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At least 271 records · Page 15
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Machine Learning for Additive Manufacturing of Functionally Graded Materials

Additive Manufacturing (AM) is a transformative manufacturing technology enabling direct fabrication of complex parts layer-by-layer from 3D modeling data. Among AM applications, the fabrication of Functionally Graded Materials (FGMs) has significant importance due to the potential to enhance component performance across several industries. FGMs are manufactured with a gradient composition transition between dissimilar materials, enabling the design of new materials with location-dependent mechanical and physical properties. This study presents a comprehensive review of published literature pertaining to the implementation of Machine Learning (ML) techniques in AM, with an emphasis on ML-based methods for optimizing FGMs fabrication processes. Through an extensive survey of the literature, this review article explores the role of ML in addressing the inherent challenges in FGMs fabrication and encompasses parameter optimization, defect detection, and real-time monitoring. The article also provides a discussion of future research directions and challenges in employing ML-based methods in the AM fabrication of FGMs.

36 - MATERIALS SCIENCE↗
DOE OSTI2024

Corrosion testing needs and considerations for additively manufactured materials in nuclear reactors

Additive manufacturing (AM) technologies have developed rapidly in recent years, creating new opportunities and challenges for the nuclear industry; however, adoption requires that their corrosion performance be evaluated. Here, we discuss known reactor-specific corrosion issues for multiple reactor types and engineering concerns such as regulations and standards. A review of corrosion studies conducted on select AM alloys informs a discussion on key bulk and surface factors likely to impact corrosion behaviors. Recommendations to assess corrosion performance for AM materials are provided, including management of the unique nature of as-built AM surfaces and the inherent process variability that occurs for AM components.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Dislocation channel broadening–A new mechanism to improve irradiation-assisted stress corrosion cracking resistance of additively manufactured 316 L stainless steel

Additively manufactured (AM) 316 L stainless steel (SS) after hot isostatic pressing (HIP) was found to exhibit superior resistance to irradiation-assisted stress corrosion cracking (IASCC) in high-temperature water, as compared to wrought 316 L SS. The well-accepted IASCC factors of radiation-induced segregation (RIS) and radiation hardening are not accurate descriptions of IASCC susceptibility in this case. A decreased strain localization along grain boundaries, caused by dislocation channel broadening, was confirmed to suppress crack initiation. A unique distribution of irradiation-induced defects in HIP AM 316 L SS eased dislocation cross-slip compared to those in the wrought counterpart, thus increasing the channel width near the grain boundaries. Here for the first time, this study highlights the importance of dislocation channel broadening as a potential mechanism to further improve the IASCC resistance of 316 L SS and provides direct experimental evidence based on commercial-grade materials.

316L stainless steel↗
DOE OSTI2022

Prospects for additive manufacturing of nuclear fuel forms

Additive manufacturing (AM) is viewed as a critical enabling technology for achieving superior performance and improved economics across many sectors. Although the past decade has seen increased application of AM methods to nuclear reactor cladding and structural materials, exploration of AM as applied to the uranium-bearing nuclear fuel forms has been limited. The two major families of nuclear fuel forms (monolithic, particle/dispersion) are utilized with their own set of core objectives in mind, and their differences require distinct fabrication infrastructures. These reference fabrication methods impose many limitations on nuclear fuels. Further, both currently operating reactors and future concepts have the potential for improved performance if these accepted limitations are relaxed or removed entirely. The primary limitations of reference fabrication processes for the common nuclear fuel forms are outlined in this paper. This groundwork is then used to identify avenues of fuel performance specific to each of these fuel architectures that could be exploited if the restrictions of conventional fuel fabrication are removed. Moreover, multiple targets for AM studies are laid out for each of the major nuclear fuel variants. Finally, key strategic components to guide research activities in AM of nuclear fuels are outlined, with an emphasis on use of modeling and simulation to motivate research aims and embrace of an accelerated testing methodology to screen and quality new fuel forms.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2023

Virtual Volumetric Additive Manufacturing (VirtualVAM)

Abstract Tomographic volumetric additive manufacturing (VAM) produces arbitrary 3D geometries by exposure of a rotating volume of photopolymer resin to tomographically‐patterned illumination. This enables high speed, layer‐less printing of parts from a wide range of photopolymers not amenable to layer‐by‐layer processes. Since the entire geometry is produced at once over the course of a few seconds to minutes, molecular diffusion length scales become significant to the printing process. Understanding these molecular reaction and diffusion processes is imperative for advancing VAM to a usable technology. These processes are experimentally very difficult to monitor and measure. Herein, VirtualVAM ‐ a simulation framework for modeling the tomographic VAM process, is developed and experimentally validated. VirtualVAM simulates reaction, diffusion, and heat generation processes over the course of a print with single‐voxel resolution. From a few experimentally‐determined input parameters and a set of images for projection, VirtualVAM is able to generate a large spatio‐temporal data set for any given tomographic VAM print. Using VirtualVAM, a number of experimentally‐unattainable aspects of the VAM process are investigated such as single‐voxel conversion profiles, effect of molecular oxygen, and stopping time determination. VirtualVAM also enables the optimization of exposure patterns to further improve contrast between in‐part and out‐of‐part delivered dose.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2021

In situ X-ray imaging of pore formation mechanisms and dynamics in laser powder-blown directed energy deposition additive manufacturing

Directed energy deposition (DED) additive manufacturing (AM) is receiving growing attention in many applications, such as repair, remanufacturing, and fabrication of functionally graded structures. However, the laser-matter interactions and melt pool dynamics in laser DED with powder flow are still unclear, particularly in how pores form and flow inside the melt pool during the process. Understanding the porosity formation mechanisms is critical in the qualification, certification, and overall properties of a DED AM part. Porosity is a common phenomenon and can significantly hinder the quality of DED fabricated parts, as the pores can act as sites of crack nucleation and propagation. Here in this paper, we reveal four types of pore formation mechanisms through in-situ and operando high-speed high-resolution X-ray imaging in the DED AM process. Our results confirm that porosity within the feedstock powder induces pores in the process. We also observed pore formation mechanisms unique to the laser-based, powder-blown DED process as a result of powder delivery, keyhole dynamics, melt pool dynamics, and shield gas. High-speed X-ray images provide direct evidence for pore formation mechanisms and show that the pores related to the interaction between the delivered powder and melt pool are the largest in size in laser-based powder-blown DED AM. These results will guide porosity mitigation, elimination, and control in DED AM.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Additive manufacturing of multi-component parts for customizable energetic systems

An apparatus, system, and method utilizes at least two separate components during the process of producing the final product. At least one component during the process is produced using additive manufacturing, and additional components are components that are combined with the additively manufactured part. The apparatus, system, and method includes at least one energetic component and at least one second inert component. An additive manufacturing system produces a scaffold of said first energetic component(s). A system adds the second component(s) to the scaffold to produce the energetic material product.

Sullivan, Kyle T.↗
DOE OSTI2024

Additive manufacturing of LiCoO 2 electrodes via vat photopolymerization for lithium ion batteries

Additive manufacturing has the potential to revolutionize the fabrication of lithium-ion batteries for a diversity of applications including in portable, biomedical, aerospace, and the transportation fields. Standard commercial batteries consist of stacked layers of various components (current collectors, cathode, anode, separator and electrolyte) in a two-dimensional manner. By leveraging the latest advances in additive manufacturing and computer-aided design, an improved geometric and electrochemical configuration of these batteries can maximize energy efficiency while allowing design optimization to reduce dead space for a given application. In this work, a composite UV photosensitive resin was prepared and used as feedstock in a vat photopolymerization system. The resin was loaded with LiCoO 2 acting as electrochemically active material for the cathode of a lithium-ion battery, and was further improved with the addition of conductivity-enhancing carbonaceous additives. Challenges to additive manufacturing arise from the opacity and high viscosity of the composite nature of these electrochemically-active resins, which cause light refraction during selective UV curing. Subsequently, items were printed and subjected to a thermal post-processing step to obtain an adequate compromise between electrochemical performance and mechanical integrity. Both sintered and green state 3D printed cathodes were assembled into half-cell lithium-ion batteries using lithium metal as a reference and counter electrode. Electrochemical cycling of these batteries yielded satisfactory results approaching commercial LiCoO 2 cathodes’ performance, with the potential advantages of additive manufacturing – high surface area anode–cathode configurations for power performance as well as shape conformability.

25 ENERGY STORAGE↗
DOE OSTI2020

Development of Monitoring Techniques for Laser Powder Bed Additive Manufacturing of Metal Structures (Progress Report)

The Transformational Challenge Reactor (TCR) program is leveraging additive manufacturing (AM) technologies to fabricate nuclear grade components to be assembled into a fully functional microreactor core. Compared to traditional manufacturing technologies, additive manufacturing technologies allow (1) observation of the manufacturing process at a much higher resolution in real time using in situ monitoring technologies to capture the sensor signature that scientifically describes each event occurring over time and space, and (2) validation of the manufacturing process quality using domain-informed data analytics techniques as a potential qualification and certification methodology for the final component. This report provides an update on the program work on laser powder bed fusion in-situ process monitoring and associated data analytics results. Examples are provided to illustrate the progress. Elements of the Digital Thread and data management are discussed in the main document, and an extensive supplemental material section is provided detailing the Digital Platform, as well as its implementation and components. In conclusion the path forward for the next fiscal year is discussed.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

On the Prediction of Uniaxial Tensile Behavior Beyond the Yield Point of Wrought and Additively Manufactured Ti-6Al-4V

In this paper, phenomenological relationships are presented that permit the prediction of the plastic regime of stress–strain curves using a limited number of parameters. These relationships were obtained from both conventional (wrought + β annealed) and additively manufactured (i.e., “3D printed”) Ti-6Al-4V. Three different methods of additive manufacturing have been exploited to produce the materials, including large-volume electron beam additive manufacturing, large-volume laser hot wire additive manufacturing, and small-volume selective laser melting. The general fundamental expressions are independent not only of the additive manufacturing process, but also of a wide variety of post-deposition heat treatments, however the coefficients are specific to material states. Thus, this work demonstrates that it is possible to predict not only the ultimate tensile strength, but also the full true stress, true strain curves, if certain parameters of the material are known. In general, the prediction of ultimate tensile strength are within 5% of the experimentally measured values across all additive manufacturing variants and subsequent heat treatments. The absolute values of ultimate tensile strength range from ~ 910 MPa to ~ 1170 MPa for the single alloy Ti-6Al-4V. Data representing 113 explicit samples are included in this work.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Tailoring additive manufacturing to optimize dynamic properties in 316L stainless steel

With the advent of additive manufacturing, manipulation of typical microstructural elements such as grain size, texture, and defect densities is now possible at a faster time scale. While the processing–structure–property relationship in additive manufactured metals has been well studied over the past decade, little work has been done in understanding how this process affects the dynamic behavior of materials. We postulate that additive manufacturing can be used to alter the material microstructure and used to enhance its dynamic strength. In this work, 316L stainless steel (SS) was manufactured via selected laser melting and its microstructure was altered through changing build parameters like laser power, speed, and hatch spacing systematically. These samples were then subjected to spall recovery experiments to measure the spall strength and quantify the amount of damage as a function of build parameters. By mapping the spall strength as a function of build parameters, this work demonstrated that indeed additive manufacturing can be used to tailor the spall strength of 316L SS. This work also determined the optimum build parameters (laser power=195W; scanning speed=1083mm/s; hatch spacing=0.09mm; layer thickness=0.02mm) to obtain the highest spall strength and the least amount of total damage in 316L SS. Microstructural characterization of the pre- and post-mortem samples revealed that increased grain average misorientation and textural index were the main driving force behind this higher spall strength. This work aims to enhance microstructural engineering techniques to design materials with greater resistance to dynamic shock loading.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Additively manufacturing fluorine-containing polymers

A system and method of additively manufacturing a part including electrically conductive or static dissipating fluorine-containing polymers. The method includes depositing fluorine-containing polymer additive manufacturing material onto a build platform, selectively cross-linking portions of the deposited additive manufacturing material, and curing the selectively cross-linked portions such that the part is at least one of electrically conductive and static dissipating.

Selter, Thomas Matthew↗
DOE OSTI2025

Electroslag additive manufacturing: A pathway for high throughput near net shape production

Electroslag Additive Manufacturing (ESAM), a new high-throughput additive manufacturing (AM) method that combines Electroslag Strip Cladding (ESC) and wire arc AM (WAAM) is introduced. This combination enables the high deposition rate of ESC (more than 20 kg/h with a 60 mm strip electrode) to benefit from the precise geometric control of WAAM. As a precursor to ESAM, the ESC process is investigated in an AM context independently by evaluating both direct and staggered bead-stacking strategies and analyzing the microstructural and mechanical properties of each. This is followed by an ESAM demonstration producing an annular geometry by pairing ESC with gas tungsten arc welding (GTAW), wherein GTAW is utilized to construct annular walls that are subsequently infilled via ESC. The microstructure and mechanical properties of ESC-only AM are compared with that of the ESAM method and it is shown that printed integral retaining walls do not impact the resulting mechanical properties of ESAM. Furthermore, results indicate that ESAM-produced Alloy 625 parts exhibit tensile properties on par with cast counterparts, supporting the method’s scalability to components exceeding one metric ton, and possibly making ESAM a viable future manufacturing approach for competitive production of large-scale components currently manufactured by casting and forging.

Additive manufacturing↗
DOE OSTI2025

Slicing Solutions for Wire Arc Additive Manufacturing

Both commercial and research applications of wire arc additive manufacturing (WAAM) have seen considerable growth in the additive manufacturing of metallic components. However, there remains a clear lack of a unified paradigm for toolpath generation when slicing parts for WAAM deposition. Existing toolpath generation options typically lack the appropriate features to account for all complexities of the WAAM process. This manuscript explores the key slicing challenges specific to toolpaths for WAAM geometry and pairs each consideration with multiple solutions to mitigate most negative effects on completed components. These challenges must be addressed to minimize voids, prevent bead collapse, and ensure deposited components accurately approximate the desired geometry. Slicing considerations are grouped into four general categories: geometric, process, thermal, and productivity. Geometric considerations are addressed with overhang compensation, corner-sharpening, and toolpath-smoothing features. Process considerations are addressed with start point configuration and controls for the bead lengths and end points. Thermal and productivity considerations are addressed with island optimization, multi-material printing, and connected insets. Finally, tools for the post-processing of generated G-code are explored. Overall, these solutions represent a critical set of slicing features used to improve generated toolpaths and the quality of the components deposited with those toolpaths.

36 MATERIALS SCIENCE↗
DOE OSTI2020

Femtosecond Laser Additive Manufacturing of Multi-Material Layered Structures

Laser additive manufacturing (LAM) of a multi-material multi-layer structure was investigated using femtosecond fiber lasers. A thin layer of yttria-stabilized zirconia (YSZ) and a Ni–YSZ layer were additively manufactured to form the electrolyte and anode support of a solid oxide fuel cell (SOFC). A lanthanum strontium manganite (LSM) layer was then added to form a basic three layer cell. This single step process eliminates the need for binders and post treatment. Parameters including laser power, scan speed, scan pattern, and hatching space were systematically evaluated to obtain optimal density and porosity. This is the first report to build a complete and functional fuel cell by using the LAM approach.

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 OSTI2022

Particulates for additive manufacturing techniques

A method of making a particulate for an additive manufacturing technique includes receiving particulate at a chemical vapor deposition (CVD) reactor, flowing a hydrocarbon gas into the CVD reactor, decomposing the hydrocarbon gas in the CVD reactor, and depositing a carbonaceous coating on the particulate using a product of the decomposed hydrocarbon gas. The coating deposited over the particulate has a reflectivity that is lower than the reflectivity the underlying particulate body to reduce an energy input requirement for purposes of fusing the particulate into a layer of an article using an additive manufacturing technique. In embodiments, the coated particulate can be received at an additive manufacturing apparatus and fused into a layer of an article as a metallic-carbon composite using a high-density energy source.

42 ENGINEERING↗
DOE OSTI2021

TCR Input to NUREG-1537 Process for Advanced Nuclear Technologies Derived from Additive Manufacturing

There has been a renewed interest by several advanced reactor developers to use NUREG-1537 “Guidelines for Preparing and Reviewing Applications for the Licensing of Non-Power Reactors” as a basis for their safety analysis report content and organization. Recently, SHINE Medical Technologies, LLC (SHINE), which is a non-power, Aqueous Homogenous Reactor design radioisotope production facility, received a construction permit based around their NUREG-1537 safety evaluation report (ADAMS No. ML16229A140). Advanced reactor developers are interested in using NUREG-1537 as a basis for their safety analysis report content and organization because of its successful application towards research reactors, graded approach, and simplicity in structure and requirements. However, NUREG-1537 is still largely geared toward light water reactors (LWRs) and many improvements could be made or supported through guidance documents for advanced reactors. For nuclear power to play a role in the future zero-carbon energy portfolio, a supportive regulatory structure is needed to lower regulatory uncertainty and barriers to deployment. At the time of this report, no such document or pathway exists for advanced nuclear technologies, including those derived from nontraditional technology such as advanced manufacturing technology (AMT) and, specifically, additive manufacturing. This report will explore and provide recommendations as to how advanced nuclear technologies derived from additive manufacturing technologies could employ the use of an ISG, other guidance document, or revisions to NUREG-1537 to lower the regulatory uncertainty and barriers for adoption.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗