Optimization of a thermoacoustic refrigerator with an evolutionary algorithm approach

Current non-environmentally friendly refrigerants released into our environment have caused serious concern over reports of the depleting of the ozone layer and global warming. Alternative technologies and efficient energy-related systems are being investigated to perhaps reduce if not stop the environmental degradation. This paper reports the outcomes of an optimization procedure performed on an environmentally friendly standing wave thermoacoustic refrigerator. A typical system to date has a low coefficient of performance (COP) and thus is not attractive to the general public. Optimization is completed using genetic algorithm over four design variables; the stack length and center position within a thermoacoustic resonator, the blockage ratio, and drive ratio. Optimization results show a maximum COP obtainable at 1.64. The outcomes indicate a potential for better thermoacoustic refrigerators in future

Single-objective optimization of a thermoacoustic refrigerator

Optimization of energy-related systems with by-products that involve environmental degradation has never been so crucial today with depleting resources and global concerns over negative impacts on our environment. This paper reports the results of an optimization scheme on the coefficient of performance (COP) of a standing wave thermoacoustic refrigerator based on genetic algorithm. The environmentally friendly refrigerator operates without any CFCs, which has been associated with the depletion of ozone, a substance that prevents uv light from reaching the earth’s atmosphere. A single- objective optimization to maximize the COP of a thermoacoustic refrigerator has been completed. The variables investigated include the length of the stack, Lsn, center position of the stack, xsn, blockage ratio, B and drive ratio, DR. The results show that a COP of up to 1.64 is achievable which provides promise for future improvements in the present systems

Optimization of Temperature Rise in Turning Using Single Objective Genetic Algorithm

Temperature rise is an essential element that must be consider during machining process which will contribute to the satisfactory end products. All the factors such as cutting environments, methods and work material must be emphasize since it will influence the outcome. The optimization of the machining process was carried out in this research to optimize the machining process by minimizing temperature rise for turning machining. The parameters involve during this optimization are cutting speed, feed rate, depth of cut and nose radius by using genetic algorithm optimization. This study was separated into three sections, each of which was optimized to see what effect each parameter had on temperature rise. The minimum temperature attained was 23.07 °C, while the cutting variables for cutting speed, feed rate, and depth of cut were 81.22 m/min, 0.08 mm/rev, and 0.12 mm, respectively

Optimal frictional pressure drop and vapor quality relationship of ammonia and R22 in two-phase flow

Research in two-phase flow in heat exchanging devices plays an important part in today’s applications in miniaturization of engineering systems. The phase change process factors in the flow conditions and heat transfer in evaporators and condensers. Numerous studies in the past have looked at the predicted and measured frictional pressure drop of coolants as the vapor quality increases. This paper reports a preliminary attempt at modeling of the relationship between the frictional pressure drop and vapor quality in an ammonia-cooled and R22-cooled mini-channel of 1.5 mm diameter under optimized conditions using multi-objective genetic algorithm. R22 is a being phased-out due to its ozone-depleting characteristic and ammonia is being considered as its potential replacement. The properties of ammonia and R22 used have been obtained experimentally at the saturation temperature of 5?C and 10?C respectively. Modeling of the minimized pressure drop per unit tube length together with the Lockhart-Martinelli parameter was completed under optimized flow rate and vapor quality.The outcomes obtained are similar to those that have been reported experimentally with other coolants, increasing pressure drop with increasing vapor quality

Development of stack component for thermoacoustic refrigerator using 3d printer

The development of thermoacoustic technology is motivated by the prospect that this technology will replace or reduce the dependence on the current vapor compression technology .The thermoacoustic refrigerator is an innovative alternative for clean cooling. The thermoacoustic effect is significant for intense sound waves in pressurized chamber. This effect can be utilized to produce a powerful engine, pulsating combustion, heat pumps, refrigerators, and mixture separator

Optimization of Machining Parameters in Turning for Different Hardness using Multi-Objective Genetic Algorithm

Surface finish and temperature rise are the crucial machining outcomes since it determines the quality of the machining and the tool life. During machining operations, choosing optimal machining parameters is critical since it affects the machining outcome. In this work, Multi-Objective Genetic Algorithm (MOGA) optimization is used to find the combination of machining parameters at different levels of hardness of 20, 36, and 43 to obtain minimum surface roughness and minimum cutting temperature in turning operation. Cutting depth, cutting speed, and feed rate are the machining variables that are used in the process of optimization. From the results, it shows that the minimum temperature rise is 243.333 ℃ with a surface roughness of 1.975 µm during machining of 20 hardness. It also observed that the hardness of the material significantly affects the surface roughness and temperature rise. The outcome shows that as the hardness of the material is increasing the temperature is increasing while the surface roughness is decreasing. This research also revealed that using a MOGA to optimize multi-objective replies produces positive outcomes

Modeling of the minimized two-phase flow frictional pressure drop in a small tube with different correlations

The major parameters of interest in heat transfer research are the refrigerant charge, pressure drop, and heat transfer capacity. Smaller channels reduce the refrigerant charge with higher heat transfer capability due to the increased in surface area to volume ratio but at the expense of a higher pressure drop. Differences between the predicted and experimental frictional pressure drop of two-phase flow in small tubes have frequently been discussed. Factors that could have contributed to that effect have been attributed to the correlations used to model the flow, some being modified from the originals developed for a macro system. Experimental test-rigs have varied in channel geometry, refrigerant type, and flow conditions. Thousands of data have been collected to find a common point among the differences. This paper reports an investigation of four different two-phase friction factor correlations used in the modeling of the frictional two-phase flow pressure drop of refrigerant R-22. One had been specifically developed for laminar flow in a smooth channel, another was modified from a laminar flow in a smooth pipe to be used for a rough channel, and two correlations are specific for turbulent flow that consider internal pipe surface roughness. Genetic algorithm, an optimization scheme, is used to search for the minimum friction factor and minimum frictional pressure drop under optimized conditions of the mass flux and vapor quality. The results show that a larger pressure drop does come with a smaller channel. A large discrepancy exists between the correlations investigated; between the ones that does not consider surface roughness and that which does, as well as between flow under laminar and turbulent flow conditions

Flow pattern analysis for oscillatory flow inside resonator tube for thermoacoustic refrigerator using PIV measurement

A thermoacoustic refrigerator system is an alternative cooling system that uses air or inert gas as a cooling fluid. The environmentally friendly characteristics make this system potential as a green alternative for a cooling system. However, due to its low efficiency compared to conventional vapor compression systems, its application is limited. Since a thermoacoustic refrigerator is based on the oscillatory flow to generate a cooling effect, the understanding of a flow pattern inside the resonator tube is crucial to enhance the coefficient of performance (COP) of the system. In this study, Particle Image Velocimetry (PIV) is used to visualize the flow pattern inside the resonator tube. PIV is an optical, noninvasive technique that uses a high-speed camera, highpower multipulse laser, and synchronizer to capture the particle movement in the resonator with a length of 1 m, and the frequency applied is 100 Hz. The result shows that there is a formation of a vortex at the entrance and at the exit of the stack. The formation of the vortex at the entrance induces by the flow disturbance created by the stack. This vortex formation varied with the location of the stack and the amplitude of the wave applied. The velocity distribution of the particle inside the resonator tube is also presented and discussed in this paper. These findings indicate that the flow patterns and velocity distribution should be further analyzed to interpret the effect of these characteristics on the system. These results are expected to give a better understanding of the future development of the thermoacoustic system

A review: Use of evolutionary algorithm for optimisation of machining parameters

Optimisation of machining parameters is crucial to ensure higher productivity and optimum outcomes in machining processes. By optimising machining parameters, a particular machining process can produce better machining outcomes within equivalent resources. This paper reviews past studies to achieve the desired outputs; minimum surface roughness (SR), highest material removal rate (MRR), lowest production cost, and the shortest production time of machining processes and various optimisation attempts in terms of varying parameters that affect the outcomes. The review deliberates the optimisation methods employed and analyses the performance discussing the relevant parameters that must have been considered by past researchers. To date, most studies have been focusing on optimising conventional machining processes such as turning, milling, and drilling. Optimisation works have been performed parametrically, experimentally, and numerically, where discrete variations of the parameters are investigated, while others are remained constant. Lately, evolutionary algorithm, statistical approaches such as genetic algorithm (GA), particle swarm optimisation (PSO), and cuckoo search algorithm (CSA) have been utilised in simultaneous optimisation of the parameters of the desired outputs and its great potential in optimising machining processes is recognisable

The prospective of particle image velocimetry (PIV) measurement velocity profile in thermoacoustic system

Precise measurement of fluid velocities is essential in several applications, including thermoacoustic refrigeration systems. A thermoacoustic refrigeration system uses a high-amplitude acoustic standing wave to generate a cooling effect. Understanding the fluid flow characteristic between the refrigerant and a stack is important to improve the heat transfer process and minimise thermal and viscous losses. This paper reviews the various methods employed by previous researchers in analysing the velocity profiles in the thermoacoustic refrigeration system and the prospective implementation of Particle Image Velocimetry (PIV). PIV is a non-invasive technique that estimates velocity at several points of the measuring region. This review looked at the method employed to analyse the velocity profile, error analysis, and the effectiveness of another measurement method compared to the PIV measurement. The discussions include related parameters that past researchers have considered