Many existing reinforced concrete (RC) structures are suffering from corrosion damage. The development of reliable tools to characterise and localise such damage is essential to assess the structural capacity. The acoustic emission (AE) technique has proven to be promising for this purpose. However, this technique poses challenges to reliably interpret the results and lacks rigourous validation.
The present work investigates the transient response of a three-layer sandwich beam with an electrorheological (ER) core. Electrorheological fluids are a class of smart materials, which exhibit reversible changes in mechanical properties when subjected to an electric field. As applying an electric field to the core layer changes the dynamic characteristics of the structure, the ER layer can be used for suppressing the vibrations and reducing the settling time of the beam. A finite element model of the structure is developed and a direct integration algorithm is used to simulate the impulse response of the proposed sandwich beam. The core is modeled as a Bingham plastic material and effects of changes in the applied electric field on the structure settling time and its natural frequencies are represented for several thickness ratios. The variations of damping force vector, due to the dependence of the ER fluid shear stress, to the sign of shear rate, are considered in each iteration. The ER layer thickness and the applied electric field level have a significant influence on the damping behavior of the model.
Acoustic emission source localization is a promising monitoring technique for concrete structures. However, the accuracy of acoustic emission source localization is influenced by many factors, such as the presence of cracks, which are commonly observed in existing reinforced concrete structures. In this article, the acoustic emission source localization is evaluated using a numerical model with a total number of 11,827,200 independent simulated tests. In this work, the investigated influential factors include the presence of cracks, arrival time picking error, and senor layout. The accuracy of source localization is quantified by the characteristic error defined in this article. Using the proposed wave propagation properties, a relatively stable characteristic error of 150 mm is estimated in the detection zone with the maximum sensor spacing less than 1 m. The evaluation approach and simulated characteristic error are validated experimentally by comparing the 200 manually generated signals using hammer hits on a cracked concrete beam.
Piezoelectric sensors can be embedded in carbon fibre-reinforced plastics (CFRP) for continuous measurement of acoustic emissions (AE) without the sensor being exposed or disrupting hydro- or aerodynamics. Insights into the sensitivity of the embedded sensor are essential for accurate identification of AE sources. Embedded sensors are considered to evoke additional modes of degradation into the composite laminate, accompanied by additional AE. Hence, to monitor CFRPs with embedded sensors, identification of this type of AE is of interest. This study (i) assesses experimentally the performance of embedded sensors for AE measurements, and (ii) investigates AE that emanates from embedded sensor-related degradation. CFRP specimens have been manufactured with and without embedded sensors and tested under four-point bending. AE signals have been recorded by the embedded sensor and two reference surface-bonded sensors. Sensitivity of the embedded sensor has been assessed by comparing centroid frequencies of AE measured using two sizes of embedded sensors. For identification of embedded sensor-induced AE, a hierarchical clustering approach has been implemented based on waveform similarity. It has been confirmed that both types of embedded sensors (7 mm and 20 mm diameter) can measure AE during specimen degradation and final failure. The 7 mm sensor showed higher sensitivity in the 350–450 kHz frequency range. The 20 mm sensor and the reference surface-bounded sensors predominately featured high sensitivity in ranges of 200–300 kHz and 150–350 kHz, respectively. The clustering procedure revealed a type of AE that seems unique to the region of the embedded sensor when under combined in-plane tension and out-of-plane shear stress.
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