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International audience; Structural Health Monitoring (SHM) system offers new approaches to interrogate the integrity of structures. However, their reliability has still to be demonstrated an quantified to enable confidence transition from R&D to field implementation. In general, SHM algorithms performances are illustrated by topography study but it is not sufficient in a reliability assessment context. In the sense, that there is no quantification of the performance. To address this key issue, a dedicated maturation procedure is proposed in this paper. It is strongly inspired from the six sigma procedure for processes improvement to gradually improve SHM algorithms in order to reach the required maturity level. This paper presents the application of this procedure to a damage SHM localization algorithm as case study. To address this issue, finite element models and experimentation on the monitored structure have been used. It is concluded with a need of a new specific SHM algorithm intrinsic maturity scale. These maturity scales can be defined with respect to the functions of the considered SHM algorithm and the type of the used data.

The objective of this paper is to present the advantages of Model reference adaptive control (MRAC) motion cueing algorithm against the classical motion cueing algorithm in terms of biome- chanical reactions of the participants during the critical maneuvers like chicane in driving simu- lator real-time. This study proposes a method and an experimental validation to analyze the ves- tibular and neuromuscular dynamics responses of the drivers with respect to the type of the con- trol used at the hexapod driving simulator. For each situation, the EMG (electromyography) data were registered from arm muscles of the drivers (flexor carpi radialis, brachioradialis). In addi- tion, the roll velocity perception thresholds (RVT) and roll velocities (RV) were computed from the real-time vestibular level measurements from the drivers via a motion-tracking sensor. In or- der to process the data of the EMG and RVT, Pearson’s correlation and a two-way ANOVA with a significance level of 0.05 were assigned. Moreover, the relationships of arm muscle power and roll velocity with vehicle CG (center of gravity) lateral displacement were analyzed in order to assess the agility/alertness level of the drivers as well as the vehicle loss of control characteristics with a confidence interval of 95%. The results showed that the MRAC algorithm avoided the loss of adhe- sion, loss of control (LOA, LOC) more reasonably compared to the classical motion cueing algo- rithm. According to our findings, the LOA avoidance decreased the neuromuscular-visual cues lev- el conflict with MRAC algorithm. It also revealed that the neuromuscular-vehicle dynamics conflict has influence on visuo-vestibular conflict; however, the visuo-vestibular cue conflict does not in- fluence the neuromuscular-vehicle dynamics interactions.; International audience; The objective of this paper is to present the advantages of Model reference adaptive control (MRAC) motion cueing algorithm against the classical motion cueing algorithm in terms of biome- chanical reactions of the participants during the critical maneuvers like chicane in driving simu- lator real-time. This study proposes a method and an experimental validation to analyze the ves- tibular and neuromuscular dynamics responses of the drivers with respect to the type of the con- trol used at the hexapod driving simulator. For each situation, the EMG (electromyography) data were registered from arm muscles of the drivers (flexor carpi radialis, brachioradialis). In addi- tion, the roll velocity perception thresholds (RVT) and roll velocities (RV) were computed from the real-time vestibular level measurements from the drivers via a motion-tracking sensor. In or- der to process the data of the EMG and RVT, Pearson’s correlation and a two-way ANOVA with a significance level of 0.05 were assigned. Moreover, the relationships of arm muscle power and roll velocity with vehicle CG (center of gravity) lateral displacement were analyzed in order to assess the agility/alertness level of the drivers as well as the vehicle loss of control characteristics with a confidence interval of 95%. The results showed that the MRAC algorithm avoided the loss of adhe- sion, loss of control (LOA, LOC) more reasonably compared to the classical motion cueing algo- rithm. According to our findings, the LOA avoidance decreased the neuromuscular-visual cues lev- el conflict with MRAC algorithm. It also revealed that the neuromuscular-vehicle dynamics conflict has influence on visuo-vestibular conflict; however, the visuo-vestibular cue conflict does not in- fluence the neuromuscular-vehicle dynamics interactions.

The purpose of this study was to highlight the technical and economic issues arising in lithium-ion cells for automotive applications, and to indicate some potential solutions to lower the cost. This topic has already been the subject of some studies, but, although of primary importance, the role on cost of a cell design parameter, the electrode coating thickness, has rarely been described. This study intends to explore particularly the influence of this parameter. To do so, the cost of cells with four positive electrode materials (NMC, NCA, LFP, and LMO), and the same negative electrode material are compared at several electrode thickness. The cost of these cells is computed using an innovative model and varies between 230 and 400 $ per kWh. With the assumptions used, it appears that the potential savings resulting from doubling the electrode coating thickness from 50 to 100 lm at a given porosity represent roughly 25% of the cell cost. The electrode coating thickness emerges as an essential parameter for an unbiased cells cost comparison. This article gives a view ofof the current lithium-ion cells costs, and provides guidelines to lower cells cost. ANRT CIFRE

Arts et Metiers ParisTech built the SAAM driving simulator in collaboration with Renault and Grand Chalon. This research study was realized in the framework of the geDriver project.; International audience; This paper deals with driving simulation and in particular with the important issue of motion sickness. The paper proposes a methodology to evaluate the objective illness rating metrics deduced from the motion sickness dose value and questionnaires for both a static simulator and a dynamic simulator. Accelerations of the vestibular cues (head movements) of the subjects were recorded with and without motion platform activation. In order to compare user experiences in both cases, the head-dynamics-related illness ratings were computed from the obtained accelerations and the motion sickness dose values. For the subjective analysis, the principal component analysis method was used to determine the conflict between the subjective assessment in the static condition and that in the dynamic condition. The principal component analysis method used for the subjective evaluation showed a consistent difference between the answers given in the sickness questionnaire for the static platform case from those for the dynamic platform case. The two-tailed Mann-Whitney U test shows the significance in the differences between the self-reports to the individual questions. According to the two-tailed Mann-Whitney U test, experiencing nausea (p = 0.019 < 0.05) and dizziness (p = 0.018 < 0.05) decreased significantly from the static case to the dynamic case. Also, eye strain (p = 0.047 < 0.05) and tiredness (p = 0.047 < 0.05) were reduced significantly from the static case to the dynamic case. For the perception fidelity analysis, the Pearson correlation with a confidence interval of 95% was used to study the correlations of each question with the x illness rating component IRx, the y illness rating component IRy, the z illness rating component IRz and the compound illness rating IRtot. The results showed that the longitudinal head dynamics were the main element that induced discomfort for the static platform, whereas vertical head movements were the main factor to provoke discomfort for the dynamic platform case. Also, for the dynamic platform, lateral vestibular-level dynamics were the major element which caused a feeling of fear.