Impact of Wind Pressure Coefficients on the Natural Ventilation Effectiveness of Buildings through Simulations
Abstract
:1. Introduction
Research Scope and Methodology
2. Review of Air Infiltration and Ventilation Studies
2.1. Ventilation Thresholds
2.2. Assessing Natural Ventilation Performance
Airflow Network Models
3. Natural Ventilation Effectiveness (NVE)—Building Performance Metric
3.1. Minimum Airflow Rate
3.2. Required Airflow Rate
3.3. Available Airflow Rate
4. Simulation Method
4.1. Reference Building and Measured Data
4.2. I-MA—Building Energy Simulation (BES) Model
Cp Source | Primary or Direct | Secondary or Indirect | |
---|---|---|---|
i | E+ values (default values) Swami and Chandra [68] | x | |
iia iib iic | Cloud-based platform—simulator [86] Terrain type: Very flat (Vf) * Terrain type: Open country (Oc) * Terrain type: Suburban (Su) * | x x x | |
iii | AIVC database [64] | x | |
iv | TPU database [67] | x |
Case | Considered Options | Z0 [m] | Zref [m] | Uref [m/s] |
---|---|---|---|---|
1. Very flat terrain | iia | 0.0025 | 250 | 40 |
2. Open country | iib | 0.025 | 350 | 40 |
3. Suburban | iic | 0.25 | 450 | 40 |
4. Urban | - | 2.5 | 550 | 40 |
4.2.1. NVE—Required Airflow Rate (Cooling Loads—)
4.2.2. NVE—Available Airflow Rate ()
4.3. Cp Simulator
5. Values Considered in the E+ AFN Model
5.1. Primary Source—Cloud-Based Platform—Cp Simulator
5.2. Secondary Sources
5.3. Cp Impact over Predicted Temperatures and ACH
6. NVE Effectiveness
7. Research Constraints and Remarks
8. Conclusions
- The method of applying the Natural Ventilation Effectiveness (NVE) as a performance metric supports the design of naturally ventilated buildings. It provides quantitative data on NV performance and offers interactive feedback during project development based on BES airflow networks;
- The cloud-based platform (CpSimulator) appears to be a reliable source, representing a significant contribution to the BES community. It allows for the generation of primary wind pressure coefficient data for natural ventilation investigations (AFN E+) by employing external CFD resources. Thus, researchers and designers are better assisted when making preliminary design decisions for buildings with natural ventilation;
- The impact of different values on NVE performance was only 3% for the small building used in this study. In such cases, using secondary sources, such as the one implemented in E+ AFN, seems to be more convenient. Primary sources may be required for more complex buildings, which can be more easily obtained through the CpSimulator platform, for example.
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
Abbreviations
References
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Country/State | Standard | Whole Building Ventilation Rates |
---|---|---|
Brazil | ANVISA—RE n° 176, de 24 de outubro de 2000 [28] | The adequate air renewal rate for air conditioning environments (Workspaces): (1) 27 m3/h person; (2) 17 m3/h person for stores, shopping centers, and other places where the occupancy rate per m2 is critical. |
Europe | EN 16798-1 [29] | Continuous flow rate with occupancy: (1) 0.42 L/s.m2; (2) 7 L/s person in living and bedroom; (3) 1 L/m2 for living and bedroom floor areas. Without occupancy: 0.05 L/s.m2–0.1 L/s.m2 |
Finland | NBC—D2 [30] | >0.4 h−1 General rule: Outdoor airflow should be at least 0.35 L/s.m2 (1.26 m3/h.m2) |
France | Arrêté du 24 Mars 1982. Modifié par arrêté du 28 octobre 1983 relatif à l’aération des logements [31] | Continuous ventilation must be assured during winter Total minimum flow assured for whole dwelling with regulation control device: 9.72 L/s (35 m3/h)–37.5 L/s (135 m3/h)—1- to 7-room house. Total minimum flow assured for whole dwelling with mechanical ventilation and control device: 2.77 L/s (10 m3/h)–9.72 L/s (35 m3/h)—1- to 7-room house |
Germany | DIN 1946-6 [32] | Mechanical ventilation is required if the necessary air volume flow for moisture-proofing exceeds the infiltration air volume flow Demand-controlled ventilation specifies four levels for fan air flow: Pos 1, protection against humidity— 4.16 L/s (15 m3/h)–23.6 L/s (85 m3/h)—30 m2–210 m2; Pos 2, reduced ventilation— 11.11 L/s (40 m3/h)–41.66 L/s (150 m3/h)—30 m2–210 m2; Pos 3, nominal ventilation; 15.27 L/s (55 m3/h)–59.72 L/s (215 m3/h)—30 m2–210 m2; Pos 4, intensive ventilation— 19.44 L/s (70 m3/h)–79.16 L/s (285 m3/h)—30 m2–210 m2 |
Greece | Greek Legislative Framework Document (as cited in [33]) | Detached houses, estimated five persons/100 m2 of floor area. Block of flats, estimated seven persons/100 m2 of floor area. |
India | Low Energy Cooling and Ventilation [34] | Design charts that correlate airflow rates from 0 to 1.2 (m3/s) and free area of openings from 0 to 8 (m2) Application examples: desired ventilation rates (m3/s) for different room types (master bedroom—MB, small bedroom—SB, hall + open kitchen—HK) for eight cities (climates) and two case study apartments MB: 0.09–0.35 (case 1), 0.13–0.53 (case 2) SB: 0.08–0.32 (case 1), 0.09–0.36 (case 2) HK: 0.48–1.06 (case 1), 0.51–1.14 (case 2) |
Italy | Ministerial Decree 05.07.75 [35] | Naturally ventilated dwelling 0.35–0.5 h−1 |
Netherlands | Building Decree (as cited in [33]) | 300 m3/h |
Norway | Norwegian Building Code [36] | Not less than 0.5 h−1 |
Passivhaus | Standard Passivhaus [37,38] | 8.33 L/s–8.88 L/s (30–32 m3/h) per person Controlled ventilation depending on the occupancy |
Portugal | NP 1037-1 Standard for natural ventilation [39] | 1.0–4.0 h−1: depending on the room type |
Sweden | Swedish Building Regulations BBR94 [40] | Rooms shall have a continuous 0.35 L/s/m2 floor area (1.26 m3/h/m2) when in use. This corresponds to 0.5 h−1 in a room with a height of 2.5 m. |
Switzerland | SIA 180, 2014 SIA 382/2, 1992 (as cited in [33]) | 12–15 m3/h/person (non-smoking, max CO2 1500 ppm) 30–70 m3/h/person (smoking) 25–30 m3/h/person (non-smoking, max CO2 1000 ppm). Air change rate in unoccupied rooms more than 0.3 h−1. |
UK | Approved Doc. F Ventilation 2010 [41] | 13 L/s–29 L/s: 1- to 5-room house. The whole ventilation flow rate is always higher than 0.3 L/s m2. If dwelling permeability is 5 m3/(h m) to 50 Pa, it takes 0.15 ACH as the infiltration rate, which will be subtracted from the total ventilation rate. |
US | ASHRAE Standard 62-1-2019 [42] | 2.5 L/s person, 0.3 L/s m2 |
Database | Air Infiltration and Ventilation Centre (AIVC) [64] Data are presented for wind attack angles from 0° to 315° (45° range) for low-rise and high-rise buildings ASHRAE Handbook of fundamentals (Airflow around buildings) [66] Data are presented for wind attack angles from 0° to 180° (45° range) for low-rise/high-rise buildings Tokyo Polytechnic University (TPU) Aerodynamic database of low-rise buildings [67] Data are presented for wind attack angles from 0° to 90° (15° range) for different buildings examples (web-based application tool) |
Analytical models | Swami and Chandra [68] One equation for low-rise buildings (from eight different investigators) and another for high-rise buildings (one source) CPCALC + [69,70] This is a program developed within the PASCOOL program as an upgrade of the CpCalc [71], an integrated module of the multizone airflow and contaminant transport model (COMIS) [72] Cp Generator [23,73] Web-based program developed by the Dutch institution TNO based on fits of measured data to mathematical expressions. New parametric equation [74] Developed through curve fits of the low-rise data from the TPU database, and it is easier to calculate by hand or with a spreadsheet than the Swami and Chandra equations. Artificial neural networks (ANN) [75] ANN is used to obtain analytical models to accurately predict the surface-averaged wind pressure coefficients in walls and roofs of low-rise buildings. |
Database | North Façade | South Façade | West Façade | |||||||
---|---|---|---|---|---|---|---|---|---|---|
East Façade | ||||||||||
Cellar ACH | Cellar Temp | LV ACH | LV Temp | BR2 ACH | BR2 Temp | BR3 ACH | BR3 Temp | BR1 ACH | BR1 Temp | |
iia CpSimVf | 142.7% | 5.6% | 12.1% | 1.6% | 7.7% | 2.1% | 4.7% | 1.9% | 7.9% | 1.6% |
iib CpSimOc | 129.7% | 5.4% | 20.2% | 1.6% | 7.4% | 2.1% | 5.3% | 1.9% | 10.3% | 1.8% |
iic CpSimSb | 120.3% | 5.2% | 17.2% | 1.6% | 7.4% | 2.0% | 5.1% | 1.7% | 11.8% | 1.9% |
iii AIVC | 14.2% | 2.8% | 7.2% | 2.0% | 6.7% | 2.7% | 10.2% | 2.9% | 11.6% | 3.2% |
iv TPU | 15.3% | 3.0% | 9.5% | 2.2% | 7.2% | 2.7% | 10.3% | 2.2% | 11.6% | 3.3% |
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© 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
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Sakiyama, N.R.M.; Carlo, J.C.; Sakiyama, F.I.H.; Abdessemed, N.; Frick, J.; Garrecht, H. Impact of Wind Pressure Coefficients on the Natural Ventilation Effectiveness of Buildings through Simulations. Buildings 2024, 14, 2803. https://doi.org/10.3390/buildings14092803
Sakiyama NRM, Carlo JC, Sakiyama FIH, Abdessemed N, Frick J, Garrecht H. Impact of Wind Pressure Coefficients on the Natural Ventilation Effectiveness of Buildings through Simulations. Buildings. 2024; 14(9):2803. https://doi.org/10.3390/buildings14092803
Chicago/Turabian StyleSakiyama, Nayara Rodrigues Marques, Joyce Correna Carlo, Felipe Isamu Harger Sakiyama, Nadir Abdessemed, Jürgen Frick, and Harald Garrecht. 2024. "Impact of Wind Pressure Coefficients on the Natural Ventilation Effectiveness of Buildings through Simulations" Buildings 14, no. 9: 2803. https://doi.org/10.3390/buildings14092803
APA StyleSakiyama, N. R. M., Carlo, J. C., Sakiyama, F. I. H., Abdessemed, N., Frick, J., & Garrecht, H. (2024). Impact of Wind Pressure Coefficients on the Natural Ventilation Effectiveness of Buildings through Simulations. Buildings, 14(9), 2803. https://doi.org/10.3390/buildings14092803