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NEAR DRUM THINNING OF GENERATING BANK TUBES IN COASTAL POWER BOILERS, 2012 TAPPI PEERS Conference

NEAR DRUM THINNING OF GENERATING BANK TUBES IN COASTAL POWER BOILERS, 2012 TAPPI PEERS Conference

An Optimized UASB System Design As Applied to Paper Mill Secondary Sludge [Based on an Existing World-Wide UASB Systems Meta-Analysis] , 2012 TAPPI PEERS Conference

An Optimized UASB System Design As Applied to Paper Mill Secondary Sludge [Based on an Existing World-Wide UASB Systems Meta-Analysis] , 2012 TAPPI PEERS Conference

Environmental Regulartory Compliance for Process Tanks: Using Databases to Increase Compliance-Related Data Availability, 2012 TAPPI PEERS Conference

Environmental Regulartory Compliance for Process Tanks: Using Databases to Increase Compliance-Related Data Availability, 2012 TAPPI PEERS Conference

Powerhouse Energy Management and Reporting Systems (EMRS) Improve the Mill Bottom Line, 2012 TAPPI PEERS Conference

Powerhouse Energy Management and Reporting Systems (EMRS) Improve the Mill Bottom Line, 2012 TAPPI PEERS Conference

Pulp and Paper Mills as A Scalable and Cost-Effective Pathway to Atmospheric CO? Removal, TAPPICon26

Data driven modeling to reduce fossil fuel consumption in a lime kiln integrated with biomass gasifier, TAPPI Journal September 2026

ABSTRACT: Biomass gasification, although already known and applied, is currently being consolidated as a sustainable alternative in the pulp industry, contributing to the reduction of fossil carbon dioxide (CO2) emissions and to the utilization of forest residues. In this context, pulp mills are beginning to adopt biomass gasification within their chemical recovery cycles by integrating the technology with lime kilns. However, further process studies are still needed to support and optimize this application. Thus, the present study aimed to analyze lime mud feed temperature by applying an artificial neural network model to a gasification system integrated with a lime kiln. For this evaluation, 10 periods of system stability throughout 2024 were selected under different operational conditions. Data from 28 potential predictive variables were collected, a total of 348 observations. This dataset was then processed using R software, where data treatment and model dimensionality reduction were performed, resulting in 10 predictive variables between gasifier and kiln. Next, the dataset was randomly divided into training (70% of the observations) and testing data. The established neural network model (using “neuralnet” package) was optimized, resulting in a configuration containing one hidden layer with three neurons. This setup enabled optimal estimation of the flue gas kiln outlet temperature, with mean absolute error (MAE) = 3.0°C and root mean square error (RMSE) = 4.1°C, applying the resilient backpropagation algorithm with backtracking — both below the thermocouple’s measurement error (±5.0°C) for the evaluated average temperature range (668.2°C). When the same dataset was modeled using the resilient backpropagation algorithm without backtracking, even better results were achieved: MAE = 2.5°C and RMSE = 3.7°C. Thus, after evaluating these and other configurations, it was concluded that the best model required 10 predictive variables and the backpropagation algorithm without backtracking to determine flue gas kiln outlet temperature. These results provide a better understanding of how gasifier and kiln variables influence the temperature in the lime kiln, which is essential to improve control and optimize the calcination process, avoiding supplementary fossil fuel consumption.

Biomass gasification for green ammonia production in kraft mills, TAPPI Journal September 2026

ABSTRACT: As the global energy sector transitions toward net-zero emissions, kraft pulp mills present a compelling opportunity to produce green fuels and achieve net-negative emissions by capturing biogenic carbon, helping offset hard-to-abate sectors. This study explores the techno-economics of integrating biomass gasification for green ammonia production within kraft mills, using KraftSIM modeling to evaluate ammonia production, steam balance, emissions, and utility impacts. The proposed design enables energy and water system integration with the existing mill and allows for a gradual scale-up without disrupting the chemistry and operation of the recovery cycle. Across five scenarios representing different biomass gasification rates ranging from 100 to 1000 bone-dry metric tons per day (BDMT/d), the process yields ammonia at approximately 0.51 metric tons per bone-dry metric ton (t/ BDMT), while generating significant low- and medium-pressure steam and hot water that offset mill utility demands. The incineration of pressure swing adsorption tail gas and ammonia plant purge gas in the power boiler reduces biomass combustion and enhances power boiler efficiency. Economic analysis suggests a net revenue potential of approximately CA$380/BDMT, which could increase with the implementation of biogenic carbon pricing. Overall profitability is strongly influenced by biomass procurement costs, electricity prices, and prevailing green fuel and chemical market premium. This work outlines a practical, near-term decarbonization pathway for kraft mills by coupling green fuel production with potential opportunities for carbon removal.

Replacing Natural Gas with High-Temperature Electric Turbomachinery for Lime Burning in Kilns, TAPPICon26

Towards Process Excellence: Advanced Optimization of Grade Change Operations in Paper, TAPPICon26

The Impact of Process Technology and Bleaching Sequences on the Composition of Pulp Extractives and Pulp Market Quality, TAPPICon26