@phdthesis{Ali2025, author = {Ali, Mohammed Liaket}, title = {Detailed numerical modeling of the iron ore direct reduction process}, doi = {10.26127/BTUOpen-6969}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-69695}, school = {BTU Cottbus - Senftenberg}, year = {2025}, abstract = {The iron and steelmaking industry is among the largest contributors to global CO₂, driven by its energy-intensive processes and reliance on carbon-rich fuels. As steel demand rises in an increasingly competitive global market, innovative and sustainable production methods are urgently needed. The Direct Reduction (DR) process using syngas or hydrogen presents a promising approach to reducing CO₂ emissions and energy consumption in steel production. Computational modeling plays a crucial role in accelerating technology development, yet traditional models, such as the shrinking core model, fail to fully capture the complexities of the reduction process. More advanced models are necessary to simulate interactions between iron ore pellets and reducing gases and to scale effectively to industrial applications. To address these challenges, this dissertation introduces an improved porous solid model that overcomes biases in the shrinking core model, accurately representing the reduction of single iron ore pellets in H₂ and CO environments while accounting for carbon deposition and porosity changes. A comprehensive reduction mechanism is developed and validated against extensive experimental data without parameter adjustments, providing a solid foundation for advanced simulations. Besides the stand-alone kinetic model, a Computational Fluid Dynamics (CFD) solver has been developed, bringing the considerations to a spatially resolved environment, including pellet and gas phase regions. Building on the insights gained from single-pellet models, the research advances to the more complex modeling of fixed beds; a crucial step in bridging the gap between detailed small-scale studies and the case of industrial-sized reactors. A comprehensive methodology is developed, incorporating realistic packed-bed structures and high-quality computational meshes, for particle-resolved CFD simulations of the hydrogen-based direct reduction process in a fixed-bed setup. These simulations reveal crucial insights into the reduction process, such as the non-uniform reduction within the bed, the presence of gas pockets, and the impact of temperature variations due to the endothermic nature of hydrogen-based reduction. Finally, the study explores the influence of pellet sizes and shapes in the DR process via different reconstruction techniques, including computed tomography. By examining beds with various particle characteristics and structures, the research highlights the significant impact of these factors on reduction efficiency and overall conversion rates. This comprehensive modeling approach offers critical insights for optimizing the hydrogen-based direct reduction process, paving the way for its application in industrial-scale reactors. By addressing these research questions and providing innovative solutions, this dissertation contributes to the advancement of DR-technology, offering a path toward more sustainable steel production.}, subject = {Kinetics; Kinetik; Stahlherstellung; Direktreduktion; Modellierung; CFD; Steelmaking; Direct Reduction; Modeling; Stahlherstellung; Numerische Str{\"o}mungssimulation; Direkte Eisengewinnung; Modellierung}, language = {en} } @phdthesis{Ebenezer2014, author = {Ebenezer, Ngozi}, title = {Adaptive Polynomial Tabulation : a computationally efficient strategy for complex kinetics}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:co1-opus4-30051}, school = {BTU Cottbus - Senftenberg}, year = {2014}, abstract = {In this work Adaptive Polynomial Tabulation (APT) is presented. It is a new approach to solve the initial value chemical rate equation system. In this approach zeroeth, first and second order polynomials are used in real-time to approximate the solution of the initial value chemical rate equation system. The sizes of the local regions encountered for the different orders of polynomial approximation are calculated in real-time. To improve accuracy the chemical state space is partitioned into hypercubes. During calculations the hypercubes accessed by the reactive mixture are divided into adaptive hypercubes depending on the accuracy of the local solution. Mixture initial conditions are stored in the adaptive hypercubes. Around each stored initial condition two concentric ellipsoids of accuracy (EOA) are defined. These include the ISAT and identical EOAs. The time evolution of mixture initial conditions which encounter an identical and ISAT EOA are approximated by zero and first order polynomials respectively. With a certain number of stored initial conditions within an adaptive hypercube, its second order polynomial coefficients are constructed from the stored initial conditions. The time evolution of additional mixture initial conditions that encounter this adaptive hypercube are approximated with second order polynomials. The APT model is simplified by the replacement of the entire set of species mass fractions with a progress variable based on the enthalpy of formation evaluated at 298 K. APT has 3 degrees of freedom which include the progress variable, total enthalpy and pressure. The APT model was tested with a zero dimensional Stochastic Reactor Model (SRM) for HCCI engine combustion. A skeletal n-heptane/toluene mechanism with 148 chemical species and 1281 reactions was used. In the tests, the HCCI engine simulations using APT were in very good agreement with the model calculations using the ODE solver. The cool flame and main ignition events were accurately captured. The major and minor species were also accurately captured by APT. In SRM-HCCI calculations without cyclic variations, a computational speed up factor greater than 1000 was obtained when APT was used for all the operating points considered without significant loss in accuracy. For the SRM-HCCI engine calculations with cyclic variations, APT demonstrated a computational speed up exceeding 12 without significant loss in accuracy.}, subject = {ISAT; PRISM; APT; SRM; Polynom; Approximation; ISAT; PRISM; APT; SRM}, language = {en} }