Health assessment based on dynamic characteristics of reinforced concrete beam using realtime wireless structural health monitoring sensor

2020 ◽  
Vol 5 (3) ◽  
pp. 204-210
Author(s):  
Aamar Danish ◽  
Faran Tayyab ◽  
Muhammad Usama Salim
Author(s):  
Diego L. Castañeda-Saldarriaga ◽  
Joham Alvarez-Montoya ◽  
Vladimir Martínez-Tejada ◽  
Julián Sierra-Pérez

AbstractSelf-sensing concrete materials, also known as smart concretes, are emerging as a promising technological development for the construction industry, where novel materials with the capability of providing information about the structural integrity while operating as a structural material are required. Despite progress in the field, there are issues related to the integration of these composites in full-scale structural members that need to be addressed before broad practical implementations. This article reports the manufacturing and multipurpose experimental characterization of a cement-based matrix (CBM) composite with carbon nanotube (CNT) inclusions and its integration inside a representative structural member. Methodologies based on current–voltage (I–V) curves, direct current (DC), and biphasic direct current (BDC) were used to study and characterize the electric resistance of the CNT/CBM composite. Their self-sensing behavior was studied using a compression test, while electric resistance measures were taken. To evaluate the damage detection capability, a CNT/CBM parallelepiped was embedded into a reinforced-concrete beam (RC beam) and tested under three-point bending. Principal finding includes the validation of the material’s piezoresistivity behavior and its suitability to be used as strain sensor. Also, test results showed that manufactured composites exhibit an Ohmic response. The embedded CNT/CBM material exhibited a dominant linear proportionality between electrical resistance values, load magnitude, and strain changes into the RC beam. Finally, a change in the global stiffness (associated with a damage occurrence on the beam) was successfully self-sensed using the manufactured sensor by means of the variation in the electrical resistance. These results demonstrate the potential of CNT/CBM composites to be used in real-world structural health monitoring (SHM) applications for damage detection by identifying changes in stiffness of the monitored structural member.


Author(s):  
Mohsen Ghabdian ◽  
Seyed BB Aval ◽  
Mohammad Noori ◽  
Wael A Altabey

An important and critical area within the broad domain of structural health monitoring, as related to reinforced civil and mechanical structures, is the assessment of creep, shrinkage, and high-temperature effects on reliability and serviceability. Unfortunately, the monitoring and impact of these inherent mechanical characteristics and behaviors, and subsequent impact on serviceability, have rarely been considered in the literature in structural health monitoring. In this paper, the microprestress-solidification creep theory for beams is generalized for the simultaneous effect of linear/nonlinear creep, shrinkage, and high temperature in a reliability framework. This study conducts a systematic time-dependent procedure for the reliability analysis of structures using a powerful nanoscale method. It must be noted that this paper aims to extend the previously developed microprestress-solidification method in a health monitoring reliability-based framework with a close look at a nonlinear creep, parameters affecting creep, and long-time high temperature. A finite element approach is proposed where creep, shrinkage, temperature, and cracking are considered using strain splitting theory. First, the model performance was evaluated by comparing the results with the experimental test available in the literature in the case of creep and shrinkage. Then, the simultaneous effect of creep, shrinkage, and temperature was compared with experimental results obtained by the authors. Reliability analysis was applied to reinforced concrete beams subjected to sustained gravity loading and uniform temperature history in order to calculate exceedance probability in the serviceability limit state. It was found that the exceedance probability of reinforced concrete beams was dependent on the shear span-to-depth ratio. In the serviceability limit state, exceedance probabilities of 0.012 and 0.157 were calculated for the span-to-depth ratios of 1 and 5, respectively. In addition, it was shown that temperature plays an important role in the reliability of reinforced concrete beams. A 4.27-fold increase was observed in the case of moderate to high temperature. Finally, for three different load levels of 40%, 70%, and 80%, the exceedance probabilities were 0.156, 0.328, and 0.527, respectively, suggesting that load level is another key parameter affecting the reliability of reinforced concrete beams. It is thus concluded these fundamental phenomenological studies should be further considered as part of the broad field of structural health monitoring.


2020 ◽  
pp. 147592172095112
Author(s):  
Lidor Yosef ◽  
Yiska Goldfeld

The goal of this study is to develop a structural health monitoring methodology for smart self-sensory carbon-based textile reinforced concrete elements. The self-sensory concept is based on measuring the electrical resistance change in the carbon roving reinforcement and by means of an engineering gage factor, correlating the relative electrical resistance change to an integral value of strain along the location of the roving. The concept of the nonlinear engineering gage factor that captures the unique micro-structural mechanism of the roving within the concrete matrix is demonstrated and validated. The estimated value of strain is compared to a theoretical value calculated by assuming a healthy state. The amount of discrepancy between the two strain values makes it possible to indicate and distinguish between the structural states. The study experimentally demonstrates the engineering gage factor concept and the structural health monitoring procedure by mechanically loading two textile reinforced concrete beams, one by a monotonic loading procedure and the other by a cyclic loading procedure. It is presented that the proposed structural health monitoring procedure succeeded in estimating the strain and in clearly distinguishing between the structural states.


2018 ◽  
Vol 199 ◽  
pp. 06011
Author(s):  
Elsabe Kearsley ◽  
SW Jacobsz

Reinforced concrete is the most widely used construction material and thus effective condition assessment of reinforced concrete elements forms a significant part of structural health monitoring. An effective structural health monitoring system should be able to give the owner prior warning that structural elements are reaching conditions approaching either serviceability or ultimate limit states. The aim of this investigation is to compare strain data recorded during load testing of a reinforced concrete beam using Fibre optic Bragg Gratings (FBG) and a photographic technique to determine circumstances most suitable for the use of each of the techniques. The test results indicate that FBG sensors can be used to detect small strains as well as large strains in uncracked concrete elements, while optical images can be used to accurately map crack development over the surface area of the structure.


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