Application of parametric standardization in the calculation of rows of hydraulic cylinder diameters

Currently, the ordering of standardization objects and their properties, optimization of the parameters of standardization objects, normalization of requirements for objects are the most important areas of standardization as a science. In this regard, the issues of choosing parametric series are very relevant. In order to increase the level of interchangeability and reduce the range of products and standard sizes of blanks, overall cutting tools, tooling, productivity, speed, speed, power, etc., used in a particular industry, as well as to create conditions for effective specialization and cooperation of plants, reduce the cost of products, the principle of preference is used in the unification and development of standards. There are two methods for choosing parametric series: the method of technical justification and the method of economic justification. The technical method is easier to use and is used to expand the technologies of unification of standard sizes of parts of homogeneous products. This method was used to calculate a number of diameters of hydraulic cylinders of broaching machines of the same series based on the mathematical dependence between the force developed on the hydraulic cylinder rod, which is formed by the initial parametric series laid down by the designers. As a result of technical optimization of the choice of the parametric series, a number of diameters of hydraulic cylinders R20/2(45-224) mm was installed, fully corresponding to the main functional parameter - a number of forces on the rod of broaching machines R10/2(0.63-16.0) kN.

Effect of domain knowledge encoding in CNN model architecture—a prostate cancer study using mpMRI images

Background Prostate cancer is one of the most common cancers worldwide. Currently, convolution neural networks (CNNs) are achieving remarkable success in various computer vision tasks, and in medical imaging research. Various CNN architectures and methodologies have been applied in the field of prostate cancer diagnosis. In this work, we evaluate the impact of the adaptation of a state-of-the-art CNN architecture on domain knowledge related to problems in the diagnosis of prostate cancer. The architecture of the final CNN model was optimised on the basis of the Prostate Imaging Reporting and Data System (PI-RADS) standard, which is currently the best available indicator in the acquisition, interpretation, and reporting of prostate multi-parametric magnetic resonance imaging (mpMRI) examinations. Methods A dataset containing 330 suspicious findings identified using mpMRI was used. Two CNN models were subjected to comparative analysis. Both implement the concept of decision-level fusion for mpMRI data, providing a separate network for each multi-parametric series. The first model implements a simple fusion of multi-parametric features to formulate the final decision. The architecture of the second model reflects the diagnostic pathway of PI-RADS methodology, using information about a lesion’s primary anatomic location within the prostate gland. Both networks were experimentally tuned to successfully classify prostate cancer changes. Results The optimised knowledge-encoded model achieved slightly better classification results compared with the traditional model architecture (AUC = 0.84 vs. AUC = 0.82). We found the proposed model to achieve convergence significantly faster. Conclusions The final knowledge-encoded CNN model provided more stable learning performance and faster convergence to optimal diagnostic accuracy. The results fail to demonstrate that PI-RADS-based modelling of CNN architecture can significantly improve performance of prostate cancer recognition using mpMRI.

DETERMINATION OF DEPENDENCE OF OPERATING INDICATORS OF TWO-SHAFT CENTRIFUGAL MODULE ON VARIABLE PARAMETERS

The article presents the results of studies of a new design of a two-shaft centrifugal vibration module, which was created on the basis of the modernization of a two-shaft disintegrator. A distinctive feature of this design is the presence of an additional device that provides the operation of vibrational classification by size of the crushed rock mass directly in the grinding chamber. This eliminates its regrinding and increases the performance of the module. Since structural changes were introduced into the previously existing disintegrator design and new technological operations were added, a set of studies was carried out to determine the performance and expended drive power of the module, depending on the most influential operating parameters and rock mass characteristics. The main variable parameters were adopted: the number of revolutions of the beater shaft in the grinding chamber, the frequency and amplitude of oscillations of the grinding chamber, the size and strength of the crushed rock mass, and the effect of the screening process of the finished size class in the grinding chamber on the productivity and power consumption of the drive was established. It has been established that the efficiency of rock mass screening in a centrifugal vibration module is within 60 ÷ 70% depending on the separation size class and the density of the processed rock mass, as well as on the content of the finished size class in its loading. In this case, the performance of the module increases by 20%, and with the use of vibration excitation of the grinding chamber - by 25 ÷ 30%. The obtained experimental dependences of these values on variable parameters are presented in the form of graphs with their further identification by regression models, which will allow us to determine its main structural and power parameters when designing the parametric series of the module (based on the initial requirements). The results of studies of the experimental model of the module showed the effectiveness of the modernization and allow us to recommend it for wide industrial use.

Instability of Stationary Spherical Models with Orbits Arbitrarily Close to Radial

The classical problem of the stability of stationary stellar spherical models with purely radial motion is reconsidered. The problem is due to strong central singularity in the density distribution, resulting in not entirely rigorous proof made in the well-known Antonov's paper. To avoid this difficulty, we construct a suitable two-parametric series of models with moderately elongated and nearly radial orbits, without singularity, and pass to the limiting case of models with orbits arbitrarily close to purely radial. The stability of the series with respect to odd and even spherical harmonics is considered. The growth rates of aperiodic even modes increase indefinitely when approaching purely radial models.

Guide expansions for the recursive parametric solution of polynomial dynamical systems

Recursive parametric series solutions are developed for polynomial ODE systems, based on expanding the system components in series of a form studied by Weiss. Individual terms involve first-order driven linear ODE systems with variable coefficients. We consider Lotka-Volterra systems as an example.

Experimental Force Coefficients for a Parametric Series of Spinnakers

A parametric series of eight spinnaker models was built and tested in a wind tunnel according to the theory of statistical Design of Experiments. In these models, three sail shape parameters were varied - cross section camber ratio, sail aspect ratio, and sweep. Lift and drag forces were measured for a range of angles of attack, and the thrust force coefficient was determined as a function of apparent wind angle for each of the eight sails. It was found that flat spinnakers are faster than full spinnakers and that spinnakers with low sweep (more vertical) are faster than spinnakers with high sweep. This is consistent with general sailing practice, which maximizes projected sail area by pulling the pole back and down. The influence of aspect ratio on drag coefficient was small and within experimental error. A description of the sail shapes and corresponding force coefficients is presented for future validation of Reynolds Averaged Navier-Stokes simulations.