Accurate estimation of rockfall trajectories is essential for mitigation of rockfall hazards.Nowadays,Doppler radar technologies can measure rockfall trajectories with centimeter resolution.Calibrating a numerical mod...Accurate estimation of rockfall trajectories is essential for mitigation of rockfall hazards.Nowadays,Doppler radar technologies can measure rockfall trajectories with centimeter resolution.Calibrating a numerical model to fit these measured trajectories,i.e.back analysis,often involves manual trial-anderror processes and subjective goodness-of-fit criteria.Here,we propose a framework that uses the chi-square statistic to quantify the misfit between modeled and measured rockfall trajectories.The framework can also quantify the uncertainty bounds on the best-fit model parameters.The approach is validated using field data from an Australian copper mine under two scenarios.(1)We perform an unconstrained back-analysis where the initial position and velocity of the rock,in addition to the coefficients of restitution(COR),are free variables.This scenario yields a normal COR Rn?0.866±0.109 and tangential COR R_(t)=0.29±0.151 with 68%confidence.(2)We perform a constrained back-analysis using predetermined initial position and velocity of the rock,which further constrains Rn to 0.8±0.014 and Rt to 0.39±0.065.Both scenarios show a higher uncertainty in Rt than in Rn.We also demonstrate the adaptability of the back-analysis framework to two-dimensional(2D)rockfall modeling using the same data.To the best of our knowledge,this is the first quantitative goodness-of-fit metric for trajectorybased rockfall back analysis that supports the estimation of inherent uncertainty.The simplicity of the metric lends itself to robust model optimization of rockfall back-analysis and can be adapted to other model assumptions(e.g.rigid-body mechanics)and metrics(e.g.velocity or energy).展开更多
Open pit mining operations generate significant spoil dumps that need to be characterised for stability to identify potentially unstable slopes.However,the current subjective practice for spoil characterisation often ...Open pit mining operations generate significant spoil dumps that need to be characterised for stability to identify potentially unstable slopes.However,the current subjective practice for spoil characterisation often involves tedious and risky field work.To this end,this study demonstrated the use of periodically acquired unmanned aerial vehicle(UAV)-based images over a coal mine spoil dump in New South Wales,Australia.A granular approach that captures the variability of each truck offload pile on a dump was adopted through morphology-based segmentation and ensemble algorithm-based classification which consolidates predictions from multiple classifiers.Overall accuracy of over 90% in the material characterisation based on the classification framework was achieved.The two-dimensional classification outcome was then transformed into three-dimensional(3D)block models using a point-based interpolation approach for stability analysis.The factor of safety derived from the granular approach offered improved assessment of failure risk compared to the conventional approaches,which treat the entire dump as a uniform category.This rapid classification and assessment method proposed in this study will help reduce the uncertainty associated with the variability of spoil dumps in slope stability assessments,thereby enhancing the safety and efficiency of mining operations.展开更多
Slope failures are an inevitable aspect of economic pit slope designs in the mining industry.Large open pit guidelines and industry standards accept up to 30%of benches in open pits to collapse provided that they are ...Slope failures are an inevitable aspect of economic pit slope designs in the mining industry.Large open pit guidelines and industry standards accept up to 30%of benches in open pits to collapse provided that they are controlled and that no personnel are at risk.Rigorous ground control measures including real time monitoring systems at TARP(trigger-action-response-plan)protocols are widely utilized to prevent personnel from being exposed to slope failure risks.Technology and computing capability are rapidly evolving.Aerial photogrammetry techniques using UAV(unmanned aerial vehicle)enable geotechnical engineers and engineering geologists to work faster and more safely by removing themselves from potential line-of-fire near unstable slopes.Slope stability modelling software using limit equilibrium(LE)and finite element(FE)methods in three dimensions(3D)is also becoming more accessible,user-friendly and faster to operate.These key components enable geotechnical engineers to undertake site investigations,develop geotechnical models and assess slope stability faster and in more detail with less exposure to fall of ground hazards in the field.This paper describes the rapid and robust process utilized at BHP Limited for appraising a slope failure at an iron ore mine site in the Pilbara region of Western Australia using a combination of UAV photogrammetry and 3D slope stability models in less than a shift(i.e.less than 12 h).展开更多
The conventional pseudo-dynamic(CPD)and modified pseudo-dynamic(MPD)methods are invoked to obtain the seismic bearing capacity of strip foundations using the limit equilibrium method,with a two-wedge failure mechanism...The conventional pseudo-dynamic(CPD)and modified pseudo-dynamic(MPD)methods are invoked to obtain the seismic bearing capacity of strip foundations using the limit equilibrium method,with a two-wedge failure mechanism.A spectral version of the conventional pseudo-dynamic method(SPD)is also invoked by considering the ground motion amplification factor,to be a function of the non-dimensional frequencyλ/B and soil damping.Numeric analyses show that bearing capacity results obtained by the MPD and SPD methods are generally consistent.Both experience the same general reduction in bearing capacity with the increase ofλ/B,with successive ups and downs corresponding to soil′s natural frequencies.For 5<λ/B<10,SPD and MPD results fluctuated between falling above and below CPD results.Forλ/B<2.5,SPD and MPD results were consistent with attenuation of the shear wave,while for 10<λ/B,amplification was exhibited.Results obtained by the CPD method monotonically decrease,due to the fact that CPD fails to inherently consider site effects and damping,and instead and relies on a single factor to consider the ground motion amplification.展开更多
基金funding from NSERC Alliance Grant ALLRP 576858e22 in partnership with Rocscience Inc.
文摘Accurate estimation of rockfall trajectories is essential for mitigation of rockfall hazards.Nowadays,Doppler radar technologies can measure rockfall trajectories with centimeter resolution.Calibrating a numerical model to fit these measured trajectories,i.e.back analysis,often involves manual trial-anderror processes and subjective goodness-of-fit criteria.Here,we propose a framework that uses the chi-square statistic to quantify the misfit between modeled and measured rockfall trajectories.The framework can also quantify the uncertainty bounds on the best-fit model parameters.The approach is validated using field data from an Australian copper mine under two scenarios.(1)We perform an unconstrained back-analysis where the initial position and velocity of the rock,in addition to the coefficients of restitution(COR),are free variables.This scenario yields a normal COR Rn?0.866±0.109 and tangential COR R_(t)=0.29±0.151 with 68%confidence.(2)We perform a constrained back-analysis using predetermined initial position and velocity of the rock,which further constrains Rn to 0.8±0.014 and Rt to 0.39±0.065.Both scenarios show a higher uncertainty in Rt than in Rn.We also demonstrate the adaptability of the back-analysis framework to two-dimensional(2D)rockfall modeling using the same data.To the best of our knowledge,this is the first quantitative goodness-of-fit metric for trajectorybased rockfall back analysis that supports the estimation of inherent uncertainty.The simplicity of the metric lends itself to robust model optimization of rockfall back-analysis and can be adapted to other model assumptions(e.g.rigid-body mechanics)and metrics(e.g.velocity or energy).
基金supported by the Australian coal industry's research(Grant No.C29048).
文摘Open pit mining operations generate significant spoil dumps that need to be characterised for stability to identify potentially unstable slopes.However,the current subjective practice for spoil characterisation often involves tedious and risky field work.To this end,this study demonstrated the use of periodically acquired unmanned aerial vehicle(UAV)-based images over a coal mine spoil dump in New South Wales,Australia.A granular approach that captures the variability of each truck offload pile on a dump was adopted through morphology-based segmentation and ensemble algorithm-based classification which consolidates predictions from multiple classifiers.Overall accuracy of over 90% in the material characterisation based on the classification framework was achieved.The two-dimensional classification outcome was then transformed into three-dimensional(3D)block models using a point-based interpolation approach for stability analysis.The factor of safety derived from the granular approach offered improved assessment of failure risk compared to the conventional approaches,which treat the entire dump as a uniform category.This rapid classification and assessment method proposed in this study will help reduce the uncertainty associated with the variability of spoil dumps in slope stability assessments,thereby enhancing the safety and efficiency of mining operations.
文摘Slope failures are an inevitable aspect of economic pit slope designs in the mining industry.Large open pit guidelines and industry standards accept up to 30%of benches in open pits to collapse provided that they are controlled and that no personnel are at risk.Rigorous ground control measures including real time monitoring systems at TARP(trigger-action-response-plan)protocols are widely utilized to prevent personnel from being exposed to slope failure risks.Technology and computing capability are rapidly evolving.Aerial photogrammetry techniques using UAV(unmanned aerial vehicle)enable geotechnical engineers and engineering geologists to work faster and more safely by removing themselves from potential line-of-fire near unstable slopes.Slope stability modelling software using limit equilibrium(LE)and finite element(FE)methods in three dimensions(3D)is also becoming more accessible,user-friendly and faster to operate.These key components enable geotechnical engineers to undertake site investigations,develop geotechnical models and assess slope stability faster and in more detail with less exposure to fall of ground hazards in the field.This paper describes the rapid and robust process utilized at BHP Limited for appraising a slope failure at an iron ore mine site in the Pilbara region of Western Australia using a combination of UAV photogrammetry and 3D slope stability models in less than a shift(i.e.less than 12 h).
文摘The conventional pseudo-dynamic(CPD)and modified pseudo-dynamic(MPD)methods are invoked to obtain the seismic bearing capacity of strip foundations using the limit equilibrium method,with a two-wedge failure mechanism.A spectral version of the conventional pseudo-dynamic method(SPD)is also invoked by considering the ground motion amplification factor,to be a function of the non-dimensional frequencyλ/B and soil damping.Numeric analyses show that bearing capacity results obtained by the MPD and SPD methods are generally consistent.Both experience the same general reduction in bearing capacity with the increase ofλ/B,with successive ups and downs corresponding to soil′s natural frequencies.For 5<λ/B<10,SPD and MPD results fluctuated between falling above and below CPD results.Forλ/B<2.5,SPD and MPD results were consistent with attenuation of the shear wave,while for 10<λ/B,amplification was exhibited.Results obtained by the CPD method monotonically decrease,due to the fact that CPD fails to inherently consider site effects and damping,and instead and relies on a single factor to consider the ground motion amplification.
