Pore Network Model and Simulation of Transport Process for Grain Drying

Chang, Jian; Yuan, Yuejin; Yang, Dongya; Liu, Xiangdong

doi:10.1002/ceat.201100036

Cited by 3 publications

(2 citation statements)

References 15 publications

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“…Based on the data presented in Figure 2, we may derive the following qualitative chemical ''mass transfer'' model (see, e.g., Chang et al, 2011;Likhoshvai and Ratushny, 2007) represented, in our case, by the coupled biochemical reactions…”

Section: Ode Modelsmentioning

confidence: 99%

Model Discrimination in Dynamic Molecular Systems: Application to Parotid De-differentiation Network

Kim

Venkatesh

et al. 2013

Journal of Computational Biology

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In modern systems biology the modeling of longitudinal data, such as changes in mRNA concentrations, is often of interest. Fully parametric, ordinary differential equations (ODE)-based models are typically developed for the purpose, but their lack of fit in some examples indicates that more flexible Bayesian models may be beneficial, particularly when there are relatively few data points available. However, under such sparse data scenarios it is often difficult to identify the most suitable model. The process of falsifying inappropriate candidate models is called model discrimination. We propose here a formal method of discrimination between competing Bayesian mixture-type longitudinal models that is both sensitive and sufficiently flexible to account for the complex variability of the longitudinal molecular data. The ideas from the field of Bayesian analysis of computer model validation are applied, along with modern Markov Chain Monte Carlo (MCMC) algorithms, in order to derive an appropriate Bayes discriminant rule. We restrict attention to the two-model comparison problem and present the application of the proposed rule to the mRNA data in the de-differentiation network of three mRNA concentrations in mammalian salivary glands as well as to a large synthetic dataset derived from the model used in the recent DREAM6 competition.

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Section: Ode Modelsmentioning

confidence: 99%

Model Discrimination in Dynamic Molecular Systems: Application to Parotid De-differentiation Network

Kim

Venkatesh

et al. 2013

Journal of Computational Biology

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“…Generally, the constructional procedure of the pore network physical model for porous media is shown in Figure 2, which includes four key steps: factual structure, distilled grids, regularized grids, and physical model. The model is mainly composed of two parts: pore-throat-pore network and solid skeleton [5,[14][15][16].…”

Section: Introductionmentioning

confidence: 99%

Pore Network Analysis of Zone Model for Porous Media Drying

Yuan

Zhao

Junnan

et al. 2014

Mathematical Problems in Engineering

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In view of the fact that the zone model for porous media drying cannot disclose the mechanism of liquid phase distribution effectively, a pore network model for the slow isothermal drying process of porous media was developed by applying the theories of pore network drying and transport-process, which fused the physical parameters of porous media, such as porosity, pore mean diameter, and pore size distribution into the model parameters, and a sand bed drying experiment was conducted to verify the validity of this model. The experiment and simulation results indicate that the pore network model could explain the slow isothermal drying process of porous media well. The pore size distributions of porous media have a great effect on the liquid phase distribution of the drying process. The dual-zone model is suitable for the porous media whose pore size distribution obeys Gaussian distribution, while the three-zone model is suitable for the porous media whose pore size distribution obeys the lognormal distribution when the drying analysis of porous media is conducted.

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Modelagem e simulação da secagem de arroz com casca: uma análise bibliométrica

Venturin

Silva

2019

RSD

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Rice is one of the staple foods of the Brazilian and world population. As part of post-harvest processing, drying is a critical step as it can affect the chemical, physical and nutritional properties of the final product. In this sense, the objective of this research consisted in the realization of a bibliometric review on the use of modeling and simulation in the drying process of paddy, providing an overview of the progress achieved, aspects to be developed and opportunities. A quantitative analysis of the related publications found in the Web of Science database was carried out, followed by a qualitative analysis of the most relevant articles. The results demonstrated the evolution of the subject and a great potential to be explored, mainly in the application of these models in the control, automation of the systems and in the support to decision making in real and large scale processes.

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Pore Network Model and Simulation of Transport Process for Grain Drying

Cited by 3 publications

References 15 publications

Model Discrimination in Dynamic Molecular Systems: Application to Parotid De-differentiation Network

Model Discrimination in Dynamic Molecular Systems: Application to Parotid De-differentiation Network

Pore Network Analysis of Zone Model for Porous Media Drying

Modelagem e simulação da secagem de arroz com casca: uma análise bibliométrica

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