FIRE RISK INDEXING AND FIRE RISK ANALYSIS: A COMPARISON OF PROS AND CONS

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1 FIRE RISK INDEXING AND FIRE RISK ANALYSIS: A COMPARISON OF PROS AND CONS Jurgta Šakėnatė, Egdjus R. Vadogas Vnus Gedmnas technca unversty, Sauėteko ave., LT-0 Vnus, Lthuana. E-ma: [email protected], [email protected] Abstract. The paper consders the probem of fre safety assurance by means of fre rsk ndeng and fre rsk assessment. The attenton n focused on the comparson of these two prncpa approaches and possbtes of ther appcaton n a combned set. The paper ams to defne, compare and anayse fre safety assessment by appyng the aforementoned approaches. The practcabty of both approaches s compared by means of an eampe whch consders fre safety of an estng offce budng. It s stated that t makes sense to combne the merts both fre rsk ndeng and assessment n order to appy them to a comprehensve decson-makng concernng fre safety assurance. The paper aso states that ths can be done wthn the framework of a mut-attrbute decson-makng methodoogy. Keywords: fre, safety, nde, assessment, rsk, budng, comparson.. Introducton The am of budng fre rsk anayss s to comprehensvey understand and characterze fre-reated rsks to better nform the wde range of decsons that must be made as part of budng desgn, constructon and operaton. Specfcay, fre rsk s the possbty of an unwanted outcome n an uncertan stuaton, where fre s the hazard that may nduce the oss or harm to that whch s vaued (e.g., fe, property, busness contnuty, hertage, the envronment, or some combnaton of these) (e.g. Rasbash et a. 004; Póka 008; Chow and Chow 009; Gaaj 009; Koneck and Poka 009). Budng fre rsk assessment s the process of understandng and quanttatve characterzng the fre hazard n budng, the unwanted outcomes (reevant oss or harm) that may resut from a fre, and the kehood of fre and unwanted outcomes occurrng (Meacham 000; Rassmussen 990). Fre rsk ndeng and fre rsk assessment are the nk between fre scence, fre safety, and safety cuture (Rasbash et a. 004; SFPE 00). Fre rsk ndeng s evovng as a method of evauatng fre safety that s vauabe n assmatng research resuts. Fre safety decsons often have to be made under condtons where the data are sparse and uncertan. Indeng can provde a cost-effectve means of rsk evauaton that s both usefu and vad. Fre rsk ndeng systems are heurstc modes of fre safety. They consttute varous processes of anayzng and scorng hazard and other system attrbutes to procedure a rapd and smpe estmate to reatve fre rsk. There are numerous approaches to fre safety evauaton that can be construed as a rsk ndeng (Watts 00). Contrary to the fre rsk ndeng, detaed rsk assessment can be an epressve and abour-ntensve process. On the other hand, the assessment of fre rsk by the forma statstca means aows a hghy ndvdua characterzaton of fre safety budng. Therefore, t makes sense to combne the merts both fre rsk ndeng and assessment n order to appy them to a comprehensve decson-makng concernng budng safety. Ths paper can be seen as a preparatory work for a combnaton of both approaches n the framework of a mut-attrbute seecton. The methodoogca background for such a combnaton was prepared by Zavadskas and Vadogas (008, 009). The paper presents a short revew of nput varabes used for cacuaton of fre rsk ndces and assessment of ths rsk. The dscusson embraces an appcaton of both fre rsk nde and fre rsk assessment for a specfc budng. The attenton n focused on the comparson of these approaches and possbtes of ther appcaton. The fndngs presented n the paper are vewed as knowedge whch coud factate the decson-makng wth respect to fre rsk.. Fre safety assessment by fre rsk ndeng.. Descrpton of the approach Fre rsk ndeng s consdered to be a nk between fre scence and fre safety (SFPE 00). Indeng s a 97

2 Tabe. The man components of the four basc types of sprnker systems Inde Mathematca epresson of the nde Epresson of toerabe rsk Reference Gretener;s nde I G () FRAME nde I FR Dow s fre and eposon nde (F&EI) I D () Fre safety evauaton system (FSES) nde I F () P(,, ) A(,, ) I G I N( ) S( ) F( ) G, Kaser (979) P(,, ) I FR I A(,, ) D(, ) FR,0 F.R.A.M.E. (008) 6 I I D 96 Dow (994) D 0 5 F I I F jk ( ) Rasbash et a. (004) j Herarchca approach (HA)nde I H (4) n I w H I H I H,to Rasbash et a. (004), SFPE (00) () A() s the probabty that a fre w start (the rsk of actvaton); P() s the possbe dangers (the potenta rsk); N() refers to standard measures; S() refers to speca protecton measures and F() s the fre resstance factor of the budng; the components of the vectors,, are epaned n Tabe. () The vaues to 96 of I D embrace the categores of the ght and moderate hazard (potenta damage); ntermedate, heavy and severe hazard s represented by the ntervas I D [97, 7], I D [8, 58], and I D 58 (Dow 994) ; the components of the vectors,, are epaned n Tabe 4. () jk ( ) an ndcator (zero-one) functon reated the fre safety parameter ; the components of the vectors,, are epaned n Tabe. (4) The symbo w denotes the weghts of normazed attrbutes ; I H,to s a toerabe vaue of the nde I H (not specfed n the terature). practca approach aternatve to a detaed rsk assessment, whch s often an epensve and abour-ntensve process. Indeng can provde a cost-effectve means of rsk evauaton. Fre rsk ndces are heurstc modes of fre safety assessment. They aow a smpe scorng of fre hazard and ratng budngs accordng to ndvdua ndces. Fre rsk ndeng as professona judgment and past eperence for assgnng vaues to seected varabes representng both postve and negatve features of fre safety. The seected varabes and vaues assgned to them are then transformed nto a snge vaue, whch s compared to other smar assessments or to a standard. A rsk nde s defned as a snge number measure of the rsk assocated wth a budng. Thus, nsurance rates are fre rsk ndces, as are the outputs of other smar schedues or scorng methods. Fre rsk ndeng, then, s the process of modeng and scorng hazard and eposure attrbutes to produce a rapd and smpe estmate of fre rsk. The concept has ganed wdespread acceptance as a cost-effectve prortzaton and screenng too for fre rsk assessment programs. It s a usefu and powerfu approach that can provde vauabe nformaton on the rsks assocated wth fre. The mportance of fre rsk ndeng has been wdey recognzed. A workng group of educators and researchers addressed the ssue of fre rsk ndeng at the Natona Academy of Scences 987 Workshop on Anaytca Methods for Desgnng Budngs for Fre Safety (Budng Research Board 988). They concuded there s a need for three-part system of fre safety comprsed of () codes; () the methods of fre rsk ndeng, referred to as numerca gradng systems; and () the means of suppyng nputs to that system derved, as far as feasbe, from basc prncpes of decson scence. The workng group went on to state the ratonae for ts concuson. It s dffcut to descrbe a typca fre rsk nde method. The practca necessty of tryng to assess mutfaceted fre rsks wth mted resources has ed to the creaton of severa of fre rsk ndeng. Representatve eampes of fre rsk ndeng were seected from the terature and are summarzed n Tabe. They provde some dea of the types of varatons nvoved wth modeng and quantfyng fre rsk... Wdey-used fre rsk ndces Four fre rsk ndces most often mentoned n the terature on fre safety assessment are summarsed n Tabe. The common feature od of for methods s that: a of then appy a redefned st of varabes (attrbutes) as to specfy the nput; the cacuaton of fre rsk ndces yeds a snge number whch represents the magntude of rsk, how ever, ths vaue s nether frequency nor consequence severty; 98

3 the cacuaton fre rsk ndeng can be compared wth some toerabe or target vaue whch s the dfferent for each nde. Input varabes used for cacuaton wth Gretener s as we as FSES and herarchca methods as a sted n Tabes and. The varabes from Tabe represent partay physca characterstcs and partay abstract vaues used for cacuaton of the Gretener s nde. In the case of FSES method, and herarchca approach normazed vaues of attrbutes are apped (Tabe ). They vaues depend on specfc feature of the budng beng assessed. For eampe, f the varabe represents the presence and type of fre aarm, t can take on vaues 0,,, 4, 5; the owest vaue 0 stand for the absence of any aarm system, whereas hghest the vaue 5 means a tota coverage of the entre budng foor area by the aarm system (SPFE 00). It s obvous that assgnng one of these vaues to s rather an outcome of agreement than a resut of same measurement for observaton. Tabe. Input vectors,, and (set of fre safety attrbutes) used to cacuate Gretener s nde I G Varabe Comp. Geometry data (vector ) heght between the foor and the ceng of the storey (m) a budng heght (m) heght of basement (m) the theoretca ength of the compartment (m) 4 the equvaent wdth, epressed n meter (m) 5 Fre-specfc data (vector ) mmobe fre oad (MJ/m ) mobe fre oad (MJ/m ) the fame propagaton cass (-) destructon temperature ( C) 4 a combnaton of a ow fre oad and a ow number of gnton sources, such as for resdenta budngs 5 (-) a combnaton of a ow fre oad and a moderate number of gnton sources, such as n the ndustry 6 of non-combustbe products (-) a combnaton of moderate fre oad and a moderate number of gnton sources, such as n many ndustres (-) 7 a combnaton of a hgh fre oad and a moderate number of gnton sources, such as n the paper 8 and woodwork ndustry (-) a combnaton of a hgh fre oad and a ow number of gnton sources, such as a n storage ndustry (-) 9 the mobty sub factor consders evacuaton tme under such condtons as a mutpe of the cacuated tme for heathy mobe and ndependent 0, persons (-) the number of persons that can be present n the compartment (persons/m ), the number of et unts (-), sub factor (the number of separate et drectons or, et paths avaabe) (mn.) automatc fre detecton (-) 4, mproved water suppes (-) 5, sprnker system and other automatc detecton (-) 6, respondng fre staton (-) 7, the average fre resstance of the structura and 8, separatng eements (mn.) the average fre resstance of the outsde was (mn.) 9, the average fre resstance of the ceng or the roof (mn.) 0, the average fre resstance of nteror was (mn.), Method specfc data (vector ) the number of cardna ponts (north, east, south, west) (-) The average dmenson of the content and refects the rato between the tota voume of the content and the tota surface (m) eve number of the budng (the man access eve has number E 0; eves above:,,, etc., eves beow: -,-,-, etc.) (-) w evauate the possbty to repace the budng and ts content (-) w refect the monetary vaue of the goods (euro) 5 dependng on the ndvdua actvty (-) 6 dscovery of a fre and warnng (-) 7 manua etngushers and hose statons to permt a rapd nterventon of the occupants on a startng fre (-) fre brgade tme factor (-) 9 occupants tranng eve (-) 0, Tabe shows the parameter of the FSES and vaues of ther genera fre safety scores. The tweve fre safety parameters are sted n the eft-hand coumn. The thrd and fourth coumns specfy the mnmum and mamum vaues for each parameter, etracted from Tabe 7- of NFPA 0A. Tabe. Input varabes (fre safety attrbutes) used to cacuate FSES nde I F (varabes,,,, are used aso to cacuate HA nde I H ) (Watts and Kapan 00) Varabe Vaue Mn. Ma. Occupancy rsk varabes Patenty mobty Patent densty.0.0 Zone ocaton..6 Rato of patents to attendants Patent average age 5.0. Fre safety varabes Constructon -0 0 Segregaton of hazard -7 0 Vertca Openngs -0 Automatc sprnkers 4 0 Smoke detecton Fre aarm 6-4 Interor fnsh 7 - Smoke contro Et access 9 - Et system 0, -6 5 Corrdor/room separaton, -6 4 Occupant Emergency Program, - The ndces cacuated by means of the methods sted n Tabe can be compared to some toerabe vaues, say, the vaue. n case of Gretener s method. Athough these vaue are some answer to the we-known queston,,how safe n safe enough, both ndces and the

4 to toerabe vaues are a sort of agreement and not some statstcay or economcay substantated characterstcs of fre safety. In addton, methods used for the cacuaton of fre rsk ndces use a consderabe amount of nformaton, many, for specfyng nput data. In ths sense, fre rsk ndces are smar to forma methods of rsk assessment. The atter use the consderabe amount subjectve nformaton, many n the Bayesan framework. However, contrary to the resuts of the forma rsk assessment, vaues of fre rsk ndces can used be verfed, at stng n theory, by statstca data on fre accdents. The man advantage of fre rsk ndces seems to the reatve mpcty of ther cacuaton. Tabe 4. Input varabes (fre safety attrbutes) used to cacuate the Dow s nde I D (Dow 994) Varabe Vaue Dmensoness varabes representng genera process hazards,,, 6 Dmensoness varabes representng speca process hazards,,,, Dmensoness varabe representng the ntrnsc rate of potenta energy 0 reease from fre or eposon three epressons for the cacuaton of P(), A(), and D(). In the present eampe, vaues of I FR were cacuated for the frst to categores of fre rsk: PB (,, ) I FR, B 0. 6 () A (,, ) D (, ) B PO (,, ) I FR, O. 7 () AO (,, ) DO (, ) where the subscrpts B and O stand for budng and ts content and occupants. Vaues of P(), A(), and D() reated to respectve cases were cacuated by means of formuas gven n the manua F.R.A.M.E. (008): P B ().5; A B ().6, and D B ().76 P O ().86; A O ().09, and D O (). Wth these resuts, the ndces I FR,B and I FR,O take on the foowng vaues: I FR,B 0.6 and I FR,O.7. They suggest that rsk to budng and content s acceptabe, whereas the rsk to occupants s too hgh. A sprnker system and/or fre aarm may be necessary to nsta. Ths w aow to ncrease the protecton eve D O () and so to decrease the vaue of I FRO. B.. Numerca eampe To ustrate the use of fre ndces for the quantfcaton of fre rsk, the FRAME nde I FR brefy descrbed n Tabe w be cacuated for the a three-storey offce budng wth open-pan foors shown n Fg.. The tota are of the three foors s 8400 m. The vaue of one square meter of compartment and content s 440. Ths amount to the tota vaue of the budng equa to 7 mn. The average number of peope stayng n each foor of the budng durng the workday s equa to 50. It s assumed that the budng s used wthout standard fre protecton measures (sprnkers and fre aarm). The genera epresson of the nde under consderaton, I FR, s represented by the nequaty I FR Potenta rsk Acceptabe rsk Probabty of occurence Severty Acceptabe rsk Fg. A three open-pan offce budng wth one area of fre orgn n each foor.4. The pros and cons of the approach / D(, ) P(,, A(,, ) ).0 where the nput vectors are epaned n Tabe. Vaues of components of these vectors are sted n Tabe 5. Detaed epresson used to cacuate the quanttes P(), A(), D() are gven n the FRAME technca gude (F.R.A.M.E. 008). The nverse vaue of the quantfy /D(), that s, D(), s caed a protecton eve. The FRAME nde I FR can be cacuated for three categores of potenta fre rsk: rsk to budng and content, rsk to occupants, and rsk to actvtes carred out n and n vcnty of the budng. Correspondngy, there are 00 () The obvous advantage of fre rsk ndces s a reatve smpcty of ther cacuaton. Input nformaton for ths cacuaton (vaues of the fre safety attrbutes) can be specfed wth reatve ease. The mathematca epressons of the ndces themseves are trva n terms of computatona effort. Some ndces are wdey used n some countres and brng nfuence of fre safety cuture of these countres (e.g. Kaser 979). Fre rsk ndces aow a smpe comparson of fre rsk of ndvdua budng wth a forma quantfcaton of ths rsk. On the other hand, fre rsk ndces a non-scentfc measures of fre safety (Kaser 979). It s dffcut to say, how are these ndces reated to statstca data on fres. In

5 Tabe 5. Input vectors,, and (set of fre safety attrbutes) used to cacuate F.R.A.M.E. nde I FR,B and I FR,O Comp. Notaton of varabe n the F.R.A.M.E manua Comp. Vaue Notaton of varabe n the F.R.A.M.E manua addton, vaues of fre safety varabes used for the cacuaton of ndces are specfed by eperts; however, the process of specfcaton s not documented. It s dffcut to say, why a specfc vaue of fre safety attrbute, for nstance,.4 was chosen why ths vaue can not be changed. Fnay, fre rsk ndces are reatvey dfferent modes and t s far from obvous that one of them shoud preva aganst others. The use of a specfc fre nde seems to be a sort of tradton of a partcuar country (group of countres), rather than a choce based on some scentfc reasonng.. Fre safety assessment by rsk anayss.. Descrpton of the approach Vaue Geometry data (vector ) k 8, h 5 f s 9, 90 H + 5 f f 0, 0 70 f d, 5 b 4 40 f w, 0 Fre-specfc data (vector ) u, 0 Q 00 u 4, 0 Q m 400 u 5, 8 M w 6, 0 T 4 50 w 7, 0 a 5 0 w 8, 0 a 6 0. w 4 9, a 7 0 w 5 0, 0 a Method-specfc data (vector ) a Z p 0, m 0. X, 0. E, 4 c 4 0 K, 4 c s 4, 0 n 6 0 s 5, n 7 0 s 6, 0 n 8 s 4 7, 4 n A very comprehensve measure of fre safety s the rsk defned n ne wth quanttatve rsk assessment, that s, n the form of kehood-outcome pars (Kumamoto an Heney 996; Aven 00; Ayyub 00). In contet of the present paper, the rsk due to eposure to the fre (fre orgnatng n the area or, n terms of quanttatve rsk assessment, the th ntatng event) w consst of possbe outcomes (consequences) o r of the fre and kehoods r of these consequences. Generay, each o r s represented by severa measures of sgnfcance or, n bref, sgnfcances (e.g. Kumamoto and Heney 996). Each o r can be charactersed by severa, say, n sgnfcances of dfferent nature and wth dfferent measurement unts. They can be grouped nto the vector s s, s,..., s,..., s ) (4) r ( r r rj rn Natura canddates for components of s r are drect monetary osses due to the fre, (s r, say), numbers of peope ked and njured n ths fre (s r and s r ), the tme of busness nterrupton due to the fre (s r4 ), etc. Wth r, o r, s r, the rsk reated to fre takes the foowng form: Rsk {,, s ), r,,, n } (5) ( r o r r In genera, the tota number of the outcomes, n, may vary from one fre to another. Let us consder the threestorey offce budng shown n Fg. Fre can orgnate n each foor (.e., three fres are possbe,,, ). Fg shows smpfed event trees deveoped for these fres (ntatng events E 0 ). In ths eampe, n n 4 and n. The rsk (5) may epress fary dverse nformaton, especay when the severty of each o r s represented by more than one sgnfcance measure. In the atter case the rsk of the fre w be assocated wth the matr of sgnfcances s s s K s j K sn s s s K s j K sn M M M O M O M (6) sr sr sr K srj K srn M M M O M O M sn sn s n K s n j K sn n Wth ths matr, one can cacuate n-dmensona vector of epected sgnfcances assocated wth the fre and appy ths vector to, say, a mut-attrbute comparson of consequences of potenta fres, namey, n n n n c rsr, rsr,..., rsrj,..., rsrn (7) r r r r The correspondng components of the vectors c can be summed up and ths w yed the vector n n f c r srj, j,..., n (8) r 0

6 Ignton, st / nd / rd foors Sef-etgushng (manua etgushng) Etngushng by fre brgade Evacuaton routes bocked by smoke, peope trapped n the nd and rd foors/ rd foor Outcomes Lkehood Severty (a) no / / / no no yes 7 / / / 0/ 0 yes 7 / / / 0/ 0 yes 7 4/ 4 4/ 4 4/ 4 (b) no no 0 yes 7 0 yes 7 Fg. Event tree dagrams deveoped for the ntaton of fre n three foors of the budng shown n Fg. : (a) dagrams for the fre ntaton n the st and nd foors (, ); (b) dagrams for the ntaton n the rd foor ( ) where n f s the number of potenta fres. The vector can be used as a mut-attrbute measure of fre safety cacuated by means of quanttatve rsk assessment. The epected sgnfcances n (7) contan the kehoods r, whch n many cases can be estmated ndependenty of s rj (ths ndependence shoud be assumed wth cauton, see Kumamoto and Heney 996). Each r can be epressed as annua frequency (number of occurrences per year). The frequency of reatvey rare occurrences of the fres and so of the outcomes o r can be estmated by means of cassca Bayesan approach to quanttatve rsk assessment (Aven and Pörn 998; Vauro and Jänkää 006; Vadogas and Juocevcus 009). In contet of ths approach, the kehoods r w be estmated n the form of epstemc uncertanty dstrbutons reated to true vaues of r (Zavadskas and Vadogas 009). Such estmatng s usuay carred out by propagatng epstemc uncertantes through such ogca modes of quanttatve rsk assessment as the event trees shown n Fg.. Input nformaton for the cacuaton wth the event tree dagrams are the kehoods of fre ntaton ( 0 ) and branchng probabtes p k. Both 0 and p k can be uncertan n the epstemc sense and so can be the outcome kehoods r of the outcomes o r. The cacuaton of the rsk defned by Eq. (5) conssts n the estmaton of r and assessment of the severtes s r. Input nformaton use for the cacuaton of rsk conssts many n hard statstca data and epert knowedge when ths data s scarce or not avaabe at a. The fre rsk assessment s smar to the genera engneerng rsk anayss. The summaton (7) ndcates,,tota rsk from mutpe scenaros. Ths type of fre rsk anayss, commony referred to as probabstc rsk assessment (PRA) or quanttatve rsk anayss (QRA), s wdey used n the chemca process ndustry and for fre safety assessments of nucear factes (Apostoaks 99), and s begnnng to see broader appcaton n fre protecton engneerng appcatons (SFPE 999 and 000; Magnusson et a. 995; Magnusson 995; Frantzch 998). 0.. Numerca eampe Let us return to the budng shown n Fg.. In the case where the fre safety of ths budng s measured by means of a rsk profe (5), fre scenaros eadng to some specfc and generay adverse outcomes must be dentfed. A smpfed graphca representaton of such scenaros s gven n Fg.. These dagrams assume that fre can be ntated n each of the three foors and thus,,. The kehoods of the outcomes of these scenaros are gven by p p,; n p p p p p (- p) p (- p) (- p ) p (- p) n (- p ) 4 (9) (0) One can see that the nput nformaton requred to cacuate the kehoods r conssts of the fre ntaton kehoods 0 as we as the branchng probabtes p k (k,, ). The ntaton kehoods 0 can be estmated from the annua frequency cacuated for the tota foor area A 8400 m by means of a generased Barros mode (Hasofer et a. 007): f ( A) r c A + c 0 s A , 05 per square metre per annum Then ths frequency of fre ntaton reated to A w be equa to 6 A f ( A) per annum Consequenty the fre can be eported every 6. years n average. As ong as a three foors are used for dentca occupancy, the fre ntaton frequency 0.06a

7 reated to the entre foor area can be A can be dvded by the number of foors and the kehoods 0 obtaned: / a (,, ) Further numerca nput nto the probem s the branchng probabtes p k, the hypothetca vaues of whch are gven n Tabe 6. Puttng these vaues n the epressons (9) and (0) aong wth the fre ntaton kehoods 0 yeds the kehoods of ndvdua outcomes, r (Tabe 7). Tabe 6. Input nformaton n for the quantfcaton of rsk represented by the event tree dagram shown n Fg. Event Symbo Vaue Sef-etngushng of fre p 0. Etngushng of fre by fre brgade p 0.87 Bockage of evacuaton routes p 0.07 The vectors of severtes, s r, are assumed n ths eampe to consst of three components, namey, drect monetary osses due to the fre, (s r ), the number of fre vctms (s r ), and the tme durng whch the use of budng s nterrupted (s r ). Iustratve vaues of components of s r are summarsed n Tabe 7. Wth these vaues as we as the kehoods r, one can cacuate the vectors of epected severtes defned by Eq. (7) and reated to the three ndvdua fre, namey, the vectors c. In ths eampe, the vectors c w have three components: c (05.77 /a; 0.9 vctms/a; months/a) c (4. /a; 0.4 vctms/a; months/a) c (49.06 /a; vctms/a; months/a) As a three fres ead to the outcomes charactersed by the same trpet of severtes, the epected severtes c can be gathered up nto one vector charactersng a possbe fres n the budng: c (89.5 /a; 0.8 vctms/a; months/a ) The atter vector can be seen as a fna resut of a fre safety assessment by means of a forma QRA. Ths vector mpes that one budng s charactersed by three attrbutes havng dfferent unts of measurement. In prncpe, the number of such attrbutes can be ncreased by addng addtona component to the severty vectors s r. Decsons and actons concernng fre safety can be drected towards reducng some or each of them. The cacuaton of the epected severtes c s straghtforward gven the vaues 0 and p k as we as components of s r. Unfortunatey, specfcaton of these vaues s the most probematc part of QRA, especay, ths appes to the branchng probabtes p k. On the other hand, fres n budngs smar to the one consdered n the present eampe are reatvey frequent and we-nvestgated phenomena. One can suggest that the branchng probabtes can be estmated by a combned appcaton of data on smar fres, computer smuaton of fre process and evacuaton as we as epert judgement... The pros and cons of the approach The advantage of an appcaton of QRA methods to the fre rsk assessment s obvous. Fre safety measures cacuated on the bass of the rsk defned by Eq. (5), for nstance, the vector of epected sgnfcances, c, epress the eve of fre safety n a very comprehensve way. The reason for ths s that event tree modeng, quatatve and quanttatve, wdey used for PRA aows dentfyng a foreseeabe scenaros whch can be ntated by gnton or an event causng gnton. In addton, event trees can be adapted to a hghy specfc stuaton n an ndvdua budng subjected to ts own fre hazards. For nstance, PRA-based fre rsk assessment can take nto account such events as: A deberate gnton as an act of sabotage or revenge; Faure of a fre safety system (e.g., sprnkers or fre aarm) eadng to a dangerous escaaton n the course of fre; Strange and unepected behavour of peope durng the fre (e.g., unwngness to act for some tme when fre aarm s actvated). A further advantage of the PRA-based fre rsk assessment es n the very nature of PRA methods. A quantfcaton of rsk n ne wth these methods requres an Tabe 7. Iustratve vaues of the severtes reated to ndvdua fre scenaros represented by the event tree dagram shown n Fg. Fre Outcome kehoods r, a - Scenaro r s r, Severtes s r s r, no of vctms s r, months. 0-5 r r r r r r r r r r r

8 etensve use of statstca data and whch s often combned wth epert judgement. Consequenty, the PRAbased fre rsk assessment s abe to utse genera statstca data on fres, component reabty data, data human reabty, and the vast knowedge of eperts on varous and sometmes hghy specfc aspects of fre safety. Such data and knowedge can be hardy utsed n a drect way when fre safety s assessed by means of fre ndces. A quanttatve part of QRA used for a fre safety assessment aows to utse the state-of-the-art methods deveoped to modeng the physca processes of fre and budng evacuaton. These methods, after some stochastc augmentaton, can be used to estmate branchng probabtes pk (Hostkka and Kesk-Rahkonen 00). The genera engneerng rsk anayss s a wordwde spread methodoogy. It s we-documented by such organsatons as Internatona Atomc Energy Agency (e.g., IAEA 99, 995). Therefore fna and ntermedate resuts of fre-reated appcatons of QRA can be understood and apped n varous countres wth reatve ease. Data necessary for such an assessment can aso be shared word-wde as ong as such data s reevant to a partcuar rsk assessment probem. On the other hand, the comprehensveness of QRA creates stumbng bocks for an appcaton of ths methodoogy to a practca assessment of fre rsk. An accurate rsk assessment requres a great dea of epertse, frst and foremost, n the use of hard data and epert knowedge. QRA s, to a arge degree, a process of an estmaton of probabtes and frequences whch are transformed eventuay nto a rsk profe. Ths process may ncude a subte use of subjectve nformaton n combnaton wth sparse emprca data. As compared to the cacuaton of fre rsk ndces, the estmaton of probabtes and frequences nvoved n a fre-reated QRA may be a demandng and tedous task. The compety of nformaton epressed by a rsk profe can aso be seen as an obstace to a practca appcaton of QRA to the case of budng fres. Most rsk ndces are snge numbers whch can be easy compared and ranked. Contrary to the ndces, a rsk profe s, n essence, a mut-attrbute charactersaton of the budng under assessment. A comparson of two or more rsk profes deveoped for budngs (budng desgns, aternatve fre protecton systems n one specfc budng, etc.) s not straghtforward, especay, when components of the profes are uncertan n the epstemc sense. On the other hand, the methodoogy of mut-attrbute decsonmakng s we-deveoped and can be smoothy apped to such a comparson (Zavadskas and Vadogas 008, 009). Concusons The possbe ways of evauaton of budng fre rsk has been consdered. The probem of such an evauaton s as ubqutous as the hazard of fres n budngs tsef. The attenton was focused on two prncpa approaches to a quantfcaton of fre rsk: the appcaton of fre ndces and a forma assessment of rsk posed by fres by appyng methods of quanttatve rsk assessment (QRA). The- 04 se two prncpa approaches offer two poar etreme possbtes of fre rsk evauaton. The rsk ndces are smpe measures of fre rsk whch can be cacuated wth a reatve ease for most budngs. However, the ndces are consdered to be non-scentfc means of fre rsk evauaton. The forma evauaton of the rsk posed by potenta fres s a rgorous scentfc procedure aowng to reate the event of fre ntaton to potenta outcomes of fre. Fre rsk ndeng and forma fre rsk assessment has ts own pros and cons. The queston whch of these approaches suts better for decson-makng reated to fre safety, nsurance, and desgn of budngs s dffcut to answer. One can ony say that the use of rsk ndces s more practcabe that a forma rsk assessment. Ths s many due to a reatve smpcty of specfyng nput data used to cacuate fre ndces. On the other hand, the rsk assessment requres a very subte specfcaton of nput nformaton whch conssts many of estmated of probabtes and frequences. Resuts of rsk assessment can be ntegrated nto mut-crtera (mut-attrbute) decson makng concernng fre safety. These resuts are epected severtes reated to potenta outcomes of fre: epected monetary osses, number of vctms, epected tme of busness nterrupton due to fre. The rsk ndces, on the other hand, are generay snge numbers whch refect a aspects of fre safety. The fact that specfc nformaton, say, on potenta harm of fre to occupants s usuay hdden n fre ndces makes them dffcut to appy to a comprehensve decson makng. References Apostaaks, G. 99. Fre Rsk Assessment and Management n Nucear Power Pants, Fre Scence and Technoogy : 9. Aven, T. 00. Foundatons of Rsk Anayss. A Knowedge and Decson-Orented Perspectve. Wey, Chchester. Aven, T.; Pörn, K Epressng and nterpretng the resuts of quanttatve rsk anayses, Reabty Engneerng & System Safety 6: 0. do:0.06/s095-80(97) Ayyub, B. M. 00. Rsk Anayss n Engneerng and Economcs. Chapman & Ha/CRC, Boca Raton etc. Budng Research Board Report from the 987 Workshop on Anaytca Methods for Desgnng Budngs for Fre Safety. Washngton: Natona Academy Press, DC. Chow, C. 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