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Results for “Wire Arc Additive Manufacturing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 37 records · Page 2

Characterization and prediction of the electromechanical wear of contact tips during wire arc additive manufacturing of 316L stainless steel

Here, this study seeks to better understand the degradation of the contact tip with respect to WAAM for a 316L wire electrode as well as explore methods of monitoring the contact tip state from process data. The contact tip, a consumable component, positions the wire and serves as the electrical contact surface between the wire electrode and the welding power supply. The wear of the contact tip was characterized in terms of material loss and material contamination for a set of tips worn to discrete levels as measured by the amount of wire fed or arc time. Geometrical characterization found a 49% increase in the bore exit area at 180 meters of wire fed. Machine learning models were developed to predict the relative bore exit area of the contact tip from arc-based process data and a random forest classifier exhibited favorable performance with a cross-validated f1-score of 0.84. The regression architecture implemented a multi-layer perceptron with the ability to predict the relative exit area with an $R^2$ score of 0.75. Key features used in the prediction include the standard deviation of the voltage and the time between shorts.

Contact tip wear↗

Wire-arc Additive Manufacturing Benchmark

This is the dataset associated with the 2022 SRP Additive Manufacturing Prediction Challenge, originally hosted on Github at https://github.com/SRP-AM/SRP_AM_Prediction_Challenge. The benchmark was designed for validating prediction for the temperature history, residual stress, and distortion of an additively manufactured metal part with relatively simple geometry. A calibration problem with the same as-built geometry is provided with measured quantities of interest; including temperature histories at selective locations, post-build residual stress at selective locations, and overall distortion measurements. The challenge problem is presented with a different build sequence (i.e. thermal history). In this dataset, we include the actual recorded calibration and challenge measurements, as well as benchmark template files for testing predictions without incorporating the challenge data. Supplementary files around the materials and setup are available for transparency and reproducibility.

Bachus, Nicholas [UC Davis, Davis, CA]↗

Feature Based Qualification (FBQ) of Wire Arc Additively Manufactured (WAAM) 17-4PH Martensitic Stainless Steels

The Department of Defense (DOD) programs of records desire to reduce the time and cost of the development and delivery loop in metal additive manufacturing (AM), including establishing forwarded AM capabilities. The success of these efforts relies on a robust and qualified process. To achieve this, the United States Army Combat Capabilities Development Command Ground Vehicle Systems Center Materials Engineering (GVME) needs to be able to quickly evaluate, test, and develop feedstocks, processes, and parts. This report is directed towards demonstrating the need for a framework for metal AM processes, defining and exploring geometries for metal AM process qualification, testing resultant deposition, and delivering actionable data.

36 MATERIALS SCIENCE↗

Denoising diffusion probabilistic models for generative alloy design

Inverse material design is an extremely challenging optimization task made difficult by, in part, the highly nonlinear relationship linking performance with composition. Quantitative approaches have improved significantly owing to advances in high throughput experimentation and computational thermodynamics. However, existing physics-based tools are mostly forward models; input a chemistry and obtain a prediction. More recently the materials community has leveraged advances in the machine learning community to establish novel inverse design frameworks. Very recently denoising diffusion probabilistic models have been shown to be extremely powerful generators producing synthetic data of various modalities e.g. images, text, audio, tables, etc.. In this work a novel framework for alloy design and optimization is proposed leveraging these class of models. Five key generative tasks are demonstrated (1) unconditional generation (2) composition conditioned generation (3) property conditioned generation (4) multi-feedstock conditioned generation and (5) generative optimization. These methods were tested on three case studies: high entropy alloy design, superalloy binder jet additive manufacturing, and in-situ dual-feedstock wire-arc additive manufacturing. Results indicate that the established models are extremely flexible, expressive, and robust. The architecture’s flexibility and training procedure empower the model to learn complex intra-compositional and composition-property relationships. Furthermore, the probabilistic nature of these models makes them well suited for addressing solution non-uniqueness and tackling uncertainty quantification tasks. While the fidelity and quantity of the underlying training data is paramount, we envision that future alloy design frameworks will make extensive use of these kinds of machine learning models as “search” tools bolstering the utility of experimental and computational approaches.

36 MATERIALS SCIENCE↗

CALPHAD-based ICME design of single-step aging to enhance mechanical strength of WAAM Haynes 282

To match the strength of wire-arc additive manufactured Haynes 282 to its wrought counterpart via a single-step aging heat treatment, the CALPHAD (Calculation of Phase Diagrams) method is integrated with physics-based process-structure-property models and experimental validation. The integrated computational materials engineering (ICME) framework simulates the effects of aging on γ′ and M 23 C 6 precipitation and the resulting yield strength. To improve simulation reliability, the interfacial energies between γ/γ′ and γ/M 23 C 6 carbides were estimated by comparison with precipitation kinetic modeling and measured precipitate sizes. γ′ and M23C6 were found to precipitate simultaneously between 640 and 860 °C, producing microstructures similar to those produced by two-step aging. The optimal γ′ size for peak yield stress was calculated to be 20–23 nm. WAAM Haynes 282 aged at 780 °C for 50 h exceeded the mechanical performance of its wrought counterpart subjected to two-step aging, though desired properties can also be achieved at 800 °C for 16 h or less. The error in yield strength is less than 20 MPa, demonstrating good agreement between the modeling framework and experiments. Creep studies showed that WAAM Haynes 282 exceeded the calculated rupture time, reaching 481 h. This proposed methodology can accelerate the design of aging heat treatments for any γ′-strengthened nickel-base alloy, minimizing the resources required for trial-and-error experiments.

CALPHAD↗

Process-level cost analysis of hybrid manufacturing pathways for aerospace structural components

Hybrid manufacturing is a promising route for producing complex aerospace components, yet systematic cost benchmarking across multiple additive-subtractive pathways remains limited. This study presents a comprehensive process-based cost analysis of seven hybrid manufacturing routes, including laser powder bed fusion (L-PBF), powder- and wire-directed energy deposition (DED), wire arc additive manufacturing (WAAM), additive friction stir deposition (AFSD), metal binder jetting (MBJ), and agility forging, followed by scanning and finish machining. Parametric cost models incorporating direct material, labor, and energy costs were developed. L-PBF results are discussed in detail for a pickle fork component and directly compared with commercial pricing. Across all hybrid routes, labor emerged as the dominant cost driver, contributing more than 70% of total manufacturing cost in some cases. AFSD exhibited the lowest cost for aluminum components, with MBJ being its 316 L stainless steel counterpart, after accounting for geometric scaling. Benchmarking against industrial quotes suggests that hybrid manufacturing can achieve cost levels comparable to those of commercial services, although labor-intensive processes exhibit greater deviation. The analysis highlights automation of material handling, setup, and supervision as key opportunities for improving economic competitiveness. Overall, the proposed framework provides a quantitative basis for evaluating and optimizing hybrid manufacturing pathways for aerospace applications.

Baruah, Sweta [ORNL] (ORCID:0009000174256207)↗

Machine tool cross beam design, fabrication, and testing using metal big area additive manufacturing

This paper describes the application of metal Big Area Additive Manufacturing (mBAAM) to the fabrication of a machine tool cross beam. The replacement of a traditional box design weldment with a new design printed by wire arc additive manufacturing using the MedUSA system at Oak Ridge National Laboratory (ORNL) is detailed. This requires a new design strategy based on the unique mBAAM capabilities. The intent of the new design is to reduce mass, while maintaining the dynamic stiffness. To compare the two designs, the natural frequencies and mode shapes are measured using impact testing and predicted using finite element analysis. It is confirmed that the printed structure dynamics agreed with the numerical model predictions, which demonstrates that it is feasible to model a large-scale mBAAM part and understand its behavior prior to printing. Another notable outcome of this study is that the significant residual stress and distortion in the print indicate that knowledge gaps remain for widespread implementation of mBAAM.

42 ENGINEERING↗

Oxide Dispersion Strengthened Ferritic Steel Wire Feedstock Development for Larger Format Additive Manufacturing (CRADA Final Report)

This CRADA project funded through DOE’s INFUSE program sought to demonstrate the viability of fabricating large, complex parts from oxide dispersion strengthened (ODS) steel with advanced manufacturing. Exhibiting excellent radiation tolerance and high mechanical performance at elevated temperatures, ODS steel is a promising structural material candidate for near-plasma components in fusion energy systems. Its use, however, has been limited by a lack of manufacturability. This project sought to produce ODS steel wire through a solid-state shear assisted extrusion process and then demonstrate that the wire can undergo controlled local melting while being welded with the final part sufficiently retaining the beneficial properties of ODS steel. This would allow the use of wire-arc additive manufacturing (WAAM) to manufacture large-scale ODS parts, even though ODS is currently only available as a powder. WAAM is a promising technique for producing components like the replaceable ARC vacuum vessel in CFS’ fusion reactor design. Meanwhile, this project will also expand PNNL’s capability in producing custom wire feedstock with friction extrusion, enabling downstream large-scale manufacturing with WAAM and solid-state based additive manufacturing. The project achieved its goals of developing tooling and fixturing to produce ODS wire at smaller diameters than previous projects. Several small lengths of wire of 1.5 mm and 2.5 mm diameter in the range of 2.5-30 mm long were produced at tool temperatures that are known to cause ODS particle coarsening (~1200 °C). Fixtures and tooling for longer (>1 m) wires were developed but further process development is needed reduce tool temperature during extrusions and to increase wire length needed for WAAM testing and development.

36 MATERIALS SCIENCE↗

AMVOS: Additive Manufacturing Video Object Segmentation Dataset

This dataset provides labeled video frames from four additive manufacturing (AM) processes for video object segmentation (VOS) tasks. It contains 90 video segments comprising 900 individually annotated frames across five AM datasets: laser hot-wire directed energy deposition (LHW-DED), tungsten inert gas wire arc additive manufacturing (TIG-WAAM), plasma arc welding (PAW), visible-light polymer extrusion (visPolymer), and near-infrared polymer extrusion (irPolymer). Each video segment consists of 10 contiguous frames with corresponding pixel-level object instance annotations. Depending on the process, two of four object classes are labeled per frame: Melt Pool, Feed Wire, Nozzle, or Material. Raw frames are provided as .jpg files and annotations as palettized .png files. The dataset follows the directory structure of established VOS benchmarks (DAVIS, YouTube-VOS, MOSE), enabling direct integration into VOS model training and evaluation pipelines for foundation model fine-tuning, domain adaptation, or zero-shot performance benchmarking. Data was collected at Oak Ridge National Laboratory's Manufacturing Demonstration Facility.

Wetzel, Jon [ORNL]↗

High temperature tensile properties of H13 tool steel fabricated via binder jet additive manufacturing

H13 is one of the most used steels for hot work tooling applications like die casting. Binder jet additive manufacturing (BJAM) offers a cost-effective solution to fabricate tools with performance enhancing features like internal cooling channels. While full densification of BJAM H13 has been demonstrated in the literature, the room and high temperature tensile properties of the material, and the effect of post-process treatments like hot isostatic pressing (HIP), and heat treatment (HT) are unknown. Here we use HIP+HT to obtain a combination of ultimate tensile strength (UTS) and elongation to failure that is superior to H13 fabricated via laser powder bed fusion and wire arc additive manufacturing. HIP+HT BJAM H13 has a superior UTS (1836 MPa) compared with conventionally processed (1671 MPa) H13 but has lower plastic elongation. We report that as-sintered samples have an extensive network of continuous grain boundary (GB) carbides that contribute to brittle fracture. HIP+HT results in partial dissolution of GB carbides and formation of a fine martensitic microstructure resulting in superior tensile strength and elongation compared with as-sintered H13. We use thermo-kinetic calculations to rationalize the effects of HIP+HT on microstructure and properties.

36 MATERIALS SCIENCE↗

Impact of Heat Input and Step Over Distance on Part Geometry for Multi-Bead WAAM Components

Abstract This study investigates the impact of heat input and overlap ratio or stepover distance on part geometry in wire arc additive manufacturing (WAAM). In this work, an experimental approach was taken to quantify the variation in height and aspect ratio of walls at different combinations of overlap and heat input. Multi-bead walls were deposited with the overlap ratio varying from ½, ⅔, and 1 at a low, medium, and high-power set point on the welding power supply. A relationship between heat input, overlap ratio, and the resultant part geometry is established. Trials with an overlap ratio of one and low to medium heat input exhibited greater lack of fusion defects than the high heat input trials. At higher heat input levels, the as-deposited geometry was found to have less variation in height and an increase in aspect ratio compared to lower heat input trials. The aspect ratio of deposited walls ranged from approximately 1, for the low-power trial with an overlap ratio of ½, to approximately 7, for the high-power trial with an overlap ratio of 1. Additionally, the low and medium power trials with an overlap ratio of ⅔ exhibited the least height variation in the top surface for those heat input levels with an average range of 2.9 mm and 1.8 mm respectively. For the high heat input trials, an overlap ratio of 1 was observed to have the least variation in height with a standard deviation of 0.42 mm and an average range of 1.7 mm; however, lack of fusion defects were present in the top surface and the part cross section.

Hussein, Zaky↗

Understanding the Thermal Physics and Metallurgy of Metal Big Area Additive Manufacturing

The research goal of this EPSCoR-DOE partnership is to mitigate defects in parts made using a new type of additive manufacturing (AM) process called metal Big Area Additive Manufacturing (m-BAAM). To realize this goal, the PIs will detect and correct defects in the part as it is being printed by combining fundamental knowledge of the thermal physics and metallurgy of m-BAAM with in-process sensor data. Developed at the DOE-funded Manufacturing Demonstration Facility at Oak Ridge National Laboratory, the m-BAAM process involves one or more robots working together to produce a part by fusing metal wire layer-by-layer using arc welding. The process can print large metal parts such as turbine blades, which is not possible using other AM processes. In addition, m-BAAM production rates are more than ten times faster than other AM processes while requiring one-tenth of the material cost. Despite their potential to become a critical force multiplier in the energy generation industry, m-BAAM parts may fail to print accurately due to retention of heat and uneven cooling. Overheating and anomalous cooling rates in turn can cause inconsistencies in the microstructure, leading to sudden failure when used in safety-critical applications. In other words, flaw formation in m-BAAM parts is governed by the thermal history – intensity and spatial distribution of heat inside the part during printing. The thermal history is a complex function of the part shape and process settings such as welding energy, path taken by the welding torch for deposition (tool path), wire feed rate, among others.

36 MATERIALS SCIENCE↗

Electroslag additive manufacturing: A pathway for high throughput near net shape production

Electroslag Additive Manufacturing (ESAM), a new high-throughput additive manufacturing (AM) method that combines Electroslag Strip Cladding (ESC) and wire arc AM (WAAM) is introduced. This combination enables the high deposition rate of ESC (more than 20 kg/h with a 60 mm strip electrode) to benefit from the precise geometric control of WAAM. As a precursor to ESAM, the ESC process is investigated in an AM context independently by evaluating both direct and staggered bead-stacking strategies and analyzing the microstructural and mechanical properties of each. This is followed by an ESAM demonstration producing an annular geometry by pairing ESC with gas tungsten arc welding (GTAW), wherein GTAW is utilized to construct annular walls that are subsequently infilled via ESC. The microstructure and mechanical properties of ESC-only AM are compared with that of the ESAM method and it is shown that printed integral retaining walls do not impact the resulting mechanical properties of ESAM. Furthermore, results indicate that ESAM-produced Alloy 625 parts exhibit tensile properties on par with cast counterparts, supporting the method’s scalability to components exceeding one metric ton, and possibly making ESAM a viable future manufacturing approach for competitive production of large-scale components currently manufactured by casting and forging.

Additive manufacturing↗

Extending wire-arc directed energy deposition using non-gravity aligned (NGA) torch methods

For standard Additive Manufacturing (AM) processes, traditional path planning typically relies on a 2.5-dimensional approach. In wire-arc directed energy deposition (DED), commonly referred to as wire-arc additive manufacturing (WAAM), this 2.5D approach inherently limits final near net shape due to the stair-step effect and restricts the maximum overhang angle achievable without part degradation. To achieve better near net shape and part quality, a 3D planning approach that modulates the tool tip position and angle without process changes is demonstrated in components containing up to 105° of unsupported overhang. The experimental methods are validated with half and fully enclosed cylinder sections containing 90° of overhang. The non-gravity aligned methods are then applied to a commercial WAAM system for a composite tool mold demonstrator part. As a result, the methods developed in this paper enable expansion of WAAM system capabilities to parts containing large overhangs without compromising the net shape or material structure of the resulting parts and without the need for a part positioner.

Additive manufacturing↗

Future foundries: A convergent manufacturing platform

This article introduces the Future Foundries platform developed at Oak Ridge National Laboratory, a first-generation research system designed to demonstrate convergent manufacturing. Convergent manufacturing brings together additive, subtractive, and transformative processes in a digitally interconnected environment to enable end-to-end production workflows. By linking traditionally discrete steps, convergent platforms accelerate production, improve repeatability, and support high-mix, low-volume manufacturing. The Future Foundries platform exemplifies this vision in practice by combining four modular, vendor-agnostic process cells that include robotic WAAM, induction heating, optical metrology, and machining, coordinated through an automated pallet handler and a ROS 2-based digital thread. This architecture provides the flexibility and scalability needed for agile production in small and medium-sized manufacturing enterprises and for field deployable manufacturing. Two case studies illustrate the platform’s capabilities. The first presents an integrated workflow for fabricating, transforming, and repairing critical replacement components, showing how consolidated thermal, additive, inspection, and machining operations reduce manual part handling and streamline process flow. The second case study highlights coordinated multi-part production enabled by automated pallet logistics and multi-cell scheduling. Together, these examples showcase convergent manufacturing as a practical and scalable strategy for strengthening domestic casting and forging capacity, improving supply-chain resilience, and enabling rapid, adaptable production of mission-critical components.

Convergent manufacturing↗