The results of this study will help turbomachinery manufacturers to design a more efficient labyrinth seal. However, if the number of cavities is too high, the beneficial effect of more cavities can be reversed. When the whole axial length is fixed, the most effective way to decrease the discharge coefficient is to reduce the cavity width by increasing the number of cavities. The objective of the current study is to understand the effects of changing the geometric parameters of the seal on the leakage flow rate and the discharge coefficient, and to determine the optimized geometry for a fixed axial length. The space for installing a labyrinth seal in turbomachinery is limited, and so it is important to optimize its geometry for a fixed axial length in order to minimize the leakage flow rate and the discharge coefficient. The geometric parameters of the straight-through labyrinth seal, such as clearance, tooth width, tooth height, cavity width, and tooth inclination angle, affect its performance.
A straight-through labyrinth seal is one of the most popular non-contacting annular seals through which energy dissipation by turbulence viscosity interaction is achieved with a series of teeth and cavities. create_dataset ( 'Data', ) for i in range ( 3 ): r = list ( np. linspace ( 0, npoints, npoints + 1 ) frame = tp. Import numpy as np import tecplot as tp from nstant import PlotType, ThetaMode, NumberFormat, AxisAlignment np. See the example shown for the theta axis. offset = - pos * ( viewport_width / 100 ) tp. color # convert position in viewport width units to offset in frame width units yax. left for i, pos in enumerate (): lmap = plot. right = 75 # set position of the y axes based on viewport width viewport_width = plot. join ( examples_dir, 'XY', 'y_t' ) dataset = tp. tecplot_examples_directory () infile = path. save_png ( 'axes_line.png', 600 )įrom os import path import tecplot as tp from nstant import PlotType, AxisAlignment examples_dir = tp. y_axis_index = 1 # Color the line and the y-axis for pressure press. color # set pressure linemap to second x-axis press. variable ( 'Pressure (Pa)' )) # Color the line and the y-axis for temperature temp. variable ( 'Temperature (K)' )) press = plot.
values ( 'Pressure (Pa)' ) = p plot = frame. create_dataset ( 'data', ) zone = dataset. Import numpy as np import tecplot as tp from nstant import PlotType, Color frame = tp.
save_png ( 'axis_3d.png', 600 )Ĭartesian3DFieldAxis.
anchor_position = 1.5, 95 axes = assignments = for ax, asgn in zip ( axes, assignments ): ax. colormap_name = 'Sequential - Yellow/Green/Blue' contour. join ( examples_dir, '3D_Volume', 't' ) dataset = tp. Ratio between scales to 1 if they first exceed a ratio of 10:įrom os import path import tecplot as tp from nstant import PlotType, Color, AxisLine3DAssignment examples_dir = tp. The following example will set the aspect This is the limit above which the axes relative scales will be pegged Recalculate and set the scale factors for each axis.Ĭartesian3DFieldAxes. Recalculate and set the ranges for each axis. Set the origin to the specified location.
Preserve scale (spacing between ticks) on range change.Īxes range aspect ratio used range_aspect_ratio_limit is exceeded. Values are set to have the smallest number of significant digitsĪxes scale aspect ratio used when aspect_ratio_limit is exceeded.Įnable automatically choosing which edges to label. This adjusts the axis label values such that all currently displayed Set range of axis to nice values near variable minimum and maximum.Ĭartesian2DFieldAxis. Set range of axis to variable minimum and maximum. Index of the Variable assigned to this axis. Marker line to indicate a particular position along an axis.Īxis major and minor ticks style control. join ( examples_dir, '2D', 't' ) dataset = tp. From os import path import tecplot as tp from nstant import PlotType, AxisMode, AxisTitleMode examples_dir = tp.