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Texas A&M welcomes uranium conversion research
The Texas A&M Engineering Experiment Station (TEES) has signed a research agreement with Quantum Leap Energy (QLE) “to advance and de-risk the commercial production of high-purity uranium hexafluoride (UF6).”
QLE is an Austin, Texas–based subsidiary of ASP Isotopes (ASPI), which is developing an isotope enrichment platform for applications in nuclear energy, nuclear medicine, and semiconductors. QLE specializes in the uranium conversion step of the nuclear fuel cycle—the conversion of yellowcake uranium concentrate (U3O8) into UF6 prior to enrichment.
Huayang Zhang, Bin Zhong, Huayun Shen, Li Cheng, Jinhong Li
Nuclear Science and Engineering | Volume 196 | Number 10 | October 2022 | Pages 1236-1246
Technical Paper | doi.org/10.1080/00295639.2022.2070386
Articles are hosted by Taylor and Francis Online.
Pinhole imaging is an important test technique to obtain information on the spatial distribution of the radiation field in the target region and has been widely used in nuclear physics and inertial confinement fusion (ICF). Coded-aperture, able to maintain good resolution as well as enhancing signal strength, has become a more frequently used method than pinhole imaging in experimental studies. Thus, implementing Monte Carlo simulations of coded-aperture imaging will improve coded-aperture design, image reconstruction, and other related works. However, the current international mainstream Monte Carlo transport simulation programs do not possess the ability to directly simulate coded-aperture imaging. This paper develops a relatively complete coded-aperture imaging simulation function on the Neutron Photon Transport System code based on the next-event estimation method. With the application of Monte Carlo simulation techniques, such as variance reduction and rejection sampling, it is capable of simulating coded-aperture accurately, flexibly, and efficiently, including problems of multiple shapes and even irregular geometry. The results are consistent with combined pinhole imaging, and the computational efficiency has been improved significantly.