Using the SC/Tetra cavitating flow analysis function helps design engineers accurately predict possible cavitation issues while designing fluid machinery. Cavitation is a highly unsteady phenomenon that can cause many problems. These include device disorientation, aerodynamic noise, and surface erosion. Performing transient cavitating flow analyses early in the design process and implementing appropriate countermeasures are critical for achieving equipment performance and durability. Keita Fujiyama from Software Cradle, Software Engineering Department, explains the background and development of the cavitating flow analysis function.
Cavitation often occurs on machines that are driven by liquid motions. Some equipment, such as an ultrasonic eyeglass cleaner, are effective because cavitation is a positive attribute. However, in most cases, cavitation is a negative attribute. Machinery such as pumps, marine propellers, and power plant pipes degrade in performance or vibrate unnecessarily due to cavitation.
Due to increasing demand for device miniaturization and high performance, a major challenge faced by designers of hydraulic turbine products such as pumps and marine propellers, has been to continually improve efficiency. While CFD has been used to predict machine performance, the demand for better efficiency requires engineers to predict and understand even more detailed phenomena such as when and how cavitation occurs. Since cavitation can impair performance, cause physical damage, and create noise, design engineers must identify the risks and develop solutions to avoid them prior to production.
Physically simulating cavitation bubbles in the size of few microns is not easy. In addition, simulating the highly complex transient flows would be extremely challenging. Considering these issues, one simulation approach is to model the cavitation phenomenon using caviation models. Cavitation models have progressed substantially over the last several years assisted by hardware and software advancements. Calculations are fast and highly accurate. This has enabled design engineers to use the analytical results to develop design solutions.
Since cavitation is a highly transient phenomenon, the commonly used RANS (Reynolds-Averaged Navier–Stokes equations) model is not really appropriate. A better approach is to use a hybrid RANS and LES (Large Eddy Simulation) model with relatively high spatial and time tolerance. This is often used as a general engineering model and can be more suitable. Fig 1 shows a Software Cradle analysis example*3 that analyzed periodical shedding of cavitation. Intermittent shedding could not be replicated using the RANS model, whereas applying the SST-SAS (Shear Stress Transport-Scale Adaptive Simulation) hybrid model, produced a more accurate simulation.
Predicting the occurrence of cavitation has become analytically more feasible, but predicting the extent of cavitation areas and how it changes its states are still great challenges. Our continuous challenge is to develop and verify the cavitation function for the inputs provided by both the cavitation and turbulence models.
Erosion refers to the phenomena, where micro-jet and shock waves generated by the rapture of bubbles damage the surfaces of the physical object. It likely occurs when the pressure rises rapidly as the bubbles collapse.
Predicting erosion, and considering the phenomena at the micro level is unrealistic using current technology. With SC/Tetra, a simplified index for erosion risks as proposed by Nohmi et al.*4 can be displayed on the target surface. This index is based on the combination of absolute values and variances of pressure and vapor volume.
The erosion risk index is a simplified parameter since detailed prediction, such as estimating the volume of erosion, is not possible. Despite this limitation, the index allows engineers to evaluate possible locations where erosion may occur and assess the risks. This can lead to the development of erosion-free equipment.
（*1）Okuda, K. and Ikohagi, T., "Numerical Simulation of Collapsing Behavior of Bubble Clouds", Trans. of the Japan Society of Mechanical Eng. B, Vol. 62, 1996
（*2）Singhal, A.K., Athavale,M.M., Li,H.Y., Jiang, Y., "Mathematical Basis and Validation of the full Cavitation model", Journal of Fluids Engineering, vol.124, 2002
（*3）Fujiyama, K., Kim, J-H., Hitomi, D., and Irie, T., "Numerical Analysis of Unsteady Cavitation Phenomena by using RANS Based Methods", Proc. of the 16th Cavitation Symposium, 2012
（*4）Nohmi, M., Iga, Y., and Ikohagi, T., "Numerical Prediction Method of Cavitation Erosion", Proc. of Turbomachinery Society of Japan,Vol.59, 2008
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*Contents and specifications of products are as of April 1, 2015 and subject to change without notice. We shall not be held liable for any errors in figures and pictures, or any typographical errors.
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