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43 results on '"Byakov, A. V."'

12. Optimizing ultrasonic welding parameters for multilayer lap joints of PEEK and carbon fibers by neural network simulation

Author

Panin, Sergey V., Stepanov, Dmitry Yu., and Byakov, Anton V.

Subjects
адгезия, нейросетевое моделирование, соединение внахлестку, machine learning, neural network simulation, ultrasonic welding, lap joint, PEEK, prepreg, interface, adhesion, Taguchi method, General Materials Science, ультразвуковая сварка, интерфейс, машинное обучение, Тагучи метод
Abstract

The aim of this study is to substantiate the use machine learning methods to optimize a combination of ultrasonic welding (USW) parameters for manufacturing of multilayer lap joints consisting of two outer PEEK layers, a middle prepreg of unidirectional carbon fibers (CFs), and two energy directors (EDs) between them. As a result, a mathematical problem associated with determining the optimal combination of technological parameters was formulated for the formation of USW joints possessing improved functional properties. In addition, a methodology was proposed to analyze the mechanical properties of USW joints based on neural network simulation (NNS). Experiments were performed, and threshold values of the optimality conditions for the USW parameters were chosen. Accordingly, NNS was carried out to determine the parameter ranges, showing that the developed optimality condition was insufficient and required correction, taking into account other significant structural characteristics of the formed USW joints. The NNS study enabled specification of an extra area of USW parameters that were not previously considered optimal when designing the experiment. The NNS-predicted USW mode (P = 1.5 atm, t = 800 ms, and τ = 1500 ms) ensured formation of a lap joint with the required mechanical and structural properties (σUTS = 80.5 MPa, ε = 4.2 mm, A = 273 N·m, and Δh = 0.30 mm).

Published
2022

41. Applying an Ultrasonic Lamb Wave Based Technique to Testing the Condition of V96ts3T12 Aluminum Alloy.

Author

Burkov, M. V., Eremin, A. V., Lyubutin, P. S., Byakov, A. V., and Panin, S. V.

Subjects
NONDESTRUCTIVE testing, STRUCTURAL health monitoring, ULTRASONIC imaging
Abstract

Possibilities offered by an ultrasonic inspection technique that is based on using Lamb waves for monitoring the state of metal materials under static and cyclic loading have been studied. Dogbone V96ts3T12-aluminum-alloy specimens of the following two types have been used for research: initial material and a sample with a weld at the working zone center. The digital-image correlation method has been used as an additional source of information. Based on the tests, dependences of various informative parameters of acoustic vibrations on the applied load (for static tests) and running time (for cyclic tests) have been obtained. These dependences have been further supplemented with the results of calculation of deformation fields. The data gathered indicate sensitivity of the proposed ultrasonic inspection technique to various (elastic and plastic) deformation processes and allow one to monitor the growth of cracks under cyclic tests. Further development of the method assumes its examination from the viewpoint of embedded testing systems (the Structural Health Monitoring concept). [ABSTRACT FROM AUTHOR]

Published
2017
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