Dynamic Characteristics Analysis of Hollow Shafts Based on Higher Order Shear Theory

This paper investigates the dynamic characteristics of hollow shaft rotor systems using a higher-order shear deformation theory (HOSDT). The authors based on the HOSDT and combined with the finite element method, a novel finite element model has been established, enabling rapid modeling and dynamic characteristic analysis of hollow shaft rotor system models with arbitrary dimensional parameters. And compare its performance with classical beam theories (Euler-Bernoulli and Timoshenko) and 3D solid element simulations in ANSYS. They analyze modal analysis, unbalanced response analysis, and stress computation. The results suggest that the HOSDT model offers superior accuracy compared to classical beam theories, especially for short, thick beams and thin-walled beams where shear effects are prominent, while also providing computational advantages over 3D solid element models. The study addresses the limitations of classical beam theories in accurately capturing shear effects in hollow shaft rotor systems, particularly in short, thick, and thin-walled scenarios. While 3D FEA can provide accurate results, it comes with high computational cost. The proposed HOSDT-based FEA model provides a balance between accuracy and computational efficiency. The application of HOSDT to hollow shafts and the comparative analysis with existing methods represent a valuable contribution.

Authors

Publication Details

Journal
Open Journal of Applied Sciences
Published
2025-01-01
DOI
https://doi.org/10.4236/ojapps.2025.154063
Primary Topic
Vibration and Dynamic Analysis
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Dynamic Characteristics Analysis of Hollow Shafts Based on Higher Order Shear Theory

Zhichao Feng, Shan Zeng, Yi‐Jun Lin, Zhangjun Dai et al.
Open Journal of Applied Sciences
Vibration and Dynamic Analysis
article

Dynamic Characteristics Analysis of Hollow Shafts Based on Higher Order Shear Theory

Zhichao Feng, Shan Zeng, Yi‐Jun Lin, Zhangjun Dai, Fei Wang, Penghui Qian
article en

Abstract

This paper investigates the dynamic characteristics of hollow shaft rotor systems using a higher-order shear deformation theory (HOSDT). The authors based on the HOSDT and combined with the finite element method, a novel finite element model has been established, enabling rapid modeling and dynamic characteristic analysis of hollow shaft rotor system models with arbitrary dimensional parameters. And compare its performance with classical beam theories (Euler-Bernoulli and Timoshenko) and 3D solid element simulations in ANSYS. They analyze modal analysis, unbalanced response analysis, and stress computation. The results suggest that the HOSDT model offers superior accuracy compared to classical beam theories, especially for short, thick beams and thin-walled beams where shear effects are prominent, while also providing computational advantages over 3D solid element models. The study addresses the limitations of classical beam theories in accurately capturing shear effects in hollow shaft rotor systems, particularly in short, thick, and thin-walled scenarios. While 3D FEA can provide accurate results, it comes with high computational cost. The proposed HOSDT-based FEA model provides a balance between accuracy and computational efficiency. The application of HOSDT to hollow shafts and the comparative analysis with existing methods represent a valuable contribution.

Open Journal of Applied SciencesVol. 15(04)
Openalex Percentile: Top 93%
Vibration and Dynamic Analysis
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.