Efficacy and Damage Diagnosis of Reinforced Concrete Columns and Joints Strengthened with FRP Ropes Using Piezoelectric Transducers

Establishment of a Mass Concrete Strength-Monitoring Method Using Barium Titanate-Bismuth Ferrite/Polyvinylidene Fluoride Nanocomposite Piezoelectric Sensors with Temperature Stability

Mass concrete is widely used in large-scale projects, including metro upper cover structures, water conservancy dams, and heavy equipment foundations, among others, necessitating the process of health monitoring in mass concrete construction. The development of reliable and simple strength-monitoring methods for mass concrete is challenging because the inner temperature of mass concrete is high and changes a lot. This study proposes a strength-monitoring approach for mass concrete using barium titanate-bismuth ferrite/polyvinylidene fluoride (BT-BFO/PVDF) nanocomposite piezoelectric sensors, wherein the new sensors are embedded as actuators and sensors in mass concrete. The stress wave generated by the BT-BFO/PVDF piezoelectric sensors is used to monitor the specimen's strength for 28 days. The piezoelectric voltage received by the sensors in mass concrete is analyzed. The experimental results indicate that the signal received by the BT-BFO/PVDF sensors is not easily affected by the internal temperature of mass concrete compared with that of the traditional PVDF piezoelectric sensors. The signal parameters sensitive to concrete strength variation and the change trend of concrete strength are closely related to the piezoelectric voltage. Therefore, the proposed approach using BT-BFO/PVDF nanocomposite piezoelectric sensors is efficient (error < 10%) in mass concrete monitoring. Moreover, the monitoring results do not need temperature compensation. The physical meaning of the obtained strength prediction formula is proposed. An experimental system based on PVDF dynamic strain-sensing characteristics is established.

Experimental Study on the Detection of the Existence and Location of Mimicked and Unexpected Interface Debonding Defects in an Existing Rectangular CFST Column with PZT Materials

Interface bonding conditions between concrete and steel materials play key roles in ensuring the composite effect and load-carrying capacity of concrete-steel composite structures such as concrete-filled steel tube (CFST) members in practice. A method using both surface wave and electromechanical impedance (EMI) measurement for detecting the existence and the location of inaccessible interface debonding defects between the concrete core and steel tube in CFST members using piezoelectric lead zirconate titanate (PZT) patches as actuators and sensors is proposed. A rectangular CFST specimen with two artificially mimicked interface debonding defects was experimentally verified using PZT patches as the actuator and sensor. By comparing the surface wave measurement of PZT sensors at different surface wave travelling paths under both a continuous sinusoidal signal and a 10-period sinusoidal windowed signal, three potential interface debonding defects are quickly identified. Furthermore, the accurate locations of the three detected potential interface debonding defects are determined with the help of EMI measurements from a number of additional PZT sensors around the three potential interface debonding defects. Finally, the accuracy of the proposed interface debonding detection method is verified with a destructive observation by removing the local steel tube at the three detected interface debonding locations. The observation results show that the three detected interface debonding defects are two mimicked interface debonding defects, and an unexpected debonding defect occurred spontaneously due to concrete shrinkage in the past one and a half years before conducting the test. Results in this study indicate that the proposed method can be an efficient and accurate approach for the detection of unknown interface debonding defects in existing CFST members.

Practicability and environmental impact assessment of synthetic fibre reinforced polymer (SFRP) stirrups in reinforced concrete beams

In this study, the objective is to explore the practicability of incorporating synthetic fibre reinforced polymer (SFRP) stirrups into reinforced concrete beams. This investigation revolves around evaluating their effectiveness from two key perspectives: their structural performance and environmental impact. To accomplish this, four set of specimens were prepared, each integrating SFRP stirrups, and testing them under a rigorous three-point bending load test. The structural performance analysis entails a comprehensive examination on the critical design factors such as: the load-deflection relationship and the contribution these SFRP stirrups to improve the ductility performance, flexural stiffness, deformability factor, flexural toughness and energy absorption capacity. The findings of this study indicate that the SFRP stirrups exhibit commendable shear capacity, meeting the necessary requirements, and simultaneously demonstrate satisfactory ductility. It is determined, that the optimal design for these SFRP stirrups involves utilizing narrow and thin stirrups placed at relatively larger intervals. Furthermore, this research delves into assessing the environmental impact of incorporating SFRP stirrups. This assessment enables us to comprehensively evaluate the environmental implications of the entire life cycle of these stirrups in structural beam. Moreover, the analysis reveals that, SFRP stirrups yields lower environmental impacts compared to their steel counterparts, they still provide valuable insights into the overall sustainability considerations within the context of reinforced concrete structures.

A Deep Learning Approach for Autonomous Compression Damage Identification in Fiber-Reinforced Concrete Using Piezoelectric Lead Zirconate Titanate Transducers

Effective damage identification is paramount to evaluating safety conditions and preventing catastrophic failures of concrete structures. Although various methods have been introduced in the literature, developing robust and reliable structural health monitoring (SHM) procedures remains an open research challenge. This study proposes a new approach utilizing a 1-D convolution neural network to identify the formation of cracks from the raw electromechanical impedance (EMI) signature of externally bonded piezoelectric lead zirconate titanate (PZT) transducers. Externally bonded PZT transducers were used to determine the EMI signature of fiber-reinforced concrete specimens subjected to monotonous and repeatable compression loading. A leave-one-specimen-out cross-validation scenario was adopted for the proposed SHM approach for a stricter and more realistic validation procedure. The experimental study and the obtained results clearly demonstrate the capacity of the introduced approach to provide autonomous and reliable damage identification in a PZT-enabled SHM system, with a mean accuracy of 95.24% and a standard deviation of 5.64%.

Monitoring and Analysis of the Collapse Process in Blasting Demolition of Tall Reinforced Concrete Chimneys

Aiming at the problem of displacement of collapse direction caused by the impact of the high-rise reinforced concrete chimney in the process of blasting demolition, combined with the monitoring methods such as high-speed photography observation, piezoelectric ceramic sensor, and blasting vibration monitor, the impact process of the 180 m high chimney was comprehensively analyzed. The results show that the chimney will experience multiple 'weight loss' and 'overweight' effects during the sit-down process, inducing compressive stress waves in the chimney. When the sit-down displacement is large, the broken reinforced concrete at the bottom can play a significant buffering effect, and the 'overweight' effect gradually weakens until the sit-down stops. The stress of the inner and outer sides of the chimney wall is obviously different in the process of collapsing and touching the ground. The waveform of the monitoring point of the piezoelectric ceramic sensor is divided into three stages, which specifically characterizes the evolution process of the explosion load and the impact of the chimney. The vibration induced by explosive explosion is mainly high-frequency vibration above 50 Hz, the vibration induced by chimney collapse is mainly low-frequency vibration below 10 Hz, and the vibration characteristics are obviously different. In the process of blasting demolition and collapse of high-rise reinforced concrete chimney, due to the impact of sitting down, the wall of the support tube is subjected to uneven force, resulting in the deviation of the collapse direction. In practical engineering, the control measures of chimney impact, blasting vibration, and collapse touchdown vibration should be fully strengthened to ensure the safety of the protection target around the blasting demolition object.

Smart Cementitious Sensors with Nano-, Micro-, and Hybrid-Modified Reinforcement: Mechanical and Electrical Properties

The current paper presents the results of an experimental study of carbon nano-, micro-, and hybrid-modified cementitious mortar to evaluate mechanical performance, energy absorption, electrical conductivity, and piezoresistive sensibility. Three amounts of single-walled carbon nanotubes (SWCNTs), namely 0.05 wt.%, 0.1 wt.%, 0.2 wt.%, and 0.3 wt.% of the cement mass, were used to prepare nano-modified cement-based specimens. In the microscale modification, 0.05 wt.%, 0.5 wt.%, 1.0 wt.% carbon fibers (CFs) were incorporated in the matrix. The hybrid-modified cementitious specimens were enhanced by adding optimized amounts of CFs and SWCNTs. The smartness of modified mortars, indicated by their piezoresistive behavior, was investigated by measuring the changes in electrical resistivity. The effective parameters that enhance the composites' mechanical and electrical performance are the different concentrations of reinforcement and the synergistic effect between the types of reinforcement used in the hybrid structure. Results reveal that all the strengthening types improved flexural strength, toughness, and electrical conductivity by about an order of magnitude compared to the reference specimens. Specifically, the hybrid-modified mortars presented a marginal reduction of 1.5% in compressive strength and an increase in flexural strength of 21%. The hybrid-modified mortar absorbed the most energy, 1509%, 921%, and 544% more than the reference mortar, nano-modified mortar, and micro-modified mortar, respectively. The change rate of impedance, capacitance, and resistivity in piezoresistive 28-day hybrid mortars improved the tree ratios by 289%, 324%, and 576%, respectively, for nano-modified mortars and by 64%, 93%, and 234%, respectively, for micro-modified mortars.

Cracking and Fiber Debonding Identification of Concrete Deep Beams Reinforced with C-FRP Ropes against Shear Using a Real-Time Monitoring System

Traditional methods for estimating structural deterioration are generally costly and inefficient. Recent studies have demonstrated that implementing a network of piezoelectric transducers mounted to critical regions of concrete structural members substantially increases the efficacy of the structural health monitoring (SHM) method. This study uses a recently developed electro-mechanical-admittance (EMA)-based SHM system for real-time damage diagnosis of carbon FRP (C-FRP) ropes installed as shear composite reinforcement in RC deep beams. The applied SHM technique uses the frequency response measurements of a network of piezoelectric lead zirconate titanate (PZT) patches. The proposed strengthening methods using C-FRP ropes as ETS and NSM shear reinforcement and the applied anchorage techniques significantly enhanced the strength and the overall performance of the examined beams. The retrofitted beams exhibited increased shear capacity and improved post-peak response with substantial ductility compared with the brittle failure of the non-strengthened specimens. The health condition and the potential debonding failure of the applied composite fiber material were also examined and quantified using the proposed SHM technique. Damage quantification of C-FRP ropes is achieved by comparing and assessing the values of several statistical damage indices. The experimental results demonstrated that the proposed monitoring system successfully diagnosed the region where the damage occurred by providing early warning of the forthcoming critical shear cracking of concrete and C-FRP rope debonding failures. Furthermore, the internal PZT transducers showed sound indications of the C-FRP rope's health condition, demonstrating a direct correlation with the mechanical performance of the fibers.

Fiber Reinforced Polymer Debonding Failure Identification Using Smart Materials in Strengthened T-Shaped Reinforced Concrete Beams

The favorable contribution of externally bonded fiber-reinforced polymer (EB-FRP) sheets to the shear strengthening of reinforced concrete (RC) beams is widely acknowledged. Nonetheless, the premature debonding of EB-FRP materials remains a limitation for widespread on-site application. Once debonding appears, it is highly likely that brittle failure will occur in the strengthened RC structural member; therefore, it is essential to be alerted of the debonding incident immediately and to intervene. This may not be always possible, particularly if the EB-FRP strengthened RC member is located in an inaccessible area for fast inspection, such as bridge piers. The ability to identify debonding immediately via remote control would contribute to the safer application of the technique by eliminating the negative outcomes of debonding. The current investigation involves the detection of EB-FRP sheet debonding using a remotely controlled electromechanical admittance (EMA)-based structural health monitoring (SHM) system that utilizes piezoelectric lead zirconate titanate (PZT) sensors. An experimental investigation on RC T-beams strengthened for shear with EB-FRP sheets has been performed. The PZT sensors are installed at various locations on the surface of the EB-FRP sheets to evaluate the SHM system's ability to detect debonding. Additionally, strain gauges were attached on the surface of the EB-FRP sheets near the PZT sensors to monitor the deformation of the FRP and draw useful conclusions through comparison of the results to the wave-based data provided by the PZT sensors. The experimental results indicate that although EB-FRP sheets increase the shear resistance of the RC T-beams, premature failure occurs due to sheet debonding. The applied SHM system can sufficiently identify the debonding in real-time and appears to be feasible for on-site applications.

Degradation Feature Extraction Method for Prognostics of an Extruder Screw Using Multi-Source Monitoring Data

Laboratory-scale data on a component level are frequently used for prognostics because acquiring them is time and cost efficient. However, they do not reflect actual field conditions. As prognostics is for an in-service system, the developed prognostic methods must be validated using real operational data obtained from an actual system. Because obtaining real operational data is much more expensive than obtaining test-level data, studies employing field data are scarce. In this study, a prognostic method for screws was presented by employing multi-source real operational data obtained from a micro-extrusion system. The analysis of real operational data is more challenging than that of test-level data because the mutual effect of each component in the system is chaotically reflected in the former. This paper presents a degradation feature extraction method for interpreting complex signals for a real extrusion system based on the physical and mechanical properties of the system as well as operational data. The data were analyzed based on general physical properties and the inferred interpretation was verified using the data. The extracted feature exhibits valid degradation behavior and is used to predict the remaining useful life of the screw in a real extrusion system.