Multi-array workflow in CST Array Task
It is not so often nowadays that wireless device supports only one frequency band. Many applications require multi-band functionality, such as: base station antennas, 5G and cellular connectivity, multi-band Wi-Fi and so on.
In some cases engineer can create an antenna, that supports several frequency bands, in other cases multi-antenna approach required. When scaled up to array level, things get more complicated, as multi-arrays require thorough engineering and modeling.
The following example of multi-array was designed in CST Studio Suite using Array task functionality.
Initial setup
Designed multi-array consists of two independent dual-polarized arrays: Low-Band array (0.8GHz central frequency) and Middle-band array (2.2GHz central frequency).
The workflow starts with single element design (Figure 1). Each antenna is simulated in open air to resonate at required frequency. The dummy vacuum box is needed for easier meshing on later stages of simulation using Domain Decomposition Method.
Figure 1. Middle-band (MB) element -left; Low-band (LB) element – right.
Separately, radome and ground plane models are created as an individual project. It is important to pay attention to coordinate system, as it must be the same in each project in order to provide smooth creation of full array.
When single elements and enclosure are ready, the workflow starts with Schematic blank sheet. Low-band, middle-band and enclosure models are imported as a “CST block” files. Elements placement in future array is arranged by TSV file. The setting is shown on figure 2.
Figure 2. Import of single elements and TSV file. (1) – Low-band element, (2) – middle-band element, (3) – radome.
TSV file is a text file that allows engineer to create any array (or multi-array) in 3D. Alongside with X, Y, Z coordinates of each element, TSV file contains excitation and phase data. TSV file that was used for this workflow can be observed on figure 3.
Figure 3. TSV file.
After applying the settings, multi-array is shown in simplified form, allowing grouping of elements and excitation modifications. Figure 4 shows the grouping for current project: Low-band elements are grouped together (green color) with single LB dipole is assigned to the group. Same with middle-band elements (blue color). Enclosure is set to imported radome model with coordinates’ origin aligned with array.
Figure 4. Grouping settings.
Full array model
When elements placement and excitation are set, full array model can be created. It is important to set reference model for global settings correctly, as the full array project will be based on that reference, including frequency settings, boundaries and field monitors (figure 5).?
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Figure 6. Full array model. Top and side view.
The side view of figure 6 shows low-band and middle-band arrays with dummy vacuum boxes, that were mentioned before. They are needed for proper meshing with Domain Decomposition Method, so intersections between vacuum boxes are not desired.
Due to using Array task, each component of two arrays is recognized by Domain settings and can be embraced in individual domains, which have the highest priority. The advantage of this method is that the simulation is split into multiple domains which are solved parallelly. Figures 7 and 8 show component and base domains.
Figure 7. Component domain.
Figure 8. Base domain.
Base domain provides plain distributions throughout the model, including enclosure and free space around the antenna. It is possible to use only base domains without component domain, but the repetitions can be assigned more efficiently by using both.
Repetitions for components domain are shown on figure 9. The reference domain marked in blue and dependent ones are green. The mesh adaptation and port calculation are done only for reference domain, saving time for simulation dramatically.
Figure 9. Repetitions in Domain Decomposition method
On figure 10 result mesh is shown. The benefit of using dummy vacuum blocks is visible the most here, as they allow to have even mesh on domains boundaries. If elements were left as they were, the mesh on the edges of domains would be much denser in order to repeat the shape of the element. Result mesh of the elements with dummy vacuum boxes hidden can be observed on figure 11.
Figure 10. Result mesh of multi-array.
Figure 11. Close up to elements meshing (vacuum boxes are hidden).
What’s next
This concludes the setup of custom multi-array in CST Array task using Domain Decomposition Method. By using repetitions run time can be decreased significantly, while memory consumption is controlled by the size of domains. The run time comparison between solvers can be found HERE.?
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Junior Researcher at Universidade Federal da Bahia
2 年I find the research interesting, especially the simulation time you are talking about, I think it depends in which domain you are simulating when it comes to the time domain the choice of the mesh size has an impact on the simulation time. I think it depends on which domain you are simulating in when it comes to the time domain, the choice of mesh size has an impact on the simulation time. There is a technique that allows you to simulate on different domains but in my experience it has never had results similar to normal simulations. I would like to hear your point of view.
share one video on simulation i.e . beam focus and beam steering