Automated Author ProfileFarage, Michele C. R.
Farage, Michele C. R.
Current S-Index
Sum of Dataset Indices for all datasets
Average Dataset Index per Dataset
Average Dataset Index per dataset
Total Datasets
Total datasets for this author
Average FAIR Score
Average FAIR Score per dataset
Total Citations
Total citations to the author's datasets
Total Mentions
Total mentions of the author's datasets
S-Index Interpretation
The S-Index (Sharing Index) is a comprehensive metric that represents the cumulative impact of all your datasets. It is calculated as the sum of Dataset Index scores across all your claimed datasets.
What it means:
- A higher S-index indicates greater overall impact of your datasets relative to typical datasets in their fields of research
- The S-Index grows as you add more datasets or as existing datasets gain more citations and mentions
- It provides a single number to track your research data impact over time
Current S-Index: 2.4 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Abstract Compressive strength and Young’s modulus are the main properties used in the design of concrete structures. They are responsible for the cost, safety and dimensioning of the structure, and are generally measured in expensive and time-demanding tests. This fact encourages researches for fast and cost-effective methods to investigate the concrete’s properties. Among the concrete types, structural Lightweight Aggregate Concrete (LWAC) is one of the most employed worldwide, but it presents limited studies and mix design techniques. Thus, this work evaluates and compares the performances of two methods to predict the compressive strength of LWAC samples: Support Vector Machine and Finite Element Method. To this end, both strategies use the LWAC’s mix proportions and the Young’s modulus, and the compressive strength of mortars and aggregates obtained from an experimental program from the literature. The results encourage further researches towards the development of a numerical tool that may assist engineers for practical purposes, since both methods show good agreement with the validation data.
Authors
- Aldemon L. Bonifácio ;
- Mendes, Julia C. ;
- Farage, Michele C. R. ;
- Barbosa, Flavio S. ;
- Barbosa, Ciro B. ;
- Anne-Lise Beaucour
Abstract Compressive strength and Young’s modulus are the main properties used in the design of concrete structures. They are responsible for the cost, safety and dimensioning of the structure, and are generally measured in expensive and time-demanding tests. This fact encourages researches for fast and cost-effective methods to investigate the concrete’s properties. Among the concrete types, structural Lightweight Aggregate Concrete (LWAC) is one of the most employed worldwide, but it presents limited studies and mix design techniques. Thus, this work evaluates and compares the performances of two methods to predict the compressive strength of LWAC samples: Support Vector Machine and Finite Element Method. To this end, both strategies use the LWAC’s mix proportions and the Young’s modulus, and the compressive strength of mortars and aggregates obtained from an experimental program from the literature. The results encourage further researches towards the development of a numerical tool that may assist engineers for practical purposes, since both methods show good agreement with the validation data.
Authors
- Aldemon L. Bonifácio ;
- Mendes, Julia C. ;
- Farage, Michele C. R. ;
- Barbosa, Flavio S. ;
- Barbosa, Ciro B. ;
- Anne-Lise Beaucour