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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 55 records · Page 3
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Evaluation of In-Situ AM Process Monitoring Techniques and Potential for Detecting Process Anomalies and Undesirable Microstructures

The US Department of Energy’s Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing rapid qualification of new materials for fabrication of nuclear relevant components using advanced manufacturing techniques. Particular interest is placed on code-qualifying stainless steel (SS) 316H processed by laser powder bed fusion (LPBF) additive manufacturing. A paradigm that incorporates data from in-situ sensing during the printing, ex-situ characterization, and advanced artificial intelligence–based models was established under the Transformation Challenge Reactor (TCR) program to develop a pedigree for each fabricated component that could be tracked from the feedstock to the component’s release for application. Under the TCR program, the Peregrine software was developed as a tool for incorporating the vast amounts of in-situ and ex-situ characterization data collected; all data stored on a rapidly growing digital platform. The digital platform allows for users to link site-specific process anomalies to the macro- and microstructure. The platform will eventually be able to predict component performance, which will be crucial to qualifying materials and components in risk-averse industries such as those supporting and building nuclear reactors. Current in-situ process monitoring techniques that are already integrated with software like Peregrine are advantageous for identifying process anomalies including powder spatter, component edge swelling, recoating-build interactions, and so on. However, additional data are required to fully predict the resulting microstructures needed for identifying relationships to component performance. The rapid cooling rates observed in LPBF are some of the highest of any bulk manufacturing process, resulting in heterogenous microstructures and typically causing anisotropy in mechanical properties. Moreover, evolved residual thermal stresses are high, which can cause severe defects such as delamination or cracking. Therefore, other in-situ monitoring methods are warranted for exploration to measure and map the thermal history, and potentially the stress state, of each build. This report summarizes different in-situ monitoring strategies proposed for LPBF with a focus on the more developed sensor systems. Novel capabilities for measuring melt pool temperatures are also addressed to better inform modeling efforts.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Rapid Solidification Effects in Additively Manufactured Si and SiGe Compositions

SiGe alloys have a proven track record as robust high-temperature thermoelectric materials, powering NASA missions like SNAP-10A, LES-9, and Voyager 1 and 2. Enhancing thermoelectric efficiency hinges on minimizing thermal conductivity while preserving electrical conductivity. Rapid solidification via LPBF can generate microstructural features such as subgrain cellular boundaries and twinning, which may help reduce thermal conductivity while preserving semiconducting behavior. Here, this study investigates the potential of laser powder bed fusion (LPBF) additive manufacturing to fabricate nanostructured Si and SiGe thermoelectric materials. High cooling rates (10 5 to 10 7 K/s) rates inherent to the LPBF process are conducive to forming such nanostructures. Moreover, this fabrication technique could also be suitable for fabricating complex geometries needed to achieve improved device level performance. Process mapping of commercial Si powder with irregular morphology was first performed to understand the LPBF processing behavior of this semiconductor material. Subsequent studies included in-house synthesized B-doped (p-type) Si7 8 Ge 22 spherical powder that was produced via ultrasonic atomization. Scan strategies involved multiple laser exposures to mitigate solidification cracking: a high density of >98% was achieved, but solidification cracking could not be fully eliminated. Subsequently, a high electrical resistivity (i.e., low conductivity) was observed, but the measured Seebeck coefficient, ∼230 μV/K @ 500 °C, proved that good semiconductor material was being fabricated. A subgrain cellular structure (5–10 μm) was observed as defined by Ge segregation to the intercellular boundaries. The remelting strategies helped lower the cooling rates in processing SiGe, but this still resulted in high residual stresses, which induced a remarkably high density of twins (78–95%) to accommodate the deformation. This unique grain structure offers an avenue for phonon scattering and potential improvements in thermoelectric performance.

figure of merit↗
DOE OSTI2025

Tensile Performance Sensitivity to Variations of Standard 17-4 PH Heat Treatments on LPBF-Produced Material

Standard heat treatments for metals of a particular composition are typically designed with the assumption of a conventional starting microstructure, such as that produced by casting or wrought processing. When applied to metals fabricated by Laser Powder Bed Fusion (LPBF) metal additive manufacturing (AM), these heat treatments can produce inconsistent performance due to the unique as-built microstructures. This study investigates how modifications to standard heat treatments for 17-4 PH steel influence the microstructure and mechanical properties of LPBF-fabricated material. Specimens were produced and subjected to varying solutionizing and homogenizing treatments followed by standard aging treatments. Microstructures were characterized using optical microscopy, Electron Backscatter Diffraction (EBSD), and X-ray diffraction (XRD), and mechanical properties were evaluated through uniaxial tensile testing. Based on these results, recommendations are provided for achieving improved wrought-like performance in LPBF 17-4 PH steel.

17-4 PH↗
DOE OSTI2025

Compatibility of molten plutonium with wrought and additively manufactured metal crucibles

Understanding plutonium’s interaction with metals is crucial for optimizing pyrochemical operations, nuclear fuel containment, and various actinide processing techniques. Traditionally, tantalum crucibles are employed for plutonium processing due to their high durability, excellent temperature stability, and low solubility in plutonium. However, tantalum faces challenges such as plutonium wetting and diffusion, making surface coatings particularly important for crucibles in pyrochemical applications to enhance corrosion resistance against plutonium. Tantalum is also expensive and difficult to machine, prompting the need for advanced manufacturing techniques to address these challenges. Here, in this work, we investigate the interaction of Pu with tantalum and titanium crucibles fabricated using both traditional machining methods and laser powder bed fusion (LPBF) additive manufacturing (AM). LPBF-AM is an advanced technique that allows for the creation of complex geometries from traditionally difficult-to-machine metals by using a high-powered laser to build parts. Previous studies of conventional manufactured tantalum have utilized oxidation and carburization of the surface to mitigate plutonium wetting; however, no studies of surface modified LPBF-AM material have been undertaken. These studies are crucial, given the typical differences in the grain structure between conventional and LPBF-AM materials. All crucibles underwent differential scanning calorimetry to confirm the melting of plutonium. Subsequently, the crucibles were sectioned and mounted in epoxy for microstructural analysis using optical microscopy and scanning electron microscopy. This investigation, comparing the performance of wrought vs AM metal crucibles, provides a basis for future tooling applications in actinide processing techniques and can address the challenges associated with traditional machining, particularly in pyrochemical applications.

Actinides↗
DOE OSTI2025

Effect of laser melt schedule on the microstructure of additively manufactured IN718 Superalloy

Laser powder bed fusion (L-PBF) has enabled the fabrication of geometrically complex metallic structures and components that are challenging to producing using conventional manufacturing approaches. The site-specific and far from equilibrium thermal conditions of L-PBF offer the potential to facilitate multi-length scale design of structure and properties across the atomic-through macro-levels. However, L-PBF systems face scalability challenges due to throughput constraints. Laser rotary powder bed fusion (L-RPBF) systems are being investigated as a solution to enhance the deposition rates compared to conventional L-PBF. Rotary systems also offer additional flexibility for controlling the time structure of melting through laser interleaving on alternating layers. Here, in this study, IN718 test samples were printed using single-laser or interleaved dual-laser configuration in a L-RPBF system to investigates the effect of process settings and melt-interleaving on as-fabricated microstructure. The microstructural evolution, such as grain size and crystallographic texture, was assessed by determining variations in the melt-pool shapes. Laser interleaving leads to a reduction in average grain size compared to single laser by ∼ 40 % at high power (400 W) and by ∼36 % at medium power (370 W). Results presented here identify key challenge for obtaining uniform microstructures and barriers for the broader adoption of high-deposition rate L-RPBF.

Dual-laser↗
DOE OSTI2025

Chemistry effects on ODS steel consolidated via laser powder bed fusion from GARS powder

Oxide Dispersion Strengthened (ODS) steels are promising candidate alloys for structural and cladding applications in extreme environments. They contain a high density of nanoscale oxides for high temperature mechanical strength and radiation resistance. In this work, gas atomization reaction synthesis (GARS) was used to produce powders that were used for additive manufacturing (AM) Laser Powder Bed Fusion consolidation of ODS steels, in order to skip the traditional mechanical alloying of blended yttria and alloy powders. Powder containing iron, chromium, and tungsten with varying amounts of yttrium, titanium, oxygen and zirconium were used to produce ODS steel samples. AM consolidated specimens and powder samples were characterized with transmission electron microscopy. TEM imaging, diffraction patterns, and energy dispersive X-ray spectroscopy (EDS) was used to identify phases present before and after consolidation across chemistries. The effect of the controlled oxygen input (from GARS) and the oxide-forming additions (Y, Ti, Zr) on precipitate size distribution and composition is substantiated and discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Design of Novel Hot Gas Path Component for Gas Turbine Engines Enabled by Materials and Additive Manufacturing Process Development

This report covers the activities associated with the development and evaluation of two high-γ’ superalloys that were designed by external partners on this project, namely Carpenter Technologies Corporation and the University of California-Santa Barbra. One alloy was GammaPrint-700, a cobalt-base superalloy, and the other a nickel-base (Ni-base) superalloy GammaPrint-1100. Both were found to be printable through laser powder bed fusion (LPBF) additive manufacturing, with optimal process parameter sets being identified for each alloy. Further, high temperature mechanical testing was conducted on each alloy that showed both materials performed better than the comparative baseline (LPBF Hastelloy X), with the Ni-base superalloy being down-selected for scaling and printing of the tip shoe components.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Multimodal Defect Imaging of Pure Tungsten Components Fabricated via Electron Beam Powder Bed Fusion

The utilization of additive manufacturing (AM) techniques for refractory materials in high-temperature environments has significantly expanded because of the ability to fabricate geometrically complex components. Electron beam powder bed fusion (EB-PBF), which provides lower residual stress, a cleaner vacuum environment, and better efficiency for high melting point, is one of the best-suited AM methods to produce advanced refractory components. However, the property variation attributed to the heterogeneous microstructure and process-induced defects has hindered the widespread adoption of EB-PBF-produced material like tungsten. While numerous in-situ monitoring and defect detection methods have been demonstrated for EB-PBF, a workflow that compares and evaluates process-induced abnormalities from different imaging perspectives is still limited. This study examines a feature-embedded tungsten component manufactured via the EB-PBF process to demonstrate the defect detection capabilities of a multimodal defect imaging workflow. The predefined and process-induced defects are evaluated by harnessing various imaging techniques, including in-situ electron imaging, layerwise near-infrared (NIR) imaging, post-build high-energy x-ray computed tomography (CT), and conventional destructive metallography. The results highlight the strengths and limitations of distinctive defect imaging techniques concerning specific defect types, sizes, and conditions. It was found that electron imaging can provide more abnormal detection capabilities while maintaining a higher measuring accuracy, against the conventional metallography in this case study, compared with NIR and CT imaging techniques.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Modeling low cycle fatigue (LCF) of additively manufactured Hastelloy X using An accelerated crystal plasticity fatigue damage model

This paper presents a microstructure-based model for low cycle fatigue (LCF) behavior and life of Nickel-based alloy Hastelloy X manufactured using laser-powder bed fusion (L-PBF) additive manufacturing (AM). AM Hastelloy X, a solution-strengthened alloy, is tested at elevated temperature under fully reversed LCF conditions at different strain levels. A generalized plane strain finite element model is generated from electron backscatter diffraction (EBSD) characterization. The constitutive behavior of the material under fatigue is modeled using crystal plasticity and calibrated with both monotonic tensile and cyclic stress–strain data. The fatigue micro-crack initiation and propagation in the microstructure is modeled using a modified Chaboche fatigue damage model. An embedded boundary condition with a homogenous medium is used to apply the cyclic deformation and prevent numerically introduced over-constraints during fatigue simulation. A ‘cycle-jump’ method is used to accelerate the fatigue simulation and reduce the computational cost. The simulation results are compared to LCF experiments, showing satisfactory matches in cyclic stress behavior and number of cycles to macro-crack initiation for all applied strain ranges. In addition, the model illustrates the potential for quantifying microscale fatigue life impacting factors such as microstructure and surface roughness, which is needed to accurately quantify the reliability of AM components in service.

36 MATERIALS SCIENCE↗
DOE OSTI2024

A Microchannel Heat Exchanger Produced From a Metal Matrix Composite by Hybrid Laser Powder Bed Fusion and Inkjet Printing

Abstract This paper explores the production of an oxide dispersion strengthened (ODS) 304L stainless steel microchannel heat exchanger (HX) using a hybrid additive manufacturing process of laser powder bed fusion and inkjet printing. The study investigates the capabilities and economics of the hybrid inkjet-laser powder bed fusion (LPBF) process and evaluates the dimensional accuracy, functionality, and mechanical properties of the resulting ODS alloy. The effectiveness and pressure drop of the ODS heat exchangers produced by the hybrid LPBF tool are also determined. Results show that the inkjet-doped samples have a lower mean channel height with higher standard deviation than samples produced by LPBF alone. This is attributed to greater absorption of laser energy for the powder coated with the oxide precursor. The economic analysis shows that the hybrid process has a potential for reducing the unit cost of the heat exchanger based on cost modeling assumptions.

Engineering↗
DOE OSTI2026

Shock-induced phase transitions and stacking fault formation in additively manufactured eutectic high-entropy alloy Ni 40 Co 20 Fe 10 Cr 10 Al 18 W 2

Ni 40 Co 20 Fe 10 Cr 10 Al 18 W 2 additively manufactured using laser powder bed fusion (LPBF) is among the toughest as-built alloys reported and is a promising candidate for use in extreme environments. However, its behavior under multi-megabar pressure regimes remains unexplored. We used femtosecond in situ X-ray diffraction to investigate the shock response of LPBF Ni40Co20Fe10Cr10Al18W2 under laser-driven shock compression and release. Our results reveal that the initial dual-phase face-centered + body-centered structure transforms to a single face-centered phase over a wide pressure range of 84±10 to 277±55 GPa, followed by a transition to a single body-centered phase at 431±48 GPa. We establish the Hugoniot equation-of-state of LPBF Ni 40 Co 20 Fe 10 Cr 10 Al 18 W 2 and compare it to the benchmark alloy AlCoCrFeNi 2.1 , demonstrating the effects of W-doping and increased Al content. High stacking fault probabilities, close to those measured in Au and Ag, are observed upon compression. A portion of the stacking faults are annihilated upon release to ambient pressure.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Temperature-dependent mechanical properties and crystal plasticity parameters for additively manufactured Haynes-214 alloy: Experiments and numerical modeling

Our experimental mechanical testing data demonstrated that the additively manufactured (AM) laser powder bed fusion (L-PBF) Haynes-214 alloy exhibits non-linear mechanical properties as the temperature rises from ambient to 870 °C. Crystal plasticity (CP) simulations provide an effective approach to gaining deeper insights into microstructure-property linkages under thermomechanical loading. This method can reduce the need for costly high-temperature mechanical testing while accounting for the effects of crystallographic texture and grain morphology on the mechanical behavior of AM materials. However, calibrating a CP model is time-consuming because individual simulations are computationally expensive and hundreds (or more) of iterations over parameter sets may be required. To address this issue, we have designed a machine learning-differential evolution (ML-DE) CP framework that can accurately interpolate the tensile properties of AM L-PBF Haynes-214 alloy across a wide temperature range from ambient to 870 °C, with minimal reliance on experimental data. The framework uses electron backscatter diffraction (EBSD) measurements to generate statistically equivalent microstructural volume elements to serve as inputs to the CP modeling framework. Stress–strain curves were generated from 1000 CP simulations, which serve as the training data set for the three ML regression algorithms explored: linear, extra-trees, and multi-layer perceptron. These three regression models were independently evaluated to compare their efficiency and identify the most suitable algorithm for the given problem. Results revealed that the extra-trees ML regressor outperforms the other models in both qualitative and quantitative aspects with an R 2 of 0.98. Subsequently, the differential evolution optimization approach is employed to calibrate the ML-based CP material parameters with experimental results obtained at various temperatures. Finally, temperature-dependent CP material parameters are formulated. The effectiveness and efficiency of the designed framework are validated through comparison with experimental results, demonstrating a high degree of agreement. These calibrated parametric constitutive equations enable further use of the CP model to study the deformation behavior of this alloy under a wide range of thermo-mechanical loading conditions.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Solidification and crystallographic texture modeling of laser powder bed fusion Ti-6Al-4V using finite difference-monte carlo method

Laser powder bed fusion (LPBF) additive manufacturing makes near-net-shaped parts with reduced material cost and time, rising as a promising technology to fabricate Ti-6Al-4V, a widely used titanium alloy in aerospace and medical industries. However, LPBF Ti-6Al-4V parts produced with 67° rotation between layers, a scan strategy commonly used to reduce microstructure and property inhomogeneity, have varying grain morphologies and weak crystallographic textures that change depending on processing parameters. Here, this study predicts LPBF Ti-6Al-4V solidification at three energy levels using a finite difference-Monte Carlo method and validates the simulations with large-area electron backscatter diffraction (EBSD) scans. The developed model accurately shows that a <001> texture forms at low energy and a <111> texture occurs at higher energies parallel to the build direction but with a lower strength than the textures observed from EBSD. A validated and well-established method of combining spatial correlation and general spherical harmonics representation of texture is developed to calculate a difference score between simulations and experiments. The quantitative comparison enables effective fine-tuning of nucleation density (N 0 ) input, which shows a nonlinear relationship with increasing energy level. Future improvements in texture prediction code and a more comprehensive study of N 0 with different energy levels will further advance the optimization of LPBF Ti-6Al-4V components. These developments contribute a novel understanding of crystallographic texture formation in LPBF Ti-6Al-4V, the development of robust model validation and calibration pipeline methodologies, and provide a platform for mechanical property prediction and process parameter optimization.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

Unsupervised learning-enabled pulsed infrared thermographic microscopy of subsurface defects in stainless steel

Metallic structures produced with laser powder bed fusion (LPBF) additive manufacturing method (AM) frequently contain microscopic porosity defects, with typical approximate size distribution from one to 100 microns. Presence of such defects could lead to premature failure of the structure. In principle, structural integrity assessment of LPBF metals can be accomplished with nondestructive evaluation (NDE). Pulsed infrared thermography (PIT) is a non-contact, one-sided NDE method that allows for imaging of internal defects in arbitrary size and shape metallic structures using heat transfer. PIT imaging is performed using compact instrumentation consisting of a flash lamp for deposition of a heat pulse, and a fast frame infrared (IR) camera for measuring surface temperature transients. However, limitations of imaging resolution with PIT include blurring due to heat diffusion, sensitivity limit of the IR camera. We demonstrate enhancement of PIT imaging capability with unsupervised learning (UL), which enables PIT microscopy of subsurface defects in high strength corrosion resistant stainless steel 316 alloy. PIT images were processed with UL spatial–temporal separation-based clustering segmentation (STSCS) algorithm, refined by morphology image processing methods to enhance visibility of defects. The STSCS algorithm starts with wavelet decomposition to spatially de-noise thermograms, followed by UL principal component analysis (PCA), fine-tuning optimization, and neural learning-based independent component analysis (ICA) algorithms to temporally compress de-noised thermograms. The compressed thermograms were further processed with UL-based graph thresholding K-means clustering algorithm for defects segmentation. The STSCS algorithm also includes online learning feature for efficient re-training of the model with new data. For this study, metallic specimens with calibrated microscopic flat bottom hole defects, with diameters in the range from 203 to 76 µm, were produced using electro discharge machining (EDM) drilling. While the raw thermograms do not show any material defects, using STSCS algorithm to process PIT images reveals defects as small as 101 µm in diameter. To the best of our knowledge, this is the smallest reported size of a sub-surface defect in a metal imaged with PIT, which demonstrates the PIT capability of detecting defects in the size range relevant to quality control requirements of LPBF-printed high-strength metals.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Design Overview of a High-Pressure Helium Flow Visualization Apparatus for Blanket Cooling Studies

Cooling of the fusion blanket first wall remains a significant challenge given the adverse conditions of heat and particle flux encountered near the plasma. Helium emerges as an attractive cooling candidate because of its chemical and neutronic inertness and separability from hydrogenic species (e.g. tritium). Because of the low thermal mass of helium, optimization of these coolant channels is warranted to provide high heat transfer performance at low pumping costs. Increasingly, computational fluid dynamics (CFD) simulations are employed to model and optimize these flow channels, and accompanying experimental data are needed to validate the predictions of these models. To provide the aforementioned experimental data, a high-pressure helium flow visualization upgrade has been designed for the Helium Flow Loop Experiment facility. This apparatus was built to American Society of Mechanical Engineers boiler and pressure vessel standards to withstand operating pressure of 4 MPa and mated to high-pressure glass windows. Seedless flow visualization is performed via high-speed background oriented schlieren (BOS), with image correlation used for time-resolved two-dimensional velocimetry at frequencies in excess of 60 kHz. Rectangular flow channel test articles are additively manufactured via laser powder bed fusion and installed into this visualization apparatus, with one-sided heating supplied by resistive heaters. In conclusion, the chosen test geometries were informed by prior CFD simulations, and the helium flow structures observed via BOS (detachment, recirculation, etc.) will be used for the validation of these accompanying models, in support of the design and optimization of blanket cooling channel configurations.

Helium flow↗
DOE OSTI2026

Effect of stress and temperature on zero group velocity Lamb modes

Zero group velocity (ZGV) Lamb wave resonances are highly localized and sensitive to changes in material properties, making them a viable option for probing residual stresses and elastic nonlinearity through acoustoelastic effects. Temperature changes also influence ZGV modes and need to be accounted for, particularly when measuring the small frequency shifts associated with acoustoelastic effects. We use a laser-based ultrasonic system to measure the third-order elastic constants of several materials. A temperature compensation scheme is devised to remove the effects of temperature fluctuations from the measurements. Furthermore, the measured third-order elastic constants are used to predict the temperature dependence of the ZGV resonances using thermo-acoustoelasticity theory, and these predictions are compared to experimental measurements. We find that thermo-acoustoelasticity theory was unable to reliably predict the shift in ZGV resonances with temperature. These results could have important implications in understanding the limitations of thermo-acoustoelasticity theory and in developing precision ZGV resonance-based systems to detect and quantify residual stress in parts, a particularly relevant problem in additive manufacturing techniques including powder bed fusion and directed energy deposition.

Engineering↗
DOE OSTI2025

Lattice Structured Lightweight Structural Materials

The development of lightweight structural materials is crucial for enhancing the performance and deployment feasibility of fission batteries. This study aims to produce lightweight structural materials whose strength-to-weight ratios exceed those of current widely used structural materials. To achieve this, advanced modeling and simulation tools were employed to design lattice structures with different lattice parameters and different lattice types. A process was successfully developed for transforming lattice-structured models into Multiphysics Object Oriented Simulation Environment (MOOSE) inputs. Finite element modeling (FEM) was used to simulate the uniaxial tensile testing of the lattice-structured parts to investigate the stress distribution at a given displacement. The modeling results showed that the lattice-structured sample displayed a lower Young’s modulus in comparison to the solid material; the increase in solid shell thickness and blend radius enhances the mechanical performance; and the effect of unit cell size on macro scale stress is minimal. Tensile testing was conducted on the solid and lattice-structured materials fabricated by laser powder bed fusion (LPBF) additive manufacturing. The experimental results agreed well with the model prediction. The approach of using modeling as a guiding tool for preliminary material design can significantly save time and cost for new material development.

lightweight material↗
DOE OSTI2025

Vector-level feedforward control of LPBF melt pool area using a physics-based thermal model

Laser powder bed fusion (LPBF) is an additive manufacturing technique that has gained popularity thanks to its ability to produce geometrically complex, fully dense metal parts. However, these parts are prone to internal defects and geometric inaccuracies, stemming in part from variations in the melt pool. Here, this paper proposes a novel vector-level feedforward control framework for regulating melt pool area in LPBF. By decoupling part-scale thermal behavior from small-scale melt pool physics, the controller provides a scale-agnostic prediction of melt pool area and efficient optimization over it. This is done by operating on two coupled lightweight models: a finite-difference thermal model that efficiently captures vector-level temperature fields and a reduced-order, analytical melt pool model. Each model is calibrated separately with minimal single-track and 2D experiments, and the framework is validated on a complex 3D geometry in both Inconel 718 and 316L stainless steel. Results showed that feedforward vector-level laser power scheduling reduced geometric inaccuracy in key dimensions by 62%, overall porosity by 16.5%, and photodiode root-mean-squared deviation by 38.5% on average. Overall, this modular, data-efficient approach demonstrates that proactively compensating for known thermal effects can significantly improve part quality while remaining computationally efficient and readily extensible to other materials and machines.

Additive manufacturing↗