All Issue

2025 Vol.58, Issue 11S-1

Research Article

Proposal of target reliability indices for structural design of plastic greenhouses against heavy snow damage

대설 피해에 대응한 온실 구조 설계를 위한 목표 신뢰성 지수 제안

Byung-hun Seoa
,
Sangik Leeb
,
Dongsu Kimc
,
Dongwoo Kimd
,
Yerim Joe
,
Seong-yoon Limf
,
Won Choig*
서 병훈a
,
이 상익b
,
김 동수c
,
김 동우d
,
조 예림e
,
임 성윤f
,
최 원g*
aPh.D. Candidate, Department of Rural Systems Engineering, Integrated Major in Global Smart Farm, Seoul National University, Seoul, Korea
bAssistant Professor, Department of Agricultural Civil Engineering, Kyungpook National University, Daegu, Korea
cPh.D. Candidate, Department of Rural Systems Engineering, Seoul National University, Seoul, Korea
dPh.D. Student, Department of Rural Systems Engineering, Seoul National University, Seoul, Korea
eMaster Student, Department of Rural Systems Engineering, Seoul National University, Seoul, Korea
fResearcher, Department of Agricultural Engineering, National Institute of Agricultural Sciences, Wanju, Korea
gProfessor, Department of Rural Systems Engineering, Integrated Major in Global Smart Farm, Seoul National University, Seoul, Korea
a서울대학교 농업생명과학대학 지역시스템공학과·융합전공스마트팜 박사수료
b경북대학교 농업생명과학대학 농업토목공학과 조교수
c서울대학교 농업생명과학대학 지역시스템공학과 박사수료
d서울대학교 농업생명과학대학 지역시스템공학과 박사과정
e서울대학교 농업생명과학대학 지역시스템공학과 석사과정
f국립농업과학원 농업공학부 스마트팜개발과 연구사
g서울대학교 농업생명과학대학 지역시스템공학과·융합전공스마트팜·농업생명과학연구원 교수
*Corresponding Author
30 November 2025. pp. 1141-1151
PDF XML Citation
Abstract

Climate change has increased the frequency and intensity of heavy-snow events, causing substantial damage to plastic greenhouses; however, the current blueprints of greenhouse structures based on allowable stress design have limitations in ensuring a consistent safety level and in supporting claim determinations of storm‑and‑flood insurance. To enable the adoption of LSD (Limit State Design) for greenhouse structures, this study aimed to derive the key metric—the target reliability index. We compiled a database of 43 disaster‑resilient blueprints in Korea and applied a greenhouse‑specific, active-learning-based structural reliability analysis to compute the reliability index for snow loads. The analysis shows that the group of designs, prepared after the announcement of ｢Guideline for Greenhouse Structural Design (Draft)｣ in 2017, exhibits a failure probability approximately 92.5 times lower than the group prepared beforehand. Also, the lower bounds of the reliability index are 3.29 and 1.95, respectively. Considering these reliability levels together with international design standard, we propose target reliability indices of 3.30 for the ultimate limit state and 2.00 for the serviceability limit state. The proposed indices are expected to serve as key foundational data for advancing LSD‑based greenhouse structural design standard and for establishing criteria for storm‑and‑flood insurance.

Keywords
Structural reliability analysis
Plastic greenhouse
Heavy snow
Disaster-resilient greenhouse
Target reliability index
Storm and flood insurance

기후변화로 인한 대설 사상의 빈도와 강도 증가는 비닐 온실의 막대한 피해를 유발하고 있으나, 현행 허용응력설계 기반의 온실 구조 설계도는 일관된 안전 수준 확보와 풍수해 보험 판정에 한계가 있다. 이에 본 연구는 신뢰성 기반 한계상태설계의 온실 설계 도입을 위해, 핵심 지표인 목표 신뢰성 지수를 도출하는 것을 목표로 하였다. 이를 위해 국내 내재해형 단동 온실 규격으로 고시된 43종의 설계도를 데이터베이스로 구축하였으며, 온실에 특화된 능동학습 기반 구조 신뢰성 해석 기법을 적용하여, 각 설계도의 적설 하중에 대한 신뢰성 지수를 산출하였다. 분석 결과, 2017년 「온실구조설계기준(안)」 제정 이후 마련된 설계도 그룹은 이전에 마련된 설계도 그룹에 비해 파괴확률이 약 92.5배 낮았으며, 신뢰성 지수 하한값은 각각 3.29와 1.95로 뚜렷한 성능 차이를 보였다. 이러한 온실 설계도의 신뢰성 수준과 국제 설계 기준을 종합적으로 고려하여, 극한한계상태의 목표 신뢰성 지수로 3.30, 사용성한계상태의 목표 신뢰성 지수로 2.00을 제안하였다. 제안된 목표 신뢰성 지수는 향후 한계상태설계 기반의 온실 구조 설계 기준을 고도화하고, 풍수해 보험 기준을 수립하는데 핵심 기초 자료로 활용될 수 있을 것으로 기대된다.

키워드
구조 신뢰성 해석
비닐 온실
대설
내재해형 온실
목표 신뢰성 지수
풍수해 보험
References
1

American Association of State Highway and Transportation Officials (AASHTO). (2020). LRFD bridge design specifications, 9th edition. Washington, D.C., U.S.

2

American Concrete Institute (ACI). (2019). Building code requirements for structural concrete (ACI 318-19). Farmington Hills, MI, U.S.

3

American Institute of Steel Construction (AISC). (2016). Specification for structural steel buildings (AISC 360-16). Chicago, IL, U.S.

4

American Society of Civil Engineers (ASCE). (2010). Minimum design loads and associated criteria for buildings and other structures (ASCE 7). Reston, VA, U.S.

5

Arrayago, I., and Rasmussen, K.J. (2021). “System-based reliability analysis of stainless steel frames under gravity loads.” Engineering Structures, Elsevier, Vol. 231, 111775.

10.1016/j.engstruct.2020.111775
6

Arrayago, I., Rasmussen, K.J., and Real, E. (2020). “Statistical analysis of the material, geometrical and imperfection characteristics of structural stainless steels and members.” Journal of Constructional Steel Research, Elsevier, Vol. 175, 106378.

10.1016/j.jcsr.2020.106378
7

Bartlett, F., Hong, H.P., and Zhou, W. (2003). “Load factor calibration for the proposed 2005 edition of the national building code of Canada: companion-action load combinations.” Canadian Journal of Civil Engineering, NRC, Vol. 30, No. 2, pp. 440-448.

10.1139/l02-086
8

Briassoulis, D., Dougka, G., Dimakogianni, D., and Vayas, I. (2016). “Analysis of the collapse of a greenhouse with vaulted roof.” Biosystems Engineering, Elsevier, Vol. 151, pp. 495-509.

10.1016/j.biosystemseng.2016.10.018
9

Choi, M.K., Ryu, H.R., Cho, M.W., and Yu, I.H. (2017). “Effect of the member joint on structural performance of an arch-type multi-span greenhouse: A full-scale experimental and numerical study.” Journal of Bio-Environment Control, KSBEC, Vol. 26, No. 4, pp. 402-410.

10.12791/KSBEC.2017.26.4.402
10

de Santana Gomes, W.J. (2019). “Structural reliability analysis using adaptive artificial neural networks.” ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering, ASCE/ASME, Vol. 5, No. 4, 041004.

10.1115/1.4044040
11

European Committee for Standardization (CEN). (1990). Eurocode 0: Basis of structural design, annex B. Brussels, Belgium.

12

European Committee for Standardization (CEN). (2001). Greenhouses: Design and construction - part 1: Commercial production greenhouses (EN 13031-1). Brussels, Belgium.

13

European Committee for Standardization (CEN). (2005). EN 10088-1: Stainless steels - part 1: List of stainless steels. Brussels, Belgium.

14

European Committee for Standardization (CEN). (2015). EN 1993-1-4:2006/A1:2015: Eurocode 3: Design of steel structures - part 1-4: general rules - supplementary rules for stainless steels. Brussels, Belgium.

15

Hochstenbach, F.M., Irwin, P.A., and Gamble, S.L. (2004). “Parametric studies of unbalanced snow loads on arched roofs.” Structures 2004: Building on the Past, Securing the Future, ASCE, Nashville, TN, U.S., pp. 1-11.

10.1061/40700(2004)55
16

Hong, H., and Ye, W. (2014). “Analysis of extreme ground snow loads for Canada using snow depth records.” Natural Hazards, Springer, Vol. 73, pp. 355-371.

10.1007/s11069-014-1073-z
17

Huang, Y., and Young, B. (2012). “Material properties of cold-formed lean duplex stainless steel sections.” Thin-Walled Structures, Elsevier, Vol. 54, pp. 72-81.

10.1016/j.tws.2012.02.003
18

Joint Committe on Structural Safety (JCSS). (2001). JCSS probabilistic model code, accessed 20 August 2025, <https://www.jcss-lc.org/jcss-probabilistic-model-code-pmc/>.

19

Lee, J.Y., and Ryu, H.R. (2022). “Structural analysis of pipe-framed greenhouses using interface elements for cross-over connections.” Engineering Structures, Elsevier, Vol. 266, 114504.

10.1016/j.engstruct.2022.114504
20

Lee, S., Lee, J.H., Seo, B.H., Kim, D.S., Kim, D., Jo, Y., and Choi, W. (2025). “Stiffness evaluation of semi-rigid connection using steel clamps in plastic greenhouse structure.” Biosystems Engineering, Elsevier, Vol. 250, pp. 15-27.

10.1016/j.biosystemseng.2024.11.018
21

Lee, S.I. (2023). Reliability analysis framework integrating deep learning-based meta model and nonlinear finite element method. Ph.D. Dissertation, Seoul National University, pp. 1-259.

22

Lee, S.I., Lee, J.H., Jeong, Y.J., and Choi, W. (2020). “Development of a structural analysis model for pipe structures to reflect ground conditions.” Biosystems Engineering, Elsevier, Vol. 197, pp. 231-244.

10.1016/j.biosystemseng.2020.06.018
23

Lee, S.I., Lee, J.H., Jeong, Y.J., Kim, D.S., Seo, B.H., Seo, Y.J., and Choi, W. (2022). “System reliability analysis of semi-rigid frame structures - Focusing on greenhouses.” Journal of the Korean Society of Agricultural Engineers, KSAE, Vol. 64, No. 5, pp. 67-77.

24

Leffler, B. (1990). “A statistical study of the mechanical properties of hot rolled stainless plate.” Nordic Symposium on Mechanical Properties of Stainless Steels, Sigtuna, Sweden, pp. 32-42.

25

Li, M., Wei, X., Zhao, Q., and Wang, L. (2024). “Numerical simulation of structural performance in a single-tube frame for 12 m-span Chinese solar greenhouses subjected to snow loads.” Agronomy, MDPI, Vol. 14, No. 6, 1122.

10.3390/agronomy14061122
26

Li, S.H. (2023). “Effect of nonstationary extreme wind speeds and ground snow loads on the structural reliability in a future Canadian changing climate.” Structural Safety, Elsevier, Vol. 101, 102296.

10.1016/j.strusafe.2022.102296
27

Lieu, Q.X., Nguyen, K.T., Dang, K.D., Lee, S., Kang, J., and Lee, J. (2022). “An adaptive surrogate model to structural reliability analysis using deep neural network.” Expert Systems with Applications, Elsevier, Vol. 189, 116104.

10.1016/j.eswa.2021.116104
28

Liu, T., and Meidani, H. (2024). “Graph neural network surrogate for seismic reliability analysis of highway bridge systems.” Journal of Infrastructure Systems, ASCE, Vol. 30, No. 4, 05024004.

10.1061/JITSE4.ISENG-2264
29

Ministry of Agriculture, Food and Rural Affairs (MAFRA). (2007). Notification on the designation of disaster-resilient standards for horticultural and special crop facilities (Notification No. 2007-55), accessed 20 August 2025, <https://www.law.go.kr/LSW/admRulLsInfoP.do?admRulSeq=2100000214838>.

30

Ministry of the Interior and Safety (MOIS). (2024a). 2023 disaster report.

31

Ministry of the Interior and Safety (MOIS). (2024b). Flood and earthquake disaster insurance Act (Act No. 20378), accessed 20 August 2025, <https://www.law.go.kr/LSW/lsInfoP.do?urlMode=lsInfoP&lsId=010168#0000>.

32

Ren, J., Wang, J., Guo, S., Li, X., Zheng, K., and Zhao, Z. (2019). “Finite element analysis of the static properties and stability of a large-span plastic greenhouse.” Computers and Electronics in Agriculture, Elsevier, Vol. 165, 104957.

10.1016/j.compag.2019.104957
33

Rural Development Administration (RDA). (2017). Greenhouse structural design standards (draft).

34

Ryu, H.R., Lee, E.H., Cho, M.W., Yu, I.H., and Kim, Y.C. (2012). “Evaluation on the behavioral characteristics of plastic greenhouse by full-scale testing and finite element analysis.” Journal of Bio-Environment Control, KSBEC, Vol. 21, No. 4, pp. 459-465.

10.12791/KSBEC.2012.21.4.459
35

Seo, B.H., Lee, S.I., Lee, J.H., Kim, D.S., Kim, D.W., Cho, Y.R., Kim, Y.Y., Lee, J.M., and Choi, W. (2024). “Structural shape estimation based on 3D LiDAR scanning method for on-site safety diagnostic of plastic greenhouse.” Journal of the Korean Society of Agricultural Engineers, KSAE, Vol. 66, No. 5, pp. 1-13.

36

Suh, W.M., Choi, M.K., Bae, Y.H., Lee, J.W., and Yoon, Y.C. (2008). “Structural safety analysis of a modified 1-2W type greenhouse enhanced for culturing paprika.” Journal of Bio-Environment Control, KSBEC, Vol. 17, No. 3, pp. 197-203.

37

Xu, H., and Rahman, S. (2005). “Decomposition methods for structural reliability analysis.” Probabilistic Engineering Mechanics, Elsevier, Vol. 20, No. 3, pp. 239-250.

10.1016/j.probengmech.2005.05.005
38

Zhang, L., Lu, Z., and Wang, P. (2015). “Efficient structural reliability analysis method based on advanced Kriging model.” Applied Mathematical Modelling, Elsevier, Vol. 39, No. 2, pp. 781-793.

10.1016/j.apm.2014.07.008
39

Zhao, Y.G., and Ono, T. (2001). “Moment methods for structural reliability.” Structural Safety, Elsevier, Vol. 23, No. 1, pp. 47-75.

10.1016/S0167-4730(00)00027-8
40

Zhou, X., Qiang, S., Peng, Y., and Gu, M. (2016). “Wind tunnel test on responses of a lightweight roof structure under joint action of wind and snow loads.” Cold Regions Science and Technology, Elsevier, Vol. 132, pp. 19-32.

10.1016/j.coldregions.2016.09.011
Information
  • Publisher :KOREA WATER RESOURECES ASSOCIATION
  • Publisher(Ko) :한국수자원학회
  • Journal Title :Journal of Korea Water Resources Association
  • Journal Title(Ko) :한국수자원학회 논문집
  • Volume : 58
  • No :11
  • Pages :1141-1151
  • Received Date : 2025-08-20
  • Accepted Date : 2025-09-24
  • DOI :https://doi.org/10.3741/JKWRA.2025.58.S-1.1141
Journal Informaiton Journal of Korea Water Resources Association Journal of Korea Water Resources Association
Online Submission
Archives
  • scopus
  • KCI-수자원
  • NRF
  • KOFST
  • KISTI Current Status
  • KISTI Cited-by
  • crosscheck
  • orcid
  • open access
  • ccl
Journal Informaiton Journal Informaiton - close