An empirical estimation of underground thermal performance for Malaysian climate

In this study, the soil temperature profile was computed based on the harmonic heat transfer equations at various depths. The meteorological data ranging from January, 1st 2016 to December, 31st 2016 measured by local weather stations were employed. The findings indicted that as the soil depth increases, the temperature changes are negligible and the soil temperature is nearly equal to the mean annual air temperature. Likewise, the results have been compared with those reported by other researchers. Overall, the predicted soil temperature can be readily adopted in various engineering applications in Malaysia

Passive thermal performance prediction and multi-objective optimization of naturally-ventilated underground shelter in Malaysia

The impact of global warming has urged a prudent spending of energy in the building sector nowadays. In general, a typical HVAC system consumes about 60%e70% of the total energy consumption of a building. Therefore, designing an energy-efficient HVAC system is essential to alleviate the worsening greenhouse effect. Recent research works have reported that geothermal energy coupled with optimal insulation is the best approach in minimising the energy consumption. Thus, we attempted to analyse the thermal performance of a naturally-ventilated underground shelter in a hot and humid country such as Malaysia. We proposed an optimal design to enhance the sustainability of the low-energy building. The model was numerically simulated using CFD, and a statistical surrogate model was implemented for obtaining the optimal design. The findings indicated that the room temperature of the shelter was significantly lower than the outdoor temperature during the hottest month and vice-versa during the coldest month. Moreover, the proposed optimal design showed about 3.4% increase in ventilation rate and about 2.8% decrease in room temperature as compared to the previous design. In general, the current work could be used as a guideline for designing low-energy building in Malaysia

The potential influence of building optimization and passive design strategies on natural ventilation systems in underground buildings: The state of the art

Most of the underground buildings rely on mechanical ventilation system for achieving an acceptable indoor thermal comfort level. In order to alleviate the greenhouse effect, it is essential to incorporate a passive system in an underground building to reduce the overall building energy consumption. From the perspective of the indoor occupant, the Indoor Environmental Quality (IEQ) should be maintained at a reasonable level as well if the passive system is used in a building ventilation system. The above problem could be addressed by devising an integrated design procedure that combines both underground building simulation and design optimization methods. The review of this topic, however, is rather scarce in the open literature. Thus, this review paper assesses existing scientific literatures that address the potential influence of building optimization and passive design strategy on the control of IEQ level. The topics covered in this review paper are histories and design considerations of underground buildings, consideration factors required, concept of building ventilation system, IEQ level assessments reported by buildings’ occupants, critical element in building optimization and passive design strategy in the underground building. From the current review, we have found that integrating both optimization approach and passive design strategy into building performance simulation is a promising technique in improving the IEQ level of the underground building. Moreover, the adoptions of soil and natural ventilation can effectively reduce the energy consumption in underground conditioning system. Indeed, there are several important factors that should be taken into account while designing an underground building. Also, there are a few passive designs that can improve thermal comfort and reduce energy consumption in underground buildings. All in all, the primary target of this paper is to assist building engineers and designers in designing an energy-efficient underground building. Meanwhile, the acceptable IEQ level could be maintained

Design analysis of open and ducted propellers in UAV application

The aim of the study was to determine the feasibility of implementing a ducted propeller system for small scale drones. 5” propeller drones are common in first person view (FPV) drone racing and cinematography, increasing the likelihood of injury due to untrained pilots, of which the majority are laceration injuries due to the propeller blades. Furthermore, the addition of a duct improves the thrust output of the entire system. A few key parameters are identified, of which were manipulated to determine the optimum values through a series of ANSYS Fluent CFD simulations. Introducing a duct is shown to reduce the lift a propeller produces; however, the reduction is offset by the lift generated by the duct. Blade tip clearance was investigated, with the optimum value found to be 0.25 mm, producing the most lift from the duct and least reduction of propeller lift, and with thrust outputs up to 35.568% more in some cases compared to open propeller. It was observed that increasing the BTC significantly reduced duct lift. Diffuser length simulations provided unconclusive results, with the duct lift varying depending on the diffuser length. However, the optimum diffuser length was determined to be 65 mm with respect to thrust outputs. In comparison, inlet lip radius shows a clear pattern, deviating from the optimum value of 16.5 mm reduces the duct lift produced, with smaller values severely decreasing performance

Substitution of diesel fuel in conventional compression ignition engine with waste biomass-based fuel and its validation using artificial neural networks

This study aims to derive bioenergy from waste lather fat and citronella grass. Lather fat oil (LFO), citronella grass oil (CGO), a mixture of leather fat oil and citronella grass oil (LFCGO), and a nano-additive-incorporated mixture of lather fat oil and citronella grass oil (NFCO) were synthesized and used in diesel engines as the novelty of this study. ASTM standards were used to investigate and guarantee the fuel’s properties. According to the experimental report, the nanoadditive’s brake thermal efficiency and brake-specific fuel consumption were more comparable to diesel fuel. Compared to diesel, the NFCO blend reduced hydrocarbon, carbon monoxide, and particulate emissions by 6.48%, 12.33%, and 16.66%, respectively, while carbon dioxide and oxides of nitrogen emissions increased. The experiment’s outcomes were verified using an artificial neural network (ANN). The trained model exhibits a remarkable coefficient of determination of 98%, with high R values varying from 0.9075 to 0.9998 and low mean absolute percentage error values ranging from 0.97% to 4.24%. Based on the experimental findings and validation report, it can be concluded that NFCO is an efficient diesel fuel substitute.The Deanship of Scientific Research at King Khalid University.https://www.journals.elsevier.com/process-safety-and-environmental-protectionam2024Mechanical and Aeronautical EngineeringSDG-07:Affordable and clean energySDG-09: Industry, innovation and infrastructureSDG-12:Responsible consumption and productio

Sensitivity analysis and thermodynamic evaluation of a combined cooling, heating and power system utilizing exhaust gases of smelting furnace

Exhaust gases from the smelting furnace have high temperature and mass flow rate, and there is huge potential to use them for energy-related purposes such as electricity generation, cooling and heating. Utilization of the gases for energy-related purposes would lead to fuel savings and emissions reduction. To use this potential, it is necessary to design proper systems and cycles and apply a heat recovery unit. Several technologies are useable for heat recovery depending on the characteristics of exhaust gases, such as their mass flow rate, temperature and compositions. Due to the higher potential of combined heating, cooling and power (CCHP) generation systems compared with the systems with a single output, a CCHP is designed and investigated in the present study by consideration of the specifications of the exhaust gases. The applied system in this study comprises a Supercritical CO2 (SCO2) cycle, heat exchanger and single-stage absorption chiller for simultaneous heating, cooling and power production. Engineering Equation Solver (EES) is employed to model the proposed system by considering the properties of the flows and characteristics of the components. To get deep insight into the effective parameters on the outputs of the designed system, the impact of three factors, namely the mass flow rate of the gases, the effectiveness of heat exchanger and temperature of exhaust gases, are analyzed and investigated by the implementation of sensitivity analysis. As one of the main conclusions, it is found that an increment in the mass flow rate of exhaust gases from 30 kg/s to 70 kg/s causes augmentation in the power generation from 2037 kW to 4754 kW. Furthermore, exergy analysis is carried out, and it is found that an increase in the temperature or mass flow rate of exhaust gases or a decrease in the effectiveness of heat exchangers would lead to decrement in the exergy efficiency of the system. According to the performed sensitivity analysis, the mass flow rate of exhaust gases has the most remarkable influence on the heating and cycle-generated power among the considered factors.https://www.cell.com/heliyonhj2024Mechanical and Aeronautical EngineeringSDG-09: Industry, innovation and infrastructur

Chemical and thermal performance analysis of a solar thermochemical reactor for hydrogen production via two-step WS cycle

DATA AVAILABILITY : No data was used for the research described in the article.Ceria-based H2O/CO2-splitting solar-driven thermochemical cycle produces hydrogen or syngas. Thermal optimization of solar thermochemical reactor (STCR) improves the solar-to-fuel conversion efficiency. This research presents two conceptual designs and thermal modelling of RPC-ceria-based STCR cavities to attain the optimal operating conditions for CeO2 reduction step. Presented hybrid geometries consisting of cylindrical–hemispherical and conical frustum–hemispherical structures. The focal point was positioned at x = 0, -10 mm, and -20 mm from the aperture to examine the flux distribution in both solar reactor configurations. Case-1 with 2 milliradian S.E (slope error) yields a 27% greater solar flux than case-1 with 4 milliradians S.E, despite the 4 milliradian S.E produces an elevated temperature in the reactor cavity. The mean temperature in the reactive porous region was most significant for case-2 (x = -10 mm) with 4 mrad S.E for model-2, reaching 1966 K and 2008 K radially and axially, respectively. In case-2 (x = -10 mm) for 4 mrad S.E, model-1 attained 1720 K. The efficiency analysis shows that the highest conversion efficiency value was obtained to be 7.95% for case-1 with 4 milliradian S.E.http://www.elsevier.com/locate/egyram2024Mechanical and Aeronautical EngineeringSDG-07:Affordable and clean energ

CFD: assessment on different bed height effect over drag model of fluidized bed

Fluidized beds are widely used by various industries because of low pressure drop, uniform temperature distribution, high heat transfer rate and large contact area which enhances chemical reaction. It seems that the efficiency of the fluidized bed depends on the knowledge of the flow behaviour which are important for scaling, design and optimization. In modelling of gas-solid phase, drag force is one of the main mechanisms for inter-phase momentum transfer. Therefore in this study, 2D model of fluidized bed was developed to study the effect of using various drag models over different bed height of H/D ratio such as 0.5, 1 and 2. The drag correlations of Gidaspow, Wen Yu, Syamlal-O'Brien, Hill Koch Ladd (HKL) and Representative Unit Cell (RUC) are to be implemented using a multiphase Eulerian Granular Model (EGM) to simulate the interaction between phases. Simulation of the model is be conducted via commercial CFD software ANSYS FLUENT 14. The main contribution of this study is to identify the important of bed height during gasification process in order to contribute in the development of TNB Research of IGCC. From the results obtained show that EGM greatly suitable for dense particle flow. As overall, the result shows Wen Yu and Gidaspow drag model are suitable for dense fluidized bed application. While for Syamlal-O'Brien drag model is more suitable for all range of application. Finally for RUC and HKL can predict highest drag at volume fraction which is more likely occur in dense phase

Design optimization for ventilation shafts of naturally-ventilated underground shelters for improvement of ventilation rate and thermal comfort

A good ventilation system is essential for an underground shelter to provide a comfortable environment with better indoor air quality. Ventilation shafts are widely used for ventilation purpose in an under- ground shelter. In the current work, the position of the ventilation shaft is optimized by employing the Response Surface Methodology (RSM). Two RSMs are constructed. The first RSM is constructed by 32 CFD models via Fractional Factorial Design (FFD) and the second model is constructed by 53 CFD models via Central Composite Rotatable Design (CCRD). The first and the second models are subsequently analysed by using the linear and quadratic models, respectively. The result indicates that both models lead to similar predictions on the inputs (factors) that strongly affect the response. Moreover, the response surface values agree well with the CFD values. Based on desirability functions, the optimized design improves the ventilation system by 24.5% as compared to the actual design. Also, the optimized design meets the comfort temperature and design criteria recommended for a naturally-ventilated underground shelter. Overall, this study finds that statistical analysis is a useful tool for the improvements of venti- lation rate and thermal comfor

A machine learning-based comparative analysis of surrogate models for design optimisation in computational fluid dynamics

Complex computer codes are frequently used in engineering to generate outputs based on inputs, which can make it difficult for designers to understand the relationship between inputs and outputs and to determine the best input values. One solution to this issue is to use design of experiments (DOE) in combination with surrogate models. However, there is a lack of guidance on how to select the appropriate model for a given data set. This study compares two surrogate modelling techniques, polynomial regression (PR) and kriging-based models, and analyses critical issues in design optimisation, such as DOE selection, design sensitivity, and model adequacy. The study concludes that PR is more efficient for model generation, while kriging-based models are better for assessing max-min search results due to their ability to predict a broader range of objective values. The number and location of design points can affect the performance of the model, and the error of kriging-based models is lower than that of PR. Furthermore, design sensitivity information is important for improving surrogate model efficiency, and PR is better suited to determining the design variable with the greatest impact on response. The findings of this study will be valuable to engineering simulation practitioners and researchers by providing insight into the selection of appropriate surrogate models. All in all, the study demonstrates surrogate modelling techniques can be used to solve complex engineering problems effectively