An Integrated Systems Approach to the Engineering and Management of the

Highway Transportation Infrastructure

K. Grimmelsman, K. Ciloglu, Emin Aktan and Dan Faust

Drexel University and DRPA of PA &NJ

First International Conference onStructural Health Monitoring and

Intelligent InfrastructureTokyo, Japan 13-15 November 2003

CRITICAL INFRASTRUCTURES• Telecommunications• Electric Power• Gas and Oil Storage and Delivery• Transportation• Water Supply• Food and Agriculture• Medicine and Health Care• Chemical Industry• Banking and Finance• Emergency Services• Government

Natural Environment

Human Elements

EngineeredElements

TRANSPORTATION

USDOT: OST, FAA, FHWA, FTA, FRA, USCG, MARAD, RSPA (http://www.dot.gov/DOTagencies.htm)

•Highways: Pavements, bridges and tunnels; embankments, fills and walls; lighting systems, signals, surveillance and ITS; maintenance facilities•Railroads

•Mass Transit

•Ports and Waterways

•Air Transportation Facilities

TRANSPORTATION INFRASTRUCTURE

USDOT 2002 Report to Congress:Capital Investment Requirements:

The average annual investment required by alllevels of government to maintain highways andbridges so that critical indicators of overallconditions and performance in the year 2020will match their year 2000 values: $106.9 Billion

(Note that 21.5% of bridges on the Strategic

Highway Network were deficient in 2000)

Highway Transportation

2003 Urban Mobility Study by TTI:• The cost of congestion continues to climb.

Wasted fuel and lost productivity resulting from traffic congestion in 2001 cost the nation $69.5 billion, $4.5 billion more than the previous year.

• The extra time needed for rush hour travel has tripled over two decades. A rush hour trip took 39 percent longer than a non-rush hour trip.

INTERCONNECTED HYPER-SYSTEMS

The sewers, the water, the gasconnections, the electrical connections all went down together with one hole in the middle of Fifth Avenue, in Manhattan, NY

The New York Times, January 3 rd , 1998

Dense fog caused a 71-vehicle pileup that injured about 30 people on the morning of December 28, 2002 in south Houston.

About 125 vehicles smashed in thick fog on Interstate 75 in Tennessee, on March 14, 2002, killing at least 4 people, injuring at least 39

Transportation: Nature and Human Interactions

War on Road Fog Lacks EasySolution (NY Times June 18, 2003)

HOMELAND SECURITY

Is this the solution ?

Infrastructure Systems: Issues• Complex interactions between natural,

human and engineered elements, systems• Performance falling short of expected• Vulnerability due to hidden intersections

between elements and systems • Lack of valuation, objective descriptions for:

Condition, Performance, Health • Research ? Effective tech leveraging ?• Multi-hazards risk management for

metropolitan regions with new emphasis on homeland security ?

Engineering and Management of Large Hyper-Systems:

• Observe (need a telescope)• Model – Physical and Analytical • Measure – Perturb – Controlled Exp• Conceptualize Mechanisms of Behavior

and Uncertainty • Identify – Simulate Systems, Connections

and Intersections• Monitor – Control• Interpret – Optimize – Decide• Manage performance, preserve, protect

DELAWARE RIVER PORT AUTHORITY OF PA & NJ

WALT WHITMAN BRIDGE

COMMODORE BARRY BRIDGE

COMMODORE BARRY BRIDGE

PHILADELPHIA PORT PIER ONE

BETSY ROSS BRIDGE

BENJAMIN FRANKLIN

GIS BASED E-DATABASE OF ALL DRPA INFRASTRUCTURE:

TBA

PATCO

Military/Dept. of Defense

FEMAFederal Level

Air Transportation

Airport Security

AMTRAK

SEPTA PATCO

NJT

Penn DOT

Penn Turnpike

NJ Turnpike

County Road Systems

MunicipalityRoad Systems

FHWA

DRPA

FIREDEPT.

MEDICALEMERGENCY

Police Department

Red Cross Other Non-profitOrganizationsRegional Level

Local LevelHOSPITALS

Dept. of Health

Operational Organizational First Responders Civil Organizations Federal Emergency

SYSTEMS ENGINEERING: ORGANIZATIONS AND SECURITY

THE COMMODORE BARRY BRIDGE

Structural Identification

Conceptualize

A-priori Model(s)Utilization

Controlled Tests, Monitoring

ModelCalibration

Process data

1

3

2

45

6

Common Analytical Modeling Options• Physics-Based Models:

– Geometric:• Element Level • Microscopic FE• Mixed

– Modal, Ritz Vectors• Numerical Models

– K,M,C Coefficients– Soft Models (ANN, Fuzzy ANN, Agents)– Statistical (Time Series) Models: ARMA

• Macroscopic – Smeared Models– Continuum (Wave Eq.) – Rule-Based Models– Probabilistic Models

Reduction, Expansion and Transformations

Calibrated FE Models: Uses

– Evaluate vulnerability (changes in live-load demands, threats, hazards or increase in performance requirements)

– Design structural modification, retrofit or hardening (changes in use-modes, codes, aging, and/or for increasing the reliability of non-redundant systems)

– Evaluate reliability following an overload, hazard– Design and interpret measurements during

health monitoring, maintenance, repair, retrofit– Help design health monitoring for optimum

lifecycle management

Quality Control Issues in FE Modeling of Large Structural Systems

§ INCOMPLETENESS AND CONCEPTUAL ERRORS:§ Site Visits, Photography, Photogrammetry§ Virtual Reconstruction in 3D CAD§ Expert Input

§ INPUT ERRORS:§ Systematic Checking by a Second Person§ Graphical User Interface§ Spreadsheet Manipulations for Patterning§ Diagnostic Analyses/Structural Response Interface

§ SOFTWARE/HARDWARE VERIFICATION §Benchmark Problems

§ CALIBRATION and EXPERIMENTAL VALIDATION

Conceptualization and FEM ProcessDesign Drawings

Photograph

CAD Model

Structural Model

Drawings

PP27

Upper Chord at PP27

PP27

Panel Point 27Lower Chord at PP 27

PP27

L27U27

L27L28L26L27

L27U28

Moment Release (Axis 3)Axial Force Release (Axis 1)

Moment Release (Axis 3)

PP 27 – PlanPP 27

LowerChord

Verticals and Diagonals

Floor System

PP27

Lower Chord at PP27

Floor System

PP 27 and Floor

System

Plan View at PP27

Floor System

•Graphical Visualization of Input Geometry and Responses Simulated By Diagnostic Analyses•Spreadsheet Manipulation of Inputs

Field Tests at CBB for FE Model Calibration

fexp = 0.666 Hz

fnominal = 0.456 Hzfcalibrated= 0.670 Hz

Mode 2

fexp = 0.360 Hz

Mode 1

fexp = 0.252 Hz

fnominal = 0.205 Hzfcalibrated = 0.250 Hz

fnominal = 0.311 Hzfcalibrated = 0.365 Hz

Global Calibration

AccelerometersUtilized

Vert. Accel.

Long. Accel.

Lat. Accel.

Pier W1

~416'

Pier W1 CL

Bottom Chord Level

… Mode 5

0 10 20 30 40 50 60 70-5

0

5

10

15

20

25

30

35

PP275-7

mph

panel points

Hanger Influence Line

430L3 210480-130L26010L4 675098806450L1

H1

Calibrated (ksi)

Nominal (ksi)

Test (psi)

Sensor ID

Sensor Location

Local Calibration

Ambient Vibration Test

Floor System

108 kip per crane

45

Summary of Calibration Results For The Main Truss

24 %48 %55 %Remaining RMS Error With Stresses (20 Measurements)

LOCAL CALIBRATION

1.5 %2 %28 % Remaining RMS Error With The First 6 Experimental Freq

GLOBAL CALIBRATION

Body ConstraintsFixed or Expansion ShoesFixed or Expansion ShoesFloorbeam

Body ConstraintBody ConstraintBody ConstraintStringer

Body ConstraintBody ConstraintBody ConstraintDeck

Floor System

Fully RestrainedFully RestrainedMoment ReleasesWind Linkage

Fully RestrainedFully RestrainedAxial and Moment ReleasesLow and Upp Chord Membs

Fully RestrainedFully RestrainedMoment ReleaseHangers

at Suspended Span (PP27,PP45)

Fully RestrainedFully RestrainedExpansion Bearingat Piers (W2,E2)

Fully RestrainedFully RestrainedFixed Bearingat Piers (W1,E1)

Movement System

(0.50-0.75)L FlexibleFully RigidFully FlexiblePier Stiffness

STRUCTURAL PROPERTIES

BOTH GLOBALLY AND LOCALLY CALIBRATED

ONLY GLOBALLY CALIBRATED

NOMINAL MODELPARAMETER

3D Model StatisticsNodes: ~8,000, DOF’s ~50,000Frame Elements: ~5500Shell Elements: ~3,000

FE Model of Commodore Barry Bridge Through Truss

Scalability/Interpretation Issues in Modeling Large Systems:• Conceptualizing Sub-Systems, Local Behaviors, Initial,

Boundary and Continuity Conditions, Movement systems • Mitigating Input, Analysis & Output Errors• Simulating non-stationary inputs and behaviors • Modeling socio-technical elements • Incorporating different mechanisms/levels of uncertainty

Health Monitoring: Issues• Systems-level conceptualization and modeling • Challenges to Sys-Id: Observability, uncertainty • Purpose, scope, temporal, spatial needs/constraints:

Operational, structural and/or security surveillance ?• Design of sensing, imaging, networking, computing,

Communication and Information Management • Measurement calibration and scalability studies• Data quality assurance and management• Information, interpretation and decision-making• Self-intelligence and related issues

System needs to help the users !

Health Monitoring: Rewards• Data and knowledge essential for management:

“You cannot manage what you cannot measure”• “Performance-based” engineering by factual data• Enable innovation in materials, construction, other• Pro-actively diagnose health and mitigate

circumstances that may eventually affect health • Effective maintenance and renewal by identifying

root causes of deterioration• Integrate operational and maintenance management

reduced cost, improved performance and revenue• Mitigate and effectively respond to incidents,

accidents and emergencies

Money Magazine, Nov 03, Special Report on HealthCare

Commodore Barry Bridge Instrumentation LAN

Commodore Barry Bridge Instrumentation Map

Pier W2

Pier W1

Pier E1

Pier E2

PP45

PP36PP27

PP08

ACB

D

E

F G

HJ

Toll Plaza

Total Data Channels = 485

PHENOMENA

Traffic

Weather

MEASURANDImageSpeed & WeightAir TemperatureRelative Humidity

Wind Speed & Dir.

SENSOR

Solar Radiation

Bridge Responses

Live Load StrainsEnviron. Strains

DisplacementsTiltsAccelerations

Video CameraWIM System

Temperature

Ultrasonic Wind

Weather Station

Q.B. Strain GageV.W. Strain Gage

V.W. CrackmeterV.W. TiltmeterCap. Accelerometer

Thermistor

QTY4

2 Lanes

4

1

56148

173616

201

LOCATIONSD , E JK

,

G

E , G ,C , D E, F,A , C D, E F J, , ,A , C D, E F G J, , , ,A , D F, J,A , C D, F G J, , ,B , D F, H,

K

Video CameraWind Sensor

WIM

Sample Acceleration, High Freq. strain, Tilt,Temperature, Low Freq. strain, andLF Displacement Data Characterizing the Operating and Serviceability Responses of the Commodore Barry Bridge

Collection SystemField Collection

Measurement sys. calibrationsInstallation qualityOperator trainingSynchron. and formattingSystem redundancies

Raw

Dat

a

Online-Real Time PresentationVisual verificationReal-time I/O correlationLogical consistency

Elementary Data ChecksTime-range validitySensor-range validityRepeated readingsSampling frequencyData smoothnessOther

Storage and SharingSecondary Data Check

Time-series analysisFrequency analysisVisualization tools

IntegrityData change trackingBackup and safetyAuthorization protocols

Tertiary Data CheckData interpretationData presentationCorrelationsMultivariate correlationFuzzy and ANN models

Legacy Data AccessRaw dataInterpretations

Authorized Access / FirewallOnline via Internet

Data Transfer

HeadersHandshake

Receipts

Clea

n D

ata

Dat

a Ta

ggin

g

Post-processed D

ataStored D

ata

Database Safety

Information

Data Quality Assessment, Processing and Archival

DEMONSTRATION ON CBB

Web based data and legacy documentation archival system

DEMONSTRATION ON CBBInternet Front Page for Real-Time Monitoring Data

Synchronization of Truck Images and Response

Red Line: Current TimeOct 30, 2002 09:56:02

Camera at PP 13Oct 30, 2002 09:56:02

Camera at PP 35Oct 30, 2002 09:56:02

Camera at PP 57Oct 30, 2002 09:56:02

PP45 North Hanger Lower North West Flange Strain (uE):

PP45 North Hanger Lower North East Flange Strain (uE):

PP37 Floor Beam Top Flange Strain (uE):

PP37 Floor Beam Bottom Flange Strain (uE):

Monitored Truck

-15

-10

-5

0

5

10

15

10/30/20029:48

10/30/20029:54

10/30/200210:00

10/30/200210:06

-10

-5

0

5

10

15

10/30/20029:48

10/30/20029:54

10/30/200210:00

10/30/200210:06

-40

-30

-20

-10

0

10

20

30

40

10/26/2002 12:00 10/28/2002 12:00 10/30/2002 12:00-70

-60

-50

-40

-30

-20

-10

0

10

20

30

40

10/26/2002 10/28/2002 10/30/2002 11/1/2002 11/3/2002

Synchronization of Truck Images and Response

Camera at PP 13Oct 30, 2002 09:56:02

Camera at PP 35Oct 30, 2002 09:56:02

Camera at PP 57Oct 30, 2002 09:56:02

PP45 South Lower Hanger Strain Average (uE)

PP45 North Lower Hanger Strain Average (uE)

Red Line: Current TimeOct 30, 2002 09:56:02High-Speed LL Induced:

20 Seconds

Intrinsic, Slowly Varying Strains: One Week

High-Speed LL Induced: 20 Seconds

Monitored Truck

Intrinsic, Slowly Varying Strains: One Week

SYSTEMS ENGINEERING

Objective-Function Elements For Optimum Performance of a Major Bridge System

SECURITYSECURITY

•Traffic Enforcement

•Weight Enforcement

•Hazardous materials

•Detection/Response to Incidents/Accidents

•Security Surveillance (bridge/river traffic)

•Emergency Response to Natural and Man-Made Hazards:

•Hit & Run•Terrorism

OPERATIONOPERATION•Safety:ØWeather ØRoad SurfaceØIncidents ØAccidents

•Traffic Flow:ØE-AdvisoriesØSpeed LimitsØTruck/Auto/HOV

•Revenue:ØE-TollingØZone/Time TollØWeight-TollingØLoad PermitsØStatistical Data

MAINTENANCEMAINTENANCE• Detect and Mitigate Deterioration (eg corrosion)

• Detect and Intercept Damage (eg fatigue- crack)

• Harden • Repair Damage (eg accident)• Retrofit (eg fracture-critical)• Rapid Condition Evaluation (Immediately after a Hazard)

Natural Environment

Operating Environment

ConstructedSystems

Properly modify materials and/or application procedures until results are as anticipated or satisfactory

Verify that amplitude and patterns agree with anticipated counterparts

Monitor in the context of Structural Health as described above

Check amplitudes and patterns of responses before, during and after implementation

Capture critical element responses before/during and following maintenance or retrofit application

Effective Maintenance, Repair, RetrofitMaterials and Renewal Engineering

Intercept causes of deterioration, alert and direct experts for close inspection, maintenance and repair when needed, alarms if damage detected

Evaluate response amplitudes, damage indicators and normalized influence coefficients against measured and simulated benchmarks

Load and response amplitudes and patterns at critical locations, changes in intrinsic conditions given environment and history, establish indicators of normalcy

Truck weight, speed, positions, piers, foundations, ground, and water conditions, critical bridge intrinsic conditions and environmental inputs

Monitoring Loading Inputs and Structural Health Under Operating and Rare-Extreme Conditions

Adjust model features and tune parameters until model reliability is acceptable and close correlations between simulated and measured are demonstrated

Correlation of simulated against measured phenomena to evaluate analytical model’s reliability: Physics errors completeness in simulating all critical mechanisms, correlation

Deterministic and stochastic features and parameter sensitivity patterns from nominal analytical model (s)

External loading, environmental conditions, selected structural responses over sufficient duration.

System-Identification, Field-Calibrated Analytical Modeling

Plan of Action and Implementation:

Test Patterns Retrospectively:

Identify Patterns:

Track, Map and Integrate Multiple Images, Data and Information:

Structural Eng. Applications of Intelligent Health Monitor

Advise/adjust speed limits, signaling, lane allocations, toll rates, operations, etc for maximum efficiency. Re-route trucks to less congested bridges during rush hours.

Are these patterns repetitive given season, weather, time of day? Are there long-term means to enhance flow efficiency?

Regional and local patterns indicating congestion, backup and any inefficiency in traffic flow at either level

Monitor current and expected weather, any ongoing maintenance restricting lanes and any incidents within the region that may affect traffic along roadway or on bridge

Traffic Management: Speed Limits, Signals, Tolling, Special Lanes, Lane directions

Adjust speed limits, Truck lane allocations, Advise/Alert via smart-signs and in-vehicle communication systems, intercept for enforcement and or accident avoidance, E-Citations

Issue citations; Alert drivers for safety risks for any detected anomaly given the traffic, roadway and weather conditions. Check License Plate of vehicles against outstanding tickets and warrants.

Check for anomalies in the movements of vehicles given traffic, weather and roadway conditions. Alert if slippery roadway or deck, or if overheadbridge members have ice built-up

Map-track traffic along critical stretches of roadway or a bridge in real-time together with roadway and weather conditions. Based on visibility, various image and data integrations are needed.

Safety: Road Conditions, Weather and Traffic advisory, Aggressive andReckless Driver Imaging, Enforcing Traffic Regulations

Clear or Intercept truck. Permit to cross bridge but send e-citation. Contact owner-agency for confirmation. Communicate with vehicle.

Check toll paid. Trace transponder. Info related to past incidents and citations for the truck and other trucks operated by the same agency. If no transponder, pull-over for security check.

Axle-weights, height exceeding limits ? Correct toll paid ? Any safety risk given visibility, wind, deck and overall traffic conditions. Is HAZMAT crossing permitted ?

Identify truck license plates, weight, speed and geometry in motion by embedded WIM scale and vehicle imaging, including imaging underside, check for transponders, HAZMAT registration.

Weight-Height Enforcement:Truck Weight, Geometry, Load Content and Toll Enforcement

Plan of Action and Implementation:

Test Patterns Retrospectively:

Identify Patterns:

Track, Map and Integrate Multiple Images, Data, Information:

Operations Support By Intelligent Health Monitor

Help direct law enforcement to intercept vehicle

Check if there is an outstanding alert or warrant associated with a license plate. Check vehicles spotted at more than one crime scene in region

Check License Plate and vehicle attributes against those reported and being searched as suspects

Monitor License Plate, type, weight and driving patterns of individual vehicles 24/7/365 in the vicinity of critical intersections, parking areas, city blocks

Profile/Identify Vehicles Associated With Suspicious Activity, Crime

If vehicle does not emerge within time, check location and alert special response squad/vehicles

Update vehicle classifications by patterns from past incidents and new information

Make certain all vehicles that enter will exit properly in a timely manner

Weigh/image/tally vehicles permitted to enter (yellow, green), track during passage and confirm at exit

Track Vehicles For Ensuring Timely Exit of All Vehicles That Entered a Facility or a Throughway

Alert vehicle by smart-signs and alert security personnel before the vehicle enters. Direct yellow vehicles to hardened lanes.

Identify vehicles that have to be inspected (red), and those (yellow) that should be inspected for future patterning. Identify drivers that should be intercepted with caution.

Identify vehicle type, License Plate, other parameters, driver profile and driving patterns in conjunction with composition and volume of traffic

Monitor License Plate, type, weight and driving patterns of individual vehicles 24/7/365 in the vicinity of bridge and tunnel entry points. Slow vehicles for driver imaging.

Identify and Classify Vehicles for Inspection at Bridge, Tunnel, Garage Entries

Plan of Action and Implementation:

Test Patterns Retrospectively:

Identify Patterns: Profiling the Vehicle and Driver

Track, Map-Integrate Multiple Images, Data, Information:

Security Applications of Intelligent Health Monitor System

Field Laboratories - Test Beds• Essential if we wish to develop a new discipline

focused on the engineering and management of infrastructure hyper-systems

• Develop and integrate technology to demonstrate innovative paradigms such as performance-based engineering, health management, intelligent systems and integrated asset management

• Include all of the interacting human, natural and engineered elements

• Include known (and unknown) connections, intersections and interactions between various infrastructures

BRIDGES

Deck Superstructure Substructure

1 11 ALLEGHENY RIVER & I579 VETERANS BR I-579 VETERANS BRIDGE 1986 134 320 7 6 7

2 11 ALLEGHENY RIVER & I279 FORT DUQUESNE BR I279 NB-SB FT.DUQ.BR. 1959 129 130 5 6 6

3 11 MON RV & RT 30 FORT PITT BR FORT PITT BR. 1960 229 371 3 5 44 11 MON RIV.& SMITHFIELD ST. SMITHFIELD ST SMITHFIELD ST.BRIDGE 1883 110 359 7 5 5

5 11 MON RIV,764,736,& 2ND AV LIBERTY BR NORTH OF LIBERTY TUNNELS 1928 143 812 5 4 5

6 8 I81;SUS.RIV;CONRAIL I-81; SR 0081 HARRISBURG (WADE BR) 1973 41 1,581 6 6 5

7 8 US 230; I83 I-83; SR 0083 JOHN HARRIS BR 1960 41 582 7 7 5

8 8 SUSQ.RI,AMTR;EB-300 PA TURNPIKE (I-76) FAIRVIEW TWP 1949 37 1,380 6 5 6

9 6 DELAWARE RIVER/RR/ROADS US 322 COMMODORE BARRY BR 43E09 1974 501 4,241 5 6 5

10 6 SCHUYLKILL RIVER & I291 PENROSE AVENUE GEORGE PLATE MEM. 36J09 1949 207 2,676 6 4 6

11 6 SCHUYLKILL RIVER, I95 I-95'DOUBLE DECKER GIRARD POINT BRD. 37A10 1973 213 1,575 6 5 5

12 6 DELAWARE R & I-95;I-676 I-76 WALT WHITMAN BRG. 37A08 1957 610 3,561 5 7 7

13 6 DELAWARE R; I676; US30 I676; US30; PATCO BEN FRANKLIN BRD. 29A12 1926 533 2,490 7 5 5

14 6 DELA R. RIVER AVE CONRAI NJ ROUTE 90 BETSY ROSS BRIDGE 30A06 1973 222 2,587 6 7 7

15 6 DELAWARE RIVER NJ ROUTE 73 TACONY-PALMYRA BRIDGE 1929 164 1,115 4 5 5

16 6 LR150(US13),PA RR, DEL. PA TURNPIKE (I-76) DELAWARE RIVER 1954 208 1,990 5 5 7

TUNNELS17 11 I-279 & RT 837 FORT PITT TUNNEL PITTSBURGH 1960 1,102

18 11 PA 51, LIBERTY BLV LIBERTY TUNNELS MOUNT WASHINGTON 1924 1,795

19 8 US I-76 KITTATINY MOUNT. TUNNEL PA TURNPIKE 1940 1,441

20 8 US I-76 BLUE MOUNTAIN TUNNEL PA TURNPIKE 1940 1,323

Length of Max Span (meter)

Structure Length(meter)

Contition RatingsBridge Code

Name / Location Year BuiltHighwayDistrict

Features Intersected Facility Carried By Structure