Thermo-magnetic-fluid dynamics analysis of an OsNAN distribution transformer cooled with mineral oil and biodegradable esters

This work introduces a coupled electromagnetic, thermal and fluid flow analysis of an oil-natural air-natural distribution transformer in order to study the changes in the heat dissipation performance when a biodegradable ester is used to cool the device instead of mineral oil. The transformer has a rated power of 315kVA and a voltage ratio of 13.2kV / 0.4kV. The heat losses in the magnetic core and the windings are computed with the ANSYS® Maxwell software and they are transferred as volume heat source terms to compute the heat conduction. The natural convection of the fluid flow is taken into account using a temperature-dependent density. The heat conduction through the solid walls and radiators panels are also considered. The thermo–hydraulic problem is solved with the software Code_Saturne. Data from experimental tests carried out with mineral oil are used to validate the numerical simulations. Equivalent and anisotropic thermal conductivities in the core and the windings are calculated both with a semi-analytic procedure and finite element simulations to simplify the heat conduction model in the active parts. It is found that, after reaching a steady state, the transformer cooled with the ester shows a temperature difference between specific locations at the top and the bottom higher than that cooled with mineral oil. The magnetic core and the windings also work hotter when ester is used. Finally, the analysis of the flow through the cooling ducts of the windings confirms that the oil velocity is, on average, 25% higher than the ester one.Fil: Garelli, Luciano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Rios Rodriguez, Gustavo Adolfo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Kubiczek, K.. Silesian University Of Technology; PoloniaFil: Lasek, P.. Silesian University Of Technology; PoloniaFil: Stepien, M.. Silesian University Of Technology; PoloniaFil: Smolka, J.. Silesian University Of Technology; PoloniaFil: Storti, Mario Alberto. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Santa Fe. Centro de Investigaciones en Métodos Computacionales. Universidad Nacional del Litoral. Centro de Investigaciones en Métodos Computacionales; ArgentinaFil: Pessolani, F.. No especifíca;Fil: Amadei, M.. No especifíca

Physicochemical Characterization and Sugar Profile of Argentinian Honeys From the Phytogeographic Provinces Paranaense and Pampeana in Misiones

The characterization of honeys from the Biomes and vegetation units of the Phytogeographical Provinces (PP) located in the Province of Misiones (Argentina) was performed by analysis of sugar profile and physicochemical parameters (Free Acidity, pH, Electrical Conductivity (EC), colour and contents of moisture, ash, total soluble solids and hydroxymethylfurfural) used for quality control of honey. The honeys analysed were authentic and traceable, and met the specifications of the national and/or international standards for the evaluated parameters, denoting blossom origin and confirming high quality, maturity and freshness. The influence of biome and Vegetation Units (VU) on physical and chemical parameters of the studied honeys was defined regarding both flora and pedoclimatic conditions. Honeys from VU-27 presented significantly higher contents of fructose, ash and total soluble solids, pH and EC and lower moisture content than those from VU-3. To the authors’ best knowledge, sugar profiles, free acidity and contents of ash and total soluble solids in honeys from the different PPs, vegetation units and Biomes of Misiones are reported for the first time. This study contributes to the classification of honeys from Misiones, helping to increase added value and access new markets.Fil: Poliero, Aimará Ayelen. Universidad Nacional de Mar del Plata. Instituto de Investigaciones en Producción, Sanidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Producción, Sanidad y Ambiente; ArgentinaFil: Aubone, Ines. Universidad Nacional de Mar del Plata. Instituto de Investigaciones en Producción, Sanidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Producción, Sanidad y Ambiente; ArgentinaFil: Amadei Enghelmayer, Marisa. No especifíca;Fil: Rosso, Valeria Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Müller, P. F.. No especifíca;Fil: Fuselli, Sandra Rosa. Universidad Nacional de Mar del Plata. Instituto de Investigaciones en Producción, Sanidad y Ambiente - Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Mar del Plata. Instituto de Investigaciones en Producción, Sanidad y Ambiente; ArgentinaFil: Alonso Salces, Rosa Maria. Universidad Nacional de Mar del Plata. Instituto de Investigaciones En Produccion, Sanidad y Ambiente. - Consejo Nacional de Investigaciones Cientificas y Tecnicas. Centro Cientifico Tecnologico Conicet - Mar del Plata. Instituto de Investigaciones En Produccion, Sanidad y Ambiente.; Argentin

Recurrence quantification analysis as a tool for the characterization of molecular dynamics simulations

A molecular dynamics simulation of a Lennard-Jones fluid, and a trajectory of the B1 immunoglobulin G-binding domain of streptococcal protein G (B1-IgG) simulated in water are analyzed by recurrence quantification, which is noteworthy for its independence from stationarity constraints, as well as its ability to detect transients, and both linear and nonlinear state changes. The results demonstrate the sensitivity of the technique for the discrimination of phase sensitive dynamics. Physical interpretation of the recurrence measures is also discussed.Comment: 7 pages, 8 figures, revtex; revised for review for Phys. Rev. E (clarifications and expansion of discussion)-- addition of the 8 postscript figures previously omitted, but unchanged from version

Combining Optimal Control Theory and Molecular Dynamics for Protein Folding

A new method to develop low-energy folding routes for proteins is presented. The novel aspect of the proposed approach is the synergistic use of optimal control theory with Molecular Dynamics (MD). In the first step of the method, optimal control theory is employed to compute the force field and the optimal folding trajectory for the atoms of a Coarse-Grained (CG) protein model. The solution of this CG optimization provides an harmonic approximation of the true potential energy surface around the native state. In the next step CG optimization guides the MD simulation by specifying the optimal target positions for the atoms. In turn, MD simulation provides an all-atom conformation whose positions match closely the reference target positions determined by CG optimization. This is accomplished by Targeted Molecular Dynamics (TMD) which uses a bias potential or harmonic restraint in addition to the usual MD potential. Folding is a dynamical process and as such residues make different contacts during the course of folding. Therefore CG optimization has to be reinitialized and repeated over time to accomodate these important changes. At each sampled folding time, the active contacts among the residues are recalculated based on the all-atom conformation obtained from MD. Using the new set of contacts, the CG potential is updated and the CG optimal trajectory for the atoms is recomputed. This is followed by MD. Implementation of this repetitive CG optimization - MD simulation cycle generates the folding trajectory. Simulations on a model protein Villin demonstrate the utility of the method. Since the method is founded on the general tools of optimal control theory and MD without any restrictions, it is widely applicable to other systems. It can be easily implemented with available MD software packages

Coarse-Graining Protein Structures With Local Multivariate Features from Molecular Dynamics

A multivariate statistical theory, local feature analysis (LFA), extracts functionally relevant domains from molecular dynamics (MD) trajectories. The LFA representations, like those of principal component analysis (PCA), are low dimensional and provide a reduced basis set for collective motions of simulated proteins, but the local features are sparsely distributed and spatially localized, in contrast to global PCA modes. One key problem in the assignment of local features is the coarse-graining of redundant LFA output functions by means of seed atoms. One can solve the combinatorial problem by adding seed atoms one after another to a growing set, minimizing a reconstruction error at each addition. This allows for an efficient implementation, but the sequential algorithm does not guarantee the optimal mutual correlation of the sequentially assigned features. Here, we present a novel coarse-graining algorithm for proteins that directly minimizes the mutual correlation of seed atoms by Monte Carlo (MC) simulations. Tests on MD trajectories of two biological systems, bacteriophage T4 lysozyme and myosin II motor domain S1, demonstrate that the new algorithm provides statistically reproducible results and describes functionally relevant dynamics. The well-known undersampling of large-scale motion by short MD simulations is apparent also in our model, but the new coarse-graining offers a major advantage over PCA; converged features are invariant across multiple windows of the trajectory, dividing the protein into converged regions and a smaller number of localized, undersampled regions. In addition to its use in structure classification, the proposed coarse-graining thus provides a localized measure of MD sampling efficiency

A modified empirical criterion for strength of transversely anisotropic rocks with metamorphic origin

A modified empirical criterion is proposed to determine the strength of transversely anisotropic rocks. In this regard, mechanical properties of intact anisotropic slate obtained from three different districts of Iran were taken into consideration. Afterward, triaxial rock strength criterion introduced by Rafiai was modified for transversely anisotropic rocks. The criterion was modified by adding a new parameter α for taking the influence of strength anisotropy into consideration. The results obtained have shown that the parameter α can be considered as the strength reduction parameter due to rock anisotropy. The modified criterion was compared to the modified Hoek–Brown (Saroglou and Tsiambaos) and Ramamurthy criteria for different anisotropic rocks. It was concluded that the criterion proposed in this paper is a more accurate and precise criterion in predicting the strength of anisotropic rocks

Specialized dynamical properties of promiscuous residues revealed by simulated conformational ensembles

The ability to interact with different partners is one of the most important features in proteins. Proteins that bind a large number of partners (hubs) have been often associated with intrinsic disorder. However, many examples exist of hubs with an ordered structure, and evidence of a general mechanism promoting promiscuity in ordered proteins is still elusive. An intriguing hypothesis is that promiscuous binding sites have specific dynamical properties, distinct from the rest of the interface and pre-existing in the protein isolated state. Here, we present the first comprehensive study of the intrinsic dynamics of promiscuous residues in a large protein data set. Different computational methods, from coarse-grained elastic models to geometry-based sampling methods and to full-atom Molecular Dynamics simulations, were used to generate conformational ensembles for the isolated proteins. The flexibility and dynamic correlations of interface residues with a different degree of binding promiscuity were calculated and compared considering side chain and backbone motions, the latter both on a local and on a global scale. The study revealed that (a) promiscuous residues tend to be more flexible than nonpromiscuous ones, (b) this additional flexibility has a higher degree of organization, and (c) evolutionary conservation and binding promiscuity have opposite effects on intrinsic dynamics. Findings on simulated ensembles were also validated on ensembles of experimental structures extracted from the Protein Data Bank (PDB). Additionally, the low occurrence of single nucleotide polymorphisms observed for promiscuous residues indicated a tendency to preserve binding diversity at these positions. A case study on two ubiquitin-like proteins exemplifies how binding promiscuity in evolutionary related proteins can be modulated by the fine-tuning of the interface dynamics. The interplay between promiscuity and flexibility highlighted here can inspire new directions in protein-protein interaction prediction and design methods. © 2013 American Chemical Society

Detection of Functional Modes in Protein Dynamics

Proteins frequently accomplish their biological function by collective atomic motions. Yet the identification of collective motions related to a specific protein function from, e.g., a molecular dynamics trajectory is often non-trivial. Here, we propose a novel technique termed “functional mode analysis” that aims to detect the collective motion that is directly related to a particular protein function. Based on an ensemble of structures, together with an arbitrary “functional quantity” that quantifies the functional state of the protein, the technique detects the collective motion that is maximally correlated to the functional quantity. The functional quantity could, e.g., correspond to a geometric, electrostatic, or chemical observable, or any other variable that is relevant to the function of the protein. In addition, the motion that displays the largest likelihood to induce a substantial change in the functional quantity is estimated from the given protein ensemble. Two different correlation measures are applied: first, the Pearson correlation coefficient that measures linear correlation only; and second, the mutual information that can assess any kind of interdependence. Detecting the maximally correlated motion allows one to derive a model for the functional state in terms of a single collective coordinate. The new approach is illustrated using a number of biomolecules, including a polyalanine-helix, T4 lysozyme, Trp-cage, and leucine-binding protein