Transient thermal analysis of power devices based on Fourier-series thermal model

A new thermal model based on Fourier series expansion method has been presented for dynamic thermal analysis on power devices. The thermal model based on the Fourier series method has been programmed in MATLAB SIMULINK and integrated with a physics-based electrical model previously reported. The model was verified for accuracy using a two-dimensional Fourier model and a two-dimensional finite difference model for comparison. To validate this thermal model, experiments using a 600V 50A IGBT module switching an inductive load, has been completed under high frequency operation. The result of the thermal measurement shows an excellent match with the simulated temperature variations and temperature time-response within the power module. ©2008 IEEE.

Breakdown voltage for superjunction power devices with charge imbalance: An analytical model valid for both punch through and non punch through devices

An analytical model for the electric field and the breakdown voltage (BV) of an unbalanced superjunction (SJ) device is presented in this paper. The analytical technique uses a superposition approach treating the asymmetric charge in the pillars as an excess charge component superimposed on a balanced charge component. The proposed double-exponentialmodel is able to accurately predict the electric field and the BV for unbalanced SJ devices in both punch through and non punch through conditions. The model is also reasonably accurate at extremely high levels of charge imbalance when the devices behave similarly to a PiN diode or to a high-conductance layer. The analytical model is compared against numerical simulations of charge unbalanced SJ devices and against experimental results. © 2009 IEEE.

Mathematical model for solids transport power in a decanter centrifuge

A mathematical model of the transport of sedimented solids within a decanter centrifuge has been developed. The primary purpose of the model is to calculate the power, torque and axial force required for the scroll to transport the solids along the bowl. The model is presented in a non-dimensional form and the procedure for implementing the model is included. The model is compared to test data from an existing publication; there was good agreement between the model and data. Example results are presented in the form of graphs to illustrate the influence of key parameters. © 2013 Elsevier Ltd.

A novel low-power input-independent MOS AC/DC charge pump

This paper presents a novel fully integrated MOS AC to DC charge pump with low power dissipation and stable output for RFID applications. To improve the input sensitivity, we replaced Schottky-diodes in conventional charge pumps with MOS diodes with zero threshold, which has less process defects and is thus more compatible with other circuits. The charge pump in a RFID transponder is implemented in a 0.35um CMOS technology with 0.24 sq mm die size. The analytical model of the charge pump and the simulation results are presented.

Changes in midbrain pain receptor expression, gait and behavioral sensitivity in a rat model of radiculopathy.

Intervertebral disc herniation may contribute to inflammatory processes that associate with radicular pain and motor deficits. Molecular changes at the affected dorsal root ganglion (DRG), spinal cord, and even midbrain, have been documented in rat models of radiculopathy or nerve injury. The objective of this study was to evaluate gait and the expression of key pain receptors in the midbrain in a rodent model of radiculopathy. Radiculopathy was induced by harvesting tail nucleus pulposus (NP) and placing upon the right L5 DRG in rats (NP-treated, n=12). Tail NP was discarded in sham-operated animals (n=12). Mechanical allodynia, weight-bearing, and gait were evaluated in all animals over time. At 1 and 4 weeks after surgery, astrocyte and microglial activation was tested in DRG sections. Midbrain sections were similarly evaluated for immunoreactivity to serotonin (5HT(2B)), mu-opioid (µ-OR), and metabotropic glutamate (mGluR4 and 5) receptor antibodies. NP-treated animals placed less weight on the affected limb 1 week after surgery and experienced mechanical hypersensitivity over the duration of the study. Astroctye activation was observed at DRGs only at 4 weeks after surgery. Findings for pain receptors in the midbrain of NP-treated rats included an increased expression of 5HT(2B) at 1, but not 4 weeks; increased expression of µ-OR and mGluR5 at 1 and 4 weeks (periaqueductal gray region only); and no changes in expression of mGluR4 at any point in this study. These observations provide support for the hypothesis that the midbrain responds to DRG injury with a transient change in receptors regulating pain responses.

BAYESIAN MODEL SEARCH AND MULTILEVEL INFERENCE FOR SNP ASSOCIATION STUDIES.

Technological advances in genotyping have given rise to hypothesis-based association studies of increasing scope. As a result, the scientific hypotheses addressed by these studies have become more complex and more difficult to address using existing analytic methodologies. Obstacles to analysis include inference in the face of multiple comparisons, complications arising from correlations among the SNPs (single nucleotide polymorphisms), choice of their genetic parametrization and missing data. In this paper we present an efficient Bayesian model search strategy that searches over the space of genetic markers and their genetic parametrization. The resulting method for Multilevel Inference of SNP Associations, MISA, allows computation of multilevel posterior probabilities and Bayes factors at the global, gene and SNP level, with the prior distribution on SNP inclusion in the model providing an intrinsic multiplicity correction. We use simulated data sets to characterize MISA's statistical power, and show that MISA has higher power to detect association than standard procedures. Using data from the North Carolina Ovarian Cancer Study (NCOCS), MISA identifies variants that were not identified by standard methods and have been externally "validated" in independent studies. We examine sensitivity of the NCOCS results to prior choice and method for imputing missing data. MISA is available in an R package on CRAN.

Model sensitivity and uncertainty analysis using roadside air quality measurements

Most of the air quality modelling work has been so far oriented towards deterministic simulations of ambient pollutant concentrations. This traditional approach, which is based on the use of one selected model and one data set of discrete input values, does not reflect the uncertainties due to errors in model formulation and input data. Given the complexities of urban environments and the inherent limitations of mathematical modelling, it is unlikely that a single model based on routinely available meteorological and emission data will give satisfactory short-term predictions. In this study, different methods involving the use of more than one dispersion model, in association with different emission simulation methodologies and meteorological data sets, were explored for predicting best CO and benzene estimates, and related confidence bounds. The different approaches were tested using experimental data obtained during intensive monitoring campaigns in busy street canyons in Paris, France. Three relative simple dispersion models (STREET, OSPM and AEOLIUS) that are likely to be used for regulatory purposes were selected for this application. A sensitivity analysis was conducted in order to identify internal model parameters that might significantly affect results. Finally, a probabilistic methodology for assessing urban air quality was proposed.

A comprehensive copper stockpile leach model: background and parameter sensitivity

The design and development of a comprehensive computational model of a copper stockpile leach process is summarized. The computational fluid dynamic software framework PHYSICA+ and various phenomena were used to model transport phenomena, mineral reaction kinetics, bacterial effects, and heat, energy and acid balances for the overall leach process. In this paper, the performance of the model is investigated, in particular its sensitvity to particle size and ore permeability. A combination of literature and laboratory sources was used to parameterize the model. The simulation results from the leach model are compared with closely controlled column pilot scale tests. The main performance characteristics (e.g. copper recovery rate) predicted by the model compare reasonably well with the experimental data and clearly reflect the qualitiative behavior of the process in many respects. The model is used to provide a measure of the sensitivity of ore permeability on leach behavior, and simulation results are examined for several different particle size distributions.

Model-based pilot and data power adaptation in psam with periodic delayed feedback

We consider the optimum design of pilot-symbol-assisted modulation (PSAM) schemes with feedback. The received signal is periodically fed back to the transmitter through a noiseless delayed link and the time-varying channel is modeled as a Gauss-Markov process. We optimize a lower bound on the channel capacity which incorporates the PSAM parameters and Kalman-based channel estimation and prediction. The parameters available for the capacity optimization are the data power adaptation strategy, pilot spacing and pilot power ratio, subject to an average power constraint. Compared to the optimized open-loop PSAM (i.e., the case where no feedback is provided from the receiver), our results show that even in the presence of feedback delay, the optimized power adaptation provides higher information rates at low signal-to-noise ratios (SNR) in medium-rate fading channels. However, in fast fading channels, even the presence of modest feedback delay dissipates the advantages of power adaptation.

The carbonate system of the NW European shelf: sensitivity and model validation

The ocean plays an important role in regulating the climate, acting as a sink for carbon dioxide, perturbing the carbonate system and resulting in a slow decrease of seawater pH. Understanding the dynamics of the carbonate system in shelf sea regions is necessary to evaluate the impact of Ocean Acidification (OA) in these societally important ecosystems. Complex hydrodynamic and ecosystem coupled models provide a method of capturing the significant heterogeneity of these areas. However rigorous validation is essential to properly assess the reliability of such models. The coupled model POLCOMS–ERSEM has been implemented in the North Western European shelf with a new parameterization for alkalinity explicitly accounting for riverine inputs and the influence of biological processes. The model has been validated in a like with like comparison with North Sea data from the CANOBA dataset. The model shows good to reasonable agreement for the principal variables, physical (temperature and salinity), biogeochemical (nutrients) and carbonate system (dissolved inorganic carbon and total alkalinity), but simulation of the derived variables, pH and pCO2, are not yet fully satisfactory. This high uncertainty is attributed mostly to riverine forcing and primary production. This study suggests that the model is a useful tool to provide information on Ocean Acidification scenarios, but uncertainty on pH and pCO2 needs to be reduced, particularly when impacts of OA on ecosystem functions are included in the model systems.