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Abstract This study aims to reach a sustainable solution for waste management of medical plastics through value-added product extraction. It uses the DOE technique to examine the effect of natural zeolite and synthetic Al2O3 and SiO2 as catalysts. A small lab-scale pyrolysis setup was used for medical plastic waste management treatment. Pyrolysis of medical plastics with temperature range (350–450 °C), three catalysts, and wt.% are examined. This process is designed for 3 factors and 3 levels, such as type of catalyst, catalyst wt.%, and temperature, to create an L9 orthogonal array. At the same time, the heating rate and residence time are maintained constant at 5 °C/min and 75 minutes, respectively. Furthermore, this study analyzed the input variables in catalytic pyrolysis using response surface methodology. As a result of the study, generating the regression equation for oil yield, F and P values assure the model is significant. Optimization result shows the type of catalyst, temperature, and catalyst concentration values are found as aluminum oxide, 376 °C, and 6.6 wt.%, respectively. HDPE and LDPE oil yield a value of 58.3648 and 61.2051 wt%, respectively, under the optimum variables condition. For oil yield prediction, HDPE and LDPE’s correlation coefficient (R2) were 0.9949 and 0.9943, respectively. Authentication of the model response using a regression equation validated with the experimental result shows good agreement. The produced medical plastic oil has a density, viscosity, flash & fire point, carbon residue, and cetane number 904 kg/m3, 2.3 cSt, 42 & 45 °C, 7.1 wt.% and 51 respectively. Finally, this study concludes that plastic oil extraction from medical waste through catalytic pyrolysis can be a potential source of alternative fuels in IC engines. Priority to optimization and low-cost catalysts highlights medical plastics waste management under the socio-economic model.

This study experimentally investigates the inclined solar still (ISS) with the incorporation of fins and natural bio-jute cloth under dynamic flow. Experiments are conducted on bright sunny summer days in Coimbatore, Tamil Nadu, India. The newly developed ISS features greatly support passive solar desalination. An increase in mass flow rate (Mf) increases heat transfer meticulously pointing out 0.65, 0.8, and 1 kg/min case absorber, and the water temperature difference is within 3°C. An Mf of 0.285 kg/min is secure for the maximum water temperature reach and clean water yield of 70°C and 4.1 kg/m2, respectively, along with jute cloth, it was 1.6 kg/m2 more against without jute cloth. The presence of a jute cloth cumulative water yield of 2.5 kg/m2 at 0.635 kg/min is very close to the absence of a wick cumulative yield of 2.3 kg/m2 during 0.285 kg/min. From these results, the authors conclude higher Mf is feasible to increase the still performance and clean water yield. The implementation of a fully renewable passive solar still is strongly recommended to attain renewable and sustainable desalination. HIGHLIGHTS The proposed modification of the still and wick substantially increases the water yield and reinforces the passive solar still desalination.; The presence of jute cloth has multiple benefits, such as porosity, and the height of the capillary effect enhance the evaporative rate by effective contact-making to absorber fin–wick–water.; A higher mass flow rate makes it possible to increase the still performance and clean water yield.;

Abstract The present study aims to improve the palatable water production from the hemispherical cover solar distiller (HSD). To augment the palatable water produced from the hemispherical cover, a black sponge was utilized as a porous medium using different thicknesses, which augments the interfacial evaporation through the capillary effect of the water through the sponge. The rate of condensation of the hemispherical cover depends on the higher interaction of air from the ambient through wind velocity as the exposure area of the hemispherical cover is relatively higher as compared to the other traditional distillers. The rate of evaporation from the distillers depends on the interfacial materials used in the distillation unit, and this is achieved by using a highly porous black sponge to attain a higher evaporation rate. The thickness of the black porous sponge was optimized (1 to 4 cm), which was the operating parameter for better interfacial evaporation through the sponge, and the same has been compared to the conventional HSD without a porous sponge medium. Results showed a significant improvement in the evaporation rate using a porous medium as the palatable water produced from the HSD was improved by 72.29% using 3 cm as sponge thickness inside compared to the conventional HSD without the porous medium. The cumulative palatable water produced from the HSD using 3 cm as sponge thickness was found as 7150 mL/m2, whereas the conventional HSD without sponge, it was found as 4150 mL/m2. Moreover, using a porous sponge layer as an interfacial evaporation medium, the exergy and energy efficiencies were improved by about 512.87 and 70.53%, respectively. Similarly, with the influence of a porous sponge as an interfacial evaporation medium, the distilled water cost decreased by 41.67% more than the conventional HSD.

Seaweeds are a primitive type of plant and macro algae, which usually grow in the regions of backwaters, estuaries, and seas, especially in shallow water. They are typically formed, attached, and visualized to the coral reef, rocks, and other substrata wherever available. The seaweeds are collected from the Kanyakumari region and processed for methanol production. The methanol is extracted from the processed seaweed using the Saccharification method. The physicochemical properties of methanol are determined as per ASTM standards. The yield (%) of methanol production depends on the concentration of the substrate and the time duration (24, 48, and 72 h). It is observed that for a substrate concentration of 15%, a maximum yield of methanol is observed. In contrast, when the substrate concentrations lie below 10%, there is a decrease in the methanol yield for all the time durations investigated. Therefore, the maximum yield (51.2%) of methanol is obtained for a substrate concentration of 15% with a time period of about 48 h.The present work concentrated on producing methanol from a high concentration and choice of seaweed (Sargassum wightii).

In the current study, the impact of energy storage material on triangular pyramid solar still operating under constant water depth is investigated in an experimental setting. Experiments were carried out in a pyramidal solar still with various types of energy storage materials to determine their effectiveness. To increase the amount of freshwater that can be obtained from the solar still, materials such as quartz rock, mild steel, and sieved red bricks were utilized as a part of the construction of the basin material. The conventional correlation method was used to calculate the evaporative and convective heat transfer coefficients based on experimental data. It is dependent on the kind of material utilized within the basin for efficient energy storage as well as the depth of water maintained whether or not the output of fresh water improves. As a result of using 1 1/4” red bricks within the basin rather than a typical solar still, the results indicate that the utilization of thermal energy storage inside the basin increased the output of fresh water by 30 %. Additionally, the yield of fresh water obtained was found to be 3.5, 4, 4.3, and 4.2 for 14-inch quartz rock, 3/4-inch quartz rock, 1-1/4-inch red bricks, and mild steel scraps, while the yield of fresh water obtained was found to be 3.5, 4, 4.3, and 4.2 Litres/day.

An experimental investigation on the effect of water mass on performance, and yield of a triangular slope and a typical single slope solar still is presented in this paper. The condensing cover of the triangular slope solar still is made using polyethylene, and the area of the solar still is made as 0.25 m2 for conventional and triangular slope solar still. The influencing parameters such as wind velocity, intensity, and ambient temperatures are considered, and the entire experiments were carried out during the month of December 2018 and June 2019. Furthermore, the operating parameter on the effect of the mass of water placed in both solar still is analyzed experimentally for both the solar still. The comparative analysis results revealed that the triangular single slope solar still performed better than conventional single slope solar still. The temperature of water in the basin of triangular slope solar still is 6.8 % higher as compared to conventional solar still. Also, the daily yield produced using a square basin, and triangular basin were found as 3.29 and 3.67 kg/m2, respectively.

This study is aimed to produce biodiesel from Pithecellobium dulce seed oil with methanol (CH3OH) and sodium hydroxide (NaOH) using transesterification process. The impact of operating variables including time of reaction, oil to methanol molar ratio, and concentration of catalyst on yield of biodiesel is also studied. The experiments were designed based on Box–Behnken approach considering three factors with three levels. Regression analysis was employed to model the experimental results and a quadratic model was established to study the effects of selected variables on the biodiesel yield. Response surface technique was used to determine the optimal parameters for the transesterification process (RSM). An optimum yield of 96.6% at 6:1 methanol to oil molar ratio, 0.5 weight percentage of catalyst concentration and 3 h of time for reaction was obtained from the developed RSM model and the optimized conditions were validated with experimental results. Finally, the quality of the produced biodiesel was assessed by determining its properties and met with ASTM D6751 standards.

Alkali treatment of natural fibers will improve the mechanical, chemical, and thermal characteristics of natural fiber reinforced epoxy composites. The influence of alkali treatment on the improvement of mechanical strength of natural fiber reinforced epoxy composites depends on the selection of process parameters of the treatment. In this work, the optimization of four key process parameters for alkali treatment of kenaf fiber has been studied using orthogonal array-oriented fractional factorial experimental design. The concentration of sodium hydroxide solution, process temperature, time, and fiber to solution weight ratio were the four chosen parameters and the tensile strength of the composite sample fabricated with treated kenaf fiber and epoxy resin was taken as output response. The hand layup method was used to fabricate the composite materials, and specimens were prepared for the tensile test. All samples were fabricated by ensuring the fiber weight ratio of 40%. Five samples were prepared at each experiment category, and mean values were taken for analysis. The results revealed that 6% NaOH solution, 30°C process temperature, 8 hours process time, and 1:15 fiber to solution weight ratio are identified as optimum process parameters for a tensile strength of 58.16 MPa.

The importance of automatic seedling transplantation in plant-growing companies cannot be overstated. The key step of intelligent transplanting is the effective and precise detection of fresh saplings. To attain good production, dependability, and reproducibility, enterprises use automation extensively. The use of automatic quality control and assurance system results in a procedure that is cost-effective, dependable, and long-lasting. The sapling tray expressing methodology, the unusual disc comparison four-bar duck mouthpiece seeding method, the electric detector for plantlets detection and classification of a seedling plate, the motion detector, stepping motor, and Programmable Logic Controllers (PLC) management system are all used in the creation of an intelligent different planting structure. It could be used to determine if the soil foundation is filled or not using computer logic programming and management, as well as to regulate the automatic seedling plate transportation. The tray is shifted to minimize scooping up vacant soil foundation by skipping the manipulator’s operation path. Jalapeno plants were used to evaluate the system in an indoor environment. The analysis revealed that if the transplantation speed was 90 min per minute, the percentage of successfully seedling harvesting was 88.24% as well as the percentage of leaking was 17.47%, which met the jalapeno transplantation requirements. The annual percentage of leaks was decreased by around 12% relative to the transplantation model without seedlings recognition. The study serves as a valuable resource for the advancement of smart agricultural transplantation techniques and infrastructure.

Under the influence of cosmic improvement, photovoltaic (PV) container power capability decreases. In this case study, several passive and active chilling exploratory studies are carried out on a PV container to determine their effects on the energetic and warm depiction of a PVT scheme. All experiments are carried out on a cosmic person who poses as an expert while working with a wide range (regular-condensed) of energy from the sun’s capability. The temperature of the PV container rises as heat is generated along its course, resulting in a lower power delivered. The heat produced during the operation can be eliminated by attaching phase change material (PCM) to the PV committee afterward, which can retain the PV heat for a long time to increase overall effectiveness. Fins may be secondhand inside the PCM canister to improve the heat transmission. In research, it is noticed that as directly as PCM is melted entirely, the heat ancestry rate of PCM reduces that repeated leads to development in PV hotness. An oily acid was preferred as the PCM with a development change hotness. For the time being the investigation, research inspected two various sporadic warm requirement approaches utilizing a water distribution loop in the PV/T-PCM arrangement to boost the overall solar energy exercise effectiveness, and particularized contrasting were accomplished. The results showed that using PCM in a solar-powered battery can essentially reduce the PV committee’s hotness vacillation and improve photoelectric efficacy. Using the warm regulation method’s low hotness backdrop, excess heat may be extracted from the PCM in the solar panel. It was decided that an acceptable thermal management policy might improve the overall energy exercise percentage of the PV/T-PCM plan; however, more effect on the commerce research of the system that regulates organization is still needed. The research is developed to analyze a combination of solar Photovoltaic power systems using the PCM performance is analyzed.

Using renewable energies such as wind and solar energy, two types of renewable energy, we may adjust the structure of the energy system, addressing both energy and environmental challenges at the same time. As a result of its impact on the environment, wind and solar energy generation are inherently unreliable sources of energy. Lithium batteries, a technology that is becoming increasingly mature in terms of energy storage, are a critical component of the answer to the problem of instability. In order to avoid waste and expense increases, the capacity should not be too large or too small, respectively. Power consumption restricts the amount of energy that may be stored, but industrial power usage is unpredictable and non-periodic. This is a significant task that needs the development of a model that can dispatch while still providing a reasonable amount of storage. In this paper, we develop a KNN classification model that considers the test cyclic of photovoltaic (PV) generation that includes battery installation, data on electricity consumption and data on PV generation in India. These metrics are used to develop an energy management model. The model aims at the reduction of operation cost and optimal storage of energy that should satisfy the grid demands. The results of simulation and the comparison of the theoretical results shows that the proposed model has higher optimisation of energy in the storage devices in case of distributed systems.

In order to reduce waste and boost efficiency, smart cities must first and foremost eliminate trash. Effectiveness can be demonstrated in virtually any field of endeavour by saving energy, reducing energy intensity, sustaining economic growth, increasing productivity, protecting the environment, and collaborating in the battle against climate change. Because of a lack of money and technological capabilities, smart and sustainable city goals are difficult for impoverished towns to achieve. The study aims at finding the renewable energy solutions with energy efficiency and that should be technically feasible and practicable in poor communities in order to improve living conditions and overall life quality in these communities. In this paper, we use Naïve Bayes classifier to classify the input data to find the situation in which the climate can be maintained in such a way that it reduces the burden of environment in smart cities. The results of simulation shows that the Naïve Bayes classifier is effective enough in building sustainable environment with various tests.

In deep learning, it is possible that training efficiency will suffer as a result of redundant data. A lower amount of training data, on the other hand, may result in a model that is unable to capture the necessary features hidden within the dataset. In this paper, we use machine-deep-statistical model to analyse the stability of thermal storage systems i.e., battery in terms of managing the energy storage. These three models offer a prominent success across various applications and in this study, it uses life prediction, state estimation, defect diagnosis, fault detection, behaviour and property analysis via proper modelling and optimization. The validation is conducted in terms of various metrics to estimate the proposed model against various methods. The results of simulation shows that the proposed method achieves higher degree of accuracy with reduced prediction errors than other methods.

Climate change and sustainable development are significant challenges that must be addressed as soon as possible. As a result of this vision, the renewable energy (RE) industry has experienced great growth, with artificial intelligence being applied to improve its overall efficiency (AI). However, when it comes to achieving the sustainable development goals (SDGs), they are not sufficiently explored or considered. Countries all across the world are seeking to achieve 100% renewable energy by 2050, and this is a goal shared by a large number of other nations. More research is needed to evaluate whether renewable energy (RE) can assist us in meeting our sustainable development goals, given that it has lately experienced a considerable increase in popularity and is having an increasing impact on the global energy industry. In addition, an assessment of AI potential contribution to the achievement of the Sustainable Development Goals is being carried out. In this paper, we develop a machine learning model using Regression Kriging to classify the radiative energy flux at the earth surface in order of attaining environmental sustainability using solar panels. Various factors are given as input to the model that takes into account the modelling of data in obtaining the environmental sustainability. The simulation is conducted to test the efficacy of the model in obtaining the environmental sustainability and the results shows improved sustainability than other methods.

In order to reduce carbon emissions, a growing reliance on renewable energy sources such as solar energy is required. As a result of their ability to store excess solar electricity that may be used at a later time to reduce waste and increase utility profits, battery energy storage systems (BESSs) have emerged as a factor for power systems that integrates solar power system. BESSs are traditionally put on buses in solar farms, allowing extra electricity via solar to be stored instantaneously and transmission line losses to be kept to an absolute minimum. According to this placement strategy, BESS is exclusively built in the proximity of solar power plants. In this way, deployment of BESS without network topology consideration, and collaboration among BESSs is limited with capacity pooling to store excess electricity from photo voltaic (PV) panels. In this paper, we develop an optimal deployment of BESSs and it is associated with the estimation of the capacity using a multi-objective constraint modelling. The soft margin classifier minimize the curtailment associated with solar energy that considers both the power flow constraint and network topology. The results of entire model shows that the proposed soft margin classifier is efficient in storing the surplus power in the batter devices than other methods.

Renewable energy has gained enormous popularity in recent years. Both independent and grid-connected renewable energy generating capacity has increased. The potential to create green energy that is both ecologically benign and financially operative is the primary argument. To reduce the cost of maintaining a hybrid microgrid, this study provides a novel control algorithm as well as a suitable energy management system. The energy storage technologies are used in the hybrid microgrid system which consist of photovoltaic cell, fuel cell and supercapacitor. The optimal power flow in the hybrid microgrid component is developed using energy management system which consents control system to batteries, load and economic analysis with the input of electric grid. In this paper supercapacitor is which is directly connected to DC and provide fast response to load changing. DC voltage, current and hybrid microgrid is managed using the local control system. The power change in photovoltaic system is solved using energy storage system. The purpose of control method in hybrid microgrid is used to enhance the hybrid microgrid flexibility and generation of renewable resources and stored it in grid. The effectiveness and the flexibility of the proposed controller in energy management of hybrid microgrid system is simulated. The proposed energy management system provides high performance related to the existing energy management system.

The ability to predict battery residual life (RL) in advance is critical for ensuring a reliable supply of energy and the most efficient use of that energy. When it comes to precisely predicting the level of charge of batteries, battery management systems must be durable and trustworthy (SoC). Because of the non-linear nature of battery depreciation, it is extremely difficult to predict SoC estimation with considerably less degradation than is now possible. In this paper, we tend to reduce the data degradation for the prediction of RL using ensemble random forest model. The model enables collection of data, pre-processing and classification using random forest and ensemble random forest for the prediction of RL. The simulation is conducted in terms of R2 and root mean square error (RMSE). The simulation shows that the ensemble random forest model achieves higher prediction accuracy.

Water shortage is a global problem, and the demand for fresh water is growing at an ever-increasing rate. The only method to meet the demand for water is via water filtration. Water purification may be done in a variety of methods, including cleaning saltwater or holding rainfall and then releasing it into the environment. There are still several kinds of solar still are available, which may be utilized to improve the amount of water that is generated. The inclined solar still (ISS) is a particularly successful option because it has a large outer water surface to supplement the normal potable water production, as well as because it has a shallow depth of water to increase the overall efficacy of the inclined solar still. Increasing the water’s surface area has been the subject of much investigation. As a result of this study, an evaluation was conducted on the present state of various ISS designs in order to make advanced adjustments and research to increase the productivity of the ISS in order to meet the rising need for potable water. According to this analysis, active ISS and hybrid ISS are shown to be the most successful ISS methods.

Energy storing could correct an imbalance in the solar to electric power ratios among a Combined Heating, cooling and power system and its consumers, improving energy performance dramatically. Energy storage, on the other hand, adds to the complexities of the device’s operational efficiency. While assessing the device’s CO2 emissions in the operational state, the analysis comprises complete thermodynamics and thermo-economic evaluation. The effect of designing element modification on application functionality was examined next by varying the designed characteristics. Lastly, the proposed hybrid CCHP system is optimized for three objective operations: normalized exergy performance, CO2 emissions, and energy effectiveness. This paper presents a unique tri-generation method depending on the Trans-critical Brayton cycle and carbon dioxide energy storage (CO2ES). The stored capacity has a minor impact on the framework’s operating and cooling ranges, but the development in pressure change through the first throttle valve and temperature conditions broadens them. The capacity for heating and cooling rises in lockstep with stored pressures and falls in lock-step with differential pressure via the first throttle pressure regulator and ambient temperature. Moreover, the computational power is adequate for power system management. The proposed approach could also be used to optimize the functioning of a CCHP framework while taking into account demand-side responses.

The use of phase change materials (PCM), a type of heat transfer thermal storage substance, shows the opportunity to enhance the thermal inertia of these structures lacking significantly altering present construction methods. Because of the decreased indoor temperature swings and the load reduction, the usage of PCMs in buildings has the potential to deliver higher indoor temperatures for inhabitants as well as weaker export power consumption. Thermal energy storage (TES) systems based on phase change material (PCM) is identified as among the most enhanced energy techniques to improve eco-efficiency and conservation. The proposed dynamic insulating material and system (DIMS) allows for thermal resistance to be adjusted based on interior and outside variables. While it can be shown that using PCM and DIMS in facades enhances energy efficiency, there have been no previous studies that looked at the combined effect of the two technologies. Explore a unique wall design that includes a sheet of PCM made up of two levels of DIMS in this research. In most of the seasons and building orientations studied in this research, the PCM-DIMS-integrated wall saves much more energy than the DIMS-only combined barrier or the PCM-only combined walls. The PCM-DIMS-integrated walls can give a 15% to 72% decrease in yearly radiant heat then a 7% to 38% reduction in annual heat loss, based on the environment. The findings of this study highlight the necessity for scaled dynamic insulating layers for structures, as well as thermal storage devices.

In the present work, an experimental investigation is being carried out to increase the quality of fresh water produced by a tubular solar still connected to an electrical heater that is connected to a photovoltaic (PV) panel. With an effective evaporative area of 0.1425 m2, experiments were conducted and analysed for the climatic condition of Chennai, India. On the basis of the amount of fresh water generated by a tubular solar still without the use of an external heater, a comparative study is conducted. With the addition of electrical heater with the absorber, the average temperature of water is improved from 49 °C to 52 °C. The cumulative yield from TSS and TSS with external heater is found as 2.5 and 3.4 kg with a daily efficiency of 30.28 and 59.52% respectively. Results also revealed that the accumulated fresh water produced from the TSS with external heater is improved by 32.67% than TSS without additional heater.

When it comes to the expansion of the renewable energy business in today technological age, the ability to predict power and energy output based on shifting weather patterns is crucial. It is possible to support and even improve an economy and quality of life by using renewable energy sources rather than traditional fossil fuels, rather than by using fossil fuels at all. Because global warming and climate change are posing serious challenges to our planet, the findings of this study may be valuable in the development of smart grids that can properly predict future weather conditions. In this study, we develop an artificial neural network (ANN) model to estimate the energy generated at PV and the energy from the hybrid PV and wind energy systems considering several weather factors. The modelling is conducted to potentially predict the energy generation. The results shows that the proposed classifier is efficient in terms of reduced mean squared error with increased accuracy than other methods.

Energy is a conserved quantity. The world demands increased energy supply in the future as a means to support life, in specific eco-friendly electricity. In this study, paraffin wax is doped using CNT and CNT/MgO composite at different composition namely 1, 2 and 3%. Similarly, the composition of CNT with MgO is varied in 50 and 75%. Various tests were performed such as thermal conductivity, zeta potential and electrical conductivity were conducted. Results showed that the thermal conductivity of the PCM with 3% CNT concentration is higher about 60% whereas, using CNT and MgO in the composition of 75/25 the thermal conductivity is enhanced to about 75%. On using MgO and 50% CNT–50% MgO, the thermal conductivity reduced. The average zeta potential of the material containing 50%, 75%, and 100% CNT is 0.298, −0.862, and −0.111 mV, respectively. Because of molecular interaction, the impact of electrical conductivity is lower in 100 percent CNT when compared to the hybrid mixture of both nanoparticles. When contrast to the hybrid mixes, the CNT has a low molecular interaction.

Owing to its use of solar radiation and ambient energy, solar based heat pump water heaters are environmentally friendly. Several recommendations for system optimization are offered based upon the experimental study and thermodynamics analysis to enhance the efficiency of the model. The goal of this work was to create and maintain a solar based heat pump prototype as well as to propose a comprehensive theoretical examination into the social-economic and energy efficiency of a new solar based heat pumping (SHP) model for water heater application. The ultimate focus of the performance evaluation and interpretation is to evaluate the viability and logical consistency of deploying a solar-based heat pump as an auxiliary water heating mechanism during local weather scenarios. Subsequently, a modelling approach is created for optimizing the performance. Moreover, the suggested system’s performance characteristics are assessed using the Solar Collector Efficiency (SCE) and Coefficient of Performance (COP). The optimal case’s simulation results demonstrate that the solar-based heat pump’s average COP is about 9.0. The comfortable level of temperature could be accomplished when a pleasant indoor temperature reaches 92.6 percent of the whole heating season. Traditional air source heat pump systems may not be as promising for domestic use in cold temperature areas as the optimal proposed system does.

The present study deals with the emhancement of thermophysical properties of paraffin wax using Silver nanoparticles and to study the feasibility of its application in a stepped solar still through an experimental approach. Along with the experimentation, the yield, temperature of water are predicted using a machine learning approach. The thermophysical properties such as melting temperature, latent heat, thermal conductivity and thermal stability of the paraffin wax using different concentrations (1 and 2%) are investigated and compared to that of paraffin wax without nanoadditives. The thermal conductivity of paraffin wax was enhanced by about 35.71% and 78.57% using nano-additives concentrations of 1% and 2%, respectively. Three different stepped SS namely, SS with paraffin wax, SS with paraffin wax doped with Ag nanoparticles, and SS without paraffin wax are fabricated and tested for the climatic conditions of Coimbatore, India. From the experimental results of fresh water generation, it is identified that the SS using nanocomposite PCM and PCM without nanoadditives are enhanced by about 75.65% and 114.81% respectively, while compared to the SS without any thermal energy storage. In order to estimate the amount of water that can be produced by each of the three solar stills, a single adaptive neuro-fuzzy inference system (ANFIS) and a hybrid adaptive neuro-fuzzy inference system-particle swarm optimizer (PSO) were used as machine learning models. According to the statistical assessment, the ANFIS-PSO model had a greater level of accuracy than that of the standalone ANFIS. ANFIS-PSO had very high determination coefficient ranged between 0.981 and 0.995 which indicates its capability to predict water yield of the tested solar stills.

Abstract Alternate fuels are in great need as the world's natural resources are depleting with continuous consumption. Furthermore, with a continuous increase in the use of conventional fuel which emits a large number of harmful pollutants to the environment and thus increasing global warming, the need for alternative fuel is in great need. This investigation thus focused on the impact identification on the use of biodiesel from fish waste-based biodiesel [BDWFO (Bio-Diesel of Waste Fish Oil)] with Nanoparticles in single cylinder water cooled IC engine. The fish wastes in fish processing industries/fish markets are used to produce oil and its biodiesel is produced by the transesterification method. The individual BDWFO, Diesel, and blends of 20% of BDWFO were tested with the engine. Then another two combinations of fuel created 200 ppm of 40 nm Aluminium Oxide nanoparticles (AN) mixed with BDWFO, blends of 20% of BDWFO. These five fuels were considered to study the engine performance, combustion, and emissions from the exhaust. The experimental results confirmed the presence of aluminium oxide nanoparticles in BDWFO provides improved engine performance and reduced emissions from exhaust gas except for CO2.

Biodiesel can serve as an alternative to petroleum-based fuels. It has been shown that standard biodiesel cannot be mixed to improve efficiency and emissions characteristics. It has a major effect on emissions but has a limited capacity to mix with co-feed at varying temperatures and different ratios. In this study, 63 tertiary blends and three binary blends were mixed to create a stable fuel. Biodiesel was stable after having blended with amphipathioic liquor of a broad range of compatibility for a period of 168 h is recorded. Four samples were chosen for reproducibility, and 2 were selected for higher than average ethanol content in ethanol. These can be defined as one-observed, inferred, and derived in the three-layer, double-blurred, double-layer, two-blurred, one-blurred ring formation, and a single-blurred double-layer format. Even at 27.2 °C, biodiesel micelles could not shape micelles were used. The fuel blend, which has a wider range of miscibility, suitable for transportation and stability, causes more aromatic emissions when used in a ternary formulation than a micro formulation. The blend properties were found to be within tolerable limits.

The solar radiation is a critical metric for design and optimal operation of the solar energy system. Most of the locations available solar radiation records are not available due to high cost for buying and maintaining the measuring instruments. Aim of this paper is building an efficient neural network model that can reliably estimate solar radiation. In this work, different ANN models with three popular algorithms admired from the literature are investigated. The models were trained using meteorological data collected over a year from six different places from the hot area locations of Tamil Nadu, India. Based on minimal Mean Absolute Deviation (MAD), Mean Square Error (MSE), Root Mean Square Error (RMSE) and Mean Absolute Percentage Error (MAPE), the optimum ANN algorithm and model are determined (R). Furthermore, the research illustrates that the ANN model’s prediction performance is dependent on the entire set of data utilised to train the network. Also, this article aims at finding out the accurate number of hidden layer neurons for the developed model. The proposed ANN model offers improved accuracy and applicability for estimating hourly average global radiation for the purpose of designing or evaluating photovoltaic (PV) installations in areas without meteorological data collection facilities.

The impact of Sal tree (Shorea Robusta) gum powder on the mechanical, visco elastic, and thermal characteristics of epoxy resin was studied. Using the hand layup technique, composite specimens were created by adding bio filler (Sal tree gum powder) at various volume percentages in epoxy resin. Experiments were carried out to assess the epoxy composite's mechanical, thermogravimetric, and viscoelastic characteristics. Results showed that the bio filler had a substantial impact on the mechanical, thermal, and dynamic mechanical characteristics of the samples. Better mechanical and dynamic mechanical properties were obtained at 16% v/v of Sal Tree gum powder. The inclusion of the bio filler, on the other hand, had no appreciable impact on the flexural and tensile strengths of the composite. The morphological features of a tensile cracked specimen were investigated using scanning electron microscopy (SEM) images of the specimen. The homogeneity of the bio composite was also examined by using the Cole Cole plot. According to the findings, the composite specimens containing the bio filler showed uniform features. It was observed that the composite specimens incorporated with the bio filler exhibited homogeneous characteristics. The thermal stability of the composite was investigated using thermogravimetric (TGA) test, and it was found that the inclusion of filler enhanced the thermal stability of the composite, with the composite remaining stable up to 431 °C after the addition of filler. The results of dynamic mechanical analysis (DMA) tests showed that the inclusion of bio filler resulted in an increase in storage modulus, suggesting that the composite is capable of greater energy absorption within the elastic limit. The glass transition temperature was calculated to be 110 °C.

The environmental friendly and renewability nature of PV Module has aroused the interest of researchers. The precise modelling of PV Module is mandatory before the installation part. However, the specific modelling is cumbersome as some parameters are not available in the manufacturer’s specifications. Predator–Prey based firefly optimization algorithm is proposed and implemented to optimize the unknown values in PV Module non-linear equations by changing the curve at various environmental conditions. The achievement of proposed technique is analysed with the flower pollination and Jaya algorithm based on the convergence curve.

Inconel 718 is a hard-to-machine alloy with very poor machinability and low thermal conductivity. Machining of such alloy is a critical manufacturing issue that should be carefully controlled to obtain machined components with acceptable accuracy and surface integrity. In this paper, hybrid machine learning (ML) models are developed to predict the induced residual stresses (RSes) during turning of Inconel 718 alloy. The developed models are composed of a traditional artificial neural network (ANN) incorporated with bio-inspired optimizers, namely pigeon optimization algorithm (POA) and particle swarm optimization (PSO). These optimizers are used to fine-tune the ANN parameters to enhance its prediction accuracy. The models were trained using measured RSes at different cutting conditions. The effects of the cutting conditions, such as cutting speed, cutting depth, and feed rate on the induced RSes are also investigated. The predicted RSes obtained by the developed models were compared with the measured ones as well as with those predicted by traditional ANN. The prediction accuracy of the models was statistically evaluated using seven statistical measures. The ANN–POA and ANN–PSO outperformed the traditional ANN. The coefficient of determination of ANN–POA, ANN–PSO, and ANN was 0.991, 0.938, and 0.585, respectively, while root mean square error was 11.870, 31.487, and 119.437, respectively.

CFD and experimental approaches are used to carry out the design of a Solar Chimney Power Plant (SCPP) that consists of a Semi Convergent Collector that is equipped with a Divergent Chimney. The present work engages in figuring out the importance of study variables in statistic modelling thereby improving the efficiency. Both the response surface methodology (RSM) and the single objective approach (SOA) are used in the process of determining the amounts of influential parameters and optimizing the model. Experiment test on a small-scaled model is carried out with inclined Collector to a Divergent Chimney. The CFD result indicates that the updraft effect increases because of the convergent collector with mean temperature rise of 18 K. Experiment and simulation results are in good agreement. The numerical model predicted that the increment in outside temperature leads to increment in mass flow rate, velocity, inside temperature, power output and efficiency of the plant. Hence the single input model predicted the values for five outputs. The numerical model seems to be fit with experimental study with an increase in mass flow rate from 0.04 kg/s to 0.06 kg/s with incremental time step. The deviation between the experimental and numerical studies lies only 0.423. Developing a larger size model helps in achieving larger power output. It is recommended that the semi convergent collector with a divergent chimney adopts for construction of large size SCPP for generating greener energy.

This study presented a detailed investigation into the performance of a plate–frame water gap membrane distillation (WGMD) system for the desalination of untreated real seawater. One approach to improving the performance of WGMD is through the proper selection of cooling plate material, which plays a vital role in enhancing the gap vapor condensation process. Hence, the influence of different cooling plate materials was examined and discussed. Furthermore, two different hydrophobic micro-porous polymeric membranes of similar mean pore sizes were utilized in the study. The influence of key operating parameters, including the feed water temperature and flow rate, was examined against the system vapor flux and gained output ratio (GOR). In addition, the used membranes were characterized by means of different techniques in terms of surface morphology, liquid entry pressure, water contact angle, pore size distribution, and porosity. Findings revealed that, at all conditions, the PTFE membrane exhibits superior vapor flux and energy efficiency (GOR), with 9.36% to 14.36% higher flux at a 0.6 to 1.2 L/min feed flow rate when compared to the PVDF membrane. The copper plate, which has the highest thermal conductivity, attained the highest vapor flux, while the acrylic plate, which has an extra-low thermal conductivity, recorded the lowest vapor flux. The increasing order of GOR values for different cooling plates is acrylic < HDPE < copper < aluminum < brass < stainless steel. Results also indicated that increasing the feed temperature increases the vapor flux almost exponentially to a maximum flux value of 30.36 kg/m2hr. The system GOR also improves in a decreasing pattern to a maximum value of 0.4049. Moreover, a long-term test showed that the PTFE membrane, which exhibits superior hydrophobicity, registered better salt rejection stability. The use of copper as a cooling plate material for better system performance is recommended, while cooling plate materials with very low thermal conductivities, such as a low thermally conducting polymer, are discouraged.

This work reports the use of tubular solar dryer for drying the Mexican mint (Plectranthus amboinicus) under various mass of leaves. Experiments were carried out in a tubular solar dryer under natural convection mode with direct solar heating. Parameters such as the temperature of dryer tray, relative humidity, and moisture content were recorded for 0.25, 0.5, 0.75 and 1 kg of P. amboinicus leaves placed in the dryer tray. Results showed that under an increased mass of P. amboinicus leaves in the tray the parameters such as dryer tray temperature are reduced, and the moisture content available with 0.75 kg of P. amboinicus leaves is higher as compared to 0.25 kg of P. amboinicus leaves. Also, it is found that the relative humidity inside the drying chamber is higher with increased mass of P. amboinicus leaves in the drying chamber.

The present investigation reports the soxhlet assisted solvent extraction technique to derive the oil from seeds of the rain tree. The optimization of the factors affecting the extraction process has been carried out by Response Surface Methodology (RSM) technique, and a Box-Behnken Design (BBD) consisting of three process variables has been developed to optimize the yield of oil. Using the RSM technique, the predicted optimum oil yield of 11.15% at an optimized condition of powder weight of 20 g, volume of solvent of 380 mL, and extraction time of 6 h. The physiochemical properties of the oil showed liquid greenish-yellow with 0.88, 1.473 of specific gravity and refractive index, respectively. Similarly, the moisture content, free fatty acid, acid value, saponification value, iodine value, and peroxide value were found to be 0.16%, 13.615, 27.23, 187.1 mg KOH per g oil, 65.8 g I2 per 100 g, and 4.02 meq O2 per kg, respectively. From the obtained results, it was found that the extracted oil could be used for various applications.

Conventionally accessible silicon solar cells experience two major drawbacks, such as reduced efficiency and increased fabrication costs. The prospects for the reduction in the cost of the photovoltaic form of energy conversion are bifacial solar cells. Bifacial solar cells show potential opportunity in reducing the cost of solar energy conversion when analyzed with respect to monofacial cells. The bifacial solar cells exploit sunlight occurrence on both sides of the cell more efficiently. Bifacial-based solar photovoltaic (PV) is a technology that increases the generation of electrical energy per square meter of PV module through the utilization of light absorption from the albedo. This technology can generally be categorized based on the type of solar cell material and the fabrication technique. PV devices are classified as a silicon-based, thin film, organic, and advanced nano PV. This paper takes a second look at some recent initiatives and significant issues in enhancing the efficiency of bifacial solar cells from material sciences and chemical composition aspects. From this review, it is concluded that screen-printed solar cells have produced a maximum efficiency of 22%. Additionally, triode structure single-crystalline cells produced a maximum front side efficiency of 21.3% and rear side efficiency of 19.8%. Considering the recycling of solar panels, organic solar panels can be developed.

In the field of advanced concrete science, the construction industry has risen to great heights. Due to its own characterisation, the manufacturing cost of reactive powder concrete (RPC) is very high. This can be minimised by substituting the components of the RPC with the aid of agro waste. Because of the production of sugar from the sugar cane industry, bagasse ash is abundantly available in India. It is not ideal for the direct replacement of ingredients in concrete because of the presence of carbon dioxide in bagasse ash. The study of bagasse ash’s actions under different temperatures and different exposure times is discussed in this paper. It is inferred from the findings obtained from the energy dispersive study of X-ray (EDAX) that the presence of reactive silica in bagasse ash could be substituted by RPC ingredients due to heat treatment. RPC is composed of exceptionally fine powders (cement, sand, quartz powder and silica smolder) and superplasticiser. The superplasticiser, utilised at its ideal dose, decreases the water to cement proportion (w/c) while enhancing the workability of the concrete. A thick matrix is accomplished by optimising the granular packing of the dry fine powders. This compactness gives RPC ultra-high quality and durability. Reactive powder concretes have compressive qualities extending from 200 to 800 MPa.

Diesel Powered engines are predominately used in transport and power generators. Due to rapid depletion of fossils fuels like diesel, there is need to find alternate resources for as a fuel for transport and power sector. The use of third generation fuels like algae seems to be a promising solution to satisfy our energy demands in future. In these work algae is used as an alternative fuel with different blend combination with diesel and the results obtained are summarized. Algae fuel is blended with diesel on a volume basis, namely A10, A20, A30, A40 and A100 and made to run in diesel engines. The properties of the fuels were found according to American Society for Testing and Materials standards. Experimental testing was carried out in a single cylinder direct injection diesel engine. Among the various blends tested A20 shows closer estimation with diesel results in higher thermal efficiency lower HC, CO, Smoke and particulate matter emissions. However, the other emissions like Nitrous oxide and carbon dioxide were shown marginally higher. Regarding cylinder pressure and heat release rate curves, the peak value obtained is considerably lower at higher load condition while compared with diesel.

Renewable wind power is productive and feasible to manage the energy crisis and global warming. The wind turbine’s blades are the essential components. The dimension of wind turbine blades has been increased with blade sizes varying from approx. 25 m up to approx. 100 m or even greater with a specific purpose to increase energy efficiency. While wind turbine blades tend to be highly stressed by environmental conditions, the wind turbine blade must be constantly tested, inspected, and monitored for wind turbine blades safety monitoring. This research presents a methodology adaptation on machine learning technique for appropriate classification of different failure conditions on blade during turbine operation. Five defects were reported for the diagnosis study of defective wind turbine rotor blades, and the considered defects are blade crack, erosion, loose hub blade contact, angle twist, and blade bend. The statistical features have been drawn from the recorded vibration signals, and the important features was selected through J48 classifier. Eight tree-dependent classifiers were used to categorize the state of the rotor blades. Among the classifiers, the least absolute deviation tree performed better with the classification percentage of 90% (Kappa statistics=0.88, MAE=0.0362, and RMSE=0.1704) with a computational time of 0.06 s.

The traditional method of obtaining fresh water for drinking is by burning fossil fuels, emitting greenhouse gases into the atmosphere. However, renewable energy is gaining more traction since it is available free of cost for producing fresh water. In this study, Al2O3 nanoparticles were distributed in a phase change material (paraffin wax) that had been fixed at a hemispherical distiller water basin. Three scenarios with three hemispherical distillers were examined. A conventional hemispherical distiller (CHD), a conventional hemispherical distiller with paraffin wax as a phase change material (CHD-PCM), and a conventional hemispherical distiller with PCM partially filled with Al2O3 nanoparticles (CHD-N-PCM) were tested under the same climatic conditions. The experimental results showed that CHD gave a daily yield of 4.85 L/m2/day, while CHD-PCM increased the yield to up to 6.2 L/m2/day with a 27.84% daily yield enhancement. The addition of Al2O3 nanoparticles to paraffin wax CHD-N-PCM improved hemispherical distillate yield up to 8.3 L/m2/day with a 71.13% increase over CHD yield.

There are other issues related to humans, including respiratory problems and even death. The present study deals with the analysis of cerium oxide nanoparticles at different concentration in corn oil methyl ester diesel blend with an optimum concentration of biodiesel of 10% with diesel fuel. The concentration of CeO2 nanoparticles with the COB10 is varied in the range of 25, 50, and 75 ppm. Results showed that the physicochemical properties of the fuel improved with the addition of CeO2 nanoparticles. The brake thermal efficiency (BTE) of the engine is improved with an optimum concentration of 50 ppm CeO2 nanoparticle with the fuel, and it is found as 34.7% whereas, the formation of NOx is increased. The other emission from the engine, such as CO, UBHC decreased with increased oxygen content available in the fuel with nano additives. At maximum engine load, the UBHC is reduced by 11, 16.6, and 20.8% for COB10, COB10 + 25 ppm, COB10 + 50 ppm respectively. Also, the reduced ignition delay reduced the formation of CO and unburnt hydrocarbons. From the experimental study it is found that the optimized nanoparticle concentration with COB10 is 50 ppm, which costs around Rs. 8. Similarly, the total cost of biodiesel with cerium oxide nanoparticles is estimated as Rs. 76/kg.

In this work, experiments on mechanical properties such as tensile, flexural, effects, and stiffness testing are performed on natural fiber granulated composites (NFGC) manufactured using a hybrid additive manufacturing technique. The natural fiber granulated composites are prepared using the powdered form of sugarcane, jute, ramie, banana, pineapple fiber, and seashell powder with a volume fraction of 0.8. In the hybrid additive manufacturing technique, the fused deposited modeling (FDM) machine is modified by combining with the shape deposition modeling (SDM) to print the specimens layer by layer, and the influence of the number of layers on the mechanical properties is analyzed. The results concluded that increasing the number of layers from 6 to 12 improved the mechanical properties such as tensile strength, flexural strength, impact strength, and hardness values by 40.84, 50.04, 21.55, and 20.55%, respectively. Further, a novel technique can be utilized for developing the composites in replacement with conventional methods.

The disposal of used photovoltaic panels is increasing day by day around the world. Therefore, an efficient method for recycling disposed photovoltaic panel is required to decrease environmental pollution. This work is aimed at efficiently recovering pure silicon and other materials such as aluminium, silver, and lead from disposed solar cells using chemical treatments. Earlier, the pure silicon was recovered by treating the solar cells with hydrofluoric acid or mixture of hydrofluoric acid and other chemicals. The usage of hydrofluoric acid is eliminated in the present work as it is highly toxic and corrosive chemical. The pure silicon (99.9984%) has been recovered by sequentially treating with three different chemicals. Aluminium, silver, and lead are also recovered as aluminium hydroxide, silver chloride, and lead oxide, respectively.

Researches in many laboratories on solar still desalination are concerned with increasing efficiency using only solar energy. One of the techniques is the difference in the thickness of the glass cover of the distiller. In order to see the influence of this parameter on efficiency, three similar stills with three different glass coverings were investigated. The flow of heat goes through the cover, and higher glass temperature leads to solar still productivity becoming lower. This paper presents an optimization of glass thickness (Gt) of a conventional solar still (CSS) in El Oued climate, Algeria. Based on the experimental results, the distilled water production rate, energy, and energy efficiency of the CSS have been discussed. The results showed that the suitable Gt of the CSS was 3 mm. The distilled water of around 3.15, 2.02, and 1.13 kg was produced by the CSS at energy efficiency of 30.71, 19.02, and 11.44% with the Gt of 3, 5, and 6 mm, respectively. The daily average exergy efficiency of 2.46, 1.38, and 0.84% was calculated for the CSS at Gt of 3, 5, and 6 mm, respectively.

This paper reported the experimental testing of a triangular and conventional basin solar still (TBSS and CBSS). Solar basin and absorber are made of glass and a polyethylene cover, respectively, with an area of 0.25 m2. Square and triangular absorber with the same area of 0.25 m2 with square and triangular glass cover for condensation was fixed. Experimentations were conducted during the month of December 2018, and different natural criteria such as intensity, wind speed, and surrounding ambient temperatures were considered. Also, the modified model was compared to the CBSS on its performance and efficiency characteristics. The experimental results also revealed that the temperature of the water inside the TBSS was higher as compared with that of the CBSS. The daily yield obtained from CBSS and TBSS was found to be 2.7 and 3.2 kg/m2, respectively. Also, the daily efficiency of the TBSS was improved by 11.36% than the CBSS.

The search for alternate and sustainable fuel for internal combustion engines which fulfils around 25% of energy needs has lead the researchers towards biodiesel which can be easily extracted from vegetable oils. Biodiesels can also be extracted from waxes, oligenius species of algae and pyrolysis oils. In the above mentioned materials waxes can be used predominantly because, they are entirely composed of esters of higher chain aliphatic alcohols. In the current study biodiesel from beeswax has been studied for its characteristics with the aid of analytical techniques such as GC-MS and FTIR spectrum. And also the properties of fuel and combustion chemistry of biodiesels have been discussed. The spectrum results have clearly shown the presence of five methyl esters of palmitic acid and oleic acid. Further the biodiesel is found to have density of 880 kg/m3 and calorific value of 38.5 MJ/kg with the Cetane number of 48. The analysis of the combustion of the fuel gives compromising results proving biodiesels from wax esters will be an excellent alternative to mineral diesel and will find a valuable position in list of materials that can be used for biodiesel formulation. Keywords: Beeswax biodiesel, Standardization, Spectrometric studies, Combustion chemistry

Effects of utilizing nanomaterial on the solar still productivity investigated experimentally. Cuprous oxides (CuO) chosen as a nanoparticles material. The nanoparticles added to the black paint of the solar still walls to enhance the solar still performance. Experiments conducted with cuprous oxide nanoparticles weight concentrations ranged from 10% to 40%. It is found that adding nanoparticles to paint increase heat transfer rate and saline water temperature. Solar still productivity of the proposed system is higher than that for the conventional still. Results acquired that utilizing CuO nanoparticles boosted the distillate by 16% and 25% as compared to the conventional solar still (CSS) at weight fraction concentration of 10% and 40%, respectively. Payback period of the distillation system for the modified still using CuO nanomaterials is about 96 days, at weight fraction 10%, which is considerable as compared by 89 days for CSS. Keywords: Nanomaterial, Solar still, Distillation, Nanoparticle

In the present paper, the effects of the indirect evaporative cooler with internal baffle on the performance of the hybrid air conditioning system are numerically investigated. The hybrid air conditioning system contains two indirect evaporative coolers with internal baffle, one is utilized to pre-cool the air inlet to the desiccant wheel and the other is utilized to pre-cool the supply air inlet to the room. The effects of the inlet conditions of the process and reactivation air and working air ratio on the thermal performance of the hybrid air conditioning system have been analyzed. The results of this study show that in the hybrid air conditioning system for using the indirect evaporative cooler with internal baffle as a pre-cooling unit, the supply air temperature reduced by 21% and the coefficient of performance improved by 71% as compared to previous designs of the hybrid air conditioning system at the same inlet conditions. For increasing process air inlet temperature from 25 °C to 45 °C, supply air temperature increases from 12.7 °C to 14.2 °C, thermal COP increases from 1.87 to 2.84, and supply air relative humidity increases from 76.7% to 77.4%. Also, for increasing the reactivation air inlet temperature from 70 °C to 110 °C, supply air temperature dropped from 15.9 °C to 10.9 °C, supply air relative humidity dropped from 82.7% to 71.8%, and thermal COP dropped from 4.5 to 1.7. The recommended optimal air working ratio in the indirect evaporative cooler with internal baffle should be 0.15. Keywords: Desiccant material, Solar air collector, Evaporative cooler, Internal baffles, Air conditioning

In isolated and arid areas, especially in the almost Maghreb regions, the abundant solar radiation intensity along the year and the available brackish water resources are the two favorable conditions for using solar desalination technology to produce fresh water. The present study is based on the use of three groups of correlation, for evaluating mass transfer. Theoretical results are compared with those obtained experimentally for a Simple Solar Distiller (SSD) and a Simple Solar Distiller Hybrid with a Heat Pump (SSDHP) stills. Experimental results and those calculated by Lewis number correlation show good agreements. Results obtained by Dunkle, Kumar and Tiwari correlations are not satisfactory with the experimental ones. Theoretical results, as well as statistical analysis, are presented. The model with heat pump ( for two configurations (111) and (001) give more output compared with the model without heat pump ((000) and (110)). This results where agree for the use of the statistic results, the error it less with Lewis number as compared with the different correlation.