1,876 research outputs found
Analysis and design of dirty paper coding by transformation of noise
No full textThis work was supported by the center for Broadband
OFDM Mobile Access (BrOMA) at POSTECH through the
ITRC program of the Korean MIC, supervised by IITA.
(IITA-2006-C1090-0603-0037
Underwater spark discharge with long transmission line for cleaning horizontal wells
No full textA transmission line is discussed for application in an underwater spark-discharge technique in the cleaning of a horizontal well by incorporating a power-transmission model into the simulation. The pulsed-spark-discharge technique has been proposed for clogged-well rehabilitation, because it removes incrustations that are attached to well screens by using strong pressure waves that are generated by the rapid expansion of a spark channel. To apply the pulsed-spark-discharge technique to the cleaning of horizontal wells, the coaxial cable between the pulsed power supply and the spark gap as a load needs to be extended to a few hundred meters. Prior to field application, pulsed-spark-discharge experiments were conducted and the role of the transmission line was examined using an improved simulation model. In the model, a non-linear interaction of the spark channel and the capacitor bank is described by the pulse-forming action of the coaxial cable. Based on the accurate physical properties of the water plasma, such as the equation of state and electrical conductivity within the region of interest, the amount of energy contributed to the development of a shock wave was evaluated. The simulation shows that if the initial conditions of the spark channel are the same, no further reduction in strength of the pressure wave occurs, even if the cable length is increased above 50 m. Hence, the degraded peak pressure that was observed in the experiments using the longer cable is attributed to a change in the initial condition of the spark channel. The parametric study suggests that the low initial charging voltage, the high ambient water pressure, and the long cable length yield the low initial spark-channel density, which results in a reduced peak pressure. The simulation of line charging is presented to discuss the principle of disturbing the pre-breakdown process by an extended cable. © 2017 Author(s).OAIID:RECH_ACHV_DSTSH_NO:T201719639RECH_ACHV_FG:RR00200001ADJUST_YN:EMP_ID:A080568CITE_RATE:0DEPT_NM:에너지시스템공학부EMAIL:[email protected]_YN:NN
Genetic algorithm-based optimization of a target for the production of atmospheric-like neutrons via 100 MeV proton beam
No full text© 2021 Elsevier B.V.This paper presents the optimization of a white neutron target for 100 MeV proton beam to produce a fast neutron spectrum shape similar to that of the atmospheric neutron at ground level. The neutron target consists of 0.5 mm-thick discs consecutively placed in front of a cooling water channel. A sensitivity analysis is performed with different materials to assimilate resulting neutron spectrum with the ground-level cosmic ray-induced neutron spectrum by applying the genetic algorithm (GA). Optimization of the spectrum is conducted in consideration of neutron impact to semiconductor devices. To reconstruct a target-generated neutron spectrum, parametrization on neutron generation and stopping power by target material and position is configured. The loss function in the GA is defined to evaluate similarity between the target neutron spectrum and the atmospheric neutron spectrum. The GA is modeled with a package of consecutive discs as a gene for optimization, and the length and material of target for each disc are decided throughout generations. As a result, the target is configured with six different materials, with approximately half of the weighted deviation of atmospheric neutrons being compared with any other single-solid neutron target. The GA-based optimization process shown here suggests further use for designing targets with other incident proton energies or neutron spectra for various applications.N
sj-docx-1-jdr-10.1177_00220345221106676 – Supplemental material for Deep Learning–Based Prediction of the 3D Postorthodontic Facial Changes
No full textSupplemental material, sj-docx-1-jdr-10.1177_00220345221106676 for Deep Learning–Based Prediction of the 3D Postorthodontic Facial Changes by Y.S. Park, J.H. Choi, Y. Kim, S.H. Choi, J.H. Lee, K.H. Kim and C.J. Chung in Journal of Dental Research</p
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