2019 PHM Conference Data Challenge – Submission Page
Submissions Due by Sunday, 31 July 2019 at 23:59:59 PDT
- Validation results must be submitted between Sunday, 14 July 2019 and Sunday, 31 July 2019 at 23:59:59 Pacific Daylight Time (PDT = UTC-7:00).
- One team noticed a discrepancy in the scoring spreadsheet. The spreadsheet uses m = 100 for the monotonicity penalty function, whereas the scoring description has m = 10. The correct monotonicity penalty function will be m = 10. For further information or to post a comment or concern, please respond to the Forum post on this topic here or copy/paste the URL below.
- Please see the forum post (here) or copy & paste the following for explanation of the update to the training and the impact to the competition.
Validation Data (All Stages):
Description of Submission Process
- You are asked to estimate the crack length (in millimeters) for each specimen and submit your estimates in the tables below.
- Note that the validation data only corresponds to the first few cycles listed in the each table. For the remaining cycles, you are asked to predict the crack length (again, in millimeters) for the future cycle numbers.
- Once submitted, the estimates you entered will be displayed back in the table below. PLEASE VERIFY YOU ENTERED THE VALUES CORRECTLY.
- You may modify your submitted values at any point up to the submission deadline. The latest values entered prior to the deadline will be used to score your submission.
- The submission forms (tables) for T7 and T8 are not linked. Please fill out (or modify) each table separately.
- Please use a period (“.”) as the decimal separator and not a comma (“,”). For example, pi would be entered as 3.14159 (as opposed to 3,14159).
If Submissions Due by Sunday, 31 July 2019 at 23:59:59 PDTat any point you have a problem with the submission process, please contact firstname.lastname@example.org so that we may investigate. We will not be able to revert any values that have been confirmed if you have downloaded subsequent data or our logs indicate suspected tampering of the system.