Application of neural networks specific forms for estimation of crushing signal parameters of multilevel structural absorbers implemented in passive safety research
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60162694%3AG43__%2F26%3A00563675" target="_blank" >RIV/60162694:G43__/26:00563675 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S0263224124017020" target="_blank" >https://www.sciencedirect.com/science/article/pii/S0263224124017020</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.measurement.2024.115817" target="_blank" >10.1016/j.measurement.2024.115817</a>
Alternative languages
Result language
angličtina
Original language name
Application of neural networks specific forms for estimation of crushing signal parameters of multilevel structural absorbers implemented in passive safety research
Original language description
In case of classic thin-walled energy absorber the energy dissipation is not sufficiently controlled during a collision. A significant part of the columns does not participate in plastic deformation sufficiently. This is due to a lack of proper crush initiators for the formation of subsequent joints. The research problem of the article is to presents a method of applying artificial intelligence methods for determining the optimal parameters of crush initiators, in order to make proper use of plastic deformation zones and improve the efficiency of energy absorption. The methodology is based on the artificial neural network models made possible to select the best and optimal design parameters of multilevel crush initiators. The results of numerical tests were verified on the test bench. The values of all crashworthiness indicators improved, the PCF has been reduced up to 30% from for certain geometric parameters of the multilevel crush initiator.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
21100 - Other engineering and technologies
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
MEASUREMENT
ISSN
0263-2241
e-ISSN
1873-412X
Volume of the periodical
242
Issue of the periodical within the volume
115817
Country of publishing house
GB - UNITED KINGDOM
Number of pages
18
Pages from-to
115817
UT code for WoS article
001328199700001
EID of the result in the Scopus database
2-s2.0-85204953090