On the vibrations of the imperfect sandwich higher-order disk with a lactic core using generalize differential quadrature method

Melting process of nanoparticle enhanced PCM through storage cylinder incorporating fins

Approaches for expedition of discharging of PCM involving nanoparticles and radial fins

Moth flame optimization (MFO) is a swarm-based algorithm with mediocre performance and marginal originality proposed in recent years. It tried to simulate the fantasy navigation mode of moth lateral positioning. The basic MFO has no specific, deep strategies in different periods of the algorithm and a fragile evolutionary basis, which may lead to the problem of falling into local optimum and slow convergence trend. Therefore, this paper introduces a double adaptive weight mechanism into the MFO algorithm, termed as WEMFO, to boost the search capability of the basic MFO and provide a more efficient tool for optimization purposes. The proposed WEMFO adjusts the search strategy adaptively in different periods of the algorithm, making it more flexible between global search (diversification) and local search (intensification). The WEMFO algorithm is compared with some illustrious metaheuristic solvers and advanced metaheuristic methods developed in recent years on thirty benchmark functions. The experimental results expose that the developed WEMFO has apparent compensations in terms of convergence speed and solution accuracy. Moreover, this paper analyzes the diversity and balance of WEMFO and applies the algorithm to several engineering problems. The experimental results show that the WEMFO algorithm has good performance in engineering problems. Additionally, the proposed WEMFO was also applied to train Kernel Extreme Learning Machine (KELM), the resultant optimized WEMFO-KELM model was applied to six clinical disease classification problems. By comparing with MFO-KELM and other five classification models, the experimental results showed that the proposed algorithm had shown better performance in practical problems. An online guide for the algorithm in this research WEMFO and proposed classifier WEMFO-KELM will be publicly available at https://aliasgharheidari.com .

Double adaptive weights for stabilization of moth flame optimizer: Balance analysis, engineering cases, and medical diagnosis

In the current report, characteristics of the propagated wave in a sandwich structure with a soft core and multi-hybrid nanocomposite (MHC) face sheets are investigated. The higher-order shear deformable theory (HSDT) is applied to formulate the stresses and strains. Rule of the mixture and modified Halpin–Tsai model are engaged to provide the effective material constant of the multi-hybrid nanocomposite face sheets of the sandwich panel. By employing Hamilton’s principle, the governing equations of the structure are derived. Via the compatibility rule, the bonding between the composite layers and a soft core is modeled. Afterward, a parametric study is carried out to investigate the effects of the CNTs' weight fraction, core to total thickness ratio, various FG face sheet patterns, small radius to total thickness ratio, and carbon fiber angel on the phase velocity of the FML panel. The results show that the sensitivity of the phase velocity of the FML panel to the 
$${W}_{\rm{CNT}}$$

 and different FG face sheet patterns can decrease when we consider the core of the panel more much thicker. It is also observed that the effects of fiber angel and core to total thickness ratio on the phase velocity of the FML panel are hardly dependent on the wavenumber. The presented study outputs can be used in ultrasonic inspection techniques and structural health monitoring.

A computational framework for propagated waves in a sandwich doubly curved nanocomposite panel

In this study, the finite element method (FEM) for phased array technology in ultrasonic time of flight diffraction (TOFD) for the defect detection of two-dimensional (2-D) geometric materials was researched. The phased array technology generated the FEM model for the TOFD signal. We
 have established the finite element model by the FEM software ANSYS based on the ultrasonic mechanism about the defects and the phased array transducer. A plane strain elements have simulated the reflected signal of the defect. We can compare the error ratio between simulation and experiment
 by using the theoretical calculation value as the benchmark, and find the feasibility of the FEM detection.

Finite Element Analysis Model on Ultrasonic Phased Array Technique for Material Defect Time of Flight Diffraction Detection

Nonlinear Lamb wave analysis for microdefect identification in mechanical structural health assessment

The present invention discloses a gearbox malfunction identification method based on the sequential hypothesis test. The method is that an identification system carries out an adaptive intelligent query to a propagation channel with available data. Firstly, an extracted vibration signal is pretreated with the wavelet packet analysis method. Secondly, a sequence of kurtosis values of the extractedvibration signal is taken as a test object of the sequential probability ratio test. Then effective identification for the mode and gear crack degradation under four states of the gearbox is performedaccording to the sequential probability ratio test algorithm. Finally the gearbox vibration signal is subjected to the three-layer sequential ratio test by combining the sequential probability ratiotest and the root mean square error algorithm. The invention solves the problems of slow identification speed, inaccurate target identification and low identification efficiency in malfunction detection and multi-malfunction identification.

Gearbox malfunction identification method based on sequential hypothesis test

In this paper, the ultrasonic phased array technology is used to detect the defects in the welded seam test specimens. Using pulse echo method to detect a specimen with defects and establishing the corresponding numerical model. At the same time, the finite element is used to simulate the propagation of ultrasonic waves in the defective test specimens, and figures of the sound pressure amplitude are obtained. Compared with the theoretical values, the experimental values and the simulated values show good agreement, and the errors are only - 1.37% and 4.11%, respectively. The results show that the ultrasonic phased array with finite element simulation is effective.

Finite element numerical simulation analysis based on ultrasonic phased array

The invention discloses a flaw reflection signal identification method and device based on sequential hypothesis testing. An ultrasonic emitting probe is adopted to emit an ultrasonic signal on a flawtest specimen, and an ultrasonic receiving probe is adopted to receive an ultrasonic echo signal on the same surface of the flaw test specimen; after the echo signal is collected, the echo signal issubjected to wavelet packet transformation de-noising processing; the echo signal subjected to the wavelet packet transformation de-noising processing is subjected to sequential probability ratio testidentification processing to obtain the starting point of a diffraction signal; and according to the starting point of the diffraction signal, the position of the flaw is determined. The invention puts forward an identification detection and positioning method based on the sequential probability ratio test, can be widely applied to the detection and the positioning of different types of structural flaws, and accuracy and universality are high.

Chen Hanxin

Papers

Finite Element Analysis Model on Ultrasonic Phased Array Technique for Material Defect Time of Flight Diffraction Detection

Nonlinear Lamb wave analysis for microdefect identification in mechanical structural health assessment

Gearbox malfunction identification method based on sequential hypothesis test

Finite element numerical simulation analysis based on ultrasonic phased array

Flaw reflection signal identification method and device based on sequential hypothesis testing