Tadej Kosel

Location of acoustic emission sources generated by air flow

The location of continuous acoustic emission sources is a difficult problem of non-destructive testing. This article describes one-dimensional location of continuous acoustic emission sources by using an intelligent locator. The intelligent locator solves a location problem based on learning from examples. To verify whether continuous acoustic emission caused by leakage air flow can be located accurately by the intelligent locator, an experiment on a thin aluminum band was performed. Results show that it is possible to determine an accurate location by using a combination of a cross-correlation function with an appropriate bandpass filter. By using this combination, discrete and continuous acoustic emission sources can be located by using discrete acoustic emission sources for locator learning.

Determination of plate source, detector separation from one signal

We address the problem of locating a transient source, such as an acoustic emission source, in a plate. We apply time-frequency analysis to the signals detected at a receiver. These highly dispersive and complex waveforms are measured for source-receiver separations ranging from 40 to 180 plate thicknesses and at frequencies such that 10 to 20 Rayleigh-Lamb branches are included. Reassigned, smoothed, pseudo-Wigner-Ville distributions are generated that exhibit the expected sharp ridges in the time-frequency plane, lying along the predicted frequency-time-of-arrival relations. The source-receiver separation can be determined from such plots.

Computational Fluid Dynamics Analysis of an Optimized Load-Distribution Propeller

B = number of propeller blades CD = drag coefficient CL = lift coefficient CP = power coefficient, P= n D CT = thrust coefficient, T= n D c = chord D = propeller diameter G = normalized circulation function GG = Goldstein’s normalized circulation function GP = Prandtl’s normalized circulation function J = advance ratio, v0=nD M = Mach number n = propeller revolutions per second, =2 P = power Q = torque R = propeller radius Re = Reynolds number RH = propeller hub radius R1 = wake radius r = radial coordinate S = propeller disk area, R T = thrust ua = axial induced velocity u = angular induced velocity v = resultant velocity v0 = advance velocity w = axial vortex displacement velocity y = nondimensional wall distance = angle of attack = blade pitch angle = circulation = drag-to-lift ratio = propeller efficiency = propeller blade pitch, v0t0 2 v0= 1 = wake pitch = speed ratio, v0= R 1 = wake speed ratio, v0 w = R1 = nondimensional radius, r=R 1 = nondimensional wake radius, r=R1 = fluid density = flow angle = propeller angular velocity

Location of continuous AE sources by sensory neural networks

A brief classification of location problems which appear in acoustic emission (AE) analysis is given. Empirical treatment of corresponding inverse problems is explained and applied to location of sources which generate continuous AE signals. A continuous AE phenomenon is treated as a stochastic process which is represented by the source coordinates and the correlation function of the emitted sound. The empirical model of AE phenomenon is formed based on a set of samples. The model includes a network of AE sensors and a neural network (NN). During formation of the model, the AE signals are generated by sources at typical positions on a specimen. Recorded ultrasonic signals are transmitted to the NN together with the source coordinates. The first layer of NN determines the cross-correlation functions of signals and forms from them and source coordinates the data vectors. In the second layer, a set of prototype vectors is formed from the data vectors by a self-organized learning. After learning, the network is capable to locate the source based on detected sound. For this purpose, the sensors provide AE signals, while the NN determines the corresponding correlation function and associates to it the source coordinates. The association is performed by a non-parametric regression which is implemented in the third layer of NN.

Intelligent location of simultaneously active acoustic emission sources: Part I

Part I describes an intelligent acoustic emission locator, while Part II discusses blind source separation, time delay estimation and location of two continuous acoustic emission sources. Acoustic emission (AE) analysis is used for characterization and location of developing defects in materials. AE sources often generate a mixture of various statistically independent signals. A difficult problem of AE analysis is separation and characterization of signal components when the signals from various sources and the mode of mixing are unknown. Recently, blind source separation (BSS) by independent component analysis (ICA) has been used to solve these problems. The purpose of this paper is to demonstrate the applicability of ICA to locate two independent simultaneously active acoustic emission sources on an aluminum band specimen. The method is promising for non-destructive testing of aircraft frame structures by acoustic emission analysis.

Design of Flexible Propellers with Optimized Load-Distribution Characteristics

The mathematical model and experimental verification of flexible propeller blades are presented in this paper. The propeller aerodynamics model is based on an extended blade-element momentum model, while the Euler–Bernoulli beam theory and Saint–Venant theory of torsion are used to account for bending and torsional deformations of the blades, respectively. The proposed blade-element momentum model extends the standard blade-element momentum theory with the aim of providing a quick and robust model of propeller action capable of treating high-aspect-ratio propeller blades with a blade axis of arbitrary geometry. Based on the proposed mathematical model, a static flexible propeller blade design procedure and its associated analysis algorithm are established. Dynamic aeroelastic phenomena like propeller flutter and divergence are not covered by the presented mathematical model, design, and analysis algorithm. Experimental validation was carried out with an objective of evaluating the performance of the devel...

Time-delay estimation of acoustic emission signals using ICA

Acoustic emission (AE) analysis is used for characterization and location of developing defects in materials. AE sources often generate a mixture of various statistically independent signals. One difficult problem of AE analysis is the separation and characterization of signal components when the signals from various sources and the way in which the signals were mixed are unknown. Recently, blind source separation by independent component analysis (ICA) has been used to solve these problems. The main purpose of this paper is to demonstrate the applicability of ICA to time-delay (T-D) estimation of two independent continuous AE sources on an aluminum beam. It is shown that it is possible to estimate T-Ds by ICA, and thus to locate two independent simultaneously emitted sources.

Buckling of a Shallow Rectangular Bimetallic Shell Subjected to Outer Loads and Temperature and Supported at Four Opposite Points

We have formulated a geometric non-linear mathematical-physical model of the snap-through of the system of a thin-walled shallow bimetallic translation shell in a homogenous temperature field according to the theory of large displacements, moderate rotations, and small strains of the shell element. The model enables the calculation of the geometric conditions, of shallow translation shells, due to the influences of temperature and mechanical loads. The results are based on the numeric solution of a non-linear system of partial differential equations with boundary conditions according to the finite difference method.

Reducing shear-lag in thin-walled composite I-beam wing spars

Purpose – The purpose of this paper was to investigate and evaluate the influence of geometrical and structural design changes in order to reduce shear-lag and increase specific strength and stiffness of thin-walled composite I-beam wing spars. Design/methodology/approach – A detailed FEM model of a cantilevered I-beam spar was used to investigate the influence of increased transition fillet radius and increased web sandwich core thickness on the shear-lag effect at different width to thickness ratios of flanges. Evaluation functions were used to assess specific strength and stiffness of different spar configurations. Findings – Increased web core thickness has greater influence on normal stress distribution and the reduction of the shear-lag than fillet size. Additional weight of thicker core is not compensated enough through reduction of stress concentration. Increased transition fillet and web core thickness increase optimum flanges width to thickness ratio. Shear-lag reduces the strength of the spar m...

Aeroelastic Design of Propellers with Optimized Load-Distribution Characteristics

The mathematical model and experimental verification of deformable propeller blades are presented in this paper. The propeller aerodynamics model is based on an extended bladeelement momentum model while the Euler-Bernoulli beam theory and Saint-Venant theory of torsion are used to account for bending and torsional deformations of the blades, respectively. The proposed blade-element momentum model extends the standard bladeelement momentum theory with the aim of providing a quick and robust model of propeller action capable of treating high aspect-ratio propeller blades with a blade axis of arbitrary geometry. Based on the proposed mathematical model a propeller blade aeroelastic design procedure and its associated analysis algorithm are established. Experimental validation was carried out with an objective of evaluating the performance of the developed mathematical model and the design strategy. Both theoretical and experimental results are presented along with pertinent concluding remarks.