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Finite element analysis of RC beams using static experimental data to predict static and dynamic behaviors
Arvindan Sivasuriyan1, D S Vijayan2, Naveen Sankaran3
1Institute of Civil Engineering, Warsaw University of Life Sciences-SGGW, 02-787, Warsaw, Poland.
This study compares dynamic and static forces in reinforced concrete (RC) beams using experimental tests and finite element analysis (FEA). Results show sensor data closely aligns with FEA, validating the computational approach for RC beam analysis.
Area of Science:
- Structural Engineering
- Materials Science
Background:
- Reinforced concrete (RC) beams are crucial structural elements.
- Understanding their dynamic and static behavior under load is essential for safety and design.
- Existing research often focuses on either static or dynamic analysis separately.
Purpose of the Study:
- To comprehensively compare the dynamic and static forces in RC beams.
- To validate experimental findings with finite element analysis (FEA) results.
- To investigate the efficacy of various sensors in capturing beam deflection.
Main Methods:
- Experimental testing of 1m x 150mm x 150mm RC beams under monotonic two-point loading using a universal testing machine (UTM).
- Deflection measurement at three locations (S1-S3) using force resisting sensors (FRS), flex sensors (FLS), MEMS accelerometers, and Piezoelectric sensors.
- Finite Element Analysis (FEA) using ANSYS 16.0 software for comparison with experimental data, including dynamic analysis with mode shape and harmonic response evaluation.
Main Results:
- Experimental deflection measurements were closely correlated with FEA results.
- Dynamic analysis provided insights into mode shapes and harmonic responses.
- The study demonstrated the reliability of the chosen sensors for capturing structural responses.
- FEA results effectively simulated the static and dynamic behavior of RC beams.
Conclusions:
- The study successfully validated FEA results against experimental data for RC beams.
- The findings offer a robust approach for analyzing the dynamic and static behavior of RC structures.
- This research contributes valuable insights for structural engineers and material scientists.
- The close agreement between sensor outcomes and FEA enhances confidence in computational modeling for structural health monitoring.
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