ABSTRACT
The growth of additive manufacturing processes has enabled the production of complex and smart structures. These fabrication techniques have led research efforts to focus on the application of cellular materials, which are known for their thermal and mechanical benefits. Herein, we studied the mechanical behavior of stainless-steel (AISI 316L) lattice structures both experimentally and computationally. The lattice architectures were body-centered cubic, hexagonal vertex centroid, and tetrahedron in two cell sizes and at two different rotation angles. A preliminary computational study assessed the deformation behavior of porous cylindrical samples under compression. After the simulation results, selected samples were manufactured via laser powder bed fusion. The results showed the effects of the pore architecture, unit cell size, and orientation on the reduction in the mechanical properties. The relative densities between 23% and 69% showed a decrease in the bulk material stiffness up to 93%. Furthermore, the different rotation angles resulted in a similar porosity level but different stiffnesses. The simulation analysis and experimental results indicate that the variation in the strut position with respect to the force affected the deformation mechanism. The tetrahedron unit cell showed the smallest variation in the elastic modulus and off-axis displacements due to the cell orientation. This study collected computational and experimental data for tuning the mechanical properties of lattice structures by changing the geometry, size, and orientation of the unit cell.
ABSTRACT
Laparoscopic surgery demands highly skilled surgeons. Traditionally, a surgeon's knowledge is acquired by operating under a mentor-trainee method. In recent years, laparoscopic simulators have gained ground as tools in skill acquisition. Despite the wide range of laparoscopic simulators available, few provide objective feedback to the trainee. Those systems with quantitative feedback tend to be high-end solutions with limited availability due to cost. A modular smart trainer was developed, combining tool-tracking and force-using employing commercially available sensors. Additionally, a force training system based on polydimethylsiloxane (PDMS) phantoms for sample stiffness differentiation is presented. This prototype was tested with 39 subjects, between novices (13), intermediates (13), and experts (13), evaluating execution differences among groups in training exercises. The estimated cost is USD $200 (components only), not including laparoscopic instruments. The motion system was tested for noise reduction and position validation with a mean error of 0.94 mm. Grasping force approximation showed a correlation of 0.9975. Furthermore, differences in phantoms stiffness effectively reflected user manipulation. Subject groups showed significant differences in execution time, accumulated distance, and mean and maximum applied grasping force. Accurate information was obtained regarding motion and force. The developed force-sensing tool can easily be transferred to a clinical setting. Further work will consist on a validation of the simulator on a wider range of tasks and a larger sample of volunteers.
