Luo Dong

Dr. Luo Dong


Research Focus & Metrics

Academic Career Length

11Years (2016-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 December 2016 in Sensors
Verified
Journal Article
Open access
PDF file
LDLuo Dong
Luo Dong
ZIZainah Ibrahim
Zainah Ibrahim
JMJianxun Ma
Jianxun Ma
ZIZubaidah Ismail
Zubaidah Ismail
DIDavid Thomas Iseley
David Thomas Iseley
In this study, tapered polymer fiber sensors (TPFSs) have been employed to detect the vibration of a reinforced concrete beam (RC beam). The sensing principle was based on transmission modes theory. The natural frequency of an RC beam was theoretically analyzed. Experiments were carried out with sensors mounted on the surface or embedded in the RC beam. Vibration detection results agreed well with Kistler accelerometers. The experimental results found that both the accelerometer and TPFS detected the natural frequency function of a vibrated RC beam well. The mode shapes of the RC beam were also found by using the TPFSs. The proposed vibration detection method provides a cost-comparable solution for a structural health monitoring (SHM) system in civil engineering.

11 April 2025 in Applied Sciences
Verified
Journal Article
Open access
PDF file
CJCheng Ji
Cheng Ji
LDLuo Dong
Luo Dong
XSXiaole Shen
Xiaole Shen
LXLeilei Xu
Leilei Xu
HPHongwei Pan
Hongwei Pan
YLYuwei Liu
Yuwei Liu
Risk assessment in tunnel construction using the drilling and blasting method presents a complex multi-criteria decision-making challenge due to numerous interacting factors. This study develops an advanced risk assessment model integrating game theory-based combination weighting with nonlinear fuzzy analytic hierarchy process (FAHP). The methodology establishes a comprehensive risk evaluation system through the systematic coupling of a work breakdown structure (WBS) and a risk breakdown structure (RBS), effectively combining subjective weights from an analytic hierarchy process (AHP) with objective weights derived through principal component analysis (PCA). A specialized nonlinear operator addresses the inherent fuzziness in the risk evaluation processes. The model is applied to the Daliangshan No. 1 Tunnel flat guide entrance drilling and blasting construction section, with the risk level determined to be high. Detailed analysis further revealed that the detonation network reliability and ventilation system performance constituted the most significant secondary risk elements. Comparative validation demonstrates the model’s superior accuracy over conventional methods in both weight determination and risk classification. The results demonstrate the effectiveness of the proposed model in improving risk assessment accuracy and supporting decision-making in complex tunnel construction environments.