# A Practical Approach to Modeling and Performance Analysis of a Turboshaft Engine Using Matlab
## 1 Introduction  
Turboshaft engines, also known as gas turbines, have a wide range of applications in engineering, from aviation--where they are used to power turboprop airplanes and helicopters--to powering heavy vehicles, locomotives, tanks, and ships, as well as in the energy sector for electricity generation [1]. Their wide application drives broad research efforts in this field, encompassing both practical experimentation [2, 3, 4, 5] and numerical studies [6, 7, 8]. However, numerical studies are typically supported by experimental research, as is the case in the study by [9]. Aircraft engine modeling involves adopting an appropriate, simplified representation that best reflects the features intended for numerical testing. It is a balancing act between model accuracy and complexity, preparation time, computational cost, accepted calculation error, and other important factors [10]. Classical models for design-point calculations of a turboshaft engine can be found in several studies [6, 7, 11]. These models are used toassess improvements in engine performance through modifications of cycle operating parameters [11; 12] or enhancements in its component's efficiency [6; 7]. A similar approach, but with consideration of changes in the gas flow parameters within the engine, is presented in [8] for modeling engine performance with various fuels, including hydrogen. More complex models for off-design performance calculations use correlations based on the interactions between engine components and parameters adjusted to reference conditions or the design point. This approach is presented in studies by [7; 9], where, based on design-point data, engine performance under different operating conditions can be recalculated relatively quickly. Advanced models for performance determination additionally incorporate the characteristics of engine components, most often limiting themselves to the compressor performance map only [11; 13] or to both the compressor and turbine maps [14; 15]. Highly advanced numerical models of aircraft engines use fully 3D models in their calculations. The study by [16] includes a report on recent research conducted with 3D models. The scientists of Numeca conducted steady-state and unsteady-state three-dimensional numerical simulations of the micro turbojet engine KJ66 [17; 18]. The model was more complex and needed time for preparation and calculation. The total number of grids was approximately 19.2 million, of which the computational domain includes one blade passage for every turbomachinery blade row, a 60\({}^{\circ}\) sector for the combustion chamber, and a half exhaust hood. The steady calculation of the whole engine used 288 cores and took about 52 h to reach the convergence state. To reduce costs and time consumption, simplified models are often employed, taking into account 2D flow [19; 20], or models where some components are modeled with greater precision using CFD while others are simplified, like in the multi-fidelity approach presented in [21; 22]. The implementation of these methods provides a more accurate and comprehensive analysis method for whole-engine simulation and is expected to have a positive impact on aero-engine design and performance evaluation with lower calculation costs than in a fully 3D approach, but it still needs a lot of effort and time to model preparation and to run it. The analysis of engine models for performance applications [11; 12; 14; 15] shows that 1D models incorporating the characteristics of engine components--primarily compressors and turbines--continue to dominate. This is because they are the simplest to prepare and execute, while the accuracy of the obtained calculations remains at an acceptable level. A typical approach to model preparation involves creating it in the form of blocks that reflect the functional components of the engine, as seen in the GSP11 program applied in the studies by [23; 24] or in the approach presented in [25].