Published July 18, 2024
| Version v3
Dataset
Open
Dataset for Crashworthiness in preliminary design: Mean crushing force prediction for closed-section thin-walled metallic structures
Authors/Creators
Description
This dataset is the official implementation of the following paper published in the International Journal of Impact Engineering journal:
Shreyas Anand, René Alderliesten, Saullo G. P. Castro. "Crashworthiness in preliminary design: Mean crushing force prediction for closed-section thin-walled metallic structures". International Journal of Impact Engineering, 2024. 10.1016/j.ijimpeng.2024.104946
Highlights
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Evaluation of analytical models to predict mean crushing force
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Analysis of both extensional and inextensional analytical crushing models.
- Use of numerical and experimental dataset to improve existing analytical models.
- Generalized expression for predicting mean crushing force
Abstract
To design crash structures for disruptive aircraft designs, it is required to have fast and accurate methods that can predict crashworthiness of aircraft structures early in the design phase. Axial crushing is one of the key energy absorbing mechanisms during a crash event. In this study, various analytical models proposed for calculation of mean crushing force for thin-walled tubular structures are compared with a database of numerical and experimental values to ascertain their accuracy. Improvements to some of the models have also been proposed. Finally a generalized model based on the studied and improved analytical models for prediction of mean crushing force for closed section thin-walled tubular structures is introduced. The generalized model demonstrates high accuracy when compared against experimental/numerical dataset as evidenced by a high coefficient of determination (R^2) value of 0.97 and can therefore be used to estimate the mean crushing force for closed-section thin-walled metallic tubular structures with various cross-sectional shapes and crushing modes early in the design phase.
Files
AA6060_T4_Circular_input_files.zip
Files
(37.4 MB)
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