Issued Call 2.0_Appendix C - Research Topics.pdf

Broad Agency Announcement

693JJ3-23-BAA-0002

Issued Call 2.0

Appendix C – Research Topics

Broad Agency Announcement (BAA)

Office of Acquisition and Grants Management

Federal Highway Administration

Research Initiatives in Support of FHWA’s Office of Infrastructure Research and Development (HRDI)

Note: Concept papers may be submitted at any time up to the closing date of the research topic.

Advanced Digital Construction (ADC)

Topic Number Title Closing Date for

Concept Papers

See Note

Below Table

HRDI-ADC-01

Case Studies with BIM/Digital Twin Return on

Investment

TBA

HRDI-ADC-02

Research with Model and Operational Digital

Twins

TBA

HRDI-ADC-03

Automated Vehicle Impacts and Interactions with Physical Infrastructure

TBA

HRDI-ADC-04

Using Automated Vehicle Operational Data with

Digital Twins

HRDI-ADC-05

Maintenance Equipment Fleet Electrification

Infrastructure

HRDI-ADC-06

Integrating Maintenance and Preservation Asset

Management with Digital Twins

HRDI-ADC-12 Bid Items Standard Assessment 45 days after posted on SAM.gov C

Transportation Resilience and Safety (TRS)

Topic Number Title Closing Date for

Concept Papers

See Note

Below Table

HRDI-TRS-02

Impact of Environmental Factors on Pavement

Infrastructure

HRDI-TRS-03

Long Term Friction Performance for Concrete

Pavements

HRDI-TRS-04

Risk Assessment for Bridge

Preservation/Management Decision Making and

Resilience Enhancement

HRDI-TRS-05

Enhancing Pavement Surface Macrotexture

Measurement Quality

45 days after posted on SAM.gov D

HRDI-TRS-06

Predicting Infrastructure Deterioration Under

Future Climate for Asset Management

45 days after posted

F

Enhanced Pavement Management (EPM)

Topic Number Title Closing Date for

Concept Papers

See Note

Below Table

HRDI-EPM-02

Life-Cycle Assessment to Inform the Pavement

Treatment Selection Process

TBA

HRDI-EPM-04

Update and implement the next-generation asset management methodologies incorporating the cross-asset tradeoff analysis.

45 days after posted

B

Bridge Preservation and Management (BPM)

Topic Number Title Closing Date for

Concept Papers

See Note

Below Table

HRDI-BPM-01

Automated Data Collection and Automated

Decision Making for Bridge Performance

Evaluation and Preservation/Management

Decision Making

TBA

HRDI-BPM-02 Bridge Preservation Technology Evaluation

HRDI-BPM-03

Bridge Preservation and Management

Enhancement with Digital Twins

HRDI-BPM-04

A Holistic Approach: Integration of NDE with

Bridge Preservation and Asset Management

Practice

HRDI-BPM-05

3D Bridge Digitalization in Support of Effective

Bridge Asset Management

45 days after posted on SAM.gov E

HRDI-BPM-06

Developing a Bridge Maintenance Data

Collection Framework to Understand Bridge

Preservation Activities

45 days after posted

D

Pavement Modeling and Performance (PMP)

Topic Number Title Closing Date for

Concept Papers

See Note

Below Table

HRDI20-PMP-02

PEM Durability Test Thresholds and Design

Adjustment

As specified by note in the table above, the following are the expected funding ranges for the corresponding research topics and should be considered in the preparation of concept papers and proposals accordingly. Innovative concept papers and proposals with high technical merit and high value that exceed expected funding ranges must clearly identify items that exceed the range.

The Government reserves the right to select for award any, all, part, or none of the proposals received in response to this announcement. The Government will consider the overall availability of funding for allocations or awards selected.

Note A: $50,000 - $75,000

Note B: $155,000 - $170,000

Note C: $150,000 - $200,000

Note D: $200,000 - $300,000

Note E: $250,000 - $350,000

Note F: $250,000 - $400,000

Note G: $350,000 - $500,000

Note H: $450,000 - $650,000

Note I: $550,000 - $700,000

Note J: $650,000 - $750,000

Advanced Digital Construction

Topic: HRDI-ADC-01

Title: Case Studies with BIM/Digital Twin Return on Investment (ROI)

Transportation agencies (DOTs) are interested in the concepts of Building Information

Management (BIM) for Infrastructure and Digital Twins, how they apply to capital and network-level projects, and if the cost of transforming their business processes is worth the investment.

To-date, limited research has been completed that looks at the business case, or return on investment (ROI), of adopting BIM and Digital Twin processes into an agency’s workflow.

Further, the work that has been done has been limited to higher-value capital projects. This research topic seeks to address:

1. Identify and develop good case study subject projects that encompass a range of project values.

2. Tools to help DOTs ease into taking on BIM/Digital Twin projects.

3. Identify and develop a range of ROI tools and methodologies that are applicable to the value range of DOT highway projects.

Topic: HRDI-ADC-02

Title: Research with Model and Operational Digital Twins

The term Digital Twin encompasses many different forms and concepts, and can look very different from application to application, depending on the context and implementation. Some digital twins are entirely physical model-based, where limited or no operational information is managed in the business process. There are also digital twins that are only operational, such as public transit systems or traffic control networks. Research is needed to study the interaction of model-based and operational digital twins and look toward the goal of a transportation system integrating both physical and operational elements to have a true real world-representative digital twin.

Topic: HRDI-ADC-03

Title: Automated Vehicle Impacts and Interactions with Physical Infrastructure

As Automated Vehicle (AV) use is expected to increase and contribute to a significant percentage of highway use, it is imperative to understand the interaction between the vehicles and highway infrastructure. There are many unknowns associated with the deployment of SAE

Automation Level 4 and 5 vehicles; being proactive as to their use from a highway design and maintenance perspective will serve to contribute to the readiness of DOTs for their use. This topic will address research needs that include:

Optimum pavement marking design, maintenance, and reflectivity.

Highway design that is conducive to both AV and non-AV use.

Steps that may be taken now to be best positioned for future AV use.

Impacts unique to AV deployment.

Topic: HRDI-ADC-04

Title: Using Automated Vehicle Operational Data with Digital Twins

Assistive (SAE Levels 1-3) and fully automated (SAE Levels 4-5) driving technology relies on a cadre of sensing and image processing equipment coupled with machine learning (ML) and artificial intelligence (AI) algorithms to accomplish automation tasks. Along with capturing situational data for the vehicle’s own uses, such data could be beneficial to provide operational information in near real-time, feeding into a digital twin. This data might include traffic, infrastructure condition, and information about non-motorized modes such as bikes and pedestrians. This topic would explore such applications and look at the feasibility and applicability of AV information being used toward supplying information to digital twins.

Topic: HRDI-ADC-05

Title: Maintenance Fleet Equipment Electrification Infrastructure

As some states move toward mandating DOT vehicles and equipment be powered with energy sources other than gasoline and diesel, DOT equipment fleet operators are looking ahead to modify their existing servicing, fueling, and storage facilities to accommodate this paradigm shift. Battery electric vehicles (BEVs) will need sufficient charging infrastructure to keep them ready for the demands of heavy DOT use, and an accompanying technical staff well-trained in the maintenance and repair of electric vehicles. The Bipartisan Infrastructure Law (BIL) provides for an aggressive increase in the number of highway charging stations for the travelling public but is generally silent on the topic of DOT equipment and vehicle electrification infrastructure. FHWA has identified, via input from the national maintenance equipment fleet stakeholders, a need for research in this general area. Focus on this topic may include:

Changes to DOT equipment fleet operational, storage, and maintenance facilities in an environment where the DOT will transition away from petroleum-powered vehicles to other power sources such as BEVs, hydrogen fuel cells, and hybrid technologies.

Sourcing, training, and retaining qualified vehicle technicians that are well positioned to provide traditional in-house maintenance and repair of mixed-fleet, BEV, and other alternative-fueled vehicles.

Topic: HRDI-ADC-06

Title: Integrating Maintenance and Preservation Asset Management with Digital Twins

As DOTs move toward the adoption of lifecycle-based business processes such as BIM for

Infrastructure/Digital Twins, it will be important to incorporate infrastructure maintenance and preservation activities into the overall process. Such activities generally fall within the operations and maintenance part of the lifecycle spectrum. Although some states and a few international cases have been successful in starting to accomplish this, there is still an overall need for research into how to best incorporate maintenance processes and the accompanying data into the lifecycle model or digital twin. This research topic aims to explore operations and maintenance/preservation activities and data into DOT lifecycle business processes.

Topic: HRDI-ADC-11

Title: Bid Items Standard Assessment

Modern practices and technologies have brought compelling opportunity to FHWA and state agencies for utilizing agency-wide asset data not possible in the past. A critical aspect to ensure success is the development and adoption of data standards to ensure data preservation and exchange.

Utilizing uniform bid data, open data exchange standards, and data-linking approaches, a unit bid item standard ensures that business inefficiencies associated with information loss are minimized and the data and information chain is preserved for all subsequent users and their needs.

FHWA investigated the impacts of Material Source Mergers and Acquisitions (M&A) on

Competition (HRT-22-081). The research was inconclusive in determining trends associated with unit prices and impacts on competition in the materials supply chain; and researchers did not identify any clearly defined, quantitative evidence of M&A impacts on pricing. A significant hurdle identified during the research was lack of uniformity and inconsistent application of unit bid item data formats, descriptions, selection, and use across state agencies; i.e. lack of standardization.

Additionally, FHWA’s OIG has initiated audits on topics that rely on unit bid items and costs in the areas of competition, change orders, and engineers estimates. And there has been recent interest by the current administration on a standardizing bid items thru outreach with AASHTO.

A bid item standard can provide many benefits and improve the above items, including:

1. Provide consistent project planning, delivery, and management of multiple diverse projects and contracts.

2. Provide a common description and structure to reduce efforts needed to prepare and review estimates, bids, change orders, and competition impacts; and improve accuracy.

3. Provide consistency and uniformity to facilitate data mining, comparisons, and evaluating state, local, regional, and national trends, and efficient and effective cost controls.

4. Provide improved data integration and analysis of data from various projects, leading to improved decision making and strategic planning.

5. Provide ability to benchmark performance across different projects and contractors and help identify areas for improvement.

6. Provide data exchange and lifecycle needs for successful application of BIM for

Infrastructure and digital project delivery initiatives.

7. Provide the ability to compare costs across jurisdictional lines.

Goals of this research are to assess, examine the considerations, and layout the steps needed to develop and implement a national highway construction unit bid item data standard in the U.S.

The assessment will document the benefits and needs with priorities, identify areas of pushback and provide methods and strategies to address, and provide development and implementation strategies and plans. The result will lay the groundwork and provide a path forward to facilitate the adoption and use of a national unit bid item standard.

Transportation Resilience and Safety

Resilience is becoming an increasing critical consideration for highway and transportation engineers. It is time to incorporate resilience into the transportation design, management, and decision-making processes. A recent report summarizing feedback from state agency design engineers and industry stakeholders on pavement design identified resiliency as a factor to be incorporated into the design process (FHWA Summary Report).

According to FHWA Order 5520, resilience is the ability to anticipate, prepare for, and adapt to changing conditions and withstand, respond to, and recover rapidly from disruptions. As noted in that order, climate change and extreme weather events present significant and growing risks to the safety, reliability, effectiveness, and sustainability of the Nation’s transportation infrastructure.

Topic: HRDI-TRS-02

Title: Impact of Environmental Factors on Pavement Infrastructure

This study offers the use of historical LTPP data (SPS-8 sections) and National Park Services’

PMS database (i.e., EFL manages the PMS for NPS) to develop a series of deterioration models for different family groups of pavements to select the appropriate time-based preservation/rehabilitation strategies for pavement sections in the absence of heavy loads. These sections will be evaluated to assess the impact of climate change and matched with test sections from other LTPP experiments that have normal truck traffic to compare and show the proportion of total damage caused by environmental effects.

The materials used for construction, however, are often selected on the assumption of a stationary climate. Anthropogenic climate change may therefore result in rapid infrastructure failure and, consequently, increased maintenance costs, particularly for paved roads where temperature and precipitation are key determinants for material selection. Failing to update engineering standards of practice in light of climate change therefore significantly threatens pavement infrastructure in the United States. For the purpose of this study, different pavement family groups will be identified in different climate zones, and comprehensive evaluation of existing pavements will be conducted through analysis of different datasets.

Performance measures will be used to create the deterioration curves for each group of pavement family to fully characterize the condition of existing pavements, and damage factor determined from FWD data will be suggested as trigger factor to select rehabilitation candidates. Different levels of rehabilitation/preservation activities will be considered as potential alternatives for rehabilitation candidates. The deterioration curves will be employed to assess the impact of climate and obtain an estimate of environmental-induced damage as well as the performance of rehabilitation treatment and so extension in service lives of pavements. Also, an assessment output matrix will be developed, which can be served as a supplemental tool to help the decision-makers in the highway agencies with the climate related decision-making process.

This project will provide states with information related to the impact of climate change on pavement performance to improve planning for future renewal solutions.

Topic: HRDI-TRS-03

Title: Long Term Friction Performance for Concrete Pavements

Portland cement concrete production is around 200 million tons per annum into road pavements.

The microtexture and macrotexture of concrete pavement surfaces are largely controlled by the type of texturing used. There needs to be research done on how grinding procedures, aggregate quality, truck traffic impacts, concrete strength, and some other factors affect long-term friction performance. The impacts of Portland Cement Concrete mixture design materials and specifications, grooving and grinding processes, and truck traffic on friction values needs to be evaluated and documented.

This research will document the effects of Portland Cement Concrete mixture design materials and parameters, grooving and grinding methods, and truck traffic on friction values. Data from the LTPP Program database as well as DOT’s pavement friction management database could be used to establish the long-term friction performance for concrete pavements. This project is focused on both existing concrete pavements and new construction. This study aims to establish the friction performance of various materials and mix designs using different surface texturing techniques under various conditions (traffic load, climate, etc.).

This project will enhance the understanding of major factors impacting friction values and develop a friction toolbox to progress toward long-term friction performance for concrete pavements. Also, the objective is to establish a selection protocol for concrete pavement materials and texturing methods to provide suitable and sustainable friction performance.

Topic: HRDI-TRS-04

Title: Risk Assessment for Bridge Preservation/Management Decision Making and

Resilience Enhancement

Risk based bridge preservation/management decision making is needed for both action prioritization practice and after event repair/rebuild. Data requirements, methodologies, models, and tools are needed for bridge risk assessment and management. Research is needed to evaluate the risk caused by bridge deterioration, climate change, extreme events, etc. Certain level of validation, which may include inventory data analysis, lab testing, and field testing, is important for result acceptance.

Once a risk assessment/management tool is developed, it can be used to optimize decision making and recognize cost-effective actions to avoid damage or repair damage quickly.

Topic: HRDI-TRS-05

Title: Enhancing Pavement Surface Macrotexture Measurement Quality

The various components of pavement surface texture have a high influence on vehicle-road interactions. Pavements need appropriate surface texture to meet safety performance needs. Two types of surface texture affect pavement friction: microtexture (wavelengths of 1µm to 0.5mm) and macrotexture (wavelengths of 0.5mm to 50mm). In particular, macrotexture features contribute to pavement friction, tire-pavement noise, splash and spray, and rolling resistance.

Furthermore, from another safety perspective, macrotexture becomes more critical as speed increases. Therefore, accurate and repeatable macrotexture measurement data would significantly help State Highway Agencies (SHA) in assessing the adequacy of pavement surface macrotexture.

The August 2023 report, FHWA/NC/2022-05, Development of Friction Performance Models, recommended a mean profile depth macrotexture investigatory level of 0.80 mm, while acknowledging that this value was specific for the device used as the researchers determined that different systems provided differing mean profile depth values. Based on the NCHRP 10-98 project findings, most commercial macrotexture equipment measurement results are repeatable and generally agree well with one another if similar sensing technologies are used. There is a need for a highway speed macrotexture data collection and analysis quality system that will result in various systems reporting comparable results, similar in concept to the quality system utilized for ride quality/International Roughness Index.

The primary objective of this project is to develop, test, and validate a highway speed macrotexture data collection and analysis quality system. As part of this project, the research team needs to complete these tasks:

Assess and recommend the macrotexture measurements for which the quality system will be designed.

Define the data requirements of the selected macrotexture measurements.

Investigate and define the required data filtering/processing per selected macrotexture measurement.

Investigate and propose the conceptual data analysis approach of the quality system.

Develop highway speed macrotexture data collection and analysis quality system with field validation using different data collection systems.

This project outcomes would help agencies obtain comparable macrotexture information from various systems.

Topic: HRDI-TRS-06

Title: Predicting Infrastructure Deterioration under Future Climate for Asset

Management

Climate factors play critical roles in pavement and bridge deterioration due to their significant influences on material behavior, structural responses, and long-term performance. Milder winters, more extreme summers, and changing precipitation events have led to differences in the deterioration rates of assets such as pavement, bridges, and culverts. Fluctuations in temperatures will lead to changes in pavement distresses, such as rutting under hot conditions and cracking under cold conditions that affects rideability and safety. The temperature variations may also cause expansion and movement of concrete bridge decks, possibly increasing concentrated stress and inducing joint failure or slab buckling. Precipitations weaken the support for pavement and bridge structure due to increased moisture contents of unbound materials or hydraulic scouring.

Since the historical climate data are used for performance prediction in the current transportation infrastructure design and management, the prediction results may not be reliable for decision making of maintenance strategy under future climate conditions. In addition, current performance prediction models are limited when it comes to the impact of extreme weather events on infrastructure performance. Therefore, there is an urgent need to better predict infrastructure performance under changing climate conditions.

Research efforts are needed to develop reliable prediction models of infrastructure performance for transportation asset management. The performance model can be built using the comprehensive dataset included in the LTPP InfoPave and InfoBridge. The impact of future climate scenarios on infrastructure performance need be quantified considering climate change scenarios and distress types observed in pavements and bridges. Performance measures will be used to create the deterioration curves for each group of asset type to fully characterize the condition of existing asset, and damage factor determined from various dataset will be suggested as trigger factor to select rehabilitation candidates. Different levels of rehabilitation/preservation activities will be considered as potential alternatives for rehabilitation candidates. The deterioration curves will be employed to assess the impact of climate and obtain an estimate of environmental-induced damage as well as the performance of rehabilitation treatment and so extension in service lives of the asset. Also, an assessment output matrix will be developed, which can be served as a supplemental tool to help the decision-makers in the highway agencies with the climate related decision-making process.

As part of this project, the research must include these items:

Literature review and identification of gaps

Development and validation of performance prediction model

Determination of projected climate scenarios and inputs

Quantification of future climate impacts on infrastructure performance

Recommendations to infrastructure asset management

The research outputs can provide valuable information for decision making of infrastructure asset management under future climate and help with developing more accurate resilience plans.

Enhanced Pavement Management

Pavement management is a strategic approach to the optimal allocation of resources for the maintenance, preservation and upgrading of the pavement network. Pavement monitoring and data collection are an essential component of pavement management. Traditionally pavement management combined engineering and economic principles with sound business practices to support decision making at the strategic, network, and project levels. Consequently, current pavement monitoring and data collection and performance models developed were primarily focused on those two considerations – engineering and economic. In addition, the pavement management prioritizes treatment selection process based on engineering and economic considerations. However, with the increased awareness of the effect of climate change and the impact of the choices we make today on the society at present and future, a more encompassing consideration is the concept of sustainability that brings in the need to consider environmental and social consequences, in addition to engineering and economics, of our decisions. Pavement management data can also provide valuable information for improving pavement design, material selection, and optimization techniques for achieving construction quality, all of which contribute to improved sustainability. Data collection is a continuous process, starting with documentation of pavement construction and continuing throughout the pavement life.

Information that should be collected and stored over the pavement lifecycle needs to be reimagined to support the engineering, economic, environmental, and social aspects and will include data that are currently collected and new data items. In addition, network level pavement monitoring produces large amount of raw data, and this raw data is often converted to specific index or metric that are relevant to current decision making for ease of analysis and storage and performance models developed for those indices to support forward looking analyses. Additional such indices and performance models may be needed to support the incorporation of environmental and social considerations.

Topic: HRDI-EPM-02

Title: Life-Cycle Assessment to Inform the Pavement Treatment Selection Process

Pavement management systems (PMS) use decision trees or other procedures to prioritize treatment locations, timings, and types to maintain a pavement network given funding constraints. With the establishment of life cycle planning (LCP) requirement in 23 CFR 515.7 (b) that defines life cycle planning as a process to estimate the cost of managing an asset class, or asset sub-group over its whole life with consideration for minimizing cost while preserving or improving the condition, there is steps towards considering lifecycle perspective in prioritizing treatment locations, timings, and types that is focused on engineer and economics. However, there exists an opportunity and need to additionally consider environmental impacts as part of this selection process. This topic will address research needs that include how environmental considerations can be incorporated into the pavement management treatment selection process, data needs and collection opportunities, and LCA based metrics that can support such consideration.

Topic: HRDI-EPM-04

Title: Update and implement the next-generation asset management methodologies incorporating the cross-asset tradeoff analysis.

Transportation Asset Management (TAM) is a critical process for optimizing funding levels and policies within transportation agencies. Integrating Cross Asset Tradeoff Analysis (CATA) is essential for enhancing decision-making processes, enabling agencies to allocate resources more efficiently, plan for different scenarios, manage risks, and communicate decisions transparently to stakeholders. By incorporating tradeoff analysis, agencies can achieve better performance outcomes, ensure equitable resource distribution, and make more informed investment decisions.

The Tradeoff Analysis for Multi-asset Performance Objectives (TA-MAPO) tool is a key component in the TAM process. It provides a comprehensive solution for conducting tradeoff analysis, offering both optimal and suboptimal funding scenarios. These scenarios assist in making informed decisions, from selecting optimal funding to managing under-constrained funding situations. The tool comprises several components, including the Investment Candidate

File, Target Setting Worksheet, Funding Allocation Worksheet, and more, all designed to facilitate data-driven, performance-based decision-making across multiple asset classes.Challenges and Gaps

Current Methodology Limitations: The existing Transportation Asset Management

Methodology (TAMM) requires a review and assessment to identify areas for improvement, particularly in cross-asset analysis and lifecycle cost modeling.

Tool Integration: Enhancements to the TA-MAPO tool may be required to enable seamless integration with existing systems, ensuring that it can be effectively utilized across various State Departments of Transportation (DOTs).

Validation and Testing: There is a need for validation and testing through pilot programs in selected State DOTs to ensure the methodologies are robust and applicable in real-world scenarios.

Training and Documentation: Adequate training and documentation are essential for practitioners to effectively implement the new methodologies and tools.

Output and Outcome

The proposed plan aims to deliver the following outputs and outcomes:

Enhanced Methodologies: Revision and enhancement of the current TAMM, focusing on cross-asset tradeoff analysis, lifecycle cost analysis, and user cost modeling.

Improved Tool Functionality: Upgrades to the TA-MAPO tool to enable better integration and functionality, facilitating more effective decision-making.

Pilot Program Implementation: Successful execution of pilot programs to validate and test the enhanced methodologies, ensuring they meet the needs of transportation agencies.

Comprehensive Training: Conducting training sessions and workshops to introduce new methodologies and tools, including hands-on exercises and demonstrations.

Ongoing Support and Refinement: Providing continuous support and refinement of the methodologies and tools to ensure their successful adoption and implementation across various transportation agencies.

By addressing the challenges of Integrating Cross Asset Tradeoff Analysis (CATA) and delivering the subsequent outputs, the plan aims to significantly enhance the efficiency and effectiveness of transportation asset management, ultimately leading to improved resource allocation and investment decisions.

Bridge Preservation and Management

Topic: HRDI-BPM-01

Title: Automated Data Collection and Automated Decision Making for Bridge

Performance Evaluation and Preservation/Management Decision Making

Although not yet ready for current operational practice, automated data collection and decision making represent the future operation for bridge evaluation, preservation, and management. The fast development in sensing and energy harvesting technologies, data analysis algorithms, data storage, computational, and communication capacity makes this more and more realistic.

Identifying data requirements and recognizing appropriate sensing and energy harvesting technologies for bridge applications are essential for automated data collection. Improving and optimizing data storage (in digital twin framework), analysis (AI-based edging computing approaches), and communication strategy can facilitate automated decision making and effective information dissemination.

Some existing Structural Monitoring (SM) systems already demonstrate basic applications for automated data collection and decision making. For examples, bridge fire, flooding, wind, and collision monitoring systems have allowed near-real-time actionable messages to be sent to related personnel for implementation. Recognize and demonstrate successful SM application cases will encourage a wider adoption of the technology and build momentum for future research. In the meanwhile, it was also realized that evaluating the benefit of this type of SM systems in a monetary way can be hard in some cases. Therefore, in addition to ROI or life cycle analysis, more benefit evaluation approaches are needed to justify the adoption of SM technology.

This project includes:

1) Recognize and demonstrate successful systems for automated data collection and decision making

2) Develop system justification tool (other than ROI tool)

3) Standardize data framework for maintenance/preservation action and bridge damages reporting to support decision making (the data framework can be used for other bridges’ data collection too)

4) Develop AI based data analysis approach for bridge condition evaluation and decision making.

Topic: HRDI-BPM-02

Title: Bridge Preservation Technology Evaluation

Bridge preservation has been widely used and proved to be a cost-effective way to extend bridge service life. However, quality control approach and effectiveness of each technology are not fully evaluated. Research is needed for each technology to:

1) Recognize best practice and standardize procedure (some have been done)

2) Standardize quality control approach

3) Evaluate of the effectiveness

4) Conduct ROI and LCCA (include environmental analysis if possible)

5) Predict deterioration after action (correction of base structural deterioration model)

6) Establish a standardized preservation action database

Topic: HRDI-BPM-03

Title: Bridge Preservation and Management Enhancement with Digital Twins

Digital twin is a relatively new technology in bridge community and current applications are focused on digital deliverables which represent the lifecycle of bridge design and construction.

Once bridge is built and open to traffic, operational mode is initiated in physical domain.

Parallelly, in the digital domain, the digital as-built model will be passed into operational mode too. Data from all resources will be integrated to update the model and support decision making.

Compared to traditional data model, the digital twin framework allows more information (e.g., 3D damage location information, etc.) to be stored and applied in performance evaluation and decision making. The research include:

1) Define bridge preservation/management work procedure

2) Define data requirements and data dictionaries

3) Update digital twin model with available data in a near-real time fashion

4) Use the digital twin model in bridge evaluation/preservation/management/operational decision making

5) Evaluate the ROI for adopting digital twin technology in bridge preservation/management

Topic: HRDI-BPM-04

Title: A Holistic Approach: Integration of NDE with Bridge Preservation and Asset Management

Practice

Current bridge management and preservation decision making is mostly based on inventory data collected through mandated biennial bridge inspection and engineer judgment, sometimes supplemented by physical model analysis with material level parameters determined through lab testing. The component data provide the general performance condition of deck, superstructure, and substructure, which are important for asset management planning. Element data provide more granular information that is important for preservation decision making. Due to the requirements of MAP 21, most state established data-driven bridge management system. Some states also developed and integrated deterioration models and other action criteria into bridge management system for automated and optimized decision making.

Recent development in NDE technology provides a way to collect bridge performance data automatically, faster, with less traffic interference, and potentially more reliable. The data include the features that are typically used in visual inspection to determine the condition rating of components or condition status of elements, such as, crack, spall, delamination, etc. In addition, NDE data provide features that are not typically used in inventory data such as, cover depth, corrosion condition, and corrosion potential etc. These feature data are very important for preservation decision making (especially for early intervention) and deterioration and remaining service life prediction too.

NDE technology has the potential for future automated data collection and automated decision making. A wider adoption can be achieved if the data reliability can be approved, and the data can be integrated into current management and preservation practice effectively and efficiently.

Currently NDE data have been used at project level to help engineers determine preservation/repair method and determine project quantity. However, how to integrate NDE data into current bridge management system and use them systematically in bridge management and preservation decision making is rarely researched and far from solved. As more and more DOT starting to collect more NDE data, there is a timely need to find an effective and efficient way to integrate NDE data into current bridge management and preservation practice.

There is a need for FHWA to establish an evaluation system that does a quantitative reliability analysis and can quantify the performance of NDE data collection module, data interpretation and analysis module, as well as operators’ qualification. Standardize operation and data interpretation and analysis procedure is also important for data quality. Authorized recommendation for appropriate technologies for appropriate applications from FHWA will also help state DOTs find better way to collect data for more effective decision making. In this research, available NDE data (field and lab collected data) will be used in conjunction with inventory data to provide guidance to bridge owners on the reliability and probability of detection (POD) of NDE technologies to help them in comparing the cost/benefit ratio for different NDE technologies, selecting the appropriate technology for that application, and demonstrating the improvement in bridge asset management and preservation decision making using NDE data.

Topic: HRDI-BPM-05

Title: 3D Bridge Digitalization in Support of Effective Bridge Asset Management

Background: 3D bridge digitalization is an important step towards bridge digital twin creation and utilization. Digital twin is a virtual representation of an object or system designed to reflect a physical object accurately. It spans the object’s lifecycle, is updated from real-time data, and may use simulation, machine learning and reasoning to help make decisions. A digital twin of a bridge is composed by multiple components, which interact with each other and affect the actionable decisions. In some applications, only part of the information from digital twin is needed to support decision making, however a complete digital twin is still an idealized concept beyond current practice. Steps can be taken today to work toward it and take advantage of the information (include the 3D reference data) to enhance decision making. In the case of asset management 3D digitalization provides opportunities to improve modeling, analysis, and decision making which over the short-term may include adaption of current datasets to include location referencing, refined member representations (e.g. size, area), etc. and over the long-term may include advanced technologies such as simulation and machine learning.

Currently, State DOTs and other bridge owners are advancing the concept of model as deliverable from design through construction concluding with digital as-builts that include associated contextual properties and metadata. This provides a foundation and make it practical to explore the data needs to establish a digital twin for a bridge once construction is completed. It is a baseline and starting point, containing as much as practical information for future operation, inspection, and management. For in-service bridges the digital model and referenced information may originate from project delivery or it may be created post-construction. Any time something is done to a bridge, the data should be collected and integrated into the system of record to support asset management.

Current and expanded datasets that are used for bridge asset management and can potentially benefit from 3D digitalization or referencing are extensive. Example data includes, but is not limited to, design and as-built data, construction quality data, bridge inventory data, condition assessment, suggested work candidates generated by bridge inspector or bridge management systems (BMS), preservation/maintenance history data, load rating evaluation data, environment data (macro and micro), natural or hazardous event occurrence, frequency, magnitude, and effect, operational data including load history and inspection/monitoring history, etc. Recording and tracking some data with the location and temporal specificity offered by 3D referencing will provide opportunities for more effective data collection and for improved data representation, data types, models, analysis procedures, and use within bridge asset management.

This project will focus on assessing the benefits of 3D digitization and 3D referenced information, identifying the new, revised, or expanded datasets that would support the benefits, and developing a framework and strategic work plan for using 3D bridge digitalization data for bridge asset management. ISO 19650 and IFC4.3 accommodation and results from FHWA study

“Advancing BIM for infrastructure: National Strategic Roadmap” [1]and TPF-5(372) – BIM for bridges and structures [2] shall be considered.

Objective: The goals of this project is to assess and document the benefits that digital information will provide for bridge asset management from start of operation through replacement or decommissioning and develop a strategic work plan for the advancements that would be required to achieve the benefits. The uniform framework for bridge data and data exchange standards will be developed to support state DOT needs for BIM applications and roadmap integration.

Activities must include:

1. Document what data is available and/or needed to develop an optimized digital as-built model which can represent the bridge at the start point for operation in support of asset management.

2. Identify what application functions are included in bridge asset management practice and how current bridge management systems or other systems support the functions.

3. Identify how digital models or model referenced data can advance the achievement of bridge asset management objectives and enhance its functions.

4. Develop a potential framework and workflow from digital-as-built creation to management decision making (include multiple application functions) and what mechanism can be used to facilitate the information/data access.

5. Investigate data needs, source, collection, standardization, and management strategies for each step identified in the workflow and shown them in an interactable plot. Consistency with ISO 19650, buildingSMART International’s IFC4.3 (ISO16739) accommodation, and results from TPF-5(372) shall be considered in this project.

6. Identify the required interactions and enhancements to bridge asset management applications, including at a minimum, bridge management systems, inspection data collection. Processes, and maintenance management systems to provide, receive, and utilize digital model or model referenced information.

7. Develop a strategic roadmap for using currently available and proposed data/information in a digital twin framework that is ISO 19650 and IFC4.3 conforming with the purpose of enhancing bridge asset management.

The proposed research includes the following tasks:

Task 1: Literature review and in-depth state DOT interviews to understand and document:

1. Any experience in bridge digitalization related practice (digital as-built, digital-delivery, in-service bridge inspection, etc.).

2. Document bridge asset management objectives and data driven functions, including modeling and analyses performed by bridge management systems, the datasets used to perform the functions, and the importance and current limitations of those datasets.

3. Expected short- and long-term uses and benefits of digital models and/or model referenced data for bridge asset management occurring from end of construction through total replacement or decommissioning.

4. State DOT’s perspective on how digital information (especially 3D referenced information) can benefit bridge asset management functions to include at a minimum condition assessment, maintenance, modeling, analysis, and associated decision processes and workflow.

5. Data availability and data needs to achieve the benefits and workflow.

6. Data needs and availability to create an optimized digital model for bridges.

Task 2: Identify the potential data types (existing, refined, and/or proposed), the asset management functions which the data will serve, and how the data could be collected and recorded or referenced in digital form. Inputs from stakeholders shall be incorporated. Link the data types and functions to specific Task 1 benefits and to processes and procedures that are used in practice. Detail how new or improved processes and procedures may compare to existing.

Task 3: Develop a potential framework and workflow for use of digital models and/or model referenced data in bridge asset management from the end of construction through total replacement or decommissioning.

Task 4: Develop an interactive plot showing the workflow and associated data needs and data transfer identified in Task 3.

Task 5: With stakeholder inputs, develop a bridge specific annex to the BIM for Infrastructure:

National Strategic Roadmap , June 2021 - FHWA-HRT-21-064 to address major actions or investigations that are needed to implement the digital model and/or model referenced data uses and achieve the expected benefits.

Task 6: With stakeholder inputs, provide recommendations for technology providers regarding direction, function, and features that will support bridge owner asset management needs. Among other technologies include inspection data collection applications, bridge management systems, and maintenance management systems.

Task 7: Hold a national virtual workshop to present the project deliverables.

Deliverables

1. Intermediate reports for each task.

2. Integrate the intermediate reports into a project final report (include a standalone document for “Benefits of 3D digitization for bridge asset management” and a “Strategic work plan to achieve the benefits of 3D digitization from operation to replacement”)

3. A virtual workshop that meets FHWA’s 508 requirements to post the recording link on

FHWA’s website.

4. A standalone annex and workflow infographic for the BIM Roadmap that incorporates the project findings.

Topic: HRDI-BPM-06

Title: Developing a Bridge Maintenance Data Collection Framework to Understand Bridge

Preservation Activities

Background: Required by MAP-21 and FAST-ACT legislation, state DOTs started to establish data driven asset management programs that focuses on national transportation goals, accountability and transparency of the Federal highway programs, and use of performance data to drive investment decision making. Since 2014, the State DOTs have been collecting inspection data at the element level for bridges on the National Highway System. Some states collect this data for their entire bridge inventory. In year 2022, NCHRP Synthesis 585, Bridge

Element Data Collection and Use was completed that documented current state DOT practices for collecting element-level data and ensuring data accuracy. This synthesis also requested information on how the state DOTs are using bridge element data in asset management decision-making. The synthesis found that the most common use of element data in asset decision-making are the selection of bridge preservation projects; bridge-level decision-making, such as choice of work type or scoping for individual structures; and selection of bridge rehabilitation or replacement projects. In May 2022, FHWA released the Specifications for the National Bridge

Inventory (SNBI) as part of the update to the National Bridge Inspection Standards. SNBI requires collecting additional data items, and there is a six-year transition time for its full implementation.

In addition to collecting inspection data, States perform a variety of maintenance actions to preserve highway bridges in good and fair condition. These actions are performed by either in-house forces or by contractors. There is no uniformity or consistency in recording the maintenance data. In 2010, under NCHRP Project 14-15, “Developing a National Database

System for Maintenance Actions on Highway Bridges”, project team published the NCHRP

Report 668, where they developed a framework for national database system for the collection and archiving of bridge maintenance actions, materials, and methods, and their effectiveness.

The report outlined several tasks that were necessary for its implementation. However, the project did not get support from the states as collecting this data on a national level was not required. So, now states have either their own maintenance management systems or other in-house developed systems to capture bridge maintenance data, and most of them are managed by maintenance unit of State DOTs, and not directly accessible to bridge management systems and personnel. Therefore, many bridge owners have found that the bridge maintenance and preservation data are not always available or accessible to support the advanced preservation decision-making.

There is a need to understand state DOT’s current maintenance/preservation data collection practices, and, from there, develop a future data collection framework that could be integrated with states’ existing systems. The bridge owners could use this framework to facilitate an efficient and effective bridge preservation decision-making.

With the availability of bridge maintenance/preservation data, it will be possible for bridge owners to understand the extension of service life benefit of preservation actions.