Abstract
In the high-humidity, hot-summer-cold-winter (HSCW) zone of China, the moisture buffering effect in the envelope is found to be significant in optimum insulation thickness. However, few studies have considered the effects of indoor moisture buffering on the optimum insulation thickness and energy consumption. In this study, we considered the energy load of an exterior wall under moisture transfer from the outdoor to the indoor environment. An optimum insulation thickness was obtained by integrating the P1−P2 model. A residential building was selected for the case study to verify the proposed method. Finally, a comparison was made with two other widely used methods, namely the transient heat transfer model (TH) and the coupled heat and moisture transfer model (CHM). The results indicated that the indoor moisture buffering effect on the optimum insulation thickness is 2.54 times greater than the moisture buffering effect in the envelope, and the two moisture buffering effects make opposing contributions to the optimum insulation thickness. Therefore, when TH or CHM was used without considering the indoor moisture buffering effect, the optimum insulation thickness of the southern wall under one air change per hour (1 ACH) and 100% normal heat source may be overestimated by 2.13% to 3. 59%, and the annual energy load on a single wall may be underestimated by 10.10% to 11.44%. The decrease of airtightness and the increase of indoor heat sources may result in a slight reduction of optimum insulation thickness. This study will enable professionals to consider the effects of moisture buffering on the design of insulation thickness.
Abstract
目的
探讨室内和外墙中的湿缓冲效应对外墙最佳保温层厚度的影响, 提高夏热冬冷地区外墙最佳保温层厚度的预测精度。
创新点
1. 通过结合热湿耦合传递模型和室内热湿环境模型, 构建考虑室内湿缓冲效应的最佳保温层厚度优化方法; 2. 获得室内湿缓冲对最佳保温层厚度的影响规律及与外墙湿缓冲的对抗关系。
方法
1. 通过理论分析, 构建水分从室外环境转移至室内环境时的外墙能量负荷, 并得到最佳保温层厚度的优化方法(图1); 2. 通过案例研究, 得到气密性和室内热源对最佳保温层厚度的影响(图6); 3. 通过优化方法间的对比, 探讨室内湿缓冲和外墙湿缓冲对最佳保温层厚度的影响。
结论
1. 室内湿缓冲效应对最佳保温层厚度的影响是围护结构外墙中湿缓冲效应的2.54倍, 而且这两种湿缓冲效应对最佳保温厚度的贡献相反。2. 在每小时换气一次(1 ACH)和100%正常热源条件下, 南墙的最佳保温厚度可能被高估了2.13%~3.59%, 而单面墙的年能量负荷可能被低估了10.10%~11.44%; 在同属夏热冬冷地区的不同城市中, 外墙湿缓冲的影响差异较大。3. 气密性的降低和室内热源的增加会导致最佳保温厚度的轻微降低。
References
Ali Kallioglu M, Sharma A, Chinnasamy V, et al., 2021. Optimum insulation thickness assessment of different insulation materials for mid-latitude steppe and desert climate (BSH) region of India. Materials Today: Proceedings, 44:4421–4424. https://doi.org/10.1016/j.matpr.2020.10.590
ASHRAE (American Society of Heating, Refrigerating and Air Conditioning Engineers), 2016. Criteria for Moisture Control Design Analysis in Buildings, ASHRAE Standard 160:2016. ASHRAE, Atlanta, USA.
BSI (British Standards Institution), 2012. Hygrothermal Performance of Building Components and Building Elements. Internal Surface Temperature to Avoid Critical Surface Humidity and Interstitial Condensation. Calculation Methods, BS EN ISO 13788:2012. BSI Standards Limited, London, UK.
Chbani Idrissi Y, Belarbi R, Ferroukhi MY, et al., 2022. Development of a numerical approach to assess the effect of coupled heat and moisture transfer on energy consumption of residential buildings in Moroccan context. Journal of Building Physics, 45(6):774–808. https://doi.org/10.1177/17442591211056068
Chen S, Zhang GM, Xia XB, et al., 2020. A review of internal and external influencing factors on energy efficiency design of buildings. Energy and Buildings, 216:109944. https://doi.org/10.1016/j.enbuild.2020.109944
Chung D, Wen J, Lo LJ, 2020. Development and verification of the open source platform, HAM-tools, for hygrothermal performance simulation of buildings using a stochastic approach. Building Simulation, 13(3):497–514. https://doi.org/10.1007/s12273-019-0594-5
D’Agostino D, De’Rossi F, Marigliano M, et al., 2019. Evaluation of the optimal thermal insulation thickness for an office building in different climates by means of the basic and modified “cost-optimal” methodology. Journal of Building Engineering, 24:100743. https://doi.org/10.1016/j.jobe.2019.100743
Dlimi M, Iken O, Agounoun R, et al., 2019. Energy performance and thickness optimization of hemp wool insulation and air cavity layers integrated in Moroccan building walls’. Sustainable Production and Consumption, 20:273–288. https://doi.org/10.1016/j.spc.2019.07.008
Duffie JA, Beckman WA, 1991. Solar Engineering of Thermal Processes. Wiley, Hoboken, USA, p.475–478.
Elmaz F, Eyckerman R, Casteels W, et al., 2021. CNN-LSTM architecture for predictive indoor temperature modeling. Building and Environment, 206:108327. https://doi.org/10.1016/j.buildenv.2021.108327
Fang JZ, Zhang HB, Ren P, et al., 2022. Influence of climates and materials on the moisture buffering in office buildings: a comprehensive numerical study in China. Environmental Science and Pollution Research, 29(10):14158–14175. https://doi.org/10.1007/s11356-021-16684-3
Fang ZS, Li N, Li BZ, et al., 2014. The effect of building envelope insulation on cooling energy consumption in summer. Energy and Buildings, 77:197–205. https://doi.org/10.1016/j.enbuild.2014.03.030
Ferroukhi MY, Djedjig R, Belarbi R, et al., 2015. Effect of coupled heat, air and moisture transfers modeling in the wall on the hygrothermal behavior of buildings. Energy Procedia, 78:2584–2589. https://doi.org/10.1016/j.egypro.2015.11.293
Geng YC, Han X, Zhang H, et al., 2021. Optimization and cost analysis of thickness of vacuum insulation panel for structural insulating panel buildings in cold climates. Journal of Building Engineering, 33:101853. https://doi.org/10.1016/j.jobe.2020.101853
Hagentoft CE, Kalagasidis AS, Adl-Zarrabi B, et al., 2004. Assessment method of numerical prediction models for combined heat, air and moisture transfer in building components: benchmarks for one-dimensional cases. Journal of Thermal Envelope and Building Science, 27(4):327–352. https://doi.org/10.1177/1097196304042436
Hens HLSC, 2015. Combined heat, air, moisture modelling: a look back, how, of help? Building and Environment, 91: 138–151. https://doi.org/10.1016/j.buildenv.2015.03.009
Kaynakli O, 2012. A review of the economical and optimum thermal insulation thickness for building applications. Renewable and Sustainable Energy Reviews, 16(1):415–425. https://doi.org/10.1016/j.rser.2011.08.006
Landuyt L, de Turck S, Laverge J, et al., 2021. Balancing environmental impact, energy use and thermal comfort: optimizing insulation levels for the mobble with standard HVAC and personal comfort systems. Building and Environment, 206:108307. https://doi.org/10.1016/j.buildenv.2021.108307
Li BZ, Du CQ, Yao RM, et al., 2018. Indoor thermal environments in Chinese residential buildings responding to the diversity of climates. Applied Thermal Engineering, 129: 693–708. https://doi.org/10.1016/j.applthermaleng.2017.10.072
Liu XW, Chen YM, Ge H, et al., 2015. Determination of optimum insulation thickness for building walls with moisture transfer in hot summer and cold winter zone of China. Energy and Buildings, 109:361–368. https://doi.org/10.1016/j.enbuild.2015.10.021
Martínez-Mariño S, Eguía-Oller P, Granada-Álvarez E, et al., 2021. Simulation and validation of indoor temperatures and relative humidity in multi-zone buildings under occupancy conditions using multi-objective calibration. Building and Environment, 200:107973. https://doi.org/10.1016/j.buildenv.2021.107973
Meng QL, Yan XY, Ren QC, 2015. Global optimal control of variable air volume air-conditioning system with iterative learning: an experimental case study. Journal of Zhejiang University-SCIENCE A (Applied Physics & Engineering), 16(4):302–315. https://doi.org/10.1631/jzus.A1400137
MOHURD (Ministry of Housing and Urban-Rural Development of the People’s Republic of China), 2010. Design Standard for Energy Efficiency of Residential Buildings in Hot Summer and Cold Winter Zone, JGJ 134–2010. National Standards of the People’s Republic of China (in Chinese).
MOHURD (Ministry of Housing and Urban-Rural Development of the People’s Republic of China), 2012. Design Code for Heating Ventilation and Air Conditioning of Civil Buildings, GB 50736-2012. National Standards of the People’s Republic of China (in Chinese).
Moon HJ, Ryu SH, Kim JT, 2014. The effect of moisture transportation on energy efficiency and IAQ in residential buildings. Energy and Buildings, 75:439–446. https://doi.org/10.1016/j.enbuild.2014.02.039
NOAA (National Oceanic and Atmospheric Administration), 2001. Global Hourly-Integrated Surface Database (ISD). https://www.ncei.noaa.gov/products/land-based-station/integrated-surface-database
Olivieri F, Grifoni RC, Redondas D, et al., 2017. An experimental method to quantitatively analyse the effect of thermal insulation thickness on the summer performance of a vertical green wall. Energy and Buildings, 150:132–148. https://doi.org/10.1016/j.enbuild.2017.05.068
Qin MH, Yang J, 2016. Evaluation of different thermal models in energyplus for calculating moisture effects on building energy consumption in different climate conditions. Building Simulation, 9(1):15–25. https://doi.org/10.1007/s12273-015-0263-2
Qin MH, Belarbi R, Aït-Mokhtar A, et al., 2009. Simulation of coupled heat and moisture transfer in air-conditioned buildings. Automation in Construction, 18(5):624–631. https://doi.org/10.1016/j.autcon.2008.12.006
Rode C, Peuhkuri R, Woloszyn M, 2006. Simulation tests in whole building heat and moisture transfer. Proceedings of the 3rd International Building Physics Conference, p.527–534.
Tariku F, Kumaran K, Fazio P, 2010. Integrated analysis of whole building heat, air and moisture transfer. International Journal of Heat and Mass Transfer, 53(15–16):3111–3120. https://doi.org/10.1016/j.ijheatmasstransfer.2010.03.016
Tariku F, Kumaran K, Fazio P, 2011. Determination of indoor humidity profile using a whole-building hygrothermal model. Building Simulation, 4(1):61–78. https://doi.org/10.1007/s12273-011-0031-x
Trindade AD, Coelho GBA, Henriques FMA, 2021. Influence of the climatic conditions on the hygrothermal performance of autoclaved aerated concrete masonry walls. Journal of Building Engineering, 33:101578. https://doi.org/10.1016/j.jobe.2020.101578
Tunçbilek E, Komerska A, Arıcı M, 2022. Optimisation of wall insulation thickness using energy management strategies: intermittent versus continuous operation schedule. Sustainable Energy Technologies and Assessments, 49: 101778. https://doi.org/10.1016/j.seta.2021.101778
Wang SH, Kang YM, Yang ZL, et al., 2019. Numerical study on dynamic thermal characteristics and optimum configuration of internal walls for intermittently heated rooms with different heating durations. Applied Thermal Engineering, 155:437–448. https://doi.org/10.1016/j.applthermaleng.2019.04.005
Wang YY, Ma C, Liu YF, et al., 2018. A model for the effective thermal conductivity of moist porous building materials based on fractal theory. International Journal of Heat and Mass Transfer, 125:387–399. https://doi.org/10.1016/j.ijheatmasstransfer.2018.04.063
Woloszyn M, Kalamees T, Olivier Abadie M, et al., 2009. The effect of combining a relative-humidity-sensitive ventilation system with the moisture-buffering capacity of materials on indoor climate and energy efficiency of buildings. Building and Environment, 44(3):515–524. https://doi.org/10.1016/j.buildenv.2008.04.017
Woods J, Winkler J, 2016. Field measurement of moisture-buffering model inputs for residential buildings. Energy and Buildings, 117:91–98. https://doi.org/10.1016/j.enbuild.2016.02.008
Xu CC, Li SH, Zou KK, 2019. Study of heat and moisture transfer in internal and external wall insulation configurations. Journal of Building Engineering, 24:100724. https://doi.org/10.1016/j.jobe.2019.02.016
Zhang MJ, Qin MH, Chen Z, 2017. Moisture buffer effect and its impact on indoor environment. Procedia Engineering, 205:1123–1129. https://doi.org/10.1016/j.proeng.2017.10.417
Zhang YM, Jie PF, Liu CH, et al., 2022. Optimizing environmental insulation thickness of buildings with CHP-based district heating system based on amount of energy and energy grade. Frontiers in Energy, 16:613–628. https://doi.org/10.1007/s11708-020-0700-5
Zhou XH, Carmeliet J, Sulzer M, et al., 2020. Energy-efficient mitigation measures for improving indoor thermal comfort during heat waves. Applied Energy, 278:115620. https://doi.org/10.1016/j.apenergy.2020.115620
Acknowledgments
This work is supported by the National Natural Science Foundation of China (Nos. 51978623 and 52076189).
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Yan-hao FENG: investigation, conceptualization, data curation, methodology, software, validation, and writing—original draft. Zi-tao YU: project administration, supervision, and writing—review & editing. Jiang LU: project administration, supervision, and writing—review & editing. Xu XU: supervision.
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Yan-hao FENG, Zi-tao YU, Jiang LU, and Xu XU declare that they have no conflict of interest.
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Optimum insulation thickness of external walls by integrating indoor moisture buffering effect: a case study in the hot-summer-cold-winter zone of China
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Feng, Yh., Yu, Zt., Lu, J. et al. Optimum insulation thickness of external walls by integrating indoor moisture buffering effect: a case study in the hot-summer-cold-winter zone of China. J. Zhejiang Univ. Sci. A 23, 998–1012 (2022). https://doi.org/10.1631/jzus.A2200158
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DOI: https://doi.org/10.1631/jzus.A2200158
Key words
- Insulation thickness optimization
- Coupled heat and moisture transfer
- Indoor moisture buffering effect
- Exterior wall
- Lifecycle cost