A common problem in transient rotordynamic simulations is the numerical effort necessary for the computation of hydrodynamic bearing forces. Due to the nonlinear interaction between the rotordynamic and hydrodynamic systems, an adequate prediction of shaft oscillations requires a solution of the Reynolds equation at every time step. Since closed-form analytical solutions are only known for highly simplified models, numerical methods or look-up table techniques are usually employed. Numerical solutions provide excellent accuracy and allow a consideration of various physical influences that may affect the pressure generation in the bearing (e.g., cavitation or shaft tilting), but they are computationally expensive. Look-up tables are less universal because the interpolation effort and the database size increase significantly with every considered physical effect that introduces additional independent variables. In recent studies, the Reynolds equation was solved semianalytically by means of the scaled boundary finite element method (SBFEM). Compared to the finite element method (FEM), this solution is relatively fast if a small discretization error is desired or if the slenderness ratio of the bearing is large. The accuracy and efficiency of this approach, which have already been investigated for single calls of the Reynolds equation, are now examined in the context of rotordynamic simulations. For comparison of the simulation results and the computational effort, two numerical reference solutions based on the FEM and the finite volume method (FVM) are also analyzed.

The article presents a methodology for determining the value of the expansion coefficient of a reconsolidated caving zone in the context of forecasting the rise in underground mine water levels and consequent surface subsidence caused by the process of flooding the closed coal mines. The paper also provides a brief characterisation of analytical predictive models regarding surface subsidence during the process of flooding coal mines. In order to describe the vertical deformation of the reconsolidated porous rock mass in the caving zone, a linear-elastic medium of Biot was utilised. The conducted theoretical calculations demonstrate a high agreement with the results obtained through the identification of the expansion coefficient parameter based on the analysis of in-situ subsidence measurements in Dutch and German mining areas. The proposed methodology was applied to a real case study involving the forecasting of the impact of the flooding process on the underground workings of the German Ibbenbüren mine. The article constitutes a significant contribution to the field of forecasting the rise in underground mine water levels and surface subsidence during the process of flooding closed coal mines. The presented methodology and obtained results can be valuable for researchers, engineers, and decision-makers involved in the planning and management of mining areas.

The chemical composition of commercial thyme oils, freshly hydrodistilled EO (essetntial oil) from dried thyme herb and thymol, the main thyme oil constituent, were analyzed in the aspect of possible cytotoxic effect against MCF-7 breast cancer and normal L929 mouse fibroblast cell lines. Based on the GC-MS analysis, it was found that the commercial essential oils revealed similarities in their chemical composition. The content of main components such as thymol, linalool and α-pinene was almost equal. Interestingly, the EO obtained by hydrodistillation from Thymi herba showed considerable differences in the percentage content of some main constituents. The reason for the differences may be caused by the intraspecific chemical variability of T. vulgaris L. Four types of tested EOs can be classified as a ‘thymol’ chemotype, with thymol as the predominant compound. The thymol alone and the freshly hydrodistilled EO demonstrated the highest cytotoxic effect against used cell lines. The difference in IC50 values suggests more sensitive L929 cells are more sensitive in both the CCK-8 assay (except EOs Kawon) and the NRU assay.

Background: The aim of the study was to answer two questions: 1 – Can data processing algorithms ensure sufficient accuracy for estimating human body pose via wearable systems? 2 – How to process the IMU sensor data to obtain the most accurate information on the human body pose? To answer these questions, the authors evaluated proposed algorithms in terms of accuracy and reliability. Methodology: data acquisition was performed with tested IMU sensors system mounted onto a Biodex System device. Research included pendulum movement with seven angular velocities (10-120°/s) in five angular movement ranges (30-120°). Algorithms used data from accelerometers and gyroscopes and considered complementary and/or Kalman filters with adjusted parameters. Moreover, angular velocity registration quality was also taken into consideration. Results: differences between means for angular velocity were 0.55÷1.05°/s and 1.76÷3.11%. In the case of angular position relative error of means was 4.77÷10.84%, relative error of extreme values was 2.15÷4.81% and Spearman’s correlation coefficient was 0.74÷0.89. Conclusions: Algorithm calculating angles based on acceleration-derived quaternions and with implementation of Kalman filter was the most accurate for data processing and can be adapted for future work with IMU sensors systems, especially in wearable devices that are designated to support human in daily activity.

Additive manufacturing (AM) technologies have been gaining popularity in recent years due to patent releases – and in effect – better accessibility of the technology. One of the most popular AM technologies is fused deposition modeling (FDM), which is used to manufacture products out of thermoplastic polymers in a layer-by-layer manner. Due to the specificity of the method, parts manufactured in this manner tend to have non-isotropic properties. One of the factors influencing the part’s mechanical behavior and quality is the thermoplastic material’s bonding mechanism correlated with the processing temperature, as well as thermal shrinkage during processing. In this research, the authors verified the suitability of finite element method (FEM) analysis for determining PET-G thermal evolution during the process, by creating a layer transient heat transfer model, and comparing the obtained modelling results with ones registered during a real-time process recorded with a FLIR T1020 thermal imaging camera. Our model is a valuable resource for providing thermal conditions in existing numerical models that connect heat transfer, mesostructure and AM product strength, especially when experimental data is lacking. The FE model presented reached a maximum sample-specific error of 11.3%, while the arithmetic mean percentage error for all samples and layer heights is equal to 4.3%, which the authors consider satisfactory. Model-to-experiment error is partially caused by glass transition of the material, which can be observed on the experimental cooling rate curve after processing the temperature signal.