In this paper, a first- and second-law analysis of vapor compression refrigeration is presented to estimate and propose the replacement of R134 with working fluids having less global warming potential (GWP) and less exergy destruction and irreversibilities. Six different refrigerants were studied, namely, R717, R1234yf, R290, R134a, R600a, and R152a. A thermodynamic model was designed on Engineering Equation Solver (EES) software, and performance parameters were calculated. The model was deployed on all six refrigerants, while the used output parameters of performance were cooling capacity, coefficient of performance, discharge temperature, total exergy destruction, relative exergy destruction rates of different components, second-law efficiency, and efficiency defect of each component. The performance parameters were estimated at different speeds of the compressor (1000, 2000, and 3000 rpm) and fixed condenser and evaporator temperatures of 50 °C and 5 °C, respectively. The isentropic efficiency of the compressor was the same as the volumetric efficiency, and it was taken as 75%, 65%, and 55% at the compressor speeds of 1000 rpm, 2000 rpm, and 3000 rpm, respectively. A comparison of the performance parameters was presented by importing the results in MATLAB. It was found that the compressor had the highest exergy destruction compared to the other components. It was found that R152 was the refrigerant with zero ozone depletion potential (ODP) and a GWP value of 140 with less exergy destruction and irreversibilities. Moreover, it was easy to use R152a with good thermodynamic characteristics. It is estimated that R152a is a suitable replacement for R134a, as it can be used with few modifications.

The unique thing about this research work is that it is the first comprehensive study out of all its kinds in Pakistan. Pakistan is an agricultural country and faces dearth of water resources availability for crops. This research work is very inevitable because it fulfils the water needs and also helps to minimize the energy deficit. This research article represents the means of wind speed data collection, design of wind-driven water pumping system and analysis of the design under different wind conditions in Pakistan. Wind speed data for province Punjab and Sindh are collected from Global Wind Atlas, Pakistan Meteorological Department and World Weather Online. First, design calculations have been made on the basis of analytical methods. Then proposed design is analysed using ANSYS Fluent Simulation models. Wind energy input, lift and drag on blades, rotor power output transmitted to the pump and water discharge from the pump have been calculated and verified from the simulation results. It has been shown that for any rotor size windmill produces maximum power output when angle between blade chord and axis of blade rotation is in the range of 23°–27°. Recommended height of windmill tower for 8–12 ft rotor diameter is 35–50 ft. Designed wind pump system can lift the ground water from 50 ft depth and discharge depends upon the size of windmill used. From the outcomes of the analysis, different designs having different power output and water pumping capacity have been proposed for different operating and wind conditions in the country.

Using modern machines like robots comes with its set of challenges when encountered with unstructured scenarios like occlusion, shadows, poor illumination, and other environmental factors. Hence, it is essential to consider these factors while designing harvesting robots. Fruit harvesting robots are modern automatic machines that have the ability to improve productivity and replace labor for repetitive and laborious harvesting tasks. Therefore, the aim of this paper is to design an improved orange-harvesting robot for a real-time unstructured environment of orchards, mainly focusing on improved efficiency in occlusion and varying illumination. The article distinguishes itself with not only an efficient structural design but also the use of an enhanced convolutional neural network, methodologically designed and fine-tuned on a dataset tailored for oranges integrated with position visual servoing control system. Enhanced motion planning uses an improved rapidly exploring random tree star algorithm that ensures the optimized path for every robot activity. Moreover, the proposed machine design is rigorously tested to validate the performance of the fruit harvesting robot. The unique aspect of this paper is the in-depth evaluation of robots to test five areas of performance that include not only the accurate detection of the fruit, time of fruit picking, and success rate of fruit picking, but also the damage rate of fruit picked as well as the consistency rate of the robot picking in varying illumination and occlusion. The results are then analyzed and compared with the performance of a previous design of fruit harvesting robot. The study ensures improved results in most aspects of the design for performance in an unstructured environment.