A large-scale validation study of aircraft noise modeling for airport arrivals.

In the U.S., the Federal Aviation Administration's Aviation Environmental Design Tool (AEDT) is approved to predict the impacts of aircraft noise and emissions. AEDT's critical role in regulatory compliance and evaluating the environmental impacts of aviation requires asking how accurate are its noise predictions. Previous studies suggest that AEDT's predictions lack desired accuracy. This paper reports on a large-scale study, using 200 000 flight trajectories paired with measured sound levels for arrivals to Runways 28L/28R at San Francisco International Airport, over 12 months. For each flight, two AEDT studies were run, one using the approved mode for regulatory filing and the other using an advanced non-regulatory mode with exact aircraft trajectories. AEDT's per aircraft noise predictions were compared with curated measured sound levels at two locations. On average, AEDT underestimated LAmax by -3.09 dB and SEL by -2.04 dB, combining the results from both AEDT noise-modeling modes. Discrepancies appear to result from limitations in the physical modeling of flight trajectories and noise generation, combined with input data uncertainties (aircraft weight, airspeed, thrust, and lift configuration) and atmospheric conditions.

SKOLAR MD: a model for self-directed, in-context Continuing Medical Education.

UNLABELLED: SKOLAR has implemented a web-based CME program with which physicians can earn AMA Category 1 credit for self-directed learning. METHODS: Physicians researched their questions in SKOLAR and applied for CME. Physician auditors reviewed all requests across two phases of the project. A selection rule set was derived from phase one and used in phase two to flag a subset of requests for detailed review. The selection rule set is described. RESULTS: In phase one, SKOLAR received 1039 CME applications. Applicants frequently found their answer (94%) and would apply it clinically (93%). A linear regression analysis comparing time awarded to time requested (capped at actual time spent) had R2=0.79. DISCUSSION: We believe that that this self-directed approach to CME is effective and an important complement to traditional CME programs. However, selective audit of self-directed CME requests is necessary to ensure validity of credits awarded.