In-situ condition monitoring of reinforced concrete structures

Verma, Sanjeev Kumar; Bhadauria, Sarita Singh; Akhtar, Saleem

doi:10.1007/s11709-016-0336-z

Cited by 9 publications

(2 citation statements)

References 35 publications

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“…Common defects in concrete structures include corrosion, cracking and spalling, deterioration, de-bonding, surface and subsurface deformations, delamination, and material performance impairment [ 56 , 57 , 58 , 62 ]. The classification scheme proposed by Rehman et al [ 63 ] (see Figure 5 ) suggests that ultrasonic sensors and IR thermography for structural health monitoring are suitable techniques for assessing various types of defects, including spalling, corrosion, cracking, and delamination.…”

Section: Sensors For Health Monitoring Of Agricultural Structuresmentioning

confidence: 99%

Sensors for Structural Health Monitoring of Agricultural Structures

Maraveas

Bartzanas

2021

Sensors

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The health diagnosis of agricultural structures is critical to detecting damages such as cracks in concrete, corrosion, spalling, and delamination. Agricultural structures are susceptible to environmental degradation due to frequent exposure to water, organic effluent, farm chemicals, structural loading, and unloading. Various sensors have been employed for accurate and real-time monitoring of agricultural building structures, including electrochemical, ultrasonic, fiber-optic, piezoelectric, wireless, fiber Bragg grating sensors, and self-sensing concrete. The cost–benefits of each type of sensor and utility in a farm environment are explored in the review. Current literature suggests that the functionality of sensors has improved with progress in technology. Notable improvements made with the progress in technology include better accuracy of the measurements, reduction of signal-to-noise ratio, and transmission speed, and the deployment of machine learning, deep learning, and artificial intelligence in smart IoT-based agriculture. Key challenges include inconsistent installation of sensors in farm structures, technical constraints, and lack of support infrastructure, awareness, and preference for traditional inspection methods.

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Section: Sensors For Health Monitoring Of Agricultural Structuresmentioning

confidence: 99%

Sensors for Structural Health Monitoring of Agricultural Structures

Maraveas

Bartzanas

2021

Sensors

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“…In order to overcome the existing problems, a workflow used to evaluate structure stability under the impact of local damage was developed in this study, as demonstrated in Figure 1. Nondestructive testing (NDT) technology was adopted to detect the actual status of the structure and to determine damage positions in the field, because a number of previous studies have indicated that this method has high accuracy in testing the internal conditions of an object without causing further damage [14,19]. In order to ensure the reliability of detection results, the different wave phase patterns for the geophysical inversion results were calibrated via an experiment in advance.…”

Section: Framework For Local Damage Assessmentmentioning

confidence: 99%

Analysis of Local Damages Effect on Mechanical Responses of Underwater Shield Tunnel via Field Testing and Numerical Simulation

et al. 2020

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The investigation of concrete structural performance is crucial to maintain the stability of infrastructure. In order to assess structural stability, this work focuses on the development of an integrated framework to detect damaged conditions in the field and analyze their effect on mechanical performance through nondestructive testing (NDT) technology and numerical models. First, a ground penetrating radar (GPR) and an infrared camera work collaboratively to identify the damaged positions of the concrete structure, with parameters calibrated by laboratory experiments. Then, a finite element model is established to study structural mechanical performance based on field conditions and detected results. In addition, the influenced regions induced by local damage are studied under different boundary conditions. As a case study, the devised method was employed in the Nanjing Yangtze River tunnel for stability assessment and disaster prevention. The detected results of the damaged conditions agree well with the actual conditions in the field. Numerical results show that the circumferential stress component is more significant than that observed longitudinally. The effect of local damage on stress implies a positive correlation with the rise of water pressure, in which the maximum stress response to the variation of water level is 45KPa per meter.

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