Spinal Fatigue Prediction in High-G Environments Using Human Digital Twins
PI: Reuben Kraft (ME/Biomedical)
Tuition support for graduate students will be provided through existing funds from AFRL Contract FA8650-22-C-6462.
Effort Requested: 25% RA (academic year or summer)
Project Description
This project develops a digital twin framework to evaluate spinal fatigue in pilots subjected to high G acceleration. Using the Toyota Human Model for Safety (THUMS), we simulate cervical spine stress and fatigue damage progression across seat configurations found in fighter aircraft. The computational damage model incorporates mechanical fatigue, age related degeneration, and recovery processes to estimate long term degradation of intervertebral discs.
The ICDS Junior Researcher will contribute to simulation refinement, parameter studies, and data processing. Tasks may include automating input and output workflows, running comparative studies across anthropometries, and examining sensitivity to material and loading assumptions. The research lies at the intersection of biomechanics, computational modeling, and human performance prediction, and offers a substantive interdisciplinary experience aligned with ICDS priorities.
Desired Skills and Expectations
The ideal candidate will have experience with finite element modeling using tools such as LS DYNA, along with scripting abilities in Python or MATLAB. Background in biomechanics or interest in digital twins applied to human physiology is encouraged. The Junior Researcher should be a post comps PhD student in mechanical or biomedical engineering and available for weekly check ins and regular collaborative work.
Objectives for the Period of Support
During the period of ICDS support, the goal is to complete parametric simulations across multiple seat angles and loading conditions, extract relevant stress and fatigue metrics, and prepare data and visuals for AFRL program reporting. In addition, the student will contribute to manuscript preparation and presentation materials. The effort will culminate in a structured dataset that may be used to inform reduced order models or surrogate methods in follow on phases.
Long Term Goal
This project lays the foundation for an expanded research agenda on human digital twins for defense applications. In parallel with the work supported by ICDS, we will prepare a secondary proposal to the Department of Defense aimed at establishing a more comprehensive digital twin framework that integrates real world pilot data, sensor feedback, and predictive modeling tools for operational decision support. The combined effort will position us to submit follow on proposals to NSFprograms such as BMMB,with a focus on AI agents for human body meshing—a complex task that requires foundational research at the interface of biomechanics and computation.
Connection to the ICDS Mission
This project supports the ICDS mission by integrating physics based simulation, data driven modeling, and digital twin methods to predict spinal fatigue in pilots, demonstrating how computational science can inform human health, performance, and safety in extreme environments.