Cooperative agreements are awarded to nonprofit institutions of higher education under the competitive academic agreement program (caap)

The University of Dayton Research Institute Division was awarded a $1.26 million Cooperative Agreement on September 30, 2025, under the Pipeline Safety Research Competitive Academic Agreement Program (CAAP), CFDA 20.724, administered by the Pipeline and Hazardous Materials Safety Administration (PHMSA). The project, titled "Risk-Informed and Uncertainty-Aware Strain Capacity Prediction Model Development and Verification for Vintage Pipelines," will be conducted over a 36-month performance period through September 29, 2028. The primary deliverable is the development and verification of an advanced predictive model designed to assess strain capacity in aging pipeline infrastructure, incorporating both risk-informed methodologies and uncertainty quantification to enhance safety assessment capabilities across the nation's vintage pipeline systems.

The cooperative agreement engages multiple academic and research institutions as subrecipients, including Texas A&M Engineering Experiment Station, Rutgers University, University of Cincinnati, and the Center for Reliable Energy Systems, reflecting the collaborative nature of the CAAP initiative. These partnerships leverage subject matter expertise and student involvement across the consortium to develop solutions with potential for nationwide implementation. The research outputs are expected to generate factual, verifiable, and repeatable technical results that PHMSA can transition into its core research program, ultimately benefiting pipeline safety and infrastructure integrity across the United States.

Grant funding is used to research innovative solutions in various pipeline safety topic areas, that are expected to benefit the entire nation by enhancing pipeline safety. Texas a & m engineering experiment station, rutgers university, university of cincinnati, and the center for reliable energy systems have been identified as subrecipients. ''risk-informed and uncertainty-aware strain capacity prediction model development and verification for vintage pipelines.''