Orthodontic measurements and nasal respiratory function after surgically assisted rapid maxillary expansion: an acoustic rhinometry and rhinomanometry study

The present study sought to assess nasal respiratory function in adult patients with maxillary constriction who underwent surgically assisted rapid maxillary expansion (SARME) and to determine correlations between orthodontic measurements and changes in nasal area, volume, resistance, and airflow. Twenty-seven patients were assessed by acoustic rhinometry, rhinomanometry, orthodontic measurements, and use of a visual analogue scale at three time points: before surgery; after activation of a preoperatively applied palatal expander; and 4 months post-SARME. Results showed a statistically significant increase (p < 0.001) in all orthodontic measurements. The overall area of the nasal cavity increased after surgery (p < 0.036). The mean volume increased between assessments, but not significantly. Expiratory and inspiratory flow increased over time (p < 0.001). Airway resistance decreased between assessments (p < 0.004). Subjective analysis of the feeling of breathing exclusively through the nose increased significantly from one point in time to the next (p < 0.05). There was a statistical correlation between increased arch perimeter and decreased airway resistance. Respiratory flow was the only variable to behave differently between sides. The authors conclude that the SARME procedure produces major changes in the oral and nasal cavity; when combined, these changes improve patients' quality of breathing.

Modeling random corrosion processes via polynomial chaos expansion

Polynomial Chaos Expansion (PCE) is widely recognized as a flexible tool to represent different types of random variables/processes. However, applications to real, experimental data are still limited. In this article, PCE is used to represent the random time-evolution of metal corrosion growth in marine environments. The PCE coefficients are determined in order to represent data of 45 corrosion coupons tested by Jeffrey and Melchers (2001) at Taylors Beach, Australia. Accuracy of the representation and possibilities for model extrapolation are considered in the study. Results show that reasonably accurate smooth representations of the corrosion process can be obtained. The representation is not better because a smooth model is used to represent non-smooth corrosion data. Random corrosion leads to time-variant reliability problems, due to resistance degradation over time. Time variant reliability problems are not trivial to solve, especially under random process loading. Two example problems are solved herein, showing how the developed PCE representations can be employed in reliability analysis of structures subject to marine corrosion. Monte Carlo Simulation is used to solve the resulting time-variant reliability problems. However, an accurate and more computationally efficient solution is also presented.