This article reviews network models and their applications for the simulation of various physical phenomena related to grain-boundary migration. It discusses the steps involved in the implementation of two and three-dimensional network models, namely, acquisition and discretization of the microstructure, formulation of the equation of motion, and implementation of the topological transformations. The article presents examples that illustrate the simulation of physical phenomena to demonstrate the predictive power and flexibility of network models.

The microstructure that develops during the solidification stage of cast iron largely influences the subsequent solid-state transformations and mechanical properties of the cast components. This article provides a brief introduction of methods that can be used for simulating the solidification microstructure of cast iron. Analytical as well as numerical models describing solidification phenomena at both macroscopic and microscopic scales are presented. The article introduces macroscopic transport equations and presents analytical microscopic models for solidification. These models include the dendrite growth models and the cooperative eutectic growth models. The article provides some solutions using numerical models to simulate the kinetics of microstructure formation in cast iron. It concludes with a discussion on cellular automaton (CA) technique that can handle complex topology changes and reproduce most of the solidification microstructure features observed experimentally.

This article reviews the performance of power electronics components, namely, power rectifiers, insulated-gate bipolar transistors, metal-oxide semiconductor field-effect transistors, diodes, and silicon-controlled rectifiers. It provides information on induction heating power supplies with multiple heat stations, such as switching units and multiple (zone) outputs. The article describes power supply operational control and power supply protection circuits. It details duty cycle, power factor, and harmonics of power supplies. The article also describes system parameters, software analysis-calculations, human analysis-decisions, multiple system arrangements, and zone control systems for power supply selection. It provides information on the maintenance of induction power supplies, detailing the safety precautions to be taken and the need for routine inspection and servicing.

This article focuses on the technologies and applications of additive manufacturing (AM) in the oil and gas industry. It then presents the challenges of AM and the oil and gas industry. The article provides a detailed description of the critical steps in the AM process chain, including part selection, design optimization, and process planning, control, and inspection. Qualification and certification standardization is discussed, as is a commitment to reduce the carbon footprint of the manufacturing sector through AM. It ends with the future outlook of AM in the oil and gas industry.

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 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 summarizes the general features of microstructure evolution during the thermomechanical processing (TMP) of nickel-base superalloys and the challenges posed by the modeling of such phenomena. It describes the fundamentals and implementations of various modeling methodologies. These include JMAK (Avrami) models, topological models, and mesoscale physics-based models.

This article is a compilation of abbreviations and symbols related to metallography and microstructures.

This article focuses on two streams of the research on part consolidation (PC): PC in the conventional manufacturing context, and PC in the additive manufacturing (AM) context. It reviews the challenges of applying AM-PC potentials. The article includes research literature on the selection of part candidates for consolidation and summarizes the conversion of assembly design to consolidated design. Then, a holistic approach for supporting PC design is introduced with integrated modules of part filtering and fusion of parts. Details of the key techniques of the two modules are later introduced with a gas pedal example. Finally, emerging trends in PC research are discussed.

This article provides information on the general structural features and origins of metals. The characteristic structural features of single-phase metals and alloys, such as grain structure and substructure, are discussed. The article also describes the major types of multiphase structures and macrostructure of metals and alloys.

This article presents the analytics challenges in additive manufacturing. It discusses the types and applications of data analytics. Data analytics can be classified into four types: descriptive, diagnostic, predictive, and prescriptive. The diverse applications of data analytics and machine learning include design, process-structure-properties (PSP) relationships, and process monitoring and quality control. The article also presents tools used for data analytics.

This article discusses tools that are used for the systematic optimization of engineering designs. It focuses on the practical application of optimization technology in a computer-aided engineering environment. The article presents numerical optimization algorithms and provides some background on how these algorithms make decisions when searching for the optimal design. It also provides information on structural optimization, topology optimization, materials processing optimization, multidisciplinary optimization, and global optimization.

The diffraction pattern of any material contains structural and chemical property information that can be extracted using radial distribution function analysis. This article provides an introduction to the technique and presents several examples highlighting various ways in which it can be used. It begins with a discussion on the principles of diffraction and scattering and the effectiveness of x-ray, neutron, and electron energy sources for different types of measurements. It provides information on data collection and reduction and explains how to create atomic distribution plots from intensity and scattering angle data. The article also presents application parameters for defining short distances and background intensity and describes a procedure for generating pair distribution functions.