879 resultados para finite-time stability
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Electron transport in nanoscale structures is strongly influenced by the Coulomb interaction that gives rise to correlations in the stream of charges and leaves clear fingerprints in the fluctuations of the electrical current. A complete understanding of the underlying physical processes requires measurements of the electrical fluctuations on all time and frequency scales, but experiments have so far been restricted to fixed frequency ranges, as broadband detection of current fluctuations is an inherently difficult experimental procedure. Here we demonstrate that the electrical fluctuations in a single-electron transistor can be accurately measured on all relevant frequencies using a nearby quantum point contact for on-chip real-time detection of the current pulses in the single-electron device. We have directly measured the frequency-dependent current statistics and, hereby, fully characterized the fundamental tunnelling processes in the single-electron transistor. Our experiment paves the way for future investigations of interaction and coherence-induced correlation effects in quantum transport.
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This paper deals with the development and the analysis of asymptotically stable and consistent schemes in the joint quasi-neutral and fluid limits for the collisional Vlasov-Poisson system. In these limits, the classical explicit schemes suffer from time step restrictions due to the small plasma period and Knudsen number. To solve this problem, we propose a new scheme stable for choices of time steps independent from the small scales dynamics and with comparable computational cost with respect to standard explicit schemes. In addition, this scheme reduces automatically to consistent discretizations of the underlying asymptotic systems. In this first work on this subject, we propose a first order in time scheme and we perform a relative linear stability analysis to deal with such problems. The framework we propose permits to extend this approach to high order schemes in the next future. We finally show the capability of the method in dealing with small scales through numerical experiments.
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The structure, thermal stability, morphology and ion conductivity of titanium perovskites with the general formula Li3xLn2/3−xTiO3 (Ln = rare earth element; 3x= 0.30) are studied in the context of their possible use as solid electrolyte materials for lithium ion batteries. Materials are prepared by a glycine-nitrate method using different sintering treatments, with a cation-disorder-induced structural transition from tetragonal to cubic symmetry, detected as quenching temperature increases. SEM images show that the average grain size increases with increasing sintering temperature and time. Slightly higher bulk conductivity values have been observed for quenched samples sintered at high temperature. Bulk conductivity decreases with the lanthanide ion size. A slight conductivity enhancement, always limited by grain boundaries, is observed for longer sintering times. TDX measurements of the electrolyte/cathode mixtures also show a good stability of the electrolytes in the temperature range of 30-1100ºC.
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Despite recent advances in ocean observing arrays and satellite sensors, there remains great uncertainty in the large-scale spatial variations of upper ocean salinity on the interannual to decadal timescales. Consonant with both broad-scale surface warming and the amplification of the global hydrological cycle, observed global multidecadal salinity changes typically have focussed on the linear response to anthropogenic forcing but not on salinity variations due to changes in the static stability and or variability due to the intrinsic ocean or internal climate processes. Here, we examine the static stability and spatiotemporal variability of upper ocean salinity across a hierarchy of models and reanalyses. In particular, we partition the variance into time bands via application of singular spectral analysis, considering sea surface salinity (SSS), the Brunt Väisälä frequency (N2), and the ocean salinity stratification in terms of the stabilizing effect due to the haline part of N2 over the upper 500m. We identify regions of significant coherent SSS variability, either intrinsic to the ocean or in response to the interannually varying atmosphere. Based on consistency across models (CMIP5 and forced experiments) and reanalyses, we identify the stabilizing role of salinity in the tropics—typically associated with heavy precipitation and barrier layer formation, and the role of salinity in destabilizing upper ocean stratification in the subtropical regions where large-scale density compensation typically occurs.
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We investigate the Becker-Döring model of nucleation with three generalisations; an input of monomer, an input of inhibitor and finally, we allow the monomers to form two morphologies of cluster. We assume size-independent aggregation and fragmentation rates. Initially we consider the problem of constant monomer input and determine the steady-state solution approached in the large-time limit, and the manner in which it is approached. Secondly, in addition to a constant input of monomer we allow a constant input of inhibitor, which prevents clusters growing any larger and this removes them from the kinetics of the process; the inhibitor is consumed in the action of poisoning a cluster. We determine a critical ratio of poison to monomer input below which the cluster concentrations tend to a non-zero steady-state solution and the poison concentration tends to a finite value. Above the critical input ratio, the concentrations of all cluster sizes tend to zero and the poison concentration grows without limit. In both cases the solution in the large-time limit is determined. Finally we consider a model where monomers form two morphologies, but the inhibitor only acts on one morphology. Four cases are identified, depending on the relative poison to monomer input rates and the relative thermodynamic stability. In each case we determine the final cluster distribution and poison concentration. We find that poisoning the less stable cluster type can have a significant impact on the structure of the more stable cluster distribution; a counter-intuitive result. All results are shown to agree with numerical simulation.
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This paper describes the preparation of poly(DL-lactide-co-glicolide) (PLGA) nanocapsules as a drug carrier system for the local anesthetic bupivacaine. The system was characterized and its stability investigated. The results showed a size distribution with a polydispersity index of 0.12, an average diameter of 148 nm, a zeta potential of -43.5 mV and an entrapment efficiency of 75.8%. The physicochemical properties of polymeric nanocapsule suspensions (average diameter, polydispersity, zeta potential and drug association efficiency) were evaluated as a function of time to determine the formulation stability. The formulation did not display major changes in these properties over the time, and it was considered stable up to 120 days of storage at room temperature. The results reported here which refer to the initial characterization of these new formulations for the local anesthetic bupivacaine show a promising potential for future in vivo studies.
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The present study deals with a new analytical procedure based on a cellulose diffusion membrane and immobilised tetraethylene-pentamine-hexaacetate chelator (DM-TEPHA) for an in situ differentiation of labile and inert metal species in aquatic systems. The DM-TEPHA system was prepared by placing TEPHA chelator in pre-purified cellulose bags and in situ applied immersing the system in two Brazilian rivers to study the relative lability of metal species (Cu, Pb, Fe, Mn and Ni) as a function of the time and the quantity of exchanger, respectively. The procedure is simple and enables a new perspective for understanding the complexation, transport, stability and lability of metal species in aquatic systems rich in organic matter.
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Determining effective hydraulic, thermal, mechanical and electrical properties of porous materials by means of classical physical experiments is often time-consuming and expensive. Thus, accurate numerical calculations of material properties are of increasing interest in geophysical, manufacturing, bio-mechanical and environmental applications, among other fields. Characteristic material properties (e.g. intrinsic permeability, thermal conductivity and elastic moduli) depend on morphological details on the porescale such as shape and size of pores and pore throats or cracks. To obtain reliable predictions of these properties it is necessary to perform numerical analyses of sufficiently large unit cells. Such representative volume elements require optimized numerical simulation techniques. Current state-of-the-art simulation tools to calculate effective permeabilities of porous materials are based on various methods, e.g. lattice Boltzmann, finite volumes or explicit jump Stokes methods. All approaches still have limitations in the maximum size of the simulation domain. In response to these deficits of the well-established methods we propose an efficient and reliable numerical method which allows to calculate intrinsic permeabilities directly from voxel-based data obtained from 3D imaging techniques like X-ray microtomography. We present a modelling framework based on a parallel finite differences solver, allowing the calculation of large domains with relative low computing requirements (i.e. desktop computers). The presented method is validated in a diverse selection of materials, obtaining accurate results for a large range of porosities, wider than the ranges previously reported. Ongoing work includes the estimation of other effective properties of porous media.
H-infinity control design for time-delay linear systems: a rational transfer function based approach
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The aim of this paper is to present new results on H-infinity control synthesis for time-delay linear systems. We extend the use of a finite order LTI system, called comparison system to H-infinity analysis and design. Differently from what can be viewed as a common feature of other control design methods available in the literature to date, the one presented here treats time-delay systems control design with classical numeric routines based on Riccati equations arisen from H-infinity theory. The proposed algorithm is simple, efficient and easy to implement. Some examples illustrating state and output feedback design are solved and discussed in order to put in evidence the most relevant characteristic of the theoretical results. Moreover, a practical application involving a 3-DOF networked control system is presented.
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Oil wells subjected to cyclic steam injection present important challenges for the development of well cementing systems, mainly due to tensile stresses caused by thermal gradients during its useful life. Cement sheath failures in wells using conventional high compressive strength systems lead to the use of cement systems that are more flexible and/or ductile, with emphasis on Portland cement systems with latex addition. Recent research efforts have presented geopolymeric systems as alternatives. These cementing systems are based on alkaline activation of amorphous aluminosilicates such as metakaolin or fly ash and display advantageous properties such as high compressive strength, fast setting and thermal stability. Basic geopolymeric formulations can be found in the literature, which meet basic oil industry specifications such as rheology, compressive strength and thickening time. In this work, new geopolymeric formulations were developed, based on metakaolin, potassium silicate, potassium hydroxide, silica fume and mineral fiber, using the state of the art in chemical composition, mixture modeling and additivation to optimize the most relevant properties for oil well cementing. Starting from molar ratios considered ideal in the literature (SiO2/Al2O3 = 3.8 e K2O/Al2O3 = 1.0), a study of dry mixtures was performed,based on the compressive packing model, resulting in an optimal volume of 6% for the added solid material. This material (silica fume and mineral fiber) works both as an additional silica source (in the case of silica fume) and as mechanical reinforcement, especially in the case of mineral fiber, which incremented the tensile strength. The first triaxial mechanical study of this class of materials was performed. For comparison, a mechanical study of conventional latex-based cementing systems was also carried out. Regardless of differences in the failure mode (brittle for geopolymers, ductile for latex-based systems), the superior uniaxial compressive strength (37 MPa for the geopolymeric slurry P5 versus 18 MPa for the conventional slurry P2), similar triaxial behavior (friction angle 21° for P5 and P2) and lower stifness (in the elastic region 5.1 GPa for P5 versus 6.8 GPa for P2) of the geopolymeric systems allowed them to withstand a similar amount of mechanical energy (155 kJ/m3 for P5 versus 208 kJ/m3 for P2), noting that geopolymers work in the elastic regime, without the microcracking present in the case of latex-based systems. Therefore, the geopolymers studied on this work must be designed for application in the elastic region to avoid brittle failure. Finally, the tensile strength of geopolymers is originally poor (1.3 MPa for the geopolymeric slurry P3) due to its brittle structure. However, after additivation with mineral fiber, the tensile strength became equivalent to that of latex-based systems (2.3 MPa for P5 and 2.1 MPa for P2). The technical viability of conventional and proposed formulations was evaluated for the whole well life, including stresses due to cyclic steam injection. This analysis was performed using finite element-based simulation software. It was verified that conventional slurries are viable up to 204ºF (400ºC) and geopolymeric slurries are viable above 500ºF (260ºC)
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We propose a positive, accurate moment closure for linear kinetic transport equations based on a filtered spherical harmonic (FP_N) expansion in the angular variable. The FP_N moment equations are accurate approximations to linear kinetic equations, but they are known to suffer from the occurrence of unphysical, negative particle concentrations. The new positive filtered P_N (FP_N+) closure is developed to address this issue. The FP_N+ closure approximates the kinetic distribution by a spherical harmonic expansion that is non-negative on a finite, predetermined set of quadrature points. With an appropriate numerical PDE solver, the FP_N+ closure generates particle concentrations that are guaranteed to be non-negative. Under an additional, mild regularity assumption, we prove that as the moment order tends to infinity, the FP_N+ approximation converges, in the L2 sense, at the same rate as the FP_N approximation; numerical tests suggest that this assumption may not be necessary. By numerical experiments on the challenging line source benchmark problem, we confirm that the FP_N+ method indeed produces accurate and non-negative solutions. To apply the FP_N+ closure on problems at large temporal-spatial scales, we develop a positive asymptotic preserving (AP) numerical PDE solver. We prove that the propose AP scheme maintains stability and accuracy with standard mesh sizes at large temporal-spatial scales, while, for generic numerical schemes, excessive refinements on temporal-spatial meshes are required. We also show that the proposed scheme preserves positivity of the particle concentration, under some time step restriction. Numerical results confirm that the proposed AP scheme is capable for solving linear transport equations at large temporal-spatial scales, for which a generic scheme could fail. Constrained optimization problems are involved in the formulation of the FP_N+ closure to enforce non-negativity of the FP_N+ approximation on the set of quadrature points. These optimization problems can be written as strictly convex quadratic programs (CQPs) with a large number of inequality constraints. To efficiently solve the CQPs, we propose a constraint-reduced variant of a Mehrotra-predictor-corrector algorithm, with a novel constraint selection rule. We prove that, under appropriate assumptions, the proposed optimization algorithm converges globally to the solution at a locally q-quadratic rate. We test the algorithm on randomly generated problems, and the numerical results indicate that the combination of the proposed algorithm and the constraint selection rule outperforms other compared constraint-reduced algorithms, especially for problems with many more inequality constraints than variables.
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In this work, we further extend the recently developed adaptive data analysis method, the Sparse Time-Frequency Representation (STFR) method. This method is based on the assumption that many physical signals inherently contain AM-FM representations. We propose a sparse optimization method to extract the AM-FM representations of such signals. We prove the convergence of the method for periodic signals under certain assumptions and provide practical algorithms specifically for the non-periodic STFR, which extends the method to tackle problems that former STFR methods could not handle, including stability to noise and non-periodic data analysis. This is a significant improvement since many adaptive and non-adaptive signal processing methods are not fully capable of handling non-periodic signals. Moreover, we propose a new STFR algorithm to study intrawave signals with strong frequency modulation and analyze the convergence of this new algorithm for periodic signals. Such signals have previously remained a bottleneck for all signal processing methods. Furthermore, we propose a modified version of STFR that facilitates the extraction of intrawaves that have overlaping frequency content. We show that the STFR methods can be applied to the realm of dynamical systems and cardiovascular signals. In particular, we present a simplified and modified version of the STFR algorithm that is potentially useful for the diagnosis of some cardiovascular diseases. We further explain some preliminary work on the nature of Intrinsic Mode Functions (IMFs) and how they can have different representations in different phase coordinates. This analysis shows that the uncertainty principle is fundamental to all oscillating signals.
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The effects of the Linear Alkylbenzene Sulphonate (LAS) were evaluated on the mussel Perna perna (Linnaeus, 1758), using a cellular level biomarker. The Neutral Red Retention Time (NRRT) assay was used to estimate effects at cellular levels. Significant effects were observed for the NRRT assay, even in low concentrations. The effects at cellular level were progressive, suggesting that the organisms are not capable to recover of such increasing effects. Additionally, the results show that the levels of LAS observed for Brazilian coastal waters may chronically affect the biota.
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The color stability of resin cements is essential for aesthetic restorations. Aim: To evaluate the influence of shade and aging time on the color stability of two light-cured and two dual-cured resin cements. Methods: The CIE-Lab color parameters (n=6) were measured immediately after sample preparation and at 7, 30 and 90 days of aging in distilled water. The color difference (ΔE) was calculated and then analyzed by three-way ANOVA for repeated measures and Tukey’s HSD test (α=0.05). Results: ΔE was higher for transparent resin colors, followed by dark and light colors. The mean values of ΔE were lower for both light-cured resin cements compared to the dual-cured cements. As the aging time increased, ΔE values increased. Conclusions: The light-cured resin cements showed greater color stability. The lighter shades of luting were more likely to display a greater color change.
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One of the main concerns in the technological application of several metal–organic frameworks (MOFs) relates to their structural instability under pressure (after a conforming step). Here we report for the first time that mechanical instability can be highly improved via nucleation and growth of MOF nanocrystals in the confined nanospace of activated carbons.