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At least 775 records · Page 43
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Reactor physics phenomena in additively manufactured control elements for the High Flux Isotope Reactor

Additive manufacturing is under investigation as a novel method of fabricating the control elements (CEs) of the High Flux Isotope Reactor (HFIR) at Oak Ridge National Laboratory with greater simplicity, eliminating numerous highly complex fabrication steps and thereby offering potential for significant savings in cost, time, and effort. This process yields a unique CE design with lumped absorbers, a departure from traditionally manufactured CEs with uniformly distributed absorbing material. Here, this study undertakes a neutronics analysis of the impact of additively manufactured CEs on the HFIR core physics, seeking preliminary assessment of the feasibility of their practical use. The results of the MCNP transport simulations reveal changes in the HFIR reactor physics arising from geometric and nuclear effects. Absorber lumping in the discrete CEs yields a large volume of unpoisoned material that is not present in the homogeneous design, in turn yielding increases in free thermal flux in the CE absorbing regions and their immediate vicinity. The availability of additional free thermal neutrons in the core yields an increase in fission rate density in the fuel closest to the CEs and a corresponding increase in neutron multiplication on the order of 100 pcm. The absorption behavior exhibited by the discrete CEs is markedly different from the homogeneous CEs due to several competing effects. Self-shielding arising from absorber lumping acts to reduce the effective absorption cross section of the discrete CEs, but this effect is offset by geometric and spectral effects. The operational performance of the discrete CEs is found to be comparable to the homogeneous CEs, with only limited deficiencies in reactivity worth that are expected to be operationally recoverable via limited adjustment of the CE positions and withdrawal rate. On the whole, these results indicate that the discrete CEs perform reasonably similarly to the homogeneous CEs and appear feasible for application in HFIR. In conclusion, the physical phenomena identified in this study provide valuable background for follow-up design studies.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Waste plastic- and coke-derived flash graphene as lubricant additives

Lubricants play an essential role in reducing wear in mechanical systems. Carbon nanomaterial additives, such as graphene, have been found to significantly improve tribological performance when used as lubricant additives. Here, in this study, post-consumer plastic and metallurgical coke are converted into turbostratic flash graphene (FG) through flash Joule heating (FJH). The FG is then added to either poly(alpha olefin) 6 or 9 (PAO 6 or PAO 9). Adding waste plastic-derived FG (WPFG) and metallurgical coke-derived FG (MCFG) to lubricants resulted in a significant decrease in the coefficient of friction (CoF), wear scar diameter (WSD), and roughness during four-ball testing. WPFG and MCFG decrease the CoF in PAO 9 by 6% and 9% at 0.1 mg mL -1 , respectively, and in PAO 6 by 23% and 6% at 0.5 mg mL -1 , respectively. WPFG and MCFG decrease the WSD of steel balls in PAO 9 by 14% and 8% at 0.5 mg mL -1 , respectively, and in PAO 6 by 12% and 14% at 0.5 mg mL -1 , respectively, by forming a coating-like layer between the metal surfaces. Roughness decreased by 38% and 32% for WPFG and MCFG in PAO 6, respectively, and by 35% and 29% for WPFG and MCFG in PAO 9, respectively. Finally, preliminary life cycle analyses demonstrate that production of FG produces up to 99% less greenhouse gas emissions, requires 98% less energy, and consumes 99.9% less water when compared to conventional production techniques of graphene. Hence, metallurgical coke and waste plastic are shown to be ready feedstocks for high-quality FG lubricant additives.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Kinetic Monte Carlo simulations of structural evolution during anneal of additively manufactured materials

Our experiments indicated that upon a post-processing anneal, an additively manufactured 316L stainless steel exhibits cubic grains rather than the conventional equiaxed grains. In this work, we have used kinetic Monte Carlo simulations to explore the origin of these cubic grains. First, we implemented a new kinetic Monte Carlo model in parallel code SPPARKS to simulate grain growth and recrystallization under a residual energy distribution. Our model incorporates physical properties and real-time, as opposed to generic properties and relative time. We further validated that our SPPARKS simulations reproduced the expected kinetic behavior of single-grain evolution. We then used the validated approach to simulate the anneal of an additively manufactured material under the same conditions used in our experiments. We found that the cubic grains can origin from a periodically varying residual energy that may be present in additively manufactured materials.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Spatiotemporal parallelization of an analytical heat conduction model for additive manufacturing via a hybrid OpenMP + MPI approach

The ability to do thermal simulations for entire additive manufacturing builds is a key computational problem facing the additive manufacturing community; however, complex numerical models considering multiple physical phenomena currently do not have the capacity for simulations at this scale. To this end, conduction only analytic models offer a viable approach due to the massive drop in computational expense. In this work, we extend an existing implementation which uses a governing equation which can be evaluated at any point in space and time. This implementation already utilizes OpenMP with a spatial decompositions scheme stemming from a melt pool tracking algorithm. Furthermore, we then combine this with a parallel in time (PinT) approach to make the problem highly parallelizable. The new scheme, which uses MPI for internode communication and OpenMP for intranode communication, is shown to scale very well across multiple computational nodes. This approach results in the ability to simulate the 3D solidification conditions for entire layers of additively manufactured parts in minutes making part scale thermal simulations more practical.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Understanding structure-processing relationships in metal additive manufacturing via featurization of microstructural images

Understanding and predicting accurate property-structure-processing relationships for additively manufactured components is important for both forward and inverse design of robust, reliable parts and assemblies. While direct mapping of process parameters to properties is sometimes plausible, it is often rendered difficult due to poor microstructural control. Exploring the direct relationship between processing conditions and microstructural features can thus provide significant physical insights and aid the overall design process. Here, in this study, we develop an automated high-throughput framework to simulate an uncertainty-aware additive manufacturing (AM) process, characterize microstructural images, and extract meaningful features/descriptors. A kinetic Monte Carlo (KMC) based model of the AM process is used to simulate microstructural evolution for a diverse set of experimentally relevant processing conditions. We perform a parametric study to explore the relationship between microstructural features and processing conditions. Our results indicate that a many-to-one mapping can exist between processing conditions and typical descriptors; therefore, multiple descriptors are thus necessary to unambiguously represent microstructural images. Our work provides crucial quantitative and qualitative in-formation that would aid in the selection of features for microstructural images. Featurized microstructures could then be utilized to build data-driven models for predictive control of microstructures and thereby properties of additively manufactured components.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Self-supervised learning of spatiotemporal thermal signatures in additive manufacturing using reduced order physics models and transformers

Microstructure control via additive manufacturing has enormous potential as manufacturers, materials scientists, and designers alike seek to exploit novel fabrication technologies to improve component performance. Recent works have demonstrated the feasibility of producing materials with controlled microstructures across various length scales. However, the experimental approach towards exploring the process-structure space can be laborious and costly. This is particularly true if also considering scan pattern optimization which is well suited for processes such as powder bed fusion electron beam melting. In this work we propose an approach for encoding additive manufacturing layer-wise thermal response signatures using self-supervised representation learning. Thermal simulations from a reduced order model are utilized to estimate the spatiotemporal response during printing. A machine learning framework, using video-transformers, is utilized to efficiently distill spatiotemporal patterns into a compact latent space representation. This latent state representation encodes the relevant physics which is then utilized to establish a data-driven process-structure model for an additively manufactured Ni-based superalloy. In conclusion, the proposed methodology could potentially be used towards in-situ process monitoring, scan pattern experimental design, and component qualification.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Numerical framework for integrated additive manufacturing-compression molding (AM-CM) of thermoplastic composites

Additive manufacturing-compression molding (AM-CM) has emerged as a transformative technology in advanced composite manufacturing. Additive manufacturing (AM) offers high design flexibility and the ability to produce complex geometries with precisely aligned fibers in the preferred orientation. Compression molding (CM) enhances composite materials by providing excellent dimensional stability, reduced porosity, high production rates, and a smooth surface finish. Despite these advantages, extensive integrated analysis is required to optimize processing conditions for improved fiber orientation distribution (FOD) and porosity control. Here, this study develops a comprehensive numerical model to simulate the AM-CM manufacturing process. The model isolates the effects of both the AM and CM phases while also capturing their integration. Additionally, it accounts for heat transfer, temperature-dependent viscosity, and fiber orientation in the extruded fiber-filled polymer, accurately representing material behavior during processing. This approach enables the analysis of interactions between deposited beads of complex strand shapes and their interface regions after full compression. Moreover, the model predicts key parameters such as polymer flowability, fiber orientation, and temperature evolution in AM-CM parts. By optimizing processing conditions, it facilitates a controlled and predictable microstructure.

36 MATERIALS SCIENCE↗
DOE OSTI2026

Engineering mechanical and thermomechanical performance in additive manufacturing–Compression molded composites through multiplexed extrusion

Traditional extrusion-based additive manufacturing is limited to single material systems, restricting the multifunctional properties of composites. For this work to overcome this limitation, multiplexed additive manufacturing–compression molding (AM-CM) was employed to fabricate multi-material thermoplastic composites with spatially tailored architectures. Neat acrylonitrile butadiene styrene (ABS) and 20 wt% carbon-fiber reinforced ABS (CF-ABS) were co-extruded through a core–sheath nozzle to produce hybrid composites with neat ABS as sheath (30-50 wt%) and CF-ABS as core (50 – 70 wt%). The results show that the hybrid composites have balance of mechanical and thermomechanical performance. The tensile strength and modulus of hybrid composites exhibited a 61–95% and 173–473% increase compared to neat ABS with increases in CF-ABS content whereas the impact resistance improved by 41% compared to CF-ABS at 50 wt% ABS. Additionally, hybrid composites showed significant reduction (54 - 70%) in creep strain at 100 °C compared to neat ABS. These findings demonstrate that multiplexed AM-CM enables tunable structure–property relationships, reducing CF-ABS usage up to 50 wt% while maintaining balanced stiffness, toughness, and creep resistance.

Additive manufacturing↗
DOE OSTI2016

Microstructural design and additive manufacturing and characterization of 3D orthogonal short carbon fiber/acrylonitrile-butadiene-styrene preform and composite

In contrast to conventional preforming techniques, additive manufacturing features direct and layer-by-layer fabrication, which provides viable new capabilities for the fabrication of reinforced composites. In this paper, we explore the microstructural design as well as additive manufacturing and characterization of 3D orthogonal, short carbon fiber/acrylonitrile-butadiene-styrene (ABS) preforms and composite. First, an array of 3D orthogonal preforms is designed based on topological consideration and validated by fused filament fabrication of pure ABS wire; high fidelity between models and preforms is accomplished. Then, short carbon fibers are introduced into the designed 3D orthogonal preforms as reinforcement, using a short carbon fiber/ABS wire. Lastly, the compressive behavior of a 3D orthogonal, short carbon fiber/ABS preform and that of its silicone infused composite are characterized. Finally, the preform design methodology developed in this research as well as the preliminary effort made in composite fabrication and characterization demonstrates the feasibility of additive manufacturing of 3D orthogonal preform based fiber composites.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Interlayer fusion bonding of semi-crystalline polymer composites in extrusion deposition additive manufacturing

This work focuses on the evolution of interlayer fracture toughness properties of fiber-reinforced, semi-crystalline polymers in the extrusion deposition additive manufacturing (EDAM) process. Further, this work bridges the gap between the additive process conditions (time-temperature history) and the effective layer-to-layer fracture properties developed within a printed component. This is the first step to predict delamination that can occur during printing, during cooling to room temperature after printing, and during service performance of an additively manufactured geometry. A phenomenological model is developed for fusion bonding of semi-crystalline polymer matrix composites by coupling the interdiffusion of polymer chains with the evolution of polymer crystallinity. While the interdiffusion is captured by reptation theory of polymer dynamics, the evolution of crystallinity is modeled by phenomenological crystallization kinetics and crystal melting dynamics. Further, a methodology is developed to determine the critical strain energy release rate, G IC of the interlayer interface and experiments are conducted utilizing the double cantilever beam fracture test geometry. In conclusion, predictions of GIC as a function of thermal history are compared with experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Defects and anomalies in powder bed fusion metal additive manufacturing

Metal additive manufacturing is a disruptive technology that is revolutionizing the manufacturing industry. Despite its unrivaled capability for directly fabricating metal parts with complex geometries, the wide realization of the technology is currently limited by microstructural defects and anomalies, which could significantly degrade the structural integrity and service performance of the product. Accurate detection, characterization, and prediction of these defects and anomalies have an important and immediate impact in manufacturing fully-dense and defect-free builds. As such, this review seeks to elucidate common defects/anomalies and their formation mechanisms in powder bed fusion additive manufacturing processes. They could arise from raw materials, processing conditions, and post-processing. While defects/anomalies in laser welding have been studied extensively, their formation and evolution remain unclear. Additionally, the existence of powder in powder bed fusion techniques may generate new types of defects, e.g., porosity transferring from powder to builds. Practical strategies to mitigate defects are also addressed through fundamental understanding of their formation. Such explorations enable the validation and calibration of models and ease the process qualification without costly trial-and-error experimentation.

42 ENGINEERING↗
DOE OSTI2024

Multifunctional nitrile additives for inducing pseudo-concentration gel-polymer electrolyte: Enabling stable high-voltage lithium metal batteries

High-voltage lithium metal batteries (LMBs) are promising for next-generation high-energy storage systems. Unfortunately, their implementation has been severely plagued by the interfacial instability between the high-voltage cathodes/lithium metal (LM) anodes and electrolytes. To tackle these challenges, a novel nitrile additive, 1,4-dicyanobenzene (DCB) (Synonyms: terephthalonitrile), is added to the in situ polymerized pentaerythritol tetraacrylate-based gel polymer electrolyte (GPE). The DCB additive, as demonstrated both theoretically and experimentally, plays a crucial role in altering the Li+ coordinated solvation structure within the GPE. This alteration leads to the formation of a pseudo-concentrated electrolyte with a tightly packed Li+ cluster, expanding the electrochemical stability window of the electrolyte. Moreover, the DCB-included GPE significantly improves its compatibility with both LM anode and high-voltage cathode, attributed to the modified solvation structure and the generated LiF-rich electrolyte/electrode interphases. Accordingly, the GPE enables stable cyclic performance of LMBs based on a 4.9 V LiNi 0.5 Mn 1.5 O 4 cathode at a low relative negative/positive ratio of 4, achieving a high reversible capacity of 123.8 mAh g -1 with a capacity retention of 87.7% over 500 cycles at 0.5 C. This work provides new insights into enhancing the cyclability of high-voltage LMBs via the synergistic effect of additives and GPE.

25 ENERGY STORAGE↗
DOE OSTI2019

Binder jet additive manufacturing method to fabricate near net shape crack-free highly dense Fe-6.5 wt.% Si soft magnets

High silicon (Si) electrical steel has the potential for efficient use in applications such as electrical motors and generators with cost-effective in processing, but it is difficult to manufacture. Increasing the Si content beyond 3 wt.% improves magnetic and electrical properties, with 6.5 wt.% being achievable. The main goal of this research is to design, develop, and implement a scalable additive manufacturing process to fabricate Fe with 6.5 wt.% Si (Fe–6Si) steel with high magnetic permeability, high electrical resistivity, low coercivity, and low residual induction that other methods cannot achieve because of manufacturing limitations. Binder jet additive manufacturing was used to deposit near net shape components that were subsequently sintered via solid-state sintering to achieve near full densification. Here, it is shown that the use of solid-state sintering mitigates cracking since no rapid solidification occurs unlike fusion-based additive technologies. The Fe–6Si samples demonstrated an ultimate tensile strength of 434 MPa, electrical resistivity of 98 μΩ cm, and saturation magnetization of 1.83 T with low coercivity and high permeability. The results strongly supports to replace the only available 0.1 mm thick chemical vapor deposition (CVD) produced Si steel using the cost effective AM method with good mechanical and magnetic properties for motor ap

36 MATERIALS SCIENCE↗
DOE OSTI2025

Convective heat transfer enhancement through additively built multiscale micro-tetrahedron features

Use of Additive Manufacturing (AM) to improve the heat transfer characteristics of tip shrouds in high-pressure turbines is being considered by industries. Existing designs of these components integrate micro-cooling channels to reduce the bulk temperature for improved life. In this research, closely packed micro tetrahedron features in addition to AM roughness has been considered. Further, this multiscale surface characteristics increased surface area per unit volume available for heat exchange. Micro-tet features were designed, manufactured, characterized, and evaluated systematically while increasing their height. An enormous increase in the overall wetted surface area by 200 % was measured. The convective heat transfer enhancement was ~3.72 times EDM rough coupon, and friction factor enhancement was ~5.5 times EDM rough coupon. Furthermore, the proposed design offers 2.5 times enhanced heat transfer for a given 2 W pumping power compared to our EDM rough coupon. Heat transfer enhancement was observed to not vary strongly with increased Reynolds number. Such complex designs are only possible through additive manufacturing for increased heat transfer with little pressure penalty. Finally, increasing the micro-tet height for increased surface area and improved heat exchange beyond an upper limit might not be a significant benefit as it gets compensated by increasing skin friction.

42 ENGINEERING↗
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 OSTI2023

Gradient process parameter optimization in additive friction stir deposition of aluminum alloys

As one of the most novel additive manufacturing methods, currently selection and optimization of processing parameters in additive friction stir deposition (AFSD) have mainly relied on experiments and subsequent characterization of microstructural and mechanical properties. Such approaches are both time- and resource-consuming. Therefore, an ultrasound elastography enhanced gradient process parameter optimization method was applied in the present work to obtain a window of optimized processing parameters for AFSD processing of aluminum alloy by varying both rotational and linear deposition speeds. Further, the quality of AFSD processed layer was investigated for physical nature of surface, dynamic elastic modulus, and microstructural aspects in cross-sections of the deposited layer. The efficiency in exploring process parameters was significantly enhanced by implementing a high-throughput screening experimental design based on application of gradient process parameters and continuous ultrasound elastographs. In addition, the applied ultrasonic elastography technique assisted in evaluating the homogeneity in microstructure and mechanical properties of AFSD sample over the entire gradients of the process parameters. The techniques adopted in current work can be further extended to identify suitable parameters for AFSD fabrication of components with desired mechanical properties such as hardness, fatigue, etc.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Microstructure and high temperature properties of tungsten processed via electron beam melting additive manufacturing

There is considerable interest in the adoption of additive manufacturing for processing refractory metals. The layer-wise fabrication approach enables opportunities for producing complex geometries which cannot be otherwise be achieved via powder metallurgy. However, the processing science is still in its nascent stages and structure–property relations are relatively unexplored. Fundamental research is needed to further develop the technology and enable the fabrication of refractory metals for high temperature applications. Here we focus on the processing of pure tungsten using electron beam melting additive manufacturing. Experimentally we develop a suitable processing window for achieving high density crack free material. Microstructural analysis reveals that the microstructure generally consists of a columnar structure with a (111) build direction fiber preference, although, fiber switching was observed. Process induced deformation is believed to drive the formation of subgrains whose boundaries exhibit a high dislocation density. Additionally, high temperature tensile testing reveals that the material exhibits excellent properties closer to that of annealed tungsten. Significant mechanical anisotropy was observed to be present which is likely driven by strong crystallographic texture.

36 MATERIALS SCIENCE↗
DOE OSTI2021

In situ synchrotron X-ray imaging and mechanical properties characterization of additively manufactured high-entropy alloy composites

Laser beam directed energy deposition has become an increasingly popular advanced manufacturing technique for materials discovery as a result of the in situ alloying capability. In this study, we leverage an additive manufacturing enabled high throughput materials discovery approach to explore the composition space of a graded W x (CoCrFeMnNi) 100–x sample spanning 0 ≤ x ≤ 21 at%. In addition to microstructural and mechanical characterization, synchrotron high speed x-ray computer aided tomography was conducted on a W 20 (CoCrFeMnNi) 80 composition to visualize melting dynamics, powder-laser interactions, and remelting effects of previously consolidated material. Results reveal the formation of the Fe 7 W 6 intermetallic phase at W concentrations> 6 at%, despite the high configurational entropy. Unincorporated W particles also occurred at W concentrations> 10 at% accompanied by a dissolution band of Fe 7 W 6 at the W/matrix interface and hardness values greater than 400 HV. In this work, the primary strengthening mechanism is attributed to the reinforcement of the Fe 7 W 6 and W phases as a metal matrix composite. The in situ high speed x-ray imaging during remelting showed that an additional laser pass did not promote further mixing of the Fe 7 W 6 or W phases suggesting that, despite the dissolution of the W into the Fe 7 W 6 phase being thermodynamically favored, it is kinetically limited by the thickness/diffusivity of the intermetallic phase, and the rapid solidification of the laser-based process.

36 MATERIALS SCIENCE↗