989 resultados para Dynamic Equations


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This paper reports the dynamic compression behavior of ultrafine grained (Hf, Zr)B-2-SiC composites, sintered using reactive spark plasma sintering at 1600 degrees C for 10 min. Dynamic strength of similar to 2.3 GPa has been measured using Split Hopkinson Pressure Bar (SHPB) tests in a reproducible manner at strain rates of 800-1300 s(-1). A comparison with competing boride based armor ceramics, in reference to the spectrum of properties evaluated, establishes the potential of (Hf, Zr)B-2-SiC composites for armor applications. (C) 2015 Elsevier Ltd and Techna Group S.r.l. All rights reserved.

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Experiments on micrograined (mg) and nanocrystalline (nc) Ni revealed strengthening and weakening following repeated dynamic impact. The strengthening in mg-Ni arises from intragranular dislocations without a significant change in grain size, whereas the weakening in nc-Ni is due to concurrent grain growth. The strength of mg and nc-Ni samples after deformation settles at similar to 900 MPa, with differing contributions from intragranular dislocations and grain sizes. (C) 2015 Elsevier B.V. All rights reserved.

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Piezo-composite membranes have advantages over motorized flapping where frequencies are high and certain coupling between bending and twisting is useful to generate lift and forward flight. We draw examples of fruit fly and bumble bee. Wings with Piezo ceramic PZT coating are realized. The passive mechanical response of the wing is characterized experimentally and validated using finite element simulation. Piezoelectric actuation with uniform electrode coating is characterized and optimal frequencies for flapping are identified. The experimental data are used in an empirical model and advanced ratio for a flapping insect like condition for various angular orientations is estimated.

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An abundance of spectrum access and sensing algorithms are available in the dynamic spectrum access (DSA) and cognitive radio (CR) literature. Often, however, the functionality and performance of such algorithms are validated against theoretical calculations using only simulations. Both the theoretical calculations and simulations come with their attendant sets of assumptions. For instance, designers of dynamic spectrum access algorithms often take spectrum sensing and rendezvous mechanisms between transmitter-receiver pairs for granted. Test bed designers, on the other hand, either customize so much of their design that it becomes difficult to replicate using commercial off the shelf (COTS) components or restrict themselves to simulation, emulation /hardware-in-Ioop (HIL), or pure hardware but not all three. Implementation studies on test beds sophisticated enough to combine the three aforementioned aspects, but at the same time can also be put together using COTS hardware and software packages are rare. In this paper we describe i) the implementation of a hybrid test bed using a previously proposed hardware agnostic system architecture ii) the implementation of DSA on this test bed, and iii) the realistic hardware and software-constrained performance of DSA. Snapshot energy detector (ED) and Cumulative Summation (CUSUM), a sequential change detection algorithm, are available for spectrum sensing and a two-way handshake mechanism in a dedicated control channel facilitates transmitter-receiver rendezvous.

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In this paper, we design a new dynamic packet scheduling scheme suitable for differentiated service (DiffServ) network. Designed dynamic benefit weighted scheduling (DBWS) uses a dynamic weighted computation scheme loosely based on weighted round robin (WRR) policy. It predicts the weight required by expedited forwarding (EF) service for the current time slot (t) based on two criteria; (i) previous weight allocated to it at time (t-1), and (ii) the average increase in the queue length of EF buffer. This prediction provides smooth bandwidth allocation to all the services by avoiding overbooking of resources for EF service and still providing guaranteed services for it. The performance is analyzed for various scenarios at high, medium and low traffic conditions. The results show that packet loss is minimized, end to end delay is minimized and jitter is reduced and therefore meet quality of service (QoS) requirement of a network.

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The current day networks use Proactive networks for adaption to the dynamic scenarios. The use of cognition technique based on the Observe, Orient, Decide and Act loop (OODA) is proposed to construct proactive networks. The network performance degradation in knowledge acquisition and malicious node presence is a problem that exists. The use of continuous time dynamic neural network is considered to achieve cognition. The variance in service rates of user nodes is used to detect malicious activity in heterogeneous networks. The improved malicious node detection rates are proved through the experimental results presented in this paper. (C) 2015 The Authors. Published by Elsevier B.V.

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From sensing perspective, smaller electromechanical devices, in general, are expected to be more responsive to the stimuli. This enhanced performance, however, is contingent upon the noise sources remaining unchanged and the onset of nonlinear behavior not being precipitated by miniaturization. In this paper, we study the effect of strain on the nonlinearities and dynamic range in graphene nanoresonators. The dynamic response and the onset of nonlinearity in these devices are sensitive both to the electrostatic field used to actuate the device and the strain. By tuning the strain of the device by two orders of magnitude, we observe an enhancement of 25 dB in the dynamic range leading to a mass resolution of 100 yoctogram. The increase in dynamic range in our devices is modeled as a combined effect of strain and partial cancellation of elastic and electrostatic nonlinearities. (C) 2015 AIP Publishing LLC.

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This paper presents the development and application of a stochastic dynamic programming model with fuzzy state variables for irrigation of multiple crops. A fuzzy stochastic dynamic programming (FSDP) model is developed in which the reservoir storage and soil moisture of the crops are considered as fuzzy numbers, and the reservoir inflow is considered as a stochastic variable. The model is formulated with an objective of minimizing crop yield deficits, resulting in optimal water allocations to the crops by maintaining storage continuity and soil moisture balance. The standard fuzzy arithmetic method is used to solve all arithmetic equations with fuzzy numbers, and the fuzzy ranking method is used to compare two or more fuzzy numbers. The reservoir operation model is integrated with a daily-based water allocation model, which results in daily temporal variations of allocated water, soil moisture, and crop deficits. A case study of an existing Bhadra reservoir in Karnataka, India, is chosen for the model application. The FSDP is a more realistic model because it considers the uncertainty in discretization of state variables. The results obtained using the FSDP model are found to be more acceptable for the case study than those of the classical stochastic dynamic model and the standard operating model, in terms of 10-day releases from the reservoir and evapotranspiration deficit. (C) 2015 American Society of Civil Engineers.

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A modified approach to obtain approximate numerical solutions of Fredholin integral equations of the second kind is presented. The error bound is explained by the aid of several illustrative examples. In each example, the approximate solution is compared with the exact solution, wherever possible, and an excellent agreement is observed. In addition, the error bound in each example is compared with the one obtained by the Nystrom method. It is found that the error bound of the present method is smaller than the ones obtained by the Nystrom method. Further, the present method is successfully applied to derive the solution of an integral equation arising in a special Dirichlet problem. (C) 2015 Elsevier Inc. All rights reserved.

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Analysis of the variability in the responses of large structural systems and quantification of their linearity or nonlinearity as a potential non-invasive means of structural system assessment from output-only condition remains a challenging problem. In this study, the Delay Vector Variance (DVV) method is used for full scale testing of both pseudo-dynamic and dynamic responses of two bridges, in order to study the degree of nonlinearity of their measured response signals. The DVV detects the presence of determinism and nonlinearity in a time series and is based upon the examination of local predictability of a signal. The pseudo-dynamic data is obtained from a concrete bridge during repair while the dynamic data is obtained from a steel railway bridge traversed by a train. We show that DVV is promising as a marker in establishing the degree to which a change in the signal nonlinearity reflects the change in the real behaviour of a structure. It is also useful in establishing the sensitivity of instruments or sensors deployed to monitor such changes. (C) 2015 Elsevier B.V. All rights reserved.

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The cybernetic modeling framework provides an interesting approach to model the regulatory phenomena occurring in microorganisms. In the present work, we adopt a constraints based approach to analyze the nonlinear behavior of the extended equations of the cybernetic model. We first show that the cybernetic model exhibits linear growth behavior under the constraint of no resource allocation for the induction of the key enzyme. We then quantify the maximum achievable specific growth rate of microorganisms on mixtures of substitutable substrates under various kinds of regulation and show its use in gaining an understanding of the regulatory strategies of microorganisms. Finally, we show that Saccharomyces cerevisiae exhibits suboptimal dynamic growth with a long diauxic lag phase when growing on a mixture of glucose and galactose and discuss on its potential to achieve optimal growth with a significantly reduced diauxic lag period. The analysis carried out in the present study illustrates the utility of adopting a constraints based approach to understand the dynamic growth strategies of microorganisms. (C) 2015 Elsevier Ireland Ltd. All rights reserved.

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In this paper, we present the solutions of 1-D and 2-D non-linear partial differential equations with initial conditions. We approach the solutions in time domain using two methods. We first solve the equations using Fourier spectral approximation in the spatial domain and secondly we compare the results with the approximation in the spatial domain using orthogonal functions such as Legendre or Chebyshev polynomials as their basis functions. The advantages and the applicability of the two different methods for different types of problems are brought out by considering 1-D and 2-D nonlinear partial differential equations namely the Korteweg-de-Vries and nonlinear Schrodinger equation with different potential function. (C) 2015 Elsevier Ltd. All rights reserved.

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We report on the resonant frequency modulation of inertial microelectromechanical systems (MEMS) structures due to squeeze film stiffness over a range of working pressures. Squeeze film effects have been studied extensively, but mostly in the context of damping and Q-factor determination of dynamic MEMS structures, typically suspended over a fixed substrate with a very thin air gap. Here, we show with experimental measurements and analytical calculations how the pressure-dependent air springs (squeeze film stiffness) change the resonant frequency of an inertial MEMS structure by as much as five times. For capturing the isolated effect of the squeeze film stiffness, we first determine the static stiffness of our structure with atomic force microscope probing and then study the effect of the air spring by measuring the dynamic response of the structure, thus finding the resonant frequencies while varying the air pressure from 1 to 905 mbar. We also verify our results by analytical and Finite Element Method calculations. Our findings show that the pressure-dependent squeeze film stiffness can affect a rather huge range of frequency modulation (>400%) and, therefore, can be used as a design parameter for exploiting this effect in MEMS devices. 2014-0310]

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The inverted pendulum is a popular model for describing bipedal dynamic walking. The operating point of the walker can be specified by the combination of initial mid-stance velocity (v(0)) and step angle (phi(m)) chosen for a given walk. In this paper, using basic mechanics, a framework of physical constraints that limit the choice of operating points is proposed. The constraint lines thus obtained delimit the allowable region of operation of the walker in the v(0)-phi(m) plane. A given average forward velocity v(x,) (avg) can be achieved by several combinations of v(0) and phi(m). Only one of these combinations results in the minimum mechanical power consumption and can be considered the optimum operating point for the given v(x, avg). This paper proposes a method for obtaining this optimal operating point based on tangency of the power and velocity contours. Putting together all such operating points for various v(x, avg,) a family of optimum operating points, called the optimal locus, is obtained. For the energy loss and internal energy models chosen, the optimal locus obtained has a largely constant step angle with increasing speed but tapers off at non-dimensional speeds close to unity.

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Nanoparticle deposition behavior observed at the Darcy scale represents an average of the processes occurring at the pore scale. Hence, the effect of various pore-scale parameters on nanoparticle deposition can be understood by studying nanoparticle transport at pore scale and upscaling the results to the Darcy scale. In this work, correlation equations for the deposition rate coefficients of nanoparticles in a cylindrical pore are developed as a function of nine pore-scale parameters: the pore radius, nanoparticle radius, mean flow velocity, solution ionic strength, viscosity, temperature, solution dielectric constant, and nanoparticle and collector surface potentials. Based on dominant processes, the pore space is divided into three different regions, namely, bulk, diffusion, and potential regions. Advection-diffusion equations for nanoparticle transport are prescribed for the bulk and diffusion regions, while the interaction between the diffusion and potential regions is included as a boundary condition. This interaction is modeled as a first-order reversible kinetic adsorption. The expressions for the mass transfer rate coefficients between the diffusion and the potential regions are derived in terms of the interaction energy profile. Among other effects, we account for nanoparticle-collector interaction forces on nanoparticle deposition. The resulting equations are solved numerically for a range of values of pore-scale parameters. The nanoparticle concentration profile obtained for the cylindrical pore is averaged over a moving averaging volume within the pore in order to get the 1-D concentration field. The latter is fitted to the 1-D advection-dispersion equation with an equilibrium or kinetic adsorption model to determine the values of the average deposition rate coefficients. In this study, pore-scale simulations are performed for three values of Peclet number, Pe = 0.05, 5, and 50. We find that under unfavorable conditions, the nanoparticle deposition at pore scale is best described by an equilibrium model at low Peclet numbers (Pe = 0.05) and by a kinetic model at high Peclet numbers (Pe = 50). But, at an intermediate Pe (e.g., near Pe = 5), both equilibrium and kinetic models fit the 1-D concentration field. Correlation equations for the pore-averaged nanoparticle deposition rate coefficients under unfavorable conditions are derived by performing a multiple-linear regression analysis between the estimated deposition rate coefficients for a single pore and various pore-scale parameters. The correlation equations, which follow a power law relation with nine pore-scale parameters, are found to be consistent with the column-scale and pore-scale experimental results, and qualitatively agree with the colloid filtration theory. These equations can be incorporated into pore network models to study the effect of pore-scale parameters on nanoparticle deposition at larger length scales such as Darcy scale.