Civil and Structural Engineering, Building and Construction, General Economics, Econometrics and Finance
2
Scopus Publications
Scopus Publications
Experimental studies of concrete materials for the restoration of hydraulic structures K.I. Ilyassova, Zh.N. Moldamuratov, O.D. Seitkazinov, G.S. Abiyeva, A.Z. Tukhtamisheva, М. Paktin Nanotechnologies in Construction, 2025 Introduction.The objective of this research is to substantiate the application of advanced concrete materials for restoring hydraulic structures in Kazakhstan and Central Asia, where service conditions are severe due to sharp temperature swings, sulfate-chloride attack, and high seismicity.The relevance of the study is determined by the widespread deterioration of existing infrastructure and the demonstrated inadequacy of traditional repair methods.Methods and materials.To evaluate the properties of the original concrete and promising repair materials (polymer-modified mortars, geopolymer systems, and ultra-high-performance concrete-UHPC), a comprehensive set of laboratory tests was conducted.The research included: physico-mechanical tests (strength, elastic modulus, adhesion), durability tests (RCPT, NT Build 492, freeze-thaw resistance, sulfate resistance, abrasion-cavitation wear), and micro/nanostructural analysis (SEM/EDS, XRD, nanoindentation).Results and discussion.The original concrete exhibited high permeability (~5.2 thousand C according to RCPT), low adhesion, and significant strength loss under cyclic loading, which can be explained by pronounced porosity and cracking of the structure.UHPC demonstrated minimal permeability (<0.3 thousand C), high adhesion (2.2 MPa), low strength loss under freeze-thaw cycles (3%), and the highest local elastic modulus (40-50 GPa).Geopolymer materials showed strong sulfate resistance (expansion 0.038%) and a fine-pore structure with a low diffusion coefficient (510 -12 m 2 /s).Polymer-modified mortars (PMM) exhibited intermediate characteristics, remaining the most economically feasible option.SEM confirmed the significant densification of the UHPC and geopolymer matrices compared to the original concrete; XRD revealed a reduction in portlandite content and the formation of sulfate-resistant phases in geopolymers, while UHPC showed a predominance of amorphous C-S-H phases.Conclusion.The comprehensive analysis demonstrated that the rational use of materials depends on the balance between durability, reliability, and economic-environmental indicators.UHPC is recommended for zones exposed to intensive cavitation and abrasion; geopolymers are optimal for structures in sulfate environments; and PMM are suitable for localized repairs under budget constraints.The results confirm the effectiveness of a multi-level approach: diagnostics material selection laboratory verification durability prediction practical recommendations.This provides a scientifically grounded basis for designing restoration measures for hydraulic structures.
Machine Learning on the Role of Eliminating Human Error on the Manufacturing Industry Supriya Addanke, Mangalapalli Vamsi Krishna, Pradeep K V, Khel Prakash Jayant, Karlygash Ilyassova, Kalya Lakshmi Sainath 2022 6th International Conference on Trends in Electronics and Informatics Icoei 2022 Proceedings, 2022 Human errors within a manufacturing industry are an essential factor that needs to be prevented to continue their operation. However, human errors can be a major obstacle within the production process and its safety. Companies need to focus on their human error detection process to prevent this type of disruption. Human errors within a manufacturing industry need to be eliminated and identified within a less time and that can only be possible after the engagement of machine learning techniques. Focus of this research article will be on different types of machine learning tools used within the Indian manufacturing Industry to eliminate human errors and the challenge they might have faced during its post and pre implementation process. In the introduction part, the background of this research area based on global context and aim, and objectives of this research has been presented. In the LR section, different findings from journal articles have been presented which focuses on the Python script used by construction sites, to improve the process of manufacturing Geopolymer. Moreover, various other tools such as different regression models in the food production industry and other manufacturing industries will be discussed in this research paper with challenges. A mixed method has been used in this research paper to identify primary and secondary both data. It has been found that, effect of ML models to eliminate human errors in the manufacturing industry is mainly positive, apart from some specific technical challenges and poor algorithms.
