Gasification of wood particles in a co-current packed bed: Experiments and model analysis

This study focuses on addressing the propagation front movement in a co-current downdraft gasification system. A detailed single particle modeling analysis extended to the packed bed reactor is used to compare with the experimental measurement as well those available in the literature. This model for biomass gasification systems considered pyrolysis process, gas phase volatile combustion, and heterogeneous char reactions along with gas phase reactions in the packed bed. The pyrolysis kinetics has a critical influence on the gasification process. The propagation front has been shown to increase with air mass flux, attains a peak and then decreases with further increase in air mass flux and finally approaches negative propagation rate. This indicates that front is receding, or no upward movement() bra her it is moving downward towards the char bed. The propagation rate correlates with mass flux as (m) over dot `'(0.883) during the increasing regimes of the front movement The study clearly identifies that bed movement is an important parameter for consideration in a co-current configuration towards establishing the effective bed movement. The study also highlights the importance of surface area to volume ratio of the particles in the packed bed and its influence on the volatile generation. Finally, the gas composition for air gasification under various air mass fluxes is compared with the experimental results. (C) 2016 Elsevier B.V. All rights reserved.

Cumulative Impulse Strength for Epoch Extraction

Algorithms for extracting epochs or glottal closure instants (GCIs) from voiced speech typically fall into two categories: i) ones which operate on linear prediction residual (LPR) and ii) those which operate directly on the speech signal. While the former class of algorithms (such as YAGA and DPI) tend to be more accurate, the latter ones (such as ZFR and SEDREAMS) tend to be more noise-robust. In this letter, a temporal measure termed the cumulative impulse strength is proposed for locating the impulses in a quasi-periodic impulse-sequence embedded in noise. Subsequently, it is applied for detecting the GCIs from the inverted integrated LPR using a recursive algorithm. Experiments on two large corpora of speech with simultaneous electroglottographic recordings demonstrate that the proposed method is more robust to additive noise than the state-of-the-art algorithms, despite operating on the LPR.

Space-Vector-Based Hybrid PWM Technique to Reduce Peak-to-Peak Torque Ripple in Induction Motor Drives

Constant-volts-per-hertz induction motor drives and vector-controlled induction motor drives utilize pulsewidth modulation (PWM) to control the voltage applied on the motor. The method of PWM influences the pulsations in the torque developed by the motor. A space-vector-based approach to PWM facilitates special switching sequences involving the division of active state time. This paper proposes a space-vector-based hybrid PWM technique, which is a combination of the conventional and special switching sequences. The proposed hybrid PWM technique results in a lower peak-to-peak torque ripple than conventional space vector PWM(CSVPWM) at high speeds of an induction motor drive. Furthermore, the magnitude of the dominant torque harmonic due to the proposed hybrid PWM is significantly lower than that due to CSVPWM at high speeds of the drive. Experimental results from a 3.75-kW sensorless vector-controlled induction motor drive under various load conditions are presented to support analytical and simulation results.