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Relevant bibliographies by topics / Fast mesoscopic model

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Journal articles

Academic literature on the topic 'Fast mesoscopic model'

Author: Grafiati

Published: 13 April 2024

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Journal articles on the topic "Fast mesoscopic model"

1

Sakout, Sofia, Daniel Weisz-Patrault, and Alain Ehrlacher. "Energetic upscaling strategy for grain growth. i: Fast mesoscopic model based on dissipation." Acta Materialia 196 (September 2020): 261–79. http://dx.doi.org/10.1016/j.actamat.2020.06.032.

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2

Zhou, Xuesong, Jeffrey Taylor, and Filippo Pratico. "DTALite: A queue-based mesoscopic traffic simulator for fast model evaluation and calibration." Cogent Engineering 1, no. 1 (2014): 961345. http://dx.doi.org/10.1080/23311916.2014.961345.

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3

Wang, Enjiang, José M. Carcione, and Jing Ba. "Wave simulation in double-porosity media based on the Biot-Rayleigh theory." GEOPHYSICS 84, no. 4 (2019): WA11—WA21. http://dx.doi.org/10.1190/geo2018-0575.1.

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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 visco

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4

Needell, Zachary A., and Jessika E. Trancik. "Efficiently Simulating Personal Vehicle Energy Consumption in Mesoscopic Transport Models." Transportation Research Record: Journal of the Transportation Research Board 2672, no. 25 (2018): 163–73. http://dx.doi.org/10.1177/0361198118798244.

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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 a

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5

Li, Zilong, and Yang Tang. "Mesoscopic Simulation Method for Uniaxial Compression Test of RCC Dam Material Based on DEM." Mathematical Problems in Engineering 2020 (December 17, 2020): 1–13. http://dx.doi.org/10.1155/2020/6686609.

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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

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6

Biscarini, Chiara, Silvia Di Francesco, Fernando Nardi, and Piergiorgio Manciola. "Detailed Simulation of Complex Hydraulic Problems with Macroscopic and Mesoscopic Mathematical Methods." Mathematical Problems in Engineering 2013 (2013): 1–14. http://dx.doi.org/10.1155/2013/928309.

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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

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7

Zhao, Liang, Chang-Hua Li, Fa-Ning Dang, Chu-Jun Li, and Zhong-Xing Duan. "Concrete CT Image Quick Three-Dimensional Reconstruction Research." International Journal of Pattern Recognition and Artificial Intelligence 31, no. 10 (2017): 1757005. http://dx.doi.org/10.1142/s0218001417570051.

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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 reco

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8

Koltcov, Sergei, Vera Ignatenko, and Sergei Pashakhin. "Fast Tuning of Topic Models: An Application of Rényi Entropy and Renormalization Theory." Proceedings 46, no. 1 (2019): 5. http://dx.doi.org/10.3390/ecea-5-06674.

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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 searchi

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9

Guo, Yutai, Jialong He, Hui Jiang, Yuande Zhou, Feng Jin, and Chongmin Song. "A Simple Approach for Generating Random Aggregate Model of Concrete Based on Laguerre Tessellation and Its Application Analyses." Materials 13, no. 17 (2020): 3896. http://dx.doi.org/10.3390/ma13173896.

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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

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10

Köksal Ersöz, Elif, Julien Modolo, Fabrice Bartolomei, and Fabrice Wendling. "Neural mass modeling of slow-fast dynamics of seizure initiation and abortion." PLOS Computational Biology 16, no. 11 (2020): e1008430. http://dx.doi.org/10.1371/journal.pcbi.1008430.

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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 therap

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