ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

ストープ区画最適化×Lerchs-Grossmann アルゴリズム×ロックマス・レーティング(RMR)×
分野鉱山工学鉱山工学鉱山工学
系統Process / pipelineProcess / pipelineProcess / pipeline
提唱年196019651973
提唱者Mining Engineering PracticeHelmut Lerchs and Israel GrossmannZbigniew T. Bieniawski
種類Optimization framework for underground mine excavation designGraph-theoretic algorithm for pit limit optimizationEmpirical classification for geotechnical engineering
原典Brady, B. H. G., & Brown, E. T. (2004). Rock mechanics for underground mining. Springer Science+Business Media. link ↗Lerchs, H., & Grossmann, I. F. (1965). Optimum design of open-pit mines. Canadian Mining and Metallurgical Bulletin, 58(633), 47-54. link ↗Bieniawski, Z. T. (1989). Engineering rock mass classifications. John Wiley & Sons. ISBN: 978-0-471-60437-4
別名Stope Design, Underground Mine Layout, Panel DesignLerchs-Grossmann Method, LG AlgorithmRMR, Bieniawski Classification, RMR89
関連343
概要Stope layout optimization is the process of designing the size, shape, and spatial arrangement of underground mine excavations (stopes) to maximize ore recovery while maintaining safety and economic viability. It balances the desire for large extraction volumes against rock mechanics constraints and support costs. The layout determines mining productivity, capital investment in support systems, and long-term mine life.The Lerchs-Grossmann Algorithm is a graph-theoretic method for determining the ultimate pit limit in open-pit mining operations. Introduced by Helmut Lerchs and Israel Grossmann in 1965, it maximizes the net present value of extracted ore while respecting slope stability constraints. This algorithm forms the theoretical foundation for most modern pit optimization software.The Rock Mass Rating (RMR) system, developed by Zbigniew Bieniawski starting in 1973, is an empirical classification that characterizes rock mass quality and estimates mining and civil engineering behavior. RMR combines five measurable geotechnical parameters into a single index ranging from 0 to 100, where higher values indicate stronger, more stable rock masses. It is the most widely used rock classification system worldwide for underground mining design.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 2 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Stope Layout · Lerchs-Grossmann Algorithm · Rock Mass Rating. 2026-06-19に以下より取得 https://scholargate.app/ja/compare