Interaction behavior between binary xCe-yNd alloy and HT9

Kim, Junhwan; Cheon, Jin-Sik; Lee, Byoung Oon; Kim, June Hyung

doi:10.1016/j.jnucmat.2016.07.040

Cited by 10 publications

(3 citation statements)

References 9 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Since DL-1 and DL-2 are located on each side of the original interface boundary, they are formed by the diffusion of Fe into Ce, and the diffusion of Ce into HT9, respectively. The formation of CeFe 2 in DL-1 results in the decrease of Fe in DL-2, which is consistent with the previous study where Fe in the cladding material rapidly migrated into Ce, leaving an Fe-depleted region into which Ce diffuses [25]. The Cr content in DL-2 is much higher than HT9 due to the reduction of Fe content.…”

Section: Ht9/ce Interfacesupporting

confidence: 91%

Diffusion behavior of lanthanide-additive compounds (Ce4Sb3, Ce2Sb, and CeTe) against HT9 and Fe

Xie

Zhang

Benson

et al. 2019

Materials Characterization

View full text Add to dashboard Cite

A B S T R A C TAntimony and tellurium have been identified as promising additives in metallic fuel, which can immobilize freelanthanide fission products into stable intermetallic compounds in order to mitigate the fuel-cladding chemical interaction. Ce 4 Sb 3 , Ce 2 Sb, and CeTe are the primary compounds formed by Sb or Te with the lanthanide Ce present in the fuel. If these compounds are present at the outer periphery of the fuel, they will come in contact with and react with the cladding after the fuel swells. The present study investigates the reactivity of these compounds with two cladding materials, HT9 and Fe. The diffusion couple tests between these compounds and HT9 or Fe were conducted at 853 K. Scanning electron microscopy and transmission electron microscopy were used to analyze the morphology, microstructure, and phase distribution of the diffusion region. It was observed that the diffusion region thickness formed by the three compounds was significantly reduced compared to free Ce. There was no observed diffusion or reaction between Ce 4 Sb 3 or Ce 2 Sb with either HT9 or Fe. CeTe was found to diffuse and react with HT9, forming Cr 3 Te 4 and TeFe at the diffusion region, as well as to penetrate into Fe, mostly by intergranular diffusion.

show abstract

Section: Ht9/ce Interfacesupporting

confidence: 91%

Diffusion behavior of lanthanide-additive compounds (Ce4Sb3, Ce2Sb, and CeTe) against HT9 and Fe

Xie

Zhang

Benson

et al. 2019

Materials Characterization

View full text Add to dashboard Cite

show abstract

“…As IoT devices can generate high-dimensional data with obvious characteristics, such as temperature measurement, video monitoring, and water level telemetry, IoT devices have been deeply applied in many aspects [8,9]. e interaction of mobile network is mainly aimed at interaction behavior, because the interactive network is easy to accept, simple to operate, and so on and has been applied in many computer networks, bringing a lot of mobile network interaction behavior [10,11]. erefore, how to effectively identify abnormal behavior and distinguish normal mobile network interaction is worth studying.…”

Section: Introductionmentioning

confidence: 99%

“…Some scholars use a genetic algorithm to build a detection model to realize the aggregation of interactive behavior for overall anomaly detection. In addition, specific classification of abnormal behaviors is realized based on the discrimination of abnormal data by the wavelet model [10,12,13]. However, these methods have certain limitations, especially in feature extraction and direction recognition, which are difficult to be finely divided [14].…”

Section: Introductionmentioning

confidence: 99%

Application of a FL Time Series Building Model in Mobile Network Interaction Anomaly Detection in the Internet of Things Environment

Chen

Lee

Jeong

2022

Computational Intelligence and Neuroscience

View full text Add to dashboard Cite

With the continuous development of the social economy, mobile network is becoming more and more popular. However, it should be noted that it is vulnerable to different security risks, so it is extremely important to detect abnormal behaviors in mobile network interaction. This paper mainly introduces how to detect the characteristic data of mobile Internet interaction behavior based on IOT FL time series component model, set the corresponding threshold to screen the abnormal data, and then use K-means++ clustering algorithm to obtain the abnormal set of multiple interactive data, and conduct intersection operation on all abnormal sets, so as to obtain the final abnormal detection object set. The simulation results show that the FL time series component model of the Internet of Things is effective and can support abnormal detection of mobile network interaction behavior.

show abstract

Aging effect on the thermal transient behavior of the fuel cladding of a sodium-cooled fast reactor

Shin

Kim

Ryu

et al. 2017

Journal of Nuclear Materials

View full text Add to dashboard Cite

Interaction behavior between binary xCe-yNd alloy and HT9

Cited by 10 publications

References 9 publications

Diffusion behavior of lanthanide-additive compounds (Ce4Sb3, Ce2Sb, and CeTe) against HT9 and Fe

Diffusion behavior of lanthanide-additive compounds (Ce4Sb3, Ce2Sb, and CeTe) against HT9 and Fe

Application of a FL Time Series Building Model in Mobile Network Interaction Anomaly Detection in the Internet of Things Environment

Aging effect on the thermal transient behavior of the fuel cladding of a sodium-cooled fast reactor

Contact Info

Product

Resources

About