104 resultados para Dynamic environments

em Indian Institute of Science - Bangalore - Índia


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Avoidance of collision between moving objects in a 3-D environment is fundamental to the problem of planning safe trajectories in dynamic environments. This problem appears in several diverse fields including robotics, air vehicles, underwater vehicles and computer animation. Most of the existing literature on collision prediction assumes objects to be modelled as spheres. While the conservative spherical bounding box is valid in many cases, in many other cases, where objects operate in close proximity, a less conservative approach, that allows objects to be modelled using analytic surfaces that closely mimic the shape of the object, is more desirable. In this paper, a collision cone approach (previously developed only for objects moving on a plane) is used to determine collision between objects, moving in 3-D space, whose shapes can be modelled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained and used to derive dynamic inversion based avoidance strategies.

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The problem of collision prediction in dynamic environments appears in several diverse fields, which include robotics, air vehicles, underwater vehicles, and computer animation. In this paper, collision prediction of objects that move in 3-D environments is considered. Most work on collision prediction assumes objects to be modeled as spheres. However, there are many instances of object shapes where an ellipsoidal or a hyperboloid-like bounding box would be more appropriate. In this paper, a collision cone approach is used to determine collision between objects whose shapes can be modeled by general quadric surfaces. Exact collision conditions for such quadric surfaces are obtained in the form of analytical expressions in the relative velocity space. For objects of arbitrary shapes, exact representations of planar sections of the 3-D collision cone are obtained.

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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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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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In this paper, we use reinforcement learning (RL) as a tool to study price dynamics in an electronic retail market consisting of two competing sellers, and price sensitive and lead time sensitive customers. Sellers, offering identical products, compete on price to satisfy stochastically arriving demands (customers), and follow standard inventory control and replenishment policies to manage their inventories. In such a generalized setting, RL techniques have not previously been applied. We consider two representative cases: 1) no information case, were none of the sellers has any information about customer queue levels, inventory levels, or prices at the competitors; and 2) partial information case, where every seller has information about the customer queue levels and inventory levels of the competitors. Sellers employ automated pricing agents, or pricebots, which use RL-based pricing algorithms to reset the prices at random intervals based on factors such as number of back orders, inventory levels, and replenishment lead times, with the objective of maximizing discounted cumulative profit. In the no information case, we show that a seller who uses Q-learning outperforms a seller who uses derivative following (DF). In the partial information case, we model the problem as a Markovian game and use actor-critic based RL to learn dynamic prices. We believe our approach to solving these problems is a new and promising way of setting dynamic prices in multiseller environments with stochastic demands, price sensitive customers, and inventory replenishments.

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In this paper, we investigate the use of reinforcement learning (RL) techniques to the problem of determining dynamic prices in an electronic retail market. As representative models, we consider a single seller market and a two seller market, and formulate the dynamic pricing problem in a setting that easily generalizes to markets with more than two sellers. We first formulate the single seller dynamic pricing problem in the RL framework and solve the problem using the Q-learning algorithm through simulation. Next we model the two seller dynamic pricing problem as a Markovian game and formulate the problem in the RL framework. We solve this problem using actor-critic algorithms through simulation. We believe our approach to solving these problems is a promising way of setting dynamic prices in multi-agent environments. We illustrate the methodology with two illustrative examples of typical retail markets.

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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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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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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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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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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.

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The variable temperature 1H and 13C NMR behaviour of two trisubstituted thioureas, namely N,N-diethyl N'-(2-thiazolyl) thiourea and N,N-diethyl N'-(3-pyridyl)thiourea has been investigated. The barrier to rotation of the diethylamino group has been obtained.