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Working Paper E Relationships of Ground Motion, Damage, end toss Although in actual practice the steps in a loss estimation study do not necessarily proceed sequentially, the previously discussed tasks of seismic hazard analysis (Working Paper C) and inventory (Work- ing Paper D) are conceptually the two steps that precede the process of relating the ground motion or ground failure to a given construc- tion class to estimate damage. This paper also discusses relating damage to property low, casualties, or functional loss. The discus- sion here is limited to the eEects of ground shaking on buildings and lifelines; the effects of ground failures are treated in Working Paper G. Material presented in the two earlier working papers is directly applicable here. Working Paper C discussed the limitations of the Modified Mercalli Intensity (MMI) scale and other problems in the accurate definition of the ground motion to which the inventory should be subjected in the motion-damage analysis step. Working Paper D explained that the construction classification system is a part of both the inventory process and the motion-damage analysis step because the inventory information must be collected with the same construction classes used in relating the seismic hazard to construction classes through motion-damage relationships. Many methods of relating ground motion, or less commonly ground failures, to damage have been proposed or developed. How- ever, in the context of large-scale, general-purpose loss estimation 159
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160 studies the number of basic approaches is relatively small. In this paper, three particular methods are discussed because they bring out different aspects of the possible ways to approach this problem of relating motion, damage, and loss. The loss estimation method referred to here and elsewhere in this report as the NOAA-USGS method is also, in terms of the motion-damage analysis step, essentially the Insurance Services Of- fice (ISO) method. As explained earlier, this method was used In the first large-scale studies produced by the National Oceanic and Atmo- spheric Administration (NOAA) and later, with essentially the same personnel, by the U.S. Geological Survey (USGS) when NOAA's earthquake loss estimation functions were shifted to USGS. This method has been molded by the work of AIgermissen, Stein- brugge, and others. The studies of San Francisco (AIgermissen et al., 1972), Los Angeles (AIgermissen et al., 1973), Puget Sound (Hopper et al., 1975), and Salt Lake City (Rogers et al., 1976) are examples of the use of this method. It is the method that has been applied in most of the urban- or regional-scale studies of the type focused on in this report (studies intended for disaster planning and hazard reduction purposes). It is also the method that has been most widely used in the prop- erty insurance industry. The NOAA-USGS or ISO method produces damage estimates in the form of mean damage ratios for each con- struction class percentages associated with each MMI level indicat- ing the average property loss In terms of cost of repair or replacement divided by replacement cost. In the NOAA-USGS method, lifelines and nonbuilding structures are analyzed by different methods than the mean damage approach applied to buildings. The ATC-13/FEMA approach was produced by the Applied Technology Council and funded by FEMA (Applied Technology Council, 1985~. While it has yet to be carried out in a loss study resulting in a published report of the type produced for several re- gions of the country by the NOAA-USGS method, it is a recent, comprehensive effort that involved many experts and it surveyed and evaluated a broad range of analysis methods and data. The ATC-13 method uses the format of the damage probability matrix to present its damage estimates for each MMI level: the percentage of facilities that wouic] fall into each of seven damage levels is given for each construction class (with these damage levels described verbally, with property damage ratio ranges, and with central damage ratios). For each MMI, the distribution of damage
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161 for a construction class can also be converted into an overall damage ratio. In the ATC-13 method, lifelines and nonbuilding structures are essentially handled with damage probability matrices the same way as for buildings. A third basic method to be discussed is the application of fragility curves to the task of estimating regional-scale earthquake losses. The Central U.S.-Six Cities study (ABen and Hoshall et al., 1985) used this approach. The motion-damage portion of this study's method, the development of fragility curves based on a combination of em- pirical or historical data and theoretical calculations, was developed by Jack Benjamun and Associates, Inc. (Kircher and McCann, 1984) and is occasionally referred to as the lBA method later. One fragility curve describes the probability a given construction class will reach or exceed one particular level of damage at various intensities of shaking. A set of curves, to cover all the damage states, is used for each construction class. Fragility curves and damage probability matrices are similar in the information they provide and one can be converted into the other. Fragility curves present the information graphically, while damage probability matrices present the infor- mation in tabular form. In the dBA-Central U.S. study's method, lifelines and nonbuilding structures were treated with fragility curves in a manner parallel to that used for buildings. NOAA-USGS MOTION-DAMAGE RE[ATIONE3HIPS The earliest U.S. attempt at estimating earthquake property loss on a large scale began in 1925 when engineers Harold Engle and Jack Shields gathered data on the damage caused by the Santa Barbara earthquake for use by the insurance industry. This work has con- tinued and has resulted, after several developments and refinements, into the NOAA-USGS method or the similar ISO method. The generic NOAA-USGS motion-damage relationship is shown in Figure Ad. The truncation of the mean damage ratio curve at MMI X-X is due to the fact that intensities above this point have sometimes been assigned to sites in previous earthquakes on the basis of ground failure, not ground shaking. Table ~1 briefly tabulates the construction classes. Each class is described with approximately a paragraph in the Commercial Earthquake Insurance Manual (ISO, 1977). The damage ratio is the percentage damage related to cost of
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162 100 a' ILL - co an o J IL] G IL .~. ale....... ..~.............. ,A ~ 2.- - 2..2 - - .. ~ 2 2. . ~ ' Geologic ~ ~= , ~ effects .~............................................................................... Ace . .................. ' ~^ SAC O ~ a.,, . ~ ~~ D 1 1 1 E 1 1 IV V Vl Vll Vlil IX X Xl X11 MODIFIED MERCALLI INTENSITY FIGURE E-1 Relationship of ground failures to ground shaking in the Modified Mercalli Intensity scale. Source: Steinbrugge (1982~. replacement. Mean damage ratios are used because they are aver- age factors for all buildings of given classes. They do not give the distribution of damage, such as how many buildings had little or no damage or how many had moderate damage. The mean damage
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163 TABLE E-1 Construction Classes Used in the ISO and NOAA/USGS Methods Building Class Brief Description of Building Subelasses lA-1 Wood-frame and stuccoed frame dwellings regardless of area and height 1A-2 Wood-frame and stuccoed frame buildings, other than dwellings not exceeding three stories in height or 3,000 square feet in ground floor area 1B 2A 2B 3A 3B 3C 4B 1A-3 Wood-frame and stuccoed frame structures not exceeding three stories in height regardless of area Wood-frame and stuccoed frame buildings not qualifying under class 1A One-story, all metal; floor area less than 20,000 square feet All metal buildings not under 2A Steel frame, superior damage control features Steel frame, ordinary damage control features Steel frame, intermediate damage control features (between 3A and 3B) 3D Steel frame, floors and roofs not concrete 4A Reinforced concrete, superior damage control features Reinforced concrete, ordinary damage control features 4C 4D 4E 5A 5B 5C 5D BE 6 Reinforced concrete, intermediate damage control features (between 4A and 4B) Reinforced concrete, precast reinforced concrete, lift slab Reinforced concrete, floors and roofs not concrete Mixed construction, small buildings and dwellings Mixed construction, superior damage control features Mixed construction, ordinary damage control features Mixed construction, intermediate damage control features Mixed construction, unreinforced masonry Buildings specifically designed to be earthquake resistant SOURCE: Algermissen and Steinbrugge, (1984~. For more complete descriptions of each class, see Iso (1977) and McClure et al. (1979~.
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164 35 30 25 - a) ~ 20 a) cat a) _' in 1 5 o J 10 5 r - ~5~ /~B 3D 4C 5C / _~, ~ ~ , 3C 4A 5B/ - - /' 3A 2B A/— 1 1 V Vl V11 MM INTENSITY V11 IX FIGURE ~2 Mean damage ratio curves used in the NOAA-USGS method. Source: Algermmsen and Steinbrugge (1984~. ratio directly defines property loss, but does not directly indicate loss of function or number of casualties. Figure ~2 shows some of the mean damage ratio curves used in the NOAA-USGS method. The amount of historic damage data available on some of the classes of construction, particularly wood-frame dwellings, is exten- sive, whereas more judgment and fewer data are employed to develop damage ratios for high-rise buildings or many low-rise commercial- industrial construction classes for which there is less experience. The ISO system generally limits itself to classes of construction for which there are historic data. Single-family wood-frame dwellings are the class of construction
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165 having the greatest historical data, with the possible exception of mobile homes. The accuracy of the basic NOAA-USGS method for this class is high as judged by the work of McClure (1967),* whose property loss relationships (based on the 1952 Kern County earthquakes) predicted a total loss of $3.8 million when applied to the 1969 Santa Rosa earthquakes, whereas the actual postearthquake estimated dwelling loss figure was $4 million (Steinbrugge et al., 1970~. Another test of a loss estunation method for single-family dweD- ings is provided in Rinehart et al. (1976) wherein the results of a modified version of the 1969 method by Steinbrugge and others are favorably compared with data from the 1971 San Fernando earth- quake. The 1971 data on all of the approximately 12,000 dwellings in one area of the San Fernando Valley where the shaking was strongest are unusually large and detailed. Often only rough or sem~quanti- tative data on a few dozen buildings of one construction class are available Tom an earthquake, or the reports are selective (typically only noting cases of dramatic damage). ATC-13 MOTION-DAMAGE RELATIONSHIPS The ATC-13 method does not describe its building construction classes in as much detail as in the NOAA-USGS scheme, but includes many structures that are not addressed in the NOAA-USGS method. It has a total of 78 classes of structures, 40 of which are buildings and 38 of which are lifeline-related or equipment classes. These classes are listed in Table ~2. Lacking the major source of hard data in the ISO or NOAA- USGS method, which was proprietary to the insurance industry, ATC-13 relied on the expert opinion of experienced individuals in the earthquake engineering field to produce motion-damage relation- ships. The techniques used for processing the questionnaire answers are described in the AT~13 report. The form in which the ATC-13 motion-damage relationship for each class was solicited from the experts, and the way in which the combined or consensus expert opinion was presented, was the damage probability matrix. This format and idea was originated by Marte} (1964) and independently developed in the Massachusetts Institute * Given the loose definition of aNOAA-USGSn method used here, the McClure work fits this definition.
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166 TABLE E-2 Earthquake Engineering Facility Classification Facility Classification Number BUILDINGS Wood frame (low rise) Light metal (low rise) Unreinforced masonry (bearing wall) Low rise (1-3 stories) Medium rise (4-7 stories) Unreinforced masonry (with load-bearing frame) Low rise Medium rise High rise (> 8 stories) Reinforced concrete shear wall (with moment-resisting frame) Low rise Medium rise High rise Reinforced concrete shear wall (without moment-resisting frame) Low rise Medium rise High rise Reinforced masonry shear wall (without moment-resisting frame) Low rise Medium rise High rise Reinforced masonry shear wall (with moment-resisting frame) Low rise Medium rise High rise Braced steel frame Low rise Medium rise High rise Moment-resisting steel frame (perimeter frame) Low rise Medium rise High rise Moment-resisting steel frame (distributed frame) Low rise Medium rise High rise Moment-resisting ductile concrete frame (distributed frame) Low rise Medium rise High rise 2 75 76 78 79 80 3 4 6 7 8 9 10 11 84 85 ~6 12 13 14 15 16 17 72 73 74 18 19 20
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167 TABLE E-2 (Continued) Facility Classification Number Moment-resisting nonductile concrete frame (distributed frame) Low rise Medium rise High rise Precast concrete (other than tilt-up) Low rise Medium rise High rise Long-span (low rise) Tilt-up (low rise) Mobile homes BRIDGES Conventional (less than 500-ft spane) Multiple simple spans Continuous/monolithic (includes single-span bridges) Major (greater than 500-ft spans) PIPELINES Underground At grade DAMS Concrete Earthfill and rockfill TUNNELS Alluvium Rock Cut and cover STORAGE TANKS Underground Liquid Solid On ground Liquid Solid Elevated Liquid Solid 87 88 89 81 82 83 91 21 23 24 25 30 31 32 ~5 56 38 39 40 41 42 43 44 45 46
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168 TABLE E-2 (Continued) Facility Classification Number ROADWAYS AND PAVEMENTS Railroad Highways Runways CHIMNEYS (high industrial) Masonry Concrete Steel CRANES CONVEYOR SYSTEMS TOWERS Electrical transmission lines Convention (less than 100-ft high) Major (more than 100-ft high) Broadcast Observation Offshore OTHER STRUCTURES Canal Earth-retaining structures (over 20-ft high) Waterfront structures EQUIPMENT Residential Office (e.g., furniture, computers) Electrical Mechanical High technology and laboratory Trains, trucks, airplanes, and other vehicles 47 48 49 50 51 52 53 54 55 56 57 58 59 61 62 63 64 65 66 68 70 90 SOURCE: Applied Technology Council (1985).
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169 TABLE E-3 General Form of Damage Probability Matrix as Used in ATC-13 (in percent) D amage Central a Factor Damage Probability of Damage by MMI Range Factor VI VII VIII IX X XI XII 1--None 0 0.0 95.0 49.0 30 14 3 1 0.4 2--Slight 0-1 0.5 3.0 38.0 40 30 10 3 0.6 3--Light 1-10 5.0 1.5 8.0 16 24 30 10 1.0 4--Moderate 10-30 20.0 0.4 2.0 8 16 26 30 3.0 5--Hea~ry 30-60 45.0 0.1 1.5 3 10 18 30 18 6--Major 60-100 80.0 -- 1.0 2 4 10 1 39 7--Destroyed 100 100.0 -- 0.5 1 1 3 8 38 aExample values are listed. NOTE: These definitions are used as a guideline: 1--None: no damage. 2--Slight: limited localized minor damage not requiring repair. 3--Light: significant localized damage of some components generally not . . . requlrlng repair. 4--Moderate: significant localized damage of many components warranting repair. 5--Heavy: extensive damage requiring major repairs. 6--Major: major widespread damage that may result in the facility being razed. 7--Destroyed: total destruction of the majority of the facility. SOURCE: Applied Technology Council (1985~. Of Technology Seismic Design Decision Analysis research program by Whitman et al. (1973~. Table ~3 shows a generic ATC-13 damage probability matrix. MMI XI and XIT are used here to refer to increasingly severe ground motion, beyond the X-X point; this is not a literal interpretation of the scale's reference to ground failure indicators at these highest two intensities. Examples of damage probability matrices produced by expert opinion in the ATC-13 project are shown in Table ~4. Facility class 73 (medium-r~se moment-resisting distributed steel frame) and 74 (same, except high riser are very earthquake resistant. Classes 75 and 76 are low-rise and medium-rise, unreinforced-masonry bearing walls, which are very damageable. At any given intensity, the dis- tribution for the steel frames will be seen to be concentrated at a much lower level of damage than for the unreinforced masonry. In any column, the percentages total to 100. Although these expert opinion matrices show that for any in- tensity the buildings are usually contained within two or three dam- age levels, this is not quite consistent with observations of actual
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184 of every possible effect, and yet they also demand accuracy. Quali- tative statements identifying high-risk areas or high-r~k factors may be a suitable substitute. The ATC-13 method is the most ambitious to date in several key respects: The number of construction classes; The number of use classes; Reliance on structured expert opinion to produce motion- damage and damage-Ioss relationships; and ~ Extrapolation from nonconstruction (socioeconomic) data to synthesize an inventory. Each of these four aspects was largely determined by the orig- inal scope of the study-for example, the need to enumerate every individual facility by construction and use class, because of the re- quirements of the intended econorn~c use and the decision to rely primarily on presently computerized FEMA data. If the method is now to be applied or adapted to different uses, each of these four aspects requires re-evaluation and revision. 1. construction classes. The number of construction classes could be reduced to be closer to that in the NOAA-USGS system, at least for buildings. Fewer lifeline or nonbuild~g structure classes might be warranted as well, although dealing with these classes in a manner parallel to that for buildings is generally valid and is one of the significant contributions of the ATC-13 effort. 2. Use classes. The number of use classes could be greatly reduced, because for most emergency planning and hazard reduction purposes, the fine distinctions between various commercial and in- dustrial economic sectors wiD not be used. In some cases, greater definition of essential emergency services facilities would be desirable, but this relates to facility-specific field surveys that are not discussed in ATC-13. 3. Reliance exclusively on expert opinion. In attempting fewer predictions, less expert opinion would be needed. For example, to forecast the number of days after the earthquake when 30 percent, 60 percent, and 100 percent of pre-earthquake function is restored for each of 60 use categories (an expanded version of the 35 use or social functions is used for this purpose), and for each of six damage states, 1,080 judgmental answers are needed: 3 functional levels x 6 use categories x 6 damage levels = 1,080 judgments.
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185 If the method will be used to evaluate the hazards of unreinforced- masonry buildings in local jurisdictions, use of the historic data available and the increasing number of building-specific structural evaluations of such structures in communities with retroactive ordi- nances would seem to be obvious information sources to incorporate into a method. ATC-13's original broad scope does not make it the best method for such specific application. 4. Extrapolation of inventory `data. Although the synthesis of construction data from economic or social data bases is to some extent necessary in any method, AT~13's extensive reliance on this approach, primarily for budgetary reasons, emerges as a limitation. Other large-scale loss estimation studies have afforded the cost of at least some fieldwork to assemble information on key facilities, to sample areas to develop extrapolations that can be relied on as valid for a particular reg~on's inventory of facilities, and to check at least some of the existing file data's accuracy. The above critique has emphasized the weak points of ATC-13, but the project also resulted in some impressive accomplishments. The ATC-13 final report combines in one volume more data, a more comprehensive review of possible methods, and more discussion by experts of the various tasks involved in the earthquake loss estima- tion process than any other single publication. To some extent, the admirable degree to which the ATC-13 project documented each step of its method is the reason why criticism can be so precisely aimed at its weak points—the transparency allows the critic to see its blem- ishes as well as its attractive aspects. In this respect, the ATC-13 method is much superior to the NOAA-USGS and Six Cities studies discussed in this working paper, and allows independent investigators to analyze and evaluate each detail of the method in a very useful way. While the NOAA-USGS literature makes frequent references to the fact that judgment has been used, these references are not so explicit as to allow investigators unconnected with these studies to replicate the results. Historical lo~ data are relied on to a much greater extent than expert opinion. Moreover, no indication is given as to how expert judgment was structured, whereas the ATCi13 method devoted consiclerable effort to an explicit process of struc- turing the opinions of its expert team. Hence, one of the reasons the ATC-13 study was launched was that The body of historical dam- age data for earthquakes was largely proprietary and not publicly available" (Wilson, 1987~.
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186 The NOAA-USGS method, were its publications to define as ex- plicitly the numerous judgments needed to interpret data or produce relationships based on expert opinion where data are lacking, would probably be seen to have comparable weaknesses to ATC-13. The NOAA-USGS method does not attempt to provide estimates of the loss of function experienced by many different economic sectors, to estimate equipment damage in buildings, or to analyze lifeline out- ages in a quantitative manner comparable to buildings. Due to its less ambitious scope and less explicit documentation, these NOAA- USGS weaknesses are less apparent. In summary, the ATC-13 expert opinion method documents at least some of its uncertainties, while these are left quantitatively untreated in the NOAA-USGS reports. The fragility curve approach of the Six Cities study also attempts to portray at least some of its uncertainties. Whether damage probability matrices or fragility curves are the best way to represent loss estimates is an issue apart from the point that the explicit accounting for uncertainty must be attempted by all methods. RE[ATIONSEIP OF DAMAGE TO PROPERTY LOSS Steinbrugge (1986) discusses several complications in the prop- erty loss estimation process. Property damage may be repaired by hiring contractors ("impersonal loss" cost basis), or the owners of buildings (especially lightly damaged dwellings) may perform their own work ("personals basest. For the 1971 San Fernando earthquake, his calculated difference between losses on a personal or ~rnpersonal loss basis amounts to $17 million in 1971 dollars. The difference between defining property loss as the cost of rep air or reconstruction divided by replacement cost, or as a percentage of cash value, can also be very large. McClure (1967) found that the actual cash value of dwellings in Bakersfield at the time of the 1952 Kern County earthquakes was only about a third of their replacement cost, and thus losses calculated on a replacement cost basis would have been about three times greater than if calculated on a cash value basis. (With wood-frame dwellings, where the accuracy of loss estimation is generally considered to be well developed, this is a large difference.) The definition of actual cash value, of great interest in some legal proceedings, is also variable. For legal purposes in some states
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187 this is defined as the present market value, while in others it is the replacement cost less depreciation. In spite of these difficulties, the translation of damage estimates into property loss estimates is easier than the task of translating damage into either casualty or functional loss estimates. RELATIONSHIP OF DAMAGE TO CASUALTIES Of all the kinds of loss to be estimated by a study, casualties are perhaps the most important to emergency services organizations and agencies. The data on casualty experience In individual buildings are more anecdotal than is the case with property loss. While there has never been a total collapse without an accompanying property loss of nearly 100 percent (depending on the definition of property loss as discussed above), there have been many buildings that have completely Pancaked and yet have not hurt anyone sunply because the earthquake occurred when the building was empty. Even when buildings are fully occupied at the time of the earthquake, the ca- sualty ratios may differ greatly for the same damage level. This suggests that the casualty experience in previous earthquakes in a larger number of buildings must be collected and analyzed than in the case of relating property loss to damage. At this tune, data that relate building damage to casualties are almost nonexistent. Three pages in the ATC-13 report (257-259) provide most of the known information. The casualty-estimation method used In most large-scale studies is to consult overall (city-wide or larger) casualty statistics from previous earthquakes, rather than to relate casualties directly to damage or property loss estimates. The NOAA-USGS studies, for example, generally applied one casualty rate to wood-frame dwellings and one or more other rates to other kinds of construction. While the overall fatality rate in any of the U.S. metropolitan area studies has always been less than ~ percent, the relative differ- ence between 0.1 percent and 0.2 percent, for example, is a doubling of the predicted fatalities. In the NOAA-USGS studies, serious in- juries that would require hospitalization were estimated at four times the number of fatalities, and thus the spread in the number of injuries predicted could fluctuate widely based on a seemingly small fatality ratio difference. Data collected from a larger number of earthquakes, with the type and degree of injury related to the physical Carnage that caused it, may slowly refine this state of the art.
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188 RELATIONSHIP OF DAMAGE TO FUNCTIONAL LOSS Of the three basic kinds of loss, functional loss is the most dif- ficult to relate to damage. In the case of lifelines, areawide average outages from past events are often used, adjusted for local condi- tions, to reach a first approximation of the functional loss problem. For losses caused by building darnage, the methods reviewed above attempt to associate a damage level with functional loss, in some cases inexplicitly (NOAA-USGS), in some cases explicitly (ATC-133. As the ATC-13 report notes, data are insufficient to allow for a sta- tistica] approach, so the relationships are based on judgments of how severely affected various occupancies or uses would be by various levels of damage. The same engineers selected for their expertise on predicting damage were used to develop these relationships. Estimates of homelessness are a form of functional loss projec- tion. The NOAA-USGS method assumed that a 50 percent dwelling damage ratio was the indicator that the building could not be oc- cupied, resulting in homelessness and a need for alternative shelter. While the NOAA-USGS method is usually said to be a mean damage ratio method, the estunation of homelessness required a representa- tion of the spread of the building damage lever. This distribution was obtained prunariTy from the distribution pattern of damage for the 1933 Long Beach and ~L971 San Fernando earthquakes. The 1969 study by Steinbruggefet al. on dwelling losses was also used, and this study essentially used a damage probability matrix: for each MMI, and for each damage ratio range, the per- centage of buildings falling in that MMI/damage cell was produced. This indicates that seemingly clear lines of demarcation between different methods become blurred on closer examination and empha- sizes the potential In developing hybrid methods that combine the best elements of different methods. The damage rati~h~torical data (NOAA-USGS), damage probability matrix-expert opinion (ATC- 13), and fragility curve-analysis of archetypes and historical data (JBA) approaches all have their strong and weak points. The property los~oriented studies of housing from past earth- quakes "identify the dollar losses to wood frame dwellings but do not state at what damage level the houses were evacuated. Indeed, there probably was no consistent practice in this regard; in some earthquakes, social needs were sometimes confused with safety re- quirements when it came to buildings condemnations" (AIgermissen et al., 1972~.
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189 Gulliver (1986) reviewed the relationships between damage ra- tio and building condemnation by local authorities that had been researched by Whitman (1974), Lee and Eguchi (1977), and the Of- fice of Emergency Services (1979), and informally consulted some earthquake engineers. She concluded that a 20 percent damage ratio (with damage ratio defined in teens of replacement value) was the threshold past which homelessness would result. In addition to homelessness caused by structural damage for both ground shaking and ground failure, Gulliver estunated homelessness caused by utility outage. Temporary homelessness was estimated according to intensity for eight construction classes, and permanent homeless caseload figures, related to irreparably damaged dwellings, were estunated for the higher damage ratios. Evans and Arnold (1986) proposed a triage-based division of housing damage, defined in terms of habitability: habitable, tem- porarily uninhabitable, and permanently uninhabitable. Severe dam- age to a garage, porch, or deck would not affect the habitability of the adjacent single-fam~ly dwelling, and even severe structural damage might be repairable depending on the occupants' ability to finance the cost. Therefore, this classification system does not correlate homelessness with damage ratio or with overall damage level. The bet of indicators assumed to match these three habitability states require dweDing-by-dweDing inspection, and this method is oriented toward postdisaster housing inspection procedures rather than loss estunation. LIFELINES Lifelines, or utilities and infrastructure systems, include rail- road, motor vehicle, water, electricity, sewage, and communications services. The words systems and services are central to the distinc- tion between the loss estimation process for lifelines as compared to buildings. Service outages are almost Sways a prominent concern addressed by lifeline studies. In many cases, the central concern with the estimation of damage to the building stock is to identify life safety or property risks. With some lifeline components, for exam- ple, dams that are part of a water system, life safety may also be a primary concern, but this does not apply to the majority of lifeline components. A lifeline such as a water or electrical utility's facilities and functions must be analyzed as a system rather than as separate, unrelated structures.
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190 ~ v ~ ~ Loss estimation studies have seldom incorporated lifelines to the same extent as building losses. Lifeline loss estimation methodology is not an mature. Most lifeline earthquake engineering studies have either concentrated on deterministic evaluations of specific lifeline designs or on research into lifeline network analyses. The techniques used tent} to be too complicated and tune consuming for incorpo- ration into a large geographic area loss estimation study. However, many recent loss estimation studies are attempting to incorporate lifelines into loss estunations. Future loss estunation studies should be encouraged to include lifelines partially for the purpose of aiding in the maturing of lifeline loss estunation. Because the various components of a lifeline system are interre- lated, lifeline loss estimation methods tend to rely on a probabilistic approach bred on the idea of the reliability of networks. The net- work is defined in terms of serial (in-line, nonredundant) and parallel (redundant) components of the system, and the failure implications of individual components are analyzed in this context. Applying a given level of conservatism to the evaluation of a single switchyard, the result of an expert's evaluation may be that a complete outage should be assumed for emergency planning pur- poses. Applying this judgment to all switchyards in an entire region, forecasting a 100 percent outage throughout the system would not necessarily be appropriate. This same expert, if asked to estimate the overall system's postearthquake capacity, would probably take into account that performance wait vary among a large number of fa- cilities, even if seern~ngly identical in construction characteristics and subjected to the same presumed intensity. The systems approach to lifeline loss estimation also can point out instances where the loss to a single facility could have a widespread effect throughout a system, far out of proportion to the size or property value of that one key facility. The estimation of losses to the individual components of a lifeline system the individual bridge, power transmission or radio tower, docks and quaywalIs, and so on—has a led extensive historical loss experience data base than for buildings. The most ambitious attempt at developing classes that include nonbuilding structures ~ AT~13 (Applied Technology Council, 1985), in which 38 of the 78 total construction classes are nonbuilding structures and most of these 38 classes are related to lifelines. Lifeline service outage estimates can be stated in various ways. The simplest form of the estimate is to state, for example, that a
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191 certain segment of a highway route should be presumed either closed or open. A more complex statement, requiring more information and analysis to produce valid results, would be to assign a postearthquake traBic flow capacity to highway segments. This latter approach is unusual, but was used in a study of the San Erancisco Bay Area's transportation system (Jones, 1983~. In the first of the urban-scale 1088 studies by NOAA, the essence of the telephone loss estimate was as follows: It is anticipated that 50 percent of the telephone system will be out of service in the counties of San E`rancisco, San Mateo, Santa Clara and Marin for an indefinite period of time due to equipment damage in the event of a magnitude 8.3 shock on the Bad Andreas fault.... Even without damage to the system, the lines will be overloaded and for all practical purposes it will be useless for telephoning in emergency situations. (Algermmsen et al., 1972) A California Division of Mines and Geology study of the same area and scenario earthquake, although with different scenario intensities, was done 10 years later (Davis et al., 1982b) and provided telephone outage statements with greater detail. The geographic breakdown of outage zones was approximately at the county scale, as for the earlier NOAA study, but the outage was estimated in terms of recovery patterns where the percentage of normal service was graphed versus the number of days after the earthquake. One of four different graphs or levels of outage was assigned to each county-s~zed zone. Losses in the level of service provided by the lifeline should take into account a noneng~neering factor that may be difficult to evaluate: the emergency response capability of the lifeline operator or of other emergency response agencies. A utility with an earthquake-resistant radio system, personnel who undergo annual earthquake exercises to test their ability to carry out preassigned tasks, and back-up plans for handling significant damage beyond that occurring in weather- related incidents, should be much more able to contain the impact of earthquake damage than another utility without these attributes. The first of the large-scale loss estunates (AIgermissen et al., 1972) established the basic table of contents followed by most other lose estimate studies. The categories of lifelines used were: com- munications (primarily radio, television, and telephone service, al- though newspaper and post office services were also briefly consid- ered); transportation (railroads, highways, bridges, mass transit, airports, and ports); and public utilities (electricity, natural gas,
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192 water, sewage, and petroleum pipelines). There were 15 systems in all. The Central U.S.-Six Cities loss study (Allen and Hoshall et al., 1985) used fragility curves to analyze individual lifeline components. Bridges, for example, were divided into five classes based on type and length of spans. Network analysis was used to relate the performance of individual components to overall performance of the system. Of the large-scale multipurpose low estimation studies, this appears to be the most extensive use of network analysm to date. Network analysis has been more routinely used with one given lifeline system. The probabilistic analysis of the semi risk faced by a gas utility's system in Utah, where 52 different earthquakes was considered, illus- trates an approach that has become increasingly common in the field of lifeline earthquake loss analysis (McDonough and Taylor, 1986~. Reviews of the state of the art of lifeline earthquake analysis are found in the works of Eguchi (1984), Cooper (1984), Smith (1981), Shah and Benjamin (1977), Whitman et al. (1975), and Duke and Moran (1972~. The Applied Technology Council (1985) reviewed the field in the process of developing ways to deal with the problem of estunating lifeline losses, and another broad review of the field from the hazard reduction perspective is provided by the Building Seismic Safety Council (1987~. The fact that the proceedings of the Eighth World Conference on Earthquake Engineering (Earthquake Engineering Research Insti- tute, 1984) contain 14 papers on the topic and the American Society of Civil Engineering Technical Council on Lifeline Earthquake Engi- neering is engaged in numerous ongoing activities are signs of rapid growth in the field. -v ~ - ~~ J ~ SUMMARY As to the question of the accuracy or uncertainty of these meth- ods, some options can be presented, although little is available concerning controlled, statistically valid comparisons of the results produced by different methods with the actual losses produced by earthquakes. However expressed (e.g., curves or matrices), estimates almost always are used as single numbers. This is true for estimates of forces in engineering design ultimately one force number is developed for design purposes. It is also true for estimates of casualties and
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193 property loss that are used for planning and earthquake awareness purposes. The uncertainty contained in a loss study's motion-damage or damage-Ioss analysis method should be documented, as well as that of the seismic hazard and inventory components. When ranges of numbers are provided, however, many users will still need to select a s~ngle-value result the best estimate or maximum estimate, for example. Many disaster planning, public education, and hazard reduction program development purposes require a single number on the bottom Ime of the analysis. At present, accuracy Is not great. A prudent claim would be to within a factor of one and one-half for single-family dwellings, a factor of three for commercial, industrial, and institutional buildings, and a factor of ten for areas with no recent earthquake history.* The amount of systematic data for building damage is very small compared to the variety of conditions applying to any future earth- quake. At present, typical estimating techniques relate a single, gross, structural parameter (construction cIa - ) to a single, gross, ground-motion parameter (intensity) to arrive at a damage estimate. The variety of parameters that In fact significantly affect building performance are indicated in Table ~7, for one claw of construc- tion. Clearly, with even a small uncertainty in each parameter, the cumulative uncertainty must be very large. At present however, there is little point in incorporating these additional parameters in estimating methods because matching damage data do not exist. If the expected accuracy noted above is accepted, then a central concern is the relative accuracy of different methods of relating mo- tion to damage cases. Significant improvements in the state of the art should be sought, but the users of loss studies should not expect dramatic improvements in the near future. Comparisons done so far indicate variations between methods to be well within the limits of overall accuracy. As shown in Table ~5, the most extreme discrete ancy between the NOAA-USGS and ATC-13 estimates is for tilt-up structures, where ATC-13 shows a mean damage ratio of 15.8 per- cent, compared to 30 percent in NOAA-USGA. All other structural types show a much closer level of agreement. Attempts to refine methods, such as greatly increasing the range and definition of structural types, will not improve accuracy until *These ranges have not been established on statistical grounds, and repre- sent a consensus of the panel.
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194 TABLE E-7 Damage Estimate Based on Simple Estimating Parameters Contrasted to Listing of All Factors That Affect Damage - E)uilding Description Ground Motion Damage Ratio Estimatea 4A Reinforced concrete, superior MMI IX Reality Height, low, medium, high Structural system types Concrete types and quality Building size Design of connection details Irregularity of plan Irregularity of elevation Building age (code) Building period 13 Percent Acceleration Displacement Velocity Duration Frequency content Foundation type Soil type Dispersion as indicated by DPM or fragility curve aExample category from ISO classification. damage information matches those structural types. The same is true for the effects of ground motion. Use of the Modified Mercalli Scale, with all its limitations, still matches the available Carnage information.
Representative terms from entire chapter: