The Experts below are selected from a list of 324 Experts worldwide ranked by ideXlab platform
R Nuoezqueija - One of the best experts on this subject based on the ideXlab platform.
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heavy traffic analysis of a multiple Phase Network with discriminatory processor sharing
Operations Research, 2011Co-Authors: I M Verloop, Urtzi Ayesta, R NuoezqueijaAbstract:We analyze a generalization of the discriminatory processor-sharing (DPS) queue in a heavy-traffic setting. Customers present in the system are served simultaneously at rates controlled by a vector of weights. We assume that customers have Phase-type distributed service requirements and allow that customers have different weights in various Phases of their service. In our main result we establish a state-space collapse for the queue-length vector in heavy traffic. The result shows that in the limit, the queue-length vector is the product of an exponentially distributed random variable and a deterministic vector. This generalizes a previous result by Rege and Sengupta [Rege, K. M., B. Sengupta. 1996. Queue length distribution for the discriminatory processor-sharing queue. Oper. Res.44(4) 653--657], who considered a DPS queue with exponentially distributed service requirements. Their analysis was based on obtaining all moments of the queue-length distributions by solving systems of linear equations. We undertake a more direct approach by showing that the probability-generating function satisfies a partial differential equation that allows a closed-form solution after passing to the heavy-traffic limit. Making use of the state-space collapse result, we derive interesting properties in heavy traffic: (i) For the DPS queue, we obtain that, conditioned on the number of customers in the system, the residual service requirements are asymptotically independent and distributed according to the forward recurrence times. (ii) We then investigate how the choice for the weights influences the asymptotic performance of the system. In particular, for the DPS queue we show that the scaled holding cost reduces as classes with a higher value for dk/E(Bkfwd) obtain a larger share of the capacity, where dk is the cost associated to class k, and E(Bkfwd) is the forward recurrence time of the class-k service requirement. The applicability of this result for a moderately loaded system is investigated by numerical experiments.
W. Theisen - One of the best experts on this subject based on the ideXlab platform.
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Effect of heat treatment on Phase structure and thermal conductivity of a copper-infiltrated steel
Journal of Materials Science, 2015Co-Authors: S. Klein, S. Weber, W. TheisenAbstract:Infiltration of tool steels with copper is a suitable and cheap method to create dense parts using powder metallurgy. In this work, it is shown that the copper Network that forms inside the steel skeleton during infiltration enhances the thermal conductivity of the resulting composite. The level of enhancement is dependent on the thermal conductivity of the copper Phase and the volume fraction of copper. Multiple heat treatments of this composite revealed a strong dependency between the thermal conductivity of the composite and the solution state of Fe in the copper Network. The latter is highly dependent on the heat-treated condition of the multi-Phase material. Using infiltration, the thermal and electrical conductivity was increased from $$21.3\hbox { to }50.1\,\hbox {Wm}^{-1}\, \hbox {K}^{-1}$$ 21.3 to 50.1 Wm - 1 K - 1 and from $$2.5\,\hbox { to }7.7\,{\upmu \Omega }^{-1}\, \hbox {m}^{-1},$$ 2.5 to 7.7 μ Ω - 1 m - 1 , respectively, for aged steel-copper composite in comparison with original X245VCrMo9-4-4 steel. In addition, a model alloy that represents the copper-Phase Network in the composite was manufactured. By measuring both, the thermal conductivity of this model alloy and the bulk steel, and comparing it to the data for the composite, different models for calculating the overall conductivity of the composite are discussed.
Hua Wang - One of the best experts on this subject based on the ideXlab platform.
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a transformer based poly Phase Network for ultra broadband quadrature signal generation
IEEE Transactions on Microwave Theory and Techniques, 2015Co-Authors: Jong Seok Park, Hua WangAbstract:This paper presents a transformer-based poly-Phase Network to generate fully differential quadrature signals with low loss, compact area, and high-precision magnitude and Phase balance over an ultra-wide bandwidth. A fully differential high-coupling 8-port folded transformer-based quadrature hybrid serves as the basic building block for the poly-Phase unit stage to achieve significant size reduction and low loss. Multiple poly-Phase unit stages can be cascaded to form the multistage poly-Phase Network to substantially extend the quadrature signal generation bandwidth. The designs of the high-coupling transformer-based quadrature hybrid, the poly-Phase unit stage, and the multistage transformer-based poly-Phase Network are presented with the closed-form design equations in this paper. As a proof-of-concept design, a 3-stage transformer-based poly-Phase Network is implemented in a standard 65 nm bulk CMOS process with a core area of 772 $\mu$ m $\,\times\,$ 925 $\mu$ m. Measurement results of this poly-Phase Network over 3 independent samples demonstrate that the output In-Phase and Quadrature (I/Q) magnitude mismatch is less than 1 dB from 2.8 GHz to 21.8 GHz with a passive loss of 3.65 dB at 6.4 GHz. The measured output I/Q Phase error is less than 10 $^{\circ}$ from 0.1 GHz to 24 GHz. The effective Image Rejection Ratio (IRR) based on the measured I/Q balancing is more than 30 dB from 3.7 GHz to 22.5 GHz. The 3-stage transformer-based poly-Phase Network design achieves high-quality quadrature signal generation over a first-ever one-decade bandwidth together with low-loss and compact area.
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A transformer-based poly-Phase Network for ultra-broadband quadrature signal generation
2015 IEEE MTT-S International Microwave Symposium, 2015Co-Authors: Jong Seok Park, Hua WangAbstract:This paper presents a novel transformer-based poly-Phase passive Network for generating high-quality fully differential quadrature signals with low-loss, ultra-broad bandwidth, and high compactness. A differential folded transformer quadrature coupler serves as the building block in the proposed poly-Phase Network. The poly-Phase Network can be readily extended to high-order configurations for broadband operation. Unlike the RC-CR poly-Phase Network, the transformer-based design offers inherently low loss and compatibility with output loading. As a proof-of-concept design, a 3-stage transformer poly-Phase Network is implemented in a standard 65 nm bulk CMOS process and achieves high-quality differential quadrature generation over a decade bandwidth. Measurements demonstrate the maximum differential quadrature outputs Phase error within ±2° from 2 GHz to 20 GHz, maximum magnitude mismatch within ±1 dB from 2.6 GHz to 25 GHz, and a worst-case image rejection ratio of 25 dB. The measured passive loss is 3.5 dB at 6.4 GHz.
I M Verloop - One of the best experts on this subject based on the ideXlab platform.
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heavy traffic analysis of a multiple Phase Network with discriminatory processor sharing
Operations Research, 2011Co-Authors: I M Verloop, Urtzi Ayesta, R NuoezqueijaAbstract:We analyze a generalization of the discriminatory processor-sharing (DPS) queue in a heavy-traffic setting. Customers present in the system are served simultaneously at rates controlled by a vector of weights. We assume that customers have Phase-type distributed service requirements and allow that customers have different weights in various Phases of their service. In our main result we establish a state-space collapse for the queue-length vector in heavy traffic. The result shows that in the limit, the queue-length vector is the product of an exponentially distributed random variable and a deterministic vector. This generalizes a previous result by Rege and Sengupta [Rege, K. M., B. Sengupta. 1996. Queue length distribution for the discriminatory processor-sharing queue. Oper. Res.44(4) 653--657], who considered a DPS queue with exponentially distributed service requirements. Their analysis was based on obtaining all moments of the queue-length distributions by solving systems of linear equations. We undertake a more direct approach by showing that the probability-generating function satisfies a partial differential equation that allows a closed-form solution after passing to the heavy-traffic limit. Making use of the state-space collapse result, we derive interesting properties in heavy traffic: (i) For the DPS queue, we obtain that, conditioned on the number of customers in the system, the residual service requirements are asymptotically independent and distributed according to the forward recurrence times. (ii) We then investigate how the choice for the weights influences the asymptotic performance of the system. In particular, for the DPS queue we show that the scaled holding cost reduces as classes with a higher value for dk/E(Bkfwd) obtain a larger share of the capacity, where dk is the cost associated to class k, and E(Bkfwd) is the forward recurrence time of the class-k service requirement. The applicability of this result for a moderately loaded system is investigated by numerical experiments.
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Heavy-traffic analysis of a multiple-Phase Network with discriminatory processor sharing
2009Co-Authors: I M Verloop, Urtzi Ayesta, R. Núñez QueijaAbstract:We analyze a generalization of the Discriminatory Processor Sharing (DPS) queue in a heavy-traffic setting. Customers present in the system are served simultaneously at rates controlled by a vector of weights. We assume that customers have Phase-type distributed service requirements and allow that customers have different weights in various Phases of their service. In our main result we establish a state-space collapse for the queue length vector in heavy traffic. The result shows that in the limit, the queue length vector is the product of an exponentially distributed random variable and a deterministic vector. This generalizes a previous result by Rege and Sengupta (1996) who considered a DPS queue with exponentially distributed service requirements. Their analysis was based on obtaining all moments of the queue length distributions by solving systems of linear equations. We undertake a more direct approach by showing that the probability generating function satisfies a partial differential equation that allows a closed-form solution after passing to the heavy-traffic limit. Making use of the state-space collapse result, we derive interesting properties in heavy traffic: (i) For the DPS queue we obtain that, conditioned on the number of customers in the system, the residual service requirements are asymptotically i.i.d. according to the forward recurrence times. (ii) We then investigate how the choice for the weights influences the asymptotic performance of the system. In particular, for the DPS queue we show that the scaled holding cost reduces as classes with a higher value for d_k/E(B_k^fwd) obtain a larger share of the capacity, where d_k is the cost associated to class k, and E(B_k^fwd) is the forward recurrence time of the class-k service requirement. The applicability of this result for a moderately loaded system is investigated by numerical experiments.
Amritanshu Pandey - One of the best experts on this subject based on the ideXlab platform.
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robust steady state analysis of the power grid using an equivalent circuit formulation with circuit simulation methods
2019Co-Authors: Amritanshu PandeyAbstract:A robust framework for steady-state analysis (power flow and three-Phase power flow problem) of the transmission as well as distribution Networks is essential for operation and planning of the electric power grid. The critical nature of this analysis has led to this problem being one of the most actively researched topics in the field of energy in the last few decades. This has produced significant advances in the related technologies; however, the present state-of-the-art methods still lack the general robustness needed to securely and reliably operate as well as plan for the ever-changing power grid. The reasons for this are manifold, but the most important ones are: lack of general assurance toward convergence of power flow and three-Phase power flow problems to the correct physical solution when a good initial state is not available; the use of disparate formulation and modeling frameworks for transmission and distribution steady-state analyses that has led to the two analyses being modeled and simulated separately.This thesis addresses the existing limitations in steady-state analysis of power grids to enable a more secure and reliable environment for power grid operation and planning. To that effect, we develop a generic framework based on equivalent circuit formulation that can model both the positive sequence Network of the transmission grid and the three-Phase Network of the distribution grid without loss of generality. Furthermore, we demonstrate that when combined with novel as well as adapted circuit simulation techniques, the framework can robustly solve for the steady-state solution for both these Network models (positive sequence and three-Phase) by constraining the developed models in their physical space, independent of the choice of initial conditions. Importantly, the developed framework treats the transmission grid no differently than the distribution grid and, therefore, allows for any further advances in the field to be directly applicable to the analysis of both. One of which is the ability to robustly simulate the “combined” positive sequence Network of the transmission grid and three-Phase Network of the distribution grid. To validate the applicability of the proposed equivalent circuit formulation to realistic industry sized systems as well to demonstrate the robustness of the developed methods, we simulate large positive-sequence and three-Phase Networks individually and jointly from arbitrary initial conditions and show convergence to correct physical solution. Examples for positive sequence transmission Networks include 75k+ nodes test cases representing the U.S. Eastern Interconnection high-voltage grid and for three-Phase Networks include 8k+ nodes taxonomy feeders.
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robust power flow and three Phase power flow analyses
IEEE Transactions on Power Systems, 2019Co-Authors: Amritanshu Pandey, Marko Jereminov, Martin R Wagner, David M Bromberg, Larry PileggiAbstract:Robust simulation is essential for reliable operation and planning of transmission and distribution power grids. At present, disparate methods exist for steady-state analysis of the transmission (power flow) and distribution power grid (three-Phase power flow). Due to the nonlinear nature of the problem, it is difficult for alternating current power flow and three-Phase power flow analyses to ensure convergence to the correct physical solution, particularly from arbitrary initial conditions, or when evaluating a change (e.g., contingency) in the grid. In this paper, we describe our equivalent circuit formulation approach with current and voltage variables, which models both the positive sequence Network of the transmission grid and three-Phase Network of the distribution grid without loss of generality. The proposed circuit models and formalism enables the extension and application of circuit simulation techniques to solve for the steady-state solution with excellent robustness of convergence. Examples for positive sequence transmission and three-Phase distribution systems, including actual 75k+ nodes Eastern Interconnection transmission test cases and 8k+ nodes taxonomy distribution test cases, are solved from arbitrary initial guesses to demonstrate the efficacy of our approach.