Particles moisture content

A measurement of particle moisture content will normally be taken at the exit of the dryer. This allows the process operators to make such adjustments as may be needed to maintain moisture within the desired range. Various instmments are used, none of which are entirely satisfactory, and periodic hand samples are used in some mills. Considering the importance of moisture sensing and control at the dryers, it is unfortunate that a truly efficient, consistent, and accurate sensing system is not yet available to the industry. The primary reasons for the difficulty of measuring moisture at the dryer exit are the extreme and adverse conditions of heat, dust, and moisture present at this location. 

Triboelectric Series. Prediction of triboelectric behavior in granular solids is hampered by difficult-to-control factors such as particle shape, prior mechanical contacts, material purity, and particle moisture content (which is usually related to airborne humidity). In the absence of any reliable predictive model for powder electrification, the practical requirements of industry necessitate an empirical approach (Taylor and Seeker,... 

Moisture content (density of particles) Moisture content (density of particles)... 

The integral model is a development of a simple scale-up model which allows for mixing and residence time effects, first suggested for fluidized beds by Vanecek et al. (1964, 1966). The mean outlet moisture content is given by summing the product of the particle moisture content and the probability that it emerges at time t ... 

FIGURE 10.13 Evolution of particle moisture content (kg/kg). (a) 2D axisymmetric simulations and (b-d) frontal, side, and isometric views— 3D case study. 

FIGURE 10.21 Drying kinetics of droplets injected along stream 1. Droplet initial diameters are as indicated, (a, b) Particle surface temperatures (c, d) particle moisture contents. 

Al-Haj Ali et al. [5,6] developed different types of linear time invariant models by system identification, which adequately represent the fluidized-bed drying dynamics. MBC techniques such as IMC and model predictive control (MPC) were used for the designing of the control system. Simulations with multivariable MPC strategy provided robust, fast, stable, and non-oscillatory closed loop responses. A stationary form of Kalman filter was designed to estimate the particle moisture content (state observer). Performance studies showed that the Kalman filter provided satisfactory estimates even in the presence of significant noise levels and inaccurate initial states feed to the observer. 

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