Showing 2 results for Sanaieian
Sahar Rahimifar, Abbas Tarkashvand, Haniyeh Sanaieian,
Volume 33, Issue 2 (4-2023)
Abstract
In recent years, optimizing the energy consumption of buildings has become one of the important environmental and economic goals in sustainable architecture and urban planning. A group of factors affecting the energy consumption of buildings is their physical characteristics and form. In this regard, in the present research, the effect of volumetric porosity in high-rise buildings on their energy consumption has been investigated. The purpose of this research is to explain the correlation between the volumetric porosity of a building, as an independent variable, and its cooling and heating load, as a dependent variable, in a high-rise residential complex in Tehran. In this regard, first, a modular-generative model has been created in the Grasshopper plugin of Rhino software, which can create a porosity of 0 to 50% parametrically. Then, the cooling and heating load of each of the produced models in the city of Tehran and on the June 21 (summer solstice) and December 21 (winter solstice) were calculated using the Honeybee plugin, with standard settings. The data obtained from the simulation were entered into the SPSS software environment and the correlation test of the percentage of volume porosity and energy consumption was performed on the two aforementioned dates in Tehran. In order to validate the research method, this process was performed in 3 other climatic zones of Iran and the findings were compared with other studies in this field. The results of this research showed that the increase in porosity, assuming the number of modules is kept constant (the total volume of the building remains constant) and the site coverage ratio - as is common and inevitable in high-rise buildings - have a significant positive correlation with increased energy consumption in high-rise residential buildings in Tehran.
Ali Izadi, Shahram Minooee Sabery, Forough Farazjou, Haniyeh Sanaieian,
Volume 33, Issue 3 (8-2023)
Abstract
In recent years, increasing attention has been given to improving the energy efficiency of buildings in order to reduce their environmental impact and operational costs. As a result, multi-objective optimization methods have become an important tool for optimizing building energy performance. This research reviews building performance analysis approaches in a comparative method and results in a systematic overview of the existing multi-objective optimization methods used in the field of building energy performance. This review covers a wide range of optimization techniques, including genetic algorithms (NSGA-II), evolutionary algorithms, particle swarm intelligence algorithms, and other metaheuristic approaches. Furthermore, the review provides a comprehensive analysis of the strengths and weaknesses of each method in different fields such as daylight, ventilation, and thermal performance analysis. In order to achieve the aims of the research alongside reviewing the Scopus scientific database, various relevant studies were investigated. Eventually, this study provides. Eventually, this review identifies gaps in the literature potential in research directions and proposes multiple ways for future research.
