Engineering topics

Charit, Indrajit

Publications and source records attributed to Charit, Indrajit.

7 records

DOE OSTI2024

Characterization of Fuel Cladding Chemical Interaction on a High Burnup U-10Zr Metallic Fuel via Electron Energy Loss Spectroscopy Enhanced by Machine Learning

Fuel cladding chemical interaction (FCCI) is one of the main performance limiting factors for metallic nuclear fuels. The interaction destabilizes the martensitic microstructure and deteriorates mechanical properties of HT-9 cladding. The detection of low atomic number elements (Z<10) and overlapping of elemental peaks can be problematic in interpreting energy dispersive X-ray spectroscopy (EDS) data. Electron energy loss spectroscopy (EELS) provides precise elemental edge energy values and can detect elements with a low atomic number. This work utilizes EELS to study the distribution of lanthanides and light elements at the interaction region. The sample was prepared from the FCCI region of a U-10Zr (wt.%) solid fuel with HT-9 cladding, irradiated to a burnup of 13.2 at.%. Processing the EELS data included three major steps: 1) enhance the signal to noise ratio by denoising the spectrum with principal component analysis (PCA) method, removing background and performing deconvolution; 2) identify chemical elements with core energy loss edges; 3) confirm different phases using a popular machine learning method, K-means. This work presents qualitative assessment of lanthanides and light elements like carbon (C) and oxygen (O) enhanced by the application of machine learning algorithms. By comparing with EDS elemental maps, EELS provides higher resolution chemical maps, reveals the distribution of carbon at the interaction region supporting the formation of zirconium carbide, a rind-like microstructure feature that was proposed to mitigate the chemical interaction. Furthermore, the plasmon peak map was also found to indicate an energy shift associated with the formation of phases/compounds. K-means clustering method was used on the processed electron energy loss (EEL) spectrum to automatically reveal different phases. The resulting clustered maps from K-means clustering align well with elemental maps confirming certain phases, especially Fe-Ce and Zr-C, in the FCCI region.

EELS↗

DOE OSTI2024

Post-irradiation examination of UN-Mo-W fuels for space nuclear propulsion

The National Aeronautics and Space Administration's return to space nuclear propulsion stems from the need for a more efficient method of space travel. Nuclear thermal propulsion systems have been shown to be two times more efficient than chemical propulsion. NASA's Sirius program was created to fabricate and test fuels for space nuclear propulsion, specifically to determine their performance under prototypical startup conditions. The Sirius project featured 4 test capsules, Sirius-1 featured uranium nitride fuel dispersed in a matrix of tungsten and rhenium, while Sirius-2A, -2B, and -3 featured uranium nitride-molybdenum-tungsten fuel (UN-Mo-W). This study discusses the Sirius-2A and -2B irradiation experiments at the Idaho National Laboratory, specifically their performance under irradiation at the Transient Reactor Test Facility. It was found that the fuel samples overall did not exhibit significant cracking, though the Sirius-2A fuel did have one large crack on the surface of the fuel. There was minimal hydrogen absorption in the samples, though it is unknown if the absorption occurred during irradiation or during fabrication. Mechanical testing indicated that the UN fuel demonstrated ceramic behavior as expected, and the Mo/W matrix demonstrated linear elastic behavior to failure.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Transmission electron microscopy of ion irradiated ODS MA956 samples

Oxide dispersion strengthened (ODS) alloys are promising candidate materials for the next generation advanced nuclear reactors due to their superior irradiation resistance and mechanical properties. To better understand the effect of irradiation on MA956, it is essential to study higher dose (50-100 dpa) samples, so that the general trend of microstructural evolution and the resulting radiation-hardening can be deduced. Currently, ion irradiations are considered the only way to achieve doses beyond ~50 dpa in a practical time frame relevant to alloy and welding development programs. This dataset contains TEM characterization results of ODS MA956 samples that were ion irradiated under different conditions: Sample #5 (1.25 dpa at 190℃); Sample #9 (50 dpa at 190℃); Sample #15 (1.25dpa under 320℃); and Sample 17 (25 dpa at 320℃). TEM characterization focused on the irradiation induced defects (dislocation lines and loops) using the on-zone axis bright field STEM technique. These data were collected using a FEI Tecnai G2 F30 S/TEM at Microscopy and Characterization Suite (MaCS) at Center for Advanced Energy Studies (CAES), Idaho Falls, ID. This project (ion irradiation and TEM studies) was supported by the U.S. Department of Energy, Office of Nuclear Energy under DOE Idaho Operations Office Contract DE-AC07-05ID14517 as part of Nuclear Science User Facilities award #18-14784 (PI: Ramprashad Prabhakaran, PNNL).

Prabhakaran, Ramprashad↗

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

Formation of uranium nitride nanoparticles via mechanical alloying of uranium-molybdenum alloy fuels in gaseous nitrogen

Uranium-molybdenum (U-Mo) alloys show promise as a nuclear fuel system due to their high thermal conductivity and fuel loading capability. However, U-Mo systems are susceptible to irradiation induced swelling ultimately affecting the cladding via mechanical and chemical interactions. To address these shortcomings, this research investigated the formation of uranium mononitride (UN) nanoparticles within a 90 wt% U/10 wt% Mo (U-10Mo) matrix to act as a prospective defect sink for fission products at nanometric hetero-interfaces. To promote the formation of UN, U-10Mo powders were mechanically alloyed under a high purity nitrogen atmosphere. Variations of the milling process investigated included media size, duration of milling, and number of times the milling jar was re-aerated with nitrogen gas. Characterization of the fuel microstructure was completed using light element analysis, X-ray diffraction, scanning and transmission-electron microscopy, electron energy loss spectroscopy, and atom probe tomography. UN nanoparticles measuring 1–5 nm in radius were observed in the U-Mo matrix as early as 1 h into the mechanical alloying process. Milling time in excess of 10 h was found to lead to deleterious effects induced by the stainless-steel milling media.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2024

Chloride-Induced Stress Corrosion Cracking of Friction Stir-Welded 304L Stainless Steel: Effect of Microstructure and Temperature

Dry storage canisters of used nuclear fuels are fabricated using SUS 304L stainless steel. Chloride-induced stress corrosion cracking (CISCC) is one of the major failure modes of dry storage canisters. The cracked canisters can be repaired by friction stir welding (FSW), a low-heat input ‘solid-phase’ welding process. It is important to evaluate the ClSCC resistance of the friction stir welded material. Stress corrosion cracking (SCC) studies were carried out on mill-annealed base materials and friction stir welded 304L stainless U-bend specimens in 3.5% NaCl + 5 N H2SO4 solution at room temperature and boiling MgCl2 solution at 155 °C. The engineering stress on the outer fiber of the FSW U-bend specimen was ~60% higher than that of the base metal (BM). In spite of the higher stress level of the FSW, both materials (FSW and BM) showed almost similar SCC failure times in the two different test solutions. The SCC occurred in the thermo-mechanically affected zone (TMAZ) of the FSW specimens in the 3.5% NaCl + 5 N H2SO4 solution at room temperature, while the stirred zone (SZ) was relatively crack-free. The failure occurred at the stirred zone when tested in the boiling MgCl2 solution. Hydrogen reduction was the cathodic reaction in the boiling MgCl2 solution, which promoted hydrogen-assisted cracking of the heavily deformed stirred zone. The emergence of the slip step followed by passive film rupture and dissolution of the slip step could be the SCC events in the 3.5% NaCl + 5 N H2SO4 solution at room temperature. However, the slip step height was not sufficient to cause passivity breakdown in the fine-grained SZ. Therefore, the SCC occurred in the partially recrystallized softer TMAZ. Overall, the friction-stirred 304L showed higher tolerance to ClSCC than the 304L base metal.

304L austenitic stainless steel↗

DOE OSTI2024

Intelligent Manufacturing for Extreme Environments Conference Proceedings

The Intelligent Manufacturing for Extreme Environments (IMEE) workshop was held at the Center for Advanced Energy Studies (CAES) in Idaho Falls, Idaho, May 2–3, 2023, in support of the United States (U.S.) National Science Foundation (NSF) Established Program to Stimulate Competitive Research: Workshop Opportunities (EPSCoR-WO) program. This workshop featured keynote speakers, panels, and breakout sessions with 58 participants. Nuclear reactors need to operate under extreme service conditions, such as high temperatures, corrosive environments, and high-radiation doses. Hence, reactor components must be able to withstand those conditions. The participants envision a future where on demand manufacture of components for small modular reactors (SMRs), microreactors, and other advanced reactor designs are possible. In this future, regulatory bodies accept validated manufacturing processes and standardized feedstocks, thus eliminating the need for individual component testing. However, the necessary technologies and regulatory policies needed for this future do not exist today. Successful innovation would revolutionize the nuclear power sector, enable fast commercial development, create economic opportunities in the U.S., reduce the carbon footprint and associated risks, and promote a skilled and highly competitive workforce. The objective of the workshop was to convene world-class experts, researchers, educators, and students to identify gaps and envision solutions for five interrelated challenges for intelligent manufacturing in extreme environments. The key outcomes of the conference were: (1) to take the opportunity for researchers and educators to network and form collaborations; and (2) to produce a full report to inform policy-makers, industry, and the academic community of various challenges and opportunities in the nuclear energy sector.

36 MATERIALS SCIENCE↗