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At least 757 records · Page 42
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Methods and apparatus for embedding heating circuits into articles made by additive manufacturing and articles made therefrom

Methods of embedding a heating circuit in an article fabricated by additive manufacturing. The methods describe techniques such as co-extruding a wire, capable of being heated, along with print material in additive manufacturing of the article, and placing a pre-shaped wire capable of being heated between adjacent layers of the article. A third method includes dispensing a wire, capable of being heated, during the additive manufacturing of the article, and compacting the wire into the printed material. An apparatus for embedding a heating circuit in an article fabricated by additive manufacturing. The apparatus contains a wire dispenser, a cutter to control the length of the wire dispensed, and a compactor capable of embedding the wire capable of being heated into the printed material. An article made by additive manufacturing is disclosed. The article contains at least one heating element embedded in the article during the additive manufacturing process.

Barocio, Eduardo↗
DOE OSTI2024

3D printed features on nuclear fuel cladding for optimized heat transfer

A nuclear fuel cladding with improved thermomechanical properties is provided. The nuclear fuel cladding includes a double-walled construction having inner and outer hexagonal sidewalls. The inner sidewall and the outer sidewall are spaced apart from each other to form a cooling channel therebetween, and the inner sidewall surrounds a nuclear fuel and is spaced apart from the nuclear fuel by a small gap. Helical fins extend into the cooling channel to interconnect the inner sidewall and the outer sidewall. Resilient fingers extend toward the nuclear fuel through the small gap to comply with variations in the size of the nuclear fuel due to fabrication tolerances as well as thermal expansion and swelling of the nuclear fuel, for example UO 2 , when undergoing fission. The nuclear fuel cladding is formed according to an additive manufacturing process, for example laser powder bed fusion printing.

Petrie, Christian M.↗
DOE OSTI2024

System and method for powder detection in part

A system and method of testing a part manufactured using an additive manufacturing process. The part may be excited via an input mechanism that imparts an excitation force on the part to induce a dynamic response in the part. An output mechanism may be used to sense the dynamic response in the part. A processing element may be used to compare the dynamic response with a reference to identify an indication of excess powder in the part.

Conner, Brett Page↗
DOE OSTI2024

Supports with integrated sensors for nuclear reactor steam generators, and associated systems and methods

Supports with integrated sensors for nuclear reactor steam generators, and associated systems and methods, are disclosed. A representative method for forming a nuclear-powered steam generator includes forming an instrumented support, the instrumented support including a carrier portion and a retainer portion, with at least one of the carrier portion or the retainer portion being integrally formed with a sensor via an additive manufacturing process. The method can further include coupling the sensor to a communication link, supporting a helical steam conduit on the instrumented support, and installing the helical steam conduit and the instrumented support in a nuclear reactor. The helical steam conduit is positioned along a primary flow path, which is in turn positioned to circulate a heated primary flow in thermal communication with the helical steam conduit.

Welter, Kent↗
DOE OSTI2025

A comparison of plastic and visco-plastic constitutive models for accurate predictions in PM-HIP

Powder metallurgy hot isostatic pressing (PM-HIP) is an advanced manufacturing process that can efficiently produce near net shape parts with high material utilization and uniform microstructures. While the PM-HIP process is used frequently to produce small-scale components, its application to large-scale components is still limited due to inadequate understanding of its complex processes that cause unpredictable post-HIP shape distortions. A computational model can be a cost-effective alternative to exhaustive experimentation required to understand the PM-HIP process fully. Therefore, we present a comparison of plastic and visco-plastic models that are frequently used to model the PM-HIP process. We show that the predictions of powder densification behavior and shape distortions obtained from both the models are similar under most conditions and agree well with experimental observations.

Sarkar, Subrato [ORNL]↗
DOE OSTI2024

Experimental investigation of thermal conductivity of high entropy ceramics

In this talk, we will present the experimental investigation of thermal conductivity of high entropy carbides (HEC) and borides (HEB) with different compositions. Thermal conductivity determines the capability of a material to transport thermal energy and is considered as one critical physical property, specially in the energy industry. Due to the presences of disordered cation sublattice, it is expected that thermal conductivity of high entropy ceramics is lower than the counterparts with simpler compositions, but the experimental studies are relatively few. Using laser-based spatial-domain and frequency-domain thermoreflectance technique, we measured thermal conductivity of HECs and HEBs in a temperature range from 77K to 773K. Furthermore, by focusing the laser using an objective lens, we were able to perform the thermal property mapping on samples with the spatial resolution of micrometer. Such measurements could reveal important microstructure information in a rapid and efficient way without using scanning electron microscopy. The high spatial resolution also enables thermal conductivity measurements on ion-irradiated HECs with the damage layer of merely 1.1µm. These measurements can provide valuable information to predict the performances of HECs and HEBs with different compositions and from different manufacturing processes, and in the extreme environments such as nuclear reactors.

36 - MATERIALS SCIENCE↗
DOE OSTI2026

Developing a Digital Twin for SRF Cavity Assembly at Fermilab

When assembling Superconducting Radio Frequency (SRF) Cavities, maintaining an environment devoid of particulates like dust and other small particles is essential. If a single spec of dust enters the cavity a significant degradation of performance can occur. To avoid a cavity failure Fermilab assembles the SRF cavities within a ISO-4 (Class 10) environment. This environment though is still susceptible to foreign contaminants when technicians enter and new components are added to the cleanroom. To reduce the risk even more Fermilab has introduced a cobot manipulator into the cleanroom environment to speed up the assembly time which will reduce the time that the technicians operate in the cleanroom. But, this still leaves the potential of contaminants to enter the cleanroom if new components need to be tested within the cleanroom. This project aims to lay the groundwork to develop a Digital Twin environment of the cleanroom to aid in manufacturing processes and testing. In its simplest form, a digital twin is a bidirectional link between a physical system and its digital counterpart or twin. NVIDIA Isaac Sim is used as the digital twin foundation for the digital representation of the cleanroom, specifically for the UR16e assembly area. A simulated UR16e was used to validate the performance of Isaac Sim as a testing environment by comparing the tool center points (TCP) positional data between the simulated and digital representation of the UR16e. Due to a new vision based robotic assembly process being introduced to the cleanroom a digital representation of the physical camera was tested and validated to ensure that it will produce close to the same outcome as the physical environment. The TCP comparison results showed a peak translational error of approximately 0.1mm and rotational errors of up to 8 between the simulated and digital UR16es. While the camera validation performed with high repeatability across multiple runs, it still requires minor tuning before it can accurately replicate a physical camera.

Imburgia, Joseph [Northern Illinois U.]↗
DOE OSTI2026

Design and Modeling of the Charge Readout of a SiMOS Quantum Dot with a Single Electron Transistor and CryoCMOS

Single electron spin qubits trapped in SiMOS quantum dots are a promising technology for scaling to thousand- or million-qubit systems due to their compatibility with mature CMOS manufacturing processes. A readout system that combines a single electron transistor with a custom cryogenic CMOS amplification and digitization chain offers key advantages by avoiding the use of bulky RF components or room-temperature interconnects. We present design techniques and simulation results for an optimized qubit-SET cryoCMOS interface, culminating in the design of the QNDR1 ASIC, the first cryogenic readout ASIC designed under the Quandarum project, which targets the development of a many-channel spin qubit based detector for use in high energy physics.

Quinn, Adam [Fermilab] (ORCID:0009000605056371)↗
DOE OSTI2022

Status of Additive Manufacturing Capabilities for Processing Refractory Alloys Under the Mo-99 Program

The enriched 100 Mo target, denoted as aMo, that Northstar Medical Radioisotopes is developing to produce 99 Mo from an accelerator-based method is a disk-type geometry with a 0.5–0.715 mm thickness and a 29 mm outer diameter. A press and sinter method was adopted to fabricate these samples from aMo powder feedstock. Inherent porosity from the press and sinter method makes the disks more easily dissolvable during 99 Mo postprocessing. However, the disk-type geometry will be subject to thermal stresses due to temperature variations once the geometry is in line with the accelerated electron beam, causing warping and possible failure. Additive manufacturing (AM) processes such as laser powder bed fusion (LPBF) enable the manufacturing of custom, complex geometries that may otherwise be difficult to produce with more conventional methods (e.g., press and sinter approach). Therefore, the National Nuclear Security Administration’s Molybdenum-99 Program invested in developing an AM facility dedicated to processing and printing refractory powders. This report details the LPBF process, how irregular refractory powder can be prepared for LPBF, and the equipment that is available to support the program.

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 OSTI2023

Preliminary Characterization and Evaluation on FFF Manufactured 316H and ODS Steels

The Advanced Materials and Manufacturing Technology (AMMT) program develops cross-cutting technologies in support of a broad range of nuclear reactor technologies and maintains U.S. leadership in materials and manufacturing technologies for nuclear energy applications. The overarching vision of AMMT is to accelerate the development, qualification, demonstration, and deployment of advanced materials and manufacturing technologies to enable reliable and economical nuclear energy. Solid-state advanced manufacturing techniques can overcome some of the challenges in liquid-based additive manufacturing (AM) processes and should therefore be considered in material design and manufacturing as well. The work presented in this report forms part of a study on solid-state AM techniques of 316 stainless steels (SS) and oxide dispersion strengthened (ODS) steel components and supports the vision and goals of the AMMT program relevant to accelerate the development and deployment of advanced manufacturing processes. Achieving this can provide a safety improvement through larger safety margins, economic benefit for higher efficiency during operation, and a cost reduction through more effective manufacturing processes and less waste. This study provides preliminary information on development of the fused-filament fabrication (FFF) process using different powder types to demonstrate the sensitivity, and therefore the characterization of these sample components. The full solid-state manufacturing feasibility study will be completed and reported in a final feasibility evaluation during 2025. The study investigation used two 14YWT ODS powder batches, which provided information and the effect of different powder morphologies on manufacturability. The two 316SS powders demonstrated the effect of powder size on the manufacturability using FFF. Two product forms, namely a honeycomb structure and flat samples, were manufactured to demonstrate the flexibility of product form.

36 MATERIALS SCIENCE↗
DOE OSTI2025

Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials: Part II Resveratrol Exemplar

This SAND report summarizes work supported by an Engineering Sciences Research Foundation (ESRF) Lab Directed Research and Development (LDRD) project entitled “Beyond Magic Barrels: Digital manufacturing for crystallization, process development and optimization of explosive materials.” This SAND report is written in two parts with Part 1 discusses recrystallization of our explosive exemplar and Part 2 summarizing our work with recrystallization of resveratrol. We have studied resveratrol recrystallization with a multiscale approach combining experiments, modeling and simulation. At the single crystal scale, microscopy experiments illuminate crystal time-dependent growth rates using advanced image analysis. Bench scale experiments were carried out to look at growth of multiple particles in a small reactor creating thousands of particles and analyzing the results with microscopy and μCT. For the modeling we combine kinetic Monte Carlo (kMC) models with subscale information from density functional theory (DFT) or molecular dynamics. This work is discussed in Part 1 and can also be found in a paper from the project discussing a coarse-grained kMC model specifically developed for resveratrol. For well-mixed systems, we have population balance equations (PBE) linked with species mass conservation forming a set of ordinary differential equations that can be solved quickly. For more complicated geometries, such as the vat crystallization used throughout the complex, a coupled computational fluid dynamic (CFD)/PBE method was developed to account for gradients in temperature and concentration and differences in crystallization rates throughout the domain. These simulations are more complex and require high performance computing. We present results for two cases: 5% seed fast cool with parameters fit to the well-mixed case and 5% seed slow cool using the same parameters. We show reasonable agreement with experiments though are particles are significantly larger than the experiments.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Scalable in situ non-destructive evaluation of additively manufactured components using process monitoring, sensor fusion, and machine learning

Laser Powder Bed Fusion (L-PBF) Additive Manufacturing (AM) is among the metal 3D printing technologies most broadly adopted by the manufacturing industry. However, the current industry qualification paradigm for critical-application L-PBF parts relies heavily on expensive non-destructive inspection techniques, which significantly limits the use-cases of L-PBF. In situ monitoring of the process promises a less expensive alternative to ex situ testing, but existing sensor technologies and data analysis techniques struggle to detect sub-surface flaws (e.g., porosity and cracking) on production-scale L-PBF printers. In this work, an in situ NDE (INDE) system was engineered to detect subsurface flaws detected in X-Ray Computed Tomography (XCT) directly from process monitoring data. A multilayer, multimodal data input allowed the INDE system to detect numerous subsurface flaws in the size range of 200–1000µm using a novel human-in-the-loop annotation procedure. Furthermore, a framework was established for generating probability-of-detection (POD) and probability-of-false-alarm (PFA) curves compliant with NDE standards by systematically comparing instances of detected subsurface flaws to post-build XCT data. Here, we also introduce for the first time in the AM in situ sensing literature the a 90/95 – the flaw size corresponding to a 90% detection rate on the lower 95% confidence interval of the POD curve. The INDE system successfully demonstrated POD capabilities commensurate with traditional NDE methods. Traditional ML performance metrics were also shown to be inadequate for assessing the ability of the INDE system’s flaw detection performance. It is the hope of the authors that future studies will adopt the POD and PFA approach outlined here to provide better insight into the utility of process monitoring for AM.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Silicon carbide fiber composite receiver tubes manufactured by PIP process

The performance of SiC fiber composites made by a polymer infiltration and pyrolysis (PIP) process was investigated. Two types of tubular composites were manufactured using Hi-Nicalon and Nicalon-CG silicon carbide fibers infiltrated with SMP10 silicon carbide matrix. The fiber content in both composites was about 25 vol.% with an average density of 2.39 g/cc. The tubular SiC composites showed stable solar absorptance and emittance of 0.97 and 0.91, respectively, at 800 °C. The composites were thermally shocked at 900, 1000, and 1100 °C with a waterjet simulating raindrops. As a result, the hoop tensile strength of the composites revealed no loss of mechanical strength due to the thermal shock experiments up to 1100 °C.

14 SOLAR ENERGY↗
DOE OSTI2025

Fast-rate joining of thermoplastic composites using integrated additive manufacturing and compression molding process

The integration of additive manufacturing (AM) technology with compression molding (CM), has emerged as a high-performance composite manufacturing technology in recent years. In the AM-CM process, quickly deposited AM preform on a mold undergoes a rapid compaction cycle to fabricate structurally robust composite parts due to highly controlled fiber alignment (from AM) and reduced porosity (from CM). Currently, AMCM-based part size is limited by the size of the mold volume, thus posing a challenge to manufacture scalable parts. Here, this work focuses on joining techniques developed to enable fast rate joining of short fiber-reinforced thermoplastic composite parts using the AM-CM process. Acrylonitrile butadiene styrene resin reinforced with 20 wt% short carbon fiber composites was printed onto a flat mold and pressed under a hydraulic press. Fabricated panels were joined by the (a) mechanical impression at the joining interface and (b) over-molded continuous carbon fiber (CCF) sheet. Tensile tests were performed to characterize the joining strength of both mechanical impression-based joints and CCF over molded joints. Among the mechanical impression-based joints, a U-shape channel allowed the fibers to flow between two joint parts, and 280 % increased mechanical properties were observed. The continuous carbon fiber-based over molded joint CCF showed 350 % increase in tensile strength compared to the butt joints.

36 MATERIALS SCIENCE↗
DOE OSTI2024

7 Innovations in high-rate composite manufacturing: integrating additive manufacturing with compression molding process

Advanced composites play a pivotal role in modern engineering, offering exceptional strength-to-weight ratios and tailored properties, essential for various industries. High-rate composite manufacturing techniques have rapid production capabilities, which are essential for meeting the demands of industries requiring cost-saving, efficiency, and quick turnaround times. This chapter explores the Additive Manufacturing- Compression Molding (AM-CM) system developed by Oak Ridge National Laboratory (ORNL) for advanced composites manufacturing. The AM-CM system integrates additive manufacturing with compression molding, facilitating the production of polymer composite parts with superior mechanical properties and meticulously controlled microstructures. This innovative system not only ensures precise material deposition but also operates as a fast composite manufacturing process, enhancing productivity and performance, which are needed attributes across industrial applications. Through comprehensive mechanical testing and microstructural analysis, AM-CM promotes remarkable fiber alignment and reduced porosity in composite parts compared to alternative thermoplastic high-rate composite manufacturing methods. Furthermore, AM-CM enables overmolding reinforcement using continuous carbon fiber and supports selective reinforcement through customizable toolpaths. It also facilitates the production of hybrid materials to achieve tailored mechanical properties. Future advancements in AM-CM technology aim to enhance process efficiency, broaden material versatility, and improve part performance. This involves exploring novel materials, advancing process monitoring, implementing automation technologies, and integrating artificial intelligence (AI) and machine learning (ML) for predictive modeling and real-time optimization in composite manufacturing. These developments will establish the AM-CM system as a transformative technology in composite manufacturing, driving innovation across industries.

Hassen, Ahmed [ORNL] (ORCID:0000000328521222)↗
DOE OSTI2026

Virtual Inspection of Advanced Manufacturing via Process-Scale Digital Twins (Abbreviated Report)

Inspection and certification comprise the most significant bottlenecks in advanced manufacturing for NNSA applications, often requiring far more time and resources than the fabrication of the parts themselves. Traditional methods, such as manual review and X-ray computed tomography, are not only slow and costly, but also struggle to provide a clear connection between manufacturing instructions and the final performance of critical components. This gap limits both the agility and assurance needed to support the modernization and safety of the United States nuclear stockpile. In response, our Strategic Initiative established a digital twin framework that integrates realtime process monitoring, automated data analysis, and immersive virtual reality collaboration into a unified inspection pipeline. By leveraging data from sensors, machine instructions, and imaging, we created high-fidelity virtual models of manufactured parts that could be rapidly analyzed and certified. This approach was first demonstrated with Direct Ink Write, and then extended to other manufacturing settings, including conventional (or “subtractive”) manufacturing and to predict the end of life performance of parts per the aging and lifetimes programs. The result is a transformational capability: inspection times have been reduced by a factor of 120,000 without loss of accuracy and while simultaneously improving traceability and confidence in part quality. This framework not only streamlines certification for critical applications, but also positions the national security enterprise to respond more flexibly to emerging challenges, supporting agile manufacturing and digital engineering practices across a broad range of mission-relevant domains.

42 ENGINEERING↗
DOE OSTI2021

Digital Twin Model for Advanced Manufacture of a Rotating Detonation Engine Injector

A digital twin material model (DTMM) of an additive manufacturing (AM) process was created to advance the state of the art in rotating detonation engine (RDE) injector design. Current RDE injectors are designed with large pressure drops, enabling a stable and repeatable combustion process. However, this comes at the cost of system efficiency. For the technology to transition to commercial fossil-based power generation, it is important to develop injectors with reduced flow losses. Low-loss injectors are difficult to design and manufacture with conventional manufacturing techniques. AM enables new design options, but the AM manufacturing process must be thoroughly understood to result in a robust design. A DTMM provides the necessary insight by defining the cause-effect relationships between process parameters, microstructure features, and properties. Therefore, a DTMM to support the design and manufacturing process was developed and applied to the design of a new additively manufactured low-loss injector. The injector combustion behavior was characterized through hot-fire tests, and mechanical performance was compared to the DTMM predictions. The two project goals were the successful development of the DTMM and the demonstration of an improved RDE injector design. The RDE injector design and DTMM developments occurred on parallel but dependent paths. The injector was designed to reduce pressure drop by increasing the cross-sectional flow area ratio between the injector air passages and the combustor annulus. This resulted in less structural material, raising the concern that thin members would be susceptible to high-cycle fatigue (HCF) under the periodic loading inherent to an RDE. It was most important for the DTMM to predict behavior in these features; therefore, the injector design concept guided the material thicknesses used in fatigue tests. The DTMM development started by manufacturing a series of coupons over the range of possible AM process variations. A design-of-experiment approach was used to select which process variable combinations gave the most efficient coverage relevant to the injector design space. The microstructure in each of these coupons was characterized, and then computational methods were used to create a numerical model of the correlation between process variables and microstructure. Next, a set of HCF samples were tested to calibrate existing models that map microstructure to HCF performance. Together, these two links formed the DTMM that calculates HCF behavior from AM process variables. Two injector prototypes were additively manufactured. The first injector design strategy aggressively pursued low-loss performance by substantially increasing the oxidizer flow area. The combination of manufacturing lead times and the fatigue testing schedule meant that the DTMM was not available when building this first prototype. Therefore, its process parameters were chosen based on a manual review of the available coupon data. This prototype was built successfully and evaluated in 58 combustion tests. Sustained detonation was achieved with remarkably reduced pressure loss, and some tests even displayed pressure loss characteristics similar to conventional gas turbine combustors. This achieved the project goal of improving RDE injector design. The second injector was manufactured according to the optimized parameters predicted by the DTMM. The flow area modifications of this injector were less aggressive than the first injector since demonstrating low pressure loss was not an objective of the second hot-fire test series. Rather, the test objective was to cause high cycle fatigue failure in the part due to periodic loading from the rotating detonation wave. The observed number of cycles to failure was to be compared to the number predicted by the DTMM and thereby assess the utility of the DTMM in component design. However, the required level of vibration was not obtained during combustion. Therefore, high cycle fatigue was not experienced in the hot-fire tests of the second injector. Fatigue data was obtained by further testing the second injector in a conventional HCF test apparatus. The injector demonstrated HCF strength above the DTMM prediction. In fact, it did not fail and testing was only discontinued due to reaching the end of the period of performance. This points to some success in the project’s primary goal of successfully developing and applying the DTMM to a component design. Implementing the DTMM recommendations for optimal processing parameters led to a part with acceptable properties. The DTMM was also shown to be an efficient correlator of data and to provide insight into the relationship between process settings, microstructure, and property performance. However, the failure of the DTMM prediction to match the experimental result of the injector fatigue test also points to the need to include significantly more data in the model development. In this project, coupons made with identical processing parameters exhibited drastically different properties from each other and from the injector part, which clearly influences the accuracy of a model that predicts performance based on parameters. Uncertainties in the build process must be quantified to develop more robust models. A denser and broader matrix of coupon process and geometry variations, several repeated builds of every point, more in-situ build process measurements, and direct observation of tensile and HCF sample microstructure (as opposed to separate microstructure specimens) are recommendations to improve future AM modeling efforts.

20 FOSSIL-FUELED POWER PLANTS↗