Modal characterization of the ASCIE segmented optics testbed: New algorithms and experimental results

New frequency response measurement procedures, on-line modal tuning techniques, and off-line modal identification algorithms are developed and applied to the modal identification of the Advanced Structures/Controls Integrated Experiment (ASCIE), a generic segmented optics telescope test-bed representative of future complex space structures. The frequency response measurement procedure uses all the actuators simultaneously to excite the structure and all the sensors to measure the structural response so that all the transfer functions are measured simultaneously. Structural responses to sinusoidal excitations are measured and analyzed to calculate spectral responses. The spectral responses in turn are analyzed as the spectral data become available and, which is new, the results are used to maintain high quality measurements. Data acquisition, processing, and checking procedures are fully automated. As the acquisition of the frequency response progresses, an on-line algorithm keeps track of the actuator force distribution that maximizes the structural response to automatically tune to a structural mode when approaching a resonant frequency. This tuning is insensitive to delays, ill-conditioning, and nonproportional damping. Experimental results show that is useful for modal surveys even in high modal density regions. For thorough modeling, a constructive procedure is proposed to identify the dynamics of a complex system from its frequency response with the minimization of a least-squares cost function as a desirable objective. This procedure relies on off-line modal separation algorithms to extract modal information and on least-squares parameter subset optimization to combine the modal results and globally fit the modal parameters to the measured data. The modal separation algorithms resolved modal density of 5 modes/Hz in the ASCIE experiment. They promise to be useful in many challenging applications

The multiplicative property characterizes ℓp\ell_p and LpL_p norms

We show that $\ell_p$ norms are characterized as the unique norms which are both invariant under coordinate permutation and multiplicative with respect to tensor products. Similarly, the $L_p$ norms are the unique rearrangement-invariant norms on a probability space such that $\|X Y\|=\|X\|\cdot\|Y\|$ for every pair $X,Y$ of independent random variables. Our proof relies on Cram\'er's large deviation theorem.Comment: 8 pages, 1 figur

Decision with Bayesian network in the concurrent faults event

The purpose of this article is to present a new method for process diagnosis with Bayesian network. The interest of this method is to propose a new structure of Bayesian network allowing to diagnose a system with the model-based framework or with the data-driven framework. A particular interest of the proposed approach is the use of continuous nodes in the network in order to evaluate the status of the process. The effectiveness and performances of the method are illustrated on a heating water process corrupted by various faults

Using Bayesian networks for decision in the simultaneous faults case

The purpose of this article is to present a new method for process diagnosis with Bayesian network. The interest of this method is to propose a new structure of Bayesian network allowing to diagnose a system with the model-based framework or with the data-driven framework. A particular interest of the proposed approach is the use of continuous nodes in the network in order to evaluate the status of the process. The effectiveness and performances of the method are illustrated on a heating water process corrupted by various faults

Fracture properties characterization of nuclear fuel using micro-cantilever bending

International audienc

A complementary approach to estimate the internal pressure of fission gas bubbles by SEM-SIMS-EPMA in irradiated nuclear fuels

International audienceThe behaviour of gases produced by fission is of great importance for nuclear fuel in operation. Within this context, a decade ago, a general method for the characterisation of the fission gas including gas bubbles in an irradiated UO$_2$ nuclear fuel was developed and applied to determine the bubbles internal pressure. The method consists in the determination of the pressure, over a large population of bubbles, using three techniques: SEM, EPMA and SIMS. In this paper, a complementary approach using the information given by the same techniques is performed on an isolated bubble under the surface and is aiming for a better accuracy compared to the more general measurement of gas content. SEM and EPMA enable the detection of a bubble filled with xenon under the surface. SIMS enables the detection of the gas filling the bubble. The quantification is achieved using the EPMA data as reference at positions where no or nearly no bubbles are detected

LPV subspace identification for robust fault detection using a set-membership approach: Application to the wind turbine benchmark

This paper focuses on robust fault detection for Linear Parameter Varying (LPV) systems using a set-membership approach. Since most of models which represent real systems are subject to modeling errors, standard fault detection (FD) LPV methods should be extended to be robust against model uncertainty. To solve this robust FD problem, a set-membership approach based on an interval predictor is used considering a bounded description of the modeling uncertainty. Satisfactory results of the proposed approach have been obtained using several fault scenarios in the pitch subsystem considered in the wind turbine benchmark introduced in IFAC SAFEPROCESS 2009.Postprint (author's final draft

Multicentre, prospective, double-blind, randomised controlled clinical trial comparing different non-opioid analgesic combinations with morphine for postoperative analgesia: the OCTOPUS study

BACKGROUND: Head-to-head comparisons of combinations of more than one non-opioid analgesic (NOA) with morphine alone, for postoperative analgesia, are lacking. The objective of this multicentre, randomised, double-blind controlled trial was to compare the morphine-sparing effects of different combinations of three NOAs-paracetamol (P), nefopam (N), and ketoprofen (K)-for postoperative analgesia. METHODS: Patients from 10 hospitals were randomised to one of eight groups: control (C) received saline as placebo, P, N, K, PN, PK, NK, and PNK. Treatments were given intravenously four times a day during the first 48 h after surgery, and morphine patient-controlled analgesia was used as rescue analgesia. The outcome measures were morphine consumption, pain scores, and morphine-related side-effects evaluated 24 and 48 h after surgery. RESULTS: Two hundred and thirty-seven patients undergoing a major surgical procedure were included between July 2013 and November 2016. Despite a failure to reach a calculated sample size, 24 h morphine consumption [median (inter-quartile range)] was significantly reduced in the PNK group [5 (1-11) mg] compared with either the C group [27 (11-42) mg; P<0.05] or the N group [21 (12-29) mg; P<0.05]. Results were similar 48 h after surgery. Patients experienced less pain in the PNK group compared with the C, N, and P groups. No difference was observed in the incidence of morphine-related side-effects. CONCLUSIONS: Combining three NOAs with morphine allows a significant morphine sparing for 48 h after surgery associated with superior analgesia the first 24 h when compared with morphine alone. CLINICAL TRIAL REGISTRATION: EudraCT: 2012-004219-30; NCT01882530