Buildings2015, 5(2), 581-596; doi:10.3390/buildings5020581 (registering DOI) - published 22 May 2015 Show/Hide Abstract
Abstract: In order to achieve a material and energy balance in buildings that is sustainable in the long run, there is an urgent need to assess the renewable and non-renewable resources used in the manufacturing process and to progressively replace non-renewable resources with renewables. Such progressive disinvestment in the non-renewable resources that may be substituted with renewable resources is referred to as “Renewable Substitutability” and if implemented, this process will lead to a paradigm shift in the way building materials are manufactured. This paper discusses the development of a Renewable Substitutability Index (RSI) that is designed to maximize the use of renewable resources in a building and quantifies the substitution process using solar emergy (i.e., the solar equivalent joules required for any item). The RSI of a building or a building component, i.e., floor or wall systems, etc., is the ratio of the renewable resources used during construction, including replacement and maintenance, to the building’s maximum renewable emergy potential. RSI values range between 0 and 1.0. A higher RSI achieves a low-energy building strategy promoting a higher order of sustainability by optimizing the use of renewables over a building’s lifetime from formation-extraction-manufacturing to maintenance, operation, demolition, and recycle.
Buildings2015, 5(2), 560-580; doi:10.3390/buildings5020560 (registering DOI) - published 21 May 2015 Show/Hide Abstract
Abstract: Integrating daylight and energy performance with optimization into the design process has always been a challenge for designers. Most of the building environmental performance simulation tools require a considerable amount of time and iterations for achieving accurate results. Moreover the combination of daylight and energy performances has always been an issue, as different software packages are needed to perform detailed calculations. A simplified method to overcome both issues using recent advances in software integration is explored here. As a case study; the optimization of external shadings in a typical office space in Australia is presented. Results are compared against common solutions adopted as industry standard practices. Visual comfort and energy efficiency are analysed in an integrated approach. The DIVA (Design, Iterate, Validate and Adapt) plug-in for Rhinoceros/Grasshopper software is used as the main tool, given its ability to effectively calculate daylight metrics (using the Radiance/Daysim engine) and energy consumption (using the EnergyPlus engine). The optimization process is carried out parametrically controlling the shadings’ geometries. Genetic Algorithms (GA) embedded in the evolutionary solver Galapagos are adopted in order to achieve close to optimum results by controlling iteration parameters. The optimized result, in comparison with conventional design techniques, reveals significant enhancement of comfort levels and energy efficiency. Benefits and drawbacks of the proposed strategy are then discussed.
Buildings2015, 5(2), 536-559; doi:10.3390/buildings5020536 (registering DOI) - published 21 May 2015 Show/Hide Abstract
Abstract: Because the student residences of the Vrije Universiteit Brussel built in 1973 are not adapted to current comfort standards, the university decided to construct new accommodation facilities at the border of the campus. However, besides demolition, there was no strategy on how to deal with the existing ones. In the search for a more sustainable strategy, the university’s administration assigned the TRANSFORM research team to define various design strategies and to assess the long-term environmental consequences in order to select the best strategy by the use of Life Cycle Environmental Assessment. Current Life Cycle Environmental Assessments generally include maintenance, repair, replacement and operational energy consumption during use, but do not include future refurbishments. However, it is likely that their impact cannot be neglected either. Therefore, this article offers a framework which takes future refurbishments into account, in addition to the standard use impacts: initial and end-of-life impact. We report on the construction assemblies, the results of the assessments conducted and the advice provided. The results confirm that the impact of future refurbishments cannot be neglected. In addition, we observed that there were significant environmental savings when transforming the residences compared to new construction, and long-term benefits of a design enabling the reuse of building elements.
Abstract: Sustainability and buildability requirements in building envelope design have significantly gained more importance nowadays, yet there is a lack of an appropriate decision support system (DSS) that can help a building design team to incorporate these requirements and manage their tradeoffs at once. The main objective of this study is to build such a tool to facilitate a building design team to take into account sustainability and buildability criteria for assessment of building envelopes of high-rise residential buildings in Singapore. Literature reviews were conducted to investigate a comprehensive set of the sustainability and buildability criteria. This also included development of the tool using a Quality Functional Deployment (QFD) approach combined with fuzzy set theory. A building design team was engaged to test the tool with the aim to evaluate usefulness of the tool in managing the tradeoffs among the sustainability and buildability criteria. The results from a qualitative data analysis suggested that the tool allowed the design team to effectively find a balance between the tradeoffs among the criteria when assessing multiple building envelope design alternatives. Main contributions of using this tool are achievement of a more efficient assessment of the building envelopes and more sustainable and buildable building envelope design.
Abstract: Green roofs improve building energy performance and constitute an alternative to sustainable buildings. A green roof model is dynamically coupled with a building thermal model to assess its energy performance that takes into account the indoor air temperature dynamic changes. Under the climate conditions in Antananarivo, we compared green and conventional roofs. The present study shows that green roofs protect the roof structure under extreme temperature and large temperature fluctuations. For the case of Antananarivo, the amplitude of the temperature fluctuations at the top face of the support is reduced by 28 °C when using green roof. The impact of the green roof on indoor air temperature and energy demand is investigated. The vegetation decreases the maximum indoor air temperature and improves the building thermal comfort during summer days. It has no effect on the minimum indoor air temperature, but additional soil thickness can increase it. In addition, a global sensitivity analysis, which is carried out on the proposed model without considering any specific weather data, allows us to identify the most influential parameters on the energy demand. It has been found that green roofs have almost insignificant thermal impact in insulated buildings; however, their potential prevails over the building envelope and weather characteristics in the case of non-insulated building.
Abstract: Currently, there is no manual blind control guideline used consistently throughout the energy modeling community. This paper identifies and compares five manual blind control algorithms with unique control patterns and reports blind occlusion, rate of change data, and annual building energy consumption. The blind control schemes detailed here represent five reasonable candidates for use in lighting and energy simulation based on difference driving factors. This study was performed on a medium-sized office building using EnergyPlus with the internal daylight harvesting engine. Results show that applying manual blind control algorithms affects the total annual consumption of the building by as much as 12.5% and 11.5% for interior and exterior blinds respectively, compared to the Always Retracted blinds algorithm. Peak demand was also compared showing blind algorithms affected zone load sizing by as much as 9.8%. The alternate algorithms were tested for their impact on American Society of Heating, Refrigeration and Air-Conditioning Engineers (ASHRAE) Guideline 14 calibration metrics and all models were found to differ from the original calibrated baseline by more than the recommended ±15% for coefficient of variance of the mean square error (CVRMSE) and ±5% for normalized mean bias error (NMBE). The paper recommends that energy modelers use one or more manual blind control algorithms during design stages when making decisions about energy efficiency and other design alternatives.