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As external temperatures and internal gains from equipment rise, office buildings’ cooling demand and issues are likely to increase. Solutions such as demand-driven controls can help minimise energy consumption and maintain thermal comfort in buildings by coordinating the real-time heating, ventilation and air-conditioning (HVAC) use to the requirements of the conditioned spaces. The present study introduces a real-time equipment usage detection and recognition approach for demand-driven controls using a deep learning method. A Faster R-CNN model was trained and deployed to a camera. The performance of this model was assessed through different evaluation metrics. Based on the initial field experiment results, a detection accuracy of 76.21% was achieved. To investigate the impact of the proposed approach on building heating and cooling energy demand, the case study building was modelled and simulated. The results showed that the deep learning–based method predicted up to 35.95% lower internal heat gains compared to static or ‘fixed’ schedules based on the set conditions. Practical Application: As the appliances and equipment in building spaces contribute to the internal heat gains, their usage can influence the building energy demand and indoor thermal environment. Linking equipment usage with occupants’ presence in space may not be fully accurate and may lead to the over- or under-estimation of heat emissions, especially when the space is unoccupied, and the equipment is powered ON or the opposite. This approach can be integrated with demand-driven controls for HVAC systems, which can minimise unnecessary building energy consumption while maintaining a comfortable indoor environment using computer vision and deep learning detection and recognition methods.
Shuangyu Wei; Paige Wenbin Tien; Yupeng Wu; John Kaiser Calautit. The impact of deep learning–based equipment usage detection on building energy demand estimation. Building Services Engineering Research and Technology 2021, 1 .
AMA StyleShuangyu Wei, Paige Wenbin Tien, Yupeng Wu, John Kaiser Calautit. The impact of deep learning–based equipment usage detection on building energy demand estimation. Building Services Engineering Research and Technology. 2021; ():1.
Chicago/Turabian StyleShuangyu Wei; Paige Wenbin Tien; Yupeng Wu; John Kaiser Calautit. 2021. "The impact of deep learning–based equipment usage detection on building energy demand estimation." Building Services Engineering Research and Technology , no. : 1.
To host the 2022 FIFA World Cup, Qatar is facing the greatest challenge in balancing the energy consumptions for cooling the stadiums and the thermal comfort for both players and spectators. Previous studies have not considered using a combined configuration of air curtain and roof cooling supply slot in stadiums to prevent the infiltration of outside hot air and reduce the cooling system’s energy consumption. This paper presents a Computational Fluid Dynamics (CFD) study of thermal and wind modeling around a baseline stadium and simulates the cooling scenarios of air curtains and roof cooling along with the energy consumption estimations for the World Cup matches using Building Energy Simulation (BES). Sensitivity analysis of different supply speeds and supply temperatures of air curtain gates and roof cooling was carried out, and the results showed that scenario six, which provides supply air of 25 m/s and 20 m/s at the roof and air curtain gates with a supply temperature of 10 °C, demonstrates optimal thermal performances on both the spectator tiers and the pitch. Compared with the baseline stadium performance, the average reductions in temperature on the pitch and spectator tiers under scenario six could reach 15 °C and 14.6 °C. The reductions in the Predicted Percentage of Dissatisfied values for the upper and lower tiers as well as the pitch were 63%, 74%, and 78%. In terms of the estimated energy consumptions, scenario six would consume electric energy per match at a rate of 25.5 MWh compared with 22.8 MWh for one of the stadiums in the 2010 South Africa World Cup and 42.0 MWh for the 2006 Germany World Cup. Future research is recommended to explore the influence of supply angle on air curtain gates and roof cooling supply slots’ performances.
Fangliang Zhong; Hassam Chaudhry; John Calautit. Effect of Roof Cooling and Air Curtain Gates on Thermal and Wind Conditions in Stadiums for Hot Climates. Energies 2021, 14, 3941 .
AMA StyleFangliang Zhong, Hassam Chaudhry, John Calautit. Effect of Roof Cooling and Air Curtain Gates on Thermal and Wind Conditions in Stadiums for Hot Climates. Energies. 2021; 14 (13):3941.
Chicago/Turabian StyleFangliang Zhong; Hassam Chaudhry; John Calautit. 2021. "Effect of Roof Cooling and Air Curtain Gates on Thermal and Wind Conditions in Stadiums for Hot Climates." Energies 14, no. 13: 3941.
Occupancy behaviour in buildings can impact the energy performance and the operation of heating, ventilation and air-conditioning systems. To ensure building operations become optimised, it is vital to develop solutions that can monitor the utilisation of indoor spaces and provide occupants’ actual thermal comfort requirements. This study presents the analysis of the application of a vision-based deep learning approach for human activity detection and recognition in buildings. A convolutional neural network was employed to enable the detection and classification of occupancy activities. The model was deployed to a camera that enabled real-time detections, giving an average detection accuracy of 98.65%. Data on the number of occupants performing each of the selected activities were collected, and deep learning–influenced profile was generated. Building energy simulation and various scenario-based cases were used to assess the impact of such an approach on the building energy demand and provide insights into how the proposed detection method can enable heating, ventilation and air-conditioning systems to respond to occupancy’s dynamic changes. Results indicated that the deep learning approach could reduce the over- or under-estimation of occupancy heat gains. It is envisioned that the approach can be coupled with heating, ventilation and air-conditioning controls to adjust the setpoint based on the building space’s actual requirements, which could provide more comfortable environments and minimise unnecessary building energy loads. Practical application Occupancy behaviour has been identified as an important issue impacting the energy demand of building and heating, ventilation and air-conditioning systems. This study proposes a vision-based deep learning approach to capture, detect and recognise in real-time the occupancy patterns and activities within an office space environment. Initial building energy simulation analysis of the application of such an approach within buildings was performed. The proposed approach is envisioned to enable heating, ventilation and air-conditioning systems to adapt and make a timely response based on occupancy’s dynamic changes. The results presented here show the practicality of such an approach that could be integrated with heating, ventilation and air-conditioning systems for various building spaces and environments.
Paige Wenbin Tien; Shuangyu Wei; John Kaiser Calautit; Jo Darkwa; Christopher Wood. Vision-based human activity recognition for reducing building energy demand. Building Services Engineering Research and Technology 2021, 1 .
AMA StylePaige Wenbin Tien, Shuangyu Wei, John Kaiser Calautit, Jo Darkwa, Christopher Wood. Vision-based human activity recognition for reducing building energy demand. Building Services Engineering Research and Technology. 2021; ():1.
Chicago/Turabian StylePaige Wenbin Tien; Shuangyu Wei; John Kaiser Calautit; Jo Darkwa; Christopher Wood. 2021. "Vision-based human activity recognition for reducing building energy demand." Building Services Engineering Research and Technology , no. : 1.
Building ventilation accounts for up to 30% of the heat loss in commercial buildings and 25% in industrial buildings. To effectively aid the reduction of energy consumption in the building sector, the development of demand-driven control systems for heating ventilation and air-conditioning (HVAC) is necessary. In countries with temperate climates such as the UK, many buildings depend on natural ventilation strategies such as openable windows, which are useful for reducing overheating prevalence during the summer. The manual opening and adjustment of windows by occupants, particularly during the heating season, can lead to substantial heat loss and consequent energy consumption. This could also result in the unnecessary or over ventilation of the space, or the fresh air is more than what is required to ensure adequate air quality. Furthermore, energy losses build up when windows are left open for extended periods. Hence, it is important to develop control strategies that can detect and recognise the period and amount of window opening in real-time and at the same time adjust the HVAC systems to minimise energy wastage and maintain indoor environment quality and thermal comfort. This paper presents a vision-based deep learning framework for the detection and recognition of manual window operation in buildings. A trained deep learning model is deployed into an artificial intelligence-powered camera. To assess the proposed strategy's capabilities, building energy simulation was used with various operation profiles of the opening of the windows based on various scenarios. Initial experimental tests were conducted within a university lecture room with a south-facing window. Deep learning influenced profile (DLIP) was generated via the framework, which uses real-time window detection and recognition data. The generated DLIP were compared with the actual observations, and the initial detection results showed that the method was capable of identifying windows that were opened and had an average accuracy of 97.29%. The results for the three scenarios showed that the proposed strategy could potentially be used to help adjust the HVAC setpoint or alert the occupants or building managers to prevent unnecessary heating demand. Further developments include enhancing the framework ability to detect multiple window opening types and sizes and the detection accuracy by optimising the model.
Paige Wenbin Tien; Shuangyu Wei; Tianshu Liu; John Calautit; Jo Darkwa; Christopher Wood. A deep learning approach towards the detection and recognition of opening of windows for effective management of building ventilation heat losses and reducing space heating demand. Renewable Energy 2021, 177, 603 -625.
AMA StylePaige Wenbin Tien, Shuangyu Wei, Tianshu Liu, John Calautit, Jo Darkwa, Christopher Wood. A deep learning approach towards the detection and recognition of opening of windows for effective management of building ventilation heat losses and reducing space heating demand. Renewable Energy. 2021; 177 ():603-625.
Chicago/Turabian StylePaige Wenbin Tien; Shuangyu Wei; Tianshu Liu; John Calautit; Jo Darkwa; Christopher Wood. 2021. "A deep learning approach towards the detection and recognition of opening of windows for effective management of building ventilation heat losses and reducing space heating demand." Renewable Energy 177, no. : 603-625.
Students' performance is negatively influenced by poor indoor environments. In Sudan that is characterised by extreme climate, providing comfortable classrooms is required to improve the educational system that suffers from restricted budgets. To address this issue, the local government in Khartoum, the capital city of Sudan, and the Ministry of Education released a joint project to construct new schools' buildings following one of two unified prototype models. This paper evaluates the impact of a new passive wall system that combines natural ventilation and evaporative cooling on the classrooms' thermal conditions. The wall consists of two brick layers that accommodate a wet porous ceramic layer, and it has two configurations. In the first configuration, the exhausted air is circulated to the system to cool it before ejecting it into the classroom. In the second configuration, the exhausted air is dissipated from the classroom through an outlet located at a wall opposite to the wall that integrates the system. The effectiveness of the system was evaluated via assessing the classrooms’ conditions before and after activating it using EDSL TAS and ANSYS ICEM CFD programmes. The findings revealed considerable reductions in indoor air temperatures from 30.3–44.8 °C before activating the system to 18.9–26.5 °C and 21.3–23.8 °C after activating the system in the first and second configurations, respectively, which concludes the system effectiveness. The wall is environmentally clean as its operation barely consumes active energy, which makes it attractive considering the limited budget allocated for the education sector in Sudan.
Sara Mohamed; Hanan Al-Khatri; John Calautit; Siddig Omer; Saffa Riffat. The impact of a passive wall combining natural ventilation and evaporative cooling on schools’ thermal conditions in a hot climate. Journal of Building Engineering 2021, 44, 102624 .
AMA StyleSara Mohamed, Hanan Al-Khatri, John Calautit, Siddig Omer, Saffa Riffat. The impact of a passive wall combining natural ventilation and evaporative cooling on schools’ thermal conditions in a hot climate. Journal of Building Engineering. 2021; 44 ():102624.
Chicago/Turabian StyleSara Mohamed; Hanan Al-Khatri; John Calautit; Siddig Omer; Saffa Riffat. 2021. "The impact of a passive wall combining natural ventilation and evaporative cooling on schools’ thermal conditions in a hot climate." Journal of Building Engineering 44, no. : 102624.
Article: A Coupled Modelling Method for the Evaluation of the Impact of Pavement Solar Collector on Urban Air Temperature and Thermal Collection
Weijie Xu; Carlos Jimenez-Bescos; Conrad Allan Jay Pantua; John Calautit; Yupeng Wu. A Coupled Modelling Method for the Evaluation of the Impact of Pavement Solar Collector on Urban Air Temperature and Thermal Collection. Future Cities and Environment 2021, 7, 1 .
AMA StyleWeijie Xu, Carlos Jimenez-Bescos, Conrad Allan Jay Pantua, John Calautit, Yupeng Wu. A Coupled Modelling Method for the Evaluation of the Impact of Pavement Solar Collector on Urban Air Temperature and Thermal Collection. Future Cities and Environment. 2021; 7 (1):1.
Chicago/Turabian StyleWeijie Xu; Carlos Jimenez-Bescos; Conrad Allan Jay Pantua; John Calautit; Yupeng Wu. 2021. "A Coupled Modelling Method for the Evaluation of the Impact of Pavement Solar Collector on Urban Air Temperature and Thermal Collection." Future Cities and Environment 7, no. 1: 1.
This paper reviewed related research works and developments on the traditional architectural element “mashrabiya” focusing on its history, design and structure, typology, and functions in hot climates. Moreover, the paper assessed the effect of the traditional mashrabiya on the indoor thermal environment and thermal comfort in a selected case study building. For this purpose, two similar rooms were investigated in a selected historic building with abundant mashrabiyas located in the Makkah Region, specifically in Old Jeddah, Saudi Arabia. The field tests were conducted during a typical hot summer month with two different configurations. The study demonstrated that opening the mashrabiya allowed more airflow into the room during the day and reduced the indoor temperature by up to 2.4 °C as compared to the closed mashrabiya. Besides, the building envelope played an important role in preventing the high fluctuation of the indoor air temperature, where the fluctuation of the rooms air temperature ranged between 2.1 °C and 4.2 °C compared to the outdoor temperature which recorded a fluctuation between 9.4 °C and 16 °C. The data presented here can be used for the future development of the mashrabiya concept and the potential incorporation with passive cooling methods to improve its design according to the requirements of modern buildings in hot climates. Moreover, further studies and tests on mashrabiyas under different climatic conditions are required. Also, the different strategies or materials can be incorporated with mashrabiyas in order to improve its thermal performance.
Abdullah Abdulhameed Bagasi; John Kaiser Calautit; Abdullah Saeed Karban. Evaluation of the Integration of the Traditional Architectural Element Mashrabiya into the Ventilation Strategy for Buildings in Hot Climates. Energies 2021, 14, 530 .
AMA StyleAbdullah Abdulhameed Bagasi, John Kaiser Calautit, Abdullah Saeed Karban. Evaluation of the Integration of the Traditional Architectural Element Mashrabiya into the Ventilation Strategy for Buildings in Hot Climates. Energies. 2021; 14 (3):530.
Chicago/Turabian StyleAbdullah Abdulhameed Bagasi; John Kaiser Calautit; Abdullah Saeed Karban. 2021. "Evaluation of the Integration of the Traditional Architectural Element Mashrabiya into the Ventilation Strategy for Buildings in Hot Climates." Energies 14, no. 3: 530.
Crop residues are common in rural Ghana due to the predominant role agriculture plays in livelihood activities in these communities. In this paper we investigate the prospects of exploiting agricultural crop residues for rural development in Ghana through bioenergy schemes. A theoretical energy potential of 623.84 PJ per year, which is equivalent to 19,781 MW was estimated using crop production data from the Food and Agricultural Organization of the United Nations and residue-to-product ratios. Ghana has a total installed generation capacity of 4577 MW which is four times less the energy potential of crop residues in the country. Cocoa pod husks were identified as important biomass resources for energy generation as they are currently wasted. To further assess the energy potential of cocoa pod husks, different cocoa pod husks samples were collected across the six cocoa growing regions in Ghana and thermo-chemically characterised using proximate and ultimate analysis. The low levels of nitrogen and sulphur observed, together with the high heating value, suggest that cocoa pod husks and for that matter crop residues are eco-friendly feedstock that can be used to power rural communities in Ghana.
Nii Nelson; Jo Darkwa; John Calautit; Mark Worall; Robert Mokaya; Eunice Adjei; Francis Kemausuor; Julius Ahiekpor. Potential of Bioenergy in Rural Ghana. Sustainability 2021, 13, 381 .
AMA StyleNii Nelson, Jo Darkwa, John Calautit, Mark Worall, Robert Mokaya, Eunice Adjei, Francis Kemausuor, Julius Ahiekpor. Potential of Bioenergy in Rural Ghana. Sustainability. 2021; 13 (1):381.
Chicago/Turabian StyleNii Nelson; Jo Darkwa; John Calautit; Mark Worall; Robert Mokaya; Eunice Adjei; Francis Kemausuor; Julius Ahiekpor. 2021. "Potential of Bioenergy in Rural Ghana." Sustainability 13, no. 1: 381.
Because of extensive variations in occupancy patterns around office space environments and their use of electrical equipment, accurate occupants’ behaviour detection is valuable for reducing the building energy demand and carbon emissions. Using the collected occupancy information, building energy management system can automatically adjust the operation of heating, ventilation and air-conditioning (HVAC) systems to meet the actual demands in different conditioned spaces in real-time. Existing and commonly used ‘fixed’ schedules for HVAC systems are not sufficient and cannot adjust based on the dynamic changes in building environments. This study proposes a vision-based occupancy and equipment usage detection method based on deep learning for demand-driven control systems. A model based on region-based convolutional neural network (R-CNN) was developed, trained and deployed to a camera for real-time detection of occupancy activities and equipment usage. Experiments tests within a case study office room suggested an overall accuracy of 97.32% and 80.80%. In order to predict the energy savings that can be attained using the proposed approach, the case study building was simulated. The simulation results revealed that the heat gains could be over or under predicted when using static or fixed profiles. Based on the set conditions, the equipment and occupancy gains were 65.75% and 32.74% lower when using the deep learning approach. Overall, the study showed the capabilities of the proposed approach in detecting and recognising multiple occupants’ activities and equipment usage and providing an alternative to estimate the internal heat emissions.
Paige Wenbin Tien; Shuangyu Wei; John Calautit. A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand. Energies 2020, 14, 156 .
AMA StylePaige Wenbin Tien, Shuangyu Wei, John Calautit. A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand. Energies. 2020; 14 (1):156.
Chicago/Turabian StylePaige Wenbin Tien; Shuangyu Wei; John Calautit. 2020. "A Computer Vision-Based Occupancy and Equipment Usage Detection Approach for Reducing Building Energy Demand." Energies 14, no. 1: 156.
Many high-rise buildings have semi-enclosed landscaped spaces, which act as design elements to improve the social and environmental aspects of the building. Designs such as skygardens are open to outdoor airflow and allow occupants to observe the city skyline from a height. Due to their often high location, they are subjected to strong wind speeds and extreme environmental conditions. The current study investigates the effects of three common wind buffers (railing, hedges, and trees) located at a height of 92 m on the performance of a skygarden, in terms of occupants’ wind comfort. Computational fluid dynamics (CFD) simulations were carried out using the realisable k-epsilon method, where the vegetation was modelled as a porous zone with cooling capacity. The computational modelling of the high-rise building and vegetation were validated using previous works. The quality class (QC) of the Lawson comfort criteria was used for the evaluation of the wind comfort across the skygarden. The results indicate that, although the three wind buffers offer varying levels of wind reduction in the skygarden, the overall wind conditions generated are suitable for occupancy. Furthermore, vegetation is also able to offer slight temperature reductions in its wake. The right combination and dimension of these elements can greatly assist in generating aero-thermal comfort across skygardens.
Murtaza Mohammadi; Paige Tien; John Kaiser Calautit. Influence of Wind Buffers on the Aero-Thermal Performance of Skygardens. Fluids 2020, 5, 160 .
AMA StyleMurtaza Mohammadi, Paige Tien, John Kaiser Calautit. Influence of Wind Buffers on the Aero-Thermal Performance of Skygardens. Fluids. 2020; 5 (3):160.
Chicago/Turabian StyleMurtaza Mohammadi; Paige Tien; John Kaiser Calautit. 2020. "Influence of Wind Buffers on the Aero-Thermal Performance of Skygardens." Fluids 5, no. 3: 160.
Mashrabiya is one of the primary features of Arab-Islamic architecture which can be found and still used in different cities around the world. It can be defined as an opening covered with wooden lattice for ventilation, daylight, privacy, and an aesthetic appeal for houses. The motivation for this work stems from the lack of existing field studies on the ventilation and thermal performance of buildings incorporated with Mashrabiya and the potential to enhance its capabilities by combining it with different passive cooling techniques. The present study aims to investigate the influence of Mashrabiya on the indoor environment in a traditional building situated in a hot climate. The case study selected for this work is the Baeshen House which is located in the heart of historic Jeddah and the area with the most traditional Mashrabiyas in Saudi Arabia. The field data of air temperature, relative humidity, globe temperature, and air velocity were collected for two similar rooms (one open Mashrabiya and one close) in the building during typical hot summer conditions when the outdoor temperature ranged between 40 and 41.6 °C in the afternoon. Different techniques of passive/evaporative cooling strategy were integrated with the Mashrabiya: thermal mass, water pots, water spray, and cloth. The results showed that the closed Mashrabiya contributed to reducing the flow of hot air into rooms during the afternoon, and the indoor temperature was maintained at 35.4–35.8 °C. Increasing the speed of airflow into the room by opening the Mashrabiya had a minimal effect during the afternoon, but it was observed that the night cooling improved. It was found that the most effective strategy was the use of wetted cloth near the inlet of the Mashrabiya (33.8 °C indoor average when the outdoor temperature was at 41.6 °C). The study demonstrated that comfortable conditions could be attained between 1 and 9 a.m. during hot summer conditions. Overall, the Mashrabiya with evaporative cooling was not able to provide comfort during the midday, and other strategies should be considered for hot summer conditions. Future work will focus on investigating different materials and strategies to enhance the performance of Mashrabiyas.
Abdullah Abdulhameed Bagasi; John Kaiser Calautit. Experimental field study of the integration of passive and evaporative cooling techniques with Mashrabiya in hot climates. Energy and Buildings 2020, 225, 110325 .
AMA StyleAbdullah Abdulhameed Bagasi, John Kaiser Calautit. Experimental field study of the integration of passive and evaporative cooling techniques with Mashrabiya in hot climates. Energy and Buildings. 2020; 225 ():110325.
Chicago/Turabian StyleAbdullah Abdulhameed Bagasi; John Kaiser Calautit. 2020. "Experimental field study of the integration of passive and evaporative cooling techniques with Mashrabiya in hot climates." Energy and Buildings 225, no. : 110325.
Windcatchers are considered as promising passive ventilation and cooling strategy, but the ventilation performance of this system is still of concern in areas with low speed and unpredictable winds. The air short circuiting in windcatchers can reduce its ventilation performance and ability to introduce clean air and remove stale air. The current work aimed to evaluate the indoor environmental quality (IEQ) performance of a two-sided windcatcher fitted with an anti-short-circuit device (ASCD) for improving its performance in low wind speed conditions. Computational Fluid Dynamics (CFD) simulations were performed for different ASCD configurations. The CFD method was verified using grid-sensitivity analysis and validated by comparing the simulation results with wind tunnel data. The results indicated that the average difference between CFD results and previous experimentation was below 10%, therefore indicating good agreement. Building on the findings of the previous research, the study focused on evaluating the impact of the length of ASCD on the achieved fresh air supply rates and air change rate. The length of the ASCD was varied between 5 cm to 50 cm, while the angle was maintained at 80°. The shorter ASCD was still able to minimize the fresh supply airflow short-circuiting to the exhaust stream, and at the same time, it would also require a smaller ceiling space for installation and lower material cost. Hence, the 15 cm ASCD with 80° angle was selected for further analysis in this study. Then, consideration of low wind speed and various directions were studied to evaluate the ventilation performance of windcatcher with ASCD. The study simulated wind speeds between 0.5–2 m/s and two wind directions. Based on the assessment of IEQ factors, including mean age of air and percentage of dead zone, a 0° incident angle demonstrated slightly better results. The achieved fresh air supply rates ranged between 180 L/s to 890 L/s in 45° wind angle, while, for 0°, these values were from 160 L/s to 642 L/s. Likewise, the range of air change rates (ACH) was from 8 ACH to 32 ACH in 0° wind angle and increased to 9 ACH and then to 45 ACH in 45° wind angle.
Payam Nejat; Hasanen Mohammed Hussen; Fodil Fadli; Hassam Nasarullah Chaudhry; John Calautit; Fatemeh Jomehzadeh. Indoor Environmental Quality (IEQ) Analysis of a Two-Sided Windcatcher Integrated with Anti-Short-Circuit Device for Low Wind Conditions. Processes 2020, 8, 840 .
AMA StylePayam Nejat, Hasanen Mohammed Hussen, Fodil Fadli, Hassam Nasarullah Chaudhry, John Calautit, Fatemeh Jomehzadeh. Indoor Environmental Quality (IEQ) Analysis of a Two-Sided Windcatcher Integrated with Anti-Short-Circuit Device for Low Wind Conditions. Processes. 2020; 8 (7):840.
Chicago/Turabian StylePayam Nejat; Hasanen Mohammed Hussen; Fodil Fadli; Hassam Nasarullah Chaudhry; John Calautit; Fatemeh Jomehzadeh. 2020. "Indoor Environmental Quality (IEQ) Analysis of a Two-Sided Windcatcher Integrated with Anti-Short-Circuit Device for Low Wind Conditions." Processes 8, no. 7: 840.
User demand for increased internal thermal comfort conditions have resulted in rising energy costs for space-heating consumption. The present study aims to recover the thermal energy in ventilation exhaust air and transfer the energy to the incoming air, to be redistributed using natural ventilation windcatcher. A comprehensive review was carried out to explore heat recovery systems that can potentially be incorporated with natural ventilation wind catchers. A rotary heat recovery device suitable to be incorporated with a roof mounted multi directional windcatcher system was developed. Computational Fluid Dynamics (CFD) modelling and laboratory experimental tests were conducted to investigate the proposed system. In the first phase, a full-scale prototype of the passive rotary thermal wheel device was developed and tested in a crossflow channel to initially assess the concept and performance of the design. Two configurations of the passive heat recovery wheel were tested: 20 and 32 radial blades. The second phase focused on investigating the integration of heat recovery wheel into a windcatcher system. CFD modelling and scaled wind tunnel testing were conducted to assess the airflow and temperature distribution around the multi-directional windcatcher with a passive rotary wheel. The results showed that the addition of the heat recovery wheel rotating at 15 rpm reduced the indoor airflow speed between 14 and 30%, depending on the outdoor wind conditions. The system was able to provide the recommended fresh air rates when the outdoor wind speed was 1.5 m/s and higher. In addition to sufficient ventilation, the heat recovery system had a positive impact on the indoor air temperature, raising the temperature up to 3.7 °C depending on the indoor/outdoor conditions.
John Kaiser Calautit; Dominic O’Connor; Paige Wenbin Tien; Shuangyu Wei; Conrad Allan Jay Pantua; Ben Hughes. Development of a natural ventilation windcatcher with passive heat recovery wheel for mild-cold climates: CFD and experimental analysis. Renewable Energy 2020, 160, 465 -482.
AMA StyleJohn Kaiser Calautit, Dominic O’Connor, Paige Wenbin Tien, Shuangyu Wei, Conrad Allan Jay Pantua, Ben Hughes. Development of a natural ventilation windcatcher with passive heat recovery wheel for mild-cold climates: CFD and experimental analysis. Renewable Energy. 2020; 160 ():465-482.
Chicago/Turabian StyleJohn Kaiser Calautit; Dominic O’Connor; Paige Wenbin Tien; Shuangyu Wei; Conrad Allan Jay Pantua; Ben Hughes. 2020. "Development of a natural ventilation windcatcher with passive heat recovery wheel for mild-cold climates: CFD and experimental analysis." Renewable Energy 160, no. : 465-482.
A windcatcher is a wind-driven natural ventilation system that catches the prevailing wind to bring fresh airflow into the building and remove existing stale air. This technology recently regained attention and is increasingly being employed in buildings for passive ventilation and cooling. The combination of windcatchers and evaporative cooling has the potential to reduce the amount of energy required to ventilate and cool a greenhouse in warm and hot climates. This study examined a greenhouse incorporated with a passive downdraught evaporative cooling windcatcher (PDEC-WC) system using Computational Fluid Dynamics (CFD), validated with experimental data. Different hot ambient conditions of temperature (30–45 °C) and relative humidity (15–45%) were considered. The study explored the influence of different spray heights, layouts, cone angles and mass flow rates on indoor temperature and humidity. The average error between measurements and simulated results was 5.4% for the greenhouse model and 4.6% for the evaporative spray model. Based on the results and set conditions, the system was able to reduce the air temperature by up to 13.3 °C and to increase relative humidity by 54%. The study also assessed the influence of neighbouring structures or other greenhouses that influence the flow distribution at the ventilation openings. The study showed that the windcatcher ventilation system provided higher airflow rates as compared to cross-flow ventilation when other structures surrounded the greenhouse.
Marouen Ghoulem; Khaled El Moueddeb; Ezzedine Nehdi; Fangliang Zhong; John Calautit. Design of a Passive Downdraught Evaporative Cooling Windcatcher (PDEC-WC) System for Greenhouses in Hot Climates. Energies 2020, 13, 2934 .
AMA StyleMarouen Ghoulem, Khaled El Moueddeb, Ezzedine Nehdi, Fangliang Zhong, John Calautit. Design of a Passive Downdraught Evaporative Cooling Windcatcher (PDEC-WC) System for Greenhouses in Hot Climates. Energies. 2020; 13 (11):2934.
Chicago/Turabian StyleMarouen Ghoulem; Khaled El Moueddeb; Ezzedine Nehdi; Fangliang Zhong; John Calautit. 2020. "Design of a Passive Downdraught Evaporative Cooling Windcatcher (PDEC-WC) System for Greenhouses in Hot Climates." Energies 13, no. 11: 2934.
The 2022 FIFA World Cup brings Qatar great challenges in terms of minimizing the cooling energy consumption and providing thermal comfort for both spectators and players. This paper presents comparisons among the results of thermal and wind environment modelling of a semi-outdoor stadium under three different cooling configurations and a baseline configuration without cooling using the Computational Fluid Dynamics (CFD) tool ANSYS Fluent 18.2. The three cooling configurations are: (1) vertical jets only above upper tiers, (2) vertical jets above upper tiers and horizontal jets at the back of lower tiers and around the pitch, (3) integrated vertical jets above upper tiers, horizontal jets at the back of lower tiers and air curtains at gates. De-coupled solar radiation simulations are implemented using the solar irradiance data in Doha under fair weather conditions method in Fluent in order to capture realistic thermal boundary conditions for the ground, stadium and surrounding buildings. On the basis of the set conditions, the results show that air curtains, employed in configuration 3 are effective in preventing the penetration of hot outside air through the gates of the stadium, which is an existing issue for stadiums in hot climates, and also contribute to lower energy consumption per match than the other configurations of cooling jets. The results presented in this study are useful not only for future design and retrofits of stadiums in hot climates but also for stadiums that incorporate mechanical cooling.
Fangliang Zhong; John Calautit. An Integrated Cooling Jet and Air Curtain System for Stadiums in Hot Climates. Atmosphere 2020, 11, 546 .
AMA StyleFangliang Zhong, John Calautit. An Integrated Cooling Jet and Air Curtain System for Stadiums in Hot Climates. Atmosphere. 2020; 11 (5):546.
Chicago/Turabian StyleFangliang Zhong; John Calautit. 2020. "An Integrated Cooling Jet and Air Curtain System for Stadiums in Hot Climates." Atmosphere 11, no. 5: 546.
After winning the bid of the FIFA’s World Cup 2022, Qatar is facing the greatest challenges in terms of minimizing substantial energy consumptions for air-conditioning of stadiums and maintaining aero-thermal comfort for both players and spectators inside stadiums. This paper presents the results of temperature distributions and wind environment of the original stadium under the hot-humid climate and improvements on them for optimized scenarios of cooling jets. A combined computational fluid dynamics and building energy simulation approach was used to analyse the cooling performance and energy consumption per match of cooling air jets for 10 scenarios with different supply velocities, supply temperatures and locations of jets. The optimal scenario is to employ vertical jets above the upper tiers at supply temperature of 20°C and velocities of 2–12 m/s, integrated with horizontal jets of the same temperature at the lower tiers with 4 m/s and around the pitch with 7 m/s. This scenario can maintain the spectator tiers at an average temperature of 22°C and reduce the maximum predicted percentage of dissatisfied of thermal comfort from the original 100% to 63% for the pitch and 19% for the tiers, respectively. In terms of the energy consumption for the air-conditioning system per match, compared with one of the 2010 South Africa World Cup stadiums Royal Bafokeng stadium which consumed approximately 22.8 MWh energy for air-conditioning in winter (highest outdoor temperature 24.4°C), the maximum energy consumption of the optimal scenario in November (highest outdoor temperature 34.2°C) can reach 108 MWh. In addition, the spectator zones with scenario 8 have the potential to be resilient to the seasonal change of outdoor temperature if slight modifications of the supply velocities and precise temperature control on the spectator zones are applied. Moreover, the configurations presented in this paper can be used as a foundation of jets arrangement for future stadium retrofits in the hot climates. Practical application: This study assesses the aero-thermal conditions of a case study stadium under the hot climate of Qatar and explores the potential of applying cooling jets with different supply velocities, supply temperatures and their locations on the enhancement of both thermal and wind environment of spectator tiers and pitch. The assessment of the original stadium indicates that the ascending curved roof structure impedes the fresh air entering into the stadium and results in an asymmetric temperature distribution on the spectator tiers. The optimized design suggests a combination of vertical jets under the roof and both three arrays of horizontal jets at lower tiers and around pitch for future stadium optimizations in hot climates. It also recommends enhancing the thermal conditions on the pitch by optimizing the velocity of horizontal jets around the pitch. Moreover, the future design of the exact stadiums to be resilient to the seasonal changing outdoor temperature can be implemented based on scenario 8.
Fangliang Zhong; John K Calautit; Ben R Hughes. Analysis of the influence of cooling jets on the wind and thermal environment in football stadiums in hot climates. Building Services Engineering Research and Technology 2019, 41, 561 -585.
AMA StyleFangliang Zhong, John K Calautit, Ben R Hughes. Analysis of the influence of cooling jets on the wind and thermal environment in football stadiums in hot climates. Building Services Engineering Research and Technology. 2019; 41 (5):561-585.
Chicago/Turabian StyleFangliang Zhong; John K Calautit; Ben R Hughes. 2019. "Analysis of the influence of cooling jets on the wind and thermal environment in football stadiums in hot climates." Building Services Engineering Research and Technology 41, no. 5: 561-585.
The present study provides an analysis of existing literature encompassing the wind and thermal analysis of football stadia, and how both can be manipulated through the modification of roof geometry. It introduces the potential for cooling strategies to create an internal environment capable of hosting elite-level international football in a hot climate. The motivation for the study stems from an absence of existing literature focussing on thermal flow in hot conditions for stadia and the requirement to investigate the hosting capabilities of Qatar for the 2022 FIFA World Cup. Stadium design plays a crucial role in determining the success of the tournament not only through the month-long event, but also with the legacy it leaves afterwards. To carry out the analysis, Computational Fluid Dynamics (CFD) simulations were conducted in an effort to produce internal conditions that satisfy official FIFA guidelines on optimal playing conditions in terms of wind and temperature distribution. These are ran on a model validated against existing literature to ensure accuracy, but considering the potential for error between model generations. The conclusions drawn suggest that a downward-pitched, large-radius retractable roof subsidised by the introduction of a mechanical system to create a cooling strategy reduces the external temperature down to 23 °C, with wind velocities not exceeding 4 m/s. Reinforced by results, these desired playing conditions can be achieved by closing the roof to precondition the stadium before an event, with the roof then retracted to ensure compliance with FIFA guidelines. The results from the present study can be a component in achieving a sustained positive legacy for the upcoming FIFA World Cup.
Sam Bonser; Ben Richard Hughes; John Kaiser Calautit. Investigation of the impact of roof configurations on the wind and thermal environment in football stadiums in hot climates. International Journal of Ventilation 2019, 19, 260 -279.
AMA StyleSam Bonser, Ben Richard Hughes, John Kaiser Calautit. Investigation of the impact of roof configurations on the wind and thermal environment in football stadiums in hot climates. International Journal of Ventilation. 2019; 19 (4):260-279.
Chicago/Turabian StyleSam Bonser; Ben Richard Hughes; John Kaiser Calautit. 2019. "Investigation of the impact of roof configurations on the wind and thermal environment in football stadiums in hot climates." International Journal of Ventilation 19, no. 4: 260-279.
The main purpose of research on occupant behaviour is to enhance building energy performance. However, it is difficult to reduce the energy use without understanding the occupant, their needs and preferences. Individual differences and preferences for the thermal environment in relation to the spatial context are overlooked in the main stream of research. This study investigates the patterns of occupant thermal preference based on individual differences in perceiving the thermal environment to enhance user comfort and energy performance. A novel method of Visual Thermal Landscaping is used, which is a qualitative method to analyse occupant comfort and user behaviour according to the spatial context. This method drives away from the notion of ‘thermal neutrality’ and generic results, rather it opens to details and meaning through a qualitative analysis of personal-comfort, based on individual differences and spatial context information. Field test studies of thermal comfort were applied in five office buildings in the UK, Sweden and Japan with overall 2313 data sets. The primary contribution of the study was the recognition of four patterns of thermal preference, including consistent directional preference; fluctuating preference; high tolerance and sensitive to thermal changes; and high tolerance and not-sensitive to thermal changes. The results were further examined in a longitudinal field test study of thermal comfort. In several cases, occupant thermal comfort and preferences were observed to be influenced by the impact of outdoor conditions, when the windows were fixed. Practical solutions for research, practice and building design were recommended with direct implications on occupant comfort and energy use.
Sally Shahzad; John Kaiser Calautit; Ben Richard Hughes; B.K. Satish; Hom B. Rijal. Patterns of thermal preference and Visual Thermal Landscaping model in the workplace. Applied Energy 2019, 255, 113674 .
AMA StyleSally Shahzad, John Kaiser Calautit, Ben Richard Hughes, B.K. Satish, Hom B. Rijal. Patterns of thermal preference and Visual Thermal Landscaping model in the workplace. Applied Energy. 2019; 255 ():113674.
Chicago/Turabian StyleSally Shahzad; John Kaiser Calautit; Ben Richard Hughes; B.K. Satish; Hom B. Rijal. 2019. "Patterns of thermal preference and Visual Thermal Landscaping model in the workplace." Applied Energy 255, no. : 113674.
Research activity in the field of air pollution forecasting using artificial neural networks (ANNs) has increased dramatically in recent years. However, the development of ANN models entails levels of uncertainty given the black-box nature of ANNs. In this paper, a protocol by Maier et al. (2010) for ANN model development is presented and applied to assess journal papers dealing with air pollution forecasting using ANN models. The majority of the reviewed works are aimed at the long-term forecasting of outdoor PM10, PM2.5, and oxides of nitrogen, and ozone. The vast majority of the identified works utilised meteorological and source emissions predictors almost exclusively. Furthermore, ad-hoc approaches are found to be predominantly used for determining optimal model predictors, appropriate data subsets and the optimal model structure. Multilayer perceptron and ensemble-type models are predominantly implemented. Overall, the findings highlight the need for developing systematic protocols for developing powerful ANN models.
Sheen Mclean Cabaneros; John Kaiser Calautit; Ben Richard Hughes. A review of artificial neural network models for ambient air pollution prediction. Environmental Modelling & Software 2019, 119, 285 -304.
AMA StyleSheen Mclean Cabaneros, John Kaiser Calautit, Ben Richard Hughes. A review of artificial neural network models for ambient air pollution prediction. Environmental Modelling & Software. 2019; 119 ():285-304.
Chicago/Turabian StyleSheen Mclean Cabaneros; John Kaiser Calautit; Ben Richard Hughes. 2019. "A review of artificial neural network models for ambient air pollution prediction." Environmental Modelling & Software 119, no. : 285-304.
This work builds on previous experience in windcatcher design, maximising the ventilation rate of the windcatcher, whilst integrating low energy cooling technologies. The present study aims to investigate the thermal comfort and indoor air quality in buildings ventilated with a passive cooling windcatcher integrated with heat pipes and extended surface using numerical modelling, wind tunnel and far-field testing in the UAE during a summer month. Results of the scaled wind tunnel tests showed that the addition of the heat pipes and extended surfaces reduced the airflow through the windcatcher but did not impede the flow even at low outdoor wind speeds, this was further confirmed by the smoke visualisation tests. Analysis of pollutant concentration in the building model showed that the proposed windcatcher configuration was capable of delivering fresh air at a sufficient rate to lower CO2 concentration levels below the recommended guidelines for air quality. The thermal comfort analysis was conducted and it was observed that for the present design, equal distribution of thermal comfort was not achieved due to combination of high air movement, colder temperature and high humidity below the windcatcher which resulted in higher thermal discomfort in this area. Further work is required to develop a suitable control strategy in the form of volume control dampers which would enable the supply flowrate to be monitored and altered as required and optimized the distribution in the occupied space. Field tests data was used to validate the numerical modelling, showing good agreement between both methods.
John Kaiser Calautit; Paige Wenbin Tien; Shuangyu Wei; Katrina Calautit; Ben Hughes. Numerical and experimental investigation of the indoor air quality and thermal comfort performance of a low energy cooling windcatcher with heat pipes and extended surfaces. Renewable Energy 2019, 145, 744 -756.
AMA StyleJohn Kaiser Calautit, Paige Wenbin Tien, Shuangyu Wei, Katrina Calautit, Ben Hughes. Numerical and experimental investigation of the indoor air quality and thermal comfort performance of a low energy cooling windcatcher with heat pipes and extended surfaces. Renewable Energy. 2019; 145 ():744-756.
Chicago/Turabian StyleJohn Kaiser Calautit; Paige Wenbin Tien; Shuangyu Wei; Katrina Calautit; Ben Hughes. 2019. "Numerical and experimental investigation of the indoor air quality and thermal comfort performance of a low energy cooling windcatcher with heat pipes and extended surfaces." Renewable Energy 145, no. : 744-756.