Michal Šofer

The paper presents the process of optimizing the duty cycle of a rotary crane. The minimization of the carried load’s trajectory was chosen as the objective function. The research was conducted using the genetic algorithm and the particle swarm algorithm. The influence of particular algorithm parameters on the obtained optimal solution was characterized. For the obtained best case, the inverse kinematics problem was solved, allowing us to determine the control functions of individual crane members. The presented redundant system was solved with the use of an algorithm for temporarily limiting the movement of specific kinematic pairs. On the basis of the obtained results, it was determined which of the algorithms used is more favorable, taking into account the crane’s operational safety and lifting capacity.

Scaled rolling contact fatigue tests, used to practically simulate the wear of the wheel and rail material under laboratory conditions, are typically classified into two categories. Tests in the first category use twin-disc stands, while the second group of test rigs use two discs of different diameters considering the rail disc as the larger one. The latter setup is closer to the real situation, but problems can occur with high contact pressures and tractions. The focus of this paper is on two main contributions. Firstly, a case study based on finite element analysis is presented, allowing the optimization of the specimen geometry for high contact pressures. Accumulated plastic deformation caused by cycling is responsible for abrupt lateral deformation, which requires the use of an appropriate cyclic plasticity model in the finite element analysis. In the second part of the study, two laser profilers are used to measure the dimensions of the specimen in real time during the rolling contact fatigue test. The proposed technique allows the changes in the specimen dimensions to be characterized during the test itself, and therefore does not require the test to be interrupted. By using real-time values of the specimen’s dimensional contours, it is possible to calculate an instantaneous value of the slip ratio or the contact path width.

In the present study, the evolution of different failure mechanisms in carbon fiber reinforced polymer composites is being investigated using acoustic emission technique, unsupervised clustering technique and improved b-value analysis. The experimental part involved the realization of tensile tests of different materials, namely samples with [0/90]2S uniaxial layer configuration and [0/90]2S twill fabric samples. Both types of tests were monitored using one wideband acoustic emission sensor, while the tensile tests of twill fabric samples were additionally supplemented with resonant acoustic emission sensor to perform a comparative analysis between datasets from resonant/wideband acoustic emission sensor. The comparative study itself was preceded by the failure mechanisms characterization process, which has been performed on the tensile test dataset of [0/90]2S layer configuration with the contribution of clustering technique. The subsequent analysis of the twill fabric resonant/wideband acoustic emission sensor datasets included the improved b-value technique, which relates the magnitude of fracture with the slope of the amplitude distribution. The presented results, especially in terms of the improved b-value technique applied to individual clusters, show enhanced ability to assess in more detail the actual structural integrity depending on the applied load.

The study analyzed the influence of materials and different types of damping on the dynamic stability of the Bernoulli-Euler beam. Using the mode summation method and applying an orthogonal condition of eigenfunctions and describing the analyzed system with the Mathieu equation, the problem of dynamic stability was solved. By examining the influence of internal and external damping and damping in the beam supports, their influence on the regions of stability and instability of the solution to the Mathieu equation was determined.

The characterisation of failure mechanisms in carbon fibre-reinforced polymer (CFRP) materials using the acoustic emission (AE) technique has been the topic of a number of publications. However, it is often challenging to obtain comprehensive and reliable information about individual failure mechanisms. This situation was the impetus for elaborating a comprehensive overview that covers all failure mechanisms within the framework of CFRP materials. Thus, we performed tensile and compact tension tests on specimens with various stacking sequences to induce specific failure modes and mechanisms. The AE activity was monitored using two different wideband AE sensors and further analysed using a hybrid AE hit detection process. The datasets received from both sensors were separately subjected to clustering analysis using the spectral clustering technique, which incorporated an unsupervised k-means clustering algorithm. The failure mechanism analysis also included a proposed filtering process based on the power distribution across the considered frequency range, with which it was possible to distinguish between the fibre pull-out and fibre breakage mechanisms. This functionality was particularly useful in cases where it was evident that the above-mentioned damage mechanisms exhibited very similar parametric characteristics. The results of the clustering analysis were compared to those of the scanning electron microscopy analysis, which confirmed the conclusions of the AE data analysis.

Although the study of oscillatory motion has a long history, going back four centuries, it is still an active subject of scientificr esearch. In this review paper prospective research directions in the field of mechanical vibrations were pointed out. Four groups of important issues in which advanced research is conducted were discussed. The first are energy harvester devices, thanks to which we can obtain or save significant amounts of energy, and thus reduce the amount of greenhouse gases. The next discussed issue helps in the design of structures using vibrations and describes the algorithms that allow to identify and search for optimal parameters for the devices being developed. The next section describes vibration in multi-body systems and modal analysis, which are key to understanding the phenomena in vibrating machines. The last part describes the properties of granulated materials from which modern, intelligent vacuum-packed particles are made. They are used, for example, as intelligent vibration damping devices.

The article presents the process of identifying discrete-continuous models with the use of heuristic algorithms. A stepped cantilever beam was used as an example of a discrete-continuous model. The theoretical model was developed based on the formalism of Lagrange multipliers and the Timoshenko theory. Based on experimental research, the theoretical model was validated and the optimization problem was formulated. Optimizations were made for two algorithms: genetic (GA) and particle swarm (PSO). The minimization of the relative error of the obtained experimental and numerical results was used as the objective function. The performed process of identifying the theoretical model can be used to determine the eigenfrequencies of models without the need to conduct experimental tests. The presented methodology regarding the parameter identification of the beams with the variable cross-sectional area (according t