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Transient CFD Results Analysis and Data Processing

Release Time：16 Jan,2026

<p style="text-align: center;"><img src="/ueditor/php/upload/image/20260118/1768712505510873.png" title="1768712505510873.png" alt="1.png"/></p><p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif; font-size: 12px;">While the analysis is running, the user can monitor scalar variables through graphs. To determine if the flow is fully developed, key values such as torque on rotating parts and lubricant volume within specific regions should be observed. These variables should stabilize and tend towards a fixed value to confirm that the flow has reached a steady state. Due to the highly turbulent nature of the splashing, some oscillations may appear and must be interpreted carefully. However, there should be no significant variations or trends indicating an increase or decrease. Figure 4 illustrates the distribution of the lubricant in different volumes of the gearbox. After 2 seconds, around 56 percent of the lubricant is inside the rear half, and 57 percent is in the half left. On the graph, a transient phase is evident during the first second with important oscillations, before the flow begins to stabilize. Once the flow is confirmed to be fully developed, the first post-processing phase begins. At this stage, a wealth of information can be extracted prior to the heat transfer analysis. Qualitative insights are derived from the generated animations, which offer valuable visuals inside the gearbox, revealing details that would otherwise be impossible to observe. In Figure 5, the left image shows a global cut view of the gearbox with a colored representation of the lubricant velocity. The right image shows a cut view in another direction, allowing for visualization of the lubricant movement close to the overheating bearing. These visuals serve as a first qualitative indicator to evaluate the lubrication efficiency. Visualizing the flow velocity, dark areas are noticed above the deflector. It seemed that the flow was obstructed by the deflector, and very little was directed towards the overheating bearing. We tried removing the deflector. Figures 6 and 7 present a comparison of the lubricant movement with (left) and without (right) the deflector. The red bent arrow tells the rotation direction of the intermediate gear. In the left image, the darker areas above the deflector and next to the gearbox floor indicate lower lubricant velocity, which could indicate some recirculation pockets inducing inefficient cooling. In the right image, without the deflector, the lubricant velocities are higher, suggesting that the lubrication should be more efficient. Without the deflector, the lubricant flows faster closer to the gearbox floor, moves up faster against the left wall and more lubricant seems to come in contact with the overheating bearing.</span></p><p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif; font-size: 12px;">A zoomed-in image in Figure 7 confirms that more lubricant appears to reach the overheating bearing without the deflector. Without the deflector, in the right image, more colored particles are seen in front and around the overheating bearing. Another visual tool can be used to evaluate the cooling efficiency, using the wet areas. They can be displayed by projecting the flow onto solid surfaces. Because the flow is very turbulent, these visuals are challenging to obtain precise information from. While these observations are qualitative, quantitative data can be extracted to compare the two designs. Churning losses of all rotating parts provide measurable values to track and compare. Figure 8 reveals a table comparing the measured churning losses on the input and second gear, with and without the deflector. The graph on the right shows the evolution of the churning loss (moment, Mx) with time. After the transition phase that lasts for about 0.5 seconds, the value stabilizes, and an average is computed.</span></p><p style="text-align: justify;"><span style="font-family: arial, helvetica, sans-serif; font-size: 12px;">Churning loss refers to the resistance created by lubricant splashing on a rotating part. Higher churning loss indicates greater lubricant activity. We observed that the churning losses on the input gear are 2.4 times higher without a deflector, and 6.5 times higher on the second gear. Creating surfaces for post-processing allows the integration of the quantity of lubricant passing through them with time, enabling comparison of the amount reaching specific areas of concern. The distribution of lubricant on these surfaces can also be measured in terms of VOF percentage (volume of fluid). A higher VOF percentage indicates that the lubricant covers a greater area of the surface. In Figure 9, the tables present the quantity of lubricant crossing several surfaces, allowing for comparison with and without a deflector. The Target Cyl refers to the narrow gap between the input gear and the second gear. The Entry #1 refers to the access to the overheating bearing, below the input gear. Entry #2 identifies the access to the roller bearing below the second gear. Both mass flow and VOF distribution show higher values without the deflector. Through Entry #1, which leads to the overheating bearing, 4.7 times more lubricant flows, indicating that the cooling could be more efficient without the deflector. The heat transfer coefficients (HTC) are scalar values projected onto all surfaces and can be exported for each part into a text file containing the HTC values and the associated node coordinates (x, y, and z). The user must select a time span during which the flow is fully developed, typically covering at least one rotation of the slowest gear. For each time increment within this period, a text file must be exported. During the heat transfer analysis, the mesh is static, so the node coordinates from the initial increment must also be exported. These initial node coordinates are then associated with the average HTC values at each node, for every part. This process is automated using a Python script. Once the HTC values are processed, they can be imported into the heat transfer analysis to predict the temperatures accurately.</span></p>