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At least 379 records · Page 21
All sourcesNASA NTRSDOE OSTI
DOE OSTI2017

Understanding the role of carbon atoms on microstructure and phase transformation of high Nb containing TiAl alloys

The microstructure and solidification behavior of high Nb containing TiAl alloys with the composition of Ti-46Al-8Nb-xC (x = 0.1, 0.7, 1.4, 2.5 at.%) prepared by arc-melting method have been investigated in this work. The results give evidence that the addition of carbon changes the solidification behavior from solidification via the β phase to the peritectic solidification. And carbon in solid solution enriches in the α{sub 2} phase and increases the microhardness. As the carbon content increases to 1.4 at.%, plate-shape morphology carbides Ti{sub 2}AlC (H phase) precipitate from the TiAl matrix which leads to the refinement microstructure. By aging at 1173 K for 24 h after quenching treatment, fine needle-like and granular shape Ti{sub 3}AlC (P phase) carbides are observed in the matrix of Ti-46Al-8Nb-2.5C alloy, which distribute along the lamellar structure or around the plate-shape Ti{sub 2}AlC. Transmission electron microscope observation shows that the Ti{sub 3}AlC carbides precipitate at dislocations. The phase transformation in-situ observations indicate that the Ti{sub 2}AlC carbides partly precipitate during the solid state phase transformation process. - Highlights: •Carbon changes the solidification behavior from β phase to peritectic solidification. •Dislocations in solution treated γ phase act as nucleation sites of Ti{sub 3}AlC precipitations. •Ti{sub 3}AlC precipitates as fine needle-like or granular shape in the solution treated matrix. •Ti{sub 2}AlC carbides precipitate during the solid state phase transformation process.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Selective laser melting of Co-29Cr-6Mo alloy with laser power 180–360 W: Cellular growth, intercellular spacing and the related thermal condition

Highlights: • Increasing laser power increases the track size but not the track shape significantly. • Solidification mode and texture are similar over the range of laser power used. • Intercellular spacing is not affected by laser power but decreases slightly with growth angle. • Thermal gradient and cooling rate have been estimated to be ~ 2 × 10{sup 7} K/m and ~ 2 × 10{sup 6} K/s, respectively. - Abstract: A feature of solidification during selective laser melting (SLM) is cellular growth. Thus, how growth direction and cell size may be affected and possibly be controlled by SLM parameters are important to be understood. Furthermore, intercellular spacing (λ{sub 1}) is suggestive of the thermal condition during solidification which needs to be known for advancing the understanding of SLM. In this work, grain solidification orientation and λ{sub 1} of a Co-Cr-Mo alloy produced by SLM over a range of laser power (P = 180–360 W) with other parameters kept unchanged have been evaluated. It has been found that the overall preferred growth of cellular solidification is not significantly affected by P. This is because, over the range of P values used, the shape of track did not change sufficiently to result in a significant variation of growth direction during epitaxial growth. It has also been found that P does not affect λ{sub 1}. This suggests, since growth rate (R) relates to scan speed (v) which is unchanged, P does not significantly affect the temperature gradient of the solidification front (G). From the measured λ{sub 1} and estimated R, G and thus cooling rate ( T-dot ) can be estimated following the commonly used primary arm spacing model. The estimated G and T-dot which could not be directly measured will be compared with those predicted by simulation and the estimated T-dot will also be compared with those determined by using an emperical relationship from literature.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Effect of Solute Elements on Boron Segregation in Boron-Containing Steels

The addition of boron to steel alloys results in an increase in both hardenability and casting defects. The casting difficulties are predicted to stem from a metatectic reaction, δ + γ → L + γ, where a fully solidified material begins to locally remelt as the temperature decreases. Another possible source of casting defects is a boride-rich phase that is predicted to remain liquid at low temperatures. To experimentally determine which reaction is the likely source of the casting defects, the predicted reactions and the effect of solute elements on those reactions are investigated. Levitation zone melting is used to control segregation in a ternary Fe–C–B alloy and a commercial 22MnB5 alloy. Carbon segregation and a peritectic reaction result in a peritectic jump during directional solidification where the first directionally solidified (DS) zone undergoes δ-bcc solidification followed by a peritectic jump to steady state planar solidification of γ-fcc in the second DS zone. The presence of other solute elements in the zone melted 22MnB5 alloy lead to a breakdown in the planar solidification front before steady state solidification could be achieved in the second DS zone. With a cellular solid/liquid interface, boron-rich intercellular liquid formed low melting iron boro-carbide particles. The controlled solidification conditions in a levitation zone melter were unable to prevent ~0.003 wt% boron from segregating to high enough levels to form boride particles. Therefore, it is likely that during commercial casting, the formation of the low melting boride phase from interdendritic segregation is a key source of the casting issues.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Synergistic Effect of Nitrogen and Refractory Material on TiN Formation and Equiaxed Grain Structure of Ferritic Stainless Steel

The effect of nitrogen content on the formation of an equiaxed solidification structure of Fe-16Cr steel was investigated. Moreover, two different kinds of refractory materials, i.e., alumina and magnesia, were employed to control the type of oxide inclusion. The characteristics of TiN(-oxide) inclusions were quantitatively analyzed in both molten steel and solidified samples. When the melting was carried out in the alumina refractory, the grain size continuously decreased with increasing nitrogen content. However, a minimum grain size was observed at a specific nitrogen content (approx. 150 ppm) when the steel was melted in the magnesia refractory. Most of the single TiN particles had a cuboidal shape and fine irregularly shaped particles were located along the grain boundary due to the microsegregation of Ti at the grain boundary during solidification. The type of TiN-oxide hybrid inclusion was strongly affected by the refractory material where Al{sub 2}O{sub 3}-TiN and MgAl{sub 2}O{sub 4}-TiN hybrid-type inclusions were obtained in the alumina and magnesia refractory experiments, respectively. The formation of oxide inclusions was well predicted by thermochemical computations and it was commonly found that oxide particles were initially formed, followed by the nucleation and growth of TiN. When the nitrogen content increased, the number density of TiN linearly increased in the alumina refractory experiments. However, the number of TiN exhibits a maximum at about [N] = 150 ppm, at which a minimum grain size was obtained in the magnesia refractory experiments. Therefore, the larger the number density of TiN, the smaller the primary grain size after solidification. The number density of TiN in the steel melted in the magnesia refractory was greater than that in the steel melted in the alumina refractory at given Ti and N contents, which was due to the lower planar lattice disregistry of MgAl{sub 2}O{sub 4}-TiN interface rather than that of Al{sub 2}O{sub 3}-TiN interface. When ∆T{sub TiN} (= difference between the TiN precipitation temperature and the liquidus of the steel) was 20 K to 40 K, the number density of effective TiN was maximized and thus, the grain size was minimized after solidification. Finally, although most of the TiN particles were smaller than 1 μm in the molten steel samples irrespective of the nitrogen content, TiN particles larger than 10 μm were observed in the solidified samples when the nitrogen content was greater than 150 ppm. The growth of TiN particles during melting and solidification was well predicted by the combinatorial simulation of the ‘Ostwald ripening model’ based on the Lifshitz–Slyozov–Wagner theory in conjunction with the ‘Diffusion controlled model’ using Ohnaka’s microsegregation equation.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Modeling of Crucial Process Parameters for the Continuous Improvement of Special Steels at the Stomana Plant

In this study, a heat transfer model that takes under consideration the micro-segregation phenomena and has been extensively deployed for solidification studies concerning the plant casters is also applied to show the casting speed and superheat effects upon internal soundness. Τhe solidification path of C45R, 42CrMo4, S355 grades was simulated using Thermocalc{sup ®} and DICTRA software in order to examine the phases formed in crucial process temperature windows for the casting. Coupled Heat Transfer/Simple Micro-Segregation Model software has been deployed to simulate the effect of cooling rate on solidus temperature, and solid fraction during solidification. The solidus temperature results computed by the HT/SM and DICTRA were found to be in good agreement. However, the differences in the predicted solidification fractions may derive from the fact that DICTRA uses an average cooling rate whereas the heat transfer SM model takes into account also the local cooling rates in the solidification progress.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Influence of geometry on columnar to equiaxed transition during electron beam powder bed fusion of IN718

Correlation between spot-melt scan parameters (linear spot-density aka areal energy density), build geometry, and solidification microstructure evolution (columnar vs equiaxed) in a powder bed fusion technology is investigated. It is shown that to maintain the equiaxed solidification microstructure evolution in electron beam powder bed additive manufacturing (AM), the areal energy density per layer needs to be scaled with respect to the 2D cross-sectional area of the layer being melted. Samples with two different cross-sectional areas (40 × 40 mm and 20 × 20 mm) have been fabricated with varying areal energy densities. For a given square cross-section (20 × 20 mm), increasing the areal energy density (4.8 MJ/sq.m to 14.7 MJ/sq.m) transitioned the solidification microstructure from columnar to equiaxed. The observed microstructure data (Electron Back Scattered Diffraction - EBSD) is quantified by calculating the principal component (PC) score using a spatial statistics methodology. The sample with equiaxed grains is found to have a low PC score while the sample with columnar grain had a high PC score. A semi-analytical model is used to simulate the heat transfer and the local solidification conditions as a function of processing parameters (linear spot-density). The result from the heat transfer model is correlated with previously quantified microstructure data. Space-Time analysis of the melt pattern is done and correlated with the observed microstructure. In addition, from the findings, appropriate parameters have been used to additively manufacture a turbine blade with site-specific or hybrid solidification microstructure (traditional fabrication possible via a patented method of localized cold working and heat treatment).

36 MATERIALS SCIENCE↗
DOE OSTI2023

Leveraging the digital thread for physics-based prediction of microstructure heterogeneity in additively manufactured parts

A major limitation of additive manufacturing (AM) processes is that local conditions of material deposition frequently lead to unintentional heterogeneities in microstructure and properties within a single component, despite nominally uniform process conditions. Up to now, there has been no way to a priori determine the distribution of these heterogeneities, requiring expensive trial-and-error approaches to fabrication, testing, and characterization. Here, a physics-based framework for creating a digital representation of the laser powder bed fusion (PBF) process is proposed to predict the variation in solidification behavior that leads to heterogeneous microstructures in an as-built part. By leveraging in situ process data stored in the part’s digital thread, the scan path and process parameters were input into a heat transfer model which predicted solidification data at the melt pool scale. A two-step unsupervised clustering algorithm was used to first cluster the local solidification conditions (12.5µm 3 voxels) and then to cluster the regional behavior on the scale of multiple scan passes and print layers (250µm 3 super-voxels). This process was used to identify regions with similar solidification characteristics for multiple locations in a Stainless Steel 316-L component. The corresponding as-built part was sectioned and characterized using electron backscatter diffraction (EBSD). Quantitative analysis of the pole figures confirmed that the predicted regions of heterogeneity in the solidification conditions corresponded with differences in the observed microstructure. In conclusion, this work shows a viable path for estimating the microstructural heterogeneity for additively manufactured parts to either limit microstructural variation throughout a part or to enable functionality-based variation of the microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Non-intrusive data-driven model reduction for differential–algebraic equations derived from lifting transformations

In this paper we present a non-intrusive data-driven approach for model reduction of nonlinear systems. The approach considers the particular case of nonlinear partial differential equations (PDEs) that form systems of partial differential–algebraic equations (PDAEs) when lifted to polynomial form. Such systems arise, for example, when the governing equations include Arrhenius reaction terms (e.g., in reacting flow models) and thermodynamic terms (e.g., the Helmholtz free energy terms in a phase-field solidification model). Using the known structured form of the lifted algebraic equations, the approach computes the reduced operators for the algebraic equations explicitly, using straightforward linear algebra operations on the basis matrices. The reduced operators for the differential equations are inferred from lifted snapshot data using operator inference, which solves a linear least squares regression problem. The approach is illustrated for the nonlinear model of solidification of a pure material. The lifting transformations reformulate the solidification PDEs as a system of PDAEs that have cubic structure. The operators of the lifted system for this solidification example have affine dependence on key process parameters, permitting us to learn a parametric reduced model with operator inference. Numerical experiments show the effectiveness of the resulting reduced models in capturing key aspects of the solidification dynamics.

42 ENGINEERING↗
DOE OSTI2024

Considering interplay between multiple physical phenomena to elucidate single crystal-like texture, phase transformations, and mechanical behavior of directed energy deposited SS316L

A widespread implementation of large scale additive manufacturing (AM) processes, such as wire arc-directed energy deposition (WA-DED) AM can transform the current manufacturing supply chain networks. Naturally, such implementation requires control of the microstructural attributes, such as texture and phase evolution in the processed alloys. Currently, the texture evolution in fusion-based AM (F-BAM) processes is majorly rationalized by the phenomena occurring only during solidification. However, such rationalization is insufficient for understanding the evolution of primary and secondary crystallographic orientations, and consequently, fails to offer a comprehensive understanding and control of overall texture in F-BAM processed alloys. To this end, we report a single crystal (SX)-like texture in WA-DED processed SS316L for the first time. Furthermore, we assess the physical phenomena that may lead to such unique microstructural evolution during WA-DED AM. Subsequently, using microstructural characterization spanning the build height and thermomechanical simulations we investigate the effect of competitive growth and epitaxial growth occurring during solidification and thermally induced plastic deformation occurring post solidification on the overall texture of WA-DED processed SS316L. A spatial variation in solidification pathway is also established and correlated with variation in undercoolings across the build. Tensile tests revealed a strong orientation dependence of deformation mechanisms with over 110% elongation to failure of specimens deformed along <011>. Such anisotropy is rationalized using Schmid's analysis of dislocation slip and deformation twinning. Importantly, overall, the mechanisms outlined in this work will facilitate an enhanced understanding and subsequent control of texture evolution, solidification behavior and mechanical behavior of WA-DED processed steels.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multiscale and Machine Learning Modeling for Process-informed Microstructure Prediction in Additively Manufactured Materials using MALAMUTE

The Advanced Materials and Manufacturing Technologies (AMMT) program under the Department of Energy Office of Nuclear Energy aims to develop and qualify additively manufactured materials for nuclear applications. One key challenge to this is the microstructural variability observed in the additively manufactured products and their impact on the properties and performance of the material in extreme environments. AMMT is using a combination of high-throughput experimental and modeling techniques to accelerate qualification. Conventionally, in-situ and ex-situ characterizations and testing are performed to correlate different aspects of the additive manufacturing process to the final product and its performance. However, adopting a trial-and-error approach to experimentally evaluate the vast range of process parameters required to capture microstructural variability is cost-prohibitive. Modeling and simulation provide a comparatively inexpensive way to understand and correlate the microstructural evolution to the processing conditions. The modeling and simulation work-packages within the AMMT program aims to use physics-based and machine learning models to develop a digital twin for additive manufacturing that can correlate the process conditions to the final product and establish a process-structure-property-performance (PSPP) correlation. The melting and subsequent solidification that occurs during the additive process is a complex phenomenon that requires multiscale multiphysics analysis. This work package focuses on understanding the role of process variabilities on the unique microstructural characteristics of additively manufactured materials. Microstructural features at the subgrain level, such as compositional micro-heterogeneity and dislocation cells, are of particular interest here since they can influence the creep properties and radiation performance. Idaho National Laboratory’s Multiphysics Object-Oriented Simulation Environment (MOOSE), specifically the MOOSE Application Library for Advanced Manufacturing UTilitiEs (MALAMUTE) software, provides an ideal platform for developing the multiphysics multiscale model to explore the intricacies of the microstructural evolution during the AM processes within a single framework. Furthermore, given that such full-fidelity simulations can be computationally intensive, reduced order models are necessary to explore the PSPP space for additively manufactured materials in an efficient, reliable, and cost-effective way. This work focuses on capturing the microstructural variabilities at the subgrain level that are often missing in the part-scale models. In fiscal year 2025, we significantly advanced upon our work in the last fiscal year, in terms of the predictive capabilities of the physics-based and ML models, by adding the capabilities to capture subgrain-level micro-segregation during solidification using phase-field model and to predict the time-dependent dynamics of the AM process through the MOGPAR model. The alloy solidification model in MOOSE incorporates the thermodynamic properties and free energy relevant to 316 stainless steel. The model demonstrates the Cr and Ni segregation that occurs during solidification, including that the rate of solidification. The microstructural evolution model is connected to the process conditions via the surrogate model developed in this work. This enables predictions of the final microstructure in conjunctions with the manufacturing process. This work supports AMMT's rapid qualification goals by laying the foundation for an efficient and cost-effective model establishing the PSPP correlation for AM. The generated microstructures and predicted micro-segregation can be used by other work packages under AMMT to evaluate the properties and environmental response of the material at the mesoscale. Thus, this work helps to identify the key microstructural features at the subgrain level that are significant in property and performance predictions of additively manufactured components. This work will also provide inputs to the large-scale process variability models to reevaluate and validate assumptions and simplifications made in the part-scale models. Furthermore, through active learning this work can help identify the data need from both modeling and experimental sides for development of a robust digital twin for additive manufacturing and accelerate the AMMT's qualification efforts.

36 - MATERIALS SCIENCE↗
DOE OSTI2023

The Influence of Nominal Composition on the Microstructure, Tensile Properties, and Weldability of Cast Monel Alloys

Cast Monel alloys are used in many industrial applications that require a combination of good mechanical properties and excellent resistance to corrosion. Despite relative widespread use, there has been limited prior research investigating the fundamental composition–structure–property relationships. Here in this work, microstructural characterization, thermal analysis, electron probe microanalysis, tensile testing, and Varestraint testing were used to assess the effects of variations in nominal composition on the solidification path, microstructure, mechanical properties, and solidification cracking susceptibility of cast Monel alloys. It was found that Si segregation caused the formation of silicides at the end of solidification in grades containing at least 3 wt pct Si. While increases to Si content led to significant improvements in strengthening due to the precipitation of β 1 -Ni 3 Si, the silicide eutectics acted as crack nucleation sites during tensile loading which severely reduced ductility. The solidification cracking susceptibility of low-Si Monel alloys was found to be relatively low. However, increases to Si concentration and the onset of associated eutectic reactions increased the solidification temperature range and drastically reduced cracking resistance. Increases in the Cu and Mn concentrations were found to reduce the solubility limit of Si in austenite which promoted additional eutectic formation and exacerbated the reductions in ductility and/or weldability.

36 MATERIALS SCIENCE↗
DOE OSTI2025

On the numerical sensitivity of cellular automata grain structure predictions to large thermal gradients and cooling rates

Cellular automata (CA) models of as-solidified grain structure, originally developed and applied to casting, have become a common means of predicting grain structure resulting from Additive Manufacturing (AM) processes. The majority of these models are based on the decentered octahedron approach, which attempts to correct for the effect of grid anisotropy on the prediction of competitive solidification of dendritic grains. However, AM solidification occurs under cooling rates ($\dot{T}$) and thermal gradients (G) that are orders of magnitude larger than those encountered in casting, and no systematic investigation on the effect of the CA model cell size (Δx) and time step (Δt) on AM microstructure predictions has been performed. Here, in this study, such an investigation is first performed via simulation of individual grains of various crystallographic orientations with a fixed, unidirectional G, showing that CA prediction of the steady-state undercooling matched the expected values based on the interfacial response function at small G and deviated from the expected values at large G. Simulation of competitive growth of multiple grains showed a weakening of the predicted texture as G and Δx became large. Simulation of solidification under AM conditions, where G and $\dot{T}$ vary spatially across the melt pools, showed that not only does grain selection weaken and deviate from expectations at large Δx, but grains with crystallographic $\langle$100$\rangle$ aligned with the grid directions are more adversely affected by the temperature field discontinuities than grains with other crystallographic orientations. Despite the fact that the exact grain competition results depended on Δt, the overall texture development was notably less sensitive to Δt than Δx, provided that a reasonable value of Δt is selected based on the ratio of Δx to the maximum local solidification velocity in the simulation domain. Finally, from the directional solidification and AM simulation results, an analysis of computational cost compared to simulation resolution is performed based on an equation derived to quantify the relatively inaccuracy in grain selection based on the model and temperature field inputs. From this analysis, it is concluded that there is a need for algorithmic improvements to improve CA grain competition accuracy for large G processing conditions as sufficiently small Δx to resolve the necessary competition is intractable for many AM processing conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Prediction of good glass forming ability in amorphous soft magnetic alloys by thermocalc simulation with experimental validation

Alloys in a (Fe 70 Ni 30 ) 80 (BeSieNb) 20 system, with good glass forming ability (GFA), were identified using Thermocalc software to simulate liquidus temperatures (T's) and solidification ranges (areas between the liquidus and solidus in a binary phase diagram,a line at fixed T). Here, a region with excellent GFA was identified at 14-18% B and 0-7% Si with the balance Nb, showing minima in liquidus and solidification range. A region with a solidification range minimum, but no corresponding liquidus minimum was identified at 3-8% B and 5-10% Si but had lower GFA. A shallow liquidus minimum, with no minimum in solidification range, at 3-5% B and 1-3% Si had the lowest GFA and did not produce amorphous material. Measured GFA was ranked using parameters T rg , DT xg , and γ m , defined herein. Only the reduced glass transition temperature, T rg , was predictive for the alloys. Differential Scanning Calorimetry (DSC) data showed liquidus T's to agree. Curie temperatures, T c 's were observed to increase with B/Nb ratio. Simulations of liquidus and solidification range for alloys with 18 and 15% glass formers do not show regions with minima in both, indicating good GFA is not expected.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Microstructure and Hard Magnetic Properties of Sm 1-x Zr x (Fe,Co) 11.3-y Ti 0.7 By Ingots and Thick Melt-Spun Ribbons

Permanent magnets made from Sm(Fe,Co) 12 -based compounds are being actively pursued through nanostructuring and powder metallurgy. This study was aimed at the development of hard magnetic properties in bulk as-cast alloys and in melt-spun alloys for very low wheel speeds. Slower solidification rates and alloying with Zr promote the tetragonal ThMn 12 -type crystal structure, whereas higher solidification rates and alloying with B replace the ThMn 12 structure type with the TbCu 7 structure type. When introduced simultaneously, Zr and B dramatically reduce the alloy solidification rates required for both the refinement of the 1:12 crystallites and their replacement with the 1:7 phase. In bulk arc-melted alloys, this allowed for a microstructure of separated 1:12 crystallites 1–3 μm in size, although, because of the ferromagnetic nature of a minority phase, the coercivity of these fine-grained alloys reached only 0.73 kOe. A moderately accelerated solidification further refined the 1:12 crystallites and increased the coercivity; a Sm 0.7 Zr 0.4 (Fe,Co) 10.8 Ti 0.7 B 0.5 alloy exhibited a coercivity of 1.5 kOe and a maximum energy product of 3.4 MGOe when it was melt-spun into a 0.26-mm-thick ribbon. A more rapid solidification suppressed the 1:12 phase and after annealing at 800–850 °C, the alloys modified with Zr and B developed reasonably high coercivity and maximum energy product even when melt-spun at a wheel speed of 6 m/s. For the above-mentioned alloy, these values were 4.1 kOe and 7.8 MGOe, respectively. Further, a similarly processed very-Sm-lean Sm 0.5 Zr 0.6 (Fe,Co) 10.6 Ti 0.7 B 0.7 alloy exhibited a remanence of 8.8 kG and an energy product of 7.4 MGOe.

36 MATERIALS SCIENCE↗
DOE OSTI2015

Materials for Advanced Ultrasupercritical Steam Turbines Task 4: Cast Superalloy Development

The Steam Turbine critical stationary structural components are high integrity Large Shell and Valve Casing heavy section Castings, containing high temperature steam under high pressures. Hence to support the development of advanced materials technology for use in an AUSC steam turbine capable of operating with steam conditions of 760°C (1400°F) and 35 Mpa (5000 psia), Casting alloy selection and evaluation of mechanical, metallurgical properties and castability with robust manufacturing methods are mandated. Alloy down select from Phase 1 based on producability criteria and creep rupture properties tested by NETL-Albany and ORNL directed the consortium to investigate cast properties of Haynes 282 and Haynes 263. The goals of Task 4 in Phase 2 are to understand a broader range of mechanical properties, the impact of manufacturing variables on those properties. Scale up the size of heats to production levels to facilitate the understanding of the impact of heat and component weight, on metallurgical and mechanical behavior. GE Power & Water Materials and Processes Engineering for the Phase 2, Task 4.0 Castings work, systematically designed and executed casting material property evaluation, multiple test programs. Starting from 15 lbs. cylinder castings to world’s first 17,000 lbs. poured weight, heavy section large steam turbine partial valve Haynes 282 super alloy casting. This has demonstrated scalability of the material for steam Turbine applications. Activities under Task 4.0, Investigated and characterized various mechanical properties of Cast Haynes 282 and Cast Nimonic 263. The development stages involved were: 1) Small Cast Evaluation: 4 inch diam. Haynes 282 and Nimonic 263 Cylinders. This provided effects of liquidus super heat range and first baseline mechanical data on cast versions of conventional vacuum re-melted and forged Ni based super alloys. 2) Step block castings of 300 lbs. and 600 lbs. Haynes 282 from 2 foundry heats were evaluated which demonstrated the importance of proper heat treat cycles for Homogenization, and Solutionizing parameters selection and implementation. 3) Step blocks casting of Nimonic 263: Carried out casting solidification simulation analysis, NDT inspection methods evaluation, detailed test matrix for Chemical, Tensile, LCF, stress rupture, CVN impact, hardness and J1C Fracture toughness section sensitivity data and were reported. 4) Centrifugal Casting of Haynes 282, weighing 1400 lbs. with hybrid mold (half Graphite and half Chromite sand) mold assembly was cast using compressor casing production tooling. This test provided Mold cooling rates influence on centrifugally cast microstructure and mechanical properties. Graphite mold section out performs sand mold across all temperatures for 0.2% YS; %Elongation, %RA, UTS at 1400°F. Both Stress-LMP and conditional Fracture toughness plots data were in the scatter band of the wrought alloy. 5) Fundamental Studies on Cooling rates and SDAS test program. Evaluated the influence of 6 mold materials Silica, Chromite, Alumina, Silica with Indirect Chills, Zircon and Graphite on casting solidification cooling rates. Actual Casting cooling rates through Liquidus to Solidus phase transition were measured with 3 different locations based thermocouples placed in each mold. Compared with solidification simulation cooling rates and measurement of SDAS, microstructure features were reported. The test results provided engineered casting potential methods, applicable for heavy section Haynes 282 castings for optimal properties, with foundry process methods and tools. 6) Large casting of Haynes 282 Drawings and Engineering FEM models and supplemental requirements with applicable specifications were provided to suppliers for the steam turbine proto type feature valve casing casting. Molding, melting and casting pouring completed per approved Manufacturing Process Plan during 2014 Q4. The partial valve casing was successfully cast after casting methods were validated with solidification simulation analysis and the casting met NDT inspection and acceptance criteria. Heat treated and sectioned to extract trepan samples at different locations comparing with cast on coupons test data. Material properties requisite for design, such as tensile, creep/rupture, LCF, Fracture Toughness, Charpy V-notch chemical analysis testing were carried out. The test results will be presented in the final report. The typical Haynes 282 large size Steam Turbine production casting from Order to Delivery foundry schedule with the activity break up is shown in Figures 107 and 108. • From Purchase Order placement to Casting pouring ~ 26 weeks. 1. Sales and commercial review 3 2. Engineering Drawings/models review 4 3. Pattern and core box manufacturing 6 4. Casting process engineering review 4 5. FEM and solidification simulation analysis 4 6. Gating & Feeder Attachments, Ceramic tiling 2 7. Molding and coremaking production scheduling 6 8. Melting planning and schedule 3 9. Pouring, cooling and shake out 2 • From Pouring to casting Delivery ~ 29 weeks 10. Shot blast and riser cutting, gates removal 3 11. Homogenizing , solutionizing HT furnace prep 4 12. Grinding, Fettling 2 13. Aging HT Cycle, cooling 2 14. VT and LPT NDT inspections 2 15. Radiographic inspection 4 16. Mechanical testing, Chemical analysis test certs 4 17. Casting weld repair upgrades and Aging PWHT 4 18. NDT after weld repairs and casting upgrades 3 19. Casting Final Inspection and test certifications 3 20. Package and delivery 2 Hence the Total Lead time from P.O to Casting delivery is approximately 55 weeks. The Task 4.2 and Task 4.3 activities and reporting completed.

Thangirala, Mani↗
DOE OSTI2022

ADDITIVE MANUFACTURING OF REFRACTORY ALLOYS

Refractory alloys are known for their high temperature capabilities and are intended for use at ultra-high temperatures above even 1200°C, which exceeds the capabilities of conventional superalloys. Additive manufacturing (AM) is an attractive alternative processing route because refractory alloys are difficult to fabricate through traditional methods; AM can form a near net-shape part with a tailored microstructure. This work seeks to evaluate the solidification behavior of refractory alloys under AM conditions and establish corresponding solidification models. Two binary alloys, Mo30Nb and Nb7.5Ta, as well as the commercial Nb alloy, C103, and one refractory high entropy alloy (RHEA), MoNbTaTi, were subjected to single track melts in a laser powder bed fusion (LPBF) machine. Each melt track was evaluated in the scanning electron microscope (SEM), which determined that some AM conditions used led to non-ideal behavior. Electron backscatter diffraction (EBSD) revealed that the Nb7.5Ta, C103, and MoNbTaTi all exhibited new grain nucleation to various extents while the Mo30Nb exhibited primarily epitaxial growth. This was found to be inconsistent with solidification models that were developed for each alloy and each set of AM conditions to predict the columnar to equiaxed transition behavior (CET) of the experimental microstructures. This disparity was largely attributed to the input parameters for the solidification model, which were developed using Thermo-Calc and SYSWELD. These input parameters include the alloy specific Gibbs-Thomson coefficient and thermophysical properties, the solute specific liquidus slopes and partitioning coefficients, as well as the process specific thermal gradients. Each input parameter was evaluated to determine the likely changes required for the modeled values to generate solidification models that better correspond to what was observed experimentally.

Miklas, Abigail↗
DOE OSTI2023

Strontium Effects on the Formation of Iron-Intermetallic Phases in Secondary Al–9Si–0.6Fe Alloys

The presence and morphology of Fe-containing intermetallic phases affect the mechanical properties of aluminum alloys, especially in secondary Al–Si-based cast alloys. Although strontium (Sr) addition of 50 to 500 ppm is known to refine the needle-type eutectic silicon structure, the influence of Sr on the formation of Fe-intermetallic phases remains unclear. The present work investigates the combined additions of Sr and Mn to Al–9Si–0.6Fe–0.35Mg (All compositions are in wt pct except otherwise stated.) alloys on the formation of Fe-intermetallic phases at different solidification rates from ~ 1.5 to ~ 60 °C/s. Long and branched-type AlFeSi phase with size ranging from 50 to 120 µm are more common when solidified at the rate of 1.5 °C/s regardless of Sr and Mn additions. However, at the fast solidification rate of 60 °C/s, a 60 ppm Sr addition significantly reduced the average length of needle-shaped AlFeSi phase to less than 3 to 5 µm. Thermodynamic simulations have been performed using CALculation of PHAse Diagrams (CALPHAD) models to predict the formation of various phases and their possible interactions during solidification. The results indicated that the combination of a high solidification rate and about 60 ppm of Sr is beneficial to refining the δ-Al 3 FeSi 2 phase in Al–Si–Mg alloys containing 0.6 pctFe. As a result, this unexpected finding of Fe-intermetallic refinement by low Sr addition (~60 ppm) provides an important guide in designing secondary alloys for sustainable casting applications.

36 MATERIALS SCIENCE↗