Sustainable structures are critical for addressing global climate change. Hence, their structural resilience or ability to recover from natural events must be considered comprehensively. Green roofs are a widely used sustainable feature that improve the environment while providing excellent occupant amenity. To expand their usage, their inherent damping and layout sensitivity to seismic performance are investigated in this study. The soil of a green roof can serve as a damper to dissipate the energy generated by earthquakes or other dynamic events. Results of preliminary analysis show that a green roof soil can increase localized damping by 2.5% under both dry and saturated conditions. Based on these findings, nonlinear time-history analyses are conducted on a three-story building in SAP2000 to monitor the structural behavior with and without a green roof. The increased damping in the green roof soil is beneficial to the structural performance, i.e., it reduces the building displacement and acceleration by 10% and 12%, respectively. Additionally, certain configurations are more effective and beneficial to the structural response than others, which suggests the possibility of design optimization. Based on the findings of this study, new methods of modeling and considering green roofs in structural design are established.
To realize seismic-resilient reinforced concrete (RC) moment-resisting frame structures, a novel self-centering RC column with a rubber layer placed at the bottom (SRRC column) is proposed herein. For the column, the longitudinal reinforcement dissipates seismic energy, the rubber layer allows the rocking of the column, and the unbonded prestressed tendon enables self-centering capacity. A refined finite element model of the SRRC column is developed, the effectiveness of which is validated based on experimental results. Results show that the SRRC column exhibits stable energy dissipation capacity and no strength degradation; additionally, it can significantly reduce permanent residual deformation and mitigate damage to concrete. Extensive parametric studies pertaining to SRRC columns have been conducted to investigate the critical factors affecting their seismic performance.
In this study, the concrete cone capacity, concrete cone angle, and load–displacement response of cast-in headed anchors in geopolymer concrete are explored using numerical analyses. The concrete damaged plasticity (CDP) model in ABAQUS is used to simulate the behavior of concrete substrates. The tensile behavior of anchors in geopolymer concrete is compared with that in normal concrete as well as that predicted by the linear fracture mechanics (LFM) and concrete capacity design (CCD) models. The results show that the capacity of the anchors in geopolymer concrete is 30%–40% lower than that in normal concrete. The results also indicate that the CCD model overestimates the capacity of the anchors in geopolymer concrete, whereas the LFM model provides a much more conservative prediction. The extent of the difference between the predictions by the numerical analysis and those of the above prediction models depends on the effective embedment depth of the anchor and the anchor head size. The influence of concrete surface cracking on the capacity of the anchor is shown to depend on the location of the crack and the effective embedment depth. The influence of the anchor head profile on the tensile capacity of the anchors is found to be insignificant.
This paper reports a comparative study of microcapsules with enhanced thermal stability and electrical conductivity inspired by the bionic thermal insulation of birds’ feathers for self-healing aged asphalt. The work is based on an in situ polymerization with composite shell components of graphene and hexamethoxymethylmelamine resin. By using graphene, microcapsules with rough surfaces are achieved, improving the interface between microcapsules and asphalt. In addition, the microcapsules’ initial thermal decomposition temperature is appropriately high, so that the stability of the microcapsule in the asphalt highway system is protected. The proportion of graphene in the microcapsule shell can regulate the microcapsule’s heat resistance because graphene modifies the shell’s structural makeup. Additionally, the microcapsules’ electrical conductivity is relatively high. The self-healing capability of bitumen sharply increases, providing benefit to the effect of microcapsules on the properties of aged asphalt.
The grade crossings and adjacent pavements of urban trams are generally subjected to complex load conditions and are susceptible to damage. Therefore, in this study, a novel pavement structure between tram tracks and roads constructed using polyurethane (PU) elastic concrete and ultra-high-performance concrete (UHPC), referred to as a track-road transitional pavement (TRTP), is proposed. Subsequently, its performance and feasibility are evaluated using experimental and numerical methods. First, the mechanical properties of the PU elastic concrete are evaluated. The performance of the proposed structure is investigated using a three-dimensional finite element model, where vehicle-induced dynamic and static loads are considered. The results show that PU elastic concrete and the proposed combined TRTP are applicable and functioned as intended. Additionally, the PU elastic concrete achieved sufficient performance. The recommended width of the TRTP is approximately 50 mm. Meanwhile, the application of UHPC under a PU elastic concrete layer significantly reduces vertical deformation. Results of numerical calculations confirmed the high structural performance and feasibility of the proposed TRTP. Finally, material performance standards are recommended to provide guidance for pavement design and the construction of tram-grade crossings in the future.
The primary aim of this study is to correlate the impact of aggregates, if any, on the viscoelastic behavior of rejuvenated asphalt mixtures containing very high amounts of reclaimed asphalt pavement (RAP) (> 50%). First, gradation of 100% RAP was rectified, using a modified Bailey method by adding virgin aggregates to achieve two coarse dense-graded and one fine dense-graded blends. Complex modulus test was then performed from −35 to +35 °C and 0.01–10 Hz. In addition to performance grade (PG) testing, extracted and recovered binders from different asphalt mixtures underwent shear complex modulus test within −8 °C to high temperature PG and frequencies from 0.001 to 30 Hz. Cole−Cole, Black space, complex modulus and phase angle master curves were constructed and Shift-Homothety-Shift in time-Shift (SHStS) transformation was used to compare the linear viscoelastic behavior of asphalt binders and mixtures. The influence of aggregates on the viscoelastic behavior of asphalt mixtures depends on temperature and/or frequency. The role of asphalt binders in the behavior of asphalt mixtures is more pronounced at high temperatures and the effect of the aggregate structure increases as the temperature falls. The maximum difference (60% to 70%) in the viscoelastic behavior of the binder and mixture based on SHStS transformed Cole−Cole curves is within the phase angle of 15°–20°.
This study presents experimental and numerical investigations on the mechanical properties of ultra-high-performance concrete (UHPC) reinforced with single and hybrid micro- and macro-steel and polypropylene fibers. For this purpose, a series of cubic, cylindrical, dog-bone, and prismatic beam specimens (total fiber by volume = 1%, and 2%) were tested under compressive, tensile, and flexural loadings. A method, namely multi-target digital image correlation (MT-DIC) was used to monitor the displacement and deflection values. The obtained experimental data were subsequently used to discuss influential parameters, i.e., flexural strength, tensile strength, size effect, etc. Numerical analyses were also carried out using finite element software to account for the sensitivity of different parameters. Furthermore, nonlinear regression analyses were conducted to obtain the flexural load-deflection curves. The results showed that the MT-DIC method was capable of estimating the tensile and flexural responses as well as the location of the crack with high accuracy. In addition, the regression analyses showed excellent consistency with the experimental results, with correlation coefficients close to unity. Furthermore, size-effect modeling revealed that modified Bazant theory yielded the best estimation of the size-effect phenomenon compared to other models.
Model tests and numerical calculations were adopted based on the New Yuanliangshan tunnel project to investigate the water pressure resistance of lining construction joints in high-pressure and water-rich karst tunnels. A large-scale model test was designed and conducted, innovatively transforming the external water pressure of the lining construction joint into internal water pressure. The effects of the embedded position and waterstop type on the water pressure resistance of the construction joint were analyzed, and the reliability of the model test was verified via numerical calculations. The results show that using waterstops can significantly improve the water pressure resistance of lining construction joints. The water pressure resistance of the lining construction joint is positively correlated with the lining thickness and embedded depth of the waterstop. In addition, the type of waterstop significantly influences the water pressure resistance of lining construction joints. The test results show that the water pressure resistance of the embedded transverse reinforced waterstop is similar to that of the steel plate waterstop, and both have more advantages than the rubber waterstop. The water pressure resistance of the construction joint determined via numerical calculations is similar to the model test results, indicating that the model test results have high accuracy and reliability. This study provides a reference for similar projects and has wide applications.
In this study, mercury intrusion porosimetry (MIP) and X-ray micro-computed tomography (XRμCT) were used to characterize the pore structures and investigate the permeability characteristics of clay after aging and contamination with diesel. The results of the MIP tests showed that aging leads to reductions in porosity and average diameter, as well as an increase in tortuosity. The XRμCT analysis yielded consistent results; it showed that aging renders pores more spherical and isotropic and pore surfaces smoother. This weakens the pore connectivity. Micromorphological analysis revealed that aging led to the rearrangement of soil particles, tighter interparticle overlapping, and a reduction in pore space. The combination of MIP and XRμCT provided a comprehensive and reliable characterization of the soil pore structure. An increased diesel content increased the porosity and average diameter and reduced the tortuosity of the pores. Mechanistic analysis showed that aging weakens interparticle cohesion; this causes large agglomerates to break down into smaller agglomerates, resulting in a tighter arrangement and a subsequent reduction in porosity. An increase in diesel content increases the number of large agglomerates and pore spaces between agglomerates, resulting in increased porosity. Both aging and diesel content can weaken the permeation characteristics of soil.
Concrete is widely used in various large construction projects owing to its high durability, compressive strength, and plasticity. However, the tensile strength of concrete is low, and concrete cracks easily. Changes in the concrete structure will result in changes in parameters such as the frequency mode and curvature mode, which allows one to effectively locate and evaluate structural damages. In this study, the characteristics of the curvature modes in concrete structures are analyzed and a method to obtain the curvature modes based on the strain and displacement modes is proposed. Subsequently, various indices for the damage diagnosis of concrete structures based on the curvature mode are introduced. A damage assessment method for concrete structures is established using an artificial bee colony backpropagation neural network algorithm. The proposed damage assessment method for dam concrete structures comprises various modal parameters, such as curvature and frequency. The feasibility and accuracy of the model are evaluated based on a case study of a concrete gravity dam. The results show that the damage assessment model can accurately evaluate the damage degree of concrete structures with a maximum error of less than 2%, which is within the required accuracy range of damage identification and assessment for most concrete structures.
