Modelling and validation: Casting of Al and TiAl alloys in gravity and centrifugal casting processes

Humphreys, N.J.; McBride, D.; Shevchenko, D.; Croft, Nick; Withey, Paul; Green, Nick; Cross, M.

doi:10.1016/j.apm.2013.03.030

Cited by 32 publications

(12 citation statements)

References 22 publications

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“…The relative importance of these process uncertainties on casting quality is not well understood. Although the physical principles governing fill and solidification are well established, 12 it is difficult to account for uncertainties in process parameters when defining boundary conditions for simulations.…”

mentioning

confidence: 99%

Effects of Process Related Variations on Fillablity Simulation of Thin-Walled IN718 Structures

et al. 2017

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Simulation tools have improved significantly and are now capable of accurately predicting mould filling behavior. The quality of prediction is highly dependent on material properties and set-up of boundary conditions for the simulation. In this work material properties were measured and casting conditions were analyzed to accurately replicate the casting process in simulation. The sensitivity of the predictions to minor process variations commonly found in foundries was evaluated by comparing simulation and cast samples. The observed discrepancies between simulation and cast samples were evaluated and discussed in terms of their dependency on process variations. It was concluded that the simulation set-up was capable of reasonable predictions and could replicate the asymmetry of the filling however did not accurately predict the absolute value of the unfilled area. It was discovered that asymmetric flow due to variations in the orientation of the casting mould during filling could have greater influence on the predictions than the actual variation in fill time. The quality of simulation is dependent on equipment and techniques used in the foundry as well as the metallurgical model to simulate the process.

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confidence: 99%

Effects of Process Related Variations on Fillablity Simulation of Thin-Walled IN718 Structures

et al. 2017

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“…[10] and [11] with the boundary conditions given in Eq. [22]. Otherwise, evaluate the air gap thickness as…”

Section: ½23mentioning

confidence: 99%

“…Naturally, a simplest approach would be an assumption of a perfect contact formed throughout the entire casting, which was used, e.g., by Xu et al, [18] Gao and Wang, [19] and Cook et al [20] Bohacek et al [21] pointed out the importance of an air gap in their findings and conclusions, yet in the numerical model, it was not taken into account. Humphreys et al [22] calculated the heat transfer at the interface by employing a ''virtual wall'' technique with cumulative thermal resistances; however, they did not provide parameters to calculate them. Chang et al [23] used arbitrary values of heat transfer coefficients at the interface, constant during the casting and increasing for higher rotation rates.…”

Section: Introductionmentioning

confidence: 99%

“…Lagerstedt, a colleague of Kron, pointed out in the future work chapter of his doctoral thesis [43] that including plasticity in the stress model probably should be the next step in developing an accurate shrinkage model. Xu et al [18] perfect contact Gao and Wang [19] perfect contact Cook et al [20] perfect contact Bohacek et al [21] perfect contact Humphreys et al [22] not available Chang et al [23] constant 1000 to 2600 Kang et al, [24] Kang and Rohatgi [25] constant 1000 Ebisu [26] variable not available Kamlesh [27] variable not available Lajoye and Suery [28] variable 400 to 80,000 (1/10)* Raju and Mehrotra [29] variable 100 to 10,000 (1/10) Drenchev et al [30] variable 420 to 84,000 (1/10) Panda et al [31] variable 50 to 5000 (1/10) Nastac [32] variable 90 to 6000 (3/100) Vacca et al [33] variable (exp.) 50 to 870 (6/100) *h f /h 0 ratio.…”

Section: Introductionmentioning

confidence: 99%

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Heat Transfer Coefficient at Cast-Mold Interface During Centrifugal Casting: Calculation of Air Gap

Boháček

Kharicha

Ludwig

et al. 2018

Metall Mater Trans B

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During centrifugal casting, the thermal resistance at the cast-mold interface represents a main blockage mechanism for heat transfer. In addition to the refractory coating, an air gap begins to form due to the shrinkage of the casting and the mold expansion, under the continuous influence of strong centrifugal forces. Here, the heat transfer coefficient at the cast-mold interface h has been determined from calculations of the air gap thickness d a based on a plane stress model taking into account thermoelastic stresses, centrifugal forces, plastic deformations, and a temperature-dependent Young's modulus. The numerical approach proposed here is rather novel and tries to offer an alternative to the empirical formulas usually used in numerical simulations for a description of a time-dependent heat transfer coefficient h. Several numerical tests were performed for different coating thicknesses d C , rotation rates X, and temperatures of solidus T sol . Results demonstrated that the scenario at the interface is unique for each set of parameters, hindering the possibility of employing empirical formulas without a preceding experiment being performed. Initial values of h are simply equivalent to the ratio of the coating thermal conductivity and its thickness (~1000 Wm À2 K À1 ). Later, when the air gap is formed, h drops exponentially to values at least one order of magnitude smaller (~100 Wm À2 K À1 ).

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“…In nature, it can be observed during the formation of ice as well as volcanic lava, while in industry, it is found in freezing, casting and welding (Tan, Li, & Li, 2011, Verma & Gómez-Arias, 2013, Yajun, Pengfei, Yongjun, Zhijun, & Yintao, 2013, Humphreys et al, 2013.…”

Section: Introductionmentioning

confidence: 99%

<b>Inverse problem for porosity estimation during solidification of TNT

2016

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ABSTRACT. In the present study, the porosity formed during the solidification process is estimated by an inverse problem technique based on particle swarm optimization. The effective heat capacity method is adopted to model the heat transfer problem. The transient-diffusive heat transfer equation is solved numerically by the finite volume method with an explicit scheme, employing the central difference interpolation function. The solution of the direct problem is compared to reference solutions. The model is applied to trinitrotoluene (TNT) solidification process. The results show that the proposed procedure was able to estimate the porosity for different Stefan numbers. The analysis of the heat flux in the mold is indicated to predict the porosity formation during the casting process.

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Modelling and validation: Casting of Al and TiAl alloys in gravity and centrifugal casting processes

Cited by 32 publications

References 22 publications

Effects of Process Related Variations on Fillablity Simulation of Thin-Walled IN718 Structures

Effects of Process Related Variations on Fillablity Simulation of Thin-Walled IN718 Structures

Heat Transfer Coefficient at Cast-Mold Interface During Centrifugal Casting: Calculation of Air Gap

<b>Inverse problem for porosity estimation during solidification of TNT

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