In the wake of the Minneapolis bridge collapse, which sent cars and trucks plummeting 60 feet into the Mississippi River during the evening rush hour on August 1, it is reassuring to know that Connecticut has a secret weapon in the battle to ensure bridge safety. Dr. John DeWolf, a professor of Civil & Environmental Engineering at UConn, has spent more than two decades on field research involving bridge monitoring. With funding from the U.S. Federal Highway Administration and the Connecticut Department of Transportation (ConnDOT), in 1985 he began research aimed at learning how existing technologies can be used to monitor in-service bridges on a variety of performance criteria, and how bridges perform and age over time.
Bridge safety is something most people take for granted. But the Minneapolis bridge collapse reminded Americans that parts of our increasingly decaying infrastructure require attention and regular repair. According to reports, the I-35W bridge – which is inspected yearly because of suspected cracking problems – had been judged safe in 2006, though inspectors recommended the bridge be reinforced with steel plating. Connecticut’s last bridge collapse took place in 1983, when a 100-foot portion of I-95 spanning the Mianus River in Greenwich crumbled, killing three people. The State has come a long way since 1983, due in no small part to the efforts of Dr. DeWolf.
According to the American Society of Civil Engineers (ASCE), the U.S. has 596,842 public bridges. Of these, in 2003 more than 27% were judged structurally deficient or functionally obsolete; 33% of Connecticut’s over 5,350 bridges were deemed deficient or obsolete. Twelve have received ratings so low they are considered to be in critical condition; of these, three are currently closed for repairs, while others have been placed on more frequent inspection schedules or reduced load limits. Governor M. Jodi Rell has ordered increased inspections of Connecticut’s bridges and called for $100 million to be spent over two years to make necessary repairs.
In carrying out their research, Dr. DeWolf and his team selected a cross section of the State’s most important bridges and paired them with different sensor systems to determine which provided the most useful and reliable information. Each monitoring array is custom tailored based on the inspection concerns, traffic, age and materials specific to the bridge. The monitoring apparatus includes a computer and hardware that operates various sensors. The data are collected at intervals and stored in the computer, from which they can be accessed remotely. Dr. DeWolf uses sophisticated finite element analysis to make sense of the raw data. The resulting profile is then compared against the field inspection results; the points of convergence or deviation allow Dr. DeWolf to refine his analytical model and examine differences to glean a better understanding of bridge behavior.
Dr. DeWolf conducts both short-term and long-term monitoring studies. He explained that the short-term monitoring is meant to complement the State’s inspection system and is conducted on selected bridges that have been targeted for some type of repair, with the objective of helping ConnDOT to better understand the nature of the identified problem and how it can best be resolved. “For example, if inspectors find a crack, we can help them determine more precisely the nature of the problem and how it can be addressed for optimal safety while avoiding unnecessary repair costs,” said Dr. DeWolf.
U.S. bridge inspection regulations were developed by the Federal Highway Administration, which launched the 1971 National Bridge Inspection Standards (NBIS, revised in 2005). The standards emerged in the wake of the 1967 collapse of the Silver Bridge over the Ohio River during rush hour, killing 46 people. The NBIS calls for every public bridge to be inspected a minimum of every two years. Currently, inspectors examine and rate bridges based on a “visual condition” rating system with values ranging from 9 (best score) to 0 (worst). Bridge inspectors grade each span in three critical areas: the deck, the superstructure under the road and the substructure, which includes piers and footings. Bridges rated 2 in one of these areas show “advanced deterioration,” which could include fatigue cracks in steel, shear cracks in concrete or severe damage to the substructure of the bridge because of scour, the erosion caused by flowing water. Since these ratings are observation-based, rather than discrete measurements, they involve a fair degree of subjectiveness. Dr. DeWolf’s studies involve quantifying metrics that reduce the subjective nature of the inspections and enhance bridge safety.
Dr. DeWolf has used as many as 52 sensors on any one bridge, and as few as 14. The arrays may include a combination of tiltmeters, accelerometers, strain gauges, and thermocouples that measure tilt, vibration, strain and temperature at various locations on a bridge. He currently has long-term monitoring arrays installed on four Connecticut bridges, with another two coming online this summer. His objective with these long-term monitoring studies is to better understand how bridges perform and degrade over time, under different weather and temperature conditions, with varying use, etc., and to develop assessment guidelines that can be applied uniformly and universally.
“We have learned a great deal about how bridges perform over time. Our field research has allowed us to develop techniques for structural health monitoring of bridges that can be applied broadly to assess the bridge infrastructure,” said Dr. DeWolf. One of the new systems Dr. DeWolf’s team deployed is the first of its kind: an array that relies on solar panels for its power source. Wireless structural monitoring systems require batteries located at each sensor, but the monitors mounted at various places on bridges are often extremely difficult to reach, said Dr. DeWolf, making it difficult to change spent batteries and keep the monitoring system operational. The introduction of solar energy will improve the team’s ability to keep an array in place and capture critical data over long periods. His next goal is to automate the entire process.
