Development of python tools on the Abaqus software

Our Abaqus Viewer tool allows us to generate a large number of images to automatically produce our client's reports. Until now, this tedious and recurring task was carried out manually.

We proposed a graphical interface in Python Qt that allows you to preconfigure all the post-treatments to be performed in order to automatically generate the requested images.

Our solution takes into account pre-established configurations for certain types of post-treatments that are regularly performed. Thanks to these configurations, the tool makes it possible to generate a hundred images in a very short time, of the order of a minute.

Our Mean Stress tool aims to automate a task that is particularly laborious to perform manually: the verification of all the criteria defined by classification societies (LR, ABS, DNV, BV, etc.).

The calculation of these criteria is based on the local averaging of the stresses exerted on the structure. The tool automatically performs these calculations, checks whether the criteria are validated or not, and generates a results report to the user.

Different criteria and different methods can be used during this post-treatment allowing a much more complete scan of the study than what can be done manually.

From a mesh of a structure, our Weld Detection tool makes it possible to automatically extract all the edges that represent the welds in the structure and to classify them into different groups in order to prepare for fatigue studies. We proposed an innovative algorithmic method based on the construction of a graph to extract these welds.

To perform this extraction, our method goes through several steps:

Step 1 — Adjacent cells are determined, i.e. cells sharing a common edge.

Step 2 — Calculate the angle between each pair of adjacent cells.

Step 3 — We build a graph: each mesh represents one node in the graph, and two nodes in the graph are linked if the pair of cells has a common edge.

Step 4 — We establish a form of connectivity according to the angle, thus allowing us to extract all the substructures that make up the mesh.

Step 5 — Finally, the welds that are at the intersection of these substructures are detected, and classified according to their geometric specificities.