Browsing by Subject "Distillation apparatus"
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Item A comparison of Berl saddles and Nor-Pac rings for absorption in the air-ammonia-water system(Texas Tech University, 1990-05) Caraway, Trina L.This research has two objectives. The first objective is to determine three conventional packed tower performance characteristics for each of two packings: 1/2-in. (nominal) ceramic Berl saddles and 5/8-in. (nominal) polypropylene Nor-Pac® rings. The characteristics are the gas-handling capacity; the height of a transfer unit; and the overall, gas-associated with each packing. The second objective is to compare these performance characteristics in order to determine which packing has the higher gas-handling capacity, the lower height of a transfer unit, and the higher overall, gas-side, mass-transfer coefficient. The first objective was met by obtaining experimental data from a single laboratory-scale gas absorber packed first with the Berl saddles, then with the Nor-Pac® rings when they became available. The data includes the pressure drop at various air and water flowrates, which was used to determine a set of flooding and loading points. The operating range and the gas-handling capacity associated with each packing were based on the flooding- and loading-point data. The packed tower was then used as an absorber to remove ammonia from air using water as the liquid solvent. The steady-state inlet and outlet compositions were used to calculate the number of transfer units (NTU), which represent the amount of contacting required to accomplish a phase enrichment, divided by the driving force in phatphase.^ The HTU values were obtained from the NTU and the height of the packed section. Subsequently, the HTU and other proces parameters were used to calculate KoG. The second objective was met by comparing the flooding points and operating ranges of each packing, as well as the HTUs and KQGS. These last two parameters were reported as functions of both the gas and the liquid flowrates.Item Packed reactive distillation columns: modeling, simulation, and control analyses(2003) Lextrait, Sébastien Walter; Edgar, Thomas F.Item Simulation and control of complex distillation processes(Texas Tech University, 2000-05) Huang, HaitaoThe proper choice and implementation of control method improve reliability and performance of distillation column control, which can translate into a reduction of energy usage while maintaining product quality and rates, hence economic benefit. However, clear guidelines to determine which and when advanced control strategies should be used instead of traditional control strategies are still not available. Previous work has been focused on two-product single columns. In this study, two complex distillation processes, a fluid catalytic cracker unit (FCCU) main fractionator and a gas recovery unit, are simulated with rigorous models. Traditional decentralized and model predictive control (MPC) are applied to both processes, and their performances are compared in terms of their capability to handle constrained multivariable processes. A detailed tray-to-tray rigorous model for the FCCU main fractionator is developed, in which the Soave-Redlich-Kwong (SRK) equations are used to model vapor-liquid phase equilibrium. The feed is characterized as a mixture of 36 pseudo-components and 9 defined components including water, hydrogen and light hydrocarbons from CI to C4. An efficient algorithm is developed to solve the dynamic model equations. Two decentralized control systems, one without decoupler, one with a simple decoupler are implemented, and compared with a DMCPlus™ controller. The DMCPlus™ controller performs better than both decentralized controls due to its superior decoupling power. The gas recovery unit consists of three distillation columns operated in series with feed-bottoms heat integration for the first column. Rigorous models are developed for the columns and the heat exchanger, including pressure and heat transfer dynamics. The process is a highly coupled system and has interactive constraints that exist in different units. A decentralized control system with override controls for constraints is designed, implemented on the GRU simulator, and is compared with a DMCPlus™ controller with 10 independent variables and 12 dependent variables. The DMCPlus™ controller outperforms the decentralized control system in terms of constraint handling due to its flexibility. The effects of including level control into MPC are also investigated. Three DMCPlus™ controllers with different strategies for controlling the bottom level of the first column are implemented for the GRU process. The first DMCPlus™ controller does not control the level, while the second one moves setpoint to the PI level controller, and the third one controls the level directly by manipulating the deethanizer bottoms flow. The results show that including level into MPC controller improves composition control in cases that the manipulated variable for the level control has significant impact on compositions.Item Using neural networks for control of multicomponent distillation(Texas Tech University, 1995-05) Flathouse, Scott E.Distillation colunms comprise a large part of the chemical industry's processing infrastructure. Currently, distillation is the most widely used separation process in the industry. The behavior of these processes, however, can be highly nonideal and nonlinear. Additionally, the variables that contiol the columns can be highly coupled. Thus, contiol of distillation columns is often a difficult, yet important process contiol challenge. Three-product distillation is a process where, in addition to the overhead and bottoms products, an additional vapor or liquid product is removed from the side of the column. This distillation technique is applied to process cmde stieams with multiple components. The side stieam draw is used to recover a product whose boiling point lies between those of other components in the feed. Normally, a vapor draw is removed below the feed stage, or a liquid draw is removed above it. This additional product provides an extia dimension of complexity over ordinary distillation in the control challenge by adding another manipulated and controlled variable.