Multi-scale computational study of the molten salt based recycling of spent nuclear fuels

2014 ◽  
Vol 38 (15) ◽  
pp. 1987-1993 ◽  
Author(s):  
Dohyun Kwak ◽  
Seunghyo Noh ◽  
Byungchan Han
Keyword(s):  
Molten Salt ◽  
Computational Study ◽  
Nuclear Fuels ◽  
Multi Scale

A Computational Study of Perfusion During the ExtraCorporeal Membrane Oxygenation (ECMO)

2017 ◽  
Vol 5 (1) ◽  
pp. 40-52
Author(s):  
Maria Vittoria Caruso ◽  
Vera Gramigna ◽  
Attilio Renzulli ◽  
Gionata Fragomeni
Keyword(s):  
Shear Stress ◽  
Extracorporeal Membrane Oxygenation ◽  
Computational Study ◽  
Fluid Dynamic ◽  
Scale Model ◽  
Common Procedure ◽  
Multi Scale ◽  
Membrane Oxygenation ◽  
Clinical Complications ◽  
The One

The extracorporeal membrane oxygenation (ECMO) is a common procedure of extracorporeal circulation (ECC) used in case of cardiopulmonary diseases. The major clinical complications are related to hemodynamic changes and to the mechanical shear stress. The aim of this study is to evaluate the effects of the modality of perfusion during ECMO, comparing the hemodynamic behavior generated by constant flow (normal modality) with the one obtained by pulsed perfusion induced by the intra-aortic balloon pump (IABP). To carry out the study, the computational fluid dynamic (CFD) approach was chosen, realizing a multi-scale model. The numerical results have highlighted that the IABP-induced pulsed perfusion increases both flow and pressure in the supraaortic vessels, even if the balloon makes the wall shear stress (WSS) pattern and the hemolysis index worse.

Computational Study for Inventory Estimation of Se-79, Tc-99, Sn-126, and Cs-135 in High-Level Radioactive Wastes From Spent Nuclear Fuels of Light Water Reactors

2011 ◽  
Author(s):  
Keisuke Okumura ◽  
Shiho Asai ◽  
Yukiko Hanzawa ◽  
Tsutomu Okamoto ◽  
Hideya Suzuki ◽  
...  
Keyword(s):  
Parametric Study ◽  
Computational Study ◽  
Estimation Method ◽  
Fission Products ◽  
Radioactive Wastes ◽  
Light Water Reactors ◽  
Nuclear Fuels ◽  
Light Water ◽  
Water Reactors ◽  
High Level

Inventory estimation of long-lived fission products (LLFPs) in high-level radioactive wastes (HLW) from spent nuclear fuels of light water reactors is important for a safety assessment of their disposal. In order to develop an inventory estimation method of difficult-to-measure LLFPs (Se-79, Tc-99, Sn-126, and Cs-135), a parametric study was carried out by using a sophisticated burnup calculation code and data. In the parametric study, fuel specifications and irradiation conditions are changed in the conceivable range. The considered parameters are fuel assembly types (PWR / BWR), U-235 enrichment, moderator temperature, void fraction, power density, and so on. From the calculated results, we clarify the burnup characteristics of the target LLFPs and their possible ranges of generations. Finally, candidates of the key nuclide are proposed for the scaling factor method of HLW.

scholarly journals Multi-scale computational study of the mechanical regulation of cell mitotic rounding in epithelia

2017 ◽  
Vol 13 (5) ◽  
pp. e1005533 ◽  
Author(s):  
Ali Nematbakhsh ◽  
Wenzhao Sun ◽  
Pavel A. Brodskiy ◽  
Aboutaleb Amiri ◽  
Cody Narciso ◽  
...  
Keyword(s):  
Computational Study ◽  
Multi Scale ◽  
Mechanical Regulation

scholarly journals Probabilistic associative learning suffices for learning the temporal structure of multiple sequences

2019 ◽  
Author(s):  
Ramon H. Martinez ◽  
Anders Lansner ◽  
Pawel Herman
Keyword(s):  
Associative Learning ◽  
Internal Control ◽  
Computational Study ◽  
Brain Activity ◽  
Temporal Structure ◽  
Learning Rule ◽  
Multi Scale ◽  
Temporal Aspects ◽  
And Behavior ◽  
Multiple Sequences

AbstractMany brain phenomena both at the cognitive and behavior level exhibit remarkable sequential characteristics. While the mechanisms behind the sequential nature of the underlying brain activity are likely multifarious and multi-scale, in this work we attempt to characterize to what degree some of this properties can be explained as a consequence of simple associative learning. To this end, we employ a parsimonious firing-rate attractor network equipped with the Hebbian-like Bayesian Confidence Propagating Neural Network (BCPNN) learning rule relying on synaptic traces with asymmetric temporal characteristics. The proposed network model is able to encode and reproduce temporal aspects of the input, and offers internal control of the recall dynamics by gain modulation. We provide an analytical characterisation of the relationship between the structure of the weight matrix, the dynamical network parameters and the temporal aspects of sequence recall. We also present a computational study of the performance of the system under the effects of noise for an extensive region of the parameter space. Finally, we show how the inclusion of modularity in our network structure facilitates the learning and recall of multiple overlapping sequences even in a noisy regime.

753 A Multi-scale Computational Study about Left Ventricle form and performance

2006 ◽  
Vol 2006.6 (0) ◽  
pp. 47-48
Author(s):  
Michito AKAGIRI ◽  
Hisasi TANIGUCHI ◽  
FUYOU Liang ◽  
Shinichi FUJIMOTO
Keyword(s):  
Left Ventricle ◽  
Computational Study ◽  
Multi Scale ◽  
And Performance

A multi-scale computational study on the mechanism of protonation of isobutene and 2-butene over HY zeolite

2017 ◽  
Vol 43 (13-16) ◽  
pp. 1348-1355 ◽  
Author(s):  
Kui Ren ◽  
Jun Long ◽  
Qiang Ren ◽  
Yongxiang Li ◽  
Zhenyu Dai
Keyword(s):  
Computational Study ◽  
Hy Zeolite ◽  
Multi Scale

The effect of R249S carcinogenic and H168R–R249S suppressor mutations on p53–DNA interaction, a multi scale computational study

2010 ◽  
Vol 40 (5) ◽  
pp. 498-508 ◽  
Author(s):  
Shah Md. Abdur Rauf ◽  
Mohamed Ismael ◽  
Kamlesh Kumar Sahu ◽  
Ai Suzuki ◽  
Michihisa Koyama ◽  
...  
Keyword(s):  
Computational Study ◽  
Dna Interaction ◽  
Multi Scale ◽  
Suppressor Mutations
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