In conventional processing, metals go through multiple manufacturing steps including casting, plastic deformation, and heat treatment to achieve the desired property. In additive manufacturing (AM) the same target must be reached in one fabrication process, involving solidification and cyclic remelting. The thermodynamic and kinetic differences between the solid and liquid phases lead to constitutional undercooling, local variations in the solidification interval, and unexpected precipitation of secondary phases. These features may cause many undesired defects, one of which is the so-called hot cracking. The response of the thermodynamic and kinetic nature of these phenomena to high cooling rates provides access to the knowledge-based and tailored design of alloys for AM. Here, we illustrate such an approach by solving the hot cracking problem, using the commercially important IN738LC superalloy as a model material. The same approach could also be applied to adapt other hot-cracking susceptible alloy systems for AM.

Heat exchangers (HXs) have gained increasing attention due to the intensive demand of performance improving and energy saving for various equipment and machines. As a natural application, topology optimization has been involved in the structural design of HXs aiming at improving heat exchange performance (HXP) and meanwhile controlling pressure drop (PD). In this paper, a novel multiphysics-based topology optimization framework is developed to maximize the HXP for 2D cross-flow HXs, and concurrently limit the PD between the fluid inlet and outlet. In particular, an isogeometric analysis solver is developed to solve the coupled steady-state Navier-Stokes and heat convection-diffusion equations. Non-body-fitted control mesh is adopted instead of dynamically remeshing the design domain during the evolution of the boundary interface. The method of moving morphable voids is employed to represent and track boundary interface between the hot and the remaining regions. In addition, various constraints are incorporated to guarantee manufacturability of the optimized structures with respect to practical considerations in additive manufacturing, such as removing sharp corners, controlling channel perimeters, and minimizing overhangs. To implement the iterative optimization process, the method of moving asymptotes is employed. Numerical examples show that the HXP of the optimized structure is greatly improved compared with its corresponding initial design, and the PD between the fluid inlet and outlet is controlled concurrently. Moreover, a smooth boundary interface between the channel and the cold fluid, and improved manufacturability are simultaneously obtained for the optimized structures.

Hot cracking is one of the major defects that can occur in laser-based additive manufacturing. During the terminal stage of solidification, hot cracking initiates when the semi-solid matrix builds up excessive negative (tensile) pressure induced by thermal contraction. This study presents a new quantification of the trends in the above process: we estimate the volume change brought by thermal deformation through a perspective of energy conservation and combine it with the intergranular volume change induced by grain growth and liquid backflow to derive a criterion for hot-cracking initiation. Based on this, we propose two modified indexes that build on prior work, namely: (1) vertical bar dT/d root fs vertical bar 1/root 1-beta and (2) vertical bar dT/d root fs vertical bar 1/E. Here, T is temperature, f(s) is the solid fraction of the semi-solid region, beta is the shrinkage factor and (E) over bar is the material toughness near the solidus temperature. Evaluating these indexes against experimental data reveals that hot-cracking susceptibility is strongly correlated with the second index and indeed is a function of material high-temperature toughness. (C) The Minerals, Metals \& Materials Society and ASM International 2022

A major factor in determining the fatigue life of fracture-critical parts is the effect of process-induced porosity. Prediction of critical pore size in different process regimes of a laser powder bed fusion (L-PBF) processed part could provide invaluable information for process development and qualification and certification efforts. However, the amount of data required to accurately populate the pore size distribution to predict the critical pore size is still unknown. To address this gap, the present study utilizes extreme value statistics to determine the data required to characterize porosity in the L-PBF additively manufactured parts fabricated using different processing conditions. 2D cross-sectional porosity data obtained via optical microscopy was used as an example to demonstrate the statistical modeling approach. The statistical modeling described here can also be applied to other manufacturing processes and other types of data such as 3D porosity measurements, grain size, and inclusions.

In the laser powder bed fusion additive manufacturing of metals, extreme thermal conditions create many highly dynamic physical phenomena, such as vaporization and recoil, Marangoni convection, and protrusion and keyhole instability. Collectively, however, the full set of phenomena is too complicated for practical applications and, in reality, the melting modes are used as a guideline for printing. With an increasing local material temperature beyond the boiling point, the mode can change from conduction to keyhole. These mode designations ignore laser-matter interaction details but in many cases are adequate to determine the approximate microstructures, and hence the properties of the build. To date no consistent, common, and coherent definitions have been agreed upon because of historic limitations in melt pool and vapor depression morphology measurements. In this review, process-based definitions of different melting modes are distinguished from those based on postmortem evidence. The latter are derived mainly from the transverse cross sections of the fusion zone, whereas the former come directly from time-resolved x-ray imaging of melt pool and vapor depression morphologies. These process-based definitions are more strict and physically sound, and they offer new guidelines for laser additive manufacturing practices and create new research directions. The significance of the keyhole, which substantially enhances the laser energy absorption by the melt pool, is highlighted. Recent studies strongly suggest that stable-keyhole laser melting enables efficient, sustainable, and robust additive manufacturing. The realization of this scenario demands the development of multiphysics models, signal translations from morphology to other feasible signals, and in-process metrology across platforms and scales.

In the laser powder bed fusion additive manufacturing of metals, extreme thermal conditions create many highly dynamic physical phenomena, such as vaporization and recoil, Marangoni convection, and protrusion and keyhole instability. Collectively, however, the full set of phenomena is too complicated for practical applications and, in reality, the melting modes are used as a guideline for printing. With an increasing local material temperature beyond the boiling point, the mode can change from conduction to keyhole. These mode designations ignore laser-matter interaction details but in many cases are adequate to determine the approximate microstructures, and hence the properties of the build. To date no consistent, common, and coherent definitions have been agreed upon because of historic limitations in melt pool and vapor depression morphology measurements. In this review, process-based definitions of different melting modes are distinguished from those based on postmortem evidence. The latter are derived mainly from the transverse cross sections of the fusion zone, whereas the former come directly from time-resolved x-ray imaging of melt pool and vapor depression morphologies. These process-based definitions are more strict and physically sound, and they offer new guidelines for laser additive manufacturing practices and create new research directions. The significance of the keyhole, which substantially enhances the laser energy absorption by the melt pool, is highlighted. Recent studies strongly suggest that stable-keyhole laser melting enables efficient, sustainable, and robust additive manufacturing. The realization of this scenario demands the development of multiphysics models, signal translations from morphology to other feasible signals, and in-process metrology across platforms and scales.

Grain boundaries undergo thermally-activated, first-order transitions that result in discontinuous changes of interfacial properties. Importantly, grain boundary transitions lead to changes in bulk material prop-erties (e.g., embrittlement) and/or behavior (e.g., abnormal grain growth). Numerous studies have been completed on the equilibrium states of grain boundaries and their transitions (i.e., complexion transi-tions), but there have been far fewer investigations of complexion transition kinetics; complexion transi-tions occur on the atomic-scale and are therefore challenging to detect experimentally. In this work, a 3D Potts grain growth model with stochastic complexion transitions was employed to investigate complexion transition kinetics. A Johnson-Mehl-Avrami-Kolmogorov (i.e., JMAK) approach was used to extract nucle-ation and growth rates (i.e., transformation rates) , while point process analyses and correlation functions were used to infer complex interrelated nucleation and growth events. Time-temperature-transformation (TTT) diagrams, in particular grain-boundary complexion, transformed grain, and abnormal grain TTT di-agrams, were constructed to summarize the progress of complexion-related transformations. Such dia-grams relate complexion-induced grain growth to the underlying complexion transitions and, in the case of abnormal grain growth (AGG), permit one to assess the role of AGG as a temperature-dependent, time -displaced indicator of complexion transitions. Overall, this work details a theoretical framework that can be used to better understand complexion transition kinetics as well as to develop tools for the design of bulk microstructures.(c) 2022 Acta Materialia Inc. Published by Elsevier Ltd. All rights reserved.