admin

Developing User Material Subroutines in CALCULIX: 2 Compiling CALCULIX

This 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 step-by-step of the procedure that we have followed, as an example of the process. Move to /usr/local Edit Make.inc Change: Make the library Unpack Modify […]

Developing User Material Subroutines in CALCULIX: 2 Compiling CALCULIX Leer más »

Developing User Material Subroutines in CALCULIX: 1 A Comprehensive Guide with UMAT Structure Examples in ABAQUS

This 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 the User Material (UMAT). These subroutines allow for defining complex material behaviors not included in the material models library. In this article, we provide an overview of

Developing User Material Subroutines in CALCULIX: 1 A Comprehensive Guide with UMAT Structure Examples in ABAQUS 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

This 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 in collaboration with the research group of Professor Jesús Rodríguez-Pérez (DIMME, Grupo de Durabilidad e Integridad Mecánica de Materiales Estructurales, Escuela Superior de Ciencias Experimentales

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 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

Recently, 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 Integridad Mecánica de Materiales Estructurales, Escuela Superior de Ciencias Experimentales y Tecnología, Universidad Rey Juan Carlos) in the European Conference of Fracture 2024 We share

Numerical code corresponding to our publication titled: Bayesian analysis of fracture of polyamide 12 U-notched specimens. Part -1 Bayesian non-linear regression Leer más »

Cement and Concrete Modeling with VCCTL: A Step-by-Step Guide

Ever 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 allows you to model and analyze the mechanical properties of concrete before it’s even mixed. Let’s dive into how you can leverage VCCTL to develop

Cement and Concrete Modeling with VCCTL: A Step-by-Step Guide Leer más »

Bayesian Fitting of Data from Three Groups with Parallel Linear Regression Lines

When 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 from three different groups where each group can be described by a linear regression model, and the three regression lines are parallel).

Bayesian Fitting of Data from Three Groups with Parallel Linear Regression Lines Leer más »

Programming a Bayesian Statistical Fit in Python for Linear Regression

Bayesian 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 perform a Bayesian fit for linear regression using Python, with the goal of estimating the model parameters while quantifying uncertainty. This tutorial describes step by

Programming a Bayesian Statistical Fit in Python for Linear Regression Leer más »