方法对比

	Tromp曲线	McCabe-Thiele 方法	Rosin-Rammler 分布
领域	采矿工程	采矿工程	采矿工程
方法族	Process / pipeline	Process / pipeline	Process / pipeline
起源年份	1937	1925	1933
提出者	K. Tromp	Warren L. McCabe and Ernest W. Thiele	Paul Rosin and Erich Rammler
类型	Empirical model for size classifier performance	Graphical design method for distillation columns	Empirical probability distribution for crushed material fineness
开创性文献	Tromp, K. (1937). Separation of fine particles from slurries by hydrocyclone. Colliery Guardian, 155(4), 251-256.	McCabe, W. L., & Thiele, E. W. (1925). Graphical design of fractionating columns. Transactions of the American Institute of Chemical Engineers, 21, 30-60.	Rosin, P., & Rammler, E. (1933). The laws governing the fineness of powdered coal. Journal of the Institute of Fuel, 7, 29-36.
别名	Partition Curve, Classification Efficiency Curve, Grade Recovery Curve	McCabe-Thiele Diagram, Graphical Distillation Method	Rosin-Rammler Model, RRS Distribution, Weibull Distribution (particle size)
相关	3	3	3
摘要	The Tromp Curve, introduced by K. Tromp in 1937, is an empirical model that quantifies the performance of size classifiers (cyclones, screens, jigs) by showing the fraction of particles at each size that report to the target stream (overflow or underflow). It is universally used in mineral processing to evaluate classifier performance, design circuits, and diagnose operational problems.	The McCabe-Thiele Method, introduced by Warren L. McCabe and Ernest W. Thiele in 1925, is a graphical technique for designing and analyzing distillation columns. It predicts the number of theoretical plates (stages) needed to achieve a desired separation between light and heavy components. While primarily a chemical engineering tool, it applies to liquid-vapor separation problems in mining operations such as mercury recovery and rare earth element refining.	The Rosin-Rammler Distribution, introduced by Paul Rosin and Erich Rammler in 1933, is an empirical probability distribution that describes the particle size distribution of ground or crushed materials. It characterizes fineness by two parameters: the characteristic size (d-prime) and the uniformity index (n). This distribution is remarkably accurate for mineral processing streams and is ubiquitous in comminution engineering.