Comparer des méthodes
Examinez les méthodes sélectionnées côte à côte ; les lignes qui diffèrent sont mises en évidence.
| Algorithme de Lerchs-Grossmann× | Classification RMR (Rock Mass Rating)× | |
|---|---|---|
| Domaine | Génie minier | Génie minier |
| Famille | Process / pipeline | Process / pipeline |
| Année d'origine≠ | 1965 | 1973 |
| Auteur d'origine≠ | Helmut Lerchs and Israel Grossmann | Zbigniew T. Bieniawski |
| Type≠ | Graph-theoretic algorithm for pit limit optimization | Empirical classification for geotechnical engineering |
| Source fondatrice≠ | 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 |
| Alias≠ | Lerchs-Grossmann Method, LG Algorithm | RMR, Bieniawski Classification, RMR89 |
| Apparentées≠ | 4 | 3 |
| Résumé≠ | 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. |
| ScholarGateJeu de données ↗ |
|
|