Thermal History Prediction for Investment Ca L. Maestro 1 , A. Eguidazu 1 , I. Vicario 1 , A. Zryd 2 , J.A. Torroba 2 , E.C. M 1 Precicast Bilbao SA, Barakaldo-Bizkaia, Spain, 2 University of Applied Sciences Western Switzerland, 4 Calcom ESI SA PSE-A, EPFL, CH-1015, Lausanne, Switzerland, 5 IMDEA #0081 Due to the high cost and variability of investment casting process, simulation tools are needed to reduce the number of trials and ensure the required metallurgic quality. For this reason, the adaptation of modelling capabilities to investment casting foundry conditions is required. This work aims to present an investment casting modelling tool (ProCAST) that can provide a good correlation between its thermal history prediction and the real plant process. ProCAST software (ESI) inverse modelling tools were used to get accurate values of the parameters involved Nozzle guide vanes (NGV), which are considered as one of the most important stationary structures in gas turbines, were instrumented and employed for selected investment casting trials of NGV in vacuum in order to obtain thermal data. Lost wax process features and high variability complicate the achievement of thermal data. The measurement of temperatures during all the casting process (pre-heating of the mould, transfer to pouring chamber, high vacuum process and solidification), wax and ceramic clusters manipulation, positioning of the thermocouples and the high temperatures and variability of the process were the main difficulties of this work. The equipment for in-situ temperature measurement consisted of K and S type thermocouples and a standalone data-logger. Thermocouples were placed thoroughly during pre-casting process in specific locations of wax, shell and wrapping along the airfoils of the NGV. After several casting and simulation trials, material thermal properties, process parameters and boundary conditions were successfully adapted to fit the model to the experimental thermal measurements. Ni C Base 0.15 Material Property (units) Value MAR-M247 Thermal conductivity (W·m -1 ·K -1 ) 15-35 ∗ Density (kg·m -3 ) 7300-8600 ∗ Enthalpy (kJ/kg) 100-800 ∗ Viscosity (kg·m -1 ·s -1 ) 2-3.25·10 -3 ∗ Liquidus temperature ( o C) 1366 Solidus temperature ( o C) 1266 Mould Thermal conductivity (W·m -1 ·K -1 ) 0.4-1.7 ∗ Density (kg·m -3 ) 1860-1915 ∗ Specific heat (kJ·kg -1 ·K -1 ) 0.7-1.3 ∗ Emissivity 0.7 Insulation wrap Thermal conductivity (W·m -1 ·K -1 ) 0.1-0.5 ∗ Specific heat (kJ·kg -1 ·K -1 ) 0.9-1.3 ∗ Emissivity 0.7 Material Property (units) Value Metal-mould HTC (W·m -2 ·K -1 ) 200-2500 ∗ Mould-wrap HTC (W·m -2 ·K -1 ) 100 Mould- enclosure HTC (W·m -2 ·K -1 ) 3 Wrap- enclosure HTC (W·m -2 ·K -1 ) 10.6 Enclosure Emissivity 0.9 Others Units Value Melt pouring velocity (mm/s) 1700 Melt temperature ( o C) 1549 Pre-heating temperature ( o C) 1200 ABSTRACT THERMAL Thermo-physical properties and boundary conditions used in the thermal model. The chemical c Temperat conductiv The NGV prod POROSITY Temperature-time plots for metal, mould (shell) and insulation wrap: comparison of the thermal model prediction with the experimental results. Schematic presentation of the porosity prediction model. Porosity prediction by the ProCast model (left) and optical microscop defined areas (right). The location of the analyzed section in the NGV Porosity results from simulation (middle) and experimental analysis (left and right hand sides). Top, middle and bottom sections of the hollow vane are considered. The locations of the analyzed section in the NGV are marked by red circles.. Leading edge Middle part Trailing edge Local porosity fraction [%] 0.63 3.07 no porosity Average pore size [μm] 20.4 22.0 - Area Top M Average porosity fraction [%] 0.06 Average pore size [μm] 19 Modeling Tool asting Morelli 2 , A. Carosi 3 , O. Koeser 4 , S. Milenkovic 5 , I. Sabirov 5 , J. LLorca 5 n Switzerland,CH-1950 Sion, 3 Precicast Novazzano SA, CH-6883, Novazzano, A Materials Institute, Madrid, Spain Cr Co Mo W Ta Al Ti Hf 8.4 10 0.7 10 3.1 5.5 1.05 1.4 EXPERIMENTS MODEL composition of the MAR-M247 Ni-based superalloy. Model of half shell with insulation wrapping. Positioning of thermocouples during wax assembly, ceramic process and wrapping. Registered thermal history of the specific locations in the cluster. ture dependent thermal vity for ceramic shell. Temperature dependent thermal conductivity for insulation wrap. Temperature dependent heat transfer coefficient at the metal-mould interface. duced by investment casting. Investment casting of NGV from Ni-based superalloys was simulated by means of the finite element model. The simulation strategy is targeted to predict the heat exchange during solidification and cooling and the porosity. The casting assembly, consisting of the hollow ceramic mould with NGV-shape interior and insulation wrap, is created and meshed. The thermo-physical parameters and boundary conditions are defined for all the parts of the casting assembly, and simulation is carried out using ProCast. Experimental casting trials are performed for validation of the developed models. The thermal history of the metal and the insulation wrap during investment casting was accurately predicted. The critical thermal-physical parameters of the casting system were obtained either from the literature or by an inverse simulation procedure by comparing the simulation results for simple casting geometries with experimental data. The hot spots and areas with enhanced porosity which are located in the thickest parts of the NGV were accurately predicted. In addition, the porosity predictions were in good agreement with the experimental results in many NGV areas. The shortcomings of the porosity predictions include a slight underestimation of porosity in the hot spots and an overestimation of shrinkage porosity in the thinnest parts of the NGV. It is concluded that the developed modelling tool can be successfully utilized for further improvement of NGV design allowing to minimize the number of casting trials. MODEL Comparison of experimental measurements from metal with the thermal model prediction in the temperature range between liquidus (1366 °C) and solidus (1266 °C).. py images of porosity for the V is marked by red circle Porosity prediction by the ProCast model (left) and optical microscopy images of porosity for defined areas (right). Area a b c d Local porosity fraction [%] 0.19 4.87 4.82 0.14 Average pore size [μm] 32 113 27 29 Location of the hot spot in the solid vane represented in the figure on the left Middle Bottom 0.08 0.08 17 15 CONCLUSIONS T M B