George Stefanou

Size-Dependent Mechanisms in AC Magnetic Hyperthermia Response of Iron-Oxide Nanoparticles

This paper correlates the magnetic properties of iron-oxide nanoparticles in the size range 5-18 nm with the occurring heating loss mechanisms when magnetic nanoparticle colloidal suspensions are subjected to high-frequency ac magnetic fields. The narrow size distribution of the nanoparticles enabled their clear classification into: 1) the superparamagnetic region (as large as 10 nm) where heating is mainly attributed to Neel relaxation; 2) the intermediate superparamagnetic-ferromagnetic transition region (10-13 nm); and 3) the ferromagnetic region (above 13 nm) where hysteresis losses dominate. The results from specific loss power measurements suggest that for size and concentration optimization, superparamagnetic nanoparticles may release significant amounts of heat to the surroundings, while the hysteresis losses mechanism appears to be much more efficient and the heat transfer provided through may be easier tuned for magnetically driven hyperthermia applications.

Stochastic finite element analysis of shells

In the present paper the stochastic formulation of the triangular composite (TRIC) facet shell element is presented using the weighted integral and local average methods. The elastic modulus of the structure is considered to be a two-dimensional homogeneous stochastic field which is represented via the spectral representation method. As a result of the proposed derivation and the special features of the element, the stochastic stiffness matrix is calculated in terms of a minimum number of random variables of the stochastic field giving a cost-effective stochastic matrix. Under the assumption of a pre-specified power spectral density function of the stochastic field, it is possible to compute the response variability of the shell structure. Numerical tests are provided to demonstrate the applicability of the proposed methodologies.

Computational Methods in Stochastic Dynamics

Preface.- Random Dynamical Response of a Multibody System with Uncertain Rigid Bodies, by Anas Batou and Christian Soize.- Dynamic Variability Response for Stochastic Systems, by Vissarion Papadopoulos and Odysseas Kokkinos.- A Novel Reduced Spectral Function Approach for Finite Element Analysis of Stochastic Dynamical Systems, by Abhishek Kundu and Sondipon Adhikari.- Computational Stochastic Dynamics based on Orthogonal Expansion of Random Excitations, by X. Frank Xu and George Stefanou.- Numerical solution of the Fokker-Planck equation by finite difference and finite element methods - a comparative study, by L. Pichler, A. Masud and L. A. Bergman.- A Comparative study of Uncertainty Propagation Methods in Structural Problems, by Manuele Corradi, Marco Gherlone, Massimiliano Mattone and Marco Di Sciuva.- Fuzzy and fuzzy stochastic methods for the numerical analysis of reinforced concrete structures under dynamical loading, by Frank Steinigen, Jan-Uwe Sickert, Wolfgang Graf and Michael Kaliske.- Application of interval fields for uncertainty modeling in a geohydrological case, by Wim Verhaeghe, Wim Desmet, Dirk Vandepitte, Ingeborg Joris, Piet Seuntjens and David Moens.- Enhanced Monte Carlo for Reliability-Based Design and Calibration, by Arvid Naess, Marc Maes and Marcus R. Dann.- Optimal Design of Base-Isolated Systems under Stochastic Earthquake Excitation, by Hector A. Jensen, Marcos A. Valdebenito and Juan G. Sepulveda.- Systematic formulation of model uncertainties and robust control in smart structures using Hinfinity and mu-analysis, by Amalia Moutsopoulou, Georgios E. Stavroulakis and Anastasios Pouliezos.- Robust Structural Health Monitoring Using a Polynomial Chaos Based Sequential Data Assimilation Technique, by George A. Saad and Roger G. Ghanem.- Efficient model updating of the GOCE satellite based on experimental modal data, by B. Goller, M. Broggi, A. Calvi and G.I. Schueller.- Identification of properties of stochastic elastoplastic systems, by Bojana V. Rosic and Hermann G. Matthies.- SH surface waves in a half space with random heterogeneities, by Chaoliang Du and Xianyue Su.- Structural seismic fragility analysis of RC frame with a new family of Rayleigh damping models, by Pierre Jehel, Pierre Leger and Adnan Ibrahimbegovic.- Incremental dynamic analysis and pushover analysis of buildings: A probabilistic comparison, by Yeudy F. Vargas, Luis G. Pujades, Alex H. Barbat and Jorge E. Hurtado.- Stochastic analysis of the risk of seismic pounding between adjacent buildings, by Enrico Tubaldi and Michele Barbato.- Intensity Parameters as Damage Potential Descriptors of Earthquakes, by Anaxagoras Elenas.- Classification of Seismic Damages in Buildings Using Fuzzy Logic Procedures, by Anaxagoras Elenas, Eleni Vrochidou, Petros Alvanitopoulos and Ioannis Andreadis.- Damage identification of masonry structures under seismic excitation, by G. De Matteis, F. Campitiello, M.G. Masciotta, and M. Vasta.

Tunable AC Magnetic Hyperthermia Efficiency of Ni Ferrite Nanoparticles

Nickel ferrite nanoparticles, with sizes lying within the superparamagnetic ferrimagnetic transition region, were synthesized using the solvothermal and the thermal decomposition method. Iron and nickel precursors as well as a variety of surfactants were used at adequate proportions to achieve structural and morphological, and hence magnetic tuning of the nanoparticles. X-ray diffraction and electron microscopy were used to visualize the actual particle size, morphology, and monodispersity aspects and to verify the obtained crystal structure. The magnetic hyperthermia response of nickel ferrite nanoparticles and the corresponding mechanisms of heating losses are studied in an effort to unravel the interconnections between the physical properties of magnetic nanoparticles and the tunable ac magnetic hyperthermia efficiency.

Buckling load variability of cylindrical shells with stochastic imperfections

In this paper, the effect of random initial geometric, material and thickness imperfections on the buckling load of isotropic cylindrical shells is investigated. To this purpose, a stochastic spatial variability of the elastic modulus as well as of the thickness of the shell is introduced in addition to the random initial geometric deviations of the shell structure from its perfect geometry. The modulus of elasticity and the shell thickness are described by two-dimensional univariate (2D-1V) homogeneous non-Gaussian translation stochastic fields. The initial geometric imperfections are described as a 2D-1V homogeneous Gaussian stochastic field. A numerical example is presented examining the influence of the non-Gaussian assumption on the variability of the buckling load. In addition, useful conclusions are derived concerning the effect of the various marginal probability density functions as well as of the spectral densities of the involved stochastic fields on the buckling behaviour of shells, as a result of a detailed sensitivity analysis.

Sequentially Linear Analysis of Structures with Stochastic Material Properties

This paper investigates the influence of uncertain spatially varying material properties on the fracture behavior of structures with softening materials. Structural failure is modeled using the sequentially linear analysis (SLA) proposed by Rots (Sequentially linear continuum model for concrete fracture. In: de Borst R, Mazars J, Pijaudier-Cabot G, van Mier J (eds) Fracture mechanics of concrete structures. Balkema, Lisse, 2001, pp 831–839), which replaces the incremental nonlinear finite element analysis by a series of scaled linear analyses and the nonlinear stress-strain law by a saw-tooth curve. In this work, SLA is implemented in the framework of a stochastic setting. The proposed approach constitutes an efficient procedure avoiding the convergence problems encountered in regular nonlinear FE analysis. The effect of uncertain material properties (Young’s modulus, tensile strength, fracture energy) on the variability of the load-displacement curves and crack paths is examined. The uncertain properties are described by homogeneous stochastic fields using the spectral representation method in conjunction with translation field theory. The response variability is computed by means of direct Monte Carlo simulation. The influence of the variation of each random parameter as well as of the coefficient of variation and correlation length of the stochastic fields is quantified in a numerical example. It is shown that the load-displacement curves, the crack paths and the failure probability are affected by the statistical characteristics of the stochastic fields.

COMPUTATIONAL STOCHASTIC DYNAMICS BASED ON ORTHOGONAL EXPANSION OF RANDOM EXCITATIONS

A major challenge in stochastic dynamics is to model nonlinear systems subject to general non-Gaussian excitations which are prevalent in realistic engineering problems. In this work, an n-th order convolved orthogonal expansion (COE) method is proposed. For linear vibration systems, the statistics of the output can be directly obtained as the first-order COE about the underlying Gaussian process. The COE method is next verified by its application on a weakly nonlinear oscillator. In dealing with strongly nonlinear dynamics problems, a variational method is presented by formulating a convolution-type action and using the COE representation as trial functions.

Nonlinear Dynamic Response Variability and Reliability of Frames with Stochastic Non-Gaussian Parameters

Current research efforts for the efficient prediction of the dynamic response of structures with parameter uncertainty concentrate on the development of new and the improvement of existing methods. However, they are usually limited to linear elastic analysis considering only monotonic loading. In order to investigate realistic problems of structures subjected to transient seismic actions, a novel approach has been recently introduced by the authors. This approach is used here to assess the nonlinear stochastic response and reliability of a three-storey steel moment-resisting frame in the framework of Monte Carlo simulation (MCS) and translation process theory. The structure is modeled with a mixed fiber-based, beam-column element, whose kinematics is based on the natural mode method. The adopted formulation leads to the reduction of the computational cost required for the calculation of the element stiffness matrix, while increased accuracy compared to traditional displacement-based elements is achieved. The uncertain parameters of the problem are the Young modulus and the yield stress, both described by homogeneous non-Gaussian translation stochastic fields that vary along the element. The frame is subjected to natural seismic records that correspond to three levels of increasing seismic intensity. Under the assumption of a pre-specified power spectral density function of the stochastic fields that describe the two uncertain parameters, the response variability of the frame is computed using MCS. Moreover, a parametric investigation is carried out providing useful conclusions regarding the influence of the correlation length of the stochastic fields on the response variability and reliability of the frame.

STOCHASTIC RESPONSE OF NONLINEAR BASE ISOLATION SYSTEMS

A hybrid base isolation system was used to retrofit two residential buildings in Solarino, Sicily. Subsequently, five free vibration tests were carried out in one of these buildings to assess its functionality. The hybrid base isolation system combined high damping rubber bearings with low friction sliders. In terms of numerical modeling, a single-degree-of-freedom system is used here with a new five-parameter trilinear hysteretic model for the simulation of the high damping rubber bearing, coupled with a Coulomb friction model for the simulation of the low friction sliders. Next, experimentally obtained data from the five free vibration tests were used for the calibration of this six parameter model. Following up on the model development, the present study employs Monte-Carlo simulations in order to investigate the effect of the unavoidable variation in the values of the six-parameter model on the response of the base isolation system. The calibrated parameters values from all the experiments are used as mean values, while the standard deviation for each parameter is deduced from the identification tests employing best-fit optimization for each experiment separately. The results show that variation in the material parameters of the base isolation system produce a nonstationary effect in the response. In addition, there is a magnification effect, since the coefficient of variation of the response, for most of the parameters, is larger than the coefficient of variation in the parameter values. 4726 Available online at www.eccomasproceedia.org Eccomas Proceedia COMPDYN (2017) 4726-4739

DETERMINATION OF MESOSCALE RANDOM FIELDS FOR THE APPARENT PROPERTIES OF SPATIALLY RANDOM COMPOSITES

The macroscopic mechanical and physical properties of heterogeneous materials can be efficiently determined using either analytical or numerical homogenization techniques where the identification of a representative volume element (RVE) is required over which a fine-scale boundary value problem is solved. In this work, an efficient computational scheme is proposed for the determination of mesoscale random fields for the apparent properties and of the RVE size of particle-reinforced composites based on computer-simulated images of their microstructure. A variable number of microstructure models are directly constructed by segmentation of the composite material image into windows of certain size. The proposed numerical procedure takes into account the particle volume fraction variation through digital image processing of the microstructure models. The proposed approach couples the extended finite element method (XFEM) with Monte Carlo simulation in order to analyze the microstructure models and obtain statistical information (probability distribution, correlation structure) for the apparent properties of the composite in each window size. The XFEM analysis of the microstructure models also leads to upper and lower bounds for their constitutive behavior by solving Dirichlet and Neumann boundary value problems. The RVE is attained within a prescribed tolerance by examining the convergence of these two bounds with respect to the mesoscale size and useful conclusions are derived about the effect of matrix/inclusion stiffness ratio as well as of inclusion volume fraction on the apparent properties and on the RVE size.