Laser Beam Directed Energy Deposition (LB-DED) Fabrication of Novel Refractory High Entropy Alloys (RHEAs)
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This comprehensive investigation examines the structure–property relationships in two nuclear alloy systems—Alloy 709 (A709) austenitic stainless steel and Grade 92 (G-92) ferritic/martensitic (F/M) steel—manufactured via directed energy deposition (DED) for sodium-cooled fast reactor applications. This study establishes the fundamental mechanisms for controlling microstructures for optimizing the mechanical performance of additively manufactured nuclear materials through systematic heat treatment optimization and multiscale characterization. As-deposited A709 steel develops a complex multiscale strengthening architecture consisting of a fine cellular solidification structure with diameter of 2-3 µm within10–50 µm grains, elevated dislocation densities from rapid thermal cycling, and grain boundary precipitates that activate concurrent Hall–Petch, dislocation, and precipitation hardening mechanisms to achieve exceptional properties [yield strength (YS): 603 MPa, ultimate tensile strength (UTS): 844 MPa, Vickers hardness: 220 HV] that achieve a 44% superior strength compared to that of the wrought material. Heat treatments produce different results. Solution annealing (SA) dissolves the cellular structure and reduces the hardness to 190 HV. Precipitation treatment (PT) keeps the cellular structure but adds carbides, allowing the hardness to reach 205 HV. The best approach combines both treatments (SA+PT) and creates uniform precipitate distributions with M 23 C 6 carbides at the grain boundaries and MX carbonitrides in the matrix, achieving a hardness of 195 HV. However, directional differences persist, with a 12%–15% strength variation between orientations due to the inherited layered microstructural architecture that survives aggressive heat treatment. While tensile testing at 550°C demonstrates 40%–50% thermal softening with dynamic strain aging, DED A709 steel still maintains a 71% higher YS than that of the wrought material. Ion irradiation studies (100–400 dpa) of DED A709 steel reveal progressive radiation damage with increasing void density and radiation-induced segregation causing nickel enrichment and chromium depletion, which will ultimately compromise mechanical properties. As-deposited G-92 exhibits exceptional strength (UTS: 1650–1700 MPa, 430 HV) through a complex microstructure containing both ferrite and martensite phases, a high geometrically necessary dislocation (GND) density (17.04×10 14 /m 2 ), and fine carbides. Heat treatments create distinct changes. Normalizing produces fresh martensite with the highest hardness (460 HV) and an increased GND density (20.23×10 14 /m 2 ). Tempering develops dual precipitation systems and reduces the hardness to 290 HV. The optimal approach uses sequential normalizing plus tempering, achieving balanced properties with the lowest hardness (250 HV) and a reduced GND density (11.01×10 14 /m 2 ). A processing-dependent anisotropy is observed: horizontal specimens achieve superior ductile behavior, while vertical specimens exhibit brittle failure. A tempering heat treatment successfully mitigates this anisotropic behavior by transforming the hard martensitic as-deposited structure into tempered martensite enabling both horizontal and vertical specimens to exhibit similar stress–strain characteristics with visible necking behavior. Remarkably, testing at 550°C reveals a reversal in the anisotropy, where as-deposited specimens achieve near isotropy with superior thermal stability (a 15%–20% strength reduction), while tempered specimens develop an orientation dependence with a 25%–30% strength reduction. Both alloy systems demonstrate that DED processing creates specimens with a superior strength through refined microstructural features, though with distinct strengthening mechanisms—austenitic through cellular structures and precipitates versus F/M through phase transformations and precipitates. Heat treatment optimization requires alloy-specific approaches, with A709 benefiting from controlled precipitation while G-92 requires careful phase transformation control. The results show that DED manufacturing can produce nuclear materials with exceptional performance, but directional effects and temperature-dependent behavior must be carefully considered for reactor component design and qualification.
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Defects are a leading issue for the rejection of parts manufactured through the Directed Energy Deposition (DED) Additive Manufacturing (AM) process. In an attempt to illuminate and advance in situ quality monitoring and control of workpieces, we present an innovative data-driven method that synchronously collects sensing data and AM process parameters with a low sampling rate during the DED process. The proposed data-driven technique determines the important influences that individual printing parameters and sensing features have on prediction at the inter-layer qualification to perform feature selection. Three Machine Learning (ML) algorithms including Random Forest (RF), Support Vector Machine (SVM), and Convolutional Neural Network (CNN) are used. During post-production, a threshold is applied to detect low-density occurrences such as porosity sizes and quantities from CT scans that render individual layers acceptable or unacceptable. This information is fed to the ML models for training. Training/testing are completed offline on samples deemed “high-quality” and “low-quality”, utilizing only features recorded from the build process. CNN results show that the classification of acceptable/unacceptable layers can reach between 90% accuracy while training/testing on a “high-quality” sample and dip to 65% accuracy when trained/tested on “low-quality”/“high-quality” (respectively), indicating over-fitting but showing CNN as a promising inter-layer classifier.
Large-Eddy Simulations (LES) of a gasoline spray, where the mixture was ignited rapidly during or after injection, were performed in comparison to a previous experimental study with quantitative flame motion and soot formation data [SAE 2020-01-0291] and an accompanying Reynolds-Averaged Navier–Stokes (RANS) simulation at the same conditions. The present study reveals major shortcomings in common RANS combustion modeling practices that are significantly improved using LES at the conditions of the study, specifically for the phenomenon of rapid ignition in the highly turbulent, stratified mixture. At different ignition timings, benchmarks for the study include spray mixing and evaporation, flame propagation after ignition, and soot formation in rich mixtures. A comparison of the simulations and the experiments showed that the LES with Dynamic Structure turbulence were able to capture correctly the liquid penetration length, and to some extent, spray collapse demonstrated in the experiments. For early and intermediate ignition timings, the LES showed excellent agreement to the measurements in terms of flame structure, extent of flame penetration, and heat-release rate. However, RANS simulations (employing the common G-equation or well-stirred reactor) showed much too rapid flame spread and heat release, with connections to the predicted turbulent kinetic energy. With confidence in the LES for predicted mixture and flame motion, the predicted soot formation/oxidation was also compared to the experiments. The soot location was well captured in the LES, but the soot mass was largely underestimated using the empirical Hiroyasu model. An analysis of the predicted fuel–air mixture was used to explain different flame propagation speeds and soot production tendencies when varying ignition timing.
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Abstract not provided.
An apparatus, comprising: Mach-Zehnder modulators (MZMs) numbered MZM #1 to MZM #n that exhibit nonlinearity between an input electrical domain signal and an output optical domain signal; a waveform source for applying a first voltage waveform to a first optical arm of said MZM #1; a laser source configured to direct laser light into the two arms of at least said MZM #1 to produce a first output optical domain signal; the apparatus being provided for utilizing said first output optical signal and the nonlinearities of MZMs numbered MZM #2 to said MZM #n to produce a final output voltage waveform that, compared to said input voltage, comprises at least one of: a shorter rise time, a shorter fall time, an increased signal temporal resolution or small signal dynamic range, an increased vertical resolution for small signals or large signals, a reduced noise on small signals or large signals and an increased bandwidth.
Laser-direct-drive symmetric implosions on OMEGA illuminate a target with 60 laser beams and are designed to produce spherical implosions. Each beam is smoothed using orthogonal polarizations obtained by passing through distributed polarization rotators (DPR’s). Observations of the scattered light from OMEGA implosions do not show the expected symmetry and have much larger variation than standard predictions. For the first time, we have quantified the scattered-light nonuniformity from individual beams and identified the DPR’s as the source of the enhanced nonuniformity. An instrument was invented that isolated and measured the variation in the intensity and polarization of the light scattered from each OMEGA beam. The asymmetric intensity and polarization measurements are explained when the on-target offsets between the two orthogonal polarizations produced by the DPR’s are modeled using a 3-D cross-beam energy transfer (CBET) code that tracks the polarizations of each beam. The time-integrated nonuniformity in laser absorption and scattered light due to CBET and the DPR polarization offsets during high-performance OMEGA implosions is predicted to be significant and dominated by low spherical harmonic mode numbers. Further, the nonuniformity is predicted to be greatly reduced by replacing the DPR’s with new optics that create smaller offsets.
The mechanical performance of an Fe-Co intermetallic alloy processed by laser powder bed fusion (L-PBF) and laser directed energy deposition (L-DED) additive manufacturing is compared. L-PBF material was characterized by high strength (500–550 MPa) and high ductility (35%) in tension, corresponding to a ~250% increase in strength and an order-of-magnitude improvement in ductility relative to conventional material. Conversely, L-DED material exhibited similarly poor tensile properties to the conventional wrought alloy, with low strength (200–300 MPa) and low ductility (0–2.7%). Finally, the disparity in properties between L-PBF and L-DED material is discussed in the context of the fundamental differences between manufacturing methods.
Abstract Powder fed laser directed energy deposition systems show significant promise and their widespread adoption could greatly advance manufacturing technology; however, a significant amount of gas atomized metal powder is wasted during material deposition. As contaminated powder must be collected and disposed of as hazardous waste, this process is often criticized for its low catchment efficiency. This presents potential implementation and scaling issues, as widespread use of this technology would directly increase the amount of contaminated powder in need of safe disposal. A direct contribution to this waste issue was identified in past work as wearing exterior and interior surfaces on a replaceable nozzle component within the additive head of such a system integrated into a hybrid manufacturing machine tool. A computational fluid dynamics simulation is developed specifically for use within the manufacturing process by predicting catchment efficiency losses before a deposition operation is performed. The model is robust enough to calculate a catchment efficiency estimate within a reasonable transition time before deposition and is designed to replace visual estimation of nozzle deterioration by the machine operator. Both of two previously identified wear modes are represented in the simulation. Their effects on powder stream geometry are discussed in detail and the results are compared with in-situ measurements of powder stream geometry and concentrations. The resulting work contributes to the growing understanding of using prediction and prevention methods on catchment efficiency related part defects within these systems.
Laser three-dimensional (3D) manufacturing technologies have gained substantial attention to fabricate 3D structured electrochemical rechargeable batteries. Laser 3D manufacturing techniques offer excellent 3D microstructure controllability, good design flexibility, process simplicity, and high energy and cost efficiencies, which are beneficial for rechargeable battery cell manufacturing. In this review, notable progress in development of the rechargeable battery cells via laser 3D manufacturing techniques is introduced and discussed. The basic concepts and remarkable achievements of four representative laser 3D manufacturing techniques such as selective laser sintering (or melting) techniques, direct laser writing for graphene-based electrodes, laser-induced forward transfer technique and laser ablation subtractive manufacturing are highlighted. Finally, major challenges and prospects of the laser 3D manufacturing technologies for battery cell manufacturing will be provided.
The transition to condition-based, risk-informed automated maintenance will contribute to a significant reduction of operations and maintenance costs that account for the majority of nuclear power generation costs. Furthermore, of the operations and maintenance costs in U.S. plants, approximately 80% are labor costs. To address the issue of rising operating costs and economic viability, technologies used to perform online monitoring of piping and other secondary system structural components in commercial nuclear power plants (NPPs) are under evaluation. These online monitoring systems have the potential to identify when a more detailed inspection is needed using real time measurements, rather than at a pre-determined inspection interval thus reducing the maintenance cost. This paper describes distributed high-temperature stable fiber sensors fabricated in optical fibers through a roll-to-roll laser direct writing process using femtosecond lasers. Using phase-sensitive optical time domain reflectometry, distributed acoustic and vibration sensors can be developed and deployed to critical components and systems in NPPs to perform active measurements with spatial resolution down to 0.5-meter throughout the piping systems. Complex acoustic and vibration signatures harnessed by distributed sensors are registered and analyzed by artificial intelligence algorithms for degradation detection and flaw identification. Piping elbows with machined-in flaws were instrumented with fiber sensors. High-spatial-resolution data were used to develop and validate machine learning algorithms, including both linear and nonlinear regression, and classification. Additionally, classification and sensor analysis were also performed for data analysis. The paper concludes with recommendations and future work on applications of machine learning enabled high-resolution fiber sensors for piping degradation monitoring in current or future NPPs.
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Three dimensional polarization-dependent CBET plus beam balance and pointing are required to model nonuniformity in direct-drive implosions on OMEGA. Uniform laser energy absorption is essential for successful laser-direct-drive inertial confinement fusion but a growing body of evidence suggests OMEGA implosions are more asymmetric than predictions. By measuring the intensity and polarization of light scattered from individual beams, we have identified OMEGA’s polarization smoothing via distributed polarization rotators (DPR’s) as one previously unrealized source of nonuniformity. Polarization-dependent CBET along with beam energy balance, and beam pointing require three-dimensional modeling. Laser absorption mode 1 predictions from a fully three-dimensional CBET model correlate well with the observed direction of the core flow.
Abstract Relativistic transparency enables volumetric laser interaction with overdense plasmas and direct laser acceleration of electrons to relativistic velocities. The dense electron current generates a magnetic filament with field strength of the order of the laser amplitude (>10 5 T). The magnetic filament traps the electrons radially, enabling efficient acceleration and conversion of laser energy into MeV photons by electron oscillations in the filament. The use of microstructured targets stabilizes the hosing instabilities associated with relativistically transparent interactions, resulting in robust and repeatable production of this phenomenon. Analytical scaling laws are derived to describe the radiated photon spectrum and energy from the magnetic filament phenomenon in terms of the laser intensity, focal radius, pulse duration, and the plasma density. These scaling laws are compared to 3D particle-in-cell (PIC) simulations, demonstrating agreement over two regimes of focal radius. Preliminary experiments to study this phenomenon at moderate intensity ( a 0 ∼ 30) were performed on the Texas Petawatt Laser. Experimental signatures of the magnetic filament phenomenon are observed in the electron and photon spectra recorded in a subset of these experiments that is consistent with the experimental design, analytical scaling and 3D PIC simulations. Implications for future experimental campaigns are discussed.