Evaluation of surface defect detection in reinforced concrete bridge decks using terrestrial LiDAR

Routine bridge inspections require labor intensive and highly subjective visual interpretation to determine bridge deck surface condition. Light Detection and Ranging (LiDAR) a relatively new class of survey instrument has become a popular and increasingly used technology for providing as-built and inventory data in civil applications. While an increasing number of private and governmental agencies possess terrestrial and mobile LiDAR systems, an understanding of the technology’s capabilities and potential applications continues to evolve. LiDAR is a line-of-sight instrument and as such, care must be taken when establishing scan locations and resolution to allow the capture of data at an adequate resolution for defining features that contribute to the analysis of bridge deck surface condition. Information such as the location, area, and volume of spalling on deck surfaces, undersides, and support columns can be derived from properly collected LiDAR point clouds. The LiDAR point clouds contain information that can provide quantitative surface condition information, resulting in more accurate structural health monitoring. LiDAR scans were collected at three study bridges, each of which displayed a varying degree of degradation. A variety of commercially available analysis tools and an independently developed algorithm written in ArcGIS Python (ArcPy) were used to locate and quantify surface defects such as location, volume, and area of spalls. The results were visual and numerically displayed in a user-friendly web-based decision support tool integrating prior bridge condition metrics for comparison. LiDAR data processing procedures along with strengths and limitations of point clouds for defining features useful for assessing bridge deck condition are discussed. Point cloud density and incidence angle are two attributes that must be managed carefully to ensure data collected are of high quality and useful for bridge condition evaluation. When collected properly to ensure effective evaluation of bridge surface condition, LiDAR data can be analyzed to provide a useful data set from which to derive bridge deck condition information.

Determining bridge deck deterioration through the use of 3D photogrammetry

The bridge inspection industry has yet to utilize a rapidly growing technology that shows promise to help improve the inspection process. This thesis investigates the abilities that 3D photogrammetry is capable of providing to the bridge inspector for a number of deterioration mechanisms. The technology can provide information about the surface condition of some bridge components, primarily focusing on the surface defects of a concrete bridge which include cracking, spalling and scaling. Testing was completed using a Canon EOS 7D camera which then processed photos using AgiSoft PhotoScan to align the photos and develop models. Further processing of the models was done using ArcMap in the ArcGIS 10 program to view the digital elevation models of the concrete surface. Several experiments were completed to determine the ability of the technique for the detection of the different defects. The cracks that were able to be resolved in this study were a 1/8 inch crack at a distance of two feet above the surface. 3D photogrammetry was able to be detect a depression of 1 inch wide with 3/16 inch depth which would be sufficient to measure any scaling or spalling that would be required be the inspector. The percentage scaled or spalled was also able to be calculated from the digital elevation models in ArcMap. Different camera factors including the distance from the defects, number of photos and angle, were also investigated to see how each factor affected the capabilities. 3D photogrammetry showed great promise in the detection of scaling or spalling of the concrete bridge surface.

NANOSCALE ELECTROCHEMISTRY BY IN-SITU TRANSMISSION ELECTRON MICROSCOPY

Nanoscale research in energy storage has recently focused on investigating the properties of nanostructures in order to increase energy density, power rate, and capacity. To better understand the intrinsic properties of nanomaterials, a new and advanced in situ system was designed that allows atomic scale observation of materials under external fields. A special holder equipped with a scanning tunneling microscopy (STM) probe inside a transmission electron microscopy (TEM) system was used to perform the in situ studies on mechanical, electrical, and electrochemical properties of nanomaterials. The nanostructures of titanium dioxide (TiO2) nanotubes are characterized by electron imaging, diffraction, and chemical analysis techniques inside TEM. TiO2 nanotube is one of the candidates as anode materials for lithium ion batteries. It is necessary to study their morphological, mechanical, electrical, and electrochemical properties at atomic level. The synthesis of TiO2 nanotubes showed that the aspect ratio of TiO2 could be controlled by processing parameters, such as anodization time and voltage. Ammonium hydroxide (NH4OH) treated TiO2 nanotubes showed unexpected instability. Observation revealed the nanotubes were disintegrated into nanoparticles and the tubular morphology was vanished after annealing. The nitrogen compounds incorporated in surface defects weaken the nanotube and result in the collapse of nanotube into nanoparticles during phase transformation. Next, the electrical and mechanical properties of TiO2 nanotubes were studied by in situ TEM system. Phase transformation of anatase TiO2 nanotubes into rutile nanoparticles was studied by in situ Joule heating. The results showed that single anatase TiO2 nanotubes broke into ultrafine small anatase nanoparticles. On further increasing the bias, the nanoclusters of anatase particles became prone to a solid state reaction and were grown into stable large rutile nanoparticles. The relationship between mechanical and electrical properties of TiO2 nanotubes was also investigated. Initially, both anatase and amorphous TiO2 nanotubes were characterized by using I-V test to demonstrate the semiconductor properties. The observation of mechanical bending on TiO2 nanotubes revealed that the conductivity would increase when bending deformation happened. The defects on the nanotubes created by deformation helped electron transportation to increase the conductivity. Lastly, the electrochemical properties of amorphous TiO2 nanotubes were characterized by in situ TEM system. The direct chemical and imaging evidence of lithium-induced atomic ordering in amorphous TiO2 nanotubes was studied. The results indicated that the lithiation started with the valance reduction of Ti4+ to Ti3+ leading to a LixTiO2 intercalation compound. The continued intercalation of Li ions in TiO2 nanotubes triggered an amorphous to crystalline phase transformation. The crystals were formed as nano islands and identified to be Li2Ti2O4 with cubic structure (a = 8.375 Å). This phase transformation is associated with local inhomogeneities in Li distribution. Based on these observations, a new reaction mechanism is proposed to explain the first cycle lithiation behavior in amorphous TiO2 nanotubes.