Centre for Computational Sciences and Intelligence (CSI) is an autono
mous research
organization with the aim
to c
onduct research and provides
modeling and computational support
to the other interested organizations.
We are in the age in which to perform experiments directly again and again to get the good
results becomes too costly.
Even if we somehow manage to perform experiment then it results
huge amount of data, which too cannot be solved without the involvement o
f computer or
computational techniques.
For this
, in the recent decades, in every
branch of science
s
, researcher
are using computer as a tool to perform experiments in the form of computer simulation with the
help of different programming languages. Throug
h this they all are designing computational
models for
different problems of
their domains. In the areas of computational science, like
computational physics (CP),
Neuroscience,
material sciences, computational fluid dynamics
,
reduced order modeling (ROM),
computational biology (or bioinformatics), computational
chemistry, and in the areas of Nano

technology, Nano

medicine
and robotics/quantum
consciousness
, researchers are using high performance computing (HPC) techniques for the
parallel solution of their
respective complex problems.
For the parallel solutions,
In the recent
years there has been seen a paradigm shift from traditional high performance computing
techniques to modern high performance computing techniques such as graphical processing unit
(GPU
).
CSI mainly focus on the application of computational and intelligent techniqu
es in different
areas of sciences
,
and
Quantum aspect of machine intelligence.
The focused areas
of C
S
I
are
Computational Fluid Dynamics
Molecular Dynamics
Quantum Artificial
Intelligence and Machine Consciousness
Image Processing
Techniq
ues for Parallel and Distributed
Computing
Computational Analysis of Seismic data
Computational Geometry and Mesh Generation
1. COMPUTATIONAL FLUID DYNAMICS
CFD is a cost effective means of
simulating real flows by numerical solution of the governing
equations. The development of the reduced form of Navier

stokes equations (Equations for
Newtonian fluid dynamics) is an active area of research, in particular, the turbulent closure
problem of
the Reynold’s

averged Navier

stokes equations.
Computational techniques replace the governing partial differential equations with system of
algebraic equations that are much easier to solve using computers. It also allow for testing of
conditions which are
not possible or extremely difficult to measure experimentally and are not
amendable to analytic solutions. The purpose of a flow simulation is to find out how the flow
behaves in a given system for a given set of inlet and outlet conditions to find the va
lues of the
flow quantities at a large number of points in the system. These points are usually connected
together in a mesh.
CFD methods offer more complete set of information as compare to experimental procedures.
They usually provide all relevant flow i
nformation throughout the domains of interest. Following
are the areas of the applications, where CFD is actively used;
Aerospace
Automotive
Industrial
Biomedical
2. Molecular Dynamics
Molecular dynamics allows the user to determine three fundamental
items of interest of a
molecule or system of molecules,
Structure
, or geometry of the molecule
Property
or properties of a molecule or system of molecules
Activity
, or reactivity, of a molecule or system of molecules
These determinations can be undertaken
to validate experimental studies, or can be carried out to
predict experimental results. With increased sophistication of the technologies, molecular
modeling can be used to reduce dependence on wet, or traditional, chemical experimental
procedures.
In usi
ng molecular modeling techniques and tools, modelers can calculate structure, properties,
and/or activities.
The list below provides a
partial
list of the types of calculations that can be
performed:
Single poin
t energies (molecular energies)
Molecular
orbital calculations, including det
ermination of frontier orbital.
Vib
rational frequency calculations
Reaction mechanisms and reaction pat
h following studies
Determin
ation of IR and UV

Vis spectra
Transition structures and activation energy diagrams
El
ectr
on and charge distributions
Potential energy surfaces (PES)
Thermodynamic calculations
3.
Image Processing
In this group different reduced order modeling techniques are being developed and simulated to
reduce the size of the image for different area such a
s CFD, Aeronautics, Computer vision and
satellite system etc.
The goal of Reduced Order Modeling is to find a low

dimensional
approximation for a system of ordinary differential equations (ODEs). The main idea is that a
high

dimensional state vector actually belongs to a low

dimensional subspace, Provided that the
lo
w

dimensional subspace is known, and the ordinary differential equations can be projected on
it.
Reduced Order Modeling (ROM) studies properties of dynamical systems in application for
reducing their complexity, while preserving (to the possible extent) their input

output behavior.
This problem applies both to continuous

time and discrete

time systems
. Reduced Order
Modeling
is an active research domain among many seemingly desperate fields.
4. Computational Geometry & Mesh Generation
Geometric modeling deal with the mathematical representation of curves, surfaces, and solids
necessary in the definitio
n of complex physical or engineering objects. The development,
analysis, and computer implementation of algorithms are also encountered in geometric
modeling. Geometric modeling attempts to provide a complete, flexible, and unambiguous
representation of th
e object. Typically, engineers deal with the definition of complex shapes such
as engines, automobiles, aircraft, ships, submarines, underwater robots, offshore platforms, etc.
The shape of these objects is usually not fully known in advance (except when a
baseline design
is available).
The mesh generation is rooted in doing computer simulations of physical systems. In order to
simulate a continuous physical domain, it has to be
discretized
in such a way that meaningful
results can be obtained by applying
mathematical techniques). The numerical solution of partial
differential equations requires some discretization of the field into a collection of points or
elemental volumes (cells). A numerically

generated mesh is the organized set of points formed
by th
e intersections of the lines of a boundary

conforming a certain coordinate system. All
computations are to be done on a fixed square mesh when the partial differential equations of
interest have been transformed.
Mesh generation is a critical step in comp
uter simulation, because the elements of the mesh and
the size of the mesh determine the numerical properties of the
outcome and the
running time of
the simulation.
Quantum Artificial Intelligence and Machine Consciousness
Human brain fundamentally proce
ss information quantum mechanically. All the phenomenon of
brain like intelligence, consciousness, emotions, etc. are due to the processing of brain. The
focus of artificial intelligence is to replicate the intelligence in machine. The techniques of
artifi
cial intelligence are based on classical physics.
Quantum artificial intelligence is an area of study whose aim is to develop intelligent techniques
on the principle of quantum mechanics. Focus of quantum artificial intelligence and machine
consciousness g
roup is to develop state of the art algorithm for quantum artificial intelligence.
The research conducting in this group mainly covers the following topic
Quantum Neural Networks
Quantum Genetic Algorithms
Quantum Evolutionary Computing
Quantum Cognition
Quantum machine consciousness
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