Experimental Study of Lightning-Induced Currents in a Buried Loop Conductor and a Grounded Vertical Conductor

Currents induced in: (1) a 100 mtimes30 m buried rectangular loop conductor (counterpoise) and (2) a grounded vertical conductor of 7-m height by natural and rocket-triggered lightning at distances ranging from 60 to 300 m were recorded in 2005 at the International Center for Lightning Research and Testing (ICLRT). The peak values of 12 triggered lightning channel-base currents and the peak values of the induced currents in the counterpoise are strongly correlated. The first few microseconds of the current induced in the vertical conductor by triggered lightning return strokes 100 m away resemble electric field time-derivative waveforms simultaneously measured at the ICLRT. During a close natural lightning flash, five pre-first-return-stroke current pulses with peak currents up to 140 A were measured in the vertical conductor. These are apparently associated with multiple attempts of an upward-moving unconnected leader occurring in response to the charge lowered by downward-propagating leader steps.     

Decentralized variable structure control design for a two-pendulum system

This note presents a decentralized variable structure control design for a nonlinear state model of two coupled pendulums. This was motivated by the swing equation model of a two-machine power system whose behavior is similar. The control objective is to drive the pendulum motion from one equilibrium point to another.     

Hybrid Model Predictive Power Management of A Fuel Cell‐Battery Vehicle

This paper considers optimal power management of a fuel cell‐battery hybrid vehicle (FCHV) powertrain having three distinct modal configurations (modes): electric motor propelling/battery discharging, propelling/charging, and generating/charging. Each mode has a distinct set of dynamics and constraints. Using component dynamical/algebraic models appropriate to power flow management, the paper develops a supervisory‐level switched system model as an interconnection of subsystems. Given the model, the paper sets forth a hybrid model predictive control strategy based on a minimization of a performance index (PI) that trades off tracking and fuel economy in each operational mode. Specifically, the PI trades off velocity tracking error, battery state of charge variance, and electric drive and hydrogen fuel usages while penalizing frictional braking to encourage regenerative braking. The optimization is performed using an embedded system model and collocation with matlab 's fmincon to compute mode switches and continuous time controls. The methodology avoids the computational complexity of alternate approaches based on, e.g., mixed integer programming. Projection methods for approximating the switched system solution from the embedded solution are empirically evaluated. To demonstrate the methodology, an example of a FCHV is simulated using three standard velocity driving profiles: a sawtooth profile with a hill climb, the EPA urban dynamic driving schedule, and the New European Driving Cycle. Also, drive cycle fuel usage is compared to that from the Equivalent Consumption Minimization Strategy.     

Intelligent interdomain distributed service management

This article presents an overview of a prototype for management of a large‐scale distributed system. The prototype objective is to demonstrate a capability for intelligent management of distributed services, which correlates network and service elements faults to diagnose events. Copyright © 1999 John Wiley & Sons, Ltd.     

Evaluation of the particle measurement programme (PMP) protocol to remove the vehicles' exhaust aerosol volatile phase

European regulation for Euro 5/6 light duty emissions introduced the measurement of non-volatile particles with diameter > 23 nm. The volatile phase is removed by using a heated dilution stage (150 °C) and a heated tube (at 300-400 °C). We investigated experimentally the removal efficiency for volatile species of the specific protocol by conducting measurements with two Euro 3 diesel light duty vehicles, a Euro 2 moped, and a Euro III heavy duty vehicle with the system's heaters on and off. The particle number distributions were measured with a Scanning Mobility Particle Sizer (SMPS) and a Fast Mobility Particle Sizer (FMPS). An Aerosol Mass Spectrometer (AMS) was used to identify the non-refractory chemical composition of the particles. A Multi-Angle Absorption Photometer (MAAP) was used to measure the black carbon concentration. The results showed that the condensed material in the accumulation mode (defined here as particles in the diameter range of ∼ 50-500 nm) was removed with an efficiency of 50-90%. The (volatile) nucleation mode was also completely evaporated or was decreased to sizes < 23 nm; thus these particles wouldn't be counted from the particle counter, indicating the robustness of the protocol.     

On the meaning and use of kurtosis.

For symmetric unimodal distributions, positive kurtosis indicates heavy tails and peakedness relative to the normal distribution, whereas negative kurtosis indicates light tails and flatness. Many textbooks, however, describe or illustrate kurtosis incompletely or incorrectly. In this article, kurtosis is illustrated with well-known distributions, and aspects of its interpretation and misinterpretation are discussed. The role of kurtosis in testing univariate and multivariate normality; as a measure of departures from normality; in issues of robustness, outliers, and bimodality; in generalized tests and estimators, as well as limitations of and alternatives to the kurtosis measure β?, are discussed. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Systematic method for determining intravenous drug treatmentstrategies aiding the humoral immune response

This paper delineates a systematic method for determining “optimal” intravenous drug delivery strategies for patients having illnesses that primarily evoke a humoral immune response and are treatable by antibiotics. The method derives from a nonlinear, distributed predator-prey model that captures the dominant antigen and antibody interaction. This model is developed from relevant physiology, past predator-prey-type modeling work, available data, and pertinent parameter identification. Embedding this predator-prey model into a larger class of uncertain systems, by a finite dimensional approximation and a transformation to a linear fractional representation, enables the application of robust control based on linear matrix inequality optimization techniques. The optimization problem is solved by minimizing an upper bound on a measure of the total drug delivered subject to patient recovery (stability to healthy equilibrium state). Specifically, the paper addresses the treatment of Haemophilus influenzae through modeling, controller development, and simulations of infected adult patients subjected to typical and proposed intravenous antibiotic treatments. Through simulations the proposed intravenous drug strategy shortens patient recovery time, lowers peak drug concentrations and decreases the total drug administered when compared to standard antibiotic strategies     

Real‐time transformation of outdoor aerosol components upon transport indoors measured with aerosol mass spectrometry

Outdoor aerosols are transported indoors, where their component concentrations depend on aerosol size, physiochemical properties, indoor sources and losses, and cross‐environment gradients of temperature and relative humidity. We explored these dependencies by measuring real‐time outdoor and indoor non‐refractory, submicron (PM₁) aerosol component mass concentrations in a mixed‐use laboratory space with an Aerodyne mini‐aerosol mass spectrometer (AMS) and black carbon (BC) with an aethalometer. The median indoor/outdoor (I/O) ratios were 0.60 for sulfate, 0.25 for nitrate, 0.52 for ammonium, 0.73 for organics, and 0.61 for BC. Positive matrix factorization (PMF) on organic aerosol data identified hydrocarbon‐like (HOA), cooking (COA), and oxygenated (OOA) factors. By assuming sulfate was nonvolatile, lost only by mechanical processes, and without indoor sources, the transformations of other components i due to partitioning changes or indoor sources were parameterized by normalizing their I/O ratios by sulfate's I/O ratio, that is, (I/O)_i/SO4. Component‐specific behavior was quantified by regressions of (I/O)_i/SO4 to outdoor‐to‐indoor temperature differences. Nitrate and HOA strongly and OOA weakly showed losses with increasing temperatures indoors vs. outdoors, and HOA likely had an indoor source. To our knowledge, this is the first reported deployment of an AMS to analyze real‐time indoor aerosol composition and outdoor‐to‐indoor transformation.     

Using sensitivity analysis to validate a state variable model of the software test process

We report on the sensitivity analysis of a state variable model (Model S) proposed earlier. Model S captures the dominant behavior of the system test phase of the software test process. Sensitivity analysis is a mathematical methodology to compute changes in the system behavior due to changes in system parameters or variables. This is particularly important when parameters are calibrated using noisy or small data sets. Nevertheless, by mathematically quantifying the effects of parameter variations on the behavior of the model, and thereby the STP, one can easily and quickly evaluate the effect of such variations on the process performance without having to perform extensive simulations. In all cases studied, model S behaved according to empirical observations which serves to validate the model. It is also shown that sensitivity analysis can suggest structural improvements in a model when the model does not behave as expected.     

Blended deformable models

This paper develops a new class of parameterized models based on the linear interpolation of two parameterized shapes along their main axes, using a blending function. This blending function specifies the relative contribution of each component shape on the resulting blended shape. The resulting blended shape can have aspects of each of the component shapes. Using a small number of additional parameters, blending extends the coverage of shape primitives while also providing abstraction of shape. In particular, it offers the ability to construct shapes whose genus can change. Blended models are incorporated into a physics-based shape estimation framework which uses dynamic deformable models. Finally, we present experiments involving the extraction of complex shapes from range data including examples of dynamic genus change