Stochastic modelling of clay/epoxy nanocomposites

2014 ◽  
Vol 118 ◽  
pp. 241-249 ◽  
Author(s):  
Mohammad Silani ◽  
Hossein Talebi ◽  
Saeed Ziaei-Rad ◽  
Pierre Kerfriden ◽  
Stéphane P.A. Bordas ◽  
...  
Keyword(s):  
Stochastic Modelling ◽  
Epoxy Nanocomposites

Synthesis and characterization of graphene-epoxy nanocomposites

2015 ◽  
Vol 57 (11-12) ◽  
pp. 1001-1005 ◽  
Author(s):  
Alperen Acar ◽  
Özgen Ümit Çolak ◽  
Deniz Uzunsoy
Keyword(s):  
Synthesis And Characterization ◽  
Epoxy Nanocomposites

INFLUENCE OF SILANE TREATMENTS ON THE PROPERTIES OF GRAPHITE NANOPLATELET/EPOXY NANOCOMPOSITES

2018 ◽  
Author(s):  
Alessandra Lavoratti ◽  
Ademir J. Zattera ◽  
Sandro C. Amico
Keyword(s):  
Epoxy Nanocomposites

Incorporating concepts from physical theory into stochastic modelling of urban runoff pollution

1998 ◽  
Vol 37 (1) ◽  
pp. 179-185
Author(s):  
Morten Grum
Keyword(s):  
Stochastic Model ◽  
Continuous Time ◽  
Measurement Errors ◽  
Physical Theory ◽  
Oxygen Demand ◽  
Stochastic Modelling ◽  
Urban Runoff ◽  
Primary Input ◽  
Deterministic Modelling ◽  
Runoff Pollution

On evaluating the present or future state of integrated urban water systems, sewer drainage models, with rainfall as primary input, are often used to calculate the expected return periods of given detrimental acute pollution events and the uncertainty thereof. The model studied in the present paper incorporates notions of physical theory in a stochastic model of water level and particulate chemical oxygen demand (COD) at the overflow point of a Dutch combined sewer system. A stochastic model based on physical mechanisms has been formulated in continuous time. The extended Kalman filter has been used in conjunction with a maximum likelihood criteria and a non-linear state space formulation to decompose the error term into system noise terms and measurement errors. The bias generally obtained in deterministic modelling, by invariably and often inappropriately assuming all error to result from measurement inaccuracies, is thus avoided. Continuous time stochastic modelling incorporating physical, chemical and biological theory presents a possible modelling alternative. These preliminary results suggest that further work is needed in order to fully appreciate the method's potential and limitations in the field of urban runoff pollution modelling.

Stochastic Modelling of Particle Segregation in a Horizontal Drum Mixer

1992 ◽  
Vol 57 (10) ◽  
pp. 2100-2112 ◽  
Author(s):  
Vladimír Kudrna ◽  
Pavel Hasal ◽  
Andrzej Rochowiecki
Keyword(s):  
Differential Equation ◽  
Diffusion Coefficient ◽  
Stochastic Model ◽  
Diffusion Process ◽  
Stochastic Modelling ◽  
Solid Particles ◽  
Kolmogorov Equation ◽  
Particle Segregation ◽  
Drum Mixer ◽  
Horizontal Drum

A process of segregation of two distinct fractions of solid particles in a rotating horizontal drum mixer was described by stochastic model assuming the segregation to be a diffusion process with varying diffusion coefficient. The model is based on description of motion of particles inside the mixer by means of a stochastic differential equation. Results of stochastic modelling were compared to the solution of the corresponding Kolmogorov equation and to results of earlier carried out experiments.

Synthesis and characterization of (Fe3O4/MWCNTs)/ epoxy nanocomposites

2010 ◽  
pp. NA-NA ◽  
Author(s):  
Wanda D. Jones ◽  
Vijaya K. Rangari ◽  
Tarig A. Hassan ◽  
Shaik Jeelani
Keyword(s):  
Synthesis And Characterization ◽  
Epoxy Nanocomposites
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