Vibration in rotating machinery leads to a series of undesired effects, e.g. noise, reduced service life or even machine failure. Even though there are many sources of vibrations in a rotating machine, the most common one is mass unbalance. Therefore, a detailed knowledge of the system behavior due to mass unbalance is crucial in the design phase of a rotor-bearing system. The modelling of the rotor and mass unbalance as a lumped system is a widely used approach to calculate the whirling motion of a rotor-bearing system. A more accurate representation of the real system can be found by a continuous model, especially if the mass unbalance is not constant and arbitrarily oriented in space. Therefore, a quasi-analytical method called Numerical Assembly Technique is extended in this paper, which allows for an efficient and accurate simulation of the unbalance response of a rotor-bearing system. The rotor shaft is modelled by the Rayleigh beam theory including rotatory inertia and gyroscopic effects. Rigid discs can be mounted onto the rotor and the bearings are modeled by linear translational/rotational springs/dampers, including cross-coupling effects. The effect of a constant axial force or torque on the system response is also examined in the simulation.

The paper presents an analysis of the influence of the shape of the rigid body pressed into the micro-periodic composite half-space on the examples of two punch shapes – parabolic and rectangular. The presented material is a layered body that consists of infinitely many thin alternately arranged homogenous layers. Layers of the presented composite are oblique to the boundary surface. Two cases of punch tip shape are examined – parabolic and rectangular. The presented problem has been formulated within the framework of a homogenized model with microlocal parameters and solved using the elastic potentials method and averaged boundary condition. Fourier integral transform method has been used to obtain the solution and the inverse integrals have been calculated numerically. Solutions in terms of contact pressure and maximum pressure characteristics were shown in the form of graphs.

This paper presents the design of a versatile mechanism that can enable new directions in amphibious, all-terrain locomotion. The simple, passive, flapped-paddle can be integrated with several structures that are well-suited for locomotion in terrestrial applications. The flapped-paddle overcomes a serious limitation of the conventional flipper where the net lateral forces generated during oscillatory motion in aquatic environments averages out to zero. The flapped-paddle and its mounting, collectively, rests in natural positions in the aquatic environment so as to maximize hydrodynamic force utilization and consequently the propulsive efficiency. The simplicity of the design enabled us to develop a simulation model that concurs well with experimental results. The results reported in the paper are based on integrating the flapped-paddle with the curved leg of the RHex hexapod robot.

The analysis of subsonic stall flutter in turbomachinery blade cascade is carried out using a medium-fidelity reduced-order aeroelastic numerical model. The model is a type of field mesh-free approach and based on a hybrid boundary element method. The medium-fidelity flow solver is developed on the principle of viscous-inviscid two-way weak-coupling approach. The hybrid flow solver is employed to model separated flow and stall flutter in the 3D blade cascade at subsonic speed. The aerodynamic damping coefficient w.r.t. inter blade phase angle in traveling-wave mode is estimated along with other parameters. The same stability parameter is used to analyze the cascade flutter resistance regime. The estimated results are validated against experimental measurements as well as Navier-Stokes based high fidelity CFD model. The simulated results show good agreement with experimental data. Furthermore, the hybrid flow solver has managed to bring down the computational cost significantly as compared to mesh-based CFD models. Therefore, all the prime objectives of the research have been successfully achieved.

The rod specimens were produced from Pr9Fe50 + xCo13Zr1Nb4B23 – x (x = 0, 5, 8) alloys using the suction-casting technique. Subsequent devitrification annealing of those samples resulted in the change of their phase structure and magnetic properties. For annealed specimens of all investigated compositions, the Rietveld analyses of X-ray diffractions have shown the presence of three crystalline phases: the hard magnetic Pr2Fe11.2Co2.8B, soft magnetic α-Fe, and paramagnetic Pr1 + xFe4B4, which have precipitated within the amorphous matrix. This technique allowed us to determine the weight fractions of constituent phases. Furthermore, the microstructural changes with the alloy composition were observed. Magnetic measurements of annealed rods allowed us to calculate the switching field distributions (SFD) and δM plots in order to determine the strength and character of magnetic interactions between grains of constituent phases.

Computer aided detection systems are used for the provision of second opinion during lung cancer diagnosis. For early-stage detection and treatment false positive reduction stage also plays a vital role. The main motive of this research is to propose a method for lung cancer segmentation. In recent years, lung cancer detection and segmentation of tumors is considered one of the most important steps in the surgical planning and medication preparations. It is very difficult for the researchers to detect the tumor area from the CT (computed tomography) images. The proposed system segments lungs and classify the images into normal and abnormal and consists of two phases, The first phase will be made up of various stages like pre-processing, feature extraction, feature selection, classification and finally, segmentation of the tumor. Input CT image is sent through the pre-processing phase where noise removal will be taken care of and then texture features are extracted from the pre-processed image, and in the next stage features will be selected by making use of crow search optimization algorithm, later artificial neural network is used for the classification of the normal lung images from abnormal images. Finally, abnormal images will be processed through the fuzzy K-means algorithm for segmenting the tumors separately. In the second phase, SVM classifier is used for the reduction of false positives. The proposed system delivers accuracy of 96%, 100% specificity and sensitivity of 99% and it reduces false positives. Experimental results shows that the system outperforms many other systems in the literature in terms of sensitivity, specificity, and accuracy. There is a great tradeoff between effectiveness and efficiency and the proposed system also saves computation time. The work shows that the proposed system which is formed by the integration of fuzzy K-means clustering and deep learning technique is simple yet powerful and was effective in reducing false positives and segments tumors and perform classification and delivers better performance when compared to other strategies in the literature, and this system is giving accurate decision when compared to human doctor’s decision.

Full-floating ring bearings are state of the art at high speed turbomachinery shafts like in turbochargers. Their main feature is an additional ring between shaft and housing leading to two fluid films in serial arrangement. Analogously, a thrust bearing with an additional separating disk between journal collar and housing can be designed. The disk is allowed to rotate freely only driven by drag torques, while it is radially supported by a short bearing against the journal. This paper addresses this kind of thrust bearing and its implementation into a transient rotor dynamic simulation by solving the Reynolds PDE online during time integration. Special attention is given to the coupling between the different fluid films of this bearing type. Finally, the differences between a coupled and an uncoupled solution are discussed.

Accurate determination of material parameters, such as carrier lifetimes and defect activation energy, is a significant problem in the technology of infrared detectors. Among many different techniques, using the time resolved photoluminescence spectroscopy allows to determine the narrow energy gap materials, as well as their time dynamics. In this technique, it is possible to observe time dynamics of all processes in the measured sample as in a streak camera. In this article, the signal processing for the above technique for Hg(1-x)CdxTe with a composition x of about 0.3 which plays an extremely important role in the mid-infrared is presented. Machine learning algorithms based on the independent components analysis were used to determine components of the analyzed data series. Two different filtering techniques were investigated. In the article, it is shown how to reduce noise using the independent components analysis and what are the advantages, as well as disadvantages, of selected methods of the independent components analysis filtering. The proposed method might allow to distinguish, based on the analysis of photoluminescence spectra, the location of typical defect levels in HgCdTe described in the literature.