Results 191 to 200 of about 64,864 (311)

A Dislocation Perspective on Strength and Toughness in Ceramics

open access: yesAdvanced Engineering Materials, EarlyView.
Dislocations in ceramics enjoy a long but yet under‐appreciated history. The three research waves for dislocations in ceramics highlight the topic evolution over the last 90 years. This review focuses on the impact of dislocation on strength and toughness in ceramics.
Xufei Fang
wiley   +1 more source

Regression Analysis of Technical Parameters Affecting Nuclear Power Plant Performances

open access: yes, 2012
Since the 80’s many studies have been conducted in order to explicate good and bad performances of commercial nuclear power plants (NPPs), but yet no defined correlation has been found out to be totally representative of plant operational experience. In
RICOTTI, MARCO ENRICO   +2 more
core  

Feasibility of Nitrogen as a Carrier Gas for Inconel Cold Spray in Hydropower Application

open access: yesAdvanced Engineering Materials, EarlyView.
N2, despite being nearly two orders of magnitude cheaper than He, is a feasible carrier gas for cold spray Inconel coatings in hydropower repair applications when higher gas temperature and pressure are used. Reducing powder size significantly improved cavitation resistance, while the addition of fine chromium carbide particles further enhanced erosion
Tianhao Wang   +4 more
wiley   +1 more source

Implications of diverging social and private discount rates for investments in the German power industry: a new case for nuclear energy? [PDF]

open access: yes
For power-plant investments, utilities rely after liberalisation on private financial markets, which are in general distorted. The (related) split of social and private time-preference rates provides a new reason for a welfare-enhancing policy ...
Heinzel, Christoph
core  

Machine Learning‐Supported Analysis for Predicting and Visualizing Nonlinear Relationships Between Material Properties in Electroplated Chromium Layers

open access: yesAdvanced Engineering Materials, EarlyView.
This study applies machine learning regression to predict chromium layer thickness in decorative trivalent chromium electroplating, using 441 experiments from laboratory‐scale (1L) and pilot‐scale (14L) setups. Tree‐based models, particularly CatBoost, outperformed linear regression by capturing nonlinear parameter interactions (R2$R^2$ up to 0.77 ...
Christoph Baumer   +4 more
wiley   +1 more source

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