21 resultados para Lyapunov coefficient


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This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to assess the performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implications for generation policy in Korea as outlined in this study.

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We examine how the most prevalent stochastic properties of key financial time series have been affected during the recent financial crises. In particular we focus on changes associated with the remarkable economic events of the last two decades in the volatility dynamics, including the underlying volatility persistence and volatility spillover structure. Using daily data from several key stock market indices, the results of our bivariate GARCH models show the existence of time varying correlations as well as time varying shock and volatility spillovers between the returns of FTSE and DAX, and those of NIKKEI and Hang Seng, which became more prominent during the recent financial crisis. Our theoretical considerations on the time varying model which provides the platform upon which we integrate our multifaceted empirical approaches are also of independent interest. In particular, we provide the general solution for time varying asymmetric GARCH specifications, which is a long standing research topic. This enables us to characterize these models by deriving, first, their multistep ahead predictors, second, the first two time varying unconditional moments, and third, their covariance structure.

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A cascaded DC-DC boost converter is one of the ways to integrate hybrid battery types within a grid-tie inverter. Due to the presence of different battery parameters within the system such as, state-of-charge and/or capacity, a module based distributed power sharing strategy may be used. To implement this sharing strategy, the desired control reference for each module voltage/current control loop needs to be dynamically varied according to these battery parameters. This can cause stability problem within the cascaded converters due to relative battery parameter variations when using the conventional PI control approach. This paper proposes a new control method based on Lyapunov Functions to eliminate this issue. The proposed solution provides a global asymptotic stability at a module level avoiding any instability issue due to parameter variations. A detailed analysis and design of the nonlinear control structure are presented under the distributed sharing control. At last thorough experimental investigations are shown to prove the effectiveness of the proposed control under grid-tie conditions.

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In the paper the identification of the time-dependent blood perfusion coefficient is formulated as an inverse problem. The bio-heat conduction problem is transformed into the classical heat conduction problem. Then the transformed inverse problem is solved using the method of fundamental solutions together with the Tikhonov regularization. Some numerical results are presented in order to demonstrate the accuracy and the stability of the proposed meshless numerical algorithm.

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We measure the radial profile of the photoelastic coefficient C(r) in single-mode polymer optical fibers (POFs), and we determine the evolution of C(r) after annealing the fibers at temperatures from 40°C to 80°C. We demonstrate that C(r) in the fibers drawn from a preform without specific thermal pre-treatment changes and converges to values between 1.2 and 1.6×10-12 Pa-1 following annealing at 80°C. The annealed fibers display a smoothened radial profile of C(r) and a lowered residual birefringence. In contrast, the mean value of C(r) of the fiber drawn from a preform that has been pre-annealed remains constant after our annealing process and is significantly higher, i.e., 4×10-12 Pa-1. The annealing process decreases the residual birefringence to a lower extent as well. These measurements indicate the impact of annealing on the thermal stability of the photoelastic coefficient of POFs, which is an essential characteristic in view of developing POF-based thermomechanical sensors.

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We have systematically measured the differential stress-optic coefficient, ΔC, and Young's modulus, E, in a number of PMMA fibers drawn with different stress, ranging from 2 up to 27 MPa. Effect of temperature annealing on those parameters was also investigated. ΔC was determined in transverse illumination by measuring the dependence of birefringence on additional axial stress applied to the fiber. Our results show that ΔC in PMMA fibers has a negative sign and ranges from -4.5 to -1.5×10-12 Pa -1 depending on the drawing stress. Increase of the drawing stress results in greater initial fiber birefringence and lower ΔC. The dependence of ΔC and initial birefringence upon drawing stress is nonlinear and gradually saturates for higher drawing stress. Moreover, we find that ΔC is linearly proportional to initial fiber birefringence and that annealing the fiber has no impact on the slope of this dependence. On the other hand, no clear dependence was observed between the fiber drawing stress and the Young's modulus of the fibers as measured using microscopic digital image correlation with the fibers tensioned using an Instron tension tester. © 2010 SPIE.