Energy and Buildings

By A. Richards. 2012

665 citations recorded by the source corpus.

a b s t r a c t The incorporation of phase change materials (PCM) into traditional mortars give to these products the ability to store and release heat. In this way it is possible to reduce the energy consumption and improve the thermal comfort in buildings. The introduction of micro and nanomaterials in the mortars matrix can cause microstructural changes that need to be addressed in order to optimize the PCM addition. The relationship between the hardened state performance of different PCM-mortars, its internal microstruc- ture and pore distribution as been observed for different binders such as lime, cement and gypsum. Their hardened state properties, microstructural modifications and heat storage capabilities were evaluated. The ability to store and release heat depends strongly on the size and distribution of internal pores and not only on the PCM content. Using a thermal efficiency test, an important correlation between thermal performance and the mortars microstructure was established, for mortars with 0-30% of PCM added. © 2013 Elsevier B.V. All rights reserved.

Subfields: Electrical and Electronic Engineering, Renewable Energy, Sustainability and the Environment

View Paper: https://www.semanticscholar.org/paper/a1da295616f9667a21bdcf6113599d91f5b45be3

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In Electrical and Electronic Engineering

1. Chongqing Kang
2. Qixin Chen
3. Yi Wang
4. Benjamin C. M. Fung
5. Ying Sun
6. F. Haghighat
7. Tao Hong
8. Rafal Weron

In Renewable Energy, Sustainability and the Environment

1. Chongqing Kang
2. Yi Wang
3. Qixin Chen
4. F. Haghighat
5. Tao Hong

Citations in the corpus

• A review of the-state-of-the-art in data-driven approaches for building energy prediction (2020, background): “Otherwise, studies tend to ignore the effect of set-point temperature in energy prediction accuracy, even though residents in residential buildings have the ability to adjust the set-point temperature to meet their thermal comfort requirement and save energy [34].”
• Is disaggregation the holy grail of energy efficiency? The case of electricity (2013, critical): “Several studies have documented that LEED and other green buildings are only about as efficient as conventional buildings (Scofield, 2002, 2009; Nilsson & Elmroth, 2005; Kunz, Maile, & Bazjanac, 2009; Maile, 2010).”
• Sustainable Building Certification and the Rent Premium: A Panel Data Approach (2012, neutral): “Other studies, however, find that the energy use of LEED certified buildings varies considerably or that these buildings do not necessarily save energy (Barrientos, Bhattacharjee, Martinez, and Duffy, 2007; Newsham, Mancini, and Birt, 2009; Scofield, 2009).”
• A game theory based analysis of decision making for green retrofit under different occupancy types (2016, background): “Scofield (2009) likewise found that the energy savings of certified buildings are not significantly different from those of comparable buildings.”
• Review of Smart Meter Data Analytics: Applications, Methodologies, and Challenges (2018, methodology): “A highly cited study compared seven existing techniques, including linear regression, ANN, SVM and their variants [111].”
• A review of methods to match building energy simulation models to measured data (2014, neutral): “Numerous studies [12 – 14] have indicated discrepancies, often signi fi cant (up to 100% differences), between BEPS model-predicted and the actual metered building energy use.”