Materials and Structures最新文献

Incorporating phase change materials (PCMs) into asphalt mixture can effectively improve high-temperature rutting resistance. However, existing conventional wheel tracking test (CWTT) procedures apply a constant test temperature (60 °C), which does not reflect the phase transition process of PCMs. The suitability of CWTT for evaluating the rutting resistance of PCMs-modified asphalt mixtures (P-MAM) remains unclear. If the CWTT is unsuitable for evaluating the rutting resistance of P-MAM, an improved wheel tracking test (IWTT) must be proposed for accurate rutting resistance assessment. In this study, PEG/SiO₂ with different molecular weights were prepared and incorporated into asphalt mixture slabs. CWTT results (internal temperature, dynamic stability, rutting depth) were analyzed to identify the test limitations. An IWTT methodology was proposed which takes into account the whole phase transition process of PCMs over the temperature range of 40–70 °C. The IWTT protocol was subsequently applied to eight P-MAM specimens (including single- and double-layer configurations) to determine the most effective PCM incorporation strategy. Results indicate that the CWTT cannot reliably evaluate the rutting resistance of P-MAM. The IWTT successfully captures the thermal–mechanical coupling behavior of PCMs across phase transition process and provides reliable evaluation results. For single-layer P-MAM slabs, the addition of PEG6000/SiO₂ has the best rutting resistance. For double-layer P-MAM slabs, adding PEG6000/SiO₂ to the upper layer exhibits the optimal rutting resistance.

Thermal exposure is a critical challenge for carbonate stones as widely used materials in architecture, given their aesthetic and mechanical characteristics. This study examines the behaviour of eleven limestones and marbles heated to 300 °C and 600 °C, assessing bulk density, capillary absorption, compressive strength, and colour variation. A penalty-based framework was applied to evaluate performance against thresholds adapted to architectural uses such as cladding, masonry, slabs, and columns. At 600 °C, some lithologies showed up to 30% strength loss, and water absorption increased by up to two orders of magnitude. Marbles, particularly coarse-grained types, were most affected, while compact limestones (e.g., AV, BML) retained acceptable performance. These results highlight the need for lithology-specific assessment under thermal stress and support post-fire decision-making. The proposed framework offers a practical tool for material selection and rehabilitation, while emphasising the importance of refining thresholds and integrating complementary evaluation methods.

In order to study the influence of large volume of mineral admixtures on the compressive strength and working performance of sea sand reactive powder concrete (SSRPC), Box-Behnken design response surface method (RSM) was used to optimize the experimental design. Based on the response surface test results, a high-precision prediction model of genetic algorithm optimized artificial neural network (ANN-GA) was constructed. Finally, the microscopic morphology and hydration products of the multi-component admixture system were analyzed by scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The results showed that the dosage of silica fume and slag powder had the most significant effect on the strength and workability of SSRPC. In contrast, the interaction of the two similarly had the most significant effect on the performance of SSRPC. When the SF: SG: FA dosage ratio was 20:8:16, the hydrated calcium aluminosilicate hydrate (C-(A)-S–H) and ettringite (AFt) in the matrix intertwined with each other, which contributed to a significant increase in the strength. The relative error accuracies in the optimized matrix ratios for the RSM and the ANN-GA were 4.73% and 2.07%, respectively. Compared with the RSM model, the ANN-GA model has more accurate prediction performance with mean relative error (MRE), root mean square error (RMSE), and goodness of fitting R² of 0.003, 0.41, and 99.2%, respectively, and therefore, the application of this model can achieve high-precision fit ratio optimization for SSRPC.

To overcome the challenges of high energy demand and weather constraints inherent in traditional Hot Mix Asphalt (HMA) in pavement crack sealing and pothole repair, this study proposes a novel composite cold patch asphalt mortar (CPAM) and cold patch asphalt mixture (CPAMix). By optimizing aggregate gradation and binder content, CPAM can be directly applied for crack sealing, while the addition of coarse aggregates enables its use as CAPMix for pothole repair. A composite-modified cold patch asphalt (CPA) was first developed using Styrene Butadiene Styrene (SBS) and one-component moisture-curing polyurethane, with the optimal formulation determined through orthogonal experimental design. The mechanical performance and microstructural development mechanisms of CPAM for crack repair were systematically evaluated using tensile and scanning electron microscopy (SEM) tests. Additionally, the road performance of CPAMix for pothole repair was assessed through Marshall stability tests, Wheel Tracking Tests (WTT), three-point bending tests and immersed Marshall tests. The results demonstrated that LB-CPAM exhibited superior mechanical and interfacial bonding properties. Moreover, LB-13 CPAMix demonstrated outstanding initial strength, formed strength, high-temperature stability, low-temperature crack resistance, and water stability, surpassing the technical requirements for conventional HMA. These findings provide a promising guidance for the development of environmentally friendly, high-performance materials for asphalt pavement crack and pothole repair.

Carbonating fillers and supplementary cementitious materials (SCMs) before their use in concrete offers a promising approach to sequester CO₂ without compromising the performance of SCM-blended cementitious systems. This study investigates the carbonation of fillers and SCMs with CaO + MgO content ranging from 16 to 50%. Preliminary experiments were conducted to determine the optimal conditions for CO₂ uptake, and all fillers/SCMs were exposed to CO₂ under these conditions. The effects of CO₂ exposure were evaluated using thermogravimetric analysis, Fourier transform infrared spectroscopy, and x-ray diffraction. The changes in material reactivity after carbonation were also tested using a modified R³ test. Recycled cement materials and steel slags showed substantial CO₂ uptake. Otherwise, CO₂ uptake is generally low. CO₂ exposure has minimal impact on filler/SCM reactivity.

A 455-day uniaxial compressive creep test program was conducted on a total of 28 ALSCC cylindrical specimens, with variables including concrete strength, loading age, and reinforcement ratio. The results showed that under stable temperature and humidity, specimens loaded at earlier ages and with lower strength grades exhibited significantly higher creep coefficients. Specifically, after 400 days, specimens loaded at 7 and 14 days exhibited creep coefficients 11.7–21 and 1.3–6.7% higher, respectively, than those loaded at 28 days. In contrast, specimens loaded at 90 days exhibited a 50.8–60.0% reduction in creep coefficients. Before 100 days, the creep coefficient increased rapidly, indicating an accelerated creep phase. Between 100 and 200 days, the rate of increase slowed and stabilized. Reinforced ALSCC columns exhibited lower creep coefficients than unreinforced ones, with loading age having negligible effects in the later stages. A modified ALSCC multi-coefficient creep prediction model was developed, which considered loading age, strength grade, ambient temperature and humidity, and specimen dimensions. A comparative analysis of creep data revealed the average error and standard deviation between predicted and measured values were 4.4 and 4.9%, respectively, confirming the model achieved high accuracy in predicting the creep characteristics of lightweight aggregate concrete.

Chloride ingress in reinforced concrete (RC) structures deteriorates the structural service performance, seriously threating to the structural safety. In real-world, uncertainty and stochasticity are inevitably involved in testing and modeling of the diffusion profile of chloride ingress concrete (CIC). In this paper, a hierarchical Bayesian estimation framework is developed to predict the chloride concentration profile in concrete. Firstly, a CIC stochastic model based on the Fick’s second law of diffusion is constructed to characterize chloride concentration profile. Error terms are included in the stochastic model to capture measurement errors associated with inspections. Secondly, by an instruction to a universal parameter vector and an equivalence of lower order moments, a hierarchical Bayesian estimation method based on trans-distributional reversible jump Markov chain Monte Carlo algorithm (RJ-MCMC) is developed to select a single best distribution-form of the stochastic model parameters from among their multiple distribution-forms or structures. Thirdly, given that distribution-form was specified, the hierarchical Bayesian estimation method and Hybrid Markov chain Monte Carlo (H-MCMC) algorithm are incorporated to update the parameters in the CIC model based on measurement data from inspections. An example involving an in-service RC bridge was employed to validate the developed CIC model and demonstrate the proposed Bayesian estimation framework for the analysis of chloride concentration profile. Results of the analysis indicate both the uncertainty and stochasticity in the parameters of the CIC model as well as the uncertainty in distribution-form must be accounted for in the prediction of chloride concentration profile. The proposed framework will facilitate better decision-making for maintenance and repair activities.

Stabilization/solidification (S/S) is a primary approach for the treatment of waste containing heavy metal ions. However, conventional silicate cement-based S/S systems often suffer from limited long-term stability and poor intrinsic compatibility. In contrast, basic magnesium sulfate cement (BMSC), characterized by rapid setting, early strength development, and high stability, demonstrates greater potential for heavy metal immobilization. Nevertheless, current studies lack a comprehensive assessment of the solidification performance and a clear understanding of its immobilization mechanisms. In this study, Cr³⁺ and Pb²⁺ were selected as target contaminants to systematically evaluate the physical and mechanical properties, leaching toxicity, hydration characteristics, microstructure, and phase composition of BMSC solidified bodies. The role of slag was also investigated to propose a more effective strategy for heavy metal immobilization. The main findings are as follows: BMSC exhibits multiple immobilization mechanisms, including lattice substitution, chemical bonding, and physical adsorption, which collectively enhance the efficiency and stability of heavy metal fixation. With increasing ion content, BMSC displays prolonged setting times, reduced hydration heat release rates, and delayed hydration progression. Concurrently, the principal diffraction peaks of the 5·1·7 phase decrease in intensity and shift position, while the phase morphology becomes more sparse. Furthermore, BMSC demonstrates superior immobilization for Cr³⁺ and exhibits notable water resistance. The incorporation of 30% slag further improves the durability of the solidified body. This work elucidates BMSC’s multi-pathway heavy metal immobilization mechanisms and demonstrates its feasibility for safe, efficient hazardous waste treatment, offering both theoretical insights and practical guidance.

To determine the stress loading path suitable for true triaxial tests on asphalt mixtures, enabling accurate testing and analysis of their mechanical behavior under complex stress states. This study employed a triaxial sliding interlocking true triaxial testing system to conduct stress–strain testing and analysis of asphalt mixtures under three loading paths: equal-proportion loading, constant-rate loading, and sequential loading. It revealed the strain variation patterns of asphalt mixtures under different loading paths and comprehensively evaluated the applicability of the three loading paths for asphalt mixtures through error analysis. Results indicate: Under the equal-proportion loading path, the average strain error in all three directions is approximately 10%, demonstrating optimal deformation consistency and measurement accuracy. As the maximum principal stress σ₁ increases, the strain evolution patterns and magnitudes in the intermediate (σ₂) and minimum (σ₃) principal stress directions remain generally consistent. With increasing σ₂, specimen deformation primarily develops along the least constrained σ₃ direction. Under the constant-rate loading path, strain errors in both σ₂ and σ₃ directions exceeded 400%. Strain curves for both directions exhibited distinct “plateau” characteristics, with the plateau length in the σ₃ direction varying up to tenfold. The magnitude of the difference between σ₁ and σ₂ or σ₃ was the key factor influencing plateau length, and a “reversal” feature also appeared in the σ₂ direction. The sequential loading path yielded the highest strain testing errors in all three directions, with σ₂ exhibiting the greatest error exceeding 1200%. Both the σ₂-ɛ₂ and σ₃-ɛ₃ curves displayed longer “plateau” lengths than the constant-rate loading path, and the maximum “reversal” length surpassed the “plateau” length. Under both constant-rate and sequential loading paths, strain errors in the σ₂ direction showed significant variation across different stress combinations. This indicates that the stress loading path and the duration of the stress holding phase are key factors contributing to large errors. The research findings can provide reference for experimental studies on the mechanical properties of asphalt mixtures under complex three-dimensional stress states.