996 resultados para dynamic mesh


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Although LH is essential for survival and function of the corpus luteum (CL) in higher primates, luteolysis occurs during nonfertile cycles without a discernible decrease in circulating LH levels. Using genome-wide expression analysis, several experiments were performed to examine the processes of luteolysis and rescue of luteal function in monkeys. Induced luteolysis with GnRH receptor antagonist (Cetrorelix) resulted in differential regulation of 3949 genes, whereas replacement with exogenous LH (Cetrorelix plus LH) led to regulation of 4434 genes (1563 down-regulation and 2871 up-regulation). A model system for prostaglandin (PG) F-2 alpha-induced luteolysis in the monkey was standardized and demonstrated that PGF(2 alpha) regulated expression of 2290 genes in the CL. Analysis of the LH-regulated luteal transcriptome revealed that 120 genes were regulated in an antagonistic fashion by PGF(2 alpha). Based on the microarray data, 25 genes were selected for validation by real-time RT-PCR analysis, and expression of these genes was also examined in the CL throughout the luteal phase and from monkeys treated with human chorionic gonadotropin (hCG) to mimic early pregnancy. The results indicated changes in expression of genes favorable to PGF(2 alpha) action during the late to very late luteal phase, and expressions of many of these genes were regulated in an opposite manner by exogenous hCG treatment. Collectively, the findings suggest that curtailment of expression of downstream LH-target genes possibly through PGF(2 alpha) action on the CL is among the mechanisms underlying cross talk between the luteotropic and luteolytic signaling pathways that result in the cessation of luteal function, but hCG is likely to abrogate the PGF(2 alpha)-responsive gene expression changes resulting in luteal rescue crucial for the maintenance of early pregnancy. (Endocrinology 150: 1473-1484, 2009)

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Among the multitude of test specimen geometries used for dynamic fiacture toughness evaluation, the most widely uscd specimen is lhc Chavpy specimen due its simple geomclry and availability of testing machines. The standard Chatpy specimen dimensions may llOl always give plane st~ain condilions and hence, it may be necessary Io coilduct lcs/s using specimens of dillEvcnt thicknesses to establish the plane strain K~a. An axisymmct/ic specimen, on the otlaev hand would always give flow constraints l~n a nominal specimen thickness i~rcspcctive of the test matctial. The notched disk specimen pVOl)oscd by Bcrn:ud ctal. [1] for static and dynamic initiation toughness measurement although p~ovicles plain-strain conditions, the crack plopagatcs at an angle to the direction of applied load. This makes inteq~retation of the test results difficult us it ~Ccluivcs ~actial slices to be cut fiom the fractured specimen to ascertain the angle o1 crack growth and a linite element model l~)r tl);t{ pa~ticulat ctack o~icntalion.

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The Artificial Neural Networks (ANNs) are being used to solve a variety of problems in pattern recognition, robotic control, VLSI CAD and other areas. In most of these applications, a speedy response from the ANNs is imperative. However, ANNs comprise a large number of artificial neurons, and a massive interconnection network among them. Hence, implementation of these ANNs involves execution of computer-intensive operations. The usage of multiprocessor systems therefore becomes necessary. In this article, we have presented the implementation of ART1 and ART2 ANNs on ring and mesh architectures. The overall system design and implementation aspects are presented. The performance of the algorithm on ring, 2-dimensional mesh and n-dimensional mesh topologies is presented. The parallel algorithm presented for implementation of ART1 is not specific to any particular architecture. The parallel algorithm for ARTE is more suitable for a ring architecture.

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An experimental investigation into the dynamic strain ageing (DSA) of a wrought Ni-base superalloy 720Li was conducted. Characteristics of jerky, flow have been studied at intermediate temperatures of 350, 400 and 450 degrees C at strain-rates between 10(-3) and 10(-5) s(-1). Serrations of Type C are predominant within the temperature/strain-rate range explored. The major characteristics of the serrations-i.e. (a) critical plastic strain for onset of serrations, epsilon(c); (b) average stress decrement, Delta sigma(avg); and (c) strain increment between serrations. Delta epsilon(BS)-have been examined at selected temperatures and strain-rates. Negative strain-rate sensitivity was observed in the DSA regime. However. temperature did not influence tensile properties such as yield strength, ultimate strength. elongation, reduction in area, and work hardening rate or fracture features in DSA regime. Analysis of the results Suggests that locking of the mobile dislocations by substitutional alloying elements is responsible for the DSA in alloy 720Li.

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Robot Path Planning (RPP) in dynamic environments is a search problem based on the examination of collision-free paths in the presence of dynamic and static obstacles. Many techniques have been developed to solve this problem. Trapping in a local minima and maintaining a Real-Time performance are known as the two most important challenges that these techniques face to solve such problem. This study presents a comprehensive survey of the various techniques that have been proposed in this domain. As part of this survey, we include a classification of the approaches and identify their methods.

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This paper presents a methodology for dynamic analysis of short term small signal voltage instability in a multi-machine power system. The formulation of the problem is done by decoupling the angle instability from the voltage instability. The method is based on the incremental reactive current flow network (IRCFN), where the incremental reactive current injection at each bus is related to the incremental voltage magnitude at all the buses. Small signal stability using the eigenvalue analysis is illustrated utilizing a single-machine load bus (SMLB) and three-machine system examples. The role of a static var compensator (SVC) at the load bus is also examined.

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Thin films are developed by dispersing carbon black nanoparticles and carbon nanotubes (CNTs) in an epoxy polymer. The films show a large variation in electrical resistance when subjected to quasi-static and dynamic mechanical loading. This phenomenon is attributed to the change in the band-gap of the CNTs due to the applied strain, and also to the change in the volume fraction of the constituent phases in the percolation network. Under quasi-static loading, the films show a nonlinear response. This nonlinearity in the response of the films is primarily attributed to the pre-yield softening of the epoxy polymer. The electrical resistance of the films is found to be strongly dependent on the magnitude and frequency of the applied dynamic strain, induced by a piezoelectric substrate. Interestingly, the resistance variation is found to be a linear function of frequency and dynamic strain. Samples with a small concentration of just 0.57% of CNT show a sensitivity as high as 2.5% MPa-1 for static mechanical loading. A mathematical model based on Bruggeman's effective medium theory is developed to better understand the experimental results. Dynamic mechanical loading experiments reveal a sensitivity as high as 0.007% Hz(-1) at a constant small-amplitude vibration and up to 0.13%/mu-strain at 0-500 Hz vibration. Potential applications of such thin films include highly sensitive strain sensors, accelerometers, artificial neural networks, artificial skin and polymer electronics.

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This paper presents the modeling and analysis of a voltage source converter (VSC) based back-to-back (BTB) HVDC link. The case study considers the response to changes in the active and reactive power and disturbance caused by single line to ground (SLG) fault. The controllers at each terminal are designed to inject a variable (magnitude and phase angle) sinusoidal, balanced set of voltages to regulate/control the active and reactive power. It is also possible to regulate the converter bus (AC) voltage by controlling the injected reactive power. The analysis is carried out using both d-q model (neglecting the harmonics in the output voltages of VSC) and three phase detailed model of VSC. While the eigenvalue analysis and controller design is based on the d-q model, the transient simulation considers both models.

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Despite great advances in very large scale integrated-circuit design and manufacturing, performance of even the best available high-speed, high-resolution analog-to-digital converter (ADC) is known to deteriorate while acquiring fast-rising, high-frequency, and nonrepetitive waveforms. Waveform digitizers (ADCs) used in high-voltage impulse recordings and measurements are invariably subjected to such waveforms. Errors resulting from a lowered ADC performance can be unacceptably high, especially when higher accuracies have to be achieved (e.g., when part of a reference measuring system). Static and dynamic nonlinearities (estimated independently) are vital indices for evaluating performance and suitability of ADCs to be used in such environments. Typically, the estimation of static nonlinearity involves 10-12 h of time or more (for a 12-b ADC) and the acquisition of millions of samples at high input frequencies for dynamic characterization. ADCs with even higher resolution and faster sampling speeds will soon become available. So, there is a need to reduce testing time for evaluating these parameters. This paper proposes a novel and time-efficient method for the simultaneous estimation of static and dynamic nonlinearity from a single test. This is achieved by conceiving a test signal, comprised of a high-frequency sinusoid (which addresses dynamic assessment) modulated by a low-frequency ramp (relevant to the static part). Details of implementation and results on two digitizers are presented and compared with nonlinearities determined by the existing standardized approaches. Good agreement in results and time savings achievable indicates its suitability.

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Timoshenko's shear deformation theory is widely used for the dynamical analysis of shear-flexible beams. This paper presents a comparative study of the shear deformation theory with a higher order model, of which Timoshenko's shear deformation model is a special case. Results indicate that while Timoshenko's shear deformation theory gives reasonably accurate information regarding the set of bending natural frequencies, there are considerable discrepancies in the information it gives regarding the mode shapes and dynamic response, and so there is a need to consider higher order models for the dynamical analysis of flexure of beams.

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Despite great advances in very large scale integrated-circuit design and manufacturing, performance of even the best available high-speed, high-resolution analog-to-digital converter (ADC) is known to deteriorate while acquiring fast-rising, high-frequency, and nonrepetitive waveforms. Waveform digitizers (ADCs) used in high-voltage impulse recordings and measurements are invariably subjected to such waveforms. Errors resulting from a lowered ADC performance can be unacceptably high, especially when higher accuracies have to be achieved (e.g., when part of a reference measuring system). Static and dynamic nonlinearities (estimated independently) are vital indices for evaluating performance and suitability of ADCs to be used in such environments. Typically, the estimation of static nonlinearity involves 10-12 h of time or more (for a 12-b ADC) and the acquisition of millions of samples at high input frequencies for dynamic characterization. ADCs with even higher resolution and faster sampling speeds will soon become available. So, there is a need to reduce testing time for evaluating these parameters. This paper proposes a novel and time-efficient method for the simultaneous estimation of static and dynamic nonlinearity from a single test. This is achieved by conceiving a test signal, comprised of a high-frequency sinusoid (which addresses dynamic assessment) modulated by a low-frequency ramp (relevant to the static part). Details of implementation and results on two digitizers are presented and compared with nonlinearities determined by the existing standardized approaches. Good agreement in results and time savings achievable indicates its suitability.

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Error estimates for the error reproducing kernel method (ERKM) are provided. The ERKM is a mesh-free functional approximation scheme [A. Shaw, D. Roy, A NURBS-based error reproducing kernel method with applications in solid mechanics, Computational Mechanics (2006), to appear (available online)], wherein a targeted function and its derivatives are first approximated via non-uniform rational B-splines (NURBS) basis function. Errors in the NURBS approximation are then reproduced via a family of non-NURBS basis functions, constructed using a polynomial reproduction condition, and added to the NURBS approximation of the function obtained in the first step. In addition to the derivation of error estimates, convergence studies are undertaken for a couple of test boundary value problems with known exact solutions. The ERKM is next applied to a one-dimensional Burgers equation where, time evolution leads to a breakdown of the continuous solution and the appearance of a shock. Many available mesh-free schemes appear to be unable to capture this shock without numerical instability. However, given that any desired order of continuity is achievable through NURBS approximations, the ERKM can even accurately approximate functions with discontinuous derivatives. Moreover, due to the variation diminishing property of NURBS, it has advantages in representing sharp changes in gradients. This paper is focused on demonstrating this ability of ERKM via some numerical examples. Comparisons of some of the results with those via the standard form of the reproducing kernel particle method (RKPM) demonstrate the relative numerical advantages and accuracy of the ERKM.

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For a multiarmed bandit problem with exponential discounting the optimal allocation rule is defined by a dynamic allocation index defined for each arm on its space. The index for an arm is equal to the expected immediate reward from the arm, with an upward adjustment reflecting any uncertainty about the prospects of obtaining rewards from the arm, and the possibilities of resolving those uncertainties by selecting that arm. Thus the learning component of the index is defined to be the difference between the index and the expected immediate reward. For two arms with the same expected immediate reward the learning component should be larger for the arm for which the reward rate is more uncertain. This is shown to be true for arms based on independent samples from a fixed distribution with an unknown parameter in the cases of Bernoulli and normal distributions, and similar results are obtained in other cases.

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During the past few decades, developing efficient methods to solve dynamic facility layout problems has been focused on significantly by practitioners and researchers. More specifically meta-heuristic algorithms, especially genetic algorithm, have been proven to be increasingly helpful to generate sub-optimal solutions for large-scale dynamic facility layout problems. Nevertheless, the uncertainty of the manufacturing factors in addition to the scale of the layout problem calls for a mixed genetic algorithm–robust approach that could provide a single unlimited layout design. The present research aims to devise a customized permutation-based robust genetic algorithm in dynamic manufacturing environments that is expected to be generating a unique robust layout for all the manufacturing periods. The numerical outcomes of the proposed robust genetic algorithm indicate significant cost improvements compared to the conventional genetic algorithm methods and a selective number of other heuristic and meta-heuristic techniques.

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A new method of modeling material behavior which accounts for the dynamic metallurgical processes occurring during hot deformation is presented. The approach in this method is to consider the workpiece as a dissipator of power in the total processing system and to evaluate the dissipated power co-contentJ = ∫o σ ε ⋅dσ from the constitutive equation relating the strain rate (ε) to the flow stress (σ). The optimum processing conditions of temperature and strain rate are those corresponding to the maximum or peak inJ. It is shown thatJ is related to the strain-rate sensitivity (m) of the material and reaches a maximum value(J max) whenm = 1. The efficiency of the power dissipation(J/J max) through metallurgical processes is shown to be an index of the dynamic behavior of the material and is useful in obtaining a unique combination of temperature and strain rate for processing and also in delineating the regions of internal fracture. In this method of modeling, noa priori knowledge or evaluation of the atomistic mechanisms is required, and the method is effective even when more than one dissipation process occurs, which is particularly advantageous in the hot processing of commercial alloys having complex microstructures. This method has been applied to modeling of the behavior of Ti-6242 during hot forging. The behavior of α+ β andβ preform microstructures has been exam-ined, and the results show that the optimum condition for hot forging of these preforms is obtained at 927 °C (1200 K) and a strain rate of 1CT•3 s•1. Variations in the efficiency of dissipation with temperature and strain rate are correlated with the dynamic microstructural changes occurring in the material.