In this study, the building ventilation potentials were assessed at building group level. Exceedance probability analysis was applied to estimate the uncertainties associated with the influence of climate on wind environment. The criterion was proposed based on building facade pressures. Tw o typical residential building arrangements were investigated. Simulation results show that facade pressure based exceedance probability are efficient in assessing the natural ventilation potentials of building groups and building height variations are important for improving building natural ventilation potentials

Ding, Wowo

Tang, Lian

You, Wei

English

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Ventilation Potential Assessments for Residential Building Arrangements Based on Exceedance Probability Analysis

Syracuse University Research Facility and Collaborative Environment

Healthy, Intelligent and Resilient Buildings and Urban Environments7th International Building Physics ConferenceProceedingsibpc2018.org    #ibpc2018Ventilation Potential Assessments for Residential Building Arrangements Based on Exceedance Probability Analysis Wei You1, Lian Tang1 and Wowo Ding1,* 1 School of Architecture and Urban Planning, Nanjing University, Nanjing 210093, China *Corresponding email: dww@nju.edu.cnABSTRACT In this study, the building ventilation potentials were assessed at building group level. Exceedance probability analysis was applied to estimate the uncertainties associated with the influence of climate on wind environment. The criterion was proposed based on building facade pressures. Two typical residential building arrangements were investigated. Simulation results show that facade pressure based exceedance probability are efficient in assessing the natural ventilation potentials of building groups and building height variations are important for improving building natural ventilation potentials. KEYWORDS  Residential buildings, Ventilation potential, Exceedance probability, Facade wind pressure. INTRODUCTION Natural ventilation is a common adopted passive building design strategy. It can improve indoor thermal comfort and air quality by removing excess heat and airborne contaminants. Optimizing building natural ventilation design is not only related to building façade opening size and location, but also refers to the arrangements of buildings. Thus, the assessments of natural ventilation potentials require an investigation at building group level. For building natural ventilation, wind pressure distribution of building facade is an important boundary condition, as wind is the driving force. Many studies had investigated the indoor natural ventilation in terms of wind pressures for building groups. Tsutsumi et al. (1992) experimentally studied the wind pressure on a building surrounded by a group of buildings. The relations between average wind pressure coefficients and various layouts of buildings are discussed under different wind conditions. Similar studies were also carried out by Kim et al. (2012) and Shirzadi et al. (2018). In addition, Asfour (2010) investigated the effect of building layout patterns on ventilation potential of these buildings. Six hypothetical arrangements of buildings were assessed by calculating wind pressure difference. Bady et al. (2011) carried out wind tunnel experiments to study wind pressure characteristics on groups of buildings located within high density building arrays. The results all show that buildings configuration and wind direction are important factors in determining urban ventilation. However, most studies had investigated single building under typical wind directions.  For wind environment evaluation considering the uncertain upper wind parameters, some researches introduced the probability analysis into wind performance studies. This method estimates the probability of ventilation performance satisfying certain criteria. In past researches, probability analysis had most been applied in investigation of pedestrian-level wind environment, generally focusing on wind comfort/safety issues (Blocken and Persoon, 2009; Du et al. 2017). Recently, several researchers had introduced the probability concept into other wind performance area. Pietrzyk (2008) developed a probabilistic model and 14977th International Building Physics Conference, IBPC2018studied the problem of air infiltration in low-rise buildings. Bu et al. (2009) analyzed the exceedance probability of local air change rate and local kinetic energy for investigating the ventilation performance and thermal comfort within urban street canyons. This study attempted to introduce probability concept into wind-driven natural ventilation area for valuating natural ventilation potentials of building groups. Exceedance probability was calculated in terms of wind pressure on building facades. Two typical residential building arrangements, namely multi-story buildings and high-rise buildings, were adopted as the evaluation objects. The cases were located at a typical southeast monsoon wind city - Nanjing. And residential building units were investigated for natural ventilation potentials. To calculate building facade pressures, computational fluid dynamics (CFD) method with ANSYS-Fluent was adopted. The exceedance probabilities were post-processed by MATLAB and ArcGIS. RESIDENTIAL BUILDING GROUP CONFIGURATION A 3 x 3 building group were built for building arrangement analysis. The central group (CG) was the analysis unit, and surrounding units (SG) were arranged around the studied area as environmental conditions, as shown by Figure 1a. Road widths (Sr1, Sr2) were determined as 30m according to design code. Two residential building types were established for case comparison (Figure 1b-c). Case A was multi-storey building group (building height H=18m), and Case B was high-rise building group (H=36m). Building widths L and depth D were determined as 72 and 12m, respectively. Lateral spacing S were 12m, and north-south spacing was 24m and 48m for multi-storey and high-rise building group. Figure 1d shows the data extracted zones for probability calculation and comparison. W1-W6 numbered the south and north facade of living units. W0 and W7 numbered the east and west facade of living units. For vertical partition, multi-storey building was divide into three part, which represent the living unit at low, middle and high levels, and high-rise building was divide into six levels.  Figure 1. a) Building groups setting, b) Case A, c) Case B, d) Data extracted zones SG SG SG CG SG SG SG SG SG S L L L L S B1 B1 B1 B1 B2 B2 a) b) c) Sr1 Sr1 Sr2 Sr2 Low Middle High Low Middle High High1 High2 High3 W0 W7 E7 W1 W2 W3 W4 W5 W6 E6 E5 E4 E3 E2 E1 E0 W1 W2 W3 W4 W5 W6 E6 E5 E4 E3 E2 E1 W0 W7 E7 E0 North room South room N Multi-storey building High-rise building Living unit ID d)14987th International Building Physics Conference, IBPC2018EXCEEDANCE PROBABILITY CALCULATION FOR VENTIALION POTENTIALS The exceedance probability based building ventilation assessment consisted of three parts, as shown in Figure 2. The first part was the base data collection, which include weather data, building geometry data and wind flow data. The second part was MATLAB based data processing. In this step, wind data and façade pressure data were extract from the weather file and simulation results. Exceedance probability for each building façade were calculated by processing façade pressure data. At last, building façade geometry and the corresponding probability data were linked and by ArcGIS’s spatial join tool for further ventilation potential analysis. The probability distributions were also visualized for each studied surface. Figure 2. Flow chart of exceedance probability calculation Base data obtaining The wind climate of Nanjing was obtained from calibrating the hourly wind data of the solar and Wind Energy Resource Assessment (SWERA) weather file, which were download from EnergyPlus Weather Data (EPW) website. Building façade pressure data were obtained from CFD simulation results. The study referred to the AIJ (Architectural Institute of Japan) guidelines (Tominaga et al. 2008). For turbulence model selection, the Reynolds-Averaged Navier-Stokes (RANS) approach with standard k-ε model was adopted in this study due to its less time consumption and less complexity in boundary condition setting. Exceedance probability calculation The pressure based exceedance probability (Pg-EP) at each point above building facade was assumed to follow a two-parameter Weibull distribution in this study. And the Pg-EP for 12 azimuths was calculated as follow:                  ( )*12*1( ) ( )exp( )metk ig metg gi metP HP P P A iR C i(3)( )grefabs P HRV     (2) Where P(Pg>Pg*) is the probability of exceeding the specified Pg*. i is the wind direction number, and A(i) is the occurrence frequency, and K(i), C(i) are two parameters of Weibull distribution. Pg is the façade pressure extracted from CFD simulation results. Vref is the Weather data Building geometry CFD simulation Wind classify and wind rose make Façade Pressure data extraction Wind frequency and Weibull distribution parameter Exceedance probability calculation model Building ventilation potential post-analysis and visualization Base Data MATLAB Process ArcGIS Process Wind threshold calculation 14997th International Building Physics Conference, IBPC2018reference up wind speed at the height H. α, αmet, δ and δmet are the wind speed profile exponent and boundary layer thickness of the studied building located terrain and the weather station located terrain. Hmet is the wind measured height at the the weather station. RESULTS AND DISCUSSION Figure 3 showed the distributions of exceedance probability percentage (Pg-EP) on building facade for multi-story and high-rise buildings. In subplot (a)-(b), the facade Pg-EP distribution were viewed from southeast and in subplot (c)-(d), the Pg-EP distribution were viewed from northeast. The natural ventilation potentials of the building groups were clearly revealed by the Pg-EP distribution on each building facades. High-rise buildings obviously improved the building natural ventilation potentials, comparing with that of multi-story buildings. The variation range of Pg-EP was between 30% and 70% for high-rise buildings, while between 20% and 60% for multi-story buildings. For high-rise building group, the more ventilation living units were located at the first (south) and third (north) row, which the Pg-EPs of first row building’s south facade (Figure 3b) and the third row building’s north facade (Figure 3d) were almost above 60%. It was because the surrounding buildings were multi-story buildings, which wind can directly reach the up part of the high-rise building facades. For the multi-story building group (Figure 3a) and the middle row high-rise buildings (Figure 3b), the more ventilation living units were located at the building’s eastside. It was due to effect of southeast monsoon in summer. Due to the recirculation flow phenomenon, the middle level Pg-EPs of the multi-story buildings’ north facade increase (Figure 3c). It revealed the ventilation potentials of north living units at the third and fourth storey building are improved. Figure 3. Distributions of the exceedance probability percentage on building facades. More detailed quantitative analysis of natural ventilation potentials of the building groups was shown in Figure 4 and Figure 5. Figure 4 were the Pg-EP compassion of different height level residential units for multi-story and high-rise buildings. From the figure, it can be found that for the multi-story building group, the Pg-EPs were all below 50% (Figure 4a). And the natural ventilation potentials of low, middle and high levels of high-rise building units all increased, with Pg-EP around 50% (Figure 4b). It was due to the strengthen of air flow by the North North North North a) b) d) c) 15007th International Building Physics Conference, IBPC2018upper facade of the high-rise building. The natural ventilation potentials of higher levels (high1 high2 and high3) of high-rise buildings were improved greatly due to the less effect of surrounding buildings. The Pg-EPs of these areas were all generally above 50% (Figure 4c). In terms of the positions of residential units at one storey, ventilation potentials of side units are better than that of middle units, and ventilation potentials of east side units are better than that of west side units. It is more obviously reflected within the multi-story building group. Figure 5 shows the Pg-EPs of south and north units for multi-story and high-rise buildings. The simulation results showed that Pg-EPs of north units were slightly better than that of south room for multi-story building. It was due to the turbulence flow, which acted on the north facade of the multi-story residential building, which discussed above. Figure 4. Comparison of different living-unit levels for multi-story and high-rise buildings. Figure 5. Comparison of living-unit facade directions for multi-story and high-rise buildings. 15017th International Building Physics Conference, IBPC2018CONCLUSIONS This paper provided a simple method to assess building group’s natural ventilation potentials considering the effect of local wind climate. The cases studies show that, by calculation the exceedance probability of wind pressure on building facades, the natural ventilation potentials of building group can be revealed for each living units. Two typical residential building arrangements were investigated using the façade pressure based exceedance probability. Simulation results show that high-rise buildings could obviously improve the building’s natural ventilation potentials by increasing Pg-Eps of around 20%, comparing to that of the same levels (1-6 storey) of multi-story buildings. In southeast monsoon regions, the ventilation potentials of eastside living units is indeed improved especially for multi-story buildings. The Pg-Eps could increase by about 10%. And the ventilation of north façade living units could also be beneficial by the turbulence flows. This study is a preliminary test of using façade pressure based exceedance probability as an indicator for assessing of building natural ventilation potentials. Only two typical residential building groups were investigated. In the following study, more building arrangement cases will be evaluated to provide design strategies for architects. ACKNOWLEDGEMENT The project is supported by the National Natural Science Foundation of China (Nos.51508262 and 51538005). REFERENCES  Blocken B. and Persoon J. 2009. Pedestrian wind comfort around a large football stadium in an urban environment: CFD simulation, validation and application of the new Dutch wind nuisance standard. Journal of Wind Engineering and Industrial Aerodynamics, 97, 255-270 Du Y.X, Mak C.M, Kwok K, Tse K-T, Lee T-C, Ai Z.T, Liu J.L, and Niu J.L. 2017. New criteria for assessing low wind environment at pedestrian level in Hong Kong. Building and Environment, 123, 23-36 Bady M, Kato S, Takahashi T, and Huang H. 2011. Experimental investigations of the indoor natural ventilation for different building configurations and incidences. Building and Environment, 46, 65-74 Shirzadi M, Naghashzadegan M, and Mirzaei P.A. 2018. Improving the CFD modelling of cross-ventilation in highly-packed urban areas. Sustainable Cities and Society, 37, 451–465 Asfour, O.S. 2010. Prediction of wind environment in different grouping patterns of housing blocks. Energy and Buildings, 42, 2061–2069. Tsutsumi J, Katayama T, and Nishida M. 1992. Wind tunnel tests of wind pressure on regularly aligned buildings. Journal of Wind Engineering and Industrial Aerodynamics, 43, 1799-1810 Kim Y.C, Yoshida A, and Tamur Y. 2012. Characteristics of surface wind pressures on low-rise building located among large group of surrounding buildings. Engineering Structures, 35,18-28. Pietrzyk K, Hagentoft C-E. 2008. Probabilistic analysis of air infiltration in low-rise buildings. Building and Environment, 43(4), 537–49. Bu Z, Kato S, Ishida Y, and Huang H. New criteria for assessing local wind environment at pedestrian level based on exceedance probability analysis. Building and Environment, 44, 1501-1508 Tominaga, Y.; Mochida, A.; Yoshie, R.; Kataoka, H.; Nozue, H.; Yoshikawa, M.; Shirasawa, T. 2008. AIJ guidelines for practical applications of CFD to pedestrian wind environmentaround buildings. Journal of Wind Engineering and Industrial Aerodynamics, 96, 1749-176115027th International Building Physics Conference, IBPC2018

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Ventilation Potential Assessments for Residential Building Arrangements Based on Exceedance Probability Analysis

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