Kamal Sharma’s research while affiliated with GLA University and other places

Solar stills are simple devices that can be used to remove salts from water. However, it has a lower distillate yield; hence, it is not popular. Increasing the solar energy collection at the absorber may help to address these issues. This is feasible by adopting highly absorbent energy storage substances. Hybrid nanomaterials have significant potential for this purpose, and they can boost the absorptivity of the absorber plate of solar stills. Taking this into account, a hybrid nanomaterial was synthesized in a laboratory and applied to the surface of a solar still absorber to achieve higher performance. Iron oxide (Fe 2 O 3 ) and copper oxide (Cu 2 O) nanoparticles were used in a 50:50 ratio. In addition, the current research employed a water sprinkler to enhance the condensation rate in the condensing region and consequently increase the distillation output of the solar still. A cooling water flow rate of 10 kg/h was used to sprinkle the condensing surface. According to the results, combining Fe 2 O 3 and Cu 2 O with epoxy resin increased the efficiency of the solar still by 34% when using a glass cooling approach and by 28% when operating without a glass cover cooling technique.

The use of technologies such as robotics, image processing, and machine learning has the potential to bring about substantial shifts in agriculture. This is particularly true when it comes to ploughing, one of the agricultural practices that demands the most rigorous physical effort there is to be found. As a consequence of the continuous use of traditional agricultural practices, which are marked by a strong dependence on human effort as well as huge pieces of equipment, there are numerous worries about the long-term sustainability of both the economy and the environment. These practices are characterised by a high reliance on both human labour and large pieces of gear. These concerns are principally brought about bythe fact that conventional farming practices substantially, and to varied degrees, depend on both the work of humans and considerable quantities of technology. In order to find solutions to these issues, the primary emphasis of our study has been placed on the development of an image-processing-based robotic automobile that has the capability of tilling agricultural land. Thanks to computer vision and machine learning algorithms, the self-driving robotic vehicle is able to travel the fields while simultaneously assessing the depth of the ploughing, as well as the pace and direction of the ploughing. Due to the fact that the vehicle is capable of driving itself, this is not an improbable scenario at all. It is essential to cut down on the quantity of manpower that is necessary, as well as the expenses of operations and the negative consequences that existing agricultural practices have on the surrounding environment. The findings of the trial indicate that the technology is able to accurately recognise crops, navigate around obstacles, and determine the appropriate depth at which to plough the soil. These findings offer light on the potential for this technology to raise agricultural production and sustainability, which in turn will promote both the development of the agricultural sector as well as the degree of global food security.

Phase change materials (PCMs) are important constituents for the storage of thermal energy available from the sun. It acts as a bridge between energy demand and supply while reducing the mismatch. Organic and inorganic constituents have been used for a long time for thermal energy storage applications. In recent years, the focus has been shifted to eutectics. A eutectic is a minimum melting substance of two or more constituents. It has the advantage of having a sharp melting temperature and possessing high volumetric heat storage density. The eutectics possess a wide range of temperatures and have the properties of all of their constituents. At present organic-organic, organic-inorganic, and organic-inorganic eutectics are widely studied. In the present paper, various eutectic PCMs for low and medium temperature ranges have been analyzed. Their thermophysical properties and thermal stability and reliability concerning thermal cycling have been thoroughly discussed. The melting temperature lies in the range of −23.50 °C to 80 °C and the latent heat of fusion can be as high as 280 kJ/kg. Thermal cycle tests of up to 30000 have been conducted by various research groups, but at least 300 melt/freeze cycles are recommended so that they can be stable for a year of application. The organic eutectic PCMs are found stable in terms of deviation in melting temperature with the maximum deviation in latent heat of fusion observed was ± 20 %. The inorganic eutectic PCMs are somewhat unstable having a large deviation in melting temperature and latent heat of fusion. The low thermal conductivity of organic eutectics can be eliminated with suitable nanoparticle additives. The leakage issue can be eliminated by providing shape stabilization to the PCMs. These PCMs are suitable for various photovoltaic/thermal, buildings, textiles, solar water heating, solar air heaters, and heat recovery systems applications.

Central workshop is an integral part of any higher education institution, and it will be generally operated in a gable-roofed metallic shed. The users of the building are affected physiologically and psychologically due to the thermal discomfort conditions caused by improper ventilation. It is necessary to study the cause for discomfort and propose cost and effective methods to mitigate the problem. In this work, the thermal comfort inside a gable-roofed workshop was analyzed, and it was found that the discomfort was predominant from 2 PM to 5 PM. It was predicted that the conduction heat transfer could be reduced upto 55% with the help of passive cooling technique carried out using aluminium bubble wrap. During the life cycle cost study, the aluminium bubble wrap technique was found to be more economical over high-volume low-speed fan. The computer simulation aided in the prediction of overall heat transfer coefficient and conduction heat transfer through wall. The results from numerical study deviated by less than 0.1% when compared with that from the theoretical model.