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At least 1,045 records · Page 58
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Fatigue behavior and modeling for additive manufactured 304L stainless steel: The effect of surface roughness

The fatigue strength of additively manufactured metallic parts in their as-built surface condition is mainly dominated by the surface roughness. Post-processing is often inevitable to reduce surface roughness effects even though post-processing diminishes the main advantage of additive manufacturing, which is net-shaped direct-to-service production. This work investigates the underlying mechanisms responsible for fatigue failure of additively manufactured 304L stainless steel parts in as-built and machined/polished surface conditions. Both strain- and force-controlled, fully reversed fatigue tests were conducted to gain a comprehensive understanding of surface roughness effects on fatigue behavior. The sensitivity to surface roughness is shown to be dependent on the control mode, with stress-based fatigue tests showing greater sensitivity than strain-based fatigue tests. Moreover, the fatigue life estimation for as-built specimens was performed based on surface roughness parameters as well as the fatigue properties of the specimens in machined/polished surface condition of the material without using any fatigue data of specimens in as-built surface condition. Accordingly, the effect of surface roughness on the fatigue behavior could be estimated reasonably well in both strain-life and stress-life approaches.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Creep anisotropy modeling and uncertainty quantification of an additively manufactured Ni-based superalloy

The advantages offered by additive manufacturing over traditional processes has driven a great deal of industrial and academic interest in recent years. However, the process is relatively new and requires additional investigation to become sufficiently mature for wide scale industrial adoption. Electron beam melting powder bed fusion is one technology that has shown promise for fabricating high temperature resistant materials such as nickel based superalloys. The resulting microstructures typically exhibit a strong fiber texture in the build direction giving rise to anisotropic time-dependent deformation behavior. In order to accelerate the qualification of these materials for industrial adoption accurate numerical models are needed for simulating their behavior. In this work a crystal plasticity model including non-Schmid effects is presented for capturing creep anisotropy observed in additively manufactured IN738LC. The model is calibrated via a probabilistic framework where model parameters are treated as random variables. An iterative sequential design strategy is utilized to efficiently identify the probability density of the unknown model parameters. As a case study the model is utilized to investigate the behavior of randomly oriented equiaxed grain clusters sometimes observed embedded in the additively manufactured columnar structure. A synthetic realization is simulated and uncertainty is propagated through to the full-field response. Results indicate that these features are the source of significant creep relaxation and strain accumulation which partially explains observed grain boundary decohesion at these locations.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Heterogeneous phase transformation pathways in additively manufactured Al-Ce-Mn alloys

Heat treatment of additively manufactured Al-Ce based multicomponent alloys leads to complex microstructure evolution. In this research, the ability to extend the phase transformation theories involving nucleation of a product phase from a heterogeneous multi-phase microstructure typical to that of additively manufactured samples is explored. The Al-10Ce-8Mn (wt%) was used as a model alloy system. Under additive manufacturing conditions different solidification microstructures were obtained due to spatial and temporal variations of thermal gradients (G) and liquid-solid interface velocities (R) within a given melt pool. Near the melt pool boundary (high G and low R, referred as MPB region), initially, Al 20 Mn 2 Ce forms from the liquid followed by a eutectic of FCC Al and Al 11 Ce 3 . In the melt pool interiors (low G and high R referred as ES region) a eutectic structure between FCC Al and Al 20 Mn 2 Ce is observed. During subsequent heat treatments, the MPB and ES regions transform into different sets of microstructures. In the MPB region, a fine globular microstructure containing FCC Al, Al 11 Ce 3 , Al 6 Mn, and Al 12 Mn results from the decomposition of Al 20 Mn 2 Ce. In the ES region a faceted Al 51 Mn 7 Ce 4 plate phase results from the decomposition of Al 20 Mn 2 Ce. The formation of the Al 51 Mn 7 Ce 4 phase within the eutectic microstructure at the boundaries of FCC Al and Al 20 Mn 2 Ce has not been reported in the literature. Further, these two distinct phase transformation pathways are rationalized based on the role of driving force on the nucleation of (Al 6 Mn) and/or metastable intermetallic (Al 51 Mn 7 Ce 4 ) phases at the interface of aluminum (FCC) and the non-equilibrium intermetallic (Al 20 Mn 2 Ce) phases.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Machinability comparison of additively manufactured and traditionally wrought Ti-6Al-4V alloys using single-point cutting

Post-machining is often needed to provide high dimensional accuracy and fine surface finish for additively manufactured Ti-6Al-4V (Ti64). The material inhomogeneity, such as pores and microstructures, can affect the machining behavior of this already difficult-machine alloy. This study adopts a holistic approach to compare the machinability of additively manufactured and traditionally wrought Ti64 in terms of key machining factors, including forces, temperature, and vibration and the major machining outcomes including tool life, surface finish, and dimensional accuracy. Stress-relief annealing is applied to each of the part conditions as a secondary variable to observe the additional effects. The results show that AM is not particularly more difficult to machine in terms of cutting force and temperature, but it creates high cutting vibrations across a wide range of frequencies (to and over 5 kHz). The high vibrations do not lead to worse surface finish or dimensional accuracy but tend to worsen the tool life by chipping off the cutting edge. The vibration can be attributed to the brittle martensitic microstructure found in additively manufactured Ti64, which is also evidenced by the more serrated chips. Stress-relieving is found to change the microstructure and reduce the level of vibration to that of the wrought counterpart.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Evolution of carbide precipitates in Haynes® 282 superalloy processed by wire arc additive manufacturing

Precipitation hardening regulated with heat treatments is a critical technique for tuning the mechanical properties of Ni-based superalloys fabricated with additive manufacturing, where mechanical deformation is no longer viable for microstructural refinement. As one of the key precipitates, carbides prevail in the additively manufactured alloys, whose precipitation kinetics remain largely vague. This work studies the influence of heat treatments on the evolution of MC- and M 23 C 6 -type carbides within a Haynes® 282 superalloy prepared by wire arc additive manufacturing (WAAM). SEM-EDS analysis was performed to identify the evolution pathways of the carbides, and TEM and XRD characterizations were carried out to track the crystallographic features. The MC-type carbides are originally present in the as-printed alloy, which distribute uniformly across the whole material and remain largely unchanged in size during the heat treatments. By contrast, the incipiently non-existent M 23 C 6 -type carbides precipitate during an aging treatment at 1010 °C, which majorly extend along the grain boundaries as kinetically feasible sites. Further experimental and computational analysis confirms the enhancing effect of the M 23 C 6 -type carbides on the Vickers hardness. For the first time, this work revealed the evolution pathways of carbides within a Haynes® 282 superalloy prepared by WAAM, providing critical information for tunning the microstructure and mechanical properties. Finally, the carbide evolution kinetics established in this work can be potentially extended to other alloys prepared with WAAM, providing critical information to prevent mechanical failures associated with carbide coarsening.

36 MATERIALS SCIENCE↗
DOE OSTI2019

A manufacturing process design for producing a membrane-based energy recovery ventilator with high aspect ratio support ribs

Heating, ventilation, and air conditioning systems represent nearly half of building energy usage in the United States. Recent building regulations requiring increased air turnover within buildings will result in even greater air conditioning usage. To alleviate these concerns, membrane-based heat-and-moisture exchangers known as energy recovery ventilators have been developed to reduce the energy expenditure of air conditioning systems by pre-conditioning incoming air through sensible and latent heat transfer with building air exhaust. Here in this work, we propose and validate a manufacturing process design for channel lamination based on surface mount adhesives capable of meeting the process requirements of a membrane-based ventilator. In particular, the device requires rib supports with height-to-width aspect ratios greater than one. The proposed manufacturing process design is capable of meeting this process requirement by stretching the adhesive after initial adhesive tacking. A manufacturing process flow diagram, a machine tool specification and a cost model are proposed for meeting process requirements. A set of design constraints are developed detailing the adhesive requirements necessary for meeting requirements. The cost model is validated by building a sub-scale mesochannel array demonstrating the ability to meet process requirements. Results show that additional work is needed to validate the curing step but that the process is capable of producing a mesochannel array with an acceptable level of variation.

42 ENGINEERING↗
DOE OSTI2025

Mechanical properties, strain hardening, and fracture behavior of ultrasonic additively manufactured Zircaloy-4 after low-temperature neutron irradiation

Ultrasonic additive manufacturing (UAM) is a solid-state, layer-by-layer advanced manufacturing process that has the potential to create custom spatially controlled composites with embedded wires and sensors for nuclear component manufacture. For this work, to assess the feasibility of using UAM for nuclear-relevant materials research, the technique was used to produce a 3.5-mm-thick Zircaloy-4 plate for irradiation testing. The UAM Zircaloy-4 specimens were irradiated in the High Flux Isotope Reactor at a target irradiation temperature of 117 °C to 2.9 displacements per atom (dpa) to assess differences in irradiation-hardening behavior as a function of alloy processing path. The UAM and reference baseplate (BP) materials increased in yield strength by 372±27 MPa and 346±21 MPa, respectively, and both suffered significant reductions in uniform and total elongation attributed to irradiation hardening at low-temperature. Although the materials had similar nanoscale defect structures, including nanoscale black dot/loop features and strain-induced dislocation channels, the UAM material’s processing-related defects resulted in accelerated strain localization and failure as demonstrated by lower post-irradiation uniform elongation of UAM specimens (0.5 %) compared to BP (1.5 %) material. The UAM material also showed considerable anisotropy in mechanical response due to crack propagation along weld boundaries, resulting in differences in strength & ductility when tested parallel and perpendicular to the prior UAM build orientation. Therefore, although the fundamental irradiation response of UAM-processed Zircaloy-4 was phenomenologically comparable to that of BP reference material, additional optimization of the UAM processing is needed to produce irradiation-resistant and nuclear-relevant materials.

Digital image correlation↗
DOE OSTI2023

Roll-to-roll solvent-free manufactured electrodes for fast-charging batteries

In response to the growing demand for lithium-ion batteries (LIBs), we demonstrate a solvent-free manufacturing technology that can avoid toxic organic solvents and form unique electrode structures to overcome the bottlenecks in low costs and fast charging. The lower tortuosity achieved by the open pores in the dry-printed (DP) electrode allows for a shorter Li+ diffusion pathway, which leads to better rate performance. The DP pouch cells exhibit higher capacity retention of 78% and 69% at 3C and 4C, respectively, compared with 67% and 52% for the slurry cast (SL) cells at the same rates. Moreover, the coating layer on the surface of active materials prevents the excess side reaction between active materials and electrolytes, which prolongs the cycle life of the DP cells. This manufacturing process is a roll-to-roll system with immense potential to be scaled up, providing a more efficient and economical way for battery manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Direct measurement of the effective properties of an additively manufactured titanium octet truss unit cell using high energy X-ray diffraction

Additively manufactured lattice structures offer a high specific strength-to-density ratio in comparison to conventional, fully dense parts. The small feature size and intricate geometry of lattice structures make it challenging to directly characterize their mechanical properties. This study presents direct measurement of the elastic mechanical properties of an additively manufactured titanium alloy octet truss unit cell. Strut stress and strain were measured using high-energy X-ray diffraction during quasi-static compressive loading. The crystallographic stress-strain relationship was converted into the stress-strain relationship of the octet truss lattice unit cell using the known symmetry of the struts. The sample studied herein was best fit by an orthorhombic linear elastic stress-strain relationship. In conclusion, this technique shows promise for studying additively manufactured lattice structures at length scales not previously reported.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Dual X-ray computed tomography-aided classification of melt pool boundaries and flaws in crept additively manufactured parts

In metal additive manufacturing (AM), understanding the process-structure-performance relationships requires a combination of multi-scale characterization techniques that allows for the measurement of the melt pool shape and boundary and classifying various defects and flaws in the AM parts. Such approaches can be destructive, only 2D in nature, or have a small field of view and can be complex to co-register and analyze. Here, in this work, we present a non-destructive 3D inspection technique that employs dual-energy X-ray computed tomography (XCT) along with a model-based iterative reconstruction (MBIR) and a new segmentation algorithm. The proposed approach and algorithm are not only capable of classifying and quantifying flaws such as pores, cracks, and inclusions, but they also allow for the extraction of microstructural features such as melt pool boundaries (MPB) and melt pool regions (MPR), that can help understand process-structure-performance relationships for alloys under study. As an exemplar application, we employed the method for characterization of an additively manufactured aluminum alloy crept under tensile stress at 300 °C for 1064 h. Our results demonstrate high quality segmentation and classification of various flaws and MPB and MPR, for the first time, using 3D X-ray CT inspection. The delineated MPB and MPR in the crept samples reveal the preferential growth paths of cracks that formed during creep deformation. The technique was used for successfully quantifying the characteristics (number of defects, their density, volume fraction, etc.) of the manufacturing-induced pores and creep-induced cracks, which is necessary to better understand the creep failure mechanisms of the material.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Investigation of interfacial structures for hybrid manufacturing

Hybrid manufacturing is a combination of additive and subtractive manufacturing in a single machine. Typically, planar substrate substrates are used for deposition and do not correspond to scenarios encountered in repair applications where the substrate can often be non-planar. Hybrid manufacturing opens the possibility for repairs by leveraging the five-axis mill to prepare the substrate for deposition. However, as the substrate geometry changes, so does the associated heat transfer during deposition and subsequent microstructures. This paper focuses on understanding the changes in microstructure and material properties with changing substrate geometries.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Hybrid manufacturing of Invar mold for carbon fiber layup using structured light scanning

This paper describes coordinate system definition and transfer for five-axis machining of additively-manufactured preforms. In this method, a set of fiducials are attached to the temporarily attached to the part, and their location relative to the preform geometry is calibrated using a structured light scanner. Those fiducials can then be measured in the machine tool to determine the location and orientation of the part. The method is demonstrated by finish-machining a carbon fiber layup mold from an additively manufactured Invar preform. In addition to showing the coordinate transfer methods necessary to machine the part, several key challenges with machining additively-manufactured preforms are discussed and potential solutions are proposed. Unfortunately, the final part was ultimately unusable due to porosity inside the part left from the additive process. Future work will remanufacture this part while taking steps to avoid porosity and other challenges encountered.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Process window estimation in manufacturing through Entropy-Sigma active learning

In manufacturing, there exist boundary identification problems for defining parameter spaces that meet desired thresholds on outcomes. This paper presents an Entropy-Sigma acquisition function for active learning of the process window/map in manufacturing using a Gaussian Process surrogate. Here, the method is applied to identify the stability boundary for the stability process map in machining using time-domain simulations with a periodic sampling stability metric. Results show that the proposed Entropy-Sigma method significantly outperforms Latin hypercube sampling or grid-based methods. The described method can be applied to identify the process window/map for any manufacturing application using a quantitative process outcome metric.

42 ENGINEERING↗
DOE OSTI2026

Improved manufacturability of vacuum thermoforming molds by segmentation

Thin polymer shell components used in consumer goods, the automotive industry, and marine applications are often produced by thermoforming. Depending on the quantity of parts, molding processes can increase throughput significantly when compared to processes such as milling or additive manufacturing. One disadvantage to mold-based manufacturing methods, however, is that molds must be produced to form the required geometry. Mold production is often complex and requires a large capital investment. For large-scale molding processes, mold production is sometimes complicated by the requirement for large working volume machine tools which are capable of machining the cavities to the appropriate tolerances for the selected molding process. Here, this paper focuses on a segmented design for a large draw ratio (>3:1 molded surface area to sheet surface area) thermoforming mold and a cost-benefit analysis of segmentation versus monolithic design. Discussion of the thermoforming tests are included. The primary goals were to improve manufacturability and reduce the overall cost of the mold.

Manufacturability↗
DOE OSTI2019

Towards an integrated experimental and computational framework for large-scale metal additive manufacturing

In this work using the Metal Big Area Additive Manufacturing (MBAAM) system, a thin steel wall was manufactured from a low carbon steel wire. The wall was then characterized comprehensively by high-throughput high-energy X-ray diffraction (HEXRD), electron backscatter diffraction (EBSD), and in-situ HEXRD tensile tests. With the predicted temperature histories from the finite element-based additive manufacturing process simulations, the correlations between processing parameters, microstructure, and properties were established. The correlation between the final microstructure with the predicted temperature history is well explained with the material's continuous cooling transformation (CCT) diagram calculated based on the composition of the low carbon steel wire. The final microstructure is dependent on the cooling rate during austenite to ferrite/bainite transformation during initial cooling and the subsequent reheating cycles. Fast cooling rate resulted in small ferrite grain size and fine bainite structure at the location closest to the base plate. Slower cooling rate at the side wall location and repeated reheating cycles to the ferrite-pearlite regions resulted in all allotriomorphic (equiaxed) ferrite with medium grain size with small amount of pearlite. With no reheating cycles, the top location has the slowest cooling rate and a large grained allotriomorphic ferrite and bainitic structures. The measured mechanical strength is then related to the microstructural feature size (grain or lath size) observed in those locations. Thus, a good correlation is found between the mechanical properties, microstructure features and the temperature history at various locations of the printed wall.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Additively manufactured tantalum microstructures

Additively manufacturing tantalum is a challenging process in which obstacles are stemming from the high melting temperature and susceptibility to oxidation of tantalum. In this paper, several combinations of deposition parameters were considered in an effort to obtain fully dense additively manufactured tantalum produced on an EOSINT M280 DMLS system. Deposition parameters significantly affect the resulting microstructure of additively manufactured tantalum, altering grain morphology, grain size, crystallographic preferred orientation, and deposition porosity. Due to the nature of the laser sintering process applied, which implies large directional temperature gradients, the resulting microstructures were strongly columnar along the building direction. Microstructural differences for different deposition conditions manifested themselves in both grain morphology and preferred crystal orientations in the columnar grains. Deposition speed and laser power were important parameters to consider for obtaining porosity-free material. Finally, stripe width had the most significant effect on grain growth.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Chemical composition based machine learning model to predict defect formation in additive manufacturing

With a goal of exploiting additive manufacturing to improve the manufacturing of existing reactor materials, we developed a chemical composition-based machine learning model to predict the printability of any given alloy in laser powder bed fusion (L-PBF) using experimental data from peer-reviewed literature. We defined printability as the ability to avoid defects like cracking, balling, porosity, and lack of fusion, that are caused by thermal stresses (during solidification or liquation), molten pool disintegration into disconnected small beads or lack of heat input respectively. Our models predict the tendency of balling defect formation and porosity percentage for a given composition, under a given set of processing conditions. To predict the likelihood of balling defect, three models: a random forest classifier, a gradient boost regressor and a neural network were trained on a dataset containing both traditional alloys and high entropy alloys. The neural network model showed the highest accuracy of 92.3 % in predicting the balling defect formation. A random forest regressor, gradient boost regressor and neural network were trained and tested on a dataset of various alloys to predict porosity. The random forest regressor showed the best predictions with an R 2 score of 0.97. The models also revealed the relative importance of the input descriptors on defect-formation tendency. Of particular significance was the identification of carbon as an important element in determining the occurrence of balling and percent porosity in alloys like steel, as well as being moderately important to the percentage porosity in other alloys as well as steel. Manganese was also identified as a key descriptor for the percentage of porosity in steel and other alloys. Manganese’s low thermal conductivity and consistent presence in the dataset is the likely cause for its contribution. Carbon’s role is attributable to its relatively high specific heat and high melting temperature. In conclusion, our model serves as a swift, chemistry-based tool to design experiments and find modified compositions better suited for additive manufacturing.

36 MATERIALS SCIENCE↗
DOE OSTI2018

Structural Optimization of a Direct-Drive Wind Turbine Generator Inspired by Additive Manufacturing

This study explores the structural freedom and design opportunities of additive manufacturing for a 5-MW direct-drive generator for a wind turbine and compares it to more traditional spoke-arm designs using NREL's GeneratorSE. The work focuses on light-weighting the stator within the generator, complementing previous rotor work. The light-weighting approach uses complex geometries and lattice structures made possible by additive manufacturing to realize increased strength with reduced mass. By reducing the mass at the top of the tower, wind turbines face lower loading along with decreased cost and improved structural stability. Furthermore, an altered bedplate support location facilitates lighter stator designs by better load transfer. Design optimization suggests additive manufacturing has the potential to transform generator designs to realize light-weighting. Since these machines are large, simulation and modeling are essential first steps before future experimental validation.

17 WIND ENERGY↗