AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home Building Simulation Article
Article Link
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Research Article

An effective method to determine bedding system insulation based on measured data

Nan Zhang1,2, Bin Cao1,2( ), Yingxin Zhu1,3
Department of Building Science, School of Architecture, Tsinghua University, Beijing 100084, China
Beijing Key Laboratory of Indoor Air Quality Evaluation and Control (Tsinghua University), Beijing 100084, China
Key Laboratory of Eco Planning & Green Building, Ministry of Education (Tsinghua University), Beijing 100084, China
Show Author Information

Abstract

The thermal environment is an essential factor that affects sleep quality. In many circumstances, the bed microenvironment is more important than the ambient environment because of the large covered area of the human body and the close contact between the bedding system and the human body. The main objective of this research is to establish an effective method to determine bedding system insulation. A thermal manikin was used in the measurement of bedding system insulation. Three different types of quilts, which were filled with cotton, polyester and duvet respectively, were chosen to be tested. In total ten different quilts with different materials and weights were involved in the test. Four regular arrangements of covers were chosen with coverage rates of 94.1%, 85.9%, 70.6%, and 54.4% to test. A total of 64 bedding systems were tested to build an effective method to determine the bedding system insulation. On the basis of test data, the change of bedding system insulation with coverage was found to be nonlinear. Exponential fitting was applied to establish an insulation evaluation method for bedding system insulation. In addition, the effects of quilt cover and sleepwear on bedding system insulation were discussed and thermal insulation increment caused by quilt cover and sleepwear were estimated. The relationships between neutral indoor temperature and weight per unit area of the quilt for different coverage rates have been quantified based on existing subject experiments. This research provides an effective method to determine bedding system insulation, which can be widely used in thermal comfort research and HVAC system design.

Keywords

thermal comfortthermal insulationsleep environmentbedding system

References

 

Aminoff MJ, Boller F, Swaab DF (2011). Handbook of Clinical Neurology. Amsterdam: Elsevier.
 

Amraoui K, Sriti L, Di Turi S, et al. (2021). Exploring building's envelope thermal behavior of the neo-vernacular residential architecture in a hot and dry climate region of Algeria. Building Simulation, 14: 1567–1584.
Crossref Google Scholar
 
ASHRAE (2017). ASHRAE Standard 55-2017: Thermal Environmental Conditions for Human Occupancy. Atlanta, GA, USA: American Society of Heating, Refrigerating and Air-Conditioning Engineers.
 
ASTM (2010). ASTM-F1291-10. Standard Test Method for Measuring the Thermal Insulation Of Clothing Using a Heated Manikin. American Society of Testing and Materials (ASTM).
 

Bach V, Telliez F, Libert J-P (2002). The interaction between sleep and thermoregulation in adults and neonates. Sleep Medicine Reviews, 6: 481–492.
Crossref Google Scholar
 

Bogusławska-Baczek M, Hes L (2011). The effect of moisture on thermal resistance and water vapour permeability of nomex fabrics. Journal of Materials Science and Engineering, 1: 358–366.
Google Scholar
 

Cao T, Lian Z, Zhu J, et al. (2022). Parametric study on the sleep thermal environment. Building Simulation, 15: 885–898.
Crossref Google Scholar
 
EN (2018). EN 12130-2018. Feather and down—Test methods—Determination of the filling power (massic volume). European Norm (EN).
 

Fanger PO (1970). Thermal Comfort. Copenhagen: Danish Technical Press.
 

Gangwisch JE, Malaspina D, Boden-Albala B, et al. (2005). Inadequate sleep as a risk factor for obesity: analyses of the NHANES Ⅰ. Sleep, 28: 1289–1296.
Crossref Google Scholar
 

Haskell E, Palca J, Walker J, et al. (1981). The effects of high and low ambient temperatures on human sleep stages. Electroencephalography and Clinical Neurophysiology, 51: 494–501.
Crossref Google Scholar
 

Hes L, Bogusławska-Baczek M, Geraldes MJ (2014). Thermal comfort of bedsheets under real conditions of use. Journal of Natural Fibers, 11: 312–321.
Crossref Google Scholar
 
ISO (2009). ISO 9920. Estimation of the Thermal Insulation and Evaporative Resistance of a Clothing Ensemble. International Organization for Standardization (ISO).
 
ISO (2016). ISO 23537-2: 2016. Requirements for Sleeping Bags—Part 2: Fabric and material properties. International Organization for Standardization (ISO).
 
ISO (2022). ISO 23537-1: 2022. Requirements for Sleeping Bags—Part 1: Thermal, mass and dimensional requirements for sleeping bags designed for limit temperatures of −20℃ and higher. International Organization for Standardization (ISO).
 

Kräuchi K, Cajochen C, Werth E, et al. (1999). Warm feet promote the rapid onset of sleep. Nature, 401: 36–37.
Crossref Google Scholar
 

Lai D, Chen B, Liu K (2020). Quantification of the influence of thermal comfort and life patterns on outdoor space activities. Building Simulation, 13: 113–125.
Crossref Google Scholar
 

Lan L, Pan L, Lian Z, et al. (2014). Experimental study on thermal comfort of sleeping people at different air temperatures. Building and Environment, 73: 24–31.
Crossref Google Scholar
 

Lan L, Lian ZW, Lin YB (2016). Comfortably cool bedroom environment during the initial phase of the sleeping period delays the onset of sleep in summer. Building and Environment, 103: 36–43.
Crossref Google Scholar
 

Lin Z, Deng S (2008). A study on the thermal comfort in sleeping environments in the subtropics—Measuring the total insulation values for the bedding systems commonly used in the subtropics. Building and Environment, 43: 905–916.
Crossref Google Scholar
 

Lu Y, Niu M, Song W, et al. (2021). Investigation on the total and local thermal insulation of the bedding system: Effects of filling materials, weights and body postures. Building and Environment, 204: 108161.
Crossref Google Scholar
 

McCullough EA, Zbikowski PJ, Jones BW (1987). Measurement and prediction of the insulation provided by bedding systems. ASHRAE Transactions, 93(1): 1055–1068.
Google Scholar
 

Milewski MD, Skaggs DL, Bishop GA, et al. (2014). Chronic lack of sleep is associated with increased sports injuries in adolescent athletes. Journal of Pediatric Orthopaedics, 34: 129–133.
Crossref Google Scholar
 

Nicol F, Humphreys M, Roaf S (2012). Adaptive Thermal Comfort: Principles and Practice. London: Routledge
Crossref
 

Pan D, Lin Z, Deng S (2010). A mathematical model for predicting the total insulation value of a bedding system. Building and Environment, 45: 1866–1872.
Crossref Google Scholar
 

Pan L, Lian Z, Lan L (2012). Investigation of sleep quality under different temperatures based on subjective and physiological measurements. HVAC & R Research, 18: 1030-1043.
Google Scholar
 
Pannain S, Beccuti G, van Cauter E (2012). The connection between sleep loss, obesity, and type 2 diabetes. In: Shiromani P, Horvath T, Redline S, et al. (eds), Sleep Loss and Obesity. New York: Springer.
Crossref
 

Rudnicka AR, Nightingale CM, Donin AS, et al. (2017). Sleep duration and risk of type 2 diabetes. Pediatrics, 140: e20170338.
Crossref Google Scholar
 

Siegel JM (2005). Clues to the functions of mammalian sleep. Nature, 437(7063): 1264–1271.
Crossref Google Scholar
 

Song C, Liu Y, Zhou X, et al. (2016). Temperature field of bed climate and thermal comfort assessment based on local thermal sensations. Building and Environment, 95: 381–390.
Crossref Google Scholar
 

Tsuzuki K, Mori I, Sakoi T, et al. (2015). Effects of seasonal illumination and thermal environments on sleep in elderly men. Building and Environment, 88: 82–88.
Crossref Google Scholar
 

Wang Y, Liu Y, Song C, et al. (2015). Appropriate indoor operative temperature and bedding micro climate temperature that satisfies the requirements of sleep thermal comfort. Building and Environment, 92: 20–29.
Crossref Google Scholar
 

Wilson CA, Niven BE, Laing RM (1999). Estimating thermal resistance of the bedding assembly from thickness of materials. International Journal of Clothing Science and Technology, 11: 262–276.
Crossref Google Scholar
 

Wilson CA, Chu MS (2005). Thermal insulation and SIDS—An investigation of selected 'Eastern' and 'Western' infant bedding combinations. Early Human Development, 81: 695–709.
Crossref Google Scholar
 

Wu Y, Liu H, Li B, et al. (2021). Individual thermal comfort prediction using classification tree model based on physiological parameters and thermal history in winter. Building Simulation, 14: 1651–1665.
Crossref Google Scholar
 

Xie L, Kang H, Xu Q, et al. (2013). Sleep drives metabolite clearance from the adult brain. Science, 342: 373–377.
Crossref Google Scholar
 

Zhang N, Cao B, Zhu Y (2018). Indoor environment and sleep quality: A research based on online survey and field study. Building and Environment, 137: 198–207.
Crossref Google Scholar
 

Zhang N, Cao B, Zhu Y (2019). Effects of pre-sleep thermal environment on human thermal state and sleep quality. Building and Environment, 148: 600–608.
Crossref Google Scholar
 

Zhang N, Cao B, Wang Z, et al. (2020). Effects of bedding insulation and indoor temperature on bed microclimate and thermal comfort. Energy and Buildings, 223: 110097.
Crossref Google Scholar
 

Zhang J, Zhou X, Lei S, et al. (2022). Energy and comfort performance of occupant-centric air conditioning strategy in office buildings with personal comfort devices. Building Simulation, 15: 899–911.
Crossref Google Scholar
 
Zhu M (2017). Research on the adjustment mechanism of the air velocity produced by residential fans for the sleeping human in hot and humid climate. PhD Thesis, Donghua University, China. (in Chinese)
Building Simulation
Volume 16 Issue 1,
January 2023
Pages 121-132
DOI: 10.1007/s12273-022-0916-x
Cite this article:
Zhang N, Cao B, Zhu Y. An effective method to determine bedding system insulation based on measured data. Building Simulation, 2023, 16(1): 121-132. https://doi.org/10.1007/s12273-022-0916-x

563

Views

10

Crossref

10

Web of Science

10

Scopus

3

CSCD

Altmetrics
Received: 07 April 2022
Revised: 31 May 2022
Accepted: 22 June 2022
Published: 13 July 2022
© Tsinghua University Press 2022
Return