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Notas técnicas del equipo de AMS: subrutinas de material, modelización numérica y métodos para la caracterización de materiales.
- Developing User Material Subroutines in CALCULIX: 4 UMAT neural network exampleIn this post, we explore how to integrate a neural network in a user material subroutine (UMAT) for CalculiX. The main idea is that the material’s plastic behavior is learned… Leer más: Developing User Material Subroutines in CALCULIX: 4 UMAT neural network example
- Developing User Material Subroutines in CALCULIX: 3 Converting ABAQUS UMAT into CALCULIX UMATConverting user material subroutines from ABAQUS to CALCULIX can significantly boost flexibility in open-source finite element simulations. Thanks to the ABAQUS UMAT examples shared on GitHub and similar platforms, it… Leer más: Developing User Material Subroutines in CALCULIX: 3 Converting ABAQUS UMAT into CALCULIX UMAT
- Developing User Material Subroutines in CALCULIX: 2 Compiling CALCULIXThis blog explains how to compile CALCULIX. This is a critical point required for introducing new user subroutines. The blog is not a comprehensive guide; it is only a description… Leer más: Developing User Material Subroutines in CALCULIX: 2 Compiling CALCULIX
- Developing User Material Subroutines in CALCULIX: 1 A Comprehensive Guide with UMAT Structure Examples in ABAQUSThis blog initiates a series of post about creating user material subroutines, with illustrative examples. Finite element software, as ABAQUS or CALCULIX supports advanced material modeling through user-defined subroutines, specifically… Leer más: Developing User Material Subroutines in CALCULIX: 1 A Comprehensive Guide with UMAT Structure Examples in ABAQUS
- Numerical code corresponding to our publication titled: Bayesian analysis of fracture of polyamide 12 U-notched specimens. Part -2 Model selection based on Bayesian StatisticsThis blog is the second part of our series, where we share the Python code used in our paper titled: Bayesian Analysis of Fracture of Polyamide 12 U-Notched Specimens, developed… Leer más: Numerical code corresponding to our publication titled: Bayesian analysis of fracture of polyamide 12 U-notched specimens. Part -2 Model selection based on Bayesian Statistics
- Numerical code corresponding to our publication titled: Bayesian analysis of fracture of polyamide 12 U-notched specimens. Part -1 Bayesian non-linear regressionRecently, we have presented a paper titled: Bayesian analysis of fracture of polyamide 12 U-notched specimens, in collaboration with the group of Professor Jesús Rodríguez-Pérez (DIMME, Grupo de Durabilidad e… Leer más: Numerical code corresponding to our publication titled: Bayesian analysis of fracture of polyamide 12 U-notched specimens. Part -1 Bayesian non-linear regression
- Cement and Concrete Modeling with VCCTL: A Step-by-Step GuideEver wondered how engineers and researchers can test the strength and durability of concrete before it’s even mixed? Enter VCCTL (Virtual Cement and Concrete Testing Laboratory), a powerful tool that… Leer más: Cement and Concrete Modeling with VCCTL: A Step-by-Step Guide
- Bayesian Fitting of Data from Three Groups with Parallel Linear Regression LinesWhen fitting data distributed across multiple groups, Bayesian modeling offers a powerful approach to account for uncertainty in parameter estimation. In this blog, we’ll walk through how to fit data… Leer más: Bayesian Fitting of Data from Three Groups with Parallel Linear Regression Lines
- Programming a Bayesian Statistical Fit in Python for Linear RegressionBayesian statistical fitting is a powerful technique for data analysis that allows us to incorporate prior information and update it with observed evidence. In this blog, we’ll explain how to… Leer más: Programming a Bayesian Statistical Fit in Python for Linear Regression