Penn State uses iVABS framework to advance real-world composite rotorcraft blades

The first phase of an integrate design-manufacture-test campaign for an iVABS-designed composite blade. This phase focuses on a spar structure that is similar to that of Bell 412. Source (All Images) | Penn State

Penn State (University Park, Pa., U.S.) has been participating in the AnalySwift (West Lafayette, Ind., U.S.) Academic Partner Program (AAP) to improve the manufacturability of composite rotor blades used for helicopters, air mobility and other rotorcraft. The work is part of the Penn State Vertical Lift Research Center of Excellence (VLRCOE), a research and education hub at Penn State dedicated to advancing vertical lift technologies — such as helicopters, drones and VTOL systems — in key areas like aeromechanics, flight dynamics, propulsion, acoustics and survivability.

The APP offers participating universities no-cost licenses of engineering software programs VABS and SwiftComp so students, researchers and faculty can leverage the tools in their academic research.

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“The optimization of rotor blade design plays a critical role in improving overall rotorcraft performance,” explains Jiwoo Song, who is pursuing a Ph.D. in aerospace engineering at Penn State. “Recent advancements in computational toolchains, such as iVABS, enable rapid exploration of design spaces while satisfying prescribed performance objectives. The goal of the project is to achieve a design-to-production capability by developing a drastically more manufacturing-aware iVABS blade design framework. Looking ahead, this project aims to move beyond virtual optimization into physical realization, with plans to fabricate a composite rotor blade in collaboration with the Penn State Applied Research Laboratory, validating the computational design process through experimental testing.”

Song says the VABS software has been central to his research. Its high-fidelity cross-sectional analysis capability enables him to rapidly compute stiffness, mass and coupling properties for complex, realistic blade geometries. Employing the iVABS design framework — which enables VABS for design and optimization, parametric studies and uncertainty quantifications in a user-friendly way — “we have been able to evaluate large numbers of candidate designs efficiently, narrowing down to configurations that meet demanding structural targets such as stiffness, strength constraints and weight requirements,” says Song. “This level of accuracy and computational speed would be challenging to achieve with traditional 3D finite element modeling alone.”

IVABS design workflow. 

In the current phase of the project, VABS/iVABS is being used to incorporate manufacturing constraints directly into the design process, enabling more realistic geometry parameterization. The blade template includes features such as rounded spar corners, airfoil trailing-edge treatment, continuous skin laminates and variable spar thickness along the span. These details improve structural fidelity in the analysis but also make the designs more directly transferrable into manufacturable hardware.

Prior to developing a full-scale blade, the team fabricated a composite spar using aerospace-grade carbon fiber prepreg materials assembled from an iVABS-derived stacking sequence to validate the manufacturing methodology. After fabrication, the spar was tested to determine cross-sectional and spanwise properties while establishing confidence in the iVABS optimizer by comparing the experimental and analytical results.

“Future work will expand this effort by modeling, fabricating and validating progressively higher-complexity spar configurations, building toward a representative blade section with elements such as an outer composite skin and sandwich core section aft of the spar,” says Michael Sheppard, graduate student in the PSU Applied Research Lab. “At each phase, experimental measurements will be used to verify and refine the computational results to achieve the desired product. The iVABS framework has also been instrumental in predicting failure loads prior to physical testing, enabling informed experimental planning while strengthening the correlation between analysis and testing.”