Pre-stressed concrete circular spun piles are widely used in various infrastructure projects around the world and offer an economical deep foundation system with consistent and superior quality compared to cast in-situ and other concrete piles. Conventional methods for measuring the lateral response of piles have been limited to conventional instrumentation, such as electrical based gauges and pressure transducers. The problem with existing technology is that the sensors are not able to assist in recording the lateral stiffness changes of the pile which varies along the length depending on the distribution of the flexural moments and appearance of tensile cracks. This paper describes a full-scale bending test of a 1-m diameter spun pile of 30 m long and instrumented using advanced fibre optic distributed sensor, known as Brillouin Optical Time Domain Analysis (BOTDA). Optical fibre sensors were embedded inside the concrete during the manufacturing stage and attached on the concrete surface in order to measure the pile's full-length flexural behaviour under the prescribed serviceability and ultimate limit state. The relationship between moments-deflections and bending moments-curvatures are examined with respect to the lateral forces. Tensile cracks were measured and compared with the peak strains observed from BOTDA data which corroborated very well. By analysing the moment-curvature response of the pile, the structure can be represented by two bending stiffness parameters, namely the pre-yield (EI) and post-yield (EI_cr), where the cracks reduce the stiffness property by 89%. The pile deflection profile can be attained from optical fibre data through closed-form solutions, which generally matched with the displacements recorded by Linear Voltage Displacement Transducers (LVDTs).

In this article, a novel propagation formulation of Rayleigh waves in a compressible isotropic half-space with impedance boundary condition is proposed by embedding the normal stress. In a two-dimensional case, it is assumed that a design boundary is free of normal traction and a shear traction depends on linearly a normal component of displacements multiplied by frequencies. Therefore, impedance boundary conditions affect the normal stress, where the impedance parameters correspond to dimensions of stresses over velocity. On the other hand, vanished impedance values are traction-free boundary conditions. The main purpose of this article is to present theoretically the existence and uniqueness of a Rayleigh wave formulation relying on secular equation's mathematical analyses. Its velocity varies along with the impedance parameters. Moreover, numerical experiments with different values for the velocity of Rayleigh waves are carried out. The present Rayleigh waves study is a fundamental step in analyzing the cause and effect of physical states such as building or structure damages resulting from natural dynamics. The results of the study generate a basic design formulation theory to test the effects of Rayleigh waves affecting structures when an earthquake occurs. The presence and uniqueness of the proposed formulation is verified by mutual comparisons of several numerical examples.

Rather than using smartphones as seismometers with designated locations and orientations, this study proposes to employ crowds' smartphones in buildings to perform fast safety assessment of buildings. The principal advantage of using crowds' smartphones is the potential to monitor the safety of millions of buildings without hardware costs, installation labor, and long-term maintenance. This study's goal is to measure the maximum interstory drift ratios during earthquake excitation using crowds' smartphones. Beacons inside the building are required to provide the location and relevant building information for the smartphones via Bluetooth. Wi-Fi Direct is employed between nearby smartphones to conduct peer-to-peer time synchronization and exchange the acceleration data measured. An algorithm to align the orientation between nearby smartphones is proposed, and the performance of the orientation alignment, interstory drift measurement, and damage level estimation are studied numerically. Finally, the proposed approach's performance is verified using large-scale shaking table tests of a scaled steel building. The results presented in this study illustrate the potential to use crowds' smartphones with the proposed approach to record building motions during earthquakes and use those data to estimate buildings' safety based on the interstory drift ratios measured.

Protective coatings are most widely used anticorrosive structures for steel structures. The corrosion under the coating damages the host material, but this damage is completely hidden. Therefore, a field-applicable under-coating-corrosion visualization method has been desired for a long time. Laser ultrasonic technology has been studied in various fields as an in situ nondestructive inspection method. In this study, a comparative analysis was carried out between a guided-wave ultrasonic propagation imager (UPI) and pulse-echo UPI, which have the potential to be used in the field of under-coating-corrosion management. Both guided-wave UPI and pulse-echo UPI were able to successfully visualize the corrosion. Regarding the field application, the guided-wave UPI performing Q-switch laser scanning and piezoelectric sensing by magnetic attachment exhibited advantages owing to the larger distance and incident angle in the laser measurement than those of the pulse-echo UPI. Regarding the corrosion visualization methods, the combination of adjacent wave subtraction and variable time window amplitude mapping (VTWAM) provided acceptable results for the guided-wave UPI, while VTWAM was sufficient for the pule-echo UPI. In addition, the capability of multiple sensing in a single channel of the guided-wave UPI could improve the field applicability as well as the relatively smaller size of the system. Thus, we propose a guided-wave UPI as a tool for under-coating-corrosion management.

A model of plastic deformation of the shape memory alloys which describes dislocation slip at the microlevel is developed. A condition similar to the Schmid law was adopted for the determination of dislocation slip onset. A description of the interaction of plastic deformation and martensitic transformations by taking into account the densities of deformation defects is proposed. It is shown that the model can correctly describe the effect of plastic strain on the shape memory effect. The proposed model is also capable of describing the two-way shape memory effect.

Model uncertainty is a key factor that could influence the accuracy and reliability of numerical model-based analysis. It is necessary to acquire an appropriate updating approach which could search and determine the realistic model parameter values from measurements. In this paper, the Bayesian model updating theory combined with the transitional Markov chain Monte Carlo (TMCMC) method and K-means cluster analysis is utilized in the updating of the structural model parameters. Kriging and polynomial chaos expansion (PCE) are employed to generate surrogate models to reduce the computational burden in TMCMC. The selected updating approaches are applied to three structural examples with different complexity, including a two-storey frame, a ten-storey frame, and the national stadium model. These models stand for the low-dimensional linear model, the high-dimensional linear model, and the nonlinear model, respectively. The performances of updating in these three models are assessed in terms of the prediction uncertainty, numerical efforts, and prior information. This study also investigates the updating scenarios using the analytical approach and surrogate models. The uncertainty quantification in the Bayesian approach is further discussed to verify the validity and accuracy of the surrogate models. Finally, the advantages and limitations of the surrogate model-based updating approaches are discussed for different structural complexity. The possibility of utilizing the boosting algorithm as an ensemble learning method for improving the surrogate models is also presented.

This paper focuses on predicting the post-heating mechanical properties of cementitious composites reinforced with multi-scale additives using the Artificial Neural Network (ANN) approach. A total of four different feed-forward ANN models are developed using 261 data sets collected from 18 published sources. The models are optimized using 12 input parameters selected based on a comprehensive literature review to predict the residual compressive strength, the residual flexural strengths, elastic modulus, and fracture energy of heat-damaged cementitious specimens. Furthermore, the ANN is employed to predict the impact of several variables including; the content of polypropylene (PP) microfibers and carbon nanotubes (CNTs) used in the concrete, mortar, or paste mix design, length of PP fibers, the average diameter of CNTs, and the average length of CNTs. The influence of the studied parameters is investigated at different heating levels ranged from 25℃ to 800℃. The results demonstrate that the developed ANN models have a strong potential for predicting the mechanical properties of the heated cementitious composites based on the mixing ingredients in addition to the heating conditions.

The present study investigated the synergistic effects of carbon nanotube (CNT) and carbon black (CB) inclusions on the piezoresistive sensing behaviors of cementitious composites. Four different CNT and CB combinations were considered to form different conductive networks in the binder material composed of Portland cement and fly ash. The cement was substituted with fly ash at levels of 0 or 50% by the mass of binder. The specimens were cured up to 100 days to observe the variations of the electrical characteristics with hydration progress, and the piezoresistive sensing behaviors of the specimens were measured under cyclic loading tests. The fabricated specimens were additionally evaluated with flowability, resistivity and cyclic loading tests, and morphological analysis. The scanning electron microscopy and energy disperse X-ray spectroscopy test results indicated that CNT and CB inclusion induced synergistic formations of electrically conductive networks, which led to an improvement of piezoresistive sensing behaviors. Moreover, the incorporation of fly ash having Fe³⁺ components decreased the electrical resistivity, improving both the linearity of fractional changes in the electrical resistivity and reproducibility expressed as R² under cyclic loading conditions.

As civil infrastructure has continued to age worldwide, its structural integrity has been threatened owing to material deteriorations and continual loadings from the external environment. Structural Health Monitoring (SHM) has emerged as a cost-efficient method for ensuring structural safety and durability. As SHM research has gradually addressed an increasing number of structure-related problems, it has become difficult to understand the changing research topic trends. Although previous review papers have analyzed research trends on specific SHM topics, these studies have faced challenges in providing (1) consistent insights regarding macroscopic SHM research trends, (2) empirical evidence for research topic changes in overall SHM fields, and (3) methodological validations for the insights. To overcome these challenges, this study proposes a framework tailored to capturing the trends of research topics in SHM through a bibliometric and network analysis. The framework is applied to track SHM research topics over 15 years by identifying both quantitative and relational changes in the author keywords provided from representative SHM journals. The results of this study confirm that overall SHM research has become diversified and multi-disciplinary. Especially, the rapidly growing research topics are tightly related to applying machine learning and computer vision techniques to solve SHM-related issues. In addition, the research topic network indicates that damage detection and vibration control have been both steadily and actively studied in SHM research.

One of the latest teaching strategies is smart classroom teaching. Teaching is carried out with the assistance of smart teaching technologies to improve teacher-student contact, increase students' learning autonomy, and give fresh ideas for the fulfillment of students' deep learning. Computer-based technology has improved students' language learning and significantly motivating them to continue learning while also stimulating their creativity and enthusiasm. However, the difficulties and barriers that many EFL instructors are faced on seeking to integrate information and communication technology (ICT) into their instruction have raised discussions and concerns regarding ICT's real worth in the language classroom. This is a case study that includes observations in the classroom, field notes, interviews, and written materials. In EFL classrooms, both computer-based and non-computer-based activities were recorded and analyzed. The main instrument in this study was a survey questionnaire comprising 43 items, which was used to examine the efficiency of ICT integration in teaching and learning in public schools in Kuala Lumpur. A total of 101 questionnaires were delivered, while each responder being requested to read the statements provided. The total number of respondents for this study was 101 teachers from Kuala Lumpur's public secondary schools. The questionnaire was randomly distributed to respondents with a teaching background. This study indicated the accuracy of utilizing Teaching-Learning-Based Optimization (TLBO) in analyzing the survey results and potential for students to learn English as a foreign language using computers. Also, the usage of foreign language may be improved if real computer-based activities are introduced into the lesson.