The brittleness of cement composites makes cracks almost inevitable, producing a serious limitation on the lifespan, resilience, and safety of concrete infrastructure. To address this brittleness, self-healing concrete has been developed for regaining its mechanical and durability properties after becoming cracked, thereby promising sustainable development of concrete infrastructure. This paper provides a comprehensive review of the latest developments in self-healing concrete. It begins by summarizing the methods used to evaluate the self-healing efficiency of concrete. Next, it compares strategies for achieving healing concrete. It then discusses the typical approaches for developing self-healing concrete. Finally, critical insights are proposed to guide future studies on the development of novel self-healing concrete. This review will be useful for researchers and practitioners interested in the field of self-healing concrete and its potential to improve the durability, resilience, and safety of concrete infrastructure.
The hazardous environmental effects of greenhouse gas emissions and climate change demand alternative sources for cementitious materials in the construction industry. The development of geopolymer structures provides a way of producing 100% cement-free construction. In this research work, a novel and simple way of deriving nano particles from waste fly ash particles is promoted. The effect of adding the synthesized nano fly ash particles as a filler medium in geopolymer mortars was investigated by considering strength and durability properties. Parameter optimization was done by using regression analysis on the geopolymer mortar and the impact of adding nano fly ash particles was studied by varying different percentages of addition ranging from 0 to 7.5% by weight of binder content. From the results, it was observed that 1% nano fly ash acted not only as a filler but also as nano-sized precursors of the polymerization process, resulting in denser geopolymer medium. This can explain the extraordinary gain in strength of 72.11 MPa as well as the denser core with negligible level of chloride ion penetration, making the material suitable for the development of structures susceptible to marine environment.
Time-dependent characteristics (TDCs) have been neglected in most previous studies investigating the deviation mechanisms of bridge pile foundations and evaluating the effectiveness of preventive measures. In this study, the stress-strain-time characteristics of soft soils were illustrated by consolidation-creep tests based on a typical engineering case. An extended Koppejan model was developed and then embedded in a finite element (FE) model via a user-material subroutine (UMAT). Based on the validated FE model, the time-dependent deformation mechanism of the pile foundation was revealed, and the preventive effect of applying micropiles and stress-release holes to control the deviation was investigated. The results show that the calculated maximum lateral displacement of the cap differs from the measured one by 6.5%, indicating that the derived extended Koppejan model reproduced the deviation process of the bridge cap-pile foundation with time. The additional load acting on the pile side caused by soil lateral deformation was mainly concentrated within the soft soil layer and increased with the increase in load duration. Compared with t = 3 d (where t is surcharge time), the maximum lateral additional pressure acting on Pile 2# increased by approximately 47.0% at t = 224 d. For bridge pile foundation deviation in deep soft soils, stress-release holes can provide better prevention compared to micropiles and are therefore recommended.
Researchers are paying increasing attention to the development of low-cost and microcontroller-based accelerometers, in order to make structural health monitoring feasible for conventional bridges with limited monitoring budget. Parallel with the low-cost sensor development, the use of the embedded accelerometers of smartphones for eigenfrequency analysis of bridges is becoming popular in the civil engineering literature. This paper, for the first time in the literature, studies these two promising technologies by comparing the noise density and eigenfrequency analysis of a self-developed, validated and calibrated low-cost Internet of things based accelerometer LARA (low cost adaptable reliable accelerometer) with those of a state of the art smartphone (iPhone XR). The eigenfrequency analysis of a footbridge in San Sebastian, Spain, showed that the embedded accelerometer of the iPhone XR can measure the natural frequencies of the under study bridge.
With the three dimensional (3D) oblique incident waves exactly determined for the free field, the soil seismic responses in both frequency and time domains are studied by the 2.5 dimension (2.5D) finite/infinite element method. First, the free-field responses in frequency domain are solved exactly for 3D arbitrary incident P and SV waves, which requires no coordinate conversion or extra effort for SV waves with super-critical incident angles. Next, the earthquake spectra are incorporated by the concept of equivalent seismic forces on the near-field boundary, based only on the displacements input derived for unit ground accelerations of each frequency using the 2.5D approach. For the asymmetric 2.5D finite/infinite element model adopted, the procedure for soil seismic analysis is presented. The solutions computed by the proposed method are verified against those of Wolf’s and de Barros and Luco’s and for inversely calculated ground motions. Of interest is that abrupt variation in soil response occurs around the critical angle on the wave propagation plane for SV waves. In addition, the horizontal displacements attenuate with increasing horizontal incident angle, while the longitudinal ones increase inversely for 3D incident P and SV waves.
The drill and blast (D&B) method is widely used to excavate underground spaces, but explosions generally cause damage to the rock. Still, no blast simulation method can provide computational accuracy and efficiency. In this paper, a blast equivalent simulation method called the blast damage zone strength reduction (BDZSR) method is proposed. This method first calculates the range of the blast-induced damage zone (BDZ) by formulae, then reduces the strength and deformation parameters of the rock within the BDZ ahead of excavation, and finally calculates the excavation damage zone (EDZ) for the D&B method by numerical simulation. This method combines stress wave attenuation, rock damage criteria and stress path variation to derive the BDZ depth calculation formulae. The formulae consider the initial geo-stress, and the reliability is verified by numerical simulations. The calculation of BDZ depth with these formulae allows the corresponding numerical simulation to avoid the time-consuming dynamic calculation process, thus greatly enhancing the calculation efficiency. The method was applied to the excavation in Jinping Class II hydropower station to verify its feasibility. The results show that the BDZSR method can be applied to blast simulation of underground caverns and provide a new way to study blast-induced damage.
Face passive failure can severely damage existing structures and underground utilities during shallow shield tunneling, especially in coastal backfill sand. In this work, a series of laboratory model tests were developed and conducted to investigate such failure, for tunnels located at burial depth ratios for which C/D = 0.5, 0.8, 1, and 1.3. Support pressures, the evolution of failure processes, the failure modes, and the distribution of velocity fields were examined through model tests and numerical analyses. The support pressure in the tests first rose rapidly to the elastic limit and then gradually increased to the maximum value in all cases. The maximum support pressure decreased slightly in cases where C/D = 0.8, 1, and 1.3, but the rebound was insignificant where C/D = 0.5. In addition, the configuration of the failure mode with C/D = 0.5 showed a wedge-shaped arch, which was determined by the outcropping shear failure. The configuration of failure modes was composed of an arch and the inverted trapezoid when C/D = 0.8, 1, and 1.3, in which the mode was divided into lower and upper failure zones.
Aluminum alloys have been widely applied in coastal and marine structures because of their superior sustainability and corrosion resistance. Concrete-filled double-skin aluminum tubular columns (CFDAT) possess higher strength and better ductility than traditional reinforced concrete structures. However, few studies have been conducted on numerical simulation methods for circular CFDATs. Specifically, there has been no experimental or numerical study on intermediate-to-slender circular CFDATs. Here, a comprehensive numerical study was conducted on a modeling method for the first time to simulate the axial behavior of a slender circular CFDAT. This study outlines the development of numerical modeling techniques and presents a series of comparative studies using various material nonlinearities, confinement effects, and nonlinearity of the initial geometric imperfections for a slender column. The numerical results were compared with more than 80 previously available stub and slender experimental test results for verification. It was confirmed that the proposed numerical technique was reliable and accurate for simulating the axial behavior of intermediate and slender circular CFDAT. Furthermore, a parametric study was conducted to investigate the effects of geometric and material properties on the axial capacity of the CFDAT. Additionally, the slenderness and strength-to-width ratio of CFDAT were compared with those of concrete-filled double-skin steel tubular columns (CFDST). The simulated axial strengths were compared with those predicted using AS 5100 and AISC 360. New design equations for the CFDATs should be proposed based on AS 5100.
This paper proposes a machine-learning-based methodology to automatically classify different types of steel weld defects, including lack of the fusion, porosity, slag inclusion, and the qualified (no defects) cases. This methodology solves the shortcomings of existing detection methods, such as expensive equipment, complicated operation and inability to detect internal defects. The study first collected percussed data from welded steel members with or without weld defects. Then, three methods, the Mel frequency cepstral coefficients, short-time Fourier transform (STFT), and continuous wavelet transform were implemented and compared to explore the most appropriate features for classification of weld statuses. Classic and convolutional neural network-enhanced algorithms were used to classify, the extracted features. Furthermore, experiments were designed and performed to validate the proposed method. Results showed that STFT achieved higher accuracies (up to 96.63% on average) in the weld status classification. The convolutional neural network-enhanced support vector machine (SVM) outperformed six other algorithms with an average accuracy of 95.8%. In addition, random forest and SVM were efficient approaches with a balanced trade-off between the accuracies and the computational efforts.
This study discusses the effects of local sites and hazard amplification on the seismic vulnerability assessment of existing masonry buildings. In this context, a rapid seismic evaluation procedure was implemented on an old masonry building stock in the historical center Galata, located in İstanbul, to determine the seismic risk priority of the built heritage. Damage scenarios were generated for all soil classes, different moment magnitudes, and source-to-site distances to obtain more accurate results for the seismic vulnerability assessment of the studied building stock. Consequently, damage distributions estimated under nine different scenarios with/without site effects were compared and illustrated in maps to discuss changes in vulnerability owing to amplification effects. In this study, by re-examining the rapid seismic evaluation procedure by including geo-hazard-based assessment, the importance of site effects on the vulnerability and risk assessment of built heritage was underlined. The proposed framework integrating field data and local site effects is believed to advance the current applications for vulnerability assessment of masonry buildings and provide an improvement in the application of rapid seismic assessment procedures with more reliable results.
