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Records with Keyword: Multiscale Modelling
Achieving Optimal Paper Properties: A Layered Multiscale kMC and LSTM-ANN-Based Control Approach for Kraft Pulping
Parth Shah, Hyun-Kyu Choi, Joseph Sang-Il Kwon
April 11, 2023 (v1)
Keywords: layered kMC simulation, long short-term memory, Machine Learning, Model Predictive Control, Multiscale Modelling, pulp digester
The growing demand for various types of paper highlights the importance of optimizing the kraft pulping process to achieve desired paper properties. This work proposes a novel multiscale model to optimize the kraft pulping process and obtain desired paper properties. The model combines mass and energy balance equations with a layered kinetic Monte Carlo (kMC) algorithm to predict the degradation of wood chips, the depolymerization of cellulose, and the spatio-temporal evolution of the Kappa number and cellulose degree of polymerization (DP). A surrogate LSTM-ANN model is trained on data generated from the multiscale model under different operating conditions, dealing with both time-varying and time-invariant inputs, and an LSTM-ANN-based model predictive controller is designed to achieve desired set-point values of the Kappa number and cellulose DP while considering process constraints. The results show that the LSTM-ANN-based controller is able to drive the process to desired set-poin... [more]
Multiscale Modeling for Reversible Solid Oxide Cell Operation
Fiammetta Rita Bianchi, Arianna Baldinelli, Linda Barelli, Giovanni Cinti, Emilio Audasso, Barbara Bosio
April 3, 2023 (v1)
Keywords: Aspen Plus simulation, experimental validation, Multiscale Modelling, reversible cell, SOLID oxide cell
Solid Oxide Cells (SOCs) can work efficiently in reversible operation, allowing the energy storage as hydrogen in power to gas application and providing requested electricity in gas to power application. They can easily switch from fuel cell to electrolyzer mode in order to guarantee the production of electricity, heat or directly hydrogen as fuel depending on energy demand and utilization. The proposed modeling is able to calculate effectively SOC performance in both operating modes, basing on the same electrochemical equations and system parameters, just setting the current density direction. The identified kinetic core is implemented in different simulation tools as a function of the scale under study. When the analysis mainly focuses on the kinetics affecting the global performance of small-sized single cells, a 0D code written in Fortran and then executed in Aspen Plus is used. When larger-scale single or stacked cells are considered and local maps of the main physicochemical prop... [more]
Multiscale Molecular Dynamics Simulations of Fuel Cell Nanocatalyst Plasma Sputtering Growth and Deposition
Pascal Brault
March 27, 2023 (v1)
Keywords: gas aggregation source, molecular dynamics, Multiscale Modelling, nanocatalyst, PEM fuel cell electrodes, plasma sputtering
Molecular dynamics simulations (MDs) are carried out for predicting platinum Proton Exchange Membrane (PEM) fuel cell nanocatalyst growth on a model carbon electrode. The aim is to provide a one-shot simulation of the entire multistep process of deposition in the context of plasma sputtering, from sputtering of the target catalyst/transport to the electrode substrate/deposition on the porous electrode. The plasma processing reactor is reduced to nanoscale dimensions for tractable MDs using scale reduction of the plasma phase and requesting identical collision numbers in experiments and the simulation box. The present simulations reproduce the role of plasma pressure for the plasma phase growth of nanocatalysts (here, platinum).
Fuel Reactor CFD Multiscale Modelling in Syngas-Based Chemical Looping Combustion with Ilmenite
Vlad-Cristian Sandu, Ana-Maria Cormos, Calin-Cristian Cormos
March 9, 2023 (v1)
Keywords: 3D particle, carbon capture and storage, chemical looping combustion, Computational Fluid Dynamics, ilmenite oxygen carrier, Multiscale Modelling, reaction chamber, Syngas
As global power generation is currently relying on fossil fuel-based power plants, more anthropogenic CO2 is being released into the atmosphere. During the transition period to alternative energy sources, carbon capture and storage seems to be a promising solution. Chemical-looping combustion (CLC) is an energy conversion technology designed for combustion of fossil fuel with advantageous carbon capture capabilities. In this work, a 1D computational fluid dynamics (CFD) multiscale model was developed to study the reduction step in a syngas-based CLC system and was validated using literature data (R=0.99). In order to investigate mass transfer effects, flow rate and particle dimension studies were carried out. Sharper mass transfer rates were seen at lower flow rates and smaller granule sizes due to suppression of diffusion limitations. In addition, a 3D CFD particle model was developed to investigate in depth the reduction within an ilmenite particle, with focus on heat transfer effect... [more]
Effects of Composite Electrode Structure on Performance of Intermediate-Temperature Solid Oxide Electrolysis Cell
Zaiguo Fu, Zijing Wang, Yongwei Li, Jingfa Li, Yan Shao, Qunzhi Zhu, Peifen Weng
February 27, 2023 (v1)
Keywords: composite electrode, multi-component diffusion, multiphysics modeling, Multiscale Modelling, porous media, SOEC
The composite electrode structure plays an important role in the optimization of performance of the intermediate-temperature solid oxide electrolysis cell (IT-SOEC). However, the structural influence of the composite electrode on the performance of IT-SOEC is not clear. In this study, we developed a three-dimensional macroscale model coupled with the mesoscale model based on percolation theory. We describe the electrode structure on a mesoscopic scale, looking at the electrochemical reactions, flow, and mass transport inside an IT-SOEC unit with a composite electrode. The accuracy of this multi-scale model was verified by two groups of experimental data. We investigated the effects of operating pressure, volume fraction of the electrode phase, and particle diameter in the composite electrode on electrolysis reaction rate, overpotential, convection/diffusion flux, and hydrogen mole fraction. The results showed that the variation in the volume fraction of the electrode phase had opposite... [more]
Application of LSTM Approach for Predicting the Fission Swelling Behavior within a CERCER Composite Fuel
Jian Zhao, Zhenyue Chen, Jingqi Tu, Yunmei Zhao, Yiqun Dong
February 24, 2023 (v1)
Keywords: data-driven, finite element analysis, fission swelling, LSTM deep learning, Multiscale Modelling
Irradiation-induced swelling plays a key role in determining fuel performance. Due to their high cost and time demands, experimental research methods are ineffective. Knowledge-based multiscale simulations are also constrained by the loss of trustworthy theoretical underpinnings. This work presents a new trial of integrating knowledge-based finite element analysis (FEA) with a data-driven deep learning framework, to predict the hydrostatic-pressure−temperature dependent fission swelling behavior within a CERCER composite fuel. We employed the long short-term memory (LSTM) deep learning network to mimic the history-dependent behaviors. Training of the LSTM is achieved by processing the sequential order of the inputs to do the forecasting; the input features are fission rate, fission density, temperature, and hydrostatic pressure. We performed the model training based on a leveraged dataset of 8000 combinations of a wide range of input states and state evaluations that were generated by... [more]
Use of Multiscale Data-Driven Surrogate Models for Flowsheet Simulation of an Industrial Zeolite Production Process
Vasyl Skorych, Moritz Buchholz, Maksym Dosta, Helene Katharina Baust, Marco Gleiß, Johannes Haus, Dominik Weis, Simon Hammerich, Gregor Kiedorf, Norbert Asprion, Hermann Nirschl, Frank Kleine Jäger, Stefan Heinrich
February 23, 2023 (v1)
Keywords: data-driven modeling, flowsheet simulation, kiln, Multiscale Modelling, solid–liquid separation, spray drying, synthesis, zeolite production
The production of catalysts such as zeolites is a complex multiscale and multi-step process. Various material properties, such as particle size or moisture content, as well as operating parameters—e.g., temperature or amount and composition of input material flows—significantly affect the outcome of each process step, and hence determine the properties of the final product. Therefore, the design and optimization of such processes is a complex task, which can be greatly facilitated with the help of numerical simulations. This contribution presents a modeling framework for the dynamic flowsheet simulation of a zeolite production sequence consisting of four stages: precipitation in a batch reactor; concentration and washing in a block of centrifuges; formation of droplets and drying in a spray dryer; and burning organic residues in a chain of rotary kilns. Various techniques and methods were used to develop the applied models. For the synthesis in the reactor, a multistage strategy was us... [more]
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