Results 111 to 120 of about 23,712,988 (293)
Modeling proppant transport and settling in a 3D propagating fracture
Deep Underground Science and Engineering, EarlyView.A versatile multiphysics tool is presented for simulating the complex processes involved in hydraulic fracturing treatments. The model couples fracture opening and propagation, variable‐density slurry flow, and proppant particle transport within the multiphysics object‐oriented simulation environment framework, based on two‐phase mixture equations and ...
Robert Egert +2 more
wiley +1 more source
Spiked Dirichlet Process Priors for Gaussian Process Models
Journal of Probability and Statistics, 2010 We expand a framework for Bayesian variable selection for Gaussian process (GP) models by employing spiked Dirichlet process (DP) prior constructions over set partitions containing covariates.
Terrance Savitsky, Marina Vannucci
doaj +1 more source
Journal of Advanced Transportation, 2020 A crucial task in traffic data analysis is similarity pattern discovery, which is of great importance to urban mobility understanding and traffic management.
Yaxiong Han, Zhaocheng He
doaj +1 more source
Finite Element Analysis for Li Batteries at the Mesoscale
ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.Finite element analysis (FEA), through multi‐physics coupling, has been widely employed to calculate mesoscale structures in LIBs that exhibit inherent randomness and disorder (Figure a). It has been extensively applied to the investigation of critical phenomena such as Li dendrite evolution, Li+ concentration gradients, SEI film growth, particle ...
Guanwu Li +3 more
wiley +1 more source
Chemical Engineering Transactions, 2018 Process scheduling is one key layer of decision hierarchy for process industries to optimize their production schedule in order to gain the long-term economic viability.
Cen Guo, Fengqi You
doaj +1 more source
High‐Order Projection‐Based Upwind Method for Simulation of Transitional Turbulent Flows
International Journal for Numerical Methods in Fluids, EarlyView.In this study, we evaluated the implicit large‐eddy simulation capabilities of the mass‐conserving mixed stress method for transitional turbulent flows and proposed an efficient solution method for large‐scale applications. The results presented in this work show promising outcomes for incompressible aerodynamic flow problems, which can be further ...
Philip L. Lederer +2 more
wiley +1 more source
Environment International, 2015 Background: Airborne particles are a complex mix of organic and inorganic compounds, with a range of physical and chemical properties. Estimation of how simultaneous exposure to air particles affects the risk of adverse health response represents a ...
Monica Pirani +5 more
doaj +1 more source
A Dirichlet Process Mixture Model of Discrete Choice
, 2018 We present a mixed multinomial logit (MNL) model, which leverages the truncated stick-breaking process representation of the Dirichlet process as a flexible nonparametric mixing distribution. The proposed model is a Dirichlet process mixture model and accommodates discrete representations of heterogeneity, like a latent class MNL model.
Krueger, Rico +2 more
openaire +2 more sources
Dynamic clustering via asymptotics of the dependent Dirichlet process mixture [PDF]
, 2013 This paper presents a novel algorithm, based upon the dependent Dirichlet process mixture model (DDPMM), for clustering batch-sequential data containing an unknown number of evolving clusters.
Carin, Lawrence +8 more
core
Bayesian Multivariate Two‐Stage Volatility‐Return Models (MTS‐VR)
Journal of Forecasting, EarlyView.ABSTRACT This paper develops a class of models to capture the joint dynamics of asset returns and multivariate volatility. Owing to its two‐stage construction, this class is referred to as the multivariate two‐stage volatility‐return (MTS‐VR) model.
Zhenglyu Huang +2 more
wiley +1 more source