Modeling of environmental effect factor and exergetic sustainability index with cuckoo search algorithm for a business jet

Abstract

Purpose: The purpose of this paper is to create models that predict exergetic sustainability index (ESI) and environmental effect factor (EEF) values with high accuracy according to various engine parameters. Design/methodology/approach: In this study, models were created to estimate ESI and EEF sustainability parameters in various flight phases for a business jet with a turboprop engine using the cuckoo search algorithm (CSA) method. The database used for modeling includes the various engine parameters (torque, engine airflow, gas generator speed, fuel mass flow, power and air-fuel ratio) obtained by running a business aircraft engine more than once at different settings and the actual ESI and EEF values obtained depending on these parameters. In addition, sensitivity analysis was performed to measure the effect of engine parameters on the models. Finally, the effect of the CSA number of nest (n) parameter on the model accuracy was investigated. Findings: It has been observed that the models predict ESI and EEF values with high accuracy. As a result of the sensitivity analysis, it was seen that the air-fuel ratio had a greater effect on the output parameters. Practical implications: These models are thought to assist in the exergetic environment analysis used to find the greatest losses for turboprop business jets and identify their causes and further improve system performance. Thus, they will be a useful tool to minimize the negative impact of business jet on environmental sustainability. Originality/value: To the best of the authors’ knowledge, this study stands out in the literature because it is the first exergo-metaheuristic approach developed with CSA for business aircraft engine; moreover, the data set used consists of real values.