Numerical optimization of small-scale thermo-acoustic refrigerators considering maximum cooling

Abstract: The use of sound wave to remove heat could potentially contribute significantly to the development of a more affordable, sustainable search of an effective solution for electronics coolers. This work provides details of the implementation of a lexicographic optimization scheme in order to address the issue of dimensional optimization of a small-scale standing-wave thermo-acoustic refrigerator system. The cooling load has been considered as main criteria in the formulation and the measurement of the performance of the system. The dimensional parameters describing the heart of the device, namely the porous media (or the stack), where the heat pumping takes place are the variables to optimize. The problem has been formulated as a non-linear programming problem with discontinuous derivatives and implemented in the General Algebraic Modelling Systems (GAMS). The main contributions of the work are the detailed GAMS model and the clarity about the most preferred position and length of the stack considering prior knowledge of its porosity. This work reveals that shorter stack perform relatively better with respect to the cooling load performance. In addition, it appears that the position of the stack within the resonator tube is closely related to its length for maximum performance of the device

Forecasting net energy consumption of South Africa using artificial neural network

Abstract: This work proposes the use of Artificial Neural Network (ANN) as a new approach to determine the future level of energy consumption in South Africa. Particle Swarm Optimization (PSO) was used in order to train Artificial Neural Networks. The population size, the percentage losses, the Gross Domestic Product (GDP), the percentage growth forecasts, the expected Final Consumption Expenditure of Households (FCEH) as well as the relevant manufacturing and mining indexes are the “drivers” values used for the forecasts. Three growth scenarios have been considered for the forecasting namely low, moderate and high (less energy intensive) scenarios. These inputs values for the period of 2014 to 2050, from the Council for Scientific and Industrial Research (CSIR), were used to test data and validate the use of this new approach for the prediction of electricity demand. An estimate of the annual electricity demand forecasts per scenario was calculated. Besides the speed of the computation, the proposed ANN approach provides a relatively good prediction of the energy demand within acceptable errors. ANN was found to be flexible enough, as a modelling tool, showing a high degree of accuracy for the prediction of electricity demand. It is expected that this study will contribute meaningfully to the development of highly applicable productive planning for energy policies

A sustainable solution for electricity generation using thermo-acoustic technology

Abstract: This work explores the use of thermo-acoustic system as alternative technology for electricity generation. This technology is proposed as a potential replacement for low-cost electrical power generation because of its simplicity and lack of moving parts. Thermo-acoustic generators providing clean electrical energy to power small appliances. The energy conversion from heat into sound wave is done within thermo-acoustic engine. The latter is coupled to a linear alternator for electricity generation. The study investigates the influence of the geometrical configuration of the device on to the whole functionality of the generator. The paper studies the technology through experimental trails performed using a simple arrangement to simulate the generator. The experiment is conducted in phases; the first phase identifies the best geometrical configuration of the thermo-acoustic engine by measuring the sound pressure level and the temperatures. The second phase consist of measuring the electricity generated using a Loudspeaker. The results obtained show the potential for this sustainable solution for electricity generation

Evaluation of the Stirling heat engine performance prediction using ANN-PSO and ANFIS models

Abstract: The work presents the prediction performance results of three algorithms, namely Artificial Neural Network (ANN), Artificial Neural Network trained with Particle Swarm Optimization (PSO) and Adaptive Neuro-Fuzzy Inference System (ANFIS) models. ANFIS and ANN trained by PSO are applied to predict the power and torque values of a Stirling heat engine with a level controlled displacer driving mechanism. Data from experimental work done by Karabulut et al. is used to train and assess the algorithms. MATLAB is used to develop, implement and train the algorithms. The Root Mean Square Error (RMSE, Coefficient of determination (R2) and computational time are used to assess the performance of the algorithms

Development of solar powered water purification systems

Abstract: In this paper, we highlight the effects of contaminated water on humans as well as the crisis of water supply and distribution of potable water in many areas of developing countries. Water is the most important substance on earth. While water is a primary human need, contaminated water can cause and spread diseases. It is, therefore, necessary to ensure that water is purified and decontaminated for daily use at a low-cost. Therefore, the design of solar-powered water purification systems is considered to produce clean water. Solar energy poses no polluting effect; thus, has become a dependable energy source for usage. The design of a solar-powered water purification system is based totally on the thermal method by using the thermal heating system principle. This principle converts sunlight rays into heat. The most vital aspect is the absorption of heat to induce evaporation of water. Research shows that flat plate collectors produce heat at relatively low temperatures (27°C to 60°C) and are commonly used to heat liquids. A solar-powered water purification system consists of a solar collector that absorbs sunlight to ensure vaporisation which is the first stage of purifying and a filter that removes contaminants. Four different concepts have been developed. A detailed description of the components and the operation of the systems constitute the main contribution of this paper

Performance evaluation of ceramic substrates for cooling applications in thermo-acoustic refrigerators

Abstract: Thermo-acoustic refrigerators have recently drawn more attentions because of its eco-friendlier potential to address the current environmental issues resulting from the use of traditional vapour compression refrigerators. This paper aims at evaluating different selected ceramic substrates, with square pores, from the point of view of their performance as stack materials in the design of thermo-acoustic standing wave refrigerators. A 465 mm standing wave thermo-acoustic refrigerator was designed using numerical approximation provided by a modeling code called DELTAEC (Design Environment for Low-amplitude ThermoAcoustic Energy Conversion). The design developed focuses, in particular, on the effects of different ceramic substrate configurations (diameter, length, porosity and position) on the performance of the device. Meaningful comparison on the effect of the ceramic substrates configuration is provided in order to assess the performance of the device. Guidance on the identification and the selection of the best geometrical configurations of ceramic substrates are the main contributions of this work

Experimental investigation of ceramic substrates in standing wave thermoacoustic refrigerator

Abstract: This work experimentally investigates the performance of ceramic substrates used as stacks in standing wave thermoacoustic coolers. Thermoacoustic technology is proposed in this study as an alternative sustainable solution to current issues with vapour compression refrigerators because of its environmentally friendlier attributes. However, the main hindrance to the expansion of this technology is its current lack of efficiency. Hence, an experimental investigation is conducted in this study. The influence of the geometrical configuration of the stack, described as the heart of the device, is investigated. The device was equipped with different selected low-cost porous materials (ceramic substrates) for performance testing and studies. Porosity, length and position of the ceramic substrates are variables that are considered in order to investigate the performance of the cooler. Eight cordierite honeycomb ceramic substrates with square cross sections and of four different lengths (26 mm, 48 mm, 70 mm and 100 mm) were considered. Five different stack positions, measured from the hot ends of the stack to the pressure antinode in increments of 100 mm, were investigated. Measurement of temperature difference at steady state was used to determine the performance of a particular configuration. Guidance on the design of this sustainable solution for refrigeration and selection of the best geometrical configuration of ceramic substrates are provided. In addition, clarity on the relation between the geometrical configurations and the frequencies of the sound wave is highlighted

Experimental investigation of an adjustable thermoacoustically-driven thermoacoustic refrigerator

Abstract: An experimental investigation is conducted on a new adjustable thermoacoustically-driven thermoacoustic refrigerator (TADTAR). This refrigerator comprises of a thermoacoustic engine which drives a thermoacoustic refrigerator. This study aims to demonstrate the possibility to alter the TADTAR performance through the adjustment of specific design parameters. An adjustable resonator, which consisted of stacks, spacing couplings and shell-tube heat exchangers was designed and built. Six different honeycomb ceramic stacks were investigated. For each system, three different stack configuration were studied. Measurements of temperature difference across the refrigerator stack and sound pressure levels at steady states were used to determine the performance of the device. Through the adjustment of the length and the insertion of the heat exchanger, the performance of the device with a longer resonator was relatively higher. This study shows that an adjustable resonator successfully alters the frequency output of the thermoacoustic engine to match the frequency required by the thermoacoustic refrigerator and achieve resonance. In addition, this study demonstrates the possibility to change the geometrical configuration of the device and ultimately alter the performance of the TADTAR. Through the adjustment of the length of the resonator, this study shows that a single device could have different operating points. This creates new possibilities to introduce control system able to adjust the geometry of thermoacoustic system while in operation

Sustainable supplier selection in a paint manufacturing company using hybrid meta-heuristic algorithm

Abstract: Supplier selection in a manufacturing system is highly complex due to the stochastic nature and structure of organizations, thereby necessitating a paradigm shift from the rule of thumb and classical methods of supplier selection to a reliable technique, using the hybrid algorithm to provide higher accuracy in the selection process. Hence, this study proposes the use of hybrid computational intelligence technique, Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for effective prediction and sustainable selection of suppliers (SSS). This hybrid modelling configuration was applied in a paint manufacturing company to select the best possible supplier. Information obtained from the company within the period of investigation was fed into the model. The result obtained shows a faster and reliable prediction of the creative model. Professionals and business managers will benefit greatly from SSS in an in-bound and out-bound supply chain system