Experimental investigation of cutting forces in high-feed milling of titanium alloy

Titanium super alloys are often used in the chemical and aerospace industries, especially because of financial savings. resulting primarily from cheaper operation of equipment. Machinability of titanium alloys is more difficult than that of other metals. In addition, the low thermal conductivity causes the alloy to stick to the cuffing edge of the cutting tool, thereby causing it to become dull faster. The article deals with the experimental evaluation of cutting forces and the design of suitable cutting parameters for the machining of the UNS R56260 titanium alloy with high-feed milling technology. Testing was carried out in climb and conventional milling under different cutting conditions. The cutting components of forces Fx, Fy, Fz were measured and evaluated. The results of the measurements were processed into a graphical form and suitable cutting conditions were designed in terms of the acting cutting forces.Web of Science141958

Hierarchical real-time optimal planning of collision-free trajectories of collaborative robots

In collaborative robotics the manipulator trajectory has to be planned to avoid collisions, yet in real-time. In this paper we pose the problem as minimization of a quadratic functional among piecewise linear trajectories in the angular (joint) space. The minimization is subjected to novel nonlinear inequality constraints that simplify the original non-penetration constraints to become cheap to evaluate in real time while still preserving collision-avoidance. The very first and most critical step of the computation is to find an initial trajectory that is free of collisions. To that goal we minimize a weighted sum of the violated constraints until they become feasible or a maximal number of steps is reached. Sometimes an incremental growing of the obstacle helps. By incremental growing we mean that we sequentially solve auxiliary subproblems with obstacles growing from ground or falling from top and use as the initial trajectory the one optimized in the previous step. The initial trajectory is then optimized while preserving feasibility at each step. We solve a sequence of simple-bound constrained quadratic programming problems formulated in the dual space of Lagrange multipliers, which are related to the original linearized inequality constraints that are active or close-to-active. Finally, we refine the trajectory parameterization and repeat the optimization, which we refer to as an hierarchical approach, until an overall prescribed time limit, being well below a second, is reached.Web of Science1074art. no. 5

SPECTRAL ANALYSIS OF ATRIAL COMPONENTS OF ABLATION CATHETER SIGNALS DURING SLOW PATHWAY ABLATION FOR TYPICAL ATRIOVENTRICULAR NODAL REENTRANT TACHYCARDIA

Ablation of the slow pathway is the treatment standard for typical atrioventricular nodal reentrant tachycardia (AVNRT). However, the risk of complete heart block due to ablation of the fast pathway remains approximately 1%. Spectral analysis of the atrial components of ablation catheter signals during slow pathway ablation can provide additional information for precisely defining ablation sites. A retrospective study of the atrial components of 70 ablation catheter signals obtained from 20 patients was performed. Signals immediately prior to ablations wereanalyzed. The signals were divided into two groups: “good” (desired ablation answer) and “bad.” MATLAB software was used to analyze the signals. The amplitude spectrum received most attention. Afterwards, we compared similarities between “good” and “bad” signals from one patient using cross-correlation. The study population consisted of 20 patients. Each patient had one “good” signal and two or more “bad” signals. The mean frequency of the “good” signals was 13.37 ± 6.78 Hz and of the “bad” signals was 15.79 ± 6.82 Hz (p = n.s.). The relationship between “good” and “bad” signals was 0.73 ± 0.19. The amplitude spectrum of the atrial components of ablation catheter signals did not provide any useful differentiation for improving ablation accuracy

Vysokoteplotní fázové transformace kaolinitu v závislosti na krystalinitě

Although kaolinite is one the most important industrial minerals, the processes of its transformation to mullite have not been completely explained so far. The study is focused on kaolinite crystallinity calculation and its effect on high-temperature phases transitions in the series kaolinite-mullite. Samples of purified natural kaolins from several sites were analysed using X-ray diffraction (XRD). Besides the determination of the complex mineral composition, kaolinite crystallite size was calculated from XRD data by the Rietveld method, Scherrer equation and using the Hinckley crystallinity index. Thermal analysis (DSC/TG) was used as the principal approach to examine endothermic and exothermic effects of kaolinite transformations. The course and maximum temperatures of the observed effects were correlated with the original crystallite size of kaolinite. Two samples with different kaolinite crystallinity were also analysed by high-temperature X-ray diffraction (ht-XRD) to study the formation of mullite. Scanning electron microscope (SEM) was used to visualize morphology of kaolinite.It was found out that the original crystallinity of kaolinite affects all three examined processes-kaolinite dehydroxylation, formation of crystalline phases from metakaolinite and development of mullite crystal structure. Dehydroxylation of samples with higher kaolinite crystallinity takes place at higher temperatures. Similar effect applies for the reaction(-s) at the temperature about 980 °C observed at heat flow curve where crystallization of spinel type phase and mullite with very low crystallinity occurs. Broadening of FWHM of the exothermic effect points to decreasing kaolinite crystallinity. Crystallization of mullite exhibits different dependence on kaolinite crystallinity than the previous processes. The results show that mullite with larger crystallite size develops faster from kaolinite of low crystallinity and vice versa

Combined fit to the spectrum and composition data measured by the Pierre Auger Observatory including magnetic horizon effects

The measurements by the Pierre Auger Observatory of the energy spectrum and mass composition of cosmic rays can be interpreted assuming the presence of two extragalactic source populations, one dominating the flux at energies above a few EeV and the other below. To fit the data ignoring magnetic field effects, the high-energy population needs to accelerate a mixture of nuclei with very hard spectra, at odds with the approximate E$^{-2}$ shape expected from diffusive shock acceleration. The presence of turbulent extragalactic magnetic fields in the region between the closest sources and the Earth can significantly modify the observed CR spectrum with respect to that emitted by the sources, reducing the flux of low-rigidity particles that reach the Earth. We here take into account this magnetic horizon effect in the combined fit of the spectrum and shower depth distributions, exploring the possibility that a spectrum for the high-energy population sources with a shape closer to E$^{-2}$ be able to explain the observations

Extraction of the Muon Signals Recorded with the Surface Detector of the Pierre Auger Observatory Using Recurrent Neural Networks

We present a method based on the use of Recurrent Neural Networks to extract the muon component from the time traces registered with water-Cherenkov detector (WCD) stations of the Surface Detector of the Pierre Auger Observatory. The design of the WCDs does not allow to separate the contribution of muons to the time traces obtained from the WCDs from those of photons, electrons and positrons for all events. Separating the muon and electromagnetic components is crucial for the determination of the nature of the primary cosmic rays and properties of the hadronic interactions at ultra-high energies. We trained a neural network to extract the muon and the electromagnetic components from the WCD traces using a large set of simulated air showers, with around 450 000 simulated events. For training and evaluating the performance of the neural network, simulated events with energies between 1018.5, eV and 1020 eV and zenith angles below 60 degrees were used. We also study the performance of this method on experimental data of the Pierre Auger Observatory and show that our predicted muon lateral distributions agree with the parameterizations obtained by the AGASA collaboration