A Qualitative Model of Gradient Flow in a Spatially Distributed Parameter

This paper presents a qualitative common-sense model of gradient flow processes caused by concentration differences in a distributed parameter. A physical system is modelled by the spatial distributions of its parameters . Space is discretized into a pattern of regions according to the landmark values in the quantity space of each parameter. Gradient flow processes occur between adjacent regions with different values and create new regions of intermediate value that grow at the expense of the source and sink regions. The spatial and temporal evolution of the system depends on the relative sizes of the regions and the speeds of the flow processes. Ambiguities arise because shape information is not required . However, a plausible least complex evolution can be generated based on shapeinvariant inferences and assumptions. An example of aqualitative simulation of heat flow processes is given.