Previous investigators have shown that the Newtonian viscosity of black liquor (BL), a byproduct of kraft pulping process, can be estimated online from the performance parameters of an installed centrifugal pump (CP). Unfortunately, the existing models from which such estimates can be obtained lack the necessary robustness for process control applications and/or would require a substantial amount of data for periodic updates. This study developed a generalized artificial neural network (ANN)-based model which directly accounts for the effect of aging on the pump performance (hence the model). Simulation results show that ANN predicts BL viscosity better than the existing linear models as the former gives accurate and robust predictions at all practical operating points of the pump. Moreover, the ANN model requires just a single data point for its periodic recalibration as the pump ages significantly. The methodologies presented here can easily be adapted for use in any process industry where Newtonian process fluids are transferred by a CP.

No abstract

No abstract

The purpose of this research was to investigate the feasibility of installing gasification based combined heat and power plants in the New Zealand wood processing industry. This is in accordance with Objective Four of the BIGAS Consortium.This thesis builds on previous work on Objective Four (Rutherford, 2006) where integration into MDF (Medium Density Fibreboard) was investigated. The previous research identified the most suitable form of combined heat and power was a BIG-GE (Biomass Integrated Gasification Gas Engine) process, due to both lower capital investment and overall breakeven electricity production cost. This technology has therefore been adopted, and the investigation has been carried further in this research to incorporate integration into sawmills and LVL (Laminated Veneer Lumber) plants.It is recognised, however, especially when reviewing overseas successes and failures, that the base economics are only one factor in the feasibility of a plant. The research, therefore, has moved further to investigate New Zealand policy, the power market, lower capital alternatives and novel methods of integration.

Availability of accurate models for prediction of the viscosity of black liquor (BL) from the chemical pulping of pine will facilitate its online monitoring and control and subsequently the optimisation of combustion in a recovery boiler. New Zealand (NZ) BL viscosity data are limited, and no predictive model is available. The viscosities of the NZ BL samples at solids concentrations (SCs) <50% were obtained at temperature of 25-85• C and shear rate up to ∼2000 s −1 . The samples showed Newtonian behaviour. Existing models from the literature and a binomial model developed in this work were used to fit the viscosity data as a function of SC and temperature. Accuracies of these models were examined for both the log-transformed and the untransformed viscosity data using coefficient of correlation (R) and maximum absolute relative error (MARE) (between the actual and predicted viscosities), respectively, as indices. Although the existing models fit NZ BL viscosity data well when they were log-transformed, they performed poorly when not transformed. Conversely, the new binomial model gave accurate predictions with both the log-transformed and untransformed viscosity data (R = 0.9997; MARE = 5.7%). It is concluded that at low SCs, the viscosity of Newtonian BL can be accurately predicted using the new binomial model. 