Forecasting Rockfall Retention Performance of Catch Bench Configurations in Mining Models Calibrated to Rockfall Field Data
Public Domain
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2025/06/08
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Series: Mining Publications
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Journal Article:59th US Rock Mechanics/Geomechanics Symposium, June 8-11, 2025, Santa Fe, New Mexico
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Description:Rockfall hazards pose significant safety risks in open-pit mining, endangering both personnel and equipment. To mitigate these risks, catch benches are designed to retain falling rocks, with a common industry target of 90% retention on the first bench. However, quantifying retention rates remains challenging due to variable slope geometries and rockfall behaviors, necessitating calibrated predictive modeling. This study uses RocFall2 to simulate rockfall behavior based on field data from the Highwall Safety Project. A calibration was performed using single-bench tests, determining a 90% retention distance of 10.9 m (approx. 35.76 ft) from the bench toe for 6-inch synthetic rocks. The calibrated model was then applied to a five-bench configuration, which showed a first bench retention efficiency of 88.7%, with cumulative retention reaching 100% by the fifth bench. To explore the impact of bench geometry, a second simulation was conducted using the Modified Ritchie Criterion (MRC), reducing the catch bench width to 9.4 m. In this scenario, a six-bench system was needed to achieve full containment. The results reveal that achieving similar retention outcomes with narrower benches requires more sequential benches. These findings demonstrate the effectiveness of multi-bench systems while highlighting areas for improvement in bench geometry and energy dissipation strategies.
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Source:59th US Rock Mechanics/Geomechanics Symposium, June 8-11, 2025, Santa Fe, New Mexico. Alexandria, VA: American Rock Mechanics Association (ARMA), 2025 Jun; :ARMA-25-0852
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ISBN:9780989484428
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Pages in Document:8 pdf pages
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NIOSHTIC Number:nn:20071276
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Federal Fiscal Year:2025
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Peer Reviewed:False
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Main Document Checksum:urn:sha-512:773c929633bbd94a2f406e0a219c84750228a43b6314e828ad19c613aea4d115a2a636f75a70e3cd45ed984e89bbec3a7738f45281738a024c2075b3471387c4
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