Academic literature on the topic 'Fast mesoscopic model'

We have developed a numerical algorithm for simulation of wave propagation in double-porosity media, where the pore space is saturated with a single fluid. Spherical inclusions embedded in a background medium oscillate to yield attenuation by mode conversion from fast P-wave energy to slow P-wave energy (mesoscopic or wave-induced fluid-flow loss). The theory is based on the Biot theory of poroelasticity and the Rayleigh model of bubble oscillations. The differential equation of the Biot-Rayleigh variable is approximated with the Zener mechanical model, which results in a memory-variable viscoelastic equation. These approximations are required to model mesoscopic losses arising from conversion of the fast P-wave energy to slow diffusive modes. The model predicts a relaxation peak in the seismic band, depending on the diameter of the patches, to model the attenuation level observed in rocks. The wavefield is obtained with a grid method based on the Fourier differential operator and a second-order time-integration algorithm. Because the presence of two slow quasistatic modes makes the differential equations stiff, a time-splitting integration algorithm is used to solve the stiff part analytically. The modeling has spectral accuracy in the calculation of the spatial derivatives.

Mesoscopic transport models can efficiently simulate complex travel behavior and traffic patterns over large networks, but simulating energy consumption in these models is difficult with traditional methods. As mesoscopic transport models rely on a simplified handling of traffic flow, they cannot provide the second-by-second measurement of vehicle speeds and accelerations that are required for accurately estimating energy consumption. Here we present extensions to the TripEnergy model that fill in the gaps of low-resolution trajectories with realistic, contextual driving behavior. TripEnergy also includes a vehicle energy model capable of simulating the impact of traffic conditions on energy consumption and CO2 emissions, with inputs in the form of widely available calibration data, allowing it to simulate thousands of different real-world vehicle makes and models. This design allows TripEnergy to integrate with mesoscopic transport models and to be fast enough to run on a large network with minimal additional computation time. We expect it to benefit from and enable advances in transport simulation, including optimizing traffic network controls to minimize energy, evaluating the performance of different vehicle technologies under wide-scale adoption, and better understanding the energy and climate impacts of new infrastructure and policies.

The roller compacted concrete (RCC) dam has become one of the most competitive dam types due to its fast construction speed, low cost, and strong adaptability. However, the macroscale compaction test can hardly reflect the mesoscopic structure on the RCC’s rolling characteristics. According to the characteristics of RCC dam materials, a numerical discrete element method (DEM) is proposed in this paper, which is used to simulate the irregular shape and proportion of RCC aggregates. Moreover, a mesoscopic parameter inversion method based on the adaptive differential evolution (ADE) algorithm is proposed to enhance the efficiency of model contact parameters determination and overcome the inconvenience and time-consumption of conventional methods. Compared with the physical test, the simulation compression curve has good consistency with the physical test curve, and the proposed method can adequately reflect the physical and mechanical properties of RCC dam materials, which provides a basis for the subsequent research on the properties of RCC dam materials under different filling times.

The numerical simulation of fast-moving fronts originating from dam or levee breaches is a challenging task for small scale engineering projects. In this work, the use of fully three-dimensional Navier-Stokes (NS) equations and lattice Boltzmann method (LBM) is proposed for testing the validity of, respectively, macroscopic and mesoscopic mathematical models. Macroscopic simulations are performed employing an open-source computational fluid dynamics (CFD) code that solves the NS combined with the volume of fluid (VOF) multiphase method to represent free-surface flows. The mesoscopic model is a front-tracking experimental variant of the LBM. In the proposed LBM the air-gas interface is represented as a surface with zero thickness that handles the passage of the density field from the light to the dense phase and vice versa. A single set of LBM equations represents the liquid phase, while the free surface is characterized by an additional variable, the liquid volume fraction. Case studies show advantages and disadvantages of the proposed LBM and NS with specific regard to the computational efficiency and accuracy in dealing with the simulation of flows through complex geometries. In particular, the validation of the model application is developed by simulating the flow propagating through a synthetic urban setting and comparing results with analytical and experimental laboratory measurements.

The research of the mechanical properties of concrete, a kind of heterogeneous composite material, was previously established on basis of the mathematical model of random aggregate, which is used to study and analyze the mesoscopic damage mechanism of concrete. Although the shape and distribution of aggregate in the model built by this method are closer to the real structure of concrete, there is still a big difference between them and the real concrete specimen. In order to solve the problem of large amount of redundant computation in the CT reconstruction of full size cube space, a fast reconstruction method based on ray-casting algorithm is proposed. First, a method integrating the new bounding box technology with the plane intersection algorithm clusters were adopted to cut the body data and ray-casting effectively, and then, the polygon scanning and conversion was utilized to reduce the number of cast rays, finally, the adaptive sampling method was used to avoid repeatedly sampling same voxel so that the reconstruction efficiency of whole algorithm and the feasibility of numerical calculation can be enhanced. The experimental results demonstrate that the proposed algorithm can greatly improve the 3D rendering speed of concrete CT without affecting the image quality. It provides a more effective and reliable approach for correctly analyzing the mesoscopic damage mechanism and mechanical characteristics of concrete.

In practice, the critical step in building machine learning models of big data (BD) is costly in terms of time and the computing resources procedure of parameter tuning with a grid search. Due to the size, BD are comparable to mesoscopic physical systems. Hence, methods of statistical physics could be applied to BD. The paper shows that topic modeling demonstrates self-similar behavior under the condition of a varying number of clusters. Such behavior allows using a renormalization technique. The combination of a renormalization procedure with the Rényi entropy approach allows for fast searching of the optimal number of clusters. In this paper, the renormalization procedure is developed for the Latent Dirichlet Allocation (LDA) model with a variational Expectation-Maximization algorithm. The experiments were conducted on two document collections with a known number of clusters in two languages. The paper presents results for three versions of the renormalization procedure: (1) a renormalization with the random merging of clusters, (2) a renormalization based on minimal values of Kullback–Leibler divergence and (3) a renormalization with merging clusters with minimal values of Rényi entropy. The paper shows that the renormalization procedure allows finding the optimal number of topics 26 times faster than grid search without significant loss of quality.

Generating random aggregate models (RAMs) plays a key role in the mesoscopic modelling of concrete-like composite materials. The arbitrary geometry, wide gradation, and high volume ratio of aggregates pose a great challenge for fast and efficient numerical construction of concrete meso-structures. This paper presents a simple strategy for generating RAMs of concrete based on Laguerre tessellation, which mainly consists of three steps: tessellation, geometric smoothing, and scaling. The computer-assisted design (CAD) file of RAMs obtained by the proposed approach can be directly adopted for the construction of random numerical concrete samples. Combined with the image-based octree meshing algorithm, the scaled boundary finite element method (SBFEM) was adopted for an automatic stress analysis of mass concrete samples, and a parametric study was conducted to investigate the meso-structural effects on concrete elasticity properties. The modelling results successfully reproduced the increasing trend of concrete elastic modulus with the grading of coarse aggregates in literature test data and demonstrate the effectiveness of the proposed strategy.

Epilepsy is a dynamic and complex neurological disease affecting about 1% of the worldwide population, among which 30% of the patients are drug-resistant. Epilepsy is characterized by recurrent episodes of paroxysmal neural discharges (the so-called seizures), which manifest themselves through a large-amplitude rhythmic activity observed in depth-EEG recordings, in particular in local field potentials (LFPs). The signature characterizing the transition to seizures involves complex oscillatory patterns, which could serve as a marker to prevent seizure initiation by triggering appropriate therapeutic neurostimulation methods. To investigate such protocols, neurophysiological lumped-parameter models at the mesoscopic scale, namely neural mass models, are powerful tools that not only mimic the LFP signals but also give insights on the neural mechanisms related to different stages of seizures. Here, we analyze the multiple time-scale dynamics of a neural mass model and explain the underlying structure of the complex oscillations observed before seizure initiation. We investigate population-specific effects of the stimulation and the dependence of stimulation parameters on synaptic timescales. In particular, we show that intermediate stimulation frequencies (>20 Hz) can abort seizures if the timescale difference is pronounced. Those results have the potential in the design of therapeutic brain stimulation protocols based on the neurophysiological properties of tissue.

Cette thèse concerne l’étude de fiabilité des structures travaillant en fatigue. L’un des sujets importants tient à la compréhension et la modélisation des phénomènes de fatigue tant dans les situations normales qu’accidentelles. Dans les polycristaux, ces phénomènes sont de nature probabiliste : pour un même chargement cyclique, deux éprouvettes macroscopiquement identiques ont en effet des durées de vie différentes. Ceci provient du fait que les microstructures présentent une certaine variabilité. L’approche traditionnelle consiste à établir expérimentalement des courbes S-N. Du fait de la nature aléatoire des phénomènes de fatigue, cette procédure expérimentale doit être répétée un grand nombre de fois pour être statistiquement représentative. On considère en général que la prédiction sécuritaire de la durée de vie pour un niveau de chargement donné se situe à la moyenne du nombre de cycles à rupture moins deux fois l’écart-type. Cette approche est extrêmement lourde en termes d’efforts expérimentaux, mais aussi insuffisante du point de vue de l’analyse des risques. L’ objectif principal de ce travail est de développer un modèle d’évolution polycristallin intégrant plasticité et rupture, suffisamment rapide en temps de calcul pour permettre une analyse probabiliste et applicable à l’échelle d’une structure entière. Le modèle proposé repose sur un principe de minimisation de l’énergie incrémentale et cible les chargements de faible amplitude, pour lesquels la plasticité est confinée à quelques grains critiques supposés éloignés les uns des autres et sollicités selon un seul système de glissement. Dans un premier temps, nous nous plaçons dans le cadre d’un écrouissage isotrope et cinématique linéaire, en négligeant les interactions élastiques entre grains critiques. L’incrément de glissement plastique dans chaque grain critique est alors obtenu comme une fonction explicite des paramètres du matériau, du chargement, et d’un tenseur de localisation entièrement déterminé par la géométrie du grain et ses modules élastiques. Pour des grains ellipsoïdaux, ce tenseur de localisation s’identifie au tenseur d’Eshelby. La validité du modèle est étudiée par une comparaison avec des calculs aux éléments finis. Le modèle est ensuite étendu pour prendre en compte les effets dominants de l’interaction élastique entre grains. A partir d’une analyse des dislocations, on propose également une loi d’écrouissage non linéaire faisant apparaître l’effet de la taille des grains. Une extension du modèle polycristallin à ce type de loi est présentée. Pour un chargement cyclique, l’approche proposée permet de calculer l’évolution incrémentale d’un polycristal via des formules de récurrence analytiques, sans nécessiter aucune discrétisation spatiale. Dans la situation la plus simple où les interactions élastiques sont négligées, on obtient des formules directes donnant l’état stabilisé atteint au bout d’un grand nombre de cycles. Ce modèle polycristallin est exploité pour une analyse de la sensibilité de la durée de vie par rapport aux paramètres microstructuraux, tels que la taille des grains, les textures morphologiques et cristallographiques. L’influence du gradient de contraintes est également discutée. Enfin, l’applicabilité du modèle a des structures réelles est illustré sur l’étude des stents, dispositifs biomédicaux de petite taille qui sont soumis à un chargement cyclique en raison des battements cardiaques et pour lesquels la durée de vie en fatigue est cruciale
This thesis concerns the study of the reliability of structures working in fatigue. One of the most important subjects is the understanding and modelling of fatigue phenomena in both normal and accidental situations. In polycrystals, these phenomena are of a probabilistic nature: for the same cyclic loading, two macroscopically identical specimens have different lifetimes. This is because the microstructures exhibit a certain variability. The traditional approach is to establish S-N curves experimentally. Due to the random nature of the fatigue phenomena, this experimental procedure must be repeated a large number of times to be statistically representative. It is generally considered that the safe prediction of service life for a given loading level is the average number of cycles to failure minus twice the standard deviation. This approach is extremely cumbersome in terms of experimental effort, but also inadequate from the point of view of risk analysis.The main objective of this work is to develop a polycrystalline evolution model integrating plasticity and fracture, sufficiently fast in calculation time to allow probabilistic analysis and applicable on the scale of an entire structure. The proposed model is based on the principle of minimising incremental energy and targets low-amplitude loading, for which plasticity is confined to a few critical grains that are assumed to be distant from one another and loaded according to a single sliding system. Initially, we assume isotropic and linear kinematic strain hardening, neglecting elastic interactions between critical grains. The plastic slip increment in each critical grain is then obtained as an explicit function of the material parameters, the loading, and a localization tensor determined entirely by the grain geometry and its elastic moduli. For ellipsoidal grains, this location tensor is identified with the Eshelby tensor. The validity of the model is studied by comparison with finite element calculations. The model is then extended to take into account the dominant effects of elastic interaction between grains. Based on an analysis of dislocations, a non-linear strain-hardening law is also proposed, showing the effect of grain size. An extension of the polycrystalline model to this type of law is presented.For cyclic loading, the proposed approach makes it possible to calculate the incremental evolution of a polycrystal using analytical recurrence formulae, without requiring any spatial discretisation. In the simplest situation, where elastic interactions are neglected, direct formulae are obtained giving the stabilized state reached after a large number of cycles. This polycrystalline model is used to analyse the sensitivity of fatigue life to microstructural parameters such as grain size, morphological and crystallographic textures. The influence of the stress gradient is also discussed. Finally, the applicability of the model to real structures is illustrated by the study of stents, small biomedical devices that are subjected to cyclic loading due to heartbeats and for which fatigue life is crucial

Signal processing methods may constitute a substantial complement to visual analysis of SEEG signals in providing quantified information on signals (e.g. morphological characteristics) and in computing meaningful quantities that are not accessible to visual inspection (e.g. spectral properties or synchrony). In addition, and complementary to signal processing, computational neuroscience aims at developing models of epileptogenic networks and ultimately explaining some mechanisms involved in the generation of epileptiform activity. This chapter reviews a number of signal processing methods (time–frequency analysis, epileptogenicity index, and nonlinear correlation analysis) and computational models (at micro- and mesoscopic levels). The methods and models described illustrate the insight that can be gained about the information conveyed by SEEG signals recorded from epileptogenic networks observed during interictal (spikes and high-frequency oscillations) and ictal (fast-onset discharges) periods. Provided examples show that appropriate processing/modelling methods applied to electrophysiological signals can considerably improve the interpretation of SEEG recordings.

On the idea that fatigue damage is localized at the microscopic scale, a scale smaller than the mesoscopic one of the Representative Volume Element (RVE), a three-dimensional two scale damage model has been proposed in the past decade at LMT-Cachan for High Cycle Fatigue applications. It consists in the micromechanics analysis of a weak micro-inclusion subjected to plasticity and damage embedded in an elastic meso-element (the RVE of continuum mechanics). The consideration of plasticity coupled with damage equations at microscale, altogether with Eshelby-Kro¨ner localization law, allows to compute the value of microscopic damage up to failure for any kind of loading, 1D or 3D, cyclic or random, isothermal or anisothermal, mechanical, thermal or thermomechanical. A robust numerical scheme makes the computations fast and the new programming of a graphical user interface gives a software simple to use with facilities for material parameters identification: DAMAGE-2005. Examples of thermal and thermomechanical fatigue as well as applications on E.D.F. FATHER and INTHERPOL structures subjected to complex thermo-mechanical fatigue are detailed.

Governing key phenomena in core disruptive accidents (CDAs) in sodium-cooled fast reactors (SFRs) are supposed to be (1) fuel pin failure and disruption, (2) molten pool boiling, (3) melt freezing and blockage formation, (4) duct wall failure, (5) low-energy disruptive core motion, (6) debris-bed coolability, and (7) metal-fuel pin failure with eutectics between fuel and steel [1]. Although the systematic assessment program for SIMMER-III [4–7] has provided a technological basis that SIMMER-III is practically applicable to integral reactor safety analyses, further model development and validation efforts should be made to make future reactor calculations more reliable and rational. For mechanistic model development, a mesoscopic approach with the COMPASS code [1, 2, 3] is expected to advance the understanding of these key phenomena during event progression in CDAs. The COMPASS code has been developed since FY2005 (Japanese Fiscal Year, hereafter) to play a complementary role to SIMMER-III. In this paper, the overall analysis of SCARABEE-BE+3 test with the SIMMER-III and those with COMPASS, focusing the duct wall failure in a small temporal and spatial window cut from the SIMMER-III analysis results of the test, are described.

A five-year research project started in FY2005 (Japanese Fiscal Year, hereafter) to develop a code based on the Moving Particle Semi-implicit (MPS) method for detailed analysis of core disruptive accidents (CDAs) in sodium-cooled fast reactors (SFRs). The code is named COMPASS (Computer Code with Moving Particle Semi-implicit for Reactor Safety Analysis). CDAs have been almost exclusively analyzed with SIMMER-III [2], which is a two-dimensional multi-component multi-phase Eulerian fluid-dynamics code, coupled with fuel pin model and neutronics model. The COMPASS has been developed to play a role complementary to SIMMER-III in temporal and spatial scale viewpoint; COMPASS for mesoscopic using a small window cut off from SIMMER-III for macroscopic. We presented the project’s outline and the verification analyses of elastic structural mechanics module of the COMPASS in ICONE16 [1]. The COMPASS solves physical phenomena in CDAs coupling fluid dynamics and structural dynamics with phase changes, that is vaporization/condensation and melting/ freezing. The phase changes are based on nonequilibrium heat transfer-limited model and all “phase change paths” considered in SIMMER-III are implemented [20]. In FY2007, the elastoplastic model including thermal expansion and fracture are formulated in terms of MPS method and implemented in the COMPASS, where the model adopts the von Mises type yield condition and the maximum principal stress as fracture condition. To cope with large computing time, “stiffness reduction approximation” was developed and successfully implemented in the COMPASS besides parallelization effort. Verification problems are set to be suitable for analyses of SCARABEE tests, EAGLE tests and hypothetical CDAs in real plants so that they are suggesting issues to be solved by improving the models and calculation algorithms. The main objective of SCARABEE-N in-pile tests was to study the consequences of a hypothetical total instantaneous blockage (TIB) at the entrance of a liquid-metal reactor subassembly at full power [21]. The main objectives of the EAGLE program consisting of in-pile tests using IGR (Impulse Graphite Reactor) and out-of-pile tests at NNC/RK are; 1) to demonstrate effectiveness of special design concepts to eliminate the re-criticality issue, and 2) to acquire basic information on early-phase relocation of molten-core materials toward cold regions surrounding the core, which would be applicable to various core design concepts [22, 23]. In this paper, the formulations and the results of functional verification of elastoplastic models in CDA conditions will be presented.

Mathematical models that predict performance can aid in the understanding and development of solid oxide fuel cells (SOFCs). Of course, various modeling approaches exist involving different length scales. In particular, very significant advances are now taking place using microscopic models to understand the complex composite structures of electrodes and three-phase boundaries. Ultimately these advances should lead to predictions of cell behavior, which at present are measured empirically and inserted into macroscopic cell models. In order to achieve this ambitious goal, simulation tools based on these macroscopic models must be redesigned by matching them to the complex microscopic phenomena, which take place at the pore scale level. As a matter of fact, the macroscopic continuum approach essentially consists of applying some type of homogenization technique, which properly averages the underlying microscopic phenomena for producing measurable quantities. Unfortunately, these quantities in the porous electrodes of fuel cells are sometimes measurable only in principle. For this reason, this type of approach introduces additional uncertainties into the macroscopic models, which can significantly affect the numerical results, particularly their generality. This paper is part of an ongoing effort to address the problem by following an alternative approach. The key idea is to numerically simulate the underlying microscopic phenomena in an effort to bring the mathematical description nearer to actual reality. In particular, some recently developed mesoscopic tools appear to be very promising since the microscopic approach is, in this particular case, partially included in the numerical method itself. In particular, the models based on the lattice Boltzmann method (LBM) treat the problem by reproducing the collisions among particles of the same type, among particles belonging to different species, and finally among the species and the solid obstructions. Recently, a model developed by the authors was proposed which, based on LBM, models the fluid flow of reactive mixtures in randomly generated porous media by simulating the actual coupling interaction among the species. A parallel three–dimensional numerical code was developed in order to implement this model and to simulate the actual microscopic structures of SOFC porous electrodes. In this paper, a thin anode (50 micron) of Ni-metal / YSZ-electrolyte cermet for a high–temperature electrolyte supported SOFC was considered in the numerical simulations. The three–dimensional anode structure was derived by a regression analysis based on the granulometry law applied to some microscopic pictures obtained with an electron microscope. The numerical simulations show the spatial distribution of the mass fluxes for the reactants and the products of the electrochemical reactions. The described technique will allow one to design new improved materials and structures in order to statistically optimize these fluid paths.