Superalloy 718 and Derivatives: Modeling & Data Analytics
Program Organizers: Joel Andersson, University West; Chantal Sudbrack, National Energy Technology Laboratory; Eric Ott, GE Additive; Zhongnan Bi, Central Iron and Steel Research Institute
Tuesday 8:00 AM
May 16, 2023
Room: Admiral
Location: Sheraton Pittsburgh Hotel at Station Square
Session Chair: Michael Fahrmann, Haynes International; Chantal Sudbrack, National Energy Technology Laboratory
8:00 AM Introductory Comments
8:05 AM Invited
Application of CALPHAD Based Tools to Modeling of Alloy 718: Paul Mason1; Carl-Magnus Lancelot2; Taiwu Yu1; Thomas Barkar2; Adam Hope1; 1Thermo-Calc Software Inc; 2Thermo-Calc Software AB
For forty years, CALPHAD based tools have been used to design alloys of industrial importance and gain insight into composition-process-structure-property relationships. This presentation will illustrate how such tools can be applied to alloy 718 and its derivatives for applications relevant to solidification, heat treatment and additive manufacturing. Examples will be given of calculations made under equilibrium and non-equilibrium conditions to predict phase stability, phase transformation temperatures and thermophysical properties, such as density, coefficients of thermal expansion and thermal conductivity which can be used in an ICME framework. The simulation of precipitation kinetics for non-isothermal heat treatments to predict volume fraction, coarsening and average size of precipitates will also be described along with how such calculations can be extended to model yield strength. Finally, examples will be given of how CALPHAD can be incorporated to improve the accuracy of finite element simulations for additive manufacturing.
8:35 AM
Multi-variate Process Models for Predicting Site-specific Microstructure and Properties of Inconel 706 Forgings: Nishan Senanayake1; Reese Capo1; Tiffany Dux2; Jennifer Carter1; 1Case Western Reserve University; 2Howmet Aerospace Forgings
The performance of Inconel 706 forgings hinges on the careful design of the thermomechanical history to promote distributions of oft-dependent microstructural features. Establishing predictive process-structure-property (PSP) models to tailor manufacturing routes requires immense cost due to the time and cost-consuming tasks of quantifying statistically significant observations of different predictor and property metrics. Power analysis indicates that for a simple multivariate linear model of one performance metric, P, dependent on six input process predictors (k = 6) (i.e., P = f(k1, k2, … k6)) with 80% predictive power would require over 120 observations; to predict n performance metrics (P1, P2, ...Pn), a statistical study protocol would require 120n observations (ANOVA would require 175n). Most processing and microstructure predictors and property metrics are observed/measured destructively. This motivates the development of high-throughput measurements of both experimental approaches and physics-based simulations that enable dimensionality reduction of the predictor space (i.e., time and temperature are not independent predictors of diffusion-mediated metrics such as precipitate fraction). In this paper, we highlight how thermal profiles from finite element simulations (processing predictors) can establish time-temperature boundary conditions for CALPHAD predictions of the combined 𝛾′, 𝛾′′ precipitate distribution in Inconel 706 (structure predictors). Experimental observations of these precipitate distributions allow for the tailoring of the CALPHAD interfacial energy. In this manner, a 25x reduction in the number of physical observations of 𝛾′ and 𝛾′′ distribution (100 to 4) still results in site-specific PSP models of forged parts with 80% predictive power.
8:55 AM
Linking Stress Rupture Properties to Processing Parameters of HAYNES® 718 Nickel Superalloy via Machine Learning: David Farache1; George Nishibuchi1; John Gulley1; Sebastian Elizondo1; Alex Post2; Kyle Stubbs2; Keith Kruger2; Arun Mannodi-Kanakkithodi1; Michael Titus1; 1Purdue University; 2Haynes International
Requirements of stress rupture life and elongation of nickel alloy 718 are often prescribed by specification AMS5596 or AMS5663, which broadly state that the stress rupture life and elongation must exceed 23 h and 4% at 649 ºC (1200 ºF), respectively. Variability in product stress-rupture life can range from less than 2 h to more than 1000 h, which can cause significant delays for testing, shipping, and delivery of product. In this work, we predict the stress-rupture life and elongation of HAYNES® 718 sheet product utilizing machine learning models. The models utilized data from 448 lots of material and inputs including composition, room temperature mechanical property data, processing data such as finish gauge, total reduction, final reduction, rule of mixture average properties including density, electronegativity, and bulk and Young’s modulus, and environmental factors such as daily maximum and minimum temperatures and humidity. Different sets of input features were chosen from the highest absolute Pearson correlation values, Gini coefficient, SHAP, and SISSO analysis, and four separate random forest models were trained using an 80%-20% split between training and testing data. The resulting mean squared errors of best performing models of stress-rupture life and elongations were 102 h and 7.2%, respectively. Input features of highest importance were observed to be room temperature tensile properties, finish gauge, and tramp elements such as Co, P, and Si. These models can be utilized to accelerate acceptance testing of 718 product by identifying product exhibiting anomalously low or high creep rupture life and elongation.
9:15 AM
Competitor Ti-comprising Refractory High Entropy Alloys to Superalloy 718 for Aeroengine Applications: Tanjore Jayaraman1; Ramachandra Canumalla2; 1University of Michigan-Dearborn; 2Weldaloy Specialty Forgings
Superalloy 718 and its derivatives are ubiquitous to aeroengine applications owing to their excellent formability, ultra-high-strength, good thermal stability, adequate weldability, and so forth. However, currently, the relatively lighter Ti-comprising high entropy alloys, having a unique combination of ambient and elevated temperature mechanical properties and corrosion resistance, are projected as potential competitors to superalloy 718 and their derivatives. We analyzed the data of several Ti-comprising high entropy alloys available in the literature by a novel combination of multiple attribute decision making (MADM) and advanced statistics— hierarchical clustering (HC) and principal component analysis (PCA)—to identify the probable competitors to superalloy 718 for aeroengine applications. The ranks assigned by six MADMs, chosen for the investigation, including ARAS (additive ratio assessment), MEW (Multiplicative exponent weighing), OCRA (operational competitiveness ratio), ROVM (range of value method), SAW (simple additive method), and WEDBA (weighted Euclidean distance-based approach), were concordant. PCA consolidated the MADM ranks of the alloys, while HC identified similar top-ranked alloys. The analyses identify the Ti-comprising high entropy alloys having properties comparable to superalloy 718 and reveal the potential of the Ti-comprising high entropy alloys to substitute critical parts in aeroengines.
9:35 AM
An ICME Framework to Predict the Microstructure and Yield Strength of INCONEL 718 for Different Heat Treatments: Taiwu Yu1; Thomas Barkar2; Carl-Magnus Lancelot2; Paul Mason1; 1Thermo-Calc Software Inc; 2Thermo-Calc Software AB
The superalloy 718 stands out for its excellent manufacturability and strength at ambient temperature. In most studies currently, people tried to improve the mechanical properties of the 718 alloy through adjusting different processing conditions such as solution annealing temperature, aging temperature and holding time, and the amount of intermediate cold work. Such study could be expensive and time consuming. In this study, we would like to build an ICME framework to investigate the microstructural stability and mechanical properties through CALPHAD method as well as TC-PRISMA tools incorporated in Thermo-Calc Software. In this study, the formation of secondary phases such as gamma prime-phase, gamma double prime-phase, and delta-phase as well as consequent mechanical properties of the microstructure with respect to the processed conditions has been studied. The evolution of precipitates can be characterized by TC-PRISMA tool with TC databases. Furthermore, Reppich’s model is applied to predict the precipitate strengthening of the alloy, and grain boundary and solid solution strengthening mechanisms are also quantified to predict the yield strength with respect to different processing. The framework can be built by the Thermo-Calc software to design alloys in terms of the processing to obtain properties needed.
9:55 AM Break