Moduleering’s flagship product is SunShine, a powerful, robust, multiphysics simulation software. It supports a wide variety of analyses needed in engineering, from structural to thermal, electromagnetics, and computational fluid dynamics.
- Structural linear analysis
- Structural nonlinear analysis
- Normal modes analysis
- Buckling analysis
- Complex eigenvalue analysis
- Frequency response analysis (direct/modal)
- Transient response analysis (direct/modal)
- Steady-state heat transfer analysis
- Transient heat transfer analysis
SunShine is designed to solve large-scale problems much faster and demanding less computer resources than many other competitive software. Moreover, it takes advantage of systems with either shared or distributed memory, with both in-core and out-of-core techniques, working on both Linux and Windows OS. By making use of its parallel features, it can exhibit incredible performance on the appropriate hardware.
As a software, SunShine combines all the trading fields on which Moduleering acts, e.g., CAE analysis, multiphysics computing, HPC. It can also be interlinked with other CAE software. During its development stage, it passes through a solid testing phase, applying CI/CD techniques. This helps the developers and the engineers to early identify any bugs, assuring at the same time every client the great quality of the final product delivered in their hands.
SunShine is part of the complete CAE platform, Jupiter, developed by Technostar (Japan). It can run either within the platform or independently, bridging the procedure from pre- to post-processing in an intuitive way. It is already selected by established companies in the international market of automotive, shipbuilding, and electronics industry. They trust SunShine for its accurate results and its efficiency of solution.
SunShine’s users can benefit by its speed and accuracy of solution, which allow them to try different scenarios during their analysis, without the need of extensive physical prototyping. It exhibits tools to early detect possible modeling errors, while a wide set of error messages directly drive the user towards the root of the problem.