796 research outputs found

    Determination of Reactivity and Neutron Flux Using Modified Neural Network for HTGR

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    Nuclear kinetic calculations based on point kinetic model have been generally applied as the standard method for neutronics codes. As the central control rod (C-CR) withdrawal test has demonstrated in a prismatic core type high-temperature gas-cooled reactor (HTGR) named High Temperature Engineering Test Reactor (HTTR), the transient calculation of kinetic parameter, reactivity, and neutron fluxes, requires a new method to shorten calculation-process time. Development of neural network method was applied to point kinetic model as the necessity of real-time calculation that could work in parallel with the digital reactivity meter. The combination of Time Delayed Neural Network (TDNN) and Jordan Recurrent Neural Network (Jordan RNN) named TD-Jordan RNN was the result of the modeling approach. The application of TD-Jordan RNN with adequate learning, tested offline, determined results accurately even when signal inputs were noisy. Furthermore, the preprocessing for neural network input utilized noise reduction as one of the equations to transform two of twelve time-delayed inputs into power corrected inputs

    Calculation of Control Rods Reactivity Worth of RSG-GAS First Core Using Deterministic and Monte Carlo Methods

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    The control rod worth is a key parameter for the research reactor operation and utilization. Control rod worth computation is a challenge for the fully-deterministic and Monte Carlo calculations, including the few-group cross section generation, and the core analysis. The safe and reliable utilization of research reactor demands the possible accurate information of control rod worth because they are used to compensate the excess reactivity for safe reactor operation and its controlled shut down. The criticality positions of the control rods change with time due to buildup of fission products during the reactor operation. It is therefore important to determine the reactivity worth of control rods. The aim of this article is to obtain reliable control rod worth of the first core of RSG-GAS as a verification and validation result. For this purpose, deterministic and Monte Carlo models of the reactor core were developed and confirmed by the experimental results of excess reactivity, shutdown margin, and combined control rod reactivity worth using the combination of WIMSD-5B and Batan-3DIFF computer codes. WIMSD-5B is a neutron transport theory-based lattice cell modeling code that is used for the generation of group constants for different regions of the reactor core. These are provided as input to the diffusion theory based Batan-3DIFF code which performs the global core calculations for the reactor system. For the Monte Carlo model, to estimate the reactivity worth of control rods, the MCNP6 code is used. The result of this analysis showed that for the integral control rod worth a good agreement was found between experimental data and Monte Carlo simulation results but up to 5 % difference occurred between experimental results and diffusion result

    Pure nematic state in iron-based superconductor

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    Lattice and electronic states of thin FeSe films on LaAlO3_3 substrates are investigated in the vicinity of the nematic phase transition. No evidence of structural phase transition is found by x-ray diffraction below T∗∼90T^\ast \sim 90 K, while results obtained from resistivity measurement and angle-resolved photoemission spectroscopy clearly show the appearance of a nematic state. These results indicate formation of a pure nematic state in the iron-based superconductor and provide conclusive evidence that the nematic state originates from the electronic degrees of freedom. This pure nematicity in the thin film implies difference in the electron-lattice interaction from bulk FeSe crystals. FeSe films provide valuable playgrounds for observing the pure response of "bare" electron systems free from the electron-lattice interaction, and should make important contribution to investigate nematicity and its relationship with superconductivity

    Determination of Reactivity and Neutron Flux Using Modified Neural Network for HTGR

    Get PDF
    Nuclear kinetic calculations based on point kinetic model have been generally applied as the standard method for neutronics codes. As the central control rod (C-CR) withdrawal test has demonstrated in a prismatic core type high-temperature gas-cooled reactor (HTGR) named High Temperature Engineering Test Reactor (HTTR), the transient calculation of kinetic parameter, reactivity, and neutron fluxes, requires a new method to shorten calculation-process time. Development of neural network method was applied to point kinetic model as the necessity of real-time calculation that could work in parallel with the digital reactivity meter. The combination of Time Delayed Neural Network (TDNN) and Jordan Recurrent Neural Network (Jordan RNN) named TD-Jordan RNN was the result of the modeling approach. The application of TD-Jordan RNN with adequate learning, tested offline, determined results accurately even when signal inputs were noisy. Furthermore, the preprocessing for neural network input utilized noise reduction as one of the equations to transform two of twelve time-delayed inputs into power corrected inputs

    Differential Expressions of Adhesive Molecules and Proteases Define Mechanisms of Ovarian Tumor Cell Matrix Penetration/Invasion

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    Epithelial ovarian cancer is an aggressive and deadly disease and understanding its invasion mechanisms is critical for its treatment. We sought to study the penetration/invasion of ovarian tumor cells into extracellular matrices (ECMs) using a fibroblast-derived three-dimensional (3D) culture model and time-lapse and confocal imaging. Twelve ovarian tumor cells were evaluated and classified into distinct groups based on their ECM remodeling phenotypes; those that degraded the ECM (represented by OVCAR5 cells) and those that did not (represented by OVCAR10 cells). Cells exhibiting a distinct ECM modifying behavior were also segregated by epithelial- or mesenchymal-like phenotypes and uPA or MMP-2/MMP-9 expression. The cells, which presented epithelial-like phenotypes, penetrated the ECM using proteases and maintained intact cell-cell interactions, while cells exhibiting mesenchymal phenotypes modified the matrices via Rho-associated serine/threonine kinase (ROCK) in the absence of apparent cell-cell interactions. Overall, this study demonstrates that different mechanisms of modifying matrices by ovarian tumor cells may reflect heterogeneity among tumors and emphasize the need to systematically assess these mechanisms to better design effective therapies
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