Cellular Automata BIORemediation system

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Cellular Automata BIORemediation system


M.C.Baracca, P. Ornelli, G.Clai

E
-
mail: baracca@bologna.enea.it

E
-
mail: ornelli@bologna.enea.it

ENEA HPCN

Via Martiri di Montesole 4

40129
-
Bologna, ITALY


Abstract



We present the CABIOR system developed on SGI O
nyx2 for an application
of parallel computing to the simulation of the bioremediation interventions on
polluted soils. The CABIOR system is devoted to the needs of the
bioremediation user which generally is not skilled enough in modelling or in
computer s
cience, so it has been designed in order to hide as many
computational technical details as possible and at the same time to provide
advanced features to analyze and to test the model outcome.


1

Introduction



The CABIOR system has been developed on SGI

Onyx2 platform by ENEA in
the framework of the Esprit HPCN COLOMBO project coordinated by CRA
Montecatini.


The main objective of this two
-
years collaborative Project was the application of
parallel computing to the simulation of the
in situ

bioremed
iation of contaminated
soils: a three layers (fluid
-
dynamic, chemical, biological) bioremediation CA based
model, including three phases (water, pollutant, air), has been implemented and
tested both on pilot plants and real fields [1]. The theory of CA len
ds itself well to
the bioremediation simulation. The automaton is related to a finite three
-
dimensional
space and consists of a number of cells. Each cell is associates with a set of
neighbouring cells. All cells contain a set of qualities, which are known

as its
substates. For example, each cell has a substate defining it as a piece of ground ( as
opposed to being a well ) and others substates indicating its porosity, its depth from
the surface, its water content and so on. The cells are assumed to intera
ct to the
neighbours through a specified rule that decides the state of each cell in the next
time
-
step based on the current state of the cell in question and that of its neighbours.
Bacteria and pollutants interact gradually over time and only within thei
r
neighbourhood area. This locality feature also benefits parallel programming since
one can decompose the model and map the components to cooperating computing
processors with relative easy and acceptable communication overhead. Moreover the
flow of the s
imulation could be affected by a computational steering mechanism
which controls particular cell substates values on regions of the model. From the SW
point of view, the Project has achieved these results:

-

the CAMELot environment (built on MPI) used by the

modelists for
developing, executing in parallel and monitoring CA
-
based models [2,4];

-

the CABIOR system providing a graphical interfaces for computational
features and complex data visualization, portable across various platforms [3].


2 CABIOR Overvie
w



The CABIOR system is taylored on the needs of the bioremediation user which
generally is not skilled enough in modelling or in computer science, so it has been
designed in order to hide as many computational technical details as possible and at
the

same time to provide advanced features to analyze and to test the model
outcome. It has been developed by means of AVS/Express [5], a commercial
visualization package, portable across several platforms of industrial interest, that
provides the graphical p
rimitives allowing a sophisticated data visualization. Since
at the beginning of the current year the AVS/Express version for LINUX platform
was released, the CABIOR application has been succesfully ported by ENEA on the
end
-
user PC cluster.


The CABIO
R system consists in a graphical environment allowing to enter the
pre
-
processing and post
-
processing facilities as well as to run the batch simulation
and the parameters optimization algorithms.



Fig
1
: CABIOR Main Window


In t
he following sections the features and the functionalities provided by the
CABIOR system are briefly summarized. More detailed information can be found at
the web site: http://eboals.bologna.enea.it/colombo.


3 Pre
-
processing tool



The graphical pr
e
-
processing tool assists the user during the preparation of input
data since it allows the visualization, while editing, of the binary data files required
by the CA
-
based model simulating the bioremediation intervention. The input data
files are of two d
ifferent kinds: one describing the general automaton characteristcs
and several other files representing the automaton substates, that is the variables
defining the state of each cell.


The general characteristics of the automaton can be set or modi
fy by means of
the General Parameters Menu while the Parameters Set Menus allow the separated
input of the simulation parameters referred to each of the specific bioremediation
layers.




Fig
2
: Automaton General Parameters Menu




Pressing the Edit.cmt button, a further panel (Fig.3) opens for the editing of
1/2/3D automaton substates with the possibility to combine a random or constant
initialization of the cell values with the single cell value setting, in order to easily
initi
alize homogeneous cells arrays and discontinuities like surfaces, lateral walls,
injection and extraction wells. Relevant to the user is the panel capability to show
the numerical cell values of a chosen automaton plane simultaneously with its
discrete vis
ualization according to the colormap at the bottom of the window.





Fig
3
: Substates Editor





4 Simulation tool



The aim is to allow the end
-
user to start the bioremediation parallel simulation
in batch mode and to pro
duce the periodic outputs which could be visualized
subsequently by means of the post
-
processing tool.


The related window simply requires the user to choose the input files following
the CAMELot files name convention, the output files name and the nu
mber of
processes to handle the task, while hiding the practical issues to obtain the
executable and then run it on the underlying parallel architecture.




5 Optimization tool



In the model there are some parameters which cannot be directly deter
mined, so
that their values will be adjusted by comparing the model outcome with a set of
experimental data.


The basic idea is that it is possible to tune these parameters using experimental
data resulting from small scale tests, and that they could b
e succesfully applied on a
much larger scale simulation.


Fig
4
: Parameters Tuning


The optimization procedure applied to bioremediation simulation results,
interacts with the simulation code as sketched below


Fig
5
: Optimization Overview


The optimization sequence panels permit to choose the optimization technique
(Genetic Algorithm or Simulated Annealing), to turn on the model parameters
suitable for optimization, to set the parameters required by the

method itself, to input
the experimental data file and finally to run the optimization procedure.





Fig
6
:

Simulated Annealing Settings Window


6 Post
-
processing tool



The aim of the post
-
processing 3D visualization is to pe
rform a detailed analysis
of the data gathered during the simulation in order to obtain meaningful insights into
simulation results. Using this tool, a bioremediation user may analyze, study and
discover useful features and numerical results that cannot be

discovered during the
simulation.
Its main features can be summarized as follows:

-

to visualize 3D data sets in a 3 dimensional space, using different geometrical
modalities like orthoslices, isosurfaces, isovolumes and volumes of cells whose
values range
in a chosen interval (Bounded volume feature);

-

to rotate, to translate, to scale and to zoom the picture;

-

to show the substate value and the coordinates of a single cell simply clicking
on the image in the Visualization space (Probe feature);

-

to visualize
vectorial fields;

-

to visualize the temporal evolution of a substate, according to a chosen
geometrical modality, using a sequence of snapshots taken during the
simulation at different steps.


The user can activate or deactivate the geometrical visualiz
ation modalities and
the implemented feature addressed in the Select Visibility panel of the Manage
Visibility module simply clicking on the toggles.





Fig
7
:

Orthoslices and Probe feature




In Fig.7 the 3D matrix values rela
ted to pollutant pression substate are
represented by means of three orthoslices and the value of the cell selected by the
mouse is shown.


The isosurface modality creates a surface of a given constant value level in the
selected substate. The isosurf
ace feature provides a graphic depiction of the
locations of a particular data value in a 3D field. Moreover, the isosurface modality
(Fig.8) has been improved adding the opportunity to map on a substate isosurface
the values of another substate of the aut
omaton, in order to give evidence to related
cell qualities.





Fig
8
:

Example of oil potential isosurface with porosity cell values mapped on



The aim of the isovolume module (Fig.9) is to display the interpolated volume of
th
e cells whose values are greater or less than a specified level: the input mesh of the
selected substate is cut using the isolevel value set by means of the slider in the
panel. The Above toggle turned on, means that the output values are greater than
t
he cut level.


Fig
9
: Isovolume


Fig
10
:

Example of vectorial field: water flux superposed to water potential




Vectorial fields visualization has been included in order to show in an effective
way the sub
states related to the phase fluxes. The vector field is visualised by
arrows representing the flux direction while the module is mapped within a
suitable chosen color scale. In Fig.10, a more significant visualization has been
obtained by means of the
superposition of a phase substate and its relative flux as a
vector field: in the example the water flux is superposed on the water potential
substate.


The visualization of the temporal evolution of substates, using a sequence of
snapshots taken dur
ing the simulation at different steps has been implemented too.
The animation may be performed for each one of the supplied geometrical modality,
as well as for the vector fields visualization.



5

Conclusions



The CABIOR System has been accomplished
taking into account the end
-
user
requirements, the portability demand across various platforms, including PC cluster,
and the need of an easy
-
to
-
use interface. This graphical tool allows the flexible and
user friendly input of the data required by the bior
emediation model, the setting and
the execution of the optimization procedures and the accurate analysis of the
bioremediation simulation outcame.







References


1.

M.Villani, M.Mazzanti, R.Serra, M.Andretta, S.Di Gregorio "Simulation model
implementation
description", Deliverable D11 of COLOMBO Project, July 1999.

2.

S.D.Telford, G.Smith, M.C.Baracca, A.Longo, P.Ornelli, G.Spezzano, D.Talia " Design
for Portable, Parallel CA Software Environment", Deliverable D6 of COLOMBO Project,
May 1998.

3.

M.C.Baracca, P.O
rnelli, G.Spezzano, D.Talia "Functional Requirements and Software
Package Design", Deliverable D10 of COLOMBO Project, November 1998.

4.

K.Kavoussanakis, S.D.Telford, S.Booth, L.Clarke, G.Smith, A.Trew, A.Simpson,
G.Spezzano, D.Talia "CAMELot Implementation a
nd User Guide", Deliverable D9 of
COLOMBO Project, May 2000.

5.

Advanced Visual System Inc. "Using AVS/Express", July 1998.