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High-strength concrete generates a significant amount of heat during curing, which can cause delayed ettringite formation and early thermal cracking. Such problems are particularly acute in Hong Kong because of the local practice of designing concrete mixes to have rather high cementitious contents to avoid non-compliance with the stringent strength requirements. Moreover, in Hong Kong, there is still a lack of clear specifications of the temperature control limits to be imposed. Hence, the temperature control of curing high-strength concrete in massive columns/walls has, up to now, remained guess work. In this paper, temperature control limits are proposed, and a case study on temperature control of massive C80 concrete columns during curing is presented. Due to the high cementitious content and large column size, an internal water-cooling system, designed with the help of thermal analysis by the finite element method, was installed. In this system, each pipe was a double-pipe for both water inflow and outflow. It had successfully avoided exceedance of temperature control limits and formation of early thermal cracks. The lessons learned, as summarized in the Conclusions, should be useful for the optimum design of temperature control regimes for massive high-strength concrete members.

Box girder bridges are often subject to cracking due to wet temperature changes caused by the heat of hydration in the early stages; however, current studies do not provide an effective method for considering this effect. The reasonable temperature control of concrete box girders can prevent early concrete cracking and ensure concrete quality, but box girder temperature control becomes an important focus in construction. To fill this gap, a two-dimensional temperature field study was carried out for a large-span box bridge by the finite element method. The advantages and disadvantages of the two innovative combination curing methods and the early curing effects on the construction of a box girder in summer were investigated and analyzed based on the temperature field of the box girder under different curing methods, the time–history curves of the temperature at each key node of the box girder, and the time–history curves of the temperature difference between the inside and outside of the box girder. The research results show that the mold paste and automatic water spray method (Combination B method) is more suitable for the early curing of box girders in summer.

This study addresses the formation, detection, and repair of cracks in concrete elements exposed to temperatures above 25 °C, where accelerated evaporation compromises their structural strength. An automated intelligent curing system with embedded sensors (DS18B20, HD-38) and Arduino controllers was developed and applied to solid slabs, columns, and concrete test specimens (1:2:3.5 mix ratio). The electronic design was simulated in Proteus and validated experimentally under tropical conditions. Data with normal distribution (p > 0.05) showed a significant correlation between internal and ambient temperature (r = 0.587; p = 0.001) and a low correlation in humidity (r = 0.143; p = 0.468), indicating hygrometric independence. The system healed cracks of 0.01 mm observed two hours after pouring the mixture, associated with an evaporation rate of 1.097 mL/s in 4 m2. For 28 days, automated irrigation cycles were applied every 30 to 60 min, with a total of 1680 L, achieving a 20% reduction in water consumption compared to traditional methods. The system maintained stable thermal conditions in the concrete despite ambient temperatures of up to 33.85 °C. A critical evaporation range was identified between 11:00 and 16:00 (UTC-5). The results demonstrate the effectiveness of the embedded system in optimizing curing, water efficiency, and concrete durability.

This study investigates the early-age performance of large-area C30 concrete slabs under different curing regimes using a multi-scale approach combining laboratory experiments, field monitoring, and numerical simulation. The experimental results indicated that standard curing (SC7) maximized the mechanical properties. In contrast, the thermal insulation and moisture retention curing (TC) regime significantly reduced temperature gradients and stress mutation amplitudes by 42% compared to wet curing (WC) by leveraging the synergistic effect of aluminum foil and insulating cotton. This makes TC a preferred solution in situations where engineering constraints apply. Field monitoring demonstrated that WC is suitable for humidity-sensitive scenarios with low-temperature control requirements, while TC is more suitable for large-area concrete or low-temperature environments, balancing early strength development and long-term durability. This multi-field coupled model exhibits significant deviations during the early stage (0–7 days) due to complex boundary interactions, but achieves high quantitative accuracy in the long-term steady state (after 14 days), with a maximum error below 8%. The analysis revealed that the key driving factors for stress evolution are early hydration heat–humidity coupling and mid-term boundary transient switching. The study provides a novel, multi-scale validated curing optimization path for crack control in large-area concrete slabs.

Nowadays, developing economical and environmentally friendly concretes along with considering mechanical and durability objectives is of great significance. This study developed optimal concrete mixture proportions for different heating and re-curing regimes. The objective functions were 28-day, residual, and re-cured compressive strengths, cost, and embodied CO 2 emissions. A data set, including approximately 500 mix designs, was collected from the literature to develop an optimal ANN model to predict the first three objectives. The genetic algorithm and particle swarm optimization were used to tune the ANN model’s hyperparameters. NSGA-II and MOPSO algorithms, besides this optimal ANN model, were then used to develop the optimal mixture proportions for different heating and re-curing regimes. TOPSIS was utilized to sort the non-dominated solutions and select the optimal one based on different weight vectors. The results showed that the R 2 values for the verification set in predicting the 28-day, residual, and re-cured compressive strengths were 0.999, 0.987, and 0.977, respectively. The sensitivity analysis revealed that the heating regime (especially peak temperature) is the most fundamental input feature in predicting the post-fire behavior of concretes. The optimal concrete mixture proportion depends mainly on the case study, which considers economic, environmental, and post-fire mechanical objectives. Most of the mixtures were high-strength concretes when all objectives were equally weighted. Increasing the cost and embodied CO 2 emissions weights resulted in cost-efficient and environmentally friendly concretes in exchange for inferior mechanical properties. The developed mixtures by NSGA-II were mostly blended with metakaolin when all objectives equally weighted. Silica fume appeared as SCM in mixtures when the cost and embodied CO 2 emissions weighted five times that of the mechanical objectives. The proposed framework facilitates the appropriate selection of the mixture proportion.

A properly optimized concrete mix design yields the required workability and strength for the fresh and hardened concrete to sustain desired loads and stresses over time, preventing premature failure. Thus, it is imperative to investigate the behavioural sensitivity of blended cement concrete to mix design variations. The research uses the Box-Behnken design of the response surface method to optimize the slump and compressive strength of blended cement concrete incorporating Shea nutshell ash (SNA). SNA was partially utilized as a Portland limestone cement (PLC) substitute at 5–15 wt% replacement levels using C25, C30, and C40 MPa mix design proportions and tested for compressive strength after 7–90 curing ages. Binder (SNA-to-PLC) ratio, water-to-binder ratio, binder-to-aggregate ratio, and curing age were engaged as continuous (independent) variables to optimize the response (dependent) variables (slump and compressive strength). The slump and compressive strength responses were optimized by the Box-Behnken design. The results exhibited a minimized slump and a maximized compressive strength with approximately 40–63% reduction and 10% increment. The correlations between the optimized and experimental variables were accurate and strong, with 98.89% and 98.44% R 2 for slump and compressive strength. Ultimately, this response model is beneficial in determining the optimum mix design proportions to achieve the desired compressive strength of blended cement concrete incorporating repurposed waste materials.

In recent years, UHP self-compacted concrete is an innovative category of concrete that has attached a lot of attention because of its higher durability and compressive strength than conventional concrete. So, to overcome the cost of preparation of UHPC and preservation of high-strength deformation and rheological characteristic of self-compacting concrete when replacing a part of expensive cement with three types of production waste. In addition, the problem of reducing environmental pollution is solved. In this study. recycled glass (GP) and lime (LP) powder were used as substitution materials in the manufacture of the UHPSCC. The flowability of UHPSCC was measured by slump flow,  T50, V-funnel tests as an indication for the capability of filling and J-ring tests as an indication for the capability of passing. Furthermore, durability and mechanical properties were investigated. The elevated temperature effect was investigated on several UHPCSCC samples with glass (GP) and lime (LP) powder. The test results showed that the incorporation of GP and LP partially replaced cement improved the flowability of UHPSCC. The compressive, tensile, and flexural strength were enhanced by using GP till 20% replacement of cement also, the compression strength values were highly improved by using LP replacement of cement at different ages for (hot and normal curing). The highly compressive strength values for UHPSCC mixes with a 20% replacement ratio of GP and LP as cement replacement materials were 119.0 and 128.8 MPa under hot curing regimes and increased by 6.25% and 9.62%, respectively, than that of similar mixes under normal curing regimes at 90 days. The highly splitting and flexural strength values for UHPSCC 7 mix with 20% replacement level of LP and UHPSCC 9 mix with 20% replacement level of LP and GP were reported at 11.80 and 17.85 MPa which increased by 24.20% and 58.60%, respectively, compared to the control mix.

Geopolymers are innovative cementitious materials that can completely replace traditional Portland cement composites and have a lower carbon footprint than Portland cement. Recent efforts have been made to incorporate various nanomaterials, most notably nano-silica (nS), into geopolymer concrete (GPC) to improve the composite’s properties and performance. Compression strength (CS) is one of the essential properties of all types of concrete composites, including geopolymer concrete. As a result, creating a credible model for forecasting concrete CS is critical for saving time, energy, and money, as well as providing guidance for scheduling the construction process and removing formworks. This paper presents a large amount of mixed design data correlated to mechanical strength using empirical correlations and neural networks. Several models, including artificial neural network, M5P-tree, linear regression, nonlinear regression, and multi-logistic regression models, were utilized to create models for forecasting the CS of GPC incorporated with nS. In this case, about 207 tested CS values were collected from literature studies and then analyzed to promote the models. For the first time, eleven effective variables were employed as input model parameters during the modeling process, including the alkaline solution to binder ratio, binder content, fine and coarse aggregate content, NaOH and Na 2 SiO 3 content, Na 2 SiO 3 /NaOH ratio, molarity, nS content, curing temperatures, and ages. The developed models were assessed using different statistical tools such as root mean squared error, mean absolute error, scatter index, objective function value, and coefficient of determination. Based on these statistical assessment tools, results revealed that the ANN model estimated the CS of GPC incorporated with nS more accurately than the other models. On the other hand, the alkaline solution to binder ratio, molarity, NaOH content, curing temperature, and ages were those parameters that have significant influences on the CS of GPC incorporated with nS.

Low-heat Portland (LHP) cement is a kind of high-belite cement, which has the characteristic of low hydration heat. Currently, it is extensively used in the temperature control of mass concrete. Based on the thermodynamic database of OPC-based materials, the thermodynamic software GEM-Selektor (noted as GEMS) is used for simulating the hydration products of the LHP cement paste. Then, according to the GEMS thermodynamic simulation results, MATLAB is used to visualize the initial and ultimate stages of LHP cement pastes; the effects of curing temperature and water to cement (w/c) ratio on hydration products are addressed; and the porosity, fractal dimension, and tortuosity of different pastes are calculated. It is found that an appropriately high curing temperature is important for reducing porosity, especially in the early hydration stage. Hydration time also has a significant impact on the hydration of LHP cement paste; long hydration time may reduce the impact of temperature on hydration products. The w/c ratio is another important consideration regarding the hydration degree and porosity of LHP paste, and under different curing temperatures, hydration times, and w/c ratios, the porosity varies from 5.91–32.91%. The fractal dimension of this work agrees with the previous findings. From tortuosity analysis, it can be concluded that the high curing temperature may cause significant tortuosity, further affecting the effective diffusivity of LHP cement paste. For cement pastes with low w/c ratio, this high curing temperature effect is mainly reflected in the early hydration stage, for ones with high w/c ratio, it is in turn evident under long-term curing.

Low-heat Portland (LHP) cement is a new type of Portland cement that has been widely used in recent years due to its low heat of hydration, which makes it exceptional in temperature control for mass concrete construction. However, limited studies have investigated the impact of temperature and magnesium oxide (MgO) content on LHP cement-based materials. This study utilizes thermodynamic simulations to study the hydration process, pore structure, and autogenous shrinkage of LHP cement pastes with different water-to-cement ratios (0.3, 0.4, and 0.5), curing temperatures (5, 15, 20, and 30 °C), and MgO contents (mass fractions of 2%, 4%, and 5%). Higher curing temperature is found to promote the hydration reactions in cement paste. Moreover, the incorporation of 4% MgO moderately decreases both porosity and dimensional shrinkage in pastes. The microstructural evolution of different LHP pastes is examined through a comparative analysis, lending insights into LHP cement-based material applications.