State Highway 6 is a bypass from I-196 to I-96. It is the quick route to the airport if you live south of Grand Rapids and was a topic of conversation in the late 2010s.
It is well known that something went wrong when the concrete was originally poured in the late 90s. Yet, the state allowed the highway to decay until summer 2017, especially the portion from I-196 to Byron Center Avenue. The degradation of the road is centralized around the cut joints in the concrete that are 14 feet apart for much of the highway.
The impact of these damaged concrete joints could be felt and heard in the vehicle. This made the drive particularly miserable for both the vehicle operator and any passengers, but what effects did this have on the vehicle?
Any time a vehicle is driven, it is being damaged in some way. Automotive manufacturers design and test vehicles to withstand a specific amount of average damage per mile. They use a variety of road conditions and approximate how many miles of each condition the vehicle will be exposed to in its lifetime.
The question we ask today: if the repaired section of the highway is a normal environment, how much additional damage was applied to my vehicle for each mile driven on M-6?
M-6 Case Study
The western four miles of M-6 were in the worst condition until the summer of 2017 when all 4 lanes were torn out and replaced with new asphalt. With the expectation that the road was going to be fixed, engineers from Vibration Research Corporation set out to conduct a small case study. The goal was a simple comparison of the damage caused to vehicles by operating on the old highway versus the new one.
Using Vibration Research’s ObserVR1000 data acquisition hardware and triaxial accelerometers from Dytran Instruments, the engineers recorded the road vibration before and after the section of the road was repaired. With the recordings and subsequent analysis, they reached several interesting conclusions.
Recording and Analysis
Several recordings were acquired by making multiple passes across the 4-mile section of road in both directions in a 2016 Chevy Silverado 1500 truck. Then, the measured road vibration recordings were evaluated independently using accepted industry means.
There were a few minor discrepancies where the old road was less damaging than the new one at certain frequencies. One specific point was at the y-axis (horizontal and forward) at approximately 13.7Hz. This frequency was the wheel speed, so any differences in speed throughout the recording shifted this point.
The concrete joints on the old road were spread 14 feet apart. At 65MPH, a driver crosses 6.8 joints per second. This means that the impact frequency at 65MPH is 6.8Hz, 7.8Hz at 75MPH, and 8.3Hz at 80MPH.
When a vehicle is exposed to these types of impact events, the frequency of the impact is not necessarily at fault for the damage. Rather, it is the higher frequency content generated from the exposure. This high-frequency energy is much more likely to excite resonances in the vehicle components and cause additional damage.
For instance, if a vehicle’s component had a natural resonance of 34Hz, the damage difference would be approximately 10Hz. The average driver crosses this section of the highway 4 times per week. On the old road conditions with the 10x damage multiple and at 34Hz, the vehicle would experience nearly 4,000 miles of damage in 400 miles of driving.
The data show that there was significantly more damage applied to the vehicle due to the degraded condition of the highway section. There is no point between 10Hz and 2,000Hz (the typical frequency range for automotive testing) where the old road is less or equally damaging than the new one. This would mostly affect the suspension components and bushings inside of the vehicle, as they are most prone to low-frequency damage.
State, county, and city officials could use this comparison as an example of how to determine which roads need to be replaced or repaired. It could also be used as a reference tool to determine the rate of degradation a road experiences year after year. As more data are collected, it could be utilized to more efficiently predict when road sections will need to be repaired or replaced. This would allow for more efficient budgeting and work from local to national levels.