Hybrid model for vascular tree structures

This paper proposes a new representation scheme of the cerebral blood vessels. This model provides information on the semantics of the vascular structure: the topological relationships between vessels and the labeling of vascular accidents such as aneurysms and stenoses. In addition, the model keeps information of the inner surface geometry as well as of the vascular map volume properties, i.e. the tissue density, the blood flow velocity and the vessel wall elasticity. The model can be constructed automatically in a pre-process from a set of segmented MRA images. Its memory requirements are optimized on the basis of the sparseness of the vascular structure. It allows fast queries and efficient traversals and navigations. The visualizations of the vessel surface can be performed at different levels of detail. The direct rendering of the volume is fast because the model provides a natural way to skip over empty data. The paper analyzes the memory requirements of the model along with the costs of the most important operations on it.Postprint (published version

Hybrid dynamic modeling of 4-CBA hydrogenation fixed-bed catalytic reactor of PTA production plant

In this paper, a dynamic hybrid model of 4-carboxybenzaldehyde (4-CBA) hydrogenation fixed-bed catalytic reactor of Purified Terephthalic Acid (PTA) production plant has been developed. At the first step, the deactivation model of the reaction system has been predicted by using artificial neural network (ANN) technique. Then, the deactivation model estimated by ANN as black box incorporated to first principle model (FPM) as white box. Therefore, the established hybrid model has been utilized to model the hydrogenation reactor of PTA plant. Finally, the simulated results have been compared with the industrial reactor data. It has been concluded that hybrid model is more precise than a FPM model