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At least 55 records · Page 3

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

Investigation of residual stress distribution in wire-arc directed energy deposited refractory molybdenum alloy utilizing numerical thermo-mechanical analysis and neutron diffraction method

Directed energy deposition (DED), a metal additive manufacturing (AM) technique, offers higher deposition rates and energy efficiency, making it suitable for fabricating components from refractory molybdenum alloys, such as molybdenum-titanium-zirconium (TZM). However, large thermal gradients and non-equilibrium thermal cycles in DED could generate high residual stress in the component, potentially deteriorating quality and performance. Thus, this study aims to investigate residual stress generation and its distribution in wire-arc DED of TZM thin-wall, utilizing thermo-mechanical analysis and high-fidelity neutron diffraction (ND) method. Two interpass temperatures (50°C and 200°C) have been considered to investigate their impact on residual stress formation. During experiments, in-situ thermal data has been recorded using thermocouples, which have been utilized for calibrating the thermal model. Thermocouple data shows a good agreement with the simulation results, having a difference of less than 10 %. Post-deposition part deformation has been observed, which is measured using a coordinate measuring machine, showing maximum values of 0.93 mm and 0.78 mm for interpass temperatures of 50°C and 200°C, respectively. Numerical predictions of distortion deviated by less than 15% from the experimental results. ND measurement and simulation results indicate that residual stress magnitude and evolution vary across the TZM deposits, revealing microstructural anisotropy in both conditions. Notably, lower interpass temperatures resulted in higher residual stresses, confirmed by experimental and simulation data. Further, this study demonstrated that an integrated experimental and thermo-mechanical analysis can potentially reveal the temperature history, part deformation, and residual stress formation in wire-arc DED TZM alloy.

36 MATERIALS SCIENCE

Digital bead modeling for wire-arc directed energy deposition

Prediction of 2D cross-section and full 3D geometry for stacked weld beads is critical for the outcome of wire-arc directed energy deposition (DED) parts; however, most additive path planning software packages model beads as extrusions of a rectangle. Weld beads are not rectangular, and the resulting shape is dependent upon physics effects at the moment of deposition. Physics phenomena such as the geometry of the underlying surface, the heat input of the welding mode, and the direction of gravity contribute to bead shape. Here, this paper presents a novel implicit modeling method that discretizes a 2D area or 3D volume of space into pixels or voxels and constructs fields based on these physics phenomena. The fields are combined using a weighting scheme trained on 3D scan measurements of welds and wire-arc DED prints. Pixels or voxels are added until the known amount of deposited volume has been achieved. Thereby, a strong conservation of mass principle is applied to the process. Utilizing machine learning techniques, the present model can be trained on a database of scans allowing for the representation of a wide variety of prints. Results show that this method can produce predictions with realistic bead morphology and sub-millimeter form error.

Bead geometry modeling

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

Advancing Temperature Monitoring of the Bottom Anode in a Direct Current Electric Arc Furnace Operations with Distributed Optical Fiber Sensors.

The bottom anode in the Direct Current Electric Arc Furnace (DC EAF) is critical for completing the electrical circuit necessary for sustaining the arc within the furnace. For pin-type bottom anodes, monitoring of the temperature of select pins instrumented with thermocouples is performed to track bottom wear in the EAF and inform the operator when the furnace should be removed from service. Furthermore, this work presents the results from a plant trial using distributed temperature monitoring of bottom anode pins in a 165-ton DC EAF over a two-month service period utilizing two optical fiber sensing techniques: fiber Bragg grating (FBG) and Rayleigh backscattering (RBS). The early detection of temperature anomalies along the length of the anode pin through distributed sensing enhances operational safety, providing a robust alternative to traditional thermocouples.

42 ENGINEERING

UZrCN Synthesis via Arc Melting

The next generation of nuclear reactors for both power production and space nuclear propulsion require fuel that is more durable, thermally stable, and more thermally conductive to support rapid heat transfer. High temperature gas reactors (HTGR), advanced gas reactors (AGR), and space-based nuclear thermal propulsion (NTP) are advanced reactor concepts that require a fuel type that can withstand high temperatures (1000-2900K) and flow of corrosive gas coolants such as helium, hydrogen, and carbon dioxide. One fuel with the potential to meet these demanding requirements is uranium-zirconium-carbonitride (UZrCN). UZrCN has many favorable fuel qualities compared to other eligible fuel forms such as uranium dioxide (UO 2 ) and uranium mononitride (UN) that could support the aforementioned reactor concepts. UZrCN has an exceptionally high operating temperature and thermal conductivity which are highly desirable to improve reactor economics and safety. It far exceeds the properties of UO 2 which is the most common fuel form in the United States. UZrCN also surpasses UN in terms of thermal conductivity and operating temperature by eliminating the dissociation problem UN has at 1700K. UZrCN could improve gas reactor performance and enable NTP technologies; however, it is an under-researched fuel that lacks rigorous scientific study. In recent efforts by the Idaho National Laboratory, a variety of novel methods to produce this fuel composition have been explored. One such method is via arc melting of uranium, zirconium, and carbon under a nitrogen atmosphere. Alloy fabrication using arc melting has been utilized for close to 150 years now and is well-understood as a method for rapid alloy prototyping. This process will be used to perform in-situ nitriding to form UZrCN.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS

Dynamic Heat Flow and Current Distribution Analysis in the Bottom Anode of an Electric Arc Furnace Using Fiber-Optic Sensors

A reliable method for monitoring bottom anode wear during DC Electric Arc Furnace (DC-EAF) operation is of critical importance for safe and efficient steel production. Underestimation of bottom wear poses a serious safety risk that must be avoided, while overestimation of bottom wear also poses challenges, as premature anode replacement is expensive and affects EAF productivity. Previously, we demonstrated that fiber-optic sensors can be successfully deployed to create a spatially distributed temperature map to monitor the health of the anode. The present work explores the heat flow and current density distribution in bottom anode pins to predict bottom wear, steel penetration events, and monitor refractory erosion. Small dynamic variations in pin temperature induced by joule heating during arcing also provide a means to observe local current flows in each pin. When mapped, these measurements provide a real-time view of the non-uniform and dynamic current flow in the bottom anode during EAF operation that can affect bottom wear.

Bottom Anode

UZrCN Formation via Arc Melting – A Novel Synthesis Study

The next generation of nuclear reactors for both power production and space nuclear propulsion require fuel that is more durable, thermally stable, and more thermally conductive to support rapid heat transfer. High temperature gas reactors (HTGR), advanced gas reactors (AGR), and space-based nuclear thermal propulsion (NTP) are advanced reactor concepts that require a fuel type that can withstand high temperatures (1000-2900K) and flow of corrosive gas coolants such as helium, hydrogen, and carbon dioxide. One fuel with the potential to meet these demanding requirements is uranium-zirconium-carbonitride (UZrCN). UZrCN has many favorable fuel qualities compared to other eligible fuel forms such as uranium dioxide (UO2) and uranium mononitride (UN) that could support the aforementioned reactor concepts. UZrCN has an exceptionally high operating temperature and thermal conductivity which are highly desirable to improve reactor economics and safety. It far exceeds the properties of UO2 which is the most common fuel form in the United States. UZrCN also surpasses UN in terms of thermal conductivity and operating temperature by eliminating the dissociation problem UN has at 1700K. UZrCN could improve gas reactor performance and enable NTP technologies; however, it is an under-researched fuel that lacks rigorous scientific study. In recent efforts by the Idaho National Laboratory, a variety of novel methods to produce this fuel composition have been explored. One such method is via arc melting of uranium, zirconium, and carbon under a nitrogen atmosphere. Alloy fabrication using arc melting has been utilized for close to 150 years now and is well-understood as a method for rapid alloy prototyping. This process will be used to perform in-situ nitriding to form UZrCN.

36 MATERIALS SCIENCE

Oscillating surge wave energy converter using a novel above-water power takeoff with belt-arc speed amplification

We investigate the performance of a novel power takeoff (PTO) featuring belt-arc speed amplification for oscillating surge wave energy converters (OSWECs), aiming to address the challenges of extremely low rotary speed and large torque under the low-frequency ocean wave excitations. The belt-arc design significantly increases the rotary speed of the generator, enabling generator downsizing and decreasing the powertrain friction losses. The design also allows for placing the generator above water, eliminating the need for high Ingress Protection ratings for the generator and powertrain, and potentially leading to substantial reductions in capital and maintenance costs. Using the linear potential wave theory, the dynamics of the integrated system are analyzed, and key parameters are identified. To validate the numerical analysis, a 1:10 scale model is designed, fabricated, and tested in a wave tank. Performance evaluations are conducted under regular and irregular wave conditions, with quantified effects of parameter tuning. The results reveal an optimal wave-to-electric efficiency of 48% under regular wave excitation and 20% under irregular excitation. Furthermore, these findings underscore the effectiveness of the proposed novel PTO design in addressing the challenges of low rotation speed and large torque inherent in OSWECs, demonstrating its ability to efficiently convert wave power into electricity.

16 TIDAL AND WAVE POWER

The high-field tokamak physics basis for the ARC fusion power plant

This editorial summarizes the physics basis underlying the ARC high-field tokamak fusion power plant, including recent advances in tokamak plasma understanding, the role of the SPARC device, and key remaining physics questions. It describes how these results guide the ARC Version 3A design and outlines opportunities for the broader fusion community to contribute to the development of first-generation fusion power plants.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY

Topological Fermi-arc surface state covered by floating electrons on a two-dimensional electride

Two-dimensional electrides can acquire topologically non-trivial phases due to intriguing interplay between the cationic atomic layers and anionic electron layers. However, experimental evidence of topological surface states has yet to be verified. Here, via angle-resolved photoemission spectroscopy (ARPES) and scanning tunnelling microscopy (STM), we probe the magnetic Weyl states of the ferromagnetic electride [Gd 2 C] 2+ ·2e - . In particular, the presence of Weyl cones and Fermi-arc states is demonstrated through photon energy-dependent ARPES measurements, agreeing with theoretical band structure calculations. Notably, the STM measurements reveal that the Fermi-arc states exist underneath a floating quantum electron liquid on the top Gd layer, forming double-stacked surface states in a heterostructure. Our work thus not only unveils the non-trivial topology of the [Gd 2 C] 2+ ·2e - electride but also realizes a surface heterostructure that can host phenomena distinct from the bulk.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC

Simulation of metal nanoparticles growth in methane atmosphere of arc discharge: comparison to experiment

A direct current arc discharge in a methane atmosphere is a scalable and sustainable method to produce metal-carbon core–shell nanoparticles and single-walled carbon nanotubes, where a metal catalyst can be continuously supplied through evaporation of an anode made from the catalyst material. The size of catalyst particles is of critical importance as it can affect the synthesis yield and properties of nanotubes and core–shell nanoparticles. This study presents a numerical model describing the formation and growth of metal particles for the conditions representative of the arc discharge with an evaporating iron anode at near-atmospheric pressure of a methane-rich atmosphere. The model incorporates carbon adsorption to the metal surface and explains the limiting effect of carbon coverage on the size of metal nanoparticles. The predicted particle sizes are compared with experimental observations. The model also predicts higher concentrations of metal particles with the increasing partial pressure of methane.

77 NANOSCIENCE AND NANOTECHNOLOGY

ARC-DPA 1-MeV Neutron Fluence Equivalence Model for GaAs

Here, the legacy data used in the production of the American Society for Testing and Materials (ASTM) E722 standard for gallium arsenide (GaAs) were fit with the athermal recombination corrected-displacements per atom (ARC-DPA) model for the development of a novel 1-MeV neutron equivalent fluence metric. Improving on previous work, the coefficients for the ARC-DPA model were optimized using a conjugate gradient method, and the uncertainties in the observed damage in different benchmark neutron fields were sampled to quantify their contribution to the damage metric. The optimized parameters of −0.474 ± 0.03 for b arcdpa and 0.016 ± 0.002 for c arcdpa provided good agreement and indicated that the solution is not sensitive to the corresponding fluence uncertainties. Compared to the current 1-MeV neutron fluence equivalence standard for displacement damage in GaAs, our results indicate that for a thermal reactor neutron environment, displacement damage has been underestimated by around 25% and that the saturation value for the damage efficiency had been higher than previously modeled.

1-MeV equivalent fluence

A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process

Recent progress in sensing techniques and data analytics tools have significantly accelerated the development of Wire Arc Additive Manufacturing (WAAM) systems. This data centric approach emphasizes leveraging available data throughout the production process to optimize performance. Integration of extensive data analysis provides the opportunity to improve precision, reduce waste, and enhance the quality of produced parts. This method relies on AI/ML models and optimization techniques, which are developed using the data collected from various sources, including in-situ sensors, ex-situ imaging, and manufacturing process parameters. The quality and diversity of this data, along with the alignment between different data streams (achieved through spatiotemporal registration) are critical for the successful development of AI/ML and optimization models. In this work, we present a spatiotemporally registered dataset generated during the WAAM process of deposition of a rectangular block. The dataset includes the comprehensive description of deposition process, process parameters, in-situ collected welding characteristics, acoustic data, and X-Ray Computed Tomography analysis data for the build. Dataset A Co-Registered In-Situ and Ex-Situ Dataset of Electrical, Acoustic, and CT Characteristics from Wire Arc Additive Manufacturing Process has arisen under UT-Battelle, LLC’s Prime Contract No. DE-AC05-00OR22725 with the U.S. Department of Energy (DOE) to manage and operate the Oak Ridge National Laboratory. UT-Battelle, LLC will not assert any rights under United States law or under the Prime Contract it has in the dataset against any user of the dataset, including any copyrights or patent rights. UT-Battelle, LLC requests that attribution to the dataset is provided as academically appropriate.

42 ENGINEERING

Subsurface microbial community structure shifts along the geological features of the Central American Volcanic Arc

Subduction of the Cocos and Nazca oceanic plates beneath the Caribbean plate drives the upward movement of deep fluids enriched in carbon, nitrogen, sulfur, and iron along the Central American Volcanic Arc (CAVA). These compounds fuel diverse subsurface microbial communities that in turn alter the distribution, redox state, and isotopic composition of these compounds. Microbial community structure and functions vary according to deep fluid delivery across the arc, but less is known about how microbial communities differ along the axis of a convergent margin as geological features (e.g., extent of volcanism and subduction geometry) shift. Here, we investigate changes in bacterial 16S rRNA gene amplicons and geochemical analysis of deeply-sourced seeps along the southern CAVA, where subduction of the Cocos Ridge alters the geological setting. We find shifts in community composition along the convergent margin, with communities in similar geological settings clustering together independently of the proximity of sample sites. Microbial community composition correlates with geological variables such as host rock type, maturity of hydrothermal fluid and slab depth along different segments of the CAVA. This reveals tight coupling between deep Earth processes and subsurface microbial activity, controlling community distribution, structure and composition along a convergent margin.

Science & Technology - Other Topics

Beam correction for multi-pass arcs in FFA@CEBAF: status update

This work examines the multi-pass steering of six electron beams in an FFA arc ranging from approximately 10.5 GeV to 22 GeV. Shown here is an algorithm based on singular value decomposition (SVD) to successfully steer all six beams through the arc given precise knowledge of all beam positions at each of one hundred and one diagnostic locations with one hundred individual corrector magnets: that is successive application of SVD to different 100 × 101 response matrices—one for each beam energy. Further, a machine learning scheme is developed which only requires knowledge of the energy-averaged beam position at each location to provide equivalent steering. Extension of this scheme to other beam optics quantities as well as transverse and longitudinal coupling is explored.

Accelerator Physics

Code Coverage Status of the ARC Code DASSH-F

The Argonne Reactor Code (ARC) software system supports users in their fast reactor design goals by providing neutronic, thermal-hydraulic, and structural analysis capabilities. DASSH-F serves as a steady state thermal hydraulic capability within the ARC system and replaces the SE2-ANL software that preceded it. This document identifies the set of test problems used to assess the code coverage for DASSH-F. The goal is to document what parts of the existing DASSH-F code are touched by the set of test problems and which are not. Because the verification work remains to be done on DASSH-F, one can assume that most of these issues will be resolved as part of that work. The code coverage analysis of DASSH-F was performed with the Code Coverage Tool of the Intel Fortran compiler which requires modifications to the compilation of DASSH-F. The code coverage tables are given for each submodule of DASSH-F. Because DASSH-F links to modules in DIF3D, some details on coverage changes to the DIF3D linked files is provided. As will be seen, most of the uncovered parts/files can be ignored because they are either for error message and debugging output or obviously not needed by DASSH-F today. Seven features of the DASSH-F code were identified to not be covered by the existing testing suite and thus additional verification test problems are suggested to fully cover these sections.

22 GENERAL STUDIES OF NUCLEAR REACTORS

Current-Regulated Arc Modulator Optimization

n this study, the performance of a current-regulated arc modulator was investigated with a focus on its role in initiating and sustaining plasma discharge within the Magnetron Body of the LINAC system. The analysis centered on how switching components, circuit topology, and feedback loop architecture influence critical factors such as energy efficiency, discharge stability, and long-term plasma containment. Particular attention was given to variations in pulse termination behavior, as observed through oscilloscope traces, which revealed inconsistencies affecting the duty factor and cathode temperature. These fluctuations have downstream effects on the cesium-coated cathode surface, thereby impacting H⁻ ion production and beam reliability. Simulation-based testing in LTspice was used to evaluate noise suppression techniques and arc current regulation schemes, revealing how optimized snubber networks, improved pulse shaping, and feedback stability can mitigate modulator-induced noise. The results ide

Campos, Nathan