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The thermal vibration and buckling behavior of a functionally graded nanoplate are examined in this study. The nanoplate is made up of a silicon nitride/stainless steel core plate and two cobalt-ferrite/barium-titanate face plates. Four alternative porosity models were used to simulate the porosity of the nanoplate, and numerous variables that can affect the nanoplate’s behavior were taken into account. The study found that the thermomechanical behavior of nanoplates with magneto-electro-elastic face layers and a functionally graded porous core plate is affected by material gradation indices, porosity ratios, nonlocal variables, and different core plate material porosity models. © 2023 Taylor & Francis Group, LLC.

We present two statistical models for downscaling flood hazard indicators derived from upscaled shallow water simulations. These downscaling models are based on the decomposition of hazard indicators into linear combinations of spatial patterns obtained from a Principal Component Analysis (PCA). Artificial Neural Networks (ANNs) are used to model the relationship between low resolution (LR) and high resolution (HR) information drawn from hazard indicators. In both statistical models, the PCA features, i.e. the linear weights of the spatial patterns, of the LR hazard indicator are taken as inputs to the ANNs. In the first model, there is one ANN per HR cell where the hazard indicator is to be estimated and the output of the ANN is the hazard indicator value at that cell. In the second model, there is a single ANN for the whole HR mesh whose outputs are the PCA features of the HR hazard indicator. An estimate of the hazard indicator is obtained by combining the ANN’s outputs with the HR spatial patterns. The two statistical downscaling models are evaluated and compared at estimating the water depth and the norm of the unit discharge, two common hazard indicators, on simulations from five synthetic urban configurations and one field-test case. Analyses are carried out in terms of relative absolute errors of the statistical downscaling model with respect to the LR hazard indicator. They show that (i) both statistical downscaling models provide estimates that are more accurate than the LR hazard indicator in most cases and (ii) the second downscaling model yields consistently lower errors for both hazard indicators for all flow scenarios on all configurations considered. The statistical models are three orders of magnitude faster than HR flow simulations. Used in conjunction with upscaled flood models such as porosity models, they appear as a promising operational alternative to direct flood hazard assessment from HR flow simulations.

With CPU times reduced by two to three orders of magnitude compared to shallow water models, porosity models are considered as efficient tools for the modelling of urban floods on the scale of a conurbation. However, they provide only upscaled hydraulic fields that yield unreliable estimates of the flood risk in terms of financial losses and hazard to human lives. Downscaling of the porosity model simulation outputs is thus necessary. The present work puts forward a downscaling approach based on the decomposition of microscopic hydraulic fields into linear combinations of spatial patterns. The coefficients of the linear combinations are predicted with an Artificial Neural Network (ANN) whose input is derived from macroscopic hydraulic fields. Principal Component Analysis is used both to decompose the microscopic fields into linear combinations of spatial patterns and to project the macroscopic fields into lower dimensional features that are fed to the ANN. This global downscaling approach, which reconstruct the whole microscopic field at once, is compared with a local downscaling approach that relies on a similar setup except that each cell of the microscopic field is estimated separately by a dedicated ANN and that there are as many ANNs as cells. The two downscaling approaches are evaluated and compared at estimating the water depth and the norm of the unit discharge on five synthetic urban configurations and one field-test case. The analyses in terms of absolute errors show that the global approach not only provides a valid downscaling scheme but outperforms, in almost all instances, the local approach.

International audience; With CPU times 2 to 3 orders of magnitude smaller than classical shallow water-based models , the shallow water equations with porosity are a promising tool for large-scale modelling of urban floods. In this paper, a new model formulation called the Dual Integral Porosity (DIP) model is presented and examined analytically and computationally with a series of benchmark tests. The DIP model is established from an integral mass and momentum balance whereby both porosity and flow variables are defined separately for control volumes and boundaries, and a closure scheme is introduced to link control volume-and boundary-based flow variables. Previously developed Integral Porosity (IP) models were limited to a single set of flow variables. A new transient momentum dissipation model is also introduced to account for the effects of sub-grid scale wave action on porosity model solutions, effects which are validated by fine-grid solutions of the classical shallow-water equations and shown to be important for achieving self-similarity in dam-break solutions. One-dimensional numerical test cases show that the proposed DIP model outperforms the IP model, with signicantly improved wave propagation speeds, water depths and discharge calculations. A two-dimensional field scale test case shows that the DIP model performs better than the IP model in mapping the floods extent and is slightly better in reproducing the anisotropy of the flow field when momentum dissipation parameters are calibrated.

International audience; Modelling urban floods at the scale of the conurbation remains a challenging task owing to the size ratio between the hydraulic features and the modelling domain. Upscaling makes such modelling possible. Macroscopic models allow CPU and model pre-processing times to be divided by 102 to 103 compared to classical models. Macroscopic inundation fields may be interpolated for finer scale simulations. Four types of macroscopic urban flood models are currently available from the literature: the single porosity model, the integral porosity approach, the conveyance reduction factor model and the multiple porosity model. Analysing the four formulations indicates that they can be expected to exhibit significantly different behaviour in a variety of hydraulic configurations. So far, they have been applied to different types of urban layouts or only compared to numerical simulations. Identifying the best formulations call for a systematic experimental benchmarking involving steady state and transient regimes.; Le ratio entre les échelles du détail hydraulique pertinent et de la zone urbaine rend la simulation des crues urbaines difficilement envisageable à l’échelle de l’agglomération. Le transfert d’échelle rend possible ce type d’opération. Les modèles macroscopiques permettent typiquement un gain de temps de calcul d’un facteur 102 à 103 par rapport aux modèles détaillés. Ils sont obtenus à partir des modèles à surface libre classiques par des opérations de prise de moyenne. Ils permettent de produire des champs inondants à des échelles de l’ordre de la centaine de mètres. Ces champs peuvent être réutilisés comme conditions aux limites de modèles détaillés, de taille plus réduite. Les quatre modèles macroscopiques proposés jusqu’à présent dans la littérature sont le modèle à porosité simple, le modèle à formulation intégrale, le modèle à réduction de débitance et le modèle à porosité multiple. L’analyse de leur formulation indique que leurs comportements devraient être assez différents dans un certain nombre de configurations. Cependant, ils ont été en général appliqués sur des situations différentes ou comparés uniquement à des simulations numériques. L’évaluation de leurs performances respectives appelle la réalisation de benchmarks expérimentaux systématiques, faisant intervenir sur les mêmes configurations géométriques des régimes permanents et des régimes transitoires.

International audience; Modelling urban floods at the scale of the conurbation remains a challenging task owing to the size ratio between the hydraulic features and the modelling domain. Upscaling makes such modelling possible. Macroscopic models allow CPU and model pre-processing times to be divided by 102 to 103 compared to classical models. Macroscopic inundation fields may be interpolated for finer scale simulations. Four types of macroscopic urban flood models are currently available from the literature: the single porosity model, the integral porosity approach, the conveyance reduction factor model and the multiple porosity model. Analysing the four formulations indicates that they can be expected to exhibit significantly different behaviour in a variety of hydraulic configurations. So far, they have been applied to different types of urban layouts or only compared to numerical simulations. Identifying the best formulations call for a systematic experimental benchmarking involving steady state and transient regimes.; Le ratio entre les échelles du détail hydraulique pertinent et de la zone urbaine rend la simulation des crues urbaines difficilement envisageable à l’échelle de l’agglomération. Le transfert d’échelle rend possible ce type d’opération. Les modèles macroscopiques permettent typiquement un gain de temps de calcul d’un facteur 102 à 103 par rapport aux modèles détaillés. Ils sont obtenus à partir des modèles à surface libre classiques par des opérations de prise de moyenne. Ils permettent de produire des champs inondants à des échelles de l’ordre de la centaine de mètres. Ces champs peuvent être réutilisés comme conditions aux limites de modèles détaillés, de taille plus réduite. Les quatre modèles macroscopiques proposés jusqu’à présent dans la littérature sont le modèle à porosité simple, le modèle à formulation intégrale, le modèle à réduction de débitance et le modèle à porosité multiple. L’analyse de leur formulation indique que leurs comportements devraient être assez différents dans un certain nombre de configurations. Cependant, ils ont été en général appliqués sur des situations différentes ou comparés uniquement à des simulations numériques. L’évaluation de leurs performances respectives appelle la réalisation de benchmarks expérimentaux systématiques, faisant intervenir sur les mêmes configurations géométriques des régimes permanents et des régimes transitoires.

This thesis presents a study of the morphological changes that occur in selected coal chars during oxidation at low temperature (725K-875K) and at high temperature (1400K-1600K). Gas adsorption and mercury porosimetry were the primary means by which these changes were monitored. An attempt was made to relate the observed reactivity of the char in oxygen to the evolving porous structure of the char. Initial pore structure was varied by using three different raw coals: a lignite, a subbituminous and high volatile A bituminous coal. In the case of the bituminous coal, pore structure was varied further by using different pyrolysis temperatures. Of course, while there were differences in the physical structure of the chars, there were differences in the chemical structure as well. In order to account for this, the chemical nature of the chars was monitored, using elemental analysis and oxygen chemisorption. The results of this study indicate that, at low temperatures, the rate of oxidation of the subbituminous and bituminous chars is proportional to the BET surface area beyond 20% conversion. The lignite char did not show such simple behavior because of the presence of large amounts of ash. For the high-temperature case, reaction appeared to be confined to the exterior of the particle and to the interior of the macropores. Time-temperature histories of individual lignite char particles were obtained with a two-color pyrometer. A simplified model of single- particle-char combustion was used in conjunction with statistical analysis to infer kinetic parameters from the experimental time-temperature traces.