Titlebook: Bayesian Network Modeling of Corrosion; Narasi Sridhar Book 2024 The Editor(s) (if applicable) and The Author(s), under exclusive license

Coarse

书目名称Bayesian Network Modeling of Corrosion影响因子(影响力)




书目名称Bayesian Network Modeling of Corrosion影响因子(影响力)学科排名




书目名称Bayesian Network Modeling of Corrosion网络公开度




书目名称Bayesian Network Modeling of Corrosion网络公开度学科排名




书目名称Bayesian Network Modeling of Corrosion被引频次




书目名称Bayesian Network Modeling of Corrosion被引频次学科排名




书目名称Bayesian Network Modeling of Corrosion年度引用




书目名称Bayesian Network Modeling of Corrosion年度引用学科排名




书目名称Bayesian Network Modeling of Corrosion读者反馈




书目名称Bayesian Network Modeling of Corrosion读者反馈学科排名

detach

中国纪念碑

Ali Kaveh,Armin Dadras Eslamloupropagation of pitting corrosion, or corrosion fronts in general, with time. The method is promising, but exploratory in nature because parameters are selected to match average empirical trends and not necessarily based on corrosion mechanisms. Equations are provided for Markov Chain corrosion propa

臭名昭著

Nuclear Energy, metallic alloys is discussed. The approach is illustrated for SCC of Ni-base alloys in steam generator environments and stainless steels in atmospheric conditions. Additionally, the performance of nuclear waste disposal containers in geologic media is discussed from a BN perspective.

Harbor

规范就好

https://doi.org/10.1007/978-3-540-93964-1stributions, and applications of Bayesian Networks. The theoretical foundations of Bayesian Networks are explored only briefly—the focus is the chapter is to familiarize the corrosion expert on Bayesian network concepts and enable model building.

肿块

Presbycusis

Modestus O. Okwu,Lagouge K. Tartibu metallic alloys is discussed. The approach is illustrated for SCC of Ni-base alloys in steam generator environments and stainless steels in atmospheric conditions. Additionally, the performance of nuclear waste disposal containers in geologic media is discussed from a BN perspective.

过份好问

黑豹

Modestus O. Okwu,Lagouge K. Tartibustatistics of components, and not on corrosion models. In this chapter, a probabilistic framework for materials performance in production systems is presented using Bayesian networks that incorporate corrosion and environmentally assisted cracking models. The focus will be on environmentally assisted cracking of upstream metallic materials.