Recent Innovations in Chemical Engineering

Author(s): Akash Sood*, Avinash Thakur and Sandeep Mohan Ahuja

DOI: 10.2174/2405520416666221226154953

Statistical Optimization of Carbon Dioxide Capture Performance by Tri-Solvent System of MEA-DEA-PZ from the Stored Gas Reservoir

Page: [26 - 55] Pages: 30

  • * (Excluding Mailing and Handling)

Abstract

Aims/Objective: The current study evaluates the effectiveness of a blended tri-solvent system composed of monoethanolamine (MEA), diethanolamine (DEA), and piperazine (PZ) for removing the carbon dioxide (CO2) from the stored gas reservoir. The developed system is intended to be both environmentally benign and productive.

Methods: The CO2 absorption was carried out for the total solvent (5, 10, and 15% v/v), during the course of three temperature ranges (20, 25, and 30°C) while maintaining the reservoir pressure of 1.5, 2, and 2.5 bar. The fraction of DEA: MEA has been restricted to 0.2, 0.5, and 0.8, with simultaneous loading of anhydrous PZ ranging from 0 to 2 gm. and agitation speed for step intervals of 300, 600, and 900 rpm. For the purpose of investigating the synergetic effects of the process parameters on the rapid absorption of CO2 (ξ) and the initial CO2 absorption rate (ϵ0), Box-Behnken Design (BBD) of response surface methodology (RSM) has been exploited. The design of experiments (DoE) assisted artificial neural network (ANN) and metaheuristic approach of hybridising ANN-whale optimization algorithm (WOA) was also developed and utilised to train and test the developed model. Three optimization models based on RSM, DoE-WOA and ANN-WOA were compared. Under the optimized operating conditions pertaining to DoE, DoE-WOA and DoE-ANN-WOA, (ϵ0 = 3.340, 3.460 3.513 gm./min-250 mL) and (ξ = 17.114, 18.069, 18.145 gm./250 mL) were obtained.

Results: The hybridised DoE-ANN-WOA shows promising results in correlation with the experimental outcomes having error % for ϵ0 & ξ of 0.790 & 1.31.

Conclusion: The DoE-ANN-WOA tends to be selected to predict the optimal absorption conditions as compared to other optimization techniques used in current article.

Graphical Abstract

[1]
Mohammad M, Isaifan RJ, Weldu YW, Rahman MA, Ghamdi SGA. Progress on carbon dioxide capture, storage and utilisation. Int J Glob Warm 2020; 20(2): 124-44.
[http://dx.doi.org/10.1504/IJGW.2020.105386]
[2]
Sood A, Thakur A, Ahuja SM. Recent advancements in ionic liquid based carbon capture technologies. Chem Eng Commun 2021; 1-22.
[http://dx.doi.org/10.1080/00986445.2021.1990886]
[3]
d’Amore F, Bezzo F. Economic optimisation of European supply chains for CO2 capture, transport and sequestration. Int J Greenh Gas Control 2017; 65: 99-116.
[http://dx.doi.org/10.1016/j.ijggc.2017.08.015]
[4]
Dos Santos SP. Comparative Study of Amine Solutions used in CO2 Absorption/Desorption Cycles. Engenharia Quími-ca e Biológica 2013.
[5]
Notz R, Asprion N, Clausen I, Hasse H. Selection and pilot plant tests of new absorbents for post-combustion carbon dioxide capture. Chem Eng Res Des 2007; 85(4): 510-5.
[http://dx.doi.org/10.1205/cherd06085]
[6]
Yu Z, Shi H. Effective energy efficient methods for heat duty reduction for amine-based post-combustion capture pro-cess based on the theoretical reactions energy calculation. Int J Oil Gas Coal Technol 2017; 14(1/2): 172.
[http://dx.doi.org/10.1504/IJOGCT.2017.081097]
[7]
Castillo Castillo A, Angelis-Dimakis A. Analysis and recommendations for European carbon dioxide utilization policies. J Environ Manage 2019; 247(June): 439-48.
[http://dx.doi.org/10.1016/j.jenvman.2019.06.092] [PMID: 31254759]
[8]
Figueroa JD, Fout T, Plasynski S, McIlvried H, Srivastava RD. Advances in CO2 capture technology-The U.S. Depart-ment of Energy’s Carbon Sequestration Program. Int J Greenh Gas Control 2008; 2(1): 9-20.
[http://dx.doi.org/10.1016/S1750-5836(07)00094-1]
[9]
Irlam L. Global costs of carbon capture and storage 2017 update. 2017. Available from: https://policycommons.net/artifacts/1853950/global-costs-of-carbon-capture-and-storage/2601471/
[10]
Abu-Zahra MRM, Schneiders LHJ, Niederer JPM, Feron PHM, Versteeg GF. CO2 capture from power plants. Int J Greenh Gas Control 2007; 1(1): 37-46.
[http://dx.doi.org/10.1016/S1750-5836(06)00007-7]
[11]
Muchan P, Saiwan C, Narku-Tetteh J, Idem R, Supap T, Tontiwachwuthikul P. Screening tests of aqueous alkanolami-ne solutions based on primary, secondary, and tertiary structure for blended aqueous amine solution selection in post combustion CO2 capture. Chem Eng Sci 2017; 170: 574-82.
[http://dx.doi.org/10.1016/j.ces.2017.02.031]
[12]
Nakagaki T, Isogai H, Sato H, Arakawa J. Updated e-NRTL model for high-concentration MEA aqueous solution by regressing thermodynamic experimental data at high temperatures. Int J Greenh Gas Control 2019; 82: 117-26.
[http://dx.doi.org/10.1016/j.ijggc.2018.12.022]
[13]
Flø NE, et al. Assessment of material selection for the CO2 absorption process with aqueous MEA solution based on results from corrosion monitoring at Technology Centre Mongstad. Int J Greenh Gas Control 2019; 84(14): 91-110.
[http://dx.doi.org/10.1016/j.ijggc.2019.02.004]
[14]
Valeh-e-Sheyda P, Rashidi H, Ghaderzadeh F. Integration of commercial CO2 capture plant with primary reformer stack of ammonia plant. J Therm Anal Calorim 2019; 135(3): 1899-909.
[http://dx.doi.org/10.1007/s10973-018-7215-x]
[15]
Khan AA, Halder GN, Saha AK. Comparing CO2 removal characteristics of aqueous solutions of monoethanolamine, 2-amino-2-methyl-1-propanol, methyldiethanolamine and piperazine through absorption process. Int J Greenh Gas Control 2016; 50: 179-89.
[http://dx.doi.org/10.1016/j.ijggc.2016.04.034]
[16]
Khan AA, Halder G, Saha AK. Kinetic effect and absorption performance of piperazine activator into aqueous solu-tions of 2-amino-2-methyl-1-propanol through post-combustion CO2 capture. Korean J Chem Eng 2019; 36(7): 1090-101.
[http://dx.doi.org/10.1007/s11814-019-0296-9]
[17]
Closmann F, Nguyen T, Rochelle GT. MDEA/Piperazine as a solvent for CO2 capture. Energy Procedia 2009; 1(1): 1351-7.
[http://dx.doi.org/10.1016/j.egypro.2009.01.177]
[18]
Choi JH, Kim YE, Nam SC, Yun SH, Yoon YI, Lee JH. CO2 absorption characteristics of a piperazine derivative with primary, secondary, and tertiary amino groups. Korean J Chem Eng 2016; 33(11): 3222-30.
[http://dx.doi.org/10.1007/s11814-016-0180-9]
[19]
He X, Hägg MB. Energy efficient process for CO2 capture from flue gas with novel fixed-site-carrier membranes. Energy Procedia 2014; 63: 174-85.
[http://dx.doi.org/10.1016/j.egypro.2014.11.018]
[20]
Jiang C, Zhang Y, Feng H, Wang Q, Wang Y, Xu T. Simultaneous CO2 capture and amino acid production using bipolar membrane electrodialysis (BMED). J Membr Sci 2017; 542: 264-71.
[http://dx.doi.org/10.1016/j.memsci.2017.08.004]
[21]
Lai Q, Kong L, Gong W, Russell AG, Fan M. Low-energy-consumption and environmentally friendly CO2 capture via blending alcohols into amine solution. Appl Energy 2019; 254: 113696.
[http://dx.doi.org/10.1016/j.apenergy.2019.113696]
[22]
Mumford KA, Wu Y, Smith KH, Stevens GW. Review of solvent based carbon-dioxide capture technologies. Front Chem Sci Eng 2015; 9(2): 125-41.
[http://dx.doi.org/10.1007/s11705-015-1514-6]
[23]
Diab F, Provost E, Laloué N, Alix P, Fürst W. Effect of the incorporation of speciation data in the modeling of CO2–DEA–H2O system. Fluid Phase Equilib 2013; 353: 22-30.
[http://dx.doi.org/10.1016/j.fluid.2013.05.029]
[24]
Zhang Y, Chen CC. Thermodynamic modeling for CO2 absorption in aqueous MDEA solution with electrolyte NRTL model. Ind Eng Chem Res 2011; 50(1): 163-75.
[http://dx.doi.org/10.1021/ie1006855]
[25]
Li H, Li L, Nguyen T, Rochelle GT, Chen J. Characterization of piperazine/2-aminomethylpropanol for carbon dioxide capture. Energy Procedia 2013; 37: 340-52.
[http://dx.doi.org/10.1016/j.egypro.2013.05.120]
[26]
Li H, Moullec YL, Lu J, Chen J, Marcos JCV, Chen G. Solubility and energy analysis for CO2 absorption in piperazine derivatives and their mixtures. Int J Greenh Gas Control 2014; 31: 25-32.
[http://dx.doi.org/10.1016/j.ijggc.2014.09.012]
[27]
Li H, Frailie PT, Rochelle GT, Chen J. Thermodynamic modeling of piperazine/2-aminomethylp-ropanol/CO2/water. Chem Eng Sci 2014; 117: 331-41.
[http://dx.doi.org/10.1016/j.ces.2014.06.026]
[28]
Aaron D, Tsouris C. Separation of CO2 from flue gas: A review. Sep Sci Technol 2005; 40(1-3): 321-48.
[http://dx.doi.org/10.1081/SS-200042244]
[29]
Kohl AL, Nielsen R. Gas purification. 5th ed. Houston, Tenar: Elsevies 1997.
[30]
Gabrielsen J, Michelsen ML, Stenby EH, Kontogeorgis GM. A model for estimating CO2 solubility in aqueous alkanola-mines. Ind Eng Chem Res 2005; 44(9): 3348-54.
[http://dx.doi.org/10.1021/ie048857i]
[31]
Warudkar SS, Cox KR, Wong MS, Hirasaki GJ. Influence of stripper operating parameters on the performance of ami-ne absorption systems for post-combustion carbon capture: Part II. Vacuum strippers. Int J Greenh Gas Control 2013; 16: 351-60.
[http://dx.doi.org/10.1016/j.ijggc.2013.01.049]
[32]
El Hadri N, Quang DV, Goetheer ELVV, Abu Zahra MRMM. Aqueous amine solution characterization for post-combustion CO2 capture process In: Applied Energy. Amsterdan: Elsevier 2017; Vol 185(2): pp. 1433-49.
[http://dx.doi.org/10.1016/j.apenergy.2016.03.043]
[33]
Sakwattanapong R, Aroonwilas A, Veawab A. Reaction rate of CO2 in aqueous MEA-AMP solution: Experiment and modeling. Energy Procedia 2009; 1(1): 217-24.
[http://dx.doi.org/10.1016/j.egypro.2009.01.031]
[34]
Liu Y, Fan W, Wang K, Wang J. Studies of CO2 absorption/regeneration performances of novel aqueous monothanla-mine (MEA)-based solutions. J Clean Prod 2016; 112: 4012-21.
[http://dx.doi.org/10.1016/j.jclepro.2015.08.116]
[35]
Gao H, Wu Z, Liu H, Luo X, Liang Z. Experimental Studies on the Effect of Tertiary Amine Promoters in Aqueous Mo-noethanolamine (MEA) Solutions on the Absorption/Stripping Performances in Post-combustion CO2 Capture. Energy Fuels 2017; 31(12): 13883-91.
[http://dx.doi.org/10.1021/acs.energyfuels.7b02390]
[36]
Edali M, Aboudheir A, Idem R. Kinetics of carbon dioxide absorption into mixed aqueous solutions of MDEA and MEA using a laminar jet apparatus and a numerically solved 2D absorption rate/kinetics model. Int J Greenh Gas Control 2009; 3(5): 550-60.
[http://dx.doi.org/10.1016/j.ijggc.2009.04.006]
[37]
Zhang T, Yu Y, Zhang Z. An interactive chemical enhancement of CO2 capture in the MEA/PZ/AMP/DEA binary solu-tions. Int J Greenh Gas Control 2018; 74(April): 119-29.
[http://dx.doi.org/10.1016/j.ijggc.2018.04.023]
[38]
Du Y, Yuan Y, Rochelle GT. Capacity and absorption rate of tertiary and hindered amines blended with piperazine for CO2 capture. Chem Eng Sci 2016; 155: 397-404. [WE - Science Citation Index Expanded ]. [SCI-EXPANDED].
[http://dx.doi.org/10.1016/j.ces.2016.08.017]
[39]
Sun WC, Yong CB, Li MH. Kinetics of the absorption of carbon dioxide into mixed aqueous solutions of 2-amino-2-methyl-l-propanol and piperazine. Chem Eng Sci 2005; 60(2): 503-16.
[http://dx.doi.org/10.1016/j.ces.2004.08.012]
[40]
Nwaoha C, Saiwan C, Tontiwachwuthikul P, et al. Carbon dioxide (CO2) capture: Absorption-desorption capabilities of 2-amino-2-methyl-1-propanol (AMP), piperazine (PZ) and monoethanolamine (MEA) tri-solvent blends. J Nat Gas Sci Eng 2016; 33: 742-50.
[http://dx.doi.org/10.1016/j.jngse.2016.06.002]
[41]
Nwaoha C, Saiwan C, Supap T, et al. Carbon dioxide (CO2) capture performance of aqueous tri-solvent blends contai-ning 2-amino-2-methyl-1-propanol (AMP) and methyldiethanolamine (MDEA) promoted by diethylenetriamine (DE-TA). Int J Greenh Gas Control 2016; 53: 292-304.
[http://dx.doi.org/10.1016/j.ijggc.2016.08.012]
[42]
Nwaoha C, Tontiwachwuthikul P, Benamor A. A comparative study of novel activated AMP using 1,5-diamino-2-methylpentane vs. MEA solution for CO2 capture from gas-fired power plant. Fuel 2018; 234(July): 1089-98.
[http://dx.doi.org/10.1016/j.fuel.2018.07.147]
[43]
Sahraie S, Rashidi H, Valeh-e-Sheyda P. An optimization framework to investigate the CO2 capture performance by MEA: Experimental and statistical studies using Box-Behnken design. Process Saf Environ Prot 2019; 122: 161-8.
[http://dx.doi.org/10.1016/j.psep.2018.11.026]
[44]
Babamohammadi S, Shamiri A, Nejad Ghaffar Borhani T, Shafeeyan MS, Aroua MK, Yusoff R. Solubility of CO2 in aqueous solutions of glycerol and monoethanolamine. J Mol Liq 2018; 249: 40-52.
[http://dx.doi.org/10.1016/j.molliq.2017.10.151]
[45]
Hsu YH, Leron RB, Li MH. Solubility of carbon dioxide in aqueous mixtures of (reline+monoetha-nolamine) at T=(313.2 to 353.2)K. J Chem Thermodyn 2014; 72: 94-9.
[http://dx.doi.org/10.1016/j.jct.2014.01.011]
[46]
Xu F, Gao H, Dong H, et al. Solubility of CO2 in aqueous mixtures of monoethanolamine and dicyanamide-based ionic liquids. Fluid Phase Equilib 2014; 365: 80-7.
[http://dx.doi.org/10.1016/j.fluid.2013.12.020]
[47]
Hosseini-Ardali SM, Hazrati-Kalbibaki M, Fattahi M, Lezsovits F. Multi-objective optimization of post combustion CO2 capture using methyldiethanolamine (MDEA) and piperazine (PZ) bi-solvent. Energy 2020; 211: 119035.
[http://dx.doi.org/10.1016/j.energy.2020.119035]
[48]
Inayat A, Nassef AM, Rezk H, Sayed ET, Abdelkareem MA, Olabi AG. Fuzzy modeling and parameters optimization for the enhancement of biodiesel production from waste frying oil over montmorillonite clay K-30. Sci Total Environ 2019; 666: 821-7.
[http://dx.doi.org/10.1016/j.scitotenv.2019.02.321] [PMID: 30818206]
[49]
Qin L, Xu T, Li S, et al. Coot Algorithm for Optimal Carbon–Energy Combined Flow of Power Grid With Aluminum Plants. Front Energy Res 2022; 10.
[http://dx.doi.org/10.3389/FENRG.2022.856314/PDF]
[50]
Mirjalili S, Lewis A. The Whale Optimization algorithm. Adv Eng Softw 2016; 95: 51-67.
[http://dx.doi.org/10.1016/j.advengsoft.2016.01.008]
[51]
Vaheddoost B, Guan Y, Mohammadi B. Application of hybrid ANN-whale optimization model in evaluation of the field capacity and the permanent wilting point of the soils. Environ Sci Pollut Res Int 2020; 27(12): 13131-41.
[http://dx.doi.org/10.1007/s11356-020-07868-4] [PMID: 32016876]
[52]
Lee U, Mitsos A, Han C. Optimal retrofit of a CO2 capture pilot plant using superstructure and rate-based models. Int J Greenh Gas Control 2016; 50: 57-69.
[http://dx.doi.org/10.1016/j.ijggc.2016.03.024]
[53]
Abdel-Basset M, Abdel-Fatah L, Sangaiah AK. metaheuristic algorithms: A comprehensive review. Appl 2018; (Jan): 185-231.
[http://dx.doi.org/10.1016/B978-0-12-813314-9.00010-4]
[54]
Abbas G, Gu J, Farooq U, Asad MU, El-Hawary M. solution of an economic dispatch problem through particle swarm optimization: A Detailed Survey - Part I. IEEE Access 2017; 5: 15105-41.
[http://dx.doi.org/10.1109/ACCESS.2017.2723862]
[55]
Abdilahi AM, Mustafa MW. Carbon capture power plants: Decoupled emission and generation outputs for economic dispatch. Int J Greenh Gas Control 2017; 63: 12-9.
[http://dx.doi.org/10.1016/j.ijggc.2017.05.001]
[56]
Samadianfard S, Hashemi S, Kargar K, et al. Wind speed prediction using a hybrid model of the multi-layer perceptron and whale optimization algorithm. Energy Rep 2020; 6: 1147-59.
[http://dx.doi.org/10.1016/j.egyr.2020.05.001]
[57]
Arya Azar N, Kardan N, Ghordoyee Milan S. Developing the artificial neural network–evolutionary algorithms hybrid models (ANN–EA) to predict the daily evaporation from dam reservoirs. Eng Comput 2021. (0123456789):
[http://dx.doi.org/10.1007/s00366-021-01523-3]
[58]
Makridakis S, Andersen A, Carbone R, et al. The accuracy of extrapolation (time series) methods: Results of a forecas-ting competition. J Forecast 1982; 1(2): 111-53.
[http://dx.doi.org/10.1002/for.3980010202]
[59]
Gholizadeh F, Sabzi F. Prediction of CO2 sorption in poly(ionic liquid)s using ANN-GC and ANFIS-GC models. Int J Greenh Gas Control 2017; 63: 95-106.
[http://dx.doi.org/10.1016/j.ijggc.2017.05.013]
[60]
Shalaby A, Elkamel A, Douglas PL, Zhu Q, Zheng QP. A machine learning approach for modeling and optimization of a CO2 post-combustion capture unit. Energy 2021; 215: 119113.
[http://dx.doi.org/10.1016/j.energy.2020.119113]
[61]
Thakur A. Lactic acid extraction from aqueous systems by emulsion liquid membrane separation process using statisti-cal experimental design. Polytech 2019; 2(1): 62-76.
[http://dx.doi.org/10.1007/s41050-019-00015-0]
[62]
Nimmanterdwong P, Chalermsinsuwan B, Piumsomboon P. Emergy analysis of three alternative carbon dioxide captu-re processes. Energy 2017; 128: 101-8.
[http://dx.doi.org/10.1016/j.energy.2017.03.154]
[63]
Yu H, Wilamowski BM. Levenberg-Marquardt Training. In: Intelligent Systems Florida. CRC Press 2011; pp. 1-13.
[64]
MacKay DJC. Bayesian Interpolation. Neural Comput 1992; 4(3): 415-47.
[http://dx.doi.org/10.1162/neco.1992.4.3.415]
[65]
Møller MF. A scaled conjugate gradient algorithm for fast supervised learning. Neural Netw 1993; 6(4): 525-33.
[http://dx.doi.org/10.1016/S0893-6080(05)80056-5]
[66]
Hwang J, Kim J, Lee HW, et al. An experimental based optimization of a novel water lean amine solvent for post com-bustion CO2 capture process. Appl Energy 2019; 248: 174-84.
[http://dx.doi.org/10.1016/j.apenergy.2019.04.135]
[67]
Yang SS, Yu XL, Ding MQ, et al. Simulating a combined lysis-cryptic and biological nitrogen removal system treating domestic wastewater at low C/N ratios using artificial neural network. Water Res 2021; 189: 116576.
[http://dx.doi.org/10.1016/j.watres.2020.116576] [PMID: 33161328]
[68]
Soroush E, Shahsavari S, Mesbah M, Rezakazemi M, Zhang Z. A robust predictive tool for estimating CO2 solubility in potassium based amino acid salt solutions. Chin J Chem Eng 2018; 26(4): 740-6.
[http://dx.doi.org/10.1016/j.cjche.2017.10.002]
[69]
Abotaleb A, El-Naas MH, Amhamed A. Enhancing gas loading and reducing energy consumption in acid gas removal systems: A simulation study based on real NGL plant data. J Nat Gas Sci Eng 2018; 55: 565-74.
[http://dx.doi.org/10.1016/j.jngse.2017.08.011]
[70]
Iliuta I. Hasib-ur-Rahman M, Larachi F. CO2 absorption in diethanolamine/ionic liquid emulsions – Chemical kinetics and mass transfer study. Chem Eng J 2014; 240: 16-23.
[http://dx.doi.org/10.1016/j.cej.2013.11.063]
[71]
Li F, Hemmati A, Rashidi H. Industrial CO2 absorption into methyldiethanolamine/piperazine in place of monoethano-lamine in the absorption column. Process Saf Environ Prot 2020; 142: 83-91.
[http://dx.doi.org/10.1016/j.psep.2020.06.006]
[72]
Cents AHG, Brilman DWF, Versteeg GF. Gas absorption in an agitated gas-liquid–liquid system. Chem Eng Sci 2001; 56(3): 1075-83.
[http://dx.doi.org/10.1016/S0009-2509(00)00324-9]
[73]
Nabity JA, Killelea JV, Shaffer BA, et al. Ionic-liquid-based contactors for carbon dioxide removal from simulated spa-cecraft cabin atmospheres. J Spacecr Rockets 2020; 57(6): 1350-61.
[http://dx.doi.org/10.2514/1.A34750]
[74]
Noorani N, Mehrdad A. Cholinium-amino acid ionic liquids as biocompatible agents for carbon dioxide absorption. J Mol Liq 2022; 357: 119078.
[http://dx.doi.org/10.1016/j.molliq.2022.119078]
[75]
Ye C, Dang M, Yao C, Chen G, Yuan Q. Process analysis on CO2 absorption by monoethanolamine solutions in micro-channel reactors. Chem Eng J 2013; 225: 120-7.
[http://dx.doi.org/10.1016/j.cej.2013.03.053]
[76]
Yin G, Jameel Ibrahim Alazzawi F, Bokov D, et al. Multiple machine learning models for prediction of CO2 solubility in potassium and sodium based amino acid salt solutions. Arab J Chem 2022; 15(3): 103608.
[http://dx.doi.org/10.1016/j.arabjc.2021.103608]
[77]
Conversano A, Porcu A, Mureddu M, Pettinau A, Gatti M. Bench-scale experimental tests and data analysis on CO2 capture with potassium prolinate solutions for combined cycle decarbonization. Int J Greenh Gas Control 2020; 93: 102881.
[http://dx.doi.org/10.1016/j.ijggc.2019.102881]
[78]
Imran M, Ali U, Hasnain A. Impact of blends of aqueous amines on absorber intercooling for post combustion CO2 capture system. Energy Environ 2021; 32(5): 921-44.
[http://dx.doi.org/10.1177/0958305X20982835]
[79]
Zhang R, Zhang X, Yang Q, Yu H, Liang Z, Luo X. Analysis of the reduction of energy cost by using MEA-MDEA-PZ solvent for post-combustion carbon dioxide capture (PCC). Appl Energy 2017; 205(June): 1002-11.
[http://dx.doi.org/10.1016/j.apenergy.2017.08.130]
[80]
Garza-Ulloa J. Application of mathematical models in biomechatronics: artificial intelligence and time-frequency analysis. Math Model 2018; (Jan): 373-524.
[http://dx.doi.org/10.1016/B978-0-12-812594-6.00006-8]
[81]
Pradeep T, Samui P. Prediction of rock strain using hybrid approach of ann and optimization algorithms. Geotech Geol Eng 2022; 40(9): 4617-43.
[http://dx.doi.org/10.1007/s10706-022-02174-x]
[82]
Moayedi H, Tien Bui D, Dounis A, Kok Foong L, Kalantar B. Novel nature-inspired hybrids of neural computing for estimating soil shear strength. Appl Sci (Basel) 2019; 9(21): 4643.
[http://dx.doi.org/10.3390/app9214643]
[83]
Jafari-Asl J, Ben Seghier MEA, Ohadi S, van Gelder P. Efficient method using whale optimization algorithm for reliability-based design optimization of labyrinth spillway. Appl Soft Comput 2021; 101: 107036.
[http://dx.doi.org/10.1016/j.asoc.2020.107036]