Difference between revisions of "EM.Cube Application Gallery"
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Revision as of 00:48, 3 October 2016
EM.Cube provides the ultimate solution to all of your electromagnetic modeling needs. Using EM.Cube's computational modules, you can solve a wide range of EM analysis and RF design problems. These modules together cover the entire frequency spectrum from DC to light. The following table lists a few examples of electromagnetic modeling problems you can solve with one or more EM.Cube modules:
Problem Type / Application | Suitable EM.Cube Module | Example Projects |
Analyze directional communication links in high multipath urban environments |
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Model large, finite-sized, antenna arrays on the transmitter and receiver ends |
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Evaluate platform effects on the radiation characteristics of antenna systems |
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Design multilayer planar RF, microwave and millimeter wave circuits |
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Analyze metallic and dielectric waveguide and resonator structures for microwave and millimeter wave applications |
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Embed passive and active devices and circuits into your electromagnetic analysis |
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Model frequency response of multiport structures and generate S-parameter data for equivalent circuit models (for export to RF.Spice A/D) |
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Model transient propagation of arbitrary waveforms and signals in your circuits |
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Investigate the interaction of incident plane waves and focused Gaussian beams with complex geometries, biological environments or dispersive materials |
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Study reflection and transmission properties of periodic surfaces and metamaterial structures |
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Compute low frequency electric and magnetic fields, capacitance and inductance of lumped circuit devices |
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Compute quasi-static characteristic impedance and effective permittivity of physical transmission lines |
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Build complex structures using native standard geometric objects or custom expression-based curves & surface and import/export external CAD models |
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Compute radar cross section (RCS) of complex targets |
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Run parametric and random sweeps of design variables with complex interdependencies defined through mathematical functions and/or Python scripts |
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Optimize your design variables using classical and statistical methods including multi-objective Pareto genetic algorithms |
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Run lightning fast EM simulations on multicore CPU/GPU platforms using a variety of hardware and software accelerators |
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