Exergo-sustainability indicators of a target drone engine at dynamic loads

Abstract

Energy security and low environmental impact issues become hot topics due to usage of small-sized turbojet engines in many areas. In this study, thermodynamic analysis of target drone turbojet engine (TRS18) was experimentally carried out for different non-linear loads. The main goal is to reveal effects of power settings on exergetic performance of TRS18 and its components by using energy, exergy and exergo-sustainability metrics regarding the TRS18 for each load. For this aim, several input parameters related to TRS18 were measured while some of them were calculated by reverse engineering. Based on these data, energetic and exergetic computations for three components and whole engine were performed with respect to ten RPM values. According to component-based exergy results, exergy destruction of components increase due to rising RPM value. Namely, for the combustor, exergy destruction ranges from 214.46 kW to 722.54 kW whereas it changes between 12.36 kW and 98.57 kW at turbine. As for compressor, it is observed between 4.19 kW and 37.23 kW. However, increasing of RPM value affects favourably exergy efficiency of components. Namely, exergy efficiency of the combustor changes between 41.8% and 63.4% whereas that of the turbine increases from 91.9% to 96.1%. For compressor, it is observed between 83.6% and 89% through rising power settings. With respect to exergetic findings of the whole TRS18 engine, exergy efficiency of TRS18 increases 5.8%–18.07% whereas exergetic sustainability index of the engine is calculated from 0.061 to 0.22 through rising RPM values. However, exergy destruction factor of TRS18 decreases from 67.9% to 49.6% while environmental effect factor regarding the engine diminishes from 16.23 to 4.53. For thermal systems which be exposed different loads, this study could establish relationship between engine efficiency and operation load. Moreover, it could be inferred that examining sustainability aspects of TRS18 under different loads helps finding optimum operating ranges in terms of fuel consumption and environmental impact.