The results of experimental studies on the effect of randomly located circular holes of various number and diameters on the critical buckling force of longitudinally compressed cylindrical shells are ...presented in the form of curves of the critical buckling load versus the number, size, and total area of the random holes and the buckling patterns. The obtained data can be useful for predicting the residual load-bearing capacity of damaged shell structures.
One of the most important factors for improving the resolution of optical systems is to compensate for the aberrations (distortions) of the wave front. As a rule, whether special measuring devices ...(wavefront sensors) are used for such compensation or adaptive mirrors that perform iterative correction of the wavefront. However, often (for reasons of compactness or weight reduction), it is not possible to use the special equipment for measuring aberrations. To obtain certain information on the wave front, one can use the measured point spread function (PSF) or the intensity pattern in the focal plane. Methods of processing two PSFs (focal and nonfocal) with the help of neural networks are known. In this paper, we investigate the possibility of recognizing the wave front from a single intensity pattern in the focal plane. The technology of deep machine learning - convolutional neural network is chosen as the way for implementation. The idea of this technology lies in the alternation of convolutional and subsampling layers, for the purpose of efficient image recognition. Such approach will allow to optimize the process of compensation of optical system aberrations and to reduce the amount of required input data.
This paper presents the results of experimental investigation on the stability of orthotropic cylindrical shells of different lengths weakened by regular circular holes located in one zone along the ...guide cell under torque loading. The buckling modes of shells are described. The critical buckling loads as a function of the number of holes are analyzed.
Recently, intelligent data analysis and neural networks are increasingly used to detect the wavefront by interferograms and digital holograms. In this case, there is significant freedom to choose the ...structure of the reference beam. In this paper, a comparative study of the effectiveness of the neural network was performed to solve the problem of the wavefront aberration recognition based on off-axis and inline schemes of digital holography with a plane and conical reference wavefront, respectively. The feature of the inline digital holograms with the conical wavefront compared to the off-axis is the invariance of their structure to the rotation of the wavefront at some angle. In addition, a numerical analysis of the sensitivity of the types of digital holograms under consideration to changes in the wavefront for a different level of aberration showed relatively better characteristics for the average level of aberration, when it is difficult to apply detecting methods based on the Shack-Hartmann sensors or matched filtering. These features of inline digital holograms with a conical reference wavefront made it possible to increase the recognition efficiency for types and levels of aberrations using neural networks. As a result, the average absolute recognition error for model interferogram decreases more than three times. The results for the experimental conical and linear interferograms turned out to be quite close because of the sensitivity of the conical wavefront to the alignment of the optical system. Moreover, the neural network trained on a more diverse experimental data set, which contains natural distortions of image registration, gives an increase in the average recognition accuracy for linear-type interferograms. Thus, in the future, it is reasonable to consider the combined use of various types of interferograms.
Abstract
Recognition of the types of aberrations corresponding to individual Zernike functions were carried out from the pattern of the intensity of the point spread function (PSF) outside the focal ...plane using convolutional neural networks. The PSF intensity patterns outside the focal plane are more informative in comparison with the focal plane even for small values/magnitudes of aberrations. The mean prediction errors of the neural network for each type of aberration were obtained for a set of 8 Zernike functions from a dataset of 2 thousand pictures of out-of-focal PSFs. As a result of training, for the considered types of aberrations, the obtained averaged absolute errors do not exceed 0.0053, which corresponds to an almost threefold decrease in the error in comparison with the same result for focal PSFs.
It is shown that if the positive (negative) semitrajectory of some motion
, located in a metric space
, is relatively compact then the
- (
-) limit set of that motion is a compact minimal set. It ...follows that in the space
any non-recurrent motion is either positively (negatively) departing or positively (negatively) asymptotic with respect to the corresponding compact minimal set.
The article presents a method for studying the strength characteristics and optimizing the parameters of the casings of pumping and compressor equipment, gearboxes, motors, etc. structures by the ...reduced density of stripes on their holographic interferograms. It was used to study the properties of a cylindrical shell with an optimal reinforcing pad in the zone of action of a radial concentrated force. A rational redistribution of the material of the ribbed plate, bent by a transverse concentrated force, has been carried out. The deformation of the crankcase of the gearbox and clutch of a car in all gears is investigated, recommendations are given for the rational redistribution of its material. The results show that holographic interferometry makes it possible to assess the advantages of the optimal designs obtained, allows to significantly expand the class of hull structures, for which a high level of design solutions can be effectively implemented to ensure their rational parameters.
Abstract
Control of the composition after heat treatment is important stage of biomaterials production especially in case of their new versions creation, because many biocompatible synthetic ...substances are unstable at high temperatures. Interaction between components in multicomponent systems is possible with the formation of new undesirable products. In this work, the process of calcination of composite granules with a variable content of hydroxyapatite and wollastonite and binder polymer (gelatine) was studied. It was found that materials heat treatment leads to a change of their phase composition caused by the apatite decomposition, transition of β-CaSiO
3
to α-form, and calcium silicophosphate formation (in samples where apatite is the main component). Calcined products composition depends on the apatite/wollastonite ratio in the materials.
The paper investigates the sensitivity of interferograms formed using the structured reference beams. The parameters of the reference beam are selected to improve the visualization of aberrations in ...the interferograms. A study carried out on the use of reference beams with cylindrical wavefronts in the interferograms formation to improve the aberrations recognition using a convolutional neural network. The applying of a cylindrical reference beam instead of a plane one in the interference method for recognition of wave aberrations based on neural networks with Xception architecture makes it possible to reduce the mean absolute error by more than 30%. In this work, for each type of interferogram, the model was trained for 80 epochs, which took about 1.8 hours using GeForce RTX 2070 graphics card. However, after completing this training once, we obtain a model that allows us to make forecasts in 0.055 s for every new interferogram of the same type.
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