Risk-Based Optimization of Rail Defect Inspection Frequency for Petroleum Crude Oil Transportation

Transcription

1 Rsk-Based Optmzaton of Ral Defect Inspecton Frequency for Petroleum Crude Ol Transportaton Xang Lu and C. Tyler Dck The rapd expanson of producton of North Amercan petroleum crude ol from shale has led to a sgnfcant ncrease n ral transport of crude ol. Broken rals are frequent causes of tran accdents. Ultrasonc ral defect nspecton s wdely used to prevent tran accdents caused by broken rals, thereby reducng the hazardous materals transportaton rsk. Ths paper descrbes a new methodology to estmate unt-tran crude ol transportaton rsk by the frequency of locaton-specfc ral defect nspecton. The rsk model was used to develop a Pareto optmzaton model that determnes the frequency of segment-specfc ral defect nspecton to reduce the total-route rsk n a cost-effectve manner. A numercal case study was developed to llustrate the applcaton of the rsk analyss and optmzaton models. Ths research s ntended to provde new methods and nformaton to assst the ralroad ndustry n optmzng nvestment n nfrastructure mprovement, thereby mtgatng the rsk of ral transport of crude ol and other hazardous materals. North Amerca s experencng sgnfcant growth n the producton of petroleum crude ol from shale, drven by technologcal advancements n hydraulc fracturng and horzontal drllng. Ths growth has led to a dramatc ncrease n the transport of crude ol by ral. In 2005, there were only 6,000 tank carloads of petroleum crude ol shpped n the Unted States. By 2014, ths number had ncreased to more than 500,000, an 80-fold ncrease (1). Although more than 99.99% of ral carloads of crude ol safely reach ther destnatons wthout a release ncdent (2), transport of crude ol by ral stll represents a sgnfcant safety concern for both the publc and prvate sectors because of the potental mpact of a release on human health, property, and the envronment. Recently, a spate of accdents nvolvng trans transportng crude ol n North Amerca attracted more ntense attenton to the safety of ral transport of crude ol and other hazardous materals. There are two basc strateges for reducng the rsk of transportng crude ol (and hazardous materals n general) by ral: (a) reducng the lkelhood of a release ncdent and (b) reducng the consequences of a release (3, 4). Ths study focuses on the former: reducng the lkelhood of hazmat release ncdents by preventng tran accdents. X. Lu, Department of Cvl and Envronmental Engneerng, Rutgers Unversty, CoRE 606, 96 Frelnghuysen Road, Pscataway, NJ C. T. Dck, Ral Transportaton and Engneerng Center, Unversty of Illnos at Urbana Champagn, 1241 Newmark Cvl Engneerng Laboratory, MC-250, 205 North Mathews Avenue, Urbana, IL Correspondng author: X. Lu, xang.lu@rutgers.edu. Transportaton Research Record: Journal of the Transportaton Research Board, No. 2545, Transportaton Research Board, Washngton, D.C., 2016, pp DOI: / In terms of accdent preventon, t s frst necessary to dentfy the major causes of tran accdents nvolvng hazardous materals. All ralroads operatng n the Unted States are requred to submt detaled reports on all accdents exceedng a monetary threshold of damage to on-track equpment, sgnals, and track nfrastructure (5). FRA of the U.S. Department of Transportaton (DOT) comples the submtted accdent reports nto ther Ral Equpment Accdent Database. Ths database contans useful nformaton regardng the tme, locaton, crcumstances, cause, and consequence of each tran accdent. Analyss of ths database shows that broken rals are the leadng causes of cars carryng hazardous materals releasng ladng (Fgure 1). Broken rals have resulted n several recent deralments nvolvng crude ol and other flammable lquds, such as those n New Brghton, Pennsylvana, n 2006; Panesvlle, Oho, n 2007; Arcada, Oho, n 2011; Alcevlle, Alabama, n 2013; and Lynchburg, Vrgna, n Therefore, preventng the development of broken rals has been dentfed as a promsng strategy to mtgate the rsk of ral transport of hazardous materals (6 12). There are varous approaches to preventng broken rals, ncludng ral grndng (13), lubrcaton (14), ral replacement (15), and nondestructve ral defect nspecton (16 18). Ths paper focuses on ultrasonc ral defect nspecton, a prmary nondestructve nspecton technology that has been used by ralroads n the Unted States snce the 1930s. The prncpal objectve of ultrasonc ral defect nspecton s to dentfy ral defects before they grow to crtcal fracture szes and potentally cause tran deralments and correspondng hazardous materals release ncdents. How frequently ral defect nspectons should be performed s a key decson wth sgnfcant safety and cost mplcatons. Gven resource lmtatons, t s crucal to determne the optmal frequency of ral nspecton to mnmze rsk n a cost-effectve manner. To date, the authors are unaware of any publshed study drectly addressng the optmzaton of ral defect nspecton frequency as a means to manage the rsk of transportng crude ol by ral. Both the total-route rsk and the number of mles nspected were mnmzed n ths study by the development of a rsk-based Pareto optmzaton model to determne locaton-specfc ral nspecton frequency. Usng the methodology developed n ths paper, the ralroad ndustry can evaluate the crude ol transportaton rsk caused by broken rals, dentfy hgh-rsk hot spots that may requre addtonal nspectons, and better allocate nspecton resources accordngly. Although ths paper focused on crude ol transported n unt trans, the methodology can be adapted to other hazardous materals n other types of trans. Ths paper s structured as follows: (a) a revew of relevant lterature, dentfyng knowledge gaps and elaboratng on the objectves 27

2 28 Transportaton Research Record 2545 Number of Hazmat Cars Releasng Broken ral: transverse compound fssure 56 Broken ral: head and web separaton 37 Other ral and jont bar defects 25 Broken ral: weld (feld) 20 Journal (roller bearng) falure from overheatng Broken ral: detal fracture Washout, ran, slde, flood, snow, ce damage to track Jont bar broken (nonnsulated) Broken rm Cause under actve nvestgaton 9 9 FIGURE 1 Number of hazmat cars releasng n freght tran deralments on U.S. ralroads n accdents from 2002 to of ths research; (b) an explanaton of a new methodology to quantfy the relatonshp between the rsk of transportng crude ol by ral and the frequency of ral defect nspecton; (c) a dscusson of the mplementaton of the methodology and parameter estmaton; (d) an applcaton of the methodology to a numercal case study, ncludng manageral nsghts; and (e) a summary of the prncpal research fndngs and a dscusson of the lmtatons of the paper and possble future research drectons. Lterature Revew and Objectves of the Study Lterature Revew The safety of hazardous materals transportaton has long been a focus n the ralroad communty. A number of prevous studes have addressed safety and rsk aspects of hazardous materals transportaton by ral: a summary of these efforts s presented below. Some studes have analyzed how mprovng tank car safety desgn could reduce rsk (19 23). These studes addressed the trade-off between transportaton safety and effcency (n terms of tank car ladng capacty) assocated wth tank car desgn modfcaton. Wth respect to operatons, Glckman estmated the effectveness of routng changes on rsk mtgaton (24). Kawprasert and Barkan developed an optmzaton model to dentfy the optmal network desgn for hazardous materals transportaton by ral (25). They also nvestgated the relatonshp between the rsk of hazardous materals release and tran deralment speed and analyzed the safety beneft of reducng tran speeds, wth and wthout nfrastructure upgrades (26). The Center for Chemcal Process Safety has provded gudelnes for performng effectve emergency response practces (27). Recognzng that the probablty of tank car deralment vares by the tank car s poston n a tran, Bagher et al. developed rsk models to optmze the placement of hazardous materals tank cars (28 30). In the Unted States, more than 70% of freght tran deralments on manlnes were caused by nfrastructure or equpment falures (31). Ouyang et al. have dscussed the optmal deployment of waysde detectors to montor equpment condton, thereby reducng the rsk of tran accdents (32). Schlake et al. have analyzed the effects of waysde detector mplementaton on ralroad safety and effcency (33). And fnally, nfrastructure qualty s closely related to the rate of tran deralment (34, 35). FRA dvdes track qualty nto fve prncpal classes commonly used by freght ralroads n accordance wth FRA track safety standards (8). At hgher FRA track classes, hgher maxmum operatng speeds are allowed, but correspondngly more strngent track engneerng and safety standards apply. Kawprasert and Barkan (26) and Lu et al. (8) analyzed an upgrade n track class as a means to reduce the rsk. An upgrade to track class ndcates an overall mprovement n track safety standards, commensurate wth the ncrease n the maxmum speed. Of the types of nfrastructure falures, ral falures are the prmary cause of accdents (7, 31). Pror research has focused on understandng the process of ral defect formaton. More frequent ral defect nspecton s assocated wth a lower rsk of ral falure (17, 36), because more ral defects can be dentfed before they grow large enough to cause ral falures that may result n tran deralments. In practce, lmtatons on resources and track access tme constran annual nspecton frequency. Therefore, an effectve schedule of ral defect nspecton can reduce occurrences of tran deralments, thereby mtgatng hazardous materal transportaton rsk. Knowledge Gaps The authors are unaware of any publshed model that explctly descrbes how hazardous materals transportaton rsk s related to ral defect nspecton frequency, except for a prevous study by Lu et al. (37). However, that study does not account for the specfc characterstcs of possble multple tank car deralments and releases when crude ol s shpped n unt trans. Addtonally, the current practce s to nspect all segments on the same route wth equal frequency. As track segments vary by track qualty and by the densty of the

3 Lu and Dck 29 adjacent populaton, they may have dfferent rsk levels. If so, there s a need to dentfy hgh-rsk track segments and possbly nspect them more frequently to acheve more effectve mtgaton of the total-route rsk. Research Objectves Ths research was developed to acheve the followng objectves: 1. Develop a new model to quantfy the rsk of transportng crude ol by ral by nspecton frequency, 2. Develop a Pareto optmzaton model to determne rsk-based ral nspecton frequences for dfferent track segments, and 3. Provde manageral nsghts regardng effectve preventon of broken rals for management of the rsk of transport of crude ol and other hazardous materals by ral. Ths paper s ntended to provde new knowledge, manageral nsghts, and mplementaton tools to assst the ralroad ndustry n optmzng ral nspecton frequences through rsk analyss and optmzaton models. In the long run, ths research can evolve nto a larger, ntegrated rsk management framework to reduce the hazardous materals transportaton rsk on the bass of multple alternatve safety mprovement strateges, alone or n combnaton. Methodology Rsk Analyss Model Ths secton ntroduces a rsk analyss methodology to estmate the rsk of ral transport of crude ol as a functon of ral nspecton frequency. In general, hazardous materals transportaton rsk can be defned as the multplcaton of the lkelhood of a release ncdent and the release consequences (25 27, 37 39). If the populaton n the evacuaton zone s used as a measure of the release consequences, the rsk s then nterpreted as the expected number of affected people. The annual crude ol transportaton rsk caused by broken rals s expressed as follows: R= P C (1) R = annual crude ol transportaton rsk caused by broken rals on the th track segment, P = annual frequency of ncdents of release of crude ol caused by broken rals on the th track segment, and C = consequence of a release (e.g., affected populaton) on the th track segment. The probablty of a crude ol release ncdent s a product of the probablty of a tran accdent and the probablty that the tran accdent wll cause at least one crude ol tank car to release contents. Because a large porton of crude ol traffc s shpped n unt trans wth 80 to 120 tank cars, all loaded wth crude ol, ths rsk analyss model was specfcally developed for a unt-tran operaton of crude ol. The rsk model can be adapted to other types of trans n future research. D [ ( ) ] P= P( A) 1 1 P( R) (2) P (A) = frequency of crude ol tran accdents caused by broken rals, P (R) = condtonal probablty of release by a deraled crude ol tank car, and D = average number of crude ol tank cars deraled per accdent. The rate of tran accdents caused by broken rals can be estmated as a product of the rate of broken rals and the percentage of broken rals that cause accdents (there s presumably no dfference n the probablty of a broken ral causng a crude ol tran accdent and other types of freght tran accdents): P( A)= S L θ V (3) S = annual number of broken rals per mle, L = segment mleage, θ = percentage of broken rals causng tran accdents [a prevous study by Zarembsk and Joseph (13) found that 0.84% of broken rals resulted n tran accdents], and V = percentage of annual number of crude ol trans among all types of trans travelng through a segment. The annual number of broken rals per mle (S ) by nspecton frequency can be estmated by usng an engneerng model orgnally developed by the U.S. DOT Volpe Transportaton Systems Center (16, 17). Ths model represents a comprehensve mechanstc study of ral defect formaton and growth. However, ths rsk analyss framework offers the flexblty for ndustry practtoners to substtute other vald models of the occurrence of broken rals and nspecton frequency n place of Equaton 4. α β + K β S = M e e = +λ T j 1 1 µ K N α j, 1 Nj, 1 Xj, λ T µ K M = number of 39-ft ral sectons per track-mle (273 n ths model); α = Webull shape factor (3.1 n ths model); β = Webull scale factor (2,150 n ths model); λ = slope of the number of ral breaks per detected ral defect versus nspecton nterval curve (0.014 n ths model); µ = mnmum ral nspecton nterval [10 mllon gross tons (MGT) n ths model]; N,j 1 = ral age (cumulatve gross tonnage on the ral) at the ( j 1)th nspecton on the th track segment, N,j = N,j 1 + X,j ; X,j = traffc volume (n MGT) between the ( j 1)th and jth nspecton on the th track segment; T = annual traffc densty (n MGT) on the th segment; and K = annual ral defect nspecton frequency on the th segment. Equaton 4 ndcates that the annual number of broken rals per mle s a functon of nspecton frequency. If all else s equal, the hgher the nspecton frequency, the lower the rsk of broken rals. When Equaton 1 and Equaton 4 are combned, the route-specfc (4)

4 30 Transportaton Research Record 2545 crude ol transportaton rsk caused by broken rals can be expressed as follows: R route = N j= 1 = 1 K α β + β M e e +λ T 1 µ K N α j, 1 Nj, 1 Xj, D { 1 [ 1 ( )] } LθV P R C λ T µ K N s the number of track segments on a route. All other parameters are segment specfc and have been defned prevously. Equaton 5 presents an engneerng rsk analyss model to quantfy the rsk due to broken rals of ral transport of hazardous materals. The followng secton covers statstcal parameter estmators needed for mplementng the rsk model n the context of transportaton of crude ol by ral. Parameter Estmaton The total-route rsk s estmated by estmatng a number of parameters, ncludng the number of cars deraled per deralment caused by a broken ral (D ), the condtonal probablty of release by a deraled crude ol tank car [P (R)], and the consequence of a release ncdent (C ). The parameters were developed on the bass of the best data avalable to the authors. When no data were avalable, the most relevant nformaton from the lterature was used. Number of Cars Deraled per Deralment Caused by a Broken Ral, D After a tran deralment, the number of cars deraled s affected by tran speed (34, 35). As descrbed earler, maxmum speed s assocated wth FRA track class, wth hgher FRA track classes correspondng to greater maxmum speeds. In general, FRA Track Class 1 (maxmum 10 mph) and Track Class 2 (maxmum 25 mph) represent lower-speed tracks, as Track Class 3 (maxmum 40 mph), Class 4 (maxmum 60 mph), and Class 5 (maxmum 80 mph, n sgnaled track terrtory) represent tracks wth hgher operatng speeds. Because of the speed dfference, hgher track classes tend to have more cars deraled. Data from the FRA Ral Equpment Accdent Database from 2000 to 2014 were used to calculate the average number of ralcars deraled per freght tran deralment on Class I ralroad manlnes. It was found that, on average, a freght tran deralment caused by a broken ral on track of hgher classes (Class 3 to Class 5) caused 16 ralcars to deral, as approxmately nne ralcars deraled on track of lower classes, Classes 1 and 2. Condtonal Probablty of Release by a Deraled Tank Car, P (R) The condtonal probablty of release of a deraled tank car reflects ts safety performance n accdents (19 23). The Assocaton of Amercan Ralroads and the Ralway Supply Insttute have mantaned an ndustrywde tank car safety database snce the 1970s. Ths database records detaled nformaton regardng the desgn, accdent speed, and release status of each deraled or damaged tank car n a tran accdent. Although ths propretary database s not publcly avalable, the Assocaton of Amercan Ralroads and (5) the Ralway Supply Insttute perodcally publsh average tank car release probabltes. The latest tank car safety statstcs for tank cars transportng petroleum crude ol, publshed by the Assocaton of Amercan Ralroads, were used n ths paper. On May 1, 2015, the U.S. DOT ssued a fnal rule for the new specfcaton standard for crude ol tank cars, namely the DOT-117 (TC-117 n Canada) tank car (40). Accordng to the Assocaton of Amercan Ralroads, the condtonal probablty of release of a deraled DOT-117 tank car s.042 (41), whch means that out of every 100 cars of ths type that derals, an average of four tank cars s expected to release contents. Although ths was the best nformaton avalable for ths paper, there may be uncertanty regardng the probablty of tank car release n dfferent accdent condtons. The latest publshed tank car safety statstcs were used n ths paper to llustrate the overall methodology. Future research should be drected toward a better understandng of the safety performance of crude ol tank cars under specfed accdent characterstcs. Consequences of a Tank Car Release Incdent, C Release consequences can be evaluated by several metrcs, ncludng property damage, dsrupton of servce, envronmental mpact, human mpact (e.g., number of people potentally exposed to a release), ltgaton, or other types of mpacts. Among these consequence measures, populaton n the affected area (to be protected or evacuated) has often been used n prevous studes (25, 26, 42 44). The hazard exposure model provded n the U.S. DOT Emergency Response Gudebook ncludes recommendatons for the calculaton of affected areas (45). In ths paper, the affected area s assumed to be a crcle wth a 0.5-m radus on the bass of the Emergency Response Gudebook recommendaton for a fre caused by flammable hazardous materals releases. Once the affected area has been determned, the number of people affected can be estmated by multplyng the sze of the affected area by the average populaton densty wthn the affected area. Pareto Optmzaton of Ral Inspecton Frequency Ralroads often use a road ral vehcle that can operate both on ralway tracks and on conventonal roadways to nspect ral defects. Ths type of nspecton method allows for dfferent nspecton frequences on dfferent track segments. Skppng nspecton of certan lower-rsk segments mght enable more frequent nspecton of hgher-rsk track segments thus maxmzng the magntude of rsk reducton. There are two prncpal factors consdered n ral nspecton plannng, namely the total-route rsk and the total mles nspected. Each track segment can be assgned ts own nspecton frequency (denoted as K ). The deal scenaro (utopan scenaro) s the mnmzaton of totalroute rsk wth the fewest mles nspected. Mathematcally, ths can be formulated as a multattrbute decson model: mnmze RK (, K,..., K ) mnmze L( K, K,..., K ) decson varables K, K,..., K R = total hazardous materals transportaton rsk on a route, L = total mles nspected, and K = annual nspecton frequency on the th track segment. N N N

5 Lu and Dck 31 Ths concept can be llustrated by a smple hypothetcal example. It s assumed that a route has fve track segments, and each segment can be assgned an annual nspecton frequency of 2, 3, 4, 5, 6, or 7 nspectons per year. In total, there are 6 5 (7,776) possble combnatons of ral nspecton frequency schedules on ths route. For a gven number of total mles nspected, some nspecton schedules could result n lower rsks than others. These optmal schedules consttute a so-called Pareto fronter. The Pareto fronter represents the optmal schedulng of ral defect nspecton frequency gven a total mleage to nspect. The Pareto solutons can be developed by usng the followng algorthm (R and L represent the total rsk and nspected mleages, respectvely): 1. Compute R and L for all possble nspecton schedules; set = 0 (base case); ntalze the set of Pareto optmal solutons, S = { }. 2. From the th schedule, fnd the schedule wth the closest L and a lower R than the current R(). 3. Insert the soluton schedule ( + 1) that has the mnmum R from the schedules dentfed n Step 2 nto the set of Pareto optmal solutons. 4. Repeat Steps 2 and 3 untl = total number of schedules mnus 1. In the followng secton, a numercal example s developed to llustrate the applcaton of the Pareto optmzaton model for determnng segment-specfc annual ral defect nspecton frequency. Case Study In ths secton the methodology s appled to a numercal example. For convenence of llustraton, the analyss focused on one route. The methodology can be adapted to a ral network n a future study. Route Informaton Securty-senstve nformaton was preserved n ths study by the use of an anonymous, actual hazardous materals ral shpment route, whch may not necessarly have crude ol traffc. The purpose was to llustrate the mplementaton and mplcatons of the rsk and optmzaton models, wthout trggerng any possble securty ssues. The route nformaton was analyzed and dsplayed on a geographc nformaton system platform. The populaton densty along each track segment was estmated by lnkng U.S. census data to route data by usng geographc nformaton. The geographc nformaton system analyss dvded the 2,273-m route nto 1,164 track segments. The majorty of the route segments were n sgnaled terrtores and mantaned to meet FRA Class 4 and Class 5 standards. U.S. census data ndcated that the average populaton densty along ths route was 349 people per square mle. Table 1 summarzes the route nformaton. Baselne Rsk TABLE 1 Route Informaton On the case-study route, t was assumed that the average ral age (n terms of cumulatve tonnage on the ral) was 1,000 MGT, annual traffc densty was 80 MGT, and the crude ol was shpped n the new DOT-117 tank car. On average, 25% of the trans on ths corrdor were crude ol unt trans. It was also assumed that all segments on ths route were nspected three tmes per year. By usng these assumptons wth Equaton 5, t was possble to determne that the baselne annual rsk on ths route was 693. Ths value means that annually 693 people were expected to be affected by a crude ol unt-tran release ncdent caused by broken rals on ths corrdor. Identfcaton of Rsk Hot Spots Value Total length (m) 2,273 Number of segments 1,164 Dstrbuton of track class (%) Class Class Class Class Class Average populaton densty per square mle 349 For practcal consderatons, segment-specfc rsk was classfed nto three categores (low rsk, medum rsk, hgh rsk), and nspecton frequency requrements were assumed to be the same for segments wthn the same rsk category. The Jenks optmzaton algorthm was used to delneate rsk categores. Ths optmzaton algorthm mnmzes the varance wthn the same category and maxmzes the varance between dfferent categores (46). Ths classfcaton algorthm s wdely used and has been mplemented n Esr s ArcGIS software. Table 2 llustrates the number of segments, the mleage, and the rsk for each rsk category. The 22 track segments wth the hghest annual rsk account for only 4% of the route length but 29% of the total-route rsk. These hgh-rsk segments are located n hghly populated areas, wth a populaton densty of more than 1,000 people per square mle. Pareto Optmal Ral Defect Inspecton Frequency The model developed n ths paper dd not schedule ral testng solely on the bass of the broken ral rate. Rather, crude ol transportaton rsk (dependent on broken ral rate, probablty of tran deralment, number of tank cars releasng contents, and affected populaton) was used as a proxy to optmze ral-testng schedules. Addtonally, the optmzaton model n ths paper dd not explctly account for certan regulatory and engneerng requrements for schedulng ral-testng frequences. In future research, the methodology can be TABLE 2 Classfcaton of Annual Rsk on Segments on the Case Study Route Rsk Category Number of Segments Total Mleage (%) Total Rsk (%) Low (0 to 1.63) 1, Medum (1.63 to 6.04) Hgh (6.04 to 17.75) Total 1,

6 32 Transportaton Research Record 2545 adapted to account for addtonal constrants related to ral-testng schedules. For llustraton, wthn each rsk category specfed above, sx possble annual nspecton frequences can be consdered on those segments, rangng from two to seven nspectons per year. Two nspectons per year correspond to an nspecton nterval of approxmately 180 days (365/2). If there are three rsk categores and each rsk category has sx possble annual nspecton frequences, there are 6 3 (216) possble combnatons of ral nspecton schedules. For example, a schedule could call for all track segments to be nspected fve tmes per year; ths schedule would be denoted as (5, 5, 5). An alternatve nspecton schedule could be as follows: the low-rsk track segments could be nspected four tmes per year, medum-rsk tracks could receve sx nspectons per year, and hgh-rsk tracks could be nspected seven tmes per year; ths sample scenaro would be denoted as (4, 6, 7). Compared wth the frst scenaro (wth an nspecton of all tracks fve tmes per year), the alternatve schedule would reduce the route rsk by 17%, whle the total nspected mleage would be reduced by 13%. Ths example ndcates that optmzaton of rsk-based ral defect nspecton could acheve substantal rsk reducton n a cost-effectve manner (assumng that nspecton cost s related to the number of track mles nspected). The estmated crude ol unt-tran transportaton rsk caused by broken rals and total mleage nspected for each possble ral nspecton schedule was quantfed and plotted. Wth the same number of mles nspected for each schedule, some nspecton schedules resulted n lower rsk than others. These optmal schedules consttute a Pareto fronter (Fgure 2a). The Pareto fronter represents the optmal schedulng of ral defect nspecton frequency gven a total mleage to nspect. Thus, the Pareto fronter demonstrates the optmal schedulng gven lmted nspecton resources. Ultmately, a multattrbute decson model can be developed to determne the nspecton frequency on the bass of the decson maker s preferences for the amount of rsk versus cost of nspectons (nspected mleage as a proxy) and the trade-off between these or other attrbutes. In Fgure 2b, the segment rsk s classfed nto four categores (each wth ts own nspecton frequency), and the correspondng Pareto fronter s dentfed. recommended decson solutons. The approach could potentally be ntegrated wth ralroad enterprse nfrastructure and mantenance management systems to enable a better-nformed decson process to manage hazardous materals transportaton rsk n a cost-effcent fashon. Contrbutons to Industry Practce The ralroad ndustry s ncreasng the use of rsk-based approaches to mprove track nspecton effcency. One common practce s to nspect all segments on the same route at the same frequency. Ths research proposed an alternatve, rsk-based approach n whch certan track segments mght be nspected more frequently than others. Ths approach s practcally feasble gven that many ralroads use bmodal road ral nspecton vehcles for the detecton of broken rals. Ths type of vehcle can run on roadways and ralway tracks. Skppng nspecton of certan lower-rsk segments mght enable more frequent nspecton of hgher-rsk track segments, thus maxmzng the magntude of rsk reducton. One practcal decson would be the rsk categorzaton of dfferent track segments. The rsk analyss model and mplementaton protocol developed n ths paper can potentally assst the ndustry n prortzng nvestment to mprove ral nspecton effcency and reduce the assocated transportaton rsk. Concluson Ths research focused on assessng the relatonshp between the rsk of broken rals and crude ol unt-tran transportaton rsk. The model was used on an example route to demonstrate the safety effectveness of optmzng ral nspecton frequency for rsk reducton. The analyss showed that ncreased nspecton frequency on a small number of hgh-rsk segments mght sgnfcantly reduce the overall route rsk wth a mnmal ncrease n requred resources. The model can be further developed and ncorporated nto a larger rsk-management framework for mprovng ral safety n a cost-effcent manner. Dscusson of results Contrbutons to the Lterature Ths research developed a new methodology to evaluate crude ol transportaton rsk caused by broken rals by usng the annual ral defect nspecton frequency. The analyss shows that effectve schedulng of ral defect nspecton could reduce the rsk of broken rals, thereby reducng crude ol transportaton rsk from deralments caused by broken rals. The model can be adapted to account for segment-specfc nspecton frequency as dscussed above. Addtonally, the model can be further developed to quantfy the effectveness of a number of other broken-ral preventon technques (e.g., mprovng detecton accuracy, addng crcuts to nonsgnaled track terrtores) for reducng crude ol unt-tran transportaton rsk. Ultmately, ths methodology could lead to the development of an ntegrated nfrastructure management framework to reduce tran accdents, thereby reducng the rsk of transportng crude ol or other hazardous materals by ral. In addton, the methodology developed n ths paper ntegrated accdent, traffc, nfrastructure, and geographc nformaton from varous databases to mplement a complcated algorthm and yeld Future Research Ths paper focused on crude ol transportaton rsk caused by broken rals. In the next step there should be a consderaton of a varety of other factors affectng ralroad transportaton rsk, such as other track falures, rollng stock condton, operatng speed, routng, and emergency response. Addtonally, future research can account for other factors that may affect the safety effectveness of ral defect nspecton, such as the speed of the nspecton vehcle, probablty of detecton, axle load, and others (47, 48). Furthermore, ths paper concentrated on unt-tran shpments of crude ol n whch all cars n the tran contan crude ol. Future research can be drected toward development of more sophstcated rsk models for other types of crude ol trans, accountng for the placement of crude ol cars n a tran. Future research can also account for possble nterdependent tank car releases wthn the same tran accdent (49). In addton to physcal mpacts n a deralment, future research should account for tank car releases caused by thermal tear. In a crude ol unt-tran deralment, a fre frequently ensues because of the flammablty of crude ol. These fres can engulf other deraled tank cars that dd not fal durng the ntal deralment. Hot fre weakens the tank structure,

7 Lu and Dck 33 Non Pareto optmal Annual Crude Ol Transportaton Rsk Caused by Broken Rals Pareto optmal Mles Inspected (a) Non Pareto optmal Annual Crude Ol Transportaton Rsk Caused by Broken Rals Pareto optmal Mles Inspected FIGURE 2 Pareto optmzaton of crude ol transportaton rsk caused by broken rals, by total mles to nspect: (a) three categores of segment rsk, all wth the same nspecton frequency, and (b) four categores of segment rsk, all wth the same nspecton frequency. (b)

8 34 Transportaton Research Record 2545 potentally resultng n a sudden release of large quanttes of product (1). Ultmately, an ntegrated rsk-management framework can be developed to optmze the allocaton of resources to mnmze the rsk n the most cost-effcent manner. Acknowledgments The frst author was funded n part by the Department of Cvl and Envronmental Engneerng; the Center for Advanced Infrastructure and Transportaton, whch s a U.S. DOT Offce of the Assstant Secretary for Research and Technology (OST-R) Natonal Unversty Transportaton Center; and the School of Engneerng, all at Rutgers Unversty. The second author was supported n part by the Natonal Unversty Ral Center, NURal, a U.S. DOT OST-R Ter 1 Unversty Transportaton Center. References 1. Barkan, C. P. L., X. Lu, and M. R. Saat. Enhanced Tank Car Desgn Improves the Safety of Transportng Crude Ol and Alcohol by Ral. TR News, No. 298, July Aug. 2015, pp Assocaton of Amercan Ralroads. Movng Crude Ol Safely by Ral. 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