An efficient method of evaluating large scale urban residential skylight environment and an empirical study of Beijing main area

A good skylight environment in urban residential areas is an important component of a healthy city,and has always been highly valued.With the rapid development of new-type urbanization,the density of buildings continues to increase,and megacities have entered the stage of stock transformation.An effective method for evaluating the skylight environment of large-scale urban residential areas is urgently needed.However,there is still a lack of empirical research methods and cases of large-scale residential skylight environment.In this regard,this article takes the megacity Beijing as the research object,and proposes an efficient analysis method of residential skylight environment that integrates multiple real-world data at city scale.In terms of data,it collects and integrates 3D data of urban-scale building space and residential boundary data;in terms of algorithm,Sky View Factor(SVF)is used as the evaluation index of residential skylight environment,and an efficient analysis method of urban-scale skylight environment based on cloud parallel simulation is realized.Through analysis,it is found that:(1)the average SVF value of Beijing residential area is 61%,which means that its skylight quality is in general level;(2)the skylight environment of Beijing residential area is distributed in a circle,and there are 4 types of skylight environment quality residential areas;(3)The skylight environment of Beijing residential area is relatively weakly related to the distance from the residential area to the city center and the average height of the residential buildings,and is closely related to the plot volume ratio,the residential building density and the shading from surrounding buildings.The highlight of this study lies in the empirical research on the skylight environment of mega-city residential areas that incorporates multiple real data for the first time,which can promote the study of skylight environment on a city scale and provide a reference for the updating of Beijing’s residential daylight environment.

Research on the influence of outdoor trees on natural ventilation performance of an academic building

Planting trees around buildings has always been used as one of the most common viable landscaping strategies in schools.However,the impact of trees on natural ventilation inside the building has been neglected without investigation.The emphasis of this study related to the impact of outdoor trees around the academic building on indoor ventilation.Numerical simulations of the indoor wind environment of the academic building affected by trees were performed utilizing the k-εmodel with additional source terms.The numerical model was also validated by measured data.Two kinds of trees were selected,they are camphor and metasequoia.Camphor is a kind of broad-leaved tree and metasequoia is a kind of coniferous tree.26 simulation cases with six different tree canopy spacings were conducted.These results showed that the outdoor trees had great influences on the natural ventilation performance of the academic building.Compared with the case without the trees,the highest decrement in ventilation flow rate could be up to 31.97%in this study.For the cases of classrooms with horizontal distribution,the ages of air of the classrooms became fresher with the increase of the canopy spacing.While for the cases of classrooms with vertical distribution,the canopy spacing had fewer effects on the natural ventilation performances.It was also found that the blocking effects of camphor on indoor ventilation were higher than that of metasequoia.The average ventilation flow rate in cases with metasequoia was increased by 14.89%compared to the cases with camphor.This study could provide guidance for the layout design of trees around the building.

A preference-based multi-objective building performance optimization method for early design stage

A large number of cases show that the multi-objective optimization method can significantly improve building performance.The method for multi-objective building performance optimization(BPO)design has achieved rapid development in recent years.However,the BPO method still needs to be improved.Specifically,weak interaction between the optimization process and the decision-making process results in low optimization efficiency,which limits the widespread application of the optimization method in early design stage.In this paper,a new interactive BPO mode is explored to strengthen the interaction between the optimization process and decisionmaking process,and a preference-based multi-objective BPO method is proposed to account for designers'decision preferences during the optimization process,making the objective more controllable,improving the optimization efficiency and ensuring the diversity of solutions.Firstly,this paper illustrates the proposed method in detail,defines the concept of performance preference,expounds the flow of the preference-based multi-objective optimization algorithm,and proposes three indicators to evaluate the algorithm,which includes convergence speed,preference satisfaction rate,and diversity measurement.Secondly,through testing and comparison,it is found that the proposed preference-based algorithm has advantages over the non-preference optimization algorithm(represented by the NSGA-II algorithm).The proposed method leads to faster convergence and higher preference satisfaction,so it is more suitable for the BPO process in the early design stage.Specially,the proposed method can achieve 100%preference satisfaction rate with only 2400 simulations,while the non-preference method can only achieve 20%preference satisfaction rate after 5800 simulations.In this paper,a preference-based multi-objective BPO method is proposed to make the optimization process closely interact with the decision-making process and make the design preferences be accounted during the BPO process,thereby improving the optimization efficiency.In addition,this study first proposes two indicators to measure the quality of optimization results:preference satisfaction rate and diversity measurement.This study aims to guide the development of BPO methods towards providing high satisfaction rate and high quality optimization results.