Construction and Building Materials, Journal Year: 2024, Volume and Issue: 444, P. 137728 - 137728
Published: Aug. 10, 2024
Language: Английский
Construction and Building Materials, Journal Year: 2024, Volume and Issue: 444, P. 137728 - 137728
Published: Aug. 10, 2024
Language: Английский
Applied Thermal Engineering, Journal Year: 2023, Volume and Issue: 224, P. 120088 - 120088
Published: Jan. 23, 2023
Language: Английский
Citations
64Construction and Building Materials, Journal Year: 2024, Volume and Issue: 416, P. 135108 - 135108
Published: Jan. 28, 2024
Thermal energy storage in building envelopes is critical to promoting renewable energy, implementation of which requires thermal performance enhancement construction materials. In this regard, phase change materials (PCMs) are often incorporated with cement-based composites (CBCs) materials, most commonly used construction. The current article provides a state-of-the-art review PCM-incorporated CBCs (PCM-CBCs) considering various CBCs, incorporation methods, and their challenges solutions. Additionally, evaluation PCM-CBCs carried out based on thermal, mechanical, durability, sustainability, efficiency, resource conservation-based performances. It was identified that terms performance, natural conservation, the research has been well established, they find vast application TES management systems. On other hand, although healthy data available appraisal mechanical PCM-CBCs, more efforts required control detrimental impact PCM make them durable desirable for where must undergo loading. This consolidated perspective researchers, practitioners, educators working practical.
Language: Английский
Citations
30Journal of Energy Storage, Journal Year: 2025, Volume and Issue: 114, P. 115933 - 115933
Published: Feb. 24, 2025
Language: Английский
Citations
4Renewable and Sustainable Energy Reviews, Journal Year: 2025, Volume and Issue: 215, P. 115587 - 115587
Published: March 15, 2025
Language: Английский
Citations
2Materials, Journal Year: 2022, Volume and Issue: 15(1), P. 335 - 335
Published: Jan. 3, 2022
The use of phase-change materials (PCM) in concrete has revealed promising results terms clean energy storage. However, the negative impact interaction between PCM and on mechanical durability properties limits field applications, leading to a shift research incorporate into using different techniques overcome these issues. storage via significantly supports UN SDG 7 target affordable energy. Therefore, present study focuses three aspects: type, effect properties, connecting outcome composite United Nations sustainable development goals (UN SDGs). compensation reduction strength PCM-contained is possible up some extent with nanomaterials supplementary cementitious materials. As PCM-incorporated categorized type building material, large-scale this material will affect stages associated lifetimes. study, amendments lifetimes after are discussed mapped consideration SDGs 7, 11, 12. current challenges widespread lower thermal conductivity, trade-off PCM, absence link PCM-concrete SDGs. global prospects as part effort attain studied here motivate architects, designers, practicing engineers, researchers accelerate their efforts promote PCM-containing ultimately net zero carbon emissions from infrastructure for future.
Language: Английский
Citations
49Case Studies in Construction Materials, Journal Year: 2022, Volume and Issue: 17, P. e01537 - e01537
Published: Oct. 7, 2022
Time and cost-efficient techniques are essential to avoid extra conventional experimental studies with large data-set for material characterization of composite materials. This study is aimed at providing a correlation between the structural performance mechanical properties carbon nano-tubes reinforced cementitious composites through efficient predictive Machine Learning (ML) models. The Flexural (FS) Compressive (CS) Strength Carbon Nanotube (CNT)-reinforced were predicted based on data-rich framework provided in literature. Two different ensembled ML methods including Random Forest (RF) Gradient Boosting (GBM) implemented those data predicting CNT-reinforced cement-based composites. Data-set utilized training proposed models employing SciKit-Learn library Python, followed by hyper-parameter tuning k-fold cross-validation method obtaining an optimum model predict target values. It was shown that CS values more accurate than FS counterparts developed GBM has less sensitivity alteration test RF model. Finally, analysis conducted Sobol algorithm parameters highest contribution identified.
Language: Английский
Citations
48Journal of Energy Storage, Journal Year: 2022, Volume and Issue: 56, P. 105976 - 105976
Published: Oct. 31, 2022
Language: Английский
Citations
40Journal of Energy Storage, Journal Year: 2024, Volume and Issue: 83, P. 110819 - 110819
Published: Feb. 7, 2024
Language: Английский
Citations
15Journal of Materials in Civil Engineering, Journal Year: 2025, Volume and Issue: 37(4)
Published: Feb. 5, 2025
Language: Английский
Citations
1Materials Today Proceedings, Journal Year: 2022, Volume and Issue: 63, P. 685 - 691
Published: Jan. 1, 2022
Language: Английский
Citations
36