IPAT. Iowa Pavement Analysis Technique. A concept for single segment and systemic evaluation of paved roadways

Transcription

1 IPAT Iwa Pavement Analysis Technique A cncept fr single segment and systemic evaluatin f paved radways Presented by: Iwa Cunty Engineers Assciatin Service Bureau Steve De Vries, P.E., Exec. Directr Danny Waid, P.E., Sec. Rads Research Engineer August 16,

2 *IPAT Origins... Onging need t answer key questins: Segment Level: What is tday s cnditin, what s the target, when t we get there? What ptins are available? Netwrk Level: What is verall status? What is the trend? What needs t be dne when? Need t cmmunicate pavement issues t the public: Calls fr simple, easy t understand representatins: RSL mile years Need a way t assemble statewide summary Desire t cnsume cnditin data frm all surces Autmatic Distress Data Cllectin, Field CPI determinatins, direct bservatin and analysis, IRI, FWD all prduce useful data. Ability t integrate all assessments wuld achieve best pssible predictin f future cnditin trajectries FHWA and DOT asset management initiatives Participatin in ITAM awakened cunties t need fr new tls Wanting t fulfill the visin withut diverting t much staff time t perating and maintaining a system. Desire t understand full pavement picture: Distress data + structure + traffic + weathering 2

3 Sample RSL chart RSL Remaining Service Life. Chart belw illustrates gal: t be able t cmmunicate status and need t public and elected fficials. 250 mile system lses 250 mile-years f RSL annually Need target ideal graph t sht fr. 3

4 Sught an all attributes analysis methd: Cncluded the we need mre than just surface cnditin t be able t predict future cnditin trends. Tw pavements f identical cnditin can have significantly different remaining lifetimes. Need t knw additinal things t have full picture: Original ESAL capacity and design lifetime Depends n layer ages, prperties, depth in slab and prir wear Impacts f bth traffic (ESALs) and weathering/materials deteriratin Pavements wear ut frm bth traffic and envirnmental factrs Tally f cnditin bservatins at pints in time helps see trajectry but can t fully explain it. 4

5 ICEA s delegates t ITAM respnded t the afrementined issues by gradually synthesizing the IPAT cncept Lked fr a methd that culd: Take int accunt distress date, traffic, materials, weathering Be able t evaluate bth frm single segment and netwrk perspectives Enable access t data and analysis in bth field and ffice Be able t integrate data frm any and all surces Supprt prgressively tuning mdel f any segment s life ver time. Have credible sphisticatin under the hd yet remain easy t understand n utside. Decided t try digitizing a pavement deteriratin curve. 5

6 *IPAT synthesis Lked at typical pavement deteriratin curves Qualitative representatins Nt useful fr analysis Decided t see if it wuld be pssible t use mathematically defined curve Did find undcumented assertin f 40% lst at 0.75 lifetime and 60% by 0.87 Derived a frmula and experimented with using it t mdel varius pavement lifetime scenaris 6

7 IPAT curve prperties Nn-dimensinal, full life, variable deteriratin rate, cnditin znes by pwers f tw 7

8 Mdeling a segment s lifetime 8

9 Single segment mdel prcess 1. Map design life 2. Estimate ultimate life Weathering: 27,582 ESALs /yr r 100 Yr life w/ trucks 9

10 Field evaluatin Spreadsheet IPAT curves where develped fr varius rads in 15 cunties Did nt find any life cycle / traffic / pavement structure cmbinatin that culdn t be mdeled. Spreadsheet versin prved wrkable in the field Facilitated what if analysis f structural and pavement preservatin treatments Enabled determinatin f Remaining Service Life Methd did seem able t answer key questins 10

11 Curve tuning Field testing demnstrated that IPAT culd supprt successive refinement f any given segment s mdel, as new cnditin data becmes available. Decided t call it Curve tuning, since the gal is t ptimize the fit f the curve t the reality in the field Wrks as fllws: get a number f data pints regress IPAT curve frmula fr best fit repeat at each successive new bservatin. Iteratively results in curve that mst realistically represent future trajectry. Tuning adjustments are made by varying key variables used in the mdel: initial ESALs, design life, traffic, weathering, etc. Gal is frmula that best predicts future trend. 11

12 *Pavement Structure Issues As the IPAT explratin evlved, it became apparent that a reasnably gd way f estimating ESAL capacity at the start f a pavement s service lifetime was needed. Didn t need perfectin, just rder f magnitude t get started since adjustments culd cme frm tuning t fit bserved cnditins ver time. S... began lking at pavement structure in mre detail. Realized that in ur mdern preservatin era, peple seldm build new pavements frm scratch. Mre ften they apply treatments and new lifts n tp f a stack f pre-existing layers Thus future perfrmance als depends n past histry, which can be cmplicated Als realized that saying a pavement has a capacity f X-ESALs ver Y-years, carries an implicit subject t prevailing weather cnditins assumptin. 12

13 Trial structure cncept Didn t need a perfect answer t be able t set up a curve and start tuning it - but still need t start smewhere. S initially chse t mimic Structural Number cncept. Service Value Index - SVI Methd: Assign age adjusted SVI's t each layer, sum them up and use ttal t cmpute an ESAL capacity. Discvered and used a rughly 5th pwer relatinship between the SVI and life ESAL 13

14 SVI calcs led t awareness f pavement cmplexity In a multi-layer pavement, each lift has a unique age, thickness, depth in slab, stress level, material, physical cnditin, mdulus, and prir traffic carriage impacts. Began t realize that understanding cmpsite behavir with simplistic Structural Number & prir service factrs cncept, plus an ESAL capacity vs. SN curve. might nt be enugh. Discvered that Iwa Cunties have a dispersed database f pavement histries frm arund the state. Began wndering if this infrmatin culd be gathered, digitized, and used t develp a predictive mdel. 14

15 Illustrative pavement histry Example prtrays cumulative histry f a pavement thrugh five cycles f cnstructin and renewal. Thickness, age, depth in slab, prir ESALs, and prir F/T cycles change as time passes update wuld need t serve as basis fr estimating next design life and ESAL capacity ging frward. 400 vpd 2%/yr / 9% trucks w/ 0.4% grwth. 15

16 *IPAT Research prject Cnducted field evaluatins f cncept efficacy and rbustness during summer f 2015 Cntacted cunty engineers fund the methds reasnably credible Fund that all circumstances fund in the field can be mdeled Learned f desire t predict value/duratin f pavement preservatins Determined mdel culd wrk n bth segment and netwrk levels Discvered the treasure trve f pavement histries n file Discussed and refine the ideas at LTAM meetings Feb 2016 presented t CERFG and received gd scre Feb 2017 Submitted Prblem statement t IHRB. Rated as a tp pririty t becme eligible fr RFP and frmal research prpsal Nw seeking research partner(s) 16

17 IPAT research gals 1. Find the best tecnlgy t mathematically define deteriratin curves and identify hw t tune them. Is the lgistics curve the best fit r shuld curves be synthesized sme ther way? What wuld be the best way t cmbine cnditin bservatins frm disparate surces and use them cllectively t tune the mdel? Can we validate that starting ESALs, design lifetime, traffic, weathering, and subgrade are the exclusive essential variables? Can tuning be autmated? 2. Develp methd(s) t better analyze and predict lifetime ESALs f multi-layered pavements Cllect and digitize the cunties dispersed pavement data? Can we analyze it in a fashin that will help build a reliable lifetime and ESALs predictr fr the future? Can we build in MEPDG methds and prir research? 17

18 Engineering practice gals Level 1 - Be able t define and tune segment by segment curves as a basis f pavement cnditin analysis and tracking. Level 2 - Have an ability t analyze existing and predict future multi-layer pavements' ESAL capacity, service life and weathering characteristics Level 3 - Be able t analyze mid-life impacts/actins: change in VPD, Deturs, Pavement preservatin, etc Level 4 - Supprt each cunty being able t reprt the RSL f their system in terms f miles f rad at each RSL level. Supprt cnslidatin f this infrmatin at the statewide level. 18

19 Implementatin gals Initial curve and pavement layer implementatin by spreadsheet. ICEASB t fllw up with building an app that wuld enable cunties t use the curve mdel t track and predict pavement perfrmance: Cunty wuld map ut unifrm prject sectins via an nline interface. A mdel wuld be set up fr each sectin Mdels wuld be tuned, revised, and reset ver time as data cmes in. Results wuld be cnslidated t shw Miles x RSL, at bth cunty and statewide levels Parallel app wuld assist with multi-layered pavements analysis ICEASB wuld prvide mbile versin f app t enable engineers t access data n and reevaluate pavements while bserving them in the field. Over time, the cllected cnditin mdel and pavement structure data wuld becme a research resurce f its wn. 19

20 *Pssible mbile app 20

21 Questins? Ideas? 21