Design and Experimentation of a Hydrokinetic Turbine for Electricity
Generation in Closed Pipes
JAVIER ARMAÑANZAS*, MARINA ALCALÁ, JUAN PABLO FUERTES, JAVIER LEON,
ALEXIA TORRES, MIGUEL GIL
Department of Engineering,
Public University of Navarre (UPNA),
Campus de Arrosadia S/N, 31006 Pamplona,
SPAIN
*Corresponding Author
Abstract: In the present research work, a device for electrical energy generation to be used in water pipelines
has been designed, simulated, and tested. To achieve this, a study of the most influential parameters involved in
the experiment has been carried out and both, the turbine model and the geometry of the experimental test pipe,
have been selected through CFD simulations. Next, the Design of Experiments (DOE) has been used to obtain
the configuration with a higher energy extraction from running water. Finally, the turbine and the test pipe
section have been manufactured by 3D printing and the experimental tests have been carried out with the
optimal configuration to validate the results obtained in the CFD simulations. To simulate the exchange of
energy between the water and the turbine, the CFD software SIMULIA XFlow has been used.
Key-Words: - Hydrokinetic turbine, pipe, CFD, Xflow, Lattice-Boltzmann, Design of Experiments (DOE).
Received: February 11, 2023. Revised: November 24, 2023. Accepted: December 22, 2023. Published: February 23, 2024.
1 Introduction
Hydrokinetic turbines integrated in pipelines offer a
novel method of harnessing water's energy during
internal flow. Such technology garners increasing
research attention for its high innovative potential.
Nowadays, there has been an increase in new ideas
to produce energy at a low scale, which sparked a
renewed interest in microgeneration, [1]. Power
generation from water flows has evolved constantly,
with a spike in recent years. In the present day,
hydroelectric turbines are employed in large-scale
power generation, whereas hydrokinetic turbines are
considered to be a technology more focused on
microgeneration, using flows such as rivers, canals,
and sea currents. In [1] and [2], a wide state-of-the-
art revision regarding the technology used in small
hydroelectric plants is displayed, emphasizing in its
use among sustainable power systems.
In recent years, there has been a growth in
publications about obtaining electricity from
microgeneration, and specifically from hydrokinetic
turbines, due to the growing investment being made
in this technology because of its sustainable nature.
In the studies [3] and [4], a thorough review of
hydrokinetic energy conversion technologies is
carried out, paying special attention to the current
research trends and their future perspectives. In [4]
is stated that recent progress in hydrokinetic energy
conversion has advanced beyond the experimental
stage, as it has managed to generate up to 120 TWh
per year in the United States.
Based on these premises, a significant amount of
research has been concentrated on the design and
development of hydrokinetic turbines and their
installation areas. Both experimental and numerical
simulation techniques have been utilized in these
studies, [5], [6], [7], [8], [9], [10], [11], [12]. [5], is
solely focused on investigating the design and
experimentation of hydrokinetic turbines. They
emphasize the practical relevance of this technology
and propose optimization strategies for its
installation inside channels. In [6], a new full-scale
portable hydrokinetic turbine prototype for river
applications is examined, conducting both
experimental and numerical analyses. [7], provide a
review of technologies to harness energy obtained
using hydrokinetic turbines. Additionally, in [8],
scale models to characterize diverse hydrokinetic
turbine designs based on tests completed in a
laboratory water channel is utilized. In [9], an
approach to evaluate the energy potential and
economic viability of hydrokinetic turbines in rivers
using numerical predictions and experimental data is
presented. In [10], a CFD analysis of a turbine to
WSEAS TRANSACTIONS on FLUID MECHANICS
DOI: 10.37394/232013.2024.19.7
Javier Armañanzas, Marina Alcalá,
Juan Pablo Fuertes, Javier Leon,
Alexia Torres, Miguel Gil
E-ISSN: 2224-347X
64
Volume 19, 2024
determine optimal design parameters is conducted.
Lastly, in [11], the design of hydrokinetic turbines
installed in ducts using CFD is optimized.
Also, hydrokinetic turbines' practical application
across different environments and countries is
illustrated in [12], [13], [14], [15], including
research cases such as [12] in Malaysia and [13] in
the Amazon region. Furthermore, in [14], the
momentum recovery in the wake of axial-flow
hydrokinetic turbines is analyzed, providing
valuable insight into their overall efficiency.
The use of hydrokinetic energy in pipelines looks
promising as a form of energy generation with a
smaller environmental footprint than other
renewable sources, including wind, solar, or
conventional hydropower. Several studies have been
carried out on the modeling of design and
implementation within pipelines, such as [15], [16],
and [17], where drag-based, propeller-type, and
spherical turbines designs are analyzed,
respectively.
As a result, new companies are emerging to
produce this type of turbine, [18], [19], [20]. In [21],
the model developed by Purdue ECT [20] has been
implemented in cities throughout Panama,
demonstrating its exceptional performance. Finally,
several patents have been registered for electricity-
generating devices inside pipelines, [22], [23], [24],
[25], [26], [27], indicating ongoing research to
improve and diversify these designs.
This study centers on the electric power
generated by a hydrokinetic turbine inside a
pipeline. We carried out CFD simulations and
complemented them with experimental validation
tests.
2 Problem Formulation
2.1 CAD Design
To carry out the present study, different turbine
configurations were designed. Initially, a straight
blade model was used as a starting point, and
subsequently, two models were designed in which
the blades tried to cover as much surface area as
possible inside the tube. However, preliminary CFD
simulations showed that the straight blade model
was the most efficient. Figure 1 shows some of the
different turbine models that have been developed,
and Figure 2 shows the final design.
Fig. 1: Hydrokinetic turbine and Pipe CAD design
Fig. 2: Hydrokinetic turbine final design
After establishing the turbine model,
modifications were made to the pipeline section
designated for the installation of the turbine.
Initially, an unmodified pipe design was used,
resulting in a speed of 480 rpm. For the subsequent
design, the area of the pipe where the turbine would
be installed was narrowed to increase flow
acceleration, to achieve a higher speed. The turbine
was positioned in the narrowed section during the
initial attempt and achieved approximately 950 rpm.
However, the downstream flow exhibited excessive
turbulence. As such, the turbine was repositioned in
the central area of the constriction, resulting in a
speed exceeding 4000 rpm and reduced turbulence
compared to the previous scenario. This process is
shown in Figure 3.
Fig. 3: Pipe designs and turbine positioning
To avoid calculation errors due to high
pressures in small cavities resulting from CAD
assembly, all gaps were eliminated in the final
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Javier Armañanzas, Marina Alcalá,
Juan Pablo Fuertes, Javier Leon,
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assembly. Moreover, friction between parts was not
considered.
This final configuration took advantage of the
Venturi effect, which allowed for an acceleration of
the turbine. It was designed as a 3-piece assembly
that allowed the use of only one pipe with
interchangeable pieces. The system was also
designed so it could be manufactured and coupled
into a sensorized test rig (Figure 4).
Fig. 4: Hydrokinetic turbine and pipe final design
2.2 Simulation Setup
The CFD study was carried out using the SIMULIA
XFlow software, which uses a Lagrangian approach
with the Lattice-Boltzmann methodology.
To simulate the hydrokinetic turbine inside the
designed pipeline, the internal flow option was
chosen. The turbine had a 35 mm diameter in all
cases, and the pipe had a length of 295 mm. This
length is adequate for examining the flow
downstream of the turbine to determine if there is
excessive turbulence and if the need arises to adjust
the boundary conditions. Initially, these conditions
establish a fixed rotational speed for the turbine of
1500 rpm and a flow rate of 28.83 m3/h. A uniform
lattice size of 0.5 mm is used for the meshing and no
remeshing will be necessary during the simulation.
The software uses the Courant number as a time
step, which is the ratio of the time interval to the
residence time in a finite volume. This parameter is
essential as it affects the numerical stability of the
simulation methods employed. In this particular
simulation, a value of 0.5 was selected. Figure 5
provides a visualization of the simulation's
discretization.
Fig. 5: Lattice size
The configuration of the simulations was
established through prior work. Parameters were
adjusted until a stable and reliable simulation model
was reached. Figure 6 displays the velocity
distribution and generated vorticity obtained via
simulation.
Fig. 6: Velocity distribution and vorticity generated
Once the reference parameters were obtained to
carry out the simulations, it was decided to test three
different turbine heights to see which distance was
more favorable to obtain greater power in the
design. Specifically, distances of 15, 18, and 21 mm
measured from the center of the turbine concerning
the longitudinal axis of the pipe were studied. The
results revealed that at a height of 21 mm higher
angular velocities are obtained for the same torque.
2.3 Experimental Study
This device consists of two differentiated parts: a
coupling with a geometry that tries to take
advantage of the Venturi effect to accelerate the
water in the place of contact with the turbine and a
turbine-generator set as shown in Figure 7.
Fig. 7: Installation configuration
Due to the physical limitation of the test panel,
the experiments were conducted by varying the flow
rate and without brake torque to avoid breakage of
the turbine prototype. Thus, turbine models of 10, 8,
and 6 blades were used.
The manufacturing process was done mainly by
3D printing, using a FabPro1000 3D resin printer
and a Markforged Onyx 3D fiber carbon 3D printer.
In the first case the updated design shown in Figure
6 was required to meet the printer’s limitations.
Furthermore, most of the extra structural elements
(axle, DC motor) were also supplied by the
university’s workshops and only bearings and bolts
had to be bought.
The carbon fiber device shown in Figure 8 was
first fabricated, however when tested, the porosity
due to how the material was printed caused
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Javier Armañanzas, Marina Alcalá,
Juan Pablo Fuertes, Javier Leon,
Alexia Torres, Miguel Gil
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permanent and significant leakage in working
conditions across the entire surface of the material.
Therefore, the results obtained were discarded and
the experimentation focused on the resin device.
Fig. 8: Manufactured fiber carbon device
The experimentation was carried out in the pipe
test benches of the Fluid Mechanics lab at the Public
University of Navarra (UPNA) as it is shown in
Figure 9.
Fig. 9: Final installation of the resin device
The rotational speed was measured as a function
of the flow rate passing through the device during
the tests. The flow rate was measured using an
electromagnetic flowmeter. The turbine’s rotational
speed was measured by attaching a plastic cylinder
with adhesive to the turbine shaft. This setup, along
with a digital tachometer, allowed for the
measurement of the number of revolutions.
Additional checks were performed using a
stroboscope. The results obtained are shown in
Figure 10.
Fig. 10: Experimental RPM vs Flow rate results
To qualitatively measure the electrical power
generated, a DC motor was attached to the
cylindrical part and used to power LED devices
installed on an electronic board.
3 Problem Solution
A validation of the CFD model was carried out with
8 and 10-bladed turbines where the runaway speed
was measured under different water flows, and then
compared with CFD results. Validation for the 8-
blade and 10-blade turbine is shown in Figure 11.
Fig. 11: RPM vs. Flow rate in experimentation and
CFD
In Figure 11 it can be observed that the error
between the experimental data and CFD is less than
10% at higher flow rates. It is considered that with
errors <10% for higher flows and considering all the
uncertainty that comes with these types of
experimentations, the CFD model is validated.
Once the CFD models were validated, a study to
observe their behavior under different braking
moments was developed. For that, the defining
parameters obtained in the validation process were
kept the same, so the models were still valid.
For the CFD simulations design, statistical
techniques based on the Design of Experiments
(DOE) were employed. The selected design was a
22-second-order model with one central point and
four additional star points. Moreover, the design
factors were the number of blades and the braking
torque, while the two response variables were the
angular velocity and the power (shown in Equation
(1)). The number of blades was set to 6 and 12
blades, while the torque levels were 0.01 and 0.027
N-m as presented in Table 1.
Power (W)= Torque(Nm)·ω (rad/s)
(1)
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Table 1. DOE results
Nº
blades
Torque
(Nm)
Ang. velocity
(rad/s)
Power
(W)
10
0.027
244.42
6.60
10
0.0185
265.46
4.91
10
0.01
342.76
3.43
8
0.027
228.10
6.16
8
0.0185
249.69
4.62
8
0.0185
249.98
4.25
8
0.01
317.42
3.17
6
0.027
218.91
5.91
6
0.0185
231.10
4.28
6
0.01
336.68
3.37
Figure 12 shows the Pareto diagram for the
speed analysis. It can be seen that the braking torque
is the most significant factor with an inverse
interaction, i.e. the higher the torque, the lower the
revs. Likewise, it can also be seen that the number
of blades of the turbine is a significant factor -
although it is on the limit- and has a direct
interaction, where the higher the number of blades,
the higher the revolutions. The obtained results are
highly reliable given the achieved adjusted R2 of
95.9026% in this study. Also, the regression
equation is shown in Equation (2).
RPM= 610.28 - 26.711·Nº Blades -24251.9·Stroke
+ 1.68262·Nº Blades2 + 285.677·Nº Blades·Stroke
+ 431826·Stroke2
(2)
Fig. 12: Number of revolutions Pareto chart
Moreover, Figure 13 shows the Pareto diagram
for the study of the power obtained in the turbine.
According to this analysis, the torque and the
number of blades are the two most significant
factors with direct interaction. The obtained
adjusted R2 in this analysis was 99.1734%,
indicating a very high level of reliability. Also, the
regression equation is shown in Equation (3).
Power= 3.83968 – 0.371365·Nº Blades +
18.8339·Stroke + 0.0197486·Nº Blades2 +
9.23378·Nº Blades·Stroke + 2104.93·Stroke2
(3)
Fig. 13: Power Pareto chart
It should be pointed out that in both analyses the
results obtained are coherent and coincide with the
experimental and analytical studies of the vast
majority of the articles analyzed in the introduction.
Therefore, the simulations have been considered to
be validated.
Figure 14 shows the graphical results attained
from the DOE. It can be concluded that the 10-blade
turbine delivers the most torque and operates at the
highest speed. However, due to structural issues, the
experimental test of the DOE was postponed.
Fig. 14: RPM vs. torque in CFD
Finally, Figure 15 shows the circuit assembly
for voltage measurement. The motor's two terminals
are connected to the Ariston board and then to a
multimeter (Figure 16). A 10 kΩ resistor is placed
between the terminals to calculate the current
flowing through the circuit using Ohm's law.
Fig. 15: Motor connection to the board
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Fig. 16: Multimeter for voltage, current, and
resistance measurement
The current measured by the multimeter is the
same as the calculated current. The generation of
electrical energy was verified by placing LED bulbs,
as shown in Figure 17.
Fig. 17: Led bulbs
4 Conclusion
In the present study, different CAD designs of the
device and CFD simulations with the SIMULIA
XFlow software have been carried out. With that
base and after a design and optimization process, a
geometry with a narrowing in the central area was
chosen to take advantage of the Venturi effect and
generate electrical energy. Likewise, various turbine
models were generated to get the maximum
efficiency and finally, a straight 8-bladed geometry
was chosen.
A whole design process, manufacture, and
testing was carried out, all using the university’s
resources, such as 3D printers and test rigs. After
testing a prototype made of carbon fiber, it was
decided to discard it due to the excessive porosity of
the material and all the components were
manufactured by 3D printing in PET and the pipe in
resin to avoid leakages.
A final validation of the CFD model was
achieved with errors dropping below 10% for high
flows.
Finally, to find the optimal configuration that
allows for a greater generation of electricity, a
design of experiments with CFD simulations was
carried out under certain conditions of torque and
number of blades. However, due to structural
problems in the model, it could not be implemented
in the experimental tests.
As a potential development for future work, it is
considered interesting to be able to couple a
programmable 4-quadrant motor to introduce the
breakaway torque. In addition, conducting pressure
differential measurements upstream and
downstream of the turbine would allow for a more
accurate analysis of the device's efficiency, based on
an extensive literature review. Finally, ordering an
external manufacture of the turbine and the pipe
could result in better structural integrity and the
elimination of whatever leakage there could be.
Given the successful correlation between CFD
simulations and experimentation, new designs will
be implemented in domestic piping systems and
eventually at the urban level.
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Alexia Torres, Miguel Gil
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Contribution of Individual Authors to the
Creation of a Scientific Article (Ghostwriting
Policy)
The authors equally contributed to the present
research, at all stages from the formulation of the
problem to the final findings and solution.
Sources of Funding for Research Presented in a
Scientific Article or Scientific Article Itself
No funding was received for conducting this study.
Conflict of Interest
The authors have no conflicts of interest to declare.
Creative Commons Attribution License 4.0
(Attribution 4.0 International, CC BY 4.0)
This article is published under the terms of the
Creative Commons Attribution License 4.0
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