scholarly journals Neural Networks in Crashworthiness Analysis of Thin-Walled Profile with Foam Filling

2020 ◽  
Vol 14 (3) ◽  
pp. 93-99 ◽  
Author(s):  
Michał Rogala
2017 ◽  
Vol 62 (1) ◽  
pp. 435-442 ◽  
Author(s):  
P. Golewski ◽  
J. Gajewski ◽  
T. Sadowski

Abstract Artificial neural networks [ANNs] are an effective method for predicting and classifying variables. This article presents the application of an integrated system based on artificial neural networks and calculations by the finite element method [FEM] for the optimization of geometry of a thin-walled element of an air structure. To ensure optimal structure, the structure’s geometry was modified by creating side holes and ribs, also with holes. The main criterion of optimization was to reduce the structure’s weight at the lowest possible deformation of the tested object. The numerical tests concerned a fragment of an elevator used in the “Bryza” aircraft. The tests were conducted for networks with radial basis functions [RBF] and multilayer perceptrons [MLP]. The calculations described in the paper are an attempt at testing the FEM - ANN system with respect to design optimization.


Materials ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3630
Author(s):  
Michał Rogala ◽  
Mirosław Ferdynus ◽  
Katarzyna Gawdzińska ◽  
Paweł Kochmański

The demand for lightweight, strong structural profiles is currently high in the transport industry, mechanical engineering, and construction. Therefore, it is important to evaluate their properties, especially mechanical properties. The main objective of this paper is to determine energy absorption coefficients and evaluate the crush resistance of thin-walled aluminum profiles using numerical simulation and empirical verification. This paper presents the compression results of testing of thin-walled aluminum profiles filled with a porous material (cast aluminum foam). The numerical analysis was conducted using the software Abaqus/CAE. Aluminum material data were obtained from a static tensile test performed on a Shimadzu machine. The experiment was performed on an Instron CEAST 9450HES dynamic hammer. Profiles with three shapes of crush initiators filled with aluminum foam measuring 40 mm–200 mm in 20 mm increments were numerically tested. A sample with a concave initiator filled with foams of 40 mm, 60 mm, 80 mm, and 120 mm in length was used to verify the numerical analyses. Energy absorption coefficients were determined from the analyses. The results of both analyses were tabulated to show the percentage differences. The study showed an increase in the Crush Load Efficiency (CLE) index by up to 33% for samples with the same crush initiator. In addition, it was noted that the use of porous fill does not increase the value of initiating Peak Crushing Force (PCF), which indicates the generation of much smaller overloads dangerous for vehicle passengers.


Author(s):  
Zhaokai Li ◽  
Yuxing Tian ◽  
Jiantao Bai ◽  
Wenjie Zuo

The aluminium profiles of treble rectangular thin-walled tubes (TRTWT) manufactured by extrusion processes are extensively applied in energy absorption structures of automobile due to the high crashworthiness and stiffness-to-mass ratio. Therefore, this paper investigates the bending collapse characteristics of the TRTWT and its application in conceptual design for automobile crashworthiness. Firstly, the bending collapse behaviours of the TRTWT are obtained through experimental method. Then, the analytical expressions for the bending collapse characteristics are derived in detail by using the global energy equilibrium theory, which are validated by comparing with experimental and numerical results. Furthermore, the bending collapse characteristics are applied in the simplified model to conduct crashworthiness analysis and optimization for the conceptual design of the automobile with the TRTWT, which can enhance the crashworthiness and greatly shorten design cycle. Finally, application examples for the front-end and side-wall structures of automobile demonstrate that the simplified model with the analytical bending collapse characteristics can be used as a substitute of detailed model for accelerating crashworthiness design of the automobile with the TRTWT.


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