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At least 37 records · Page 2

The Additive Manufacturing Moment Measure - A Parallel Computation Technique for Determining Build Variance in the Laser Powder Bed Fusion Process

Additive manufacturing (AM) has unique process attributes that facilitate the creation of optimized, complex, and unique parts for aerospace applications. However, the multi-scale and complicated building process for AM parts can cause unexpected build conditions that result in microstructural variability within the deposited material. The need for richer datasets and computational modeling capabilities to improve AM process reliability is a consequence of this microstructural variability. A computational approach, referred to as the Additive Manufacturing Moment Measure (AM3), addresses this need by leveraging the way AM processes fuse material in precise, incremental steps. During the layering sequence, each previous step contributes to the condition of the current step at the center of the heat source. The precise steps can be selected to systematically create a time-space point field with co-located machine input and in-situ sensor data. The sequential nature of the AM process, coupled with nearest neighbor calculations, allows for a fully parallel computation for part-scale build profile analysis. The AM3 concept introduced here enables part-scale assessment directly from build files and in-situ process monitoring sensors alike. The AM moment measures were calculated for build point fields and compared with co-located in-situ and ex-situ nondestructive evaluation and optical microscopy observations. These comparisons permit a better understanding of how the sequential process actions can affect the quality of a laser powder bed fusion (LPBF) build. Details of the AM3technique will be discussed and compared to measured LPBF part characteristics. The AM3 results indicate a strong potential to advance the qualification process for aerospace applications.

Additive Manufacturing↗

Development of Laser Powder Bed Fusion NASA HR-2 for Hydrogen Sensitive Liquid Rocket Engine Applications

The National Aeronautics and Space Administration (NASA) has been involved in the development and maturation of metal additive manufacturing (AM) for space applications since the late 2000s. AM has provided new design and manufacturing opportunities to reduce cost and schedule, consolidate parts, and optimize performance. Laser Powder Bed Fusion (L-PBF) is one of the most commonly used AM processes to fabricate components of complex shape requiring fine feature resolution. Due to exposure to high-pressure gaseous hydrogen, mechanical property degradation caused by hydrogen environment embrittlement (HEE) is a critical concern for many materials in liquid hydrogen propulsion systems. NASA has identified the need to develop and advance new materials in unique engine applications using liquid hydrogen as a propellant. One such material being developed at NASA Marshall Space Flight Center is L-PBF NASA HR-2 (Hydrogen Resistant-2), a high-strength Fe-Ni-based superalloy resistant to HEE. The chemistry of NASA HR-2 was formulated to meet requirements for key liquid rocket engine (LRE) components that operate in high-pressure hydrogen environments. Initial development and material characterization found that NASA HR-2 has excellent L-PBF printability, and its microstructure evolves well after heat treatment. This new alloy has undergone fundamental metallurgical evaluations, heat treatment studies, detailed microstructure characterization, and mechanical testing across a range of temperatures. Tensile testing was performed in a pressurized gaseous hydrogen (GH2) environment to assess its resistance to HEE. L-PBF NASA HR-2 has an average yield stress of 95 ksi, an ultimate tensile stress of 165 ksi, and a very high fracture elongation of 34 - 36% when tested in a high-pressure (5 ksi) hydrogen environment. The tensile property data confirms hydrogen has little influence on HR-2’s ductility, strength, and fracture behavior. L-PBF NASA HR-2 is a promising option for many hydrogen-sensitive LRE components that require exceptional resistance to HEE. This paper will provide an overview of the L-PBF process development, material characterization, mechanical and thermophysical properties, and LRE hardware development for NASA HR-2.

Po S Chen↗

Uncertainty Quantification and Sensitivity Analysis in Process-Structure-Property Simulations for Laser Powder Bed Fusion Additive Manufacturing

Process variations and process-induced defects like porosity cause significant uncertainty in the microstructure and mechanical behavior of additively manufactured metals. Establishing process-structure-property (PSP) relationships and quantifying uncertainty using experiments alone is costly, especially for structural applications where mechanical allowables must be established for qualification and certification. This work presents a PSP simulation framework for laser powder bed fusion with a focus on uncertainty quantification through probabilistic calibration and multi-fidelity uncertainty propagation. Motivated by phenomenological input parameters related to grain nucleation and growth that are difficult to characterize, a global sensitivity analysis (GSA) is completed. Through GSA, the most important input parameters are identified based on their influence on the statistical distributions of microstructural metrics that influence mechanical behavior, including grain size, morphology, and crystallographic texture. The results provide insight on what experiments are necessary to quantify and control PSP uncertainties, particularly those associated with the more challenging input parameters.

additive manufacturing↗

Exploring the Role of Type-II Residual Stresses in A Laser Powder Bed Fusion Nickel-Based Superalloy Using Measurement and Modeling

Far-field high-energy X-ray diffraction microscopy (ff-HEDM) and the crystal plasticity finite element method (CPFEM) are used to investigate the role of grain-scale (Type-II) residual stresses on the fatigue life of additively manufactured (AM) Inconel alloy 625 (IN-625). Grain-averaged orientations, centroids, and residual elastic strain tensors from ff-HEDM data are used to instantiate a crystal plasticity model to simulate the effect of residual stresses at the grain scale. Simulation results indicate that the presence of tensile residual strains increase stress localization and heterogeneity within grains, triggering an earlier onset of plasticity. A microscale fatigue indicator parameter (FIP) is computed to model the impact of these residual strains on the cycles to fatigue crack nucleation. The crack nucleation model, based on the computed FIPs, predicts a significant reduction in the number of cycles for fatigue crack nucleation for mid- and high-cycle fatigue due to the residual strain induced localization, while the residual strains have minimal impact on low-cycle fatigue life.

Inconel↗