Investigations on welding distortion in an asymmetrical curved block by means of numerical simulation technology and experimental method

Deng, Dean; Murakawa, Hidekazu; Shibahara, Masakazu

doi:10.1016/j.commatsci.2009.12.027

Cited by 47 publications

(24 citation statements)

References 7 publications

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“…With increasing TCTP, the absorbed energy increased significantly for all T p1 conditions. However, at the cooling rate of 3uC s 21 , a T p 5800uC; b T p 5850uC; c T p 51350uC 10 Microstructures of one-cycle specimen (CR560uC s 21 ) 11 Fractography comparison of Charpy impact samples when a T p 5800uC and b T p 5850uC with same cooling rate of 60uC s 21 the absorbed energy of the whole process is relatively lower than that with the other cooling rates.…”

Section: Toughness Database Of One-cycleztempermentioning

confidence: 92%

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Neural network based toughness prediction in HAZ of low alloy steel produced by temper bead welding repair technology

Yu¹,

Sasa²,

Ohnishi³

et al. 2013

Science and Technology of Welding and Joining

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The pressure vessels of aged nuclear power plants are needed to repair or maintain, and temper bead welding (TBW) is one effective repair welding method instead of post weld heat treatment. For TBW, toughness is the key criteria to evaluate the tempering effect. A neural network based method for toughness prediction in heat affected zone (HAZ) of low alloy steel has been investigated to evaluate the tempering effect in TBW. On the basis of experimentally obtained database, the new toughness prediction system was constructed by using radial basis function neural network. With it, the toughness distribution in HAZ of TBW was calculated based on the thermal cycles numerically obtained by finite element method (FEM). The predicted toughness was in good accordance with the experimental results. It follows that our new prediction system is effective for estimating the tempering effect during TBW and hence enables us to assess the effectiveness of TBW before the actual repair welding.

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Section: Toughness Database Of One-cycleztempermentioning

confidence: 92%

“…The thermal cycles in temper bead welding were calculated using finite element method (FEM) software developed specifically for welding simulation. 11 a sample of Gleeble test (W15660 mm); b specimen of side notched Charpy impact test 5 Schematic illustration of samples 6 Specimen of temper bead welding test …”

Section: Materials and Experimental Proceduresmentioning

confidence: 99%

Neural network based toughness prediction in HAZ of low alloy steel produced by temper bead welding repair technology

Yu¹,

Sasa²,

Ohnishi³

et al. 2013

Science and Technology of Welding and Joining

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show abstract

“…Research methodology flow diagram. [10] The Annals of "Dunarea de Jos" University of Galati Fascicle XI…”

Section: Methologymentioning

confidence: 99%

Control of welding deformation in thin plate

Ali

Teodor

2018

AUGAL.ShipBuilding

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Welding is a process to join metals with different arrangements of the plates. In the shipbuilding industry, the joining of plates in such a way as to ensure higher productivity is very important, but the industry has been facing the problem of deformation for seven decades. The shipbuilding industry is trying to control this problem, but thin plates bring non-linear problems in the structure, especially in the bulkhead of the structure that leads to more deformation due to small members of the profiles. This problem occurs in the construction of yachts because clients need good outlook of the ship. To control this problem the computational analysis is the more productive method than other to solve this deformation problem. The thermal elastic plastic FEM method is used to analyse the thermal and mechanical problems. This analysis confirmed that this TEP-Finite Element Method is applicable for the control of deformation in the thin plate.

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“…The temperature distributions produced by multi-pass thermal cycles in welds during temper bead welding were calculated using three-dimensional finite element analysis code, developed specifically for welding simulation 8) . Fig.…”

Section: Prediction Of Hardness and Toughness In Haz Of Temper Bead Wmentioning

confidence: 99%

Neural network-based hardness and toughness prediction in HAZ of temper bead welding repair technology

Sasa

Ohnishi

et al. 2013

QUARTERLY JOURNAL OF THE JAPAN WELDING SOCIETY

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The aged nuclear power plant needs to be repaired or maintained, and temper bead welding is one effective repair welding methods instead of post weld heat treatment. For temper bead welding, hardness and toughness are the key criteria to evaluate the tempering effect. A neural network-based method for hardness and toughness prediction in heat affected zone of low-alloy steel has been investigated to evaluate the tempering effect in temper bead welding. On the basis of experimentally obtained database, the new hardness and toughness prediction system was constructed by using RBF-neural network. With it, the hardness and toughness distribution in heat affected zone of temper bead welding was calculated based on the thermal cycles numerically obtained by Finite Element Method. The predicted hardness and toughness were in good accordance with the experimental results. It follows that our new prediction system is effective for estimating the tempering effect during temper bead welding and hence enables us to assess the effectiveness of temper bead welding before the actual repair welding.

show abstract

Investigations on welding distortion in an asymmetrical curved block by means of numerical simulation technology and experimental method

Cited by 47 publications

References 7 publications

Neural network based toughness prediction in HAZ of low alloy steel produced by temper bead welding repair technology

Neural network based toughness prediction in HAZ of low alloy steel produced by temper bead welding repair technology

Control of welding deformation in thin plate

Neural network-based hardness and toughness prediction in HAZ of temper bead welding repair technology

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