Predicting the ultimate bending capacity of concrete beams from the モrelaxation ratioヤ analysis of AE signals
نویسنده
چکیده
This paper presents an alternative approach to the problem, based on ‘‘testing’’ the real structure rather than trying to model it. Experiments on reinforced concrete (RC) beams, representative of bridge beams, are described. The beams were loaded in cycles up to failure whilst recording the acoustic emissions (AE) generated. The analysis of the AE signals was then undertaken based on a proposed new parameter, named the ‘‘relaxation ratio’’. This quantifies the AE energy recorded during the unloading and loading phases of a cycle test and it showed a clear correlation with the bending failure load of the RC beams. A change in trend was noted when the load reached approximately the 45% of the ultimate bending load. The results appeared to be influenced by factors such as the concrete strength and loading rate and further work is needed to extend the results to full scale testing of bridge beams. 2005 Elsevier Ltd. All rights reserved.
منابع مشابه
Stepwise Regression for shear capacity assessment of steel fiber reinforced concrete beams
The addition of steel fibers into concrete improves the postcracking tensile strength of hardened concrete and hence significantly enhances the shear strength of reinforced concrete reinforced concrete beams. However, developing an accurate model for predicting the shear strength of steel fiber reinforced concrete (SFRC) beams is a challenging task as there are several parameters such as the co...
متن کاملExperimental and Numerical Study of Energy Absorption Capacity of Glass Reinforced SCC Beams
Various experimental studies have been carried out on glass fiber reinforced concrete (GFRC), but in limited studies, the behavior of this type of concrete is evaluated using finite element method (FEM). In this study an analysis model is presented for predicting energy absorption capacity of glass fiber reinforced self-compacting concrete (GFRCSCC) beams and the results are compared with exper...
متن کاملAdaptive Neural Fuzzy Inference System Models for Predicting the Shear Strength of Reinforced Concrete Deep Beams
A reinforced concrete member in which the total span or shear span is especially small in relation to its depth is called a deep beam. In this study, a new approach based on the Adaptive Neural Fuzzy Inference System (ANFIS) is used to predict the shear strength of reinforced concrete (RC) deep beams. A constitutive relationship was obtained correlating the ultimate load with seven mechanical a...
متن کاملCluster Analysis of Acoustic Emission Signals for Carbon/Epoxy Composite in Four-point Bending Test (RESEARCH NOTE)
Due to the extensive use of composites in various industries and the fact that defects reduce ultimate strength and efficiency during operation, detection of failures in composite parts is very important. The aim of this paper is to use Acoustic Emission (AE) non-destructive method in four-point bending test of carbon/epoxy composite to analyze and examine the failure mechanisms. This method is...
متن کاملFlexural Behavior of Lightweight Concrete Beams Reinforced with GFRP Bars and Effects of the Added Micro and Macro Fiber
This study evaluated the effect of macro steel fiber (SF), micro glass fiber (GF) and micro polypropylene fiber (PF) in lightweight aggregate concrete, (LWAC) beams reinforced with glass fiber reinforced polymer (GFRP) bars. Firstly, concrete mixtures with different volume fractions of GF, PF and SF were tested up to compressive strength, then determine the optimum fiber content GF, PF and SF a...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2015