Regression analysis for thermal properties of Al2O3/H2O nanofluid using machine learning techniques.

Nanofluids possess higher thermal properties than the other conventional base fluids. Many investigators suggested that the nanofluids have the potential to apply in various engineering fields. In real time situation it is challenging to determine the thermal conductivity of nanofluids with accuracy as they have many depending factors. Moreover, numerous experimental tests are required to acquire the thermal conductivity of nanofluids accurately. In this research paper, thermal conductivity ratio and dynamic viscosity ratio of Al2O3/H2O nanofluid are predicted accurately by using Gaussian Process Regression (GPR) methods. The input predictor variables used in this model are temperature, volume fraction and size of the nanoparticles. 222 experimental data sets are taken to predict the thermal conductivity ratio (TCR), dynamic viscosity ratio (DVR) and also the effectiveness of the predictor variables in predicting the response variables are extensively studied and found that the temperature is the crucial factor to enhance the thermal conductivity ratio. The proposed modeling is performed by using MATLAB software. The predictions were evaluated by various evaluation criterions. It is observed that an optimized Gaussian process regression (GPR) method with matern kernel function shows an accurate agreement with experimental data with Root Mean Square Error (RMSE) value of 0.000126 for TCR and squared exponential kernel function show good agreement with experimental data with Root Mean Square Error (RMSE) value of 0.000045 for DVR. Regression coefficient value (R2) is 0.99; nearer to one hence the predicted results are reliable.

Numerical evaluation of cooling performances of semiconductor using CuO/water nanofluids.

Now a days Very-Large-Scale Integrated (VLSI) circuits are facing critical issues to satisfy the cooling demand because of shrinking the semiconductors. In this numerical work, the surface temperature of the chip, heat transfer rate, thermal resistance, power consumption and reliability are studied by using CuO/water nanofluids as coolant and compared the nanofluids results with the results of water. The CuO/water nanofluids at 0.25%, 0.5%, and 0.75% volume concentration are used for this investigation. The modelling, meshing and simulation are carried out by CATIAv5 and ANSYS Fluent v12 CFX software package. It is observed that the heat transfer rates of semiconductor using the coolant CuO/water nanofluid at 0.25%, 0.5%, and 0.75% volume concentrations are 25%, 43%, and 57% respectively higher than that of water. Found that the surface temperature of the semiconductor is lowered by 3%, 6%, and 8%, the thermal resistances decrease up to 6%, 10%, and 13%, and the Nusselt number increases by 25%, 43%, and 56%, when compared to water. It is also studied that the power consumption of the semiconductor reduces by 3%, 6%, and 8% at 0.25%, 0.5%, and 0.75% volume concentration respectively than water as coolant. It is also found that the failure rate of the semiconductor of using CuO/water nanofluids at 0.25%, 0.5%, and 0.75% volume concentration are 69%, 76%, and 84% respectively smaller than the water.

CFD analysis on heat and flow characteristics of double helically coiled tube heat exchanger handling MWCNT/water nanofluids.

Double helically coiled tube heat exchangers are used in different heat transfer utilization due to higher heat transfer capabilities and with their compactness. The double helically coiled tube heat exchanger increases the turbulence and enhances the maximum heat transfer rate than the straight tubes. In this investigation, the heat transfer and pressure drop of the double helically coiled heat exchanger handling MWCNT/water nanofluids have been analyzed by the computational software ANSYS 14.5 version. The computational analysis was carried out under the laminar flow condition in the Dean number range of 1300-2200. The design of new shell and double helically coiled tube heat exchanger was done by using standard designing procedure and 3D modeling was done in Cre-O 2.0 parametric. The Finite Element Analysis software ANSYS Workbench 14.5 was used to perform CFD analysis under the standard working condition. The MWCNT/water nanofluids at 0.2%, 0.4%, and 0.6% volume concentrations have been taken for this investigation. The major factors like volume concentrations of nanofluids and Dean Number are considered for predicting the heat transfer rate and pressure drop. The simulation data was compared with the experimental data. It is studied that the heat transfer rate and pressure drop increase with increasing volume concentrations of MWCNT/water nanofluids. It is found that the Nusselt number of 0.6% MWCNT/water nanofluids is 30% higher than water at the Dean number value of 1400 and Pressure drop is 11% higher than water at the Dean number value of 2200. It is found that the simulation data hold good agreement with the experimental data. The common deviation between the Nusselt number and pressure dropof CFD data and the Nusselt number and pressure drop of experimental data are found to be 7.2% and 8.5% respectively.

Experimental investigation on convective heat transfer and pressure drop of cone helically coiled tube heat exchanger using carbon nanotubes/water nanofluids.

This study investigates the heat transfer and the pressure drop of cone helically coiled tube heat exchanger using (Multi wall carbon nano tube) MWCNT/water nanofluids. The MWCNT/water nanofluids at 0.1%, 0.3%, and 0.5% particle volume concentrations were prepared with the addition of surfactant by using the two-step method. The tests were conducted under the turbulent flow in the Dean number range of 2200 < De < 4200. The experiments were conducted with experimental Nusselt number is 28%, 52% and 68% higher than water for the nanofluids volume concentration of 0.1%, 0.3% and 0.5% respectively. It is found that the pressure drop of 0.1%, 0.3% and 0.5% nanofluids are found to be 16%, 30% and 42% respectively higher than water. It is studied that the prepared MWCNT/water nanofluids show good stability even after 45 days of preparation and there is no considerable deposit of nanotubes on the tube inner wall. It is also studied that there is no immediate risk of handling MWCNT and studied that there is no significant erosion of coiled tube inner wall surface even after several test runs. Therefore the MWCNT/water nanofluids are the alternate heat transfer fluids for traditional fluids in the cone helically coiled tube heat exchanger to improve the heat transfer with considerable pressure drop.

Performance and emission characteristics of compression-ignition engine handling biodiesel blends with electronic fumigation.

Many research works are being carried out to enhance the performances of internal combustion engines to meet out the current energy demand and to reduce the emission with the alternate fuels. In this experimental investigation, the performances and emission characteristics of compression ignition engine were studied by using electronic fuel fumigation method. The lemongrass biodiesel blended with 20% of biodiesel and 80% of diesel (B20) was used as primary fuel and 1-propanol is used as secondary fuel for fumigation. The Kirlosker, single cylinder four stroke, direct injection, and water cooled engine was taken for conduction of tests. The speed of the engine is maintained constant and the engine load was varied in the range of 0%-100% and fumigation injection timing is varied in the range of 1 ms, 3 ms and 5 ms to study the engine parameters. It is studied that the brake thermal efficiency of fumigation fuel at 5 ms is 6.7% higher than diesel and at 3 ms is 3.1% higher than the diesel fuel at 100% load. The specific fuel consumption at 5 ms is 16 % higher than the reference diesel fuel. The 5 ms 1-propanol fumigation produces the maximum HC and CO with minimum smoke and NO because of lower combustion temperature and incomplete combustion. The SFC of fumigation fuel at 5 ms is 18.6% higher than diesel at 100% load and 23 % higher than diesel at 80% load. The net heat release of fumigation fuel (1-propanol) at 1 ms produces 2% higher than the reference diesel at crank angle of 360°. The fumigation fuel (1-propanol) injection timing at 5 ms produces more percentage of CO at different load conditions. It is also studied that the minimum level of CO is 0.38 % at 40% load condition. The fumigation fuel at 5 ms injection timing produces minimum percentage of CO2 at different load conditions. The minimum level of CO2 is 9.3% at 80% load condition. The other emissions are also analyzed and recorded the levels based on the load condition.