Carbon nanotubes (CNTs) when used as additives in cementitious materials are known to enable the piezo-responses making them smart materials. The piezo-responses can potentially be used to monitor the applied forces, stress, and the resulting performances of the associated materials. An effective and reproducible method for smart cementitious material production needs to ensure uniform dispersion of CNTs within the cementitious base, and that should lead to better sensitivity and consistency in sensing by the smart cementitious materials. This paper presents a surface modification method of CNTs using carboxymethyl cellulose (CMC) to improve the performance of the CNT-modified smart cementitious materials for stress sensing. Compared to the two commonly used CNTs dispersion methods, the direct mixing and the surfactant surface treatment methods of dispersing CNTs, the new CMC surface modification method developed within this study significantly increased the stress detection sensitivity and consistency, and reduced the measurement hysteresis.

Frequent network-wide monitoring of the condition of roadways and railways prevent fatalities, injuries, and financial losses. Even so, agencies cannot afford to inspect vast transportation networks using present methods. Therefore, the idea of using low-cost sensors aboard connected vehicles became appealing. However, low-cost sensors introduce new challenges to improve poor signal quality which causes detection errors. Common approaches apply computationally complex filters to individual signal streams, which limits further improvements. This paper presents a method that combines signals from each traversal in a manner that leads to ever-increasing signal quality. The proposed method addresses the challenges of poor accuracy and precision of position estimates from global positioning system (GPS) receivers, and errors from the non-uniform sampling of low-cost accelerometers. The result is improved signal quality from a 20% improvement in signal alignment over GPS and a 90-fold enhancement in distance precision.

The remarkable mechanical properties and piezo-responses of carbon nanotubes (CNT) makes this group of nanomaterials an ideal candidate for use in smart cementitious materials to monitor forces and the corresponding structural health conditions of civil structures. However, the inconsistency in measurements is the major challenge of CNT-enabled smart cementitious materials to be widely applied for force detection. In this study, the modified tapioca starch co-polymer is introduced to surface treat the CNTs for a better dispersion of CNTs; thus, to reduce the inconsistency of force measurements of the CNTs modified smart cementitious materials. Cement mortar with bare (unmodified) CNTs (direct mixing method) and surfactant surface treated CNTs using sodium dodecyl benzenesulfonate (NaDDBS) were used as the control. The experimental results showed that when compared with samples made from bare CNTs, the samples made by modified tapioca starch co-polymer coated CNTs (CCNTs) showed higher dynamic load induced piezo-responses with significantly improved consistency and less hysteresis in the cementitious materials. When compared with the samples prepared with the surfactant method, the samples made by the developed CCNTs showed slightly increased force detection sensitivity with significantly improved consistency in piezo-response and only minor hysteresis, indicating enhanced dispersion effectiveness. The new CNT surface coating method can be scaled up easily to cater the potential industry needs for future wide application of smart cementitious materials.

According to the Federal Highway Administration (FHWA), in 2012, there were 1,357,430 miles of unpaved road in the United States, accounting for almost 35 percent of the more than 4 million miles of roadway in the Nation. Maintaining unpaved roads in good condition requires frequent evaluation of their ride quality. Common methods of ride quality evaluation such as the international roughness index (IRI) and profilograph index (PrI) are applicable for paved roads only. They require special types of equipment that are expensive and time-consuming to use. Hence, agencies cannot afford to extend the capabilities of existing equipment to monitor the ride quality of unpaved roads. This paper evaluates the use of smartphones on regular vehicles as an alternative. The method used a road roughness index called the road impact factor (RIF) to quantify the ride quality. Field experiments showed that the method provides consistent measurements and, therefore, is an attractive alternative for monitoring the ride quality of all unpaved roads in the Nation.