Search Results for CALPHAD framework

This article describes the integration of thermodynamic modeling, mobility database, and phase-transformation crystallography into phase-field modeling and its combination with transformation texture modeling to predict phase equilibrium, phase transformation, microstructure evolution, and transformation texture development during heat treatment of multicomponent alpha/beta and beta titanium alloys. It includes quantitative description of Burgers orientation relationship and path, discussion of lattice correspondence between the alpha and beta phases, and determination of the total number of Burgers correspondence variants and orientation variants. The article also includes calculation of the transformation strain with contributions from defect structures developed at alpha/beta interfaces as a precipitates grow in size. In the CALculation of PHAse Diagram (CALPHAD) framework, the Gibbs free energies and atomic mobilities are established as functions of temperature, pressure, and composition and serve directly as key inputs of any microstructure modeling. The article presents examples of the integrated computation tool set in simulating microstructural evolution.

This article focuses on the industrial applications of phase diagrams. It presents examples to illustrate how a multicomponent phase diagram calculation can be readily useful for industrial applications. The article demonstrates how the integration of a phase diagram calculation with kinetic and microstructural evolution models greatly enhances the power of the CALPHAD approach in materials design and processing development. It also discusses the limitations of the CALPHAD approach.

This article focuses on the modeling and simulation of diffusion-controlled processes related to both materials processing such as heat treatments, and materials degradation from a practical perspective by using the one-dimensional (1-D) sharp interface approach. It describes various diffusion simulation models, such as one-phase simulations, moving phase-boundary simulations, and dispersed system simulations. The article presents case studies that illustrate some examples where diffusion simulations have been applied to industrial-based problems, with an emphasis on the approaches used and the lessons learned from performing such simulations.

This article discusses the fundamental aspects of phase-field microstructure modeling. It describes the evolution of microstructure modeling, including nucleation, growth, and coarsening. The article reviews two approaches used in the modeling nucleation of microstructure: the Langevin force approach and explicit nucleation algorithm. Calculation of activation energy and critical nucleus configuration is discussed. The article presents the deterministic phase-field kinetic equations for modeling growth and coarsening of microstructure. It also describes the material-specific model inputs, chemical free energy and kinetic coefficients, for phase-field microstructure modeling. The article provides four examples that illustrate some aspects of phase-field modeling.

This article provides guidelines for the assessment of model quality in materials science and engineering. It discusses the fundamentals of model quality assessment and the calibration of mechanistic material models. The article reviews the considerations for the model verification during software implementation planning to identify suitable programs, software components, and programming languages. It describes the validity tests used in model validation, including boundary-value tests, degenerate problem tests, sensitivity tests, and benchmarking. The article also presents an example of model calibration, verification, and validation for the prediction of martensite start temperature of steels.

Additive manufacturing (AM) has gained increased significance and has been adopted across many industries for various applications. Specific net-shape AM fabrication methods, such as laser powder-bed fusion (LPBF), have matured significantly, leading to aerospace sector R&D focused on the feasibility of using flagship alloys to manufacture complex components. This article presents one example of an aluminum alloy design tailored for laser powder-bed fusion AM. It discusses the integrated computational materials engineering design approach. The article also presents the design for high-strength, high-temperature aluminum alloys.

Integrated computational materials engineering refers to the use of computer simulations that integrate mathematical models of complex metallurgical processes with computer models used in component and process design. This article outlines an example of a computer-aided engineering tool, such as virtual aluminum castings (VAC), developed and implemented for quickly developing durable cast aluminum power train components. It describes the procedures for the model development of the VAC system. These procedures include linking the manufacturing process to microstructure, linking microstructures to mechanical properties, linking material properties to performance prediction, and model validation and integration into the engineering process. The article discusses the benefits of the VAC system in process selection, process optimization, and improving the component design criteria.

Modeling of structure formation in casting of alloys involves several length scales, ranging from the atomic level to macroscopic scale. Intermediate length scales are used to define the microstructure of the growing phases and the grain structure. This article discusses the principles and applications of the phase field method and the cellular automaton method for modeling the direct evolution of structure at the intermediate length scales, where transport phenomena govern the spatial and temporal evolution of the structure that involves nucleation and growth.

This article focuses on the intermediate length scales, where transport phenomena govern the spatial and temporal evolution of a structure. It presents the cellular automaton (CA) and phase field (PF) methods that represent the state of the art for modeling macrostructure and microstructure. The article describes the principles of the PF method and provides information on the applications of the PF method. The CA model is introduced as a computationally efficient method to predict grain structures in castings using the mesoscopic scale of individual grains. The article discusses the coupling of the CA to macroscopic calculation of heat, flow, and mass transfers in castings and applications to realistic casting conditions.

This article provides an overview of integrated weld modeling and presents strategic goals for the welding industry. It discusses the fundamentals of the underlying physics and the methodologies to solve the same. The article presents the pioneering work done to predict the heat-affected zone and weld metal microstructure in the early 1980s and 1990s. Applications of computational thermodynamics and kinetics tools to weld metal microstructure prediction for liquid-gas reactions and liquid-slag reactions that happen as a function of high-to-low temperature during fusion welding are discussed. The article also includes a brief discussion on weldability prediction, residual stress prediction, and distortion prediction. It concludes with information on the use of optimization methodologies.

This article describes the results obtained by Volmer, Weber, Farkas, Becker, and Doring, which constitute the classical nucleation theory. These results are the predictions of the precipitate size distribution, steady-state nucleation rate, and incubation time. The article reviews a nucleating system as a homogeneous phase using the classical nucleation theory, along with heterophase fluctuations that led to the formation of precipitates. It discusses the gas cluster dynamics using the kinetic approach to describe nucleation. The article presents key parameters, such as cluster condensation and evaporation rates, to describe the time evolution of the system. The predictions and extensions of the classical nucleation theory are discussed. The article also provides the limitations of classical nucleation theories in cluster dynamics.

This article provides an overview of integrated weld modeling and discusses the fundamentals of the underlying physics and methodologies involved in process modeling. It presents approaches for microstructure modeling that help to predict phase fractions as well as grain size in the heat-affected zone and weld metal region as a function of alloy composition and thermal cycles. The article discusses the uses of computational thermodynamic and kinetic tools. It describes the concept of performance modeling, whose goal relates to the prediction of weldability, geometrical distortion, and/or locked-in residual stress as a function of material, restraint, process, and process parameters as well as service temperature. Finally, the article presents a case study, evaluating the use of X-65 steels using the E-WeldPredictor tool.

Additive manufacturing (AM) provides exceptional design flexibility, enabling the manufacture of parts with shapes and functions not viable with traditional manufacturing processes. The two paradigms aiming to leverage computational methods to design AM parts imbuing the design-for-additive-manufacturing (DFAM) principles are design optimization (DO) and simulation-driven design (SDD). In line with the adoption of AM processes by industry and extensive research efforts in the research community, this article focuses on powder-bed fusion for metal AM and material extrusion for polymer AM. It includes detailed sections on SDD and DO as well as three case studies on the adoption of SDD, DO, and artificial-intelligence-based DFAM in real-life engineering applications, highlighting the benefits of these methods for the wider adoption of AM in the manufacturing industry.

This article focuses on the concepts involved in heat-transfer modeling, thermomechanical modeling, and microsegregation modeling of hot tearing. It discusses the modeling of solidification defects, namely, inclusion entrapment, segregation, shrinkage cavities, gas porosity, mold-wall erosion, and hot-tear cracks.

This article provides a general overview of additively manufactured steels and focuses on specific challenges and opportunities associated with additive manufacturing (AM) stainless steels. It briefly reviews the classification of the different types of steels, the most common AM processes used for steel, and available powder feedstock characteristics. The article emphasizes the characteristics of the as-built microstructure, including porosity, inclusions, and residual stresses. It also reviews the material properties of AM steel parts, including hardness, tensile strength, and fatigue strength, as well as environmental properties with respect to corrosion resistance, highlighting the importance of postbuild thermal processing.

This article describes the fundamental concepts of heat treatment simulation, including the physical events and their interactions, the heat treatment simulation software, and the commonly used simulation strategies. It summarizes material data needed for heat treatment simulations and discusses reliable data sources as well as experimental and computational methods for material data acquisition. The article provides information on the process data needed for accurate heat treatment simulation and the methods for their determination. Methods for validating heat treatment simulations are also discussed with an emphasis on the underlying philosophy for the selection and design of validation tests. The article also discusses the applications, capabilities, and limitations of heat treatment simulations via selected industrial case studies for a better understanding of the effect of microstructure, distortion, residual stress, and cracking in gears, shafts, and bearing rings.