Automated Author ProfileAntônio César Silveira Baptista Da Silva
Antônio César Silveira Baptista Da Silva
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: 2.3 (sum of 2 datasets Dataset Index scores)
More information here.
S-Index Over Time
Cumulative Citations Over Time
Cumulative Mentions Over Time
Datasets
Abstract The building sector's high energy consumption and the consequent emissions of greenhouse gases has led the European Union to publish, in 2010, the 2010/31/EU Directive, determining that by the end of 2020 all new buildings should be nearly Zero Energy Buildings (nZEB). One possible way to achieve this goal is the implementation of the Passive House concept. The aim of this paper is to analyse the efficiency level of the envelope of a Passive House through using the simulation method RTQ-R (Technical Code of the Quality of the Energy Efficiency Level of Residential Buildings). The analysis is performed for the building according to the code's assumptions (naturally ventilated and artificially air conditioned), and using a mechanical ventilation system with heat recovery capacity (MVHR). Firstly, the building was classified as level B, due to the air conditioner's high consumption for heating, and, when using the MVHR system, the building was classified as Level A. In a comparative analysis of energy consumption, the system showed an economy of 56.63% for the MVHR when compared with the air conditioning system. Thus, this study has proven the success of the application of the Passive House concept for bioclimatic zone 2 (ZB2).
Authors
- Dalbem, Renata ;
- Cunha, Eduardo Grala Da ;
- Vicente, Romeu ;
- Figueiredo, António José ;
- Antônio César Silveira Baptista Da Silva
Abstract The building sector's high energy consumption and the consequent emissions of greenhouse gases has led the European Union to publish, in 2010, the 2010/31/EU Directive, determining that by the end of 2020 all new buildings should be nearly Zero Energy Buildings (nZEB). One possible way to achieve this goal is the implementation of the Passive House concept. The aim of this paper is to analyse the efficiency level of the envelope of a Passive House through using the simulation method RTQ-R (Technical Code of the Quality of the Energy Efficiency Level of Residential Buildings). The analysis is performed for the building according to the code's assumptions (naturally ventilated and artificially air conditioned), and using a mechanical ventilation system with heat recovery capacity (MVHR). Firstly, the building was classified as level B, due to the air conditioner's high consumption for heating, and, when using the MVHR system, the building was classified as Level A. In a comparative analysis of energy consumption, the system showed an economy of 56.63% for the MVHR when compared with the air conditioning system. Thus, this study has proven the success of the application of the Passive House concept for bioclimatic zone 2 (ZB2).
Authors
- Dalbem, Renata ;
- Cunha, Eduardo Grala Da ;
- Vicente, Romeu ;
- Figueiredo, António José ;
- Antônio César Silveira Baptista Da Silva