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This research study is performed on the self-compacting geopolymer concrete (SCGC) combining coal bottom ash (CBA) and metakaolin (MK) as a substitution for GGBFS alone and combined for analysing the fresh properties (slump flow, V-Funnel, and T50 flow), mechanical characteristics (compressive, splitting tensile and flexural strengths) and durability tests (permeability and sulfate attack test). Though, total 195 SCGC samples were made and tested for 28 days. It has been revealed that the consumption of CBA and MK as a substitution for GGBFS alone and combine in the production of SCGC is decreased the workability of SCGC while mechanical characteristics of SCGC are enhanced by utilizing CBA and MK as a substitution for GGBFS alone and combine up to 10%. In addition, the compressive, splitting tensile and flexural strengths were calculated by 59.40 MPa, 5.68 MPa, and 6.12 MPa while using the 5CBA5MK as a substitution for GGBFS in the production of SCGC after 28 days correspondingly. Furthermore, the permeability is decreased by growing the quantity of CBA and MK by the weight of GGBFS alone and jointly in the production of SCGC after 28 days. Besides, the minimum change in length of the SCGC specimen is recorded by 0.062 mm at 7.5MK7.5CBA while the maximum change in length is calculated by 0.11 mm at 10CBA10MK as a substitution for GGBFS at 180 days correspondingly. In addition, the embodied carbon is recorded reduce as the addition of CBA while it is getting higher when the accumulation of MK alone or combined with CBA in SCGC. Besides, response models for prediction were constructed and confirmed using ANOVA at an accuracy rate of 95%. The models' R2 fluctuated from 88 to 99%. It has been observed that the utilization of CBA and MK alone and together up to 10% as substitution for GGBFS in geopolymer concrete provides the best results therefore it is suggested for structural applications. [ABSTRACT FROM AUTHOR]

This article presents the results of an experimental parametric study on reinforced concrete (RC) beams strengthened by an external bonding of carbon fiber reinforced polymer (CFRP) laminates to their tensile faces. This experimental work investigates the effects of both CFRP laminate sizes and concrete compressive strength on the flexural behavior of strengthened RC beams. Accordingly, a total of 10 RC beams have been cast, eight of which were strengthened in flexure by external bonding of CFRP laminate by varying its sizes, such as length, width, and thickness, and two control beams. All prepared beams were tested under standard four‐point bending until failure. The load–deflection response curves and failure modes were recorded and compared. Results show that failure modes of strengthened beams varied with the CFRP laminate characteristics from steel yielding, CFRP peeling off, and interfacial debonding laminate, Also, the load–deflection curves showed a considerable increase in the load capacity by up to 1% and 112%, compared to the unstrengthen beam, if the CFRP laminate length ratio passes from 0.40 to 0.94, respectively. In addition, the load capacity contribution increases from 56% to 112% when the CFRP laminate width increases from 50 to 100 mm. On the other hand, when laminate thickness increases from 1.2 to 2.4 mm, the load capacity contribution increases from 56% to 76%. Finally, it is concluded that the mechanical behavior of strengthened beam is strongly affected by the CFRP laminate sizes. [ABSTRACT FROM AUTHOR]

This paper presents an experimental study to evaluate the effect of various percentages of RAP on the properties of asphalt mixtures. Moreover, the thermal characteristics of using asphalt mixes with RAP in asphalt concrete blocks for sustainable application in building construction was also studied. For this issue, four mixtures, which were the combination of different ratios of RAP materials viz, 0%, 30%, 60%, 90% and virgin aggregates, were studied in this research. A comprehensive experimental program was conducted to find out the highest ratio of RAP in asphalt mixes that retains an acceptable level of physical and mechanical properties. This revealed that 90% RAP has such an acceptable level. Finally, the thermal characteristics of asphalt concrete blocks for walls in building construction were analytically investigated using TAS EDSL. This software was initially validated by building a real model of walls with asphalt concrete blocks where temperature and humidity measurements were taken through data loggers for both the indoor and outdoor spaces. A comparative study was conducted to find out the energy efficient behaviour of this material in four different climate conditions. It was concluded that the asphalt concrete mixes with 90% RAP are beneficial materials for use as a thermal mass in building construction and it is suitable only for cold weathers. [ABSTRACT FROM AUTHOR]

Prediction of solar energy data is very crucial for the effective utilization of freely available renewable energy abundantly in nature. Solar energy data are widely available which must be carefully prepared and arranged for modelling. In this work, typical meteorological year (TMY) data made available by the Korea institute of energy research (KIER) and the National renewable energy laboratory (NREL) are used for modelling in different phases. TMY data at single-point location and multiple locations from KIER are initially used for training of machine learning (ML) algorithms. Later, the TMY data from NREL and KIER are combined and then modelled using radius nearest neighbour (RNN), decision tree regressor (DTR), random forest regressor (RFR), and X-gradient boosting (XGB) algorithms. The solar energy parameters modelled in this work are dew point temperature (DPT), dry bulb temperature (DBT), relative humidity (RH), surface pressure (SP), windspeed (WS), and solar insolation of horizontal plane (IHP). Quantitative analysis of the algorithms is also performed in each stage of the work. The modelling indicates that the DBT, DPT, RH, and SP are able to be predicted with a minimum accuracy of over 90% in each stage. The WS and IHP data when modelled from a single-source TMY data provide superior accuracy than when they are combined. RFR and XGB have outperformed overall as they provide good accuracy for WS and IHP data as well. RNN and DTR achieved 100% accuracy in training, while RFR and XGB showed slightly lower training accuracy due to their avoidance of overfitting. There are errors in testing for RNN/DTR. Using RNN/DTR, the training errors are 0% in all cases, while in some cases like DTP the error by RFR/XGB up to 3%, whereas RNN/DTR testing errors go up to 5% and in case of RFR/XGB they are up to 7.5%. For RH modelling RFR/XGB, training errors are max 6%. RNN/DTR testing errors go up to 11%, while for RFR/XGB up to 7.5% which indicates their robustness. It is observed that many solar parameters, when combined with different source data, can be predicted easily with good accuracy, while WS and IHP become a little bit challenging to model. [ABSTRACT FROM AUTHOR]

Evaporative cooling, an eco-friendly and energy-efficient technique, mitigates the environmental damage caused by mechanically driven air-conditioners. Recent studies have shown that rotating humidifiers are useful for large space cooling applications due to their higher efficiency. Despite the benefits, it leads to an increase in the electrical energy consumption. Vermicompost, an excellent water storage medium, replaces the pad of conventional air coolers, thereby eliminating the pump used for water circulation and the motor used in centrifugal humidifiers. However, the amount of water storage depends on the mass of the vermicompost. The supplied water should produce continuous cooling if the vermicompost is completely soaked and operated. If all the water evaporates over a period, vermicompost may dry, necessitating additional water supply. Hence, the need arises to study the influence of the mass of vermicompost and the water supply method on the performance of vermicompost-based direct evaporative cooling systems. The present study proposes to experiment with three different masses and two modes of water supply: initial and continuous. Experimental results showed that the system produced an average effectiveness of 82 % using '500 g' and '1000 g' of vermicompost through the continuous water supply, while the effectiveness augments to 85 % using '1500 g' of vermicompost with only the initial water supply. The studies reveal that a lower mass of vermicompost with a continuous water supply is preferable for cooling in small spaces. A higher mass of vermicompost with an initial water supply is helpful for large spaces like greenhouses and livestock buildings. Hence, the present system is energy-efficient, showing an energy savings of 69.43% by neglecting the pump and motor, as in centrifugal humidifiers. Moreover, it is eco-friendly as it eliminates the pump and sump that lead to the transmission of diseases like dengue and malaria caused by insect breeding in the sump. [ABSTRACT FROM AUTHOR]

Evaporative cooling, an eco-friendly and energy-efficient technique, mitigates the environmental damage caused by mechanically driven air-conditioners. Recent studies have shown that rotating humidifiers are useful for large space cooling applications due to their higher efficiency. Despite the benefits, it leads to an increase in the electrical energy consumption. Vermicompost, an excellent water storage medium, replaces the pad of conventional air coolers, thereby eliminating the pump used for water circulation and the motor used in centrifugal humidifiers. However, the amount of water storage depends on the mass of the vermicompost. The supplied water should produce continuous cooling if the vermicompost is completely soaked and operated. If all the water evaporates over a period, vermicompost may dry, necessitating additional water supply. Hence, the need arises to study the influence of the mass of vermicompost and the water supply method on the performance of vermicompost-based direct evaporative cooling systems. The present study proposes to experiment with three different masses and two modes of water supply: initial and continuous. Experimental results showed that the system produced an average effectiveness of 82 % using '500 g' and '1000 g' of vermicompost through the continuous water supply, while the effectiveness augments to 85 % using '1500 g' of vermicompost with only the initial water supply. The studies reveal that a lower mass of vermicompost with a continuous water supply is preferable for cooling in small spaces. A higher mass of vermicompost with an initial water supply is helpful for large spaces like greenhouses and livestock buildings. Hence, the present system is energy-efficient, showing an energy savings of 69.43% by neglecting the pump and motor, as in centrifugal humidifiers. Moreover, it is eco-friendly as it eliminates the pump and sump that lead to the transmission of diseases like dengue and malaria caused by insect breeding in the sump. [ABSTRACT FROM AUTHOR]

Due to the restrictions of the diesel engine emissions and the massive demand of energy, the fossil diesel fuel has been consumed quickly and the resources cannot suffice the demand. Alternative fuels that include bio alcohols, hydrogen and biodiesel can make up the diesel fuel depletion. Biodiesel is convenient for diesel engine operation due to its properties like fossil diesel properties. Response surface methodology is a statistical approach for responses prediction and optimization using definite number of experiments to provide time and cost. This study aims to predict and optimize the performance and emission attributes; of diesel engine has single cylinder and operates at 1400 rpm constant speed fuelled with pure diesel fuel or diesel fuel blended with waste cooked oil (WCO) biodiesel at different blending ratio by using response surface methodology (RSM). The influences of the independent variables that are WCO biodiesel blend percentages and the diesel engine load values on the responses that are predicted and optimized. The WCO biodiesel/ diesel fuel blend percentages are pure diesel fuel without biodiesel (B0), 40% WCO biodiesel with 60% diesel fuel (B40) and 80% WCO biodiesel with 20% diesel fuel (B80). The experiments are performed using diesel engine runs at 1400 rpm constant speed, at varying diesel engine loads are zero, 4 and 8 kW. The design of experiments (DOE) is attempted using central composite design (CCD). The RSM model is a nonlinear model developed according to the independent variables and the responses. The homogeneity between the independent variables is studied to predict and optimize their influences on the diesel engine performance and emission attributes. The RSM model is validated according to the coefficients of regression are R2, R2 adjusted and the R2 predicted that prove the satisfaction of the results. From the experiments it is observed that diesel engine performance and emissions attributes are enhanced by increasing the diesel engine load value and increasing the percentage of WCO biodiesel blending ratio compared to pure diesel only like NOx emissions which reduced from 1200 ppm to 900 ppm at the same engine load due to the reduced combustion temperatures using WCO biodiesel. According to the response optimizer tool, the optimal responses are 17.11% for the BTE, 658.9 ppm for the NOx emissions and 1.93% for CO2 emission at independent variables are 2.6667 kW diesel engine load and 100% pure diesel fuel. [ABSTRACT FROM AUTHOR]

The concern regarding local responsive building design has gained more attention globally as of late. This is due to the issue of the rapid increase in energy consumption in buildings for the purpose of heating and cooling. This has become a crucial issue in educational buildings and especially in schools. The major issue in school buildings in Saudi Arabia is that they are a form of prototype school building design (PSBD). As a result, if there is any concern in the design stage and in relation to the selection of building materials, this will spread throughout the region. In addition to that, the design is repeated regardless of the climate variation within the kingdom of Saudi Arabia. This research will focus on the influence of the window to wall ratio on the energy load in various orientations and different climatic regions. The research will use the energy computer tool TAS Environmental Design Solution Limited (EDSL) to calculate the energy load as well as solar gain. During the visit to the sample schools, a globe thermometer will be used to monitor the globe temperature in the classrooms. This research introduces a framework to assist architects and engineers in selecting the proper window to wall ratio (WWR) in each direction within the same building based on adequate natural light with a minimum reliance on energy load. For ultimate WWR for energy performance and daylight, the WWR should range from 20% to 30%, depending on orientation, in order to provide the optimal daylight factor combined with building energy efficiency. This ratio can be slightly greater in higher altitude locations. [ABSTRACT FROM AUTHOR]

The increasing demand for cement has substantially affected the environment, and its manufacturing requires substantial energy usage. However, most countries in the world recently encountered a significant energy problem. So, researchers are exploring the use of agricultural and industrial waste resources with cementitious characteristics to minimize cement manufacturing, cut energy consumption, and contribute to environmental protection. Therefore, this research is performed on roller compacted concrete (RCC) reinforced with 5%, 10%, 15%, and 20% of corn cob ash (CCA) as substitution material with different percentage of cement and 0.25%, 0.50%, 0.75%, and 1% of jute fibre (JF) together for determining the mechanical properties and embodied carbon (EC) by applying response surface methodology (RSM) modelling. The cubical samples were prepared to achieve the targeted strength about 30 MPa at 28 days and then obtained mix proportions were employed for all combinations at various water-cement ratios to maintain roller-compacted concrete's zero slump. Results showed that at 0.50% JF and 10% CCA, the flexural strength, splitting tensile strength and compressive strengths, and modulus of elasticity of RCC obtained were 5.3 MPa, 3.8 MPa, 32.88 MPa, and 33.11 GPa at 28 days, respectively. Besides, the embodied carbon of RCC is recoded reducing with combined addition of different levels of JF and CCA as compared to control mixture. In addition, the generation of response prediction algorithms was performed using analysis of variance (ANOVA) at a threshold of significance of 95%. The coefficient of determination (R2) readings for the statistical models ranged from 96 to 99%. It is observed that the use of 0.50% of JF along with 10% of CCA as cementitious constituent in RCC provides best outcomes. Therefore, this method is a superior choice for the construction industry. [ABSTRACT FROM AUTHOR]

The development of eco-friendly materials is a challenging one in the research field. Natural fibers are more accessible, biodegradable, inexpensive, and less dense. They offer fewer health risks and are eco-friendly compared to synthetic fibers. Natural fiber-reinforced polymer composites are new, eco-friendly materials with excellent mechanical and practical applications. Adding biofillers to composites improves strength and will replace synthetic materials. Utilizing cellulose as a filler for a natural starch matrix is an effective way to reduce the environmental impact of non-biodegradable materials. This study covers the influence of natural Borassus flabellifer flower microcrystalline cellulose (BFF MCC) fillers on banana fiber-reinforced polymer matrix composites. Fourier-transform infrared spectroscopic peaks at 2357, 1730, and 1245 cm-1 were absent. This indicates that the amorphous proportion of banana fiber mat/BFF MCC-reinforced hybrid composites decreased. At 1% BFF MCC, thermogravimetric examination revealed an increase in the peak temperature of maximum degradation (389.6 °C). The hybrid banana composite's tensile strength (31.36 ± 4.39 to 39.83 ± 3.07 MPa) and flexural strength (71.05 ± 2.66 to 82.4 ± 1.66 MPa) were also improved after adding 3% BFF MCC as filler material. The primary objective is to evaluate the suitability of fiber-reinforced hybrid polymers with natural fillers for future engineering applications such as automotive parts, construction materials, 3D printing, etc. In addition, this study investigated how the reinforcement of microcrystalline cellulose can result in a material with enhanced performance as well as its mechanical characteristics (XRD, FTIR, TGA, and SEM characterization). [ABSTRACT FROM AUTHOR]

Hybrid oils ensure multifaceted technological (self‐lubricating and favorable fatty acid properties), and sustainable (environmental, economic, and societal) benefits towards biodiesel conversions. The hybrid oils (Hydnocarpus wightiana oil and waste cooking oils [40:60 v/v]) were synthesized to methyl ester with alkaline catalyst sodium hydroxide through the base‐transesterification process. The resulting hybrid oil methyl ester (HOME) is 96.68%. The crude oil (CO) and its HOME underwent characterization using gas chromatography–mass spectrometry, Fourier transform infrared spectroscopy, and hydrogen‐1 nuclear magnetic resonance spectroscopy. The physicochemical properties of crude oils and hybrid biodiesel were analyzed and compared to pure diesel. Different blends of biodiesel–diesel, including binary (20% HOME + 80% diesel [D]), ternary (60% D + 20% HOME + 20% heptanol [H]), and quaternary (20% HOME + 20% H + 10% CO + 50% D) blends, were tested in a single‐cylinder compression ignition (CI) engine under various load conditions to assess their performance, emissions, and combustion properties. Experimental findings indicate that the addition of heptanol to diesel or hybrid biodiesel (ternary blend) enhances brake thermal efficiency, reduces brake‐specific fuel consumption, and leads to longer ignition delays, resulting in higher internal combustion pressure and thermal energy release rates compared to the quaternary blend. Additionally, compared to pure diesel, the ternary blend exhibits decreased emissions of carbon monoxide (CO) and hydrocarbon (HC), with a slight increase in nitrous oxide (NOx) and carbon dioxide (CO2). Notably, the ternary blend emerges as a distinct alternative biodiesel blend suitable for direct use in CI engines without requiring any engine modifications. [ABSTRACT FROM AUTHOR]

In this experimental study, we explore the potential enhancements in thermal conductivity while investigating alterations in latent heat and phase change temperature within Composite Phase Change Materials (PCMs). These composites consist of Paraffin Wax (PW) as the base material, incorporating dispersed conducting Polyaniline (PANI) powder in varying concentrations ranging from 1% wt. to 4% wt. The mass fractions of PANI added to PW include 1%, 2%, 3%, and 4%, and the composite PCMs are meticulously prepared through ultrasonication. Examining the surface morphology of Composite Phase Change Materials (PCMs) involved utilizing a Scanning Electron Microscope (SEM), while the determination of thermal conductivity employed a Heat Flow Meter. Additionally, latent heat and phase change temperatures were assessed through Differential Scanning Calorimetry (DSC). The obtained results indicate an augmentation in the thermal conductivity of the composites when compared to Paraffin Wax (PW). Specifically, thermal conductivity exhibited a 40% increase for 1% wt. of PANI, yet experienced a subsequent decline for the remaining weight percentages. Furthermore, the latent heat and phase change temperatures of the composites were observed to decrease in comparison to PW. These composite PCMs with enhanced thermal conductivity, achieved through the incorporation of Polyaniline in Paraffin Wax, are highly potential for several applications in energy storage systems, thermal regulation devices, and heat management technologies. [ABSTRACT FROM AUTHOR]

One of the most important functions of buildings is to provide comfort with minimum reliance on energy consumption. Many research focuses on the physical part of the building, which has resulted in a lack of investigation considering design and configuration. After the announcement of the Saudi vision of 2030, which aims to improve building performance, the aim of this research is to investigate the influence of models and sub-models of complex architectural configurations in various climatic regions. This will not only have its impact in the kingdom of Saudi, but it will also benefit users and institutions globally. These models have not been investigated before in terms of energy performance and thermal comfort, which makes this research highly essential. The research will use TAS EDSL modelling, which is considered as one of the most powerful and advanced tools for predicting buildings' energy performances. It can be seen that in all regions, the relationship between the indoor temperature and relative humidity has an inverse pattern. Having high relative humidity will make it difficult to achieve indoor comfort temperatures levels for the users with higher indoor air temperatures. This might require an increase in the indoor air velocity by natural pressure or even by mechanical means, such as fans. It will be concluded that linear and radial shapes are not recommended for extreme regions, whether they be hot or cold. [ABSTRACT FROM AUTHOR]

This study investigates the impacts of hydrogen (H 2) induction along with injected liquid honne biodiesel (BHO)/uppage biodiesel (BUO) as secondary pilot fuel in diesel engine. The effects of compression ratio (CR), hydrogen fuel flow rate (HFR) and different combustion chamber shapes in dual fuel (DF) mode were investigated. In the first phase of experiments, the effects of three different CR (15.5, 16.5, and 17.5) on engine efficacy and emission were presented. In the second phase, the effects of three HFR (0.1, 0.17, and 0.24 kg/h) on engine efficacy and emission, as well as the maximum possible HFR were reported. In the last phase, performance with different combustion chambers i.e., Hemispherical Combustion Chamber (HCC), Toroidal Reentrant Combustion Chamber (TRCC), and Toroidal Combustion Chamber (TCC) at maximum possible CR and HFR was highlighted. The study revealed that for knock free operation of the DF engine, the highest probable HFR was 0.24 kg/h at a CR of 17.5, fuel IT of 27obefore top dead center (bTDC) and injector opening pressure (IOP) of 250 bar. The toroidal re-entrant combustion chamber (TRCC) shape yielded 8%–12% better brake thermal efficiency (BTE) with lower emissions but 20–29% higher oxides of nitrogen (NOx) at 80% load in DF mode as contrasted to the single CI mode. Both peak pressure (PP) and heat release rate (HRR) were 12–15% higher. Response surface methodology (RSM) was used to design the experiments and to carry the optimization process. Artificial Neural Network (ANN) was used to forecast the performance and emission behaviors of the test engine. The findings demonstrated that RSM and ANN were excellent modelling techniques with good accuracy. In addition, ANN's prediction performance (R2 = 0.975 for BTE) was somewhat better than RSM's (R2 = 0.974 for BTE). Both the techniques were found to be successful in terms of agreement with experimental findings with ratios varying from 95% to 98% respectively. The prediction of BTE and NOx was also carried using different machine learning algorithms. It can be seen that R2 value for these models were slightly lower than ANN and RSM models indicating good predicting capability of ANN modelling. • Hydrogen induction along with liquid honne biodiesel (BHO)/uppage biodiesel (BUO) as secondary pilot fuel. • Compression ratio, hydrogen fuel flow rate and different combustion chamber shapes in dual fuel (DF) mode. • Toroidal re-entrant combustion chamber (TRCC) shape yielded better 8%–12% BTE with lower emissions. • 20%–29% higher oxides of nitrogen (NOx) at 80% load in DF mode was obtained as contrasted to the single CI mode. • ANN and RSM models predict the performance and emission values having 95% accuracy compared to experimental findings. [ABSTRACT FROM AUTHOR]

Solar dish Stirling system (SDSS) has generated power in rural, urban, and isolated places. Its performance is affected by weather, irradiance, wind speed, dish diameter, receiver diameter, and type of Stirling engine (SE). The modelling and design changes enhance the SDSS performance. This study covers SDSS performance optimization, design recommendations, and case analysis. The study encompasses a review of investigations of SDSS in several nations and SDSS facilities with wide examination in several domains such as solar power plants, hybridization and storage, micro-co-generation, water desalination, and solar cookery. This paper provides detailed information on SDSS performance improvement modelling and design adjustments. Reviewing the modelling and design modification studies, important findings are presented, and optimum design parameter values at specific sites are offered. The range of output power in the reviewed literature varies from 0.103 kW to 58 kW, and the overall efficiency of the system (ηSystem) is between 10.41% and 25%. The current work has the study of SDSS modelling applied to a case study in Solan City (India), based upon which optimum design recommendations and direction of future research are suggested. The study estimates SDSS’s maximum efficiency and output power as 26.17% and 40.43 kW, respectively. [ABSTRACT FROM AUTHOR]

Pavement design is a long-term structural analysis that is required to distribute traffic loads throughout all road levels. To construct roads for rising traffic volumes while preserving natural resources and materials, a better knowledge of road paving materials is required. The current study focused on the prediction of Marshall stability of asphalt mixes constituted of glass, carbon, and glass-carbon combination fibers to exploit the best potential of the hybrid asphalt mix by applying five machine learning models, i.e., artificial neural networks, Gaussian processes, M5P, random tree, and multiple linear regression model and further determined the optimum model suitable for prediction of the Marshall stability in hybrid asphalt mixes. It was equally important to determine the suitability of each mix for flexible pavements. Five types of asphalt mixes, i.e., glass fiber asphalt mix, carbon fiber asphalt mix, and three modified asphalt mixes of glass-carbon fiber combination in the proportions of 75:25, 50:50, and 25:75 were utilized in the investigation. To measure the efficiency of the applied models, five statistical indices, i.e., coefficient of correlation, mean absolute error, root mean square error, relative absolute error, and root relative squared error were used in machine learning models. The results indicated that the artificial neural network outperformed other models in predicting the Marshall stability of modified asphalt mix with a higher value of the coefficient of correlation (0.8392), R2 (0.7042), a lower mean absolute error value (1.4996), and root mean square error value (1.8315) in the testing stage with small error band and provided the best optimal fit. Results of the feature importance analysis showed that the first five input variables, i.e., carbon fiber diameter, bitumen content, hybrid asphalt mix of glass-carbon fiber at 75:25 percent, carbon fiber content, and hybrid asphalt mix of glass-carbon fiber at 50:50 percent, are highly sensitive parameters which influence the Marshall strength of the modified asphalt mixes to a greater extent. [ABSTRACT FROM AUTHOR]

Summary: Analysis of hotspots in battery system is important as it indicates the thermal stresses arising and the occurrence of thermal runways. The battery heat generation and coolant flow system are together studied in this work using finite volume method. The role of different class of coolants like nanofluids, gases, oils, and liquid metals combined with the variations in spacings between the battery cells is specifically focused. In addition, effect of battery aspect ratio, coolant velocity, and their thermal conductivity are analysed in detail. The hotspots intensity and their locations are accessed for all the factors mentioned above. Later, using modern algorithms like X‐gradient boosting (XGB) and decision tree (DT) the predictions of hotspots and their locations is performed. From the numerical analysis, it is found that the hotspots get affected by changes in the chosen parameters except aspect ratio. It is found that, in an operating range of battery system with different heat generations and coolants, there is always a limiting value above/below which simply increasing/decreasing the parameter, does not reduce battery hotspots for sustainable performance. Both the algorithms used, predict the hotspot with a low accuracy of R2 value 0.55 and 0.53 using DT and XGB algorithm. The hotspots location is predicted with high accuracy having R2 value close to 0.92 from both the models. [ABSTRACT FROM AUTHOR]

Coniferous forest residue, such as pine needles, has enormous potential in Himalayan territories and could play a significant role in energy supply. The present work, for the first time, investigates the fluidization; combustion performance; and collected fly ash analysis. Experimental results on the cold state show the mixing characteristics of pine needles with silica sand indicate that the 3-mm pine needles with 2% concentration mix well with bed material (silica sand) at fluidization number (FN = 4). The results show that among the four different cases considered for the mixing characteristics of pine needle and silica sand, concentration of pine needles and fluidizing velocity have been employing a substantial impact on the mixing characteristics during fluidization. However, improper mixing was found because of little segregation above and below FN = 4. The combustion studies on pine needles conducted in excessive air atmosphere in FBC had achieved combustion efficiency (ηCombustion) over 73.19%; the temperatures of the dilute phase region were found to higher than the combustion zone, and secondary air pours have no significant effect on flue gas temperature. The results show that the pine needles are easily combusted inside the combustor, and broad work is required for effective usage of a critical portion of pine needles as a feedstock. SEM/EDS analyzes the morphology and compositions of ash and sand. The fly ash elemental heterogeneity is analyzed by using compositional analysis. Finally, the fly ash suggests the evaluation indexes for pine needles with the help of SEM/EDS, elemental analysis and ash fusion temperature. There was no agglomeration found during the period of tests under-considered operating conditions at an average temperature of 817 ºC and received 15–20% unburned carbon in the fly ash sample. Generally, the pine needles characteristics are tremendous valuable source of power and heat. This can provide basal knowledge and may further help the researchers and academics who are working in this area. The present work showed a good agreement to generate future opportunities for using pine needles (forestry litter) in combustion technology. [ABSTRACT FROM AUTHOR]

In this study, the comparative study of the peristaltic flow of Newtonian and non‐Newtonian fluids under the consideration of the magnetic field in the porous inclined channel is investigated. The effects of velocity slip and convective boundary conditions are also considered. Moreover, the variable liquid properties are also taken. The mathematical model is developed with the help of the Jeffrey fluid model in the form of partial differential equations. After that, convert them into dimensional form by using the dimensionless quantities. The resultant system of equations is solved through the perturbation method and presented the solution of velocity, temperature, and concentration in analytical form. The impact of physical parameters on the velocity, temperature, and concentration profiles are highlighted with the help of the graphs. The outcomes revealed that the magnetic parameter slows down the velocity of the fluid while the Darcy number enhanced the velocity and temperature distribution and suppressed the concentration profile. [ABSTRACT FROM AUTHOR]

Different meta-heuristic optimization algorithms have been used in a variety of fields due to their intelligent behavior and fast convergence. However, use of these algorithms in the engine behavior optimization is very-limited. The development of so-called hybrid optimization technique when these algorithms are combined with experimental design technique is an upcoming method in the field of renewable energy. Hence in this research, meta-heuristic optimization algorithms and experimental design methods were combined to optimize the engine behavior. Additionally, artificial neural networks (ANN) were employed to forecast the performance and emission behaviors of a CI engine running on a novel hybrid biodiesel blend of Cucurbita pepo. L (pumpkin) and Prosopis juliflora , mixed with a novel Elaeocarpus ganitrus (Rudraksha) additive. To assess the success of the ANN, four statistical benchmarks (R2, and MSE) were used. Experiments were designed according to Design of Experiments (DOE) rules with performance and emission parameters as outputs. Response surface methodology (RSM) was employed to find the effect of interaction factors. Single objective and multi-objective optimization using highly efficient hybrid RSM-particle swarm optimization (RPSO) and dragon fly algorithm (RMODA) were employed to optimize the response of the obtained RSM equations. The outcomes demonstrated that RSM and ANN were excellent modelling techniques for these kinds of situations, with good accuracy. In addition, ANN's prediction performance (R2 = 0.978 for BTE) was somewhat better than RSM's (R2 = 0.960 for BTE). On the other hand, the PJB20 blend with 5 mL additive increased BTE by 52.8% and reduced BSFC by 34.9% at maximum load. The smoke opacity was lowered by 7.1% when compared to pure diesel, without any engine modifications. CO 2 emission was seen to be shortened by 19.14%. Finally, it can be concluded that this novel biodiesel can be possibly utilized in CI engines with no modification and the engine characteristics can be controlled by optimization and prediction models. [Display omitted] [ABSTRACT FROM AUTHOR]

In this study, a new procedure for drying of cashew kernels is proposed. The new methodology involves the use of solar air dryers to remove the dark sticky coating called testa on the surface of the cashew kernel to get the final product. There are several challenges in the new procedures, especially with respect to the moisture level to be retained in the cashew kernel post drying for facilitating the optimal peeling activity. In this regard, thermal performance is carried out through a set of experimental and computational trials. The experiments have revealed that the natural and forced convection solar dryers with drying speeds of 1.0 kg/h and 1.66 kg/h, respectively, showed drying efficiencies of 51.7% and 50.9%, which is within the permissible acceptable limit, thus ascertaining a moisture reduction of 40 to 42% in each of case and keeping the moisture content within the band of approximately 5%, required for effective peeling of the testa from the cashew kernel to obtain the final product. This new method has resulted in batch drying of cashew kernels of up to 30 kg capacity in a time span of 360 minutes of solar irradiation with an average consumption of 255 kJ. The results of the experiments are also validated from the artificial neural network (ANN) and response surface methodology (RSM) modelling, resulting in better prediction and optimization of the performance parameters. The error between the actual and experimental values is well within the permissible limit of +/-5%, thereby correlating the experimental and statistical values for deriving an ANN model for predicting the results for different time duration and solar irradiation. In this way, the thermal analysis of the solar dryers for drying cashew kernels has resulted in findings, which shall be utilized to improve the overall performance efficiency and the methodology adopted for maximum yield. [ABSTRACT FROM AUTHOR]

The issue of freshwater shortage is a general problem that touches almost all human beings, and everyone is trying to find creative and practical solutions to try to overcome this problem. In this paper, the proposed desalination system consists of a modified solar still (MSS), parabolic trough solar collector (PTSC), separation unit (SU), and two external condensers (EC). The idea of this proposed device is that the PTSC was utilized to heat the saline feed water to a temperature from which steam can be extracted, and then a separation is made for this steam from the remaining water that has risen in temperature and has not been evaporated to be used as feed water for MSS. Also, MSS has been modified by making all its walls (except for the back wall of the distiller) of glass to obtain a greater amount of absorbed solar radiation. Besides, a double glass cover for MSS was used instead of the single glass sheet to prevent the heat loss to the atmosphere through the glass cover. The double glass cover is two sheets of glass between which there is a slight vacuum pressure. Regarding the experimental tests conducted through July 2021, the main conclusions of this work can be pointed. It was revealed that at 12:00, the maximum water temperature of PTSC was 55 °C at 20 L/hr (0.33 L/min), where the solar radiation was 1050 W/m². Besides, the effectiveness of PTSC was 60%, and the total accumulated productivity of PTSC was 83 L/daytime (daytime = 9 hrs). Moreover, the total accumulated productivities of conventional solar still (CSS) and MSS with double glass cover were 3330 and 2325 mL/m².daytime, respectively. Therefore, the productivity of MSS with double glass cover was smaller than that of the CSS by about 30%. In addition, the total accumulated freshwater distillate of CSS and MSS with double glass and condenser was 3370 mL/m².daytime and 6150 mL/m².daytime, respectively. As a consequence, the productivity of MSS with double glass and condenser was more than that of CSS by around 82.50%. In addition, the thermal and exergy efficiencies were 31% and 2.54%, respectively for CSS and 47.5% and 3.95%, respectively for MSS with double glass and condenser. Besides, the total productivity of the hybrid system (PTSC and MSS together) was reported as 91.0 L/daytime. Also, the cost of distilled water of proposed hybrid system is 0.008 $/L, and payback period of costs on proposed system is three months. Moreover, the environmental parameters of EPF, ϕ C O 2 , and Z ′ for MSS are slightly more than the double of that for CSS. [ABSTRACT FROM AUTHOR]

The existence of man is dependent on nature, and this existence can be disturbed by either man-made devastations or by natural disasters. As a universal phenomenon in nature, symmetry has attracted the attention of scholars. The study of symmetry provides insights into physics, chemistry, biology, and mathematics. One of the most important characteristics in the expressive assessment and development of computational design techniques is symmetry. Yet, mathematical models are an important method of studying real-world systems. The symmetry reflected by such a mathematical model reveals the inherent symmetry of real-world systems. This study focuses on the contagious model of pine wilt disease and symmetry, employing the q-HATM (q-Homotopy Analysis Transform Method) to the leading fractional operator Atangana–Baleanu (AB) to arrive at better understanding. The outgrowths are exhibited in the forms of figures and tables. Finally, the paper helps to analyze the practical theory, assisting the prediction of its manner that corresponds to the guidelines when contemplating the replica. [ABSTRACT FROM AUTHOR]

In the wake of the United Nation's Sustainable Development Goals—zero hunger and affordable modern/clean energy for all—many developing countries have taken serious steps in recent years to increase clean energy access for the rural population. The government of Pakistan has similarly made numerous efforts to promote the use of clean energy sources in the rural areas of the country. Therefore, this study examines rural households' energy choices for cooking and lighting in Pakistan. In doing so, a comprehensive dataset is collected from three different districts of Pakistan between 2020 and 2021, and multivariate probit (MVP) model and Chi-square tests are employed. The Chi-square results indicate that the age, education level, and occupation of the household-head; household size and income; distance to market and wood source; and biogas system ownership are the significant factors affecting cooking choices. The MVP results show that an increase in education level, school-going children, access to credit facilities, and gender (female) are the key positive factors, whereas an increase in the distance to nearest market/road, household size, and age are the factors that negatively affect the likelihood of using clean energy sources for lighting. While comparing the propensity to use modern/clean energy fuels across the three districts, infrastructural development and literacy rate were found to be crucial factors. [ABSTRACT FROM AUTHOR]

[Display omitted] • Magnetite and lead slag aggregates improvement the physico-mechanical properties of concrete. • Slump values of concrete decreases while density and strength increases upon replacing sand by the fine magnetite and lead slag. • Concrete mix containing lead slag aggregate has higher mechanical properties and enhances the attenuation properties for fast and thermal neutrons, gamma rays compared to magnetite and dolomite concrete. For nuclear power plants construction, each country has to make use of its own available raw materials. Therefore, through the current research we had to search for the relevant local materials suitable for usage as concrete components and satisfy the needed requirements. The target of this research is to investigate the effect of some type's heavy aggregates on the physico-mechanical properties and attenuation coefficient of the high performance heavy concrete used as radiation shielding of nuclear facilities. For this purpose radiation shielding properties of high performance heavy concrete mixture prepared using different types of heavy aggregates such as magnetite in addition to industrial waste of lead slag as a coarse aggregate and fine aggregate of local sand or replacing sand by fine magnetite or lead slag, were investigated comparatively with hardened dolomite concrete. The physico-mechanical properties of type aggregates and hardened concretes were examined. Gamma transmission parameters for the studied concrete for Cs137 and Co60 as gamma source were measured, also the effective removal cross-section (ΣR) of fast neutrons spectra for a wide range of neutron energies of [2–12 MeV] with thicknesses 4, 6, 8, 10 and 12 cm of heavy concrete mixes for Plutonium-Beryllium as neutrons source. While the thermal neutrons tests were performed using californium radioisotope. An innovative material that the current research has introduced to be used as a heavy coarse aggregate in HPC is "lead slag", lead slag has been converted from a subsidiary industrial and environment polluting waste to a very valuable material as one of the ingredients of heavy concrete. It was found that, the magnetite and lead slag aggregates improved the physico-mechanical properties of heavy concrete compared to dolomite concrete. Replacing fine sand by the fine aggregates of magnetite or lead slag enhances the efficiency of attenuation by the concrete mixes against these radiations and the compressive strength values increase by 12 and 27% respectively, of heavy concrete after 28 days. The concrete mix containing lead slag aggregate has higher mechanical properties and enhances the attenuation properties for fast neutrons, gamma rays and thermal neutrons than the other concrete mixes. [ABSTRACT FROM AUTHOR]

This work aimed to optimize the parameters of discrete multi-arc shaped ribs (DMASRs) in a solar air heating system (SAHS) through multi-criteria decision-making techniques. In the experiment, the roughness parameters of DMASRs were varied to find the best parameter combination for optimal SAHS performance. The relative rib height (H r / H) was varied from 0.025 to 0.047 , and the relative rib pitch (P r / H) was varied from 0.58 to 3.1. The results obtained for the Nusselt number and friction factor, which determine the performance of the SAHS system, depend on the geometrical parameters of the roughness. The parameters of DMASRs did not show any discernible trend. Hence, a multi-decision criteria approach that uses criteria importance through inter-criteria correlation (CRITIC) and complex proportional assessment (COPRAS) hybrid techniques was employed to determine the best parameter combination for optimal performance. The novel aspect of this study includes the use of a hybrid method (experimental and analytical) to optimize the performance of SAHS roughened with DMASRs hindrance promoters and predictions of outcomes using a hybrid CRITIC-COPRAS approach. The experimental and analytical examination through the use of the hybrid CRITIC-COPRAS approach is an essential component of this research that contributes to the optimization of the design parameters of such SAHS. The finding demonstrated that when R e = 19000, P r / H = 1.7, and H r / H = 0.047 were reached, the SAHS obtained an optimal thermohydraulic performance of 4.1. [ABSTRACT FROM AUTHOR]

• Investigated the pore size effect on engine characteristics. • Fuelled the engine with hybrid nanoparticles-added waste cooking oil biodiesel. • Discussed engine performance, combustion, and emission behaviors. • Detected the smaller pore size is better for engine outputs. Environmental research is currently one of the most significant and pertinent fields of studies. Due to CI engines' unique nature, they are widely used in densely populated cities for a variety of purposes. However, due to their improper combustion for various acceptable reasons at the engine cylinder, they considerably pollute the environment. This study prepared hybrid nano fuel from waste cooking oil by adding Al 2 O 3 (aluminum oxide) and MWCNT (multi-wall carbon nanotubes) particles and adding ZnO (zinc oxide) nanoporous material fixture in the combustion chamber as an attachment for enhancing combustion efficiency to meet the aim of mitigating the CI engine emissions significantly. The research was evaluated in a 5.2 kW CI engine, and the ZnO nano-porous material is fixed to the combustor. Four distinct pores per inch (PPI) nanoporous materials of pore counts such as 60, 45, 30, and 15 PPI were considered to test the fuels such as diesel and hybrid nanofuel. The hybrid nano-fuel was created from the WCO biodiesel by mixing nanoparticles of MWCNT and Al 2 O 3 nanoparticles in the ultrasonicator. The experiments were carried out at different engine loads from no load to full load with a 25% step-up. The performance of the results was compared with conventional diesel fuel with and without ZnO nano-porous material fixtures and ZnO nano-porous material fixtures with different PPI. The result exhibited that the nanoparticles-added biodiesel fuel in 15 PPI has produced less NOx emission, CO emission, and heat release rate by 55.2%, 7%, 26.5%, and 22.67%, respectively, and this combination also exhibited an improvement of 2.62% in the brake thermal efficiency. Finally, the present work proves that better engine characteristics are generally obtained as the pore size of nanoporous materials in the engine bowl gets smaller, and the hybrid nanoparticles usage in the biodiesel fuel ensures more efficient engine combustion, performance, and emission characteristics. [ABSTRACT FROM AUTHOR]

The purpose of the present study is to evolve an alternate non-edible source for the synthesis of biodiesel and use it as a fuel substitute in diesel-ethanol blends for DI-CI engines. The use of discarded poultry fat feedstocks for the sustainable production of biofuels in the current day scenario is a novel approach that is still in its embryonic stage. For the effective utilization of these processed biofuels, it is very much required to ascertain the characteristics and their performance attributes for different blends. In this regard, a set of experiments are planned to study the emission and performance attributes of a direct injection (DI) diesel engine operating on poultry fat biodiesel, and the three proportions of diesel-biodiesel-ethanol blends with varying vol. % over the wide load range on a diesel engine. The ethanol percentage in the blend is varied from 5 vol % to 15 vol % in increments of 5 vol % with the amount of poultry fat-based biodiesel kept constant at 10 vol %. The performance and emission characteristics, particularly, the CO, CO 2 , NOx, unused Oxygen, and hydrocarbon emissions are experimentally determined for different fuel blends. From the results, it is evident that the performance characteristics of the fuel blends improve with the addition of ethanol in the diesel-biodiesel blend. Further, regression modeling of the performance characteristics is carried out to optimize the blend and operating load conditions, and the regression model is evolved for developing a mathematical relation for predictions of the results for different operating conditions. Also, Artificial Neural Network (ANN) modeling of the performance characteristics is carried out at each stage to predict the outcomes for different blends and load conditions and provide a set of empirical relations for analyzing the performance characteristics of the engines operating on poultry fat-based biodiesel-diesel-ethanol blends. Excellent predictions are obtained using regression modeling and ANN with R-squared values above 0.9. Thus, the present work provides a newer model of effectively using the ANN for the systematic study of the performance characteristics of the biodiesel blends obtained from a set of experiments through various optimization methods for better performance and a significant reduction in emissions. [ABSTRACT FROM AUTHOR]

The current study is aimed to analyze the mechanical buckling of a three-layered microplate made from honeycomb structures sandwiched between two piezoelectric face sheets. The microplate is located on an elastic foundation that stands both normal and shearing loads. Minghui and Jiuren relations were employed to determine the effective mechanical properties of the honeycomb core. The sinusoidal shear deformation theory (SSDT) was also employed as a higher-order theory with trigonometric shear deformation function to describe the displacement components. The governing equations were derived using the virtual displacement principle and modified couple stress theory (MCST) was employed to predict the results in micro dimension. Navier's solution method was chosen to analytically extract the critical buckling loads for a simply supported edges microplate. The effect of the most important parameters such as geometrical specifications of the honeycomb core on the results was also considered and discussed. Nowadays the honeycomb structures are widely used in different areas of sciences and technologies due to their lightweight and high stiffness. Also, the piezoelectric materials are applied as sensors and actuators in smart engineering structures. Therefore, the outcomes of this study may help in designing and manufacturing more applicable structures and smart devices capable of tolerating loading conditions, especially in small dimensions. [ABSTRACT FROM AUTHOR]

Recently, the phyco-synthesis of nanoparticles has been applied as a reliable approach to modern research field, and it has yielded a wide spectrum of diverse uses in fields such as biological science and environmental science. This study used marine natural resource seaweed Sargassum myriocystum due to their unique phytochemicals and their significant attributes in giving effective response on various biomedical applications. The response is created by their stress-tolerant environmental adaptations. This inspired us to make an attempt using the above-mentioned charactersitics. Therfore, the current study performed phycosynthesis of titanium dioxide nanoparticles (TiO 2 -NPs) utilising aqueous extracts of S. myriocystum. The TiO 2 -NPs formation was confirmed in earlier UV–visible spectroscopy analysis. The crystalline structure, functional groups (phycomolecules), particle morphology (cubic, square, and spherical), size (∼50–90 nm), and surface charge (negative) of the TiO 2 -NPs were analysed and confirmed by various characterisation analyses. In addition, the seaweed-mediated TiO 2 -NPs was investigated, which showed potential impacts on antibacterial activity and anti-biofilm actions against pathogens (Staphylococcus aureus , S. epidermidis , Escherichia coli , Proteus vulgaris, Pseudomonas aeruginosa, and Klebsiella pneumoniae). Additionally, some evaluations were performed on larvicidal activities of TiO 2 -NPs in oppose to Aedes aegypti and Culex quinquefasciatus mosquitos and the environmental effects of photocatalytic activities against methylene blue and crystal violet under sunlight irradiation. The highest percent of methylene blue degradation was observed at 92.92% within 45 min. Overall, our findings suggested that S. myriocystum mediates TiO 2 -NPs to be a potent disruptive material for bacterial pathogens and mosquito larvae and also to enhance the photocatalytic dye degradation. [Display omitted] • Sargassum myriocystum aqueous extracts were used to synthesize TiO 2 -NPs. • Synthesized TiO 2 -NPs have enhanced antibacterial and antibiofilm activity against pathogens. • Examined the larvicidal activity of mosquito vectors Aedes aegypti and Culex quinquefasciatus. [ABSTRACT FROM AUTHOR]