This course is for Engineers, Architects and Business Managers who have responsibility for the operation, state of good repair and reliability of transportation system infrastructure assets and who will benefit from knowledge about various resiliency planning strategies.
NJ LTAP invites you to attend this virtual seminar on Green Infrastructure and Porous Asphalt, that is designed to inform attendees about the uses, installation, and maintenance of porous asphalt. Expert speakers will explore how porous pavement applies to stormwater regulations and green infrastructure.
CAIT's BEAST Lab has been testing a full-scale, 50-ft. bridge deck for a project sponsored by the FHWA to learn about how the bridge deteriorates under exposure to extreme environmental conditions and traffic loading — and to evaluate emerging bridge preservation technologies such as UHPC.
Dr. Matthew Bandelt, an Assistant Professor in the Department of Civil and Environmental Engineering at the New Jersey Institute of Technology and a CAIT University Transportation Center partner, won the award to continue his research studying the use of highly ductile concrete materials in structural systems.
This follow up, 2-day session is intended to build upon the content previously covered in the Fundamentals of Asset Management Part 1 course and is generally geared towards folks who are involved with or responsible for maintenance and operations planning and management.
On Tuesday, March 8th, CAIT celebrated International Women's Day with a special edition of its seminar series that showcased some of the latest achievements and research of women leaders in transportation.
The way that we think about and use transportation as it exists today has been shaped by innovative women leaders throughout history. They have contributed greatly to the safety of all modes of travel, efficiency of our transportation systems, and the development of new technology that drives transportation into the future.
During this talk, Dr. Yeganeh Hayeri will evaluate this gap by utilizing a systematic review approach to categorize and synthesize the principal existing concepts in surface transportation systems using machine learning algorithms while decomposing them into their fundamental elements.