Publications

Progress in hydrogen fuel powered systems has been propelled by the implementation of secure, reliable, and cost-effective hydrogen storage and transportation technologies. The fourth category, distinguished by a polymer liner serving as a hydrogen diffusion barrier, fully encapsulated within a fiber-reinforced composite to bestow structural integrity, has garnered substantial attention from the automotive industry due to its lightweight nature and rational manufacturing process. The method of rotomolding has sparked interest among manufacturers due to its capability to directly bond the metallic component to the polymer substrate, specifically the liner, thus negating the need for welding and its attendant imperfections. In fact, a pivotal facet of fourth-generation hydrogen storage systems revolves around the interface connection between the polymer liner and the metallic boss, posing as a structural Achilles' heel. For the study's purposes, a scaled-down demonstrator was fabricated using rotomolding in which a nozzle-liner interface mimics the boss-liner interface of the actual system. This demonstrator was designed to facilitate the mechanical characterization of the interface under quasi-static and fatigue loading. The thermal cycling phases of rotational molding and the surface treatments undertaken have been optimized in order to enhance direct adhesion within the metal-polymer interface. This study commences by assessing the efficacy of two treatments (sandblasting and flaming) applied to the aluminum nozzle surface. Subsequently, we explore the adhesion microstructural and mechanical characteristics of the treated nozzle onto a medium-density polyethylene polymer (liner). Lastly, we delve into an exploration of the damage and fatigue behaviors endemic to the metal-polymer interface region. The obtained Wöhler curves disclose a linear trend for the metal-polymer interface. Moreover, the metal-polymer interface evinces heightened resilience against damage and fracture for sandblasted interfaces. This inquiry underscores the potency of innovative polymer-metal interfaces treatment in amplifying the reliability and robustness of hydrogen storage technology.

Nowadays, Deep Learning (DL) techniques are increasingly employed in industrial applications. This paper investigate the development of data-driven models for two use cases: Additive Manufacturing-driven Topology Optimization and Structural Health Monitoring (SHM). We first propose an original data-driven generative method that integrates the mechanical and geometrical constraints concurrently at the same conceptual level and generates a 2D design accordingly. In this way, it adapts the geometry of the design to the manufacturing criteria, allowing the designer better interpretation and avoiding being stuck in a timeconsuming loop of drawing the CAD and testing its performance. On the other hand, SHM technique is dedicated to the continuous and non-invasive monitoring of structures integrity, ensuring safety and optimal performances through on-site real-time measurements. We propose in this work new ways of structuring data that increase the accuracy of data driven SHM algorithms and that are based on the physical knowledge related with the structure to be inspected. We focus our study on the damage classification step within the aeronautic context, where the primary objective is to distinguish between different damage types in composite.

In this paper, we present a novel approach for the preparation of reduced graphene oxide (rGO) through the radiolytical reduction of commercial graphene oxide (GO). The method is highly efficient and environmentally friendly compared to other synthetic routes. We conducted a detailed study on the influence of absorbed doses during the synthesis process. The reduction process for the production of rGO is induced by the radiolysis of water at ambient temperature and pressure, confirmed using several sophisticated techniques. Our results demonstrate the efficiency of the radiolytical process compared to conventional methods of GO reduction. The C/O ratio increased from 3.3 (GO) to 11.2 (rGO), surpassing those of other reduction methods. Additionally, the intensity ratio of D and G bands (ID/IG) increased for rGO due to an increase in order by reduction, implying the restoration of π-conjugation. Furthermore, the thermal stability of GO improved upon irradiation. Electrochemical measurements finally showed that our rGO exhibited a specific capacitance of 229.3 F g−1, indicating its high potential as a candidate for energy storage applications. © 2024 The Royal Society of Chemistry.

X-ray Laue microdiffraction aims to characterize microstructural and mechanical fields in polycrystalline specimens at the sub-micrometre scale with a strain resolution of ∼10−4. Here, a new and unique Laue microdiffraction setup and alignment procedure is presented, allowing measurements at temperatures as high as 1500 K, with the objective to extend the technique for the study of crystalline phase transitions and associated strain-field evolution that occur at high temperatures. A method is provided to measure the real temperature encountered by the specimen, which can be critical for precise phase-transition studies, as well as a strategy to calibrate the setup geometry to account for the sample and furnace dilation using a standard α-alumina single crystal. A first application to phase transitions in a polycrystalline specimen of pure zirconia is provided as an illustrative example.

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.

Introduction Our objective was to assess abnormalities of the odontoid-hip axis (OD-HA) angle in a mild scoliotic population to determine whether screening for malalignment would help predict the distinction between progressive and stable adolescent idiopathic scoliosis (AIS) at early stage. Materials and methods All patients (non-scoliotic and AIS) underwent a biplanar X-ray between 2013 and 2020. In AIS, inclusion criteria were Cobb angle between 10° and 25°; Risser sign lower than 3; age higher than 10 years; and no previous treatment. A 3D spine reconstruction was performed, and the OD-HA was computed automatically. A reference corridor for OD-HA values in non-scoliotic subjects was calculated as the range [5th–95th percentiles]. A severity index, helping to distinguish stable and progressive AIS, was calculated and weighted according to the OD-HA value. Results Eighty-three non-scoliotic and 205 AIS were included. The mean coronal and sagittal OD-HA angles in the non-scoliotic group were 0.2° and −2.5°, whereas in AIS values were 0.3° and −0.8°, respectively. For coronal and sagittal OD-HA, 27.5% and 26.8% of AIS were outside the reference corridor compared with 10.8% in non-scoliotic (OR = 3.1 and 3). Adding to the severity index a weighting factor based on coronal OD-HA, for thoracic scoliosis, improved the positive predictive value by 9% and the specificity by 13%. Conclusion Analysis of OD-HA suggests that AIS patients are almost three times more likely to have malalignment compared with a non-scoliotic population. Furthermore, analysis of coronal OD-HA is promising to help the clinician distinguish between stable and progressive thoracic scoliosis.

Worker safety and productivity are crucial for effective job management. Interruptions to an individual’s work environment and their impact on mental health can have adverse effects. One prospective instrument for assessing and calculating an individual’s mental state in an interrupted scenario and cognitive demand levels is the use of physiological computing devices in conjunction with behavioral and subjective measurements. This study sought to address how to gather and compute data on individuals’ cognitive states in interrupted work settings through critical analysis. Thirty-three papers were considered after the literature search and selection procedure. This descriptive study is conducted from three perspectives: parameter measurement, research design, and data analysis. The variables evaluated were working memory, stress, emotional state, performance, and resumption lag. The subject recruitment, experimental task design, and measurement techniques were examined from the standpoint of the experimental design. Data analysis included computing and cognitive pre-processing. Four future research directions are suggested to address the shortcomings of the present studies. This study offers suggestions for researchers on experiment planning and using computing to analyze individuals’ cognitive states during interrupted work scenarios. Additionally, it offers helpful recommendations for organizing and conducting future research.

This systematic review provides a comprehensive analysis of studies that use electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS) to investigate how acute stress affects decision-making processes. The primary goal of this systematic review was to examine the influence of acute stress on decision making in challenging or stressful situations. Furthermore, we aimed to identify the specific brain regions affected by acute stress and explore the feature extraction and classification methods employed to enhance the detection of decision making under pressure. Five academic databases were carefully searched and 27 papers that satisfied the inclusion criteria were found. Overall, the results indicate the potential utility of EEG and fNIRS as techniques for identifying acute stress during decision-making and for gaining knowledge about the brain mechanisms underlying stress reactions. However, the varied methods employed in these studies and the small sample sizes highlight the need for additional studies to develop more standardized approaches for acute stress effects in decision-making tasks. The implications of the findings for the development of stress induction and technology in the decision-making process are also explained.

In modern manufacturing, machining remains a vital process for complex mechanical components. In particular, the aerospace industry extensively employs high-feed milling techniques to machine complex geometries from nickel-based superalloys. This study focuses on the analysis and modeling of high-feed milling for Inconel 718 in 2.5-axis machining. Its objective is to develop a generalized model of high-feed milling that enables the prediction of surface topography. The proposed model integrates crucial geometric parameters of the tool and its exact kinematic within the machine, along with tool and machine deflections caused by cutting forces. A key novelty of this research lies in its capability to determine surface topography and its quality based on a generalized model, representing significant progress in the field of high-feed milling. To validate the model, experimental efforts are measured to characterize the cutting forces and system deflections during machining. The developed approach demonstrates its ability to model surface topography and to predict surface roughness. It also highlights the influence of tool and machine deflection on surface quality. This research contributes to the advancement of the application of high-feed milling in aerospace manufacturing by enhancing machining capabilities and improving part quality.

Study design: Multicentric retrospective. Objective: The study of center of mass (COM) locations (i.e. barycentremetry) can help us understand postural alignment. This study goal was to determine relationships between COM locations and global postural alignment X-ray parameters in healthy subjects. The second objective was to determine the impact on spinopelvic alignment of increased distance between anterior body envelope and spine at lumbar apex level. Summary of background data: Unexplored relationship between COM location and spinopelvic parameters. Methods: This study included healthy volunteers with full-body biplanar radiograph including body envelope reconstruction, allowing the estimation of COM location. The following parameters were analyzed: lumbar lordosis (LL), thoracic kyphosis (TK), cervical lordosis (CL), pelvic tilt (PT), Sacro-femoral angle (SFA), Knee flexion angle (KFA), sagittal odontoid-hip axis angle (ODHA). The following COM in the sagittal plane were located: whole body, at thoracolumbar inflexion point, and body segment above TK apex. The body envelope reconstruction also provided the distance between anterior skin and the LL apex vertebral body center (“SV-L distance”). Results: This study included 124 volunteers, with a mean age of 44±19.3. Multivariate analysis confirmed posterior translation of COM above TK apex with increasing LL (P=0.002) through its proximal component, and posterior shift of COM at inflexion point with increasing TK (P=0.008). Increased SV-L distance was associated with greater ODHA (r=0.4) and more anterior body COM (r=0.8), caused by increased TK (r=0.2) and decreased proximal and distal LL (both r=0.3), resulting in an augmentation in SFA (r=0.3) (all P<0.01). Conclusions: Barycentremetry showed that greater LL was associated with posterior shift of COM above thoracic apex while greater TK was correlated with more posterior COM at inflexion point. Whole-body COM was strongly correlated with ODHA. This study also exhibited significant alignment disruption associated with increased abdominal volume, with compensatory hip extension. Level of evidence: II