Results 131 to 140 of about 11,370,086 (322)

Numerical Modelling of Frictional Sliding Induced Damage and Heating Effects on Rock With an Application to Sievers’ J‐Miniature Drilling on Granite

open access: yesInternational Journal for Numerical and Analytical Methods in Geomechanics, EarlyView.
ABSTRACT The present study develops a finite element‐based numerical method for simulation of frictional rotational sliding induced damage and heating effects on rock. The method is applied to the Sievers’ J‐ miniature drill test, which is widely used for estimating the rock drillability and predicting the cutter life.
Timo Saksala   +8 more
wiley   +1 more source

Exploring the Physical Properties of Novel Inorganic Perovskite AMgBr3 (A = Ga, Na, Tl)

open access: yesNano Select, EarlyView.
The band gap values of AMgBr3 (A = Na, Ga, and Tl) perovskites were calculated using various exchange‐correlation functionals such as generalized gradient approximation (GGA)‐Perdew–Burke–Ernzerhof (PBE), GGA‐PBEsol, GGA‐WC, Hybrid HSE06, and Tran–Blaha modified Becke–Johnson (TB‐mBJ) methods.
Md. Bayjid Hossain Parosh   +4 more
wiley   +1 more source

Investigating the Effects of Functionalized Single Wall Carbon Nanotubes on the Cure Behavior of a Carbon/Epoxy Prepreg System by an Optimized Parameter Approach

open access: yesPolymer Composites, EarlyView.
Mathematical Modeling of the Effect of Carbon Nanotubes on the Cure Behavior of a Carbon/Epoxy Prepreg Syste. ABSTRACT Carbon/Epoxy composite materials are used in a wide range of applications due to their superior performance. However, their properties are strongly related to cross‐linking reactions occurring during the curing process, and a prior ...
Murat Öz   +4 more
wiley   +1 more source

Statistical Complexity of Quantum Learning

open access: yesAdvanced Quantum Technologies, EarlyView.
The statistical performance of quantum learning is investigated as a function of the number of training data N$N$, and of the number of copies available for each quantum state in the training and testing data sets, respectively S$S$ and V$V$. Indeed, the biggest difference in quantum learning comes from the destructive nature of quantum measurements ...
Leonardo Banchi   +3 more
wiley   +1 more source

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