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An Adaptive Simulation Framework for the Exploration of Extreme and Unexpected Events in Dynamic Engineered Systems
No full textInternational audienceThe end states reached by an engineered system during an accident scenario depend not only on the sequences of the events composing the scenario, but also on their timing and magnitudes. Including these additional features within an overarching framework can render the analysis infeasible in practical cases, due to the high dimension of the system state-space and the computational effort correspondingly needed to explore the possible system evolutions in search of the interesting (and very rare) ones of failure. To tackle this hurdle, in this article we introduce a framework for efficiently probing the space of event sequences of a dynamic system by means of a guided Monte Carlo simulation. Such framework is semi-automatic and allows embedding the analyst's prior knowledge about the system and his/her objectives of analysis. Specifically, the framework allows adaptively and intelligently allocating the simulation efforts preferably on those sequences leading to outcomes of interest for the objectives of the analysis, e.g., typically those that are more safety-critical (and/or rare). The emerging diversification in the filling of the state-space by the preference-guided exploration allows also the retrieval of critical system features, which can be useful to analysts and designers for taking appropriate means of prevention and mitigation of dangerous and/or unexpected consequences. A dynamic system for gas transmission is considered as a case study to demonstrate the application of the method
Reliability model of a component equipped with PHM capabilities
No full textInternational audienceWe propose an analytic, time-variant model that conservatively evaluates the increase in reliability achievable when a component is equipped with a Prognostics and Health Management system of known performance metrics. The reliability model builds on metrics of literature and is applicable to different industrial contexts. A simulated case study concerning crack propagation in a mechanical component is considered to validate the proposed model
A Formally Proved, Complete Algorithm for Path Resolution with Symbolic Links
No full textInternational audienceIn the context of file systems like those of Unix, path resolution is the operation that given a character string denoting an access path, determines the target object (a file, a directory, etc.) designated by this path. This operation is not trivial because of the presence of symbolic links. Indeed, the presence of such links may induce infinite loops in the resolution process. We consider a path resolution algorithm that always terminates, detecting if it enters an infinite loop and reports a resolution failure in such a case. We propose a formal specification of path resolution and we formally prove that our algorithm terminates on any input, and is correct and complete with respect to our formal specification
A 14-b Two-step Inverter-based Σ∆ ADC for CMOS Image Sensor
No full textInternational audienceThis paper presents a 14-bit Incremental Sigma Delta (IΣ∆) analog-to-digital converter (ADC) suitable for a column wise integration in a CMOS image sensor. A two-step conversion is performed to improve the conversion speed. As the same Σ∆ modulator is used for both steps, the overall complexity is reduced. Furthermore, the use of inverter-based amplifiers instead of operational transconductance amplifier (OTA) facilitates the integration within the column pitch and decreases power consumption. The proposed ADC is designed in 0.18 µm CMOS technology. The simulation shows that for a 1.8 V voltage supply, a 20 MHz clock frequency and an oversampling ratio (OSR) of 70, the power consumption is 460 µW, achieving an SNR of 83.7 dB
Modelling the effects of propofol on neuronal synchronization in network of interneurons
No full textInternational audiencePropofol is a chemical agent commonly used as an intravenous general anesthetic. At the cellular level, this short-acting ananesthetic positively modulates GABAergic inhibitory activity by targeting GABA-A receptors [1]. This type of receptors are widespread in the brain and can be present both within synaptic clefts, as well as on extrasynaptic locations along the dendrites and neuron membrane where they are responsible for tonic inhibition. At the macroscopic level of SEEG (deep Stereographic-Electro Encephalogram) or EEG (Electro Encephalogram) recordings, one observes, with certain doses of propofol, a paradoxical excitation phenomenon [2] the generation mechanisms of which are not clearly understood. In this study, we suggest a potential mechanism for the appearance of paradoxical excitation occurring under propofol-induced general anaesthesia. We show, with a model network of Hodgkin-Huxley neurons, that tonic inhibition – induced by the binding of propofol to extra-synaptic receptors – together with an increase of the synaptic time constant within an certain range [3] can account for the phenomenon of paradoxical excitation. However, changes in the gain (or conductance) of the synaptic inhibition do not correspond to a sudden increase in neuronal population firing rate nor synchrony as described in the experiments [3]. The action of propofol on extrasynaptic GABAergic receptors was modelled by varying the conductance g ton of a tonic current in the form as described in [4]. Figure 1 shows the evolution of the neuronal population firing rate and the coherence (or synchrony) of the network activity as the tonic inhibition and the synaptic conductance vary. The plots are given for different values of the synaptic time constants. The increase of these three variables, synaptic time constant and conductance, and tonic conductance reflect an increase in propofol doses
Computation of effective nonlinear coupled electro-mechanical properties of graphene-reinforced nanocomposites
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Modeling and specific growth rates estimation of a two-stage anaerobic digestion process for hydrogen and methane production
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Learning with bandit feedback in potential games
No full textInternational audienceThis paper examines the equilibrium convergence properties of no-regret learningwith exponential weights in potential games. To establish convergence with minimalinformation requirements on the players’ side, we focus on two frameworks:the semi-bandit case (where players have access to a noisy estimate of their payoffvectors, including strategies they did not play), and the bandit case (where playersare only able to observe their in-game, realized payoffs). In the semi-bandit case,we show that the induced sequence of play converges almost surely to a Nashequilibrium at a quasi-exponential rate. In the bandit case, the same result holds for"-approximations of Nash equilibria if we introduce an exploration factor " > 0that guarantees that action choice probabilities never fall below ". In particular, ifthe algorithm is run with a suitably decreasing exploration factor, the sequence ofplay converges to a bona fide Nash equilibrium with probability 1