Relevant bibliographies by topics / Depropanizer

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Book chapters
  4. Conference papers

Academic literature on the topic 'Depropanizer'

Author: Grafiati
Published: 4 June 2021
Last updated: 11 February 2022

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Journal articles on the topic "Depropanizer"

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Wahid, Abdul, and Ilham Maulana. "Optimation of Depropanizer Unit using Turbo Expander and Its Controller using Model Predictive Control." E3S Web of Conferences 67 (2018): 03014. http://dx.doi.org/10.1051/e3sconf/20186703014.

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In this study, Turbo expander (TE) and Model Predictive Control (MPC) is suggested for depropanizer unit to increase propane recovery and improve control performance of the unit. The model that used in the MPC is a first order plus dead time (FOPDT), which tested the control performance using set point (SP) and disturbance change test. The measurement of the performance is the integral of the absolute error (IAE). As a result, use of TE in the depropanizer able to increase the recovery of propane of 8.44% (from 82.11% to 90.55%). The control structure of the depropanizer unit using turbo expan
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Burgos-Madrigal, Paulina, Diego F. Mendoza, and Mariano López de Haro. "On Entropy Generation and the Effect of Heat and Mass Transfer Coupling in a Distillation Process." Journal of Non-Equilibrium Thermodynamics 43, no. 1 (2018): 57–74. http://dx.doi.org/10.1515/jnet-2017-0039.

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AbstractThe entropy production rates as obtained from the exergy analysis, entropy balance and the nonequilibrium thermodynamics approach are compared for two distillation columns. The first case is a depropanizer column involving a mixture of ethane, propane, n-butane and n-pentane. The other is a weighed sample of Mexican crude oil distilled with a pilot scale fractionating column. The composition, temperature and flow profiles, for a given duty and operating conditions in each column, are obtained with the Aspen Plus V8.4 software by using the RateFrac model with a rate-based nonequilibrium
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Carling, G. A., and R. K. Wood. "The Dynamics and Control of a Depropanizer." IFAC Proceedings Volumes 19, no. 15 (1986): 167–73. http://dx.doi.org/10.1016/s1474-6670(17)59417-3.

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Fikar, M., M. A. Latifi, and Y. Creff. "Optimal changeover profiles for an industrial depropanizer." Chemical Engineering Science 54, no. 13-14 (1999): 2715–20. http://dx.doi.org/10.1016/s0009-2509(98)00375-3.

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Fikar, M., M. A. Latifi, J. P. Corriou, and Y. Creff. "CVP-based optimal control of an industrial depropanizer column." Computers & Chemical Engineering 24, no. 2-7 (2000): 909–15. http://dx.doi.org/10.1016/s0098-1354(00)00355-0.

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Adesina, Kehinde Adewale, and C. Abiodun Popoola. "Exergy Rate Profile of Multicomponent Distillation System." International Journal of Recent Contributions from Engineering, Science & IT (iJES) 4, no. 2 (2016): 29. http://dx.doi.org/10.3991/ijes.v4i2.5710.

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Exergy rate profiles, exergetic efficiency and irreversibility were used to examine the driving forces in multicomponent distillation system with the view to identifying feasible and efficient operating parameters. The mixture used comprised of 5% propane, 15% iso-butane, 25% nbutane, 20% iso-pentane and 35% n-pentane. Operating variables were feed temperature (-30 oC and -80 oC), pressure (800 kPa and 1200 kPa), and reflux-ratio (2 and 6). Stage-by-stage system exergy analysis was estimated. Column profiles of base case -30 oC, -80 oC, -30 oC-reflus ratio 6, -80 oC reflux ratio 6 and base cas
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Darabi, Mohsen, Hamid Mohammadiun, and Mohammad Mohammadiun. "Advanced exergy analysis of distillation tower and simulation and optimization by hysys." International Journal of Scientific World 3, no. 1 (2015): 163. http://dx.doi.org/10.14419/ijsw.v3i1.4582.

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<p>Exergy rate profiles, exergetic efficiency and irreversibility were used to examine the driving forces in multicomponent distillation system with the view to identifying feasible and efficient operating parameters. The mixture comprised of 5% propane, 15% iso butane, 25% n-butane, 20% iso pentane and 35% n-pentane. Operating variables were feed temperature (-30oC and -80oC), pressure (800KPa and 1200KPa), and reflux-ratio (2 and 6). Sensitivity analysis was carried out to examine the effect of varying operating parameters on the systems. Stage-by-stage system exergy analysis was estim
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Tuan, Truong Thanh, Lemma Dendena Tufa, Mohamed Ibrahim Abdul Mutalib, and Abdelraheem Faisal Mohammed Abdallah. "Control of Depropanizer in Dynamic Hysys Simulation Using MPC in Matlab-Simulink." Procedia Engineering 148 (2016): 1104–11. http://dx.doi.org/10.1016/j.proeng.2016.06.601.

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Larsson, Christian A., Cristian R. Rojas, Xavier Bombois, and Håkan Hjalmarsson. "Experimental evaluation of model predictive control with excitation (MPC-X) on an industrial depropanizer." Journal of Process Control 31 (July 2015): 1–16. http://dx.doi.org/10.1016/j.jprocont.2015.03.011.

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Rincón, Franklin, Galo Roux, and Fernando Lima. "A Novel ARX-Based Approach for the Steady-State Identification Analysis of Industrial Depropanizer Column Datasets." Processes 3, no. 2 (2015): 257–85. http://dx.doi.org/10.3390/pr3020257.

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Dissertations / Theses on the topic "Depropanizer"

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Porfirio, Carlos Roberto. "Implantação de um controlador multimodelos em uma coluna depropanizadora industrial." Universidade de São Paulo, 2001. http://www.teses.usp.br/teses/disponiveis/3/3137/tde-14122001-123029/.

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As colunas depropanizadoras existentes nas refinarias de petróleo têm como função a separação entre as correntes de propano e butano. O objetivo de controle nestas colunas é a especificação de um teor máximo de iso-butano e mais pesados (C4 +) na corrente de propano e do teor máximo de propano e mais leves (C3 -) na corrente de butano. Controladores multivariáveis tradicionais, que normalmente são implementados nas colunas depropanizadoras, apresentam grande dificuldade para manter os produtos dentro de suas especificações, isto se deve ao fato de que este processo apresenta um comportamento b
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Facchin, Samuel. "Técnicas de análise multivariável aplicadas ao desenvolvimento de analisadores virtuais." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2005. http://hdl.handle.net/10183/8294.

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A construção de um analisador virtual é sustentada basicamente por três pilares: o modelo, as variáveis que integram o modelo e a estratégia de correção/atualização do modelo. Os modelos matemáticos são classificados quanto ao nível de conhecimento do processo contido nele, indo de modelos complexos baseados em relações fundamentais e leis físico-químicas, denominados white-box, até modelos obtidos através de técnicas de análise multivariável, como técnicas de regressão multiváriavel e redes neurais, referenciados como black box. O presente trabalho objetiva uma análise de dois dos pilares: os
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Book chapters on the topic "Depropanizer"

1

Carling, G. A., and R. K. Wood. "THE DYNAMICS AND CONTROL OF A DEPROPANIZER." In Dynamics and Control of Chemical Reactors and Distillation Columns. Elsevier, 1988. http://dx.doi.org/10.1016/b978-0-08-034917-6.50030-1.

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Mojto, Martin, Karol L’ubušký, Miroslav Fikar, and Radoslav Paulen. "Advanced Process Control of an Industrial Depropanizer Column using Data-based Inferential Sensors." In Computer Aided Chemical Engineering. Elsevier, 2020. http://dx.doi.org/10.1016/b978-0-12-823377-1.50203-2.

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Conference papers on the topic "Depropanizer"

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Jiang Aipeng, Jiang Zhoushu, Wang Jian, Ding Qiang, and Huang Guohui. "Modeling, simulation and optimization of depropanizer based on rigorous mechanism modeling." In 2008 Chinese Control Conference (CCC). IEEE, 2008. http://dx.doi.org/10.1109/chicc.2008.4604952.

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Listijorini, Erny, Nanda Dian Pratama, Moudy A. Vianda, and Totok R. Biyanto. "Optimization of depropanizer column quality product by changing controller set points of reflux flow and reboiler heat rate." In 2016 6th International Annual Engineering Seminar (InAES). IEEE, 2016. http://dx.doi.org/10.1109/inaes.2016.7821918.

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