Bridging Proper Orthogonal Decomposition methods and augmented Newton-Krylov algorithms: an adaptive model order reduction for highly nonlinear mechanical problems

This article describes a bridge between POD-based model order reduction techniques and the classical Newton/Krylov solvers. This bridge is used to derive an efficient algorithm to correct, "on-the-fly", the reduced order modelling of highly nonlinear problems undergoing strong topological changes. Damage initiation problems are addressed and tackle via a corrected hyperreduction method. It is shown that the relevancy of reduced order model can be significantly improved with reasonable additional costs when using this algorithm, even when strong topological changes are involved

Model reduction by separation of variables: A comparison between hierarchical model reduction and proper generalized decomposition

Hierarchical Model reduction and Proper Generalized Decomposition both exploit separation of variables to perform a model reduction. After setting the basics, we exemplify these techniques on some standard elliptic problems to highlight pros and cons of the two procedures, both from a methodological and a numerical viewpoint

A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning

Progress in biomechanical modelling of human soft tissue is the basis for the development of new clinical applications capable of improving the diagnosis and treatment of some diseases (e.g. cancer), as well as the surgical planning and guidance of some interventions. The finite element method (FEM) is one of the most popular techniques used to predict the deformation of the human soft tissue due to its high accuracy. However, FEM has an associated high computational cost, which makes it difficult its integration in real-time computer-aided surgery systems. An alternative for simulating the mechanical behaviour of human organs in real time comes from the use of machine learning (ML) techniques, which are much faster than FEM. This paper assesses the feasibility of ML methods for modelling the biomechanical behaviour of the human liver during the breathing process, which is crucial for guiding surgeons during interventions where it is critical to track this deformation (e.g. some specific kind of biopsies) or for the accurate application of radiotherapy dose to liver tumours. For this purpose, different ML regression models were investigated, including three tree-based methods (decision trees, random forests and extremely randomised trees) and other two simpler regression techniques (dummy model and linear regression). In order to build and validate the ML models, a labelled data set was constructed from modelling the deformation of eight ex-vivo human livers using FEM. The best prediction performance was obtained using extremely randomised trees, with a mean error of 0.07 mm and all the samples with an error under 1 mm. The achieved results lay the foundation for the future development of some real-time software capable of simulating the human liver deformation during the breathing process during clinical interventions.This work has been funded by the Spanish Ministry of Economy and Competitiveness (MINECO) through research projects TIN2014-52033-R and DPI2013-40859-R, both also supported by European FEDER funds. The authors acknowledge the kind collaboration of the personnel from the hospital involved in the research.Lorente, D.; Martínez-Martínez, F.; Rupérez Moreno, MJ.; Lago, MA.; Martínez-Sober, M.; Escandell-Montero, P.; Martínez-Martínez, JM.... (2017). A framework for modelling the biomechanical behaviour of the human liver during breathing in real time using machine learning. Expert Systems with Applications. 71:342-357. doi:10.1016/j.eswa.2016.11.037S3423577

Application of hydroxyapatite nanoparticles in development of an enhanced formulation for delivering sustained release of triamcinolone acetonide

Saeid Koocheki1, Sayed Siavash Madaeni1, Parisa Niroomandi21Membrane Research Center, Chemical Engineering Department, Razi University, Kermanshah, Iran; 2Exir Pharmaceutical Co, Lorestan, Boroujerd, IranAbstract: We report an analysis of in vitro and in vivo drug release from an in situ formulation consisting of triamcinolone acetonide (TR) and poly(D,L-lactide-co-glycolide) (PLGA) and the additives glycofurol (GL) and hydroxyapatite nanoparticles (HA). We found that these additives enhanced drug release rate. We used the Taguchi method to predict optimum formulation variables to minimize the initial burst. This method decreased the burst rate from 8% to 1.3%. PLGA-HA acted as a strong buffer, thereby preventing tissue inflammation at the injection site caused by the acidic degradation products of PLGA. Characterization of the optimized formulation by a variety of techniques, including scanning electron microscopy, X-ray diffraction, differential scanning calorimetry, and Fourier transform near infrared spectroscopy, revealed that the crystalline structure of TR was converted to an amorphous form. Therefore, this hydrophobic agent can serve as an additive to modify drug release rates. Data generated by in vitro and in vivo experiments were in good agreement.Keywords: triamcinolone acetonide, glycofurol, hydroxyapatite nanoparticle, PLG

The history of design guidelines and details of reinforced concrete column in New Zealand

Existing New Zealand (NZ) building stock contains a significant number of structures designed prior to 1995 with non-ductile reinforced concrete (RC) columns. Recent earthquakes and research show that columns with such details perform poorly when subjected to seismic demand, losing gravity load carrying capacity at drift levels lower than the expected one. Therefore, in order to have a better understanding of existing RC columns in NZ, the history of these elements is investigated in this paper. The evolution of RC column design guidelines in NZ standards since the 1970s is scrutinized. For this purpose, a number of RC columns from Christchurch buildings built prior to 1995 are assessed using the current code of practice

Performance based assessment of FRP-retrofitted existing RC frames

In recent years, performance based design has become universally acceptable in seismic assessment of structures. Using this design method, performance of existing and retrofitted RC buildings can be evaluated based on the criteria suggested by ATC-40 and FEMA-356 using nonlinear pushover analysis. In this paper, performance of an FRP-retrofitted RC frame is assessed and the result is compared with steel-braced frames and unstrengthened moment resisting frames. The strong-column weak-beam principal is employed in this study. Firstly, the flexural stiffness of FRP-retrofitted joints of an existing RC ordinary moment resisting frame is determined using nonlinear finite element analysis. It is then implemented into a mathematical model for the web-bonded FRP-retrofitted frame developed by the first two authors. Subsequently, the base frame and retrofitted frames (both steel-braced and FRP-retrofitted) are analysed using nonlinear pushover analysis method. Finally, the seismic performance of the FRP retrofitted frame is compared with the corresponding base frame and steel-braced frames reported by others. The results show that the improvement in ductility and performance level of the existing RC frames is better for frames retrofitted with FRPs than the steel-braced systems

An analytical method to identify reinforced concrete walls prone to out-of-plane shear failure

One of the failure modes that got the attention of researchers in the 2011 February New Zealand earthquake was the collapse of a key supporting structural wall of Grand Chancellor Hotel in Christchurch which failed in a brittle manner. However, until now this failure mode has been still a bit of a mystery for the researchers in the field of structural engineering. Moreover, there is no method to identify, assess and design the walls prone to such failure mode. Following the recent break through regarding the mechanism of this failure mode based on experimental observations (out-of-plane shear failure), a numerical model that can capture this failure was developed using the FE software DIANA. A comprehensive numerical parametric study was conducted to identify the key parameters contributing to the development of out-of-plane shear failure in reinforced concrete (RC) walls. Based on the earthquake observations, experimental and numerical studies conducted by the authors of this paper, an analytical method to identify walls prone to out-of-plane shear failure that can be used in practice by engineers is proposed. The method is developed based on the key parameters affecting the seismic performance of RC walls prone to out-of-plane shear failure and can be used for both design and assessment purpose

Experimental study on the effects of bi-directional loading pattern on rectangular reinforced concrete walls

In this experimental study, three identical reinforced concrete (RC) walls were tested under three different lateral loading patterns. These loading patterns were cyclic in-plane, skewed with 45° angle and clover leaf. The main objective was to investigate the effects of these bi-directional loading patterns on the seismic behavior of slender rectangular RC walls. The results showed significant increase in tensile and compressive strains in concrete and longitudinal bars that led to earlier cover concrete spalling and bar buckling in the specimens subjected to bi-directional loading. The neutral axis depth and compression zone were found to be substantially larger when subjected to bi-directional loading and this led to the occurrence of concrete crushing and bar buckling in the web. Moreover, lateral instability failure triggered earlier in the specimens under bi-directional loading, as a result of reduction of out-of-plane stiffness of the wall. However, bi-directional loading did not significantly increase out-of-plane buckling of the wall in terms of out-of-plane displacement. In-plane and out-of-plane shear cracks formed in one of the specimens subjected to bi-directional loading, whereas the same wall under in-plane loading developed only flexural cracks. It was also found that in-plane shear deformation was larger when the wall was subjected to bi-directional loading. The results of this experimental study emphasize the need for further investigation of the effects of bi-directional loading on RC structural walls

Rectangular RC walls under bi-directional loading: Recent experimental and numerical findings

Following the recent earthquakes in Chile (2010) and New Zealand (2010/2011), peculiar failure modes were observed in Reinforced Concrete (RC) walls. These observations have raised a global concern on the contribution of bi-directional loading to these failure mechanisms. One of the failure modes that could potentially result from bidirectional excitations is out-of-plane shear failure. In this paper an overview of the recent experimental and numerical findings regarding out-of-plane shear failure in RC walls are presented. The numerical study presents the Finite Element (FE) simulation of wall D5-6 from the Grand Chancellor Hotel that failed in shear in the out-of-plane direction in the February 2011 Christchurch earthquake. The main objective of the numerical study was to investigate the reasons for this failure mode. The experimental campaign includes the recent experiments conducted in the Structural Engineering Laboratory of the University of Canterbury. The experimental study included three rectangular slender RC walls designed based on NZS3101: 2006-A3 (2017) for three different ductility levels, namely: nominally ductile, limited ductile and ductile. The numerical results showed that high axial load combined with bi-directional loading caused the out-of-plane shear failure in wall D5-6 from the Grand Chancellor Hotel. This was also confirmed and further investigated in the experimental phase of the study