Oförstörande materialkarakterisering med hjälp av ultraljud - matematisk modellering

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1 Oförstörande materialkarakterisering med hjälp av ultraljud - matematisk modellering Håkan Wirdelius SCIENTIFIC CENTER OF NON-DESTRUCTIVE TESTING

2 Outline Nondestructive material Characterization (NDC) Advanced NDE/SCeNDT NDE is an inverse problem Estimation of Grain Orientation in an Anisotropic Weld Nondestructive Material Characterization (PUC) Modeling of the LUS and validation Grain size estimations Nondestructive Quality Assessment based on hybrid modeling

3 Organisation 2015-> Advanced NDT Materials and Manufacturing Technology Integrity and quality assessment by NDE (IqNDE) Ultrasonic NDE Håkan Wirdelius, Kenneth Hamberg Eddy Current NDE Gert Persson, Anders Rosell? Risk Based Quality Assessment Peter Hammersberg SCeNDT Scientific Centre of NDT Project portfolio

SCeNDT Research area Applied mathematical modeling of NDE methods Develop and experimental validation of mathematical models of different NDE methods Apply mathematical modeling in the development of

4 SCeNDT Research area Applied mathematical modeling of NDE methods Develop and experimental validation of mathematical models of different NDE methods Apply mathematical modeling in the development of NDT as a tool for material characterization (NDC) Use mathematical modeling in the development of new NDT techniques Integrity and quality assessment by NDE (IqNDE) Risk Based Quality Assessment (identification of risks, classification, probability of occurrence and probability of detection) Generate Probability of Detection curves (POD) based on simulated data Education ISI Technologies (graduate and PhD) Education for industry (graduate level)

5 Optimization schemes to solve the inverse problem NDE is an inverse problem 1. H. Wirdelius, An Optimization Technique for Inverse Crack Detection, J. of Modern Physics 5, , Q. Liu and H. Wirdelius, Estimation of grain orientation in an anisotropic weld by using a model of ultrasonic propagation in an inverse scheme, Modelling and Simulation in Engineering, vol. 2014, Article ID , 11 pages, E. Lindgren, Detection, 3-D positioning, and sizing of small pore defects using digital radiography and tracking, EURASIP Journal on Advances in Signal Processing, 1-17, 2014.

6 NDE is an inverse problem Qingwei Liu (PhD 2007) Optimal Estimation of Grain Orientation in an Anisotropic Weld by Ultrasonic Techniques

7 NDC Nondestructive Material Charachterization Mathematical modeling of UT PUC Product Uniformity Control (EU-RFCS) 1 TATA STEEL NEDERLAND TECHNOLOGY, NL 2 ARCELORMITTAL MAIZIERES RESEARCH, FR 3 THYSSENKRUPP STEEL EUROPÉ, DE 4 SALZGITTER MANNESMANN FORSCHUNG, DE 5 THE UNIVERSITY OF MANCHESTER, UK 6 CENTRO DE ESTUDIOS E INVESTIGACIONES TECNICAS, ES 7 SWEREA KIMAB AB, SE 8 TNO BUILT ENVIRONMENT AND GEOSCIENCES,NL 9 CHALMERS TEKNISKA HÖGSKOLA, SE 10 SCUOLA SUPERIORE DI STUDI UNIVERSITARI E DI PERFEZIONAMENTO, IT 11 the UNIVERSITY OF BIRMINGHAM, UK 12 ARCELORMITTAL EISENHÜTTENSTADT, DE 13 UNIVERSITE JOSEPH FOURIER GRENOBLE, FR 14 COMMISSARIAT A L'ENERGIE ATOMIQUE CEA, FR 15 CEDRAT TECHNOLOGIES, FR

Attenuation Single scattering with backwall Include viscous damping (e -ax ) Validation (literature) c 1.

8 Mathematical modeling of UT Intentions within the PUC project (Chalmers) Single phase material (spherical inclusion) 1. Backscattering Single scattering Validation (literature) 2. Attenuation Single scattering with backwall Include viscous damping (e -ax ) Validation (literature) c 1. 2c I i i 3. Anisotropic behavior (UT) Statistic approach (distribution of grain size and properties) 4. LUS Modeling of the LUS Implementation in simsundt Validation

9 Modeling of the LUS LUS Aluminium 2.84 mm x u z (x) x = 0 mm x = 2.9 mm L S 3L S->R 5L 3S+4LS 3L2S

Nondestructive Characterization (NDC) Grain size correlation based on backscattered UT information z y x 5 mm 10 mm l 10 mm Ref. pore = 0.1 mm mm y Ref. pore = 0.1 mm mm z 10 mm x A.

10 Nondestructive Characterization (NDC) Grain size correlation based on backscattered UT information z y x 5 mm 10 mm l 10 mm Ref. pore = 0.1 mm mm y Ref. pore = 0.1 mm mm z 10 mm x A. Li, R. Roberts, P. Haldipur, F.J. Margetan and R.B. Thompson, Computational Study of Grain Scattering Effects in Ultrasonic Measurements, in Review of Progress in QNDE, (2003). 10 mm

11 Different grain size distributions used in the simulation

12 Backscattered amplitude (db), 5 MHz (80%) Noise levels (mean values based on 225 points above the control volume) as function of grain size and their distributions. Inclusions with identical elastic properties (blue, 10% higher stiffness than the matrix) are compared with normal distributions (black, Norm I from 0 to 20% higher stiffness).

13 Backscattered amplitude (linear), 8 MHz (75%)

mean values (FFT of back reflected echo) from 10 measuring points z y x 5 mm 10 mm l 10 mm Ref.

14 Experimental validation (LUS) The right figure (simulations) is based on mean values from 225 values above the volume with 10 individual distribution (all Norm I) and the left figure (LUS) is based on mean values (FFT of back reflected echo) from 10 measuring points z y x 5 mm 10 mm l 10 mm Ref. pore = 0.1 mm y Ref. pore = 0.1 mm z 10 mm x 10 mm Experimental data provided by Swerea KIMAB (ref. Peter Lundin)

15 Experimental validation (LUS) When only one distribution is used the correlation is not that obvious procedure based on frequency content must be based on a number of points

16 IqNDE in manufacturing industries Non-destructive Quality Assessment based on hybrid modelling Today: empirical based model is used in order to define a go/no go value Today: time consuming destructive examinations Today: amplitude, time of flight, frequency and phase information (UT) are reduced down to a binary information x 0 empirical x 0 accept Project: meta-models to combine experimental with corresponding simulated data Project: dynamically built meta-model (AI) Project: continues assessment of quality related material parameters Project: can be combined with process parameters and contribute to deeper understanding of process variations time

17 IqNDE in manufacturing industries Non-destructive Quality Assessment based on hybrid modelling -NDT is indirect in its nature. Let x 0 be the addressed material property and be the signal response (NDT) with assumed correlation Empirical model: x 0 =x 0 ( ) Analytical model: m (x 0, x 1... x k ) Semi-analytical model: analytical empirical x 0 semi-analytical production cycles

18 IqNDE in manufacturing industries Non-destructive Quality Assessment based on hybrid modelling Project organization Håkan Wirdelius and Peter Hammersberg from Chalmers, the experimental work will be supervised by Peter Lundin at Swerea KIMAB. 1) PhD, Graduate school Solid and Structural Mechanics, Håkan Wirdelius (supervisor/examiner), Peter Folkow (ass. supervisor) 2) PhD, Graduate school Materials Science, Håkan Wirdelius (supervisor/examiner), Gert Persson (ass. supervisor) 3) PhD, Graduate school Signals & Systems, Johan Carlson (supervisor/examiner), XX (ass. supervisor) 4) PhD, Graduate school Manufacturing Technology, Peter Hammersberg (supervisor) and Peter Krajnik (examiner)

Tillämpad matematisk modellering av OFP som stöd vid processtyrning

Tillämpad matematisk modellering av OFP som stöd vid processtyrning Håkan Wirdelius SCIENTIFIC CENTER OF NON-DESTRUCTIVE TESTING Organisation 2017 Advanced NDT Industrial and Materials Science Integrity