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Web monitoring provides payback for Paperboard JonquiÚre, Solutions!, March 2002, Vol. 85(3) (140KB)

Web monitoring provides payback for Paperboard Jonquière, Solutions!, March 2002, Vol. 85(3) (140KB)

The Fate of Nitrogen in the Chemical Recovery Process in a Kraft Pulp Mill. Part IV: Smelt Nitrogen and its Formation in Black Liquor Combustion, JOURNAL OF PULP AND PAPER SCIENCE: VOL. 28 NO. 5 MAY 2002 [02MAYJP151.pdf]

The fate of nitrogen in the chemical recovery process in a kraft pulp mill. Part IV: smelt nitrogen and its formation in black liquor combustion, Journal of Pulp and Paper Science, May 2002, Vol. 28(5) (321KB)

H202 bleaching of mechanical pulps. part iv: h2o2 consumption, Journal of Pulp and Paper Science, November 2002, Vol. 28(11) (309KB)

H202 bleaching of mechanical pulps. part iv: h2o2 consumption, Journal of Pulp and Paper Science, November 2002, Vol. 28(11) (309KB)

Chip Quality Optimization and Chipper Condition Monitoring Concept, 2006 Engineering, Pulping, & Environmental Conference

Chip Quality Optimization and Chipper Condition Monitoring Concept, 2006 Engineering, Pulping, & Environmental Conference

The role of pulp and paper education today, Solutions!, November 2003, Vol. 86(11) (325KB)

The role of pulp and paper education today, Solutions!, November 2003, Vol. 86(11) (325KB)

Pushing performance limits with dryer fabrics, Solutions!, November 2003, Vol. 86(11) (165KB)

Pushing performance limits with dryer fabrics, Solutions!, November 2003, Vol. 86(11) (165KB)

Editoral: Investing in the future: Writing and peer-reviewing for TAPPI Journal, TAPPI Journal July 2024

ABSTRACT: Those who actively participate in TAPPI realize how much there is to gain from the networking, educational resources, career development, and other opportunities that come with this involvement. One important opportunity is the ability to share your work and expertise with others in your field, and an excellent way to do this is by taking part in the TAPPI Journal peer-review process, either as an author or a reviewer or both.

Modeling the dynamics of evaporator wash cycles, TAPPI Journal July 2024

ABSTRACT: Kraft pulping is a process that utilizes white liquor, composed of sodium sulfide (Na2S) and sodium hydroxide (NaOH), for wood delignification and pulp production. This process involves washing the dissolved organics and spent chemicals from the pulp, resulting in the generation of black liquor. Prior to its use as fuel in the recovery boiler, the black liquor is concentrated in multiple-effect evaporators. During the evaporation process, the inorganic salts present in the liquor become supersaturated and undergo crystallization. Fluctuations in sodium, carbonate, sulfate, and oxalate can give rise to severe sodium salt scaling events, which significantly impact the thermal efficiency of the evaporators, and ultimately, pulp production. Dynamic modeling provides insights into fluctuations in liquor chemistry in the evaporators. The primary objective of this study was to employ dynamic modeling to evaluate the effects of wash liquor recovery from evaporator wash cycles. The dynamics associated with wash cycles encompass variations in the concentrations of salts and solids in the recovered wash liquor, changes in the flow rate of wash liquor recovery, and fluctuations in liquor volume within the liquor tanks. The dynamic model was developed using Matlab Simulink and applied to the evaporation plant of a pulp mill in South America. By utilizing one month of mill process data, the model enabled the evaluation of fluctuations in liquor chemistry due to evaporator wash cycles. The developed model has demonstrated the potential to estimate the concentration of key ions responsible for scaling and to contribute to enhancements in evaporator washing strategies.

Comparing a linear transfer function-noise model and a neural network to model boiler bank fouling in a kraft recovery boiler, TAPPI Journal, July 2024

ABSTRACT: Boiler bank fouling reduces heat transfer efficiency in kraft recovery boilers. Here, we model the relationships between boiler parameters and boiler bank pressure drop, an indicator of fouling, based on recovery boiler operating data. We compared two models: an autoregressive integrated exogenous (ARIX) model and a feedforward neural network. The ARIX model better simulates boiler bank pressure drop compared to the neural network (R2 of 0.64 vs. 0.58). Based on the ARIX model, we identified six boiler parameters that significantly influence boiler bank fouling and their relative contributions. Finally, we demonstrate how the models can simulate boiler bank pressure drop given artificial perturbations in boiler parameters.

Mitigating Malodors at Pulp and Paper Production Plants, Paper360º July/August 2024