Dynamic modelling of catalytic SO2 converter in a sulfuric acid plant of an industrial smelter

In industrial nickel and copper production, sulfur dioxide (SO2) is generated from the combustion of sulfide ores. With increasingly tightened regulations on SO2 emissions, a sulfuric acid plant has become a crucial part of industrial smelters. It converts environmentally harmful SO2, which is generated in smelter furnaces, roasters, and Cu-reactors, into commercially beneficial sulfuric acid. This method is recognized as one of the most effective ways to ensure that smelters are able to satisfy the SO2 emission regulations. A sulfuric acid plant is primarily comprised of a central catalytic SO2 converter, SO3 (sulfur trioxide) absorption towers and a series of interconnected heat exchangers. The catalytic SO2 converter is the key component and the focus of this research. Both steady-state and dynamic models of the converter are developed in this thesis. A steady-state model of the converter is established in accordance with steady-state mass and energy balances. The developed model provides an explicit relation between SO2 conversion ratio and gas temperature, which is denoted as the heat-up path of the converter. By combining the heat-up path with the equilibrium curve of the SO2 oxidation reaction, an equilibrium state for every converter stage can be obtained. Using the developed steady-state model, simulations are performed to investigate the effect of inlet SO2 molar fraction and gas temperature on the equilibrium conversion ratio. In an industrial SO2 converter, the SO2 concentration and conversion ratio out of each bed are important variables but are not measured in real time. To monitor these unmeasured variables in industrial operations, a soft sensor is proposed by combining the derived steadystate model with dynamic data analysis. The obtained soft sensor provides a real-time estimation of outlet SO2 concentration and the conversion ratio from measured temperatures. For synchronization between the inlet SO2 concentration and outlet temperature, a first-order exponential data filter is applied to the feed SO2 data. With the filtered signal being used, the proposed soft sensors give a satisfactory estimation of both outlet SO2 concentration and conversion ratio in the converter stages. Dynamic modelling is carried out using two different model forms: ordinary differential equation (ODE) and partial differential equation (PDE) models. The ODE model is obtained by applying dynamic mass and energy conservation to the SO2 converter. The resulting model can be used in industrial applications and describes the converter performance even if information of reaction kinetics is not available. A good fit with collected industrial data verifies the validity of the developed ODE model. The effect of process input variables is studied using simulations with the ODE model. Dynamic modelling is performed by implementing mass and energy balances on both fluid and solid-phase gas flows. The proposed two-phase dynamic model, which takes the PDE form, is able to generate detailed profiles of the SO2 converter within time and space. With the estimated parameters, this two-phase dynamic model generates a good fit between the simulated and measured outlet temperatures. Based on the PDE model, simulations are run to investigate the detailed mechanistic performance of the converter. The detailed PDE model provides useful explanation of, and prediction for the converter behaviour.Doctor of Philosophy (PhD) in Natural Resources Engineerin

Editorial: Machine learning in studies of atmospheric environment and climate change

ISSN:2296-665

Exploring Training Effect in 42 Human Subjects Using a Non-invasive Sensorimotor Rhythm Based Online BCI

Electroencephalography based brain-computer interfaces (BCIs) show promise of providing an alternative communication channel between the brain and an external device. It is well acknowledged that BCI control is a skill and could be improved through practice and training. In this study, we explore the change of BCI behavioral performance as well as the electrophysiological properties across three training sessions in a pool of 42 human subjects. Our results show that the group average of BCI accuracy and the information transfer rate improved significantly in the third session compared to the first session; especially the significance reached in a smaller subset of a low BCI performance group (average accuracy <70%) as well. There was a significant difference of event-related desynchronization (ERD) lateralization for BCI control between the left- and right-hand imagination task in the last two sessions, but this significant difference was not revealed in the first training sessions. No significant change of R2 value or event-related desynchronization and synchronization (ERD/ERS) for either channel C3 or channel C4, which were used for online control, was found across the training sessions. The change of ERD lateralization was also not significant across the training sessions. The present results indicate that BCI training could induce a change of behavioral performance and electrophysiological properties quickly, within just a few hours of training, distributed into three sessions. Multiple training sessions might especially be beneficial for the low BCI performers

Analytical and computational method of structure-borne noise and shock resistance of gear system

An approach to synthetically evaluate structure-borne noise and shock resistance of gear system is proposed. Firstly, dynamic finite element mesh model of gear system which includes shafts, bearings, gears and housing is established by using spring element, tetrahedral element and hexahedral element. Then dynamic finite element analysis model of gear system is gotten by loading the dynamic excitation force which can be calculated via the computation program of gear pair stiffness excitation, error excitation and impact excitation onto the tooth meshing line as boundary conditions. And the dynamic response of gear system is analyzed by using modal superposition method, and the vibration response experimental study of gear system is performed on the gearbox test-bed. The comparative analysis shows that computational results of the vibration response are in good agreement with the data of experiment tests and it could verify the rationality of dynamic finite element mesh model of gear system. Finally, taking acceleration shock excitation load into account on the basis of the dynamic finite element mesh model, the impact response of gear system is solved, and the shock resistance is analyzed based on the strength decision criterion

Power allocation for D2D communications in heterogeneous networks

In this paper, we study power allocation for D2D communications in heterogeneous networks utilizing game theory approach to improve the performance of the whole system. Given D2D's underlay status in the system, Stackelberg game framework is well suited for the situation. In our scheme, macrocell system and femtocell system are considered as two leaders and D2D pairs are considered as the follower, forming a two-leader-one-follower Stackelberg game. The leaders act first, charging some fees from the follower for using the channel and causing interference to jeopardize their communication equality. The follower observes the leaders' behavior and develops its strategy based on the prices offered by the leaders. We analyse the procedure and obtain the Stackeberg equilibrium, which determines the optimal prices for the leaders and optimal transmit power for the follower. In the end, simulations are executed to validate the proposed allocation method, which significantly improves data rate of user equipments. ? 2014 Global IT Research Institute (GIRI).EICPCI-S(ISTP)

(3-{[2,6-Bis(1-methyl­eth­yl)phen­yl]imino-κN}-1-phenyl­but-1-en-1-olato-κO)­di­methyl­aluminium

The mol­ecular structure of the title compound, [Al(CH3)2(C22H26NO)], displays a monomer with the AlIII atom in a distorted tetra­hedral environment defined by two methyl groups and the N and O atoms of the chelating ketiminate anion. The O—Al—N bite angle of the chelating ligand is 94.14 (9)°. The O—C—C—C—N backbone of the ligand is nearly coplanar (r.m.s. deviation = 0.029 Å) and the Al atom deviates significantly from the mean plane by 0.525 (3) Å. In the crystal, weak inter­molecular C—H⋯O inter­actions are observed

Synergistic Antitumor Effect of Dichloroacetate in Combination with 5-Fluorouracil in Colorectal Cancer

Dichloroacetate (DCA), an inhibitor of pyruvate dehydrogenase kinase (PDK), has been recently demonstrated as a promising nontoxic antineoplastic agent that promotes apoptosis of cancer cells. In the present study, we aimed to investigate the antitumor effect of DCA combined with 5-Fluorouracil (5-FU) on colorectal cancer (CRC) cells. Four human CRC cell lines were treated with DCA or 5-FU, or a combination of DCA and 5-FU. The cell viability was determined by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay. The interaction between DCA and 5-FU was evaluated by the median effect principle. Immunocytochemistry with bromodeoxyuridine (BrdU) was carried out to determine the proliferation of CRC cells. Cell cycle and apoptosis were measured by flow cytometry, and the expression of apoptosis-related molecules was assessed by western blot. Our results demonstrated that DCA inhibited the viability of CRC cells and had synergistic antiproliferation in combination with 5-FU. Moreover, compared with 5-FU alone, the apoptosis of CRC cells treated with DCA and 5-FU was enhanced and demonstrated with the changes of Bcl-2, Bax, and caspase-3 proteins. Our results suggest that DCA has a synergistic antitumor effect with 5-FU on CRC cell lines in vitro