Optimization of performance of PV panels and selection of best site for solar park in Pakistan

To incorporate solar energy efficiently into a country, it is needed to know the optimal tilt and azimuth angle of the solar collectors' location. Also, to build a solar park, it is necessary to know the most suitable and high-energy generating place inside a country, thus saving time and money. This study analyzed collector geometry for Karachi in particular and Pakistan in general. Karachi has the potential of 339.36 kW-hr/m2/annum energy at an annually optimal fixed tilt of 26°. In case collector geometry had to be changed in Karachi, a range of 40° azimuth angle and 20° tilt angle from its maximum value is available. The power produced in this case would only have a difference of 1%. Optimal yearly and monthly tilt of most of the locations of Pakistan (300+) were calculated. Through them, it was revealed that the Optimal Tilt of Pakistan follows the value of latitude closely. Generally, changing the tilt angle monthly is recommended for areas that produce more energy, while fixed annual tilt could be suitable for low energy-producing regions. Effects of temperature were also incorporated while finding the energy produced by the photovoltaic (PV) panels.

Numerical investigation of the effect of hole reaming on fatigue life by cold expansion

The reaming process of the 6061 aluminum alloy plate after cold expansion with split sleeve was simulated by finite element (FE) method based on Abaqus/CAE, the relationship between the reaming depths and the distribution of residual stress fields is obtained by analysis. The fatigue lives of the plate under different reaming depths were calculated by using the fatigue analysis software FE-SAFE, and verified by fatigue tests. The results show that reaming after expansion will increase the residual compressive stress at the hole edge on the entrance surface. In addition, the fatigue life of the specimens increases with the increase of the reaming depth, and the best fatigue gain of the specimen is obtained when the reaming depth of 0.5 mm.

Fatigue life analysis of pressure vessel based on residual strength and crack size

In the field of pressure vessel fatigue life, the study of fracture failure is very important. Based on the Paris law, the relation model between fatigue crack size and residual fatigue life is established by considering the circumferential stress. The relationship between the crack length and the crack depth is introduced. According to the specific structure of the pressure vessel, the relationship model between the fatigue crack size and the residual strength is established based on the residual strength allowable value. The S-N curve of pressure vessel is obtained based on two models. The fatigue life of the pressure vessel is predicted combined with the actual test data. By comparing with the actual service life, the feasibility of the model is verified, which provides a new method for predicting the residual life of pressure vessels.

Combine Assembly Fault Diagnosis Based on Optimized Multi-scale Reverse Discrete Entropy

An optimized multi-scale reverse discrete entropy (RDE, OMRDE) method for feature extraction is proposed to address the lack of effective feature extraction and detection methods for combining harvester assembly fault inspection. This method is used to extract vibration signal features from the harvester. A fault diagnostic method is designed to verify the efficiency of the associated methods. First, a comparative study of RDE, multi-scale inverse RDE (MRDE), and OMRDE was performed using simulated signals to verify the effectiveness of OMRDE. Second, the FSTPSO–VMD method was used to decompose the vibration signal of the combine harvester assembly fault, and the OMRDE, MRDE, and fuzzy entropy were compared and analyzed. The actual feature extraction effect of the three entropy functions reached the highest classification accuracy (88.5%) after using OMRDE to extract features. Finally, a fusion feature set is constructed to further improve the classification accuracy, and the LSSVM classifier is further optimized through FSTPSO. Analytical results show that the FSTPSO–LSSVM classifier constructed in this work adopts the fused feature with an accuracy of 93%, which is better than other common methods and verifies the validity of the fault diagnostic model. Therefore, the performance of the OMRDE proposed in this work is better than those of MRDE and MRDE. The proposed fault diagnostic model can realize accurate classification of the combine harvester assembly fault detection.

SLIDING FRICTION WEAR BEHAVIOUR OF SEASHELL PARTICULATE REINFORCED POLYMER MATRIX COMPOSITE – MODELING AND OPTIMIZATION THROUGH RSM AND GREY WOLF OPTIMIZER

In this work, the friction wear behaviour of seashell particles reinforced in thermoplastic polymer Nylon-6 is investigated.. Seashells were collected from the seashores, uniform size 75 µm is obtained using mechanical ball milling and vibrating sieve. Various proportions of seashells such as 12, 15 and 18% by weight are added to nylon-6 and the polymer composites wear performance in dry sliding is studied as per ASTM G99 standard, loss of material in wear, friction coefficient and interface temperature are optimized. For experiment design Response surface methodology (RSM) based Box-Behnken method (BBD) is adopted and multi-objective analysis is performed using desirability analysis. Observation shows that interface temperature is highly influenced by rotational speed (41.61%), % reinforcement of seashells influences the wear loss significantly (35.71%) and coefficient of friction is influenced greatly by rotational speed (41.48%)and % reinforcement of seashells (18.18%). A novel metaheuristic algorithm Grey wolf optimizer is used for constrained optimization, which shows that for 0.3 CoF and 25°C interface temperature as constraint wear loss is 35.77 microns for % reinforcement of seashell as 3.59, whereas for 0.3 CoF and 30°C interface temperature wear loss is 28.99 microns for a seashell reinforcement of 18%.

Rapid and tunable growth of well-ordered hexagonal nanoporous anodic aluminum oxide (AAO) structure by two step high temperature anodization

In this study, we have developed a swift and well-ordered growth of the Anodic Aluminum Oxide (AAO) nanoporous structure by two-step high temperature anodization of pure Aluminum substrate. The pre-anodization surface treatment of the aluminum substrate assists in the formation of well-organized nanoporous structures. The two-step anodization process was performed in 0.3 M of oxalic acid at 20 °C for 40 V and 45 V to obtain tunable pore diameters. The high temperature of the electrolyte solution helps in the rapid growth of the AAO nanoporous structure. The top surface image of AAO shows a well-ordered nanoporous structure with an average pore diameter of 70 nm at 40 V and 100 nm at 45 V. The SEM cross sectional view also illustrates the well-ordered nano channel and the elemental mapping elaborates the presence of aluminum and oxygen. The thickness of the AAO nanoporous structure was determined by using SEM for three anodization time spans (20, 24 and 28 hours), in which an increasing trend was observed. The fabricated AAO has a higher thickness and a well-ordered nanoporous structure that shows it can be used as a template for fabricating nanostructured materials.

Aircraft Fuel Thermal Management System and Flight Thermal Endurance

An aircraft thermal management model was created in which fuel is circulated through the heat dissipating components for cooling purposes. A fraction of this fuel is then fed to the engine for combustion, while the excess is cooled by rejecting heat to the ambient and returned to the tank. The thermal management system was designed with the intent of controlling the heat dissipating surface temperature, ensuring a certain heat removal rate, while safeguarding the physical integrity of the fuel. The time variation of the fuel temperature and heat transfer rates was calculated. It was observed that for a constant heat dissipating surface temperature, the heated fuel temperature increased, and the heat removal capacity degraded over time. Conversely, for a specified heat removal rate, both the heat dissipating surface temperature and heated fuel temperature increased during the flight. Lastly, when the maximum fuel temperature was specified, both the heat dissipating surface temperature and heat removal rate decreased over time. In all cases, the time taken for these variables to hit the user-defined threshold values was recorded. A detailed sensitivity analysis was also presented highlighting the critical importance of the fuel recirculation rate on the performance of the thermal management system.

On Probabilistic Assessment of Exergy Analysis of a Wind Turbine for Optimum Performance

Judgment on the performance of a wind turbine depends upon its first law efficiency as well as its second law efficiency. This paper focuses on the second law efficiency, i.e., the exergy efficiency of a wind turbine. The work introduces a novel technique to determine the optimum performance conditions of a wind turbine. Jhimpir city, Pakistan, has been selected as a case study. The wind speed distribution of the selected area is analyzed using different probability density functions. Three-parameter Weibull Distribution turns out to be the best probability density function fitting the wind speed variation. Probability distribution of total wind exergy is performed, and a one-year variation of wind exergy is plotted, showing maximum exergy around the middle of the year. The exergy efficiency of the turbine using a power curve and wind exergy is determined at different wind speeds. Probabilities of various exergy efficiencies are also determined. Results show that higher exergy efficiency has a high probability but so does low exergy efficiency due to seasonal variations. The proposed method can be extended to any wind farm provided the geographical and meteorological parameters of the site.

Effect of blowing ratio on Film-Cooling effectiveness of Ginkgo Shaped Holes: A numerical approach

Modern gas turbine engines operate at significantly high temperatures to improve thermal efficiency and power output to a greater extent. The enhancement in rotor inlet temperature (RIT) increases the heat transfer rate to the turbine blades which requires sophisticated cooling schemes to maintain the blade temperature in acceptable levels. Therefore, the present work refers to the numerical investigation of film cooling technique applied in gas turbines. The cooling performance of two different shaped holes namely Ginkgo Forward (GF) and Ginkgo Reverse (GR)) were investigated in terms of centerline and local lateral effectiveness and comprehensive comparison was made with the cooling performance of cylindrical (CY) hole. The investigations were performed at two density ratios (DR=1.6, 2.0) and three different blowing ratios (BR=1.0, 1.5 and 2.0). At all the operating conditions, the results demonstrated significant augmentation in centerline and lateral effectiveness when GR shaped hole was employed followed by the GF and CY cooling holes. For shaped holes, the low velocity gradient through the film alleviated jet lift off and turbulence intensity resulting in decreased entrainment of hot gas to bottom surface. To conclude, the lateral coverage due to the shaped cooling holes significantly enhanced the thermal protection and overall cooling performance.

AN ASSESSMENT OF VARIOUS NANOADDITIVES AND TRIBO-CORROSION WITH WASTE COOKING BIODIESEL FUELED IN A DIESEL ENGINE

The waste cooking biodiesel's steady-state coefficient of friction rate of fuel blends are B90 (18.2%), B60 (7.2%), B20 (16.72%), B10 (30.8%), and diesel (38.77%) higher compared with B40 fuel blend and wear scar diameter of the fuel blends from B40 to B100 had a minimal range of 0.5mm. The flash temperature parameter results higher from B40 to B100 fuel blends, and the corrosion rate was minimal for B40 and B50 fuel blends. Afterward, the fuel blend B40 (40% WCO+60% Diesel fuel) was chosen as fuel, along with Cerium (25ppm), Zinc (25ppm), and Titanium nanoparticles (25ppm) were selected as fuel additives. The B40+D60+Titanium (25ppm) blend resulted in improved BTE and 3.83% lowered BSEC comparison with diesel fuel. Then the fuel blend, B40+D80+Titanium (25ppm), resulted in 2.08% reduced HC, 36.36% CO, and 16.25% smoke emissions, along with marginally 8.5% higher NOx emissions comparison with diesel fuel. Also, the fuel blend, B40+D80+Titanium (25ppm) combustions characteristics are the equivalent trend of cylinder pressure (58.82 bar) and HRR (66.65 J/deg CA) related to diesel fuel at peak load.