Ninth International Conference on Permafrost ... - IARC Research

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The Account of Long-Term Air Temperature Changes for Building Design inPermafrostI.V. DavidovaThe Moscow State University, The Faculty of Geology, 119992, GSP-2, Moscow, Lenin Mountains, RussiaL.N. KhroustalevThe Moscow State University, The Faculty of Geology, 119992, GSP-2, Moscow, Lenin Mountains, RussiaIntroductionOne of the main parameters defining permafrost-bearingcapacity as a base of buildings is their temperature dependingon air temperature. According to meteorological supervision,it is established that air temperature increase becamepractically appreciable since 1970, and it is expected that, tothe middle of the 21st century, increase of mean annual airtemperature will reach from 1.5 to 7.0°С.A rise in soil and air temperature leads to an increaseof rated building base temperature, which defines ratedresistance of frozen ground. Knowing rated resistancedecrease during the time, it is possible to plan engineeringactions which will provide necessary bearing capacity of thebuilding under condition of climate warming. On a designstage the main action is the increase of supporting structureof foundation, that is, increase of reliability factor. Thusthe problem is divided into three interconnected problems:the forecast of mean annual air temperature, the forecast ofground temperature, and the definition of reliability factor.The Forecast of Mean Annual Air andPermafrost TemperatureLaws of long-term changes of mean annual air temperaturewere established by the method of autoretrospective analysisof meteorological supervision series. The method is based onharmonious decomposition of time series and considers cyclic,trend, and casual changes in meteorological series. In detail themethod is described in the work of Khroustalev et al. (2000).Received forecast air temperatures were used formodeling of temperature ground conditions. For the forecastof permafrost temperature, a numerical method—the finaldifference method—was used. The mathematical model ofpermafrost evolution was the Stefan problem. Calculationswere carried out in the program “Warm,” developed on theGeocryological Faculty of the Geological Department ofthe Moscow State University (Khruostalev et al. 1994). Themathematical model has been realized by us for 10 settlementslocated in Sakha-Yakutia Republic (6 items) and in WesternSiberia (4 items).Obtained data have been estimated by us from a positionof the reliability theory.Reliability Estimation of the BuildingFoundations in PermafrostAt first we defined a cost optimum reliability of the baseswithout taking into account climatic changes, taking as thebase data from the boundary year (standard reliability).The analytical calculation method for optimum reliabilityof the building foundations when construction is built withprinciple I (we consider only this case in the report) has beendeveloped by Pustovoit (Khrustalev & Pustovoit 1988). Itsbasis is minimization of the total expenses consisting ofthe building initial cost (C 0) and expenses connected withpossible damage before the termination of the operation life(C R).Except for optimum reliability, another important parameteris the optimum factor of reliability (K H,0), which correspondsto optimum reliability.The factor of reliability allows the connection of twodetermined approaches which are put in a basis of normativedocuments and developed by us as probability-statistical.This factor depends on many parameters: climatic,geological, constructive, and economic. Therefore, it cannotbe appointed directly, but should be calculated separately foreach area.The calculated result of optimum reliability and reliabilityfactors for the residential building bases in 10 areas allowthe following conclusions to be drawn:Optimum reliability increases, and optimum reliabilityfactor decreases when air temperature decreases andfoundation depth increases. These changes occur in intervalP(te) = 0.747 - 0.998 and K H,0= 1.1 - 2.5.Casual fluctuations of mean annual air temperatureinfluence the optimum reliability and optimum reliabilityfactor. When air temperature fluctuation increases, theoptimum reliability decreases and the optimum reliabilityfactor increases. For example, at practically identical airtemperature in areas of Chekurdah (σ = 1.3) and Tiksi (σ= 1.86), in the first case optimum reliability is above, andoptimum reliability factor is below, than in the second.Greater building cost (smaller value of economic factor)should correspond to greater base reliability and greateroptimum reliability factor. Unfortunately, this trivialconclusion does not find reflection in operating normativedocuments.After definition of optimum values of reliability andreliability factor, the forecast of the base reliability for aresidential building on the pile foundation for the nearest 50years has been executed, considering variability of air andground temperatures and depth of seasonal thawing duringthe time.For Nadym city, the optimum value of reliability factor is1.697, if long-term changes of air temperature do not occur(a modeling problem), function of reliability changes a little,59
Ni n t h In t e r n at i o n a l Co n f e r e n c e o n Pe r m a f r o s tTable 1. Recommended values of reliability and reliability factor for residential buildings during the period 2000–2050.Area T air, °C g, °C/year l=6m l=8m l=12mP(t e) K HP(t e) K HP(t e) K HYakutiaChekurdah -11.1 0.01 0.992 1.214 0.996 1.16 0.998 1.104Tiksi -10.7 0.02 0.984 1.411 0.990 1.301 0.995 1.190Verhoyansk -7.3 0.033 0.986 1.263 0.991 1.198 0.996 1.129Ust-Maya -4.0 0.042 0.913 1.403 0.923 1.316 0.943 1.214Mirniy -3.4 0.031 0.746 1.183 0.773 1.646 0.804 1.436Tuoy-Haya -2.8 0.032 0.949 1.549 0.958 1.451 0.966 1.319Western SiberiaBeliy island -8.6 0.006 0.983 1.344 0.989 1.255 0.995 1.165Salehard -2.02 0.02 0.727 2.222 0.777 1.892 0.824 1.581Nadim -1.64 0.017 0.73 2.62 0.79 2.21 0.849 1.823Poluy -0.56 0.013 0.63 3.96 0.767 2.99 0.878 2.21and reliability remains high enough. In a real case, reliabilityintensively tends to zero, reaching value 0.08 at the end ofoperation. This means that the building will be destroyedbefore the termination of operation period with probabilityof 92%. At reliability factor K H= 2.62, the reliability at theinitial stage surpasses reliability of the modeling problem,and then decreases to 0.73. Thus the material damage causedby reliability decrease remains the same as in case of themodeling problem.Values of reliability P(t e) and the factor of reliability K Hfor all 10 considered areas have similarly been calculated(Table 1).ReferencesKhroustalev, L.N., Emeljanov, N.V., Pustovojt, G.P. &Jakovlev, S.V. 1994. The Calculation Program ofThermal Interaction of Engineering Constructionswith Permafrost. The Certificate 940281. RosAPO.Khroustalev, L.N. & Pustovoit, G.P. 1988. Calculations ofthe building bases in permafrost. Novosibirsk: theScience. 253 pp.Khroustalev, L.N., Medvedev, A.V. & Pustovoit, G.P. 2000.Long-term change of air temperature and constructionstability projected in permafrost area. Cryosphere ofthe Earth IV(3): 35-41.Pavlov, A.V., Ananev, G.V & Drozdov, D.S. 2002. Monitoringof seasonal thawing layer and temperature of frozenground in the north of Russia. Cryosphere of theEarth VI(4): 30-39.Pavlov, A.V. 2003. Permafrost and climatic change in thenorth of Russia: supervision, forecast. Proceedings ofthe Russian Academy of Sciences 6: 39-50.Pustovoit, G.P. 1997. The account of climate variabilityat maintenance of construction base reliability inpermafrost area. Cryosphere of the Earth I(4) :50-53.SNiP 2.02.04-88. 1990 The Bases and the Foundations inPermafrost. Moscow: Stroyizdat, 53 pp.60
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ContentsPreface ...................
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Mapping and Modeling the Distributi
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Satellite Observations of Frozen Gr
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xiiIce Wedge Thermal Regime in Nort
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xivPermafrost Response to Dynamics
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NICOP SponsorsUniversitiesUniversit
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Deep Permafrost Studies at the Lupi
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Effect of Fire on Pond Dynamics in
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Cryological Status of Russian Soils
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Acoustical Surveys of Methane Plume
Page 30 and 31: Permafrost Delineation Near Fairban
Page 32 and 33: Preparatory Work for a Permanent Ge
Page 34 and 35: A Provisional Soil Map of the Trans
Page 36 and 37: Martian Permafrost Depths from Orbi
Page 38 and 39: Time Series Analyses of Active Micr
Page 40 and 41: Impact of Permafrost Degradation on
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Page 44 and 45: Modeling Thermal and Moisture Regim
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Page 48 and 49: Alpine Permafrost Distribution at M
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Page 52 and 53: Modeling Potential Climatic Change
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Page 58 and 59: Freeze/Thaw Properties of Tundra So
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