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In the studies of solutions for green buildings, the Computational Fluid Dynamics (CFD) method has been widely used, particularly for solar chimneys. Performance of a solar chimney for natural ventilation or cooling can be assessed numerically in terms of the induced flow rate and temperature rise through the chimney. As the CFD technique has been employed successfully by many researchers for small-scale solar chimneys, applications of this method to large-scale systems, particularly three-dimensional (3D) ones are extremely difficult due to computational cost. As an attempt to apply the CFD method to 3D solar chimneys, in this work, we built an Artificial Intelligence – based ANFIS (model) to predict performance of a simple 3D vertical solar chimney. The ANFIS model was trained with the data generated by an CFD model for various applied heat fluxes. The trained ANFIS model was then employed to predicted performance of the chimney at other heat fluxes. The results show that the ANFIS model is able to predict well the induced flow rate and temperature rise through the chimney with the maximum difference with the CFD results of less than 5.0%. Therefore, this study shows a possibility of combining CFD and ANFIS methods for large-scale solar chimneys.

Natural ventilation for buildings using solar chimney is increasingly attracting the attention of many researchers. Many techniques have been introduced to research on solar chimneys such as experimental, analytical, computational methods. Recently, with the development of computer technology, computational method, particularly, Computational Fluid Dynamics (CFD) becomes more common and widely applied in solar chimney, but this method still exists limitation. One of the main limitations is using much computational source. In this study, CFD was combined with Adaptive Neuro-Fuzzy Inference System (ANFIS) to prevail against this limitation when predicting flow field and mass flow rate in a chimney. In particular, the fluid flow and heat transfer in chimney were simulated with CFD to create dataset. Two ANFIS models were built, trained, and validated using dataset from CFD. After the training, ANFIS models can predict flow temperature, velocity and induced mass flow rate, respectively, with R-squared (R2) of 0.97, 0.997 and 0.9996 for training set, while 0.9715, 0.994 and 0.9996 for testing set; similarly, root mean squared error (RMSE) are 0.032, 1.703, 3.45x10−5 for training set, and 0.042, 1.713 and 2.95x10−5 for testing set. It is expected that the combination of CFD and ANFIS can estimate more different scenarios but using less computational time.

Solid particles impair the performance of the photovoltaic (PV) modules. The results in power losses that lower the system’s efficiency also decrease the life expectancy of the panel. An Internet of Things (IoT) based system was made to monitor, detect dust accumulation, and a cleaning system that would automatically wipe the dust on the surface of the PV solar panels. Using a specific dust sensor, it detects and monitor the amount of dust in the panel. As the dust accumulated reaches its limit, the cleaning system triggers automatically. The ambient temperature was monitored using the temperature and humidity sensor. The data will be received via internet using the Blynk app. The system will address the panel’s dust accumulation problem as it was considered one of the biggest problems globally regarding solar energy reproduction.

Using solar energy, a Trombe wall is a passive solar design in an attempt to improve the energy efficiency inside buildings. Trombe walls absorb thermal energy through a glass panel on the outside. This energy is used to heat the cold air from inside the buildings through the inlet at the bottom of the air gap between the glaze and the wall. The warm air rises and it is redirected back into the building through the outlet at the top of the air gap. The performance of Trombe walls can be improved by adding discrete heat sources. In this study, an investigation on the temperature rise and the induced flow rate of the air flow was studied with the presence of a heat source placed at different positions on the air channel. By Computational Fluid Dynamics (CFD) technique, the dimension of the heat source was varied to obtain their effects on the efficiency of the Trombe wall. An increase of 18°C in temperature was attained when the heat source was placed near the outlet of the air gap. The presence of discrete heat sources is an approach to improve the performance of Trombe walls.

With the limited water temperature dispensed by current water dispensers and the varying water temperature desired by consumers, a multiple temperature selections thermoelectric water dispenser was designed to provide the consumer’s demand. This design uses a Thermoelectric module that operates based on the Peltier effect to heat and cool the water in the respective container, thereby eliminating the harmful effects of Freon, a refrigerant used by the current water dispensers process. Arduino Uno’s implementation as a microcontroller provided consumers with a chance to input and be served with their desired water temperature. The experiment results showed that the design is accurate in providing the consumers with their desired water temperature. Thus, the implemented design is successful in meeting the objectives of the study.

Existing buildings without a fire alarm monitoring system need an alternative installation cost-effective, flexible, and scalable and will not affect the building’s aesthetics. In place of the conventional fire alarm monitoring system, an Internet of Things (IoT)fire sensor nodes were designed to monitor each room’s temperature and analog CO level and deploy through point to point technique. An IoT fire alarm monitoring system using a wireless sensor network was developed through which real-time data of temperature and analog CO level were obtained from the fire sensor nodes. The IoT fire sensor nodes were deployed from rooms LB384 to LB387. Each room has a node, and each node has its designated Internet Protocol (IP) address. The data can be easily obtained and accessed through the cloud web server, and each IoT fire sensor node will send a notification to the user of the room through the IoT ThingSpeak monitoring widget. The IoT fire alarm monitoring system reduced the installation time and did not require significant building renovations based on the assessment. With the advancement of IoT, fire detection could then be realized such that people within buildings can have a good understanding of the safety of their living environment.

Numerical simulations have been widely employed in buildings, particularly for prediction of natural ventilation. The Computational Fluid Dynamics (CFD) has been utilized successfully for prediction of the airflow and heat transfer in solar chimney, one of the common devices for natural ventilation. However, CFD requires expensive computational resources. In this study, an Adaptive Neuro-Fuzzy Inference System (ANFIS) model was tested for quick prediction of the heat transfer in a vertical solar chimney based on the data provided by a CFD model. The Nusselt number in solar chimneys at different heights and heat flux were predicted with the CFD model. The generated data were used to train two ANFIS models which were then validated with the remaining CFD data. The results show that the ANFIS models can predict the Nusselt number and mass flow rate with the maximum discrepancy between the two results of less than 5.0%.

Certain areas suffer frequent energy shortages due to their limited access to the power grid. With this notion, it is very recommended that these areas utilize alternative forms of producing electric energy. The Solar Home System (SHS) has helped millions of families gain access to electricity in Asia and requires the simplest form of a panel and battery. This setup provides a household with sufficient power for their basic needs, particularly the electrification of essential lightings and appliances. The Swarm Solar Household System (SSHS) is one of the potential ways of enjoying energy for every household for in this process, the households that need more power can connect to the interconnected households and use their energy. This research establishes a proof-of-concept for the idea of swarm solar household systems (SSHS) as an additional but beneficial feature for existing solar home systems (SHS). The IoT-based information and control system will be used to utilize SSHS powerfully. SSHS has been installed readily by each of these modeled households. Every household includes a swarm solar household system wireless connection. Monitoring the mutual power and cost process associated with this SSHS can determine the owner’s total payment. In this study, an IoT-based swarm solar household system was successfully obtained using sensors, controllers, Wi-Fi modules, and software applications via Blynk with a built-in cloud server for monitoring and controlling the connection between households; energy sharing is enabled.

An accurate simulation will assist to understand the behavior of rarefied gas flows in MEMS devices. This is useful for obtaining an optimal design for these devices. In this paper, we will comprehensively investigate the effect of viscous heat generation on the rarefied gas microflows in the microcavity and Couette flows. The considered cases have the Knudsen number ranging from 0.05 to 1, and working gas as argon. Both of the temperature jump conditions were recently derived including the viscous heat generation term such as the new type of Smoluchowski and the modified Patterson temperature jump conditions are adopted in the present work. The simulation results show that the viscous heat generation significantly affects the gas temperatures, and it makes a reduction of the gap between the CFD and DSMC data. The simulation results of the modified Patterson jump condition are close to the DSMC data for the high Kn cases, Kn = 0.5 and 1 while those of the new type of Smoluchowski jump condition are not.

Exploring solar radiation, solar chimneys are widely used in sustainable building design. Solar chimneys can ensure thermal comfort in a house by generating a heating or cooling air flow. For heating applications, the induced air flow is heated and supplied back to the house. In this study, the air flow and heat transfer in a solar chimney for heating were modelled by a numerical simulation based on Computational Fluid Dynamics (CFD) technique. An investigation on the system performance was carried out with the presence of a heated cavity above the top and below the bottom of the air channel. The length and the width of the cavity and the chimney gap have a strong influence on the flow rate and temperature rise through the chimney. The results showed that an appropriate dimension of the heated cavity can enhance the performance of the solar chimney.

Solar chimney has been widely employed for natural cooling or heating of buildings. Of its forms, wall-attached solar chimney is common. Most of previous studies examined solar chimneys with the heat source on one side of the air channel of a solar chimney. In practical applications, depending on the materials, the absorption of solar radiation can be on both sides of the air channel. Therefore, this study examines a wall-attached solar chimney with the heat source distributed on both sides of the air channel. The Computational Fluid Dynamics (CFD) model was utilized to simulate the flow dynamics and heat transfer of the problem. Performance of the solar chimney was described in terms of the heat transfer coefficient, or Nusselt number, the induced flow rate, and the temperature rise through the chimney. The results shows that the examined parameters can be improved, reduced, or unchanged depending on the gap of the air channel and the heat distribution ratio. The findings may be useful for designing wall-attached solar chimney as they show the conditions for maximizing the flow rate or the temperature rise.

As one of the most common methods for natural ventilation of building, solar chimney has been studied widely in the literature. Various forms of solar chimney have been proposed for enhancing its performance for a specific application, i.e ventilation and/or heating. In this work, we examined performance of an L-shaped comprising horizontal and vertical air channels connected serially by a numerical model based on the Computational Fluid Dynamics (CFD) method. Two different total lengths and gaps of the chimney were tested. The considered parameters included the flow rate, temperature rise, and thermal efficiency. The results show that as the horizontal portion is longer than the vertical one, the flow rate decreases while the temperature rise increases. The variation of the thermal efficiency depends on the ratio between the gap and the total length of the air channel. The findings can help to select suitable configurations of an L-shaped for a specific cooling or heating application.

A Trombe wall can be installed in buildings to reduce electricity consumption. Trombe walls are designed to absorb and store solar radiation. By thermal effects, cool air enters the air channel from the inlet and is heated during the channel’s passage. The warm air rises and is fed back into the building to achieve energy efficiency. In this study, an investigation on the induced flow rate and temperature rise was carried out with a fin’s presence by a numerical method based on Computational Fluid Dynamics (CFD) technique. The location and length of the fin were changed to improve the system performance. This work demonstrated that an increase of 16° C in temperature at the outlet can be achieved with a distance of 0.1 m between the fin and the inlet. The fin added inside the Trombe wall channel is an approach to achieve thermal comfort in sustainable building design.

Solar chimneys have been widely used for natural ventilation of buildings. It absorbs solar radiation to create stack effect to induce air flow for ventilation. To model air flow and heat transfer inside solar chimneys, numerical models based on Computational Fluid Dynamics (CFD) have been broadly employed. The size of the computational domain is one of the factors influencing computed results from CFD models. In this study, we investigated effects of the extension of the domain above the outlet of the air channel as the gap and the height of the air channel changes. Two types of the computational domains were studied. The small domain has identical physical size with a cavity inside the solar chimney while the large domain contains both the cavity and the ambient air surrounding the chimney. The induced flow rate and temperature rise of the chimney were computed and compared between those domains. It is seen that to ensure the changes of both flow rate and temperature below 1.0%, the required extension, h, of the domain above the outlet of the air channel is a function of the gap – to – height ratio G/H, not only the gap. Specifically, for G/H in the range of 0.1 – 0.4 in this study, the required h/G rises from 10 to 30.

This study investigates flow field around a building with triangular cross section by experiments and numerical simulations. The experiments were conducted in an open wind tunnel. Pressure distribution on the surfaces of a scaled model of the building was recorded at different wind speeds and wind angles. The simulation was based on Computational Fluid Dynamics (CFD) technique with computational conditions similar to those in the experiments. It was revealed that the pressure distribution on the building surfaces changed significantly with the wind angles, the direction of the surface relative to the wind angle, and position on the surface. The effect of the different wind angles in determining the drag coefficient on the building was also performed. Flow visualization with smoke and the CFD results reveal flow structure around and behind the building which strongly correlate with the measured pressure distribution on the building surface.

Experiments to examine the effects of surface roughness on the strength of rebounds from particle-wall collisions, in liquids and in air, are presented. The target walls are glass plates and have three different values of surface roughness: less than 0.3 μm, 10.5 μm, and 40.1 μm. Particles are glass beads with diameters from 1.05mm to 2.35mm. The experiments are conducted in tap water, sugar-water, and in air. Pre-impact Stokes numbers in liquids are in the range 20–170. For impacts in air, no significant effect of the surface roughness on rebound velocity is observed. In liquids, rough surfaces yield stronger rebounds than smooth surfaces. For a given ratio of surface roughness/particle’s radius, the enhancement of the surface roughness on the rebound compared to the smooth one increases when the impact Stokes number decreases toward the “rebound threshold”. These observations are in qualitative agreement with suggestions in the literature.Copyright © 2005 by ASME