Acoustic streaming (abbreviated as AS) is a technique that uses a sound wave to maintain a fluid flow and can be used to adjust the grain morphology in a metal solidification process. In order to obtain the best performance products, engineers working in metal processing need to optimize the acoustic flow phenomenon. However, experimental testing relies on expensive experimental equipment and the cost is very high. To reduce R&D costs, researchers used COMSOL Multiphysics® software to analyze acoustic flow technology.
Application of Acoustic Flow in Metal Processing Industry
As the molten metal solidifies, grains begin to form. It has a great influence on the physical properties of solid metals; for example, the finer the crystallites, the higher their strength and hardness. Metal grains are affected by many factors such as temperature and cooling time. In the metal solidification process, engineers use the acoustic flow to create a drag force on the grains to achieve the goal of adjusting the grain morphology.
Molten metal in processing. Image courtesy of Goodwin Steel Castings. Used under the CC BY-SA 2.0 license, shared via Flickr Creative Commons.
The sound flow phenomenon can be formed by continuously oscillating the ultrasonic generator into the liquid to make the liquid produce a stable flow. In order for the effect to be significant, acoustic waves require high amplitude and high frequencies, typically reaching the ultrasonic range. Therefore, this technique requires the addition of ultrasonic treatment.
Often, engineers rely on costly physics experiments to further improve and develop sound flow technology. Simulation is a reliable alternative that allows metalworking professionals to model and experiment with a variety of materials and fluids to fully analyze acoustics. Afterwards, the model was verified by experimental tests.
The feasibility of simulation analysis was tested in the School of Thermal and Fluid Sciences and Product Design and Production Engineering at the University of Applied Sciences Northwestern Switzerland. Let us check it out.
Coupled Acoustics and CFD Simulation to Accurately Analyze Sound Flow
The goal of the research team is to establish a model that supports adjustment of parameters and analysis of various fluids and validates them experimentally. The established two-dimensional axisymmetric model can simulate the distribution of time-harmonic sound pressure generated by a continuous oscillating ultrasonic generator in a fluid. They simplified the model by assuming isothermal characteristics, ignoring cavitation, and time-averaged steady state flow.
An example geometric model of sound flow. The number points indicate the position of the border, and the colored dots indicate the positions of three massless tracer particles. Image courtesy of D. Rubinetti, D. Weiss, J. Muller, and A. Wahlen, taken from their dissertation at the COMSOL User Annual Meeting 2016 in Munich.
Considering that acoustic flow is a multiphysics phenomenon, the researchers analyzed two physical phenomena:
Helmholtz equation and pressure acoustics in inhomogeneous media, frequency domain interface analysis of high frequency acoustics
Solving Navier-Stokes Equations Using Laminar Flow Interface to Analyze Low Frequency Flow of Incompressible Fluids
It should be noted that because of the coupling of density and pressure disturbances, the compressible fluid must be described when analyzing high frequency acoustics.
Performing acoustic multiphysics simulation
The researchers solved the model equations through three research steps:
Calculate sound pressure field
Solving a coefficient-type boundary partial differential equation as an intermediate step to store higher-order derivatives
Perform steady-state fluid flow simulation and introduce the time-averaged force calculated from the second step by volume force
The first step of research shows that the acceleration of the ultrasonic generator makes the speed of acoustic particles increase dramatically; through the first step of the research results, the second step of the research needs the volume force term.
The frequency domain results show the sound speed field. Image courtesy of D. Rubinetti, D. Weiss, J. Muller, and A. Wahlen, taken from their dissertation at the COMSOL User Annual Meeting 2016 in Munich.
In fluid flow studies, the starting point of the flow pattern is the axial jet emitted by the active ultrasonic generator. The jet flows straight to the bottom and after the deflection it forms a vortex in the bottom corner. The flow is almost static at the open interface area, and the flow rate is maximized below the sonotrode.
Left: The steady-state velocity field of an aluminum melt with a frequency of 20 kHz and an amplitude of 30 μm. Right: Compare the velocity of three massless particles whose color corresponds to the color of the example geometry. Image courtesy of D. Rubinetti, D. Weiss, J. Muller, and A. Wahlen, taken from their dissertation at the COMSOL User Annual Meeting 2016 in Munich.
Observe the spread of the tracer particles in the three regions. The model shows that the particles below the sonotrode (black line in the upper right figure) have greater acceleration, which increases the number of cycles.
Refer to physics experiments to verify the acoustic flow numerical model
To test the simulation, the researchers created a small laboratory model in which the lower part of the aluminum sonotrode was immersed in a liquid filled crucible. Then they tested the frequency of 20 kHz and three different amplitudes of 10, 20, and 30 μm. In order to track the fluorescence crystals used in the experiment, the team used high-speed cameras, diode lasers, and laser chips. Finally, they used particle image velocimetry to determine the interconnected velocity fields.
experimental device. Image courtesy of D. Rubinetti, D. Weiss, J. Muller, and A. Wahlen, taken from their dissertation at the COMSOL User Annual Meeting 2016 in Munich.
In the seed oil test, the axial jets in the simulation and experimental results are all obvious, as shown in the figure below. Although the results were not exactly the same, the simulations were generally consistent with the direction and position of induced flow in the right panel.
The velocity field in the simulation (left) and the seed oil test example (right) has a frequency of 20 kHz and an amplitude of 30 μm. Image courtesy of D. Rubinetti, D. Weiss, J. Muller, and A. Wahlen, taken from their dissertation at the COMSOL User Annual Meeting 2016 in Munich.
We can also compare the speeds near the axis of rotation in simulations and experiments. Both show good agreement for the speed around the sonotrode tip. As the process gradually moved away from the tip, the results began to show a gap. At about 10 mm from the tip, the simulation reached its peak speed (more than twice the maximum speed of the experiment). As the axial gap increases, the difference in speed results also gradually decreases. Both simulation and experiment show that the speed is decreasing.
Compare the speeds near the axis of rotation in simulations and experiments. Image courtesy of D. Rubinetti, D. Weiss, J. Muller, and A. Wahlen, taken from their dissertation at the COMSOL User Annual Meeting 2016 in Munich.
Differences in the results may be caused by several factors, such as inaccurate optical measurements (the experimental data is difficult to collect) and the team simplifies the simulation. The fundamental problem may be that the flow in reality is not stable. The above experimental diagram also proves that the experiment dissipates more momentum than the model. This shows that there is an unstable small vortex in the experiment, which will transfer momentum at a certain speed, but the model's average steady-state flow does not describe it.
Digital Modeling Helps Efficient Testing of Acoustic Flow Devices
The research team combined the experimental tests and concluded that in addition to the accurate description of the small area near the ultrasound probe, the acoustic model can describe the flow qualitatively. Simulation is not only a viable means of analyzing acoustic flow and predicting fluid flow characteristics, but also reduces the number of physical experiments and saves time and money.
Simulation is also a powerful tool for testing various fluids, parameters, and geometries. Engineers can customize models based on specific conditions to effectively study different sound stream processing effects. The researchers also pointed out that this model has excellent scalability and can be used to study other applications of sound-driven fluid motion products.
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