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Greenhouse technology is a practical option for the production and drying of agricultural products in controlled environment. For the successful design of a greenhouse, the selection of a suitable shape and orientation is of great importance. Of various shapes of greenhouses, the even-span roof and the Quonset shape greenhouses are the most commonly used for crop cultivation and drying. The orientation of greenhouses is kept east-west for maximum utilization of solar radiations. Hybrid and modified greenhouse dryers have been proposed for drying of products. The agricultural products dried in greenhouses are found to be better in quality as compared to open sun drying because they are protected from dust, rain, insects, birds and animals. Moreover, various greenhouses shapes along with their applications have been reviewed.

In this paper, convective and evaporative heat transfer coefficients of the Indian groundnut were computed under indoor forced convection drying (IFCD) mode. The groundnuts were dried as a single thin layer with the help of a laboratory dryer till the optimum safe moisture storage level of 8 – 10%. The experimental data were used to determine the values of experimental constants C and n in the Nusselt number expression by a simple linear regression analysis and consequently, the convective heat transfer coefficient (CHTC) was determined. The values of CHTC were used to calculate the evaporative heat transfer coefficient (EHTC). The average values of CHTC and EHTC were found to be 2.48 W/m2 oC and 35.08 W/m2 oC, respectively. The experimental error in terms of percent uncertainty was also estimated. The experimental error in terms of percent uncertainty was found to be 42.55%. The error bars for convective and evaporative heat transfer coefficients are also shown for the groundnut drying under IFCD condition.

Solar energy is a vast renewable energy source, but uncertainty in the demand and supply of energy due to various geographical regions raises a question mark. Therefore, the present manuscript includes a review to overcome this uncertainty by utilizing various thermal energy storage systems. Phase change material is the most preferred thermal energy storage system because of its high-energy storage density. The low thermal conductivity is the critical problem in phase change material that can be overcome by integrating metallic foam, carbon fiber, and metallic fins in the phase change material container. The inclusion of metallic foam limited to 0.1–3% of the Phase change material (PCM) weight leads to a slight change in thermal conductivity but a high cost. It was also seen that the addition of carbon 0.1 to 9% of the PCM weight could improve the performance of PCM. The inclusion of a metallic fin improves the thermal conductivity with the various shapes and sizes of the fin. It is found that metallic foam composites have better performance than carbon composite and metallic fin inclusion.

This article is a comparison of the date fruits drying performance of two most simple and common type of solar dryers. A simple even span type forced convection greenhouse dryer (FCGHD) and a forced convection cabinet solar dryer (FCCSD) were developed and tested under the climate of Hisar, India. The average values of convective heat transfer coefficients (HTC) were calculated as 0.46 and 0.53 W m −2  °C −1 for FCGHD and FCCSD, respectively. The respective average evaporative HTC was evaluated as 64.58 and 276.06 W m −2  °C −1 . The drying efficiency and specific energy consumption for date fruits drying under FCCSD were, respectively, 55.2% higher and 37.87% lower than that of FCGHD. Amongst seven considered thin layer drying models, Midilli–Kucuk model showed the highest commensuration to the experimentally evaluated drying data of moisture ratio for date fruits. Higher values of effective moisture diffusivity and lower values of activation energy were observed under FCCSD. The economic prospective of both the drying arrangements has also been presented.

Biomass briquetting is a viable densification technique that converts waste biomass materials into useful products and alternative energy. This work explores the characteristics and optimization of hybrid bio-briquette production by combining crop residues (paddy straw) and solid biomass materials (sawdust and sugarcane bagasse). A total number of 20 briquettes were fabricated with three input factors: sawdust (SD), sugarcane bagasse (SB), and paddy straw (PS) based on the faced-centered central composite design (FCCCD) approach in the laboratory to investigate the calorific value (CV) and ash content (AC). The bomb calorimeter technique was used to evaluate the briquette’s calorific value and ash content. The proposed work focused on optimizing the briquette input parameters (SD, SB, and PS) and output responses (CV and AC) using analysis of variance (ANOVA) and response surface methodology (RSM) and hybrid artificial neural network-integrated with multi-objective genetic algorithms (ANN-MOGA). This study shows that the MOGA-ANN-based model results in the best value of CV (17.07 MJ/kg) and AC (1.95%) with optimal input parameters SD (39.99 g), SB (29.02 g), and PS (69.02 g). The optimal results observed from the MOGA-ANN model have also been validated experimentally. The Fourier transform infrared (FTIR) spectroscopy investigation reveals that biomass briquettes are the sustainable and environment-friendly option of fossil fuels for power generation and indoor cooking. The study suggests a strategy for minimizing agro-waste, which may be converted into future fuel in the form of briquettes.

Turning biomass waste into briquettes using densification techniques is one of the most promising steps toward mitigating biomass waste pollution and fuel issues in developing countries. Despite the continuous growth of scientific output over the past few decades, only a limited amount of information is available in the literature on biomass briquette optimization and mathematical modeling, as well as the physiochemical characterization of biomass feedstocks and briquette operating variables. In light of this gap in the current literature, this study summarizes the current state of the art and recent advances in biomass-based briquettes generated from agro-residues as an alternative source of clean energy. The primary research method for this study is literature review and conceptual modeling. First, many densification processes, such as piston press, screw press, roller press, hydraulic press, and quality variables such as ash content, calorific value, moisture content, density, compressive strength, shatter index, etc., are thoroughly discussed and compared. Then characteristics of different biomass wastes are studied, together with process parameters, including temperature, type of binder used, particle size, and influence on densification process choice. The current evaluation concentrated on the mathematical modeling and optimization of the briquetting technology and the usefulness of briquettes in applications for heating, cooking, and energy production. Overall, this manuscript will help new researchers understand the basic methodology, classification, limitations, and future perspective of briquetting technology in the production of solid biofuels.

The present study investigates the compressive strength performance of polylactic acid (PLA) polymer material parts printed using the Fused Deposition Modelling (FDM) three-dimensional (3D) printing process, with a particular emphasis on various machine input parameters. The face centred central composite design matrix approach was employed for experimental modelling, which was subsequently utilised as a knowledge base for the fuzzy algorithm. A hybrid evolutionary algorithm, i.e., Genetic-Algorithm (GA) assisted with Fuzzy Logic Methodology (FLM), was used to optimize input process parameters and compressive strength of FDM technique fabricated polymer material parts. The study concluded that the maximum compressive strength observed with GA integrated FLM was 49.7303 MPa at input factors (layer thickness-0.16 mm, temperature 208°C, infill-pattern-Honeycomb, infill-density-60% and speed/extrusion velocity-41 mm/s) which is higher than the experimental (47.08 MPa) and fuzzy predicted (47.101 MPa) value. This evolutionary hybrid soft computing methodology has optimized the compressive strength of PLA polymer material parts at optimum parameters combination set.

With the increase in population globally, a big problem has been raised, which is food supply. A remedy to this problem is to use an ancient practice of sun drying to preserve harvests, vegetables, and fruits. Several types of dryers are being developed for drying agricultural commodities. They do, however, demand much energy, which is typically obtained from polluting fossil fuels. Producers, as well as researchers, are encouraged to look for alternate options because of environmental issues and the risk of fossil fuel depletion. Continual solar energy can be helpful in drying applications because it is widely available freely in most parts of the world. Solar dryers come in various sizes and designs, and they may be used to dry a wide range of products. Farmers will find a variety of driers available to meet their demands. A thorough examination of the various designs, methods of construction, and operating ideologies of the numerous sun-drying devices mentioned previously is provided. This study emphasizes the hybrid photovoltaic thermal solar dryer because of its high electrical and thermal efficiency, good mitigation of carbon dioxide levels, giving a good product with a high drying rate and less payback time. The greenhouse solar dryer is found to be best adapted to the requirement in rural locations, where there are more agricultural products accessible for drying and space is also readily available. The future scope and recommendations section of this study will assist researchers in developing an efficient photovoltaic thermal solar dryer collector system that is economical and has good electrical and thermal efficiency for large-scale applications.

The proposed work presents a novel composite polymer filament made by blending High-Density Polyethylene (HDPE) and Polycarbonate (PC) with Acrylonitrile Butadiene Styrene (ABS), resulting in improved properties such as strength-to-weight ratio and impact resistance, expanding the applicability of ABS in healthcare, automotive, and engineering industries. The composite polymer filament was fabricated using a single screw extruder at different parameters like barrel temperature, rotational speed of the screw and different thermoplastic polymer compositions. The tensile strength was measured using a Universal Testing Machine (UTM). The input/output data were optimized using hybrid tools, including genetic algorithm artificial neural networks (GA-ANN) and response surface methodology (GA-RSM). The results obtained from GA-ANN were validated experimentally, demonstrating a maximum tensile strength of 39.8 MPa at 280 °C, 10.001 RPM, 16.783%wt of HDPE, and 8.839%wt of PC. It is observed that the proposed work with GA-ANN model effectively improved the tensile strength by 7.2% in comparison with GA-RSM. This research highlights the potential of the proposed composite material in various applications, emphasizing its cost-effectiveness and improved mechanical properties.

In this work, an attempt is made to study the effect of mass on convective heat transfer coefficient (CHTC) for open sun drying (OSD) of groundnut ( Arachis hypogaea L.). Experiments were conducted during the month of May, 2016 in the climatic condition of Rohtak, India (28°54′0″N 76°34′0″E). Groundnut samples of 130 and 198 g were dried under OSD condition till almost no variation in its mass was recorded. Hourly data of the mass evaporated, groundnut temperature, relative humidity and ambient temperature were recorded. The experimental data obtained were used to determine the constants ‘C’ and ‘n’ in the Nusselt number expression using linear regression method. CHTC increased with the increase in mass of groundnuts. The experimental errors in terms of percent uncertainty were found to vary from 44.29 to 48.77%.