Kinetic models analysis

Buzzi‐Ferraris, Guido; Manenti, Flavio

doi:10.1016/j.ces.2008.10.062

Cited by 79 publications

(55 citation statements)

References 29 publications

(33 reference statements)

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“…The nonlinear iterative algorithm for parameter estimation proposed by Buzzi-Ferraris and Manenti (2009) is applied to determine the non-negative Table 1: Values of the parameters used to define the isotropic energy functions (13), the anisotropic contribution (14) and the orientation of the preferred directions (15). The values of µ iso , µ l , µ t are given in MPa, the angle ϕ in degrees.…”

Section: Model Resultsmentioning

confidence: 99%

A constitutive description of the anisotropic response of the fascia lata

Pancheri

Eng

Lieberman

et al. 2014

Journal of the Mechanical Behavior of Biomedical Materials

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In this paper we propose a constitutive model to analyze in-plane extension of the fascia lata in goats. We first perform a histological analysis of the fascia that shows a well-organized bi-layered arrangement of undulated collagen fascicles oriented along two well defined directions. To develop a model consistent with the tissue structure we identify the absolute and relative thickness of each layer and the orientation of the preferred directions. New data are presented showing the mechanical response in uniaxial and planar biaxial extension. The main part of the paper focuses on a constitutive theory to describe the mechanical response. We provide a summary of the main ingredients of the nonlinear theory of elasticity and introduce a suitable strain-energy function to describe the anisotropic response of the fascia. In the final part of the paper we validate the model by showing good agreement of the numerical results and the experimental data.

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Section: Model Resultsmentioning

confidence: 99%

A constitutive description of the anisotropic response of the fascia lata

Pancheri

Eng

Lieberman

et al. 2014

Journal of the Mechanical Behavior of Biomedical Materials

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“…Although, there are others methods and software for parameter estimation available in the literature 44 , we have used the method available within gPROMS software as it provides state-of-the art parameter estimation capabilities which includes extensive statistical analysis using the information contained in nonlinear process models.…”

Section: Estimation Of Model Parametersmentioning

confidence: 99%

Optimal Design of a Trickle Bed Reactor for Light Fuel Oxidative Desulfurization Based on Experiments and Modeling

et al. 2015

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In this work, the performance of oxidative desulfurization (ODS) of dibenzothiophene (DBT) in light gas oil (LGO) is evaluated with a homemade manganese oxide (MnO 2 /γ-Al 2 O 3 ) catalyst. The catalyst is prepared by Incipient Wetness Impregnation (IWI) method with air under moderate operating conditions. The effect of different reaction parameters such as reaction temperature, liquid hour space velocity and initial concentration of DBT are also investigated experimentally.Developing a detailed and a validated trickle bed reactor (TBR) process model that can be employed for design and optimization of the ODS process, it is important to develop kinetic models for the relevant reactions with high accuracy. Best kinetic model for the ODS process taking into account hydrodynamic factors (mainly, catalyst effectiveness factor, catalyst wetting efficiency and internal diffusion) and the physical properties affecting the oxidation process is developed utilizing data from pilot plant experiments. An optimization technique based upon the minimization of the sum of the squared error between the experimental and predicted composition of oxidation process is used to determine the best parameters of the kinetic models. The predicted product conversion showed very good agreement with the experimental data for a wide range of the operating condition with absolute average errors less than 5%.

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“…Otherwise, we have an ill‐conditioned problem . To prevent this, we must study the state of information of our system to ensure a well‐conditioned parameter estimation problem . This means we have two important factors to consider, namely the data and the structure of the model.…”

Section: Flow Diagrammentioning

confidence: 99%

An approach to mechanistic event recognition applied on monitoring organic matter depletion in SBRs

et al. 2014

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A fundamental practice in process engineering is monitoring the state dynamics of a system. Unfortunately, observability of some states is related to high costs, time, and efforts. The mechanistic event recognition (MER) aims to detect an event (defined as a change of the system with specific significance to the operation of the process) that cannot be directly observed but has some predictable effect on the dynamics of the systems. MER attempts to apply fault diagnosis techniques using mechanistic “recognition” models to describe the process. A systematic method for building recognition models using optimal experimental design tools is presented. As proof of concept, the MER approach to detect organic matter depletion in sequencing batch reactors, measuring only ammonia, dissolved oxygen, and nitroxides is applied. The event, that is, consumption of organic matter to a level below 50 gCOD/m3, was successfully detected even though microbial activity is known to continue after organic matter depletion

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Kinetic models analysis

Cited by 79 publications

References 29 publications

A constitutive description of the anisotropic response of the fascia lata

A constitutive description of the anisotropic response of the fascia lata

Optimal Design of a Trickle Bed Reactor for Light Fuel Oxidative Desulfurization Based on Experiments and Modeling

An approach to mechanistic event recognition applied on monitoring organic matter depletion in SBRs

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