Betül Ayhan‐Sarac, Bekir Karlık, Tülin Bali and Teoman Ayhan
The purpose of this paper is to study experimentally enhancement of heat transfer in a tube with axial swirling‐flow promoters. The geometric features of flow geometry to improve…
Abstract
Purpose
The purpose of this paper is to study experimentally enhancement of heat transfer in a tube with axial swirling‐flow promoters. The geometric features of flow geometry to improve heat transfer can be selected in order to yield the maximum opposite reduction in heat exchange flow irreversibility by using exergy‐destruction method. The paper seeks to illustrate the use of neural network approach to analyze heat transfer enhancement data for further study in the scope of the experimental program.
Design/methodology/approach
For this purpose, 402 experimental measurements are collected. About 225 of those are used as training data for neural networks, the rest is used for testing. Then, these testing results of artificial neural network (ANN) and experimental data are compared. A formula for presenting exergy loses in a tubular heat exchanger is derived first and then the thermodynamic optimum instead of economic optimum is found by minimizing the exergy losses in the system.
Findings
Results from all configurations studied show that the heat transfer rate of the heated increases when the swirling‐flow promoter is inserted. From the heat transfer improvement number defined, it is observed that about 100 percent increase in heat transfer rate and five times increase in the pressure drop can be achieved under the condition of constant flow for the single promoter which has three blades, its blade angle is 30° and its location is in the middle of the tube length.
Research limitations/implications
The back‐propagation (BP) algorithm was selected as the neural network algorithm, which uses the generalized delta learning rule. The training time of BP algorithm is considerably long. However, the testing of our neural network is real‐time.
Practical implications
The experimental setup is established to collect the experimental data. It consists of an entrance region, test region (heat exchanger and steam generator), and, flow measurement and control. Also, a software program of neural networks trained BP is written by using Pascal high‐level languages.
Originality/value
An alternative and new approach is proposed in the paper to find optimum flow geometry for a pipe flow with an axial swirling‐flow promoter inserts. It is too difficult to predict the response of a complex physical system that cannot be easily modeled mathematically. The result thus obtained compare well with experimental results, but the computational effort of the ANN and time required in the analysis is much faster as compared. These results show that the ANN can be used efficiently for prediction.
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Ranendra Sinha and Subrahmanyam Annamdevula
This study aims to intend to contribute to the literature by testing the effect of scepticism on green consumer behaviour through environmental concern, knowledge, value and…
Abstract
Purpose
This study aims to intend to contribute to the literature by testing the effect of scepticism on green consumer behaviour through environmental concern, knowledge, value and willingness to pay more in the Indian context. Thus, the comprehensive model with new directions of antecedents of green consumer purchase behaviour and direct and indirect effects was examined using structural equation modelling.
Design/methodology/approach
The study adopted the hypo-deductive research design to test the proposed structural model. Cross-sectional data were collected through a predesigned questionnaire from the households living in Visakhapatnam city using a purposive sampling method. The proposed theoretical model was tested using structural equation modelling.
Findings
The results support five antecedents’ direct and indirect effects on green purchase behavioural intentions and actual buying behaviour, except for the indirect effect of green scepticism on green purchase behaviour (GPB). Similarly, scepticism is responsible for significant variation in GPB.
Practical implications
The present study’s findings imply the role of scepticism on GPB, and the policies of adopting green products need to be addressed. Green buying is an obscure task; however, it can be evident by adding eco-friendly aspects and persuading consumers of a win-win situation for themselves, the environment and the company.
Originality/value
This study adds to the field of knowledge by exploring and testing the factors affecting GPB, which was not emphasized earlier in the Indian context and second, by developing a theoretical consensus on testing the antecedents of GPB. The results strengthen the argument that scepticism is an antecedent that drives GPB.