Correlated random-walk model for scattering

1987 ◽  
Vol 4 (7) ◽  
pp. 1206 ◽  
Author(s):  
E. Jakeman ◽  
E. Renshaw
1988 ◽  
Vol 25 (A) ◽  
pp. 335-346
Author(s):  
J. Gani

This paper considers a bivariate random walk modelon a rectangular lattice for a particle injected into a fluid flowing in a tank. The numbers of jumps of the particle in thexandydirections in this particular model are correlated. It is shown that when the random walk forms a bivariate Markov chain in continuous time, it is possible to obtain the state probabilitiespxy(t) through their Laplace transforms. Two exit rules are considered and results for both of them derived.


Ecology ◽  
2017 ◽  
Vol 99 (1) ◽  
pp. 217-223 ◽  
Author(s):  
Joseph D. Bailey ◽  
Jamie Wallis ◽  
Edward A. Codling

2017 ◽  
Vol 74 (9) ◽  
pp. 1474-1489 ◽  
Author(s):  
Martin Glas ◽  
Michael Tritthart ◽  
Bernhard Zens ◽  
Hubert Keckeis ◽  
Aaron Lechner ◽  
...  

Recruitment of Chondrostoma nasus and similar fish species in rivers is related to spatiotemporal linkages between larval hatching and nursery habitats. Active swimming behaviour contradicts the assumption that passive particle tracing models can serve as a proxy for larval dispersal models. A racetrack flume with an inshore area of near-natural slope was created to observe individual larval trajectories. A new three-step, raster-based analysis was developed to distinguish four types of movement patterns: active upstream, active downstream, active–passive, and passive. Both larval developmental stage-specific and release site-specific occurrences of these movement patterns were experimentally found for nine flow velocity classes (≤0.225 m·s−1). These current-induced movement patterns, and evaluated durations within them, were used to develop a biased and correlated random walk model that includes rheoreaction — a key behavioural response of fish to flow within rivers. The study introduces the concept and application of a rheoreaction-based correlated random walk model, which coupled with a 3D hydrodynamic model, allows prediction of the spatiotemporal effects of various river discharges, morphologies, and restoration scenarios on larval fish dispersal.


Ecology ◽  
2008 ◽  
Vol 89 (5) ◽  
pp. 1208-1215 ◽  
Author(s):  
Devin S. Johnson ◽  
Joshua M. London ◽  
Mary-Anne Lea ◽  
John W. Durban

1988 ◽  
Vol 25 (A) ◽  
pp. 335-346
Author(s):  
J. Gani

This paper considers a bivariate random walk model on a rectangular lattice for a particle injected into a fluid flowing in a tank. The numbers of jumps of the particle in the x and y directions in this particular model are correlated. It is shown that when the random walk forms a bivariate Markov chain in continuous time, it is possible to obtain the state probabilities pxy(t) through their Laplace transforms. Two exit rules are considered and results for both of them derived.


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