Modeling of an aluminum reduction cell for the development of a state estimator

Biedler, Philip L.

doi:10.33915/etd.2475

Cited by 3 publications

(4 citation statements)

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“…2‐D heat transfer in a reduction cell through ledge and sidewall is computed in this model based on heat equations. Heat dissipation from the cell through the top and the bottom of the reduction cell is estimated by the corresponding heat loss percentages of a typical reduction cell . The model takes individual anode currents and cell voltage signals as major inputs to calculate temperature distribution and boundary shift between ledge and bath region based on the subsystems' structure.…”

Section: Modeling Approachmentioning

confidence: 99%

“…Heat transfer coefficients between bath and ledge

{\bar{h}}_{b}

, and between metal and ledge

{\bar{h}}_{m}

, range from 830 W m −2 K −1 to 1600 W m −2 K −1 and 400 W m −2 K −1 to 1500 W m −2 K −1 in literature . As the focus of the model is to compute the change of ledge thickness based on the variation of anode current distribution, rather than the absolute thickness, the choice of heat transfer coefficients is not crucial in this article.…”

Section: Thermal and Materials Balancesmentioning

confidence: 99%

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Spatial temperature profiles in an aluminum reduction cell under different anode current distributions

et al. 2012

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The development of a thermal model to estimate energy distribution in an aluminum reduction cell and its impact on local conditions based on anode current signals are presented. In the Hall-He´roult process, routine practices carried out during operation give rise to spatial energy imbalances and consequently temperature variation in the cell. This phenomenon has been ignored in thermal models developed to date as they are only concerned with overall process dynamics. Implementing anode current signals as model inputs along with the discretization method allows the change of spatial conditions caused by current distribution to be calculated. Simulation studies have been performed to investigate the cell thermal balance affected by anode shorting. The article shows the potential of using anode current signals as model inputs to compute spatial thermal conditions based on the proposed model structure that are not considered in traditional modeling approaches. Figure 1. Schematic diagram of a reduction cell and a resistance network.where R sw and R L are the thermal resistance of the cell sidewall and the ledge, respectively. Resistance of the sidewall can vary due to the design of different cell technology. Figure 23. Deviation of ledge thickness d 0 , at upstream at the center of the cell (Case S3).

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Section: Modeling Approachmentioning

confidence: 99%

“…Heat transfer coefficients between bath and ledge

{\bar{h}}_{b}

, and between metal and ledge

{\bar{h}}_{m}

Section: Thermal and Materials Balancesmentioning

confidence: 99%

Spatial temperature profiles in an aluminum reduction cell under different anode current distributions

et al. 2012

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“…Depending on the immense amount of energy used in the aluminum reduction process, small operational improvements scan produce very significant savings. For example, a reduction in voltage of 0.1 V in a single cell that operates with 100 kA would save approximately 90.000 kWh per year [3]. The process for the production of aluminum, actually, energy consumption of is ranged between 13-14 kWh/kg aluminium [4].…”

Section: Introductionmentioning

confidence: 99%

Attenuation of magnetohydrodynamic oscillations in an aluminum reduction cell using periodic structures

Andere¹,

Oliveira²

2021

9th Edition of the International Conference on Computational Methods for Coupled Problems in Science and Engineering

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Magnetohydrodynamic instability (MHD) in an aluminum reduction cell is due to the interactions between the conductive liquid currents and the magnetic field generated by very high currents flowing through current feeding circuit buses. Such phenomenon creates oscillations in this fluid, compromising the efficiency of the process aluminum reduction. The reduction cells consist, in their usual configuration, of a container with flat walls that accommodates the liquid. In this work, a new geometry is proposed for the container based on periodic structures, with the aim of to mitigate such oscillations. The analysis of oscillations of fluid in both configurations is made with a software developed in this work to numerically simulate the process in two dimensions. The numerical formulation employed is based on the finite-difference time-domain method to solve the Navier-Stokes equations (N-S) explicitly through the Chorin projections method. The volume and surface of the fluid are mapped using the MAC method. The liquid is treated as incompressible and viscous, in addition to being electrically conductive. The accelerations caused by magnetic field and the electric currents are coupled to N-S by calculating the Lorentz Force. The results are analyzed by calculating differences between liquid heighs obtained at rest and by applying electric currents.

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“…SH-SY5Y is a subclone of SK-N-SH, which was isolated from bone marrow. 12,13 SH-SY5Y has been used for decades as an in vitro model of neuronal function, differentiation, and dysregulation. Studies using this cell line include those focusing on neurogenesis, as well as neurodegeneration research related to Parkinson's and Alzheimer's diseases.…”

mentioning

confidence: 99%

mTMT: An Alternative, Nonisobaric, Tandem Mass Tag Allowing for Precursor-Based Quantification

Paulo

Gygi

2019

Anal. Chem.

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Stable isotope labeling of peptides is the basis for numerous mass-spectrometry-based quantification strategies. Isobaric tagging and metabolic labeling, namely, tandem mass tagging (TMT) and SILAC, are among the most widely used techniques for relative protein quantification.Here we report an alternative, precursor-based quantification method using nonisobaric TMT variants: TMTzero (TMT0) and superheavy TMT (shTMT). We term this strategy mass difference tandem mass tagging (mTMT). These TMT variants differ by 11 mass units; however, peptides labeled with these reagents coelute, analogous to SILAC-labeled peptide pairs. As a proof-ofconcept, we profiled the proteomes of two cell lines that are frequently used in neuroscience studies, SH-SY5Y and SVGp12, using mTMT and standard SILAC-labeling approaches. We show similar quantified proteins and peptides for each method, with highly correlated fold-changes between workflows. We conclude that mTMT is a suitable alternative for precursor-based protein quantification.

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Modeling of an aluminum reduction cell for the development of a state estimator

Cited by 3 publications

References 0 publications

Spatial temperature profiles in an aluminum reduction cell under different anode current distributions

Spatial temperature profiles in an aluminum reduction cell under different anode current distributions

Attenuation of magnetohydrodynamic oscillations in an aluminum reduction cell using periodic structures

mTMT: An Alternative, Nonisobaric, Tandem Mass Tag Allowing for Precursor-Based Quantification

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