Skip to main content
Log in

Mathematical modeling of melting point and viscosity of a new molten salt for concentrating solar plant

  • Published:
Journal of Thermal Analysis and Calorimetry Aims and scope Submit manuscript

Abstract

Selecting the best type of molten medium as energy storage needs a good insight into various properties, which change with temperature and the combination of different compositions. This research aims to understand the influences of the temperature and composition of different mass percent of metal nitrates on the viscosity and thermal conductivity of new molten salt for concentrating solar plants. The experimental outcomes indicate that the viscosity of molten salt strongly changes with the salt composition. In addition, the thermal conductivity and density of molten salt composed of 30 mass% LiNO3, 13 mass% NaNO3, and 57 mass% KNO3 with increasing temperature experience severe decrement. To determine useful correlations for the melting point and viscosity of proposed molten salt, an Artificial Neural Network based on the Group Method of Data Handling is employed. Two polynomials for melting point temperature and viscosity of molten salt are carried out. Results indicate that suggested models predict the experimental values for viscosity and melting point temperature with high accuracy. Calculations of \({R}^{2}\) values for viscosity and melting pointe are 0.9289 and 0.9678 that show reasonable accuracy of models.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  1. Gil A, Arce P, Martorell I, Medrano M, Cabeza LF. State of the art of high temperature storage in thermosolar plants. TalonStocktonEdu n.d.

  2. Kuravi S, Trahan J, Goswami DY, Rahman MM, Stefanakos EK. Thermal energy storage technologies and systems for concentrating solar power plants. Prog Energy Combust Sci. 2013;39:285–319. https://doi.org/10.1016/j.pecs.2013.02.001.

    Article  Google Scholar 

  3. Fernández AG, Galleguillos H, Fuentealba E, Pérez FJ. Thermal characterization of HITEC molten salt for energy storage in solar linear concentrated technology. J Therm Anal Calorim. 2015;122:3–9. https://doi.org/10.1007/s10973-015-4715-9.

    Article  CAS  Google Scholar 

  4. Peng Q, Yang X, Ding J, Wei X, Yang J. Thermodynamic performance of the NaNO3-NaCl-NaNO2 ternary system. J Therm Anal Calorim. 2014;115:1753–8. https://doi.org/10.1007/s10973-013-3389-4.

    Article  CAS  Google Scholar 

  5. Peng W, Zhou JM, Li Y, Yang Y, Guo MR. A dynamic technique for the measurement of thermal conductivity of molten salt based on cylindrical melting model. J Therm Anal Calorim. 2014;115:1767–77. https://doi.org/10.1007/s10973-013-3386-7.

    Article  CAS  Google Scholar 

  6. Ushak S, Fernández AG, Grageda M. Using molten salts and other liquid sensible storage media in thermal energy storage (TES) systems A2. In: Cabeza LF, editor. BT—Advances in thermal energy storage systems. Cambridge: Woodhead Publ Ser Energy; 2015.

    Google Scholar 

  7. Cabeza LF, Gutierrez A, Barreneche C, Ushak S, Fernández ÁG, Inés Fernádez A, et al. Lithium in thermal energy storage: a state-of-the-art review. Renew Sustain Energy Rev. 2015;42:1106–12. https://doi.org/10.1016/j.rser.2014.10.096.

    Article  CAS  Google Scholar 

  8. Fernández AG, Ushak S, Galleguillos H, Pérez FJ. Development of new molten salts with LiNO 3 and Ca (NO 3) 2 for energy storage in CSP plants. Appl Energy. 2014;119:131–40. https://doi.org/10.1016/j.apenergy.2013.12.061.

    Article  CAS  Google Scholar 

  9. Mantha D, Wang T, Reddy RG. Thermodynamic modeling of eutectic point in the LiNO3-NaNO3-KNO3 ternary system. J Phase Equilib Diffus. 2012;33:110–4. https://doi.org/10.1007/s11669-012-0005-4.

    Article  CAS  Google Scholar 

  10. Bradshaw RW, Meeker DE. High-temperature stability of ternary nitrate molten salts for solar thermal energy systems. Sol Energy Mater. 1990;21:51–60. https://doi.org/10.1016/0165-1633(90)90042-Y.

    Article  CAS  Google Scholar 

  11. Wang T, Mantha D, Reddy RG. Thermal stability of the eutectic composition in LiNO3–NaNO3–KNO3 ternary system used for thermal energy storage. Sol Energy Mater Sol Cells. 2012;100:162–8. https://doi.org/10.1016/j.solmat.2012.01.009.

    Article  CAS  Google Scholar 

  12. Mohammad MB, Brooks G, Rhamdhani MA. High temperature properties of molten nitrate salt for solar thermal energy storage application. In: Wang S, Free ML, Alam S, Zhang M, editors. The Mineral Metals and Materials Series. NewYork : Springer International Publishing; 2017. p. 531–9.

    Google Scholar 

  13. Olivares RI, Edwards W. LiNO3-NaNO3-KNO3 salt for thermal energy storage: thermal stability evaluation in different atmospheres. Thermochim Acta. 2013;560:34–42. https://doi.org/10.1016/j.tca.2013.02.029.

    Article  CAS  Google Scholar 

  14. Bradshaw RW, Siegel NP, Development of molten nitrate salt mixtures for concentrating solar power systems. SolarPaces Conf 2009

  15. Nissen DA. thermophysical properties of the equimolar mixture NaN0,-KNO, from 300 to 600 °C. J Chem Eng Data. 1982;27:269–73.

    Article  CAS  Google Scholar 

  16. Bradshaw RW, Low Melting point heat transfer fluid—Patent N° US 7,828,990 B1, 2008.

  17. Bradshaw RW, Viscosity of Multi-component Molten Nitrate Salts—Liquidus to 200 °C 2010;21.

  18. Jin Y, Cheng J, An X, Su T, Zhang P, Li Z. Accurate viscosity measurement of nitrates/nitrites salts for concentrated solar power. Sol Energy. 2016;137:385–92. https://doi.org/10.1016/j.solener.2016.08.037.

    Article  CAS  Google Scholar 

  19. Coscia K. Thermophysical properties of LiNO3-NaNO3- KNO3 mixtures for use in concentrated solar thermophysical properties of for use in concentrated solar power. J Solar Energy Eng. 2013. https://doi.org/10.1115/1.4024069.

    Article  Google Scholar 

  20. Varol Y, Koca A, Oztop HF, Avci E. Forecasting of thermal energy storage performance of phase change material in a solar collector using soft computing techniques. Expert Syst Appl. 2010. https://doi.org/10.1016/j.eswa.2009.08.007.

    Article  Google Scholar 

  21. Garg S, Shariff AM, Shaikh MS, Lal B, Suleman H, Faiqa N. Experimental data, thermodynamic and neural network modeling of CO2 solubility in aqueous sodium salt of l-phenylalanine. J CO2 Util. 2017. https://doi.org/10.1016/j.jcou.2017.03.011.

    Article  Google Scholar 

  22. Hezave AZ, Raeissi S, Lashkarbolooki M. Estimation of thermal conductivity of ionic liquids using a perceptron neural network. Ind Eng Chem Res. 2012. https://doi.org/10.1021/ie202681b.

    Article  Google Scholar 

  23. Taskinen J, Yliruusi J. Prediction of physicochemical properties based on neural network modelling. Adv Drug Deliv Rev. 2003. https://doi.org/10.1016/S0169-409X(03)00117-0.

    Article  PubMed  Google Scholar 

  24. Altarazi S, Ammouri M, Hijazi A. Artificial neural network modeling to evaluate polyvinylchloride composites’ properties. Comput Mater Sci. 2018. https://doi.org/10.1016/j.commatsci.2018.06.003.

    Article  Google Scholar 

  25. Ivakhnenko A, Ivakhnenko G, The review of problems solvable by algorithms of the group method of data handling (GMDH). Pattern Recognit Image Anal C/C Raspoznavaniye Obraz I Anal Izobr 1995.

  26. Nariman-Zadeh N, Atashkari K, Jamali A, Pilechi A, Yao X. Inverse modelling of multi-objective thermodynamically optimized turbojet engines using GMDH-type neural networks and evolutionary algorithms. Eng Optim. 2005;37:437–62. https://doi.org/10.1080/03052150500035591.

    Article  Google Scholar 

Download references

Acknowledgements

This work was partially funded by the Ministerio de Ciencia, Innovación y Universidades de España (RTI2018-093849-B-C31—MCIU/AEI/FEDER, UE) and by the Ministerio de Ciencia, Innovación y Universidades—Agencia Estatal de Investigación (AEI) (RED2018-102431-T). The author at University of Lleida would like to thank the Catalan Government for the quality accreditation given to their research group GREiA (2017 SGR 1537). GREiA is a certified agent TECNIO in the category of technology developers from the Government of Catalonia.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Muhammad Zeeshan Malik.

Ethics declarations

Conflict of interest

The authors certify that they have NO affiliations with or involvement in any organization or entity with any financial interest (such as honoraria; educational grants; participation in speakers’ bureaus; membership, employment, consultancies, stock ownership, or other equity interest; and expert testimony or patent-licensing arrangements), or non-financial interest (such as personal or professional relationships, affiliations, knowledge or beliefs) in the subject matter or materials discussed in this manuscript.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Malik, M.Z., Musharavati, F., Ahmed, F.W. et al. Mathematical modeling of melting point and viscosity of a new molten salt for concentrating solar plant. J Therm Anal Calorim 147, 4533–4540 (2022). https://doi.org/10.1007/s10973-021-10783-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10973-021-10783-6

Keywords

Navigation