Optimizing the Planning of Precast Concrete Bridge Construction Methods to Maximize Durability, Safety, and Sustainability
The use of Precast Concrete (PC) bridge construction methods has steadily increased in recent years to improve the durability and sustainability of roadway infrastructure systems. To advance these goals, DOT planners often need to optimize the planning of bridge construction methods to accomplish multiple project objectives including maximizing durability, safety, sustainability, and mobility, while minimizing bridge life-cycle cost. This presents DOT planners with a number of challenges including how to (1) select an optimal bridge construction method during early design phase; (2) identify optimal size and number of bridge PC modules; (3) determine optimal shipping and onsite installation of all prefabricated PC modules; and (4) quantify and optimize the impact of construction planning decisions on bridge durability, safety, sustainability, mobility, and life-cycle cost. To address these challenges confronting DOTs, this research will focus on developing (a) predictive machine learning (ML) models to accurately estimate the construction cost of alternative construction methods during the early bridge design phase, and (b) multi-objective optimization decision support tool for quantifying and optimizing the impact of related construction decisions on durability, safety, sustainability, mobility, and life-cycle cost.
Language
- English
Project
- Status: Active
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Sponsor Organizations:
University of Illinois, Urbana-Champaign
Department of Civil and Environmental Engineering
Newmark Civil Engineering Laboratory
Urbana, IL United States 61801-2352Office of the Assistant Secretary for Research and Technology
University Transportation Centers Program
Department of Transportation
Washington, DC United States 20590 -
Performing Organizations:
University of Illinois, Urbana-Champaign
Department of Civil and Environmental Engineering
Newmark Civil Engineering Laboratory
Urbana, IL United States 61801-2352 -
Principal Investigators:
El-Rayes, Khaled
Ignacio, Ernest-John
- Start Date: 20240101
- Expected Completion Date: 20241231
- Actual Completion Date: 0
Subject/Index Terms
- TRT Terms: Bridge construction; Concrete bridges; Cost estimating; Decision support systems; Life cycle analysis; Machine learning; Optimization; Precast concrete
- Subject Areas: Bridges and other structures; Construction; Highways; Planning and Forecasting;
Filing Info
- Accession Number: 01903260
- Record Type: Research project
- Source Agency: Transportation Infrastructure Precast Innovation Center
- Files: UTC, RIP
- Created Date: Dec 24 2023 8:36AM