DETERMINATION OF FREQUENT VALUE AND QUASI-PERMANENT VALUE OF FLOOR LIVE LOAD AND WIND LOAD

Feng Yunfen; Gong Jinxin; Wang Jianchao

doi:10.13204/j.gyjz201207010

Volume 42 Issue 7

Dec. 2014

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Xie Qiang, Zhao Liang. DAMAGE IDENTIFICATION OF FRAME STRUCTURES BASED ON MODAL SENSITIVITY ANALYSIS——NUMERICAL SIMULATION AND TEST VERIFICATION[J]. INDUSTRIAL CONSTRUCTION, 2005, 35(12): 94-96. doi: 10.13204/j.gyjz200512026

Citation:

Feng Yunfen, Gong Jinxin, Wang Jianchao. DETERMINATION OF FREQUENT VALUE AND QUASI-PERMANENT VALUE OF FLOOR LIVE LOAD AND WIND LOAD[J]. INDUSTRIAL CONSTRUCTION, 2012, 42(7): 74-78. doi: 10.13204/j.gyjz201207010

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DETERMINATION OF FREQUENT VALUE AND QUASI-PERMANENT VALUE OF FLOOR LIVE LOAD AND WIND LOAD

doi: 10.13204/j.gyjz201207010

1.
1. Department of Civil Engineering,Dalian University of Technology,Dalian 116024,China;
2.
2. College of Water Conservancy,Shenyang Agricultural University,Shenyang 110866,China

Received Date: 2012-04-29
Publish Date: 2012-07-20

Abstract

Abstract

The factor of frequent value and quasi-permanent value given in the current load codes were determined onthe basis of engineering judgment rather than statistical definition. By establishing the relationships between the ratioof mean time of exceedance to design reference period and the factor of frequent value and quasi-permanent value, thefactor of frequent value and quasi-permanent value for live load and wind load on floor were determind. It was shownthat the factors of the frequent value and the quasi-permanent value for live loads on floor determined in this paper arelarger and smaller than those given in current codes, respectively, and the factor of the frequent value for wind loaddetermined was slightly larger than that provided in current codes.
- building structure,
- load,
- frequent value,
- quasi-permanent value

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References(10)

References

建筑结构安全度研究组.建筑结构安全度与设计准则概述[J].工业建筑,1978,8(4):49-54.

[2] ACI 318-08.Building code requirements for structural concrete[S].

[3] AISI-2001.North American Specification for the Design of cold-formed steel structural members[S].

[4] AASHTO LRFD.Bridge design specifications and commentary.Wshington,D.C.:American Association of State HighwayTransportation Officials,2007.

[5] EN1990:2002.Eurocode Basis of structure design[S].

[6] CSA.National code of building structures[S].

[7] GB50153-2008工程结构可靠度设计统一标准[S].

[8] 林忠民.办公楼与住宅楼面活荷载的统计分析[J].工业建筑,1982,12(1):59-61.

[9] 高虎,刘薇等.中国风资源测量和评估实务[M].北京:化学工业出版社,2008:92-95.

[10] 罗乃东.基于可靠度的高层、高耸结构抗风分析[D].大连:大连理工大学,2002.

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