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Experimental Investigation and Gaussian Process Emulation of Steel Skeleton Reinforced Concrete Behaviors in Split Hopkinson Pressure Bar Tests

Qiong-Li Wang and F. A. DiazDelaO
Institute for Risk and Uncertainty, University of Liverpool, Liverpool L69 7ZF, UK

Abstract —This paper conducts split Hopkinson pressure bar (SHPB) experiments to investigate the dynamic compressive properties of steel skeleton reinforced concrete (SSRC) materials. The SSRC specimens with the different volume fraction of steel range from 0 to 2.94% are investigated by conducting quasi-static and SHPB compression tests, respectively. In SHPB tests, the strain rate achieves from 30 s-1 to 100 s-1. The concrete matrix for all SSRC specimens is mixed to obtain a compressive strength of 45 MPa. The influences of different steel skeleton arrangements on the compressive strength, energy absorption, dynamic strain-stress relations, and failure modes are discussed and compared. The most important indicator, dynamic increase factor (DIF) relations of SSRC for compressive strength and Young’s modulus are modelled probabilistically using Gaussian process (GP) emulation under the Bayesian framework. The corresponding performances are validated by individual prediction errors (IPE) diagnostics. The experimental results demonstrate that by adding certain types of steel skeleton into plain concrete, which gives a general better bonding property to concrete materials and increases the capacities of dynamic compressive strength, dynamic resistance and energy absorption.
 
Index Terms —Steel Skeleton Reinforced Concrete (SSRC), SHPB experiments, Gaussian Process (GP) Emulation, dynamic compression, Bayesian.

Cite: Qiong-Li Wang and F. A. DiazDelaO, "Experimental Investigation and Gaussian Process Emulation of Steel Skeleton Reinforced Concrete Behaviors in Split Hopkinson Pressure Bar Tests," International Journal of Structural and Civil Engineering Research, Vol. 9, No. 1, pp. 1-9, February 2020. doi: 10.18178/ijscer.9.1.1-9

Copyright © 2020 by the authors. This is an open access article distributed under the Creative Commons Attribution License (CC BY-NC-ND 4.0), which permits use, distribution and reproduction in any medium, provided that the article is properly cited, the use is non-commercial and no modifications or adaptations are made.