsequent sticking probability, as calculated
in Section 3.3.1 is monitored. If the sticking
probability reaches unity, its path is terminated upon
collision with a wall. If the probability is zero, the
collision is considered elastic. For probabilities
between zero and unity, a random number generator
provides a number between 0 and 1; if the random
number generated is greater than the probability of
sticking, the particle reflects off the surface. It follows
that higher particle temperatures will have higher
probabilities of sticking, as the gap into which the
random number can fall decreases. This approach is
adopted from
[21]
.
If a particle is deemed to have adhered, its
location, physical properties and chemical properties
are recorded, along with the cell ID of the location.
Ideally that cell would resemble the shape of the
impacted particle and could be designated as solid.
However, the smallest cell size will still be larger
than the particle size. Instead, the cell’s permeability
and porosity is decreased to imitate the resistance to
flow caused by the presence of the particle. When
the cell’s porosity becomes zero, it is designated as
solid and influences the flow accordingly. After each
deposition ‘cycle’, in which all particle collisions have
updated their respective host cells, the flowfield is
updated and the process repeated. This approach
allows for the gradual accumulation of particulate on
the walls of a cooling hole to be modelled, and has
been applied successfully in a similar way by
Fotovati et al.
[39]
to model particle build-up on a
pleated filter. It allows the temporal reduction in
mass flow or increase in pressure loss to be found
as a function of particulate concentration and other
flow conditions. Since the work is in a nascent stage
and is yet to be verified, results are not presented
here.
3.5 Turbine Deterioration Model
The deterioration of the turbine due to the two
locations of deposition results in three main effects:
a. Increase in overall blade temperature.
b. Reduction in nozzle area.
c. Loss of pressure across stage.
To compute these effects and gain a picture of
overall engine degradation, the following parameters
are determined.
3.5.1 Reduction in Flow Parameter
The gas turbine industry generally uses a term
called flow parameter (FP) for overall estimates of
coolant flow supplied to a particular airfoil. The flow
parameter is a non-dimensional term that is the ratio
of momentum force to pressure force, as discussed
by Hill et al.
[23]
:
(26) FP =









Where

is the coolant mass flow rate,

is the
coolant total temperature,  is the gas constant for
air,

is the coolant total pressure, and 

is the
cooling hole diameter.
Walsh &Thole
[22]
state that when the engine
flow parameter and temperatures are matched to
realistic engine conditions, the residence time of the
air in a component will match the residence time in
the airfoil component during operating conditions,
even if the pressure ratio is not matched. For a
particular airfoil at a given coolant temperature,
there exists a clear relationship between the flow
parameter and the pressure ratio. The flow
parameter only changes if the coolant temperature
changes, or if the geometry changes such as due to

40
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European Rotorcraft Forum, Southampton, Sept. 2014
sand blockage. The percentage reduction in flow
parameter , due to sand blockage is given as:
(27)  





Where 

is the initial ‘clean’ flow parameter. This
parameter allows experimental or numerical
predictions of cooling hole blockage to be translated
to full-scale engine performance predictions.
3.5.2 Cooling Effectiveness
The cooling effectiveness is a dimensionless
parameter that gives an instantaneous evaluation of
the success at which the film cooling is reducing the
heat transfer from hot gas to blade. It is defined as:
(28) 










Where 

is the temperature of the hot-gas stream,


is the adiabatic blade wall temperature, and 

is
the coolant temperature. Rearranging Eq. 25 allows
the blade temperature to be found, assuming the
cooling effectiveness is known.
Igie et al.
[40]
state that the cooling effectiveness
can be obtained empirically for various cooling
techniques using a cooling mass flow function,
defined as:
(29) 




















Where 

is the coolant mass flow rate, 

is the
gas mass flow rate, 

is the coolant specific heat
capacity, 

is the gas specific heat capacity, 

is
the gas Stanton number, 

is the cross sectional
area of the blade on which the bulk gas has an
effect, 

is the number of cooling channels per
blade, 

is the blade perimeter of the coolant
channels of the blade, and  is the blade span.
3.5.3 Blade Lifetime
The consequence of ineffective cooling is an
increase in blade operating temperature upon which
the maximum allowable blade stress will strongly
depend.Under tensile stress, the blade will undergo
creep extension. For example, this maximum stress
may therefore be specified as that stress at which
the blade will not exceed a creep extension of 1%
for 100,000 hours of operation at the temperature in
question (Ref.
[23]
). Since all materials exhibit a loss
of strength with temperature, blade cooling is
essential if gas turbine inlet temperatures are to
continue to rise for better fuel efficiency.
The Larson-Miller time temperature parameter
is often used to evaluate the first rotor blade creep
life due to turbine entry temperature increase, as
described by Igie et al.
[40]
. It is based on the
assumption that an increase in blade operating
temperature will reduce the time taken to reach a
particular creep state. The L-M parameter, P, is
given as:
(30)  








Where 

is the blade operating temperature, 

is
the time to failure, and  is a material constant,
given the value of 20 in this industrial application. (A
value of  is sought for the blade material used in
turboshaft engines).
Igie et al. investigated this for a two-spool
engine, assuming uniform temperature throughout
the blade chord and span and constant cooling
effectiveness, among other constants. Clearly in the
present case these assumptions cannot be made,
but it is thought that this can be overcome by
assuming a quasi-steady approach (reduction over
time of the time to failure, 

). The P value is known
value that depends on the blade material.
3.6 Engine Model
The over-arching aim of the methodology
proposed is to predict engine degradation due to
sand ingestion, and relate this back to the physical
and chemical properties of the contaminant. By
using the equations presented, it should be possible
to calculate to first order accuracy the effect of
cooling hole blockage. This is done using the one-
dimensional gas turbine path anaylsis tool Gas
Simulation Program. The expected outputs are a
transient loss of power, quantified by a power
performance index, and a percentage reduction in
surge margin.
4 Concluding Remarks
A methodology was proposed that draws on the
existing literature on deposition in the hot end
turbomachinery. More specifically, it employs
existing empirical methods and analytical solutions
to quantify the reduction in coolant mass flow and
cooling effectiveness as a result of cooling hole
blockage.
The rate of melting and sticking potential of
ingested sand is dependent on its chemical
properties, while the rate of ingestion of a given
contaminant is dependent on its particle size
distribution and subsequent Stokes number.
Deposition at the turbine stage of a helicopter
engine can occur within the cooling holes or on the
surface of the nozzle guide vane or blade surface.
The melting point is the key parameter to find, but is

40
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European Rotorcraft Forum, Southampton, Sept. 2014
a function of the particle’s mineralogy and is not
simply a number. The softening of a material is an
evolutionary process, governed by the proportion of
mineral compounds in the sample. An important
observation from the literature is that test sands,
while being an appropriate surrogate for real sand in
terms of size distribution, do not represent the
chemical composition of the particles that evade
capture by the EAPS system.
This methodology is being developed to better
predict the degradation of engine performance.
5 References
[1] N. Bojdo and A. Filippone, “Comparative Study
of Helicopter Engine Particle Separators,”
Journal of Aircraft, vol. 51, no. 3, pp. 1030–
1042, 2014.
[2] Sgt Steve Blake RLC and UK Ministry of
Defence, RAF Merlin Helicopter Creates a
“Brownout” Dust Cloud Landing in Afghanistan.
2012.
[3] D. Barone, E. Loth, and P. Snyder, “Fluid
Dynamics of an Inertial Particle Separator,”
2014.
[4] P. H. Snyder, “Particle Separator for a Gas
Turbine Engine,” 6499285 B1, 31-Dec-2002.
[5] F. Saeed and A. Z. Al-Garni, “Analysis Method
for Inertial Particle Separator,” Journal of
Aircraft, vol. 44, no. 4, pp. 1150–1158, 2007.
[6] G. O. Musgrove, M. D. Barringer, K. A. Thole,
E. Grover, and J. Barker, “Computational
design of a louver particle separator for gas
turbine engines,” ASME Paper No. GT2009-
60199, Proceedings of ASME Turbo Exp,
Orlando, FL, 2009.
[7] M. Taslim, A. Khanicheh, and S. Spring, “A
Numerical Study of Sand Separation
Applicable to Engine Inlet Particle Separator
Systems,” Journal of the American Helicopter
Society, vol. 54, no. 4, pp. 42001–42001,
2009.
[8] J. L. Smialek, F. A. Archer, and R. G. Garlick,
“Turbine airfoil degradation in the persian gulf
war,” JOM, vol. 46, no. 12, pp. 39–41, Dec.
1994.
[9] A. Hamed, W. Tabakoff, and R. Wenglarz,
“Erosion and deposition in turbomachinery,”
Journal of Propulsion and Power, vol. 22, no.
2, pp. 350–360, 2006.
[10] W. Ai, N. Murray, T. H. Fletcher, S. Harding, S.
Lewis, and J. P. Bons, “Deposition Near Film
Cooling Holes on a High Pressure Turbine
Vane,” Journal of Turbomachinery, vol. 134,
no. 4, p. 041013, 2012.
[11] C. R. Davison and T. A. Rutke, “Assessment
and Characterization of Volcanic Ash Threat to
Gas Turbine Engine Performance,” J. Eng.
Gas Turbines Power, vol. 136, no. 8, pp.
081201–081201, Mar. 2014.
[12] M. J. Scimone, D. Flesher, and S. Frey, “High
Performance Barrier Filtration Systems,” in
Proceedings of the 56th American Helicopter
Society Annual Forum, Virginia Beach, VA,
2000.
[13] J. P. Van Der Walt and A. Nurick, “Life
prediction of helicopter engines fitted with dust
filters,” J Aircraft, vol. 32, no. 1, pp. 118–123,
Jan. 1995.
[14] S. A. Lawson and K. A. Thole, “Effects of
simulated particle deposition on film cooling,”
Journal of Turbomachinery, vol. 133, no. 2, p.
021009, 2011.
[15] M. Shinozaki, K. A. Roberts, B. van de Goor,
and T. W. Clyne, “Deposition of Ingested
Volcanic Ash on Surfaces in the Turbine of a
Small Jet Engine,” Adv. Eng. Mater., vol. 15,
no. 10, pp. 986–994, Oct. 2013.
[16] W. Song, K.-U. Hess, D. E. Damby, F. B.
Wadsworth, Y. Lavallée, C. Cimarelli, and D.
B. Dingwell, “Fusion characteristics of volcanic
ash relevant to aviation hazards,” Geophys.
Res. Lett., vol. 41, no. 7, p. 2013GL059182,
Apr. 2014.
[17] G. B. Bessee and K. B. Kohl, “Characterization
of CONUS and Saudi Arabian Fine-Grained
Soil Samples,” DTIC Document, 1993.
[18] S. Singh, D. Tafti, C. Reagle, J. Delimont, W.
Ng, and S. Ekkad, “Sand transport in a two
pass internal cooling duct with rib turbulators,”
International Journal of Heat and Fluid Flow,
vol. 46, pp. 158–167, Apr. 2014.
[19] J. Kim, M. G. Dunn, A. J. Baran, D. P. Wade,
and E. L. Tremba, “Deposition of Volcanic
Materials in the Hot Sections of Two Gas
Turbine Engines,” J. Eng. Gas Turbines
Power, vol. 115, no. 3, pp. 641–651, Jul. 1993.
[20] S. S. Sreedharan and D. K. Tafti, “Composition
Dependent Model for the Prediction of Syngas
Ash Deposition With Application to a Leading
Edge Turbine Vane,” in ASME Turbo Expo
2010: Power for Land, Sea, and Air, 2010, pp.
615–626.
[21] B. J. Barker, “Simulation of Coal Ash
Deposition on Modern Turbine Nozzle Guide
Vanes,” The Ohio State University, 2010.
[22] W. S. Walsh, K. A. Thole, and C. Joe, “Effects
of sand ingestion on the blockage of film-
cooling holes,” GT2006-90067, 2006.
[23] P. G. Hill and C. R. Peterson, Mechanics and
thermodynamics of propulsion, vol. 1. Addison-
Wesley, Reading, Massachusetts, 1992.
[24] A. Filippone and N. Bojdo, “Turboshaft engine
air particle separation,” Progress in Aerospace
Sciences, vol. 46, no. 5–6, pp. 224–245, Jul.
2010.

40
th
European Rotorcraft Forum, Southampton, Sept. 2014
[25] J. P. Van Der Walt and A. Nurick, “Erosion of
Dust-Filtered Helicopter Turbine Engines Part
II: Erosion Reduction,” J Aircraft, vol. 32, no. 1,
pp. 112–117, Jan. 1995.
[26] J. L. Smialek, F. A. Archer, and R. G. Garlick,
“The chemistry of Saudi Arabian sand - A
deposition problem on helicopter turbine
airfoils,” in 24th International SAMPE
Technical Conference, 1992, vol. 24, p. 63.
[27] C. Cowherd Jr, “Sandblaster 2 support of see-
through technologies for particulate brownout,”
DTIC Document, 2007.
[28] J. Milluzzo and G. Leishman, “Assessment of
Rotorcraft Brownout Severity in Terms of Rotor
Design Parameters,” Journal of the American
Helicopter Society, vol. 55, no. 3, pp. 032009–
1, 2010.
[29] B. Johnson, J. G. Leishman, and A. Sydney,
“Investigation of Sediment Entrainment Using
Dual-Phase, High-Speed Particle Image
Velocimetry,” Journal of the American
Helicopter Society, vol. 55, no. 4, pp. 42003–
42003, 2010.
[30] J.-C. Han, S. Dutta, and S. Ekkad, Gas turbine
heat transfer and cooling technology. CRC
Press, 2012.
[31] N. D. Cardwell, K. A. Thole, and S. W. Burd,
“Investigation of Sand Blocking Within
Impingement and Film-Cooling Holes,” J.
Turbomach., vol. 132, no. 2, pp. 021020–
021020, Jan. 2010.
[32] N. Sundaram and K. A. Thole, “Effects of
Surface Deposition, Hole Blockage, and TBC
Spallation on Vane Endwall Film-Cooling,” in
ASME Turbo Expo 2006: Power for Land, Sea,
and Air, 2006, pp. 407–418.
[33] J. P. Bons, J. E. Wammack, J. Crosby, D.
Fletcher, and T. H. Fletcher, “Evolution of
Surface Deposits on a High-Pressure Turbine
Blade—Part II: Convective Heat Transfer,”
Journal of Turbomachinery, vol. 130, no. 2, p.
021021, 2008.
[34] J. P. Bons, R. P. Taylor, S. T. McClain, and R.
B. Rivir, “The many faces of turbine surface
roughness,” Journal of Turbomachinery, vol.
123, no. 4, pp. 739–748, 2001.
[35] C. Phillips, H. W. Kim, and R. E. Brown,
“Helicopter brownout - Can it be modelled?,”
Aeronautical Journal, vol. 115, no. 1164, pp.
123–133, 2011.
[36] N. Bojdo, “Rotorcraft Engine Air Particle
Separation,” PhD Thesis, University of
Manchester, 2012.
[37] A. Haider and O. Levenspiel, “Drag coefficient
and terminal velocity of spherical and
nonspherical particles,” Powder technology,
vol. 58, no. 1, pp. 63–70, 1989.
[38] K. Brun, M. Nored, and R. Kurz, “Particle
Transport Analysis of Sand Ingestion in Gas
Turbine Engines,” Journal of Engineering for
Gas Turbines and Power, vol. 134, p. 012402,
2012.
[39] S. Fotovati, H. V. Tafreshi, and B.
Pourdeyhimi, “A macroscale model for
simulating pressure drop and collection
efficiency of pleated filters over time,”
Separation and Purification Technology, vol.
98, pp. 344–355, Sep. 2012.
[40] U. Igie and O. Minervino, “Impact of Inlet Filter
Pressure Loss on Single and Two-Spool Gas
Turbine Engines for Different Control Modes,”
J. Eng. Gas Turbines Power, vol. 136, no. 9,
pp. 091201–091201, May 2014.
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