Improved Recovery Boiler Performance Through Control of Combustion, Sulfur and Alkali Chemistry, 2004 Paper Summit, Spring Technical & International Environmental Conference (including Papermakers; Process Control, Electrical & Information; Product & Prod

Experimental and theoretical investigations of combustion characterization, sulfur chemistry, alkali chemistry, and char bed characteristics investigated in a DOE-supported project have reached mature levels of productivity. Devolatilization rate parameters appropriate for black-liquor compare well with ultimate yield data generated from laboratory entrained flow reactors. Data describing ISP formation provide definitive evidence of the amount and rate of formation of ISP from entrained droplets. Droplet size and shape investigations indicate how particle shape impacts conversion rate and temperature gradients in particles. Quantitative expressions for each of these and other relevant processes during black liquor combustion form a comprehensive, entrained-flow model for droplets.

Aerosols formed from alkali vapors scavenge sulfur from the gas phase to form fume particles. The amount and composition of such fume particles are accurately predicted using newly developed, multi-component aerosol formation computer codes. Thermochemical equilibrium programs using lattice-theory to predict non-ideal phase behavior of alkali salts are in process of debugging and validation and should shortly be ready for recovery boiler application.

Experimental measurements of char bed characteristics have been completed at both laboratory and commercial scale. In addition, theoretical descriptions of jet penetration, heat and mass transfer, and other major characteristics of bed combustion are complete. Comparisons of the theoretical and experimental data should be completed in the coming months with a comprehensive, validated bed model resulting from these efforts.

All of the models and much of the data developed in this project combine with existing CFD models of recovery boilers to improve predictions of boiler performance. This future prediction and validation will culminate in a more comprehensive and more completely validated model than was previously available.