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A process-based model for beach prof...
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Georgia Institute of Technology.
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A process-based model for beach profile evolution.
Record Type:
Language materials, printed : Monograph/item
Title/Author:
A process-based model for beach profile evolution./
Author:
Demir, Huseyin.
Description:
235 p.
Notes:
Adviser: Paul A. Work.
Contained By:
Dissertation Abstracts International68-12B.
Subject:
Engineering, Civil. -
Online resource:
http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3294469
ISBN:
9780549394600
A process-based model for beach profile evolution.
Demir, Huseyin.
A process-based model for beach profile evolution.
- 235 p.
Adviser: Paul A. Work.
Thesis (Ph.D.)--Georgia Institute of Technology, 2007.
Beach profile models predict the changes in bathymetry along a line perpendicular to the shoreline. These models are used to forecast bathymetric changes in response to storms, sea level rise or human activities such as dredging and beach nourishment. Process-based models achieve this by simulating the physical processes that drive the sediment transport as opposed to behavior models which simulate observed profile changes without resolving the underlying processes. Some of these processes are wave shoaling and breaking, boundary layer streaming, and offshore-directed undertow currents. These hydrodynamic processes control the sediment processes such as sediment pick-up from the bottom, diffusion of the sediment across the water column and its advection with waves and currents.
ISBN: 9780549394600Subjects--Topical Terms:
783781
Engineering, Civil.
A process-based model for beach profile evolution.
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Adviser: Paul A. Work.
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Source: Dissertation Abstracts International, Volume: 68-12, Section: B, page: 8220.
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Thesis (Ph.D.)--Georgia Institute of Technology, 2007.
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Beach profile models predict the changes in bathymetry along a line perpendicular to the shoreline. These models are used to forecast bathymetric changes in response to storms, sea level rise or human activities such as dredging and beach nourishment. Process-based models achieve this by simulating the physical processes that drive the sediment transport as opposed to behavior models which simulate observed profile changes without resolving the underlying processes. Some of these processes are wave shoaling and breaking, boundary layer streaming, and offshore-directed undertow currents. These hydrodynamic processes control the sediment processes such as sediment pick-up from the bottom, diffusion of the sediment across the water column and its advection with waves and currents.
520
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For this study, newly developed sediment transport and boundary layer models were coupled with existing models of wave transformation, nearshore circulation and bathymetry update, to predict beach profile changes. The models covered the region from the dry land to a depth of 6-8 meters, spanning up to 500 meters in the cross-shore direction. The modeling system was applied at storm time scales, extending from a couple of hours to several days. Two field experiments were conducted at Myrtle Beach, SC, involving the collection of wave, current and bathymetric data as a part of this study. The results were used to calibrate and test the numerical models along with data from various laboratory studies from the literature.
520
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The sediment transport model computes the variation of sediment concentrations over a wave period and over the water column, solving the advection-diffusion equation using the Crank-Nicholson finite-difference numerical scheme. Using a new approach, erosion depth thickness and sediment concentrations within the bed were also predicted. The model could predict sediment transport rates for a range of conditions, within a factor of two. It successfully computed the sediment concentration profile over the water column and within the bed and its variation throughout a wave period. Erosion depth and sheet flow layer thickness were also predicted reasonably well.
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Wave heights across the profile were predicted within ten percent when the empirical wave breaking parameter was tuned appropriately. Mean cross-shore velocities contain more uncertainty, even after tuning. The importance of capturing the location of the maximum, near-bottom, cross-shore velocity when predicting bar behavior was shown. Bar formation, erosion, accretion, onshore and offshore bar movement were all computed with the model successfully.
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School code: 0078.
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http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3294469
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