My research activity focuses on two areas:

- Computer models of reality.
- Pattern recognition and knowledge extraction.

These two subjects are tightly coupled. On the one hand, the modeling is associated with sophisticated mental and computational processes involving observations, hypotheses, rules, computer programs and computer systems. On the other hand, pattern recognition methods facilitate the processes of observations and hypotheses generation. They allow extracting relevant information from raw data, and transform it into the form of spatio-temporal patterns, which can be perceived by a human. Multi-scale nature of the real world, and thus multi-dimensional and multi-resolutional character of patterns it creates, involves construction of new methodological and computational tools both for modeling and for pattern recognition purposes. My work concentrates on discrete particle systems, as a common methodological basis for developing such the tools [1,2].

In [3] we (me, and my friend Professor Dr Dave Yuen from University of Minnesota) discuss the principles of multi-scale homogeneous computational model based on gridless discrete-particle methods. Within the context of cross-scaling systems, the particle model is homogeneous with both microscopic molecular dynamics (MD) and macroscopic smoothed particle hydrodynamics (SPH) techniques. The large-scale NEMD (non-equilibrium molecular dynamics) is situated on the bottom of this model. As shown, e.g., in [4] NEMD can bridge time scales dictated by fast modes of motion together with the slower modes, which can capture instabilities in fluid such as the Reyleigh-Taylor mixing. Apart from modeling instabilities in the Lennard-Jones fluid, we dealt also with micro-penetration and crack propagation phenomena employing molecular dynamics.

Unlike atomistic scales, the mesoscopic regimes involving scales of 1 ns and 1 mm entail the fast modes of motion to be eliminated in favor of a coarse grain representation. In the series of publications (for example [5-10]) we investigated two dissipative particle models (classical dissipative particle dynamics and more recent fluid particle model) and two-level MD-DPD model used for modeling colloidal suspensions. We employed our models for simulating thin-film flow evolution [5], R-T instability [6,7], creation of colloidal crystals [8], the growth of colloidal agglomerates [9], eventually; we attacked the problem of modeling the blood flow in micro-capillaries [10]. We show [21] that by using pattern recognition method clustering - we can considerably improve 3-D visualization of the results of modeling by extracting the most interesting features of various resolution such as micelles, arrays of micelles and large agglomerates.

In the nearest feature we plan to simulate larger blood arteries by adapting other discrete particle paradigms, which are more suitable for simulating flows in the macroscopic world. The best particle-based candidates are the smoothed particle hydrodynamics (SPH) and the generic dissipative particle dynamics (thermodynamically consistent DPD) for which the spatio-temporal scale is controlled by the amplitude of the Brownian forces acting between dissipative particles.

My works on modeling of reality concentrates also on discrete particle methods developed for simulation of macroscopic world, which is out of scope of standard methodology from computational physics. Modeling of living organisms [12], evolving populations [13,14], geological phenomena [15], crowd and traffic simulations, involves both off-lattice discrete-particles an on-lattice cellular automata (also the Lattice Bolzmann-Gas), Monte-Carlo methods and genetic algorithms. My recent investigations focus on the influence of infertile periods of life ("youth" and the "old age") for which procreation is limited) on the population evolution in various (hostile) environmental conditions [14,16].

In [1,2,11] I demonstrate that the discrete-particle methodology can be treated as a universal solver. It can be applied as a robust method for constructing animations in computer graphics and to mimic natural phenomena such as various types of flows, cloud formation, sophisticated collisions etc. The particle dynamics codes can be used as a convenient solver for extracting global minimum of multidimensional multi-modal and deceptive functions [20] or for solving problems such as robot path planning [1,2]. I showed also that the discrete-particle paradigm can be applied as an efficient engine in multidimensional-scaling algorithm pattern recognition tool used for the feature extraction - and in visual clustering of multidimensional data [11]. When combined together with modern clustering schemes it becomes invaluable tool for penetrating multidimensional and muti-resolutional data structures in various resolutions [18,19]. Currently I am dealing with developing the knowledge extraction system, which is based on MDS, clustering and visualization of N-dimensional structures. It has been exploited in the analysis of data from geophysical prospecting [20], nuclear reactor control [22], earthquake catalogs [18,19], medical images such as radiograms and as a tool for monitoring evolutionary systems [16].

References

- Dzwinel W, Virtual Particles and Search for Global Minimum, Future Generation Computer Systems, 12, 371-389, 1997.
- Dzwinel W, Alda W, Kitowski J, Yuen DA, Using discrete particles as a natural solver in simulating multiple-scale phenomena, Molecular Simulation, 20/6, 361-384 2000
- Dzwinel W, Alda W, Yuen, DA, Cross-Scale Numerical Simulations Using Discrete-Particle Models, Molecular Simulation, 22, 397-418, 1999.
- Dzwinel W, Alda W, Pogoda M, Yuen DA, Turbulent mixing in the microscale, Physica D, 137, 157-171, 2000.
- Dzwinel W, Yuen DA, Dissipative particle dynamics of the thin-film evolution in mesoscale, Molecular Simulation, 22, 369-395, 1999.
- Dzwinel W, Yuen DA, Rayleigh-Taylor Instability in the Mesoscale Modelled by Dissipative Particle Dynamics , Int. J. Mod Phys.C, 12/1, 91-118, 2001.
- Dzwinel W, Yuen DA, Boryczko K, Mesoscopic Dynamics of Colloids Simulated with Dissipative Particle Dynamics and Fluid Particle Model, J Mol. Modeling, 8, 33-45, 2002.
- Dzwinel W, Yuen DA, A Multi-level Discrete Particle Model in Simulating Ordered Colloidal Structures, J Colloid Int Sci, 225,179-190, 2000.
- Dzwinel W, Yuen DA, Mesoscopic dispersion of colloidal agglomerate in complex fluid modeled by a hybrid fluid particle model, J Colloid Int Sci, 247, 463-480, 2002.
- Dzwinel W, Boryczko K, Yuen DA, A Discrete-Particle Model of Blood Dynamics in Capillary Vessels , J Colloid Int Sci, 258/1, 163-173, 2003
- Dzwinel W, Blasiak J, Method of particles in visual clustering of multi-dimensional and large data sets, Future Generation Computers Systems, 15, 365-379, 1999.
- Krawczyk K, Dzwinel W, Yuen DA, Nonlinear Development of Bacterial Colony Modeled with Cellular Automata and Agent Objects, Int. J. Modern Phys. C, 14/10, 2003
- Broda, A., Dzwinel, W., Spatial Genetic Algorithm and Its Parallel Implementation. Lecture Notes in Computer Science. 1184, 97-106, 1996
- Dzwinel, W., A Cellular Automata Model of Population Infected by Periodic Plaque, Lecture Notes in Computer Science, 3305, 464-473, 2004
- Topa, P., Dzwinel, W., Consuming Environment with Transportation Network Modelled Using Graph of Cellular Automata, Lecture Notes in Computer Science, 3019, 513-520, 2004
- Dzwinel, W., Yuen, D.A, Aging in Hostile Environment Modelled by Cellular Automata and Genetic Algorithms, Int. J. Modern Phys. C, 16(3), 2004 (in press).
- Dzwinel, W., Dzwinel, J., Dzwinel, K., Development of Parallel Applications for MEGA-D - System for Oil and Gas Prospecting. Lecture Notes in Computer Science. 1225, 223-231, 1997
- Dzwinel W, Yuen DA, Kaneko Y, Boryczko K, Ben-Zion Y, Multi-Resolution Clustering Analysis and 3-D Visualization of Multitudinous Synthetic Earthquakes, Visual Geosciences, 8, 12-25, 2003
- Dzwinel W, Yuen DA, Boryczko K, Ben-Zion Y, Yoshika S., Ito T., Cluster analysis and visualization of earthquakes, over space time and feature space, Nonlinear Processes in Geophysics (submitted)
- Dzwinel, W., Particles Paradigm and Optimization Problems. Lecture Notes in Computer Science, 1067, 447-453, 1996
- Boryczko K, Dzwinel W, Yuen DA, Clustering Revealed in High-Resolution Simulations and Visualization of Multi-Resolution Features in Fluid-Particle Models, Concurrency and Computation: Practice and Experience, 15, 101-116, 2003
- Dzwinel W, Pepyolyshev YN, Janiczak K Predicting of slow noise and vibration spectra degradation in the IBR-2 pulsed neutron source using a neural network simulator, Prog Nucl Energ 43 (1-4), 145-150 2003