Energy Efficiency in Paper Processing
Berkeley Lab | Lawerence Livermore National Laboratory
Agenda 2020 partnered with Livermore and Berkeley labs to optimize one of the most energy-intensive steps in the papermaking process—drying the wet paper pulp.
Computation Helps Boost Energy Efficiency in Paper Processing
Under the High-Performance Computing for Manufacturing (HPC4Mfg) Program, researchers are developing detailed computer models to optimize the paper-making process.
Industry Need for More Energy- Efficient Processes
According to the U.S. Energy Information Administration, paper manufacturing is the third-largest energy consuming industry in the United States, ranking only behind petroleum-refining and chemical manufacturing. To mitigate the paper industry’s energy burden, the Agenda 2020 Technology Alliance, a nonprofit consortium of paper manufacturers, has developed a roadmap to decrease energy usage by 20 percent by the year 2020. The reduction could save the industry up to 80 trillion British Thermal Units (BTUs)—a traditional unit of heat—per year and as much as $250 million annually.
The Department of Energy’s High-Performance Computing for Manufacturing (HPC4Mfg) program is a multilaboratory effort that seeks to use high-performance computing to address complex challenges in U.S. manufacturing. Through this program, Agenda 2020 partnered with Lawrence Livermore and Lawrence Berkeley national laboratories to optimize one of the most energy-intensive steps in the papermaking process—drying the wet paper pulp.
Efforts Focus on Wet-Pressing in Paper Manufacturing
The paper drying process involves a “wet-pressing” step, in which saturated, porous paper pulp is fed onto a moving belt of fine-mesh screening that holds a felt layer. The felt–pulp layers are squeezed through rollers and passed over steam-heated cylinders to remove the remaining water. However, as the layers leave the rollers and the pressure eases, the pulp sucks up some of the residual moisture from the felt, re-wetting the paper.
In collaboration with Agenda 2020, researchers at Lawrence Livermore and Lawrence Berkeley national laboratories are using the their supercomputering resources to study the re-wetting process. By leveraging the laboratories’ advanced simulation capabilities, high-performance computing resources, and industry paper-machine press data, researchers are developing integrated numerical models to understand the physics of re-wetting and help the paper industry design more energy-efficient processes.
Collaboration Yields Fruitful Results
Using existing industry data, including felt measurements, computerized tomography (CT) images of the felt, and paper-machine press data, the laboratories developed a coupled-physics simulation framework to determine how water flows through porous paper pulp during and after the wet-pressing process. The model was designed to help researchers study how to increase paper dryness after pressing and before the final drying stage.
Lawrence Livermore developed the continuum simulation framework, integrating mechanical deformation and two-phase flow models, while Lawrence Berkeley developed a microscale flow model for the complex pore structures in the press felts, utilizing sophisticated modeling capabilities. Lawrence Berkeley used 50,000–60,000 cores at its computer facility to run these simulations, allowing the engineering-scale models to be more accurate by informing better parameterizations from microscale data.
The results from the initial continuum model clearly showed the deformation and dryness of the paper as it traverses rollers and provided a detailed numerical view of the process—an essential first step to optimizing paper drying. The model has been calibrated and validated by laboratory measurements and industry data, suggesting that the multiphysics modeling framework can adequately capture paper de-watering behaviors as observed at an operational scale. This information can be used to inform designs of more energy-efficient processes and equipment. The model results also indicate that mechanical properties of paper and felts play a key role in controlling paper de-watering processes, and thus require more rigorous evaluation through detailed laboratory measurements and high-fidelity pore-scale analysis.
Researchers are confident they can develop the computational models needed to invent optimized wet-pressing processes and achieve the goals set forth by the Agenda 2020 industry alliance. To create more accurate and reliable computational models, researchers will need to develop a fundamental understanding of the complex phenomenon associated with water flow and migration. Future work to address this problem will require a strong continued collaboration between computational scientists and experimental scientists from the paper-manufacturing industry, who can provide data on paper material properties, experimental data from controlled de-watering tests, and high-resolution micro-CT images.
How to Work with Us
For more information, visit hpc4mfg.org or contact us at hpc4mfg [at] llnl.gov (hpc4mfg[at]llnl[dot]gov).
Your Success Story Awaits
HPC4EI brings together the diverse set of computational skills and supercomputing capabilities of DOE National Laboratories to increase US industry’s energy efficiency and advance competitiveness. Learn about the next opportunity to partner with the superb talent and high performance computing platforms at DOE National Laboratories.
Please email hpc4ei [at] llnl.gov (subject: HPC4EI%20Assistance%20%28Success%20Story%29) (hpc4ei[at]llnl[dot]gov) for further assistance.
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High Performance Computing for Energy Innovation (HPC4EI) is funded by the Department of Energy’s Energy Efficiency and
Renewable Energy’s (EERE) Advanced Materials and Manufacturing Technologies Office (AMMTO), Industrial Efficiency and Decarbonization Office (IEDO) and Office of Fossil Energy and Carbon Management (FECM). The HPC4EI program pairs industry engineers and scientists with national laboratory computational experts to solve difficult production and design problems aiming to reduce national energy consumption. Since its inception 2015, the HPC4EI program has funded over 160 projects with participation by 11 different national laboratories. The world-class computational capabilities at the national laboratories are used to address problems in steel and aluminum manufacture, jet turbine design and manufacture, advanced materials for light weighting and high
temperature, high corrosion applications, chemical processing and many more topic areas.