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Biomechanics

Biomechanics - Poster Session E

Poster Q1 - Pilot Evaluation of a Cervical Spine Surrogate for Blast and Ballistic Testing of Personal Protective Equipment

Saturday, October 26, 2024
10:00 AM - 11:00 AM EST
Location: Exhibit Hall E, F & G

Introduction:  As advancements in technology drive the improvement of military personal protective equipment, human surrogate models are becoming increasingly valuable evaluation tools. Ideal traits for human blast surrogates include high biofidelity, minimal cost, and to provide data that can be used to predict the risk of injury such as traumatic brain injury (TBI). While the mechanism of injury for TBI is still debated amongst the scientific community, most risk prediction tools rely on the kinematics and kinetics of the head and brain. Thus, it is crucial that the cervical spine of the surrogate behaves as close as possible to human movement to facilitate proper motion of the head.

Materials and

Methods:  Cervical spine geometry representative of a 50th percentile male from the Global Human Body Modeling Consortium (GHBMC) was subjected to computational loading in extension and left lateral bending to determine strain energy associated with this motion (Ansys LS-DYNA, Canonsburg, PA). Using the strain energy targets, the model geometry was optimized using nTop (New York, NY) to generate a moldable, stiffness-matched design. 3D printed molds were used to cast specimens in Smooth-Cast 61D urethane resin. The molded model was subjected to 2Nm of pure moment loading using the KR 300 R2500 Ultra Robot from KUKA in flexion, extension, and left and right lateral bending. Moment angle and time history obtained from the Kuka were used to replicate the study in LS DYNA on the GHBMC geometry. The moment required to generate angles under both simulated and experimental testing were then compared.

Results, Conclusions, and Discussions: Each design was optimized under the assumption of fabrication via molding using a urethane-based material with elastic modulus of 60 MPa. Preliminary computational evaluation of the GHBMC cervical spine geometry provided a target strain energy of 0.5 J in flexion/extension, and 0.33 J in lateral bending. Simulation of the optimized design in LS-DYNA prior to fabrication confirmed the ability to hit the set targets with acceptable error. Experimental data obtained from the Kuka robotics system during manipulation of the molded, optimized design required a moment of 1.8 Nm to generate angles of 17.45 degrees in flexion, 25.24 degrees in extension, 13.91 degrees in left lateral bending, and 11.48 degrees in right lateral bending. Recreation of the Kuka test path in LS-DYNA with the GHBMC geometry yielded 1.2 Nm to generate comparable angles in flexion, 0.6 Nm in extension, and 2Nm in right and left lateral bending.

While this pilot study was able to show the ability of the cervical surrogate hit key endpoints representative of the 50th percentile human male, further work is needed to evaluate the performance with statistical significance. Data gathered in this pilot will be used to evaluate material selection for the final surrogate specimen. It is important to note that human movement, as captured in computational modeling, follows non-linear deformation. However, the nTop solver used to optimize the design is a linear solver. Additionally, further testing, both computational and experimental, will be utilized to evaluate the performance of the cervical surrogate when encased in a layer of silicone representative of the skin for the final head model. Final design and material selections will be incorporated into a modular head surrogate which can be anchored to a torso surrogate and subjected to ballistics and blast testing for the prediction of injury risk. When produced at scale, this methodology will lower costs without compromising the integrity of data collected. By optimizing the design to achieve compliance on par with the highly complex human neck, the data collected from sensors located within the skull of the head surrogate will yield more accurate injury risk predictions for TBI.

Acknowledgements (Optional):  This research is supported by U.S. Army Medical Research Acquisition Activity under contract # HT942523C0053. The views, opinions and/or findings contained in this poster are those of the author(s) and should not be construed as an official Department of the Army position, policy or decision unless so designated by other documentation.