โ Scribed by G.P. Androutsopoulos; R. Mann
No coin nor oath required. For personal study only.
A square network model has been developed to mterpret mercury penetratin and retraction behavlour m the widely employed mercury porosunetry technique for mvesbgatmg pore structure and pore SIX dlstnbubon A network of arbitrary sl~c IS constructed by assembhng cyhndncal pore segments of equal length and pseudorandom number generation IS used to assyn pore dmmeters accordmg to any stipulated sux distnbutlon fuactlon Apption of the sunpk Washburn cquanon then predlcts movement of mercury mto the network under mcreasmg pressure (peaetrahon) and the correspondmg mthdrawai under reducmg pressure (retraction) The network model IS supenor to the classical parallel bundle model, smce It ~mpl~ccrtly produces hysteresis between penetration and rctract~on. prticts that mercury entrapment on retraction IS a result of mtercoanectcdness of pore segments and provides a better estunate of the mtnnslc &stnbution of segment sizes Compmson wrath poroslmeter expernnents on a commercml hydrodesulphurmahon catalyst show that the approach can be apphed to practical measurements and the model may provide an reproved basis for the study of dlfluslon. reachon and deactivation m catalyst pellets
๐ SIMILAR VOLUMES
The pore size distribution of the active pores of Millipore MF-VS and MF-VM microfiltration membranes, having nominal pore sizes of 250 )k and 500 A, respectively, was investigated by a new evaluation method described earlier. The average values of the active pore sizes calculated from the pore size
In the first part of this study, a method for classifying non-linear systems using neural networks was proposed and validated using data from numerical simulation. In order to extend this validation to experimental data, a system was required with a repeatable non-linearity of controllable severity,