(L to R): Professor Jose Restrepo, Grigorios Antonellis, Professor Khalid Mosalam, Andrea Belleri, Michele Egidio Bressanelli, Marco Bosio
Congratulations to the winners of the 2017 PEER Blind Prediction Contest, announced on January 18, 2018, at the 2018 PEER Annual Meeting.
Winner: Practicing Engineers Category
Grigorios Antonellis, Andrew Ma, Anthony Giammona
Nabih Youssef Associates
Winner: Research & Academic Category
Michele Egidio Bressanelli, Marco Bosio, Andrea Belleri
University of Bergamo
19 teams participated in the competition, where the number of teams in the “Research & Academic” and “Practicing Engineers” categories was 10 and 9, respectively. Information provided to the contestants included structural drawings of the specimen and the test setup; tested material properties for reinforcing (mild and prestressing) steel, concrete, steel shell and the grout; construction sequence including photographs; properties of the weight blocks; and measured accelerations on the table for each test. The Blind Prediction testing experiment was conducted by a team led by Professor Jose Restrepo (UC San Diego) and Professor Khalid Mosalam (UC Berkeley).
Participating teams were asked to predict 13 response quantities for each of the applied 9 ground motions, which led to a total of 117 quantities. For each predicted quantity, the teams were ranked in the order of increasing error and the 1st, 2nd, 3rd and 4th teams received 8, 5, 3 and 1 points respectively. Scores for all quantities were summed for each team and the teams with the highest score in each category were declared as the winners.
In addition to the predictions, the contestants were asked to provide a range that they thought the measured response would be within with 80% probability. Statistical evaluation of the competition results is in progress and will be published in the form of scholarly papers and a PEER report soon.
The experimental results are posted on the contest website. Contestants are encouraged to compare their predictions with these results, update their models according to the test results and provide any feedback to the PEER Center (email peer_center@berkeley.edu) on improved modeling.