Integrated finite element and reduced-order modeling analysis of a real flat top tower crane system

Mustafa Tınkır
Department of Mechanical Engineering, Faculty of Engineering, Necmettin Erbakan University, Konya 42090, Turkey
Ali Çoban
Department of Mechanical Engineering, Faculty of Engineering and Natural Sciences, Konya Technical University, Konya 42250, Turkey; acoban@ktun.edu.tr

Article ID: 4531

Keywords: flat top tower crane; finite element analysis; reduced-order modeling; discrete parameter system; modal analysis

Abstract

This study presents the structural and dynamic analysis of a real 60/15 flat-top tower crane with a free-standing height of 48 m. Finite element analyses were performed to evaluate the stress distribution, deformation, and dynamic characteristics of the main structural components. Based on the finite element results, a 17-degree-of-freedom (17-DOF) reduced-order mathematical model was developed. The stiffness coefficients were obtained from the finite element deformations using Hooke's law, while the damping coefficients were determined analytically. An elastic multibody model of the crane was also developed in MATLAB/SimMechanics to validate the proposed reduced-order model. The finite element analyses showed that the maximum equivalent stress remained below the allowable stress limit (approximately 225 MPa), while the maximum displacement of the mast reached 183.94 mm under the design loading condition. Modal analysis indicated that the counter-jib had the lowest first natural frequency (0.64 Hz), making it the most flexible structural component of the crane. Under the same 2-t tip load, the maximum difference between the proposed 17-DOF model and the SimMechanics model was only 4.86% in the jib tip deflection. These results show that the proposed model can accurately represent the structural behavior of the crane while providing a computationally efficient reduced-order representation of the crane compared with detailed finite element modeling. The developed model provides a practical tool for structural analysis, vibration evaluation, design studies, and future control applications of real flat-top tower crane systems.

Published

2026-08-16

How to Cite

Tınkır, M., & Çoban, A. (2026). Integrated finite element and reduced-order modeling analysis of a real flat top tower crane system. Sound & Vibration, 60(5). https://doi.org/10.59400/sv4531

Download Citation

Issue

Vol. 60 No. 5 (2026)

Section

Article

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

References

[1]Augustyn M, Barski M. Numerical and analytical determination of the critical wind speed causing the overturning of the top-slewing tower crane. Applied Sciences. 2025; 15(9): 4683. doi: 10.3390/app15094683

[2]Chen W, Qin X, Yang Z, et al. Wind-induced tower crane vibration and safety evaluation. Journal of Low Frequency Noise, Vibration and Active Control. 2020; 39(2): 297–312. doi: 10.1177/1461348419847306

[3]EN 1991-1-4. Eurocode 1: Actions on Structures–Part 1-4: General Actions–Wind Actions. 2010.

[4]Federation Europeenne de la Manutention. FEM 1.001: Rules for the Design of Hoisting Appliances, 3rd ed. Federation Europeenne de la Manutention; 1998.

[5]Gerdemeli I, Kurt S, Deliktaş O. Finite element analysis of the tower crane. In: Proceedings of the 14th International Research/Expert Conference on Trends in the Development of Machinery and Associated Technology; 11–18 September 2010; Mediterranean Cruise, Turkey. pp. 11–18.

[6]Gu YQ, Wang WF, Guo SD. Analysis on tower crane under wind load by ANSYS. Applied Mechanics and Materials. 2012; 226–228: 35–38. doi: 10.4028/www.scientific.net/AMM.226-228.35

[7]Qing L, Zeng YH. Finite element analysis on tower crane based on ANSYS. Applied Mechanics and Materials. 2012; 190–191: 373–380. doi: 10.4028/www.scientific.net/AMM.190-191.373

[8]Karpe A, Karpe S, Chawrai A, et al. Validation of use of FEM (ANSYS) for structural analysis of tower crane jib and static and dynamic analysis of tower crane jib using ANSYS. International Journal of Innovative Research in Applied Engineering. 2014; 1(4): 69–75.

[9]Zeng G, Chen K, Wang Y, et al. Stress and strain analysis and parameter optimization of pipe truss tower connection of super-large tower crane based on FEM. Scientific Reports. 2024; 14(1): 3670. doi: 10.1038/s41598-024-54351-y

[10]Zhang Q, Mei B, Yang H, et al. Stress measurement and analysis of structural parameters of flat arm tower crane under different working conditions. Buildings. 2025; 15(7): 1137. doi: 10.3390/buildings15071137

[11]Huang GJ, He CZ, Wang XH. A modal analysis of giant shipbuilding tower crane. Applied Mechanics and Materials. 2013; 239–240: 473–477. doi: 10.4028/www.scientific.net/AMM.239-240.473

[12]Lei JF, Chen XH, Huang L, et al. Modeling and modal analysis of the whole structure of PT7032 tower crane based on finite element method. Advanced Materials Research. 2013; 706–708: 1433–1436. doi: 10.4028/www.scientific.net/AMR.706-708.1433

[13]Guo H, Chen K. Modal and fatigue characteristics analysis of key components of tower crane. Vibroengineering Procedia. 2024; 54: 72–77. doi: 10.21595/vp.2024.23826

[14]Trong DX, Toan LK, Ngoc HT, et al. Modal analysis of cracked tower crane with an experimental validation. Vietnam Journal of Science and Technology. 2020; 58(6): 776–788. doi: 10.15625/2525-2518/58/6/15298

[15]Jiang H, Li S. The wind-induced vibration response for tower crane based on virtual excitation method. Open Mechanical Engineering Journal. 2014; 8: 201–205.

[16]Jiang H, Li Y. Dynamic reliability analysis of tower crane with wind loading. IOP Conference Series: Materials Science and Engineering. 2019; 677(5): 052031. doi: 10.1088/1757-899X/677/5/052031

[17]Lu Y, Gao M, Liang T, et al. Wind-induced vibration assessment of tower cranes attached to high-rise buildings under construction. Automation in Construction. 2022; 135: 104132. doi: 10.1016/j.autcon.2022.104132

[18]Oliveira CS, Correia PMB. Comparison of the seismic and wind analyses of two tower cranes. Journal of Vibroengineering. 2021; 23(4): 956–975. doi: 10.21595/jve.2021.21649

[19]Liu F, Yang J, Wang J, et al. Effect on tower crane structural vibration under the lifting-luffing coupling condition. Journal of Mechanical Science and Technology. 2023; 37(10): 4935–4947. doi: 10.1007/s12206-023-0702-4

[20]Rauscher F, Sawodny O. An elastic jib model for the slewing control of tower cranes. IFAC-PapersOnLine. 2017; 50(1): 9796–9801. doi: 10.1016/j.ifacol.2017.08.886

[21]Stölzner M, Kleeberger M, Moll M, et al. Investigation of the dynamic loads on tower cranes during slewing operations. In: Proceedings of the 10th International Conference on Simulation and Modeling Methodologies, Technologies and Applications (SIMULTECH); 8–10 July 2020; Online. pp. 59–67. doi: 10.5220/0009816300590067

[22]Yang Y, Zhang Z, Xu L, et al. Mechanical performance and failure mode research on the braced frame joint of tower cranes in high-rise building construction. Frontiers in Materials. 2022; 9: 824693. doi: 10.3389/fmats.2022.824693

[23]Yang ZJ, Ai ZD, An HW. Mechanics analysis of tower crane. Applied Mechanics and Materials. 2014; 580–583: 3034–3037. doi: 10.4028/www.scientific.net/AMM.580-583.3034

[24]Gu YQ, Mao CF. The preliminary analysis on tower crane by earthquake effect. Applied Mechanics and Materials. 2013; 353–356: 1892–1895. doi: 10.4028/www.scientific.net/AMM.353-356.1892

[25]Kenan H, Azeloğlu O. Design of scaled down model of a tower crane mast by using similitude theory. Engineering Structures. 2020; 220: 110985. doi: 10.1016/j.engstruct.2020.110985

[26]Zhu L, Wang Y. Static analysis and modal analysis of crane arms of tower cranes based on ANSYS. In: Proceedings of 9th International Conference on Mechanical Engineering, Materials, and Automation Technology (MMEAT 2023); 9–11 June 2023; Dalian, China. doi: 10.1117/12.3007715

[27]Hric S, Tkac J, Matiskova D, et al. Preliminary analysis of tower crane as a type of truss structure. MATEC Web of Conferences. 2019; 299: 03003. doi: 10.1051/matecconf/201929903003

[28]Hou C, Liu C, Li Z, et al. Tower crane systems modeling and adaptive robust sliding mode control design under unknown frictions and wind disturbances. Transactions of the Institute of Measurement and Control. 2025; 47(4): 795–809. doi: 10.1177/01423312241260911

[29]Yu Z, Gu Z, Lan P, et al. Multibody system dynamic modeling and order reduction of tower crane. Journal of Dynamics and Control. 2024; 22(8): 58–65. doi: 10.6052/1672-6553-2024-023 (in Chinese)

[30]Yu Z, Li H. A novel flexible multibody system dynamic analysis platform of tower crane. Machines. 2025; 13(12): 1103. doi: 10.3390/machines13121103

[31]Liu P, Zhao C, Sun Y, et al. Impact of multiple operating parameter interactions on load swing of tower cranes. Machines. 2025; 13(2): 85. doi: 10.3390/machines13020085

[32]Chitaoui H, Megnounif A, Benadla Z. Optimal Placement of Vibration Control Systems in a Smart Civil Engineering Structure. Civil Engineering Journal. 2025; 11(8): 3495–3515. doi: 10.28991/CEJ-2025-011-08-022

[33]Abdelrheem AE, El-Helloty A, Ehab A. Integrated FEM, CFD, and BIM Approaches for Optimizing Pre-Stressed Concrete Wind Turbine Tower Design. Civil Engineering Journal. 2025; 11(2): 523–543. doi: 10.28991/CEJ-2025-011-02-08

[34]Chu TSC, Sorilla J, Chua AY. UAV-Based Structural Health Monitoring Using a Two-Stage CNN Model with Lighthouse Localization in GNSS-Denied Environments. HighTech and Innovation Journal. 2025; 6(2): 398–410. doi: 10.28991/HIJ-2025-06-02-03

[35]Çoban A. Structural Analysis and Control of Tower Crane System [Master’s thesis]. Necmettin Erbakan University; 2025.

Editor-in-Chief

Prof. Jun Yang

Institute of Acoustics, Chinese Academy of Sciences, China

ISSN

1541-0161 (Print)

2693-1443 (Online)

Publication Frequency

Bi-monthly

Indexing

Web of Science Coverage

Emerging Sources Citation Index (IF 4.2, Q1)

Elsevier Solutions

Scopus (2025 CiteScore 2.0);

Portico, etc.

About the Publisher

Academic Publishing insists on taking academic exchange and publication as the main line, carrying out comprehensive management based on science and technology, and fully exploring excellent international publishing resources. Within 5 years, it will form a strategic framework and scale with science (S), technology (T), medicine (M), education (E), and humanities and arts (H) as the main publishing fields. Academic Publishing is headquartered in Singapore and based in Malaysia, with the United States and China providing the main scientific and academic resources. At the same time, it has established long-term good cooperative relations with other publishing companies, scientific research communities, and academic organizations in more than a dozen countries and regions. Academic Publishing uses English and Chinese as its main publishing languages, mainly publishing books, journals, and conference papers in print and online. The vast majority of publications follow the international open access policy, providing stable and long-term quality and professional publications. With the joint efforts of the expert team and our professional editorial team, our publications will gradually be indexed by international databases in stages to provide convenient and professional retrieval for various scholars. At the same time, manuscripts we accept will be subject to the peer review principle, and cutting-edge and innovative research articles will be preferentially accepted for peer reference and discussion. All kinds of our publications are welcome for peer to contribute, access, and download.

more

Member of ASC

Volume Arrangement

Featured Articles

New scaling of critical damping and reduced frequency for mechanically excited systems

This paper introduces a universal framework for understanding the vibration responses of systems subjected to harmonic excitation. By examining a simplified cylinder-spring-damper model, the study refurbishes traditional scaling methods for the excitation frequency ratio and critical damping ratio. The findings indicate that in damped systems, the maximum amplitude of vibration does not align with the natural frequency. This observation leads to the introduction of a new scaling method for reduced frequency. This new approach aligns resonance peaks at the new reduced velocity of 1.0 across different damping ratios, providing a consistent characterization of vibration behavior. A new critical damping ratio of 0.707 is identified for an excited system as opposed to the traditional damping ratio of 1.0 for an unexcited system. Key properties such as maximum amplitude, phase lag, bandwidth, and quality factor are analyzed, demonstrating that the proposed reduced frequency and critical damping ratio effectively capture the dynamics of both damped and undamped excited systems. The findings offer significant insights for practical applications in engineering and various scientific fields.

Ultrasonic wave velocity as a universal metric for defect detection in timber structures: A case study on Japanese cedar wood (Cryptomeria japonica)

This study makes significant contributions to the field of ultrasonic testing (UT) by offering a novel approach to the identification of artificially introduced defects within Japanese cedar wood (Cryptomeria japonica). The findings are of particular relevance for the heritage conservation and construction sectors, where non-invasive defect detection is paramount. The study establishes a robust framework for assessing the structural integrity of timber by correlating ultrasonic wave velocity reductions with defect size and distribution. Big-sized defects led to more substantial decreases in wave velocity. The study establishes a robust framework for assessing the structural integrity of historical timber by correlating ultrasonic wave velocity reductions with defect size and distribution. This framework has the potential to be applicable to diverse wood species and defect types.

Vehicle structural road noise prediction based on an improved Long Short-Term Memory method

The control of vehicle interior noise has become a critical metric for assessing noise, vibration, and harshness (NVH) in vehicles. During the initial phases of vehicle development, accurately predicting the impact of road noise on interior noise is essential for reducing noise levels and expediting the product development cycle. In recent years, data-driven methods based on machine learning have gained significant attention due to their robust capability in navigating complex data mapping relationships. Notably, surrogate models have demonstrated exceptional performance in this domain. Numerous researchers have integrated diverse intelligent algorithms into the study of vehicle noise, leveraging advantages such as the elimination of precise modeling requirements, extensive solution space exploration, continuous learning from data, and robust algorithmic versatility. However, in NVH engineering applications, data-driven models face inherent limitations, particularly in interpretability and stability. To address these issues, this paper introduces an improved Long Short-Term Memory (LSTM) network that combines knowledge and data. Inspired by the physical information neural network concept, this approach incorporates values calculated through empirical formulas into the neural network as constraints. Comparative assessments with traditional LSTM networks highlight the advantages of this deep learning model. By integrating empirical formulas constraints, the model not only enhances interpretability but also achieves robust generalization with fewer data samples. The proposed method is validated on a specific vehicle model, showing significant improvements in prediction accuracy and efficiency.