Asphalt pavement is a key component of highway infrastructures in China and worldwide. In asphalt pavement design and condition assessment, the modulus of the asphalt mixture layer is a crucial parameter. However, this parameter varies between the laboratory and field loading modes (i.e., loading frequency, compressive or tensile loading pattern), due to the viscoelastic property and composite structure of the asphalt mixture. The present study proposes a comprehensive frequency-based approach to correlate the asphalt layer moduli obtained under two field and three laboratory loading modes. The field modes are vehicular and falling weight deflectometer (FWD) loading modes, and the laboratory ones are uniaxial compressive (UC), indirect tensile (IDT), and four-point bending (4PB) loading modes. The loading frequency is used as an intermediary parameter for correlating the asphalt layer moduli under different loading modes. The observations made at two field large-scale experimental pavements facilitate the correlation analysis. It is found that the moduli obtained via laboratory 4PB tests are pretty close to those of vehicular loading schemes, in contrast to those derived in UC, IDT, and FWD modes, which need to be adjusted. The corresponding adjustment factors are experimentally assessed. The applications of those adjustment factors are expected to ensure that the moduli measured under different loading modes are appropriately used in asphalt mixture pavement design and assessment.
This paper presents a seismic topology optimization study of steel braced frames with shape memory alloy (SMA) braces. Optimal SMA-braced frames (SMA-BFs) with either Fe-based SMA or NiTi braces are determined in a performance-based seismic design context. The topology optimization is performed on 5- and 10-story SMA-BFs considering the placement, length, and cross-sectional area of SMA bracing members. Geometric, strength, and performance-based design constraints are considered in the optimization. The seismic response and collapse safety of topologically optimal SMA-BFs are assessed according to the FEMA P695 methodology. A comparative study on the optimal SMA-BFs is also presented in terms of total relative cost, collapse capacity, and peak and residual story drift. The results demonstrate that Fe-based SMA-BFs exhibit higher collapse capacity and more uniform distribution of lateral displacement over the frame height while being more cost-effective than NiTi braced frames. In addition to a lower unit price compared to NiTi, Fe-based SMAs reduce SMA material usage. In frames with Fe-based SMA braces, the SMA usage is reduced by up to 80%. The results highlight the need for using SMAs with larger recoverable strains.
The purpose of this study is to reveal the service performance of recycled aggregate concrete (RAC) components for different values of water−cement ratio and replacement rate of recycled coarse aggregate (RCA). Generally, the concrete strength decreases with the increase of the replacement rate of RCA, in order to meet the strength requirements when changing the replacement rate of RCA, it is necessary to change the water−cement ratio at the same time. Therefore, the axial compressive strengths of prism with 25 mix proportions, the short-term mechanical properties and long-term deformation properties of reinforced concrete beams were tested respectively by changing water−cement ratio and RCA replacement rate. The bearing capacity and the strain nephogram of samples under different loads were obtained using the Digital Image Correlation (DIC) method, and a self-made gravity loading experimental device was used for long-term deformation investigation. Results showed that the damage pattern of RAC was the same as that of natural aggregate concrete (NAC), but the brittleness was more pronounced. The brittleness of concrete before failure can be reduced more effectively by adjusting the replacement rate of RCA than by adjusting the water−cement ratio. The water−cement ratio has an evident influence on the axial compressive strength and early creep of concrete, while the replacement rate of RCA has a remarkable effect on the long-term deformation of the concrete beams.
To study the damage evolution behavior of polypropylene fiber reinforced concrete (PFRC) subjected to sulfate attack, a uniaxial compression test was carried out based on acoustic emission (AE). The effect of sulfate attack relative to time and fiber hybridization were analyzed and the compression damage factor was calculated using a mathematical model. The changes to AE ringing counts during the compression could be divided into compaction, elastic, and AE signal hyperactivity stages. In the initial stage of sulfate attack, the concrete micropores and microcracks were compacted gradually under external load and a corrosion products filling effect, and this corresponded with detection of few AE signals and with concrete compression strength enhancement. With increasing sulfate attack time, AE activity decreased. The cumulative AE ringing counts of PFRC at all corrosion ages were much higher than those for plain concrete. PFRC could still produce AE signals after peak load due to drawing effect of polypropylene fiber. After 150 d of sulfate attack, the cumulative AE ringing counts of plain concrete went down by about an order of magnitude, while that for PFRC remained at a high level. The initial damage factor of hybrid PFRC was −0.042 and −0.056 respectively after 150 d of corrosion, indicating that the advantage of hybrid polypropylene fiber was more obvious than plain concrete and single-doped PFRC. Based on a deterioration equation, the corrosion resistance coefficient of hybrid PFRC would be less than 0.75 after 42 drying−wetting sulfate attack cycles, which was 40% longer than that of plain concrete.
This study presents a new systematic algorithm to optimize the durability of reinforced recycled aggregate concrete. The proposed algorithm integrates machine learning with a new version of the firefly algorithm called chaotic based firefly algorithm (CFA) to evolve a rational and efficient predictive model. The CFA optimizer is augmented with chaotic maps and Lévy flight to improve the firefly performance in forecasting the chloride penetrability of strengthened recycled aggregate concrete (RAC). A comprehensive and credible database of distinctive chloride migration coefficient results is used to establish the developed algorithm. A dataset composite of nine effective parameters, including concrete components and fundamental characteristics of recycled aggregate (RA), is used as input to predict the migration coefficient of strengthened RAC as output. k-fold cross validation algorithm is utilized to validate the hybrid algorithm. Three numerical benchmark analyses are applied to prove the superiority and applicability of the CFA algorithm in predicting chloride penetrability. Results show that the developed CFA approach significantly outperforms the firefly algorithm on almost tested functions and demonstrates powerful prediction. In addition, the proposed strategy can be an active tool to recognize the contradictions in the experimental results and can be especially beneficial for assessing the chloride resistance of RAC.
Compressive strength is the most important metric of concrete quality. Various nondestructive and semi-destructive tests can be used to evaluate the compressive strength of concrete. In the present study, a new image-based machine learning method is used to predict concrete compressive strength, including evaluation of six different models. These include support-vector machine model and various deep convolutional neural network models, namely AlexNet, GoogleNet, VGG19, ResNet, and Inception-ResNet-V2. In the present investigation, cement mortar samples were prepared using each of the cement:sand ratios of 1:3, 1:4, and 1:5, and using the water:cement ratios of 0.35 and 0.55. Cement concrete was prepared using the cement:sand:coarse aggregate ratios of 1:5:10, 1:3:6, 1:2:4, 1:1.5:3 and 1:1:2, using the water:cement ratio of 0.5 for all samples. The samples were cut, and several images of the cut surfaces were captured at various zoom levels using a digital microscope. All samples were then tested destructively for compressive strength. The images and corresponding compressive strength were then used to train machine learning models to allow them to predict compressive strength based upon the image data. The Inception-ResNet-V2 models exhibited the best predictions of compressive strength among the models tested. Overall, the present findings validated the use of machine learning models as an efficient means of estimating cement mortar and concrete compressive strengths based on digital microscopic images, as an alternative nondestructive/semi-destructive test method that could be applied at relatively less expense.
In order to study the bearing performance of a new type of prefabricated subway station structure (PSSS), firstly, a three-dimensional finite element model of the PSSS was established to study the nonlinear mechanics and deformation performance. Secondly, the bearing mechanism of a PSSS was investigated in detail. Finally, the development law of damages to a thin-walled prefabricated component and the failure evolution mechanism of a PSSS were discussed. The results showed that this new type of the PSSS had good bearing capacity. The top arch structure was a three-hinged arch bearing system, and the enclosure structure and the substructure were respectively used as the horizontal and vertical support systems of the three-hinged arch structure to ensure the integrity and stability of the overall structure. Moreover, the tongue-and-groove joints could effectively transmit the internal force between the components and keep the components deformed in harmony. The rigidity degradation of the PSSS caused by the accumulation of damages to the spandrel, hance, arch foot, and enclosure structure was the main reason of its loss of bearing capacity. The existing thin-walled components design had significant advantages in weight reduction, concrete temperature control, components hoisting, transportation and assembly construction, which achieved a good balance between safety, usability and economy.
This study presents stability analyses of layered soil slopes in unsaturated conditions and uses a limit equilibrium method to determine the factor of safety involving suction stress of unsaturated soil. One-dimensional steady infiltration and evaporation conditions are considered in the stability analyses. An example of a two-layered slope in clay and silt is selected to verify the used method by comparing with the results of other methods. Parametric analyses are conducted to explore the influences of the matric suction on the stability of layered soil slopes. The obtained results show that larger suction stress provided in unsaturated clay dominates the stability of the layered slopes. Therefore, the location and thickness of the clay layer have significant influences on slope stability. As the water level decreases, the factor of safety reduces and then increases gradually in most cases. Infiltration/evaporation can obviously affect the stability of unsaturated layered slopes, but their influences depend on the soil property and thickness of the lower soil layer.
An experimental study is performed on five post-tensioned concrete beams to explore the effects of different fracture positions on secondary transfer length and residual prestress of fractured strand. A numerical model is developed and used to predict the secondary transfer length and residual prestress of fractured strand in post-tensioned concrete beams. The model change interaction, which can deactivate and reactivate the elements for simulating the removal and reproduction of parts of the model, is used to reproduce the secondary anchorage of fractured strand. The numerical model is verified by experimental results. Results shows that the fractured strand can be re-anchored in concrete through the secondary anchorage, and the secondary transfer length of fractured strand with the diameter of 15.2 mm is 1133 mm. The residual prestress of fractured strand increases gradually in the secondary transfer length, and tends to be a constant beyond it. When the fractured strand is fully anchored in concrete, a minor prestress loss will appear, and the average prestress loss is 2.28% in the present study.