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Numerical assessment of night ventilation impact on the thermal comfort of vernacular buildings

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Abstract

Night ventilation, is one of the most effective passive cooling techniques that may contribute to the improvement of the occupants thermal comfort conditions. Despite the justified effectiveness of night ventilation, few studies quantified its influence on the thermal comfort of vernacular buildings, especially under warm dominant climates. The aim of this study is the investigation of the impact of night ventilation on the thermal comfort of vernacular buildings under summer dominant environmental conditions. The subjects under investigation was one traditional buildings in the city of Nicosia in Cyprus. In terms of this study numerical analysis regarding the thermal comfort of the investigated buildings was performed by employing Energy Plus and the flow solver of Design Builder. The indoor operative temperature distribution, the indoor air velocity and a thermal comfort related index were identified in selected thermal zones of the examined building using night ventilation. The results of this study quantified the potential temperature decrease that can result on vernacular buildings due to the use of night ventilation and revealed some restrictions with regard to the allowed percentage of the opening sizes towards achieving optimal thermal conditions in space. This study aspires to provide useful insight regarding the importance of humans’ behavior in terms of enabling night ventilation to vernacular buildings, as well as to con-tribute to the ongoing scientific discussion on this subject.

Introduction

Energy retrofitting is an area of the construction industry which has gained public awareness in the recent years. More than a quarter of the existing European building stock was constructed prior to the middle of the last century [1]. These buildings are certainly valued for their cultural and architectural significance as they reflect the unique character and identity of European cities, but they were appointed to address the needs of their original inhabitants. The difference between original and contemporary occupants’ lifestyle, clothing and activity as well as the thermal comfort perception itself, is a parameter that needs to be taken into consideration when assessing the thermal comfort of vernacular dwellings today. People’s perceptions of comfort are influenced by cues from the built environment, yet humans may adapt the indoor environment, to achieve a different set of indoor conditions.

Vernacular buildings have evolved through time acquiring their specific form and layout, through a process of trial and error. This process implicates the consideration of multiple environmental and anthropological variables. The environmental and bioclimatic design elements of vernacular architecture; amongst which are the consideration of climatic conditions, topography, rational use of local resources concerning employed materials and complexity of construction was highlighted in previous studies [2,3,4]. Passive heating and cooling strategies of vernacular buildings presumed upon the proper use of materials as well as buildings’ location and orientation. Other environmental approaches though incorporated into the building design required the active involvement of the user. Some examples include the shutters operation to control the direct solar heat gains, the watering of plants to enable evaporative cooling, and the windows opening to exploit night ventilation Natural night ventilation is an interesting passive cooling method in moderate climates. Driven by wind and stack generated pressures, it cools down the exposed building structure at night, in which the heat of the previous day is accumulated [5]. Whilst, the prediction of occupant behaviour may result to more accurate definitions of the buildings’ energy requirements, few accounts mention the role of the user in the establishment of thermal comfort; even fewer studies approach the variant of occupant behaviour when assessing vernacular buildings.

This study aims to provide useful insight regarding the impact of natural night ventilation on the thermal comfort of vernacular buildings under summer dominant climatic conditions. In the following section, a comprehensive literature review is conducted regarding previous studies examining the impact of night ventilation to energy consumption of buildings, as well as numerical analysis practices applied to vernacular buildings to investigate their thermal comfort. In Sect. 3 the employed methodology is presented and Sect. 4 presents and discusses the results of this study.

Literature review

Night ventilation

Night ventilation, also referred as night cooling, is one of the more efficient passive cooling techniques that may contribute to the reduction of the cooling load of buildings and to the improvement of occupants’ thermal comfort. Night cooling is based on the circulation of the cool ambient air in space which results to the decrease of both the temperature of the building’s structure and of the indoor air. The cooling potential is mainly based on the relative difference between the outdoor and indoor temperatures during the night period as well as the air flow rate, the thermal capacity of the building and the appropriate coupling of the thermal mass and the air flow.

Various studies were implemented in the recent parts with the aim to quantify the impact of night ventilation to buildings [6,7,8,9]. The majority of these studies regarded office buildings. Pfafferott et al. [10] conducted experiments in two offices in order to determine the efficiency of night ventilation dependent on air change rate, solar and internal heat gains. Corgnati and Kindinis [11] investigated in their study the activation of building thermal mass by means of outdoor air ventilation, exalting the effect of night ventilation. In the study conducted by Geros et al. [12], the efficiency of night cooling techniques was investigated in 10 different urban canyons. A typical room under air-conditioned and free-floating operation was investigated, considered as single-sided or cross ventilated during the night period. Ramponi et al. [13] analyzed the cooling effectiveness of night-ventilation for office buildings placed in the center of urban areas of increased density for three European locations. Night ventilation rates and energy savings were calculated for the buildings and compared to the energy demand of the unventilated buildings. A typical office room was modelled by Artmann et al. [14]. In his study, the effect of different parameters (climate, thermal mass, heat gains, air change rates and heat transfer coefficient) on the effectiveness of night ventilation was evaluated. Climatic conditions and air flow rate during night-time ventilation were found to have the largest effect. Kubota et al. [15], the effectiveness of night ventilation for residential buildings under warm and humid climatic conditions was examined. The thermal environment evaluation showed that night ventilation would provide better thermal comfort for terraced houses occupants compared with the other ventilation strategies. Santamouris et al. [16] calculated the absolute energy contribution of night ventilation based on energy data from two hundred fourteen air conditioned residential buildings using night ventilation techniques. The results showed that the higher the cooling demand of the building, the higher the potential contribution of night ventilation under specific boundary conditions. In Le Dréau et al. [17], heat transfer during 12 h of discharge by nighttime ventilation in a full scale test room was investigated. Different ventilation types, air change rates, temperature differences between the inlet air and the room, and floor emissivity were examined. Roach et al. [18] examined the effect in cooling energy of commercial office buildings from economiser cycles and night time ventilation when used separately and combined. In the study of Goethals et al. [19], a global surrogate-based optimization procedure was set up to find room/system design solutions which induce a high convective heat flux during night cooling in a generic open plan office.

Despite the fact that several studies were conducted regarding the numerical investigation of night ventilation impact on the energy consumption of buildings, few studies were implemented to examine the impact of night ventilation to vernacular buildings by means of numerical simulation.

Energy performance of vernacular buildings

The numerical investigation of the thermal performance of vernacular buildings consists a subject that was widely approached [20,21,22]. The energy and microclimatic performance of Mediterranean vernacular buildings was investigated by Cardinale et al. [23]. The study focused on two types of buildings that are the examples of vernacular architecture in Southern Italy, namely the Sassi of Matera and the Trulli of Alberobello. Zhai and Previtali [24] performed an extensive analysis and computer energy modeling for a number of representative vernacular architectural techniques and features summarized for different climatic regions. The simulation results of the energy models suggested that considering traditions seen in ancient vernacular architecture as an approach to improving building energy performance is a worthwhile endeavor and a scientific guidance can help enhance the performance. In the study conducted by Nguyen et al. [25], six old houses in rural and urban areas in Vietnam, were investigated to understand the climatic design strategies employed and their effectiveness in maintaining human comfort and health. The results of this study indicated that vernacular housing in Vietnam is creatively adapted to the local natural conditions and uses various climate responsive strategies. Kristianto et al. [26] investigated the thermal comfort conditions, particularly air velocity, inside of Minahasa Traditional House, a wooden raised floor house originated from Tomohon, North Sulawesi. Computational fluid dynamic (CFD) analysis was applied in the study and the effectiveness in creating thermal comfort several variations of openings and stilts height were evaluated. Simulations results showed that higher stilts height is higher air velocity inside the test house and that houses with roof opening has higher internal air velocity compared to houses with wall opening. The study conducted by Presetyo et al. [27] aimed to describe Rumah Lontiok, one of Malay traditional houses and to investigate its thermal performance. The authors revealed that against the existing notion, the investigated traditional house presented a poor thermal performance. The aim of the study undertaken by Stéphan et al. [28] was to evaluate the thermal inertia in high porosity limestone old buildings in summer and to determine the impact of a retrofitting solution on thermal behaviour of these stone buildings. The analysis of data underlined the advantages of insulation for thermal inertia on stone buildings. Orehounig and Mahdavi [29] collected data for five hammans that were used for the generation of building performance simulation models. The study showed that the hygrothermal conditions in hammams vary considerably over time and space and that fairly stable thermal conditions were achieved. In [30], the authors conducted a combination of field measurements and simulations in order to determine the renovation requirements. The analysis showed that the improvement of building service systems and the energy source holds the largest energy saving potential. Dili et al. [31] compared and analyzed the thermal performance of traditional and modern buildings of Kerala, India. Analysis using Bioclimatic charts revealed that the thermal comfort of traditional buildings was comparable to contemporary ones.

Methodology

Thermal Comfort Index

In terms of this study, the thermal comfort was determined according to the well-established ISO 7730:2005 [32] standard and the PMV index. The PMV index predicts the mean value of the votes of a large group of persons on the 7-point thermal sensation scale (see Table 1), based on the heat balance of the human body. PMV was calculated using Eqs. 14.

$$ \begin{aligned} PMV & = [0.303 \times \exp ( - 0.036M) + 0.028] \\ & \quad \times \{ {(M - W) - 3.05 \times 10^{ - 3} \times [5733 - 6.99 \times (M - W)p_{a} ] - 0.42} \\ & \quad \times [(M - W) - 58.15] - 1.7 \times 10^{ - 5} \times M \times (5867 - p_{a} ) - 0.0014 \\ & \quad \times M \times (34 - t_{a} ) - 3.96 \times 10^{ - 8} \times f_{cl} \\ & \quad { \times [(t_{cl} + 273)^{4} - (t_{r} + 273)^{4} ] - f_{cl} \times h_{c} \times (t_{cl} - t_{a} )} \} \\ \end{aligned} $$
(1)
$$ \begin{aligned} t_{cl} & = 35.7 - 0.028 \times (M - W) - I_{cl} \\ & \quad \times \{ {3.96 \times 10^{ - 8} \times f_{cl} \times [(t_{cl} + 273)^{4} - (t_{r} + 273)^{4} ]} \\ & \quad{ + f_{cl} \times h_{c} \times (t_{cl} - t_{a} )}\} \\ \end{aligned} $$
(2)
$$ hc = \left\{ {\begin{array}{*{20}c} {2.38\; \times \;|t_{cl} - t_{a} |^{0.25} \;for\; 2.38\; \times \;|t_{cl} - t_{a} |^{0.25} > 12.1 \times \sqrt {v_{ar} } } \\ {12.1 \times \sqrt {v_{ar} } \; for\; 2.38\; \times \;|t_{cl} - t_{a} |^{0.25} < 12.1 \times \sqrt {v_{ar} } } \\ \end{array} } \right\} $$
(3)
$$ f_{cl} = \left\{ {\begin{array}{*{20}c} {1.00 + 1.290 \times l_{cl} \; for \; l_{cl} < 0.078 \;{\text{m}}^{ 2} {\text{K/W}}} \\ {1.05 + 0.645 \times l_{cl} \; for \; l_{cl} > 0.078\; {\text{m}}^{ 2} {\text{K/W}}} \\ \end{array} } \right\} $$
(4)
Table 1 Seven-point thermal sensation scale (PMV Index) [32]

The calculation of PMV is based on the metabolic rate of the occupant (M), the temperatures of the air, the human surface and the space walls (ta, tcl, tr, respectively) which are used to quantify heat losses due to conduction (lcl), radiation (fcl) and convection (hc), the air velocity in space (Var) and the evaporation (pa) and respiration heat losses. The metabolic unit used (met) equals to 58.2 W/m2 and the clothing unit (clo) to 0.155 m2 °C/W. The intervals in which the PMV is applicable are given in Table 2.

Table 2 PMV parameter intervals in which PMV is applicable [32]

Numerical analysis process

The calculation of the PMV index requires the definition of the indoor conditions, including buildings air, radiative and operative temperatures as well as the air velocity distribution in space. To this end Energy Plus and the flow solver of Design Builder were employed. Energy Plus is an energy analysis simulation software tool performing dynamic sub-hourly thermal load calculations. Basic important capabilities of Energy Plus comprise.

  • sub-hourly time-step simulations for the interaction between the thermal zones and the environment;

  • heat balance based solution technique for building thermal loads that allows for simultaneous calculation of radiant and convective effects at both in the interior and exterior surface during each time step and;

  • the use of Conduction Transfer Functions for the calculation of Transient heat conduction through building envelope.

Energy Plus is a stand-alone simulation program without a “user-friendly” graphical interface. In this study Design Builder was used as a graphical interface. Through Design Builder and Energy Plus a very fine zoning was performed and detailed calculation took place at each time step (Fig. 1). Detailed information regarding geometry, materials, activity, internal gains, infiltration and natural ventilation was integrated into the thermal models for the accurate representation of the energy performance of the under-study buildings.

Fig. 1
figure1

a Design Builder 3D geometry simulation. b Design Builder model top view

Design Builder also contains a computational fluid dynamics (CFD) three dimensional (3D) flow solver which was applied. Design Builder CFD uses finite volume methods (FVM) to solve a set of partial differential equations that represent the conservation of mass, the conservation of energy and the second law of Newton (momentum equation). The equation set comprises the three velocity component momentum equations, the Navier–Stokes equations, the energy equation using the k-ε turbulence model and equations for turbulence kinetic energy and the dissipation rate of turbulence kinetic energy. The simulation input of airtightness building performance is given in Table 3.

Table 3 Simulation input of airtightness building performance

The results of the internal CFD analysis were the prediction of the airflow and temperature field. By using a detailed weather file, the introduction of outside air to the inside of the building through the position and the size of the openings was studied and the benefits of natural ventilation, cross ventilation and their effects to the internal environment temperatures and thermal comfort of occupants were examined.

Results and discussion

The subject of investigation was a vernacular building in the city of Nicosia (Fig. 2). The building is located in the traditional core of Kaimakli (35°11′14.08″N, 33°22′36.31″E), and it is a typical two-storey courtyard house with an “L” shape typology. The ground floor building has a lounge-circulation zone (portico) in North–South direction. The yard is located in the southern part of the plot, allowing the exposure to solar heat gains of the building. The external walls of the building are built with adobe bricks of 50 cm thickness, and the sloped roof of the building consists of tiles, MDF plywood, an insulation layer and wooden beams. In this study, results for Zone 6, a cross ventilated room next to the ground floor portico of the building was simulated (Fig. 1). The simulation results were validated using the inequality coefficient [23], based on measurements provided by the University of Cyprus research group involved in Biovernacular project [33] presenting a good agreement The inequality coefficient is used to validate prediction models used in thermal performance and describes the inequality in the magnitude domain due to three sources: unequal tendency (mean), unequal variation (variance) and imperfect co-variation (co-variance). The resultant coefficient can range in value between 0 and 1, with 0 indicating a perfect match and 1 denoting no match [34].

$$ IC = \frac{{\sqrt {\frac{1}{n}\mathop \sum \nolimits_{t = 0}^{n} (D_{{{\text{sim}},t}} - D_{{{ \exp },t}} )^{2} } }}{{\sqrt {\frac{1}{n}\mathop \sum \nolimits_{t = 0}^{n} (D_{{{\text{sim}},t}} )^{2} } + \sqrt {\frac{1}{n}\mathop \sum \nolimits_{t = 0}^{n} (D_{{{ \exp },t}} )^{2} } }} $$
(5)

where \( {\text{D}}_{{{\text{sim}},{\text{t}}}} = ({\text{T}}_{{{\text{int}},{\text{t}}}} - {\text{T}}_{{{\text{ext}},{\text{t}}}} )_{\text{sim}} \) the recorded temperature difference and \( {\text{D}}_{{{ \exp },{\text{t}}}} = ({\text{T}}_{{{\text{int}},{\text{t}}}} - {\text{T}}_{{{\text{ext}},{\text{t}}}} )_{ \exp } \) the simulated temperature difference between the interior and the environment. Since summer season has the most significant impact on the total energy consumption of the buildings in Cyprus, the validation focused on the cooling period. As night ventilation has an impact on the thermal performance of buildings during summer, simulations were performed for the warmest summer months (July, August—see Table 4). The inequality coefficient for this period was found to be equal to 0.17.

Fig. 2
figure2

Investigated Building: a exterior façades, b interior view of the “portico” [33]

Table 4 Climatic data for July–August for Nicosia
Table 5 Reduction of operational temperature for cross and single ventilation

Impact of night ventilation on operative temperature

In Fig. 3 the impact of night ventilation on the operative temperature of the investigated building is presented. The windows were considered to be open from 7 pm to 7 am, whenever the conditions were suitable for night ventilation. The operative temperature is calculated as the average value of the air and the radiant temperature. From the given figure it can be retrieved that night ventilation results to an average reduction of the operative temperature of 2.7 °C. The maxi-mum temperature reduction during night hours is 5.7 °C. This analysis also revealed the importance of night ventilation during the night, as the temperature reduction mainly occurs daily from 8 pm until early in the morning. Another expected finding is the zeroing of time lag as the operative temperature minimum in space is found to overlap with the ambient temperature minimum; for closed windows, an average time lag of 3 h is observed. The impact of the night ventilation on the operative temperature is summarized in Table 5.

Fig. 3
figure3

Night ventilation impact on operative temperature

Figure 4 presents the three dimensional operative temperature contour within space for the investigated thermal zone (9 pm, 01/07). According to this figure, the temperature gradient in space is much higher in the case of closed windows, resulting to significant temperature differences within the same space. This is not observed for the opened windows simulation, where a more homogeneous temperature distribution in space is observed. This finding results due to the circulation of the cool ambient air in space; the temperature differences given in Fig. 3 are also confirmed anew.

Fig. 4
figure4

a Operative temperature—closed windows. b Operative temperature—open windows

As it can be retrieved from Fig. 4, the main reason for the higher temperature decrease is the fact that the investigated thermal zone is cross ventilated. As expected, cross ventilation creates some further issues regarding the high air velocities that will be observed in the building, which are not in-line with the thermal comfort prerequisites (Table 1). To this end, a discussion regarding the allowed opening sizes towards achieving optimal thermal conditions, presented in the following section, is required.

Indoor air velocity restrictions in night ventilation

Figure 5 depicts the indoor air velocity contour for the investigated thermal zone for closed and opened windows respectively. In the case of the closed windows, the air motion is attributed to natural convection and thus to the temperature gradient in space, whereas in the case of open windows, it is obvious that the air is in motion due to the entrance of fresh air in the space. As it can be retrieved from the presented results the air velocity in space, exceeds 1 m/s in the case of the cross ventilated thermal zone. The maximum air velocities are found as expected near the windows. Regarding the closed windows cases, the air velocity in space has an average velocity of less than 0.1 m/s.

Fig. 5
figure5

a Indoor air velocity—closed windows. b Indoor air velocity—open windows

It can be deduced from the calculated air velocities that although natural night ventilation in cross ventilated rooms enables the significant reduction of the operative temperature, the indoor air velocities reached are much faster than those considered within the thermal comfort range. The maximum allowable indoor air velocities to meet the corresponding draught rating categories of the 7730:2005 Standard [32] do not exceed 0.8 m/s. To this end a further analysis was conducted assuming partly open windows for the cross ventilated zones. Based on an iterative process, it was found that 30% windows opening ensured air velocities in cross ventilated spaces of less than 0.8 m/s. The reduction of the windows opening area effects as expected the temperature decrease due to night ventilation.

In Fig. 6 the indoor operative temperature is provided for fully opened windows and for a 30% opening percentage for the case of the cross ventilated investigated thermal zones. In this figure the actual limitations of night ventilation with respect to the allowed indoor air velocities are presented. According to this figure, the average temperature decrease in the case of cross ventilated thermal zones was 2.2, whereas the maximum temperature difference in the examined case was 4.7. Compared to the results given in Sect. 4.1, it is deduced that limitations in indoor air velocity may reduce the impact of night ventilation up to 50%.

Fig. 6
figure6

Night ventilation impact on operative temperature—30% windows opening

Impact of night ventilation on thermal comfort

Figure 7 presents the impact of night ventilation to the thermal comfort of the investigated space, as calculated using the PMV index (see Sect. 3.1). The calculations were performed by assuming that the air conditioning system was not in use in both cases. Also a 30% opening percentage was considered. The results prove the value of night ventilation to vernacular buildings in terms of improving the thermal comfort conditions, as the PMV index presents a significant decrease. The average PMV index was found to be 1.1 for the night ventilated thermal zone, whereas the corresponding number for the non-ventilated zone was 2.25. As it can be deduced from the results, an average improvement of 51% was achieved in the investigated thermal zone with the exploitation of night ventilation.

Fig. 7
figure7

a PMV Index—closed windows. b PMV Index—OPEN WINDOWS

Although the derived PMV indexes seem to be in the range of slightly warm to warm in the seven-point thermal sensation scale, it should be stated that two schools of thought exist regarding the thermal comfort research area, namely “static” and “adaptive”. The static model meets the ISO Standard 7730 based on Fanger’s predicted mean vote (PMV/PPD) [32], as well as the ASHRAE’s Standard 55-Thermal Environmental Conditions for Human Occupancy [35] and it was employed in this study. On the other hand, the adaptive model, states that factors beyond fundamental physics and physiology play an important role in building occupants’ expectations and thermal preferences. The way people interact with the environment, their behaviour changes can modify their thermal expectations [36, 37].

Figure 8 presents the adaptive thermal comfort levels of the master bedroom, according to EN 15251 (CYS EN 2007) [38]. For Class II buildings, which is the class tailored for new buildings and renovations, the allowable maximum difference between this comfort temperature and the actual indoor operative temperature is ±3 °C. The analysis of the results showed that the adaptive thermal comfort levels are mostly satisfied, and only occasionally the thermal conditions are out of the ±3 °C set by the standard.

Fig. 8
figure8

Adaptive thermal comfort levels according to EN 15251 (CYS EN 2007)

Conclusions

The aim of this study was the investigation of the impact of night ventilation on the thermal comfort of vernacular buildings under warm climatic conditions. To this end, the thermal behaviour of a vernacular building in the city of Nicosia was numerically investigated. Energy Plus and the flow solver of Design Builder were employed. According to the findings of this study, night ventilation may have a significant impact on the temperature and on the thermal comfort levels in vernacular buildings. Some restrictions with regard to the opening percentage were revealed, resulting from the al-lowed air velocities in space. The temperature decrease due to natural ventilation was found to reduce to a factor of 2, the air velocity being within acceptable levels. Regarding the thermal comfort levels, these were found to be improved on an average percentage of 26% with the use of night ventilation. Although the thermal comfort according to the PMV scale was considered to be in the slightly warm levels, the implementation of an adaptive model, would have revealed a better performance of night ventilated spaces.

Abbreviations

Dexp:

Experimental temperature difference (°C)

Dsim:

Simulated temperature difference (°C)

fcl:

Clothing surface area factor (–)

hc:

Convective ehat transfer coefficient (W/m2K)

IC:

Inequality coefficient (–)

lcl:

Clothing insulation (m2K/W)

M:

Metabolic rate (W/m2)

Text:

Ambient temperature (°C)

ta:

Air temperature (°C)

tcl:

Clothing surface temperature (°C)

tr:

Mean radiant temperature (°C)

pa:

Water vapour partial pressure (pa)

Var:

Relative air velocity (m/s)

W:

Effective mechanical power (W/m2)

3D:

Three dimensional

CFD:

Computational fluid dynamics

FVM:

Finite volume method

exp:

Experimental

sim:

Simulated

t:

Time

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Acknowledgments

Authors are indebted to the research project “Innovative methods for protection and conservation of sustainable design elements of vernacular architecture in the historic centre of Nicosia—Biovernacular” for the financial support of this work. Biovernacular was funded by the European Regional Development Fund and the Republic of Cyprus through the Research Promotion Foundation (Project Technological Development and Innovation Δέσμη 2009–2010, ΑΝΘΡΩΠΙΣΤΙΚΕΣ/ΑΝΘΡΩ/0609/ΒΙΕ).

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Correspondence to Paris A. Fokaides.

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Exizidou, P., Christoforou, E. & Fokaides, P.A. Numerical assessment of night ventilation impact on the thermal comfort of vernacular buildings. J Build Rehabil 2, 2 (2017). https://doi.org/10.1007/s41024-016-0021-6

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Keywords

  • Vernacular building
  • Night ventilation
  • Computational fluid dynamics (CFD)