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A platform for research: civil engineering, architecture and urbanism
Rock mass quality evaluation via statistically optimized geophysical datasets
https://orcid.org/0000-0003-2195-6098
https://orcid.org/0000-0001-8974-9808
Abstract Rock quality designation (RQD) is a critical geoengineering/geotechnical parameter for evaluating rock mass quality (RMQ), which is a preliminary construction decision-making tool. As a result, the soil-rock conditions of the southern part of Penang Island, Malaysia, a typical tropical granitic terrain, were evaluated using integrated seismic P-wave velocity (Vp), electrical resistivity ($$\rho$$), and borehole-based RQD datasets. The regression analytical modeling technique was used to establish lithology-based correlations linking RQD with Vp and $$\rho$$ data. The study aims to provide novel insights for estimating RQD from Vp and $$\rho$$ based models to understand the RMQ, boundary conditions, and architecture of surficial-to-subsurface soil-rock profiles for infrastructure design. In addition, methodological approaches and empirical relationships adaptable to granitic terrains for estimating RQD where borehole drillings are impossible are being developed. The $$\rho$$ model provided significant results in addressing the limitations of the seismic refraction method by accurately delineating soil-rock conditions with shallow overburden. The study area is characterized by residual soils and poorly weathered rocks, which are the rippable and unsuitable units for the placement of infrastructure foundations. However, the potential sections for foundation placement were identified suitably on the integral/fresh bedrock between the depths of 8 m and 25 m in the study area. Reinforced concrete piling to fresh bedrock is most preferred. Most importantly, the empirical relations derived for RQD with Vp and $$\rho$$ data yielded strong correlations and potentially high prediction results, with $${R}^{2}$$ values of 0.96 (96%) to 0.99 (99%). Generally, the research findings will considerably reduce the uncertainties and costs associated with borehole-based RQD evaluation for large aerial extent investigations.
Rock mass quality evaluation via statistically optimized geophysical datasets
https://orcid.org/0000-0003-2195-6098
https://orcid.org/0000-0001-8974-9808
Abstract Rock quality designation (RQD) is a critical geoengineering/geotechnical parameter for evaluating rock mass quality (RMQ), which is a preliminary construction decision-making tool. As a result, the soil-rock conditions of the southern part of Penang Island, Malaysia, a typical tropical granitic terrain, were evaluated using integrated seismic P-wave velocity (Vp), electrical resistivity ($$\rho$$), and borehole-based RQD datasets. The regression analytical modeling technique was used to establish lithology-based correlations linking RQD with Vp and $$\rho$$ data. The study aims to provide novel insights for estimating RQD from Vp and $$\rho$$ based models to understand the RMQ, boundary conditions, and architecture of surficial-to-subsurface soil-rock profiles for infrastructure design. In addition, methodological approaches and empirical relationships adaptable to granitic terrains for estimating RQD where borehole drillings are impossible are being developed. The $$\rho$$ model provided significant results in addressing the limitations of the seismic refraction method by accurately delineating soil-rock conditions with shallow overburden. The study area is characterized by residual soils and poorly weathered rocks, which are the rippable and unsuitable units for the placement of infrastructure foundations. However, the potential sections for foundation placement were identified suitably on the integral/fresh bedrock between the depths of 8 m and 25 m in the study area. Reinforced concrete piling to fresh bedrock is most preferred. Most importantly, the empirical relations derived for RQD with Vp and $$\rho$$ data yielded strong correlations and potentially high prediction results, with $${R}^{2}$$ values of 0.96 (96%) to 0.99 (99%). Generally, the research findings will considerably reduce the uncertainties and costs associated with borehole-based RQD evaluation for large aerial extent investigations.
Rock mass quality evaluation via statistically optimized geophysical datasets
https://orcid.org/0000-0003-2195-6098
https://orcid.org/0000-0001-8974-9808
Abstract Rock quality designation (RQD) is a critical geoengineering/geotechnical parameter for evaluating rock mass quality (RMQ), which is a preliminary construction decision-making tool. As a result, the soil-rock conditions of the southern part of Penang Island, Malaysia, a typical tropical granitic terrain, were evaluated using integrated seismic P-wave velocity (Vp), electrical resistivity ($$\rho$$), and borehole-based RQD datasets. The regression analytical modeling technique was used to establish lithology-based correlations linking RQD with Vp and $$\rho$$ data. The study aims to provide novel insights for estimating RQD from Vp and $$\rho$$ based models to understand the RMQ, boundary conditions, and architecture of surficial-to-subsurface soil-rock profiles for infrastructure design. In addition, methodological approaches and empirical relationships adaptable to granitic terrains for estimating RQD where borehole drillings are impossible are being developed. The $$\rho$$ model provided significant results in addressing the limitations of the seismic refraction method by accurately delineating soil-rock conditions with shallow overburden. The study area is characterized by residual soils and poorly weathered rocks, which are the rippable and unsuitable units for the placement of infrastructure foundations. However, the potential sections for foundation placement were identified suitably on the integral/fresh bedrock between the depths of 8 m and 25 m in the study area. Reinforced concrete piling to fresh bedrock is most preferred. Most importantly, the empirical relations derived for RQD with Vp and $$\rho$$ data yielded strong correlations and potentially high prediction results, with $${R}^{2}$$ values of 0.96 (96%) to 0.99 (99%). Generally, the research findings will considerably reduce the uncertainties and costs associated with borehole-based RQD evaluation for large aerial extent investigations.
Rock mass quality evaluation via statistically optimized geophysical datasets
Akingboye, Adedibu Sunny (author) / Bery, Andy Anderson (author)
2023
Article (Journal)
Electronic Resource
English
BKL:
56.00$jBauwesen: Allgemeines
/
38.58
Geomechanik
/
38.58$jGeomechanik
/
56.20
Ingenieurgeologie, Bodenmechanik
/
56.00
Bauwesen: Allgemeines
/
56.20$jIngenieurgeologie$jBodenmechanik
RVK:
ELIB18
Rock mass quality evaluation via statistically optimized geophysical datasets
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