Thesis: Ph. D., Massachusetts Institute of Technology, Department of Mechanical Engineering, 2017. / Cataloged from PDF version of thesis. / Includes bibliographical references (pages 161-170). / Gas-solid fluidized bed reactors find many applications in the energy, chemical and biomedical industries because of their high heat and mass transfer. Their design and optimization continue to be a challenge; the dependence of mixing dynamics on operating conditions and the impact of the reactor scale are poorly understood. This is compounded by severe limitations on diagnostics in their harsh operating environment. Computational Fluid Dynamics (CFD) will play a pivotal role in advancing this technology since it enables unrestricted access inside the reactor, enhancing fundamental understanding of several coupled phenomena and their interactions at various scales. The thesis is focused on the bubbling fluidization of Geldart B particles (typically 103<Ar<105 and 100<Re<102) for application to biomass gasification reactors. 3D CFD simulations are conducted using the Two-Fluid framework, representing the solids phase as a continuum and optimally balancing fidelity and computational needs. To ensure accuracy, critical submodels accounting for unresolved particle-scale interactions (solids stress tensor, particle-gas drag force and particle-wall slip condition) are identified, and computational efficiency gains are achieved through optimal choice of coordinate system, domain discretization and grid resolution. The modeling framework is validated by comparing predictions with experimental measurements spanning a wide range of operating conditions and diagnostic techniques. We performed some of the first fine-grid 3D simulations of intermediate sized beds (30-70 cm diameter) and identified bubbling dynamics and solids circulation as key metrics for characterizing the fluidization hydrodynamics accurately. Towards this end, we developed Multiphase-flow Statistics using 3D Detection and Tracking Algorithm (MS3DATA) to detect and track bubbles using time and spatially resolved data. Our tools are employed to quantify the effect of reactor size on fluidization hydrodynamics. Under similar operating conditions, significantly larger bubbles are observed in small lab-scale beds (~10-15 cm diameter) because of flow confinement. However, the mechanism for bubble coalescence and growth is consistent across reactor scales: small bubbles are formed near the gas distributor, coalesce and rise laterally towards the bed center forming slugs. The transition to slugging also marks a shift in the dominant solids circulation pattern and is dependent on the bed geometry and excess gas velocity. The analysis conclusively demonstrates that (a) the hydrodynamics are independent of walls only when bubbles are much smaller than reactor dimensions and (b) within the regime of interest, a 50 cm diameter pilot reactor is representative of larger scales. Mixing dynamics are quantified by examining the gas and solids flow-field in and around bubbles. Bubble rise velocity is proportional to the square root of its diameter, while gas flow sufficiently far (~30 particle diameters) depends only on the particle properties. Meanwhile, voidage distribution in the vicinity of bubbles results in higher local permeability to gas flow causing (a) preferential bubble pathways, as bubbles are propelled towards areas already frequented by bubbles and (b) gas bypass or throughflow, as low resistance networks are created for interstitial dense-phase gas. Under typical bubbling conditions of Geldart B particles, throughflow almost short circuits through the reactor (residence time is 2-3x shorter than global average) and can reach 30-40% of the total gas flow with detrimental effects on solids mixing and fuel conversion. A predictive model, based on the local bubble-induced micromixing driven by solids upflow around the bubble nose and wake regions and downflow along its sides, has been developed for scaling the gross solids circulation by integrating over the bubble size and spatial distribution. Moreover, reduced models coupling mixing rates (from simulations) and gasification kinetics have been developed and used to analyze thermochemical conversion of biomass. Our CFD approach will be employed for reactive particulate systems in complex reactor geometry, while utilizing discrete element methods to further the fundamental understanding of the hydrodynamics-chemical kinetics coupling, and develop submodels for the continuum framework applications. / by Akhilesh Bakshi. / Ph. D.
| Identifer | oai:union.ndltd.org:MIT/oai:dspace.mit.edu:1721.1/108951 |
| Date | January 2017 |
| Creators | Bakshi, Akhilesh |
| Contributors | Ahmed F. Ghoniem., Massachusetts Institute of Technology. Department of Mechanical Engineering., Massachusetts Institute of Technology. Department of Mechanical Engineering. |
| Publisher | Massachusetts Institute of Technology |
| Source Sets | M.I.T. Theses and Dissertation |
| Language | English |
| Detected Language | English |
| Type | Thesis |
| Format | 173 pages, application/pdf |
| Rights | MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission., http://dspace.mit.edu/handle/1721.1/7582 |
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