uc science building testbed meeting 16 sep 2002
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UC Science Building Testbed Meeting 16 Sep 2002. Porter, Beck, & Shaikhutdinov. Methodology Overview. Decision Basis. Applies to an operational unit for a given planning period T , location O , and design D Probability of operational failure - PowerPoint PPT PresentationTRANSCRIPT
PPEEEERR
UC Science Building TestbedMeeting 16 Sep 2002
Porter, Beck, & Shaikhutdinov
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Methodology Overview
hazard model
p[IM|O,D]
site hazard
p[IM]
IM: intensitymeasure
facility def.
O, Ddecision
O, D OK?
Hazardanalysis
Structuralanalysis
struct’l model
p[EDP|IM]
structuralresponse
p[EDP]
EDP: eng'ingdemand param.
O: LocationD: Design
Damageanalysis
fragility fns
p[DM|EDP]
damage
p[DM]
DM: damagemeasure
Lossanalysis
loss model
p[DV|DM]
performance
p[DV]
DV: decisionvariable
"Whatengineering
demands (force,deformation,etc.) will this
facilityexperience?"
"How likely is anevent of
intensity IM, forthis location and
design?"
"What physicaldamage will
facilityexperience?"
"What loss(economic,
casualty, etc.)will this facilityexperience?"
"What are myoptions for thefacility locationand design?"
"Are thelocation and
designacceptable?"
PEER PBEE ANALYSIS METHODOLOGY
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Decision Basis
• Applies to an operational unit for a given planning period T, location O, and design D
• Probability of operational failure– Operational failure occurs if any component that is
critical for operations fails
• Probability of life-safety failure– Life-safety failure occurs if any component that is
critical for operations fails
• Probability distribution of repair cost• Probability distribution of repair duration
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Decision Variables
• Applies to an operational unit• DVO: binary RV for operational state
= 1 operational failure• DVL: binary RV for life-safety state
= 1 life-safety failure• CR = repair cost, a scalar RV• DR = repair duration, a scalar RV• Goal:
P[DVO=1 | T, O, D]P[DVL=1 | T, O, D]FCR|T,O,D(cr|t,o,d) – a CDF of repair cost given T,O,DFDR|T,O,D(dr|t,o,d)
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Damage Measures
• Applies to a component• DMR,i: binary RV for component i requiring repair or replacement
– DMR,i = 1 component requires repair or replacement– Assume repair or replacement required if:
• Overturns (including sliding off bench or shelf)• Impact sufficient to damage items• Stored in equipment that overturns
• DMO,i: binary RV for operation-critical-component i operational state– DMO,i = 1 operational failure of component– Operational failure means
• Operation-critical equipment or specimen & DMR,i = 1• Door of refrigerator containing operation-critical specimens opens, or
• DML,i: binary RV indicating component i life-safety state– DML,i = 1 life-safety failure of component – Life-safety failure means
• Life-safety hazard = “D” & overturns (O/T) or • Chemical hazard ≠ “N” & overturns or• Unrestrained weighty object & achieves momentum sufficient to cause trauma• Unrestrained weighty object & displacement is great enough to block egress
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DV|DM for Equipment
• DVO = maxi(DMO,i)
• DVL = maxi(DML,i)
• CR = ΣDMR,iCR,i
– CR,i = uncertain repair or replacement cost, equipment component i. The equation is different for construction.
• DR = Max(DMR,iDR,I)
– DR,i = uncertain repair or replacement time, equipment component i. The equation is different for construction.
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DV|DM for Construction Cost
• CR = (1 + CO&P)jdNj,dCj,d
CR = repair cost
CO&P = overhead & profit, ~U(0.15, 0.20)
j = index of assembly type
d = index of damage state
Nj,d = number of assemblies of type j in state d
Cj,d = unit cost to restore assemblies of type j from state d, ~LN(Cj,d, Cj,d)
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DV|DM for Construction Duration
• TR,m = T0 + jdTj,dNj,d/nj,d + tNtTt
TR,m = time to restore operational unit mT0 = design, contracting, and mobilization timeTj,d = time for one crew to restore one unit of assembly type j from
state d, weeks.nj,d = number of crews availableNt = number of changes of tradeTt = change-of-trade delay, weeks.
• Slow repair: high T0, low nj,d, high Tt, operational units restored in series (trades move from one unit to next)
• Fast repair: low T0, high nj,d, low Tt, operational units restored in parallel
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Assembly DM|EDP Fragility Functions
• Fragility function gives the probability that an undesirable event (“failure”) occurs given input excitation (engineering demand parameter)
• Possible equipment EDP– Peak diaphragm acceleration (PDA) or – Peak diaphragm velocity (PDV) or – Both
• Need P[DML,i|EDPi], P[DMO,i|EDPi]– May depend on P[O/T|EDP], P[URD|EDP] or P[O/T or
URD|EDP]
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Sample Lab
Lab Count Equipt Key
Equipt Name
Mfg Life Safety Haz.
Import. Chem Haz.
Cande 1 J Incubator Percival D Y N Cande 1 K Freezer Coldspot D Y N Cande 1 B Refrigerator Philco D N N Cande 1 G Refrigerator Kenmore D N N Cande 1 L Centrifuge Du Pont… D N N Cande 2 M Refrigerator Kenmore D N N Cande 1 N Refrigerator Fisher Sci D N N Cande 2 E Fume Hood C N CH/A Cande 1 P Fume Hood C N CH/A Cande 1 WS-1-2 Open Shelving A/SL N CH/A Cande 2 WS-3 Open Shelving A/SL N CH/A Cande 2 WS-4 Open Shelving A/SL N CH/A Cande 1 WB-2 Work Bench A N CH/A Cande 1 C Incubator C Y N Cande 1 B Low Temp. Incubator VWR Sci B Y N Cande 1 H Incubator Precision B Y N Cande 1 I CPU Silicon Gr B Y N Cande 1 K Monitor Silicon Gr B Y N Cande 1 M CPU Silicon Gr B Y N Cande 1 N Monitor Silicon Gr B Y N
24 Ct(“D”) = 8 Ct(“Y”) = 9 Ct(“CH/A”) = 9
Makris will provide fragilities from top of list through fume hoods by 1 Dec.Hutchison will provide others. Draft fragilities to be delivered by early to mid-December
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From Overturning and Unrestrained Displacement to Life-Safety and Operational Failure
Life Safety Haz D Import. Y Chem Haz Weighty p[DML,i=1|EDP] p[DMO,i=1|EDP]
0 0 0 0 0 0 0 0 0 1 P[URD|EDP] 0 0 0 1 0 P[O/T|EDP] 0 0 0 1 1 P[O/T or URD|EDP] 0 0 1 0 0 0 P[O/T|EDP] 0 1 0 1 P[URD|EDP] P[O/T|EDP] 0 1 1 0 P[O/T|EDP] P[O/T|EDP] 0 1 1 1 P[O/T or URD|EDP] P[O/T|EDP] 1 0 0 0 P[O/T|EDP] 0 1 0 0 1 P[O/T or URD|EDP] 0 1 0 1 0 P[O/T|EDP] 0 1 0 1 1 P[O/T or URD|EDP] 0 1 1 0 0 P[O/T|EDP] P[O/T|EDP] 1 1 0 1 P[O/T or URD|EDP] P[O/T|EDP] 1 1 1 0 P[O/T|EDP] P[O/T|EDP] 1 1 1 1 P[O/T or URD|EDP] P[O/T|EDP]