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Spatialized Metabolomic Annotation Combining MALDI Imaging and Molecular Networks
No full textInternational audienceMALDI mass spectrometry imaging has gained major interest in the field of chemical imaging. This technique makes it possible to locate tens to hundreds of ionic signals on the sample surface without any a priori. One of the current challenges is still the limited ability to annotate signals in order to convert m/z values into probable chemical structures. At the same time, data obtained by LC-MS/MS have benefited from the development of numerous chemoinformatics tools, in particular molecular networks, for their efficient annotation. For the first time, we present here the combination of MALDI-FT-ICR imaging with molecular networks from MALDI-MS/MS data directly acquired on plant tissue sections. Annotation improvements are demonstrated, paving the way for new annotation pipelines for MALDI imaging
Enhancing Reliability Analysis with Limited Observations: A Statistical Framework for System Safety Margins
No full textInternational audienceReliability analysis of complex systems is essential for cost-effective evaluations. This study addresses scenarios where optimal system operation is analyzed using deterministic black-box models. The input vector, x, characterizes both the system and environmental conditions, while y represents the variable of interest associated to a "failure domain''. Given the uncertainties in x, this deterministic model requires a probabilistic analysis for robust safety demonstrations. Such an analysis typically involves two key steps: first, estimating the system's probability of failure (denoted by p) which is the statistical quantity of interest, and then, evaluating it against safety standards or expert knowledge. While considerable effort has been invested in proposing efficient methods for estimating p, little attention has been paid to the decision phase, which should take into account the uncertainties (e.g., in the p estimate). This work focuses on the definition and use of safety margins in system reliability analysis with a final decision making purpose, especially when the knowledge of the input vectors x is limited to a finite set of n observations. An important distinction is made between cases where n is large or small relative to 1/p. The main contributions of the paper focus on the scenario where n is relatively small, and propose two different approaches, each of which allowing the definition of reasonable safety margins. The first method focuses on the estimation of the probability distribution of the code inputs x, while the second method, closely related to extreme value theory, focuses on the influence of the direct estimation of the tail of the model output probability distribution. The developed framework is then numerically validated on two test cases
A Joint Probability Distribution for Multivariate Wind-Wave Conditions and Discussions on Uncertainties
No full textInternational audienceThis article presents a joint statistical model, which is needed in probabilistic design and structural risk assessment, that has been fitted to data of wind and wave conditions for an offshore location off South Brittany. The data are from a numerical model and contain hourly values for several wind and wave variables over a period of 32 years. The joint distribution presented in this article considers the variables wind direction, mean wind speed, significant wave height, wave direction, and peak period. A conditional model for turbulence given wind speed is introduced to yield an additional variable for the joint model. The joint model is constructed as a product of marginal and conditional models for the various variables. Additionally, the fitted models will be used to construct environmental contours for some of the variables. For significant wave height, various models are used to obtain different extreme value estimates, illustrating the uncertainties involved in extrapolating statistical models beyond the support of the data, and a discussion on the use of nonparametric copulas for the joint distribution is presented. Moreover, bootstrap has been performed to estimate the uncertainty in estimated model parameters from sampling variability. The effect of changing which variable to model as the marginal in a conditional model is illustrated by switching from wind speed to significant wave height. Such joint distribution models are important inputs for design of offshore structures, and in particular for offshore wind turbines, and the influence of the joint model in design is illustrated by a simple case study. This article is an extension of the conference paper by Vanem et al. (2023, “A Joint Probability Distribution Model for Multivariate Wind and Wave Conditions,” 42nd International Conference on Ocean, Offshore and Arctic Engineering)
Identifying and fixing ambiguities in, and semantically accurate formalisation of, behavioural requirements
No full textInternational audienceTo correctly formalise requirements expressed in natural language, ambiguities must first be identified and then fixed. This paper focuses on behavioural requirements (i.e. requirements related to dynamic aspects and phenomena). Its first objective is to show, based on a practical, public case study, that the disambiguation process cannot be fully automated: even though natural language processing (NLP) tools and machine learning might help in the identification of ambiguities, fixing them often requires a deep, application-specific understanding of the reasons of being of the system of interest, of the characteristics of its environment, of which trade-offs between conflicting objectives are acceptable, and of what is achievable and what is not; it may also require arduous negotiations between stakeholders. Such an understanding and consensus-making ability is not in the reach of current tools and technologies, and will likely remain so for a long while. Beyond ambiguity, requirements are often marred by various other types of defects that could lead to wholly unacceptable consequences. In particular, operational experience shows that requirements inadequacy (whereby, in some of the situations the system could face, what is required is woefully inappropriate or what is necessary is left unspecified) is a significant cause for systems failing to meet expectations. The second objective of this paper is to propose a semantically accurate behavioural requirements formalisation format enabling tool-supported requirements verification, notably with simulation. Such support is necessary for the engineering of large and complex cyber-physical and socio-technical systems to ensure, first, that the specified requirements indeed reflect the true intentions of their authors and second, that they are adequate for all the situations the system could face. To that end, the paper presents an overview of the BASAALT (Behaviour Analysis and Simulation All Along systems Life Time) systems engineering method, and of FORM-L (FOrmal Requirements Modelling Language), its supporting language, which aims at representing as accurately and completely as possible the semantics expressed in the original, natural language behavioural requirements, and is markedly different from languages intended for software code generation. The paper shows that generally, semantically accurate formalisation is not a simple paraphrasing of the original natural language requirements: additional elements are often needed to fully and explicitly reflect all that is implied in natural language. To provide such complements for the case study presented in the paper, we had to follow different formalisation patterns, i.e. sequences of formalisation steps. For this paper, to avoid being skewed by what a particular automatic tool can and cannot do, BASAALT and FORM-L were applied manually. Still, the lessons learned could be used to specify and develop NLP tools that could assist the disambiguation and formalisation processes. However, more studies are needed to determine whether an exhaustive set of formalisation patterns can be identified to fully automate the formalisation process
Development of a detailed gaseous oxidation scheme of naphthalene for secondary organic aerosol (SOA) formation and speciation
No full textInternational audienceNaphthalene is the most abundant polycyclic aromatic hydrocarbon (PAH) in vehicle emissions and polluted urban areas. Its atmospheric oxidation products are oxygenated compounds that are potentially harmful for health and/or contribute to secondary organic aerosol (SOA) formation. Despite its impact on air quality, its complex structure and a lack of data mean that no detailed scheme of naphthalene gaseous oxidation for SOA formation and speciation has been established yet. This study presents the construction of the first near-explicit chemical scheme for naphthalene oxidation by OH, including kinetic and mechanistic data. The scheme redundantly represents all the classical steps of atmospheric organic chemistry (i.e., oxidation of stable species, peroxy radical formation and reaction, and alkoxy radical evolution), thus integrating fragmentation or functionalization pathways and the influence of NOx on secondary compound formation. Missing kinetic and mechanistic data were estimated using structure–activity relationships (SARs) or by analogy with existing experimental or theoretical data. The proposed chemical scheme involves 383 species (231 stable species, including 93 % of the major molar masses observed in previous experimental studies) and 484 reactions with products. A first simulation reproducing experimental oxidation in an oxidation flow reactor under high-NOx conditions shows a simulated SOA mass on the same order of magnitude as has been observed experimentally, with an error of −9 %
Machine Learning and Physics-Driven Modelling and Simulation of Multiphase Systems
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Extending the Discrete Element Method to Account for Dynamic Confinement and Strain-Rate Effects for Simulating Hard Impacts on Concrete Targets
No full textInternational audienceConcrete plays a pivotal role as a foundational material in critical infrastructure, particularly in nuclear plants. Given the imperative for robustness and safety in such contexts, the design of concrete structures necessitates methodologies capable of precisely predicting damage resulting from impacts. When subjected to impact, concrete experiences high loading rates and significant triaxial stresses in the vicinity of the impacting object, potentially resulting in fragmentation, pore closure and projectile penetration. In addressing these challenges, the discrete element method (DEM) emerges as a suitable approach primarily due to its inherent ability to model discontinuities such as cracking and fragmenta-tion. Within this framework, DEM employing spherical discrete elements (DE) has been implemented into Europlexus, a fast transient dynamics finite element (FE) code. This paper presents a refined constitutive DEM model for concrete, especially accounting for porosity closure under high confine-ment and the effect of strain-rate on tensile strength and fracture energy. The calibration of constitutive parameters is conducted through the simulations of a series of quasi-static (QS) tests encompassing tension, compression and triaxial compression. The strain-rate dependency parameters are identified through dynamic tensile tests conducted using a split-Hopkinson pressure bar apparatus. The whole constitutive model is presented as well as its calibration. Finally, the validation of the DEM approach is demonstrated through simulations of penetration and perforation tests conducted on concrete targets
Exact and heuristic methods for Anchor-Robust and Adjustable-Robust RCPSP
No full textInternational audienceThe concept of anchored solutions is proposed as a new robust optimization approach to the Resource-Constrained Project Scheduling Problem (RCPSP) under processing times uncertainty. The Anchor-Robust RCPSP is defined, to compute a baseline schedule with bounded makespan, sequencing decisions, and a max-size subset of jobs with guaranteed starting times, called anchored set. It is shown that the Adjustable-Robust RCPSP from the literature fits within the framework of anchored solutions. The Anchor-Robust RCPSP and the Adjustable-Robust RCPSP can benefit from each other to find both a worst-case makespan, and a baseline schedule with an anchored set. A dedicated graph model for anchored solutions is reviewed for budgeted uncertainty. Compact MIP reformulations are derived for both the Adjustable-Robust RCPSP and the Anchor-Robust RCPSP. Dedicated heuristics are designed based on the graph model. For both problems, the efficiency of the proposed MIP reformulations and heuristic approaches is assessed through numerical experiments on benchmark instances
Towards a better 0D-1D modelling approach for more accurate prediction of Indoor Air Quality (IAQ) in Buildings
No full textInternational audienceThe present CFD-based numerical study aims to enhance our understanding of pollutant mixing in ventilated rooms, exploring both gaseous and particulate pollutants under various air change rates and inlet/outlet configurations. Results of the 3D simulations showed that, in an isothermal room configuration, perfect pollutant mixing does not exist, although a homogeneous partitioning of the total volume seems to emerge after one hour. This homogeneity is mainly observed in zones with medium to high airflow, where the occupants breathe, excluding the corners of the room. The questioning of the perfect mixing hypothesis led to conclude that conventional one-zone models used in IAQ are inadequate for characterizing people exposure. A suitably adapted methodology will be developed to identify possible macroscopic corrections to nodal modelling which improve pollutant concentration evaluation in the breathing zone
Intégration de SOSA/SSN, SAREF, et TD dans l’ontologie CoSWoT
No full textInternational audienceCet article décrit l’ontologie CoSWoT construite au cours du projet « Constrained Semantic Web of Things » à l’aide de la méthodologie ACIMOV [13]. Cette ontologie réconcilie trois ontologies de référence du Web des Objets : « Semantic Sensor Network » (SSN/SOSA) [11] et « Thing Description » (TD) [3] du W3C, « Smart Applications REFerence » (SAREF) de ETSI [9], à travers la proposition d’un nouveau patron de conception architectural « Kinds of X and X of Interest ». Son objectif est de permettre à des dispositifs distribués sur le Web d’échanger des données sans ambiguïté. Nous illustrons les éléments de cette ontologie par un cas d’usage en bâtiment intelligent