Data & Modeling

The course will go through the entire section including clear zone, warranting obstructions, guide rail height, clearance from traveled way, rubrail, reduced post spacing at obstructions, guide rail at structures, end treatments, roadside recovery area, grading treatment, and many other topics.

The February 2018 issue of CE magazine featured THMPER—a portable, rapid testing device for bridge load-bearing capacity. THMPER is a breakthrough because it does this critical task faster, cheaper, and with less traffic disruption than other current methods.

THMPER determines bridge load ratings faster, cheaper, and with less traffic disruption than other current methods. A portable evaluation tool and data lab, it employs three refined methods outlined by AASHTO: modal impact testing, refined analysis, and calibration of FE element models.

Rutgers’ CAIT was awarded a $3.5 million grant from USDOT’s Research and Innovative Technology Administration under the University Transportation Center (UTC) program. This is the third time CAIT has successfully competed to retain its UTC status.

The Region 2 UTC consortium is focusing on developing practical tools and methods to improve infrastructure health, durability, and resilience. Partners are: Atlantic Cape Community College, Columbia, Cornell, NJIT, Polytechnic University of Puerto Rico, Princeton, Rowan, SUNY–Farmingdale, and University at Buffalo.

News from the USDOT Region 2 University Transportation Center led by Rutgers Center for Advanced Infrastructure and Transportation. Includes stories on recent events, research, and faculty accomplishments and activities.

FHWA acting administrator Brandye Hendrickson has announced the fifth round of the agency’s Every Day Counts (EDC) program, 10 selected proven, yet underutilized innovations to enhance safety, reduce congestion, shorten project timelines, and improve sustainability.

Bridge owners faced with difficult choices every day rely on multiple resources help them make maintenance and rehabilitation decisions. There are many databases out there, but no single source for comprehensive bridge performance data. Until now.

A CAIT proposal transforms part of downtown New Brunswick into a test bed for technologies that collect, process, analyze mobility big data—a crucial component to future integration of autonomous vehicles, a safer pedestrian and cycling environment, and robust public transit.

The USDOT Region 2 UTC Consortium spreads knowledge through published works, conference presentations, and other opportunities. Here are some examples of the recent activities and accomplishments of our researchers.

Dr. Xiang Liu is driving rail research and academics at RU. He is PI on several FRA research contracts. One on PTC—a hot topic after recent derailments—and another developing advanced risk analysis. Liu says RU can provide cutting-edge tech solutions and well-“trained” talent that railroads need.

As the Region 2 UTC lead institution, Rutgers CAIT gathered its consortium partners and high-level industry leaders to discuss the next round of UTC projects, clients’ priorities, and collaboration. Discussions focused on finding real-world implementable solutions for pressing transportation issues in the region.

Hurricanes or other extreme events can cause pipeline leaks, joint-weakening, or even ruptures. Dr. Jie Gong developed a mapping, monitoring, and risk-evaluation system combining lidar, infrared imagery analysis, and GIS-based assessment tools to identify vulnerable pipelines after a disaster.

A study on managing risk associated with broken rails by Dr. Xiang Liu was chosen for a special issue of Transportation Research Record that collects papers from 2016–2017 that were most frequently cited and mentioned in journal articles, federal reports, and policy publications.

FHWA selected CAIT as PI on a competitive five-year contract worth up to $25.5 million for the Long-Term Bridge Performance program. Envisioned as 20-year research study, it will be the first nationwide effort to collect uniform quantitative data on bridge performance.

CAIT expert briefed NJDOT on “gee whiz” automated systems and advanced technologies developed at the center that give bridge owners a picture of bridge health inside and out, and accelerated testing that indicates how they may hold up over time.

USDOT launched a national competition, Solving for Safety: Visualization Challenge, for crash data analysis innovations. Competition is open to local government personnel, data scientists, academics, and safety experts.