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I. Barcelos Carneiro M Da R

29 records found

Bayesian system identification is increasingly used in Structural Health Monitoring (SHM) to infer unobservable parameters of a structure from sensor data. The use of spatially dense measurements, such as those from distributed fibre optic sensors, can further enhance the results ...
Welcome to the submodule on the Matrix Method for Statics, part of Unit 2 of CIEM5000 Course base Structural Engineering at Delft University of Technology.

This book contains the material for the course.
In this work, we extend a recent surrogate modeling approach, the Physically Recurrent Neural Network (PRNN), to include the effect of debonding at the fiber–matrix interface of composite materials. The core idea of the PRNN is to implement the exact material models from the micr ...
In this work, a hybrid physics-based data-driven surrogate model for the microscale analysis of heterogeneous material is investigated. The proposed model benefits from the physics-based knowledge contained in the constitutive models used in the full-order micromodel by embedding ...

Unifying creep and fatigue modeling of composites

A time-homogenized micromechanical framework with viscoplasticity and cohesive damage

A micromechanical model for simulating failure of unidirectional composites under cyclic loading has been developed and tested. To efficiently pass through the loading signal, a two-scale temporal framework with adaptive stepping is proposed, with a varying step size between macr ...

Micromechanics-based deep-learning for composites

Challenges and future perspectives

During the last few decades, industries such as aerospace and wind energy (among others) have been remarkably influenced by the introduction of high-performance composites. One challenge, however, for modeling and designing composites is the lack of computational efficiency of ac ...
In this work, the uncertainty associated with the finite element discretization error is modeled following the Bayesian paradigm. First, a continuous formulation is derived, where a Gaussian process prior over the solution space is updated based on observations from a finite elem ...
Simulating the mechanical response of advanced materials can be done more accurately using concurrent multiscale models than with single-scale simulations. However, the computational costs stand in the way of the practical application of this approach. The costs originate from mi ...

Physically recurrent neural networks for path-dependent heterogeneous materials

Embedding constitutive models in a data-driven surrogate

Driven by the need to accelerate numerical simulations, the use of machine learning techniques is rapidly growing in the field of computational solid mechanics. Their application is especially advantageous in concurrent multiscale finite element analysis (FE2) due to t ...
In this work we present a hybrid physics-based and data-driven learning approach to construct surrogate models for concurrent multiscale simulations of complex material behavior. We start from robust but inflexible physics-based constitutive models and increase their expressivity ...

Neural networks meet physics-based material models

Accelerating concurrent multiscale simulations of pathdependent composite materials

In a concurrent multiscale (FE2) modeling approach the complex microstructure of composite materials is explicitly modeled on a finer scale and nested to each integration point of the macroscale. However, such generality is often associated with exceedingly high computational cos ...

BIOS

An object-oriented framework for Surrogate-Based Optimization using bio-inspired algorithms

This paper presents BIOS (acronym for Biologically Inspired Optimization System), an object-oriented framework written in C++, aimed at heuristic optimization with a focus on Surrogate-Based Optimization (SBO) and structural problems. The use of SBO to deal with structural optimi ...
Polymers and polymer composites are negatively impacted by environmental ageing, reducing their service lifetimes. The uncertainty of the material interaction with the environment compromises their superior strength and stiffness. Validation of new composite materials and structu ...

Neural networks meet physics-based material models

Accelerating concurrent multiscale simulations of path-dependent composite materials

In a concurrent (FE2) multiscale modeling is an increasingly popular approach for modeling complex materials. As such, it is especially suited for modeling composites, as their complex microstructure can be explicitly modeled and nested to each integration point of the macroscale ...
Service lifetimes of polymers and polymer composites are impacted by environmental ageing. The validation of new composites and their environmental durability involves costly testing programs, thus calling for more affordable and safe alternatives, and modelling is seen as such a ...
Concurrent multiscale finite element analysis (FE2) is a powerful approach for high-fidelity modeling of materials for which a suitable macroscopic constitutive model is not available. However, the extreme computational effort associated with computing a nested micromo ...

Micromechanics-based surrogate models for the response of composites

A critical comparison between a classical mesoscale constitutive model, hyper-reduction and neural networks

Although being a popular approach for the modeling of laminated composites, mesoscale constitutive models often struggle to represent material response for arbitrary load cases. A better alternative in terms of accuracy is to use the FE2 technique to upscale microscopi ...
This work presents a reduced-order modeling framework that precludes the need for offline training and adaptively adjusts its lower-order solution space as the analysis progresses. The analysis starts with a fully-solved step and elements are clustered based on their strain respo ...
In this paper, a number of techniques used to accelerate the solution of finite element problems involving a large number of load cycles areexplored and applied to the micromechanical analysis of fiber-reinforced composites. The microscopic domain consists of unidirectional linea ...
This work investigates hygrothermal aging degradation of unidirectional glass/epoxy composite specimens through a combination of experiments and numerical modeling. Aging is performed through immersion in demineralized water. Interlaminar shear testes are performed after multiple ...