# Mechanical Stress Prediction of an Aircraft Torque Tube Based on the Neural Network Application
## 1 Introduction
The aeronautical problem of turbine-blade temperature-field prediction is described in [14], in which the authors describe research that uses the FEM method and an ANN to predict the temperature fields on the turbine blade of a jet engine. The mechanical stress of a TC21 titanium alloy is presented [15], where mechanical stresses from the experimental analysis and the predicted stresses were compared by an ANN. In that article, the ANN proved to be a highly accurate model for mechanical stress prediction. Other studies of the prediction of mechanical and material properties using ANNs have been conducted [16; 17; 18], as have studies on the mechanical stresses of various mechanical parts [19; 20]. Finally, there are also studies showing that ANNs are highly accurate and useful tools for fatigue-life prediction [21; 22]. Additionally ANNs are useful tools during the design process; for example, in [23], the ANN structure was used for the optimization in a Pareto approach for stress prediction in the disk-drum structure of an axial compressor. The authors of the article reported a reduction in the time taken to perform the numerical calculation due to the application of the ANN. Furthermore, mechanical stress was calculated in [24; 25], where the calculations were performed using FEM, and in [26], a the low and high cycle fatigue of a turbine blade were estimated using FEM. However, compared to our method, that is, the application of an ANN for stress prediction, the FEM is time-consuming. Other articles focus on stress prediction using FEM [27], and [28] describes a thermal analysis and creep-lifetime prediction based on the effectiveness of a thermal barrier coating on a gas-turbine-combustor liner using coupled CFD and FEM simulation. In such complex studies, the solution times can be significant. In [29], the authors describe the stress and deformation of a rocket gas-turbine disc using FEM, in which multiple regimes are taken into consideration. Therefore, there are many studies on stress prediction using FEM. However, the FEM solution time for complex assemblies can take several minutes or hours, whereas elapsed time recorded in this article for several operational conditions is 0.03 s. During the operation of parts (in this case, an aircraft torque tube--ATT), the method can predict stress in real time according to the operating conditions and monitor the condition of the ATT. The elapsed time for the finite element analysis (FEA) solution is several minutes, so it is not possible to predict the stress of an ATT during an aircraft's landing or takeoff using this approach. Another advantage of our methodology is its application to various components beyond those used in the aviation industry. As previously described, finite element analysis is currently a common tool for the prediction of stress, deformation, etc. [30]. There are also analytical approaches to stress estimation that are too complicated for complex problems [31]. Experimental stress prediction is another form of stress estimation, but is not applicable to operating conditions in rea -time; it is more often used during experimental laboratory tests [32]. In terms of time consumption, these experiments resemble the FEM. Strain-gauge-stress measurement is a typical experimental method for estimating stress, but due to its nature, it is mainly used in the development of mechanical parts [33; 34]. In addition to numerical methods, there are also experimental methods for stress, deformation, and fatigue-life estimation [35]. A common method for modal-stress parameters is experimental modal analysis. Modal analysis is frequently used to estimate natural frequencies in jet engines, as in [36], where a jet-engine rotor was investigated. These examples also combine numerical and experimental approaches [37; 38]. One of the many ways of evaluating mechanical stress is the use of photoelasticity [39]. This method is also used for the experimental estimation of mechanical stress.