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Publication Number:  FHWA-HRT-20-039    Date:  Volume 9, Winter 2020
Publication Number: FHWA-HRT-20-039
Date: Volume 9, Winter 2020


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In This Issue:

LTBP Releases InfoBridge™ Web Portal

The Long-Term Bridge Performance (LTBP) Program released a new version of InfoBridge in January at the 99th Transportation Research Board (TRB) Annual Meeting. This latest version has many important features, such as:

In addition to these features, the 2019 National Bridge Inventory (NBI)/National Bridge Element (NBE) and additional LTBP field-collected data are also part of this version.

The new bridge deck condition statistical forecasting models implemented in InfoBridge are time-in-condition model, deep learning model, and proportional hazards deterioration model.

  1. The time-in-condition model in the base models category is the simplest of the three models. Base models are deterministic statistical models that are easy to understand and implement. With these models, historical time duration for the condition rating of each deck of selected bridge types is calculated from training subsets of the NBI data. These time durations are applied to bridges of the same type to forecast their deck condition ratings.
  2. The deep learning model uses a machine learning technique that enables computational models, composed of multiple processing layers, to learn data representations of a multidimensional and complex dataset. In the context of condition forecasting, data representations can be interpreted as the statistical data interrelationships or data patterns that describe how various factors influence the bridge deck deterioration process. The current model considers 28 factors, including traffic volumes, construction materials, and climate.
  3. The proportional hazards deterioration model is categorized as a survival model. Survival models are multivariable probabilistic bridge deterioration models that combine survival analysis and Markov chain theory. Survival analysis is a statistical approach that analyzes the time until the deck deteriorates to a lower condition rating. The transition probabilities of the Markov chain are calculated from the Cox proportional hazards survival functions and hazard ratios associated with factors influencing deterioration at each condition rating.
This photo shows a graph created in the InfoBridge program that shows bridge deck condition forecasting models. A dropdown box for deck model type shows the following selections: base models, time in condition models, machine learning models, deep learning models, survival models, and proportional hazards deterioration models. The y-axix on the graph reads "condition rating code." The x-axis reads "year." Numbers on the y-axis read 3, 4, 5, 6, 7, 8, and 9. The x-axis reads 1989, 2000, 2010, 2020, 2030, 2040, 2050, 2060, and 2070. The key shows line types for upper bound, lower bound, mean, and median graph lines.

Source: FHWA
InfoBridge features three new bridge deck condition forecasting models.

The additions to historical spec changes cover standard specifications from 1931 to 2002 for the following:

The LTBP InfoBridge web portal can be accessed at https://infobridge.fhwa.dot.gov/.

LTBP Program Session at TRB Annual Meeting

This photograph shows approximately ten rows of attendees of the LTBP session held at the 2020 TRB Annual Meeting in Washington, D.C.

Source: FHWA
LTBP Session at 2020 TRB Annual Meeting, Washington, DC.

Hari Kalla, Associate Administrator of FHWA's Office of Infrastructure, welcomed the session attendees and provided introductory remarks.

Jean Nehme, Team Leader for FHWA's Long-Term Infrastructure Performance (LTIP), provided an update of the 2019 LTBP program activities. Other presentations by LTBP staff included an update on the increased data collection, new features in InfoBridge, three bridge deck condition forecasting models in InfoBridge, and a presentation by Professor Başak Bektaş of Minnesota State University on how InfoBridge is being used in research and education.

"The Long-Term Infrastructure Performance programs, namely LTBP and LTPP, are very important to FHWA, and we fully support them because of their importance to the State DOTs [departments of transportation] and other transportation agencies."

Hari Kalla
Associate Administrator, Office of Infrastructure
Federal Highway Administration (FHWA)

The session was attended by more than 150 people. The session was sponsored by the TRB Standing Committee on Structures Maintenance (AHD30) and cosponsored by the TRB Standing Committees on Bridge Management (AHD35) and Testing and Evaluation of Transportation Structures (AFF40).

Full-Scale Accelerated Bridge Testing Research

The LTBP Program is conducting an accelerated test on a full-scale steel girder bridge. The program is conducting the test at the Bridge Evaluation and Accelerated Structural Testing (BEAST) Lab at the Rutgers Center for Advanced Infrastructure and Transportation.

The main objective is to understand the causes and rates of deterioration of different bridge components. The bridge design (based on specifications from the 1980s) was chosen to represent most of the similar bridge types in operation today. The single-span bridge is 28 ft wide by 50 ft long, and consists of four steel girders supporting an 8-inch concrete deck. The deck is subjected to a rolling (tandem) live load of 60 kip that imposes 17,500 cycles per day. The bridge also is subjected to one freeze-thaw cycle every 16 hours. Additionally, the deck is sprayed with a 6-percent solution of brine every 16 hours. The environmental and live loading frequency is equivalent to approximately 17 years of loading compressed into 1 year.

This photo shows a single-span bridge with large steel beams running across and over it. One of the beams is yellow and has the word "BEAST" in all caps on it.

© Rutgers University.
BEAST Specimen Bridge Under Construction

The bridge is instrumented with strain gages, thermocouples, linear variable differential transformers, accelerometers, and humidity gages. In addition, visual inspection and several nondestructive evaluation (NDE) measurements are taken on a 1 ft by 1 ft grid after every 14 days of testing. The NDE measurements include electrical resistivity, impact echo, ground-penetrating radar, half-cell potential, ultrasonic shear-wave tomography, ultrasonic surface waves, infrared thermography, and high-definition imaging.

LTBP Program staff will upload all data acquired through this research study onto InfoBridge.

In Brief

2020 LTBP State Coordinators' Webinar

An LTBP Program webinar was presented on Wednesday, March 18, 2020. An LTBP Program progress was presented in addition to recapping the LTBP session held during the 2020 TRB Annual Meeting. Access the recording: 2020 LTBP State Coordinators' Webinar.



InfoBridge: Easy Access to the National Bridge Inventory and Much More - Part 1
Aspire, The Concrete Bridge Magazine, Precast/Prestressed Concrete Institute
Winter 2020 [PDF]

Truck Platoons and Highway Bridges
Aspire, The Concrete Bridge Magazine, Precast/Prestressed Concrete Institute
Summer 2019 [PDF]

Advancing Bridge Repair and Preservation Using Ultra-High Performance Concrete
Aspire, The Concrete Bridge Magazine, Precast/Prestressed Concrete Institute
Spring 2019 [PDF]

Concrete Bridge Deck Service-Life Prediction Tools
Aspire, The Concrete Bridge Magazine, Precast/Prestressed Concrete Institute
Winter 2019 [PDF]

DistributionFHWA LTBP News is being distributed according to a standard distribution. Direct distribution is being made to the FHWA Divisions and Resource Center.

Key Words—Infrastructure, Bridges, Research, nondestructive evaluation, NDE, TRB, UHPC.

Notice—This document is disseminated under the sponsorship of the U.S. Department of Transportation (USDOT) in the interest of information exchange. The U.S. Government assumes no liability for the use of the information contained in this document.

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.

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