Heat and mass transfer enhancement in triangular pyramid solar still using CNT-water nanofluid

This work represents a 3 D numerical study of the effects of carbon nanotube(CNT)-water nanofluids on the double diffusive convection inside the triangular pyramid solar still.This numerical investigation is performed for wide ranges of governing parameters such as buoyancy ratio(-10≤N≤0),volumetric fraction of nanoparticles(0≤Φ≤0.05) and Rayleigh number(10^(3)≤Ra≤10^(5)).The results are presented in terms of flow structure,temperature field,heat and mass transfer rates variations.It was found that the buoyancy ratio can be considered as an optimizing parameter for the heat and mass transfer,and the use of CNT has a positive effect on the solar still performances.

Optimization of Bearing Locations for Maximizing First Mode Natural Frequency of Motorized Spindle-Bearing Systems Using a Genetic Algorithm

This paper has developed a genetic algorithm (GA) optimization approach to search for the optimal locations to install bearings on the motorized spindle shaft to maximize its first-mode natural frequency (FMNF). First, a finite element method (FEM) dynamic model of the spindle-bearing system is formulated, and by solving the eigenvalue problem derived from the equations of motion, the natural frequencies of the spindle system can be acquired. Next, the mathematical model is built, which includes the objective function to maximize FMNF and the constraints to limit the locations of the bearings with respect to the geometrical boundaries of the segments they located and the spacings between adjacent bearings. Then, the Sequential Decoding Process (SDP) GA is designed to accommodate the dependent characteristics of the constraints in the mathematical model. To verify the proposed SDP-GA optimization approach, a four-bearing installation optimazation problem of an illustrative spindle system is investigated. The results show that the SDP-GA provides well convergence for the optimization searching process. By applying design of experiments and analysis of variance, the optimal values of GA parameters are determined under a certain number restriction in executing the eigenvalue calculation subroutine. A linear regression equation is derived also to estimate necessary calculation efforts with respect to the specific quality of the optimization solution. From the results of this illustrative example, we can conclude that the proposed SDP-GA optimization approach is effective and efficient.

Effects of using sinusoidal porous object(SPO)and perforated porous object(PPO)on the cooling performance of nano-enhanced multiple slot jet impingement for a conductive panel system

Cooling system design for thermal management of electronic equipment,batteries and photovoltaic(PV)modules is important for increasing the efficiency,safety operation,and long life span the products.In the present study,two different cooling systems are proposed with nano-enhanced multiple impinging jets for a conductive panel.The present cooling systems can be used in electronic cooling and PV modules.Perforated porous object(PPO)and sinusoidal porous object(SPO)are used in the jet cooling system.2D numerical analysis usingfinite volume method is conducted considering different values of permeability of the objects(Darcy number(Da)between 10^(-6) and 10^(-1)).When PPO is used in the cooling system,num-ber of cylinders(between 1 and 6),and size of the cylinders(between 0.015 and 0.075)are considered.In the case of using SPO,amplitude(between 0.1 and 2)and wave number(be-tween 1 and 12)are varied.Alumina-water nanofluid with cylindrical shaped nanoparticles is used as the heat transferfluid.When permeability is changed for PPO,the average temper-ature increases by roughly 3.89℃ for a single cylinder and drops by roughly 0.57℃ for a six-cylinder cases.Increasing the size of the cylinder in the PPO case at highest permeability results in temperature drop of 5.3℃.When changing the number of cylinders,cooling rate varies by about 3.6%.Wave number of SPO is more influential on the cooling performance enhancement as compared to amplitude and permeability of the SPO.The average surface temperature drops by 12.4℃ when the wave number is increased to 12.As compared to reference case of jet impingement cooling without porous object,using PPO and SPO along with the nanofluid result in temperature drop of 12.3℃ and 14.4℃.

Optimizing SUS 304 wire drawing process by grey relational analysis utilizing Taguchi method

In the stainless steel 304 （SUS 304） wire drawing process, optimizing the die life and wire tensile strength, which are the larger-the-better quality characteristics （QCH） types, is of main interest. Three control factors, involving reduction ratio, lubricant temperature, and drawing speed, were investigated utilizing L9（34） orthogonal array （OA）. The grey relational analysis was conducted for the normalized signal-to-noise （S/N） ratios. The ordinal value of the grey grade was then used to decide optimal factor levels. The anticipated improvements in die life and wire tensile strength were estimated 25.31 h and 22.50 kg/mm2, respectively. To decide the significant factor which had effect on each QCH and predict the average value of each QCH, analysis of variance （ANOVA） was performed for S/N ratio and QCH. Confirmation experiments were then conducted, where a good overlap was noticed between the predicted and confirnation intervals for each QCH. The Hotelling T2 and the sample generalized variance control charts were finally utilized in controlling and monitoring future production. In conclusion, the grey relational analysis utilizing Taguchi method is an effective approach for optimizing the die life and wire tensile strength for SUS wire drawing process. 2008 University of Science and Technology Beijing. All rights reserved.

A discussion of objective function representation methods in global optimization

Non-convex optimization can be found in several smart manufacturing systems. This paper presents a short review on global optimization(GO) methods. We examine decomposition techniques and classify GO problems on the basis of objective function representation and decomposition techniques. We then explain Kolmogorov's superposition and its application in GO. Finally,we conclude the paper by exploring the importance of objective function representation in integrated artificial intelligence, optimization, and decision support systems in smart manufacturing and Industry 4.0.