Performance Prediction of Conventional and Modified Solar Stills Using Levenberg Marquardt Algorithm-Based Artificial Neural Network Model: An Experimental and Stochastic Evaluation

[1]         WWC, World Water Council Report - 8th World water forum highlights, 2018. http://www.worldwatercouncil.org/sites/default/files/2018-11/Outcomes-of-8th-WWForum_WEB.pdf.

[2]         REN21, Renewables 2015-Global status report, 2015. https://doi.org/10.1016/0267-3649(88)90030-1.

[3]         M.S.H. Boutilier, J. Lee, V. Chambers, V. Venkatesh, R. Karnik, Water filtration using plant xylem., PLoS One 9 (2014) e89934. https://doi.org/10.1371/journal.pone.0089934.

[4]         A. Ahmad, T. Azam, Water Purification Technologies, in: A.M. Grumezescu, A.M. Holban (Eds.), Bottled Packag. Water, Woodhead Publishing, 2019: pp. 83–120. https://doi.org/https://doi.org/10.1016/B978-0-12-815272-0.00004-0.

[5]         G.N. Tiwari, A. Tiwari, Shyam, Solar Distillation, Pergamon, Oxford, U.K, UK, 2016. https://doi.org/10.1007/978-981-10-0807-8_13.

[6]         G.N. Tiwari, A.K. Tiwari, Solar Distillation Practice for Water Desalination Systems, Anamaya, New Delhi, India, 2008.

[7]         K. Zarzoum, K. Zhani, H. Ben Bacha, Desalination and Water Treatment, 126 (2018) 87–96. https://doi.org/10.5004/dwt.2018.22812.

[8]         H.M. Yeh, L.C. Chen, The effects of climatic, design and operational parameters on the performance of wick-type solar distillers, Energy Convers. Manag. 26 (1986) 175–180. https://doi.org/10.1016/0196-8904(86)90052-X.

[9]         H. Panchal, Solar Desalination Technology Brief, in: A. Kumar, O. Prakash (Eds.), Sol. Desalin. Technol., Springer Singapore, 2019: pp. 167–177. https://doi.org/10.1007/978-981-13-6887-5.

[10]       B.W. Tleimat, E.D. Howe, Nocturnal production of solar distillers, Sol. Energy 10 (1966) 61–66. https://doi.org/10.1016/0038-092X(66)90037-5.

[11]       A.A. El-Sebaii, E. El-Bialy, Advanced designs of solar desalination systems: A review, Renew. Sustain. Energy Rev. (2015). https://doi.org/10.1016/j.rser.2015.04.161.

[12]       P. Prakash, V. Velmurugan, Parameters influencing the productivity of solar stills – A review, Renew. Sustain. Energy Rev. 49 (2015) 585–609. https://doi.org/10.1016/j.rser.2015.04.136.

[13]       S. Shoeibi, N. Rahbar, A. Abedini Esfahlani, H. Kargarsharifabad, A review of techniques for simultaneous enhancement of evaporation and condensation rates in solar stills, Sol. Energy 225 (2021) 666–693. https://doi.org/10.1016/j.solener.2021.07.028.

[14]       K. Selvaraj, A. Natarajan, Factors in fl uencing the performance and productivity of solar stills - A review, Desalination 435 (2018) 181–187. https://doi.org/10.1016/j.desal.2017.09.031.

[15]       M.S. Barghi Jahromi, V. Kalantar, H. Samimi Akhijahani, H. Kargarsharifabad, S. Shoeibi, Performance analysis of a new solar air ventilator with phase change material: Numerical simulation, techno-economic and environmental analysis, J. Energy Storage 62 (2023) 106961. https://doi.org/10.1016/j.est.2023.106961.

[16]       M.S. Sodha, A. Kumar, G.N. Tiwari, R.C. Tyagi, Simple multiple wick solar still: Analysis and performance, Sol. Energy 26 (1981) 127–131. https://doi.org/10.1016/0038-092X(81)90075-X.

[17]       B. Jamil, N. Akhtar, Effect of specific height on the performance of a single slope solar still: An experimental study, Desalination 414 (2017) 73–88. https://doi.org/10.1016/j.desal.2017.03.036.

[18]       P. Dumka, D.R. Mishra, Influence of salt concentration on the performance characteristics of passive solar still, Int. J. Ambient Energy 42 (2021) 1463–1473. https://doi.org/10.1080/01430750.2019.1611638.

[19]       V. Velmurugan, C.K. Deenadayalan, H. Vinod, K. Srithar, Desalination of effluent using fin type solar still, Energy 33 (2008) 1719–1727. https://doi.org/10.1016/j.energy.2008.07.001.

[20]       R. Dhivagar, S. Shoeibi, H. Kargarsharifabad, M. Sadi, A. Arabkoohsar, M. Khiadani, Performance analysis of solar desalination using crushed granite stone as an energy storage material and the integration of solar district heating, Energy Sources, Part A Recover. Util. Environ. Eff. 46 (2024) 1370–1388. https://doi.org/10.1080/15567036.2023.2299693.

[21]       R. Dhivagar, S. Shoeibi, H. Kargarsharifabad, M.H. Ahmadi, M. Sharifpur, Performance enhancement of a solar still using magnetic powder as an energy storage medium-exergy and environmental analysis, Energy Sci. Eng. 10 (2022) 3154–3166. https://doi.org/10.1002/ese3.1210.

[22]       H.S. Deshmukh, S.B. Thombre, Solar distillation with single basin solar still using sensible heat storage materials, Desalination 410 (2017) 91–98. https://doi.org/10.1016/j.desal.2017.01.030.

[23]       K. Khanafer, K. Vafai, A review on the applications of nanofluids in solar energy field, Renew. Energy 123 (2018) 398–406. https://doi.org/10.1016/j.renene.2018.01.097.

[24]       P. Dumka, D.R. Mishra, Energy and exergy analysis of conventional and modified solar still integrated with sand bed earth: Study of heat and mass transfer, Desalination 437 (2018) 15–25. https://doi.org/10.1016/j.desal.2018.02.026.

[25]       P. Dumka, D.R. Mishra, Experimental investigation of modified single slope solar still integrated with earth (I) &(II):Energy and exergy analysis, Energy 160 (2018) 1144–1157. https://doi.org/10.1016/j.energy.2018.07.083.

[26]       A.E. Kabeel, S.A. El-agouz, R. Sathyamurthy, T. Arunkumar, Augmenting the productivity of solar still using jute cloth knitted with sand heat energy storage, Desalination 443 (2018) 122–129. https://doi.org/10.1016/j.desal.2018.05.026.

[27]       W.M. Alaian, E.A. Elnegiry, A.M. Hamed, Experimental investigation on the performance of solar still augmented with pin-finned wick, Desalination 379 (2016) 10–15. https://doi.org/10.1016/j.desal.2015.10.010.

[28]       S.A. Alamshah, M. Talebzadegan, M. Moravej, Performance Evaluation of Regular Hexagonal Pyramid Three-Dimensional Solar Desalination System : An Experimental Investigation, J. Sol. Energy Res. 9 (2024) 1914–1925. https://doi.org/10.22059/jser.2024.370071.1371.

[29]       S. Shoeibi, F. Jamil, S.M. Parsa, S. Mehdi, H. Kargarsharifabad, S.A.A. Mirjalily, W. Guo, H.H. Ngo, B.J. Ni, M. Khiadani, Recent advancements in applications of encapsulated phase change materials for solar energy systems: A state of the art review, J. Energy Storage 94 (2024) 112401. https://doi.org/10.1016/j.est.2024.112401.

[30]       A. Hemmatian, H. Kargarsharifabad, A. Abedini Esfahlani, N. Rahbar, S. Shoeibi, Improving solar still performance with heat pipe/pulsating heat pipe evacuated tube solar collectors and PCM: An experimental and environmental analysis, Sol. Energy 269 (2024) 112371. https://doi.org/10.1016/j.solener.2024.112371.

[31]       R. Kumar, D.R. Mishra, P. Dumka, Improving solar still performance : A comparative analysis of conventional and honeycomb pad augmented solar stills, Sol. Energy 270 (2024) 112408. https://doi.org/https://doi.org/10.1016/j.solener.2024.112408.

[32]       P. Dumka, D.R. Mishra, B. Singh, R. Chauhan, M. Haque, I. Siddiqui, Enhancing solar still performance with Plexiglas and jute cloth additions : experimental study, Sustain. Environ. Res. 34 (2024) 2–12. https://doi.org/10.1186/s42834-024-00208-y.

[33]       N. Hashemian, A. Noorpoor, Assessment and multi-criteria optimization of a solar and biomass-based multi-generation system: Thermodynamic, exergoeconomic and exergoenvironmental aspects, Energy Convers. Manag. 195 (2019) 788–797. https://doi.org/10.1016/j.enconman.2019.05.039.

[34]       N. Hashemian, A. Noorpoor, Thermo-eco-environmental Investigation of a Newly Developed Solar/wind Powered Multi-Generation Plant with Hydrogen and Ammonia Production Options, J. Sol. Energy Res. 8 (2023) 1728–1737. https://doi.org/10.22059/jser.2024.374028.1388.

[35]       M.S. Barghi Jahromi, V. Kalantar, H. Samimi Akhijahani, H. Kargarsharifabad, Recent progress on solar cabinet dryers for agricultural products equipped with energy storage using phase change materials, J. Energy Storage 51 (2022) 104434. https://doi.org/10.1016/j.est.2022.104434.

[36]       Z. Younsi, H. Naji, A numerical investigation of melting phase change process via the enthalpy-porosity approach: Application to hydrated salts, Int. Commun. Heat Mass Transf. 86 (2017) 12–24. https://doi.org/https://doi.org/10.1016/j.icheatmasstransfer.2017.05.012.

[37]       M.P.R. Teles, M. Sadi, K.A.R. Ismail, A. Arabkoohsar, B.V.F. Silva, H. Kargarsharifabad, S. Shoeibi, Cooling supply with a new type of evacuated solar collectors: a techno-economic optimization and analysis, Environ. Sci. Pollut. Res. 31 (2024) 18171–18187. https://doi.org/10.1007/s11356-023-25715-0.

[38]       Y. Cao, H. Nikafshan Rad, D. Hamedi Jamali, N. Hashemian, A. Ghasemi, A novel multi-objective spiral optimization algorithm for an innovative solar/biomass-based multi-generation energy system: 3E analyses, and optimization algorithms comparison, Energy Convers. Manag. 219 (2020) 112961. https://doi.org/https://doi.org/10.1016/j.enconman.2020.112961.

[39]       F.A. Essa, M. Abd Elaziz, A.H. Elsheikh, An enhanced productivity prediction model of active solar still using artificial neural network and Harris Hawks optimizer, Appl. Therm. Eng. 170 (2020) 115020. https://doi.org/10.1016/j.applthermaleng.2020.115020.

[40]       S.A. Kalogirou, M. Bojic, Artificial neural networks for the prediction of the energy consumption of a passive solar building, Energy 25 (2000) 479–491. https://doi.org/10.1016/S0360-5442(99)00086-9.

[41]       S.A. Kalogirou, E. Mathioulakis, V. Belessiotis, Arti fi cial neural networks for the performance prediction of large solar systems, Renew. Energy 63 (2014) 90–97. https://doi.org/10.1016/j.renene.2013.08.049.

[42]       A. Katal, N. Singh, Artificial Neural Network: Models, Applications, and Challenges, in: R. Tomar, M.D. Hina, R. Zitouni, A. Ramdane-Cherif (Eds.), Innov. Trends Comput. Intell., Springer International Publishing, Cham, 2022: pp. 235–257. https://doi.org/10.1007/978-3-030-78284-9_11.

[43]       A.F. Mashaly, A.A. Alazba, Thermal performance analysis of an inclined passive solar still using agricultural drainage water and artificial neural network in arid climate, Sol. Energy 153 (2017) 383–395. https://doi.org/10.1016/j.solener.2017.05.083.

[44]       J. Jawad, A.H. Hawari, S. Javaid Zaidi, Artificial neural network modeling of wastewater treatment and desalination using membrane processes: A review, Chem. Eng. J. 419 (2021) 129540. https://doi.org/https://doi.org/10.1016/j.cej.2021.129540.

[45]       E. Najafi, R. Rajabi, N. Bayat, Fault Tolerant Multilevel Inverter Using Artificial Neural Network, J. Sol. Energy Res. 9 (2024) 1745–1752. https://doi.org/10.22059/jser.2024.359461.1309.

[46]       A.H. Elsheikh, S.W. Sharshir, M. Abd Elaziz, A.E. Kabeel, W. Guilan, Z. Haiou, Modeling of solar energy systems using artificial neural network: A comprehensive review, Sol. Energy 180 (2019) 622–639. https://doi.org/10.1016/j.solener.2019.01.037.

[47]       A. Bardossy, L. Duckstein, Fuzzy Rule-Based Modeling with Applications to Geophysical, Biological and Engineering Systems, CRC press, 2022. https://doi.org/10.1201/9780138755133.

[48]       R.P. Chen, P. Zhang, X. Kang, Z.Q. Zhong, Y. Liu, H.N. Wu, Prediction of maximum surface settlement caused by earth pressure balance (EPB) shield tunneling with ANN methods, Soils Found. 59 (2019) 284–295. https://doi.org/10.1016/j.sandf.2018.11.005.

[49]       K.S. Garud, S. Jayaraj, M.Y. Lee, A review on modeling of solar photovoltaic systems using artificial neural networks, fuzzy logic, genetic algorithm and hybrid models, Int. J. Energy Res. 45 (2021) 6–35. https://doi.org/10.1002/er.5608.

[50]       P. Dumka, N. Pandey, D.R. Mishra, Conventional Solar Still Augmented with Saltwater Bottles: An Experimental Study, J. Sol. Energy Res. 9 (2024) 1811–1821. https://doi.org/10.22059/jser.2024.374131.1392.

[51]       P. Dumka, R. Chauhan, D.R. Mishra, Experimental and theoretical evaluation of a conventional solar still augmented with jute covered plastic balls, J. Energy Storage 32 (2020) 101874. https://doi.org/10.1016/j.est.2020.101874.

[52]       A.F. Mashaly, A.A. Alazba, Neural network approach for predicting solar still production using agricultural drainage as a feedwater source, Desalin. Water Treat. 57 (2016) 28646–28660. https://doi.org/10.1080/19443994.2016.1193770.

[53]       R. Chauhan, S. Sharma, R. Pachauri, P. Dumka, D.R. Mishra, Experimental and theoretical evaluation of thermophysical properties for moist air within solar still by using different algorithms of artificial neural network, J. Energy Storage 30 (2020) 101408. https://doi.org/10.1016/J.EST.2020.101408.

[54]       P. Dumka, D.R. Mishra, Performance evaluation of single slope solar still augmented with the ultrasonic fogger, Energy 190 (2020) 116398. https://doi.org/10.1016/j.energy.2019.116398.

[55]       P. Dumka, A. Jain, D.R. Mishra, Energy, exergy, and economic analysis of single slope conventional solar still augmented with an ultrasonic fogger and a cotton cloth, J. Energy Storage 30 (2020). https://doi.org/10.1016/j.est.2020.101541.

[56]       R.V. Dunkle, Solar water distillation: the roof type still and a multiple effect diffusion still, in: Int. Dev. Heat Transf. ASME, Proc. Int. Heat Transf. Part V, Univ. Color., 1961: pp. 895–902.

[57]       S. Kumar, G.N. Tiwari, Estimation of convective mass transfer in solar distillation systems, Sol. Energy 57 (1996) 459–464. https://doi.org/10.1016/S0038-092X(96)00122-3.

[58]       P.T. Tsilingiris, Modeling heat and mass transport phenomena at higher temperatures in solar distillation systems – The Chilton – Colburn analogy, Sol. Energy 84 (2010) 308–317. https://doi.org/10.1016/j.solener.2009.11.012.

[59]       P.T. Tsilingiris, Parameters affecting the accuracy of Dunkle ’ s model of mass transfer phenomenon at elevated temperatures, Appl. Therm. Eng. 75 (2015) 203–212. https://doi.org/10.1016/j.applthermaleng.2014.09.010.

[60]       B. Avvaru, M.N. Patil, P.R. Gogate, A.B. Pandit, Ultrasonic atomization: Effect of liquid phase properties, Ultrasonics 44 (2006) 146–158. https://doi.org/10.1016/j.ultras.2005.09.003.

[61]       A.J. Yule, Y. Al-Suleimani, On droplet formation from capillary waves on a vibrating surface, Proc. R. Soc. A Math. Phys. Eng. Sci. 456 (2000) 1069–1085. https://doi.org/10.1098/rspa.2000.0551.

[62]       G.I. Taylor, The instability of liquid surfaces when accelerated in a direction perpendicular to their planes. I, in: Proc. R. Soc. London. Ser. A. Math. Phys. Sci., 1950: pp. 192–196. https://doi.org/10.1098/rspa.1950.0052.

[63]       J.D. Bassett, A.W. Bright, Observations concerning the mechanism of atomisation in an ultrasonic fountain, J. Aerosol Sci. 7 (1976) 47–51. https://doi.org/10.1016/0021-8502(76)90008-2.

[64]       J.P. Holman, Experimental methods for engineers, McGraw-Hill, New York, 2017.

[65]       P. Dumka, K. Gajula, K. Sharma, D.R. Mishra, R. Chauhan, M.I. Haque Siddiqui, D. Dobrotă, I.M. Rotaru, A case study on single basin solar still augmented with wax filled metallic cylinders, Case Stud. Therm. Eng. 61 (2024) 104847. https://doi.org/10.1016/j.csite.2024.104847.

[66]       B. Khalili, H. Kargarsharifabad, N. Rahbar, A. Abedini Esfahlani, E. Jamshidi, Performance evaluation of a CGS gas heater-powered HDH desalination system using thermosyphon heat pipes: An experimental study with economic and environmental assessment, Int. Commun. Heat Mass Transf. 152 (2024) 107300. https://doi.org/https://doi.org/10.1016/j.icheatmasstransfer.2024.107300.

[67]       B. Omidi, N. Rahbar, H. Kargarsharifabad, Z. Poolaei Moziraji, Performance evaluation of a solar desalination-hot water system using heat pipe vacuum tube parabolic trough solar collector – An experimental study with Taguchi analysis, Energy Convers. Manag. 292 (2023) 117347. https://doi.org/https://doi.org/10.1016/j.enconman.2023.117347.

[68]       R. Dhivagar, S. Shoeibi, S.M. Parsa, S. Hoseinzadeh, H. Kargarsharifabad, M. Khiadani, Performance evaluation of solar still using energy storage biomaterial with porous surface: An experimental study and environmental analysis, Renew. Energy 206 (2023) 879–889. https://doi.org/10.1016/j.renene.2023.02.097.

[69]       P. Gao, L. Zhang, K. Cheng, H. Zhang, W. Yaïci, E. Entchev, A. Qazi, H. Fayaz, A. Wadi, R.G. Raj, N.A. Rahim, W.A. Khan, The artificial neural network for solar radiation prediction and designing solar systems: A systematic literature review, J. Clean. Prod. 104 (2014) 1348–1359. https://doi.org/10.1016/j.jclepro.2015.04.041.

[70]       T. Ertekin, Q. Sun, Artificial neural network applications in reservoir engineering, Artif. Neural Networks Chem. Eng. (2017) 123–204. https://doi.org/10.3390/en12152897.

[71]       S.C. Kothari, H. Oh, Neural Networks for Pattern Recognition, Oxford University Press, 1993. https://doi.org/10.1016/S0065-2458(08)60404-0.

[72]       M.T. Hagan, H.B. Demuth, M. Beale, Neural network design, PWS Publishing Co., 1997.

[73]       R. Chauhan, P. Dumka, D.R. Mishra, Modelling conventional and solar earth still by using the LM algorithm-based artificial neural network, Int. J. Ambient Energy 43 (2022) 1389–1396. https://doi.org/10.1080/01430750.2019.1707113.

[74]       K. Hidouria, D.R. Mishra, A. Benhmidenea, B. Chouachia, Modelling conventional and solar earth still by using the LM algorithm-based artificial neural network, IEEE Commun. Surv. Tutorials 21 (2020) 1–5. https://doi.org/10.1016/j.est.2020.101408.

[75]       R. Chauhan, S. Sharma, R. Pachauri, Deep Neural Network-Based Prediction of the COVID-19 Spread in India, 3 (2021) 1–11. https://doi.org/http://doi.org/10.5281/zenodo.4574861.

[76]       J. Gao, Y. Zhang, Y. Du, Q. Li, Optimization of the tire ice traction using combined Levenberg–Marquardt (LM) algorithm and neural network, J. Brazilian Soc. Mech. Sci. Eng. 41 (2019) 40. https://doi.org/10.1007/s40430-018-1545-2.

[77]       F.E. Jalal, Y. Xu, M. Iqbal, M.F. Javed, B. Jamhiri, Predictive modeling of swell-strength of expansive soils using artificial intelligence approaches: ANN, ANFIS and GEP, J. Environ. Manage. 289 (2021) 112420. https://doi.org/10.1016/j.jenvman.2021.112420.

[78]       J.R. Rabuñal, J. Dorado, Artificial neural networks in real-life applications, 2005. https://doi.org/10.4018/978-1-59140-902-1.

[79]       S. Aggarwal, G.N. Tiwari, Thermal modelling of a double condensing chamber solar still: An experimental validation, Energy Convers. Manag. 40 (1999) 97–114. https://doi.org/10.1016/S0196-8904(98)00110-1.

[80]       P.T. Tsilingiris, ScienceDirect Theoretical derivation and comparative evaluation of mass transfer coefficient modeling in solar distillation systems – The Bowens ratio approach, Sol. ENERGY 112 (2015) 218–231. https://doi.org/10.1016/j.solener.2014.11.021.