Multi-Sectoral Cascading and Price Dynamics - A Bayesian Econometric Evaluation

Recent evidence by Bils and Klenow (2004) and Klenow and Kryvstov (2003) shows that the average price duration for US CPI-basket goods is in the order of one to two quarters, challenging the monetary business cycle research to try and explain how short price durations can nevertheless generate a large degree of aggregate inflation persistence. We empirically test the relevance of a cascading structure of production as an explanation for short price durations and large aggregate inflation persistence. The final good is produced through a chain of intermediate goods, which undergo several processing stages. At each stage the price is set in nominal terms, and can be adjusted only at random intervals. Though each individual price is adjusted frequently, because the final good price embeds the intermediate price movements, it will turn out to have a large degree of stickiness. We estimate the model using Bayesian techniques to evaluate the relative role of indexation, pricing contracts length, and cascading production structure in the US postwar data. The estimation shows that short pricing contracts within the standard Calvo pricing mechanism are compatible with large inflation persistence, and inflation indexation turns out to play a much less relevant role - in other words, it ends up being a reduced-form model for the cascading production structureInflation Inertia, Monetary Policy, Bayesian Estimation, Multisectoral Cascading

An improved adaptive sidelobe blanker

We propose a two-stage detector consisting of a subspace detector followed by the whitened adaptive beamformer orthogonal rejection test. The performance analysis shows that it possesses the constant false alarm rate property with respect to the unknown covariance matrix of the noise and that it can guarantee a wider range of directivity values with respect to previously proposed two-stage detectors. The probability of false alarm and the probability of detection (for both matched and mismatched signals) have been evaluated by means of numerical integration techniques

A model-based reasoning approach to sensor placement for monitorability

An approach is presented to evaluating sensor placements to maximize monitorability of the target system while minimizing the number of sensors. The approach uses a model of the monitored system to score potential sensor placements on the basis of four monitorability criteria. The scores can then be analyzed to produce a recommended sensor set. An example from our NASA application domain is used to illustrate our model-based approach to sensor placement

Actinometry of Hydrogen Plasmas

Optical emission spectroscopy (OES) can be used to map the electron energy distribution of hydrogen plasmas. Using actinometry, a type of OES where trace amounts of noble gases are introduced, the effect of discharge power on the electron temperature of hydrogen plasmas was explored. This was done using argon and krypton as actinometers for low pressure hydrogen plasmas. It was determined that the electron temperature decreased with respect to power supplied to the discharge

Spectral scaling of the Leray-α\alpha model for two-dimensional turbulence

We present data from high-resolution numerical simulations of the Navier-Stokes-$\alpha$ and the Leray-$\alpha$ models for two-dimensional turbulence. It was shown previously (Lunasin et al., J. Turbulence, 8, (2007), 751-778), that for wavenumbers $k$ such that $k\alpha\gg 1$, the energy spectrum of the smoothed velocity field for the two-dimensional Navier-Stokes-$\alpha$ (NS-$\alpha$) model scales as $k^{-7}$. This result is in agreement with the scaling deduced by dimensional analysis of the flux of the conserved enstrophy using its characteristic time scale. We therefore hypothesize that the spectral scaling of any $\alpha$-model in the sub-$\alpha$ spatial scales must depend only on the characteristic time scale and dynamics of the dominant cascading quantity in that regime of scales. The data presented here, from simulations of the two-dimensional Leray-$\alpha$ model, confirm our hypothesis. We show that for $k\alpha\gg 1$, the energy spectrum for the two-dimensional Leray-$\alpha$ scales as $k^{-5}$, as expected by the characteristic time scale for the flux of the conserved enstrophy of the Leray-$\alpha$ model. These results lead to our conclusion that the dominant directly cascading quantity of the model equations must determine the scaling of the energy spectrum.Comment: 11 pages, 4 figure

A Policy Switching Approach to Consolidating Load Shedding and Islanding Protection Schemes

In recent years there have been many improvements in the reliability of critical infrastructure systems. Despite these improvements, the power systems industry has seen relatively small advances in this regard. For instance, power quality deficiencies, a high number of localized contingencies, and large cascading outages are still too widespread. Though progress has been made in improving generation, transmission, and distribution infrastructure, remedial action schemes (RAS) remain non-standardized and are often not uniformly implemented across different utilities, ISOs, and RTOs. Traditionally, load shedding and islanding have been successful protection measures in restraining propagation of contingencies and large cascading outages. This paper proposes a novel, algorithmic approach to selecting RAS policies to optimize the operation of the power network during and after a contingency. Specifically, we use policy-switching to consolidate traditional load shedding and islanding schemes. In order to model and simulate the functionality of the proposed power systems protection algorithm, we conduct Monte-Carlo, time-domain simulations using Siemens PSS/E. The algorithm is tested via experiments on the IEEE-39 topology to demonstrate that the proposed approach achieves optimal power system performance during emergency situations, given a specific set of RAS policies.Comment: Full Paper Accepted to PSCC 2014 - IEEE Co-Sponsored Conference. 7 Pages, 2 Figures, 2 Table

Reducing Cascading Failure Risk by Increasing Infrastructure Network Interdependency

Increased coupling between critical infrastructure networks, such as power and communication systems, will have important implications for the reliability and security of these systems. To understand the effects of power-communication coupling, several have studied interdependent network models and reported that increased coupling can increase system vulnerability. However, these results come from models that have substantially different mechanisms of cascading, relative to those found in actual power and communication networks. This paper reports on two sets of experiments that compare the network vulnerability implications resulting from simple topological models and models that more accurately capture the dynamics of cascading in power systems. First, we compare a simple model of topological contagion to a model of cascading in power systems and find that the power grid shows a much higher level of vulnerability, relative to the contagion model. Second, we compare a model of topological cascades in coupled networks to three different physics-based models of power grids coupled to communication networks. Again, the more accurate models suggest very different conclusions. In all but the most extreme case, the physics-based power grid models indicate that increased power-communication coupling decreases vulnerability. This is opposite from what one would conclude from the coupled topological model, in which zero coupling is optimal. Finally, an extreme case in which communication failures immediately cause grid failures, suggests that if systems are poorly designed, increased coupling can be harmful. Together these results suggest design strategies for reducing the risk of cascades in interdependent infrastructure systems