902 resultados para Driven piles


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In a recent paper [Phys. Rev. Lett. 75, 189 (1995)] we have presented the exact analytical expression for the mean exit time, T(x,v), of a free inertial process driven by Gaussian white noise out of a region (0,L) in space. In this paper we give a detailed account of the method employed and present results on asymptotic properties and averages of T(x,v).

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Two recently reported treatments [J. M. Porrà et al., Phys. Rev. A 44, 4866 (1991) and I. L¿Heureux and R. Kapral, J. Chem. Phys. 88, 7468 (1988)] of the problem of bistability driven by dichotomous colored noise with a small correlation time are brought into agreement with each other and with the exact numerical results of L¿Heureux and Kapral [J. Chem. Phys. 90, 2453 (1989)].

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We study the mean-first-passage-time problem for systems driven by the coin-toss square-wave signal. Exact analytic solutions are obtained for the driftless case. We also obtain approximate solutions for the potential case. The mean-first-passage time exhibits discontinuities and a remarkable nonsmooth oscillatory behavior which, to our knowledge, has not been observed for other kinds of driving noise.

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PURPOSE: The objective of this experiment is to establish a continuous postmortem circulation in the vascular system of porcine lungs and to evaluate the pulmonary distribution of the perfusate. This research is performed in the bigger scope of a revascularization project of Thiel embalmed specimens. This technique enables teaching anatomy, practicing surgical procedures and doing research under lifelike circumstances. METHODS: After cannulation of the pulmonary trunk and the left atrium, the vascular system was flushed with paraffinum perliquidum (PP) through a heart-lung machine. A continuous circulation was then established using red PP, during which perfusion parameters were measured. The distribution of contrast-containing PP in the pulmonary circulation was visualized on computed tomography. Finally, the amount of leak from the vascular system was calculated. RESULTS: A reperfusion of the vascular system was initiated for 37 min. The flow rate ranged between 80 and 130 ml/min throughout the experiment with acceptable perfusion pressures (range: 37-78 mm Hg). Computed tomography imaging and 3D reconstruction revealed a diffuse vascular distribution of PP and a decreasing vascularization ratio in cranial direction. A self-limiting leak (i.e. 66.8% of the circulating volume) towards the tracheobronchial tree due to vessel rupture was also measured. CONCLUSIONS: PP enables circulation in an isolated porcine lung model with an acceptable pressure-flow relationship resulting in an excellent recruitment of the vascular system. Despite these promising results, rupture of vessel walls may cause leaks. Further exploration of the perfusion capacities of PP in other organs is necessary. Eventually, this could lead to the development of reperfused Thiel embalmed human bodies, which have several applications.

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We study the forced displacement of a thin film of fluid in contact with vertical and inclined substrates of different wetting properties, that range from hydrophilic to hydrophobic, using the lattice-Boltzmann method. We study the stability and pattern formation of the contact line in the hydrophilic and superhydrophobic regimes, which correspond to wedge-shaped and nose-shaped fronts, respectively. We find that contact lines are considerably more stable for hydrophilic substrates and small inclination angles. The qualitative behavior of the front in the linear regime remains independent of the wetting properties of the substrate as a single dispersion relation describes the stability of both wedges and noses. Nonlinear patterns show a clear dependence on wetting properties and substrate inclination angle. The effect is quantified in terms of the pattern growth rate, which vanishes for the sawtooth pattern and is finite for the finger pattern. Sawtooth shaped patterns are observed for hydrophilic substrates and low inclination angles, while finger-shaped patterns arise for hydrophobic substrates and large inclination angles. Finger dynamics show a transient in which neighboring fingers interact, followed by a steady state where each finger grows independently.

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Accurate modeling of flow instabilities requires computational tools able to deal with several interacting scales, from the scale at which fingers are triggered up to the scale at which their effects need to be described. The Multiscale Finite Volume (MsFV) method offers a framework to couple fine-and coarse-scale features by solving a set of localized problems which are used both to define a coarse-scale problem and to reconstruct the fine-scale details of the flow. The MsFV method can be seen as an upscaling-downscaling technique, which is computationally more efficient than standard discretization schemes and more accurate than traditional upscaling techniques. We show that, although the method has proven accurate in modeling density-driven flow under stable conditions, the accuracy of the MsFV method deteriorates in case of unstable flow and an iterative scheme is required to control the localization error. To avoid large computational overhead due to the iterative scheme, we suggest several adaptive strategies both for flow and transport. In particular, the concentration gradient is used to identify a front region where instabilities are triggered and an accurate (iteratively improved) solution is required. Outside the front region the problem is upscaled and both flow and transport are solved only at the coarse scale. This adaptive strategy leads to very accurate solutions at roughly the same computational cost as the non-iterative MsFV method. In many circumstances, however, an accurate description of flow instabilities requires a refinement of the computational grid rather than a coarsening. For these problems, we propose a modified iterative MsFV, which can be used as downscaling method (DMsFV). Compared to other grid refinement techniques the DMsFV clearly separates the computational domain into refined and non-refined regions, which can be treated separately and matched later. This gives great flexibility to employ different physical descriptions in different regions, where different equations could be solved, offering an excellent framework to construct hybrid methods.

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Abstract : This work is concerned with the development and application of novel unsupervised learning methods, having in mind two target applications: the analysis of forensic case data and the classification of remote sensing images. First, a method based on a symbolic optimization of the inter-sample distance measure is proposed to improve the flexibility of spectral clustering algorithms, and applied to the problem of forensic case data. This distance is optimized using a loss function related to the preservation of neighborhood structure between the input space and the space of principal components, and solutions are found using genetic programming. Results are compared to a variety of state-of--the-art clustering algorithms. Subsequently, a new large-scale clustering method based on a joint optimization of feature extraction and classification is proposed and applied to various databases, including two hyperspectral remote sensing images. The algorithm makes uses of a functional model (e.g., a neural network) for clustering which is trained by stochastic gradient descent. Results indicate that such a technique can easily scale to huge databases, can avoid the so-called out-of-sample problem, and can compete with or even outperform existing clustering algorithms on both artificial data and real remote sensing images. This is verified on small databases as well as very large problems. Résumé : Ce travail de recherche porte sur le développement et l'application de méthodes d'apprentissage dites non supervisées. Les applications visées par ces méthodes sont l'analyse de données forensiques et la classification d'images hyperspectrales en télédétection. Dans un premier temps, une méthodologie de classification non supervisée fondée sur l'optimisation symbolique d'une mesure de distance inter-échantillons est proposée. Cette mesure est obtenue en optimisant une fonction de coût reliée à la préservation de la structure de voisinage d'un point entre l'espace des variables initiales et l'espace des composantes principales. Cette méthode est appliquée à l'analyse de données forensiques et comparée à un éventail de méthodes déjà existantes. En second lieu, une méthode fondée sur une optimisation conjointe des tâches de sélection de variables et de classification est implémentée dans un réseau de neurones et appliquée à diverses bases de données, dont deux images hyperspectrales. Le réseau de neurones est entraîné à l'aide d'un algorithme de gradient stochastique, ce qui rend cette technique applicable à des images de très haute résolution. Les résultats de l'application de cette dernière montrent que l'utilisation d'une telle technique permet de classifier de très grandes bases de données sans difficulté et donne des résultats avantageusement comparables aux méthodes existantes.

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For well over 100 years, the Working Stress Design (WSD) approach has been the traditional basis for geotechnical design with regard to settlements or failure conditions. However, considerable effort has been put forth over the past couple of decades in relation to the adoption of the Load and Resistance Factor Design (LRFD) approach into geotechnical design. With the goal of producing engineered designs with consistent levels of reliability, the Federal Highway Administration (FHWA) issued a policy memorandum on June 28, 2000, requiring all new bridges initiated after October 1, 2007, to be designed according to the LRFD approach. Likewise, regionally calibrated LRFD resistance factors were permitted by the American Association of State Highway and Transportation Officials (AASHTO) to improve the economy of bridge foundation elements. Thus, projects TR-573, TR-583 and TR-584 were undertaken by a research team at Iowa State University’s Bridge Engineering Center with the goal of developing resistance factors for pile design using available pile static load test data. To accomplish this goal, the available data were first analyzed for reliability and then placed in a newly designed relational database management system termed PIle LOad Tests (PILOT), to which this first volume of the final report for project TR-573 is dedicated. PILOT is an amalgamated, electronic source of information consisting of both static and dynamic data for pile load tests conducted in the State of Iowa. The database, which includes historical data on pile load tests dating back to 1966, is intended for use in the establishment of LRFD resistance factors for design and construction control of driven pile foundations in Iowa. Although a considerable amount of geotechnical and pile load test data is available in literature as well as in various State Department of Transportation files, PILOT is one of the first regional databases to be exclusively used in the development of LRFD resistance factors for the design and construction control of driven pile foundations. Currently providing an electronically organized assimilation of geotechnical and pile load test data for 274 piles of various types (e.g., steel H-shaped, timber, pipe, Monotube, and concrete), PILOT (http://srg.cce.iastate.edu/lrfd/) is on par with such familiar national databases used in the calibration of LRFD resistance factors for pile foundations as the FHWA’s Deep Foundation Load Test Database. By narrowing geographical boundaries while maintaining a high number of pile load tests, PILOT exemplifies a model for effective regional LRFD calibration procedures.

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In response to the mandate on Load and Resistance Factor Design (LRFD) implementations by the Federal Highway Administration (FHWA) on all new bridge projects initiated after October 1, 2007, the Iowa Highway Research Board (IHRB) sponsored these research projects to develop regional LRFD recommendations. The LRFD development was performed using the Iowa Department of Transportation (DOT) Pile Load Test database (PILOT). To increase the data points for LRFD development, develop LRFD recommendations for dynamic methods, and validate the results ofLRFD calibration, 10 full-scale field tests on the most commonly used steel H-piles (e.g., HP 10 x 42) were conducted throughout Iowa. Detailed in situ soil investigations were carried out, push-in pressure cells were installed, and laboratory soil tests were performed. Pile responses during driving, at the end of driving (EOD), and at re-strikes were monitored using the Pile Driving Analyzer (PDA), following with the CAse Pile Wave Analysis Program (CAPWAP) analysis. The hammer blow counts were recorded for Wave Equation Analysis Program (WEAP) and dynamic formulas. Static load tests (SLTs) were performed and the pile capacities were determined based on the Davisson’s criteria. The extensive experimental research studies generated important data for analytical and computational investigations. The SLT measured loaddisplacements were compared with the simulated results obtained using a model of the TZPILE program and using the modified borehole shear test method. Two analytical pile setup quantification methods, in terms of soil properties, were developed and validated. A new calibration procedure was developed to incorporate pile setup into LRFD.

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An equation for mean first-passage times of non-Markovian processes driven by colored noise is derived through an appropriate backward integro-differential equation. The equation is solved in a Bourret-like approximation. In a weak-noise bistable situation, non-Markovian effects are taken into account by an effective diffusion coefficient. In this situation, our results compare satisfactorily with other approaches and experimental data.

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We present a theoretical study of the recently observed dynamical regimes of paramagnetic colloidal particles externally driven above a regular lattice of magnetic bubbles [P. Tierno, T. H. Johansen, and T. M. Fischer, Phys. Rev. Lett. 99, 038303 (2007)]. An external precessing magnetic field alters the potential generated by the surface of the film in such a way to either drive the particle circularly around one bubble, ballistically through the array, or in triangular orbits on the interstitial regions between the bubbles. In the ballistic regime, we observe different trajectories performed by the particles phase locked with the external driving. Superdiffusive motion, which was experimentally found bridging the localized and delocalized dynamics, emerge only by introducing a certain degree of randomness into the bubbles size distribution.

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In this note we prove an existence and uniqueness result for the solution of multidimensional stochastic delay differential equations with normal reflection. The equations are driven by a fractional Brownian motion with Hurst parameter H > 1/2. The stochastic integral with respect to the fractional Brownian motion is a pathwise Riemann¿Stieltjes integral.

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We consider the Cauchy problem for a stochastic delay differential equation driven by a fractional Brownian motion with Hurst parameter H>¿. We prove an existence and uniqueness result for this problem, when the coefficients are sufficiently regular. Furthermore, if the diffusion coefficient is bounded away from zero and the coefficients are smooth functions with bounded derivatives of all orders, we prove that the law of the solution admits a smooth density with respect to Lebesgue measure on R.

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We present a programmable microcontroller-driven injection system for the exchange of imaging medium during atomic force microscopy. Using this low-noise system, high-resolution imaging can be performed during this process of injection without disturbance. This latter circumstance was exemplified by the online imaging of conformational changes in DNA molecules during the injection of anticancer drug into the fluid chamber.