Optimizing the Planning of Precast Concrete Bridge Construction Methods to Maximize Durability, Safety, and Sustainability [supporting dataset]

Details

• Creators:
  El-Rayes, Khaled ; Ignacio, Ernest-John ; Helaly, Hadil
• Corporate Creators:
  University of Illinois at Urbana-Champaign
• Corporate Contributors:
  Transportation Infrastructure Precast Innovation Center (TRANS-IPIC) Tier-1 University Transportation Center (UTC) ; United States. Department of Transportation. University Transportation Centers (UTC) Program ; United States. Department of Transportation. Office of the Assistant Secretary for Research and Technology
• Subject/TRT Terms:
  Bridge Decks Cast In Place Concrete Concrete Bridges Construction Management Costs Datasets Decision Support Systems Durability Lateral Supports Machine Learning Mathematical Prediction Mobility Optimization Planning And Design Precast Concrete Safety Sustainable Development

  More +
• Resource Type:
  Dataset
• Right Statement:
  Public Domain
• Geographical Coverage:
  United States
• Corporate Publisher:
  Transportation Infrastructure Precast Innovation Center (TRANS-IPIC) Tier-1 University Transportation Center (UTC)
• Abstract:
  The main goal of this project is to provide DOT planners with much-needed support that enables them to analyze and compare the performance of alternative bridge construction methods during the early design phase and optimize their construction decisions during the preconstruction phase. To accomplish this goal, the main tasks of this project focused on: (a) developing novel machine learning models to accurately predict the condition ratings of conventional cast-in-place and precast concrete deck bridges using NBI data; (b) creating a practical decision support tool (DST) to analyze and compare the safety, mobility, sustainability, durability, and construction cost of alternative bridge construction methods during the early design phase; and (c) developing an original muti-objective optimization model for the planning of precast bridge projects to maximize their safety, mobility, and sustainability while minimizing their total construction cost during the preconstruction phase. The developed models and tools enable state DOTs and local agencies to accurately predict deck condition ratings for conventional and precast bridges; select the most suitable construction method for each planned project based on its specific requirements and constraints; and optimize the planning of precast bridge projects to achieve multiple objectives including maximizing safety, mobility, and sustainability while minimizing total construction cost.
  
  The total size of the ZIP file is 63,162 KB
  
  
• Content Notes:
  As this dataset is preserved in a repository outside U.S. DOT control, as allowed by the U.S. DOT’s Public Access Plan (https://doi.org/10.21949/1503647) Section 7.4.2 Data, the NTL staff has performed NO additional curation actions on this dataset. This dataset has been curated to CoreTrustSeal's curation level "C. Initial Curation." To find out more information on CoreTrustSeal's curation levels, please consult their "Curation & Preservation Levels" CoreTrustSeal Discussion Paper" (https://doi.org/10.5281/zenodo.11476980). NTL staff last accessed this dataset at its repository URL on 2024-08-28. If, in the future, you have trouble accessing this dataset at the host repository, please email NTLDigitalSubmissions@dot.gov describing your problem. NTL staff will do its best to assist you at that time.
• Format:
  ZIP
• Funding:
  69A3552348333
• Collection(s):
  University Transportation Centers
• Main Document Checksum:
  urn:sha-512:973288de35eb478790ceb1e6f29d610238756c7c8f4e32f27d6c7195ce355e9b424b389d664649dd9a816df6ab839a8d47680c5dadf8eaae4c5be805fd01490c
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/89223/dot_89223_DS1.zip
• File Type:
  [ZIP - 4.02 KB ]