Slope distribution in front-back asymmetric stochastic Lagrange time waves
Lindgren, Georg LU
(2010)
In Advances in Applied Probability
42(2).
p.489-508
- Abstract
- The stochastic Lagrange wave model is a realistic alternative to the Gaussian linear wave model, which has been successfully used in ocean engineering for more than half a century. This paper presents the slope distributions and other characteristic distributions at level crossings
for asymmetric Lagrange time waves, i.e. what can be observed at a fixed measuring station, thereby extending results previously given for space waves. The distributions are given as expectations in a multivariate normal distribution, and they have to be evaluated by simulation or numerical integration. Interesting characteristic variables are: slope in time, slope in space, and vertical particle velocity when the waves are observed close to instances... (More) - The stochastic Lagrange wave model is a realistic alternative to the Gaussian linear wave model, which has been successfully used in ocean engineering for more than half a century. This paper presents the slope distributions and other characteristic distributions at level crossings
for asymmetric Lagrange time waves, i.e. what can be observed at a fixed measuring station, thereby extending results previously given for space waves. The distributions are given as expectations in a multivariate normal distribution, and they have to be evaluated by simulation or numerical integration. Interesting characteristic variables are: slope in time, slope in space, and vertical particle velocity when the waves are observed close to instances when the water level crosses a predetermined level.
The theory has been made possible by recent generalizations of
Rice's formula for the expected number of marked crossings in random
fields. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/1545560
- author
- Lindgren, Georg
LU
- organization
- publishing date
- 2010
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- Palm distribution, Crossing theory, Rice formula, Slepian model, wave steepness, Gaussian process
- in
- Advances in Applied Probability
- volume
- 42
- issue
- 2
- pages
- 489 - 508
- publisher
- Applied Probability Trust
- external identifiers
-
- wos:000278796800011
- scopus:77955889280
- ISSN
- 0001-8678
- DOI
- 10.1239/aap/1275055239
- language
- English
- LU publication?
- yes
- id
- 99acf710-fc4b-4889-9bb6-f10350e93907 (old id 1545560)
- date added to LUP
- 2016-04-01 10:10:53
- date last changed
- 2022-01-25 20:36:56
@article{99acf710-fc4b-4889-9bb6-f10350e93907,
abstract = {{The stochastic Lagrange wave model is a realistic alternative to the Gaussian linear wave model, which has been successfully used in ocean engineering for more than half a century. This paper presents the slope distributions and other characteristic distributions at level crossings <br/><br>
for asymmetric Lagrange time waves, i.e. what can be observed at a fixed measuring station, thereby extending results previously given for space waves. The distributions are given as expectations in a multivariate normal distribution, and they have to be evaluated by simulation or numerical integration. Interesting characteristic variables are: slope in time, slope in space, and vertical particle velocity when the waves are observed close to instances when the water level crosses a predetermined level. <br/><br>
The theory has been made possible by recent generalizations of <br/><br>
Rice's formula for the expected number of marked crossings in random <br/><br>
fields.}},
author = {{Lindgren, Georg}},
issn = {{0001-8678}},
keywords = {{Palm distribution; Crossing theory; Rice formula; Slepian model; wave steepness; Gaussian process}},
language = {{eng}},
number = {{2}},
pages = {{489--508}},
publisher = {{Applied Probability Trust}},
series = {{Advances in Applied Probability}},
title = {{Slope distribution in front-back asymmetric stochastic Lagrange time waves}},
url = {{http://dx.doi.org/10.1239/aap/1275055239}},
doi = {{10.1239/aap/1275055239}},
volume = {{42}},
year = {{2010}},
}