ORIGINAL_ARTICLE
Table of Content
https://ijogst.put.ac.ir/article_47796_4ba356a6fbf34017a71caf08ab495655.pdf
2016-01-01
ORIGINAL_ARTICLE
Application of Modified LECA in Removing Nickel from Wastewater
In the present study, lightweight expanded clay aggregate (LECA) coated with iron oxide was investigated as a low cost sorbent to remove from wastewater. Iron oxide coated LECA (IOCL) as a new sorbent was tested for its efficiency as sorbent using operational parameters such as contact time, the initial pH of the solutions, and sorbent dosage concentration in batch systems. The adsorption characteristics of the natural LECA and IOCL were investigated through scanning electron microscopy (SEM), X-ray fluorescence spectroscopy (XRF), and X-ray diffraction (XRD) analysis. The maximum sorption efficiency was found to be 96% for IOCL at an initial pH of 6.0 and a sorbent dosage of 5 . The results revealed that the sorption kinetic data were well fitted to a pseudo second–order kinetic model. The experimental data showed that sorption was considerably high on IOCL and the new sorbent is an economical method for Ni (II) removal from effluents and aqueous media.
https://ijogst.put.ac.ir/article_13825_15a94057a7f9827a549b472ea0217c6d.pdf
2016-01-01
1
12
10.22050/ijogst.2016.13825
Nickel Adsorption
Water Treatment
LECA
Abdossamad
Rastegar
samadrastegar69@gmail.com
1
1Department of Petroleum Engineering, Petroleum University of Technology, Abadan, Iran
AUTHOR
Bagher
Anvaripour
anvaripour@put.ac.ir
2
Department of Petroleum Engineering, Petroleum University of Technology, Abadan, Iran
LEAD_AUTHOR
Nematollah
Jaafarzadeh
3
School of Health, Ahvaz Jundishapur University of Medical Sciences, Ahwaz, Iran
AUTHOR
Ashouri, A., Anvaripour, B., Motavassel, M., and Jaafarzadeh, N., Arsenate Removal from Water by Simultaneous Green Tea Nano Zero Valent Iron and Ultrasonic Wave, ISRN Chemical Engineering, Article ID 457868, 9 pages, 2014.
1
Amiri, H., Jaafarzadeh, N., Ahmadi, M., and Martínez, S. S., Application of LECA Modified with Fenton in Arsenite and Arsenate Removal as an Adsorbent, Desalination, Vol. 272, No. 1, p. 212-217, 2011.
2
Babel, S. and Kurniawan, T. A., Low-cost Adsorbents for Heavy Metals Uptake from Contaminated Water: a Review, Journal of Hazardous Materials, Vol. 97, No. 1, p. 219-243, 2003.
3
Behnood, R., Anvaripour, B., Jaafarzadeh, N., and Farasati, M., Application of Natural Sorbents in Crude Oil Adsorption, Iranian Journal of Oil & Gas Science and Technology, Vol. 2, No. 4, p. 01-11, 2013.
4
Cempel, M. and Nikel, G., A Review of its Sources and Environmental Toxicology, Polish Journal of Environmental Studies, Vol. 15, No. 3, p. 375-382, 2006.
5
Crini, G., Non-conventional Low-cost Adsorbents for Dye Removal: A Review, Bioresource Technology, Vol. 97, p. 1061-1085, 2006.
6
Edwards, M. and Benjamin, M. M., Adsorptive Filtration Using Coated Sand: a New Approach for Treatment of Metal-bearing Wastes, Research Journal of the Water Pollution Control Federation, Vol. 61, No. 9/10, p. 1523-1533, 1989.
7
Haque, N., Morrison, G., Cano-Aguilera, I., and Gardea-Torresdey, J. L., Iron-modified Light Expanded Clay Aggregates for the Removal of Arsenic (V) from Groundwater, Microchemical Journal, Vol. 88, No. 1, p. 7-13, 2008.
8
Hasar, H., Adsorption of Nickel (II) from Aqueous Solution onto Activated Carbon Prepared from Almond Husk, Journal of Hazardous Materials, Vol. 97, No. 1, p. 49-57, 2003.
9
Ho, Y. S. and McKay, G., Pseudo-second Order Model for Sorption Processes, Process Biochemistry, Vol. 34, No. 5, p. 451-465, 1999.
10
Jamei, M. R., Khosravi, M. R., and Anvaripour, B., Degradation of Oil from Soil Using Nano Zero Valent Iron, Science International (Lahore), Vol. 25, No. 4, p. 863-867, 2013.
11
Kadirvelu, K., Thamaraiselvi, K., and Namasivayam, C., Removal of Heavy Metals from Industrial Wastewaters by Adsorption onto Activated Carbon Prepared from an Agricultural Solid Waste, Bioresource Technology, Vol. 76, No. 1, p. 63-65, 2001.
12
Kalhori, E. M., Yetilmezsoy, K., Uygur, N., Zarrabi, M., and Shmeis, R. M. A., Modeling of Adsorption of Toxic Chromium on Natural and Surface Modified Lightweight Expanded Clay Aggregate (LECA), Applied Surface Science, Vol. 287, p. 428-442, 2013.
13
Kinhikar, V. R., Removal of Nickel (II) from Aqueous Solutions by Adsorption with Granular Activated Carbon (GAC), Research Journal of Chemical Sciences, Vol. 2, No.6, p. 6-11, 2012.
14
Krishna, R. H. and Swamy, A. V. V. S., Studies on the Removal of Ni (II) from Aqueous Solutions Using Powder of Mosambi Fruit Peelings as a Low Cost Sorbent, Chem. Sci. J. , Vol. 31, p. 1-13, 2011.
15
Largergren, S., Zur Theorie der Sogenannten Adsorption Geloster Stoffe. Kungliga Svenska Vetenskapsakademiens, Handlingar, Vol. 24 , p. 1-39, 1898.
16
Malakootian, M., Nouri, J., and Hossaini, H., Removal of Heavy Metals from Paint Industry’s Wastewater Using LECA as an Available Adsorbent, International Journal of Environmental Science & Technology, Vol. 6, No. 2, p. 183-190, 2009.
17
Nkansah, M. A., Christy, A. A., Barth, T., and Francis, G. W., The Use of Lightweight Expanded Clay Aggregate (LECA) as Sorbent for PAHs Removal from Water, Journal of Hazardous Materials, Vol. 217, p. 360-365, 2012.
18
Rađenović, A., Malina, J., and Štrkalj, A., Removal of Ni (II) from Aqueous Solution by Low-cost Adsorbents, The Holistic Approach to Environment, Vol. 1, No. 3, p. 109-120, 2011.
19
Rani, F., Amala, S., Vimala, J. R., and Bhuvana, T., Studies on the Removal of Nickel (II) Using Chemically Activated Pouteria Sapota Seed and Commercially Available Carbon, Der Chemica Sinica, Vol. 3, No. 3, p. 613-620, 2012.
20
Poornaseri, M., Anvaripour, B., Motavassel, M., and Jadidi, N., Removal of Trace Cadmium from Wastewater Using Batch Foam Fractionation, Science International (Lahore), Vol. 25, p. 901-904, 2013.
21
Popuri, S. R., Vijaya, Y., Boddu, V. M., and Abburi, K., Adsorptive Removal of Copper and Nickel Ions from Water Using Chitosan Coated PVC Beads, Bioresource Technology Vol. 100, No. 1, p. 194-199, 2009.
22
Seyedi, S. M., Anvaripour, B., Motavassel, M., and Jadidi, N., Comparative Cadmium Adsorption from Water by Nanochitosan and Chitosan, International Journal of Engineering and Innovative Technology, Vol. 2, No. 9, p. 145-148, 2013.
23
Shojaeimehr, T., Rahimpour, F., Khadivi, M. A., and Sadeghi, M., A Modeling Study by Response Surface Methodology (RSM) and Artificial Neural Network (ANN) on Cu(II) Adsorption Optimization Using Light Expended Clay Aggregate (LECA), Journal of Industrial and Engineering Chemistry, Vol. 20, No. 3, p. 870-880, 2013.
24
Varma, S., Sarode, D., Wakale, S., Bhanvase, B., and Deosarkar, M., Removal of Nickel from Waste Water Using Graphene Nanocomposite, International Journal of Chemical and Physical Sciences, Vol. 2, p. 132-139, 2013.
25
Yaghi, N. Z., Iron Oxide-based Materials for the Removal of Copper from Drinking Water: a Study of Freundlich Adsorption Isotherms, Site Energy Distributions and Energy Frequency Distributions, M. Sc. Thesis, Chalmers University of Technology, p. 24-25,2007.
26
Yaghi, N. and Hartikainen, H., Enhancement of Arsenite Sorption onto Oxide Coated Light Expanding Clay Aggregate by Means of Manganese Oxide, APCBEE Procedia, Vol. 5, p.76-81, 2013.
27
ORIGINAL_ARTICLE
Simulation and Assessment of Surfactant Injection in Fractured Reservoirs: A Sensitivity Analysis of some Uncertain Parameters
Fracture reservoirs contain most of the oil reserves of the Middle East. Such reservoirs are poorly understood and recovery from fractured reservoirs is typically lower than those from conventional reservoirs. Many efforts have been made to enhance the recovery and production potential of these reservoirs. Fractured reservoirs with high matrix porosity and low matrix permeability need a secondary or EOR technique to achieve the maximum production. One of the effective EOR approaches is surfactant flooding, which reduces interfacial tension and alters wettability. Due to the complexity and uncertainty associated with such reservoirs, implementing a simulation and numerical analysis is primarily necessary to evaluate the effect of key engineering parameters on ultimate reservoir performance. This study assesses and provides a good insight into surfactant injection into fractured reservoirs using ECLIPSE software as a numerical simulator. The influences of fracture-matrix permeability ratio, initial water saturation, and the number of grids on reservoir performance were assessed and a sensitivity analysis was carried out. This study takes surfactant-related phenomena such as adsorption, surface tension reduction, and wettability alteration into account. The simulation results demonstrate that fracture-matrix permeability ratio is an important screening quantity for the selection of surfactant flooding as an EOR agent and that uncertainty in the initial water saturation of matrix has a great influence on the simulation outputs.
https://ijogst.put.ac.ir/article_13826_b730ca1f657bc3eb8fd1112401d4d4d7.pdf
2016-01-01
13
26
10.22050/ijogst.2016.13826
Surfactant
Fracture Reservoir
Simulation
Dual-porosity
Mohammad Hasan
Badizad
badizad@gmail.com
1
M.S. Student, Department of Chemical Engineering, TarbiatModares University, Tehran, Iran
AUTHOR
Ahmad Reza
Zanganeh
ahmadreza.zanganeh@gmail.com
2
M.S. Student, Department of Chemical Engineering, TarbiatModares University, Tehran, Iran
AUTHOR
Amir Hossein
Saeedi Dehaghani
3
Assistant Professor, Department of Chemical Engineering, TarbiatModares University, Tehran, Ira
LEAD_AUTHOR
Adibhatla, B., Mohanty, K., Berger, P., and Lee, C., Effect of Surfactants on Wettability of Near-wellbore Regions of Gas Reservoirs, Journal of Petroleum Science and Engineering, Vol. 52, No. 1, p. 227-236, 2006.
1
Allan, J. and Sun, S. Q., Controls on Recovery Factor in Fractured Reservoirs: Lessons Learned from 100 Fractured Fields, SPE Annual Technical Conference and Exhibition, Society of Petroleum Engineers, 2003.
2
Babadagli, T., Evaluation of EOR Methods for Heavy Oil Recovery in Naturally Fractured Reservoirs, Journal of Petroleum Science and Engineering, Vol. 37, No. 2, p. 25-37, 2003.
3
Barenblatt, G. I., The Mathematical Theory of Equilibrium Cracks in Brittle Fracture, Advances in Applied Mechanics, Vol. 7, p. 104-107, 1962.
4
Delshad, M., Fathi Najafabadi, N., Anderson, G., POPE, G. and Sepehrnoori, K., Modeling Wettability Alteration by Surfactants in Naturally Fractured Reservoirs, SPE Reservoir Evaluation & Engineering, Vol. 12, No. 3, p. 361-370, 2009.
5
Delshad, M., Najafabadi, N. F., Anderson, G. A., Pope, G. A. and Sepehrnoori, K., Modeling Wettability Alteration in Naturally Fractured Reservoirs, SPE/DOE Symposium on Improved Oil Recovery, Society of Petroleum Engineers, Tulsa, Oklahoma, USA, 2006.
6
Delshad, M. and Pope, G. A., Comparison of the Three-phase Oil Relative Permeability Models, Transport in Porous Media, Vol. 4, No. 1, p. 59-83, 1989.
7
Emegwalu, C. C., Enhanced Oil Recovery for Norne Field's E-segment Using Surfactant Flooding, Norwegian University of Science and Technology, Norway, 2010.
8
Farhadinia, M. A. and Delshad, M., Modeling and Assessment of Wettability Alteration Processes in Fractured Carbonates Using Dual Porosity and Discrete Fracture Approaches, SPE Improved Oil Recovery Symposium, Tulsa, Oklahoma, USA, 2010.
9
Fathi Najafabadi, N., Modeling Chemical EOR Processes Using IMPEC and Fully IMPLICIT Reservoir Simulators, Ph.D. Thesis, The University of Texas at Austin, USA, 2009.
10
Goudarzi, A., Modeling Wettability Alteration in Naturally Fractured Carbonate Reservoirs, Ph.D. Thesis, the University of Texas at Austin, USA, 2011.
11
Kathel, P. and Mohanty, K. K. EOR in Tight Oil Reservoirs through Wettability Alteration, SPE Annual Technical Conference and Exhibition, Society of Petroleum Engineers, New Orleans, Louisiana, USA, 2013.
12
Kazemi, H. and Merrill, L., Numerical Simulation of Water Imbibition in Fractured Cores, Journal of Society of Petroleum Engineers , Vol. 16, No. 2, p.175-182, 1979.
13
Nasr-el-din, H. A., Investigation of Wettability Alteration and Oil Recovery Improvement by Low Salinity Water in Sandstone Rock, Journal of Canadian Petroleum Technology, Vol. 52, No. 2, p. 144-154, 2013.
14
Rao, D. and Girard, M., A New Technique for Reservoir Wettability Characterization, Journal of Canadian Petroleum Technology, Vol. 35, No. 2, p. 31-39, 1996.
15
Saidi, A., Simulation of Naturally Fractured Reservoirs, SPE Symposium on Reservoir Simulation, San Francisco, USA, 16-18 November, 1983.
16
Schmid, K. S., Mathematical Analysis, Scaling and Simulation of Flow and Transport during Immiscible Two-phase Flow, Ph.D. Thesis, Heriot-Watt University, Scotlan, 2012.
17
Shah, D. O., Improved Oil Recovery By Surfactant and Polymer Flooding: p. 32, Elsevier, 2012.
18
Uleberg, K. and Kleppe, J., Dual Porosity, Dual Permeability Formulation for Fractured Reservoir Simulation, Norwegian University of Science and Technology, Trondheim RUTH Seminar, Stavanger, 1996.
19
Warren, J. and Root, P. J., The Behavior of Naturally Fractured Reservoirs, Journal of Society of Petroleum Engineers, Vol. 3, No. 3, p. 245-253, 1963.
20
ORIGINAL_ARTICLE
A Novel Integrated Approach to Oil Production Optimization and Limiting the Water Cut Using Intelligent Well Concept: Using Case Studies
Intelligent well technology has provided facility for real time production control through use of subsurface instrumentation. Early detection of water production allows for a prompt remedial action. Effective water control requires the appropriate performance of individual devices in wells on maintaining the equilibrium between water and oil production over the entire field life. However, there is still an incomplete understanding of using intelligent well concept to control unwanted fluids and the way this leads to improving hydrocarbon recovery. The present study proposes using intelligent well technology to develop a new integrated methodology for selecting/ranking the candidate wells/fields, interval control valve (ICV) size determination, and ICV setting optimization. Various technical and economical parameters weighted by expert opinions are used for candidate well/field ranking to implement the intelligent technology. A workflow is proposed for ICV size determination based on its effect on a predefined objective function. Inappropriate ICV size selection leads to suboptimum production scenarios. Furthermore, this study proposes an efficient ICV setting optimization in an intelligent well. The objective function can maximize cumulative oil, minimize water production, or conduct both. It was shown that for selecting the optimized cases, the balance between water and oil production under predefined criteria should be practiced. Real case studies were considered to demonstrate the effectiveness and robustness of the proposed methodology. A considerable improvement in the objective function was achieved using the developed methodology.
https://ijogst.put.ac.ir/article_13827_19ef5e942c12de5727e01e1876290c92.pdf
2016-01-01
27
41
10.22050/ijogst.2016.13827
Intelligent Well
Screening
optimization
ICV Sizing
ICV Setting
Turaj
Behrouz
tbbehrouz@gmail.com
1
Research Institute of Petroleum Industry (RIPI), Tehran, Iran
LEAD_AUTHOR
Mohammad Reza
Rasaei
mrasaei@ut.ac.ir
2
University of Tehran, Institute of Petroleum Engineering (IPE), Tehran, Iran
AUTHOR
Rahim
Masoudi
masoudi.rahim@gmail.com
3
University of Tehran, Institute of Petroleum Engineering (IPE), Tehran, Iran
AUTHOR
Aitokhuehi, I, Real Time Optimization of Smart Wells, Master of Science Dissertation, Stanford University, 2004.
1
Al-Ghareeb, M., Monitoring and Control of Smart Wells, Master of Science Dissertation, Stanford University, 2009.
2
Alhuthali, A. H., Datta-Gupta, A., Bevan, Y., and Fontanilla, J. P., Field Applications of Waterflood Optimization via Optimal Rate Control with Smart Wells, Woodland, Texas, 2009.
3
Arenas, E. and Dolle, N. Smart Waterflooding Tight Fractured Reservoirs Using Inflow Control Valves, Denver, Colorado, 2003.
4
Behrouz, T., Motahhari, M., Nadripari, M. and Hendi, S., Presenting a Method for Determining Coefficient of Geological, Environmental and Economic Factors to Implement Intelligent Well Technology, Iranian Journal of Petroleum Geology, Vol. 3 , No. 3, p. 77-99, 2013.
5
Brouwer, D. R., Jansen, J. D., Van Der Starre, S., Van Kruijsdijk, C. P. J. W., and Berentsen, C. W. J., Recovery Increase through Water Flooding with Smart Well Technology, The Hague, The Netherlands, 2001.
6
Glandt, A. C., Reservoir Aspect of Smart Wells, Paper Presented at the SPE Latin American and Caribbean Petroleum Engineering Conference held in Port-of-Spain, Trinidad, West Indies, 27-30 April 2003.
7
Going, W. S., Thigpen, P. M., and Anderson, A. B., Intelligent-well Technology: Are We Ready for Closed Loop Control, Paper Presented at SPE Intelligent Energy Conference and Exhibition held in Amsterdam, The Netherlands, 11-13 April 2006.
8
Holmes, J. A., Barkve, T., and Lund, Ø., Application of a Multi-segment Well Model to Simulate Flow in Advanced Wells, Paper SPE 50646 Presented at the SPE European Petroleum Conference, The Hague, Netherlands, 20-22 October, 1998.
9
Ibrahim, H., Smart Wells Experiences and Best Practices at Haradh-III, Ghawar Field, Paper SPE 105618 Presented at the 15th SPE Middle East Oil & Gas Show, Bahrain International Exhibition Centre, Bahrain, 11-14 March, 2007.
10
Leo de Best, Frans van den Berg. Smart fields-Making the Most of Our Assets, Paper Presented at the SPE Russian Oil and Gas Technical Conference and Exhibition held in Moscow, Russia, 3-6 October, 2006.
11
Mochizuki, M., Saputelli, S., L. A., Kabir, C. S., Cramer, R., Lochmann, M.J., Topsail Ventures, Reese, R. D., Harms, L. K., Sisk, C. D., Hite, J. R., Real Time Optimization: Classification and Assessment, Paper Presented at Annual Technical Conference and Exhibition held in Houston, Texas, U.S.A., 26-29 September, 2004.
12
Mubarak, M., Real Time Reservoir Management from Data Acquisition through Implementation: Close-loop Approach, Amsterdam, The Netherlands, 2008.
13
Salamy, S. P., Maximum Reservoir Contact (MRC) Wells: A New Generation of Wells for Developing Tight Reservoir Facies, In: SPE Distinguish Lecturer Series, URL http://dx.doi.org/10.2118/108806-DL, 2005.
14
Vasily, M., Analytical Modeling of Wells with inflow Control Devices, Ph.D. Dissertation , Heriot- Watt University, 2010.
15
Yeten, B., Durlofsky, L. J., and Aziz, K., Optimization of Smart Well Control, Paper SPE 79031 Presented at the SPE International Thermal Operations and Heavy Oil Symposium and International Horizontal Well Technology Conference, Calgary, Canada, 4-7 November, 2002.
16
Yeten, B., Durlofsky, L. J., and Aziz, K., Optimization of Nonconventional Well Type, Location and Trajectory, SPE Journal, Vo. 8, No. 3, p. 200-210, 2003.
17
ORIGINAL_ARTICLE
Modeling and Simulation of Claus Unit Reaction Furnace
Reaction furnace is the most important part of the Claus sulfur recovery unit and its performance has a significant impact on the process efficiency. Too many reactions happen in the furnace and their kinetics and mechanisms are not completely understood; therefore, modeling reaction furnace is difficult and several works have been carried out on in this regard so far. Equilibrium models are commonly used to simulate the furnace, but the related literature states that the outlet of furnace is not in equilibrium and the furnace reactions are controlled by kinetic laws; therefore, in this study, the reaction furnace is simulated by a kinetic model. The predicted outlet temperature and concentrations by this model are compared with experimental data published in the literature and the data obtained by PROMAX V2.0 simulator. The results show that the accuracy of the proposed kinetic model and PROMAX simulator is almost similar, but the kinetic model used in this paper has two importance abilities. Firstly, it is a distributed model and can be used to obtain the temperature and concentration profiles along the furnace. Secondly, it is a dynamic model and can be used for analyzing the transient behavior and designing the control system.
https://ijogst.put.ac.ir/article_13828_64442499bdf8525ab4691ab3f633e25a.pdf
2016-01-01
42
52
10.22050/ijogst.2016.13828
Claus Process
Reaction Furnace
Kinetic Modeling
Simulation
Maryam
Pahlavan
maryam.pahlavan@ymail.com
1
Chemical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
AUTHOR
Mohammad Ali
Fanaei
fanaei@um.ac.ir
2
Chemical Engineering Department, Faculty of Engineering, Ferdowsi University of Mashhad, Mashhad, Iran
LEAD_AUTHOR
Al-Lagtah, N. M. A., Al-Habsi, S., and Onaizi, S. A., Optimization and Performance Improvement of Lekhwair Natural Gas Sweetening Plant using Aspen Hysys, Journal of Natural Gas Science and Engineering, Vol. 26, p. 367-381, 2015.
1
Garmroodi Asil, A. and Shahsavand, A., Reliable Estimation of Optimal Sulfinol Concentration in Gas Treatment Unit via Novel Stabilized MLP and Regularization Network, Journal of Natural Gas Science and Engineering, Vol. 21, p. 791-804, 2014.
2
Howboldt, K. A., Kinetic Modeling of Key Reaction in the Modified Claus Plant Front End Furnace, Ph.D. Thesis, Department of Chemical and Petroleum Engineering, University of Calgary, 1998.
3
Jones, D., Steady State and Dynamic Modeling of the Modified Claus Process as Part of an IGCC Power Plant, M.S. Thesis, Department of Chemical Engineering, West Virginia University, 2011.
4
Jones, D., Bhattacharyya, D., Turton, R., and Zitney, S. E., Rigorous Kinetic Modeling and Optimization Study of a Modified Claus Unit for an Integrated Gasification Combined Cycle (IGCC) Power Plant with CO2 Capture, Industrial & Engineering Chemistry Research, Vol. 51, No. 5, p. 2362-2375, 2012.
5
Karan, K. and Behie, L. A., CS2 Formation in the Claus Reaction Furnace: A Kinetic Study of Methane-Sulfur and Methane-Hydrogen Sulfide Reactions, Industrial & Engineering Chemistry Research, Vol. 43, No. 13, p. 3304-3313, 2004.
6
Karan, K., Mehrotra, A. K., and Behie, L. A., COS-Forming Reaction between CO and Sulfur: A High-temperature Intrinsic Kinetics Study, Industrial & Engineering Chemistry Research, Vol. 37, No. 12, p. 4609-4616, 1998.
7
Manenti, G., Papasidero, D., Menenti, F., Bozzano, G., and Pierucci, S., Design of SRU Thermal Reactor and Waste Heat Boiler Considering Recombination Reactions, Procedia Engineering, Vol. 42, p. 376-383, 2012.
8
Monnery, W. D., Hawboldt, K. A., Pollock, A., and Svrcek, W. Y., New Experimental Data and Kinetic Rate Expression for the Claus Reaction, Chemical Engineering Science, Vol. 55, No. 21, p. 5141-5148, 2000.
9
Monnery, W. D., Svrcek, W. Y., and Behie, L. A., Modeling the Modified Claus Process Reaction Furnace and the Implications on Plant Design and Recovery, The Canadian Journal of Chemical Engineering, Vol. 71, No. 5, p. 711-724, 1993.
10
Sames, J. A., Paskall, H. G., Brown, D. M., Chen, M. S. K., and Sulkowski, D., Field Measurements of Hydrogen Production in an Oxygen Enriched Claus Furnace, Proceeding of Sulfur 1990 International Conference, Alberta, Canada, 1990.
11
Santo, S. and Rameshni, M., The Challenges of Designing Grass Root Sulfur Recovery Units with a Wide Range of H2S Concentration from Natural Gas, Journal of Natural Gas Science and Engineering, Vol. 18, p. 137-148, 2014.
12
ORIGINAL_ARTICLE
Design and Practical Implementation of a New Markov Model Predictive Controller for Variable Communication Packet Loss in Network Control Systems
The current paper investigates the influence of packet losses in network control systems (NCS’s) using the model predictive control (MPC) strategy. The study focuses on two main network packet losses due to sensor to controller and controller to actuator along the communication paths. A new Markov-based method is employed to recursively estimate the probability of time delay in controller to actuator path and a generalized predictive control (GPC) method is proposed to compensate the effect of big network time-delay, which leads to packet loss. The proposed methods and algorithms have been evaluated using a practical Smar fieldbus pilot plant to judge the efficiency of the foregoing algorithms. The obtained results clearly demonstrate the superiorities of the proposed control scheme with respect to standard MPC algorithm.
https://ijogst.put.ac.ir/article_13829_0addc6918661a4c1c2e546afa62b66a7.pdf
2016-01-01
53
64
10.22050/ijogst.2016.13829
Network Control System (NCS)
Model Predictive Control (MPC)
Markov model
Packet Loss
Karim
Salahshoor
salahshoor@put.ac.ir
1
Department of Instrumentation and Industrial Automation, Petroleum University of Technology, Ahwaz, Iran
LEAD_AUTHOR
Babak
Roshanipour
2
Department of Instrumentation and Industrial Automation, Petroleum University of Technology, Ahwaz, Iran
AUTHOR
Iman
Karimi
3
Tehran Petroleum Research Center, Petroleum University of Technology, Tehran, Iran
AUTHOR
Clarke, D. W., Mohtadi, C., and Tuffs, P. S., Generalized Predictive Control: Part I., the Basic Algorithm, Part II: Extensions and Interpretations, Automatica, Vol. 23, p. 137-160, 1987.
1
Fadaei, A. and Salahshoor, K., Design and Implementation of a New Fuzzy PID Controller for Networked Control Systems, ISA Transactions, Vol. 50, p. 351-61, 4, 2008.
2
Jiang, S. and Fang, H. J., Static Output Feedback Control for Nonlinear Networked Control Systems with Time Delays and Packet Dropouts, ISA Transactions, Vol. 52, No. 2, p. 215-222, 2013.
3
Li, H., Sun, Z., Chow, M., and F. Sun, Gain-scheduling-based State Feedback Integral Control for Networked Control Systems, IEEE Transactions on Industrial Electronics, Vol. 58, No. 6, p. 2465-2472, 2011.
4
Lin, C., Wang, Z., and Yang, F., Observer-based Networked Control for Continuous-time Systems with Random Sensor Delays, Automatica, Vol. 45, No. 2, p. 578-584, 2009.
5
Liu, G., Xia, Y., Chen, J., Rees, D., and Hu, W., Networked Predictive Control of Systems with Random Network Delays in both Forward and Feedback Channels, IEEE Transactions on Industrial Electronics, Vol. 54, No. 3, p. 1282-1297, 2007.
6
Liu, G. P., Mu, J. X., Rees, D., and Chai, S. C., Design and Stability Analysis of Networked Control Systems with Random Communication Time Delay Using the Modified MPC, International Journal of Control, Vol. 79, No. 4, p. 288-297, 2006.
7
Ljung, L., System Identification Theory for the User, Prentice Hall, Englewood Cliffs, NJ, 1999.
8
Nilsson, J. and Bernhardsson, B., LQG Control over a Markov Communication Network, Proceedings of the 36th IEEE Conference on Decision and Control, p. 4586-4591, 5 December, 1997.
9
Seiler, P. and Sengupta, R., An 𝐻8 Approach to Networked Control, IEEE Transactions on Automatic Control, Vol. 50, No. 3, p. 356-364, 2005.
10
Sun, Y. and Xu, J., Finite-time Boundedness and Stabilization of Networked Control Systems with Time Delay, Mathematical Problems in Engineering, Vol. 2012, p. 1-12, 2012.
11
Wang, R., Liu, G., Wang, W., Rees, D., and Zhao, Y. B, Guaranteed Cost Control for Networked Control Systems Based on an Improved Predictive Control Method, IEEE Transactions on Control Systems Technology, Vol. 18, No. 5, p. 1226-1232, 2010.
12
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ORIGINAL_ARTICLE
Effects of Surface Treatment on Corrosion Resistance of 304L and 316L Stainless Steel Implants in Hank’s Solution
The enormous demands for metal implant have given rise to a search for cheap material with good bio-tolerability and resistance to corrosion. Although stainless steel has these properties and is widely used for this purpose, its long term application is still a concern. The corrosion resistance of stainless steel depends on the passive layer. Herein, chemical surface treatment, including passivation, electropolishing, and acid cleaning is used for improving the corrosion-resistance property of AISI 316L and 304L. Cyclic polarization, electrochemical impedance spectroscopy, and EDX analysis were used to investigate the properties obtained thereby. Finally, the corrosion resistance of the untreated and modified specimens was compared. The results show that the corrosion behavior of the passivated and electropolished specimens is improved.
https://ijogst.put.ac.ir/article_13830_4be32141809b9242b050eccafc82b3cc.pdf
2016-01-01
65
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10.22050/ijogst.2016.13830
Chemical Passivation
Impedance
corrosion
Electropolishing
Saeid
Ghanavati
1
Department of Petroleum Engineering, Petroleum University of Technology, Abadan, Iran
AUTHOR
Mohammad Reza
Shishesaz
m.r.shishesaz@gmail.com
2
Department of Petroleum Engineering, Petroleum University of Technology, Abadan, Iran
LEAD_AUTHOR
Mansoor
Farzam
dr.farzam93@gmail.com
3
Department of Petroleum Engineering, Petroleum University of Technology, Abadan, Iran
AUTHOR
Iman
Danaee
danaee@dena.kntu.ac.ir
4
Department of Petroleum Engineering, Petroleum University of Technology, Abadan, Iran
AUTHOR
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20
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ORIGINAL_ARTICLE
Persian Abstracts
https://ijogst.put.ac.ir/article_47797_c8965d00e699f7f9689bcab3646cccc0.pdf
2016-01-01
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