A Review of the Department of Transportation's Plan for Analyzing and Testing Electronically Controlled Pneumatic Brakes Letter Report (Phase 2) (2017)

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  35 FIGURE H-2. According to DOT, there is a notable benefit to ECP brakes, especially in the initial several seconds (critical time). There is about a 34 percent (momentum) advantage for ECP brakes at 10 seconds after initiation. This advantage tapers off to about 15 percent at 20 seconds. 0 20 40 60 80 100 120 0 5 10 15 20 25 Pe rc en ta ge  o f T ot al  T ra in  B ra ki ng  F or ce  (% ) Time (s) Total Train Braking Force ECP DP/EOT Difference

36 Appendix I Additional Validation of FRA Puncture Estimation Methodology from DOT24 Confidence in the DOT Methodology At a recent meeting, the NAS had requested additional metrics that might ensure confidence in the DOT methodology. Elements that address this issue include:  Confidence in the input parameters  Confirmation that the trends of model prediction are in line with expectations  Validation against physical derailment data  Validation against other studies These elements are discussed further in this presentation. Confidence in Input Parameters Calculating ‘Number of Punctures’ As outlined in the “Worked Example” that was provided, the following three elements fully define the number of punctures calculated by the DOT Methodology: 1. Derailment load spectrum 2. Distribution of impactor sizes 3. Car strength characteristics The following slides discuss the DOT’s confidence in each of these parameters. Derailment Load Spectrum The derailment load spectrum is assembled by reviewing the impact forces between any pair of tank cars over 18 simulations for each given speed and brake system combination. The spectrum of impact forces for trains with a conventional brake system at 30, 40, and 50 mph is presented in the next slide.  An inspection of this histogram shows:  The number of impacts increases with increasing speed  The maximum value of the impact force increases with increasing speed 24Briefing material from DOT, dated July 20, 2017.

 T tu This revie are in line 1This chart Give us confide These inc  B w  T sh  T w 1This effec he impact for res in real lif w offers con with expecta is based on pr n that the de nce in the sim lude: oth the sprea ith real life o he distance t ows good co he number of ith increasing tively also con ce magnitud e, based on th fidence that tions. eviously publi Addi railment spe ulation resu d and the av bservations raveled by th mparison cars deraile lateral rail s firms that the es are in line e various im the trends an Derailmen shed work. tional Consi ctrum is deriv lts, also boos erage of the n e rear car, c d increases w tiffness. ground friction   37 with expecte pact tests tha d quantities t Load Spec derations fo ed from the t our confide umber of ca ompared to ith increasin values assum d force mag t have been c associated wi trum1 r Confidence simulation r nce in the der rs derailed h observations g derailment ed in the simu nitudes that w onducted. th the impac esults, other ived derailm as been show from the A initiation for lations are rea ould cause t force histog elements tha ent load spec n to be cons liceville acci ces, and decr sonable. punc- rams t give trum. istent dent1, eases

The ment incid Qua tors from or a sill ty Rail tures and Wor (ATCCRP  T pa These elem As s done by D  E fu impactor dis ent (see next litatively, thi several derai pe impact. induced pun the smaller fr k done by D ) and sponso he average im ctor size from ents offer c hown in the r. Kirkpatric ssentially, th nction of the tribution con slide). s spectrum is lments, wher ctures tend to action of rela r. Kirkpatri red by industr pactor size Dr. Kirkpa onfidence tha following sl k, and presen ese curves re impactor siz Distributio siders a vari consistent w ein, most pun be fewer gi ted impactor ck under the y, has genera from the DO trick’s work t a reasonabl Impactor Car Streng ide, car stre ted in prior p present the e. 38 n of Impacto ety of impact ith puncture ctures are in ven the lack sizes reflects Advanced ted a similar, T’s work (8 (8.4”). e distribution Size Distrib th Characte ngth characte apers and rep force at whic r Sizes or sizes nom sizes observ the 5” – 9” r of stiffness/m this reality. Tank Car C but, probabil .7”) was les of impactors ution ristics ristics, were orts. h a given c inally encou ed by DOT a ange, consist ass associat ollaborative istic impactor s than 4% o was used fo extracted fr ar design wo ntered in a d ccident inve ent with a co ed with rail Research Pro size distribu ff the averag r the analysis om prior ana uld puncture erail- stiga- upler struc- gram tion. e im- . lyses as a

Thes The analy Ther These car The three  T  T  T As presen parameter In ad responds The formance. e research e tical methods efore, the DO strength capa main inputs i he derailmen he impactor s he car strengt ted in the pr s. dition to val appropriately following sli fforts have b used by Dr. T is confide cities are the Su nto the calcu t load spectru ize distributi h characteris ior slides, the idation again to specific ch des list some een sponsore Kirkpatrick h nt about this Car Stre result of prio mmary – Co lation of num m on, and tics DOT has go Trends st specific ph anges in the elements of   39 d by both th ave been val input. ngth Capac r simulation nfidence w/ ber of punctu od reasons t & Expectati ysical data, c input parame this effort th e DOT and i idated throug ities work done b Input Data res are: o have confi ons onfidence in ters. at give the ndustry and h multiple ph y Dr. Kirkpa dence in all the model is DOT confide are well rega ysical tests. trick. of these inpu enhanced w nce in mode rded. t data hen it l per-

40 Trends – Derailed Cars The average number of cars derailed increases with increasing derailment speed. The spread of the number of cars derailed (over each set of 18 simulations) increases with increasing speed. Within each set of 18 simulations:  A higher derailment initiating force leads to more cars derailing  A higher lateral track stiffness leads to fewer cars derailing Besides the fact that the predicted numbers are consistent with derailment observations, these trends are in line with expectations from physics and reality. Trends – Number of Punctures The average number of cars punctured increases with increasing derailment speed. The number of cars punctured reduces with improving car design. The change in number of cars punctured is somewhat proportional to the change in car shell and jacket thickness:  This is consistent with the physics of puncture, plus,  This effect has been demonstrated in prior work by Dr. Kirkpatrick and the Volpe Center. As with the previous slide, these trends are in line with expectations from physics and reality in addition to being consistent with derailment observations. Validation Against Derailment Data Validation Request Prior work presented to the public and NAS has demonstrated that the DOT model outputs are con- sistent with observations from real derailments. At the request of the NAS, the DOT has been assembling additional data on the validation and con- fidence in its methodology This document presents requested data on:  Puncture values from all 18 simulations  Comparisons to the Aliceville incident Puncture Values from 18 Simulations The DOT methodology was designed and intended to capture the relative performance benefits of car designs, speed reductions, or, brake system advancements. It was not intended to capture puncture performance at an individual simulation level. Nonetheless, at the request of the NAS, the number of punctures from each of the 18 simulations (per speed, brake system) was calculated and is presented in the next slide.

Model esti A review  T  T  C Aliceville  90  2  38  le  26  R Following of a 100-c mates (assumin of the data pr he spread of p he average is oncerns that , AL derailm cars, loaded head end loc mph, derail vel grade, tra cars deraile ear loco trave slides comp ar DP train a Punctures f g DOT-111 ta Pu esented in th unctures is i in line with r the ‘averagin Comparison ent oil train os, 1 DP loco ment initiated ck on raised d, 25 total pu lled 1,240 fe are this to the t 40 mph. Comparison rom FRA Si nk design) co ncture Valu e prior slide f n line with re eal life expec g’ process wa of FRA Sim at rear at head end embankment nctures et FRA simula of FRA Sim   41 mulations an mpared to actu es from 18 S or all 18 sim al life derailm tations s hiding poo ulation to a of train tion in which ulation to a d Actual In al incidents imulations ulations, sugg ent observa r quality base Particular I the derailme Particular I cidents ests that: tions data are unf ncident nt was initia ncident ounded. ted at the hea d end

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Whi that the m in the actu  P  N  N  T m Prediction  C [T R  D (2 D CPR AAR formance  R  T w While the the fact th AAR valu 1Across all 2Calculated le it is difficu odel faithful al derailmen ile-up configu umber of der umber of pun he distance t odeling meth Val s from the D onditional Pr he DOT wo SI-AAR on t erailment mo 007 ASME . Jeong, et. al Review (Co and DOT e of a DOT-11 SI-AAR data he DOT meth hen averaged individual C at the DOT c es include de DO speeds. from the ratio Comparison lt to make pi ly represents t. The combin rations, ailed cars, ctures, and ravelled by odology. idation Aga OT study we obability of R uld be happy his topic (wh dels develop RTDF Con .) nditional Pr stimates of C 7 car to a DO predicts a 50 odology pre over speeds PR values m alculations ar railments at m T and AAR of number of of FRA Sim le-up compar the character ation of mul the rear loco inst Other St re also compa elease (CPR to update it ich is expecte ed by the Vo ference, “Eq obability of PR benefits T-111 car (d % to 60% re dicts similar from 30 to 5 ay be higher e done over uch lower s - CPR Comp cars puncture   43 ulation to a isons withou istic saw-too tiple close co motive provi udies Comp red to: ) values from s compariso d shortly)] lpe Center uations of M Release) Refe of improved ue to car con duction in pu reduction in 0 mph). according to a higher rang peeds. arison For d to number of Particular I t detailed geo th buckling rrelations be des confiden arison to Ot the RSI-AA n once a rev otion for r to next slid car strength a struction only nctures number of pu the DOT cal e of speeds (3 Improved C cars derailed. ncident metric data, and compact tween the ce in the va her Studies R Report (RA ised report is Train Derail e for plots of re similar. C ): nctures (in t culations, thi 0 – 50 mph) ar Strength it can be obs groupings as lidity of the -05-02) published b ment Dynam comparisons omparing th he mid-50% s likely repre , whereas the erved seen FRA y the ics”, e per- range sents RSI-

DOT results fro  Pu  M These two of Motion Results ar separation  T The  C  C  V  V As demon come from puts from estimates fo m two derail rpose-built m odel develop Volpe mode for Train De e similar and , whereas the his would exp DOT has sev onfidence in onfirmation t alidation aga alidation aga strated throu just one po the model. DOT M r number of ment models odel ed using the ls produced s railment Dyn DOT M trends are th DOT model lain the min eral elements the input para hat the trends inst physical inst other stu ghout this pr int of validat ethodology cars deraile developed at commercial r imilar result amics”, D. J ethodology e same. The V does. or differences S that address meters of model pr derailment d dies esentation, th ion, but from 44 Compared t d under vario Volpe: igid-body dy s. Reference: eong, et. al. Compared t olpe model between the ummary model confid ediction are i ata e DOT’s con a review of o Volpe Mod us derailmen namics softw 2007 ASME o Volpe Mod does not allo model predi ence concern n line with ex fidence in its several elem els t scenarios a are, ADAMS RTDF Conf els w for full cou ctions s, including pectations approach an ents of both re compared . erence, “Equa pler breakag : d results, doe inputs to and with tions e and s not out-