Changeset 3394


Ignore:
Timestamp:
Jul 20, 2006, 6:53:57 PM (18 years ago)
Author:
sexton
Message:

incorporating Ole's comments into Pt Hedland report

Location:
production/pt_hedland_2006/report
Files:
5 edited

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  • production/pt_hedland_2006/report/anuga.tex

    r3375 r3394  
    77technique belongs to the class of computational fluid dynamic (CFD)
    88methods which is based on discretizing the study area in
    9 control ''volumes''. The method satisfices conservation
    10 of mass, momentum and energy and is exactly satisfied for
     9control ''volumes''. The method satisfies conservation
     10of mass and horizontal momentum and is satisfied for
    1111each control volume.
    1212An advantage of this technique is that the discretization
     
    1515is treated robustly as part of the numerical scheme.}.
    1616ANUGA is continually being developed and validated to ensure
    17 the modelling approximations reflect new theory or
    18 available experimental data sets.
     17the modelling approximations are as accurate as possible.
     18However, model sensitivity to errors in bathymetric data,
     19frictional resistance of the seafloor and the size of the
     20tsunamigenic event are not well understood and the topic
     21of ongoing research.
    1922As such, the current results are preliminary.
    2023
     
    4144the friction coefficients, and
    4245thus it has not been incorporated
    43 in the scenario. The
    44 results are therefore likely to be over estimations.
     46in the scenario.
     47The results are therefore likely to be over estimations.
    4548
  • production/pt_hedland_2006/report/damage_inputs.tex

    r3364 r3394  
    1 \begin{table}
     1\begin{table}[p]
    22\begin{center}
    33\caption{Framed residential building collapse probability. $h$ is the
     
    66\label{table:collapse}
    77\begin{tabular}{|l|l|l|l|l|l|}\hline
    8 Building Location &
     8Distance from coast ($d[m]$) &
    99$h$<1.0 &1.0<$h$<2.0&   2.0<$h$<3.0     &3.0<$h$<5.0    &$h$>5.0 \\ \hline
    10 First 2 Rows
    11 (1st block)     &0.05   &0.6    &0.8    &0.95   &0.99 \\ \hline
    12 Second 2 Rows (2nd block)       &0.02   &0.3    &0.4    &0.7    &0.9 \\ \hline
    13 Third 2 Rows
    14 (3rd block)     &0.01   &0.1    &0.25   &0.5    &0.65 \\ \hline
    15 Beyond 3rd block        &0.0    &0.05   &0.15   &0.3    &0.45 \\ \hline
     10$d < 125$        &0.05  &0.6    &0.8    &0.95   &0.99 \\ \hline
     11$125 < d < 200$ &0.02   &0.3    &0.4    &0.7    &0.9 \\ \hline
     12$200 < d < 250$ &0.01   &0.1    &0.25   &0.5    &0.65 \\ \hline
     13$200 < d$       &0.0    &0.05   &0.15   &0.3    &0.45 \\ \hline
    1614\end{tabular}
    1715\end{center}
     
    2321\label{table:casualty}
    2422\begin{tabular}{|l|l|l|l|l|l|l|}\hline
    25 Hazard Exposure &       & Unharmed      &Minor
     23Hazard Exposure & depth above floor & Unharmed  &Minor
    2624        &Moderate       &Serious        &Death \\ \hline
    2725Collapse        &<1.0   &0.3    &0.28   &0.08   &0.04   &0.30 \\ \hline
    2826        &>1.0   &0.01   &0.028  &0.008  &0.004  &0.95 \\ \hline
    29 No Collapse – 1st 3 blocks      &<1.0   &0.35   &0.40   &0.1    &0.05   &0.10
     27No Collapse - $d < 250$ &<1.0   &0.35   &0.40   &0.1    &0.05   &0.10
    3028\\ \hline
    3129        &>1.0   &0.1    &0.28   &0.08   &0.04   &0.50 \\ \hline
    32 No Collapse - Elsewhere &<1.0   &0.4    &0.4    &0.1    &0.05   &0.05 \\ \hline
     30No Collapse - $250 < d$ &<1.0   &0.4    &0.4    &0.1    &0.05   &0.05 \\ \hline
    3331        &>1.0   &0.12   &0.33   &0.1    &0.05   &0.40 \\ \hline
    3432\end{tabular}
     
    3836\begin{table}
    3937\begin{center}
    40 \caption{Injury level classifications}
     38\caption{Injury level classificationse. Floor height is assumed to be 30cm}
    4139\label{table:injury}
    4240\begin{tabular*}{\textwidth}{|l|p{.695\textwidth}|}\hline
     
    6563\end{table}
    6664\clearpage
     65
  • production/pt_hedland_2006/report/data.tex

    r3375 r3394  
    363620m Digital Elevation Model (DEM) and orthophotography
    3737covering the NW Shelf. The DTED Level 2 data is ``bare earth'' and
    38 the DLI data distorted by vegetation and buildings. 
     38the DLI data is distorted by vegetation and buildings. 
    3939
    4040Figure \ref{fig:contours_compare}(a) shows the contour lines for
     
    4242that the extent of the tidal inundation is exaggerated.
    4343In particular,
    44 parts of Port Hedland are inundated at HAT before a tsunami has
     44parts of Port Hedland appear to be inundated at HAT before a tsunami has
    4545even been generated.
    4646This is due to
  • production/pt_hedland_2006/report/execsum.tex

    r3375 r3394  
    1111threat and develop detailed response plans for a range of plausible events.
    1212
    13 This report describes the modelling methodology and the results
     13This report describes the modelling methodology and first results
    1414for a particular tsunami-genic event as it impacts the Port Hedland township
    1515and its surrounds. Future studies
  • production/pt_hedland_2006/report/modelling_methodology.tex

    r3375 r3394  
    1 GA bases its risk modelling on the process of understanding the hazard and a community's
    2 vulnerability in order to determine the impact of a particular hazard event.
    3 The resultant risk relies on an assessment of the likelihood of the event.
    4 An overall risk assessment for a particular hazard would then rely on scaling
    5 each event's impact by its likelihood.
     1Geoscience Australia aims to define the economic and social threat posed to urban communities
     2by a range of rapid onset natural hazards. Through the integration of natural hazard research, defining national exposure and
     3estimating socio-economic vulnerabilities, predictions of the likely impacts of events can be made.
     4Hazards include earthquakes, landslides, tsunami, severe winds and cyclones.
     5
     6By modelling the likely impacts on urban communities as accurately as possible and
     7building these estimates into land use planning and emergency
     8management, communities will be better prepared to respond to
     9natural disasters when they occur.
     10
     11
     12%GA bases its risk modelling on the process of understanding the hazard and a community's
     13%vulnerability in order to determine the impact of a particular hazard event.
     14%The resultant risk relies on an assessment of the likelihood of the event.
     15%An overall risk assessment for a particular hazard would then rely on scaling
     16%each event's impact by its likelihood.
    617
    718To develop a tsunami risk assessment,
     
    2536%\cite{somerville:urs} follow this paradigm.
    2637
    27 MOST, which generates and propagates the tsunami wave from its source, is not adequate to
     38While MOST is suitable for generating and propagating the tsunami wave from its source, it is not adequate to
    2839model the wave's impact on communities ashore. 
    2940To capture the \emph{impact} of a tsunami to a coastal community,
     
    3950coastal community, we use ANUGA \cite{ON:modsim}. In order to capture the
    4051details of the wave and its interactions, a much finer resolution is
    41 required than that of the hazard model. As a result, ANUGA concentrates
    42 on a specific coastal community. MOST by contrast uses a
     52required than that of the hazard model. As a result, ANUGA simulations concentrate
     53on specific coastal communities. MOST by contrast uses a
    4354coarser resolution and covers often vast areas. To develop the impact
    4455from an earthquake event from a distant source, we adopt a hybrid approach of
     
    4657In this way, the output from MOST serves as an input to ANUGA.
    4758In modelling terms, the MOST output is a boundary condition for ANUGA.
    48  
     59
     60\bigskip %FIXME (Ole): Should this be a subsection even?
    4961The risk of the scenario tsunami event cannot be determined until the
    5062likelihood of the event is known. GA is currently building a
     
    97109%\end{figure}
    98110   
     111
     112
     113
    99114 
     115
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