In the present article, we introduced a new model of the equations of general ized thermoelasticity for unbounded orthotropic body containing a cylindrical cavity. We applied this model in the context of generalized thermoelasticity with phase-lags under the effect of rotation. In this case, the thermal conductivity of the material is considered to be variable. In addition, the cylinder surface is traction free and subjected to a uniform unit step temperature. Using the Laplace transform technique, the distributions of the temperature, displacement, radial stress and hoop stress are determined. A detailed analysis of the effects of rotation, phase-lags and the variability thermal conductivity parameters on the studied fields is discussed. Numerical results for the studied fields are illustrated graphically in the presence and absence of rotation.

The paper includes experimental research using the Split Hopkinson Pressure Bar to determine dynamic compression curves and strength dynamic parameters to depend on the strain rate and moisture for silty sand soil samples. Those experiments are oedometric type based in a rigid confining cylinder. Samples of silty sand with fine a fraction content were taken for the study. To ensure sufficiently uniaxial strain of the tested material, the soil samples were placed in properly prepared casings made of duralumin for the needs of the tests. Thanks to the use of measuring strain gauges on the initiating and transmitting bars, as well as the casing, the nature of the loading pulse was obtained, which was then subjected to the process of filtration and data processing to obtain the nature of the incident, reflected and transmitted wave. During the above dynamic experiments with the representative of silty sand soils, it was observed that its dynamic compaction at a high strain rate is different than in the case of the Proctor test. This is due to higher compaction energy, which additionally changes the grain size by destroying the grains in the structure. The paper presents the results of particle size distribution analysis for two different types of soil samples - this type of analysis is unique. Hence experiments should be further continued for such soils with different granulations and various moisture using, for example, Hopkinson measuring bar technique to confirm for other silty sand soils that are often subgrade of various engineering objects.

This study addresses the issue of diagnosing faults in electric vehicle motors and presents a method utilizing Improved Wavelet Packet Decomposition (IWPD) combined with particle swarm optimization (PSO). Initially, the analysis focuses on common demagnetization faults, inter turn short circuit faults, and eccentricity faults of permanent magnet synchronous motors. The proposed approach involves the application of IWPD for extracting signal feature vectors, incorporating the energy spectrum scale, and extracting the feature vectors of the signal using the energy spectrum scale. Subsequently, a binary particle swarm optimization algorithm is employed to formulate strategies for updating particle velocity and position. Further optimization of the binary particle swarm algorithm using chaos theory and the simulated annealing algorithm results in the development of a motor fault diagnosis model based on the enhanced particle swarm optimization algorithm. The results demonstrate that the chaotic simulated annealing algorithm achieves the highest accuracy and recall rates, at 0.96 and 0.92, respectively. The model exhibits the highest fault accuracy rates on both the test and training sets, exceeding 98.2%, with a minimal loss function of 0.0035. Following extraction of fault signal feature vectors, the optimal fitness reaches 97.4%. In summary, the model constructed in this study demonstrates effective application in detecting faults in electric vehicle motors, holding significant implications for the advancement of the electric vehicle industry.