Properties and Performance of Concrete Materials and Structures

Smarzewski, Piotr; Stolarski, Adam

doi:10.3390/cryst12091193

Cited by 3 publications

(3 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…High performance concrete (HPC) is a concrete based on a cement matrix with natural aggregate and added additives and admixtures, which is distinguished by, among others, good workability for at least 1 h, compressive strength over 60 MPa at 28 days, and water/binder ratio less than 0.4. In order to obtain a tighter structure of the mixture, micro-fillers and nanoparticles are used, e.g., fly ash, silica fume, ground granulated blast furnace slag, metakaolin, and nano-silica [1][2][3][4][5][6][7][8][9][10]. Compared to normal strength concrete, HPC has a more homogeneous and dense structure with a smaller number of pores and shrinkage cracks occurring.…”

Section: Introductionmentioning

confidence: 99%

Mechanical and Microstructural Studies of High Performance Concrete with Condensed Silica Fume

Smarzewski

2023

Applied Sciences

View full text Add to dashboard Cite

This article is an extended version of the conference paper “Influence of silica fume on mechanical and fracture properties of high performance concrete” published in Procedia Structural Integrity as a part of the Special Issue for the 3rd International Conference on Structural Integrity (ICSI 2019). Tests were carried out to evaluate the compressive strength, tensile splitting strength, modulus of elasticity, flexural strength, and fracture properties of high performance concretes (HPC) having different levels of condensed silica fume (CSF) replacements for cement. It was found that CSF replacement for cement by up to 25% may have a favorable effect on the mechanical properties. HPC containing CSF was characterized by quite large increases in compressive strength (up to 14%) and flexural strength (16%). However, the most significant improvements in mechanical properties were obtained for splitting tensile strength (26%) and fracture energy (30.5%). There were slight reductions up to 2% in the elastic modulus, flexural strength and fracture properties at the 25% level of CSF substitution for cement. Microstructural studies showed that the narrowest microcracks and the smallest pores in the interfacial transition zone (ITZ) between the paste and grains of aggregate occurred in the HPC having 10% CSF. In addition, a reduction of ITZ around the aggregate and the formation of more high-strength hydration products was observed in all CSF-added HPCs. The outcomes reported that CSF can successfully replace cement. It is suggested that the substitution should not exceed 20%.

show abstract

Section: Introductionmentioning

confidence: 99%

Mechanical and Microstructural Studies of High Performance Concrete with Condensed Silica Fume

Smarzewski

2023

Applied Sciences

View full text Add to dashboard Cite

show abstract

“…Concrete is one of the most crucial and ancient construction materials used in the construction industry [1]. The primary raw materials for concrete construction include cement, water, sand, and aggregates.…”

Section: Introductionmentioning

confidence: 99%

Performance Comparison of Machine Learning Models for Concrete Compressive Strength Prediction

Sah,

Hong

2024

Materials

View full text Add to dashboard Cite

This study explores the prediction of concrete compressive strength using machine learning models, aiming to overcome the time-consuming and complex nature of conventional methods. Four models—an artificial neural network (ANN), a multiple linear regression, a support vector machine, and a regression tree—are employed and compared for performance, using evaluation metrics such as mean absolute deviation, root mean square error, coefficient of correlation, and mean absolute percentage error. After preprocessing 1030 samples, the dataset is split into two subsets: 70% for training and 30% for testing. The ANN model, further divided into training, validation (15%), and testing (15%), outperforms others in accuracy and efficiency. This outcome streamlines compressive strength determination in the construction industry, saving time and simplifying the process.

show abstract

“…Concrete is one of the most crucial and ancient construction materials used in the construction industry (Smarzewski & Stolarski, 2022). The primary raw materials for concrete construction include cement, water, sand, and aggregates.…”

Section: Introductionmentioning

confidence: 99%

Estimation of Concrete Compressive Strength Using Machine Learning

Hong,

Sah

2024

Preprint

View full text Add to dashboard Cite

This study explores the prediction of concrete compressive strength using machine learning models, aiming to overcome the time-consuming and complex nature of conventional methods. Four models—Artificial Neural Network, Multiple Linear Regression, Support Vector Machine, and Regression Tree—are employed and compared for performance. Evaluation metrics such as Mean Absolute Deviation, Root Mean Square Error, Coefficient of Correlation, and Mean Absolute Percentage Error are used. After preprocessing 1030 samples, the dataset is split into 70% for training and 30% for testing. The ANN model, further divided into training, validation (15%), and testing (15%), outperforms others in accuracy and efficiency. This outcome streamlines compressive strength determination in the construction industry, saving time and simplifying the process.

show abstract

Properties and Performance of Concrete Materials and Structures

Abstract: Concrete is one of the ancient and most widely used construction material [...]

Cited by 3 publications

References 12 publications

Mechanical and Microstructural Studies of High Performance Concrete with Condensed Silica Fume

Mechanical and Microstructural Studies of High Performance Concrete with Condensed Silica Fume

Performance Comparison of Machine Learning Models for Concrete Compressive Strength Prediction

Estimation of Concrete Compressive Strength Using Machine Learning

Contact Info

Product

Resources

About