ESAComp is software for analysis and design of composites.
The comprehensive material database of ESAComp forms the basis for design studies.
ESAComp has a vast set of analysis capabilities, which have been successfully applied to structural components made of composites within the aerospace industry for many years.
With its optimization capabilities, ESAComp has easily integrated into the design and optimization workflow of a number of aerostructures.
Here, by combining the advanced composite design capabilities provided by ESAComp software from Componeering, with the powerful tools of Altair HyperStudy.
“This work focused on optimization at preliminary design, where it is essential to be able to set up optimization problems quickly, to modify them easily and to assess various design concepts within the same framework, rather than the analysis of details.”
Demonstrate by example the design optimization approach using available powerful tools by combining Altair HyperStudy with the advanced composite design capabilities provided by ESAComp software from Componeering.
Their challenge:
- Optimization – minimize mass of generic aircraft door surround model (within strength and stiffness constraints) compared with aluminum alloy baseline design.
- Preliminary design – reserve factors, materials choice and lay-ups (number of layers, orientations)
The solution:
- Use latest technology combining existing tools: ESAComp & HyperStudy.
- ESAComp analysis of curved, stiffened panels provides failure, displacement and stability results at short calculation time.
- HyperStudy manages the optimization and offers numerous tools for data analysis to gain insight on design drivers.
- ESAComp Python scripting and dedicated laminate optimization interface benefit optimization setup.
ESAComp optimization interface keeps design variables manageable and takes into account manufacturability. It’s a fast and efficient process: manual preliminary study of analysis model and optimization setup take minutes to some hours depending on model complexity