Theodoros E Karakasidis

Theodoros E Karakasidis
University of Thessaly | UTH · Department of Physics

PhD
Materials Modeling (DFT, Molecular Dynamics, DPD, SPH, CFD). Machine learing and data analytics, time series analysis

About

145
Publications
17,024
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Introduction
Director of Comphylab whose members have long experience in Materials Modeling from the atomic scale (DFT, Molecular Dynamics) to meso scale (DPD and SPH) to macroscale (CFD) and a wide range of materials both solids and fluids. They also have expertise in data analysis and machine learning for the analysis of data from simulation, experiments and field measurement both for online and offline detection, classification, identification and property prediction.

Publications

Publications (145)
Article
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The invention of carbon nanotubes (CNT) has a wide range of industrial and medical applications. The notion of boundary layer flow is used in medicine, particularly in nanomedicine, and the use of magnetic fields is used to treat cancer tumour growth. The governing PDEs are altered into ODEs with the help of suitable transformations. The mass trans...
Article
Symbolic regression (SR) techniques are constantly gaining ground in materials informatics, as the machine learning counterpart capable of providing analytical equations exclusively derived from data. When the feature space is unknown, unsupervised learning is incorporated to discover and explore hidden connections between data points and may sugge...
Article
The ability of heavy metals to accumulate in living organisms, combined with the fact that they are not biodegradable, necessitates an expansion and improvement of the existing water purification methods. An effective mixing of contaminated water with heavy metals and magnetic nanoparticles is crucial for water treatment applications. In the presen...
Article
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The present analysis addresses the impact of reduced gravity and magnetohydrodynamics on oscillating mixed-convective electricallyconducting fluid flow over a thermal, non-conducting horizontal circular cylinder. In reduced gravity, buoyancy forces may induce fluid motion due to a weak gravitational field but in non-gravity forces, fluid motion can...
Article
Background and objective: Serious side effects are occurred during the cancer therapy. Magnetic driving of nanoparticles is a novel method for the elimination of these effects by supplying with anticancer drug or increase the temperature of the infected area. For this reason, a numerical model for optimal guidance of nanoparticles, through the gra...
Article
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Computational methods in fluid research have been progressing during the past few years, driven by the incorporation of massive amounts of data, either in textual or graphical form, generated from multi-scale simulations, laboratory experiments, and real data from the field. Artificial Intelligence (AI) and its adjacent field, Machine Learning (ML)...
Article
In the present work, the response of peak positions in Linearly Modulated Optically Stimulated Luminescence (LM-OSL) curves as a function of physical and technical parameters were investigated and compared theoretically; specifically, the time or temperature values (tm,Tm) of their maximum intensity (Im). The stimulation modes of Thermoluminescence...
Article
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This work incorporates symbolic regression to propose simple and accurate expressions that fit to material datasets. The incorporation of symbolic regression in physical sciences opens the way to replace “black-box” machine learning techniques with representations that carry the physical meaning and can reveal the underlying mechanism in a purely d...
Article
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Molecular dynamics simulations are employed to estimate the effect of nanopore size, wall wettability, and the external field strength on successful ion removal from water solutions. It is demonstrated that the presence of ions, along with the additive effect of an external electric field, constitute a multivariate environment that affect fluidic i...
Article
Understanding the underlying processes and extracting detailed characteristics of rivers is critical and has not yet been fully developed. The purpose of this study was to examine the performance of non-linear time series methods on environmental data. Specifically, we performed an analysis of water level measurements, extracted from sensors, locat...
Article
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Research on contamination of groundwater and drinking water is of major importance. Due to the rapid and significant progress in the last decade in nanotechnology and its potential applications to water purification, such as adsorption of heavy metal ion from contaminated water, a wide number of articles have been published. An evaluating frame of...
Article
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In this paper, a novel combination of deep learning recurrent neural network and Lyapunov time is proposed to forecast the consumption of electricity load, in Greece, in normal/abrupt change value areas. Our method verifies the chaotic behavior of load time series through chaos time series analysis and with the application of deep learning recurren...
Article
Upfront bubble detection is one of the holy grails in Financial Markets. In the present paper, in order to archive this goal, we consider two different methods based on the Log Periodic Power Law. We implement this early detection algorithms in the Greek Stock Market, which is a relatively “shallow” and underdeveloped market. We have examined a per...
Chapter
Being spatio-temporal variations of urban road traffic a critical information for understanding and predicting accurately traffic, the current paper focuses on urban road traffic dynamics understanding by introducing the notion of causality. Using 15-min aggregated travel time series from taxi GPS data, causal networks are developed. The results re...
Article
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The sensor-era has brought rapid changes in transportation; the abundance of data has started changing the traditional way in which planners and engineers approach mobility. Nowadays, traffic monitoring and information provision systems heavily rely on floating car data usually of special vehicles (e.g., trucks, taxi), and the question that arises...
Article
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This work incorporates machine learning (ML) techniques, such as multivariate regression, the multi-layer perceptron, and random forest to predict the slip length at the nanoscale. Data points are collected both from our simulation data and data from the literature, and comprise Molecular Dynamics simulations of simple monoatomic, polar, and molecu...
Article
Introduction: Vehicular accidents at horizontal curves are over-represented compared to accidents that occur at tangent sections. Investigations have been conducted aimed at identifying the major causes that result in higher accident risk, both in terms of severity and rate, at curved road sections. Excessive or abrupt changes in speeding and impr...
Article
Velocity time series of hydrodynamic and magnetohydrodynamic (MHD) turbulent flow are analyzed by means of complex network analysis in order to understand the mechanism of fluid patterns modification due to the external magnetic field. Direct numerical simulations of two cases are used, one for the plane hydrodynamic turbulent channel flow at the l...
Article
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The growth of two Staphylococcus epidermidis isolates (one biofilm-forming and one not) on teatcups for cattle (made of rubber) or sheep (made of silicone) were assessed in nine multiplicates for 24 h post-smearing on the teatcup surface. Staphylococci were smeared on an area of 0.0003142 m2 on the material and their growth and expansion further on...
Article
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A computational method for optimum magnetic navigation of nanoparticles that are coated with anticancer drug inside the human vascular system is presented in this study. For this reason a 3D carotid model is employed. The present model use Computational Fluid Dynamics ( CFD ) and Discrete Element Method ( DEM ) techniques along with Covariance Matr...
Article
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Simulations of fluid flows at the nanoscale feature massive data production and machine learning (ML) techniques have been developed during recent years to leverage them, presenting unique results. This work facilitates ML tools to provide an insight on properties among molecular dynamics (MD) simulations, covering missing data points and predictin...
Chapter
Urban traffic is undoubtedly a dynamic phenomenon presenting variations over both time and space, that in the majority of cases are the result of a mixture of, either well known (i.e. weather, seasonality) or not easily predictable (i.e. events, accidents) external factors. Identification of similarities in the performance of different urban road p...
Article
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The present paper employs Molecular Dynamics (MD) simulations to reveal nanoscale ion separation from water/ion flows under an external electric field in Poiseuille-like nanochannels. Ions are drifted to the sidewalls due to the effect of wall-normal applied electric fields while flowing inside the channel. Fresh water is obtained from the channel...
Article
Background and objective In-vivo MRI-guided drug delivery concept is a personalized technique towards cancer treatment. A major bottleneck of this method, is the weak magnetic response of nanoparticles. A crucial improvement is the usage of paramagnetic nanoparticles aggregates since they can easier manipulated in human arteries than isolated parti...
Conference Paper
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Effective mixing between contaminated water and nanoparticles is of great importance in various purification applications of microfluidics, especially when heavy metals are involved. Electromagnetic and shear mixing is combined here to explore optimization mixing strategies. A contaminated water stream is confined between two fresh-water streams lo...
Article
The combination of nanotechnology and microfluidics may offer an effective water and wastewater treatment. A novel approach combines the use of magnetic particles which can capture heavy metal impurities in microfluidic ducts. The purpose of this study is to investigate the mixing mechanism of two water streams, one with magnetic particles and the...
Article
In this work, a topological criterion is proposed for selecting a recurrence threshold for constructing a recurrence plot of a time series. It is based on a metric structure of the set of the recurrence plots that is defined by the recurrence plot deviation distance among recurrence plots, introduced in a previous paper by the authors. In this proc...
Article
Renewable energy sources, where wind energy is an important part, are increasingly participating in developing economies and environmental benefits. Wind power is strongly dependent on wind velocity and thus identifying patterns in wind speed data is an important issue for forecasting the generated power from a wind turbine and it has significant i...
Article
Removal of undesired substances from water is a field of investigation recently focused at the nanoscale. Towards this direction, molecular dynamics simulations are conducted in this paper to investigate unwanted ion removal in nanochannel flows. The simulation method incorporates a Poiseuille-like water/ion flow system at the nanoscale where an el...
Article
We present Recurrence Plots (RPs) and Recurrence Quantification Analysis (RQA) of time series of velocities in a low-Reynolds-number magnetohydrodynamic turbulent channel flow. The flow was simulated using a fully spectral code with Fourier and Chebyshev decomposition in the periodic and wall bounded directions, respectively. Direct numerical simul...
Article
Full-text available
Water quality problems are a persistent global issue since population growth has continually stressed hydrological resources. Heavy metals released into the environment from plating plants, mining, and alloy manufacturing pose a significant threat to the public health. A possible solution for water purification from heavy metals is to capture them...
Book
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ICDSST – the International Conference on Decision Support System Technology – is the flagship event of the Euro Working Group of Decision Support Systems (EWG-DSS). The ICDSST series of conference is relatively young and vibrant (since 2015), while its predecessor, including EWG-DSS workshops and summer schools, has a long tradition. The EWG-DSS wa...
Chapter
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The great abundance of multi-sensor traffic data (traditional traffic data sources - loops, cameras and radars accompanied or even replaced by the most recent - Bluetooth detectors, GPS enabled floating car data) although offering the chance to exploit Big Data advantages in traffic planning, management and monitoring, has also opened the debate on...
Article
In the present paper, a topological classification of recurrence plots of time series that are constructed with equal embedding dimension and delay time is proposed by defining a metric structure in the set of those recurrence plots. To achieve this, the Recurrence Plot deviation distance and the Recurrence deviation plot are introduced along with...
Article
The influence of permanent constant magnetic fields on the paramagnetic nanoparticles motion is analyzed in this study. The numerical model is developed in the OpenFOAM® platform and includes all major forces acting on particles. The model combines Navier Stokes equations for a liquid and Lagrangian kinematics for the nanoparticles and can predict...
Article
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Water flow simulations play a key role in determining how fluid properties are affected due to geometrical and flow conditions, establishing a theoretical basis so as to guide technological applications of nanofluidics for desalination and water purification. In this work, we investigate liquid water properties when downsizing a Poiseuille-flow sys...
Article
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A possible solution for water purification from heavy metals is to capture them by using nanoparticles in microfluidic ducts. In this technique, heavy metal capture is achieved by effectively mixing two streams, a nanoparticle solution and the contaminated water. In the present work, particles and water mixing is numerically studied for various inl...
Article
In this study, we present results of the application of nonlinear time series analysis on traffic data for incident detection. More specifically, we analyze daily volume records of Attica Tollway (Greece) collected from sensors located at various locations. The analysis was performed using the Recurrence Plot (RP) and Recurrence Quantification Anal...
Article
Understanding the underlying processes and extracting detailed characteristics of spatiotemporal dynamics of ocean and atmosphere as well as their interaction is of significant interest and has not been well thoroughly established. The purpose of this study was to examine the performance of two main additional methodologies for the identification o...
Article
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The use of spherical magnetic nanoparticles that are coated with drugs and can be navigated in arteries to attack tumors is proposed as an alternative to chemotherapy. Navigation of particles is due to magnetic field gradients that may be produced in an MRI device. In the present work, a computational study for the evaluation of the magnitude of th...
Article
A modification of the Darcy-Weisbach friction factor applicable to nanoscale liquid transport processes is proposed. Non-equilibrium molecular dynamics simulations allow us to access the atomic behaviour of liquids moving in nanochannels, and by comparing atomistic simulation results with continuum Navier-Stokes solutions, we extend the applicabili...
Article
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The present special issue of Fresenius Environmental Bulletin contains selected manuscripts that were initially presented at the 12th International Conference on Protection & Restoration of the Environment (PRE12) that took place on the Greek island of Skiathos, from June 29 to July 3, 2014. The Conference was organized by the Department of Civil E...
Article
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The use of magnetic nanoparticles for cleaning potable water from heavy metals is a novel technique. Suitable magnetic fields are imposed in order to separate magnetic nanoparticles from the water main stream. A numerical methodology that combines computational fluid dynamics and evolution strategy techniques for the optimum magnetic navigation of...
Article
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The usage of magnetic spherical nanoparticles, coated with substances and driven to targeted areas in tanks, is proposed for cleaning the water from heavy metals. In the present paper, a computational study for the estimation of the optimum gradient magnetic field is presented in order to ensure the optimum driving of the particles into the targete...
Article
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This contribution addresses a possible solution for water purification from heavy metals by magnetic nanoparticles in microfluidic water flow systems. In this technique, the most important component is the micromixer while efficient mixing and particle driving is achieved by external magnetic fields. For the simulation of water flow and nanoparticl...
Article
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Non-equilibrium molecular dynamics simulations are employed in order to access the detailed atomic behavior of fluids moving in nanochannels and to quantify the associated energy dissipation. Nanochannels of various degrees of wall hydrophobicity/hydrophilicity and roughness are studied. Dimensional arguments that include the role of the atomistic...
Article
A number of recent studies strongly suggest that nanostructured materials, such as carbon nanotubes, nanoporous graphene, and zeolites, can form the basis for the fabrication of next generation membranes for reverse osmosis desalination. In the present work, we investigate the influence of the wall roughness and external driving force on the flow p...
Chapter
Countless research has been conducted during the last decades aiming to investigate the relationship between driver behavior and road features. The majority of the research is focused on passenger car speed, even though other modes of transport, for instance motorcycles, may be differently affected. In most of the cases researchers used pneumatic r...
Article
Bioinformatics is a relatively new discipline where Mathematics are applied in the analysis of genetic sequences. The analysis of the genetic material of living organisms which consist of nucleic acids DNA and RNA is of great importance for diagnosis and taxonomy reasons. In the present paper we propose a new methodology for the representation of g...
Article
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In the present study, we analyzed meteorological observations from Seawatch buoys in the Mediterranean Sea and specifically from locations in the Aegean and Ionian Sea. The data were collected from buoys that have been deployed by the Hellenic Center for Marine Research (HCMR) in the framework of the POSEIDON project. Our aim was to understand the...
Article
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In the present study, the direct numerical simulation of the turbulent flow of an electrically conductive fluid in a channel is performed and time series are recorded at a range of locations along the y-direction between the parallel plates of the channel. An external streamwise magnetic field is applied and the correlations between pairs of time s...
Article
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We present molecular dynamics simulation results on fluid and transport properties for nanochannel flows. The upper channel wall is constructed from periodic roughness elements and flows are simulated both in longitudinal (ribs) and transverse (grooves) direction and are compared to respective flat-wall channel flows. Various wall/fluid interaction...
Article
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Nanofluidic applications are currently being investigated in use for water treatment systems as a power efficient and effective means of removing undesirable substances from drinking or sea water. A detailed study of liquid nanoflows, in both simulation and experimental systems, is a prerequisite for establishing the theory and guiding the technolo...
Article
Based on the boundary scanning method, a partition of the boundary of the Mandelbrot set is defined. The various classes of points of the boundary according to their divergence from the interior and the exterior of the Mandelbrot set are discussed. Then, numerical invariants of its structure under increase in the lattice resolution and the number o...
Article
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We present a quasi-continuum self-diffusion theory that can capture the ordering effects and the density variations that are predicted by non-equilibrium molecular dynamics (NEMD) in nanochannel flows. A number of properties that affect fluid ordering in NEMD simulations are extracted and compared with the quasi-continuum predictions. The proposed...
Article
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Objective The present paper focuses on the investigation of motorcycle riders’ behavior at curved road sections by introducing a new methodology based on global positioning system (GPS) technology. In the frame of the research, the determination of the optimum regression curve between the curve radius’ and the corresponding velocities, was investi...
Conference Paper
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Slip at solid walls can play an important role on flow properties especially as we go from macro to nano-scale. In the present work we investigate the effect of the external driving force and surface roughness on the slip velocity aiming to achieve a better understanding of the momentum transfer at nano-and microscale flows. The investigation is ba...
Article
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In the present study, we applied the methodology of the complex network-based time series analysis to experimental temperature time series from a vertical turbulent heated jet. More specifically, we approach the hydrodynamic problem of discriminating time series corresponding to various regions relative to the jet axis, i.e., time series correspond...
Article
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In the present work we approach the hydrodynamic problem of discriminating the state of the turbulent fluid region as a function of the distance from the axis of a turbulent jet axis. More specifically, we analyzed temperature fluctuations in vertical turbulent heated jets where temperature time series were recorded along a horizontal line through...
Article
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The study of genetic sequences is of great importance in biology and medicine. Sequence analysis and taxonomy are two major fields of application of bioinformatics. In this survey, we present results concerning genetic sequences and Chou's pseudo amino acid composition as well as methodologies developed based on this concept along with elements of...