# Reliability and Preventive Maintenance
of Ducted Wind Turbines

Shafat Sharar, Clarkson University
Carl D. Hoover, Clarkson University S. Sharar is graduate student at
Department of Mechanical and Aerospace Engineering, Clarkson University, New
York, USAC. D. Hoover is faculty at Department of Mechanical and Aerospace
Engineering, Clarkson University, New York, USA

###### Abstract

This paper presents a reliability life analysis and preventive maintenance
schedule for ducted wind turbines. Ducted wind turbines (DWT) are an emerging
segment of the renewable energy industry with innovations that promise
reliable, efficient, low-cost energy for consumer and small business markets.
Many attempts have been made to build viable ducted turbines over the last
century, but until recently none have succeeded commercially. Optimal shroud
and blade designs are the focus of most engineering research to improve
performance and efficiency, however, we hypothesize that an equally important
key to the long-term success of small wind innovations is reliability
analysis. For consumers and companies who want to efficiently maximize the
lifespan of DWTs, this has significant ramifications. Operating beyond service
life can result in catastrophic component failure and high replacement costs,
making the technology economically infeasible. Our approach is focused on the
analysis of 3.5 kW D3 turbines manufactured by Ducted Wind Turbines, Inc. We
develop a component-level reliability analysis using ASTM E3159 and a
consumer-level preventative maintenance schedule including failure modes and
life estimates. Future research can use these findings to guide options for
DWT life extension as well as localized maintenance solutions meant to reduce
operational costs while preserving energy output.

###### Index Terms:

reliability, preventive maintenance, maintenance schedule, ducted wind turbine

##  I Introduction

Renewable Energy is a developing energy sector with continued global warming
trends and energy demands driving research to make it more reliable and
accessible. Recent trends show that renewable energy adoption in the forms of
solar, hydropower, and small wind have increased since 2019. Total wind power
capacity in the US has increased from approximately 105 GW to 135 GW in 2
years [1] and is further projected to exceed 400 GW by 2050 [2]. According to
the Global Wind Energy Commission (GWEC), the rate of wind energy adoption has
increased in the last 6 years totaling a capacity of 743 GW worldwide [3]. It
is also expected that the wind energy market will have an average compound
annual growth rate (CAGR) of 4% each year. Different engineering optimizations
of wind energy production are being researched to improve efficiency and make
wind power more accessible to consumers. Ducted wind turbines (DWT) are one
new technology that promises highly efficient energy generation in a compact
form. [4]

A ‘duct’ on a turbine is an annular concentric shroud around the turbine that
helps channel airflow to improve efficiency. The shroud cross-section
typically has an airfoil-shaped profile. Ongoing studies at Clarkson
University have focused on the aerodynamic performance of ducted turbines [5,
6, 7]. Solar energy, while being popular and still having an upward trend,
becomes ineffective during nighttime [8]. Since energy storage is costly, a
wind turbine in conjunction can offset solar inefficiency. The small wind
sector has seen increased research and development investments, and with the
continuing trend of shifting to 100% renewable energy, small wind is projected
to be an integral part of the common household in the US by 2050 [2].

The IEC defines small wind turbines as having a rotor-swept area of up to
$200m^{2}$ generating power at a voltage below 1000 V AC or 1500 V DC [9].
They typically produce between 500 W and 10 kW. However, power ranges vary
depending on multiple factors and local standards. One of these factors is the
presence of a duct around the rotor. The duct concentrates the flow enabling
higher rotor rotation and efficient power generation compared to open turbines
[10].

Ducted wind turbines are more compact and are less susceptible to
environmental damage, compared to open-rotor turbines. Recent developments and
optimizations in DWTs have shown promising results. For example, the selection
of the rotor power coefficient as a design parameter changes the nature of the
annual energy production (AEP) optimization, which leads to turbine size
minimization compared to open rotor turbines [7]. The key cost driver in this
study was lowering turbine thrust, which both reduces the cost and increases
AEP.

Further design optimization can be the type of airfoil used. An example study
has been carried out by Kummer [6] where cambered plate airfoils were studied
and compared to conventional and flat airfoils. The results showed that
cambered plate airfoils can reduce the manufacturing cost greatly for a
similarly performing conventional airfoil at Reynolds number of $40,000$.

Predictive Maintenance (PdM) typically refers to a data-driven tool that uses
machine learning (ML) and statistical models to predict system failure trends
and behavioral patterns to enable early fault detection and optimal
maintenance plans, to avoid downtime [11]. Preventive maintenance (PM) on the
other hand is maintenance on a regular predetermined intervals to minimize the
chance of component failure from regular use. It is useful to discuss the
concept of life-limiting which is to replace in-service components after a
predetermined life. This is usually done for components having increasing
failure rates with age [12]. The maintenance schedule is often specified
contractually. Usage outside the suggested scenario may shorten system life.
Using a maintenance schedule geared towards commercial wind is not recommended
for small wind systems as it may be costly and unrealistic for potential
customers. An ML model aims to provide better insight into product behavior
and information on making on-demand maintenance schedules for DWTs.

A repairable system is defined as one that can be repaired and reused several
times before retiring. On the contrary, a non-repairable system is retired
after its first failure. A key metric for repairable systems is the mean time
between failures (MTBF), the mean failure time between failures. Mean time to
failure (MTTF) refers to the average life duration up to the first failure.
MTBF applies to all sequences of repair and restoration cycles over a service
life period. Another metric termed $B_{p}$ life represents the p-th percentile
of the life distribution. For example, $B_{10}$ life corresponds to a time
value, $t$ when the cumulative distribution function (CDF), $F(t)$ is equal to
$10\%$. In general, though no existing turbine specifications are presently
available, a DWT aims to achieve a high MTBF and $B_{p}$ life.

An appropriate measure of life needs to be determined before assessing
reliability. Operating time, cycles of usage, demand cycles, and calendar days
are similarly valid measures of life but relate to different activities. For
example, ‘cycles’ may last for any duration for however many cycles whereas
‘calendar time’ denotes continuous usage over that time. Life for less complex
systems is generally expected to be longer, as fewer sub-systems and/or
components are prone to failure. Small wind systems such as DWTs have fewer
components compared to their larger, open-rotor counterparts. This leads to
choosing the appropriate units for life measurements, whether years, weeks,
days, or hours. On a component level, however, multiple lifing measures and/or
units may be used for the sake of calculation. These different units can then
be unified with recommended usage conditions. One point to note during
calculations is that the duty cycle may vary depending on the system
configuration of the DWT, e.g. braked or running, affecting its service life.

Of the three general failure modes, infant mortality or early failures
occurring in some units due to special causes can be avoided by conducting a
“burn-in” application during a “break-in” period. Random failures in wind
turbines may be caused by collisions with birds, lightning strikes, flying
debris during strong gusts or hurricanes, etc [13, 14, 15]. The blades are the
most vulnerable to these external failures. For example, a total of 8 turbines
had catastrophic failures in China because of typhoon Usagi in 2013 [16].
Random-type failure modes are assumed for reliability planning in the design
phase. Wear-out failure mode is generally caused by gradual performance
degradation. In wind turbines, the most likely worn parts are moving parts
such as the yaw bearings, rotor bearings, and slip rings. In modeling these
failure modes for each component or subsystem, a broad approach is to make use
of the ‘bathtub curve’ (shown in figure 1) which depicts the failure rate over
time. For a wind turbine system, where the failure rate is variable, the
average failure rate over an interval can be calculated. Wind speed
distribution can be modeled by a Weibull curve [17, 18] from which the
instantaneous failure rate curve as well as the average failure rate over an
interval can be calculated in closed form.

Figure 1: The Bathtub curve is a general representation of type and
possibility of failures over time.

In determining reliability, a test plan is set up which generally consists of
sample size, the test duration, and a life requirement. Reliability
requirements are generally met at some confidence level such as 90% or 95%. In
case the confidence is unspecified, it is assumed to be 50%. Life requirements
imply a measure of life and reliability at the stated life. For economical and
timing purposes, an accelerated test is used where usage severity is higher
than regular usage. This is done by tuning parameters and variables according
to available accelerated models such as the Power-Weibull model [19]. This
model can be applied to ball or roller bearings testing, which are common
components in wind turbines. A distribution assumption may be made based on
the data properties, engineering knowledge, or prior performance. Furthermore,
based on the parameters of the assumed distribution, additional variations
will exist.

Field performance data are the principal indicators of reliability. Frequency,
timing, severity, and cause of failure occurrences are the key reliability
intelligence known as reliability data. Bench testing is done in development
activity, but it may be difficult to emulate all possible field conditions,
which is the case for DWTs. Often the case for such emerging technologies
during bench or field testing is right suspension. If a unit is functioning
without failure after a specific time, it is called a right suspension or a
“run-out”. Hence the failure time which is now unknown, is in the future or to
the right of the timeline.

The DWT system is a set of interconnected and interacting components and
subsystems that function as a whole. Although systems can have multiple
configurations, they have two fundamental types, series, and parallel. A
series configuration is analogous to a chain made up of links. The chain
system fails if at least one of the links fails. Whereas a parallel system
will continue functioning if at least one of the components functions. Complex
systems can combine multiple series and parallel configurations. In a simple
analysis of system reliability, the individual component reliability is
assumed to be independent of each other. So, it is possible to calculate the
system reliability from the reliability of each component or subsystem. This
simplification can be made to a certain degree based on the system properties.
It is to be noted that, in calculating reliability, the failure probability
may also be used as it is complementary to it.

There are several ways of calculating reliability or failure depending on the
selected failure type, reliability measure, and available data. The
probability plotting technique is the most appropriate for the DWT reliability
data. The assumed cumulative distribution function (CDF) versus the time plot
is scaled so that a straight line can be approximated. The slope of the line
corresponds to the respective parameter of the assumed distribution. The
system MTTF is a function of the rate of each component. The easiest way to
calculate system MTTF and associated distribution is to use Monte Carlo
simulation.

The configuration of the blade pitch angle induced by the effect of rotor tilt
affects blade fatigue life as determined by Hoghooghi [20] from testing a sub-
scale model. This may be a useful lifing factor depending on the rotor
configuration of current and future iterations of DWTs.

The remaining useful life (RUL) is the usable life left on a component at a
specific time during operation. Depending on the type of repair, the RUL of a
unit may either increase, decrease or remain the same. For example, a simple
renewal process would restore the unit almost to its new condition. It is
important to count the number of repairs during a service life period, which
also includes replacements. Repair events are exponential for random type
failures and the number of events is Poisson distributed.

The DWT is manufactured by Ducted Wind Turbines, Inc. and exclusively uses
patented technology from Clarkson University proven as a commercially feasible
small wind turbine. The purpose of the duct is to maximize energy extraction
from the air that passes through the rotor. The efficiency metric is the power
coefficient, $C_{p}$, which is the ratio of electrical power output to the
wind power input. The Betz limit is known as the limiting factor to the
efficiency in classical open rotor turbines, where maximum power coefficient,
$C_{p,max}$ is $\nicefrac{{16}}{{27}}$. The research from Jamieson [21] shows
that augmenting airflow with a duct affects this limit such that-

$C_{p,max}=\frac{16}{27}(1-a_{0})$

where, $a_{0}$ is the axial induction factor (the fractional decrease in wind
velocity between the free stream and the rotor plane) at the rotor plane. For
open rotor systems, $a_{0}$ is $0$. The total power coefficient, however,
remains within the Betz limit. A significant benefit of the duct is that it
comparatively reduces the overall size of the turbine making it easier to
install and maintain by customers. Masukume states that lack of
commercialization and appropriate engineering techniques for maintenance are
shortcomings of small ducted turbines [22]. The engineering and optimizations
in DWT design eliminates the economical drawbacks of historical small wind
turbines by reducing cost per kilowatt electricity generated [7].

Figure 2: Schematic diagram of the Ducted Wind Turbine with visible components
labeled.

The DWT can be segmented into 3 major sections, the foundation, the tower or
pole, and the nacelle. Figure 2 shows a labeled diagram of the DWT. The
foundation is the first step to installing a DWT, on which the tower stands.
The base part of the tower is installed with the foundation, while the rest of
it is assembled with the nacelle and finally lifted up with the help of a
screw jack, which remains attached for easy lowering and/or raising of the
turbine in the future. The nacelle and tower are coupled via a slewing
bearing, which enables yaw action.

In the Ducted Wind Turbines, Inc. D3 ducted turbine, the shroud or duct is
composed of four equal duct sections connected via custom-fabricated
connectors. The connectors are made of aluminum with female sockets on either
side corresponding to recessed male ends on each duct sector. The male ends of
each duct accept the connectors such that the surface of the duct remains as
smooth as possible. 32 screws secure each connector to the duct sections via
rivnuts installed in the duct. The duct is rotationally molded and made of
proprietary PVC composite material. Its width is roughly 0.6 m and the
enclosed diameter is roughly 3.7 m. The duct not only concentrates airflow but
the airfoil structure of the cross-section also acts as a passive yaw
controller aligning the rotor axis direction to that of the wind. In current
designs, there are a total of 5 pressed aluminum blades connected to the
rotor, which then couples directly to the generator. As blade designs evolve,
blade materials and types are expected to change. A slip ring connects the
wiring from the generator throughout the tower to the controller after passing
through a shunt. The shunt is an electrical braking system that is employed if
the turbine needs to be stopped for any reason. This braking is controlled by
the controller unit.

Figure 3: Schematic of the power flow in a typical DWT unit. The three lines
represent a 3-phase AC line, while single line represents DC.

Power transmission is done similarly to transmission in other renewable energy
technologies. Generator power is transmitted to a controller which rectifies
it and routes to either the brake resistors or the inverter. The inverter
regulates this power for the consumer power line and the grid as needed. A
simplified flow chart is shown in Figure 3 for the power transmission in a
typical DWT unit. A control system is built around the electromechanical
system. This monitors the components and other sensors attached to the DWT,
and controls the overall unit.

##  II Preventive Maintenance

Preventive Maintenance (PM), or more commonly known as Scheduled Maintenance,
is a routine or scheduled inspection and maintenance put in place to identify
developing or developed irregularities in system components. The goal of this
practice is to repair these irregularities or replace the affected
component(s) before they cause major failure to the system. The prime
directive of PM is to improve system reliability and increase component life.
Benefits of PM are system downtime reduction, system RUL enhancement,
operators and maintenance mechanics’ safety, and overall process cost
reduction [23].

PM is an established practice employed in industrial systems as well as
consumer equipment. The way PM works is by following a maintenance schedule.
It documents a time-frame for the schedule, the required maintenance tasks,
the typical operating conditions, and relevant comments to further improve the
scheduling. The maintenance schedule is the result of an engineering analysis
on reliability and life of the system components. The DWT system is a
relatively simple one as discussed in the introduction. This part of the paper
discusses reliability analysis on some of the major DWT components with a goal
of building an initial maintenance schedule. The component analysis is
anchored around the ASTM E3159-21, ‘Guide for General Reliability’ [12].

First, we identify and list the components of the DWT down to the fasteners. A
bill of materials (BOM) from Ducted Wind, Inc. helps in this regard. The list
is grouped by the four DWT subsystems ‘Structural’, ‘Electromechanical’,
‘Control’, and ‘Fasteners’. While fasteners are integral to the other systems,
we consider them as one distinct system because their analysis is fairly
uniform. The analysis uses manufacturer specified life whenever available,
documenting rated conditions. Some components, however, either have no
manufacturer-recommended service data or are custom manufactured. This section
of the paper analyzes those components and produces an in-depth analysis with
relevant assumptions and operating conditions.

###  II-A Foundation

The ballasted foundation contains sand and gravel which are subjected to
constant weathering and erosion. This type of foundation requires
replenishment of ballast when the level reaches a predetermined low. This
weight is uniformly distributed on the base and provides foundational strength
required to counteract the tipping moment of the tower. The ballast weight is
found from an analysis by Daniel Valyou111Daniel Valyou is the Chief Engineer
at Ducted Wind Turbines, Inc. by taking the sum of moments on the tower.

$\displaystyle\sum M=0$ $\displaystyle\implies$ $\displaystyle
T_{\text{turbine}}d_{\text{turbine}}-Wd_{\text{base}}=0$
$\displaystyle\implies$ $\displaystyle
W=T_{\text{turbine}}d_{\text{turbine}}n/d_{\text{base}}$

where, $T_{\text{turbine}}$ is the turbine thrust, $d_{\text{turbine}}$ is the
largest diameter of the nacelle, $n$ is the factor of safety and
$d_{\text{base}}$ is the foundation base diameter. The weight of the ballast
is a function of the ballast volume, $V_{\text{ballast}}$, which in turn is a
function of depth, $h_{\text{ballast}}$. So the weight is the product of
density and volume-

$\displaystyle W$
$\displaystyle=\rho_{\text{ballast}}V_{\text{ballast}}=f(V_{\text{ballast}})$
[density of ballast is constant]

And the volume is the product of the cross-sectional area of the base and the
depth-

$\displaystyle V_{\text{ballast}}$
$\displaystyle=A_{\text{base}}h_{\text{ballast}}=f(h_{\text{ballast}})$ [area
of the base is constant] $\displaystyle\therefore W$
$\displaystyle=f(h_{\text{ballast}})$

Hence, the depth or level can be a linear function of weight. The maintenance
task then is to inspect the level of the ballast every year and replenish it
as necessary to maintain the required weight. A reinforced cement concrete
(RCC) foundation has a longer life and does not require replenishment.
However, it is subject to erosion causing permanent damage. Especially when
weather conditions cause frequent freezing and thawing. The repair for the RCC
foundation is to remove and recast.

###  II-B Tower/Pole

The tower is connected to the foundation. This acts as a compression member
with the vertical eccentric loading from the weight of the nacelle and the
moment loading from the yaw rotation at the slewing bearing.

The analysis report by Valyou further evaluates a finite element analysis
(FEA) model of a DWT unit at the Council Rock Enterprises, Inc. facility in
Rochester, NY. The loads used are for a $109$ mph ($48.72ms^{-1}$) 50-year
extreme gust loading case with 3-second gusts. Valyou selects a worst-case
loading direction for the tower where the moment arm is minimum from the tower
center line and the perimeter. For the selected operating conditions the total
turbine thrust is $6035$ N. With a hub height of $1.934$ m, the moment at the
tower turbine mating flange is $11672$ N-m. The material ASTM A36 steel is
uniform throughout the tower. The determined loads from the report are $1572$
lb-f load from the nacelle weight, $100$ lb-f load along the tie rods, and
$81,500$ ft-lbs tipping moment about the axis perpendicular to azimuth and
rotor axes. The FEA simulation results showed maximum values of 1st and 3rd
principal stresses and Von Mises stress as $16.57$ ksi, $8.67$ ksi, and
$\sigma^{\prime}=13.56$ ksi respectively.

With the analysis in place, we can verify the results using the formula for a
column with eccentric loading.

$\displaystyle\frac{d^{2}y}{dx^{2}}+\frac{P}{EI}y=-\frac{Pe}{EI}$ (1)
$\displaystyle\delta=e\left[\sec{\sqrt{\frac{P}{EI}}\frac{1}{2}}-1\right]$ (2)
$\displaystyle\frac{P}{A}=\frac{S_{yc}}{1+\frac{ec}{k^{2}}\sec{\left(\frac{l}{2k}\sqrt{\frac{P}{AE}}\right)}}$
(3)

This is the secant column formula. $P$ is the eccentric load, $E$ is Young’s
modulus for the tower material, $I$ is the moment of inertia, $\delta$ is
column deflection, and $l$ is the height. Here $ec/k^{2}$ is known as the
eccentricity ratio in which, $e$ is eccentricity, $c$ is centroidal distance
in the tower cross section (typically a circle), and $k$ is the radius of
gyration.

For the lifing estimate, we use the fatigue life method. The endurance limit
is defined by-

$\displaystyle S_{e}^{\prime}=0.5S_{ut}$ (4) $\displaystyle
S_{e}=k_{a}k_{b}k_{c}k_{d}k_{e}k_{f}S_{e}^{\prime}$ (5)

where $S_{ut}$ is the minimum ultimate tensile strength which is 58 ksi,
$k_{a}$ through $k_{f}$ denote Marin modification factors related to the
operating conditions under which the endurance limit is modified to be
$S_{e}$. For the tower in axial loading and a 95% reliability, the
modification factors are shown in table I.

TABLE I: Marin Endurance Limit Modification Factors for Tower Factor | Condition | Value
---|---|---
$k_{a}$ | Machined surface | 0.92
$k_{b}$ | No size effect | 1.00
$k_{c}$ | Axial loading | 0.85
$k_{d}$ | Ambient temperature | 1.00
$k_{e}$ | 95% desired reliability | 0.87
$k_{f}$ | No miscellaneous effects | 1.00

Plugging these values result in an endurance limit of 19.68 ksi. We can use
these values to estimate the remaining life with the following equations-

$\displaystyle N=\left(\frac{\sigma^{\prime}}{a}\right)^{1/b}$ (6a)
$\displaystyle a=\frac{(fS_{ut})^{2}}{S_{e}}$ (6b) $\displaystyle
b=-\frac{1}{3}\log\left(\frac{fS_{ut}}{S_{e}}\right)$ (6c)

Here $f$ is the fatigue strength fraction which we take as 0.9. Solving for
the constants $a$ and $b$ and plugging them in to $N$ results in approximately
14M cycles. This is true only in case of fully reversed stress, denoted by
$\sigma^{\prime}$. The stress from the FEA report is a combined stress so we
expect the tower life to be much greater than this. We can define a cycle as
complete rotations of the nacelle, or oscillations of average wind direction
angle changes. If we assume the tower going through 1000 fully reversed stress
cycles per day, this will translate to 365,000 cycles a year or a life of over
38 years.

###  II-C Pole Raising System

The screw jack is a pole-raising and lowering system. The turbine can be
lowered for securing during hazardous weather conditions or for maintenance
and raised afterward. The manufacturer lists maintenance tasks of lubrication
and dust filter replacement every 15 cycles, where a cycle is referred to as 1
raising and 1 lowering task combined. They estimate life at 100 cycles or 5
years, whichever comes first. After the manufacturer specified life, the jack
is to be inspected for wear in gearing and screws. In the case of a custom-
manufactured pole raising system where a maintenance schedule is unavailable,
or if a sub-component is replaced, the life is a function of the life of the
installed gears and screws.

The possible failure modes are determined from the specified maintenance tasks
and sub-components. For example, a dust filter signals a possibility of
accumulation of debris that can interfere with the lubrication and increase
friction causing wear in the gearbox. Additionally, the motor operating the
screw jack can fail independently, so, it is imperative to use a compatible
screw jack and tower.

###  II-D Standpipe Assembly

The standpipe assembly is a welded steel component that couples with the inner
slewing bearing ring. The stress concentration points are near the flanges
where the curvature is the lowest and are the main locations of wear and crack
formation. The hub integrates into the top of this assembly and the generator
sits inside the hub. A previous iteration of the DWT used aluminum as the
material for the standpipe assembly. The component sagged in due to the load
causing the attached strut to sag with it. This caused one of the blades to
hit the duct causing the blade to bend and fail. This event shows the
importance of material selection and tracking relative component position and
resulting vibrations. An accelerometer may be fitted to these components for
this purpose. We discuss more possible sensors for tracking maintenance and
failures in the later chapters.

###  II-E Slewing Bearing

The slewing bearing is the major component in the yaw motion of the DWT. It
affects the direction of the rotor and the amount of energy extracted from the
wind. Slewing bearings primarily carry axial and moment loads. The make and
model of the bearing used in the current iteration of DWT is the Silverthin
STO-145T.

We follow a slewing bearing design guide for the equations. Moreover, we
consult a recent study on fatigue failure of slewing bearings that works with
a similar bearing to the one in the DWT. The National Renewable Energy
Laboratory in the United States published their yaw and pitch rolling bearing
design guideline [24] which specifies the basic dynamical axial load rating as
follows-

$C_{a}=f_{cm}(i\cos{\alpha_{c}})^{0.7}Z^{2/3}D_{r}^{1.8}\tan{\alpha_{c}}$ (7)

where $f_{cm}$ is the raceway groove factor which is the ratio of the groove
radius and ball diameter, $D_{r}$. $Z$ is the number of balls, $i$ is the
rolling element row, and $\alpha_{c}$ is the ball and raceway contact angle.
However, since the bearing in DWT is not a continuously rotating type, but
rather an oscillating type, the basic dynamic axial load is modified (as per
regular operating conditions) as follows-

$C_{a,osc}=C_{a}\left(\frac{180^{\circ}}{\theta}\right)^{1/p}$ (8)

Here $\theta$ is half of the total arc traced during a cycle of oscillation
and $p$ is 3 for ball bearings. We conservatively assume $\theta=30^{\circ}$
from the average turbine/wind direction data. It is important to note that
this range of oscillations occurs during gusts, so life should be greater than
the conservative result.

The dynamic equivalent axial load rating is shown below-

$P_{ea}=0.75F_{r}+F_{a}+2M/d_{m}$ (9)

Here, $F_{r}$ is radial load, $F_{a}$ is axial load, $M$ is the overturning
moment, and $d_{m}$ is the bearing diameter up to the raceway center. Finally,
the life can be estimated with the $L_{10}$ formula which is defined as-

$L_{10}=\left(\frac{C_{a,osc}}{P_{ea}}\right)^{3}$ (10)

We correct for the life estimate using ANSI/ABMA standard modified rating life
formula-

$L_{nm}=a_{1}a_{2}a_{3}a_{4}L_{10}$ (11)

Here, the lifing modification factors $a_{1}$ through $a_{4}$ are for
reliability, bearing steel material, lubrication and flexible supporting
structure respectively.

With most of the dimensional data found from available CAD models of the
bearing, we perform the calculations required. Assumptions are that the
raceway groove factor conforms to that of 0.53. Also that the bearing uses
common materials. We assume a reliability of 90%. Table II shows the geometric
data and modification factor values used. The results show that the bearings
have a modified life of 1.49M oscillations. This translates to a theoretical
number of raceway stress cycles of $T=L_{nm}Z=44.89$M cycles. The bearing
oscillates with wind direction which we estimate to be about 1,500 times per
day on average. This translates to about 550,000 per year or a life of 80
years.

TABLE II: ANSI/AGMA Life Modification Factors Factor | Condition | Value
---|---|---
$a_{1}$ | 90% desired reliability | 1.00
$a_{2}$ | Material hardness HRC 58 | 1.00
$a_{3}$ | Recommended life modification factor | 0.10
$a_{4}$ | Tubular tower | 0.85

He et al. conducted a small sample test with slewing bearings and cross-
examined the experimental, theoretical, and simulation-based results [25]. The
test was run with an axial force of 330 kN, an overturning moment of
$1.38\times 10^{5}$ kN-mm, and a test speed of 4 rpm, for 16 days. The
theoretical calculation using the equations discussed above was within 5.18%
and the FE-SAFE simulation was within 10.17% of the fatigue test results.

Among the findings from the study, it was noticed that the test platform
produced an anomalous noise halfway through the testing and the accelerometer
readings reflected a similar anomaly. This provides insight into the use of
effective sensors on the DWT, such as accelerometers can be used similarly to
how He used them in the test setup, or a sound sensor can be mounted to the
tower which is analogous to the test frame where the abnormal sound occurred.
The collected data would be useful for early failure prediction of the
bearing, given a model is made from the test data.

###  II-F Blades

The blades of the DWT are one of the most crucial components and are prone to
failure, especially random type failures such as getting hit by flying debris.
Historical failures of blades have been observed where one of the blades bent
catastrophically from colliding with the duct due to blade misalignment. The
blade is custom designed and manufactured which is assumed to be a rectangle
for the sake of simplicity. Further assumptions are the blades are cantilever
beams with its gravitational load due to weight, a torsion from the blade
design, and a thrust load at the free end. We evaluate each load separately.

The blades can be approximated as having dimensions of $L=1498.8mm$,
$b=185mm$, and $t=4mm$. They are attached to the rotor at an angle $\phi$
about the radius line. The material is Aluminum 6061 T6, with tensile
strength, $S_{ut}=310$ MPa or $45$ ksi, and a density of 2.7 g/cc. Finding the
Marin modified endurance limit for this material gives $S_{e}=17.6$ ksi. The
constants $a$ and $b$ from equation 6 are 93.196 and -0.1206 respectively. The
Marin life modification factors are shown in the Table III.

TABLE III: Marin Endurance Limit Modification Factors for Blade Factor | Condition | Value
---|---|---
$k_{a}$ | Pressed surface | 1.01
$k_{b}$ | Beam in bending | 0.89
$k_{c}$ | Bending loading | 1.00
$k_{d}$ | Ambient temperature | 1.00
$k_{e}$ | 95% desired reliability | 0.87
$k_{f}$ | No miscellaneous effects | 1.00

The bending moment from weight of the beam and the resulting stress are
calculated as follows-

$\displaystyle M_{blade}=-F_{blade}L$ (12)
$\displaystyle\sigma_{blade}=\frac{yM_{blade}}{I}$ (13)

Here, $M_{blade}$ is the moment at the blade root, $F_{blade}$ is the load due
to weight, $\sigma_{blade}$ is the bending stress, and $I$ is the moment of
inertia for the assumed rectangular cross section. The weight of one blade is
approximately 3 kg, which creates a bending moment of 22055 N-mm about the
bending axis. The orientation of the cross section depends on the angle of the
blade mounting. In the loading cases of a horizontal cross section, the
bending stress is 44.7 MPa, whereas a vertical cross section has a bending
stress of 0.97 MPa. With the rotation of the rotor, the maximum stress occurs
when the blades are in a horizontal position where the bending effects are
maximum. There is zero bending moment when the blades are vertical (upright or
hanging straight down). So this bending stress is reversible. We take the
worst case of 44.7 MPa or 6.48 ksi stress for the life calculation.

Now we solve for the equation 6 to get the number of cycles $N$. This results
in $4\times 10^{9}$ cycles. On average, the rotor rotates at 100 rpm during
regular operation222as per data logged on April 12, 2022. From the logged
frequency data, the daily number of cycles is 144,000. Given one rotor
rotation equates to one blade load cycle, the blade would have a life of over
75 years.

For the thrust loading, the maximum shear stress occurs at the center line. So
we calculate the maximum shear from the following equation.

$\displaystyle\sigma_{s,max}=\frac{T}{\alpha bt^{2}}$ (14)

where $\sigma_{s,max}$ is the maximum shear stress, $T$ is the applied torque,
$\alpha$ is an empirical constant. Alternatively, we use the following
equation with an error of less than 4%.

$\displaystyle\sigma_{s,max}=\frac{T}{bt^{3}}\left(3+1.8\frac{t}{b}\right)$
(15)

Valyou’s analysis determines the rotor thrust to be approximately 2000 N for
the 50-year extreme gust loading case with 3-second gusts. This load applies
torque on the blades. We assume this load to be distributed to the five blades
as 200 N on each blade. This translates to a torque, $T=300$ N-m. The maximum
shear stress then can be calculated to be 1.232 MPa or 0.1787 ksi. When the
blades rotate past the standpipe wake region, they see this load as
fluctuating and thus the torsional load may be considered fully reversible.
Plugging the stress value in equation 6 yields a life of $3.4\times 10^{22}$
cycles. A worst case twisting scenario is when the blades carry all the rotor
thrust, which means 400 N on each blade, or a torque of 600 N-m. The shear
stress is 0.0899 ksi. This results in a life of $1\times 10^{20}$ cycles,
which means that torsion does not have significant effect on blade fatigue.

In the case of the rotor thrust applies torque to a single blade, it will
twist. We can calculate this torque by comparing the relations for power and
torque coefficients. These equations are typically used for open rotor
turbines, but the parameters used should work for a ducted turbine with
manageable error. These relations are shown below.

$C_{p}=2\frac{P_{T}}{\rho_{air}A_{\text{rotor}}V_{\infty}^{3}}$ (16)

$C_{q}=2\frac{T}{\rho_{air}A_{\text{rotor}}V_{\infty}^{2}R}$ (17)

Where $C_{p}$ is the power coefficient of the turbine and $P_{T}$ is the power
developed. $C_{q}$ is the torque coefficient and $T$ is the torque on the
rotor. $R$ and $A_{\text{rotor}}$ are the rotor radius and cross-sectional
area respectively. $V_{\infty}$ is the wind stream velocity and $\rho_{air}$
is the air density. We know that $P_{T}=T\omega$, where $\omega$ is the
angular velocity of the rotor. Substituting this into the equations and
dividing equation 16 by equation 17 yields the following.

$\frac{C_{p}}{C_{q}}=\frac{R\omega}{V}$ (18)

The wind speed at the free stream is $48.72ms^{-1}$ and air density is
$1.24kgm^{-3}$. The DWT has a rotor diameter of 3 m. We assume the power
coefficient and rotor speed for the conditions stated to be 0.40 and 600 rpm
respectively. This results in a torque coefficient of 0.207. We can then
calculate actual developed torque $T$, using equation 17 which is
approximately 3231 N-m. Using equation 15 we solve for the shear stress on a
single blade which is 13.269 MPa or 1.924 ksi. Again, due to similar reasons
of the blades rotating past the standpipe’s wake region, this load is
reversible. Using the lifing equation 6 we get a cycle count of $2.7\times
10^{15}$. This is still higher than what was for the bending moment. We can
further vary our assumptions for power coefficient, $C_{p}$ and rotor speed,
$N$, and estimate how the life changes based on that. Table IV shows the life
estimates for different combinations of power coefficient and rotor speeds.

TABLE IV: Blade life variation due to varying turbine parameters. $C_{p}$ |  $N$ (rpm) |  $T$ (N-m) | Life (cycles)
---|---|---|---
0.5 | 600 | 4027 | $1.5\times 10^{13}$
0.6 | 600 | 4838 | $3.3\times 10^{12}$
0.4 | 900 | 2154 | $2.7\times 10^{15}$

As we can see from the life estimates in Table IV, the life is still long. The
worst case loading then is due to bending moment from a horizontally mounted
beam, meaning the twist angle is $\phi=0^{\circ}$. This yields a life of about
75 years for the blades. Due to the complex geometry of the blade, this
approximation introduces large errors. So we suggest using stresses from the
FEA simulation to get a more accurate stress estimate, similar to the tower.

Despite the conservative analysis, it is recommended to conduct failure
testing on the blades. One of the most common issues DWT faces is the blades
not matching design and material tolerances. Accelerated testing of blades
could provide invaluable data which can be used with a Weibull model to better
determine reliability. For example, the current aluminum blades can be loaded
and torqued with a higher load. Loads are scaled by a severity multiplication
factor. The scaled variables are called accelerated variables. The time to
failure is recorded for each blade. The accelerated variables will have a
relationship to the typical usage time, which can be used to scale back the
time during lifing estimation. The shape parameter ($\beta$) and scale
parameter ($\eta$) are the basis to a Weibull distribution which can be
defined by the cumulative distribution function (CDF)-

$F(t)=1-e^{-\left(\frac{t}{\eta}\right)^{\beta}}$ (19)

After testing and collecting results for two values of quantile life $B_{p}$
and $B_{q}$, equation 20 is used to calculate the value of $\beta$.

$\beta=\frac{\ln(-\ln(1-p/100))-\ln(-\ln(1-q/100))}{\ln(B_{p})-\ln(B_{q})}$
(20)

The value of $\beta$ can then be used in equation 21 to solve for $\eta$.

$B_{p}=\eta\\{-\ln(1-p/100)\\}^{1/\beta}$ (21)

With both the shape and scale parameters determined, we can create a Weibull
probability plot which provides a substantial basis for determining
reliability over time. A utility of Weibull distribution is shown in
Predictive Maintenance chapter using wind speed. It is worth mentioning that
in the design phase, a specific value of $\beta$ is set as a target to single
out some design variables. Achieving that $beta$ value essentially means
reaching the reliability goal.

###  II-G Nacelle

The nacelle consists of the hub, the generator, the duct, the struts, the
rotor, and the blades. The weight of the duct is distributed by struts that
connect to the back of the hub and are supported by the standpipe, which in
turn is supported by the slewing bearing. The struts act as the skeleton of
the duct. Random-type failure is the most probable cause of failure for them.
The 4 duct sections are connected via duct connectors which are aluminum
sockets. The duct sections are rotational molded foam-filled polyvinyl
chloride or PVC. Plastic materials thermally degrade when exposed to
ultraviolet (UV) rays radiated from the sun. As a result, they become prone to
damage from the elements causing failures such as cracking from hydrolysis.
The same is true for the nose cone, which currently is a 3D-printed component
made from acrylonitrile styrene acrylate or ASA.

###  II-H Generator

The generator manufacturer Lancor documents the generator specifications on
their brochure and website. The model is GSIP160. The generator output is
rated at 3500 W at the nominal shaft speed between 200 and 400 rpm. The
insulation is rated as class F, which means that the maximum internal
temperature is 130∘C. The lifing estimate provided by the manufacturer is 20
years at rated conditions. The generator is a direct drive meaning it is
coupled directly to the rotor.

###  II-I Slip Ring

The slip ring is manufactured by MOFLON, and its lifing and specifications are
documented on the manufacturer’s website and product manual under the model
number MW1630. It is rated for 40M cycles at a rated speed of 250 rpm and 0.06
Nm torque. The ring oscillates with the change in yaw direction of the DWT.
This implies that the number of revolutions is lower than for the rated life.
So we expect the slip ring to last a greater number of cycles. Over current or
over voltage can be a cause of burning out the slip ring as the wires are
rated for a maximum of 600 V and 30 A.

###  II-J Fasteners

The fasteners are assumed to last indefinitely as they were chosen with an
appropriate safety factor in mind, and the only maintenance task is to
retorque them periodically. Replacement would be necessary only if wear is
visible during inspection. Since fasteners are non-reparable components, MTTF
is the unit used for life.

###  II-K Controller

The control system is composed of a controller, an inverter, a shunt brake, a
dump load, and various communication cards used to extend the capabilities of
the controller. The Voltsys controller controls the cut-in and cut-off speeds,
applies brakes as necessary, logs sensory data, and channels power to the
inverter and the dump load. The data contains sensory information from the
generator, inverter, dump load, and anemometer. The controller manufacturer
Voltsys lists the specifications for their base controller shown in Table V.

TABLE V: Voltsys VS20A/800 Standard Unit Specifications Metric | Rated/Max Value
---|---
Power Rating | 6 kW
Input AC Voltage | 600 V RMS 200 Hz
Input AC Current | 16.5 A
Output DC voltage | 800 V
Output DC current | 20 A
Diversion Load DC current | 20 A
Capacitance | 470 $\mu$F
AC Power Supply | 100-240 V (0.88 A)
Operating Temperature | -10∘C $\sim$ 40∘C

We estimate the control system may fail the earliest mainly due to silicon/IC
component degradation and technological obsolescence. As we discuss in later
chapters, data has to be analyzed and accounted for as they are available. We
assume the control systems will be adjusted and upgraded as per the software
demand, which also requires that the assumption of components using silicon
are actually user serviceable. Thus we can say that the control system life is
limited by the life of the constituent silicon chips. Complementary
metal–oxide–semiconductor or CMOS chip manufacturers in general use a design
MTTF of 20 years [26]. However, MTTF is not a strong indicator of reliability
as it concerns the mean and not the failure rate. Pradeep [27] shows in his
study of MTTF as a metric for CMOS reliability that a high percentage of chips
fail before the designed MTTF of 20 years. As these chips are sourced from
multiple manufacturers who uses varying level of quality control, a system can
fail in as little as 10 years. The CDF plots from Pradeep’s study support this
conservative estimation for the controller life.

###  II-L System Life

From the reliability analysis we estimate that the life of a DWT is limited by
the generator, which is 20 years. We expect issues with the computing devices
may arise the earliest, which is 10 years. Within assumed operating conditions
we estimate the tower lasting about 38 years. The slewing bearing and the slip
ring both will last about 80 years with recommended maintenance. The blades
with nominal loading will last about 75 years. The non-repairable components
have a service life of 1 year, meaning they have to inspected annually.

##  III Maintenance Schedule

The study in the previous chapter concluded with determining RUL and key
variables leading to maintenance tasks that can lead to prolonged life of DWT
systems. This chapter in the study collects, tabulates and presents the
aforementioned results, segmented by the 4 systems detailed earlier, as a
maintenance schedule. The objective of this is to guide the DWT customers to a
set of scheduled tasks helping maintain and prolong the RUL within recommended
usage and working conditions.

The first 3 systems, i.e., structural, electromechanical, and control, contain
diverse components which have specific failure modes and servicing tasks.
These are, however, empirically established for the fasteners which are loaded
within those standard conditions. So, the loaded fasteners are listed
accompanied by a general maintenance schedule. The manufacturer recommended
specifications are marked with asterisks (*).

###  III-A Structural System

Table III-A lists the components of the structural system of the DWT along
with their respective failure modes and maintenance tasks. This system
consists of everything that is supporting the nacelle and providing the
structure required for the rotor to spin the generator.

TABLE VI: Maintenance schedule for the ‘Structural’ system of DWT

Component |  Failure Modes |  Service Life |  Specifications |  Service Tasks
---|---|---|---|---
Ballast FoundationAmbor Structures: https://www.amborstructures.com/industries/engineered-structures |  • Corrosion • Ballast loss • Loose bolts |  1 year |  • Maximum wind speed during maintenance: 38 mph* |  • Inspect ballast and hardware connections annually or upon high load event • Inspect bolt torques and service according to manualRecommended Torque: https://www.amborstructures.com/wp-content/uploads/2018/08/QuikBase-Assembly-Manual.pdf • Top off ballast material every year
Tower |  • Bending from moment • Fatigue from nacelle imbalance |  5 years* |  • Max base moment: 55000 ft-lbs* • Survival wind speed: 90 mph (3 sec gust)* • Material: ASTM A572 GR65* |  • Inspect column deflection, cracks, localized damage, every 5 years • Inspect bolt torques and service according to manualARE Tower Manual: https://aretelecom.com/wp-content/uploads/2021/04/AFS-350-60ft-Monopole.pdf
Screw Jack (Pole Raising System)Manufacturer’s Service Manuual: https://www.amborstructures.com/wp-content/uploads/2018/08/Ambor-Motorized-Assembly-Manual.pdf |  • Motor failure from weather exposure • Gearbox damage/wear/corrosion • Pin bending/corrosion |  5 years* |  • Max wind speed (during maintenance): 38 mph* |  • Inspect every 100 cycles or 5 years (whichever comes first) • Inspect monthly for visible corrosion • Lubricate every 15 cycles or once a year with recommended grease • Replace dust cover
Standpipe Assembly |  • Bolt failure • Shearing • Corrosion from gasket leakage |  10 years |  N/A |  • Check flange bolt torque • Replace gasket if corroded/worn
Hub |  • Crack formation • Chipping due to heat and vibration |  10 years |  N/A |  • Inspect cracks/wear/pitting
Hub Bushing |  • Crack formation • Pitting |  10 years |  N/A |  • Inspect cracks/wear/pitting
Blades |  • Bending • Shearing • Impact from flying debris |  75 years |  • Max operating wind speed: 130 mph |  • Inspect cracks/wear/pitting • Check alignment
Nose Cone |  • Cracking • Plastic Deformation |  10 years |  N/A |  • Inspect cracks/wear/pitting
Struts (3 for duct support) |  • Bending from compression • Shearing at joints |  10 years |  N/A |  • Inspect bending/deflection
Duct sockets |  • Distortion • Corrosion at plastic-metal interface |  10 years |  N/A |  • Inspect corrosion/wear • Clean rusting and use protectant (as required)
Duct sections |  • Thermal degradation • Cracking from hydrolysis |  20 years |  N/A |  • Inspect cracks/wear • Use UV protectant (as required)
Rain shielding |  • Rusting • Corrosion |  10 years |  N/A |  • Inspect cracks/wear/pitting

###  III-B Electromechanical System

The heart of the DWT is its electromechanical system. It consists of the
generator, slew bearing, slip ring, and their related machine elements and
wirings. The generator comes as a closed 3500 watt unit from the manufacturer
and only has replaceable filters. This makes it compact but less repairable.
It is rated at 200-400 rpm for power generation. The slew bearing and the slip
ring are subjected to the most usage cycles within this system mechanically,
and so are expected to fail earlier and more often relative to the other
components. Table VII shows the failure modes and maintenance tasks of the
included components in this system.

TABLE VII: Maintenance schedule for the ‘Electromechanical’ system of DWT

Component |  Failure Modes |  Service Life |  Specifications |  Service Tasks
---|---|---|---|---
Slew BearingSilverthin STO-145T: https://www.silverthin.com/bearings/slewing-rings/sto/detail/STO-145T |  • Raceway wear/pitting • Surface spalling • Thermal fatigue |  1 year |  • Moment rating: 19050 ft-lbs |  • Lubricate annually • Replace (if necessary)
Slip RingMOFLON MW1630 manual: https://www.moflon.com/pdf/mw1630.pdf |  • Raceway wear/pitting • Abrasion wear • Thermal fatigue |  40 years |  • Max speed: 250 rpm • Torque: 0.06 Nm • Operating Temp: $-40^{\circ}$C - $80^{\circ}$C |  • Replace after 20M cycles
Slip Ring Wiring16G cables |  • Burn-out • Tearing of wire sleeve • Shorting • Splice failure |  N/A |  • Max voltage: 600 VDC/VAC • Max current: 30 A/wire • Electrical noise: 10 m$\Omega$ @10 rpm |  • Inspect wear • Check terminal voltage • Replace (if required)
Slip Ring collar |  • Rusting/corrosion from leakage |  N/A |  N/A |  • Inspect annually
Generator Wiring to Slip RingSouthwire SOOW 600V: https://www.southwire.com/wire-cable/flexible-cord/600v-royal-soow-cord-with-black-jacket-90-c/p/55809702 |  • Burn-out • Tearing of wire sleeve • Shorting • Splice failure |  N/A |  • Max Amperage: 30 A |  • Inspect Annually
GeneratorLancor 3kW Generator: https://www.lancor.es/wp-content/uploads/2021/02/Generator-brochure-GSIP-160-280-350-650-libro.pdf |  • Transmission shaft failure • Thermal fatigue • Demagnetization • Filter wear • Stator core damage |  20 years |  • Rated output: 3 kW • Nominal speed: 200 - 400 rpm • Insulation class: F |  • Inspect filters annually • Replace filter (if necessary) • Assess performance after 20 years
Generator Shaft |  • Bending • Vibration from keyway wear • Misalignment from vibration |  20 years |  N/A |  • Lubricate • Clean rust • Use protectant (as required)
PVC Conduit |  • Wear • Cracking |  1 year |  $\nicefrac{{3}}{{4}}-6^{\prime\prime}$ |  • Inspect annually • Replace (if necessary)

###  III-C Control System

The control system consists primarily of the Voltsys controller which is the
brain of the system coordinating the inverter and its modules, shunt brake,
and dump loading. The components in this system are mainly electronics and
thus their failure criteria are nearly identical. Excess generated power is
channeled to the dump load or resistors and as a result they heat up
significantly depending on the power. That is why they are more prone to
thermal failure compared to the other components in the system. There can be
multiple dump resistors, but the other components are single quantities. The
following table contains the maintenance table for the control system.

TABLE VIII: Maintenance schedule for the ‘Control’ system of DWT

Component |  Failure Modes |  Service Life |  Specifications |  Service Tasks
---|---|---|---|---
Voltsys ControllerVoltsys: https://www.voltsys.com/voltsys-20a-wind-hydro-controller/ |  • Capacitor failure • Integrated circuit (IC) failure |  N/A |  N/A |  • Inspect after high load events
Dump Resistors |  • Overheating/Burnout |  N/A |  N/A |  • Inspect after high load events
Fimer InverterFimer UNO-DM-6.0-TLPLUS-Q: https://www.fimer.com/system/files/2022-04/FIMER_Brochure-Building%20Applications-EN-revC.pdf |  • Overvoltage • Overcurrent • Capacitor failure |  5 years |  • Output: 6000 W • Max DC input power: 3500 W • Max DC input current: 31.5 A • Max external AC overcurrent protection: 40 A • Operating temp: $-25^{\circ}$C - $60^{\circ}$C with derating above $45^{\circ}$C |  • Inspect after high load events • Inspect annually after 5 years
Comm CardCommunications card for Fimer inverters manufactured by ‘Inverter Supply’ |  • IC failure • Capacitor failure |  2 years |  • Operating temp: $-20^{\circ}$C - $60^{\circ}$C |  • Inspect after high load events
Shunt Brake |  • Burnout • Corrosion |  N/A |  N/A |  • Inspect after high load events

###  III-D Fasteners

The DWT contains various fasteners for different components and purposes. The
bill of materials (BOM) for the QuickBase foundation provides the number of
fasteners used including 6 anchor bolts with 4 nuts and washers to each for
the center pedestal, and a total of 84 bolts with 1 nut and 2 washers to each
for the bottom and side panels. The tower or pole mates with the pedestal with
the anchor bolts. The parts of the tower are connected at the flanges via 8
bolts with 1 nut and 2 washers each. The standpipe assembly and the tower are
connected via the slew bearing. This whole assembly requires a total of 32
bolts for the inner and outer rings of the bearing. The struts supporting the
duct use 8 machine screws each. 16 rivnuts are inserted into the duct
sections, which are used to mate the sections to the duct connectors with 16
machine screws each. The generator is connected to the hub of the standpipe
assembly with a grub screw. The list of fasteners is in Table IX and their
general maintenance schedule is in Table X.

TABLE IX: List of loaded fasteners used in DWT Type/Size |  Grade/Class |  Specifications |  Details
---|---|---|---
Bolt / M$12\times 35$ |  Grade 8.8 |  Torque: 48 lb-ft* |  Ballast foundation bolts
Bolt / M$12\times 35$ |  Grade 8.8 |  Torque: 119 lb-ft* |  Ballast foundation bolts
Bolt / M$33\times 200$ |  Grade 8.8 |  Torque: 1083 lb-ft* |  Ballast foundation bolts
Bolt / M$36-4\times 1000$ |  Grade 8.8 |  Torque: 777 lb-ft* |  Ballast foundation anchor bolts
Bolt / M$16-2\times 60$ |  Grade 8.8 |  Torque: 119 lb-ft* |  Ballast foundation flange bolts
Bolt / M$16\times 60$ |  Grade 8.8 |  Torque: 119 lb-ft* |  Screw jack bolts
Bolt / M$10\times 35$ |  N/A |  Torque: 27 lb-ft* |  Screw jack bolts
Bolt / M$6\times 50$ |  N/A |  N/A |  Screw jack bolts
Bolt / $\nicefrac{{5}}{{8}}-11\times 2\nicefrac{{1}}{{2}}$” |  Zn-Al Coated |  N/A |  Mfr: ARMOR COAT / Part No: UST235844
Connect tower to slew bearing and slew bearing to standpipe assembly
SHCS / M$10-1.5\times 25$ |  Class 12.9 |  N/A |  Mfr: ARMOR COAT / Part No: UST710025
Generator attachment screws
Bolt / M$14-2\times 50$ |  Class 8.8 |  N/A |  Mfr: Infasco / Part No: 67084
Generator hub bolt
SHCS / $\nicefrac{{3}}{{8}}-16\times 1\nicefrac{{1}}{{4}}$” |  Zn Plated |  N/A |  Mfr: ARMOR COAT / Part No: UST235957
Connect the blades to the hub
BHCS / #$8-32\times\nicefrac{{1}}{{2}}$” |  Black Oxide |  N/A |  Nose cone screws
SHCS / $\nicefrac{{1}}{{4}}-20\times\nicefrac{{5}}{{8}}$” |  Zn-Al Coated |  N/A |  Mfr: ARMOR COAT / Part No: UST235919
Connect struts to duct sockets and bedplate
SHCS / $\nicefrac{{1}}{{4}}-20\times\nicefrac{{7}}{{8}}$” |  Zn-Al Coated |  N/A |  Mfr: ARMOR COAT / Part No: UST235921
Connect struts to duct sockets and bedplate
FBHCS / $\nicefrac{{1}}{{4}}-20\times 1$” |  Zn Coated |  N/A |  Mfr: Socket Source / Part No: FBHA04C016US
Connect bottom socket to duct(s)
Torx T25 Truss Head Machine Screws / $\nicefrac{{1}}{{4}}-20$” |  Zn Plated |  N/A |  Mfr: Jet Fitting / Part No: 1412MTT-2500
Connect duct sockets to ducts
Rivnut Plusnuts / $\nicefrac{{1}}{{4}}-20$” |  Yellow Zn Plated |  N/A |  Mfr: Libberty Engineering
Seated into duct sections to mate with machine screws
Grub Screw / $\nicefrac{{3}}{{8}}-16\times\nicefrac{{3}}{{4}}$” |  N/A |  N/A |  Mfr: McMasterr-Carr / Part No: N/A
Slip Ring Screw / #$10-24\times\nicefrac{{1}}{{2}}$” |  N/A |  N/A |  Mfr: ARMOR COAT / Part No: UST235905

SHCS / $\nicefrac{{1}}{{4}}-20\times\nicefrac{{5}}{{8}}$” |  N/A |  N/A |  Mfr: ARMOR COAT / Part No: UST235919
Nacelle cover plate screws
Generator Shaft Key and Set Bolt |  N/A |  N/A |  Holds hub to generator shaft
TABLE X: Maintenance Schedule for fasteners in DWT Fastener Type |  Failure Modes |  Service Tasks
---|---|---
Bolts (and Nuts) |  • Loose bolts • Shearing on nuts • Bearing on bolts • Rust/Corrosion |  • Inspect • Check torque • Apply anti-rusting agent (as required) • Replace (if necessary)
Screws |  • Loose screws • Shear • Rust/Corrosion |  • Inspect • Apply anti-rusting agent (as required) • Replace (if necessary)

##  IV Conclusion

DWT is an emerging technology that aims to achieve the longest life possible
with minimum maintenance. This paper tried to touch on that goal by evaluating
RUL and exploring reliability improvements of DWTs using both traditional and
modern methods. Lifing analyses were conducted using ASTM standards and
empirical machine design methods such as $B_{p}$ life, $L_{10}$ life, Weibull
fitting, etc. This allowed us to build a simple maintenance schedule that is
meant as a conservative way of maintaining the turbine with regular
inspections. The impact of this study is on the reliability aspect of ducted
wind turbines. We conducted a component level life analysis which allowed for
understanding of the variables affecting RUL. The biggest contribution is that
a customer transferable maintenance schedule that had not existed before for
the DWT.

One of the largest limitations this study has faced is the lack of historical
failure data which left our proposed model unverified for DWT specific data.
Also, being in the design phase, the DWT sees constant change in design and
material selection which may nullify some of the component analysis. We tried
to account for that using multiple methods of analysis for some of the major
components. The equation parameters can easily be recalculated for any
dimensional or material changes in the future.

##  V Future Work

This study on reliability just scratches the surface of a reliability growth
study. We suggest doing failure testing for custom manufactured components
which can be fit with the Weibull distribution. We expect more volume and
variety of data to be available with such testing. This can be used to develop
more suitable maintenance schedules. Furthermore, failure prediction models
can be developed and validated which will bolster the reliability of DWTs.

## References

  * [1] ACP, “Clean Power Annual Market Report 2021.” [Online]. Available: https://cleanpower.org/market-report-2021/
  * [2] “Map: Projected Growth of the Wind Industry From Now Until 2050.” [Online]. Available: https://www.energy.gov/maps/map-projected-growth-wind-industry-now-until-2050
  * [3] “Global Wind Report 2021,” Mar. 2021. [Online]. Available: https://gwec.net/global-wind-report-2021/
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