Coupling an ultrasonic propagation code with a model of the heterogeneity of multipass welds to simulate ultrasonic testing

Apfel, A.; Moysan, Joseph; Corneloup, Gilles; Fouquet, Thierry; Chassignole, Bertrand

doi:10.1016/j.ultras.2004.09.004

Cited by 38 publications

(15 citation statements)

References 18 publications

(18 reference statements)

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“…Several studies can already be conducted with the model that were not possible in the past: oriented-to-misoriented and columnar-to-equiaxed transitions, 23) competition between <100> directions observed upon remelting of a single crystal, 20) structures formed upon multiple passes during GTAW. 21,22) It is yet clear that such model is not necessarily restricted to remelting processes. However, extension to processing that permits addition of metals still requires extensions.…”

Section: Discussionmentioning

confidence: 99%

“…In addition, Saluja et al 16) applied a CAFE model to predict the grain size distribution and the influence of weld defects during friction stir welding. More work was achieved in the past in order to model the computation between grains, either with respect to crystal orientation [17][18][19][20][21][22][23] or to the columnar-to-equiaxed transition (CET). 23) However, the works listed above focused on direct simulation of the growth of a few dendritic grains in representative solidification conditions of the weld pool, or on indirect modeling of the growth in the weld pool.…”

Section: Introductionmentioning

confidence: 99%

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3D Coupled Cellular Automaton (CA)–Finite Element (FE) Modeling for Solidification Grain Structures in Gas Tungsten Arc Welding (GTAW)

2014

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A coupled Cellular Automaton (CA) -Finite Element (FE) model is proposed to predict the grain structure formation during Gas Tungsten Arc Welding (GTAW). The FE model solves the heat flow problem based on an adaptive meshing. This is done on a first FE mesh. The CA model simulates the development of the envelope of the grains in the liquid. For that purpose, a second FE mesh, referred to as CA mesh, is used. Fields can be interpolated between the adaptive FE mesh and the CA mesh. A CA grid made of a regular lattice of cubic cells is defined and superimposed onto the CA mesh. A new dynamic strategy for the allocation/ deallocation of the CA grid is proposed to reduce the computation and memory costs. This CAFE model is applied to partial melting of an initial grain structure and epitaxial growth in the undercooled zone of a liquid pool, thus simulating the formation of solidification structure during the GTAW process. Examples of single linear passes simulations for various processing conditions and a multiple pass simulation are presented.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

3D Coupled Cellular Automaton (CA)–Finite Element (FE) Modeling for Solidification Grain Structures in Gas Tungsten Arc Welding (GTAW)

2014

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“…Chassignole discretised an austenitic weld into twelve homogeneous domains and determined the columnar grain direction from X-ray Diffraction analysis and Electron Back-scattered Diffraction analysis. Apfel et al [13] developed the 2D finite element propagation code, ATHENA, using a fictitious domain method such 3 that a regular mesh of the calculation domain could be combined with an irregular mesh of the defect domain, allowing a superior computation speed.…”

Section: Introductionmentioning

confidence: 99%

Ultrasonic array imaging through an anisotropic austenitic steel weld using an efficient ray-tracing algorithm

Nowers

Duxbury

Drinkwater³

2016

NDT & E International

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Ultrasonic inspection of austenitic welds is challenging due to their highly anisotropic and heterogeneous microstructure. The weld anisotropy causes a steering of the ultrasonic beam leading to a number of adverse effects upon ultrasonic array imagery, including defect mislocation and aberration of the defect response. A semi-analytical model to simulate degraded ultrasonic images due to propagation through an anisotropic austenitic weld is developed. Ray-tracing is performed using the A* path-finding algorithm and integrated into a semi-analytical beam-simulation and imaging routine to observe the impact of weld anisotropy on ultrasonic imaging. Representative anisotropy weld-maps are supplied by the MINA model of the welding process. A number of parametric studies are considered, including the magnitude and behaviour of defect mislocation and amplitude as the position of a fusion-face defect and the anisotropy distribution of a weld is varied, respectively. Furthermore, the use of the model to efficiently simulate and evaluate ultrasonic image degradation due to anisotropic austenitic welds during an inspection development process is discussed.

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“…Rapid increases in both computing power and storage capacities, and corresponding decreases in cost have paved the way for the development of improved modelling capabilities and imaging algorithms, with notable contributions from [1][2][3] .…”

Section: Introductionmentioning

confidence: 99%

Correction of ultrasonic array images to improve reflector sizing and location in inhomogeneous materials using a ray-tracing model

Connolly

Lowe²,

Temple³

et al. 2010

The Journal of the Acoustical Society of America

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Coupling an ultrasonic propagation code with a model of the heterogeneity of multipass welds to simulate ultrasonic testing

Cited by 38 publications

References 18 publications

3D Coupled Cellular Automaton (CA)–Finite Element (FE) Modeling for Solidification Grain Structures in Gas Tungsten Arc Welding (GTAW)

3D Coupled Cellular Automaton (CA)–Finite Element (FE) Modeling for Solidification Grain Structures in Gas Tungsten Arc Welding (GTAW)

Ultrasonic array imaging through an anisotropic austenitic steel weld using an efficient ray-tracing algorithm

Correction of ultrasonic array images to improve reflector sizing and location in inhomogeneous materials using a ray-tracing model

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