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The choice of a sales channel for fresh vegetables is an important decision a farmer can make. Typically, the farmers rely on their personal experience in directing the produce to a sales channel. This study examines how sales forecasting of fresh vegetables along multiple channels enables marginal and small-scale farmers to maximize their revenue by proportionately allocating the produce considering their short shelf life.

Machine learning models, namely long short-term memory (LSTM), convolution neural network (CNN) and traditional methods such as autoregressive integrated moving average (ARIMA) and weighted moving average (WMA) are developed and tested for demand forecasting of vegetables through three different channels, namely direct (Jaivasree), regulated (World market) and cooperative (Horticorp).

The results show that machine learning methods (LSTM/CNN) provide better forecasts for regulated (World market) and cooperative (Horticorp) channels, while traditional moving average yields a better result for direct (Jaivasree) channel where the sales volume is less as compared to the remaining two channels.

The price of vegetables is not considered as the government sets the base price for the vegetables.

The existing literature lacks models and approaches to predict the sales of fresh vegetables for marginal and small-scale farmers of developing economies like India. In this research, the authors forecast the sales of commonly used fresh vegetables for small-scale farmers of Kerala in India based on a set of 130 weekly time series data obtained from the Kerala Horticorp.

In any machining process, the surface profile of the workpiece is continuously changing with respect to time and input parameters. In a conventional machining process, input parameters are feed and depth of cut whilst other parameters are considered to be constant throughout the process.

The direct and indirect participation of this instantaneous curvature can be used to optimize the strategy of cutting operation in terms of different parameters like heat generation-induced stresses, etc. The concepts of the metric tensor and Riemannian curvature tensor are made use in this study as a representation of curvature itself. The objective of this study is to create a mathematical methodology that can be implemented on a highly flexible machining process to find an optimum cutting strategy for a particular output parameter.

The study also includes different case studies for the validation of this newly introduced mathematical methodology.

The study will also find its position in other mechanical processes like forging and casting where instantaneous curvature affects various mechanical properties.

This paper aims to present a comparative study of a solar dryer with and without multiple phase change materials (PCMs). It also involves designing and fabricating the experimental model of an indirect solar dryer which uses PCMs for thermal energy storage.

A corrugated aluminium sheet is used as an absorber plate. Aluminium pipes of 0.75 inch are welded under the corrugated sheet to store the PCM. Here, multiple PCMs are used – one with a high melting point and the other with a low melting point for the purpose of improving efficiency. A single air pass model in which air moves over the absorber plate is used for the study. Air is heated in an air heater section which also contains thermal energy storage. The energy obtained in the air heater section is first used to heat and melt the PCM.

Thus, heat energy is stored into the PCM and then the heated air moves into the drying chamber in which drying take place. When the sun’s insolation reduces, discharging from the PCM takes place. Thus, it reduces the fluctuation in the energy and provides continuous energy to the system. Glass wool is used as an insulation material. Different parameters for this air heater-dryer have been calculated.

The current study enhances the understanding of solar drying process and the developed model with and without multiple phase change materials can be used for optimising the drying process.

This paper aims to present the numerical models and experimental outcomes pertain to the performance of the parabolic dish concentrator system with a modified cavity-type receiver (hemispherical-shaped).

The numerical models were evolved based on two types of boundary conditions; isothermal receiver surface and non-isothermal receiver surface. For validation of the numerical models with experimental results, three statistical terms were used: mean of absolute deviation, R² and root mean square error.

The thermal efficiency of the receiver values obtained using the numerical model with a non-isothermal receiver surface found agreeing well with experimental results. The numerical model with non-isothermal surface boundary condition exhibited more accurate results as compared to that with isothermal surface boundary condition. The receiver heat loss analysis based on the experimental outcomes is also carried out to estimate the contributions of various modes of heat transfer. The losses by radiation, convection and conduction contribute about 27.47%, 70.89% and 1.83%, in the total receiver loss, respectively.

An empirical correlation based on experimental data is also presented to anticipate the effect of studied parameters on the receiver collection efficiency. The anticipations may help to adopt the technology for practical use.

The developed models would help to design and anticipating the performance of the dish concentrator system with a modified cavity receiver that may be used for applications e.g. power generation, water heating, air-conditioning, solar cooking, solar drying, energy storage, etc.

The originality of this manuscript comprising presenting a differential-mathematical analysis/modeling of hemispherical shaped modified cavity receiver with non-uniform surface temperature boundary condition. It can estimate the variation of temperature of heat transfer fluid (water) along with the receiver height, by taking into account the receiver cavity losses by means of radiation and convection modes. The model also considers the radiative heat exchange among the internal ring-surface elements of the cavity.

The purpose of this paper is to understand the effect of basin water depth towards the cumulative distillate yield of the traditional and developed single basin double slope solar still (DSSS).

Modified single basin DSSS integrated with solar operated vacuum fan and external water cooled condenser was fabricated using aluminium material. During sunny season, experimental investigations have been performed in both conventional and modified DSSS at a basin water depth of 3, 6, 9 and 12 cm. Production rate and cumulative distillate yield obtained in traditional and developed DSSS at different water depths were compared and best water depth to attain the maximum productivity and cumulative distillate yield was found out.

Results indicated that both traditional and modified double SS produced maximum yield at the minimum water depth of 3 cm. Cumulative distillate yield of the developed SS was 16.39%, 18.86%, 15.22% and 17.07% higher than traditional at water depths of 3, 6, 9 and 12 cm, respectively. Cumulative distillate yield of the developed SS at 3 cm water depth was 73.17% higher than that of the traditional SS at 12 cm depth.

Performance evaluation of DSSS at various water depths by integrating the combined solar operated Vacuum fan and external Condenser.