Energy-minimization multiscale based mesoscale modeling and applications in gas-fluidized catalytic reactors

2019 ◽  
Vol 35 (8) ◽  
pp. 879-915 ◽  
Author(s):  
Bona Lu ◽  
Yan Niu ◽  
Feiguo Chen ◽  
Nouman Ahmad ◽  
Wei Wang ◽  
...  
Keyword(s):  
Energy Minimization ◽  
Fluid Model ◽  
Scale Up ◽  
Flow Characteristics ◽  
Chemical Kinetic ◽  
Mesoscale Modeling ◽  
Catalytic Reactors ◽  
Chemical Kinetic Model ◽  
Starting Point ◽  
Wide Range

Abstract Gas-solid fluidization is intrinsically dynamic and manifests mesoscale structures spanning a wide range of length and timescales. When involved with reactions, more complex phenomena emerge and thus pose bigger challenges for modeling. As the mesoscale is critical to understand multiphase reactive flows, which the conventional two-fluid model without mesoscale modeling may be inadequate to resolve even using extremely fine grids, this review attempts to demonstrate that the energy-minimization multiscale (EMMS) model could be a starting point to develop such mesoscale modeling. Then, the EMMS-based mesoscale modeling with emphasis on formulation of drag coefficients for different fluidization regimes, modification of mass transfer coefficient, and other extensions are discussed in an attempt to resolve the emerging challenges. Its applications with examples of development of novel fluid catalytic cracking and methanol-to-olefins processes prove that the mesoscale modeling plays a remarkable role in improving the predictions in hydrodynamic behaviors and overall reaction rate. However, the product content primarily depends on the chemical kinetic model itself, suggesting the necessity of an effective coupling between chemical kinetics and flow characteristics. The mesoscale modeling can be believed to accelerate the traditional experimental-based scale-up process with much lower cost in the future.

scholarly journals One-Dimensional Simulation of Synergistic Desulfurization and Denitrification Processes for Electrostatic Precipitators Based on a Fluid-Chemical Reaction Hybrid Model

Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3249 ◽  
Author(s):  
Chao Zhang ◽  
Lixin Yang
Keyword(s):  
Flue Gas ◽  
Fluid Model ◽  
Chemical Kinetic ◽  
Discharge Voltage ◽  
Gaseous Pollutants ◽  
Chemical Kinetic Model ◽  
One Dimensional ◽  
High Purification ◽  
Electrostatic Precipitators ◽  
Control Technologies

Non-thermal plasma (NTP) technologies can be used to treat a variety of gaseous pollutants, and extensive research has been carried out worldwide because of its high purification efficiency, low dependence on temperature, and other advantages. NO and SO2 are the main gaseous pollutants in coal-fired flue gas. The plasma dynamics for desulfurization and denitrification is a hot topic in the field of NTP pollutant control technologies. In this paper, a one-dimensional fluid model for the simultaneous desulfurization and denitrification of flue gas by negative direct current (DC) corona discharge was established based on the traditional zero-dimensional chemical kinetic model. The simplified wire-cylindrical electrodes configuration and numerical simulation conditions are similar to the working process of electrostatic precipitators. The results obtained by the finite element method show that the removal efficiency of NO and SO2 is remarkable in the region with a radius of less than one centimeter around the high-voltage electrode, and the effective purification area expands with the increase of the discharge voltage. There are different removal pathways for NO at different positions in the removal region, while the removal of SO2 is mainly dependent on the oxidation by OH.

A novel mouse-driven ex vivo flow chamber for the study of leukocyte and platelet function

2004 ◽  
Vol 286 (4) ◽  
pp. C876-C892 ◽  
Author(s):  
Ali Hafezi-Moghadam ◽  
Kennard L. Thomas ◽  
Christian Cornelssen
Keyword(s):  
Shear Rate ◽  
Platelet Function ◽  
Ex Vivo ◽  
Fluid Model ◽  
Flow Characteristics ◽  
Flow Chamber ◽  
Wide Range ◽  
In Vitro Systems

Various in vitro and in vivo techniques exist for study of the microcirculation. Whereas in vivo systems impress with their physiological fidelity, in vitro systems excel in the amount of reduction that can be achieved. Here we introduce the autoperfused ex vivo flow chamber designed to study murine leukocytes and platelets under well-defined hemodynamic conditions. In our model, the murine heart continuously drives the blood flow through the chamber, providing a wide range of physiological shear rates. We used a balance of force approach to quantify the prevailing forces at the chamber walls. Numerical simulations show the flow characteristics in the chamber based on a shear-thinning fluid model. We demonstrate specific rolling of wild-type leukocytes on immobilized P-selectin, abolished by a blocking MAb. When uncoated, the surfaces having a constant shear rate supported individual platelet rolling, whereas on areas showing a rapid drop in shear platelets interacted in previously unreported grapelike conglomerates, suggesting an influence of shear rate on the type of platelet interaction. In summary, the ex vivo chamber amounts to an external vessel connecting the arterial and venous systems of a live mouse. This method combines the strengths of existing in vivo and in vitro systems in the study of leukocyte and platelet function.

scholarly journals Biodiversity Map Project – an integrative approach to biodiversity data and related scientific sources

2019 ◽  
Vol 3 ◽  
Author(s):  
Piotr Tykarski ◽  
Robert Meronka
Keyword(s):  
Scientific Information ◽  
Scale Up ◽  
Independent Solution ◽  
Scientific Data ◽  
Integrative Approach ◽  
Spatial Queries ◽  
Starting Point ◽  
Wide Range ◽  
Biodiversity Information ◽  
Occurrence Records

The Biodiversity Map is a long-term project of the Polish Biodiversity Information Network (KSIB) aimed at integration, presentation and management of comprehensive scientific data about species. The website (www.biomap.pl) was launched in 2012, following a period of extensive digitization work, covering bibliographic information, specimen collections, research notes and other sources of data. Initially, the project was focused on aggregating data about three insect orders: Coleoptera, Hemiptera and Lepidoptera, reported from Poland. Having achieved this goal, the geographic limits were removed and taxonomic scope is being gradually widened, currently including Araneae, Diptera, Hymenoptera, Odonata, Orthoptera and some other minor insect orders, intended to have a checklist of Polish fauna as a starting point. So far, it covers ca. 21,000 species concepts, including their taxonomic hierarchy and synonymy; and more than 1.1 million occurrence records with 19,000 bibliographic sources. The key functionality of the toolset supports visualization and management of links between different types of data and related underlying sources of the information, like scientific collections, literature, taxonomy, and occurrence records. The database can be accessed with a number of views, called "perspectives" and also by spatial queries through the map server, as an additional interface. This enables users to discover connections between information entities, e.g. publications based on studies from areas adjacent to a chosen locality on a map, or collections containing species covered in a publication. This approach is not common in existing systems and we trust it supports a wide range of potential scientific uses. The project database uses PostgreSQL with PostGIS for spatial queries. Two web applications are used for data presentation: the main text-based PHP browser (baza.biomap.pl) and the dynamic map, relying on JQuery, OpenLayers and MapServer (gis.biomap.pl). The latter provides users with an additional spatial dimension of interaction with the database and direct links to the main application. Recently, a third tool was built, making it possible for users to add and edit occurrence records, taxa, publications and authors. The solution is based on PHP and JavaScript combination. The data held within the system are planned to be connected to Global Biodiversity Information Facility and thus opened for a broad international community. The main obstacle hindering this step is limited resources to improve and scale up the database and software, as well as efforts to mobilize and organize the data. We need to ascertain the optimal method for dealing with numerous datasets derived from publications, and resolve the dilemma of whether to keep them separated or to merge them. The publications as a source of the scientific information and occurrence records have also been one of the main drivers for building the project software as an independent solution. Existing generic software packages popular in the GBIF community do not provide a direct way to link occurrence records with scientific literature, which is essential for scientific communities, at least in Poland.

Data-Driven Approaches to Learn HyChem Models

2021 ◽  
Author(s):  
Weiqi Ji ◽  
Julian Zanders ◽  
Ji-Woong Park ◽  
Sili Deng
Keyword(s):  
Genetic Algorithms ◽  
High Temperature ◽  
Low Temperature ◽  
Combustion Engine ◽  
Computational Cost ◽  
Model Performance ◽  
Chemical Kinetic ◽  
Stochastic Gradient Descent ◽  
Chemical Kinetic Model ◽  
Wide Range

Abstract The HyChem (Hybrid Chemistry) approach has recently been proposed for modeling high-temperature combustion of real, multi-component fuels. The approach combines lumped reaction steps for fuel thermal and oxidative pyrolysis with detailed chemistry for the oxidation of the resulting pyrolysis products. Determining the pyrolysis submodel requires extensive experimentation on speciation measurements. Recent work has been directed to learn HyChem from an existing HyChem model for a similar fuel, which requires less data. However, the approach usually shows substantial discrepancies with experimental data within the Negative Temperature Coefficient (NTC) regime, as the low-temperature chemistry is more fuel-specific than high-temperature chemistry. This paper proposes a machine learning approach to learn the HyChem models that can cover both high-temperature and low-temperature regimes. Specifically, we develop a HyChem model using the experimental datasets of ignition delay times covering a wide range of temperatures and equivalence ratios. The chemical kinetic model is treated as a neural network model, and we then employ stochastic gradient descent (SGD), a technique that was developed for deep learning, for the training. We demonstrate the approach in learning the HyChem model for F-24, which is a Jet-A derived fuel, and compare the results with previous work employing genetic algorithms. The results show that the SGD approach can achieve comparable model performance with genetic algorithms but the computational cost is reduced by 1000 times. In addition, with regularization in SGD, the SGD approach changes the kinetic parameters from their original values much less than genetic algorithm and is thus more likely to retrain mechanistic meanings. Finally, our approach is built upon open-source packages and can be applied to the development and optimization of chemical kinetic models for internal combustion engine simulations.

Laminar Flame Speed Measurements of Synthetic Gas Blends With Hydrocarbon Impurities

2015 ◽  
Author(s):  
Charles L. Keesee ◽  
Eric L. Petersen ◽  
Kuiwen Zhang ◽  
Henry J. Curran
Keyword(s):  
Laminar Flame ◽  
Initial Conditions ◽  
Chemical Kinetic ◽  
Flame Speed ◽  
Laminar Flame Speed ◽  
Coal Syngas ◽  
Chemical Kinetic Model ◽  
Wide Range ◽  
Synthetic Gas ◽  
Fuel Mixtures

New Laminar Flame Speed measurements have been taken for a wide range of syngas mixtures containing hydrocarbon impurities. These experiments began with two baseline syngas mixtures. The first of these baseline mixtures was a bio-syngas with a 50/50 H2/CO split, and the second baseline mixture was a coal syngas with a 40/60 H2/CO split. Experiments were conducted over a range of equivalence ratios from ϕ = 0.5 to 3 at initial conditions of 1 atm and 300 K. Upon completion of the baseline experiments, two different hydrocarbons were added to the fuel mixtures at levels ranging from 0.8 to 15% by volume, keeping the H2/CO ratio locked for the bio-syngas and coal syngas mixtures. The addition of these light hydrocarbons, namely CH4 and C2H6, had been shown in recent calculations by the authors to have significant impacts on the laminar flame speed, and the present experiments validated the suspected trends. For example, a 7% addition of methane to the coal-syngas blend decreased the peak flame speed by about 25% and shifted it from ϕ = 2.2 to a leaner value near ϕ = 1.5. Also, the addition of ethane at 1.7% reduced the mixture flame speed more than a similar addition of methane (1.6%). In general, the authors’ chemical kinetic model over predicted the laminar flame speed by about 10–20% for the mixtures containing the hydrocarbons. The decrease in laminar flame speed with the addition of the hydrocarbons can be explained by the increased importance of the inhibiting reaction CH3 + H (+M) ↔ CH4 (+M), which also explains the enhanced effect of C2H6 compared to CH4, where the former produces more CH3 radicals, particularly at fuel rich conditions.

Discovery of Antibacterial Agents Inhibiting the Energy-Coupling Factor (ECF) Transporters by Structure-Based Virtual Screening

2020 ◽  
Author(s):  
Eleonora Diamanti ◽  
Inda Setyawati ◽  
Spyridon Bousis ◽  
leticia mojas ◽  
lotteke Swier ◽  
...  
Keyword(s):  
Virtual Screening ◽  
Antibacterial Agents ◽  
Antimicrobial Agents ◽  
Energy Coupling ◽  
Coupling Factor ◽  
Design Synthesis ◽  
Screening Design ◽  
Starting Point ◽  
Wide Range ◽  
Vitamin Uptake

Here, we report on the virtual screening, design, synthesis and structure–activity relationships (SARs) of the first class of selective, antibacterial agents against the energy-coupling factor (ECF) transporters. The ECF transporters are a family of transmembrane proteins involved in the uptake of vitamins in a wide range of bacteria. Inhibition of the activity of these proteins could reduce the viability of pathogens that depend on vitamin uptake. Because of their central role in the metabolism of bacteria and their absence in humans, ECF transporters are novel potential antimicrobial targets to tackle infection. The hit compound’s metabolic and plasma stability, the potency (20, MIC Streptococcus pneumoniae = 2 µg/mL), the absence of cytotoxicity and a lack of resistance development under the conditions tested here suggest that this scaffold may represent a promising starting point for the development of novel antimicrobial agents with an unprecedented mechanism of action.<br>

scholarly journals The chemistry of cool circumstellar envelopes

1987 ◽  
Vol 122 ◽  
pp. 551-552
Author(s):  
L.A.M. Nejad ◽  
T. J. Millar
Keyword(s):  
Kinetic Model ◽  
Chemical Kinetic ◽  
Time Dependent ◽  
Circumstellar Envelopes ◽  
Chemical Kinetic Model ◽  
Ion Molecule Reactions ◽  
Cool Stars

We have developed a time-dependent chemical kinetic model to describe the chemistry in the circumstellar envelopes of cool stars, with particular reference to IRC + 10216. Our detailed calculations show that ion-molecule reactions are important in the formation of many of the species observed in IRC + 10216.

scholarly journals Consumer Neuroscience Techniques in Advertising Research: A Bibliometric Citation Analysis

2021 ◽  
Vol 13 (3) ◽  
pp. 1589
Author(s):  
Juan Sánchez-Fernández ◽  
Luis-Alberto Casado-Aranda ◽  
Ana-Belén Bastidas-Manzano
Keyword(s):  
Self Report ◽  
Future Research ◽  
Complex Nature ◽  
Clear Understanding ◽  
Continuous Growth ◽  
Main Research ◽  
Consumer Neuroscience ◽  
Starting Point ◽  
Wide Range ◽  
Performance Analysis Tools

The limitations of self-report techniques (i.e., questionnaires or surveys) in measuring consumer response to advertising stimuli have necessitated more objective and accurate tools from the fields of neuroscience and psychology for the study of consumer behavior, resulting in the creation of consumer neuroscience. This recent marketing sub-field stems from a wide range of disciplines and applies multiple types of techniques to diverse advertising subdomains (e.g., advertising constructs, media elements, or prediction strategies). Due to its complex nature and continuous growth, this area of research calls for a clear understanding of its evolution, current scope, and potential domains in the field of advertising. Thus, this current research is among the first to apply a bibliometric approach to clarify the main research streams analyzing advertising persuasion using neuroimaging. Particularly, this paper combines a comprehensive review with performance analysis tools of 203 papers published between 1986 and 2019 in outlets indexed by the ISI Web of Science database. Our findings describe the research tools, journals, and themes that are worth considering in future research. The current study also provides an agenda for future research and therefore constitutes a starting point for advertising academics and professionals intending to use neuroimaging techniques.

scholarly journals Development of Permeability Models for Saturated Fluid Flow across Arrays of Fibre Clusters

2002 ◽  
Vol 11 (3) ◽  
pp. 096369350201100
Author(s):  
E.M. Gravel ◽  
T.D. Papathanasiou
Keyword(s):  
Analytical Models ◽  
Dual Porosity ◽  
Hydraulic Permeability ◽  
Fibrous Media ◽  
Fibre Bundles ◽  
Hexagonal Packing ◽  
Composites Manufacturing ◽  
Starting Point ◽  
Wide Range ◽  
Flow Through

Dual porosity fibrous media are important in a number of applications, ranging from bioreactor design and transport in living systems to composites manufacturing. In the present study we are concerned with the development of predictive models for the hydraulic permeability ( Kp) of various arrays of fibre bundles. For this we carry out extensive computations for viscous flow through arrays of fibre bundles using the Boundary Element Method (BEM) implemented on a multi-processor computer. Up to 350 individual filaments, arranged in square or hexagonal packing within bundles, which are also arranged in square of hexagonal packing, are included in each simulation. These are simple but not trivial models for fibrous preforms used in composites manufacturing – dual porosity systems characterised by different inter- and intra-tow porosities. The way these porosities affect the hydraulic permeability of such media is currently unknown and is elucidated through our simulations. Following numerical solution of the governing equations, ( Kp) is calculated from the computed flowrate through Darcy's law and is expressed as function of the inter- and intra-tow porosities (φ, φt) and of the filament radius ( Rf). Numerical results are also compared to analytical models. The latter form the starting point in the development of a dimensionless correlation for the permeability of such dual porosity media. It is found that the numerically computed permeabilities follow that correlation for a wide range of φ i, φt and Rf.

Sign in / Sign up

Export Citation Format

Share Document