An agent-based simulation with NetLogo platform to evaluate forward osmosis process (PRO Mode)

doi:10.1016/j.cjche.2018.01.032

Abstract

Abstract: Forward osmosis (FO), as an emerging technology, is influenced by different factors such as operating conditions, module characteristics, and membrane properties. The general aim of this study was to develop a suitable (flexible, comprehensive, and convenient to use) computational tool which is able to simulate osmosis through an asymmetric membrane oriented in pressure retarded osmosis (PRO) mode in a wide variety of scenarios. For this purpose, an agent-based model was created in NetLogo platform, which is an easy-to-use application environment with graphical visualization abilities and well suited for modeling a complex system evolving over time. The simulation results were validated with empirical data obtained from literature and a great agreement was observed. The effect of various parameters on process performance was investigated in terms of temperature, cross-flow velocity, length of the module, pure water permeability coefficient, and structural parameter of the membrane. Results demonstrated that the increase in all parameters, except structural parameter of the membrane and the length of module led to the increase of average water flux. Moreover, nine different draw solutes were selected in order to assess the influence of net bulk osmotic pressure difference between the draw solution (DS) and feed solution (FS) (known as the driving force of FO process) on water flux. Based on the findings of this paper, the performance of FO process (PRO mode) can be efficiently evaluated using the NetLogo platform.

Key words: Agent-based model, Forward osmosis (PRO mode), Membranes, NetLogo platform, Simulation, Water flux

摘要： Forward osmosis (FO), as an emerging technology, is influenced by different factors such as operating conditions, module characteristics, and membrane properties. The general aim of this study was to develop a suitable (flexible, comprehensive, and convenient to use) computational tool which is able to simulate osmosis through an asymmetric membrane oriented in pressure retarded osmosis (PRO) mode in a wide variety of scenarios. For this purpose, an agent-based model was created in NetLogo platform, which is an easy-to-use application environment with graphical visualization abilities and well suited for modeling a complex system evolving over time. The simulation results were validated with empirical data obtained from literature and a great agreement was observed. The effect of various parameters on process performance was investigated in terms of temperature, cross-flow velocity, length of the module, pure water permeability coefficient, and structural parameter of the membrane. Results demonstrated that the increase in all parameters, except structural parameter of the membrane and the length of module led to the increase of average water flux. Moreover, nine different draw solutes were selected in order to assess the influence of net bulk osmotic pressure difference between the draw solution (DS) and feed solution (FS) (known as the driving force of FO process) on water flux. Based on the findings of this paper, the performance of FO process (PRO mode) can be efficiently evaluated using the NetLogo platform.

关键词: Agent-based model, Forward osmosis (PRO mode), Membranes, NetLogo platform, Simulation, Water flux

Mostafa Taherian, Seyed Mahmoud Mousavi, Hooman Chamani. An agent-based simulation with NetLogo platform to evaluate forward osmosis process (PRO Mode)[J]. Chin.J.Chem.Eng., 2018, 26(12): 2487-2494.

Mostafa Taherian, Seyed Mahmoud Mousavi, Hooman Chamani. An agent-based simulation with NetLogo platform to evaluate forward osmosis process (PRO Mode)[J]. Chinese Journal of Chemical Engineering, 2018, 26(12): 2487-2494.

References

[1] N. Wagner, V. Agrawal, An agent-based simulation system for concert venue crowd evacuation modeling in the presence of a fire disaster, Expert Syst. Appl. 41(2014) 2807-2815.

[2] Y. Gao, Z. Shang, A. Kokossis, Agent-based intelligent system development for decision support in chemical process industry, Expert Syst. Appl. 36(2009) 11099-11107.

[3] C.M. Macal, M.J. North, Tutorial on agent-based modelling and simulation, J. Simul. 4(2010) 151-162.

[4] H. Cheng, X. Li, Y. Qian, Integrated modelling of process operation systems using the agent-oriented approach, Can. J. Chem. Eng. 83(2005) 291-299.

[5] K.H. van Dam, A. Adhitya, R. Srinivasan, Z. Lukszo, Benchmarking numerical and agent-based models of an oil refinery supply chain, Comput. Aided Chem. Eng. 25(2008) 623-628.

[6] R. Paton, R. Gregory, C. Vlachos, J. Saunders, H. Wu, Evolvable social agents for bacterial systems modeling, IEEE Trans. Nanobiosci. 3(2004) 208-216.

[7] Y. Mansury, T.S. Deisboeck, Simulating the time series of a selected gene expression profile in an agent-based tumor model, Phys. D 196(2004) 193-204.

[8] Y. Wang, H. Yu, R. Xie, K. Zhao, X. Ju, W. Wang, Z. Liu, L. Chu, An easily recoverable thermo-sensitive polyelectrolyte as draw agent for forward osmosis process, Chin. J. Chem. Eng. 24(2016) 86-93.

[9] T.-S. Chung, L. Luo, C.F. Wan, Y. Cui, G. Amy, What is next for forward osmosis (FO) and pressure retarded osmosis (PRO), Sep. Purif. Technol. 156(2015) 856-860.

[10] A. Altaee, A. Sharif, Pressure retarded osmosis:Advancement in the process applications for power generation and desalination, Desalination 356(2015) 31-46.

[11] Q. Yang, K.Y. Wang, T.-S. Chung, A novel dual-layer forward osmosis membrane for protein enrichment and concentration, Sep. Purif. Technol. 69(2009) 269-274.

[12] E.M. Garcia-Castello, J.R. McCutcheon, Dewatering press liquor derived from orange production by forward osmosis, J. Membr. Sci. 372(2011) 97-101.

[13] J.R. McCutcheon, R.L. McGinnis, M. Elimelech, Desalination by ammonia-carbon dioxide forward osmosis:Influence of draw and feed solution concentrations on process performance, J. Membr. Sci. 278(2006) 114-123.

[14] S. Jamil, S. Jeong, S. Vigneswaran, Application of pressure assisted forward osmosis for water purification and reuse of reverse osmosis concentrate from a water reclamation plant, Sep. Purif. Technol. 171(2016) 182-190.

[15] D. Zhao, S. Chen, C.X. Guo, Q. Zhao, X. Lu, Multi-functional forward osmosis draw solutes for seawater desalination, Chin. J. Chem. Eng. 24(2016) 23-30.

[16] N.-D. Mermier, C. Borges, Direct osmosis process for power generation using salinity gradient:FO/PRO pilot plant investigation using hollow fiber modules, Chem. Eng. Process. Process Intensif. 103(2016) 27-36.

[17] K.K. Sirkar, A.G. Fane, R. Wang, S.R. Wickramasinghe, Process intensification with selected membrane processes, Chem. Eng. Process. Process Intensif. 87(2015) 16-25.

[18] S. Zhao, L. Zou, C.Y. Tang, D. Mulcahy, Recent developments in forward osmosis:Opportunities and challenges, J. Membr. Sci. 396(2012) 1-21.

[19] K. Lutchmiah, A. Verliefde, K. Roest, L.C. Rietveld, E.R. Cornelissen, Forward osmosis for application in wastewater treatment:A review, Water Res. 58(2014) 179-197.

[20] T.Y. Cath, A.E. Childress, M. Elimelech, Forward osmosis:Principles, applications, and recent developments, J. Membr. Sci. 281(2006) 70-87.

[21] D.H. Jung, J. Lee, Y.G. Lee, M. Park, S. Lee, D.R. Yang, J.H. Kim, Simulation of forward osmosis membrane process:Effect of membrane orientation and flow direction of feed and draw solutions, Desalination 277(2011) 83-91.

[22] S. Phuntsho, S. Vigneswaran, J. Kandasamy, S. Hong, S. Lee, H.K. Shon, Influence of temperature and temperature difference in the performance of forward osmosis desalination process, J. Membr. Sci. 415(2012) 734-744.

[23] S. Phuntsho, S. Hong, M. Elimelech, H.K. Shon, Osmotic equilibrium in the forward osmosis process:Modelling, experiments and implications for process performance, J. Membr. Sci. 453(2014) 240-252.

[24] S. Zhao, L. Zou, D. Mulcahy, Effects of membrane orientation on process performance in forward osmosis applications, J. Membr. Sci. 382(2011) 308-315.

[25] C.Y. Tang, Q. She, W.C. Lay, R. Wang, A.G. Fane, Coupled effects of internal concentration polarization and fouling on flux behavior of forward osmosis membranes during humic acid filtration, J. Membr. Sci. 354(2010) 123-133.

[26] W. Li, Y. Gao, C.Y. Tang, Network modeling for studying the effect of support structure on internal concentration polarization during forward osmosis:model development and theoretical analysis with FEM, J. Membr. Sci. 379(2011) 307-321.

[27] S. Zhao, L. Zou, Relating solution physicochemical properties to internal concentration polarization in forward osmosis, J. Membr. Sci. 379(2011) 459-467.

[28] M. Taherian, S.M. Mousavi, Modeling and simulation of forward osmosis process using agent-based model system, Comput. Chem. Eng. 100(2017) 104-118.

[29] G.T. Gray, J.R. McCutcheon, M. Elimelech, Internal concentration polarization in forward osmosis:Role of membrane orientation, Desalination 197(2006) 1-8.

[30] S.F. Railsback, S.L. Lytinen, S.K. Jackson, Agent-based simulation platforms:Review and development recommendations, Simulation 82(2006) 609-623.

[31] A. Achilli, T.Y. Cath, A.E. Childress, Power generation with pressure retarded osmosis:An experimental and theoretical investigation, J. Membr. Sci. 343(2009) 42-52.

[32] B. Chanukya, S. Patil, N.K. Rastogi, Influence of concentration polarization on flux behavior in forward osmosis during desalination using ammonium bicarbonate, Desalination 312(2013) 39-44.

[33] J.R. McCutcheon, M. Elimelech, Influence of concentrative and dilutive internal concentration polarization on flux behavior in forward osmosis, J. Membr. Sci. 284(2006) 237-247.

[34] A. Sagiv, A. Zhu, P.D. Christofides, Y. Cohen, R. Semiat, Analysis of forward osmosis desalination via two-dimensional FEM model, J. Membr. Sci. 464(2014) 161-172.

[35] V.t. Geraldes, V. Semiao, M.N. de Pinho, Flow and mass transfer modelling of nanofiltration, J. Membr. Sci. 191(2001) 109-128.

[36] M. Laliberte, Model for calculating the viscosity of aqueous solutions, J. Chem. Eng. Data 52(2007) 321-335.

[37] A.V. Bui, M. Nguyen, Prediction of viscosity of glucose and calcium chloride solutions, J. Food Eng. 62(2004) 345-349.

[38] OLI Stream Analyzer 3.2, OLI Systems Inc. Morris Plains, NJ, US, 2011, http://www.olisystems.com/.

[39] M. Castaldi, G. D'Errico, L. Paduano, V. Vitagliano, Transport properties of the binary system glucose-water at 25℃. A velocity correlation study, J. Chem. Eng. Data 43(1998) 653-657.

[40] J.A. Rard, D.G. Miller, The mutual diffusion coefficients of Na₂SO₄-H₂O and MgSO₄-H₂O at 25℃ from Rayleigh interferometry, J. Solut. Chem. 8(1979) 755-766.

[41] D.G. Miller, J.A. Rard, L.B. Eppstein, J.G. Albright, Mutual diffusion coefficients and ionic transport coefficients lij of magnesium chloride-water at 25℃, J. Phys. Chem. 88(1984) 5739-5748.

[42] J.A. Rard, D.G. Miller, The mutual diffusion coefficients of NaCl-H₂O and CaCl₂-H₂O at 25℃ from Rayleigh interferometry, J. Solut. Chem. 8(1979) 701-716.

[43] U. Wilensky, Netlogo (And Netlogo User Manual), Center for Connected Learning and Computer-Based Modeling, Northwestern University, 1999, http://ccl.northwestern.edu/netlogo/.

[44] M. Barbati, G. Bruno, A. Genovese, Applications of agent-based models for optimization problems:A literature review, Expert Syst. Appl. 39(2012) 6020-6028.

[45] S. Benavides, A.S. Oloriz, W.A. Phillip, Forward osmosis processes in the limit of osmotic equilibrium, Ind. Eng. Chem. Res. 54(2014) 480-490.

[46] N.T. Hancock, T.Y. Cath, Solute coupled diffusion in osmotically driven membrane processes, Environ. Sci. Technol. 43(2009) 6769-6775.

[47] C. Suh, S. Lee, Modeling reverse draw solute flux in forward osmosis with external concentration polarization in both sides of the draw and feed solution, J. Membr. Sci. 427(2013) 365-374.

[48] S.-M. Shim, W.-S. Kim, A numerical study on the performance prediction of forward osmosis process, J. Mech. Sci. Technol. 27(2013) 1179-1189.

[49] M. Ghanbari, D. Emadzadeh, W. Lau, H. Riazi, D. Almasi, A. Ismail, Minimizing structural parameter of thin film composite forward osmosis membranes using polysulfone/halloysite nanotubes as membrane substrates, Desalination 377(2016) 152-162.