Multi-Objective Optimization of Sustainable Concrete Containing Fly Ash Based on Environmental and Mechanical Considerations

Study on the Curing and Foaming of Surfactant-Modified Geopolymer Gels Based on Ash and Slag Waste from Coal Combustion

This study explores the influence of temperature-time conditions, surfactants, and varied waste compositions on the curing of geopolymer gels, a foam formation with the properties of porous geopolymers. Findings reveal that a 6 h curing period leads to a density of 435 kg/m3 and strength of 0.66 MPa, with notable improvements at 12 h. Comparing 12 to 24 h curing, differences in characteristics remain within 5%, highlighting the 12 h period as more energy-efficient. Sodium stearate-based samples exhibit excellent properties, significantly boosting strength while maintaining overall properties. Microwave curing achieves the lowest density (291 kg/m3) and closely parallels properties of samples cured conventionally for 12 h. However, it leads to complete destruction in sodium stearate-modified gels due to the Dumas reaction, making it unsuitable above 200 °C. Optimal properties emerge from compositions using sodium stearate and oven curing, achieving densities of 334 kg/m3 and strengths of 1.08 MPa (Severodvinsk CHPP-1) and 373 kg/m3 and 1.17 MPa (Novocherkassk SDPP). Although microwave curing allows for high energy efficiency, its high temperature demands necessitate careful material selection. This study offers insight into enhancing geopolymer properties while emphasizing the importance of tailored curing methods for sustainable material development.

Phosphogypsum-Based Ultra-Low Basicity Cementing Material

Traditional Portland cement is widely used in the preparation of various hydraulic concrete. However, the high alkalinity produced by cement hydration threatens the survival of aquatic animals and plants. In this paper, a new eco-friendly, ultra-low alkalinity, cementitious material was prepared with industrial waste phosphogypsum, granulated ground blast slag (GGBS) and sulphoaluminate cement. When appropriate proportions are used, the pH value of the test blocks' pore solutions at different ages were all less than 9, showing the remarkable characteristic of ultra-low alkalinity. The XRD and SEM analyses showed that the 56 d hydration products were mainly ettringite and hydrated calcium silicate, and the content of Ca(OH)₂ was not detected. The new cementitious material also has the advantages of short setting time, low heat of hydration, high strength of cement mortar and the ability to fix harmful substances in phosphogypsum, such as phosphate, fluoride and Cr and Ba elements. It has a broad application prospect in the construction of island and reef construction, river restoration and so on.

Prediction Models for Estimating Compressive Strength of Concrete Made of Manufactured Sand Using Gene Expression Programming Model

The depletion of natural resources of river sand and its availability issues as a construction material compelled the researchers to use manufactured sand. This study investigates the compressive strength of concrete made of manufactured sand as a partial replacement of normal sand. The prediction model, i.e., gene expression programming (GEP), was used to estimate the compressive strength of manufactured sand concrete (MSC). A database comprising 275 experimental results based on 11 input variables and 1 target variable was used to train and validate the developed models. For this purpose, the compressive strength of cement, tensile strength of cement, curing age, Dmax of crushed stone, stone powder content, fineness modulus of the sand, water-to-binder ratio, water-to-cement ratio, water content, sand ratio, and slump were taken as input variables. The investigation of a varying number of genetic characteristics, such as chromosomal number, head size, and gene number, resulted in the creation of 11 alternative models (M1-M11). The M5 model outperformed other created models for the training and testing stages, with values of (4.538, 3.216, 0.919) and (4.953, 3.348, 0.906), respectively, according to the results of the accuracy evaluation parameters root mean square error (RMSE), mean absolute error (MAE), and coefficient of determination (R2). The R2 and error indices values revealed that the experimental and projected findings are in extremely close agreement. The best model has 200 chromosomes, 8 head sizes, and 3 genes. The mathematical expression achieved from the GEP model revealed that six parameters, namely the compressive and tensile strength of cement, curing period, water−binder ratio, water−cement ratio, and stone powder content contributed effectively among the 11 input variables. The sensitivity analysis showed that water−cement ratio (46.22%), curing period (25.43%), and stone powder content (13.55%) were revealed as the most influential variables, in descending order. The sensitivity of the remaining variables was recorded as w/b (11.37%) > fce (2.35%) > fct (1.35%).