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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 307 records · Page 17
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Grain structure and texture selection regimes in metal powder bed fusion

Additive manufacturing (AM) offers opportunities to produce complex part geometries not possible with conventional processing and in some cases even improve part performance. However, adoption has been slowed by difficulties assessing microstructure variability and there is no straightforward approach to relate processing to grain structure characteristics. In this study, datasets from AdditiveFOAM heat transport simulations of laser powder bed fusion (LPBF) are used to drive ExaCA simulations of grain structure. The GPU utilization of ExaCA and an algorithmic update for modeling melt pool overlap region solidification enabled rapid and parallel simulation across a wider range of process conditions than previously explored with cellular automata-based solidification models. A texture selection angle $θ_s$ is defined based on melt pool overlap geometry, and the range of $θ_s$ over which a commonly observed texture transition occurs in characterized AM builds was well-reproduced by ExaCA simulations over a wide range of melt pool shape, hatch spacing, and layer height. ExaCA simulations with 90 degree rotation of the scan direction on every other layer reproduced a number of trends from the AM literature including grain refinement, the dominance of layers with larger melt pools on the final grain structure, and the weakening or strengthening of texture depending on odd and even layer melt pool overlap geometry. EBSD data from a benchmark AM part is used to validate the simulated mechanism of a layer rotation-induced texture strengthening effect. Importantly, these results expand the understanding of the mechanisms for texture selection in alloys with cubic crystal symmetry and offer an approach to easily evaluate processing conditions. With this new understanding, these modeling tools will enable anticipation of previously unexpected variations in grain structure and target specific microstructures and properties.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Sinter formation during directed energy deposition of titanium alloy powders

During directed energy deposition (DED) additive manufacturing, powder agglomeration and sintering can occur outside of the melt pool when using titanium alloy powders. Using in situ synchrotron radiography we investigate the mechanisms by which sintering of Ti6242 powder occurs around the pool, performing a parametric study to determine the influence of laser power and stage traverse speed on sinter build-up. The results reveal that detrimental sinter can be reduced using a high laser power or increased stage traverse speed, although the latter also reduces deposition layer thickness. The mechanism of sinter formation during DED was determined to be in-flight heating of the powder particles in the laser beam. Calculations of particle heating under the processing conditions explored in this study confirm that powder particles can reasonably exceed 700 °C, the threshold for Ti surface oxide dissolution, and thus the powder is prone to sintering if not incorporated into the melt pool. The build-up of sinter powder layer on deposit surfaces led to lack of fusion pores. To mitigate sinter formation and its detrimental effects on DED component quality, it is essential that the powder delivery spot area is smaller than the melt pool, ensuring most powder lands in the melt pool.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructure development and properties of micro-alloyed copper, Cu-0.3Zr-0.15Ag, produced by electron beam additive manufacturing

A micro-alloyed copper powder, Cu-0.3Zr-0.15Ag wt.%, was produced using gas atomization reaction synthesis. Zirconium was added to copper to sequester the oxygen present as copper oxide surface films on the powder particles. The as-received powders, as well as the intentionally oxidized powders were used to fabricate solid test articles by electron beam powder bed fusion additive manufacturing. Dense samples fabricated from as-received powder demonstrated nominal UTS, yield, and elongation values at 260 MPa, 150 MPa, and 34%, respectively. The average electrical conductivity of these samples was measured at 95% of the international annealed copper standard (IACS). Samples fabricated from the oxidized powder exhibited nominal UTS, yield, and elongation of 241 MPa, 146 MPa, and 43%, respectively, with an electrical conductivity of 95 % IACS. During characterization, it was observed that, rather than forming nano-scale dispersoids, the Zirconia (ZrO 2 ) appeared as discontinuous stringers in the metallographic cross-sections that crossed grain and melt pool boundaries. This was rationalized by tracing the presence of the micro-alloying addition of elemental zirconium, which was found to react with surface oxides dissociated in the melt pool to form ZrO 2 , which then solidified on the surface of the melt pool through an allotropic transformation to monoclinic ZrO 2 in discontinuous films and spheroids ranging in size from nanometers to microns. This was confirmed by microscopic analysis of the tops of the melt pools. On subsequent melt passes, these ZrO 2 structures were displaced and redistributed within the melt pool.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Simulating the Effects of Surface Energy Partitioning on Convective Organization: Case Study and Observations in the US Southern Great Plains

Realistic cloud-resolving simulations were performed to study the effects of surface energy partitioning (surface sensible and latent heat fluxes) on the organization of isolated convection into larger mesoscale convective systems (MCSs) near the US Southern Great Plains. The role of cold pools in mediating surface-convection interactions was explored. Better organized MCSs tended to occur in the experiments with perturbed wetter soil (and more active vegetation), regardless of the effects of soil moisture on the diurnal timing of convective triggering. Wetter soil led to shallower boundary layers and more convective available potential energy than drier soil. The roles of cold pools on convection are lifecycle-stage dependent: A dry surface allows more numerous colliding cold pools, thereby aiding in convective triggering by reducing entrainment in the early stages, and providing gust-front uplift in later stages. However, horizontal propagation of the cold-pool density current can outrun the convective system, creating a slantwise updraft and thus weakening the gust front uplift in later stages. This effect calls into question previous cold pool parameterizations, in which the gust front uplift is mainly proportional to the negative buoyancy of cold air. Finally, both the model and observation show an enhancement of surface latent heat flux during the passage of a gust front at night, suggesting that a positive feedback between the surface and convection helps MCSs to persist into the nighttime.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

A New 1D Model for Thermal Mixing and Stratification in Advanced Reactor Transients

Thermal mixing and stratification in large pools and enclosures play a critical role in the safety and performance of pool-type nuclear reactors, particularly during transient scenarios involving significant temperature differences between incoming and bulk coolant. Accurate modeling of these phenomena is essential for predicting system behavior and supporting passive safety features such as natural circulation. Here, this paper presents a new 1D model for thermal mixing and stratification, developed and implemented in the SAM code. The model represents a large pool as 1D coolant jet channels and zero-dimensional bulk pool volumes, enabling the simulation of a wide range of flow configurations, including hot and cold jet interactions, stratified layers, and the influence of complex geometries such as ceilings, free surfaces, and internal obstacles. Heat exchange between jet and pool regions is governed by closure relations calibrated against 3D computational fluid dynamics (CFD) simulations. The model improves upon earlier approaches by incorporating time-dependent jet characteristics and capturing the associated delay effects more accurately. Code-to-code comparisons and validation against experimental data from the Thermal Stratification Test Facility demonstrate the model’s accuracy and flexibility. This work offers two key contributions: (1) an efficient and robust method for simulating thermal mixing and stratification at the system level, eliminating the need for external coupling between system analysis codes and CFD, and (2) a significant enhancement of SAM’s capabilities to analyze thermal stratification phenomena in advanced reactor systems.

SAM↗
DOE OSTI2025

Historical Land Management Alters New Soil Carbon Inputs by Annual and Perennial Bioenergy Crops

Bioenergy and bioproduct markets are expanding to meet demand for climate-friendly goods and services. Perennial biomass crops are particularly well suited for this goal because of their high yields, low input requirements, and potential to increase soil carbon (C). However, it is unclear how much C is allocated into belowground pools by perennial bioenergy crops and whether the belowground benefits vary with nitrogen (N) fertilizer inputs. Using in situ 13 C pulse-chase labeling, we tested whether the sterile perennial grass Miscanthus × giganteus (miscanthus) or annual maize transfers more photosynthetic C to belowground pools. The experiment took place at two sites in Central and Northwest (NW) Iowa with different management histories and two nitrogen (N) fertilizer rates (0 and 224 kg N ha −1 year −1 ) to determine if the fate of plant-derived soil C depends on soil fertility and crop type (perennial or annual). Maize allocated a greater percentage of total new 13 C to roots than miscanthus, but miscanthus had greater new 13 C in total and belowground plant biomass. We found strong interactions between site and most soil measurements—including new 13 C in mineral and particulate soil organic matter (SOM) pools—which appears to be driven by differences in historical fertilizer management. The NW Iowa site, with a history of manure inputs, had greater plant-available nutrients (phosphorus, potassium, and ammonium) in soils, and resulted in less 13 C from miscanthus in SOM pools compared to maize (approximately 64% less in POM and 70% less in MAOM). In more nutrient-limited soils (Central site), miscanthus transferred 4.5 times more 13 C than maize to the more stable mineral-associated SOM pool. Our results suggest that past management, including historical manure inputs that affect a site's soil fertility, can influence the net C benefits of bioenergy crops.

13C↗
DOE OSTI2020

Sensitivity of Thermal Predictions to Uncertain Surface Tension Data in Laser Additive Manufacturing

To understand the process-microstructure relationships in additive manufacturing (AM), it is necessary to predict the solidification characteristics in the melt pool. This study investigates the influence of Marangoni driven fluid flow on the predicted melt pool geometry and solidification conditions using a continuum finite volume model. A calibrated laser absorptivity was determined by comparing the model predictions (neglecting fluid flow) against melt pool dimensions obtained from single laser melt experiments on a nickel super alloy 625 (IN625) plate. Using this calibrated efficiency, predicted melt pool geometries agree well with experiments across a range of process conditions. When fluid mechanics is considered, a surface tension gradient recommended for IN625 tends to overpredict the influence of convective heat transfer, but the use of an intermediate value reported from experimental measurements of a similar nickel super alloy produces excellent experimental agreement. Despite its significant effect on the melt pool geometry predictions, fluid flow was found to have a small effect on the predicted solidification conditions compared to processing conditions. We find that this result suggests that under certain circumstances, a model only considering conductive heat transfer is sufficient for approximating process-microstructure relationships in laser AM. Extending the model to multiple laser passes further showed that fluid flow also has a small effect on the solidification conditions compared to the transient variations in the process. Furthermore, limitations of the current model and areas of improvement, including uncertainties associated with the phenomenological model inputs are discussed.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Nondiffractive beam shaping for enhanced optothermal control in metal additive manufacturing

High thermal gradients and complex melt pool instabilities involved in powder bed fusion–based metal additive manufacturing using focused Gaussian-shaped beams often lead to high porosity, poor morphological quality, and degraded mechanical performance. We show here that Bessel beams offer unprecedented control over the spatiotemporal evolution of the melt pool in stainless steel (SS 316L) in comparison to Gaussian beams. Notably, the nondiffractive nature of Bessel beams enables greater tolerance for focal plane positioning during 3D printing. We also demonstrate that Bessel beams significantly reduce the propensity for keyhole formation across a broad scan parameter space. High-speed imaging of the melt pool evolution and solidification dynamics reveals a unique mechanism where Bessel beams stabilize the melt pool turbulence and increase the time for melt pool solidification, owing to reduced thermal gradients. Consequently, we observe a distinctively improved combination of high density, reduced surface roughness, and robust tensile properties in 3D-printed test structures.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Data for Microbial-Explicit Processes and Refined Perennial Plant Traits Improve Modeled Ecosystem Carbon Dynamics

Globally, soils hold approximately half of ecosystem carbon and can serve as a source or sink depending on climate, vegetation, management, and disturbance regimes. Understanding how soil carbon dynamics are influenced by these factors is essential to evaluate proposed natural climate solutions and policy regarding net ecosystem carbon balance. Soil microbes play a key role in both carbon fluxes and stabilization. However, biogeochemical models often do not specifically address microbial-explicit processes. Here, we incorporated microbial-explicit processes into the DayCent biogeochemical model to better represent large perennial grasses and mechanisms of soil carbon formation and stabilization. We also take advantage of recent model improvements to better represent perennial grass structural complexity and life-history traits. Specifically, this study focuses on: 1) a plant sub-model that represents perennial phenology and more refined plant chemistry with downstream implications for soil organic matter (SOM) cycling though litter inputs, 2) live and dead soil microbe pools that influence routing of carbon to physically protected and unprotected pools, 3) Michaelis-Menten kinetics rather than first-order kinetics in the soil decomposition calculations, and 4) feedbacks between decomposition and live microbial pools. We evaluated the performance of the plant sub-model and two SOM cycling sub-models, Michaelis-Menten (MM) and first-order (FO), using observations of net ecosystem production, ecosystem respiration, soil respiration, microbial biomass, and soil carbon from long-term bioenergy research plots in the mid-western United States. The MM sub-model represented seasonal dynamics of soil carbon fluxes better than the FO sub-model which consistently overestimated winter soil respiration. While both SOM sub-models were similarly calibrated to total, physically protected, and physically unprotected soil carbon measurements, the models differed in future soil carbon response to disturbance and climate, most notably in the protected pools. Adding microbial-explicit mechanisms of soil processes to ecosystem models will improve model predictions of ecosystem carbon balances but more data and research are necessary to validate disturbance and climate change responses and soil pool allocation.

Field Data↗
DOE OSTI2021

Sodium Fire Collaborative Study Progress -- CNWG Fiscal Year 2020

This report discusses the progress on the collaboration between Sandia National Laboratories (Sandia) and Japan Atomic Energy Agency (JAEA) on the sodium fire research in fiscal year 2020. First, the current sodium pool fire model in MELCOR, which is adapted from CONTAIN-LMR code, is discussed. The associated sodium fire input requirements are also presented. These input requirements are flexible enough to permit further model development via control functions to enhance the current model without modifying the source code. The theoretical pool fire model improvement developed at Sandia is discussed. A control function model has been developed from this improvement. Then, the validation study of the sodium pool fire model in MELCOR carried out by both Sandia and JAEA’s staff is described. To validate this pool fire model with the enhancement, a JAEA sodium pool fire experiment (F7-1 test) is used. The results of the calculation are discussed as well as suggestions for further model improvement. Finally, recommendations are made for new MELCOR simulations for next fiscal year, 2021.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Implementation of disruptive designs for gas turbine components using direct energy deposition additive manufacturing

This research aims to develop a framework for establishing the correlation between in-situ monitoring data, process parameters, and microstructure evolution in blown-powder laser-directed energy deposition (DED) additive manufacturing (AM). To achieve this, a comprehensive manufacturing framework has been developed, spanning from in-situ data acquisition, melt-pool simulation, microstructure modeling, and statistical microstructure quantification. A machine learning-based surrogate model is constructed to predict melt pool geometry directly from in-situ coaxial camera data. The surrogate model is trained using outputs from a high-fidelity melt pool simulation, which provides accurate melt pool dimension data under varying process conditions. The predicted melt pool geometry is then used as input to a microstructure model to predict microstructural features. To rigorously compare and analyze microstructures, the project introduces statistical metrics that quantify differences based on key features such as morphology and texture. Microstructures are represented using advanced statistical descriptors including angular chord length distribution, two-point spatial statistics, orientation distribution function, and global spherical harmonic. These representations are used to compute four distinct “dissimilarity scores” that quantitatively capture differences in texture and morphology. This framework is demonstrated to enable automated calibration of simulation parameters by minimizing discrepancies between simulated and target microstructures. The technology developed in this project enables direct correlation between in-situ monitoring data and resulting microstructure, paving the way for adaptive microstructure control in metal AM. This capability strengthens the connection between process parameters and final material properties, facilitating more precise and reliable material design.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Historical land management alters new soil carbon inputs by annual and perennial bioenergy crops

Bioenergy and bioproduct markets are expanding to meet demand for climate friendly goods and services. Perennial biomass crops are particularly well suited for this goal because of their high yields, low input requirements, and potential to increase soil carbon (C). However, it is unclear how much C is allocated into belowground pools by perennial bioenergy crops and whether the belowground benefits vary with nitrogen (N) fertilizer inputs. Using in situ 13C pulse-chase labeling, we tested whether the sterile perennial grass Miscanthus × giganteus ( miscanthus ) or annual maize transfers more photosynthetic C to belowground pools. The experiment took place at two sites in Central and Northwest (NW) Iowa with different management histories and two nitrogen (N) fertilizer rates (0 and 224 kg N ha-1 yr-1) to determine if the fate of plant-derived soil C depends on soil fertility and crop type (perennial or annual). Maize allocated a greater percentage of total new 13C to roots than miscanthus, but miscanthus had greater new 13C in total and belowground plant biomass. We found strong interactions between site and most soil measurements – including new 13C in mineral and particulate soil organic matter (SOM) pools –which appear to be driven by differences in historical fertilizer management. The NW Iowa site, with a history of manure inputs, had greater plant-available nutrients (phosphorus, potassium, and ammonium) in soils, and resulted in less 13C from miscanthus in SOM pools compared to maize (approximately 64% less in POM and 70% less in MAOM). In more nutrient-limited soils (Central site), miscanthus transferred 4.5 times more 13C than maize to the more stable mineral-associated SOM pool. Our results suggest that past management, including historical manure inputs that affect a site’s soil fertility, can influence the net C benefits of bioenergy crops.

Keiser, Ashley [Stockbridge School of Agriculture,↗
DOE OSTI2022

Assessment of Thermal Stratification in Versatile Test Reactor Transients

The Versatile Test Reactor (VTR) is a fast-spectrum test reactor currently being developed in the United States under the direction of the US Department of Energy. The conceptual design of the 300 MWth pool-type sodium-cooled fast reactor (SFR) has been led by the US National Laboratories in collaboration with General Electric-Hitachi and Bechtel National Inc. Safety performance analysis for the VTR conceptual design is being performed with the systems thermal-hydraulics (SYSTH) module of the SAS4A/SASSYS-1 liquid-metal reactor safety analysis code system. Since the current model of the VTR employs a simple perfect mixing model for large plena like the hot pool, it is not able to predict temperature variations that may develop during the transient. Prior work simulating the response of SFRs to postulated events like the Protected Station Blackout (PSBO) has shown that the phenomenon of thermal stratification, where stable thermal layers accumulate in the hot pool, may delay the transition to natural circulation and thus impact the predicted transient progression. Thus, an effort has begun to model this transient by integrating a Computational Fluid Dynamics (CFD) model of the hot pool into the SAS4A/SASSYS-1 model of the Primary Heat Transport System during the simulation of the PSBO event. A three-dimensional Volume-Of-Fluid CFD model of the VTR hot pool has been developed for the co-simulation of SAS4A/SASSYS-1 with CFD. In this work, the standalone SAS4A/SASSYS-1 calculation and the standalone CFD calculation based on the SAS4A/SASSYS-1 calculation result were produced on the Idaho National Laboratory High Performance Computing cluster, SAWTOOTH. At this time, only the standalone CFD and SAS4A/SASYS-1 simulation results are provided.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

Influence of microstructural heterogeneities on small-scale mechanical properties of an additively manufactured Al-Ce-Ni-Mn alloy

Laser powder bed fusion-based additive manufacturing (AM) is a promising method to fabricate creep-resistant Al-rare earth alloys (Al-Ce-Ni-Mn) with stable microstructures at up to 400°C. However, creep testing of these alloys at high temperatures shows that void coalescence and failure initiation occurs along the melt pool boundaries in the microstructure. Hence it is crucial to understand how the local mechanical behavior of the melt pool boundaries would influence the global properties of the AM produced alloy. In this study, in situ nanoindentation conducted at room temperature and 300°C revealed a reduced hardness at the melt pool boundaries. Similarly, micro-pillar compression showed a slight decline in yield strength at these boundaries, indicating that they are the weak spots in the microstructure. Such multimodal local mechanical property studies are necessary for understanding the influence of melt pool boundaries on the bulk response of fusion-based AM alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Effect of powder layer thickness on the microstructural development of additively manufactured SS316

By Increasing the powder layer thickness we could increase material deposition rates and reduce build times during laser powder bed fusion (LPBF). However, increasing the powder layer thickness could also negatively affect the local melting and subsequent microstructure of the printed material. This study systematically investigated, for the first time, the defect evolution and microstructural changes of LPBF stainless steel 316 (SS316) processed by using various powder layer thicknesses of 40, 80, and 120 μm while also varying the laser dwell time for the pulsed laser. Through image analysis, the pore density was found to increase with increasing powder layer thickness, particularly when the dwell time was too high or too low. The maximum achievable density (>99%) was found over a wide processing window when using the smallest powder layer thickness of 40 μm between dwell times of 60 and 100 μs. Increasing the powder layer thicknesses to 80 and 120 μm resulted in maximum densities of 98.7 and 96.8%, respectively, but the window for acceptable laser dwell times that could achieve these densities narrowed considerably. A microstructural analysis of the melt pools was performed to measure the melt pool depths and widths, both of which increased with increasing dwell time. However, increasing the powder layer thickness did not affect the melt pool depth and only minorly affected the width. A sub-grain cellular structure distinguished the melt pool boundaries. The cell size increased with increasing dwell time and decreasing powder layer thickness. Moreover, the cell size was used to calculate a cooling rate that had a magnitude of 10 7 K/s and increased with increasing powder layer thickness.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Using Resin to Reduce Silica in Borated Fluid - 20072

The Electric Power Research Institute (EPRI) strongly recommends the concentration of silica in the reactor coolant be limited, potential ingress be carefully controlled, and frequently monitored to assess potential silica deposits on fuel cladding surfaces. Boraflex is a product with silicone rubber encasing a neutron absorber for criticality control, and it was installed in the majority of nuclear power plant spent fuel pools. Over time and in the presence of radiation, the silicone rubber lining degrades into silica (SiO{sub 2}) and hydrogen gas. Silica is somewhat soluble in water and spent fuel pool water communicates with other plant systems during refueling outages, leading to a buildup of silica in the reactor coolant and connected systems. Due to the prevalence of Boraflex racks in spent fuel pools, the presence of silica is a chronic nuclear industry concern. To address this concern, many nuclear plants have installed reverse osmosis skid systems to remove the silica from their spent fuel pools and, by extension, from reactor coolant. These skids are expensive to install and maintain. Arcadis personnel demonstrated that an iron-impregnated resin could be used to remove silica from borated systems without impacting the water quality. The resin was readily available, inexpensive, and easy to install in existing plant equipment. During a nuclear power plant's refueling outage the iron-impregnated resin proved to be effective in reducing the need for feed and bleed operations, with concurrent cost savings and reduction in required outage water management activities. Thus, the following savings were realized: - Eliminated the need to purchase, install, and maintain a reverse osmosis system avoiding more than $10 million in up-front capital cost and ongoing operating and maintenance costs. - Removed 9.57 kilograms (21 pounds) of silica dioxide from the primary system fluid. - Reduced the volume of feed and bleed from 70,000 gallons (2.65 E+05 liters) to 35,000 gallons (1.32 E+05 liters). - Saved $380,000 in water production and disposal costs. (author)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Strong parallel evidence of selection during switchgrass sward establishment in hybrid and lowland ecotypes

Switchgrass sward establishment results in up to 90% seedling mortality. The degree of selection during sward establishment has not been reported using modern genetic methods. Pooled leaf samples were sequenced from replicated swards of 46 half-sib families from two breeding groups (lowland and hybrid) before and through 3 years of stand establishment. Pooled allele frequencies were then assessed using fixation indices (Fst) and an independent data set was used to predict the polygenic impact of establishment selection on two traits (heading date and winter survivorship). Last, the DNA pools were assigned survival rankings to predict the sward survival genomically estimated breeding values within the training data set. Strong and parallel selection occured in both breeding groups. Five genomic regions exceeded the significant threshold of 99.9% in >10 families, indicating consistent selection across families and breeding groups. Polygenic trait predictions determined that establishment selection was partially associated with winter survivorship but resulted in variable heading date alterations. The genomewide variation is consistent with selection for a small number of related parental lines. This study observed strong selection for a small number of hybrid and coastal ecotype individuals which are promising germplasm sources for improved sward survival. This confirms prior reports of sward selection during grassland establishment and highlights the strength of pooled DNA sequencing for survival traits.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Laser powder bed fusion parameter estimation with k-NN

Abstract Laser powder bed fusion (L-PBF) is a technique within additive manufacturing that uses a high power density laser to build parts from fused powdered metal alloy. This technology is well equipped to produce complex parts with otherwise impossible features, such as hidden voids or lattice structures. Alongside capability, reliability and quality are key characteristics considered when choosing a manufacturing method, and these are gaining attention as this method becomes more prevalent in industry. One main indicator of a stable L-PBF process is consistent melt pool geometry, and the properties of which are likely to determine the quality of the part produced. As computing power and sensing technologies become more advanced, this melt pool geometry could be studied in real time. This work addresses the challenge by leveraging a k-nearest neighbor (k-NN) model to identify key features within melt pool imagery and predict the energy density. The k-NN model was trained on data provided by the National Institute of Standards and Technology (NIST). Data preprocessing was performed on the images to extract features that were used in the k-NN model. This approach was used to accurately infer the energy density of unseen layers within the same part. The algorithm was subsequently tested with unique scan strategies and found to reasonably estimate the energy density of different parts. A fivefold cross validation found the algorithm to be consistently predicting the class of 91.4% of the in situ melt pool images.

Jung, Patrick (ORCID:0000000267890859)↗