Performance based design extreme wind loads on a tall building

PERFORMANCE BASED DESIGN EXTREME WIND LOADS ONA TALL BUILDING

ANURAG JAIN,1* MUKUND SRINIVASAN 1 AND GARY C. HART2

1Hart Consultant Group, 2425 Olympic Blvd., Suite 670E, Santa Monica, CA 90404, U.S.A.2Department of Civil and Environmental Engineering, University of California, Los Angeles, U.S.A.

SUMMARY

This paper presents a procedure for the calculation of wind loads on a proposed 385 ft tall building located instrong wind and mixed strong wind and hurricane wind regions. The procedure for the computation of design windloads uses mixed distribution and Monte Carlo simulation. The results of a probabilistic analysis of hurricane windspeeds are combined with the probability distribution of recorded extreme wind speeds (excluding hurricane data)at the site. A 50-year sample of extreme wind speeds is created and the maximum 50-year wind (from thehurricane and the recorded data) is noted. The simulation is repeated for a large number of samples (>10000) andthe probability distribution of the 50-year wind speed is computed for use in establishing the design wind speedCopyright 2001 John Wiley & Sons, Ltd.

1. INTRODUCTION

The design of tall buildings that are located in sites where both extreme winds and hurricanes, ortyphoons, occur is a topic of special significance. The structural engineering design variable that formsthe basis of modern structural engineering can be denoted byW, which is defined to be the maximumwind load that the structural system of a building will experience in the design life of the building. Thedefault design life, which represents the exposure time for the building, is typically taken as 50 years.A performance based wind design then identifies different wind hazard levels consistent with differentrisk levels. Table I provides an example of these wind hazard levels and the associated derived windreturn periods. Therefore, the structural engineering design objective is to calculate the wind forces forany desired hazard level on the building for this mixed extreme wind and hurricane environment.

The case study building used in this paper is a 30-story steel frame building that is proposed to belocated in downtown San Francisco near the San Francisco–Oakland Bay Bridge. The buildingfootprint is ‘L’ shaped with a rectangular tower rising over the base. The building was studied in aboundary layer wind tunnel to determine the wind induced floor loads for designing the structuralframe, and the wind induced pressures for designing glass and cladding. Wind forces and twistingmoments on the building and wind flow around the building were determined from a 1:304�8 scalemodel in a boundary layer wind tunnel. The model included the 30-story building and an area coveringnine city blocks around it. The historical wind speed data for the building site was obtained from theNational Climatic Data Center (NCDC) weather station at San Francisco International Airport. Thedynamic properties of the building for the wind tunnel analysis and other required data were obtained

THE STRUCTURAL DESIGN OF TALL BUILDINGSStruct. Design Tall Build.10, 9–26 (2001)

Copyright 2001 John Wiley & Sons, Ltd. Received July 2000Accepted August 2000

* Correspondence to: Anurag Jain, Hart Consultant Group, 2425 Olympic Blvd., Suite 670E, Santa Monica, CA-90404, USA.

from an ETABS model of the building. The dynamic properties of the building are necessaryfordetermining thevibrationcharacteristicsof theforcebalanceonwhich thebuilding modelis mountedin the wind tunnel.

2. WIND CLIMA TOLOGY AT THE BUILDI NG SITE

Thecasestudybuildingsiteis locatedin downtownSanFrancisco adjacentto San FranciscoBay.Thebayborders thebuildingsiteto theEast. SanBrunoMountainto theNorth risesto aheightof 1300ft.A North–Southtrendingridgeof coastal mountainsto theWestvariesin elevation from 700to 1900ft,beinghighest southward alongthe peninsula.The Pacific Ocean Westof the ridge is about6 milesfrom thebuildingsite.A broadgapto theNorthwest between theSanBrunoMountain andthecoastalmountains,allows a strongflow of marineair over theareaanddominatesthe local climate.The SanFrancisco Bay areaexperiencesa marine-type climate characterized by mild and moderately wetwintersandby dry, cool summers.

For this wind study, historical extremewind speeddatawerecollectedfrom theNationalWeatherService(NWS) stationat the SanFrancisco InternationalAirport. The datawereobtained from theNCDCin Asheville, NorthCarolina.Datafrom 1960to 1997,atotalof 38yearsof monthly maximumwind speeds,wereusedin the statisticalanalysis.

3. TOPOGRAPHIC EFFECTS

Topographiceffectsareavery importantcomponentof anywind study.Thetopography of theterrainaffectsthewind speedandcausesthewind to dragon thegroundto a lesseror greaterextent.This inturn affects thewind speedprofile andhencetheforceson thebuilding subjectedto wind forces.Thetopographyof asitecanbeexpressedin termsof aroughnesslength z0. Thelargertheroughnesslengthz0, the morepronouncedis the effect of the terrain on the wind velocity profile. Consequently, thesmoothopenseahasthe smallestroughnesslengthsandvery largevaluesof roughnesslengths arefound in thecentersof largecities.TableII showsa setof typical valuesfor roughnesslengthsfromSimiu andScanlan (1996).

The wind tunnel model includes the effects of the immediate buildingsaround the building site.What needsto be quantified is the averagetopographyof the areaaround the building site. This isaccomplishedby visually defining thetopography in thegeneralvicinity of thesitewith theaidof sitevisits andphotographs.The sitephotographsarecomparedwith standard photographic definitionsforroughnesslength, e.g.Cook(1985).This processof defining thebuilding site topography is repeatedfor thewind speeddatacollectionsiteatSan FranciscoAi rport.Thevaluesof theroughnesslengthsinthe eight principal directionsdefinethe building site topography. The topographyandsurroundingsvaryby compassdirection.Thesiteroughnesslength z0 for eachof theeightdirectionsat thebuildingsite andthe NCDC weatherstationat SanFrancisco Ai rport arelisted in TableIII.

TableI. Wind hazardlevelsandassociatedreturnperiods

Wind speedhavingprobability of exceedance Meanreturnperiod(years)

64%in 50 years 5050%in 50 years 7210%in 50 years 4752% in 50 years 2475

10 A. JAIN, M. SRINIVASAN AND G. C. HART

Copyright 2001JohnWiley & Sons,Ltd. Struct.DesignTall Build. 10, 9–26(2001)

4. WIND SPEEDDATA ANALYSIS PROCEDURE

Themost valuablesourceof informationin theestimationof futurewind speedsat thebuildingsiteisthehistorical windspeeddatathathasbeenrecordedat thebuilding siteor at anearbyNWSsitesuchas SanFrancisco InternationalAirport. Historical wind speeddata provide information about thestatistical behaviorof wind speedsandareusedextensively to predict the maximumexpectedwindspeeds during the designli fe of the building. For mostbuildings,the designlife is 50 yearsandthewind speedsin the1997Uniform Building Code(U.B.C.1997) reflectthis.Historicalwind speeddataarestudiedin termsof directionaswell asmagnitude.Thedirectionality of historical wind speeds isusually a functionof thephenomenageneratingthesewindsor of specialtopographical features.Suchinformationmay beusedto the advantageof the building in certain cases.

Thewind speedenvironmentat thesiteis characterized by wind speedrecordsthatarecollectedbyanNWSstationor areliablerecordingsitethatis closeenoughto thebuildingsite.Theprocedureusedto characterizethewind speedenvironmentat thebuildingsiteis shown in Figure1. Thewindspeedsfrom the weatherstation are collected in a database. The dataobtained includes the wind speed,direction, averaging time, height of therecording instrumentandotherrelevant information.Thedatais thengroupedby direction. For example,all of thewindscomingfrom thenorthareidentified andseparatedinto onegroup.This is donefor the eight principal directions.

Following this grouping, thelocal environmentat,aswell asupwindfrom theweather stationmustbe characterized. This characterization is throughthe determination of the surfaceroughnessat thebuildingsiteandtheweather stationsiteasdiscussed earlier.Theprocedureconvertsall thehistorical

TableII. Typical valuesof surfaceroughnesslengths

Typeof surface Roughnesslength(cm)

Seasurface 0�0003–0�5Snowsurface 0�1–0�6Mown grass 0�1–1Fallow field 2High grass 4–10Pineforest 90–100Suburbs 20–40

Town center 80–120

TableIII. Surfaceroughnesslengths

Roughnesslength(cm)

Direction Building site SanFranciscoAirport

N 51 7NE 16 7E 28 7

SE 65 7S 80 7

SW 80 7W 80 7

NW 80 7

EXTREME WIND LOADS DESIGN 11


wind speeddatarecordedat theNWSstationinto datacorrespondingto a referenceexposure referredto asan‘opencountry exposure’, whichcorrespondsto asurfaceroughnesslengthof 5–10cm.All thedatais converted to a referenceheightof 10m.

For example,a wind speedmeasuredat the NWS stationwould be converted to a referencewindspeedusing equation (1).

VREF� VNWS

ln HREFZO;OC

ln HANEZO;NWS

ZO;OC

ZO;NWS

" #0?0706

�1�

whereHREF is thereferenceheight(10m), zo,OCis theopencountryroughnesslength(7 cm),HANE isthehistorical anemometerheightat thetimethedata, VNWS, wasrecorded,andzo,NWSis theroughnesslength at the NWS station for the direction from which VNWS was recorded. This equation is arepresentationof the logarithmic profile, with thesimilarity law usedto convert from oneroughness

Figure1. Wind speeddataanalysisprocedure



length to another.After performing thesesteps, it is possible to infer from the historical data thefrequencyandmagnitudeof windsfor differentwind directionsat theNWSstationsite.Theexposureat the building site hasbeencharacterizedand a value of surfaceroughnesslength for eachwinddirection hasbeenassigned.

Theseroughnesslengthsarealsousedin thewind tunneltests thatareassociatedwith thisbuilding.Usingtheconverted historical NWSdataandthequantified exposureat thebuildingsitefor eachwinddirection, the frequency andmagnitudeof thehistorical windsthatwould havebeenmeasuredat thebuilding site over the sameperiod of recording as the original NWS datacan be determined. Thebuilding site exposure is incorporated into the datausing an equation similar to equation (1).

Following this procedure, themeanandstandard deviationof thecorrectedwind speeds from eachof theeightdirectionscanbeestimated.This is thenusedto performa statistical analysis to computethe50-yearreturnperioddesignwind speedsfrom eachof theeight directions.These50-year returnperioddesignwind speedsareusedin theWind Tunnelteststo estimatethefloor forcesandglassandcladdingpressures for the building.

Figure2. Distribution of annualmaximumwind speedsby direction

Figure3. Meanannualwind speedsat SanFranciscoAirport



5. EXTREME WIND SPEEDS

Thestatistical wind speedanalysisof theextremewind speedsat thebuilding sitewasperformedusingthe procedures described earlier.The percentagedistribution of the maximumwind speeds from agiven direction at SanFrancisco International Airport is shown in Figure 2. As can be seen,themajority of windsblow from theSouthto theNorthwestdirections, sincetheprimary climatologicalphenomenon in the SanFrancisco areais the seabreeze.The meanwind speedsfrom the differentdirectionsfor SanFranciscoInternationalAirport areshownin Figure3.Thesewind speedshavebeencorrectedto 10m height andanopencountryexposure asdescribed earlier.

Thetenlargestwind speedsrecordedatSanFranciscoInternationalAirport between1960and1997areshownin TableIV. The majority of thesewind speedsoccur from eithertheSouthor Southwestdirectionsandprimarily in thewinter months.This distributionof extremeannualwind speedsis alsoconsistentwith thepatternseenin Figures2 and3. Thestatisticaldistributionof theextremeannualwind speeds for eachgivendirectionat SanFranciscoInternational Airport wasusedto computethe50-year designwind speedswith a hazardlevel correspondingto a 64 percent, annualprobability ofbeingexceededin 50years,or asmorecommonlystated,a ‘50-yearreturnperiod’at thebuildingsite.TableV showsthestatistically computed50-yearreturnperioddesignwind speedsat thebuildingsite.Thesewind speeds were usedin the wind tunnel to measurethe floor forcesandglassandcladdingpressures.

TableIV. Tenlargestwind speedsat SanFranciscoInternationalAirport(3 s gust,10m height,opencountryroughness)

Date Wind speed(mph) Direction

January30, 1963 84�9 SJanuary20, 1964 83�5 S

November5, 1963 77�0 SWFebruary8, 1960 73�8 W

December12, 1995 73�3 SWFebruary16, 1990 73�2 SWJanuary5, 1965 72�9 S

October13, 1962 71�5 SFebruary9, 1962 71�5 SWDecember2, 1966 68�8 S

Table V. 50-year return period designwind speedsbywind directionat building site (3 s gust,10m height)

Direction Designwind speed(mph)

N 62NE 74E 62SE 68S 86SW 86W 74NW 74



6. WIND TUNNEL AND MODEL DESCRIPTION

Wind forcesandtwisting moments on the building were determined in the wind tunnel at the WestWind Laboratory, Inc. in Marina, California. The wind tunnel at the West Wind Laboratory is a3�33� 13�33ft (1� 4 m) openreturntypeatmospheric boundary layer wind tunnel. Wind speeds inthewind tunnel arecontinuously variablefrom 0 to 20 ft sÿ1. Thetestsection is openwithout wallsor aceiling. Ambient pressures within the test chamber are thereforeessentially constant. Furthermore,winds canflow aroundandover the modelswithout constriction (as in the full- scaleenvironment).Therefore,blockageeffectsareminimal, i.e.wind speedswill notbeartificially acceleratedaround themodel becausethereareno walls to constrict andacceleratethe flow.

A 1:304�8 scale model (1 mm: 1 ft) was madeof the casestudy high rise building, and allbuildings in the nine city blocks around it. The aerodynamiceffectsof the buildingsbeyondthoseblocksweremodeled generically with woodenblocksandspiresplacedupstream of thetestsectioninthe wind tunnel. The recommended50-year return period design wind velocities represent theaerodynamiceffectsin a genericsenseof thebuildingsbeyondthis nine-block group.Themodelwastestedin thewind tunnel with andwithout thesurroundingbuildingsto discountanyshieldingeffects.All models weremadeof light-weightmatboard. Themodelof thesubjectbuilding wasarigid modelmounted on a rigid force balance.

7. WIND TUNNEL TESTING RESULTS

The designfloor forcesfor the structural frame were measured in the wind tunnel using the windspeeds from the statistical analysisof the historical wind speeddata. Two setsof floor forcesweremeasured—the first is the building with surrounding buildingsandthe secondset is the building byitself. Theuseof envelopeforcesfrom thesetwo setsof dataensuresthatanyshielding effectsfromadjacent buildings are eliminated and will yield conservative results. For eachfloor level, threeforces—twolateral forcesandtwisting moment—are given.Theresults aregiven in TableVI for thecasewith the surroundingbuildingsandwindsfrom the Southeast.The building footprint andforceconvention for this analysisareshown in Figure4.

The procedureusedto determine instantaneouspeakpressuresfor thedesign of glass andcladdinginvolved the useof surfacemountedpressuretapson the model at a sufficient numberof points todetermine accurately the completepositive (inward) and negative (outward) pressuredistributionsover thebuilding. For eachposition,themodel wasrotateduntil the two wind directionswerefoundfor which positive pressuresandnegativepressures, respectively, werefoundto beextreme.Extremepositive and negative pressures were determined as mean plus (or minus) 4 standard deviationpressures.For design, there is always the possibility of non-zero internal pressures. The designpressurespresentedin this wind studyincludetheASCE7-95(1995)recommendedinternalpressureof �5 psf.For eachelevationof thebuilding,maximum measuredpositive andnegative pressures forthedesignof glassandcladding for thesoutheastelevationof thebuildingareshown in Figures5 and6. All pressures presentedin these figurescan be usedfor tributary areas of any size but may bereduced for larger tributary areas (>20ft2) asperASCE7-95 (1995).

8. CLIMAT OLOGICAL BASIS FORRISK PROFILES

Thedevelopmentof designwind speeds for different locationsin theUS andtheworld hastypicallybeenbaseduponrecordedwind speeddataat certified wind speedrecording stations.As mentionedearlier, currentdesign practice usesthe 50-yearreturn periodwind speedobtained from a statisticalanalysisof dataat thesewind speedstations.Unfortunately, the wind speeds in designcodes(UBC,ASCE7-95)arenot sitespecific andhavea largedegree of uncertainty. Whensignificant uncertainty



Table VI. 50-yearwind designfloor forces—windfrom Southeast(with surroundingbuildings)

Level Fx (kips) Fy (kips) Mz (kip-ft)

30 0�59 3�57 529 4�86 11�50 1928 17�50 20�43 34127 17�19 17�84 34126 16�42 17�22 33025 15�61 16�55 31724 14�77 15�83 30323 13�99 15�15 28922 13�17 14�42 27421 12�26 13�59 25520 11�34 12�74 23619 10�40 11�89 21718 13�15 14�44 42917 12�24 13�73 42116 11�12 12�88 39415 10�03 12�02 36614 8�96 11�17 33813 7�92 10�32 30912 6�88 9�44 27811 5�88 8�59 24810 4�89 7�72 2159 4�52 7�87 2668 3�77 7�09 2337 3�05 6�10 1976 2�39 5�13 1635 1�77 4�16 1284 1�22 3�16 933 0�74 2�13 602 0�31 1�00 28

Figure4. Forceconventionfor floor force tables



exists, structural engineers in the code development processproducecode loads that tend to beconservative. The conservatism is due to the needfor the codesto be prescriptive for a variety oflocationsandconditions.This hasgivenriseto thepracticeof performingasite-specific wind studyformany engineeringdesignbuildings. Site-specific designwind speedstudiestake into account thespecific climatologyof thesiteandtheactualwind speedsrecordedat thesite.Thedesignwind speedsobtained from suchstudiesarethemost accurate estimateof theexpectedwindsat thebuilding site.

Therearecaseswherethestandardprocedures usedin obtainingthedesignwind speedfor a site-specific wind speedstudy sufferfrom deficiencies. Thesedeficienciesarisefrom theexistenceof twoseparate climatologicalphenomenadriving the wind speedsat the building site. The most generalexample of sucha condition is that of building siteson the Atlantic Coastof the United States,theislandsof Hawaii andmany locationsonthePacific Rim. In both thesecases,thereis aprevailing localwind condition (e.g. sea breezes,trade winds) that generally dominates. In addition, there is asecondary wind condition that is not asfrequentsuchashurricanes.The actualrecordeddatafromhurricanesis quitesparseandis seenonwind instrumentrecordingsat thebuildingsiteasanoutlyingdatapoint that barelyaffectsthe computed wind statistics. However, the phenomenological basisofthehurricaneis very different from the local wind condition andreflectsa different risk profile. Thecompletepictureof thewind risk at thebuildingsiteis in realityacompositeprofileof therisk scenariofrom thelocal wind conditionsandthehurricanewind conditions.Thedistribution of thewind speedsatthebuildingsiteis thereforeamixeddistribution (amixtureof thetwo differentrisk profilesfor localwinds andhurricanewinds) andshouldbe treatedaccordingly. The existenceof suchdual extreme

Figure5. Positive(inward)pressures(psf)—southeastelevation



wind phenomenahasbeendocumentedandtreatedin the past.Simiu andScanlan (1996)provide agoodsourceof referencefor studiesof mixed climatologicaldistributions.

Now, thedesignwind speedaccording to ASCE7-95is definedasa 3 s gustwind speedthathasa50-year return period (64 per cent chance of being exceeded in 50 years).It is worth noting thatdesigning for thelocal windsalone is unconservative anddesigning for thehurricanewindsonly maybeanunsatisfactory approacheconomically. The most appropriatetechniquelies in designing for thetrue risk profile of the winds.This paperalsopresents a procedureadopted in computingthe designfloor forces and glass and cladding pressures on the 30-story building described earlier. Threelocationshavebeenchosen to illustrate the extentto which the mixed distribution approachyieldsmorerealistic valuesof the design wind speed.The threelocations represent a basecasewith onlylocal wind climatology (the actualbuilding location in SanFrancisco), a hypothetical casewith adominant local wind climatology and another hypothetical casewith a dominant hurricanewindclimatology.Forall threecases,thelocalwind climatology is heldconstantasthatof SanFrancisco toillustrate the effectsof increasing the ‘mixing’ effectswhen the risk profile is strengthenedby theadditionof a dominant hurricaneclimatology.

The threelocationschosen areasfollows.

(1) BaseCase—Building asis in SanFrancisco. Thedesignwind speedsfor differentreturn periodsat the building site from the southeast directionarelisted in TableVI I.

(2) CaseA—Building in Honolulu, Hawaii. Thedesignwind speedis thesameasin thebasecase.

Figure6. Negative(outward)pressures(psf)—southeastelevation



Additionally, thereis a hurricane risk definedthrougha 50-year returnperiodwind speedof63mph(3 sgustmeasuredat10m abovetheground). TableVI II lists thehurricanedesignwindspeeds for different return periodsin Honolulu. Therisk profile for hurricanesin theHonoluluareawasobtainedfrom the Science Applications InternationalCorporation (SAIC) and theirproprietary HUrricane RISK analysis software HURISK (1998). The hurricane risk forHonolulu is quite low, contrary to popular conceptionsof Hawaii. The predominanthurricanerisk in the Hawaiian Islandsis to Kauai andthe islandof Hawaii andthis hasbeenobservedstatistically.

(3) CaseB—Building is in CapeCanaveral,Florida. Thedesignwind speedis thesameasin thebasecase.Additionally, thereis hurricane risk definedthrough a 50-year return period windspeedof 119mph(3 s gustmeasuredat 10m abovetheground). Hurricanedesignwind speedsat CapeCanaveralfor several return periodsarelisted in TableIX. Therisk profile for theeastcoastof Florida is very high andseveralhurricaneshavestrucktheareain therecentpast.Therisk profile datafor this building site wasalsoobtained from SAIC.

9. MIX ED DISTRIBUTION ANALYSIS

Thefirst stepin theanalysis wasthecomputation of themeanannualwind speedat thebuilding site

Table VII. Base design wind speedsfor performancebaseddesignhazardlevels(3 s gust,10m height)

Meanreturnperiod(years) Designwind speed

50 6872 70

475 742475 80

Table VIII. Designwind speedsfor performancebaseddesignhazardlevels for CaseA (Honolulu, 3 s gust,10m height)

Meanreturnperiod(years) Local wind speed Hurricanewind speed Mixed distributionwind speed

50 68 61 7572 70 75 84

475 74 147 1322475 80 203 213

TableIX. Designwind speedsfor performancebaseddesignhazardlevelsfor CaseB (CapeCanaveral,3 s gust,10m height)

Meanreturnperiod(years) Local wind speed Hurricanewind speed Mixed distributionwind speed

50 68 119 11272 70 129 120

475 74 184 1642475 80 223 218



due to local wind conditions. Recorded wind speeddata were obtained from NCDC and sortedaccording to theprocessshownin Figure 1. All outlying wind speeddata(corresponding to possiblehurricane winds) were removed from the database. From the wind speeddata, a directionallyindependent wind speeddatabasewascreated andthemeanannualwind speedandits coefficient ofvariation for this databasewere computed. For the hurricanerisk profile, datawere obtained fromSAIC in the form of HURISK reportsthat profiled the hurricanewind hazardcurve.

Once the two componentparts of the underlying climatology of eachsite had beenidentifiedthroughtheir statistical distributions,the mixeddistribution wassimulatedasfollows.

(1) Simulatea sequenceof maximum annualwind speeds for 50 years corresponding to the riskprofile of the local windsusingMonte Carlo simulation.

(2) Simulatea sequenceof maximum annualwind speeds for 50 years corresponding to the riskprofile of the hurricanewinds.

(3) For a given year, the maximum annualwind speedis takenasthe maximum of the simulatedlocal wind speedandthe simulatedhurricanewind speed, whichever is the greater.

(4) From the simulatedsamples, computethe 50-year wind speed(i.e. the maximum of the 50annualwind speeds)

(5) Repeatthe processin steps (1) to (4) 10000 times.(6) From the 10000 datapointsof 50-year wind speeds, computethe design50 yearwind speed

corresponding to the mixed distribution.

Figure7 showsone50-year sampleof thesimulatedwind speeds for thelocal andhurricanewindsfor CaseA. One sampleof 50-yearsimulatedwind speeds for CaseB is shown in Figure 8. Theprobability distribution functionfor therandom variable ‘maximum50-yearwind speed’for CaseA is

Figure7. One50-yearsampleof simulationwind speedsfor CaseA (Honolulu)



shown in Figure9. As canbeseen,themixedprobability distribution function is acombinationof thedistribution functions for the local andhurricane winds.The relative contribution of the local windspeedrisk profile is significant here due to its dominance of the risk profile. The probabilitydistribution functionfor thesimulatedwind speedsfor CaseB is shown in Figure 10. In this case, the

Figure8. One50-yearsampleof simulationwind speedsfor CaseB (CapeCanaveral)

Figure 9. Probability distribution function for the maximum wind speedin 50-yeardesign life for CaseA



Figure10.Probabilitydistributionfunctionfor themaximumwind speedin 50-yeardesignlife for CaseB (CapeCanaveral)

Figure11. Positive(inward)pressures(psf)—southeastelevation(CaseA)



high risk from the hurricanewindscausesthe mixed distribution risk profile to be dominatedby thehurricanewind risk profile.

10. DESIGN WIND SPEEDS

TableVII givesthedesign wind speedsfor the four performancebaseddesignhazard levels given inTableI. The wind speedsin TableVII arederivedfrom thestatistical analysisof local extreme windspeeddataat thebuildingsiteonly.Theeffectof theinclusionof themixeddistribution analysisonthedesign wind speeds for CasesA and B can be best understood through Tables VI II and IX,respectively.

Variations in local wind speedover different return periodsare smallercomparedwith those ofhurricane wind speeds. The wide range of hurricanewind speedsis due to the uncertainty inquantifying thesewind speedsandthelack of relevant data.It is notedfrom TableVI II andIX thatasthereturnperiod increasesthemixeddistribution wind speedsarecompletelydominatedby hurricanewind speeds. Thereareseveralother pointsworth noting from the results in TablesVIII andIX.

CaseA illustratesthefallacy of usingonly the local windsto computethedesign wind speed. The50-year returnperiodwind speedfrom themixeddistribution (75mph) is 10 percenthigher thanthe

Table X. 50-Yearwind designfloor forces—windfrom Southeast(CaseA)

Floor Fx (kips) Fy (kips) Mz (kip ft)

30 0�68 4�11 5�7629 5�60 13�25 21�9028 20�17 23�55 393�0027 19�81 20�56 393�0026 18�92 19�85 380�3325 17�99 19�07 365�3424 17�02 18�24 349�2123 16�12 17�46 333�0722 15�18 16�62 315�7921 14�13 15�66 293�8920 13�07 14�68 271�9919 11�99 13�70 250�0918 15�16 16�64 494�4217 14�11 15�82 485�2016 12�82 14�84 454�0915 11�56 13�85 421�8214 10�33 12�87 389�5513 9�13 11�89 356�1212 7�93 10�88 320�4011 6�78 9�90 285�8210 5�64 8�90 247�799 5�21 9�07 306�578 4�34 8�17 268�537 3�52 7�03 227�046 2�75 5�91 187�865 2�04 4�79 147�524 1�41 3�64 107�183 0�85 2�45 69�152 0�36 1�15 32�27



wind speedfrom localwindsonly (68mph)resulting in a21percentaverageincreasein theforcesonthebuilding andtheglassandcladding pressures.This is seenin Figure11 for positivepressures.Thebuildingfloor forcesfor the50-year returnperiodmixeddistribution wind speedfor CaseA arelistedin TableX.

CaseB illustratesthestronginfluenceof thehurricanewind risk profile on themixeddistribution.While this maybe intuitive, it is worth noting that the50-yeardesignwind speedof 112mph is stilllessthanthecodeprescribedvalues.A sitespecificwind study thereforestill haseconomic benefits tothebuildingowner.Themodifiedpositive glassandcladding pressureonthesoutheast elevationof thebuilding for CaseB is shown in Figure 12. The revisedfloor forceson the building for the mixeddistribution wind speedsfor CaseB aregiven in Table XI.

For bothCaseA andCaseB, theuseof only local wind speeddatato computethe50-yeardesignwind speedas part of a site-specific wind study will yield erroneousresults (the degree of errorcorresponding to the hurricanerisk profile dominance).

The aim of any performance baseddesign procedure is to achieve a design that haspredictableperformance for a specifiedlevel of loading. The designlife and performance criteria, e.g. wind-inducedmotion perception, drift limits, etc., areeithercodemandateddepending ontheimportanceofthe structure or more stringentlevels that may sometimes be required by the building owner. Theestablishment of mixed distribution wind speeds for different return periods will assist in thedevelopment of performancelevels that arewithin prescribedlimits.

Figure12. Positive(intward)pressures(psf)—southeastelevation(CaseB)



CONCLUSIONS

Theresults for awind tunnelstudyto measurethefloor forcesandglassandcladding pressureona30-storybuildingsitedin SanFranciscoarepresented.It wasrealizedthatcodebaseddesignwind speedscanoften leadto conservative estimatesof wind-induced forceson structuressincethey encompassbroadregionsof thecountry.Performingasite-specificdesignwind speedinvestigationcanoftenleadto cost savingsfor the building owner.The probability basedmethodology usedto determine site-specific performancebaseddesignwind speedsfor usein wind tunnelmeasurementsis described.Thestandard procedure for site-specific wind speeddetermination can be deficient for hurricaneproneregions.A MonteCarloprocedureto performaprobability basedsite-specific wind study in hurricaneprone regionsof the United Statesto compute a mixed distribution designwind speedwas alsodiscussed.The impactof these mixeddistribution designwind speedson thewind-inducedforcesonthe same 30-story building were studied to demonstrate the variation produced by inclusion ofhurricanewind speeddatain the analysis. This wasstudied for two regions,onewhere local windphenomenadominatethe climatology and the other for which hurricane windsdominate.Buildingperformancelimit s are code basedand are often dictated by the importance of the structure.

Table XI. 50 year wind designfloor forces—windfrom southeast(CaseB)

Floor Fx (kips) Fy (kips) Mz (kip ft)

30 1�60 9�68 13�5629 13�18 31�20 51�5428 47�47 55�42 925�0727 46�63 48�40 925�0726 44�54 46�71 895�2225 42�35 44�90 859�9624 40�07 42�94 821�9823 37�95 41�10 784�0022 35�73 39�12 743�3121 33�26 36�87 691�7620 30�76 34�56 640�2219 28�21 32�26 588�6818 35�67 39�17 1163�7917 33�20 37�25 1142�0916 30�17 34�94 1068�8415 27�21 32�61 992�8914 24�31 30�30 916�9313 21�49 28�00 838�2612 18�66 25�61 754�1611 15�95 23�30 672�7810 13�27 20�94 583�259 12�26 21�35 721�618 10�23 19�23 632�087 8�27 16�55 534�426 6�48 13�92 442�195 4�80 11�29 347�244 3�31 8�57 252�293 2�01 5�78 162�772 0�84 2�71 75�96



Knowledgeof the probability basedmixed distribution wind speeds for differentreturnperiodswillhelp to establish theperformance levelsa particular structural systemwill conformto andwill assistdesginers to achieveprescribedperformance objectives.

REFERENCES

ASCE Standard,AmericanSocietyof Civil Engineers.1995.Minimum DesignLoadsfor Buildings andOtherStructures,ASCE7–95.AmericanSocietyof Civil Engineers.New York.CookNJ.1985.Thedesigner’sguideto wind loadingof building structures,Part1 andPart2, Building ResearchEstablishmentReport,Butterworths,London.NeumannC. 1998. Tropical cyclone occurrencein the Hawaiian Islandswith focus on Honolulu. ScienceApplicationsInternationalCorporation(SAIC), December.Simiu E, ScanlanRH. 1996.WindEffectson Structures, 3rd edn.Wiley: New York.



Performance based design extreme wind loads on a tall building

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