Optimizing Temperature Measurement Infrastructure at the MnROAD Research Facility

At the MnROAD Research Facility, construction of test cells with various materials and design factorials, instrumentation, and periodic monitoring of over 100 test sections are common. In a typical test cell construction, the labor, sensor, and infrastructure hardware costs usually outweigh the construction materials cost even when the latter is not normalized from economy of scale relative to regular network construction size and costs. In search of infrastructure optimization, this study evaluated and compared temperature data from thermistors, thermocouples, and maturity sensors in four MnROAD concrete pavement test sections that were constructed in 2022. Although t -tests frequently rejected the null hypothesis (indicating differences in mean), these differences were generally negligible (<0.02°C, for sample space n >5700 and mean of approximately 24°C in each sensor case). Kullback–Leibler (KL) divergence analysis showed slight divergence of sensor data when depth changes across and within the sensor types were examined, but it exhibited almost no divergence when depth was similar. The t -tests and F -test as well as KL divergence analysis revealed that variability within each sensor type was as significant as variability between sensor types. Additionally, maturity curves developed from thermocouple and thermistor temperature data closely matched those from maturity sensors. Given the durability and capability of thermocouples and thermistor sensors, they offer reliable alternatives to traditional maturity sensors in pavement temperature monitoring over time. Results obtained will eventuate substantial operational efficiency in the research facility, reflecting in efficient service to data users and other customers.