Optimal design of heat pipes for city gate station heaters by applying genetic and Bayesian optimization algorithms to an artificial neural network model

Abstract

This study contains a novel idea to improve the performance of city gate station heaters, using pulsating heat pipes with optimized structure. In this research, a hybrid method including Bayesian and genetic algorithms is implemented to optimize the architecture of an artificial neural network (ANN) model and find the optimal operating point for heat pipes. In the previous study, the authors have proposed a neural network-based model to predict the thermal performance of heat pipes, based on a wide range of their design parameters, including dimensions of heat pipe, number of turns, working fluid, inclination angle, filling ratio, and heat input. In the present study, the prediction model architecture is optimized using Bayesian optimization algorithm. The best performance is achieved when iterations of the employed Bayesian optimization is set to 300 iterations or samples, which 150 samples are produced to train the Bayesian model and other 150 iterations are utilized in order to find the optimal ANN structure and hyper-parameter tuning of the model. The optimal ANN model with structure of 9-97-21-68-100-1 has evaluation parameters of 0.980 and 0.014 for R2 and MSE of total dataset, respectively. The performance metrics indicate an improvement in accuracy of the ANN model with a 53.33% reduction in MSE value and a 3.15% increase in R2 score. Then, the genetic algorithm is applied to the optimal model to find the optimum operating parameters of the heat pipe. In this regard, the design parameters of the best heat pipe in order to use in the city gate station heaters, are obtained by setting the genetic algorithm population equal to 300. Finally, as a practical case study, a real heater with capacity of 10,000 SCMH which is located in Iran is selected. Considering constraints and limitations of this heater, the proposed model indicates that a vertical pulsating heat pipe with four turns which is filled 55% with water as the working fluid, has the optimal thermal resistance of 0.104 K/W. Utilizing the optimal heat pipe in the mentioned heater is a promising solution for efficiency improvement and fuel consumption and CO2 emission reduction, which decreases the operating costs of the heater as well.