A Novel Application of Photogrammetry for Retaining Wall Assessment

Application of Laser Scanning to Assess the Roughness of the Diaphragm Wall for the Estimation of Earth Pressure

The correct estimation of earth pressure is important for the design of earth retaining structures and depends, among others, on the surface morphology of retaining structures. The diaphragm wall created as a protection of a deep excavation located in an urbanized area was selected as a research object. Terrestrial Laser Scanning (TLS) was used for the investigation of the unique surface (in real-world dimension) obtained by tremieying the concrete in different soil layers. An original and innovative procedure for concrete surface description was developed, which includes steps from the TLS measurement to the determination of the roughness parameters. The tested samples from anthropogenic soil, medium sand, and sandy gravel, map the real diaphragm wall surface. The surface roughness parameters in different soil layers were compared with the reference surface obtained by cast against steel formwork. The following parameters: Sa, Sdr, and Vmc are indicated as being the most useful in numerical description of the concrete surface type and in allowing the determination of the soil surface friction. The novelty of this study is the estimation of the parameter δ (friction angle between the retaining wall surface and the soil), which is, among others, a function of the wall surface roughness. The influence of the type of surface on earth pressure are generally recognized in laboratory tests. Based on the estimated in situ values of δ, the more reliable active and passive pressure coefficients K_a, K_p were calculated for the tested soil layers. The conducted study has a practical significance for designing of retaining construction and makes progress in determination of surface roughness required in Eurocode 7.

Evaluation of Anthropogenic Substrate Variability Based on Non-Destructive Testing of Ground Anchors

The purpose of this paper is to describe the variability of soil rheological properties based on research carried out using load tests of ground anchors under complex geotechnical conditions. The heterogeneity of soil should always be considered when designing geotechnical constructions. In the present case, the earthwork created at the Warsaw Slope revealed an embankment of anthropogenic origin, located in a geologically and geomorphologically complex area of the Vistula valley slope. Excavation protection was anchored mainly in soils of anthropogenic origin. When the acceptance tests of the ground anchor were completed, the subsoil randomness was confirmed using nondirect, geostatistical methods. A standard solid rheological model with nonlinear fitting to the data was used. This model was established to describe the creeping activity of the ground anchor more accurately. The characteristics of man-made embankments were described using the parameters obtained with the rheological model of the subsoil.

Mobile LiDAR for Scalable Monitoring of Mechanically Stabilized Earth Walls with Smooth Panels

Mechanically stabilized earth (MSE) walls rely on its weight to resist the destabilizing earth forces acting at the back of the reinforced soil area. MSE walls are a common infrastructure along national and international transportation corridors as they are low-cost and have easy-to-install precast concrete panels. The usability of such transportation corridors depends on the safety and condition of the MSE wall system. Consequently, MSE walls have to be periodically monitored according to prevailing transportation asset management criteria during the construction and serviceability life stages to ensure that their predictable performance measures are met. To date, MSE walls are monitored using qualitative approaches such as visual inspection, which provide limited information. Aside from being time-consuming, visual inspection is susceptible to bias due to human subjectivity. Manual and visual inspection in the field has been traditionally based on the use of a total station, geotechnical field instrumentation, and/or static terrestrial laser scanning (TLS). These instruments can provide highly accurate and reliable performance measures; however, their underlying data acquisition and processing strategies are time-consuming and not scalable. The proposed strategy in this research provides several global and local serviceability measures through efficient processing of point cloud data acquired by a mobile LiDAR system (MLS) for MSE walls with smooth panels without the need for installing any targets. An ultra-high-accuracy vehicle-based LiDAR data acquisition system has been used for the data acquisition. To check the viability of the proposed methodology, a case study has been conducted to evaluate the similarity of the derived serviceability measures from TLS and MLS technologies. The results of that comparison verified that the MLS-based serviceability measures are within 1 cm and 0.3° of those obtained using TLS and thus confirmed the potential for using MLS to efficiently acquire point clouds while facilitating economical, scalable, and reliable monitoring of MSE walls.

A Mobile LiDAR for Monitoring Mechanically Stabilized Earth Walls with Textured Precast Concrete Panels

Mechanically Stabilized Earth (MSE) walls retain soil on steep, unstable slopes with crest loads. Over the last decade, they are becoming quite popular due to their high cost-to-benefit ratio, design flexibility, and ease of construction. Like any civil infrastructure, MSE walls need to be continuously monitored according to transportation asset management criteria during and after the construction stage to ensure that their expected serviceability measures are met and to detect design and/or construction issues, which could lead to structural failure. Current approaches for monitoring MSE walls are mostly qualitative (e.g., visual inspection or examination). Besides being time consuming, visual inspection might have inconsistencies due to human subjectivity. This research focuses on a comprehensive strategy using a mobile LiDAR mapping System (MLS) for the acquisition and processing of point clouds covering the MSE wall. The processing strategy delivers a set of global and local performance measure for MSE walls. Moreover, it is also capable of handling MSE walls with smooth or textured panels with the latter being the focus of this research due to its more challenging nature. For this study, an ultra-high-accuracy wheel-based MLS has been developed to efficiently acquire reliable data conducive to the development of the serviceability measures. To illustrate the feasibility of the proposed acquisition/processing strategy, two case studies in this research have been conducted with the first one focusing on the comparative performance of static and mobile LiDAR in terms of the agreement of the derived serviceability measures. The second case study aims at illustrating the feasibility of the proposed strategy in handling large textured MSE walls. Results from both case studies confirm the potential of using MLS for efficient, economic, and reliable monitoring of MSE walls.

Evaluation of Photogrammetry and Inclusion of Control Points: Significance for Infrastructure Monitoring

Structure from Motion (SfM)/Photogrammetry is a powerful mapping tool in extracting three-dimensional (3D) models from photographs. This method has been applied to a range of applications, including monitoring of infrastructure systems. This technique could potentially become a substitute, or at least a complement, for costlier approaches such as laser scanning for infrastructure monitoring. This study expands on previous investigations, which utilize photogrammetry point cloud data to measure failure mode behavior of a retaining wall model, emphasizing further robust spatial testing. In this study, a comparison of two commonly used photogrammetry software packages was implemented to assess the computing performance of the method and the significance of control points in this approach. The impact of control point selection, as part of the photogrammetric modeling processes, was also evaluated. Comparisons between the two software tools reveal similar performances in capturing quantitative changes of a retaining wall structure. Results also demonstrate that increasing the number of control points above a certain number does not, necessarily, increase 3D modeling accuracies, but, in some cases, their spatial distribution can be more critical. Furthermore, errors in model reproducibility, when compared with total station measurements, were found to be spatially correlated with the arrangement of control points.