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DOE OSTI2025

A high-throughput approach for statistical process optimization in Laser Powder Bed Fusion

Process variability is inherent in metal additive manufacturing (AM). However, it is often overlooked in process optimization frameworks, constraining the understanding of process uncertainties and their influence on parameter selection. To address this, we present an integrated framework that combines high-throughput single-track experiments, GAN-based melt pool geometry extraction, robust statistical and machine learning modeling, and uncertainty-quantified process mapping. Process variability is characterized through single-track melt pool behaviors, and its influence on defect formation is systematically quantified to enable statistically guided process parameter optimization. This approach is demonstrated on Laser Powder Bed Fusion (L-PBF) of stainless steel 316L, effectively capturing the interplay between process parameters, melt pool variability, and defect probability. By integrating uncertainty quantification into process optimization, this study provides a structured methodology for addressing variability challenges in AM quality control, ultimately contributing to enhanced manufacturing reliability.

Laser Powder Bed Fusion↗

DOE OSTI2023

Exceptional thermal stability of additively manufactured CoCrFeMnNi high-entropy alloy with cellular dislocation structures

CoCrFeMnNi high-entropy alloy (HEA) was additively manufactured (AM) by laser powder-bed fusion (L-PBF). The AM CoCrFeMnNi has prominent cellular dislocation structures with a small number of Mn-rich oxides. The thermal stability of the AM CoCrFeMnNi was investigated by isochronal annealing treatment at various temperatures from 400 to 1300°C for 1h. Microstructural analysis shows slow dislocation recovery, retarded recrystallization process, and precipitation of additional Cr-Mn based oxides during thermal annealing, resulting in exceptional thermal stability and retained high hardness at elevated temperatures. Further, by thermodynamic calculations, a low stored energy of 1.31 MJ/m 3 and a high activation energy of 353 kJ/mol for recrystallization were estimated for the AM CoCrFeMnNi. The exceptional thermal stability of the AM CoCrFeMnNi HEA is mechanistically attributed to the low crystallographic misorientations across the dislocation cell walls, sluggish atomic diffusion, and the pinning effects of the oxide nanoprecipitates.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Chemical composition based machine learning model to predict defect formation in additive manufacturing

With a goal of exploiting additive manufacturing to improve the manufacturing of existing reactor materials, we developed a chemical composition-based machine learning model to predict the printability of any given alloy in laser powder bed fusion (L-PBF) using experimental data from peer-reviewed literature. We defined printability as the ability to avoid defects like cracking, balling, porosity, and lack of fusion, that are caused by thermal stresses (during solidification or liquation), molten pool disintegration into disconnected small beads or lack of heat input respectively. Our models predict the tendency of balling defect formation and porosity percentage for a given composition, under a given set of processing conditions. To predict the likelihood of balling defect, three models: a random forest classifier, a gradient boost regressor and a neural network were trained on a dataset containing both traditional alloys and high entropy alloys. The neural network model showed the highest accuracy of 92.3 % in predicting the balling defect formation. A random forest regressor, gradient boost regressor and neural network were trained and tested on a dataset of various alloys to predict porosity. The random forest regressor showed the best predictions with an R 2 score of 0.97. The models also revealed the relative importance of the input descriptors on defect-formation tendency. Of particular significance was the identification of carbon as an important element in determining the occurrence of balling and percent porosity in alloys like steel, as well as being moderately important to the percentage porosity in other alloys as well as steel. Manganese was also identified as a key descriptor for the percentage of porosity in steel and other alloys. Manganese’s low thermal conductivity and consistent presence in the dataset is the likely cause for its contribution. Carbon’s role is attributable to its relatively high specific heat and high melting temperature. In conclusion, our model serves as a swift, chemistry-based tool to design experiments and find modified compositions better suited for additive manufacturing.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Phase stability of a eutectic high entropy alloy under extremes of pressures and temperatures

Additively manufactured high-entropy alloys are of interest because of their unique combination of high yield strength and large ductility achieved with far-from-equilibrium crystalline phases and micro/nanostructure morphology. We report on the phase transformation and thermal equation of state of the eutectic high-entropy alloy (EHEA) Al 18 Co 20 Cr 10 Fe 10 Ni 40 W 2 , produced by laser powder-bed fusion (L-PBF). The EHEA was studied in a large-volume Paris–Edinburgh cell using energy-dispersive x-ray diffraction to a pressure of 5.5 GPa and a temperature of 1723 K. Static compression studies in diamond anvil cells using angle-dispersive x-ray diffraction extended the high-pressure structural data to 317 GPa at ambient temperature. The initial dual-phase nanolamellar face-centered cubic (FCC) and body-centered cubic (BCC) structure of Al 18 Co 20 Cr 10 Fe 10 Ni 40 W 2 transforms into a single FCC phase under high pressure, with the BCC-to-FCC phase transformation completing at 9 ± 2 GPa. The FCC phase remained stable up to the highest pressure of 317 GPa. The measured thermal equation of state for the FCC phase of Al 18 Co 20 Cr 10 Fe 10 Ni 40 W 2 is presented up to 5.5 GPa and 1473 K. We observed melting of the EHEA at 1698 ± 25 K at a pressure of 5.5 GPa, and the recrystallized sample shows an increased fraction of the CsCl-type (B2) phase at ambient conditions following release from the high-pressure high-temperature state. The BCC-to-FCC phase transition completion pressure is correlated with the nanolamellae thickness of the BCC layer in this diffusion-less transformation at ambient temperature.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Development of a Method for Shape Optimization for a Gas Turbine Fuel Injector Design Using Metal-Additive Manufacturing

Adjoint shape optimization has enabled physics-based optimal designs for aerodynamic surfaces. Additive manufacturing (AM) makes it possible to manufacture complex shapes. However, there has been a gap between optimal and manufacturable surfaces due to the inherent limitations of commercial computational fluid dynamics (CFD) codes to implement geometric constraints during adjoint computation. In such cases, the design sensitivities are exported and used to perform constrained shape modifications using parametric information stored in computer aided design (CAD) files to satisfy manufacturability constraints. However, modifying the design using adjoint methods in CFD solvers and performing constrained shape modification in CAD can lead to inconsistencies due to different shape parameterization schemes. This paper describes a method to enable the simultaneous optimization of the fluid domain and impose AM manufacturability constraints, resolving one of the key issues of geometry definition for isogeometric analysis. Similar to a grid convergence study, the proposed method verifies the consistencies between shape parameterization techniques present within commercial CAD and CFD software during mesh movement as a part of the adjoint shape optimization routine. By identifying the appropriate parameters essential to a shape optimization study, the error metric between the different parameterization techniques converges to demonstrate sufficient consistencies for justifiable exchange of data between CAD and CFD. For the identified shape optimization parameters, the error metric to measure the deviation between the two parameterization schemes lies within the AM laser-powder bed fusion (L-PBF) process tolerance. Additionally, comparison for subsequent objective function calculations between iterations of the optimization loop showed acceptable differences within 1% variation between the modified geometries obtained using the two parameterization schemes. This method provides justification for the use of multiphysics guided adjoint design sensitivities computed in CFD software to perform shape modifications in CAD to incorporate AM manufacturability constraints during the shape optimization loop such that optimal designs are also additively manufacturable.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2022

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10)

36 MATERIALS SCIENCE↗

DOE OSTI2023

Layer-wise Imaging Dataset from Powder Bed Additive Manufacturing Processes for Machine Learning Applications (Peregrine v2022-10.1)

This release consists of six datasets which together include multi-modal layer-wise powder bed images from two different powder bed printing technologies. These datasets are designed primarily to facilitate the development and testing of new computer vision and machine learning based anomaly and defect detection algorithms. The authors provide both training data with corresponding ground truth pixel masks and evaluation data with corresponding baseline prediction pixel masks made by a trained neural network. The laser powder bed fusion (L-PBF) datasets are sourced from EOS M290 and AddUp FormUp 350 printers and the binder jet (BJ) dataset is sourced from an ExOne M-Flex printer. The materials represented in these datasets include 17-4 PH Stainless Steel, GammaPrint-700, Inconel 718, Maraging Steel, and H13 Steel. The sensor imaging modalities represented include visible-light (VL), temporally-integrated (i.e., long duration exposure) near-infrared (TI-NIR), and wide-band infrared (IR). To download the dataset: (1) Create a Globus account. (2) Create a Globus Endpoint on your computer. (3) Transfer the dataset from the OLCF DOI-DOWNLOADS Collection to your Collection. Common troubleshooting steps: (a) Confirm that the transfer is going from OLCF DOI-DOWNLOADS to your Collection. (b) Create an exception for Globus in your antivirus software so that it can create an Endpoint. (c) Manually create a Globus access directory (where the data will be downloaded) by going to the Preferences > Access tab.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A Co-Registered In-Situ and Ex-Situ Tensile Properties Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-11)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from five Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L builds containing 6,299 SS-J3 individually tracked tensile coupons. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, room-temperature static tensile test results, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗

DOE OSTI2023

A Co-Registered In-Situ and Ex-Situ Dataset from a Laser Powder Bed Fusion Additive Manufacturing Process (Peregrine v2023-10)

This release contains a co-registered in-situ and ex-situ Peregrine dataset from a single Concept Laser M2 Laser Powder Bed Fusion (L-PBF) stainless steel 316L build. These data were collected at the Manufacturing Demonstration Facility (MDF) located at Oak Ridge National Laboratory (ORNL). The dataset includes layer-wise visible-light in-situ imaging data, the laser scan paths and parameters, in-situ temporal sensor data, X-Ray Computed Tomography (X-CT) scans, pycnometry and tensile test results, etched micrographs from selected locations, and the target part geometries. Additionally, anomaly detections produced by a modified Dynamic Segmentation Convolutional Neural Network (DSCNN) are provided.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Microtructure and Low-Cycle Fatigue Behavior of Additively Manufactured 316L Stainless Steel at 300°C

Metal additive manufacturing (AM) or 3D printing has the potential to transform the nuclear industry by producing high quality components faster and cheaper, thus enhancing the operating performance of current plants and advanced reactors. Two AM 316L tubes - intended to act as surrogates for complex components where nuclear equipment vendors are more likely to consider AM technologies - were printed using a Renishaw AM400 Laser Powder Bed Fusion (L-PBF) system. The porosity of the as-built material was found to be small, 0.06%. In prior research, the fatigue and corrosion fatigue crack growth rate (CGR) response of the AM specimens in the as-built condition was found to be similar to that expected for conventional alloys, and extremely resistant to stress corrosion cracking (SCC). The present research demonstrates that the low-cycle fatigue behavior of the AM material in air is similar to that of wrought stainless steel at LWR temperature. The data suggest that low porosity levels do not have a significant effect on the fatigue performance of AM materials. Taken together, all data generated to date demonstrate that the use of AM alloys in a nuclear environment is plausible. Additional research on environmental fatigue, crack initiation, and SCC needs to be conducted to provide the performance information needed to qualify AM materials for LWR applications.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Magnetostrictive materials for enhanced sensors and electronic components

Magnetostriction is a property of magnetic materials that causes them to change their shape or dimensions proportional to their magnetization. Low-cost, mechanically robust magnetostrictive sensors would be valuable for a wide range of applications across the DOE and national security mission space, such as monitoring the internal conditions of pipelines, rapidly detecting high-impedance faults in power lines (e.g. trees touching power lines), or enhancing implantable systems for the human body. Dilute doping (<1 at.%) of rare earth elements (REE) has been shown to amplify the magnetostriction. Furthermore, alloy processing by rapid cooling from high temperature tends to result in texturing and therefore greater magnetostriction values, which bodes well for developing advanced manufacturing approaches significantly less expensive than single crystal growth. The goal of this effort was to develop robust, low-cost magnetostrictive materials compatible with advanced manufacturing techniques to exploit the rapid cooling of these approaches while retaining the ability to produce fully dense structures. To be useful as a sensor or actuator the coercivity of the material needs to be minimized so that there is minimal magnetic hysteresis. Employing a small scale laser powder bed fusion (L-PBF) system, specimens of Fe-Ga-Ce were built from alloy powder which had a magnetostriction of 289 ppm along the build direction and 197 ppm perpendicular to the build direction. These values are not far from the 310-350 ppm observed in single crystals of Fe-Ga. The results of the series of samples run suggest this is a very promising route for REE doping to higher levels, especially if the powders can be produced using far from equilibrium approaches such as ultrasonic atomization. The promising results from applying additive manufacturing techniques to these materials, particularly the inexpensive Fe-Al system, has potential for inexpensive high-performing magnetostrictive parts producible at large scales for low-cost sensors.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Thermomechanical Behavior of Advanced Manufactured Parts, Subcomponents, and Their Weldments for Gen3 CSP

Generation 3 (Gen3) concentrating solar power (CSP) plants may require the use of molten chloride salt storage systems, solar receivers, and supercritical-CO 2 primary heat exchangers (PHX). The temperatures that would be expected in these parts and subcomponents could approach 760°C for hot side and 500°C for cold side at peak operating conditions. With the design limitations, highly corrosion- and creep-resistant alloys are needed for maximizing component lives. This report presents the results for the project "Thermomechanical Behavior of Advanced Manufactured Parts, Subcomponents, and their Weldments for Gen3 CSP", award number DE-EE00036334. In this project, creep enhanced ferritic alloy Grade 91, austenitic stainless-steel (SS) 304H, Ni claddings Ni201 and C22, and nickel-based superalloys Inconel 740H and Haynes 282 and 230 were evaluated for potential applications in Gen3 CSP systems. Advanced manufacturing of these parts, subcomponents and their welds, was investigated and a full technoeconomic analysis was made in comparison to conventional manufacturing techniques. The manufacturing techniques explored are explosion clad welding and combustion synthesis/combustion reaction for transfer pipes, additive manufacturing (AM) including laser-powder bed fusion (L-PBF) and electron beam AM (EBAM) with wire feedstock for PHX and solar receivers, and conventional fusion welding for similar and dissimilar joining of these various parts and subcomponents.

14 SOLAR ENERGY↗

DOE OSTI2023

Unified Software Architecture for Advanced Materials and Manufacturing Technologies Data Management and Processing: FY 2023 Multidimensional Data Correlation Platform

This report details the various digital manufacturing activities ongoing at ORNL as part of the Advanced Materials and Manufacturing Technologies (AMMT) program. The AMMT program is exploring a data-driven approach to demonstrate the use of AM for the fabrication of components for nuclear applications, with the goal of providing a greater understanding of manufacturing quality outcomes that would pave the way toward the development of standards for certification and qualification. The objective of this work package is to establish a digital manufacturing discipline common to all participants of the AMMT program to improve the performance, reliability, and lifetime of nuclear components. As part of this effort, we will develop a unified software architecture for AMMT data management and processing, deploy the digital platform across AMMT participants’ facilities, and generate pedigreed datasets in a common format across multiple labs and facilities. To this end, the MDDC work package has focused on three activities during FY23. First, the MDF Digital Tool was overhauled to better serve the needs of the AMMT program. Next, multiple laser powder bed fusion (L-PBF) systems at the MDF were upgraded to a common sensor package for collecting comparable in situ data across machines. Finally, various improvements relevant to the AMMT program were implemented in the ORNL-developed software tool, Peregrine. This report marks the completion of FY23 milestone M3CR-22OR0403051: Report Describing the Architecture of the Digital Platform to Support AMMT Activities.

36 MATERIALS SCIENCE↗

DOE OSTI2024

Microstructure Optimization and Novel Processing Development of ODS Steels for Fusion Environments (Final ARPA-E Report)

This project aimed to develop scalable, cost-effective fabrication of high-performance, oxide- dispersion-strengthened (ODS) steel using advanced manufacturing methods (AMMs) for fusion blanket-breeding applications. Gas atomization reaction synthesis (GARS) enables the synthesis of precursor ODS steel powders without prolonged mechanical alloying. This process creates a chromium (Cr)-enriched surface oxide with yttrium/titanium (Y/Ti)-enriched intermetallics in powder interiors. GARS powders were consolidated to >99% of the theoretical density using a first-of-a-kind shear assisted processing and extrusion (ShAPE) and laser-based powder bed fusion (L-PBF) AM processes. These processes led to ODS steels containing a high-density of nano-oxide dispersoids that enhance high-temperature mechanical properties. Such scalable, cost-effective fabrication of ODS steels can enable efficient power conversion cycles (=40%) at operating temperatures beyond 900 K in future fusion power plants.

36 MATERIALS SCIENCE↗

DOE OSTI2026

Computational Design to Advance AM Fabrication of High Gamma Prime Alloys for Hot Gas Path Components in Gas Turbine Engines: A Pathway to Enhanced Gas Turbine Efficiency and Energy Saving (Final CRADA Report)

Raising turbine inlet temperature is a key lever for improving industrial gas-turbine efficiency and power output, but it increases thermo-mechanical demands on hot-gas-path components. Additive manufacturing (AM), particularly laser powder bed fusion (L-PBF), enables complex internal cooling features in critical components such as turbine tip shoes that are difficult to produce by conventional casting. However, qualification of new high-temperature AM alloys and aggressive geometries is often limited by trial-and-error iteration of build parameters and post-build heat treatments, with cracking during stress relieving or hot isostatic pressing (HIP) being a recurring failure mode.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

Investigation of Microstructures and Tensile Properties of 316L Stainless Steel Fabricated via Laser Powder Bed Fusion

In this study, a thorough investigation of the microstructures and tensile properties of 316L stainless steel fabricated via laser powder bed fusion (L-PBF) was done. 316L stainless steel specimens with two different thicknesses of 1.5 mm and 4.0 mm fabricated under similar conditions were utilized. Microstructural characterization was performed using optical microscopy (OM) and scanning electron microscopy (SEM) equipped with electron backscatter diffraction (EBSD). Melt pools and cellular structures were observed using OM, whereas EBSD was utilized to obtain the grain size, grain boundary characteristics, and crystallographic texture. The 1.5 mm thick sample demonstrated a yield strength (YS) of 538.42 MPa, ultimate tensile strength (UTS) of 606.47 MPa, and elongation to failure of 69.88%, whereas the 4.0 mm thick sample had a YS of 551.21 MPa, UTS of 619.58 MPa, and elongation to failure of 73.66%. These results demonstrated a slight decrease in mechanical properties with decreasing thickness, with a 2.4% reduction in YS, 2.1% reduction in UTS, and 5.8% reduction in elongation to failure. In addition to other microstructural features, the cellular structures were observed to be the major contributors to the high mechanical properties. Using the inverse pole figure (IPF) maps, both thicknesses depicted a crystallographic texture of {001} <101> in their as-built state. However, when subjected to tensile loads, texture transitions to {111} <001> and {111} <011> were observed for the 1.5 mm and 4.0 mm samples, respectively. Additionally, EBSD analysis revealed the pre-existence of high-density dislocation networks and a high fraction of low-angle grain boundaries. Interestingly, twinning was observed, suggesting that the plastic deformation occurred through dislocation gliding and deformation twinning.

316L stainless steel↗

DOE OSTI2024

On the Mechanical Behavior of LP-DED C103 Thin-Wall Structures

Laser Powder Directed Energy Deposition (LP-DED) can produce thin-wall features on the order of 1 mm. These features are essential for large structures operating in extreme environments such as regeneratively cooled nozzles and heat exchangers, which often make use of refractory metals. In this work, the mechanical behavior of LP-DED C103 was investigated via quasi-static tensile testing and low cycle fatigue (LCF) testing. The effects of vacuum stress relief (SR) and hot isostatic pressing (HIP) heat treatments were investigated for specimens in the vertical and horizontal build orientations during tensile testing. The AB and SR properties were lower than literature values for wrought and laser powder bed fusion (L-PBF) bulk components but higher than electron beam powder bed fusion (EB-PBF). The application of a HIP cycle improved strength by 7% and ductility by 27% past the initial as-built condition. Fracture images reveal that interlayer stress concentration sites are responsible for fracture in specimens in the vertical orientation. Meanwhile, fracture in the horizontal specimens mainly propagates at a slanted angle typical of plane stress conditions. The LCF results show cycles to failure ranging from 100 cycles to 8000 cycles for max strain levels of 2% and 0.5%, respectively. Fractography on the fatigue specimens reveals an increasing propagation zone as max strain levels are increased. The impact of these findings and future work are discussed in detail.

36 MATERIALS SCIENCE↗

DOE OSTI2023

Sensitization of 316L Stainless Steel made by Laser Powder Bed Fusion Additive Manufacturing

Additively manufactured (AM) 316L stainless steel (SS) manufactured by laser powder bed fusion (L-PBF) and wrought 316L SS were subjected to sensitization heat treatments at 700°C up to 100 h. Using two evaluation methods, double-loop electrochemical potentiokinetic reactivation (DL-EPR) and ditching tests, degree of sensitization (DOS) and intergranular corrosion (IGC) susceptibility was evaluated. It was found that the wrought samples showed slightly lower IGC susceptibility compared to their AM counterpart. DOS and IGC attacks increased with sensitization time for all samples. Dislocation cellular structures were found to have little to no impact on DOS and IGC for the AM samples. Sensitized at 100 h, the AM sample showed significant Cr depletion along high-angle grain boundaries (12.35 wt% on average) and exhibited Cr carbide precipitation. Mo-rich particles along grain boundaries were also observed. The DL-EPR test attacks the surface oxide film and grain boundaries while the ditching test attacks the melt pool boundaries and grain boundaries (IGC and pitting). Changes to the DL-EPR and ditching standards for AM application have been proposed in this work.

316L stainless steel↗