OpenSees: Análisis Estructural No Lineal I

OpenSees: Advanced Nonlinear Structural Analysis with Cyclic Loading

Unlock the power of OpenSees, a leading open-source software developed at the University of California, for advanced nonlinear structural analysis. This course focuses on applying cyclic loading scenarios to accurately predict structural behavior, especially when dealing with deformations beyond the elastic range.

You'll learn to model and analyze structures using OpenSees by programming material properties, sections, elements, connections, and load patterns. Nonlinear structural analysis is crucial for realistic structural assessments, allowing you to understand how structures behave under extreme conditions.

Key topics covered include:

• Nonlinear Behavior Prediction: Gain insights into structural response when exceeding the linear elastic limit.
• Moment and Curvature Diagrams: Learn to generate critical diagrams for structural evaluation.
• Monocyclic (Pushover) Analysis: Perform pushover analysis to observe deformation and force development beyond the elastic range.
• Cyclic Analysis: Master cyclic analysis techniques, incorporating the nonlinear properties of materials for realistic simulations.

Fundamental concepts you'll master:

• Material Modeling: Understand different curve types for modeling concrete and steel behavior.
• Integration Algorithms: Explore various integration algorithms for accurate numerical solutions.
• Element Definition: Learn to define element coordinates and nodes.
• Section Definition: Define structural sections using the fiber method.
• Load Pattern Generation: Create realistic load patterns for your models.
• Model Analysis: Perform the OpenSees analysis.
• Result Postprocessing: Extract and interpret results using Excel for effective postprocessing.

This course provides a strong foundation for using OpenSees. Future modules will expand on these concepts to address more complex structural systems.

Prerequisites: A basic understanding of structural analysis and matrix methods is highly recommended. Familiarity with any programming language is a significant advantage.

Software: You will need to download the OpenSees software (free of charge) and a version of Excel for result analysis.