An enhanced topological analysis for Lamb waves based SHM methods

Topological data analysis (TDA) is a powerful and promising tool for data analysis, but yet not exploited enough. It is a multidimensional method which can extract the topological features contained in a given dataset. An original TDA-based method allowing to monitor the health of structures when equipped with piezoelectric transducers (PZTs) is introduced here. Using a Lamb wave based Structural Health Monitoring (SHM) approach, it is shown that with specific pre-processing of the measured time-series data, the TDA (persistent homology) for damage detection and classification can be greatly improved. The TDA tool is first applied directly in a traditional manner in order to use homology classes to assess damage. After that, another method based on slicing the temporal data is developed to improve the persistence homology perception and to leverage topological descriptors to discriminate different damages. The dataset used to apply both methods comes from experimental campaigns performed on aeronautical composite plates with embedded PZTs where different damage types have been investigated such as delamination, impacts and stiffness reduction. The proposed approach enables to consider a priori physical information and provides a better way to classify damages than the traditional TDA approach. In summary, this article demonstrates that manipulating the topological the features of PZTs time-series signals using TDA provides an efficient mean to separate and classify the damage natures and opens the way for further developments on the use of TDA in SHM

Data-Driven Modelling of Polyethylene Recycling under High-Temperature Extrusion

Two main problems are studied in this article. The first one is the use of the extrusion process for controlled thermo-mechanical degradation of polyethylene for recycling applications. The second is the data-based modelling of such reactive extrusion processes. Polyethylenes (high density polyethylene (HDPE) and ultra-high molecular weight polyethylene (UHMWPE)) were extruded in a corotating twin-screw extruder under high temperatures (350 °C < T < 420 °C) for various process conditions (flow rate and screw rotation speed). These process conditions involved a decrease in the molecular weight due to degradation reactions. A numerical method based on the Carreau-Yasuda model was developed to predict the rheological behaviour (variation of the viscosity versus shear rate) from the in-line measurement of the die pressure. The results were successfully compared to the viscosity measured from offline measurement assuming the Cox-Merz law. Weight average molecular weights were estimated from the resulting zero-shear rate viscosity. Furthermore, the linear viscoelastic behaviours (Frequency dependence of the complex shear modulus) were also used to predict the molecular weight distributions of final products by an inverse rheological method. Size exclusion chromatography (SEC) was performed on five samples, and the resulting molecular weight distributions were compared to the values obtained with the two aforementioned techniques. The values of weight average molecular weights were similar for the three techniques. The complete molecular weight distributions obtained by inverse rheology were similar to the SEC ones for extruded HDPE samples, but some inaccuracies were observed for extruded UHMWPE samples. The Ludovic® (SC-Consultants, Saint-Etienne, France) corotating twin-screw extrusion simulation software was used as a classical process simulation. However, as the rheo-kinetic laws of this process were unknown, the software could not predict all the flow characteristics successfully. Finally, machine learning techniques, able to operate in the low-data limit, were tested to build predicting models of the process outputs and material characteristics. Support Vector Machine Regression (SVR) and sparsed Proper Generalized Decomposition (sPGD) techniques were chosen to predict the process outputs successfully. These methods were also applied to material characteristics data, and both were found to be effective in predicting molecular weights. More precisely, the sPGD gave better results than the SVR for the zero-shear viscosity prediction. Stochastic methods were also tested on some of the data and showed promising results

Learning the Parametric Transfer Function of Unitary Operations for Real-Time Evaluation of Manufacturing Processes Involving Operations Sequencing

For better designing manufacturing processes, surrogate models were widely considered in the past, where the effect of different material and process parameters was considered from the use of a parametric solution. The last contains the solution of the model describing the system under study, for any choice of the selected parameters. These surrogate models, also known as meta-models, virtual charts or computational vademecum, in the context of model order reduction, were successfully employed in a variety of industrial applications. However, they remain confronted to a major difficulty when the number of parameters grows exponentially. Thus, processes involving trajectories or sequencing entail a combinatorial exposition (curse of dimensionality) not only due to the number of possible combinations, but due to the number of parameters needed to describe the process. The present paper proposes a promising route for circumventing, or at least alleviating that difficulty. The proposed technique consists of a parametric transfer function that, as soon as it is learned, allows for, from a given state, inferring the new state after the application of a unitary operation, defined as a step in the sequenced process. Thus, any sequencing can be evaluated almost in real time by chaining that unitary transfer function, whose output becomes the input of the next operation. The benefits and potential of such a technique are illustrated on a problem of industrial relevance, the one concerning the induced deformation on a structural part when printing on it a series of stiffeners

Catheter ablation of atrial tachyarrhythmias in patients with atrioventricular septal defect

AIMS: The incidence of atrial tachyarrhythmias is high in patients with atrioventricular septal defect (AVSD). No specific data on catheter ablation have been reported so far in this population. We aimed to describe the main mechanisms of atrial tachyarrhythmias in patients with AVSD and to analyse outcomes after catheter ablation. METHODS AND RESULTS: This observational multi-centric cohort study enrolled all patients with AVSD referred for catheter ablation of an atrial tachyarrhythmia at six tertiary centres from 2004 to 2022. The mechanisms of the different tachyarrhythmias targeted were described and outcomes were analysed. Overall, 56 patients (38.1 ± 17.4 years, 55.4% females) were included. A total of 87 atrial tachyarrhythmias were targeted (mean number of 1.6 per patient). Regarding main circuits involved, a cavo-annular isthmus-dependent intra-atrial re-entrant tachycardia (IART) was observed in 41 (73.2%) patients and an IART involving the right lateral atriotomy in 10 (17.9%) patients. Other tachyarrhythmias with heterogeneous circuits were observed in 13 (23.2%) patients including 11 left-sided and 4 right-sided tachyarrhythmias. Overall, an acute success was achieved in 54 (96.4%) patients, and no complication was reported. During a mean follow-up of 2.8 ± 3.8 years, 22 (39.3%) patients had at least one recurrence. Freedom from atrial tachyarrhythmia recurrences was 77.5% at 1 year. Among 15 (26.8%) patients who underwent repeated ablation procedures, heterogeneous circuits including bi-atrial and left-sided tachyarrhythmias were more frequent. CONCLUSION: In patients with AVSD, most circuits involve the cavo-annular isthmus, but complex mechanisms are frequently encountered in patients with repeated procedures. The acute success rate is excellent, although recurrences remain common during follow-up.</p

A population pharmacokinetic model for sertraline in women during the perinatal period-A contribution from the ConcePTION project.

AIMS Sertraline is frequently prescribed for mental health conditions in both pregnant and breastfeeding women. According to the limited available data, only small amounts of sertraline are transferred into human milk, yet with a large amount of unexplained interindividual variability. This study aimed to develop a population pharmacokinetic (popPK) model to describe the pharmacokinetics of sertraline during the perinatal period and explain interindividual variability. METHODS Pregnant women treated with sertraline were enrolled in the multicenter prospective cohort SSRI-Breast Milk study. A popPK model for sertraline maternal plasma and breast milk concentrations was developed and allowed estimating the milk-to-plasma ratio (MPR). An additional fetal compartment allowed cord blood concentrations to be described. Several covariates were tested for significance. Ultimately, model-based simulations allowed infant drug exposure through placenta and breast milk under various conditions to be predicted. RESULTS Thirty-eight women treated with sertraline were included in the study and provided 89 maternal plasma, 29 cord blood and 107 breast milk samples. Sertraline clearance was reduced by 42% in CYP2C19 poor metabolizers compared to other phenotypes. Doubling milk fat content increased the MPR by 95%. Simulations suggested a median daily infant dosage of 6.9 μg kg-1 after a 50 mg maternal daily dose, representing 0.95% of the weight-adjusted maternal dose. Median cord blood concentrations could range from 3.29 to 33.23 ng mL-1 after maternal daily doses between 25 and 150 mg. CONCLUSIONS Infant exposure to sertraline, influenced by CYP2C19 phenotype and breast milk fat content, remains low, providing reassurance regarding the use of sertraline during pregnancy and breastfeeding

Effect of forward speed on the level-crossing distribution of kinematic variables in multidirectional ocean waves

The influence of forward speed on stochastic free-surface crossing, in a Gaussian wave field, is investigated. The case of a material point moving with a constant forward speed is considered; the wave field is assumed stationary in time, and homogeneous in space. The focus is on up-crossing events, which are defined as the material point crossing the free surface, into the water domain. The effect of the Doppler shift (induced by the forward speed) on the up-crossing frequency, and the related conditional joint distribution of wave kinematic variables is analytically investigated. Some general trends are illustrated through different examples, where three kinds of wave direction distribution are considered: unidirectional, short-crested anisotropic, and isotropic. The way the developed approach may be used in the context of slamming on marine structures is briefly discussed

An analytical model of vertical water entry for 2D asymmetric bodies with flow separation

International audienceThe vertical water entry of asymmetric two-dimensional bodies with flow separation is considered. As long as there is no flow separation, linearised Wagner's theory combined with the Modified Logvinovich Model has been shown to provide computationally fast and reliable estimates of slamming loads during water entry. Tassin et al. (2014) introduced the Fictitious Body Continuation (FBC) concept as a way to extend the use of Wagner's theory to separated flow configurations, but they only considered symmetric bodies. In the present study, we investigate the ability of the FBC concept to provide accurate estimates of slamming loads for asymmetric bodies. In this case, flow separation may not occur simultaneously on both sides of the body. During an intermediate phase, slamming loads are governed by a competition between the local drop in pressure due to partial flow separation and the ongoing expansion of the wetted area. As a first benchmark for the model, we consider the water entry of an inclined flat plate and compare the FBC estimates with the results of a nonlinear model. Then, we consider the case of a foil and compare the FBC results with Computational Fluid Dynamics predictions. In both cases, we find that the FBC model is able to provide reliable estimates of the slamming loads

A Fictitious Body Continuation model for the vertical water entry of 2D asymmetric bodies with flow separation

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