2024
3811. Parametric Weight Substantiation And Uncertainty Quantification For Aircraft Design
Walker, Andy
In: 83rd International Conference, virtual (2024), pp. 46, SAWE Society of Allied Weight Engineers, Inc., 2024.
@inproceedings{3811,
title = {3811. Parametric Weight Substantiation And Uncertainty Quantification For Aircraft Design},
author = {Andy Walker},
url = {https://www.sawe.org/product/3811-parametric-weight-substantiation-and-uncertainty-quantification-for-aircraft-design/},
year = {2024},
date = {2024-05-22},
booktitle = {83rd International Conference, virtual (2024)},
pages = {46},
publisher = {Society of Allied Weight Engineers, Inc.},
organization = {SAWE},
abstract = {Creating and substantiating weight estimation methods for future aircraft design has been completed using open-source data. Legacy best-practices were explored in corelating weight estimating relationships for configurations relating to manned fighters, carrier-based fighters, jet transports, business jets, military intelligence/ surveillance/ reconnaissance (ISR), and general aviation. Statistical methods were used to validate that each parametric method follows a normal, Gaussian distribution. This paper also makes some novel observations regarding statistical weight regressions, including: the fallacy of removing data points in regressions, the good and bad side of adding weight growth margins, employing detailed vs coarse weight method calibration factors, and how legacy aircraft validation helps in the big picture but hurts in the details.},
keywords = {Aircraft, Other Engineering},
pubstate = {published},
tppubtype = {inproceedings}
}
Creating and substantiating weight estimation methods for future aircraft design has been completed using open-source data. Legacy best-practices were explored in corelating weight estimating relationships for configurations relating to manned fighters, carrier-based fighters, jet transports, business jets, military intelligence/ surveillance/ reconnaissance (ISR), and general aviation. Statistical methods were used to validate that each parametric method follows a normal, Gaussian distribution. This paper also makes some novel observations regarding statistical weight regressions, including: the fallacy of removing data points in regressions, the good and bad side of adding weight growth margins, employing detailed vs coarse weight method calibration factors, and how legacy aircraft validation helps in the big picture but hurts in the details.
