Prediction of the mechanical behavior of mortars incorporating phase change materials using data mining techniques

Sandra Cunha; J. Aguiar; F. Martins

doi:10.3989/mc.2023.298622

Autores/as

Sandra Cunha University of Minho https://orcid.org/0000-0002-6384-1355
J. Aguiar CTAC, Department of Civil Engineering, University of Minho https://orcid.org/0000-0003-3954-5721
F. Martins ISISE, Department of Civil Engineering, University of Minho https://orcid.org/0000-0001-6088-7860

DOI:

https://doi.org/10.3989/mc.2023.298622

Palabras clave:

Morteros, Materiales de cambio de fase (PCM), Técnicas de minería de datos, Redes neuronales artificiales, Máquinas de vectores soporte

Resumen

Hoy en día es imperativo reducir la factura energética para contribuir a un planeta más sostenible. El uso de materiales que contribuyan a la eficiencia energética de los edificios es muy importante para conseguir este objetivo. Los morteros con materiales de cambio de fase (PCM), por su capacidad de almacenamiento térmico, pueden contribuir de forma importante a este fin aumentando la eficiencia energética de los edificios. En este trabajo se desarrollaron morteros con diferentes contenidos de PCM, utilizando diferentes conglomerantes (cemento, cal aérea, cal hidráulica y yeso). El objetivo de este estudio es aplicar técnicas de minería de datos como redes neuronales artificiales (ANN), máquinas de vectores de soporte (SVM) y regresiones lineales múltiples (MLR) para pronosticar las resistencias a la compresión y flexión de morteros a diferentes temperaturas de exposición. Se concluyó que los modelos ANN tienen la mejor capacidad predictiva para la resistencia a la compresión y flexión. Los modelos SVM tienen una capacidad de predicción de la resistencia a flexión semejante a los modelos ANN.

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Citas

Boemi, S.N.; Papadopoulos, A.M. (2019) Energy poverty and energy efficiency improvements: A longitudinal approach of the Hellenic households. Energy Build. 197, 242-250. https://doi.org/10.1016/j.enbuild.2019.05.027

Cunha, S., Aguiar, I.; Aguiar, J. (2022) Phase change materials composite boards and mortars: Mixture design, physical, mechanical and thermal behavior. J. Energy Storage. 53, e105135. https://doi.org/10.1016/j.est.2022.105135

Cunha, S.; Aguiar, J.B.; Tadeu, A. (2016) Thermal performance and cost analysis of PCM mortars based in different binders. Constr. Build. Mater. 122, 637-648. https://doi.org/10.1016/j.conbuildmat.2016.06.114

Yu, K.; Liu, Y.; Jia, M.; Wang, C.; Yang, Y. (2022) Thermal energy storage cement mortar containing encapsulated hydrated salt/fly ash cenosphere phase change material: Thermo-mechanical properties and energy saving analysis. J. Energy Storage. 51, e104388. https://doi.org/10.1016/j.est.2022.104388

Abden, J.; Tao, Z.; Pan, Z.; George, L.; Wuhrer, R. (2020) Inclusion of methyl stearate/diatomite composite in gypsum board ceiling for building energy conservation. Appl. Energy. 259, e114113. https://doi.org/10.1016/j.apenergy.2019.114113

Lu, S.; Liang, B.; Li, X.; Kong, X.; Jia, W.; Wang, L. (2020) Performance Analysis of PCM Ceiling Coupling with Earth-Air Heat Exchanger for Building Cooling. Materials. 13 [13], e2890. https://doi.org/10.3390/ma13132890 PMid:32605066 PMCid:PMC7372354

Cunha, S.; Aguiar, J.B. (2020) Phase Change Materials and Energy Efficiency of Buildings: A Review of Knowledge. J. Energy Storage. 27, e101083. https://doi.org/10.1016/j.est.2019.101083

Dnyandip, K. B.; Pranaynil, S.; Manish, K. R.; Dibakar, R.; Jyotirmay, B. (2021) A machine learning and deep learning based approach to predict the thermal performance of phase change material integrated building envelope. Build. Environ. 199, 107927. https://doi.org/10.1016/j.buildenv.2021.107927

Kheradmand, M.; Azenha, M.; Aguiar, J.B.; Castro-Gomes, J. (2016) Experimental and numerical studies of hybrid PCM embedded in plastering mortar for enhanced thermal behaviour of buildings. Energy. 94, 250-26. https://doi.org/10.1016/j.energy.2015.10.131

Shilei, L.; Neng, Z.; Guohui, F. (2006) Impact of Phase Change Wall Room on Indoor Thermal Environment in winter. Energy Build. 38 [1], 18-24. https://doi.org/10.1016/j.enbuild.2005.02.007

Shilei, L.; Guohui, F.; Neng, Z.; Li, D. (2007) Experimental study and evaluation of latent heat storage in phase change materials wallboards. Energy Build. 39 [10], 1088-1091. https://doi.org/10.1016/j.enbuild.2006.11.012

Kuznik, F.; Virgone, J.; Roux, J. (2008) Energetic efficiency of room wall containing PCM wallboard: a full-scale experimental investigation. Energy Build. 40 [2], 148-156. https://doi.org/10.1016/j.enbuild.2007.01.022

Darkwa, K.; O'Callaghan, P.; Tetlow, D. (2006) Phase-change drywalls in a passive solar building. Appl. Energy. 83, 425-435. https://doi.org/10.1016/j.apenergy.2005.05.001

Bake, M.; Shukla, A.; Liu, S. (2021) Development of gypsum plasterboard embodied with microencapsulated phase change material for energy efficient buildings. Mater. Sci. Energy Technologies. 4, 166-176. https://doi.org/10.1016/j.mset.2021.05.001

Singh, S.P.; Bhat, V. (2018) Performance evaluation of dual phase change material gypsum board for the reduction of temperature swings in a building prototype in composite climate. Energy Build. 159, 191-200. https://doi.org/10.1016/j.enbuild.2017.10.097

Castell, A.; Martorell, I.; Medrano, M.; Pérez, G.; Cabeza, L.F. (2010) Experimental study of using PCM in brick constructive solutions for passive cooling. Energy Build. 42 [4], 534-540. https://doi.org/10.1016/j.enbuild.2009.10.022

Saxena, R.; Rakshit, D.; Kaushik, S. (2019) Phase change material (PCM) incorporated bricks for energy conservation in composite climate: A sustainable building solution. Sol. Energy. 183, 276-284. https://doi.org/10.1016/j.solener.2019.03.035

Shaik, S; Arumugam, C.; Shaik, S.; Arıcı, M.; Afzal, A.; Ma, Z. (2022) Strategic design of PCM integrated burnt clay bricks: Potential for cost-cutting measures for air conditioning and carbon dioxide extenuation. J. Clean. Prod. 375, e134077. https://doi.org/10.1016/j.jclepro.2022.134077

Saeed, T. (2022) Influence of the number of holes and two types of PCM in brick on the heat flux passing through the wall of a building on a sunny day in Medina, Saudi Arabia. J. Build. Eng. 50, e104215. https://doi.org/10.1016/j.jobe.2022.104215

Bahrar, M.; Djamai, Z.; Mankibi, M.; Larbi, A.; Salvia, M. (2018) Numerical and experimental study on the use of microencapsulated phase change materials (PCMs) in textile reinforced concrete panels for energy storage. Sustain. Cities Soc. 41, 455-468. https://doi.org/10.1016/j.scs.2018.06.014

Entrop, A.; Brouwers, H.; Reinders, A. (2011) Experimental research on the use of micro-encapsulated Phase Change Materials to store solar energy in concrete floors and to save energy in Dutch houses. Sol. Energy. 85 [5], 1007-1020. https://doi.org/10.1016/j.solener.2011.02.017

Nagano, K.; Takeda, S.; Mochida, T.; Shimakura, K.; Nakamura, T. (2006) Study of a Floor Supply Air Conditioning System Using Granular Phase Change Material to Augment Building Thermal Mass Storage - Heat Response in Small Scale Experiments. Energy Build. 38 [5], 436-446. https://doi.org/10.1016/j.enbuild.2005.07.010

Pasupathy, A.; Athanasius, L.; Velraj, R.; Seeniraj, R. (2008) Experimental investigation and numerical simulation analysis on the thermal performance of a building roof incorporating phase change material (PCM) for thermal management. Appl. Therm. Eng. 28 [5-6], 556-565. https://doi.org/10.1016/j.applthermaleng.2007.04.016

Essid, N.; Eddhahak, A.; Neji, J. (2022) Experimental and numerical analysis of the energy efficiency of PCM concrete wallboards under different thermal scenarios. J. Build. Eng. 45, e103547. https://doi.org/10.1016/j.jobe.2021.103547

Benkaddour, A.; Faraji, M.; Faraji, H. (2020) Numerical study of the thermal energy storage behaviour of a novel composite PCM/Concrete wall integrated solar collector.Mater. Today Proc. 30, 905-908. https://doi.org/10.1016/j.matpr.2020.04.348

Ahmad, M.; Bontemps, A.; Sallée, H.; Quenard, D. (2006) Thermal Testing and Numerical Simulation of a Prototype Cell Using Light Wallboards Coupling Vacuum Isolation Panels and Phase Change Material. Energy Build. 38 [6], 673-681. https://doi.org/10.1016/j.enbuild.2005.11.002

Santos, T.; Kolokotroni, M.; Hopper, N.; Yearley, K. (2019) Experimental study on the performance of a new encapsulation panel for PCM's to be used in the PCM Air heat exchanger. Ener. Proc. 161, 352-359. https://doi.org/10.1016/j.egypro.2019.02.105

Griffiths, P.; Eames, P. (2007) Performance of chilled ceiling panels using phase change material slurries as the heat transport medium. Appl. Therm. Eng. 27 [10], 1756-1760. https://doi.org/10.1016/j.applthermaleng.2006.07.009

Jin, X.; Zhang, X. (2011) Thermal analysis of a double layer phase change material floor. Appl. Therm. Eng. 31 [10], 1576-1581. https://doi.org/10.1016/j.applthermaleng.2011.01.023

Al-Absi, Z.; Hafizal, M.; Ismail, M. (2022) Experimental study on the thermal performance of PCM-based panels developed for exterior finishes of building walls. J. Build. Eng. 52, e104379. https://doi.org/10.1016/j.jobe.2022.104379

Bogatu, D.; Kazanci, O.; Olesen, B. (2021) An experimental study of the active cooling performance of a novel radiant ceiling panel containing phase change material (PCM). Energy Build. 243, e110981. https://doi.org/10.1016/j.enbuild.2021.110981

Cunha, S.; Silva, M.; Aguiar, J.B. (2020) Behavior of cementitious mortars with direct incorporation of non-encapsulated phase change material after severe temperature exposure. Constr. Build. Mater. 230, 117011. https://doi.org/10.1016/j.conbuildmat.2019.117011

Cunha, S.; Lima, M.; Aguiar, J.B. (2016) Influence of adding phase change materials on the physical and mechanical properties of cement mortars. Constr. Build. Mater. 127, 1-10. https://doi.org/10.1016/j.conbuildmat.2016.09.119

Cunha, S.; Leite, P.; Aguiar, J.B. (2020) Characterization of innovative mortars with direct incorporation of phase change materials. J. Energy Storage. 30, 101439. https://doi.org/10.1016/j.est.2020.101439

Cunha, S.; Aguiar, J.B.; Ferreira, V. (2018) Eco-efficient mortars with incorporation of phase change materials. J. Build. Phys. 41 [5], 469-492. https://doi.org/10.1177/1744259117697397

Chang, G.; Healey, M.; McHugh, J.A.M.; Wang, J.T.L. (2001) Mining in the world wide web - An information search approach, kluwer academic publishers. https://doi.org/10.1007/978-1-4615-1639-2

Sankar, L.P.; Sivasankar, S.; Shunmugasundaram, M.; Kumar, A.P. (2020) Predicting the polymer modified ferrocement ultimate flexural strength using artificial neural network and adaptive network based fuzzy inference system. Mater. Today. 27 [2], 1375-1380. https://doi.org/10.1016/j.matpr.2020.02.760

Topçu, İ.B.; Sarıdemir, M. (2008) Prediction of rubberized mortar properties using artificial neural network and fuzzy logic. J. Mater. Process Technol. 199 [1-3], 108-118. https://doi.org/10.1016/j.jmatprotec.2007.08.042

.

Eskandari-Naddaf, H.; Kazemi, R. (2017) ANN prediction of cement mortar compressive strength, influence of cement strength class. Constr. Build. Mater. 138, 1-11. https://doi.org/10.1016/j.conbuildmat.2017.01.132

Onyari, E.K.; Ikotun, B.D. (2018) Prediction of compressive and flexural strengths of a modified zeolite additive mortar using artificial neural network. Constr. Build. Mater. 187, 1232-1241. https://doi.org/10.1016/j.conbuildmat.2018.08.079

Azimi-Pour, M.; Eskandari-Naddaf, H. (2018) ANN and GEP prediction for simultaneous effect of nano and micro sílica on the compressive and flexural strength of cement mortar. Constr. Build. Mater. 189, 978-992. https://doi.org/10.1016/j.conbuildmat.2018.09.031

Kooshkaki, A.; Eskandari-Naddaf, H. (2019) Effect of porosity on predicting compressive and flexural strength of cement mortar containing micro and nano-silica by multi-objective ANN modelling. Constr. Build. Mater. 212, 176-191. https://doi.org/10.1016/j.conbuildmat.2019.03.243

Armaghani, D.J.; Asteris, P.G. (2021) A comparative study of ANN and ANFIS models for the prediction of cement-based mortar materials compressive strength. Neural. Comput. Appl. 33, 4501-4532. https://doi.org/10.1007/s00521-020-05244-4

Asteris, P.G.; Koopialipoor, M.; Armaghani, D.J.; Kotsonis, E.A.; Lourenço, P.B. (2021) Prediction of cement-based mortars compressive strength using machine learning techniques. Neural. Comput. Appl. 33, pages13089-13121. https://doi.org/10.1007/s00521-021-06004-8

Yuzer, N.; Akbas, B.; Kizilkanat, A.B. (2011) Predicting the high temperature effect on mortar compressive strength by neural network. Comput. Concr. 8, 491-510. https://doi.org/10.12989/cac.2011.8.5.491

Çolak, A.B.; Akçaözoğlu, K.; Akçaözoğlu, S.; Beller, G. (2021) Artificial intelligence approach in predicting the effect of elevated temperature on the mechanical properties of PET aggregate mortars: an experimental study. Arab. J. Sci. Eng. 46, 4867-4881. https://doi.org/10.1007/s13369-020-05280-1

Selimefendigil, F.; Öztop, H. (2020) Impacts of magnetic field and hybrid nanoparticles in the heat transfer fluid on the thermal performance of phase change material installed energy storage system and predictive modeling with artificial neural networks. J. Energy Storage. 32, 101793. https://doi.org/10.1016/j.est.2020.101793

Bhamare, D.; Saikia, P.; Rathod, M.; Rakshit, D.; Banerjee, J. (2021) A machine learning and deep learning based approach to predict the thermal performance of phase change material integrated building envelope. Build. Environ. 199, 107927. https://doi.org/10.1016/j.buildenv.2021.107927

Marani, A.; Nehdi, M.L. (2020) Machine learning prediction of compressive strength for phase change materials integrated cementitious composites. Constr. Build. Mater. 265, 120286. https://doi.org/10.1016/j.conbuildmat.2020.120286

Marani, A.; Nehdi, M.L. (2021) Application of artificial neural networks (ANNS) in prediction of compressive strength of PCM-integrated concretes. CSCE Annual Conference - Inspired by nature.

Cunha, S.; Aguiar, J.; Pacheco-Torgal, F. (2015) Effect of temperature on mortars with incorporation of phase change materials. Constr. Build. Mater. 98, 89-101. https://doi.org/10.1016/j.conbuildmat.2015.08.077

Cunha, S.; Aguiar, J.; Ferreira, V.M.; Tadeu, A. (2015) Mortars Based in different binders with incorporation of phase change materials: Physical and mechanical properties. Eur. J. Environ. Civ. Eng. 19, 1216-1233. https://doi.org/10.1080/19648189.2015.1008651

Lai, C.; Chen, R.; Lin C. (2010) Heat transfer and thermal storage behaviour of gypsum boards incorporating micro-encapsulated PCM. Energy Build. 42 [8], 1259-1266. https://doi.org/10.1016/j.enbuild.2010.02.018

Sharma, A.; Tyagi, V.; Chen, C.; Buddhi, D. (2009) Review on thermal energy storage with phase change materials and applications. Renewable Sustainable Energy Rev. 13, 318-345. https://doi.org/10.1016/j.rser.2007.10.005

Cunha, S.; Aguiar, J. (2021) Energy efficiency of buildings - Contribution of phase change materials. Sílabas e desafios. (In Portuguese)

European Committee for Standardization (CEN) (2004) EN 1015-3:2004. Methods of test for mortar for masonry - Part 3: Determination of consistence of fresh mortar (by flow table), 2004.

European Committee for Standardization (CEN) (1999) EN 1015-11:1999. Methods of test for mortar for masonry - Part 11: Determination of flexural and compressive strength of hardened mortar.

Cortez, P. (2010) Data mining with neural networks and support vector machines using the R/rminer tool. In: P. Perner (Ed.). Proceedings of 10th Industrial Conference on Data Mining, lecture notes in artificial intelligence. Advanc. Data Mining. 6171, 572-583. https://doi.org/10.1007/978-3-642-14400-4_44

Haykin, S. (1999) Neural networks - A compreensive foundation. (2nd ed). New Jersey: Prentice-Hall.

Cortes, C.; Vapnik, V. (1995) Support vector networks. Machine learning, kluwer academic publishers. 20, 273-297. https://doi.org/10.1007/BF00994018

Smola, A.; Scholkopf, B. (2004) A tutorial on support vector regression. Stat. Comput. 14, 199-222. https://doi.org/10.1023/B:STCO.0000035301.49549.88

Cherkassy, V.; Ma, Y. (2004) Practical selection of SVM parameters and noise estimation for SVM regression. Neural Netw. 17, 113-126. https://doi.org/10.1016/S0893-6080(03)00169-2 PMid:14690712

Efron, B.; Tibshirani, R. (1993) An introduction to the bootstrap, Chapman & Hall, London. https://doi.org/10.1007/978-1-4899-4541-9

Johnson, R. (1984) Elementary statistics, Boston: Duxbury Press, 86-106. https://doi.org/10.1016/0375-9601(84)90500-0

Pilehvar, S.; Cao, V.D.; Szczotok, A.M.; Valentini, L.; Salvioni, D.; Magistri, M.; Pamies, R.; Kjøniksen, A. (2017) Mechanical properties and microscale changes of geopolymer concrete and Portland cement concrete containing micro-encapsulated phase change Materials. Cem. Concr. Res. 100, 341-349. https://doi.org/10.1016/j.cemconres.2017.07.012

Aguayo, M.; Das, S.; Maroli, A.; Kabay, N.; Mertens, J.C.E.; Rajan, S.D.; Sant, G.; Chawla, N.; Neithalath, N. (2016) The influence of microencapsulated phase change material (PCM) characteristics on the microstructure and strength of cementitious composites: Experiments and finite element simulations. Cem. Concr. Compos. 73, 29-41. https://doi.org/10.1016/j.cemconcomp.2016.06.018

Fernandes, F.; Manari, S.; Aguayo, M.; Santos, K.; Oey, T.; Wei, Z. (2014) On the feasibility of using phase change materials (PCMs) to mitigate thermal cracking in cementitious materials. Cem. Concr. Compos. 51, 14-26. https://doi.org/10.1016/j.cemconcomp.2014.03.003

Shilpa, M. (2011) Thermal response of cementitious systems incorporating phase change materials, Clarkson University.

Xu, B.; Li, Z. (2013) Paraffin/diatomite composite phase change material incorporated cement-based composite for thermal energy storage. Appl. Energy. 105, 229-237. https://doi.org/10.1016/j.apenergy.2013.01.005

Sun, D.; Wang, L. (2015) Utilization of paraffin/expanded perlite materials to improve mechanical and thermal properties of cement mortar. Constr. Build. Mater. 101 [1], 791-796. https://doi.org/10.1016/j.conbuildmat.2015.10.123