相关论文: Algorithms for TRISO Fuel Identification Based on …
U-10Zr-based metallic nuclear fuel is a promising fuel candidate for next-generation sodium-cooled fast reactors.The research experience of the Idaho National Laboratory for this type of fuel dates back to the 1960s. Idaho National…
The development of new manufacturing techniques such as 3D printing have enabled the creation of previously infeasible chemical reactor designs. Systematically optimizing the highly parameterized geometries involved in these new classes of…
Pebble-bed nuclear reactor technology, which is currently being revived around the world, raises fundamental questions about dense granular flow in silos. A typical reactor core is composed of graphite fuel pebbles, which drain very slowly…
Machine learning has emerged as a potent computational tool for expediting research and development in solid oxide fuel cell electrodes. The effective application of machine learning for performance prediction requires transforming…
We adopt the deep learning method CASI (Convolutional Approach to Shell Identification) and extend it to 3D (CASI-3D) to identify signatures of stellar feedback in molecular line spectra, such as 13CO. We adopt magneto-hydrodynamics…
We investigate the ability of an antineutrino detector to determine the fuel type of a reactor. A hypothetical 5t antineutrino detector is placed 25m from the core and measures the spectral shape and rate of antineutrinos emitted by fission…
The interaction of ionizing and far-ultraviolet radiation with the interstellar medium is of great importance. It results in the formation of regions in which the gas is ionized, beyond which are photodissociation regions (PDRs) in which…
Nuclear archaeology research provides scientific methods to reconstruct the operating histories of fissile material production facilities to account for past fissile material production. While it has typically focused on analyzing material…
Compliance of member States to the Treaty on the Non-Proliferation of Nuclear Weapons is monitored through nuclear safeguards. The Passive Gamma Emission Tomography system is a novel instrument developed by the International Atomic Energy…
On the base of analysis of experimental observations and critical assessment of existing models for oxide fuel structure evolution under operation conditions of fast reactors, new models for fuel restructuring and coring are proposed. The…
Three-dimensional particle tracking is an essential tool in studying dynamics under the microscope, namely, fluid dynamics in microfluidic devices, bacteria taxis, cellular trafficking. The 3d position can be determined using 2d imaging…
We present a novel method for characterizing the microstructure of a material from volumetric datasets such as 3D image data from computed tomography (CT). The method is based on a new statistical model for the distribution of voxel…
Nondestructive evaluation methods play an important role in ensuring component integrity and safety in many industries. Operator fatigue can play a critical role in the reliability of such methods. This is important for inspecting high…
Three-dimensional CP-DNS of reacting iron particle dust clouds in a turbulent mixing layer are conducted. The simulation approach considers the Eulerian transport equations for the reacting gas phase and resolves all scales of turbulence,…
Models for finite-rate-chemistry in underresolved flows still pose one of the main challenges for predictive simulations of complex configurations. The problem gets even more challenging if turbulence is involved. This work advances the…
Efficient energy provisioning is a fundamental requirement for modern transportation systems, making refueling path optimization a critical challenge. Existing solutions often focus either on inter-vehicle communication or intra-vehicle…
Conceiving the possibility of using plastic scintillator bars as robust detectors for antineutrino detection for the remote reactor monitoring and nuclear safeguard application we study expected basic performance by Monte Carlo simulation.…
Bridging theory and observations is a key task to understand galaxy formation and evolution. With the advent of state-of-the-art observational facilities, an accurate modelling of galaxy observables through radiative transfer simulations…
This study presents an imaging-based deep learning tool to measure the fuel regression rate in a 2D slab burner experiment for hybrid rocket fuels. The slab burner experiment is designed to verify mechanistic models of reacting boundary…
Advanced nuclear reactors often exhibit complex thermal-fluid phenomena during transients. To accurately capture such phenomena, a coarse-mesh three-dimensional (3-D) modeling capability is desired for modern nuclear-system code. In the…