TRICUT: a program to clip triangle meshes using the rapid and triangle libraries and the visualization toolkit

An efficient technique to cut polygonal meshes as a step in the geometric modeling of topographic and geological data has been developed. In boundary represented models of outcropping strata and faulted horizons polygonal meshes often intersect each other. TRICUT determines the line of intersection and re-triangulates the area of contact. Along this line the mesh is split in two or more parts which can be selected for removal. The user interaction takes place in the 3D-model space. The intersection, selection and removal are under graphic control. The visualization of outcropping geological structures in digital terrain models is improved by determining intersections against a slightly shifted terrain model. Thus, the outcrop line becomes a surface which overlaps the terrain in its initial position. The area of this overlapping surface changes with respect to the strike and dip of the structure, the morphology and the offset. Some applications of TRICUT on different real datasets are shown. TRICUT is implemented in C+ + using the Visualization Toolkit in conjunction with the RAPID and TRIANGLE libraries. The program runs under LINUX and UNIX using the MESA OpenGL library. This work gives an example of solving a complex 3D geometric problem by integrating available robust public domain software. (C) 2002 Elsevier B.V. Ltd. All rights reserved.

Damage detection in a benchmark structure using AR-ARX models and statistical pattern recognition

Structural health monitoring (SHM) is related to the ability of monitoring the state and deciding the level of damage or deterioration within aerospace, civil and mechanical systems. In this sense, this paper deals with the application of a two-step auto-regressive and auto-regressive with exogenous inputs (AR-ARX) model for linear prediction of damage diagnosis in structural systems. This damage detection algorithm is based on the. monitoring of residual error as damage-sensitive indexes, obtained through vibration response measurements. In complex structures there are. many positions under observation and a large amount of data to be handed, making difficult the visualization of the signals. This paper also investigates data compression by using principal component analysis. In order to establish a threshold value, a fuzzy c-means clustering is taken to quantify the damage-sensitive index in an unsupervised learning mode. Tests are made in a benchmark problem, as proposed by IASC-ASCE with different damage patterns. The diagnosis that was obtained showed high correlation with the actual integrity state of the structure. Copyright © 2007 by ABCM.

Visualization of Protein Folding Funnels in Lattice Models

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)