In this paper, the effect of GO/Al₂O₃ and Al₂O₃ synthesized nanoparticles on the durability of concrete is studied. To this end, after the synthesis of nanoparticles and confirmation of nanoparticles fabrication by SEM and FT‐IR spectra, three concrete samples for each experiment related to each mix design were prepared and subjected to freeze‐thaw cycles, high temperature, and acidic environment. The results show that the samples containing GO/Al₂O₃ nanoparticles had the least weight loss in freeze‐thaw cycles as well as better resistance against acidic environment and the lowest apparent changes at high temperature compared to the samples containing nano‐Al₂O₃ and the samples without nanoparticles. The replacement of 2 wt.% of cement with GO/Al₂O₃ nanoparticles results in the highest increase in concrete durability. The presence of nanoparticles in the concrete microstructure and the validation of the results are investigated by FT‐IR, SEM, and EDX spectra.

The success or failure of a project in achieving predefined objectives is largely dependent on the suitability of its execution system. An important decision in the early stages of a project is to investigate different possible ways for executing projects and selecting the best one. This requires the identification of risk taking of projects. Risk is, in fact, the same as uncertainty and a multidimensional concept affecting the project's objectives. Risk management is defined as the risk identification and assessment process and application of specific methods to reduce risks to an acceptable level. Therefore, the initial objective of project risk management is risk identification, evaluation and control for the success of projects. The risk management standard published by the Project Management Institute (PMI), entitled Project Management Body of Knowledge (PMBOK) was used in this study as the basic method for describing risk management. The general objective of this study was to develop a risk management model for water and sewage projects using Interpretive Structural Modeling (ISM). The statistical population included all experts involved in the field of water and sewage projects. The Delphi method was used for risk identification. Eventually, data was analyzed with the help of the ISM and driving power-dependence power diagram (MICMAC). According to the results, allocation of Islamic Treasury documents and bills, imprecise conduction of preliminary studies, the lack of coordination between project designers, irrelevant maps and details, imprecise initial project estimation, the lack of adequate maps and details and project failure and its conversion into some small projects with a high level of impact-dependence are highly prioritized risks needed to be controlled.

In order to build high‐quality concrete, it is imperative to know the raw materials in advance. It is possible to accurately predict the quality of concrete and the amount of raw materials used using machine learning‐enhanced methods. An automated process based on machine learning strategies is proposed in this paper for predicting the compressive strength of concrete. Fusion‐learning‐based optimization is used in the proposed approach to generate a strong learner by pooling support vector regression models. The SVR technique proposes an optimization method for finding the kernel radial basis function (RBF) parameters based on improving the innovative gunner algorithm (AIG). As a result of AIG's diverse solutions, local optima are effectively avoided. Therefore, the novelty of our research is that, in solving the uncertainty of predicted outputs based on integrated models, we use fusion‐learning‐based optimization to improve regression discrimination. We also collected a standard dataset to analyze the proposed algorithm, and subsequently, the dataset was designed from concrete laboratory tests on 244 samples, seven features, and three outputs. Different regression intensities are determined by correlation analysis of responses. Regression fusion is sufficiently accurate to estimate the number of desired outcomes examined based on the appropriate input data sample. The best quality concrete can be achieved with an error rate of less than 5%.

The global agricultural sector has persistently grappled with the effective handling of bovine waste. This research repurposes bovine waste into a cost-effective and sustainable fiber, which is subsequently treated with dendritic fibrous nanosilica (DFNS) to produce CDF/DFNS. This is then integrated into cement-based composites. This study aimed to introduce CDF/DFNS to enhance the operational efficiency and longevity of Portland cement with notable sulfate resistance. Concurrently, CDF/DFNS was incorporated into cement mortar, and an examination of the aggregation of CDF/DFNS, along with the aquation procedure and microstructure of the mortar, was conducted. The investigation indicated that incorporating CDF/DFNS enhanced the toughness, tangible attributes, and imperishability of the cement specimens. The integration of CDF/DFNS resulted in a reduction in both the parameters related to the movement of chloride ions and the volume of voids in a material. Furthermore, the ability of cement mortar to resist compression forces was improved with the presence of CDF/DFNS as opposed to control samples. These improvements in strength and imperishability suggested that CDF/DFNS holds significant potential in reducing CO₂ emissions in the concrete industry.

The utilization of nanoparticles in concrete has been propelled by their advantageous attributes, such as their fine particle size and remarkable reactivity. To enhance these properties, various nanoparticles can be integrated into the lightweight concrete matrix. We introduce a novel technique to produce TiO₂ structures resembling dandelions, featuring interfaces between anatase and TiO₂ phases as well as a distinct outer layer. This approach utilizes a deep eutectic solvent-tuning method that is both user- and environmentally friendly. The formation of this remarkable external covering is attributed to the hierarchical arrangement of two-dimensional ultrathin nanosheets with mesopores in a three-dimensional configuration. The primary focus of this study is the utilization of DFNT, a nanoparticle possessing a three-dimensional structure, within the matrix of lightweight concrete. To conduct this study, concrete cases with congestion of 1000 kg/m³ were fabricated and subjected to testing. We sought to evaluate the effect of different weight ratio proportions of DFNT on the enduring characteristics of lightweight concrete, such as the contraction caused by drying, the degree of openness, the capacity to absorb water, and the speed at which ultrasonic waves travel. The inclusion of DFNT induces a transformation in the microstructural composition of lightweight concrete, shifting it from a loose needle-like structure to a more compact and cohesive microstructure characteristic of cementitious composites. Furthermore, DFNT enhances the lightweight concrete matrix by occupying the empty spaces, tiny fractures, and gaps present within it.

In recent years, natural pozzolans have been proposed as a way to improve the mechanical and biocompatible properties of concrete. This study investigated the effects of different amounts of nanoparticles, coal slag pozzolan, and their combination on the mechanical properties and durability of concrete. For each mixed design, nine cubic samples of 101010cm and 3015cm were made and then cured in water for 28 days before being tested for compressive and tensile strength. According to the results, pozzolan at about 5 of cement weight increased the compressive strength of concrete compared to samples without pozzolan. Nanoparticles of FeNi₃ greatly enhanced the compressive and tensile strength of concrete in most samples containing nanoparticles. The compressive and tensile strength of 28-day concrete increased by 27 and 18, respectively. Pozzolan (10) and 2 of FeNi₃ (CP10F2) in concrete also reduced the water absorption of the samples, which can improve the durability parameters of concrete. In concrete exposed to sulfuric acid, sample CP0F2 (2 of FeNi₃ nanoparticles) had a positive effect on compressive strength, and samples containing 2 of FeNi₃ nanoparticles had higher compressive strength than those with pozzolan replacing cement. The simultaneous use of coal slag and FeNi₃ nanoparticles has increased the mechanical properties and durability of concrete in addition to reducing cement consumption.