Portail des publications scientifiques IMT Mines Alès
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Modeling of nonlinear viscoelasticity and stress softening in soft tissues
No full textInternational audienceThis paper deals with the mechanical behavior of soft living tissues under load-unload and relaxation cyclic strains. It proposes a thermodynamic model formulated within the Generalized Standard Materials framework that incorporates both Mullins’ effect and viscoelasticity, integrating the history dependent behavior of the material under finite strain. A key innovation lies in the use of a common softening function to modulate both the hyperelastic and viscous components, capturing history-dependent behavior more accurately. Viscous parameters are adjusted based on the loading history via the maximum strain invariant. Numerical implementation is validated against uniaxial tensile tests on porcine perineal tissues and a global Sobol sensitivity analysis confirms that elastic, viscous, and Mullins-related parameters are identifiable from different phases of the loading protocol. This model provides a unified, thermodynamical consistent tool for simulating soft tissue mechanics
Large-scale streamflow regionalization in ungauged West African catchments: How do classical and deep learning approaches compare?
No full textInternational audienceIn West Africa, limited access to hydrometric data remains a major challenge for advancing surface water research and improving water management. Since the early 1980s, many gauging stations have been decommissioned, leaving gaps in reliable streamflow records across numerous catchments. Parameter regionalization of hydrological models is commonly employed to enable runoff prediction in ungauged catchments. This study represents an assessment of rainfall-runoff model regionalization across West Africa. We used an unprecedented dataset of 189 near-natural catchments to compare two contrasting approaches: (i) a benchmark conceptual modeling framework using the GR4J model, regionalized with three parameter-transfer techniques (spatial proximity, physiographic similarity, and Random Forest), and (ii) a data-driven framework based on Long Short-Term Memory (LSTM) neural networks. Using a leave-one-out resampling approach, regionalization approaches were evaluated using different performance metrics: (i) the Kling-Gupta Efficiency (KGE), calculated between simulated and observed streamflows, (ii) the relative bias (rBias) on several hydrological signatures computed with observed or simulated discharge and (iii) the difference between observed and simulated flood quantiles. Results show that the conceptual modeling approach with traditional parameter-transfer techniques consistently underperforms compared to the LSTM, failing to reproduce key hydrological signatures. In contrast, the LSTM model showed better generalization performance, accurately simulating streamflow with a median KGE of 0.67 and reliably capturing hydrological signatures and flood quantiles across West Africa’s diverse climates and landscapes with lower biases. These findings highlight the potential of data-driven approaches to enhance hydrological prediction in data-scarce regions, supporting more effective flood risk management and water resource planning
Radiation-induced grafting for flame-retardant Miscanthus × giganteus stem fragments: Role of methodology and radiation source
No full textInternational audienceIn this study, poly(dimethyl(methacryloyloxy)methyl phosphonate)-grafted Miscanthus × giganteus stem fragments were prepared using three radiation-induced grafting methods: pre-irradiation (PIG), simultaneous irradiation grafting (SIG), and simultaneous irradiation after pre-impregnation (SIGPI). In all cases, the influence of irradiation sources (e-Beam, γ-rays and X-rays), as well as the dose, were evaluated. X-ray fluorescence spectroscopy measurements and SEM/EDX cartographies evidenced that the grafting method both influences the grafted amounts and the localization of the grafted polymer chains within the substrate. Among all the methods used, SIG yielded the highest grafted amounts. In that case, the use of e-Beam and X-rays irradiation yielded respectively a phosphorus content of 2.6 wt% and 3 wt% at 10 kGy, whereas γ-rays yielded lower results. The dose rate, and more specifically the peak dose rate, seem to play a decisive role in the results. Pyrolysis Combustion Flow Calorimetry (PCFC) measurements highlighted variations in fire performance, which were linked to differences in the distribution of the grafted polymer within the substrate. All functionalization methods employed in this study successfully imparted flame-retardant properties to Miscanthus × giganteus stem fragments
Optimizing electro-oxidation for selective trace micropollutant removal and energy efficiency in secondary effluents
No full textInternational audienceThis study investigated the electro-oxidation (EO) of three priority micropollutants: carbamazepine (CBZ), diuron (DIU), and perfluorooctane sulfonate (PFOS), in secondary-treated wastewater using boron-doped diamond (BDD) anodes. Although BDD anodes generate strong, largely non-selective oxidants; however, their performance at environmentally relevant concentrations, across different classes of micropollutants and under realistic organic-matter loads remains insufficiently characterized, especially for fluorinated and other recalcitrant contaminants. The selected compounds represent persistent pollutants with contrasting physicochemical properties and regulatory relevance (EU 2024/3019), which requires ≥ 80% CBZ between raw wastewater and the treated effluent. A four-factor central composite design (current density 10.7–33.0 mA/cm2, electrolysis time 14–56 min, COD 0.9–29 mg/L, influent concentration 0.3–8.7 µg/L; pH 7–8; flow 40 L/h) was used to quantify the influence of operating conditions on removal efficiency, energy demand and by-product formation. CBZ and DIU were efficiently removed under most conditions (> 98%), while PFOS elimination reached up to 93% under high-time/high-current regimes. At environmentally relevant influent levels (1–2 µg/L), removals of 92% (CBZ), 80% (DIU) and 41% (PFOS) were achieved with a moderate and conceivable energy demand (3.35 kWh/m3). Dissolved organic matter slightly reduced degradation rates but did not prevent effective pollutant targeting. Acute toxicity assays revealed a transient increase occurring alongside the formation of primary transformation products, followed by a decline at extended treatment durations, consistent with the progressive oxidation of toxic intermediates. Overall, the study provides a quantitative, multi-response evaluation of BDD EO under realistic wastewater conditions, clarifying operational limits, energy–performance trade-offs, and transformation-product dynamics relevant to its implementation as an advanced polishing step
A Model-Based System Engineering approach for Business Continuity Management in Hospitals
No full textInternational audienceIn hospitals, the information system is essentialfor coordinating actors and operations, as well as achievingobjectives. Its loss would have grave consequences, whetherdirectly affecting patients, finances, or logistics, thus creatinga need to preserve the health service’s critical functions and toenhance cooperation and communication among stakeholders.Business Continuity Management (BCM) is used to mitigatethese consequences. Still, traditional approaches often remaindescriptive and lack a formal method for representing the interdependenceamong governance, medical, and logistical processesin complex sociotechnical systems, which is essential for understandingthe extent of the problem and for designing appropriatesolutions. In contrast, Model-Based System Engineering (MBSE)provides a holistic view of the system, representing the problemas a whole. It has been used in healthcare to address complexitybefore, but applications that support resilience and continuity inorganizational systems remain underexplored.This paper proposes a conceptual framework, based on adomain-specific metamodel for hospital continuity management,which combines MBSE and BCM to illustrate dependenciesbetween technical and organizational elements and the collaborativedynamics among stakeholders. By showing how tasksand responsibilities are shared among actors and linking thesemodels to simulation, the framework enables the anticipationof disruptions’ impacts and the assessment of recovery options.The relevance of the framework is illustrated through a geriatricsurgical health service use case, in which critical dependenciesbetween IT, medical, and logistics processes are represented andevaluated.This paper argues that MBSE can be expanded to serve as themethodological basis for BCM in healthcare by drawing parallelsbetween MBSE and BCM processes. We illustrate how MBSEcan help predict the impact of disruptions and verify models ofdegraded hospital operations, highlighting MBSE’s potential as abasis for a decision-support tool for hospital business continuity
Leveraging model-based systems and software engineering for digital twin engineering: Methods and digital thread opportunities
No full textInternational audienceThe Digital Twin (DT) is a reciprocally connected and synchronized representation of a physical asset so-called Physical Twin. DT is a central component of a Digital Twin System (DT System), that interconnects the DT and the Physical Twin, through different components, and executes the necessary functions such as exchanging, processing or storing data. The engineering of the DT System is a long and complex process which is poorly formalised by systematic methodological approaches despite the variety of techniques and technologies used by practitioners. Fittingly, Systems Engineering (SE) offers principles, processes, methodological tools and frameworks for the engineering and lifecycle management of complex systems. More precisely, Model-Based Systems and Software Engineering (MBSSE) places modelling activities at the centre of engineering practices to facilitate exchanges and iterations between stakeholders around the system of interest through its whole lifecycle. Stakeholders’ activities during system’s lifecycle produce digital items, perceived as Data, Information or Knowledge (DIK), which may be reused for DT System engineering. First, this paper discusses SE and MBSSE application for DT System engineering to identify the foundations of a DT System MBSSE. Second, a discussion about opportunities and research questions are presented to gather and manage items produced along lifecycle in a concept designated the Digital Thread. Indeed, Digital thread formalisation and exploitation lead various interests for DT System engineering
Detecting Long-Memory Psychological Processes in Academic Settings Using Whittle’s Maximum Likelihood Estimator: An Application with R
No full textInternational audienceAbstract Person-specific approaches are best suited to account for the complex, dynamic, and idiosyncratic processes from which cognitive, emotional, motivational, relational, and behavioral patterns emerge. Among these approaches, Whittle’s approximation of the Maximum Likelihood Estimator (MLE) enables the detection of long-term memory processes in relatively short time series of data. In this chapter, we outline the principles of Whittle’s MLE, illustrate its application—using R—to the motivational dynamics of approach and avoidance in an academic context, and then discuss the theoretical and practical implications of detecting long-memory processes in the field of education and learning
Recent improvements in the analysis and characterization of fiber/matrix interfaces in biocomposites (Chap. 8)
No full textInternational audienceThis chapter aims to illustrate the correlation in the effect of free surface energy modification of natural fibers on the mechanical behavior of bio-based composites. It has been proved that enhancing the wettability of flax fibers by liquid epoxy resin implies a lower porosity amount in composites. The main outcome of multiscale consideration is that even if elementary fibers and yarns are embrittled and interface properties at the microscale are lowered by a thermal or chemical surface energy modification, the mechanical behavior of composites manufactured by liquid composite molding can be improved. Some questions are still open on the methodology to optimize treatments, especially on the scale at which the treatment is applied (yarn or fabric). The extension of those considerations to biocomposites with thermoplastic matrices should be done in the upcoming years to manufacture sustainable and circular composites
A rolling horizon framework for supplier selection and order allocation: a case study on smallholder agricultural supply chain
No full textInternational audienceIn the short-food supply chain, planning the orders that the retailer places with the farmer is essential to ensure the satisfaction of the clients and the minimization of the costs for the retailer. Some of these retailers face a distinct set of challenges that, to the best of our knowledge, we are the first to tailor a model for. We integrate a mathematical model within a rolling horizon framework to address the supplier selection and order allocation problem, accounting for dynamic demand, production, and inventory capacities, as well as unit purchasing, ordering, and holding costs. Additionally, we perform a sensitivity analysis to understand the behavior of the model. The model is able to generate an ordering schedule given the demand of the clients and different parameters of suppliers. When integrated into the rolling horizon framework, the model could adapt to new information and modify previously planned, ordered, stored, and delivered quantities to meet the demand of the clients with minimal costs. When tested on instances of thirty suppliers with planning windows of length fifty time periods, the model had an average execution time of 3.5 seconds which we deemed acceptable
Modelling fire-induced damage in limestone masonry walls using thermomechanical finite and discrete element method approaches
No full textInternational audienceFire severely affects the structural integrity of masonry structures, particularly in heritage buildings where post-fire assessment is essential for conservation and restoration efforts. While the fire behaviour of concrete has been widely studied, the thermomechanical response of masonry walls remains less documented. This study explores the behaviour of limestone masonry walls from the literature, subjected to fire and vertical compression, using Finite Element Method and hybrid finite/discrete simulations. These numerical models help analyse deformation mechanisms, crack propagation, and load-bearing capacity after fire exposure. Results show that out-of-plane displacements are highly dependent on boundary conditions and mechanical constraints. Thermal expansion leads to vertical cracking through both stones and joints, with cracks typically initiating near the lateral edges due to high tensile stresses. Post-fire residual behaviour indicates a reduction in compressive strength of about 45 %, aligning with experimental data. The stress-displacement curve of the heated wall reveals a complex failure process marked by multiple load drops, associated with crack closure and shear-induced cracking. In contrast, the unheated wall fails primarily through diagonal shear cracks, forming compression struts and confinement cones that influence its load-bearing response. These findings underline the importance of accounting for altered failure mechanisms when assessing and reinforcing fire-damaged masonry