SBIR Phase II: A Fractional-Order Computational Platform for the Multiscale and Multiphysics Analysis of Failure-Critical Systems

The broader impact of this Small Business Innovation Research (SBIR) Phase II project is to enable faster design cycles and less expensive maintenance operations of aerospace structural systems while simultaneously improving their overall safety and durability. By developing the next generation of computational tools that can efficiently and accurately predict the aging and degradation of complex structural systems at full scale, this project will provide critical technology to the aerospace industry to accelerate the design of next generation systems, track unit-specific aging of the in-service aircraft fleet, and lower the dependence from complex and expensive full-scale testing. Empowered with these new predictive tools, engineers will be able to proactively address potential failures, reduce the risk of catastrophic accidents, safeguard valuable assets, and minimize equipment downtime. The technology at the core of this project has also the potential to make transformative impacts across multiple areas of socio-economic significance whose progress strongly relies on predictive simulation tools. Examples include, but are not limited to, advancing health and welfare via enhanced modeling capabilities for drug delivery and disease spread, more accurate prediction of extreme climate events, designing safer and more sustainable infrastructure systems.

This Small Business Innovation Research (SBIR) Phase II project will focus on the development and validation of a fractional calculus-based simulation framework to perform material degradation analysis of complex aerospace structural systems. Despite the remarkable advancements in the general area of material and damage mechanics simulations, the existing gap between simulation capabilities and the complex reality of practical aerospace applications still requires industry to heavily rely on extensive full-scale experimental campaigns. These campaigns are expensive, time-consuming, and product-dependent, ultimately increasing production and maintenance costs, and potentially affecting equipment downtime. Building on the results from Phase I, this project will further explore and develop this simulation technology to achieve accurate predictive analysis of critical and potentially catastrophic material degradation mechanisms, such as fatigue and fracture propagation. Main objectives include the development of theoretical and computational technology, its integration in production-grade and industry-ready software, and its validation across multiple material systems and damage scenarios of practical aerospace relevance. The resulting software will offer a unique combination of high computational efficiency, fidelity, and accuracy, hence providing a fully integrated end-to-end predictive framework that will support the aerospace industry in developing safer, more affordable, and more sustainable transportation systems.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Award Number: 2445824
Principal Investigator: Siddharth Nair
Funds Obligated: $1,177,447
State: IN