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Maintenance and Repair
No full textInternational audienceSince the 2000s, a wave of research on maintenance and repair activities has broadened the range of sites and practices usually invested by STS. This chapter aims to emphasize three analytical movements that are renewing the study of techniques in society: the thickening of the space-time of technologies, the revisiting of the material fabric of human societies, andthe forms of expertise specific to maintenance and repair
Lien fatigue/fluage dans les composites thermoplastiques : vers une approche innovante de prédiction de durée de vie
No full textInternational audienceLien fatigue/fluage dans les composites thermoplastiques : vers une approche innovante de prédiction de durée de vi
Breeding goals and more: the multiple links between livestock farming systems and genetics
No full textSession 42 - Poster 31International audienceThe call for agro ecological transition questions the design of breeding programs. At which conditions breeding programs can contribute to develop agroecology? In other words, how to define relevant breeding goals and relevant breeding programs for livestock farming systems responding to the principles of agroecology? A core question deals with the links between livestock farming systems features and the definition of breeding goals and breeding programs. In this proposal, we elaborated a synthesis of French research works dealing with this issue, at individual and collective levels, merging contributions by researchers from different scientific fields and working on a wide range of livestock species, in a three dimensions framework. The first dimension of the framework concerns how individual farmers choose genetic types in coherence with their livestock farming system. The second dimension concerns the definition of breeding goals, at farm and population level, in link with livestock farming system features. A diversity of reasons explains farmers’ choices in terms of breeding goals, and they can combineseveral levers to get a herd that satisfies them. The third dimension of the framework underlines the need to take into account how farmers add value to products. We invite to an interdisciplinary approach of the links between genetics and farming systems, at several levels of organization. The issue of the relevant breeding goals, and how they are defined, should be an integral part of such a global approach
Optimal absorption and emission of itinerant fields into a spin ensemble memory
No full textQuantum memories integrated in a modular quantum processing architecture can rationalize the resources required for quantum computation. This work focuses on spin-based quantum memories, where itinerant electromagnetic fields are stored in large ensembles of effective two-level systems, such as atomic or solid-state spin ensembles, embedded in a cavity. Using a mean-field framework, we model the ensemble as an effective spin communication channel and develop a cascaded quantum model to describe both absorption and emission processes. We derive optimal time-dependent modulations of the cavity linewidth that maximize storage and retrieval efficiency for finite-duration wavepackets. Our analysis yields an upper bound on efficiency, which can be met in the narrow bandwidth regime. It also shows the existence of a critical bandwidth above which the efficiency severely decreases. Numerical simulations are presented in the context of microwave-frequency quantum memories interfaced with superconducting quantum processors, highlighting the protocol's relevance for modular quantum architectures
Statistical modeling and generation of inertial ductile fracture surfaces
No full textInternational audienceSpallation in ductile metals involves complex void nucleation and growth mechanisms, but the interactions between voids and the resulting statistical structure of fracture surfaces remain a persistent challenge for both experimental and theoretical modeling. This study develops a generative model to capture the statistical features of spall-induced fracture surfaces in highpurity aluminum. Aluminum samples were subjected to nanosecond laser-induced spallation, and the resulting fracture surfaces were imaged via scanning electron microscopy (SEM) and reconstructed in 3D. Individual dimples were segmented and analyzed to extract void size distributions and the spatial arrangement of nucleation sites. Boolean models and Gaussian random fields were then used to generate synthetic surfaces and compared against the experimental data using one-and two-point statistics. The analysis revealed a Poisson distribution of nucleation centers within the spall plane but significant out-of-plane spatial correlations in nucleation depth. The extended generative model successfully reproduces both the surface height distribution and the spatial covariance observed experimentally. These results emphasize the need to incorporate large-scale spatial correlations in predictive models of dynamic ductile damage. The proposed framework provides a basis for future studies of collective void growth and spall surface formation in dynamic ductile fracture
Hedging hydrogen: Planning and contracting under uncertainty for a green hydrogen producer
No full textInternational audienceGreen hydrogen production by water electrolysis using renewable electricity is considered essential for decarbonisation of certain sectors of the global economy, however development of the industry is lagging behind expectations due to the perceived financial risk for individual projects. This risk stems from a number of uncertainties, including future hydrogen demand, variable renewable energy sources, and volatile energy market prices.The interaction of these uncertainties is complex, yet the analysis of hydrogen projects is often carried out using simplified modelling that often omits uncertainty and/or energy hedging practices which are typical for intensive power consumers. In this study, we define a set of planning methods (planning policies) in order to compare the effectiveness of different modelling approaches. We propose a 2-stage market-focused stochastic program to represent a hydrogen producer supplying an industrial customer through a hydrogen offtake contract (a Hydrogen Purchase Agreement, or HPA). The model can be used to obtain equipment sizing decisions, as well as energy hedging decisions using Power Purchase Agreements (PPA's) and power futures. We find that for some HPA contract types, failure to use stochastic modelling can lead to planning decisions that result in 30% higher production costs during scenario stress-testing for the same project. This could lead to some projects being discarded by developers, incorrectly deemed to be unviable due to cost projections being too high. The results also show the importance of HPA contract volumetric obligations in limiting demand uncertainty
New strategies and new challenges for pesticide studies: how to combine the preservation of our environment and sustainable agriculture?
No full textInternational audienc
Supporting Industrial Heritage and Local Know-How to Benefit Regional Development: The Case of Terre et Fils
No full textInternational audienc
Optimal business model adaptation plan for a company under a transition scenario
No full textClimate stress-tests aim at projecting the financial impacts of climate change, covering both transition and physical risks under given macro scenarios. However, in practice, transition risk has been the main focus of supervisory and academic exercises, and existing tools to downscale these macroeconomic projections to the firm level remain limited. We develop a methodology to downscale sector-level trajectories into firm-level projections for credit risk stress-tests. The approach combines probabilistic modeling with stochastic control to capture firm-level uncertainty and optimal decision-making. It can be applied to any transition scenario or sector and highlights how firm-level characteristics such as initialintensity, abatement cost, and exposure to uncertainty shape heterogeneous firm-level responses to the transition. The model explicitly incorporates firm-level business uncertainty through stochastic dynamics on relative emissions and sales, which affect both optimal decisions and resulting financial projections. Firms’ rational behavior is modeled as a stochastic minimization problem, solved numerically through a method we call Backward Sampling. Illustrating our method with the NGFS transition scenarios and three types of companies (Green, Brown and Average), we show that firm-specific intensity reduction strategies yield significantly different financial outcomes compared to assuming uniformsectoral decarbonisation rates. Moreover, investing an amount equivalent to the total carbon tax paid at a given date is limited by its lack of a forward-looking feature, making it insufficient to buffer against future carbon shocks in a disorderly transition. This highlights the importance of firm-level granularity in climate risk assessments. By explicitly modeling firm heterogeneity and optimal decision-making under uncertainty, our methodology complements existing approaches to granular transition risk assessment and contributes to the ongoing development of scenario-based credit risk projections at the firm level