Evaluation of the Volume Measurement Optical Method Suitability for Determining the Relative Compaction of Soils

Karol Brzeziński, Maciej Maślakowski, Paweł Liszewski

Abstract


The goal of this paper is evaluation of the volume measurement optical method suitability for determining relative compaction of soils. The Structure for Motion technique was utilized in order to achieve the goal by making the three-dimensional models (with Bentley ContextCapture software). Created models were used in volume measurement of the pit-holes. The results were compared with the basic methods: the sand cone test and the water method. The laboratory tests were carried out in two stages. In the first stage, the optical method was tested in similar to operating conditions. Ten holes were made in the soil and the volumes were measured with three different methods. The results were compared and submitted for statistical analysis. Statistical analysis showed the potential of optical method. The second laboratory test focused on repeatability and accuracy of measurement. The volume of the vessel imitating a pit-hole was obtained. The results of the second stage showed that the optical method has better accuracy and lower statistical dispersion compared with sand method. On this basis it can be concluded that optical method of volume measurement has great potential in soil compaction testing.


Keywords


Relative Compaction; Volume Measurement; Structure for Motion; Photogrammetry; Context Capture.

References


BN-77 8931-12 Determining relative compaction of soils (in Polish) (1977).

BS 1377-4: 1990 Methods of test for Soils for civil engineering purposes – Part 4: Compaction-related test (1990).

“ContextCapture Quick Start Guide – 2017: www.Bentley.com/ContextCapture.”.

S. Zhang, “High-speed 3D shape measurement with structured light methods: A review,” Optics and Lasers in Engineering 106(December 2017) (2018): 119–131, doi:10.1016/j.optlaseng.2018.02.017.

R. Wrózyński et al., “Ground volume assessment using ‘Structure from Motion’ photogrammetry with a smartphone and a compact camera,” Open Geosciences 9(1) (2017): 281–294, doi:10.1515/geo-2017-0023.

M. J. Westoby et al., “‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications,” Geomorphology 179 (2012): 300–314, doi:10.1016/j.geomorph.2012.08.021.

L. Javernick, J. Brasington, and B. Caruso, “Modeling the topography of shallow braided rivers using Structure-from-Motion photogrammetry,” Geomorphology 213 (2014): 166–182, doi:10.1016/j.geomorph.2014.01.006.

F. Clapuyt, V. Vanacker, and K. Van Oost, “Reproducibility of UAV-based earth topography reconstructions based on Structure-from-Motion algorithms,” Geomorphology 260 (2016): 4–15, doi:10.1016/j.geomorph.2015.05.011.

S. Harwin, A. Lucieer, and J. Osborn, “The impact of the calibration method on the accuracy of point clouds derived using unmanned aerial vehicle multi-view stereopsis,” Remote Sensing 7(9) (2015): 11933–11953, doi:10.3390/rs70911933.

U. P. Reconstruction, R. K. Slocum, and C. E. Parrish, “Simulated Imagery Rendering Workflow for UAS-Based Photogrammetric 3D Reconstruction Accuracy Assessments,” Remote Sensing 9(4) (2017): 396, doi:10.3390/rs9040396.

V. Raoult et al., “How Reliable Is Structure from Motion (SfM) over Time and between Observers? A Case Study Using Coral Reef Bommies,” Remote Sensing 9(7) (2017): 740, doi:10.3390/rs9070740.

M. J. Westoby et al., “Cost-effective erosion monitoring of coastal cliffs,” Coastal Engineering 138(June 2017) (2018): 152–164, doi:10.1016/j.coastaleng.2018.04.008.

H. Obanawa, “Variations in volumetric erosion rates of bedrock cliffs on a small inaccessible coastal island determined using measurements by an unmanned aerial vehicle with structure-from-motion and terrestrial laser scanning,” Progress in Earth and Planetary Science (in press) (2018), doi:10.1186/s40645-018-0191-8.

A. Bhatla et al., “Evaluation of accuracy of as-built 3D modeling from photos taken by handheld digital cameras,” Automation in Construction 28 (2012): 116–127, doi:10.1016/j.autcon.2012.06.003.

B. Ruzgienė et al., “UAV photogrammetry for road surface modelling,” The Baltic Journal of Road and Bridge Engineering 10(2) (2015): 151–158, doi:10.3846/bjrbe.2015.19.

K. Nassar and Y. Jung, “Structure-From-Motion Approach to the Reconstruction of Surfaces for Earthwork Planning,” KICEM Journal of Construction Engineering and Project Management 2(3) (2012): 1–7.

K. Brzeziński et al., “The concept of validation procedure for subsoil recognition methods in road engineering (in Polish),” Drogownictwo (3) (2017): 85–91.

K. Brzeziński, P. Tutka, and M. Maślakowski, “Selected issues of validation of subsoil recognition methods (in Polish),” Technika Transportu Szynowego 12 (2017): 1–5.

K. Brzeziński, M. Maślakowski, and M. Sokołowska, “Preliminary validation of the dynamic probing methods used in estimation of the relative density of cohesionless soils,” MATEC Web of Conferences 117 (2017): 24, doi:10.1051/matecconf/201711700024.

Robert Ernest Troxler, “Optical method and apparatus for determining a characteristic such as volume and density of an excavated void in a construction material,” US2012304763 (A1)2012.


Full Text: PDF

DOI: 10.28991/cej-03091138

Refbacks

  • There are currently no refbacks.




Copyright (c) 2018 Karol Brzeziński

Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
x
Message