TY - GEN
T1 - Performance of Shrinkage Estimators for Bioburden Density Calculations in Planetary Protection Probabilistic Risk Assessment
AU - Gribok, Andrei
AU - Seuylemezian, Arman
N1 - Funding Information:
The research was partially carried out at the Jet Propulsion Laboratory, California Institute of Technology under a contract with the National Aeuronautics and Space Administration (80NM0018D0004). Copyright © 2022 All rights reserved. We would like to thank the InSight mission team of Ryan Hendrickson, Gayane Kazarians, Lisa Guan, Sarah Cruz, and Pat Bevins for providing support in data generation. The authors would also like to thank Art Avila for their management support of this project and of this manuscript. This research was supported by the National Aeuronautics and Space Administration through the interagency collaboration agreement “Probabilistic Risk Analysis for Statistical Analysis of Bioburden Sampling Efficiencies” performed at Idaho National Laboratory. This manuscript has been authored by Battelle Energy Alliance, LLC under Contract No. DE-AC07-05ID14517 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. Government purposes
Funding Information:
research was supported by the National Aeuronautics and Space Administration through the interagency collaboration agreement “Probabilistic Risk Analysis for Statistical Analysis of Bioburden Sampling Efficiencies” performed at Idaho National Laboratory. This manuscript has been authored by Battelle Energy Alliance, LLC under Contract No. DE-AC07-05ID14517 with the U.S. Department of Energy. The United States Government retains and the publisher, by accepting the article for publication, acknowledges that the U.S. Government retains a nonexclusive, paid-up, irrevocable, world-wide license to publish or reproduce the published form of this manuscript, or allow others to do so, for U.S. Government purposes
Publisher Copyright:
© 2022 Probabilistic Safety Assessment and Management, PSAM 2022. All rights reserved.
PY - 2022
Y1 - 2022
N2 - Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. The National Aeronautics and Space Administration has developed a set of requirements (NPR 8715.24) based on recommendations from the Committee on Space Research that each mission must comply with regarding both forward and backward PP. Biological cleanliness requirements to target bodies, such as Mars, include spacecraft assembly control and the direct testing of the microbial bioburden of different components to comply with PP requirements. The data for each component are collected using either swabs or wipes. For each component, a number of samples are collected on one given date or on several different dates along the course of the part assembly. Given the clean spacecraft, on the average 93% of the swabs and 63% of the wipes have no colony forming units (CFU) count at 72 hours, resulting in ~85% of the 39,379 petri dishes yielding 0 CFU. Due to low CFU counts and small sampling areas, given the Poisson distributional model, the bioburden density estimates have inflated variance and confidence intervals. Shrinkage estimators are standard tools to deal with large variance and estimate inconsistencies. This paper presents the performance results of six shrinkage estimators along with the maximum likelihood, population-average, and zero estimators applied to the bioburden density estimation using InSight mission data. The results show that, for poolable data sets, the best estimator is population average, while for nonpoolable data sets, the Tsui estimator along with the empirical Bayes estimator produced the lowest mean squared error.
AB - Planetary protection (PP) is a discipline that focuses on minimizing the biological contamination of spacecraft to ensure compliance with international policy. The National Aeronautics and Space Administration has developed a set of requirements (NPR 8715.24) based on recommendations from the Committee on Space Research that each mission must comply with regarding both forward and backward PP. Biological cleanliness requirements to target bodies, such as Mars, include spacecraft assembly control and the direct testing of the microbial bioburden of different components to comply with PP requirements. The data for each component are collected using either swabs or wipes. For each component, a number of samples are collected on one given date or on several different dates along the course of the part assembly. Given the clean spacecraft, on the average 93% of the swabs and 63% of the wipes have no colony forming units (CFU) count at 72 hours, resulting in ~85% of the 39,379 petri dishes yielding 0 CFU. Due to low CFU counts and small sampling areas, given the Poisson distributional model, the bioburden density estimates have inflated variance and confidence intervals. Shrinkage estimators are standard tools to deal with large variance and estimate inconsistencies. This paper presents the performance results of six shrinkage estimators along with the maximum likelihood, population-average, and zero estimators applied to the bioburden density estimation using InSight mission data. The results show that, for poolable data sets, the best estimator is population average, while for nonpoolable data sets, the Tsui estimator along with the empirical Bayes estimator produced the lowest mean squared error.
UR - https://www.scopus.com/pages/publications/85146224432
M3 - Conference contribution
AN - SCOPUS:85146224432
BT - 16th International Conference on Probabilistic Safety Assessment and Management, PSAM 2022
T2 - 16th International Conference on Probabilistic Safety Assessment and Management, PSAM 2022
Y2 - 26 June 2022 through 1 July 2022
ER -