Numerical detection of the Gardner transition in a mean-field glass former.

Recent theoretical advances predict the existence, deep into the glass phase, of a novel phase transition, the so-called Gardner transition. This transition is associated with the emergence of a complex free energy landscape composed of many marginally stable sub-basins within a glass metabasin. In this study, we explore several methods to detect numerically the Gardner transition in a simple structural glass former, the infinite-range Mari-Kurchan model. The transition point is robustly located from three independent approaches: (i) the divergence of the characteristic relaxation time, (ii) the divergence of the caging susceptibility, and (iii) the abnormal tail in the probability distribution function of cage order parameters. We show that the numerical results are fully consistent with the theoretical expectation. The methods we propose may also be generalized to more realistic numerical models as well as to experimental systems.

TILTED COLUMNAR THIN FILM COATINGS WITH ANISOTROPIC LIGHT SCATTERING PROPERTIES FOR SOLAR ENERGY APPLICATIONS

The main goal of this thesis is to show the versatility of glancing angle deposition (GLAD) thin films in applications. This research is first focused on studying the effect of select deposition variables in GLAD thin films and secondly, to demonstrate the flexibility of GLAD films to be incorporated in two different applications: (1) as a reflective coating in low-level concentration photovoltaic systems, and (2) as an anode structure in dye-sensitized solar cells (DSSC). A particular type of microstructure composed of tilted micro-columns of titanium is fabricated by GLAD. The microstructures form elongated and fan-like tilted micro-columns that demonstrate anisotropic scattering. The thin films texture changes from fiber texture to tilted fiber texture by increasing the vapor incidence angle. At very large deposition angles, biaxial texture forms. The morphology of the thin films deposited under extreme shadowing condition and at high temperature (below recrystallization zone) shows a porous and inclined micro-columnar morphology, resulting from the dominance of shadowing over adatom surface diffusion. The anisotropic scattering behavior of the tilted Ti thin film coatings is quantified by bidirectional reflectance distribution function (BRDF) measurements and is found to be consistent with reflectance from the microstructure acting as an array of inclined micro-mirrors that redirect the incident light in a non-specular reflection. A silver-coating of the surface of the tilted-Ti micro-columns is performed to enhance the total reflectance of the Ti-thin films while keeping the anisotropic scattering behavior. By using such coating is as a booster reflector in a laboratory-scale low-level concentration photovoltaic system, the short-circuit current of the reference silicon solar cell by 25%. Finally, based on the scattering properties of the tilted microcolumnar microstructure, its scattering effect is studied as a part of titanium dioxide microstructure for the anode in DSSCs. GLAD-fabricated TiO2 microstructures for the anode in a DSSC, consisting of vertical micro-columns, and combined vertical topped with tilted micro-columns are compared. The solar cell with the two-part microstructure shows the highest monochromatic incident photon to current efficiency with 20% improvement compared to the vertical microstructure, and the efficiency of the cell increases from 1.5% to 2% due to employing the scattering layer.

Data-Driven Dynamic Modeling of Coupled Thermal and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

Data-Driven Dynamic Prediction of Interrelated Heat and Electric Outputs of Microturbines

Microturbines are among the most successfully commercialized distributed energy resources, especially when they are used for combined heat and power generation. However, the interrelated thermal and electrical system dynamic behaviors have not been fully investigated. This is technically challenging due to the complex thermo-fluid-mechanical energy conversion processes which introduce multiple time-scale dynamics and strong nonlinearity into the analysis. To tackle this problem, this paper proposes a simplified model which can predict the coupled thermal and electric output dynamics of microturbines. Considering the time-scale difference of various dynamic processes occuring within microturbines, the electromechanical subsystem is treated as a fast quasi-linear process while the thermo-mechanical subsystem is treated as a slow process with high nonlinearity. A three-stage subspace identification method is utilized to capture the dominant dynamics and predict the electric power output. For the thermo-mechanical process, a radial basis function model trained by the particle swarm optimization method is employed to handle the strong nonlinear characteristics. Experimental tests on a Capstone C30 microturbine show that the proposed modeling method can well capture the system dynamics and produce a good prediction of the coupled thermal and electric outputs in various operating modes.

A Generalized Fuzzy Linguistic Model for Predicting Component Concentrations in an Optical Gas Sensing System

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NOx, SO2 etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

A generalized fuzzy linguistic model for predicting component concentrations in an optical gas sensing system

Motivated by environmental protection concerns, monitoring the flue gas of thermal power plant is now often mandatory due to the need to ensure that emission levels stay within safe limits. Optical based gas sensing systems are increasingly employed for this purpose, with regression techniques used to relate gas optical absorption spectra to the concentrations of specific gas components of interest (NO_x, SO₂ etc.). Accurately predicting gas concentrations from absorption spectra remains a challenging problem due to the presence of nonlinearities in the relationships and the high-dimensional and correlated nature of the spectral data. This article proposes a generalized fuzzy linguistic model (GFLM) to address this challenge. The GFLM is made up of a series of “If-Then” fuzzy rules. The absorption spectra are input variables in the rule antecedent. The rule consequent is a general nonlinear polynomial function of the absorption spectra. Model parameters are estimated using least squares and gradient descent optimization algorithms. The performance of GFLM is compared with other traditional prediction models, such as partial least squares, support vector machines, multilayer perceptron neural networks and radial basis function networks, for two real flue gas spectral datasets: one from a coal-fired power plant and one from a gas-fired power plant. The experimental results show that the generalized fuzzy linguistic model has good predictive ability, and is competitive with alternative approaches, while having the added advantage of providing an interpretable model.

Inhomogeneous cloud coverage through the Coulomb explosion of dust in substellar atmospheres

Context. Recent observations of brown dwarf spectroscopic variability in the infrared infer the presence of patchy cloud cover. Aims. This paper proposes a mechanism for producing inhomogeneous cloud coverage due to the depletion of cloud particles through the Coulomb explosion of dust in atmospheric plasma regions. Charged dust grains Coulomb-explode when the electrostatic stress of the grain exceeds its mechanical tensile stress, which results in grains below a critical radius a < a Coul crit being broken up. Methods. This work outlines the criteria required for the Coulomb explosion of dust clouds in substellar atmospheres, the effect on the dust particle size distribution function, and the resulting radiative properties of the atmospheric regions. Results. Our results show that for an atmospheric plasma region with an electron temperature of Te = 10 eV (≈105 K), the critical grain radius varies from 10−7 to 10−4 cm, depending on the grains’ tensile strength. Higher critical radii up to 10−3 cm are attainable for higher electron temperatures. We find that the process produces a bimodal particle size distribution composed of stable nanoscale seed particles and dust particles with a ≥ a Coul crit , with the intervening particle sizes defining a region devoid of dust. As a result, the dust population is depleted, and the clouds become optically thin in the wavelength range 0.1–10 μm, with a characteristic peak that shifts to higher wavelengths as more sub-micrometer particles are destroyed. Conclusions. In an atmosphere populated with a distribution of plasma volumes, this will yield regions of contrasting radiative properties, thereby giving a source of inhomogeneous cloud coverage. The results presented here may also be relevant for dust in supernova remnants and protoplanetary disks.

Wind wave prediction in the Caspian Sea

In this thesis, wind wave prediction and analysis in the Southern Caspian Sea are surveyed. Because of very much importance and application of this matter in reducing vital and financial damages or marine activities, such as monitoring marine pollution, designing marine structure, shipping, fishing, offshore industry, tourism and etc, gave attention by some marine activities. In this study are used the Caspian Sea topography data that are extracted from the Caspian Sea Hydrography map of Iran Armed Forces Geographical Organization and the I 0 meter wind field data that are extracted from the transmitted GTS synoptic data of regional centers to Forecasting Center of Iran Meteorological Organization for wave prediction and is used the 20012 wave are recorded by the oil company's buoy that was located at distance 28 Kilometers from Neka shore for wave analysis. The results of this research are as follows: - Because of disagreement between the prediction results of SMB method in the Caspian sea and wave data of the Anzali and Neka buoys. The SMB method isn't able to Predict wave characteristics in the Southern Caspian Sea. - Because of good relativity agreement between the WAM model output in the Caspian Sea and wave data of the Anzali buoy. The WAM model is able to predict wave characteristics in the southern Caspian Sea with high relativity accuracy. The extreme wave height distribution function for fitting to the Southern Caspian Sea wave data is obtained by determining free parameters of Poisson-Gumbel function through moment method. These parameters are as below: A=2.41, B=0.33. The maximum relative error between the estimated 4-year return value of the Southern Caspian Sea significant wave height by above function with the wave data of Neka buoy is about %35. The 100-year return value of the Southern Caspian Sea significant height wave is about 4.97 meter. The maximum relative error between the estimated 4-year return value of the Southern Caspian Sea significant wave height by statistical model of peak over threshold with the wave data of Neka buoy is about %2.28. The parametric relation for fitting to the Southern Caspian Sea frequency spectra is obtained by determining free parameters of the Strekalov, Massel and Krylov etal_ multipeak spectra through mathematical method. These parameters are as below: A = 2.9 B=26.26, C=0.0016 m=0.19 and n=3.69. The maximum relative error between calculated free parameters of the Southern Caspian Sea multipeak spectrum with the proposed free parameters of double-peaked spectrum by Massel and Strekalov on the experimental data from the Caspian Sea is about 36.1 % in spectrum energetic part and is about 74M% in spectrum high frequency part. The peak over threshold waverose of the Southern Caspian Sea shows that maximum occurrence probability of wave height is relevant to waves with 2-2.5 meters wave fhe error sources in the statistical analysis are mainly due to: l) the missing wave data in 2 years duration through battery discharge of Neka buoy. 2) the deportation %15 of significant height annual mean in single year than long period average value that is caused by lack of adequate measurement on oceanic waves, and the error sources in the spectral analysis are mainly due to above- mentioned items and low accurate of the proposed free parameters of double-peaked spectrum on the experimental data from the Caspian Sea.

Coagulation equations with mass loss

We derive and solve models for coagulation with mass loss arising, for example, from industrial processes in which growing inclusions are lost from the melt by colliding with the wall of the vessel. We consider a variety of loss laws and a variety of coagulation kernels, deriving exact results where possible, and more generally reducing the equations to similarity solutions valid in the large-time limit. One notable result is the effect that mass removal has on gelation: for small loss rates, gelation is delayed, whilst above a critical threshold, gelation is completely prevented. Finally, by forming an exact explicit solution for a more general initial cluster size distribution function, we illustrate how numerical results from earlier work can be interpreted in the light of the theory presented herein.

Análise por meio de espectroscopia de emissão óptica das espécies ativas em nitretação iônica e gaiola catódica

Plasma process like ionic nitriding and cathodic cage plasma nitriding are utilized in order to become hard surface of steels. The ionic nitriding is already accepted in the industry while cathodic cage plasma nitriding process is in industrial implementation stage. Those process depend of plasma parameters like electronic and ionic temperature (Te, Ti), species density (ne, ni) and of distribution function of these species. In the present work, the plasma used to those two processes has been observed through Optical Emission Spectroscopy OES technique in order to identify presents species in the treatment ambient and relatively quantify them. So plasma of typical mixtures like N2 H2 has been monitored through in order to study evolution of those species during the process. Moreover, it has been realized a systematic study about leaks, also thought OES, that accomplish the evolution of contaminant species arising because there is flux of atmosphere to inside nitriding chamber and in what conditions the species are sufficiently reduced. Finally, to describe the physic mechanism that acts on both coating techniques ionic nitriding and cathodic cage plasma nitriding

Hypothesis test for changes in variance using a statistic based in P-values in a time series of normal independent observations.

The present work proposes a Hypothesis Test to detect a shift in the variance of a series of independent normal observations using a statistic based on the p-values of the F distribution. Since the probability distribution function of this statistic is intractable, critical values were we estimated numerically through extensive simulation. A regression approach was used to simplify the quantile evaluation and extrapolation. The power of the test was simulated using Monte Carlo simulation, and the results were compared with the Chen test (1997) to prove its efficiency. Time series analysts might find the test useful to address homoscedasticity studies were at most one change might be involved.

X-Ray powder diffraction laboratory @ University of Málaga (UMA)

X-Ray Powder Diffraction (XRPD) laboratory is a facility placed at Servicios Centrales de apoyo a la Investigación (SCAI) at University of Malaga (UMA) http://www.scai.uma.es/. This facility has three XRPD diffractometers and a diffractometer to measure high-resolution thin-films. X´Pert PRO MPD from PANalytical. This is a bragg-brentano (theta/2theta) with reflection geometry diffractometer which allows to obtain high resolution XRPD data with strictly monochromatic CuKα1 radiation (λ=1.54059Å) [Ge(111) primary monochromator] and an automatic sample charger. Moreover, it has parallel monochromatic CuKα1 radiation (λ=1.54059Å) with an hybrid Ge(220) monochromator for capillary and multiproposal (bulk samples up to 1 Kg) sample holders. The HTK1200N chamber from Anton Paar allows collecting high resolution high temperature patterns. EMPYREAN from PANalytical. This diffractometer works in reflection and transmission geometries with theta/theta goniometer, using CuKα1,2 radiation (λ=1.5418Å), a focusing X-ray mirror and a ultra-fast PIXCEL 3D detector with 1D and 2D collection data modes (microstructural and preferred orientation analysis). Moreover, the TTK450N chamber allows low temperature and up to 450ºC studies. A D8 ADVANCE (BRUKER) was installed in April 2014. It is the first diffractometer in Europe equipped with a Johansson Ge(111) primary monochromator, which gives a strictly monochromatic Mo radiation (λ=0.7093 Å) [1]. It works in transmission mode (with a sample charger) with this high resolution configuration. XRPD data suitable for PDF (Pair Distribution Function) analysis can be collected with a capillary sample holder, due to the high energy and high resolution capabilities of this diffractometer. Moreover, it has a humidity chamber MHC-trans from Anton Paar working on transmission mode with MoKα1 (measurements can be collected at 5 to 95% of relative humidity (from 20 to 80 ºC) and up to 150ºC [2]). Furthermore, this diffractometer also has a reaction chamber XRK900 from Anton Paar (which uses CuKα1,2 radiation in reflection mode), which allows data collection from room temperature to 900ºC with up to 10 bar of different gases. Finally, a D8 DISVOVER A25 from BRUKER was installed on December 2014. It has a five axis Euler cradler and optics devices suitable for high resolution thin film data collection collected in in-plane and out-of-plane modes. To sum up, high-resolution thin films, microstructural, rocking-curve, Small Angle X-ray Scattering (SAXS), Grazing incident SAXS (GISAXS), Ultra Grazing incident diffraction (Ultra-GID) and microdiffraction measurements can be performed with the appropriated optics and sample holders. [1] L. León-Reina, M. García-Maté, G. Álvarez-Pinazo, I. Santacruz, O. Vallcorba, A.G. De la Torre, M.A.G. Aranda “Accuracy in Rietveld quantitative phase analysis: a comparative study of strictly monochromatic Mo and Cu radiations” J. Appl. Crystallogr. 2016, 49, 722-735. [2] J. Aríñez-Soriano, J. Albalad, C. Vila-Parrondo, J. Pérez-Carvajal, S. Rodríguez-Hermida, A. Cabeza, F. Busqué, J. Juanhuix, I. Imaz, Daniel Maspoch “Single-crystal and humidity-controlled powder diffraction study of the breathing effect in a metal-organic framework upon water adsorption/desorption” Chem. Commun., 2016, DOI: 10.1039/C6CC02908F.

Sintonia automática de controladores PID: uma abordagem neuro - genética

Dissertação de dout. em Electrónica e Computação, Faculdade de Ciências e Tecnologia, Univ. do Algarve, 2004

Improving CAS Capabilities: New Rules for Computing Improper Integrals

There are diferent applications in Engineering that require to compute improper integrals of the first kind (integrals defined on an unbounded domain) such as: the work required to move an object from the surface of the earth to in nity (Kynetic Energy), the electric potential created by a charged sphere, the probability density function or the cumulative distribution function in Probability Theory, the values of the Gamma Functions(wich useful to compute the Beta Function used to compute trigonometrical integrals), Laplace and Fourier Transforms (very useful, for example in Differential Equations).

On Some Unifications Arising from the MIMO Rician Shadowed Model

This paper shows that the proposed Rician shadowed model for multi-antenna communications allows for the unification of a wide set of models, both for multiple-input multiple-output (MIMO) and single- input single-output (SISO) communications. The MIMO Rayleigh and MIMO Rician can be deduced from the MIMO Rician shadowed, and so their SISO counterparts. Other more general SISO models, besides the Rician shadowed, are included in the model, such as the κ-μ, and its recent generalization, the κ-μ shadowed model. Moreover, the SISO η-μ and Nakagami-q models are also included in the MIMO Rician shadowed model. The literature already presents the probability density function (pdf) of the Rician shadowed Gram channel matrix in terms of the well-known gamma- Wishart distribution. We here derive its moment generating function in a tractable form. Closed- form expressions for the cumulative distribution function and the pdf of the maximum eigenvalue are also carried out.