@article{ref1,
title="Optimisation of rotorcraft fuel tank for crashworthiness based on a neural network",
journal="International journal of crashworthiness",
year="2016",
author="Kim, Hyun-Gi and Kim, Sung Chan and Kim, Sung Joon",
volume="21",
number="3",
pages="242-251",
abstract="Crashworthy fuel tank has been widely implemented among rotorcraft, and they have served a valuable contribution to improving the survivability of crews and passengers. From the early stages of military rotorcraft history, the US Army has developed and implemented a detailed military specification documenting the unique crashworthiness requirements for rotorcraft fuel tank with the aim of reducing the high incidence of fatalities due to post-crash fires. International manufacturers have followed this information to develop their own fuel tank, and have reflected the results of crash impact tests in trial-and-error design and manufacturing processes. Since the crash impact test itself requires lengthy preparation together with costly fuel cell specimens, a series of numerical simulations of the crash impact test with digital mock-ups is necessary, even at the early design stage, in order to minimise trial-and-error testing with full-scale fuel tank. In this study, a number of numerical simulations on fuel cell crash impact tests are performed with the crash simulation software, ANSYS/Autodyn. The resulting equivalent stresses are further analysed to evaluate a number of appropriate design parameters and the artificial neural network and simulated annealing method are simultaneously implemented to optimise the crashworthy performance of fuel tank.<p /> <p>Language: en</p>",
language="en",
issn="1358-8265",
doi="10.1080/13588265.2016.1165447",
url="http://dx.doi.org/10.1080/13588265.2016.1165447"
}