Modelling dosator filling and discharge of powder

Dosators and other dosing mechanisms operating on generally similar principles are very widely used in the pharmaceutical industry for capsule filling, and for dosing products that are delivered to the customer in powder form such as inhalers. This is a trend that is set to increase. However a significant problem for this technology is being able to predict how accurately and reliably, new drug formulations will be dosed from these machines prior to manufacture. This paper presents a review of the literature relating to powder dosators which considers mathematical models for predicting dosator performance, the effects of the dosator geometry and machine settings on the accuracy of the dose weight. An overview of a model based on classical powder mechanics theory that has been developed at The University of Greenwich is presented. The model uses inputs from a range of powder characterisation tests including, wall friction, bulk density, stress ratio and permeability. To validate the model it is anticipated that it will be trialled for a range of powders alongside a single shot dosator test rig.

Review of models for predicting the discharge rates of bulk particulates from silos and bins

Various models for predicting discharge rates have been developed over the last four decades by many research workers (notably Beverloo [1], Johanson [2], Brown [3], Carleton [4], Crewdson [5], Nedderman [6], Gu [7].). In many cases these models offer comparable approaches to the prediction of discharge rates of bulk particulates from storage equipment when solely gravity is acting to initiate flow (since they invariably consider the use of mass-flow design equipment). The models that have been developed consider a wide range of bulk particulates (coarse, incompressible, fine, cohesive) and most contemporary works have incorporated validation against test programmes. Research currently underway at The Wolfson Centre for Bulk Solids Handling Technology, University of Greenwich, has considered the relative performance of these models with respect to a range of bulk properties and with particular focus upon the flexibility of the models to cater for different geometrical factors for vessels.

Application of regularization methods to damage detection in large scale plane frame structures using incomplete noisy modal data

This paper presents an approach for detecting local damage in large scale frame structures by utilizing regularization methods for ill-posed problems. A direct relationship between the change in stiffness caused by local damage and the measured modal data for the damaged structure is developed, based on the perturbation method for structural dynamic systems. Thus, the measured incomplete modal data can be directly adopted in damage identification without requiring model reduction techniques, and common regularization methods could be effectively employed to solve the developed equations. Damage indicators are appropriately chosen to reflect both the location and severity of local damage in individual components of frame structures such as in brace members and at beam-column joints. The Truncated Singular Value Decomposition solution incorporating the Generalized Cross Validation method is introduced to evaluate the damage indicators for the cases when realistic errors exist in modal data measurements. Results for a 16-story building model structure show that structural damage can be correctly identified at detailed level using only limited information on the measured noisy modal data for the damaged structure.

Radio propagation modeling for capacity optimization in wireless relay MIMO systems with partial CSI

The enormous growth of wireless communication systems makes it important to evaluate the capacity of such channels. Multiple Input Multiple Output (MIMO) wireless communication systems are shown to yield significant performance improvement to data rates when compared to the traditional Single Input Single Output (SISO) wireless systems. The benefits of multiple antenna elements at the transmitter and receiver have become necessary to the research and the development of the next generation of mobile communication systems. In this paper we propose the use of Relaying MIMO wireless communication systems for use over long throughput. We investigate how Relays can be used in a "demodulate-and-forward" operation when the transmitter is equipped with spatially correlated multiple antenna elements and the receiver has only partial knowledge of the statistics of the channel. We show that Relays between the source and destination nodes of a wireless communication system in MIMO configuration improve the throughput of the system when compared to the typical MIMO systems, or achieve the desired channel capacity with significantly lower power resources needed.

Communication system model for information rate evaluation of differential detection over time-varying channels

A communication system model for mutual information performance analysis of multiple-symbol differential M-phase shift keying over time-correlated, time-varying flat-fading communication channels is developed. This model is a finite-state Markov (FSM) equivalent channel representing the cascade of the differential encoder, FSM channel model and differential decoder. A state-space approach is used to model channel phase time correlations. The equivalent model falls in a class that facilitates the use of the forward backward algorithm, enabling the important information theoretic results to be evaluated. Using such a model, one is able to calculate mutual information for differential detection over time-varying fading channels with an essentially finite time set of correlations, including the Clarke fading channel. Using the equivalent channel, it is proved and corroborated by simulations that multiple-symbol differential detection preserves the channel information capacity when the observation interval approaches infinity.

Mutual information performance of differential MPSK detection over time-varying channels

This paper provides mutual information performance analysis of multiple-symbol differential WSK (M-phase shift keying) over time-correlated, time-varying flat-fading communication channels. A state space approach is used to model time correlation of time varying channel phase. This approach captures the dynamics of time correlated, time-varying channels and enables exploitation of the forward-backward algorithm for mutual information performance analysis. It is shown that the differential decoding implicitly uses a sequence of innovations of the channel process time correlation and this sequence is essentially uncorrelated. It enables utilization of multiple-symbol differential detection, as a form of block-by-block maximum likelihood sequence detection for capacity achieving mutual information performance. It is shown that multiple-symbol differential ML detection of BPSK and QPSK practically achieves the channel information capacity with observation times only on the order of a few symbol intervals

Adaptive ordering for imperfect successive decision feedback multiuser detection

A method for selecting the order in which the users are detected in communication systems employing adaptive successive decision feedback multiuser detection is proposed. Systems employing channel coding without the assumption of perfect decision feedback are analyzed. The method is based on the mean squared error (MSE) measurements during a training period for each user. The analysis' shows that the method delivers BER performance improvement relative to other previously proposed ordering methods