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Prediction of High-Performance Concrete Strength Using Python Programming
This paper seeks and brings up combination of computer programming and the concrete technology. The high-performance concrete acts as a core in construction of infrastructure. The high-performance concrete is made with the usage of basic concrete components and admixtures, and it is both mineral and chemical admixtures. The use of admixtures, either mineral or chemical, or even both, improves the performance of the concrete (Neville and Tcin in High Performance concrete—an overview, 1998, [1]). In this present study, the basic components of concrete are used with the addition of some mineral admixtures like Metakaolin and Alco fine, which are used for the concrete grades of M80 and M100 (cast and tested). High-performance concrete performs better than high-strength concrete considering the mechanical properties, which leads to a trend in the usage of HPC in infrastructure projects (Patel and Shah in Open J Civ Eng 03:69–79, 2013, [2]). Furthermore, Python programming is an evolving trend in the field of civil engineering. The Python programming language has majorly influenced its purpose in the design and estimation fields, as well as certain management-related computing tasks (Bengfort and Bilbro in J Open Source Softw 4:1075, 2019, [3]). However, when compared to other technologies, the evolution of the programming language in concrete technology is less. The primary goal of this research is to predict high-performance concrete strength using Python programming. The compressive strength of the concrete is determined by only experimental means. But, this experimental process is time-consuming and acts as a boon to further processes. This programming with the preloaded data and features will make it easy to predict the strength by just providing certain details like composition and ratio to be used for concrete. For each and every entity entered, the programming language does a graphical analysis, which in turn helps to iterate the required results for the respective grade of concrete. Based on the cast and the programmed results, the optimum grade was found.
Prediction of High-Performance Concrete Strength Using Python Programming
This paper seeks and brings up combination of computer programming and the concrete technology. The high-performance concrete acts as a core in construction of infrastructure. The high-performance concrete is made with the usage of basic concrete components and admixtures, and it is both mineral and chemical admixtures. The use of admixtures, either mineral or chemical, or even both, improves the performance of the concrete (Neville and Tcin in High Performance concrete—an overview, 1998, [1]). In this present study, the basic components of concrete are used with the addition of some mineral admixtures like Metakaolin and Alco fine, which are used for the concrete grades of M80 and M100 (cast and tested). High-performance concrete performs better than high-strength concrete considering the mechanical properties, which leads to a trend in the usage of HPC in infrastructure projects (Patel and Shah in Open J Civ Eng 03:69–79, 2013, [2]). Furthermore, Python programming is an evolving trend in the field of civil engineering. The Python programming language has majorly influenced its purpose in the design and estimation fields, as well as certain management-related computing tasks (Bengfort and Bilbro in J Open Source Softw 4:1075, 2019, [3]). However, when compared to other technologies, the evolution of the programming language in concrete technology is less. The primary goal of this research is to predict high-performance concrete strength using Python programming. The compressive strength of the concrete is determined by only experimental means. But, this experimental process is time-consuming and acts as a boon to further processes. This programming with the preloaded data and features will make it easy to predict the strength by just providing certain details like composition and ratio to be used for concrete. For each and every entity entered, the programming language does a graphical analysis, which in turn helps to iterate the required results for the respective grade of concrete. Based on the cast and the programmed results, the optimum grade was found.
Prediction of High-Performance Concrete Strength Using Python Programming
Lecture Notes in Civil Engineering
Reddy, Krishna R. (editor) / Ravichandran, P. T. (editor) / Ayothiraman, R. (editor) / Joseph, Anil (editor) / Rohithraman, R. (author) / Ganapathy Ramasamy, N. (author) / Kannan Rajkumar, P. R. (author)
International Conference on Civil Engineering Innovative Development in Engineering Advances ; 2023 ; Kattankulathur, India
2024-01-31
12 pages
Article/Chapter (Book)
Electronic Resource
English
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