FOREWORD

This study was conducted as part of the Federal Highway Administration’s Long-Term Bridge 

Performance (LTBP) Program. The LTBP Program is a minimum 20-year research effort to collect 

scientific performance field data, from a representative sample of bridges nationwide, that will help

the bridge community better understand bridge deterioration and performance. The products from

this program will be a collection of data-driven tools, including predictive and forecasting models 

that will enhance the abilities of bridge owners to optimize their management of bridges.

This report is intended to provide a comprehensive definition of bridge performance that will be the

foundation for carefully designed research studies in the LTBP Program. The report describes the 

barriers and complications that hinder the understanding of bridge performance and identifies the 

measures by which bridge performance is currently defined. The report divides bridge performance 

into specific issues, identifies the most critical issues, and describes the types of data necessary to 

analyze these issues. This report will be of interest to engineers involved with research, design, 

construction, inspection, maintenance, and management of bridges as well as to decisionmakers 

at all levels of management in public highway agencies.

Jorge Pagán-Ortiz

Director, Office of Infrastructure

Research and Development

Notice

This document is disseminated under the sponsorship of the U.S. Department of Transportation 

in the interest of information exchange. The U.S. Government assumes no liability for the use 

of the information contained in this document. This report does not constitute a standard, 

specification, or regulation.

The U.S. Government does not endorse products or manufacturers. Trademarks or manufacturers’ 

names appear in this report only because they are considered essential to the objective of the 

document.

Quality Assurance Statement

The Federal Highway Administration (FHWA) provides high-quality information to serve 

Government, industry, and the public in a manner that promotes public understanding. Standards 

and policies are used to ensure and maximize the quality, objectivity, utility, and integrity of its 

information. FHWA periodically reviews quality issues and adjusts its programs and processes to 

ensure continuous quality improvement.
TECHNICAL REPORT DOCUMENTATION PAGE

1. Report No.

FHWA-HRT-13-051

2. Government Accession No. 3. Recipient’s Catalog No.

4. Title and Subtitle

LTBP Bridge Performance Primer

5. Report Date

December 2013

6. Performing Organization Code: 

7. Author(s)

John Hooks (JM Hooks & Associates) and Dan M. Frangopol, 

Sc.D. h.c. (Lehigh University)

8. Performing Organization Report No. 

9. Performing Organization Name and Address

Rutgers, The State University of New Jersey

The Center for Advanced Infrastructure and Transportation

100 Brett Road

Piscataway, NJ 08854-8058 

10. Work Unit No.

11. Contract or Grant No.

DTFH61-07-R-00136

12. Sponsoring Agency Name and Address

Office of Infrastructure Research and Development

Turner-Fairbank Highway Research Center

Federal Highway Administration

6300 Georgetown Pike

McLean, VA 22101-2296

13. Type of Report and Period Covered

Final Report 

14. Sponsoring Agency Code

HRDI-60

15. Supplementary Notes

The FHWA Contracting Officer’s Technical Representative (COTR) was Dr. Hamid Ghasemi, HRDI-60

16. Abstract

The performance of bridges is critical to the overall performance of the highway transportation system in the 

United States. However, many critical aspects of bridge performance are not well understood. The reasons for 

this include the extreme diversity of the bridge infrastructure, the widely varying conditions under which bridges 

serve, and the lack of reliable data needed to understand performance. The Long-Term Bridge Performance (LTBP)

Program was created to identify, collect, and analyze research-quality data on the most critical aspects of bridge 

performance. This report describes the bridge infrastructure in the United States and explains why reliable indicators 

of bridge performance are necessary. Current methods of measuring performance are described, and the need for 

more precisely targeted performance indicators is discussed. The report explains bridge performance in terms of 

the aspects that have the most impact on the ability of the bridge to serve its intended purpose in a safe, efficient,

and economical manner. The purpose of this report is to provide an understanding of what bridge performance 

means and the factors that influence bridge performance. It describes the various ways in which bridge owners 

measure and report bridge performance. It also describes how the LTBP Program will create new measures to 

allow deeper analysis and understanding, which will lead to ways to improve long-term bridge performance.

17. Key Words

Bridge, Bridge performance, Performance 

measures, Long-term bridge performance 

18. Distribution Statement

No restrictions. This document is available to the public

through the National Technical Information Service, 

Springfield, VA 22161.

19. Security Classif. (of this report)

Unclassified

20. Security Classif. (of this page)

Unclassified

21. No. of Pages

67

22. Price

N/A

Form DOT F 1700.7 (8-72) Reproduction of completed page authorized
ii

SI* (MODERN METRIC) CONVERSION FACTORS 

APPROXIMATE CONVERSIONS TO SI UNITS

Symbol When You Know Multiply By To Find Symbol 

LENGTH

in inches 25.4 millimeters mm 

ft feet 0.305 meters m 

yd yards 0.914 meters m 

mi miles 1.61 kilometers km 

AREA 

in2 square inches 645.2 square millimeters mm2

ft2 square feet 0.093 square meters m2

yd2 square yard 0.836 square meters m2

ac acres 0.405 hectares ha

mi2 square miles 2.59 square kilometers km2

VOLUME 

fl oz fluid ounces 29.57 milliliters mL 

gal gallons 3.785 liters L 

ft3 cubic feet 0.028 cubic meters m3 

yd3 cubic yards 0.765 cubic meters m3 

NOTE: volumes greater than 1000 L shall be shown in m3

MASS oz ounces 28.35 grams g

lb pounds 0.454 kilograms kg

T short tons (2000 lb) 0.907 megagrams (or "metric ton") Mg (or "t") 

TEMPERATURE (exact degrees) o

F Fahrenheit 5 (F-32)/9 Celsius oC 

or (F-32)/1.8 

ILLUMINATION 

fc foot-candles 10.76 lux lx

fl foot-Lamberts 3.426 candela/m2 cd/m2

FORCE and PRESSURE or STRESS 

lbf poundforce 4.45 newtons N 

lbf/in2 poundforce per square inch 6.89 kilopascals kPa 

APPROXIMATE CONVERSIONS FROM SI UNITS 

Symbol When You Know Multiply By To Find Symbol 

LENGTH mm millimeters 0.039 inches in 

m meters 3.28 feet ft 

m meters 1.09 yards yd 

km kilometers 0.621 miles mi 

AREA mm2 square millimeters 0.0016 square inches in2 

m2 square meters 10.764 square feet ft2 

m2 square meters 1.195 square yards yd2 

ha hectares 2.47 acres ac

km2 square kilometers 0.386 square miles mi2 

VOLUME 

mL milliliters 0.034 fluid ounces fl oz 

L liters 0.264 gallons gal 

m3 cubic meters 35.314 cubic feet ft3 

m3 cubic meters 1.307 cubic yards yd3 

MASS 

g grams 0.035 ounces oz

kg kilograms 2.202 pounds lb

Mg (or "t") megagrams (or "metric ton") 1.103 short tons (2000 lb) T 

TEMPERATURE (exact degrees) o

C Celsius 1.8C+32 Fahrenheit oF 

ILLUMINATION 

lx lux 0.0929 foot-candles fc 

cd/m2 candela/m2 0.2919 foot-Lamberts fl

FORCE and PRESSURE or STRESS 

N newtons 0.225 poundforce lbf 

kPa kilopascals 0.145 poundforce per square inch lbf/in2

*SI is the symbol for the International System of Units. Appropriate rounding should be made to comply with Section 4 of ASTM E380. 

(Revised March 2003)
iii

TABLE OF CONTENTS

CHAPTER 1. THE BASICS OF BRIDGE PERFORMANCE .................................................1

THE HIGHWAY BRIDGE INFRASTRUCTURE ..............................................................2

THE MEANING OF “BRIDGE PERFORMANCE” ..........................................................5

WHY MEASURE BRIDGE PERFORMANCE? .................................................................8

CHAPTER 2. CURRENT APPROACHES TO MEASURING BRIDGE 

PEFORMANCE................................................................................................................................11

NBI CONDITION AND APPRAISAL RATINGS .............................................................12

PERFORMANCE MEASURES BASED ON BRIDGE DEFICIENCIES.......................15

THE FEDERAL SR...............................................................................................................16

THE HEALTH INDEX.........................................................................................................17

BRIDGE PERFORMANCE MEASURES USED IN OTHER COUNTRIES.................18

Finland ...............................................................................................................................18

South Africa.......................................................................................................................20

Sweden...............................................................................................................................21

CHAPTER 3. BRIDGE PERFORMANCE INDICATORS TO ADDRESS SPECIFIC 

CONCERNS.................................................................................................................................23

STRUCTURAL PERFORMANCE INDICATORS...........................................................24

Condition Rating (CR).......................................................................................................24

Condition State (CS)..........................................................................................................25

Margin of Safety (M) .........................................................................................................25

Time-Dependent Margin of Safety (M(t)) .........................................................................25

Probability of Failure (Pf) ..................................................................................................26

Probability of Survival (Reliability) (Ps)...........................................................................26

Reliability Index ( ).........................................................................................................26

Life-Cycle Cost..................................................................................................................27

Safety Factor in Allowable Stress Design (SF) .................................................................28

Partial Factors Used in LRFD ( , )..................................................................................28

Load Modifier Factor Used in LRFD ( )........................................................................29

Collapse Load Multiplier ( ).............................................................................................29

Return Period ( )..............................................................................................................30

Cumulative Time Probability of Failure (F(t))..................................................................30

Cumulative Time Probability of Survival (S(t)) ................................................................31

Reserve Strength Factor (R1) .............................................................................................32

Residual Strength Factor (R2) ............................................................................................32

Redundancy Factor (R0).....................................................................................................32

Damage Factor (D) ............................................................................................................32

Redundancy Index (RI)......................................................................................................33

Time-Variant Redundancy Index (RI(t)) ...........................................................................33

Vulnerability (V)................................................................................................................34

Damage Tolerance (Dt)......................................................................................................34

Ductility ( ) ......................................................................................................................34

β

φ γ

ηi

λ

T

Δ
iv

Robustness (RO) ................................................................................................................35

Resilience (RE) ..................................................................................................................35

Risk ( ).............................................................................................................................35

CLASSIFICATION OF STRUCTURAL PERFORMANCE INDICATORS.................35

CHAPTER 4. IMPROVING BRIDGE PERFORMANCE .....................................................37

KEYS TO IMPROVING BRIDGE PERFORMANCE .....................................................37

BETTER DATA ON BRIDGE PERFORMANCE IN THE UNITED STATES.............38

Example: Performance of FO Bridges...............................................................................42

BETTER UNDERSTANDING OF CAUSE AND EFFECT .............................................43

CRITICAL ASPECTS OF BRIDGE PERFORMANCE...................................................45

CONCLUSIONS ..........................................................................................................................47

APPENDIX. DETAILS OF THE HIGHWAY BRIDGE INFRASTRUCTURE...................49

REFERENCES.............................................................................................................................57

R
v

LIST OF FIGURES

Figure 1. Graph. Age Distribution of All Bridges in the United States...........................................3

Figure 2. Illustration. Main Categories of Bridge Performance Issues............................................7

Figure 3. Equation. Federal SR......................................................................................................16

Figure 4. Equation. California Bridge Health Index......................................................................17

Figure 5. Equation. Finnra’s Repair Index.....................................................................................18

Figure 6. Equation. Finnra’s Rehabilitation Index.........................................................................19

Figure 7. Equation. South Africa’s Condition Index .....................................................................20

Figure 8. Equation. South Africa’s BCI.........................................................................................20

Figure 9. Equation. Sweden’s LCV...............................................................................................21

Figure 10. Chart. Integrated Life-Cycle Bridge Management Framework ...................................24

Figure 11. Equation. Range of NBI Condition Ratings.................................................................24

Figure 12. Equation. Range of AASHTOWare Bridge ManagementTM Condition States............25

Figure 13. Equation. Margin of Safety ..........................................................................................25

Figure 14. Equation. Time-Dependent Margin of Safety ..............................................................25

Figure 15. Equation. Instantaneous Probability of Failure ............................................................26

Figure 16. Equation. Probability of Survival.................................................................................26

Figure 17. Equation. Reliability Index...........................................................................................26

Figure 18. Equation. Probability of Failure for Normally Distributed Independent Variables.....27

Figure 19. Equation. Expected Life-Cycle Cost ............................................................................27

Figure 20. Equation. Expected Life-Cycle Cost with SHM ..........................................................27

Figure 21. Equation. Expected Cost of Monitoring.......................................................................27

Figure 22. Equation. Benefit of the Monitoring System................................................................28

Figure 23. Equation. Safety Factor in ASD ...................................................................................28

Figure 24. Equation. Inequality for Safety Check in LRFD..........................................................28

Figure 25. Equation. Load Modifier Factor in LRFD for Ductility, Redundancy, and 

Operational Importance .................................................................................................................29

Figure 26. Equation. Load Modifier Factor for Maximum Value of i ........................................29

Figure 27. Equation. Load Modifier Factor for Minimum Value of i .........................................29

Figure 28. Equation. Collapse Load Multiplier for Proportional Loading ....................................29

Figure 29. Equation. Collapse Load Multiplier for Combined Loading........................................29

Figure 30. Equation. Collapse Load Multiplier for Arbitrary Loading .........................................30

Figure 31. Equation. Return Period for Loads Due to Natural Phenomena ..................................30

Figure 32. Equation. Average Duration Between Consecutive Occurrences of an Event.............30

Figure 33. Equation. Cumulative Time Probability of Failure, One Random Variable ................31

Figure 34. Equation. Cumulative Time Probability of Failure, Time-Variant Resistance and

Load ...............................................................................................................................................31

Figure 35. Equation. Cumulative Time Probability of Survival....................................................31

Figure 36. Equation. Reserve Strength Factor...............................................................................32

Figure 37. Equation. Residual Strength Factor..............................................................................32

Figure 38. Equation. Redundancy Factor ......................................................................................32

Figure 39. Equation. Damage Factor.............................................................................................32

Figure 40. Equation. Probabilistic Redundancy Index 1 ...............................................................33

Figure 41. Equation. Probabilistic Redundancy Index 2 ...............................................................33

Figure 42. Equation. Probabilistic Redundancy Index 3 ...............................................................33

γ

γ
vi

Figure 43. Equation. Time-Variant Redundancy Index 1..............................................................33

Figure 44. Equation. Time-Variant Redundancy Index 2..............................................................33

Figure 45. Equation. Vulnerability ................................................................................................34

Figure 46. Equation. Damage Tolerance .......................................................................................34

Figure 47. Equation. Ductility .......................................................................................................34

Figure 48. Equation. Risk ..............................................................................................................35

Figure 49. Graph. Reasons for Bridge Rating of SD or FO...........................................................44

Figure 50. Graph. Deck Area (m2

) of Bridges by Owners.............................................................52

Figure 51. Graph. Numbers of Bridges Built in 5-Year Periods by Material................................53
vii

LIST OF TABLES

Table 1. Diversity of Bridge Characteristics....................................................................................2

Table 2. Types of Entities with Bridge Maintenance Responsibility ..............................................4

Table 3. Main Categories of Bridge Performance and General Contributing Factors.....................8

Table 4. Finnra Condition Rating ..................................................................................................19

Table 5. Finnra ADT Weighting Factor.........................................................................................19

Table 6. Classification of Structural Performance Indicators........................................................36

Table 7. Durability and Serviceability Performance Data .............................................................40

Table 8. Functionality, Cost, Structural Integrity, and Organizational Data .................................41

Table 9. Diversity of Bridge Characteristics, Parameters, and Operating Conditions ..................49

Table 10. Bridges by Functional Classification Weighted by Number, ADT, and Deck Area........50

Table 11. Numbers and Percentages of Bridges and Deck Area by Owner ..................................51

Table 12. Design Type of Main Span (NBI Item Number 43B) ...................................................52

Table 13. Kind of Material Main Span (NBI Item Number 43A) .................................................53

Table 14. Numbers of FO Bridges and Deck Area of FO Bridges by Owner...............................54

Table 15. Numbers of SD Bridges and Deck Area of SD Bridges by Owner...............................55
viii

LIST OF ACRONYMS

AASHTO American Association of State Highway and Transportation Officials

ADT Average daily traffic

ASD Allowable Stress Design

BCI Bridge condition index

FHWA Federal Highway Administration

Finnra Finnish National Road Administration

FO Functionally Obsolete

LCV Lack of capital value

LRFD Load and Resistance Factor Design

LTBP Long-Term Bridge Performance 

NBIS National Bridge Inspection Standards

NBI National Bridge Inventory

NHS National Highway System

SD Structurally Deficient

SHM Structural health monitoring

SR Sufficiency Rating

STRAHNET Strategic Highway Network 
1

CHAPTER 1. THE BASICS OF BRIDGE PERFORMANCE

The United States is more dependent than ever on its transportation system to consistently support

a thriving economy and to afford its citizens a satisfactory quality of life. The system must provide 

for rapid response in case of personal or public emergencies; ensure a high level of national security,

safety, and resilience; and provide the ability to respond quickly in times of attack or natural disaster.

However, the engineered components of the transportation infrastructure, including bridges, have

aged. Some are deteriorated, and many have exhausted their capacity to meet the ever-expanding 

operational demands in urban areas and along major freight routes. The system has also become 

more interdependent on other transportation modes and on financial, telecommunication, and 

cyber infrastructures for its operational and structural safety and security.

The transportation user community expects and deserves a system that routinely provides the highest

quality service in terms of safety, efficiency, and economy while having the least possible impact 

on the local and global environment. Optimal operation of public highway systems is dependent 

on many factors. Bridges are critical nodes in the highway infrastructure, and poor performance of 

any bridge has the potential to reduce the operating capacity of the highway system it is a part of. 

Under current circumstances, most bridges will eventually reach a state where work is necessary to 

return the bridge or some of its components to a satisfactory level of condition or safety. The true 

criticality of bridges is often only apparent when work is necessary to maintain, rehabilitate, or 

replace an existing bridge or series of bridges; a bridge is closed due to conditions or service below 

acceptable levels; or a bridge collapses with attendant damage to property, disruption to service, 

or loss of life. Work zones where bridge work is underway usually involve one or more conditions

that result in disruption to safe, efficient, and economical traffic flow. These conditions include 

narrowed or closed lanes, live load restrictions, speed reductions, inefficient detours, and safety 

hazards that result from these conditions. Negative impacts on local and regional economies 

and environments can often result from loss of productive time due to traffic delays and detours, 

work-zone accidents, or increased consumption of fuel and engine emissions, among other issues.

In the United States, the current knowledge base of inventory and condition data on bridges is 

among the best in the world. Current programs and methods of bridge inspection and the tools used

for managing bridge programs are also among the best in the world. Yet the level of understanding

of how bridges perform and how to satisfactorily measure their performance falls well short of 

desirable. Many attempts at performance assessment rely on expert opinion combined with 

significant assumptions and generalizations. 

This bridge performance primer is intended to provide a clear and comprehensive perspective on 

the concept of bridge performance and to present a path to a better and deeper understanding of 

bridge performance, including how it can be reliably measured and used to improve the highway 

transportation system. This report describes the various ways in which bridge owners can and do 

currently measure and report bridge performance. It also describes how the Long-Term Bridge 

Performance (LTBP) Program will create new measures of performance that will allow a deeper 

analysis and understanding of performance, which will lead to ways to improve long-term 

bridge performance.
2

THE HIGHWAY BRIDGE INFRASTRUCTURE

The highway bridge infrastructure in the United States is very large and diverse. In this report, the 

term bridge is defined by the National Bridge Inspection Standards (NBIS): “a structure including 

supports erected over a depression or obstruction such as water, highway, or railway and having 

a track or passageway for carrying traffic or other moving loads and having an opening measured 

along the center of the roadway of more than 20 ft.”(1) A brief look at data from the National Bridge

Inventory (NBI) provides a revealing picture of this vital public asset.

The 2011 NBI contains records for 605,098 bridges, of which 132,150 are classified as tunnels or 

culverts.(2) The remaining 472,948 are single- or multi-span bridges separating vehicular traffic 

from other traffic or some topographical feature, usually a stream or river. These bridges range 

from the average highway overpass structure to “signature bridges” such as the Golden Gate 

Bridge, the Brooklyn Bridge, or the Sunshine Skyway. Within this range, the diversity of the 

bridge infrastructure in terms of age and design parameters (including structural type, materials of 

construction, width, and length) is exceptionally broad. NBI records describe bridges using many 

different attributes or parameters. Table 1 provides an abbreviated list of these characteristics and 

indicates how many different types there are in the NBI for each.(1)

Table 1. Diversity of Bridge Characteristics.

(1)

NBI Item

Number

of Types

Kind of material, main span and/or approach span 10

Structure type, main span and/or approach span 23

Design load 10

Bridge posting 6

Deck structure type 9

Wearing surface 9

Membrane 5

Protective system 9

In addition to these mostly fixed attributes or parameters, there are wide variations in the ages of 

bridges and the service conditions under which they perform. Figure 1 illustrates the diversity in 

bridge ages by providing a histogram of bridges still in service grouped in 5-year increments.

The average age of all bridges in the NBI is 41.0 years. One of the oldest bridges in the NBI is in 

Sackets Harbor, NY, carrying Military Road over Mill Creek. It is a concrete arch bridge with a 

deck that is 44.9 ft long and 21.6 ft wide. The bridge was built in 1800 and underwent a complete 

rehabilitation in 2003. As of 2011, the bridge was rated in excellent condition and was open to 

traffic with no load restrictions.(2)
3

Figure 1. Graph. Age Distribution of All Bridges in the United States.

(2)

The National Highway System (NHS) of the United States comprises approximately 160,000 mi 

of roadway, including the Interstate Highway System and other roads, which are important to the 

nation’s economy, defense, and mobility. The total mileage of the NHS includes only 4 percent of

the nation’s roads, but it carries more than 40 percent of all highway traffic, 75 percent of heavy 

truck traffic, and 90 percent of tourist traffic. About 90 percent of the U.S. population lives within 

5 mi of an NHS road. All urban areas with a population of more than 50,000 and 93 percent of 

areas with a population of between 5,000 and 50,000 are within 5 mi of an NHS road. Counties 

that contain NHS highways also host 99 percent of all jobs in the nation, including 99 percent 

of manufacturing jobs, 97 percent of mining jobs, and 93 percent of agricultural jobs. There are 

116,523 bridges on the NHS.(2,3)

The age of a bridge serves as a rudimentary measure of the aggregate service provided during its 

service life as well as a harbinger of the level of degradation and damage the bridge may have 

experienced without consideration of periodic interventions for preservation, maintenance, repair,

or major reconstruction. Age data can also be meaningful in terms of understanding the bridge 

materials, design standards and specifications, and construction processes used in construction of 

a bridge. The overall performance of bridges of a certain age might be expected to be poorer than 

that of bridges built after more recent advancements. Advancements generally correlate with 

better current and future performance, though this is never a certainty.

Service conditions for bridges vary dramatically in terms of traffic volume; truck loading 

(including overweight permit loads); level of vulnerability to natural events such as floods, ice, 

impact of waterborne debris, wind, and seismic loading; and susceptibility to long-term effects of 

climate and the service environment. Often, there is also the potential for significant damage from

manmade hazards such as impacts by waterborne vessels or vehicular traffic, fires, explosions, 

chemical spills, or other events not considered ordinary service factors. In regions where snow 

and ice control is necessary, routine winter deicing operations result in application of chemicals 

that are known agents of deterioration of bridge elements.
4

Other critical factors affecting bridge performance are the types, frequency, and effectiveness of 

preservation, maintenance, repair, or rehabilitation actions performed on bridges by the owner. In a 

few States, the transportation department owns and is responsible for maintenance of all bridges on

public roads. However, in most States, a significant percentage of the bridges on public highways 

are owned by other types of agencies, including agencies at the county and city levels of government,

railroad companies, toll authorities, and other semiprivate or private entities. Table 2 shows the 

numbers of different types of entities that have maintenance responsibilities for bridges on public 

highways. Bridge performance is impacted significantly by the policies and procedures at any 

bridge-owning agency as well as by the agency’s culture, the knowledge and experience of bridge 

personnel, the priorities of the agency, the revenues available for bridge programs, and the 

agency’s funding mechanisms.

Table 2. Types of Entities with Bridge Maintenance Responsibility.

(1)

Entity Category

Number of 

Different Types

State and local highway agencies 4

Other State and local agencies 4

Private owners 4

Federal agencies 15

The cumulative effect of these factors may vary. At the level of State transportation departments, 

performance is generally good to very good, whereas at the level of local agencies, where resources

are limited, performance may be fair to poor. More detailed information on the demographics of 

the bridge infrastructure in the United States, as recorded in the 2011 NBI, can be found in the 

appendix.

The Federal Highway Administration (FHWA) has initiated the LTBP Program, which was 

authorized in the Safe, Accountable, Flexible, and Efficient Transportation Equity Act: A Legacy 

for Users, signed into law in August 2005. The LTBP Program is a minimum 20-year, multifaceted

research effort that is strategic in nature and has both specific short-term and long-range goals. 

Its concept is similar to the Long-Term Pavement Performance program that has been underway 

for more than 20 years. The overall objective of the LTBP Program is to inspect, evaluate, and 

periodically monitor representative samples of bridges nationwide in order to collect, document, 

maintain, and manage high-quality, quantitative performance data over an extended period of time.

The program will employ sensing technologies and non-destructive evaluation and testing tools 

in addition to typical bridge inspection approaches. It will also require close collaboration among 

stakeholders, including public agencies, academia, and industry. Data collected under the LTBP 

Program will help in the performance evaluation of certain critical elements or features of bridges

such as decks. Tools such as the Bridge Portal, data-driven deterioration models, life-cycle cost 

models, and a bridge condition index (BCI) will be developed to help engineers analyze the

long-term performance of individual bridges.
5

THE MEANING OF “BRIDGE PERFORMANCE”

One simple definition of performance is that performance equates to accomplishment of a specified 

purpose or set of purposes. For the purposes of the LTBP Program, the following definition is 

used: Bridge performance encompasses how bridges function and behave under the complex 

and interrelated factors they are subjected to day in and day out—traffic volumes, loads, deicing 

chemicals, freeze-thaw cycles, rains, or high winds. Bridge design, construction, materials, age, 

and maintenance history also play roles in performance. Performance is usually associated with 

some set of standards, whether absolute or relative, and performance can be measured against those

standards. In baseball, for example, one purpose of a batter is to hit safely, and a measure of the 

batter’s performance is the batting average—the number of hits divided by the number of at-bats. 

A batter hitting over 0.300 is considered to be performing very well. 

The purpose of a bridge is inherent in the NBIS definition: to carry vehicular traffic or other 

moving loads over a depression or obstruction such as water, highway, or railroad.

Transportation users expect a given bridge to accomplish its purpose in a satisfactory manner as 

measured against several objectives. Bridges should do the following:

• Present a minimal safety hazard to users during normal service.

• Present minimal obstruction to the free flow of traffic at all times.

• Have a minimal negative impact on the local and global environments.

• Present an acceptable level of risk against catastrophic failure.

• Present an aesthetically pleasing appearance.

• Accomplish all of the preceding elements with minimal life-cycle costs.

As a performance indicator for a baseball batter, batting average is a simple index with a range of 

0.000–1.000. The batting average is a useful measure, but it does not reflect the value of the batter

to the baseball team in a complete manner. Other related factors are also important, including hits 

with runners in scoring position; number of bases reached via singles, doubles, triples, and home 

runs; percentage of times reaching base safely; or even the outcome of at-bats in which the batter 

does not hit safely. In the same manner, the overall performance of a bridge cannot be described 

by any one rating, index value, or other individual parameter.

The differences in batters’ levels of performance are analogous to the differences in bridges’ levels

of performance. Imagine bridge A is located in an arid (dry, no-freeze) climate and bridge B is 

located in a northern (wet, freeze) climate. The bridges are steel multigirder simple span bridges

that were built in the same year. The girders on bridge A are rated 8 on the NBI scale, nearly new 

condition. The girders on bridge B are rated 4, for poor condition with advanced section loss and

deterioration. In comparing the relative performance of each bridge, factors such as annual snowfall,

amount of deicing salts applied, and condition of the joints must be considered. Also of importance

are the type and frequency of preservation treatments applied to the bridge (e.g., sealing joints, 

washing the superstructure, etc.). Continuing the analogy, baseball factors such as hits with runners

in scoring position could be the equivalent of traffic and heavy trucks carried on the bridges.
6

There are many different ways to measure bridge performance. Some of these measures are in the 

form of an index value calculated from a defined formula using input data such as NBI condition 

ratings and traffic volumes. As detailed later in this report, numerical indices such as the Federal 

Sufficiency Rating (SR), California Bridge Health Index, and Finnish National Road Administration

(Finnra) Repair Index have been used for quite some time to define bridge performance.(2,4,5) For 

example, SR is an index calculated from an established formula and has a range of 100 (representing 

an entirely sufficient bridge) to 0 (representing an entirely insufficient or deficient bridge). An 

SR value of less than 50 indicates a low level of performance but does not reveal the specific 

characteristics of the bridge that render it deficient.

Other measures are based on whether or not a bridge meets some defined criteria. These include 

classification as Structurally Deficient (SD) or Functionally Obsolete (FO) and whether a bridge

meets or exceeds defined deflection limits. Still other measures reflect a level of operational capacity 

or service, including posted load, load rating, rideability of the bridge wearing surface, traffic 

congestion near or on the bridge, number of accidents on the bridge, and percentage of rain events 

and floods that overtop the bridge. Most of these measures can be applied to an individual bridge 

or to a population of bridges, such as bridges on the NHS or bridges of a certain type and material.

Chapter 2 and chapter 3 provide insight into some of these measures, including measures for 

special considerations related to bridge safety and stability. Each measure has value depending 

on the person using the measures and the purpose for using it. For example, commercial interests,

shippers, and drivers can use simple measures of posted weight limits or geometrical dimension 

limitations to weigh performance in terms of durability, operational capacity, and roadway safety,

all important factors in supporting a free flow of goods and services. In contrast, chapter 4 shows

that these measures do not readily support a better understanding of bridge performance because it

is difficult to correlate changes in these measures with underlying causes of changes in performance.

Chapter 4 discusses what needs to be done to better understand and develop solutions to improve 

bridge performance.

Experience has shown that the performance of any specific bridge is dependent on complex 

interactions of multiple factors, many of which are closely linked, including the following: 

• The original design parameters and specifications such as bridge type, materials of 

construction, geometry, and load capacity.

• The initial quality of materials and of the as-built construction.

• The varying environmental conditions of climate, air quality, and surrounding soil.

• The extent and severity of corrosion or other deterioration processes that affect component 

strength or structural behavior (e.g., bearings locked up due to corrosion products).

• The traffic volumes and frequency and the weight of truck traffic carried by the structure.

• The type, timing, and effectiveness of preventive maintenance, minor and major 

rehabilitation actions, and ultimately, replacement actions.
7

All of these factors combine to affect the condition and operational capacities of the bridge and its 

structural elements at any given point in the life of the bridge. While simple measures such as those 

described in this chapter are currently used to evaluate overall performance, a better performance 

measure would be an indicator of the qualitative or quantitative impact of a parameter or set of 

parameters on some specific aspect of bridge performance.

Because bridge performance is a complex issue, it is useful to organize the primary issues relating

to bridge performance into general categories. As shown in figure 2, the primary issues in bridge 

performance can be divided into four general categories: structural condition (for durability and 

serviceability), functionality (safety and traffic capacity), structural integrity and risk (for safety 

and stability), and costs to the user and to the agency.

Figure 2. Illustration. Main Categories of Bridge Performance Issues.

Many relevant factors combine to affect performance under each of these four main categories. 

Table 3 lists the relevant factors that might impact various aspects of bridge performance. Within 

these categories are many specific performance issues that are of importance to the bridge 

community and that could be studied over the long term to achieve better understanding. For each 

of these specific performance issues, there are multiple data items that could be gathered to assist 

in the evaluation of performance.
8

Table 3. Main Categories of Bridge Performance and General Contributing Factors.

Category Important Data or Factor

Structural condition—

durability and

serviceability

Structure type

Structural materials and material specifications

Structure age

As-built material qualities and current conditions

As-built construction qualities and current conditions

Truck loads and other live loads

Environment—climate, air quality, and marine atmosphere

Snow and ice removal operations

Type, timing, and effectiveness of preventive maintenance

Type, timing, and effectiveness of restorative maintenance

and minor and major rehabilitation

Flooding, hydraulic design, and scour mitigation measures

Subsurface soil characteristics—settlement

Functionality—

user safety and level 

of service

Structure geometry—clear deck width, skew, and approach 

roadway alignment

Skid resistance and ride quality of riding surface

Vertical clearances—over and under

Traffic volumes and percentage of trucks

Posted speed

Structural integrity—

safety and stability in 

all failure modes

Seismic performance

Hurricane and flood resistance

Collision impacts

Blast impacts

Fire resistance

Structural redundancy and load redistribution 

Costs to

users and agency

Users: Accident costs

Users: Detour and delay costs

Agency: Initial construction costs

Agency: Maintenance, repair, and rehabilitation costs

Agency: Traffic maintenance costs

WHY MEASURE BRIDGE PERFORMANCE?

Bridge performance is an issue that is of some concern to virtually everyone in the country, 

including people in the following roles:

• Highway users, including the following:

o Commuters.

o Routine travelers and tourists.

o Deliverers of goods and services.

o Emergency responders.
9

• Legislators who create programs and provide funds for the design, construction, inspection, 

maintenance, repair, and replacement of bridges.

• Policymakers and administrators in transportation agencies.

• Engineers and planners who design and build highways and bridges.

• Bridge maintenance and bridge management engineers and personnel who work to keep 

bridges at a satisfactory level of service and prevent failures.

• Consultants and commercial interests who provide materials and services for the design, 

construction, inspection, management, maintenance, repair, demolition, and replacement 

of bridges.

• Providers of news who inform the public of issues of local and national interest related to 

highways and bridges.

Bridge performance measures may have multiple uses depending on the perspective and 

responsibilities of those using the measures. The average everyday user seeks congestion-free 

travel, reassurance about highway safety, and rapid assistance from first responders. Less apparent 

but also of great importance to the everyday user is minimization of the use of public resources 

to keep bridges safe and at a satisfactory level of service.

Engineers and planners should factor performance into future planning, design, and construction 

of bridges by applying lessons learned from the performance of previously built bridges. Bridge 

maintenance and bridge management personnel use measures of performance to evaluate the 

policies, practices, techniques, and materials that they employ to prolong bridge service at a 

satisfactory level and to project future bridge needs.

Consultants and commercial entities use performance indicators to make critical business decisions 

on what technology, equipment, materials, and services to develop or improve and to provide to 

bridge owners.

News outlets use simple performance measures and statistics to inform the general public and 

key transportation constituencies about critical issues related to the transportation system.

Engineers, planners, and bridge maintenance and management personnel have the most immediate 

use for reliable bridge performance measures because they can have the most immediate impact on

changing the factors that influence bridge performance. These individuals and their organizations 

need reliable bridge performance measures in order to do the following: 

• Accurately evaluate congestion and traffic safety.

• Provide an accurate measure of load capacity, safety, and the need for load restrictions.
10

• Identify clear links between specific policies, actions, and the resulting change in 

performance level of bridge features based on the following:

o Improved knowledge of how and why bridges deteriorate (i.e., advances in 

deterioration and predictive models).

o Better understanding of the effectiveness of various maintenance, repair, and 

rehabilitation strategies as well as management practices.

o Better understanding of the effectiveness of durability strategies for new bridge 

construction, including material selection.

o Improvements in bridge management practice using high-quality quantitative data.

• Evaluate serviceability and durability.

• Set priorities for resource allocations within the transportation system and the bridge 

infrastructure.

• Evaluate organization-wide policies and programs such as the split between maintenance 

and capital funds.

• Improve system reliability, redundancy, and accountability.

• Establish risk-based evaluations of bridges that are vulnerable to failure.
11

CHAPTER 2. CURRENT APPROACHES TO MEASURING BRIDGE PEFORMANCE

Making useful and reliable assessments of bridge performance is a challenging task. Many complex 

factors contribute to the difficulty of measuring bridge performance, including the following: 

• The large scale and extreme diversity of the bridge infrastructure.

• The many and variable causative factors that impact performance.

• A limited understanding of some of the key cause-and-effect relationships in bridge 

deterioration or diminished functional capacity.

• Data that are inconsistent, not in a usable format, not easily accessible, or unavailable.

• Different policies and practices for design, construction, inspection, preservation, 

maintenance, repair, and replacement for different samples of bridges.

• Changes in design codes, construction practices, and traditional bridge materials over time.

• The introduction of new and innovative materials.

• The widely differing objectives of various groups who assess bridge performance.

The last point is an issue of considerable importance in the assessment of bridge performance. 

Bridge engineering is not a static art or science. As new materials and techniques are developed 

and implemented on bridges, the assessment of performance, particularly of structural condition 

and integrity, is altered. Examples over the history of bridges include the following:

• Bolting and welding replaced riveting.

• Epoxy-coated reinforcing bars replaced black bars in many States.

• New alloys were developed to provide further corrosion protection for reinforcing bars.

• Design of concrete mixtures evolved, with significant improvements in strength and 

permeability characteristics.

• High-performance steels with greater strength, ductility, and corrosion resistance have 

become routinely used.

• High-performance concretes and steel have led to the possibility of lighter superstructure 

dead loads.

• Applications of non-traditional materials such as fiber-reinforced polymer composites have 

been developed both for new bridges and for repair or enhancement of in-service bridges.

• Repair materials and methods have changed and developed. 

• Joint details have changed, including the use of integral abutment bridges.
12

Many aspects of performance are moving targets and present considerable difficulty in making 

reliable and consistent measurements. Regardless of the difficulties involved, developing and 

implementing reliable bridge performance measures is of paramount importance. The array of 

consumers of bridge performance knowledge is broad, and critical social, economic, commercial,

and political decisions hinge on those measurements. Every State transportation department has 

developed a set of performance measures for its highway system. These performance measures

address a wide variety of objectives, covering issues such as the following:

• Reductions in injuries, fatalities, and property damage.

• Improvements in mobility of people and goods.

• Reductions in incident-related delays.

• Increases in the percent of pavements and bridges in satisfactory or better condition.

• Increases in the percent of bridges that are not posted with a weight limit restricting use 

by legally loaded vehicles.

• Improved customer satisfaction with maintenance, ride quality, and incidents of congestion.

Many of these performance measures are dependent on the condition and functional operation of the

owner’s bridges. But evaluating the impact of bridges on the achievement of most of these objectives 

is difficult at best, requiring intuitive reasoning and significant assumptions about cause and effect.

Most States that have established overall agency and system performance measures have also 

established more specific measures related to bridges. Some transportation departments use measures 

related to the percentage of bridges at a certain defined level of condition, such as good or excellent.

Often, these performance measures relate to numbers or deck areas of bridges that are deficient 

or involve some index calculated based on data in the NBI or on element-level inspection data 

collected for bridge management databases. Examples of measures in use include the following:

• The percentage of bridge structures on the State highway system having a condition 

rating of either excellent or good.

• The percentage of bridge structures on the State highway system with posted weight 

restrictions.

• The percentage of bridge structures on the State highway system with an SR over 80.

NBI CONDITION AND APPRAISAL RATINGS

For almost four decades, as required by NBIS, bridge owners in the United States have compiled 

a complete inventory of bridge information and condition data, and many State transportation 

departments have several years of experience compiling comprehensive bridge databases for use 

in their bridge management systems. Despite these multiyear efforts, the availability of high-quality,

useful data on many of the factors impacting bridge performance varies significantly from State 

to State. Much of the fixed data (e.g., structure type, construction materials, dimensions, clearances,
13

scour protection, functional classification) are well documented and easily accessible. Current and 

historical data on the physical condition of bridge elements are also readily accessible; however, 

these data have shortcomings that are discussed later in this report. Beyond these two types of 

data, the availability and accessibility of high-quality, useful data on factors impacting bridge 

performance are generally poor to fair.

In the United States, most of the effort in bridge performance assessment has concentrated on

measuring, recording, analyzing, and using bridge condition data. Collection of detailed information 

and condition data about bridges in the United States started with implementation of NBIS in 1971 

and has continued in a consistent, systematic, and computerized format for four decades. While these

data have been and still are used to assess bridge performance, the NBI does not represent a complete

basis for documenting and assessing long-term bridge performance with proper consideration of 

all relevant factors. A proper assessment of bridge performance over time requires systematic 

correlation of changes in bridge conditions and functional capacities with key policies, programs,

and actions that affect those conditions and capacities. 

The collapse of the Silver Bridge at Point Pleasant, WV, in December 1967 was the defining 

moment in the development of bridge inspection programs, bridge data collection, formal bridge 

improvement programs, and, ultimately, modern bridge management systems. Prior to this event, 

knowledge of bridges was poor. Immediately after the collapse, crucial questions about the bridge

population arose: How many bridges are there in the United States? What types of structures? Of 

what materials were they constructed? Where are they located? What are their current conditions? 

How vulnerable are they to failure? What are the immediate improvement priorities? What is the 

required scale of effort and associated cost to address significant deficiencies? There were virtually 

no useful answers immediately available. As a consequence, there was no basis for assessing the 

condition of individual bridges or the overall bridge population. There was certainly no basis for 

assessing the performance of bridges over time. 

The NBI was created to address the absence of knowledge about the bridge inventory and bridge 

conditions. However, the NBI was neither envisioned, nor structured, to support the assessment 

of bridge performance over the long term. Guidance on meeting the requirements of the NBI was 

published in 1971, and by the end of 1973, the States had inventoried most of the bridges on the 

Federal-Aid Highway systems. Over time, the NBI has become a current and historical database, 

comprising a consistent set of data on almost every bridge over 20 ft long on all public highways 

in the United States. As a comprehensive database of information about bridges spanning the 

majority of a continent, the NBI remains unique in the world. Inventory and condition data have been

collected on a large population of individual bridges for almost four decades, and the guidelines

for collecting, reporting, checking, editing, and storing these data have been consistent over the 

life of the NBI. The guidelines were carefully written, were accepted and used by all domestic 

transportation agencies, and have only been modified slightly when needed. In particular, the 

system of evaluating and recording the key appraisal and condition data on each bridge has remained

virtually unchanged over the full life of the NBI. A full explanation of the data and the guidelines 

for collecting and recording data can be found in the current issue of Recording and Coding Guide

for the Structure Inventory and Appraisal of the Nation’s Bridges, published by FHWA.

(1)
14

NBI data are categorized by type, as follows:

• Identification (location, features carried, and features crossed).

• Structure type and material.

• Age and time in service.

• Geometry.

• Navigation.

• Highway classification.

• Condition ratings.

• Load rating and posting.

• Appraisal ratings (current ratings of adequacy of major features such as deck width and 

approach roadway alignment).

• Proposed improvements and inspection requirements.

With regard to supporting performance assessment, the key NBI data are structure type and material,

condition ratings, and appraisal ratings. Fields that are less important but still useful are traffic 

volume data, location information (indicative of climate and environmental factors and potential for 

corrosion), and load ratings. NBI condition and appraisal ratings are generally attributed according

to a scale of 0–9. In practice, ratings in the range of 4–7 are most common for bridges in service.

As an example, applicable NBI codes and associated definitions for the condition rating of deck, 

superstructure, and substructure (NBI items 58–60) are as follows:

• 9, Excellent condition.

• 8, Very good condition: No problems noted.

• 7, Good condition: Some minor problems.

• 6, Satisfactory condition: Structural elements show some minor deterioration.

• 5, Fair condition: All primary structural elements are sound but may have minor section 

loss, cracking, spalling, or scour.

• 4, Poor condition: Advanced section loss, deterioration, spalling, or scour.

• 3, Serious condition: Loss of section, deterioration, spalling, or scour have seriously 

affected primary structural components. Local failures are possible. Fatigue cracks in 

steel or shear cracks in concrete may be present.
15

• 2, Critical condition: Advanced deterioration of primary structural elements. Fatigue 

cracks in steel or shear cracks in concrete may be present or scour may have removed 

substructure support. Unless closely monitored, it may be necessary to close the bridge 

until corrective action is taken.

• 1, Imminent failure condition: Major deterioration or section loss present in critical 

structural components or obvious vertical or horizontal movement affecting structure 

stability. Bridge is closed to traffic but corrective action may put back in light service.

• 0, Failed condition: Out of service—beyond corrective action.

Applicable NBI codes and definitions for the appraisal rating of the same items are as follows:

• NA: Not applicable.

• 9: Superior to present desirable criteria.

• 8: Equal to present desirable criteria.

• 7: Better than present minimum criteria.

• 6: Equal to present minimum criteria.

• 5: Somewhat better than minimum adequacy to tolerate being left in place as is.

• 4: Meets minimum tolerable limits to be left in place as is.

• 3: Basically intolerable requiring high priority of corrective action.

• 2: Basically intolerable requiring high priority of replacement.

• 1: This value of rating code is not used.

• 0: Bridge closed.

While these performance measures have served well when used for condition evaluation and 

apportionment of funds, these measures do not cover all of the variables that researchers would 

like to evaluate.

PERFORMANCE MEASURES BASED ON BRIDGE DEFICIENCIES

The NBI condition ratings are well established after almost four decades of use in assessing the 

current condition of the major components of bridges being inventoried and inspected. The same is 

true of NBI appraisal ratings for assessing functional capacities. Changes in these ratings over 

time reflect the general performance of the bridge. The ratings are used to classify bridges as 

deficient or not deficient.
16

Bridges with low NBI condition or appraisal ratings are flagged and classified as follows:

• SD: A highway bridge is classified as structurally deficient if item 58 (deck), item 59 

(superstructure), item 60 (substructure), or item 62 (culvert) is rated “poor” condition or 

worse (coded 4 or lower on the NBI rating scale). A bridge can also be classified as SD if 

its load-carrying capacity is significantly below current design standards, with item 67

(structural evaluation appraisal) coded 2 or lower, or if item 71 (waterway adequacy) for 

the feature below the bridge is coded 2 or lower.

• FO: A highway bridge classified as functionally obsolete is not SD, but its design is 

outdated. The bridge may have lower load-carrying capacity, narrower shoulders, or less 

clearance underneath than bridges built to the current standards. Classification as FO is 

triggered by a code of 3 or lower for item 68 (deck geometry appraisal), item 69 

(underclearances, vertical and horizontal), or item 72 (approach roadway appraisal).

A bridge is also classified as FO if item 67 (structural evaluation appraisal) or

item 71 (waterway adequacy appraisal) is coded 3.

The two classifications of deficient bridges provide simple tools for agencies to describe the overall 

performance of their bridge populations and the overall effectiveness of their bridge programs. An 

unpublished 1999 FHWA study described various ways in which State transportation departments

use these two classifications in their measurement of bridge performance. Several agencies use only 

the number of deficient bridges as a measure, whereas others use a combination of SR and the 

number of deficient bridges. When determining the proportion of a bridge population flagged as 

deficient, some agencies take into consideration the relative size of deficient bridges, represented 

by the cumulative square footage of deck the structures carry, rather than a simple count of 

structures. This approach is intended to discourage the practice of repairing small structures to 

improve the metrics while deferring repairs on larger structures that carry significant traffic for 

which repair would incur greater expense. Oftentimes, agencies will consider both metrics in 

their assessment of program performance.

THE FEDERAL SR

SR is an index that was devised by FHWA and used to evaluate the eligibility of bridges for Federal

highway bridge rehabilitation and replacement funds. The SR formula is a method of evaluating 

highway bridge data by calculating and summing four separate factors to obtain a numeric value 

indicative of bridge sufficiency to remain in service. On the resulting rating scale, 100 represents

an entirely sufficient bridge and 0 represents an entirely insufficient or deficient bridge.

SR is calculated using a complex formula wherein weighting factors are assigned to several 

bridge parameters and attributes in order to arrive at the numerical index for each bridge. The 

basic formula is shown in figure 3.

Figure 3. Equation. Federal SR.(1)

Where: 

S1 = Structural adequacy and safety (maximum value = 55 percent).

SR = S1 + S2 + S3 – S4
17

S2 = Serviceability and functional obsolescence (maximum value = 30 percent).

S3 = Essentiality for public use (maximum value = 15 percent).

S4 = Special reductions (maximum value = 6 percent).

These four factors provide consideration and weight to the following:

• Structural adequacy and safety: Condition ratings for deck, superstructure, and 

substructure plus the inventory (load) rating.

• Serviceability and functional obsolescence: Traffic lanes, average daily traffic (ADT), 

structure type, structural evaluation, waterway adequacy, and Strategic Highway Network 

(STRAHNET) designation plus several key geometric parameters.

• Essentiality for public use: Detour length, ADT, and STRAHNET designation.

• Special reductions: Detour length, traffic safety features, and structure type.

A complete description of the SR formula is available in Recording and Coding Guide for the 

Structure Inventory and Appraisal of the Nation’s Bridges.

(1)

THE HEALTH INDEX

To further its goal of preserving the bridge inventory, the California Department of Transportation 

has adopted a bridge health index as a performance measure. The health index is a single number 

indicator of the structural health of the bridge. This indicator is expressed as a value from 0 to 

100 percent, corresponding to the worst and best possible conditions, respectively. The health 

index is calculated as a function of the fractional distribution of the bridge’s element-level 

information across the range of applicable condition states, as shown in figure 4.

Figure 4. Equation. California Bridge Health Index.

(4)

Where:

HI = Health index.

QCSi = Quantity in condition state i.

WFi = Weighting factor for condition i.

TEQ = Total element value i.

We = Element indicator cost of other important indicator for each element.

Other State transportation departments also use health indices. The California Department of 

Transportation’s index is cited here as an example.

HI = (ΣQCSi × WFi)/(ΣTEQ × We) × 100% {Worst = 0%, Best = 100%}
18

BRIDGE PERFORMANCE MEASURES USED IN OTHER COUNTRIES

In the interest of understanding what other nations use to evaluate their bridge inventories, FHWA

sponsored an international scan that resulted in the report Bridge Preservation in Europe and 

South Africa.

(5) The following discussion of performance measures used in Finland, South 

Africa, and Sweden includes excerpts from that report.

Finland

Finland uses two performance indicators: one for repairs that improve a bridge’s physical 

condition and one for rehabilitation, which encompasses improvements related to functional 

deficiencies. Details of these indicators are as follows: 

• The repair index is a weighted combination of condition ratings that establishes priorities 

for repair projects and depends primarily on defect severity and ADT.

• The rehabilitation index responds to functional deficiencies and can indicate a need for 

improvement rather than repair.

The following discussion of performance measures used in Finland is representative of the 

findings in the international report and is excerpted directly:

“Finland has a reference group of 106 bridges and 26 steel culverts. The 

performance of the group is closely monitored to improve knowledge of bridge 

behavior and durability, calibrate [bridge management system] deterioration 

models, and evaluate methods for field testing. Reference bridges are used in 

training and annual recertification of bridge inspectors...

Finnra computes performance measures for defects, repair needs, and rehabilitation

needs. A repair index is computed for the set of defects at a bridge. A rehabilitation 

index is computed for functional deficiencies. A repair index contributes to priorities 

for repair, unless the rehabilitation index indicates that a repair project should be 

set aside in favor of a rehabilitation project. 

Defects in a bridge are assigned ratings in each of four categories: weight 

(importance in the load path...), condition of the structural part (apart from this 

defect), urgency of the repair (rate of growth of defect), and damage class (severity

of the defect). For each bridge, a repair index, KTI, is computed for the set of defects, 

with the greatest weight placed on the worst defect. [See figure 5. Higher values 

indicate more important and urgent repairs.]

Figure 5. Equation. Finnra’s Repair Index.

(5)

[Where:]

KTI = Repair Index.

Wt = Weight (importance) of the damaged structural part.

KTI = Max (Wti × Ci × Ui × Di

) + kΣ(Wtj × Cj × Uj × Dj)
19

C = Condition of the structural part.

U = Urgency of the repair.

D = Class (severity) of damage.

k = A weighting factor for damage summation. The default value is 0.2.

i = Worst defect.

j = Other defects.”

(5)

The importance of the various structural parts is weighted from 0.20 for expansion joints to 1.00 

for the superstructure. Condition points are assigned on a sliding scale as shown in table 4. 

Table 4. Finnra Condition Rating.(5)

Condition Rating Condition Points

0. New or like new 1

1. Good 2

2. Satisfactory 4

3. Poor 7

4. Very poor 11

Urgency of the necessary repair is classified with a point system of 10 points for repairs needed 

during the next 2 years, 5 points for repairs needed during the next 4 years, and 1 point for repairs

not needed within 4 years. The severity of the deterioration or damage is also classified using a 

point system with 1 point for mild severity, 2 points for moderate severity, 4 points for serious

severity, and 7 points for very serious severity. Finally, a weighting factor based on ADT is 

assigned for the essentiality of the repair, as shown in table 5.

Table 5. Finnra ADT Weighting Factor.

(5)

ADT (vehicles /day) Factor

> 6,000 1.15

3,000–6,000 1.10

1,500–3,000 1.00

350–1,500 0.90

< 350 0.85

Finnra’s rehabilitation index, UTI, is calculated as shown in figure 6.

Figure 6. Equation. Finnra’s Rehabilitation Index.

(5)

Where:

kp = Factor for bridge total area.

kl = Factor for ADT.

UTI = kp × kl × (Condition + Load Capacity + Functionality)
20

The authors of the FHWA report also note, “The rehabilitation and reconstruction index, UTI, 

combines deterioration, bridge load capacity, and functionality to determine whether a bridge 

should be rehabilitated or replaced rather than repaired.”(5) Finland sets annual goals for 

reducing severe deterioration in structures.

South Africa

In South Africa, performance measures are expressed as a condition index, Ic, for each defect and in 

terms of BCI for each bridge. The BCI combines the individual defect indicesto provide an 

overall measure for the bridge. Figure 7 shows the formula used to calculate Ic.

Figure 7. Equation. South Africa’s Condition Index.

(5)

Where:

D = Degree of defect.

E = Extent of defect.

R = Relevancy of defect.

D, E, and R are each assigned on a scale of 0–4, with 0 indicating no defect or that the defect is 

of no significance to the structural condition and 4 indicating the worst case in terms of severity, 

extent, or impact. The authors of the FHWA report note: “Ic equals 100 when there is no defect, and 

equals 0 when D and E and R are all equal to 4. A defect is critical if the Ic is below 40.”

(5)

Figure 8 shows the formula for BCI.

Figure 8. Equation. South Africa’s BCI.

(5)

Where:

BCIn = BCI for structure n.

Ic = Sum of condition index values for all relevant defects in structure n.

ADTn = ADT for structure n.

ADTi = Sum of values of ADT for all structures in the prioritization process.

BCI gives a combined indicator of the importance of defects and the importance of the bridge. A 

high BCI value indicates a good bridge, and a low value indicates a poor bridge. The further 

scaling by traffic volume will tend to increase BCI for heavily traveled bridges. The BCI for 

each bridge is computed, and a linear model is used for the decrease of the BCI with time.

∑

∑

=

i

i

j

j n

n ADT

Ic ADT

BCI

( )
21

The following discussion of performance measures used in South Africa is representative of the 

findings in the international report and is excerpted directly:

“The index, Ic, is the dependent variable in the ... deterioration model. Straightline deterioration is proposed with the Ic declining at about 5 points per year. ...

Priorities for repairs are developed from two considerations. First is structural 

adequacy, as indicated by BCI values. Second is functional importance, an 

evaluation computed from road class, bridge load capacity, detour length, etc.

Generally, network-level optimization seeks the set of projects that offers the 

greatest reduction in defect relevancy, R, for a given budget.

Automated optimization yields a first list of repair projects. Next, projects for bridges 

are coordinated with projects for pavements in the same road section. Usually, a 

repair project at a bridge will attempt to remedy all relevant defects, not merely 

those with the highest priority values.”

(5)

Priorities for repairs in South Africa are determined by BCI and ADT.

Sweden

In Sweden, the preferred performance measure, lack of capital value (LCV), is defined as a fraction

of the bridge replacement cost. The following discussion of performance measures used in Sweden

is representative of the findings in the international report and is excerpted directly:

“Deterioration models consider structures in groupings determined by age and 

structural type. Deterioration is forecast as a continuing loss in capital value. The 

general form is [given by figure 9].

Figure 9. Equation. Sweden’s LCV.

(5)

[Where:]

LCV = Lack of capital value.

t = time.

ao, a1 , r = parameters of the model.

Parameters ao, a1, and r are specified by the user, or calibrated to historical trends 

in loss of capital value. This exponential model can represent both accelerating 

and decelerating change in capital value.”

(5)
22

The various formulae are used in different countries around the world for calculating bridge

performance measures for individual bridges and for inventories of bridges. The measures can be 

calculated to describe the performance of an individual bridge relative to a fixed numeric scale, often

0–100. In each formula, the purpose is to calculate the sum of several weighted factors that relate 

to the performance of the bridge. Factors that are commonly used include the following:

• Condition of critical bridge components.

• Criticality of the components in the bridge structural system.

• Essentiality of the bridge to the highway network it serves.

• Cost of the element.

Essentiality of the bridge is often represented by volume of traffic carried or type of traffic 

carried (e.g., emergency responders, school vehicles, commercial traffic, military traffic, etc.).

When the performance measure is calculated for a group of bridges, the distribution of the 

performance measure values describes the performance of the group as a whole. These measures 

can be used to establish the order of priority for corrective or improvement actions or programs.

Also, the bridge owner or agency can look at trends in bridge performance measures (rising or 

falling over time) and evaluate the effectiveness of bridge programs or the need to commit more 

resources to those programs. These formulae are very useful for their intended purposes.
23

CHAPTER 3. BRIDGE PERFORMANCE INDICATORS TO ADDRESS

SPECIFIC CONCERNS

Highway bridges are normally expected to provide acceptable service for extended periods of time. 

Thus, most existing highway bridges have to be maintained in service for extended periods of time 

in spite of deterioration due to aggressive environmental stressors, aging of materials, and traffic 

increases. The safety and capacity of these bridges are highly influenced by their deterioration. In 

order to avoid the consequences of loss of serviceability or failure, maintenance programs are 

carried out by the responsible authorities. To make these programs cost-efficient, bridge life-cycle 

performance must be accurately predicted.(6–8) However, difficulties arise in the prediction of 

life-cycle performance because of the complexity and high uncertainty of deterioration mechanisms

such as cracking, corrosion, and fatigue. Consequently, proper performance indicators are essential

to evaluating bridge performance in a quantitative manner.

Many studies have focused on quantifying bridge performance by using deterministic, semiprobabilistic, and probabilistic indicators such as safety factors, partial safety factors, and the 

reliability index. Modern bridge design codes take uncertainty into account by including specific 

factors (i.e., load and resistance factors) in the computation of structural resistance and load 

effects with Load and Resistance Factor Design (LRFD) methods. However, prediction of bridge 

performance with deterioration requires the simultaneous use of several performance indicators. 

For example, the reliability index may be an adequate measure for quantifying the safety of a 

bridge component or system for ultimate capacity, but the redundancy index is required to 

evaluate the availability of warning before collapse.

Moreover, for bridges with deterioration and local damage, it is essential to consider performance 

indicators related to damage tolerance, such as reserve strength factor, residual strength factor, 

and vulnerability, together with the indicators for ultimate capacity. To obtain a desired bridge 

safety level, the values of performance indicators under consideration should not drop below 

prescribed minimum threshold levels.

The life-cycle cost of bridges is another measure that decisionmakers have to balance with 

appropriate safety indicators. In recent years, life-cycle performance, safety, reliability, and risk 

of civil infrastructure systems have become emergent and key issues due to recurring natural and 

manmade disasters, the infrastructure crisis, sustainability issues, and global warming. Uncertainties

are unavoidable in dealing with these problems. (See references 6 and 9–11.) Management of aging

civil infrastructure involves significant expenditures. At a time of constrained public resources,

difficult decisions are required to establish priorities for maintenance, rehabilitation, and replacement.

Decisions regarding requirements for design, continued service, rehabilitation, or replacement 

should be based on multicriteria optimization under uncertainty, in order to balance conflicting 

requirements such as cost and performance. This can only be achieved through proper integrated 

risk management planning in a comprehensive life-cycle framework. Such a framework is shown 

in figure 10.
24

Figure 10. Chart. Integrated Life-Cycle Bridge Management Framework.

(12)

The purpose of this study is to review several performance indicators used to evaluate bridge 

performance. These indicators are briefly presented. In addition, a classification of bridge 

performance indicators is made depending on the approach (deterministic, semi-probabilistic 

(LRFD), or probabilistic) and level of concern (cross-section, component, or system level).

STRUCTURAL PERFORMANCE INDICATORS

Condition Rating (CR)

Condition ratings, CR, are used in the NBI to describe the existing, in-place bridge as compared to 

the as-built condition. Evaluation is for the materials, physical condition of the deck, superstructure,

and substructure components of a bridge. Condition rating codes are properly used when they 

provide an overall characterization of the general condition of the entire component being rated. The 

load-carrying capacity is used in evaluating condition items. The fact that a bridge was designed for

less than current legal loads and may be posted has no influence on condition ratings. The general

condition ratings shown in chapter 2 are used as a guide in evaluating deck, superstructure, and 

substructure. The range of values possible for CR is shown in figure 11.

Figure 11. Equation. Range of NBI Condition Ratings.(1)

Bridge Performance 

Assessment &

Prediction

Information from 

Bridge Monitoring & 

Uncertainty 

Modeling & Analysis

Improved Bridge 

Performance 

Assessment & 

Prediction by Updating 

Optimum Maintenance –

Monitoring – Management 

Strategies for Bridges Using 

Multi-Criteria Optimization 

APPLICATIONS

Existing and New 

Highway Bridges and 

Networks of Bridges

COMPUTATIONAL

TOOLS

 

Optimal Bridge 

Decision Making 

1 ≤ CR ≤ 9
25

Condition State (CS)

Based on visual inspection, AASHTOWare Bridge ManagementTM, the bridge management system

of the American Association of State Highway and Transportation Officials (AASHTO), assigns

condition states, CS, for bridge components. The condition states vary between 1 and 5, with each

increasing condition state indicating a higher damage level. The range of values possible for CS

is shown in figure 12.

Figure 12. Equation. Range of AASHTOWare Bridge ManagementTM Condition States.(13)

Margin of Safety (M)

The margin of safety, M, represents how much of the bridge cross-section, component, or 

overall bridge system capacity is held in reserve at a point in time. It can be expressed as 

shown in figure 13.

Figure 13. Equation. Margin of Safety.

(14)

Where:

R = Random variable representing the resistance effect.

Q = Random variable representing the load effect.

Time-Dependent Margin of Safety (M(t))

The time-dependent margin of safety, M(t), is shown in figure 14.

Figure 14. Equation. Time-Dependent Margin of Safety.

(14)

Where:

t = Time.

R = Time-dependent variable representing the resistance effect.

Q = Time-dependent variable representing the load effects.

1 ≤ CS ≤ 5

M = R − Q

M (t) = R(t)− Q(t)
26

Probability of Failure (Pf)

Making the assumption that R and Q are statistically independent random variables, the 

instantaneous probability of failure, Pf, is shown in figure 15.

Figure 15. Equation. Instantaneous Probability of Failure.

(15,16)

Where:

R = Random resistance in a certain failure mode.

Q = Random load effect in the same failure mode.

FR(x) = Cumulative distribution function of R.

fQ(x) = Probability density function of load effect Q.

In many cases, it is impossible to evaluate Pf by analytical methods. Therefore, numerical methods

such as the first-order reliability method, second-order reliability method, and Monte Carlo 

simulation are used.

Probability of Survival (Reliability) (Ps)

Failure and survival are complementary events. Therefore, the probability of survival, Ps, (also 

called reliability) is defined as shown in figure 16.

Figure 16. Equation. Probability of Survival.

(15,16)

Reliability Index ( )

The reliability of a bridge can be expressed in terms of either Pf or its corresponding reliability 

index, . For normal (Gaussian) distributed independent variables, can be calculated as

shown in figure 17.

Figure 17. Equation. Reliability Index.

(15,16)

Where:

E(R) = Mean value of the resistance effect.

E(Q) = Mean value of the load effect.

(R) = Standard deviation of the resistance effect.

(Q) = Standard deviation of the load effect.

For normally distributed independent variables, Pf and are related as shown in figure 18.

β

β β

σ

σ

β
27

Figure 18. Equation. Probability of Failure for Normally Distributed

Independent Variables.

(15,16)

Where:

( ) = Standard normal distribution function.

For the calibration of the Strength I limit state in AASHTO LRFD Bridge Design Specifications,

= 3.5 was used.

(14)

Life-Cycle Cost

One of the most important measures in the evaluation of bridge performance is life-cycle cost.

The proper allocation of resources can be achieved by minimizing the total expected cost while 

keeping structural safety at a desired level. The expected life-cycle cost can be expressed as

shown in figure 19.

Figure 19. Equation. Expected Life-Cycle Cost.

(6)

Where:

CET = Expected life-cycle cost.

CT = Initial design/construction cost.

CPM = Expected cost of routine maintenance.

CINS = Expected cost of performing inspections.

CREP = Expected cost of repairs.

CF = Expected cost of failure.

CF is the cost of removal and replacement of an individual member or the cost of demolition of 

the existing bridge and replacement, if necessary, with a new bridge. Within this framework, all 

future costs are converted to their net present value. In the case of structural health monitoring 

(SHM), the expected life-cycle cost is as shown in figure 20, with figure 21 defining the 

expected cost of monitoring, CMON. 

Figure 20. Equation. Expected Life-Cycle Cost with SHM.(17,18)

Figure 21. Equation. Expected Cost of Monitoring.

(17,18)

Where: 

MT = Expected initial design/construction cost of the monitoring system.

MOP = Expected operational cost of the monitoring system.

Φ

β

C ET

0 = C T0 + C PM0 + C INS0 + C REP0 + C F0 + CMON

CMON = MT + MOP + MINS + MREP
28

MINS = Expected inspection cost of the monitoring system.

MREP = Expected repair cost of the monitoring system.

Using this approach, the benefit of the monitoring system, BMON, can be determined through a 

comparison of the expected life-cycle total cost with and without monitoring, as shown in figure 22.

Figure 22. Equation. Benefit of the Monitoring System.

(17,18)

Using figure 22, monitoring is economically beneficial if BMON > 0. A monitoring benefit may be 

realized through better treatment of maintenance and repair activities as well as a lower level of 

risk over the life of the structure. Bridge managers can prevent or reduce adverse consequences 

by using monitoring data.

Safety Factor in Allowable Stress Design (SF)

Allowable Stress Design (ASD) is based on the concept that the maximum stress in a component 

should not exceed a certain allowable stress under normal service conditions. The limiting stress, 

which can be yield stress or stress at instability or fracture, is divided by a safety factor to provide

the allowable stress. The safety factor, SF, is used to provide a design margin over the theoretical 

design capacity and is defined as shown in figure 23.

Figure 23. Equation. Safety Factor in ASD.

(19)

Where:

u = Maximum usable stress, which can be the yield stress, buckling stress, or ultimate stress.

all = Allowable stress.

Partial Factors Used in LRFD ( , )

In LRFD, resistance R and load Q are considered statistically independent random variables. If R

is greater than Q, a margin of safety exists. On the other hand, since R and Q are random variables, 

there is a probability that R is smaller than Q. The typical inequality for safety checks in LRFD is 

shown in figure 24.

Figure 24. Equation. Inequality for Safety Check in LRFD.

(14)

Where:

= Resistance factor associated with nominal resistance Rn.

D, L = Partial load factors associated with the dead and live loads effects QDn and QLn.

In LRFD, resistance Rn is reduced by resistance factor , and loads are amplified or reduced by 

load factors.

BMON = CET − C ET

0

σ

σ

φ γ

φRn ≥ γDQDn + γLQLn + ...

φ

γ γ

φ
29

Load Modifier Factor Used in LRFD ( )

In AASHTO LRFD Bridge Design Specifications, an additional load modifier factor, , relating 

to ductility, redundancy, and operational importance is used, as shown in figure 25.

(14)

Figure 25. Equation. Load Modifier Factor in LRFD for Ductility, Redundancy, and 

Operational Importance.

(14)

In figure 25, , is defined by figure 26 for loads for which a maximum value of i is appropriate

and by figure 27 for loads for which a minimum value of i is appropriate.

Figure 26. Equation. Load Modifier Factor for Maximum Value of i.

(14)

Figure 27. Equation. Load Modifier Factor for Minimum Value of i.

(14)

Where:

η D = Factor relating to ductility.

η R = Factor relating to redundancy.

η I = Factor relating to operational importance.

Collapse Load Multiplier ( )

In the plastic analysis of structures, collapse load multiplier, , is a theoretical factor by which a set 

of loads acting on the structure must be multiplied just enough to cause the structure to collapse. The 

load can be taken as the service load conditions, and the strength of the structure can be determined

from idealized plastic material strength properties. Three main loading histories are considered.

Proportional loading implies that the applied load can be defined at all stages by a single 

parameter, , which amplifies the service load, Q = QD + QL, so that the ultimate load, QU,

is as shown in figure 28.

Figure 28. Equation. Collapse Load Multiplier for Proportional Loading.

(20)

This extension of ASD practice is used in the plastic design of steel structures but is an unrealistic

concept because dead loads are not subject to the same variations as live loads.

Combined loading assumes that the dead load is fixed and the live load only is variable, as 

shown in figure 29.

Figure 29. Equation. Collapse Load Multiplier for Combined Loading.

(20)

ηi

ηi

ηi γ

γ

ηi = ηDηRηI ≥ 0.95

γ

ηi = 1

ηDηRηI

≤ 1.0

γ

λ

λ

λ
30

Arbitrary loading assumes that the dead and live loads vary independently in both magnitude and 

time. The dead load first reaches its full factored value, DQD, before the live load is applied 

from zero to its full value, LQL, as shown in figure 30.

Figure 30. Equation. Collapse Load Multiplier for Arbitrary Loading.

(20)

The inequality RU ≥ QU has to be satisfied at the limit, where RU is the plastic resistance of the 

structure.

Return Period ( )

The loads due to natural phenomena such as earthquakes, storms, and high winds have randomness

not only in space but also in time. The randomness in time can be considered in terms of return

period, . Return period is an average duration between consecutive occurrences of an event. It 

should be noted that the actual time between the occurrences is T, which is a random variable, 

and is only average duration. can be expressed as shown in figure 31.

Figure 31. Equation. Return Period for Loads Due to Natural Phenomena.

(21)

Where:

p = Probability of occurrence of the event.

q = Corresponding probability of nonoccurrence (therefore, q = 1 – p).

The infinite series inside the parentheses yields 1/p

2

. Therefore, the average duration between 

consecutive occurrences of an event is as shown in figure 32.

Figure 32. Equation. Average Duration Between Consecutive Occurrences of an Event.

(21)

Existing bridge design codes use different return periods for different hazards. For example, the 

calibration of the live load factors in AASHTO LRFD Bridge Design Specifications is based on 

the 75-year maximum load effect, while a 1,000-year return period has been proposed for 

seismic hazards, and 100- and 500-year flood levels are used for scour.(14)

Cumulative Time Probability of Failure (F(t))

The probability of failure within a certain period of time is called the cumulative time probability 

of failure, F(t). There are two approaches for computing cumulative probability of failure.

In the first approach, F(t) is computed considering only one random variable, the time Tf at 

which the component or system fails. Probability concepts are applied to compute F(t). In this 

approach, F(t) up to time tf can be calculated as shown in figure 33.

λ

λ

QU = λD QD + λL QL

T

T

T T

T� = E(T) = p(1 + 2q + 3q2 + ...)

p

T 1 =
31

Figure 33. Equation. Cumulative Time Probability of Failure, One Random Variable.

(22)

Where:

F(tf) = Area under the probability density function f(u) of the time to failure from t0 to tf.

In the second approach, F(t) is computed considering changes in both time-variant resistance and 

load. The cumulative time probability of failure of a component whose resistance is deteriorating 

subjected to time-variant load is shown in figure 34.

Figure 34. Equation. Cumulative Time Probability of Failure, Time-Variant Resistance 

and Load.

(22)

Where:

= Mean occurrence rate of stochastic load event in a Poisson process.

Fs( ) = Cumulative time distribution function used to define the load intensity.

fRo(r) = Probability density function of the initial resistance R0.

g(t) = Mean value of G(t).

G(t) = Resistance degradation function.

Enright and Frangopol extended the formulation in figure 34 and determined F(t) of weakest-link 

and fail-safe systems with applications to bridges.(23,24)

Cumulative Time Probability of Survival (S(t))

Cumulative time probability of survival, S(t), also called survival function, is the probability that 

a component or system survives until time t. It is equal to the reliability function, which is the 

probability that a component or system is still functioning at time t. S(t) is the complement of the 

F(t) and can be expressed as shown in figure 35.

Figure 35. Equation. Cumulative Time Probability of Survival.

(22)

Where:

S(t) = Area under the probability density function f(u) of the time to failure of tf to infinity.

∫ = ≤ =

f t

F t f P Tf t f f u du

0

( ) ( ) ( )

F {r g } f r dr

t

F t t R

t

s

L

( ) ( ) 1 ( ) 1 exp 1 0

0 0

∫ ∫

∞































 = − − λ − ⋅ ξ

λ
32

Reserve Strength Factor (R1)

Reserve strength factor, R1, is defined as the ratio of the load-carrying capacity of the intact structure 

(or component), C, to the applied load on the structure (or component), Q, as shown in figure 36.

Figure 36. Equation. Reserve Strength Factor. (See references 25–29.)

R1 varies from a value of infinity, when the intact structure (or component) has no load, to a 

value of 1.0, when the nominal load on the intact structure (or component) equals its capacity.

Residual Strength Factor (R2)

The residual strength factor, R2, provides a measure for the strength of the system in a damaged 

condition compared to the intact system. It is defined as the ratio of the capacity of the damaged 

structure (or component), Cd, to the capacity of the intact structure (or component), C, and can be 

expressed as shown in figure 37.

Figure 37. Equation. Residual Strength Factor. (See references 25–29.)

R2 takes values between 0, when the damaged structure has zero capacity, and 1.0, when the 

damaged structure does not have any reduction in load-carrying capacity.

Redundancy Factor (R0)

Redundancy factor, R0, is defined as shown in figure 38.

Figure 38. Equation. Redundancy Factor. (See references 25–29.)

R0 varies between 1.0, when the damaged structure has zero capacity, and 0, when the damaged 

structure does not have any reduction in load-carrying capacity.

Damage Factor (D)

Damage factor, D, is used to represent the loss in cross-sectional area of a bridge component. It 

is defined as shown in figure 39.

Figure 39. Equation. Damage Factor.

(19,20)

Where:

ad = Cross-sectional area of the damaged portion of the bridge component.

a = Intact cross-sectional area of the bridge component.
33

Redundancy Index (RI)

Redundancy, which is a measure of reserve capacity, can be defined as the availability of warning 

before structural collapse occurs. The failure of a single member will not cause failure of a redundant

structure. There are several measures for probabilistic redundancy index, RI, including those 

shown in figure 40 through figure 42.

Figure 40. Equation. Probabilistic Redundancy Index 1.

(25,30,31)

Figure 41. Equation. Probabilistic Redundancy Index 2. (25,30,31)

Figure 42. Equation. Probabilistic Redundancy Index 3.

(25,30,31)

Where:

intact = RI of the intact system.

damaged = RI of the damaged system. 

Pf(dmg) = Probability of damage occurrence to the system.

Pf(sys) = Probability of system failure.

To account for member ductility, system redundancy, and operation importance, AASHTO 

LRFD Bridge Design Specifications applies a load modifier factor relating to ductility ( ), 

redundancy ( ), and operational importance ( ) (see figure 27).

(14)

Time-Variant Redundancy Index (RI(t))

Frangopol and Okasha investigated several time-variant redundancy indices, RI(t), based on 

point-in-time and Pf. It was shown that the redundancy indices shown in figure 43 and

figure 44 are most consistent.

(32,33)

Figure 43. Equation. Time-Variant Redundancy Index 1.

(32,33)

Figure 44. Equation. Time-Variant Redundancy Index 2.(32,33)

Where:

Py(sys)(t) = System probability of first yield at time t.

Pf(sys)(t) = Probability of system failure at time t.

βy(sys)(t), βf(sys)(t) = Reliability indices with respect to first yield and system failure at time t.

β

β

ηi η D

η R η I

β
34

An increase in the value of RI indicates a higher system redundancy. A structural system is 

considered non-redundant if RI = 0. 

Vulnerability (V)

Vulnerability, V, is one of the key measures used to capture the essential feature of damage-tolerant 

structures. A probabilistic measure of V can be defined as the ratio of the failure probability of 

the damaged system to the failure probability of the undamaged system, as shown in figure 45.

Figure 45. Equation. Vulnerability.

(34)

Where:

rd = A particular damaged state.

r0 = An undamaged system state.

Q = Prospective loading.

P(rd, Q) = Probability of failure of the system in the damaged state.

P(r0, Q) = Probability of failure of the system in the pristine state.

V refers to vulnerability of the system in state rd for prospective loading Q. The value of V is 1.0 

if the probabilities of failure of the damaged and intact systems are the same. 

Damage Tolerance (Dt)

Damage tolerance, Dt, can be defined as the reciprocal of V, as shown in figure 46.

Figure 46. Equation. Damage Tolerance.

(34)

Ductility ( )

Ductility, , is generally defined as the ability of a bridge component or the entire bridge to sustain 

large deformations without collapse. A ductility index could be defined as shown in figure 47.

Figure 47. Equation. Ductility.

(34)

Where:

c = Deformation at collapse.

el = Deformation associated with the limit of elastic range.

Δ

Δ

Δ

Δ
35

Robustness (RO)

Robustness, RO, is one of the key measures in the field of progressive collapse and damage-tolerant 

structures. Although robustness is recognized as a desirable property in structures and systems, there

is not a widely accepted theory on robust structures.(35)

In general, RO is defined as insensitivity of

the safety of a structure to local failure or the ability of a structure to prevent failure progression. 

Resilience (RE)

Resilient structures respond well to extreme events. They reduce the probabilities of failure, 

the consequences of failure, and the time for recovery. Resilience, RE, can be measured by the 

functionality of an infrastructure system after a disaster and by the time it takes for a system to 

return to predisaster levels of performance.(36) Despite several RE measures proposed in the 

literature, a standard measure for bridge resilience has yet to be specified.

Risk ( )

Risk, , may be expressed as a function of the probability of occurrence of adverse event A, P(A), 

and the consequence of this event, K (typically expressed in monetary terms). Often, is defined 

as the product of P(A) and K, as shown in figure 48.

Figure 48. Equation. Risk.

(34)

The uncertainties in both P(A) and K will carry over in calculating .

Minimizing risk is one of the main objectives of bridge management. This can be achieved by 

minimizing the probability of occurrence of the adverse event (e.g., probability of bridge collapse),

minimizing the consequences associated with this event, or minimizing both. Low-probability,

high-consequence events are of particular relevance in risk-informed decisionmaking and 

management of aging bridges.

CLASSIFICATION OF STRUCTURAL PERFORMANCE INDICATORS

A classification of the defined structural performance indicators depending on the approach

(deterministic, semi-probabilistic (LRFD), or probabilistic) and level of concern (cross section, 

component, or system level) is presented in table 6. More than one checkmark in the same category 

indicates that the performance measure can be classified in each section depending on the situation.

Risk-informed assessment and management of the highway bridge infrastructure in the United 

States requires a set of reliability-based performance indicators and decision tools. Consideration 

of multiple performance indicators in the evaluation of structural performance is inevitable. The 

indicators that should be considered depend on the priorities and objectives of the decisionmakers.

The main remaining challenge lies in the implementation of reliability-based performance indicators

that account for the presence of both natural randomness (i.e., aleatory uncertainty representing the 

natural variability or randomness of nature) and imperfect knowledge (i.e., epistemic uncertainty 

representing our imperfect ability to model reality) in bridge engineering. The indicators for 

evaluating bridge performance are not limited to those mentioned in this study.

R

R

R

R
36

Table 6. Classification of Structural Performance Indicators.

Performance Indicator Notation

Approach Level

Deterministic

Semi-Probabilistic

(LRFD) Probabilistic

Section

Level

Component

Level

System

Level

Condition rating CR  

Condition state CS  

Margin of safety M    

Time-dependent margin of safety M(t)    

Probability of failure Pf    

Probability of survival Ps    

Reliability index    

Life-cycle cost LCC  

Safety factor in ASD SF   

Partial load factors in LRFD ,   

Load modifier factor in LRFD   

Collapse load multiplier  

Return period     

Cumulative time probability of failure F(t)   

Cumulative time probability of survival S(t)   

Hazard rate h(t)   

Cumulative hazard rate H(t)   

Reserve strength factor R1   

Residual strength factor R2   

Redundancy factor R0  

Damage factor D  

Redundancy index RI  

Time-variant redundancy index RI(t)  

Vulnerability V  

Damage tolerance Dt  

Ductility   

Robustness RO  

Resilience RE  

Risk  

Checkmark indicates performance indicator meets classification; blank cells indicate performance indicator does not meet classification.

β

φ γ

ηi

λ

T

Δ

R
37

CHAPTER 4. IMPROVING BRIDGE PERFORMANCE

KEYS TO IMPROVING BRIDGE PERFORMANCE

Bridges are a critical part of the transportation system. The bridge infrastructure is a vast and 

valuable asset that must be properly managed in the interests of efficiency, safety, economy, national

security, and protection of local and global environments. The need for useful, reliable bridge 

performance measures is clear. Additionally, there is a need for methods to evaluate the impact of 

different scenarios of funding, maintenance practices and priorities, design methodologies, and new

technologies on future bridge performance. The performance measures described in chapter 2 are 

consistently applied and well-tested in practice. However, they do not lend themselves to predictive

efforts nor to analysis of various “What if ... ?” scenarios. The LTBP Program will concentrate 

on collecting information and data that will allow exploration of scenarios that have actually 

happened. This will lead to tools such as better deterioration models, allowing better predictions 

of bridge performance.

The performance indices described in this report generally attempt to address the bridge as a whole 

entity and aggregate values among a population of bridges. However, bridges are composed of 

several unique elements that work as a system. Each of these elements responds to a different set 

of factors that govern its performance. Even when the same factor affects the performance of more 

than one element, the manner and degree to which that factor impacts each element may vary

considerably. Many aspects of bridge performance are not well understood, and current indices 

of bridge performance are usually based on objectives that are imprecise and data that are not 

consistent or well documented. Many attempts at assessment of performance (of the complete 

structure or key elements) rely on expert opinion and significant assumptions and generalizations. 

Yet, decisions at many different levels and for many important purposes are based on these 

performance assessments.

The keys to improving bridge performance measures are as follows:

• Establishing clear, objective measures that are relevant to different levels of decisionmaking.

• Identifying the elements and characteristics of a bridge that most seriously impact the bridge 

in the four performance categories: condition and durability, functionality, structural integrity

and safety, and cost. This exercise should consider both short-term issues and the long-term

potential for improved performance through innovative materials, enhanced inspection 

technology, improved design concepts, and evolving construction and maintenance methods.

• Identifying critically needed data for experimental studies that will improve the knowledge

of the multivariable cause-and-effect relationships that govern performance degradation.

• Collecting data to fill gaps and create valid models that describe deterioration mechanisms, 

predict future deterioration, and support more realistic life-cycle cost calculations. Such 

information can then be used to further calculate operational efficiency and safety versus 

various levels of condition and capacity, as well as the probability of structural system 

failure at both the service and ultimate-limit states.
38

• Improving the relevance and quality of the data collected and used to support analyses 

and calculate performance indicators.

• Developing tools and systems for calculating and disseminating results about 

performance indicators.

BETTER DATA ON BRIDGE PERFORMANCE IN THE UNITED STATES

The primary sources of data on bridges are the NBI and bridge management databases used by many 

States. Many transportation departments also have databases for recording bridge maintenance 

actions and for management and planning purposes. The NBI was created to fill the knowledge 

gap in bridge inventory and condition information but not to support the assessment of bridge 

performance over time. Various parties have been able to use the NBI to produce results and 

products that have implications for the assessment of bridge performance. When using NBI data 

to assess bridge performance, the following characteristics must be considered: 

• The NBI contains condition ratings for the major structural elements of the bridge—deck, 

superstructure, and substructure—plus channel, channel protection, and culverts. The NBI

does not contain data on the condition of the myriad individual subelements of a bridge 

such as beams, pier columns, and abutments. 

• The NBI contains appraisal ratings for a few key features of the bridge, most notably 

structural evaluation, deck geometry, and scour criticality.

• The NBI does not contain quantitative measurements of differing conditions or the locations 

of differing conditions with respect to the geometry of the element being inspected. 

• In most cases, the condition ratings are assigned based solely on visual inspections. 

Underlying causes of damage, such as rebar corrosion, are not identified until surface 

damage appears. NBI ratings do not reflect incipient degradation. 

• The full range of codes (from 9 for excellent condition to 0 for failed condition) consists 

of discrete integers corresponding to the guiding language. This type of data is not readily 

amenable to rigorous mathematical analysis with the purpose of charting continuous change

or for predicting future changes.

The most common bridge management system in the United States is the AASHTOWareTM Bridge 

Management software. The developers of this system incorporated a detailed condition assessment

approach. An element-level inspection system was developed to track both the severity and the 

extent of different problems.

AASHTOWareTM Bridge Management addresses deterioration as a probabilistic, rather than 

deterministic, process and is able to automatically update previous deterioration predictions as 

more cycles of historical inspection data are input. The initial probabilities of transition from one 

condition state to the next were determined from consensus of expert opinion. These can be 

modified by the licensing agency if desired.
39

Under the element-level inspection system, condition data are recorded on the individual elements

of the bridge rather than on the general elements of deck, superstructure, and substructure. This 

expands the data collected while allowing the use of specific guidance and employing precise 

engineering language for inspectors to rate the elements. Thus, the severity of any deterioration 

is defined, and the extent is estimated and recorded. While the element-level data system provides

more granular information than the NBI condition ratings, it is still based mostly on visual inspection

of surface conditions and relies on inspector training and experience for data quality. It does not, 

for the most part, document latent defects, such as initial corrosion of reinforcing bars that could 

soon change the observed condition at the surface level.

The NBI and element-level databases can be used as a fundamental resource in evaluating bridge 

performance. The past, current, and future data contained in these two resources are helpful for 

the following:

• Identifying trends in bridge performance.

• Identifying general parameters that govern performance.

• Identifying representative bridges and service conditions that can provide a real-life 

laboratory for studying performance issues.

Bridge owners may also possess other useful data, such as the following:

• Design drawings and specifications.

• Analytical models.

• Construction records.

• Inspection reports.

• Photographic documentation.

• History of maintenance actions and timing.

• Financial records of maintenance costs.

Beyond these current resources, the data needed to properly evaluate the important aspects of bridge 

performance can be quite extensive. Table 7 and table 8 show the breadth of data that may be 

necessary to better understand bridge performance in the four main categories.
40

Table 7. Durability and Serviceability Performance Data.

Category Data

Design and construction

Design plans and specifications

Critical design details

Change orders

Inspection notes

Construction quality assurance and quality control

Corrosion protection measures

Operating conditions

Local climate

Snow and ice removal practices

Freeze-thaw cycles

Rainfall and runoff; drainage control

Marine environment

Industrial pollutants

Dynamic loadings

Traffic volume

Truck volumes and weights

Weigh-in-motion data

Overload permits

Debris, ice

Impact loads

Flexibility, vibrations

Corrosion protection measures

Concrete cover over reinforcement

Corrosion resistant reinforcement 

Deck overlays, membranes, and sealers

Other concrete sealers

Steel coatings—high-performance or weathering steel

Concrete qualities—high-performance concrete

Material conditions

Concrete

Steel 

Reinforcing bars

Prestressing steel

Deck

Concrete superstructure

Steel superstructure

Concrete substructure

Geometric data

Deflections

Rotations

Settlements

Loss of camber

Horizontal alignment and skew

Components

Bearings

Joints

Approach slabs

Details requiring inspection by non-destructive evaluation
41

Table 8. Functionality, Cost, Structural Integrity, and Organizational Data.

Categories Data

Functionality:

User safety and

service

Operational efficiency

Traffic volumes

Congestion and delay times

Safety hazards

Accident rates and types

Network-level performance

Route redundancy

Detour lengths and costs

Other bridges in the corridor

Intersection/interconnection

Military route

Multimodal interconnections

Accommodation of other infrastructure

Societal/environmental impacts Fuel usage

Environmental issues

Air quality

Water quality

Toxic wastes

Costs: 

Agency and user

Original construction Design costs

Construction costs

Life-cycle costs

Inspection and condition assessment

Preservation

Maintenance, repairs

Rehabilitation

Demolition, removal, and disposal

Work zone maintenance of traffic

Structural integrity: 

Safety and stability 

Safety and stability

Global 

Member

Redistribution

Resilience

Structural redundancy

Extreme events

Foundation type

Accident risks—fire, impact

Soil and hydraulic conditions

Scour vulnerability

Scour mitigation measures

Seismicity

Seismic design considerations

Hazard return periods

Organizational issues

Asset management policies

Revenue sources

Distribution decision authority

Organizational structure and culture

Knowledge management

Human resources 

Quality of education

Incentives for growth
42

The steps to obtaining better data for performance assessments are as follows:

1. Isolate specific aspects of bridge performance that have the potential to significantly increase the 

costs associated with bridges (these costs may be in terms of dollars for bridge maintenance and

rehabilitation; damage to the environment; property damage, injuries, or fatalities in bridgerelated accidents; or delays associated with congestion at narrow bridges or bridges under repair).

2. Establish working hypotheses as to the cause of poor performance.

3. Identify the parameters that have the most impact on performance.

4. Identify the critical data needed to prove or disprove the hypotheses.

5. Identify the data collection methodologies that best balance effectiveness and data quality 

with the costs of data collection. The focus should be on obtaining the best available data 

rather than on trying to obtain perfect data.

This process will support the ability to design, implement, and complete statistically sound 

experimental studies to prove or disprove the hypotheses. The result will be better understanding 

of bridge performance and the knowledge necessary to implement policies, programs, and specific

actions that will result in improved performance.

An example of how this process would work for the issue of performance of FO bridges is 

described in the following section.

Example: Performance of FO Bridges

Objective

The objective of the study is to examine the performance of bridges classified as FO and evaluate the 

frequency and severity of negative impacts (e.g., accidents, vehicle-bridge collisions, and instances

where the bridge route does not function adequately) as a result of alignment disparities.

What Effect Does Inadequate Roadway Alignment Have on Road Safety and Traffic Flow?

Hypotheses: The following hypotheses are developed concerning inadequate roadway alignment: 

• A moderate to severe misalignment of the approach roadway and the bridge roadway 

may cause momentary reductions in speed and erratic movements by drivers.

• These actions may contribute to accidents close to or on the bridge. They may also 

contribute to impaired traffic flow.
43

Data: Data requirements for this study are as follows: 

• Geometry of approach roadway and bridge roadway:

o Number of traffic lanes.

o Lane widths.

o Shoulder widths.

o Approach roadway alignment.

• Functional class of highway.

• Auto and truck traffic volumes.

• One-way or two-way traffic.

• Traffic control features at and near the bridge.

• Posted speed and typical traffic speeds.

• Current and past accident data at or on the bridge:

o Type.

o Severity.

o Documented causes.

• Ambient conditions such as light and precipitation.

The effort to analyze and better understand various aspects of bridge performance should not be 

confused with the need to continue collecting required NBI data and the element-level data now 

collected to support bridge management systems. No recommendations are being made to expand

the volume or enhance the quality of the data currently collected for these purposes.

BETTER UNDERSTANDING OF CAUSE AND EFFECT

Bridge performance measures should be able to provide a link between a specific parameter (or 

set of parameters) and the level of some desirable quality or characteristic of bridges or bridge 

elements. For example, a traffic safety measure should provide a link between accident experience

and geometric characteristics such as bridge width. However, the performance of any single bridge

element is dependent on complex interactions of multiple and often interrelated factors, including

the original design parameters and specifications (bridge type, materials, geometries, and load 

capacities); the initial quality of materials and of the as-built construction; varying environmental 

conditions of climate and air quality; corrosion and other deterioration processes; traffic volumes 

and percentage of truck traffic; and the type, timing, and effectiveness of preventive maintenance,

minor and major rehabilitation actions, and ultimately, replacement actions. Realistically, it is 

usually impossible to isolate one specific parameter as the governing parameter for a specific 

quality. Even in the simple example of accident history, several different factors are linked to 
44

safety, including bridge and roadway geometry, traffic volumes and vehicle types, travel speeds, 

weather conditions and winter maintenance operations, night visibility, and pavement and deck 

riding surface condition.

Analysis of the 2011 NBI data shows that the primary cause for a bridge to be flagged as SD or FO

is related to deck geometry—a bridge is FO because the roadway width is considered too narrow 

for the traffic volumes currently using the bridge.(2) Figure 49 provides the top 10 reasons why a 

bridge is rated as deficient.

Figure 49. Graph. Reasons for Bridge Rating of SD or FO.(2)

Calculation of Federal SR for a given bridge, particularly the part of SR dependent on functional 

characteristics, is based on somewhat arbitrary definitions and significant assumptions. For bridges 

whose geometry does not meet currently accepted standards, many of the criteria used to calculate 

SR are not well documented and may not be well understood by bridge engineers. Traffic safety 

in the vicinity of bridges is an important parameter of bridge performance, yet there are no proven 

relationships that relate safety to bridge characteristics such as clear deck width, clearances, or 

approach roadway alignment. The Recording and Coding Guide for the Structure Inventory and 

Appraisal of the Nation’s Bridges presents a table for evaluating deck geometry that considers 

traffic volumes, lane widths, direction of traffic, and type of highway system.(1) No apparent 

research supports these numbers, and the method ignores possibly causative or complicating 

factors such as climatic conditions, percent of trucks in the traffic stream, approach roadway 

alignment, and posted speed.

Therefore, a study to examine the cause-and-effect relationships between bridge and traffic 

parameters and accident history near and on bridges would be useful. The data in the NBI and 

other available databases can be mined to create a subset of bridges that reflects a range of the 

key variables, including traffic volumes, truck traffic, deck widths, and perhaps other causative 

factors such as climatic conditions, approach roadway alignment, and posted speed.
45

The FHWA Bridge Management Information Systems Laboratory was established to identify and 

analyze causes and trends of deficiencies within the Nation’s bridge inventory. The laboratory has 

developed or acquired the tools to support sophisticated analytical research on existing disparate data 

sources through a geographical information system platform combined with relational database 

management systems software and advanced mathematical and statistical software. Under a 

program such as LTBP, data about type and frequency of accidents can be monitored, and 

analysis of long-term accident experience can be used to correlate accident potential with the 

most relevant bridge parameters. Ultimately, the findings could be used to better understand the 

bridge deficiencies that most affect functional characteristics of bridges.

The preceding discussion is one example of an aspect of bridge performance that could be improved

by a better understanding of cause-and-effect relationships supported by accurate, reliable data. This 

principle of establishing and proving cause-and-effect relationships using high-quality research 

data is one of the major goals of the LTBP Program. With more relevant and reliable data and 

improved understanding of key cause-and-effect relationships, the knowledge necessary to 

improve bridge performance can be obtained.

CRITICAL ASPECTS OF BRIDGE PERFORMANCE

As previously noted, it is possible to characterize bridge performance issues under four broad 

categories: structural condition, functionality, structural integrity, and costs to the user and the 

agency. Within each of these categories are specific issues that may be considered higher 

priorities than others, including consideration of one or more of the following: 

• Cost to the owner agency in terms of inspection, engineering, maintenance rehabilitation, 

preservation, and replacement.

• Risk associated with failure of the bridge or a critical element.

• Property damage, injuries, and fatalities associated with accidents.

• Delay time and detour costs for commuters, commercial shippers, and tourists due to 

restricted conditions near or on a bridge.

• Excess fuel consumption and emissions due to inefficient or extended driving times.

Because owner agency resources are often severely limited, it is necessary to examine each issue of

bridge performance and weigh the costs of poor performance against the costs of actions necessary 

to improve performance. This assumes that the causes of poor performance have been determined

and solutions are available.

Under the LTBP Program, research has been done on evaluating the highest priorities in bridge 

performance. A consensus has emerged based on expert opinion from owner agencies and other 

bridge experts. The future results of the LTBP Program will provide knowledge to assist owners 

in properly making necessary analyses. High-priority performance issues will be outlined in a 

forthcoming program report, which will identify specific research to be undertaken in terms of 

objectives, key questions, working hypotheses, and critical data needed.

47

CONCLUSIONS

One simple definition of performance is that performance equates to accomplishment of a specified

purpose or set of purposes. For the purposes of the LTBP Program, the following definition is 

used: Bridge performance encompasses how bridges function and behave under the complex and 

interrelated factors they are subjected to day in and day out—traffic volumes, loads, deicing 

chemicals, freeze-thaw cycles, rains, or high winds. Bridge design, construction, materials, age, 

and maintenance history also play roles in performance. Virtually everyone in the United States, 

from bridge maintenance engineers to the everyday road user, has a stake in ensuring that the 

performance of bridges is good or excellent in terms of durability, operational capacity, roadway 

safety, resistance against failure, environmental neutrality, and life-cycle costs. Each group needs to

have confidence in their understanding of the indicators by which they measure bridge performance.

For the everyday commuter or casual user, an indicator such as Federal SR may suffice. For 

commercial interests, shippers, and drivers, a simple measure of bridges with posted weight limits 

or geometrical dimensions may suffice. These groups also need assurance that satisfactory bridge 

performance is being provided at reasonable costs, as reflected in gasoline taxes, tolls, other 

roadway fees, and other revenue sources devoted to maintaining performance.

Members of the bridge community such as designers, construction engineers, inspectors, 

maintenance engineers, and bridge management personnel who are responsible for maintaining 

performance must be able to properly and effectively evaluate bridge performance in more precise 

and targeted manners. They must break down bridge performance into very specific issues that can

be adequately evaluated in terms of cause and effect. This will allow them to identify actions or 

programs that will ensure a high level of performance at a reasonable cost. This report describes a

breakdown of bridge performance issues into four categories of performance: structural condition

(for durability and serviceability), functionality (safety and traffic capacity), structural integrity (for 

safety and stability), and risk and costs to the user and to the agency. This breakdown helps isolate 

the most critical aspects of bridge performance and provides the basis for long-term research 

studies that will improve understanding of these issues.

Making a proper evaluation of bridge performance can be a formidable task given the many 

factors that can govern performance under different circumstances. The LTBP Program is being 

implemented to identify the most critical aspects of bridge performance and conduct studies that 

will result in the high-quality data necessary to better understand how multiple, variable factors 

govern those aspects of performance. This effort should ultimately lead to the ability to implement

policies and actions for bridge programs that will improve performance and extend the life of 

bridges at minimum cost.

49

APPENDIX. DETAILS OF THE HIGHWAY BRIDGE INFRASTRUCTURE

Each bridge in the 2011 NBI is described by an extensive set of characteristics, parameters, and 

operating conditions, all of which have some impact on some aspect of the performance of the 

bridge. Table 9 provides a list of the most important of these items.

Table 9. Diversity of Bridge Characteristics, Parameters, and Operating Conditions.

(1)

Item NBI Item Numbers

Kind of material, main span and/or approach span 43A, 43A

Structure type, main span and/or approach span 43B, 44B

Horizontal geometry and skew 47, 51, 52, 55A, 55B, 56

Vertical clearances over and under the bridge 53A, 54A, 54B

Design load 31

Bridge posting 70

Deck structure type 107

Wearing surface 108A

Membrane 108B

Protective system 108C

Type of joints and bearings Data not available in NBI

Type of foundation Data not available in NBI

Local environment Data not available in NBI

Local climate patterns Data not available in NBI

Maintenance, repair, and rehabilitation history Data not available in NBI

Permit loads history Data not available in NBI

Annual ADT and truck traffic 29, 109

Safety features 33, 36

Maintenance responsibility, owner 21, 22

Functional class of inventory route 26

Channel and channel protection 61

Critical feature inspection 92A, 92B, 92C

Scour critical 113

In addition, the age of the bridge is an important contributing factor to the current and future 

performance of the bridge. However, the simple age in years does not represent a precise measure

of the impact of age on performance. The chronological age does not accurately reveal important 

knowledge about cumulative degradation of material properties, cumulative amount of damage 

from live loads, and past maintenance and repair history. The average age of all NHS bridges in 

the NBI is 36.3 years; the average age of all non-NHS bridges is 42.3 years; and the average age 

of all bridges is 41.0 years. Figure 1 in chapter 1 shows the diversity in age of bridges with a 

histogram of bridges still in service that were built within 5-year periods.
50

Other critical factors affecting bridge performance are the type, frequency, and effectiveness of 

preservation, maintenance, repair, and rehabilitation actions performed on bridges by the owner 

or entity charged with maintenance responsibility. Bridges on public highways are owned by a 

variety of agency types at different levels of government and by railroads, toll authorities, and 

other private entities. Table 2 in chapter 1 shows the number of different types of entities that 

have maintenance responsibilities for bridges on public highways.

Based on the 2011 NBI data, the bridge infrastructure in the United States can be further 

described by table 10, table 11, and figure 50.

Table 10. Bridges by Functional Classification Weighted by Number, ADT, and Deck Area.(2)

Functional Class Number Percent Deck Area (ft2

) Percent

Rural, interstate 20,434 4.32 261,976,842 7.35

Rural, other arterial 51,304 10.84 540,109,441 15.16

Rural, collector 104,701 22.13 446,633,350 12.53

Rural, local 173,573 36.68 339,994,461 9.54

Subtotal, rural 350,012 73.97 1,588,714,083 44.58

Urban, interstate 26,774 5.66 697,385,694 19.57

Urban, other arterial 59,782 12.63 1,031,374,442 28.94

Urban, collector 14,812 3.13 117,799,536 3.31

Urban, local 21,785 4.60 128,570,034 3.61

Subtotal, urban 123,153 26.03 1,975,129,705 55.42

Total, rural and urban 473,165 100.00 3,563,843,788 100.00

Note: Table does not include culverts and tunnels.
51

Table 11. Numbers and Percentages of Bridges and Deck Area by Owner.

(2)

Bridge Owner

Number

of 

Bridges

Percent

of All 

Bridges

Deck Area 

(ft2)

Percent

of All 

Deck Area

State highway agency 214,058 45.23 2,589,978,541 72.66

State park, forest, or reservation agency 884 0.19 1,944,059 0.05

Other State agencies 1,080 0.23 10,281,397 0.29

State toll authority 6,861 1.45 127,080,287 3.57

Total, State Bridges 222,883 47.09 2,729,284,284 76.57

Other Federal agencies (not listed below) 52 0.01 1,308,741 0.04

Indian tribal government 1 0.00 312 0.00

Bureau of Indian Affairs 704 0.15 2,291,701 0.06

Bureau of Fish and Wildlife 278 0.06 371,064 0.01

U.S. Forest Service 3,579 0.76 4,647,426 0.13

National Park Service 1,150 0.24 6,227,557 0.17

Tennessee Valley Authority 35 0.01 1,072,268 0.03

Bureau of Land Management 1 0.00 1,518 0.00

Bureau of Reclamation 321 0.07 797,735 0.02

Corps of engineers (Civil) 441 0.09 5,438,014 0.15

Corps of engineers (Military) 17 0.00 659,440 0.02

Air Force 24 0.01 21,765 0.00

Navy/Marines 151 0.03 1,260,518 0.04

Army 556 0.12 2,149,574 0.06

National Aeronautics and Space 

Administration 0 0.00 0 0.00

Metropolitan Washington Airports Service 23 0.00 268,839 0.01

Total, Federal bridges 7,333 1.55 26,516,484 0.74

County highway agency 187,902 39.70 464,876,596 13.04

Town or township highway agency 23,563 4.98 41,438,795 1.16

City or municipal highway agency 27,998 5.92 235,181,884 6.60

Local park, forest, or reservation agency 64 0.01 139,285 0.00

Other local agencies 1,162 0.25 15,556,768 0.44

Local toll authority 582 0.12 37,121,035 1.04

Total, local bridges 241,271 50.98 794,314,352 22.28

Private (other than railroad) 433 0.09 6,549,226 0.18

Railroad 896 0.19 4,320,332 0.12

Total, private/railroad bridges 1,329 0.28 10,869,440 0.30

Unknown 363 0.08 1,901,929 0.05

Unclassified 89 0.02 1,597,300 0.04

Total, unknown/unclassified bridges 452 0.10 3,499,229 0.10

Note: Table does not include culverts and tunnels.
52

1 m2 = 10.76 ft2

Figure 50. Graph. Deck Area (m2) of Bridges by Owners.

(2)

These tables and chart show that while ownership of the vast majority bridges by number is 

roughly split between State- and local-level agencies, the State-level agencies are responsible for 

almost 3.5 times as much deck area of bridges.

Table 12, table 13, and figure 51 show the variety of bridge types and materials that make up the 

Nation’s bridge inventory.

Table 12. Design Type of Main Span (NBI Item Number 43B).

(2)

Design Type

Number

of 

Bridges Design Type

Number

of 

Bridges

Slab 80,239 Arch—thru 377

Stringer/multibeam girder 247,902 Suspension 97

Girder and floorbeam system 7,415 Stayed girder 46

Tee beam 35,749 Moveable lift 189

Box beam or girders—multiple 50,510 Moveable bascule 457

Box beam or girders—single or spread 9,201 Moveable swing 202

Frame (except frame culverts) 5,331 Tunnel 40

Orthotropic 472 Culverts 132,110

Truss—deck 465 Mixed types 22

Truss—thru 10,601 Segmental box girder 259

Arch—deck 6,794 Channel beam 14,442
53

Table 13. Kind of Material Main Span (NBI Item Number 43A).

(2)

Design Type

Number

of Bridges Design Type

Number

of Bridges

Concrete 176,800 Prestressed concrete continuous 22,733

Concrete continuous 74,796 Wood or timber 23,461

Steel 133,839 Masonry 1,706

Steel continuous 49,860 Aluminum, wrought or cast iron 1,470

Prestressed concrete 119,789 Moveable bascule 644

Note: Table does not include culverts and tunnels.

Figure 51. Graph. Numbers of Bridges Built in 5-Year Periods by Material.

(2)

Table 14 and table 15 show the number and deck area of bridges classified as FO and SD by 

ownership category.
54

Table 14. Numbers of FO Bridges and Deck Area of FO Bridges by Owner.

(2)

Bridge Owner

Number

of 

Bridges

Percent

of All 

Bridges

Deck Area 

(ft2)

Percent

of All 

Deck Area

State highway agency 40,502 49.87 433,803,372 67.74

State park, forest, or reservation agency 190 0.23 471,169 0.07

Other State agencies 346 0.43 3,543,619 0.55

State toll authority 2,409 2.97 37,278,080 5.82

Total, State bridges 43,447 53.49 475,096,240 74.18

Total, Federal bridges 1,423 1.75 4,908,580 0.77

County highway agency 23,409 28.82 51,244,157 8.00

Town or township highway agency 2,424 2.98 3,551,628 0.55

City or municipal highway agency 8,160 10.05 70,987,020 11.08

Local park, forest, or reservation agency 22 0.03 51,914 0.01

Other local agencies 192 0.24 9,887,168 1.54

Local toll authority 190 0.23 15,963,805 2.49

Total, local bridges 35,820 44.10 156,594,273 24.45

Private (other than railroad) 110 0.14 1,920,572 0.30

Railroad 278 0.34 1,344,412 0.21

Total, private/railroad bridges 388 0.48 3,264,985 0.51

Unknown 141 0.17 559,433 0.09

Unclassified 0 0.00 0 0.00

Total, unknown/unclassified bridges 141 0.17 559,433 0.09

Note: Table does not include culverts and tunnels.
55

Table 15. Numbers of SD Bridges and Deck Area of SD Bridges by Owner.

(2)

Bridge Owner

Number

of 

Bridges

Percent

of All 

Bridges

Deck Area 

(ft2)

Percent

of All 

Deck Area

State highway agency 23,103 31.86 224,635,480 66.71

State park, forest, or reservation agency 161 0.22 256,558 0.08

Other State agencies 204 0.28 1,502,050 0.45

State toll authority 308 0.42 5,154,697 1.53

Total, State bridges 23,776 32.78 231,548,785 68.76

Total, Federal bridges 684 0.94 2,184,912 0.65

County highway agency 38,958 53.72 59,812,887 17.76

Town or township highway agency 3,972 5.48 4,603,498 1.37

City or municipal highway agency 4,391 6.05 31,643,905 9.40

Local park, forest, or reservation agency 12 0.02 24,273 0.01

Other local agencies 112 0.15 718,190 0.21

Local toll authority 38 0.05 3,610,226 1.07

Total, local bridges 47,483 65.48 100,412,979 29.82

Private (other than railroad) 61 0.08 479,543 0.14

Railroad 439 0.61 1,747,295 0.52

Total, private/railroad bridges 500 0.69 2,226,838 0.66

Unknown 78 0.11 382,011 0.11

Unclassified 0 0.00 0 0.00

Total, unknown/unclassified bridges 78 0.11 382,011 0.11

Note: Table does not include culverts and tunnels.

57

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