Innovative stress analysis and machine learning forecasting for semi-trailer truck body durability

Oleh Lyashuk; Mykhailo Levkovych; Mykola Stashkiv; Oleh Pastukh; Volodymyr Martyniuk; Dmytro Mironov; Marcin Rabe; Yuriy Vovk

doi:10.14254/jsdtl.2023.8-2.3

Oleh Lyashuk ⁽¹⁾ , Mykhailo Levkovych ⁽²⁾ , Mykola Stashkiv ⁽³⁾ , Oleh Pastukh ⁽⁴⁾ , Volodymyr Martyniuk ⁽⁵⁾ , Dmytro Mironov ⁽⁶⁾ , Marcin Rabe ⁽⁷⁾ , Yuriy Vovk ⁽⁸⁾

(1) Department of Automobiles, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil, Ukraine , Ukraine

(2) Department of Automobiles, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil, Ukraine , Ukraine

(3) Department of Automobiles, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil, Ukraine , Ukraine

(4) Department of Software Engineering, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil, Ukraine , Ukraine

(5) Department of Administrative and Financial Management, Lviv Polytechnic National University, Stepana Bandera Str., 12, 79013 Lviv, Ukraine; WSEI University, ul. Projektowa 4, 20-209 Lublin, Poland , Ukraine

(6) Department of Automobiles, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil , Ukraine

(7) Institute of Management, University of Szczecin, al. Papieża Jana Pawła II 22a, 70 – 453 Szczecin, Poland , Poland

(8) Department of Automobiles, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil, Ukraine , Ukraine

https://doi.org/10.14254/jsdtl.2023.8-2.3

Issue
Vol. 8 No. 2 (2023)

Keywords:

transport, energy resources, semi-trailer truck body, static stress, static displacement, CAD model, algorithm, machine learning, sustainability

PDF

Abstract

This article presents an in-depth analysis of the stress-deformation state (SDS) in the bottom structure of a semi-trailer truck body. Engineering analysis was conducted utilizing the SolidWorks software, focusing on a comprehensive CAD model of the semi-trailer truck body. The study explored variations in SDS parameters resulting from alterations in the geometric parameters of the body bottom elements. The research investigated alterations in static stress and displacement relative to changes in the proportions of the cross-section of the channel while maintaining fixed geometric dimensions of the workpiece, thickness of the workpiece, and the material of the body bottom. Graphical representations were generated to illustrate the variations in static stress, displacement, and safety margin concerning the thickness of the shelf and channel. Additionally, dependencies were derived that correlate static stresses in the channel with the thickness of the channel wall and the thickness of the body bottom sheet. The study results were compiled and summarized, offering valuable insights into the stress-deformation state of the semi-trailer truck body's bottom. Furthermore, machine learning techniques, specifically the RandomForest algorithm, were implemented in a Python environment to predict changes in static stress based on various factors. The model's predictions were validated by comparing predicted static stress values with actual values on a test sample. These findings facilitate efficient selection of appropriately sized elements by predicting static stress values, employing the RandomForest machine learning algorithm.

Full text article

Generated from XML file

References

Czech, P. (2013). Intelligent approach to valve clearance diagnostic in cars. In Activities of Transport Telematics: 13th International Conference on Transport Systems Telematics, TST 2013, Katowice-Ustroń, Poland, October 23–26, 2013, Selected Papers 13 (pp. 384-391). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-642-41647-7_47
Czech, P., & Mikulski, J. (2014). Application of Bayes classifier and entropy of vibration signals to diagnose damage of head gasket in internal combustion engine of a car. In Telematics-Support for Transport: 14th International Conference on Transport Systems Telematics, TST 2014, Katowice/Kraków/Ustroń, Poland, October 22-25, 2014. Selected Papers 14 (pp. 225-232). Springer Berlin Heidelberg. https://doi.org/10.1007/978-3-662-45317-9_24
Garud, R. Y., & Pandey, A. (2018). Structural analysis of automotive chassis, design modification and optimization. International Journal of Applied Engineering Research, 13(11), 9887-9892.
Gotmare, D., & Gandhe, R. R. Resonance Prevention in Truck Body through Structure Design Modification-Result Discussion. International Journal for Innovative Research in Science & Technology, 3(02), 275-281.
Krishna, K. V., Reddy, K. Y., Venugopal, K., & Ravi, K. (2017, November). Design and analysis of truck body for increasing the payload capacity. In IOP Conference Series: Materials Science and Engineering (Vol. 263, No. 6, p. 062065). IOP Publishing. https://doi.org/10.1088/1757-899X/263/6/062065
Krishna, K. V., Reddy, K. Y., Venugopal, K., & Ravi, K. (2017, November). Design and analysis of truck body for increasing the payload capacity. In IOP Conference Series: Materials Science and Engineering (Vol. 263, No. 6, p. 062065). IOP Publishing. https://doi.org/10.1088/1757-899X/263/6/062065
Kumar, N. N., Jithendra, B., & Kumar, M. A. (2013). Optimization of weght and stress reduction of dump for automotive vehicles. Int. J. Eng. Res. Technol, 2, 2278-0181.
Lyashuk, O., Levkovych, M., Vovk, Y., Gevko, I., Stashkiv, M., Slobodian, L., & Pyndus, Y. (2023). The study of stress-strain state elements of the truck semi-trailer body bottom. Scientific Journal of Silesian University of Technology. Series Transport, 118. https://doi.org/10.20858/sjsutst.2023.118.11
Mushtaque, M., & Gangwani, D. G. (2016). Design optimization of truck body. International Journal for Innovative Research in Science & Technology, 3(02), 383-385.
Nayak, B. R. P., & Sambaiah, C. (2012). Design and Analysis of Dumped Body. Int. J. Mech. Indus. Eng, 2, 2231-6477.
Ramacharan, C., & Prashanth, A. S. (2015). Design and analysis of Dump Truck Floor Bed. Int. J. Sci. Res. Dev., 3(2015), 2321-0613.
Tson, O. (2016). Analytical evaluation of technical and operational indicators impact on the transportation technology by automobile trailers. Journal of Sustainable Development of Transport and Logistics, 1(1), 23-26. https://doi.org/10.14254/jsdtl.2016.1-1.4
Ukraine State Statistic Service (n.d.). Official Website. Retrived from https://www.ukrstat.gov.ua/
Vinjavarapu, S., Koteswararao, U., & Narayana, V. L. (2012). Design Optimization of Tipper Truck Body. International Journal of Engineering Research and Development, 4(9), 11-20.

Authors

Oleh Lyashuk

Department of Automobiles, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil, Ukraine

Mykhailo Levkovych

Department of Automobiles, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil, Ukraine

Mykola Stashkiv

Department of Automobiles, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil, Ukraine

stam77@ukr.net (Primary Contact)

Oleh Pastukh

Department of Software Engineering, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil, Ukraine

Volodymyr Martyniuk

Department of Administrative and Financial Management, Lviv Polytechnic National University, Stepana Bandera Str., 12, 79013 Lviv, Ukraine; WSEI University, ul. Projektowa 4, 20-209 Lublin, Poland

Dmytro Mironov

Department of Automobiles, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil

Marcin Rabe

Institute of Management, University of Szczecin, al. Papieża Jana Pawła II 22a, 70 – 453 Szczecin, Poland

Yuriy Vovk

Department of Automobiles, Ternopil Ivan Puluj National Technical University, 56, Ruska Str., 46001 Ternopil, Ukraine

Lyashuk, O., Levkovych, M., Stashkiv, M., Pastukh, O., Martyniuk, V., Mironov, D., Rabe, M., & Vovk, Y. (2023). Innovative stress analysis and machine learning forecasting for semi-trailer truck body durability. Journal of Sustainable Development of Transport and Logistics, 8(2), 43–57. https://doi.org/10.14254/jsdtl.2023.8-2.3

Download Citation

This work is licensed under a Creative Commons Attribution 4.0 International License.

Authors retain copyright and grant the journal right of first publication, with the work simultaneously licensed under a CC BY 4.0 License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.