A vision of sound: Yamaha Motor shares how fluid-structure-acoustics co- simulation
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Multiphysics
Section
A vision of sound:
Yamaha Motor shares
how fluid-structure-
acoustics co- simulation
helps in the design and
development of unmanned
helicopters for industrial use
Interview with Mr. Kenta Mizuno, Mechanical Design Engineer
Development Group, Engineering Division
UMS Section, Robotics Operations, Yamaha Motor Co. Ltd
Volume XIII - Summer 2021 | mscsoftware.com | 15
Japan has led in the development and engines. However, we now want to go into specifications late in the design
use of unmanned helicopters, notably further and reduce the noise caused process creates its own set of issues:
in agriculture, with Yamaha Motor Co., by the main rotor.” Engineers, for example, have to go back
Ltd. first launching its flagship RMAX to look at the impact of changes on
unmanned helicopter in the early 1990s. The challenges of designing previous design decisions, a laborious
Since then Yamaha Motor has continued unmanned helicopters process that extends lead times. For this
to build on and improve its original reason, Yamaha Motor wanted to take
designs to optimise the use of unmanned One of the main sources of sound a comprehensive approach to design
helicopters in different environments. from a helicopter is the fluid noise and factor in the multiple elements that
caused by the main rotor blades. Since impact performance early on.
A key factor to consider when designing it is not feasible to use an insulating
unmanned helicopters is where they material to physically block noise Designing unmanned helicopters
will operate. Any aircraft that flies in propagation by the rotor, Yamaha with fluid-structure-acoustics
a residential area needs to limit its Motor had to look at the design of simulation using co-simulation
production of noise pollution. Lower the rotor speed and the shape of
sound levels also benefit operators, as blades. However, both these factors As a result, Yamaha Motor turned
Mr. Kenta Mizuno, Development Group, have a large impact on a helicopter’s to MSC CoSim Engine to holistically
Engineering Division UMS Section, overall performance, with any changes assess the performance of its
Robotics Operations of the Robotics generating multiple design trade-offs unmanned helicopter “FAZER R” (Figure
Division of Yamaha Motor explains: that need to be optimised. 1). The MSC CoSim Engine provides a
co-simulation interface for the direct
“For agricultural use, we have to Assessing the acoustic performance coupling of different solvers/disciplines
reduce the noise that unmanned of industrial products is very complex with a multi-physics framework.
helicopters make because they will fly and often happens in the later stages
over a field around a residential area. of design, once product specification Using MSC’s CoSim Engine, Yamaha
Noise reduction also helps reduce details are in place. Motor is able to perform multiple
operator fatigue. Up until now, we analyses simultaneously with
have achieved engine noise reduction However, incorporating the findings of multidisciplinary software products
mainly by adopting four-stroke acoustic performance assessments that transfer data interactively. One of
the MSC CoSim Engine’s strengths is
the ease with which it enables users
to move seamlessly between different
software tools. This makes it faster
and simpler to couple analyses of
mechanical–structure, structure–fluid,
and mechanical–fluid to produce an
analysis of the virtual performance
that closely mirrors what happens in
the real physical world.
When it came to analysing the FAZER R,
Yamaha Motor performed a structure–
fluid co-simulation using “MSC
Nastran” and “scFLOW” to simulate the
air flow produced by the rotor and the
rotor deformation. It then added MSC’s
acoustic analysis software tool Actran
to calculate the propagation of the fluid
noise caused by the rotor.
16 | Engineering Reality Magazine
The MSC CoSim Engine ensured analyses, a highly accurate mapping Equipped with the MSC CoSim
accuracy and stability in several technology enables them to exchange Engine, Yamaha Motor used fluid-
ways. For example, the CoSim Engine data such as displacement and fluid structure-acoustic simulation
is optimised for MSC Nastran and force. In scFLOW 2021, moreover, to comprehensively assess
scFLOW at the source code level, mesh morphing for representing the performance of unmanned
which provides superior stability. deformation is now significantly faster helicopters for industrial use, as
When it comes to MSC Nastran and than it was in earlier versions, thereby show in figure 2:
scFLOW, meanwhile, even though each further increasing the accuracy and
generate different types of mesh for speed of co-simulation.
Figure 2
Analysis process
Yamaha Motor used the following 2. The aero-acoustic source data was
procedure to validate performance transferred to Actran on a real-time
validation (Fig. 2): basis and an acoustic simulation of the
main rotor was performed.
1. The air flow was analysed with high
accuracy using co-simulation to create • Using acoustic simulation
an aero-acoustic source. software Actran, the aero-
acoustic source was extracted
• Using fluid analysis software scFLOW, from the data obtained in co-
engineers analysed the airflow simulation before performing a
caused by the rotation of a main rotor. Fourier transform.
• Structural analysis software MSC • The propagation of sound waves
Nastran then enabled an analysis was analysed using the finite
of the elastic deformation of element method in Actran.
blades caused by rotation
• Via the MSC CoSim Engine, scFLOW Actran received the data calculated
and MSC Nastran exchanged in co-simulation on a real time basis
information about the deformation and simultaneously performed an
Figure 1 Unmanned helicopter for of blades and the airflow change. acoustic simulation.
industrial use FAZER R
Volume XIII - Summer 2021 | mscsoftware.com | 17
By combining scFLOW and MSC 2. acoustic simulation with Actran
Nastran Co-Simulation, and Actran reveal the following:
simulation, Yamaha Motor was able
to avoid repeating design cycles in 1. Co-simulation showed that the
fluid, structure, and acoustic areas blades rose and fell slightly along with
respectively. Instead, by using fluid- the airflow caused by the rotation of
structure-acoustic simulation, Yamaha the main rotor in addition to pressure
Motor was able to comprehensively distribution and vortex generation
analyse the performance of the main (Fig.3). In 2. acoustic simulation, the
rotor and noise in a single analysis directivity of sound caused by sound
process, thereby dramatically shortening wave interference and the level of
design and development lead times. sound propagation were visually
captured (Fig.4). The result of 2.
Analysis result acoustic simulation can be expressed
as the plot of sound pressure level at
The results obtained during the the observation point (Fig.5) and as
performance validation of 2D or 3D images of the directivity of
sound propagation. In addition, the
1. Co-Simulation of scFLOW and MSC result could be heard with the user’s
Nastran, and own ears.
18 | Engineering Reality Magazine
Fig.3 Visualisation of blade deformation and the
fluid vortex
What co-simulation means for
Yamaha Motor
Mr. Mizuno of Yamaha Motor says: “As for noise countermeasures, we
“We expect that effective co- can consider concrete steps such
simulation of a fluid analysis and a as planning flight routes and flying
Fig.4 Visualisation of sound pressure
structural analysis will contribute to guidelines, and can suggest not distribution in space
the development of high-performance only manufacturing, but also new
main rotors. By increasing the businesses or services.”
efficiency and speed of the process
from design, analysis and prototyping, The multiphysics solution enabled
to the specification determination, we by combining co-simulation and
can develop tailor-made main rotors Actran opens up new opportunities to
optimised for industry and usage. innovate, allowing Yamaha Motor to
The visualisation of sound, which is develop different business scenarios
invisible, has a great impact on the for unmanned helicopters and address
design development of an them using upstream to downstream
Fig.5 Sound pressure level at the
unmanned helicopter. design processes. observation point
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Fig.6 Directivity of sound propagation at a frequency
Volume XIII - Summer 2021 | mscsoftware.com | 19
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