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.

结合室内湿缓冲效应的外墙最佳保温层厚度：中国夏热冬冷地区的案例研究

[1]Ali KallioğluM, SharmaA, ChinnasamyV, 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.

[2]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.

[3](British Standards Institution)BSI, 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.

[4]Chbani IdrissiY, BelarbiR, FerroukhiMY, 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.

[5]ChenS, ZhangGM, XiaXB, et al., 2020. A review of internal and external influencing factors on energy efficiency design of buildings. Energy and Buildings, 216:109944.

[6]ChungD, WenJ, LoLJ, 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.

[7]D’AgostinoD, De’RossiF, MariglianoM, 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.

[8]DlimiM, IkenO, AgounounR, 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.

[9]DuffieJA, BeckmanWA, 1991. Solar Engineering of Thermal Processes. Wiley, Hoboken, USA, p.475-478.

[10]ElmazF, EyckermanR, CasteelsW, et al., 2021. CNN-LSTM architecture for predictive indoor temperature modeling. Building and Environment, 206:108327.

[11]FangJZ, ZhangHB, RenP, 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.

[12]FangZS, LiN, LiBZ, et al., 2014. The effect of building envelope insulation on cooling energy consumption in summer. Energy and Buildings, 77:197-205.

[13]FerroukhiMY, DjedjigR, BelarbiR, 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.

[14]GengYC, HanX, ZhangH, 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.

[15]HagentoftCE, KalagasidisAS, Adl-ZarrabiB, 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.

[16]HensHLSC, 2015. Combined heat, air, moisture modelling: a look back, how, of help? Building and Environment, 91:138-151.

[17]KaynakliO, 2012. A review of the economical and optimum thermal insulation thickness for building applications. Renewable and Sustainable Energy Reviews, 16(1):‍415-425.

[18]LanduytL, de TurckS, LavergeJ, 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.

[19]LiBZ, DuCQ, YaoRM, et al., 2018. Indoor thermal environments in Chinese residential buildings responding to the diversity of climates. Applied Thermal Engineering, 129:693-708.

[20]LiuXW, ChenYM, GeH, 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.

[21]Martínez-MariñoS, Eguía-OllerP, Granada-ÁlvarezE, 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.

[22]MengQL, YanXY, RenQC, 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.

[23]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).

[24]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).

[25]MoonHJ, RyuSH, KimJT, 2014. The effect of moisture transportation on energy efficiency and IAQ in residential buildings. Energy and Buildings, 75:439-446.

[26]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

[27]OlivieriF, GrifoniRC, RedondasD, 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.

[28]QinMH, YangJ, 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.

[29]QinMH, BelarbiR, Aït-MokhtarA, et al., 2009. Simulation of coupled heat and moisture transfer in air-conditioned buildings. Automation in Construction, 18(5):624-631.

[30]RodeC, PeuhkuriR, WoloszynM, 2006. Simulation tests in whole building heat and moisture transfer. Proceedings of the 3rd International Building Physics Conference, p.527-534.

[31]TarikuF, KumaranK, FazioP, 2010. Integrated analysis of whole building heat, air and moisture transfer. International Journal of Heat and Mass Transfer, 53(15-16):3111-3120.

[32]TarikuF, KumaranK, FazioP, 2011. Determination of indoor humidity profile using a whole-building hygrothermal model. Building Simulation, 4(1):61-78.

[33]TrindadeAD, CoelhoGBA, HenriquesFMA, 2021. Influence of the climatic conditions on the hygrothermal performance of autoclaved aerated concrete masonry walls. Journal of Building Engineering, 33:101578.

[34]TunçbilekE, KomerskaA, ArıcıM, 2022. Optimisation of wall insulation thickness using energy management strategies: intermittent versus continuous operation schedule. Sustainable Energy Technologies and Assessments, 49:101778.

[35]WangSH, KangYM, YangZL, 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.

[36]WangYY, MaC, LiuYF, 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.

[37]WoloszynM, KalameesT, Olivier AbadieM, 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.

[38]WoodsJ, WinklerJ, 2016. Field measurement of moisture-buffering model inputs for residential buildings. Energy and Buildings, 117:91-98.

[39]XuCC, LiSH, ZouKK, 2019. Study of heat and moisture transfer in internal and external wall insulation configurations. Journal of Building Engineering, 24:100724.

[40]ZhangMJ, QinMH, ChenZ, 2017. Moisture buffer effect and its impact on indoor environment. Procedia Engineering, 205:1123-1129.

[41]ZhangYM, JiePF, LiuCH, 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.

[42]ZhouXH, CarmelietJ, SulzerM, et al., 2020. Energy-efficient mitigation measures for improving indoor thermal comfort during heat waves. Applied Energy, 278:115620.