894 resultados para Scaling Criteria


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The effect of scaling (1 μm to 0.09 μm) on the non-quasi-static (NQS) behaviour of the MOSFET has been studied using process and device simulation. It is shown that under fixed gate (Vgs) and drain (Vds) bias voltages, the NQS transition frequency (fNQS) scales as 1/Leff rather than 1/L2eff due to the velocity saturation effect. However, under the practical scaling guidelines, considering the scaling of supply voltage as well, fNQS shows a turn around effect at the sub 100 nm regime. The relation between unity gain frequency (ft) and fNQS is also evaluated and it is shown that ft and fNQS have similar trends with scaling.

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A generalized power tracking algorithm that minimizes power consumption of digital circuits by dynamic control of supply voltage and the body bias is proposed. A direct power monitoring scheme is proposed that does not need any replica and hence can sense total power consumed by load circuit across process, voltage, and temperature corners. Design details and performance of power monitor and tracking algorithm are examined by a simulation framework developed using UMC 90-nm CMOS triple well process. The proposed algorithm with direct power monitor achieves a power savings of 42.2% for activity of 0.02 and 22.4% for activity of 0.04. Experimental results from test chip fabricated in AMS 350 nm process shows power savings of 46.3% and 65% for load circuit operating in super threshold and near sub-threshold region, respectively. Measured resolution of power monitor is around 0.25 mV and it has a power overhead of 2.2% of die power. Issues with loop convergence and design tradeoff for power monitor are also discussed in this paper.

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We study the quenching dynamics of a many-body system in one dimension described by a Hamiltonian that has spatial periodicity. Specifically, we consider a spin-1/2 chain with equal xx and yy couplings and subject to a periodically varying magnetic field in the (z) over cap direction or, equivalently, a tight-binding model of spinless fermions with a periodic local chemical potential, having period 2q, where q is a positive integer. For a linear quench of the strength of the magnetic field (or chemical potential) at a rate 1/tau across a quantum critical point, we find that the density of defects thereby produced scales as 1/tau(q/(q+1)), deviating from the 1/root tau scaling that is ubiquitous in a range of systems. We analyze this behavior by mapping the low-energy physics of the system to a set of fermionic two-level systems labeled by the lattice momentum k undergoing a nonlinear quench as well as by performing numerical simulations. We also show that if the magnetic field is a superposition of different periods, the power law depends only on the smallest period for very large values of tau, although it may exhibit a crossover at intermediate values of tau. Finally, for the case where a zz coupling is also present in the spin chain, or equivalently, where interactions are present in the fermionic system, we argue that the power associated with the scaling law depends on a combination of q and the interaction strength.

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Scaling laws are represented in power law form and can be utilized to extract the characteristic properties of a new phenomenon with the help of self-similar solutions. In this work, an attempt has been made to propose a scaling law analytically, for plain concrete when subjected to variable amplitude loading. Due to the application of overload on concrete structures, acceleration in the crack growth process takes place. A closed form expression has been developed to capture the acceleration in crack growth rate in conjunction with the principles of dimensional analysis and self-similarity. The proposed model accounts for parameters such as, the tensile strength, fracture toughness, overload effect and the structural size. Knowing the governed and the governing parameters of the physical problem and by using the concepts of self-similarity, a relationship is obtained between the different parameters involved. The predicted results are compared with experimental crack growth data for variable amplitude loading and are found to capture the overload effect with sufficient accuracy. Through a sensitivity analysis, fracture toughness is found to be the most dominant parameter in accelerating the crack length due to application of overload.

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This letter develops theoretical relationships for equilibrium timescale and temperature scale of a vaporizing droplet in a convective and a radiative environment. The transient temperature normalized by the respective scales exhibits a unified profile for both modes of heating. The analysis allows for the prediction of the required laser flux to show its equivalence in a corresponding heated gas stream. The theoretical equivalence shows good agreement with experiments across a range of droplet sizes. Simple experiments can be conducted in a levitator to extrapolate information in realistic convective environments like combustion and spray drying. (C) 2012 American Institute of Physics. http://dx.doi.org/10.1063/1.4720092]

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A minimum weight design of laminated composite structures is carried out for different loading conditions and failure criteria using genetic algorithm. The phenomenological maximum stress (MS) and Tsai-Wu (TW) criteria and the micro-mechanism-based failure mechanism based (FMB) failure criteria are considered. A new failure envelope called the Most Conservative Failure Envelope (MCFE) is proposed by combining the three failure envelopes based on the lowest absolute values of the strengths predicted. The effect of shear loading on the MCFE is investigated. The interaction between the loading conditions, failure criteria, and strength-based optimal design is brought out.

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Among all methods of metal alloy slurry preparation, the cooling slope method is the simplest in terms of design and process control. The method involves pouring of the melt from top, down an oblique and channel shaped plate cooled from bottom by counter flowing water. The melt, while flowing down, partially solidifies and forms columnar dendrites on plate wall. These dendrites are broken into equiaxed grains and are washed away with melt. The melt, together with the equiaxed grains, forms semisolid slurry collected at the slope exit and cast into billets having non-dendritic microstructure. The final microstructure depends on several process parameters such as slope angle, slope length, pouring superheat, and cooling rate. The present work involves scaling analysis of conservation equations of momentum, energy and species for the melt flow down a cooling slope. The main purpose of the scaling analysis is to obtain a physical insight into the role and relative importance of each parameter in influencing the final microstructure. For assessing the scaling analysis, the trends predicted by scaling are compared against corresponding numerical results using an enthalpy based solidification model with incorporation of solid phase movement.

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Organic plastic crystalline soft matter ion conductors are interesting alternatives to liquid electrolytes in electrochemical storage devices such as Lithium-ion batteries. The solvent dynamics plays a major role in determining the ion transport in plastic crystalline ion conductors. We present here an analysis of the frequency-dependent ionic conductivity of succinonitrile-based plastic crystalline ion conductors at varying salt composition (0.005 to 1 M) and temperature (-20 to 60 degrees C) using time-temperature superposition principle (TTSP). The main motivation of the work has been to establish comprehensive insight into the ion transport mechanism from a single method viz, impedance spectroscopy rather than employing cluster of different characterization methods probing various length and time scales. The TTSP remarkably aids in explicit identification of the extent of the roles of solvent dynamics and ion-ion interactions on the effective conductivity of the orientationally disordered plastic crystalline ion conductors.

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Dynamic Voltage and Frequency Scaling (DVFS) offers a huge potential for designing trade-offs involving energy, power, temperature and performance of computing systems. In this paper, we evaluate three different DVFS schemes - our enhancement of a Petri net performance model based DVFS method for sequential programs to stream programs, a simple profile based Linear Scaling method, and an existing hardware based DVFS method for multithreaded applications - using multithreaded stream applications, in a full system Chip Multiprocessor (CMP) simulator. From our evaluation, we find that the software based methods achieve significant Energy/Throughput2(ET−2) improvements. The hardware based scheme degrades performance heavily and suffers ET−2 loss. Our results indicate that the simple profile based scheme achieves the benefits of the complex Petri net based scheme for stream programs, and present a strong case for the need for independent voltage/frequency control for different cores of CMPs, which is lacking in most of the state-of-the-art CMPs. This is in contrast to the conclusions of a recent evaluation of per-core DVFS schemes for multithreaded applications for CMPs.

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We report thermally induced instability leading to catastrophic breakup in acoustically levitated vaporizing fuel droplets. Change in surface tension and viscosity with increase in droplet temperature causes wide fluctuations in droplet aspect ratio. If the viscous damping of aspect ratio oscillation is not strong enough, the droplet goes through unbounded stretching. If the droplet exceeds a critical Weber number locally, a bag type and capillary wave induced atomization can occur, which leads to catastrophic breakup. A stability criterion has been established based on the inhomogeneity of Bernoulli (acoustic) pressure and surface tension of the droplet in terms of a local Weber number and Ohnesorge number. This instability is thermally induced in a droplet which does not experience instabilities without heating. (C) 2012 Elsevier Ltd. All rights reserved.

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We address the problem of speech enhancement using a risk- estimation approach. In particular, we propose the use the Stein’s unbiased risk estimator (SURE) for solving the problem. The need for a suitable finite-sample risk estimator arises because the actual risks invariably depend on the unknown ground truth. We consider the popular mean-squared error (MSE) criterion first, and then compare it against the perceptually-motivated Itakura-Saito (IS) distortion, by deriving unbiased estimators of the corresponding risks. We use a generalized SURE (GSURE) development, recently proposed by Eldar for MSE. We consider dependent observation models from the exponential family with an additive noise model,and derive an unbiased estimator for the risk corresponding to the IS distortion, which is non-quadratic. This serves to address the speech enhancement problem in a more general setting. Experimental results illustrate that the IS metric is efficient in suppressing musical noise, which affects the MSE-enhanced speech. However, in terms of global signal-to-noise ratio (SNR), the minimum MSE solution gives better results.

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In this paper we clarify the role of Markstein diffusivity, which is the product of the planar laminar flame speed and the Markstein length, on the turbulent flame speed and its scaling, based on experimental measurements on constant-pressure expanding turbulent flames. Turbulent flame propagation data are presented for premixed flames of mixtures of hydrogen, methane, ethylene, n-butane, and dimethyl ether with air, in near-isotropic turbulence in a dual-chamber, fan-stirred vessel. For each individual fuel-air mixture presented in this work and the recently published iso-octane data from Leeds, normalized turbulent flame speed data of individual fuel-air mixtures approximately follow a Re-T,f(0.5) scaling, for which the average radius is the length scale and thermal diffusivity is the transport property of the turbulence Reynolds number. At a given Re-T,Re-f, it is experimentally observed that the normalized turbulent flame speed decreases with increasing Markstein number, which could be explained by considering Markstein diffusivity as the leading dissipation mechanism for the large wave number flame surface fluctuations. Consequently, by replacing thermal diffusivity with the Markstein diffusivity in the turbulence Reynolds number definition above, it is found that normalized turbulent flame speeds could be scaled by Re-T,M(0.5) irrespective of the fuel, equivalence ratio, pressure, and turbulence intensity for positive Markstein number flames.

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Accurate and timely prediction of weather phenomena, such as hurricanes and flash floods, require high-fidelity compute intensive simulations of multiple finer regions of interest within a coarse simulation domain. Current weather applications execute these nested simulations sequentially using all the available processors, which is sub-optimal due to their sub-linear scalability. In this work, we present a strategy for parallel execution of multiple nested domain simulations based on partitioning the 2-D processor grid into disjoint rectangular regions associated with each domain. We propose a novel combination of performance prediction, processor allocation methods and topology-aware mapping of the regions on torus interconnects. Experiments on IBM Blue Gene systems using WRF show that the proposed strategies result in performance improvement of up to 33% with topology-oblivious mapping and up to additional 7% with topology-aware mapping over the default sequential strategy.

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A supply chain ecosystem consists of the elements of the supply chain and the entities that influence the goods, information and financial flows through the supply chain. These influences come through government regulations, human, financial and natural resources, logistics infrastructure and management, etc., and thus affect the supply chain performance. Similarly, all the ecosystem elements also contribute to the risk. The aim of this paper is to identify both performances-based and risk-based decision criteria, which are important and critical to the supply chain. A two step approach using fuzzy AHP and fuzzy technique for order of preference by similarity to ideal solution has been proposed for multi-criteria decision-making and illustrated using a numerical example. The first step does the selection without considering risks and then in the next step suppliers are ranked according to their risk profiles. Later, the two ranks are consolidated into one. In subsequent section, the method is also extended for multi-tier supplier selection. In short, we are presenting a method for the design of a resilient supply chain, in this paper.