We deliver knowledge solutions and innovations so that MoDOT can make informed decisions. Research staff administer contract research to outside organizations to solve organizational challenges.
Research projects are focused on how MoDOT can change processes, products or materials in order to do our jobs in the most efficient and economical manner.
The Research Section falls under the Construction and Materials Division within MoDOT and is located in the Central Laboratory building.
What We Do
We develop an annual research program, focusing on strategic areas such as Safety, Bridges, Pavements, Materials, Geotechnical Issues, Erosion Control, Maintenance, Multimodal Transportation, Best Practices and Customer Satisfaction.
The Research Section is also responsible for other activities:
Pollinator Habitat Along Highway Right of Way
Pollinators are important components of our ecosystems, as well as being important contributors to agricultural production. Highway right of way (ROW) is one potential habitat for pollinators. The objectives of this study were to assess existing practices of other agencies for promoting pollinator habitat within the ROW and to identify potential lo...
Wireless Crack Sensing Systems for Bridges
The main objective of this research was to develop and deploy a wireless crack sensing system that can measure and monitor cracks for concrete and steel bridge structures. The system contained a sensing unit, wireless data transmitting system, as well as a data processing unit. The sensing unit consisted of single or arrays of advanced thin film-ba...
HFST Before and After Safety Analysis
Due to its high potential for safety improvement, MoDOT has deployed High Friction Surface Treatments (HFST) since 2013 at several areas experiencing high crash rates. To determine if the HFSTs are providing the expected results and if MoDOT’s HFST program is effective, this study was conducted with the primary objective of evaluating MoDOT’s exist...
Behavior and Repair of Corroded Steel H-Piles
This report summarizes the details of experimental work and finite element modeling conducted to evaluate: 1) the remaining axial capacity of H-piles having different corrosion severity and extension levels, and 2) the performance of repaired corroded H-piles. Seventeen full-scale H-piles were investigated under concentric and eccentric loads. The ...
Predictive Deep Learning for Flash Flood Management
This research used deep learning methods, along with weather information from NOAA/National Weather Service and geospatial data from the USGS National Map and other public geospatial data sources, to develop forecasting tools capable of assessing the probability of flash flooding in high risk areas. These tools build on existing models developed by...