Results 71 to 80 of about 20,277 (256)

Probabilistic prediction of rate‐dependent rock strength using natural gradient boosting and Gaussian process regression

Deep Underground Science and Engineering, EarlyView.
Probabilistic natural gradient boosting and Gaussian process regression models accurately predict rate‐dependent rock strength across lithologies. Static strength and strain rate dominate, while geometric factors have minimal influence, enabling interpretable and uncertainty‐aware predictions for dynamic geomechanical applications. Abstract The dynamic
Hadi Fathipour‐Azar
wiley   +1 more source

Probabilistic characterization of seepage‐induced tunnel face failure via a two‐phase double‐point material point method

Deep Underground Science and Engineering, EarlyView.
To address seepage‐induced tunnel face collapse, this study develops a two‐phase double‐point MPM framework to capture large‐deformation hydro‐mechanical interactions. Incorporating a cementation‐based constitutive model with dynamic permeability updates, the model is successfully validated against saturated granular‐column collapse experiments ...
Yue Tong, Mingliang Zhou, Jie Xu, Zeyu Li, Yisheng Zhao, Jin An, Hongwei Huang   +6 more
wiley   +1 more source

Nanocubes and Cuboctahedra: Entropic Stabilization Versus Thermal Segregation in Rock Salt‐ and Spinel‐Type Multinary Oxides from Spray‐Flame Synthesis

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
Spray‐flame synthesis enables highly flexible and scalable production of multinary and high‐entropy oxide nanoparticles due to high synthesis temperatures with subsequent quenching. Temperature‐dependent in situ diffraction of as‐synthesized materials clearly reveals entropy stabilization in rock salt lattices, while spinels—featuring tetrahedral and ...
Mohammed‐Ali Sheikh, Steven Angel, Sabrina Schleich, Leon Müller, Jan Ternieden, Hatem M. A. Amin, Christof Schulz, Hartmut Wiggers   +7 more
wiley   +1 more source

Ubiquitous lognormal distribution of neuron densities in mammalian cerebral cortex. [PDF]

Cereb Cortex, 2023
Morales-Gregorio A, van Meegen A, van Albada SJ.   +2 more
europepmc   +1 more source

From a Probabilistic PBEE Framework to Risk‐Targeted Structural Design With Cascading Hazards: Engineering Application for Seismic–Radiological Safety

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Earthquake‐induced damage of structures can trigger cascading hazards, linking structural performance to nonstructural consequences. In current engineering practice, these two aspects are typically addressed separately, limiting the ability to account for such coupled effects in design.
Matjaž Dolšek, Peter Fajfar, Anže Babič   +2 more
wiley   +1 more source

Improvement in the Between-Class Variance Based on Lognormal Distribution for Accurate Image Segmentation. [PDF]

Entropy (Basel), 2022
Jumiawi WAH, El-Zaart A.
europepmc   +1 more source

Analytical Framework for System‐Level Fragility Surfaces of Reinforced Concrete Bridges Under Mainshock‐Aftershock Sequences

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Conventional single intensity measure (IM) fragility approaches with simplified component dependency assumptions overlook the progressive damage accumulation and evolving inter‐component correlations that govern system behavior under mainshock‐aftershock (MSAS) loading.
Muhammad Rashid, Mayuko Nishio
wiley   +1 more source

On Modelling Insurance Data by Using a Generalized Lognormal Distribution || Sobre la modelización de datos de seguros usando una distribución lognormal generalizada [PDF]

Revista de Métodos Cuantitativos para la Economía y la Empresa, 2014
In this paper, a new heavy-tailed distribution is used to model data with a strong right tail, as often occurs in practical situations. The distribution proposed is derived from the lognormal distribution, by using the Marshall and Olkin procedure.
García, Victoriano J., Gómez-Déniz, Emilio, Vázquez-Polo, Francisco J.   +2 more
doaj  

Log-moment estimators of the Nakagami-lognormal distribution

EURASIP Journal on Wireless Communications and Networking, 2019
In this paper, estimators of the Nakagami-lognormal (NL) distribution based on the method of log-moments have been derived and thoroughly analyzed. Unlike maximum likelihood (ML) estimators, the log-moment estimators of the NL distribution are obtained ...
Juan Reig, Conor Brennan, Vicent M. Rodrigo Peñarrocha, Lorenzo Rubio   +3 more
doaj   +1 more source

Atmospheric aerosol particle size distribution from Lidar data based on the lognormal distribution mode. [PDF]

Heliyon, 2022
Shi Y, Liu W, Dong Y, Zhao X, Xiang Y, Zhang T, Lv L.   +6 more
europepmc   +1 more source