Publication

Predicting the liquid phase mass transfer coefficient kL for the Sulzer structured packing Mellapak

Urs von Stockar
1992
Book Chapters

Abstract

A model for predicting the liq. phase mass transfer coeff., kL, for the Sulzer structured packing Mellapak 250.Y and 500.Y was proposed. Exptl. data were considered together with the penetration theory. The value of kL increased with the liq. and gas flow and decreased with the geometric area of the packing. Higher kL values were assocd. with irregular packings of equal geometric area. [on SciFinder (R)]

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Urs von Stockar
1992
Book Chapters

Abstract

Official source

Related concepts (12)

Sphere packing

In geometry, a sphere packing is an arrangement of non-overlapping spheres within a containing space. The spheres considered are usually all of identical size, and the space is usually three-dimensional Euclidean space. However, sphere packing problems can be generalised to consider unequal spheres, spaces of other dimensions (where the problem becomes circle packing in two dimensions, or hypersphere packing in higher dimensions) or to non-Euclidean spaces such as hyperbolic space.

Close-packing of equal spheres

In geometry, close-packing of equal spheres is a dense arrangement of congruent spheres in an infinite, regular arrangement (or lattice). Carl Friedrich Gauss proved that the highest average density – that is, the greatest fraction of space occupied by spheres – that can be achieved by a lattice packing is The same packing density can also be achieved by alternate stackings of the same close-packed planes of spheres, including structures that are aperiodic in the stacking direction.

Packing problems

Packing problems are a class of optimization problems in mathematics that involve attempting to pack objects together into containers. The goal is to either pack a single container as densely as possible or pack all objects using as few containers as possible. Many of these problems can be related to real-life packaging, storage and transportation issues. Each packing problem has a dual covering problem, which asks how many of the same objects are required to completely cover every region of the container, where objects are allowed to overlap.