{"title":"利用灰泥的化学和物理特性预测强度活性指数","authors":"Farzaneh Elyasigorji, Habib Tabatabai","doi":"10.1016/j.cement.2024.100116","DOIUrl":null,"url":null,"abstract":"<div><div>Reductions in cement use have essential benefits in reducing the embodied energy in concrete and CO<sub>2</sub> emissions. Hence, effective assessment of potential pozzolanic materials is highly desirable to facilitate usage as sustainable supplementary cementitious materials (SCMs). However, assessment of pozzolanic reactivity using conventional experimental tests is typically time-consuming and expensive. Pozzolanic reactivity is mainly related to the chemical and physical characteristics of various pozzolans, such as amorphous silica and alumina contents and specific surface area. This study develops and presents an equation that can predict the strength activity index (SAI) as an indirect method for the assessment of potential pozzolans and their strength outcome using their chemical and physical properties. The development of a prediction equation not only saves time and resources but also helps with designing optimized and improved pozzolanic SCMs. The strength activity index (SAI) of seven different materials with varying pozzolanic properties was measured at an age of 90 days. The powdered test materials included pottery cull, brick powder, lightweight aggregate fines, glass powder, silica fume, dolostone, and Class C fly ash. In the second stage, correlation analyses were performed to find parameters (based on chemical and physical properties) that were highly correlated with SAI. An equation was then developed as a function of the chemical and physical properties of raw pozzolanic materials using an optimization tool. Consequently, an equation predicting SAI was derived which had a high degree of correlation (<em>R</em> = 0.972) with measured SAI.</div></div>","PeriodicalId":100225,"journal":{"name":"CEMENT","volume":"18 ","pages":"Article 100116"},"PeriodicalIF":0.0000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S2666549224000252/pdfft?md5=dc7fd71feb2a2f82cde2b54621e27a7c&pid=1-s2.0-S2666549224000252-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Prediction of strength activity index using chemical and physical properties of pozzolans\",\"authors\":\"Farzaneh Elyasigorji, Habib Tabatabai\",\"doi\":\"10.1016/j.cement.2024.100116\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Reductions in cement use have essential benefits in reducing the embodied energy in concrete and CO<sub>2</sub> emissions. Hence, effective assessment of potential pozzolanic materials is highly desirable to facilitate usage as sustainable supplementary cementitious materials (SCMs). However, assessment of pozzolanic reactivity using conventional experimental tests is typically time-consuming and expensive. Pozzolanic reactivity is mainly related to the chemical and physical characteristics of various pozzolans, such as amorphous silica and alumina contents and specific surface area. This study develops and presents an equation that can predict the strength activity index (SAI) as an indirect method for the assessment of potential pozzolans and their strength outcome using their chemical and physical properties. The development of a prediction equation not only saves time and resources but also helps with designing optimized and improved pozzolanic SCMs. The strength activity index (SAI) of seven different materials with varying pozzolanic properties was measured at an age of 90 days. The powdered test materials included pottery cull, brick powder, lightweight aggregate fines, glass powder, silica fume, dolostone, and Class C fly ash. In the second stage, correlation analyses were performed to find parameters (based on chemical and physical properties) that were highly correlated with SAI. An equation was then developed as a function of the chemical and physical properties of raw pozzolanic materials using an optimization tool. 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引用次数: 0
摘要
减少水泥用量对降低混凝土的内含能耗和二氧化碳排放量有着至关重要的益处。因此,对潜在的胶凝材料进行有效评估,以促进其作为可持续胶凝补充材料 (SCM) 的使用,是非常可取的。然而,使用传统的实验测试评估水青酸反应性通常既耗时又昂贵。胶凝反应性主要与各种胶凝剂的化学和物理特性有关,如无定形二氧化硅和氧化铝含量以及比表面积。本研究开发并提出了一个可以预测强度活性指数(SAI)的方程,作为一种间接方法,利用其化学和物理特性来评估潜在的胶凝剂及其强度结果。该预测方程的开发不仅节省了时间和资源,而且有助于设计优化和改良的胶凝单体材料。在 90 天的龄期内,测量了七种不同材料的强度活性指数(SAI),这些材料具有不同的水泥酚醛特性。粉状测试材料包括陶粒、砖粉、轻集料细粉、玻璃粉、硅灰、白云石和 C 级粉煤灰。在第二阶段,进行了相关性分析,以找到与 SAI 高度相关的参数(基于化学和物理特性)。然后,使用优化工具建立了一个等式,该等式是原始混合材料化学和物理特性的函数。因此,得出了一个预测 SAI 的等式,该等式与测得的 SAI 高度相关(R = 0.972)。
Prediction of strength activity index using chemical and physical properties of pozzolans
Reductions in cement use have essential benefits in reducing the embodied energy in concrete and CO2 emissions. Hence, effective assessment of potential pozzolanic materials is highly desirable to facilitate usage as sustainable supplementary cementitious materials (SCMs). However, assessment of pozzolanic reactivity using conventional experimental tests is typically time-consuming and expensive. Pozzolanic reactivity is mainly related to the chemical and physical characteristics of various pozzolans, such as amorphous silica and alumina contents and specific surface area. This study develops and presents an equation that can predict the strength activity index (SAI) as an indirect method for the assessment of potential pozzolans and their strength outcome using their chemical and physical properties. The development of a prediction equation not only saves time and resources but also helps with designing optimized and improved pozzolanic SCMs. The strength activity index (SAI) of seven different materials with varying pozzolanic properties was measured at an age of 90 days. The powdered test materials included pottery cull, brick powder, lightweight aggregate fines, glass powder, silica fume, dolostone, and Class C fly ash. In the second stage, correlation analyses were performed to find parameters (based on chemical and physical properties) that were highly correlated with SAI. An equation was then developed as a function of the chemical and physical properties of raw pozzolanic materials using an optimization tool. Consequently, an equation predicting SAI was derived which had a high degree of correlation (R = 0.972) with measured SAI.