This research explored the application potential of PUM thin-overlay technology on airport rapid maintenance. The rapid curing process of polyurethane binder determines the limited time window for mixing and construction of polyurethane-bonded mixture (PUM), which presents significant difference with hot-mix asphalt (HMA) technology. Therefore, this research investigated and optimized the mix design of PUM for airport thin-overlay technology based on its thermosetting characteristics. First, limestone and basalt were comprehensively compared as an aggregate for PUM. Then, the effects of molding and curing conditions were studied in terms of mixing time, molding method, molding parameters and curing temperature. Statistical analysis was also conducted to evaluate the effects of gradation and particle size on PUM performances based on gray relational analysis (GRA), thus determining the key particle size to control PUM performances. Finally, the internal structural details of PUM were captured by X-ray CT scan test. The results demonstrated that it only took 12 hours to reach 75% of maximum strength at a curing temperature of 50 °C, indicating an efficient curing process and in turn allowing short traffic delay. The internal structural details of PUM presented distribution of tiny pores with few connective voids, guaranteeing waterproof property and high strength.

In this paper, the seismic responses and resilience of a novel K-type superelastic shape memory alloy (SMA) self-centring (SC) eccentrically braced frame (EBF) are investigated. The simulation models of the SMA-based SC-EBF and a corresponding equal-stiffness traditional EBF counterpart are first established based on some existing tests. Then twenty-four near-fault ground motions are used to examine the seismic responses of both EBFs under design basis earthquake (DBE) and maximum considered earthquake (MCE) levels. Structural fragility and loss analyses are subsequently conducted through incremental dynamic analyses (IDA), and the resilience of the two EBFs are eventually estimated. The resilience assessment basically follows the framework proposed by Federal Emergency and Management Agency (FEMA) with the additional consideration of the maximum residual inter-storey drift ratio (MRIDR). The novel SMA-based SC-EBF shows a much better resilience in the study and represents a promising attractive alternative for future applications.

Vibration-based damage detection methods have become widely used because of their advantages over traditional methods. This paper presents a new approach to identify the crack depth in steel beam structures based on vibration analysis using the Finite Element Method (FEM) and Artificial Neural Network (ANN) combined with Butterfly Optimization Algorithm (BOA). ANN is quite successful in such identification issues, but it has some limitations, such as reduction of error after system training is complete, which means the output does not provide optimal results. This paper improves ANN training after introducing BOA as a hybrid model (BOA-ANN). Natural frequencies are used as input parameters and crack depth as output. The data are collected from improved FEM using simulation tools (ABAQUS) based on different crack depths and locations as the first stage. Next, data are collected from experimental analysis of cracked beams based on different crack depths and locations to test the reliability of the presented technique. The proposed approach, compared to other methods, can predict crack depth with improved accuracy.

This study examined the feasibility of using the grey wolf optimizer (GWO) and artificial neural network (ANN) to predict the compressive strength (CS) of self-compacting concrete (SCC). The ANN-GWO model was created using 115 samples from different sources, taking into account nine key SCC factors. The validation of the proposed model was evaluated via six indices, including correlation coefficient (R), mean squared error, mean absolute error (MAE), IA, Slope, and mean absolute percentage error. In addition, the importance of the parameters affecting the CS of SCC was investigated utilizing partial dependence plots. The results proved that the proposed ANN-GWO algorithm is a reliable predictor for SCC’s CS. Following that, an examination of the parameters impacting the CS of SCC was provided.

In this study, we developed novel hybrid models namely Adaptive Neuro Fuzzy Inference System (ANFIS) optimized by Shuffled Complex Evolution (SCE) on the one hand and ANFIS with Artificial Bee Colony (ABC) on the other hand. These were used to predict compressive strength (Cs) of concrete relating to thirteen concrete-strength affecting parameters which are easy to determine in the laboratory. Field and laboratory tests data of 108 structural elements of 18 concrete bridges of the Ha Long-Van Don Expressway, Vietnam were considered. The dataset was randomly divided into a 70:30 ratio, for training (70%) and testing (30%) of the hybrid models. Performance of the developed fuzzy metaheuristic models was evaluated using standard statistical metrics: Correlation Coefficient (R), Root Mean Square Error (RMSE) and Mean Absolute Error (MAE). The results showed that both of the novel models depict close agreement between experimental and predicted results. However, the ANFIS-ABC model reflected better convergence of the results and better performance compared to that of ANFIS-SCE in the prediction of the concrete Cs. Thus, the ANFIS-ABC model can be used for the quick and accurate estimation of compressive strength of concrete based on easily determined parameters for the design of civil engineering structures including bridges.

The effect of size on the biaxial flexural strength (BFS) of Portland cement mortar was investigated by using the recently proposed triangular plate method (TPM). An experimental program was conceived to study the size effect by keeping a constant water-cement ratio of 0.485, cement-sand ratio of 1:2.75, and using unreinforced triangular mortar plates of five different thicknesses and seven different side lengths. The BFS of the produced specimens was tested, and variations of BFS depending on specimen thickness and side length were determined. The results indicated that increases in triangular plate specimen side length and specimen thickness led to a decrease in the BFS of Portland cement mortar. The effect of specimen length increase on BFS was more significant than on the effect of the specimen thickness. The variations in specimens’ thickness indicated a deterministic Type I size effect, while the variations in specimens’ length showed an energetic-statistical Type I size effect.

Blast-induced vibration produces a very complex signal, and it is very important to work out environmental problems induced by blasting. In this study, blasting vibration signals were measured during underground excavation in carbonaceous shale by using vibration pickup CB-30 and FFT analyzer AD-3523. Then, wavelet analysis on the measured results was carried out to identify frequency bands reflecting changes of blasting vibration parameters such as vibration velocity and energy in different frequency bands. Frequency characteristics are then discussed in view of blast source distance and charge weight per delay. From analysis of results, it can be found that peak velocity and energy of blasting vibration in frequency band of 62.5–125 Hz were larger than ones in other bands, indicating the similarity to characteristics in the distribution band (31–130 Hz) of main vibration frequency. Most frequency bands were affected by blasting source distance, and the frequency band of 0–62.5 Hz reflected the change of charge weight per delay. By presenting a simplified method to predict main vibration frequency, this research may provide significant reference for future blasting engineering.

In the present study, the stability of a vertical rock escarpment is determined by considering the influence of undercut. Lower bound finite element limit analysis in association with Power Cone Programming (PCP) is applied to incorporate the failure of rock mass with the help of the Generalized Hoek-Brown yield criterion. The change in stability due to the presence of undercut is expressed in terms of a non-dimensional stability number (σ_ci/γH). The variations of the magnitude of σ_ci/γH are presented as design charts by considering the different magnitudes of undercut offset (H/v_u and w_u/v_u) from the vertical edge and different magnitudes of Hoek-Brown rock mass strength parameters (Geological Strength Index (GSI), rock parameter (m_i,), Disturbance factor (D)). The obtained results indicate that undercut can cause a severe stability problem in rock mass having poor strength. With the help of regression analysis of the computed results, a simplified design equation is proposed for obtaining σ_ci/γH. By performing sensitivity analysis for an undisturbed vertical rock escarpment, we have found that the undercut height ratio (H/v_u) is the most sensitive parameter followed by GSI, undercut shape ratio (w_u/v_u), and m_i. The developed design equation as well as design charts can be useful for practicing engineers to determine the stability of the vertical rock escarpment in the presence of undercut. Failure patterns are also presented to understand type of failure and extent of plastic state during collapse.

An optimization procedure is developed for obtaining optimal structural design of filament wound composite pipes with minimum cost utilized in pressurized water and waste-water pipelines. First, the short-term and long-term design constraints dictated by international standards are identified. Then, proper computational tools are developed for predicting the structural properties of the composite pipes based on the design architecture of layers. The developed computational tools are validated by relying on experimental analysis. Then, an integrated design-optimization process is developed to minimize the price as the main objective, taking into account design requirements and manufacturing limitations as the constraints and treating lay-up sequence, fiber volume fraction, winding angle, and the number of total layers as design variables. The developed method is implemented in various case studies, and the results are presented and discussed.