2016-03-15
RESEARCH ARTICLE Biofilm Formation Mechanisms of Pseudomonas aeruginosa Predicted via Genome-Scale Kinetic Models of Bacterial Metabolism Francisco G...jaques.reifman.civ@mail.mil Abstract A hallmark of Pseudomonas aeruginosa is its ability to establish biofilm -based infections that are difficult to...eradicate. Biofilms are less susceptible to host inflammatory and immune responses and have higher antibiotic tolerance than free-living planktonic
Systematic construction of kinetic models from genome-scale metabolic networks.
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Natalie J Stanford
Full Text Available The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments.
Systematic Construction of Kinetic Models from Genome-Scale Metabolic Networks
Smallbone, Kieran; Klipp, Edda; Mendes, Pedro; Liebermeister, Wolfram
2013-01-01
The quantitative effects of environmental and genetic perturbations on metabolism can be studied in silico using kinetic models. We present a strategy for large-scale model construction based on a logical layering of data such as reaction fluxes, metabolite concentrations, and kinetic constants. The resulting models contain realistic standard rate laws and plausible parameters, adhere to the laws of thermodynamics, and reproduce a predefined steady state. These features have not been simultaneously achieved by previous workflows. We demonstrate the advantages and limitations of the workflow by translating the yeast consensus metabolic network into a kinetic model. Despite crudely selected data, the model shows realistic control behaviour, a stable dynamic, and realistic response to perturbations in extracellular glucose concentrations. The paper concludes by outlining how new data can continuously be fed into the workflow and how iterative model building can assist in directing experiments. PMID:24324546
Genome scale metabolic modeling of cancer
DEFF Research Database (Denmark)
Nilsson, Avlant; Nielsen, Jens
2017-01-01
of metabolism which allows simulation and hypotheses testing of metabolic strategies. It has successfully been applied to many microorganisms and is now used to study cancer metabolism. Generic models of human metabolism have been reconstructed based on the existence of metabolic genes in the human genome......Cancer cells reprogram metabolism to support rapid proliferation and survival. Energy metabolism is particularly important for growth and genes encoding enzymes involved in energy metabolism are frequently altered in cancer cells. A genome scale metabolic model (GEM) is a mathematical formalization...
Genome-scale biological models for industrial microbial systems.
Xu, Nan; Ye, Chao; Liu, Liming
2018-04-01
The primary aims and challenges associated with microbial fermentation include achieving faster cell growth, higher productivity, and more robust production processes. Genome-scale biological models, predicting the formation of an interaction among genetic materials, enzymes, and metabolites, constitute a systematic and comprehensive platform to analyze and optimize the microbial growth and production of biological products. Genome-scale biological models can help optimize microbial growth-associated traits by simulating biomass formation, predicting growth rates, and identifying the requirements for cell growth. With regard to microbial product biosynthesis, genome-scale biological models can be used to design product biosynthetic pathways, accelerate production efficiency, and reduce metabolic side effects, leading to improved production performance. The present review discusses the development of microbial genome-scale biological models since their emergence and emphasizes their pertinent application in improving industrial microbial fermentation of biological products.
Use of genome-scale microbial models for metabolic engineering
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Patil, Kiran Raosaheb; Åkesson, M.; Nielsen, Jens
2004-01-01
Metabolic engineering serves as an integrated approach to design new cell factories by providing rational design procedures and valuable mathematical and experimental tools. Mathematical models have an important role for phenotypic analysis, but can also be used for the design of optimal metaboli...... network structures. The major challenge for metabolic engineering in the post-genomic era is to broaden its design methodologies to incorporate genome-scale biological data. Genome-scale stoichiometric models of microorganisms represent a first step in this direction....
Genome-scale modeling for metabolic engineering.
Simeonidis, Evangelos; Price, Nathan D
2015-03-01
We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.
Next-generation genome-scale models for metabolic engineering
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King, Zachary A.; Lloyd, Colton J.; Feist, Adam M.
2015-01-01
Constraint-based reconstruction and analysis (COBRA) methods have become widely used tools for metabolic engineering in both academic and industrial laboratories. By employing a genome-scale in silico representation of the metabolic network of a host organism, COBRA methods can be used to predict...... examples of applying COBRA methods to strain optimization are presented and discussed. Then, an outlook is provided on the next generation of COBRA models and the new types of predictions they will enable for systems metabolic engineering....
Modeling Lactococcus lactis using a genome-scale flux model
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Nielsen Jens
2005-06-01
Full Text Available Abstract Background Genome-scale flux models are useful tools to represent and analyze microbial metabolism. In this work we reconstructed the metabolic network of the lactic acid bacteria Lactococcus lactis and developed a genome-scale flux model able to simulate and analyze network capabilities and whole-cell function under aerobic and anaerobic continuous cultures. Flux balance analysis (FBA and minimization of metabolic adjustment (MOMA were used as modeling frameworks. Results The metabolic network was reconstructed using the annotated genome sequence from L. lactis ssp. lactis IL1403 together with physiological and biochemical information. The established network comprised a total of 621 reactions and 509 metabolites, representing the overall metabolism of L. lactis. Experimental data reported in the literature was used to fit the model to phenotypic observations. Regulatory constraints had to be included to simulate certain metabolic features, such as the shift from homo to heterolactic fermentation. A minimal medium for in silico growth was identified, indicating the requirement of four amino acids in addition to a sugar. Remarkably, de novo biosynthesis of four other amino acids was observed even when all amino acids were supplied, which is in good agreement with experimental observations. Additionally, enhanced metabolic engineering strategies for improved diacetyl producing strains were designed. Conclusion The L. lactis metabolic network can now be used for a better understanding of lactococcal metabolic capabilities and potential, for the design of enhanced metabolic engineering strategies and for integration with other types of 'omic' data, to assist in finding new information on cellular organization and function.
Genome-scale modeling of yeast: chronology, applications and critical perspectives.
Lopes, Helder; Rocha, Isabel
2017-08-01
Over the last 15 years, several genome-scale metabolic models (GSMMs) were developed for different yeast species, aiding both the elucidation of new biological processes and the shift toward a bio-based economy, through the design of in silico inspired cell factories. Here, an historical perspective of the GSMMs built over time for several yeast species is presented and the main inheritance patterns among the metabolic reconstructions are highlighted. We additionally provide a critical perspective on the overall genome-scale modeling procedure, underlining incomplete model validation and evaluation approaches and the quest for the integration of regulatory and kinetic information into yeast GSMMs. A summary of experimentally validated model-based metabolic engineering applications of yeast species is further emphasized, while the main challenges and future perspectives for the field are finally addressed. © FEMS 2017.
Incorporating Protein Biosynthesis into the Saccharomyces cerevisiae Genome-scale Metabolic Model
DEFF Research Database (Denmark)
Olivares Hernandez, Roberto
Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been construc......Based on stoichiometric biochemical equations that occur into the cell, the genome-scale metabolic models can quantify the metabolic fluxes, which are regarded as the final representation of the physiological state of the cell. For Saccharomyces Cerevisiae the genome scale model has been...
Using Genome-scale Models to Predict Biological Capabilities
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O’Brien, Edward J.; Monk, Jonathan M.; Palsson, Bernhard O.
2015-01-01
Constraint-based reconstruction and analysis (COBRA) methods at the genome scale have been under development since the first whole-genome sequences appeared in the mid-1990s. A few years ago, this approach began to demonstrate the ability to predict a range of cellular functions, including cellul...
BiGG Models: A platform for integrating, standardizing and sharing genome-scale models
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King, Zachary A.; Lu, Justin; Dräger, Andreas
2016-01-01
Genome-scale metabolic models are mathematically-structured knowledge bases that can be used to predict metabolic pathway usage and growth phenotypes. Furthermore, they can generate and test hypotheses when integrated with experimental data. To maximize the value of these models, centralized repo...
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Jensen Paul A
2011-09-01
Full Text Available Abstract Background Several methods have been developed for analyzing genome-scale models of metabolism and transcriptional regulation. Many of these methods, such as Flux Balance Analysis, use constrained optimization to predict relationships between metabolic flux and the genes that encode and regulate enzyme activity. Recently, mixed integer programming has been used to encode these gene-protein-reaction (GPR relationships into a single optimization problem, but these techniques are often of limited generality and lack a tool for automating the conversion of rules to a coupled regulatory/metabolic model. Results We present TIGER, a Toolbox for Integrating Genome-scale Metabolism, Expression, and Regulation. TIGER converts a series of generalized, Boolean or multilevel rules into a set of mixed integer inequalities. The package also includes implementations of existing algorithms to integrate high-throughput expression data with genome-scale models of metabolism and transcriptional regulation. We demonstrate how TIGER automates the coupling of a genome-scale metabolic model with GPR logic and models of transcriptional regulation, thereby serving as a platform for algorithm development and large-scale metabolic analysis. Additionally, we demonstrate how TIGER's algorithms can be used to identify inconsistencies and improve existing models of transcriptional regulation with examples from the reconstructed transcriptional regulatory network of Saccharomyces cerevisiae. Conclusion The TIGER package provides a consistent platform for algorithm development and extending existing genome-scale metabolic models with regulatory networks and high-throughput data.
Genome-scale metabolic models as platforms for strain design and biological discovery.
Mienda, Bashir Sajo
2017-07-01
Genome-scale metabolic models (GEMs) have been developed and used in guiding systems' metabolic engineering strategies for strain design and development. This strategy has been used in fermentative production of bio-based industrial chemicals and fuels from alternative carbon sources. However, computer-aided hypotheses building using established algorithms and software platforms for biological discovery can be integrated into the pipeline for strain design strategy to create superior strains of microorganisms for targeted biosynthetic goals. Here, I described an integrated workflow strategy using GEMs for strain design and biological discovery. Specific case studies of strain design and biological discovery using Escherichia coli genome-scale model are presented and discussed. The integrated workflow presented herein, when applied carefully would help guide future design strategies for high-performance microbial strains that have existing and forthcoming genome-scale metabolic models.
Expanding a dynamic flux balance model of yeast fermentation to genome-scale
2011-01-01
Background Yeast is considered to be a workhorse of the biotechnology industry for the production of many value-added chemicals, alcoholic beverages and biofuels. Optimization of the fermentation is a challenging task that greatly benefits from dynamic models able to accurately describe and predict the fermentation profile and resulting products under different genetic and environmental conditions. In this article, we developed and validated a genome-scale dynamic flux balance model, using experimentally determined kinetic constraints. Results Appropriate equations for maintenance, biomass composition, anaerobic metabolism and nutrient uptake are key to improve model performance, especially for predicting glycerol and ethanol synthesis. Prediction profiles of synthesis and consumption of the main metabolites involved in alcoholic fermentation closely agreed with experimental data obtained from numerous lab and industrial fermentations under different environmental conditions. Finally, fermentation simulations of genetically engineered yeasts closely reproduced previously reported experimental results regarding final concentrations of the main fermentation products such as ethanol and glycerol. Conclusion A useful tool to describe, understand and predict metabolite production in batch yeast cultures was developed. The resulting model, if used wisely, could help to search for new metabolic engineering strategies to manage ethanol content in batch fermentations. PMID:21595919
Genome Scale Modeling in Systems Biology: Algorithms and Resources
Najafi, Ali; Bidkhori, Gholamreza; Bozorgmehr, Joseph H.; Koch, Ina; Masoudi-Nejad, Ali
2014-01-01
In recent years, in silico studies and trial simulations have complemented experimental procedures. A model is a description of a system, and a system is any collection of interrelated objects; an object, moreover, is some elemental unit upon which observations can be made but whose internal structure either does not exist or is ignored. Therefore, any network analysis approach is critical for successful quantitative modeling of biological systems. This review highlights some of most popular and important modeling algorithms, tools, and emerging standards for representing, simulating and analyzing cellular networks in five sections. Also, we try to show these concepts by means of simple example and proper images and graphs. Overall, systems biology aims for a holistic description and understanding of biological processes by an integration of analytical experimental approaches along with synthetic computational models. In fact, biological networks have been developed as a platform for integrating information from high to low-throughput experiments for the analysis of biological systems. We provide an overview of all processes used in modeling and simulating biological networks in such a way that they can become easily understandable for researchers with both biological and mathematical backgrounds. Consequently, given the complexity of generated experimental data and cellular networks, it is no surprise that researchers have turned to computer simulation and the development of more theory-based approaches to augment and assist in the development of a fully quantitative understanding of cellular dynamics. PMID:24822031
Metingear: a development environment for annotating genome-scale metabolic models.
May, John W; James, A Gordon; Steinbeck, Christoph
2013-09-01
Genome-scale metabolic models often lack annotations that would allow them to be used for further analysis. Previous efforts have focused on associating metabolites in the model with a cross reference, but this can be problematic if the reference is not freely available, multiple resources are used or the metabolite is added from a literature review. Associating each metabolite with chemical structure provides unambiguous identification of the components and a more detailed view of the metabolism. We have developed an open-source desktop application that simplifies the process of adding database cross references and chemical structures to genome-scale metabolic models. Annotated models can be exported to the Systems Biology Markup Language open interchange format. Source code, binaries, documentation and tutorials are freely available at http://johnmay.github.com/metingear. The application is implemented in Java with bundles available for MS Windows and Macintosh OS X.
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Geng, Jun; Nielsen, Jens
2017-01-01
The arising prevalence of metabolic diseases calls for a holistic approach for analysis of the underlying nature of abnormalities in cellular functions. Through mathematic representation and topological analysis of cellular metabolism, GEnome scale metabolic Models (GEMs) provide a promising fram...... that correctly describe interactions between cells or tissues, and we therefore discuss how GEMs can be integrated with blood circulation models. Finally, we end the review with proposing some possible future research directions....
Genome scale models of yeast: towards standardized evaluation and consistent omic integration
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Sanchez, Benjamin J.; Nielsen, Jens
2015-01-01
Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published and are curre......Genome scale models (GEMs) have enabled remarkable advances in systems biology, acting as functional databases of metabolism, and as scaffolds for the contextualization of high-throughput data. In the case of Saccharomyces cerevisiae (budding yeast), several GEMs have been published...... in which all levels of omics data (from gene expression to flux) have been integrated in yeast GEMs. Relevant conclusions and current challenges for both GEM evaluation and omic integration are highlighted....
Identifying anti-growth factors for human cancer cell lines through genome-scale metabolic modeling
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Ghaffari, Pouyan; Mardinoglu, Adil; Asplund, Anna
2015-01-01
Human cancer cell lines are used as important model systems to study molecular mechanisms associated with tumor growth, hereunder how genomic and biological heterogeneity found in primary tumors affect cellular phenotypes. We reconstructed Genome scale metabolic models (GEMs) for eleven cell lines...... based on RNA-Seq data and validated the functionality of these models with data from metabolite profiling. We used cell line-specific GEMs to analyze the differences in the metabolism of cancer cell lines, and to explore the heterogeneous expression of the metabolic subsystems. Furthermore, we predicted...... for inhibition of cell growth may provide leads for the development of efficient cancer treatment strategies....
Genome-scale modeling of the protein secretory machinery in yeast
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Feizi, Amir; Österlund, Tobias; Petranovic, Dina
2013-01-01
The protein secretory machinery in Eukarya is involved in post-translational modification (PTMs) and sorting of the secretory and many transmembrane proteins. While the secretory machinery has been well-studied using classic reductionist approaches, a holistic view of its complex nature is lacking....... Here, we present the first genome-scale model for the yeast secretory machinery which captures the knowledge generated through more than 50 years of research. The model is based on the concept of a Protein Specific Information Matrix (PSIM: characterized by seven PTMs features). An algorithm...
Predicting growth of the healthy infant using a genome scale metabolic model.
Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens
2017-01-01
An estimated 165 million children globally have stunted growth, and extensive growth data are available. Genome scale metabolic models allow the simulation of molecular flux over each metabolic enzyme, and are well adapted to analyze biological systems. We used a human genome scale metabolic model to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body composition. The model corroborates the finding that essential amino and fatty acids do not limit growth, but that energy is the main growth limiting factor. Disruptions to the supply and demand of energy markedly affected the predicted growth, indicating that elevated energy expenditure may be detrimental. The model was used to simulate the metabolic effect of mineral deficiencies, and showed the greatest growth reduction for deficiencies in copper, iron, and magnesium ions which affect energy production through oxidative phosphorylation. The model and simulation method were integrated to a platform and shared with the research community. The growth model constitutes another step towards the complete representation of human metabolism, and may further help improve the understanding of the mechanisms underlying stunting.
Genome-scale model guided design of Propionibacterium for enhanced propionic acid production
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Laura Navone
2018-06-01
Full Text Available Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp. shermanii and the pan-Propionibacterium genome-scale metabolic models (GEMs to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp. shermanii, two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP, Zwf (glucose-6-phosphate 1-dehydrogenase and Pgl (6-phosphogluconolactonase. Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK and sodium-pumping methylmalonyl-CoA decarboxylase (MMD was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in
Irani, Zahra Azimzadeh; Kerkhoven, Eduard J; Shojaosadati, Seyed Abbas; Nielsen, Jens
2016-05-01
Pichia pastoris is used for commercial production of human therapeutic proteins, and genome-scale models of P. pastoris metabolism have been generated in the past to study the metabolism and associated protein production by this yeast. A major challenge with clinical usage of recombinant proteins produced by P. pastoris is the difference in N-glycosylation of proteins produced by humans and this yeast. However, through metabolic engineering, a P. pastoris strain capable of producing humanized N-glycosylated proteins was constructed. The current genome-scale models of P. pastoris do not address native nor humanized N-glycosylation, and we therefore developed ihGlycopastoris, an extension to the iLC915 model with both native and humanized N-glycosylation for recombinant protein production, but also an estimation of N-glycosylation of P. pastoris native proteins. This new model gives a better prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required for using these models to understand and optimize protein production processes. © 2015 Wiley Periodicals, Inc.
Sadhukhan, Priyanka P; Raghunathan, Anu
2014-01-01
Genome Scale Metabolic Modeling methods represent one way to compute whole cell function starting from the genome sequence of an organism and contribute towards understanding and predicting the genotype-phenotype relationship. About 80 models spanning all the kingdoms of life from archaea to eukaryotes have been built till date and used to interrogate cell phenotype under varying conditions. These models have been used to not only understand the flux distribution in evolutionary conserved pathways like glycolysis and the Krebs cycle but also in applications ranging from value added product formation in Escherichia coli to predicting inborn errors of Homo sapiens metabolism. This chapter describes a protocol that delineates the process of genome scale metabolic modeling for analysing host-pathogen behavior and interaction using flux balance analysis (FBA). The steps discussed in the process include (1) reconstruction of a metabolic network from the genome sequence, (2) its representation in a precise mathematical framework, (3) its translation to a model, and (4) the analysis using linear algebra and optimization. The methods for biological interpretations of computed cell phenotypes in the context of individual host and pathogen models and their integration are also discussed.
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Sriram Chandrasekaran
2017-12-01
Full Text Available Summary: Metabolism is an emerging stem cell hallmark tied to cell fate, pluripotency, and self-renewal, yet systems-level understanding of stem cell metabolism has been limited by the lack of genome-scale network models. Here, we develop a systems approach to integrate time-course metabolomics data with a computational model of metabolism to analyze the metabolic state of naive and primed murine pluripotent stem cells. Using this approach, we find that one-carbon metabolism involving phosphoglycerate dehydrogenase, folate synthesis, and nucleotide synthesis is a key pathway that differs between the two states, resulting in differential sensitivity to anti-folates. The model also predicts that the pluripotency factor Lin28 regulates this one-carbon metabolic pathway, which we validate using metabolomics data from Lin28-deficient cells. Moreover, we identify and validate metabolic reactions related to S-adenosyl-methionine production that can differentially impact histone methylation in naive and primed cells. Our network-based approach provides a framework for characterizing metabolic changes influencing pluripotency and cell fate. : Chandrasekaran et al. use computational modeling, metabolomics, and metabolic inhibitors to discover metabolic differences between various pluripotent stem cell states and infer their impact on stem cell fate decisions. Keywords: systems biology, stem cell biology, metabolism, genome-scale modeling, pluripotency, histone methylation, naive (ground state, primed state, cell fate, metabolic network
Klier, Christine
2012-03-06
The integration of genome-scale, constraint-based models of microbial cell function into simulations of contaminant transport and fate in complex groundwater systems is a promising approach to help characterize the metabolic activities of microorganisms in natural environments. In constraint-based modeling, the specific uptake flux rates of external metabolites are usually determined by Michaelis-Menten kinetic theory. However, extensive data sets based on experimentally measured values are not always available. In this study, a genome-scale model of Pseudomonas putida was used to study the key issue of uncertainty arising from the parametrization of the influx of two growth-limiting substrates: oxygen and toluene. The results showed that simulated growth rates are highly sensitive to substrate affinity constants and that uncertainties in specific substrate uptake rates have a significant influence on the variability of simulated microbial growth. Michaelis-Menten kinetic theory does not, therefore, seem to be appropriate for descriptions of substrate uptake processes in the genome-scale model of P. putida. Microbial growth rates of P. putida in subsurface environments can only be accurately predicted if the processes of complex substrate transport and microbial uptake regulation are sufficiently understood in natural environments and if data-driven uptake flux constraints can be applied.
Network Thermodynamic Curation of Human and Yeast Genome-Scale Metabolic Models
Martínez, Verónica S.; Quek, Lake-Ee; Nielsen, Lars K.
2014-01-01
Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. PMID:25028891
Vongsangnak, Wanwipa; Klanchui, Amornpan; Tawornsamretkit, Iyarest; Tatiyaborwornchai, Witthawin; Laoteng, Kobkul; Meechai, Asawin
2016-06-01
We present a novel genome-scale metabolic model iWV1213 of Mucor circinelloides, which is an oleaginous fungus for industrial applications. The model contains 1213 genes, 1413 metabolites and 1326 metabolic reactions across different compartments. We demonstrate that iWV1213 is able to accurately predict the growth rates of M. circinelloides on various nutrient sources and culture conditions using Flux Balance Analysis and Phenotypic Phase Plane analysis. Comparative analysis of three oleaginous genome-scale models, including M. circinelloides (iWV1213), Mortierella alpina (iCY1106) and Yarrowia lipolytica (iYL619_PCP) revealed that iWV1213 possesses a higher number of genes involved in carbohydrate, amino acid, and lipid metabolisms that might contribute to its versatility in nutrient utilization. Moreover, the identification of unique and common active reactions among the Zygomycetes oleaginous models using Flux Variability Analysis unveiled a set of gene/enzyme candidates as metabolic engineering targets for cellular improvement. Thus, iWV1213 offers a powerful metabolic engineering tool for multi-level omics analysis, enabling strain optimization as a cell factory platform of lipid-based production. Copyright © 2016 Elsevier B.V. All rights reserved.
Principles of proteome allocation are revealed using proteomic data and genome-scale models
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Yang, Laurence; Yurkovich, James T.; Lloyd, Colton J.
2016-01-01
to metabolism and fitness. Using proteomics data, we formulated allocation constraints for key proteome sectors in the ME model. The resulting calibrated model effectively computed the "generalist" (wild-type) E. coli proteome and phenotype across diverse growth environments. Across 15 growth conditions......Integrating omics data to refine or make context-specific models is an active field of constraint-based modeling. Proteomics now cover over 95% of the Escherichia coli proteome by mass. Genome-scale models of Metabolism and macromolecular Expression (ME) compute proteome allocation linked...... of these sectors for the general stress response sigma factor sigma(S). Finally, the sector constraints represent a general formalism for integrating omics data from any experimental condition into constraint-based ME models. The constraints can be fine-grained (individual proteins) or coarse-grained (functionally...
Reconstruction of genome-scale human metabolic models using omics data
DEFF Research Database (Denmark)
Ryu, Jae Yong; Kim, Hyun Uk; Lee, Sang Yup
2015-01-01
used to describe metabolic phenotypes of healthy and diseased human tissues and cells, and to predict therapeutic targets. Here we review recent trends in genome-scale human metabolic modeling, including various generic and tissue/cell type-specific human metabolic models developed to date, and methods......, databases and platforms used to construct them. For generic human metabolic models, we pay attention to Recon 2 and HMR 2.0 with emphasis on data sources used to construct them. Draft and high-quality tissue/cell type-specific human metabolic models have been generated using these generic human metabolic...... refined through gap filling, reaction directionality assignment and the subcellular localization of metabolic reactions. We review relevant tools for this model refinement procedure as well. Finally, we suggest the direction of further studies on reconstructing an improved human metabolic model....
Reconstruction and analysis of a genome-scale metabolic model for Scheffersomyces stipitis
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Balagurunathan Balaji
2012-02-01
Full Text Available Abstract Background Fermentation of xylose, the major component in hemicellulose, is essential for economic conversion of lignocellulosic biomass to fuels and chemicals. The yeast Scheffersomyces stipitis (formerly known as Pichia stipitis has the highest known native capacity for xylose fermentation and possesses several genes for lignocellulose bioconversion in its genome. Understanding the metabolism of this yeast at a global scale, by reconstructing the genome scale metabolic model, is essential for manipulating its metabolic capabilities and for successful transfer of its capabilities to other industrial microbes. Results We present a genome-scale metabolic model for Scheffersomyces stipitis, a native xylose utilizing yeast. The model was reconstructed based on genome sequence annotation, detailed experimental investigation and known yeast physiology. Macromolecular composition of Scheffersomyces stipitis biomass was estimated experimentally and its ability to grow on different carbon, nitrogen, sulphur and phosphorus sources was determined by phenotype microarrays. The compartmentalized model, developed based on an iterative procedure, accounted for 814 genes, 1371 reactions, and 971 metabolites. In silico computed growth rates were compared with high-throughput phenotyping data and the model could predict the qualitative outcomes in 74% of substrates investigated. Model simulations were used to identify the biosynthetic requirements for anaerobic growth of Scheffersomyces stipitis on glucose and the results were validated with published literature. The bottlenecks in Scheffersomyces stipitis metabolic network for xylose uptake and nucleotide cofactor recycling were identified by in silico flux variability analysis. The scope of the model in enhancing the mechanistic understanding of microbial metabolism is demonstrated by identifying a mechanism for mitochondrial respiration and oxidative phosphorylation. Conclusion The genome-scale
Improved annotation through genome-scale metabolic modeling of Aspergillus oryzae
DEFF Research Database (Denmark)
Vongsangnak, Wanwipa; Olsen, Peter; Hansen, Kim
2008-01-01
Background: Since ancient times the filamentous fungus Aspergillus oryzae has been used in the fermentation industry for the production of fermented sauces and the production of industrial enzymes. Recently, the genome sequence of A. oryzae with 12,074 annotated genes was released but the number...... to a genome scale metabolic model of A. oryzae. Results: Our assembled EST sequences we identified 1,046 newly predicted genes in the A. oryzae genome. Furthermore, it was possible to assign putative protein functions to 398 of the newly predicted genes. Noteworthy, our annotation strategy resulted...... model was validated and shown to correctly describe the phenotypic behavior of A. oryzae grown on different carbon sources. Conclusion: A much enhanced annotation of the A. oryzae genome was performed and a genomescale metabolic model of A. oryzae was reconstructed. The model accurately predicted...
Reliable and efficient solution of genome-scale models of Metabolism and macromolecular Expression
DEFF Research Database (Denmark)
Ma, Ding; Yang, Laurence; Fleming, Ronan M. T.
2017-01-01
orders of magnitude. Data values also have greatly varying magnitudes. Standard double-precision solvers may return inaccurate solutions or report that no solution exists. Exact simplex solvers based on rational arithmetic require a near-optimal warm start to be practical on large problems (current ME......Constraint-Based Reconstruction and Analysis (COBRA) is currently the only methodology that permits integrated modeling of Metabolism and macromolecular Expression (ME) at genome-scale. Linear optimization computes steady-state flux solutions to ME models, but flux values are spread over many...... models have 70,000 constraints and variables and will grow larger). We have developed a quadrupleprecision version of our linear and nonlinear optimizer MINOS, and a solution procedure (DQQ) involving Double and Quad MINOS that achieves reliability and efficiency for ME models and other challenging...
Improved evidence-based genome-scale metabolic models for maize leaf, embryo, and endosperm
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Seaver, Samuel M. D.; Bradbury, Louis M. T.; Frelin, Océane; Zarecki, Raphy; Ruppin, Eytan; Hanson, Andrew D.; Henry, Christopher S.
2015-03-10
There is a growing demand for genome-scale metabolic reconstructions for plants, fueled by the need to understand the metabolic basis of crop yield and by progress in genome and transcriptome sequencing. Methods are also required to enable the interpretation of plant transcriptome data to study how cellular metabolic activity varies under different growth conditions or even within different organs, tissues, and developmental stages. Such methods depend extensively on the accuracy with which genes have been mapped to the biochemical reactions in the plant metabolic pathways. Errors in these mappings lead to metabolic reconstructions with an inflated number of reactions and possible generation of unreliable metabolic phenotype predictions. Here we introduce a new evidence-based genome-scale metabolic reconstruction of maize, with significant improvements in the quality of the gene-reaction associations included within our model. We also present a new approach for applying our model to predict active metabolic genes based on transcriptome data. This method includes a minimal set of reactions associated with low expression genes to enable activity of a maximum number of reactions associated with high expression genes. We apply this method to construct an organ-specific model for the maize leaf, and tissue specific models for maize embryo and endosperm cells. We validate our models using fluxomics data for the endosperm and embryo, demonstrating an improved capacity of our models to fit the available fluxomics data. All models are publicly available via the DOE Systems Biology Knowledgebase and PlantSEED, and our new method is generally applicable for analysis transcript profiles from any plant, paving the way for further in silico studies with a wide variety of plant genomes.
Network thermodynamic curation of human and yeast genome-scale metabolic models.
Martínez, Verónica S; Quek, Lake-Ee; Nielsen, Lars K
2014-07-15
Genome-scale models are used for an ever-widening range of applications. Although there has been much focus on specifying the stoichiometric matrix, the predictive power of genome-scale models equally depends on reaction directions. Two-thirds of reactions in the two eukaryotic reconstructions Homo sapiens Recon 1 and Yeast 5 are specified as irreversible. However, these specifications are mainly based on biochemical textbooks or on their similarity to other organisms and are rarely underpinned by detailed thermodynamic analysis. In this study, a to our knowledge new workflow combining network-embedded thermodynamic and flux variability analysis was used to evaluate existing irreversibility constraints in Recon 1 and Yeast 5 and to identify new ones. A total of 27 and 16 new irreversible reactions were identified in Recon 1 and Yeast 5, respectively, whereas only four reactions were found with directions incorrectly specified against thermodynamics (three in Yeast 5 and one in Recon 1). The workflow further identified for both models several isolated internal loops that require further curation. The framework also highlighted the need for substrate channeling (in human) and ATP hydrolysis (in yeast) for the essential reaction catalyzed by phosphoribosylaminoimidazole carboxylase in purine metabolism. Finally, the framework highlighted differences in proline metabolism between yeast (cytosolic anabolism and mitochondrial catabolism) and humans (exclusively mitochondrial metabolism). We conclude that network-embedded thermodynamics facilitates the specification and validation of irreversibility constraints in compartmentalized metabolic models, at the same time providing further insight into network properties. Copyright © 2014 Biophysical Society. Published by Elsevier Inc. All rights reserved.
Genome-scale model guided design of Propionibacterium for enhanced propionic acid production.
Navone, Laura; McCubbin, Tim; Gonzalez-Garcia, Ricardo A; Nielsen, Lars K; Marcellin, Esteban
2018-06-01
Production of propionic acid by fermentation of propionibacteria has gained increasing attention in the past few years. However, biomanufacturing of propionic acid cannot compete with the current oxo-petrochemical synthesis process due to its well-established infrastructure, low oil prices and the high downstream purification costs of microbial production. Strain improvement to increase propionic acid yield is the best alternative to reduce downstream purification costs. The recent generation of genome-scale models for a number of Propionibacterium species facilitates the rational design of metabolic engineering strategies and provides a new opportunity to explore the metabolic potential of the Wood-Werkman cycle. Previous strategies for strain improvement have individually targeted acid tolerance, rate of propionate production or minimisation of by-products. Here we used the P. freudenreichii subsp . shermanii and the pan- Propionibacterium genome-scale metabolic models (GEMs) to simultaneously target these combined issues. This was achieved by focussing on strategies which yield higher energies and directly suppress acetate formation. Using P. freudenreichii subsp . shermanii , two strategies were assessed. The first tested the ability to manipulate the redox balance to favour propionate production by over-expressing the first two enzymes of the pentose-phosphate pathway (PPP), Zwf (glucose-6-phosphate 1-dehydrogenase) and Pgl (6-phosphogluconolactonase). Results showed a 4-fold increase in propionate to acetate ratio during the exponential growth phase. Secondly, the ability to enhance the energy yield from propionate production by over-expressing an ATP-dependent phosphoenolpyruvate carboxykinase (PEPCK) and sodium-pumping methylmalonyl-CoA decarboxylase (MMD) was tested, which extended the exponential growth phase. Together, these strategies demonstrate that in silico design strategies are predictive and can be used to reduce by-product formation in
Teusink, B.; Wiersma, A.; Molenaar, D.; Francke, C.; Vos, de W.M.; Siezen, R.J.; Smid, E.J.
2006-01-01
A genome-scale metabolic model of the lactic acid bacterium Lactobacillus plantarum WCFS1 was constructed based on genomic content and experimental data. The complete model includes 721 genes, 643 reactions, and 531 metabolites. Different stoichiometric modeling techniques were used for
Gu, Deqing; Jian, Xingxing; Zhang, Cheng; Hua, Qiang
2017-01-01
Genome-scale metabolic network models (GEMs) have played important roles in the design of genetically engineered strains and helped biologists to decipher metabolism. However, due to the complex gene-reaction relationships that exist in model systems, most algorithms have limited capabilities with respect to directly predicting accurate genetic design for metabolic engineering. In particular, methods that predict reaction knockout strategies leading to overproduction are often impractical in terms of gene manipulations. Recently, we proposed a method named logical transformation of model (LTM) to simplify the gene-reaction associations by introducing intermediate pseudo reactions, which makes it possible to generate genetic design. Here, we propose an alternative method to relieve researchers from deciphering complex gene-reactions by adding pseudo gene controlling reactions. In comparison to LTM, this new method introduces fewer pseudo reactions and generates a much smaller model system named as gModel. We showed that gModel allows two seldom reported applications: identification of minimal genomes and design of minimal cell factories within a modified OptKnock framework. In addition, gModel could be used to integrate expression data directly and improve the performance of the E-Fmin method for predicting fluxes. In conclusion, the model transformation procedure will facilitate genetic research based on GEMs, extending their applications.
A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.
Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien
2017-01-01
Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.
A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.
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Marko Budinich
Full Text Available Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA and multi-objective flux variability analysis (MO-FVA. Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity that take place at the ecosystem scale.
Directory of Open Access Journals (Sweden)
María P. Cortés
2017-12-01
Full Text Available Piscirickettsia salmonis is an intracellular bacterial fish pathogen that causes piscirickettsiosis, a disease with highly adverse impact in the Chilean salmon farming industry. The development of effective treatment and control methods for piscireckttsiosis is still a challenge. To meet it the number of studies on P. salmonis has grown in the last couple of years but many aspects of the pathogen’s biology are still poorly understood. Studies on its metabolism are scarce and only recently a metabolic model for reference strain LF-89 was developed. We present a new genome-scale model for P. salmonis LF-89 with more than twice as many genes as in the previous model and incorporating specific elements of the fish pathogen metabolism. Comparative analysis with models of different bacterial pathogens revealed a lower flexibility in P. salmonis metabolic network. Through constraint-based analysis, we determined essential metabolites required for its growth and showed that it can benefit from different carbon sources tested experimentally in new defined media. We also built an additional model for strain A1-15972, and together with an analysis of P. salmonis pangenome, we identified metabolic features that differentiate two main species clades. Both models constitute a knowledge-base for P. salmonis metabolism and can be used to guide the efficient culture of the pathogen and the identification of specific drug targets.
Genome-scale modelling of microbial metabolism with temporal and spatial resolution.
Henson, Michael A
2015-12-01
Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.
Novel insights into obesity and diabetes through genome-scale metabolic modeling
Directory of Open Access Journals (Sweden)
Leif eVäremo
2013-04-01
Full Text Available The growing prevalence of metabolic diseases, such as obesity and diabetes, are putting a high strain on global healthcare systems as well as increasing the demand for efficient treatment strategies. More than 360 million people worldwide are suffering from type 2 diabetes and, with the current trends, the projection is that 10% of the global adult population will be affected by 2030. In light of the systemic properties of metabolic diseases as well as the interconnected nature of metabolism, it is necessary to begin taking a holistic approach to study these diseases. Human genome-scale metabolic models (GEMs are topological and mathematical representations of cell metabolism and have proven to be valuable tools in the area of systems biology. Successful applications of GEMs include the process of gaining further biological and mechanistic understanding of diseases, finding potential biomarkers and identifying new drug targets. This review will focus on the modeling of human metabolism in the field of obesity and diabetes, showing its vast range of applications of clinical importance as well as point out future challenges.
Agren, Rasmus; Otero, José Manuel; Nielsen, Jens
2013-07-01
In this work, we describe the application of a genome-scale metabolic model and flux balance analysis for the prediction of succinic acid overproduction strategies in Saccharomyces cerevisiae. The top three single gene deletion strategies, Δmdh1, Δoac1, and Δdic1, were tested using knock-out strains cultivated anaerobically on glucose, coupled with physiological and DNA microarray characterization. While Δmdh1 and Δoac1 strains failed to produce succinate, Δdic1 produced 0.02 C-mol/C-mol glucose, in close agreement with model predictions (0.03 C-mol/C-mol glucose). Transcriptional profiling suggests that succinate formation is coupled to mitochondrial redox balancing, and more specifically, reductive TCA cycle activity. While far from industrial titers, this proof-of-concept suggests that in silico predictions coupled with experimental validation can be used to identify novel and non-intuitive metabolic engineering strategies.
Deriving metabolic engineering strategies from genome-scale modeling with flux ratio constraints.
Yen, Jiun Y; Nazem-Bokaee, Hadi; Freedman, Benjamin G; Athamneh, Ahmad I M; Senger, Ryan S
2013-05-01
Optimized production of bio-based fuels and chemicals from microbial cell factories is a central goal of systems metabolic engineering. To achieve this goal, a new computational method of using flux balance analysis with flux ratios (FBrAtio) was further developed in this research and applied to five case studies to evaluate and design metabolic engineering strategies. The approach was implemented using publicly available genome-scale metabolic flux models. Synthetic pathways were added to these models along with flux ratio constraints by FBrAtio to achieve increased (i) cellulose production from Arabidopsis thaliana; (ii) isobutanol production from Saccharomyces cerevisiae; (iii) acetone production from Synechocystis sp. PCC6803; (iv) H2 production from Escherichia coli MG1655; and (v) isopropanol, butanol, and ethanol (IBE) production from engineered Clostridium acetobutylicum. The FBrAtio approach was applied to each case to simulate a metabolic engineering strategy already implemented experimentally, and flux ratios were continually adjusted to find (i) the end-limit of increased production using the existing strategy, (ii) new potential strategies to increase production, and (iii) the impact of these metabolic engineering strategies on product yield and culture growth. The FBrAtio approach has the potential to design "fine-tuned" metabolic engineering strategies in silico that can be implemented directly with available genomic tools. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
Genome-scale metabolic models applied to human health and disease.
Cook, Daniel J; Nielsen, Jens
2017-11-01
Advances in genome sequencing, high throughput measurement of gene and protein expression levels, data accessibility, and computational power have allowed genome-scale metabolic models (GEMs) to become a useful tool for understanding metabolic alterations associated with many different diseases. Despite the proven utility of GEMs, researchers confront multiple challenges in the use of GEMs, their application to human health and disease, and their construction and simulation in an organ-specific and disease-specific manner. Several approaches that researchers are taking to address these challenges include using proteomic and transcriptomic-informed methods to build GEMs for individual organs, diseases, and patients and using constraints on model behavior during simulation to match observed metabolic fluxes. We review the challenges facing researchers in the use of GEMs, review the approaches used to address these challenges, and describe advances that are on the horizon and could lead to a better understanding of human metabolism. WIREs Syst Biol Med 2017, 9:e1393. doi: 10.1002/wsbm.1393 For further resources related to this article, please visit the WIREs website. © 2017 Wiley Periodicals, Inc.
Chatterjee, Ankita; Kundu, Sudip
2015-01-01
Chlorophyll is one of the most important pigments present in green plants and rice is one of the major food crops consumed worldwide. We curated the existing genome scale metabolic model (GSM) of rice leaf by incorporating new compartment, reactions and transporters. We used this modified GSM to elucidate how the chlorophyll is synthesized in a leaf through a series of bio-chemical reactions spanned over different organelles using inorganic macronutrients and light energy. We predicted the essential reactions and the associated genes of chlorophyll synthesis and validated against the existing experimental evidences. Further, ammonia is known to be the preferred source of nitrogen in rice paddy fields. The ammonia entering into the plant is assimilated in the root and leaf. The focus of the present work is centered on rice leaf metabolism. We studied the relative importance of ammonia transporters through the chloroplast and the cytosol and their interlink with other intracellular transporters. Ammonia assimilation in the leaves takes place by the enzyme glutamine synthetase (GS) which is present in the cytosol (GS1) and chloroplast (GS2). Our results provided possible explanation why GS2 mutants show normal growth under minimum photorespiration and appear chlorotic when exposed to air. PMID:26443104
Genome-scale model-driven strain design for dicarboxylic acid production in Yarrowia lipolytica.
Mishra, Pranjul; Lee, Na-Rae; Lakshmanan, Meiyappan; Kim, Minsuk; Kim, Byung-Gee; Lee, Dong-Yup
2018-03-19
Recently, there have been several attempts to produce long-chain dicarboxylic acids (DCAs) in various microbial hosts. Of these, Yarrowia lipolytica has great potential due to its oleaginous characteristics and unique ability to utilize hydrophobic substrates. However, Y. lipolytica should be further engineered to make it more competitive: the current approaches are mostly intuitive and cumbersome, thus limiting its industrial application. In this study, we proposed model-guided metabolic engineering strategies for enhanced production of DCAs in Y. lipolytica. At the outset, we reconstructed genome-scale metabolic model (GSMM) of Y. lipolytica (iYLI647) by substantially expanding the previous models. Subsequently, the model was validated using three sets of published culture experiment data. It was finally exploited to identify genetic engineering targets for overexpression, knockout, and cofactor modification by applying several in silico strain design methods, which potentially give rise to high yield production of the industrially relevant long-chain DCAs, e.g., dodecanedioic acid (DDDA). The resultant targets include (1) malate dehydrogenase and malic enzyme genes and (2) glutamate dehydrogenase gene, in silico overexpression of which generated additional NADPH required for fatty acid synthesis, leading to the increased DDDA fluxes by 48% and 22% higher, respectively, compared to wild-type. We further investigated the effect of supplying branched-chain amino acids on the acetyl-CoA turn-over rate which is key metabolite for fatty acid synthesis, suggesting their significance for production of DDDA in Y. lipolytica. In silico model-based strain design strategies allowed us to identify several metabolic engineering targets for overproducing DCAs in lipid accumulating yeast, Y. lipolytica. Thus, the current study can provide a methodological framework that is applicable to other oleaginous yeasts for value-added biochemical production.
Noise analysis of genome-scale protein synthesis using a discrete computational model of translation
Energy Technology Data Exchange (ETDEWEB)
Racle, Julien; Hatzimanikatis, Vassily, E-mail: vassily.hatzimanikatis@epfl.ch [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland); Swiss Institute of Bioinformatics (SIB), CH-1015 Lausanne (Switzerland); Stefaniuk, Adam Jan [Laboratory of Computational Systems Biotechnology, Ecole Polytechnique Fédérale de Lausanne (EPFL), CH-1015 Lausanne (Switzerland)
2015-07-28
Noise in genetic networks has been the subject of extensive experimental and computational studies. However, very few of these studies have considered noise properties using mechanistic models that account for the discrete movement of ribosomes and RNA polymerases along their corresponding templates (messenger RNA (mRNA) and DNA). The large size of these systems, which scales with the number of genes, mRNA copies, codons per mRNA, and ribosomes, is responsible for some of the challenges. Additionally, one should be able to describe the dynamics of ribosome exchange between the free ribosome pool and those bound to mRNAs, as well as how mRNA species compete for ribosomes. We developed an efficient algorithm for stochastic simulations that addresses these issues and used it to study the contribution and trade-offs of noise to translation properties (rates, time delays, and rate-limiting steps). The algorithm scales linearly with the number of mRNA copies, which allowed us to study the importance of genome-scale competition between mRNAs for the same ribosomes. We determined that noise is minimized under conditions maximizing the specific synthesis rate. Moreover, sensitivity analysis of the stochastic system revealed the importance of the elongation rate in the resultant noise, whereas the translation initiation rate constant was more closely related to the average protein synthesis rate. We observed significant differences between our results and the noise properties of the most commonly used translation models. Overall, our studies demonstrate that the use of full mechanistic models is essential for the study of noise in translation and transcription.
McAnulty, Michael J; Yen, Jiun Y; Freedman, Benjamin G; Senger, Ryan S
2012-05-14
Genome-scale metabolic networks and flux models are an effective platform for linking an organism genotype to its phenotype. However, few modeling approaches offer predictive capabilities to evaluate potential metabolic engineering strategies in silico. A new method called "flux balance analysis with flux ratios (FBrAtio)" was developed in this research and applied to a new genome-scale model of Clostridium acetobutylicum ATCC 824 (iCAC490) that contains 707 metabolites and 794 reactions. FBrAtio was used to model wild-type metabolism and metabolically engineered strains of C. acetobutylicum where only flux ratio constraints and thermodynamic reversibility of reactions were required. The FBrAtio approach allowed solutions to be found through standard linear programming. Five flux ratio constraints were required to achieve a qualitative picture of wild-type metabolism for C. acetobutylicum for the production of: (i) acetate, (ii) lactate, (iii) butyrate, (iv) acetone, (v) butanol, (vi) ethanol, (vii) CO2 and (viii) H2. Results of this simulation study coincide with published experimental results and show the knockdown of the acetoacetyl-CoA transferase increases butanol to acetone selectivity, while the simultaneous over-expression of the aldehyde/alcohol dehydrogenase greatly increases ethanol production. FBrAtio is a promising new method for constraining genome-scale models using internal flux ratios. The method was effective for modeling wild-type and engineered strains of C. acetobutylicum.
Hamilton, Joshua J.; Dwivedi, Vivek; Reed, Jennifer L.
2013-01-01
Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. PMID:23870272
Hamilton, Joshua J; Dwivedi, Vivek; Reed, Jennifer L
2013-07-16
Constraint-based methods provide powerful computational techniques to allow understanding and prediction of cellular behavior. These methods rely on physiochemical constraints to eliminate infeasible behaviors from the space of available behaviors. One such constraint is thermodynamic feasibility, the requirement that intracellular flux distributions obey the laws of thermodynamics. The past decade has seen several constraint-based methods that interpret this constraint in different ways, including those that are limited to small networks, rely on predefined reaction directions, and/or neglect the relationship between reaction free energies and metabolite concentrations. In this work, we utilize one such approach, thermodynamics-based metabolic flux analysis (TMFA), to make genome-scale, quantitative predictions about metabolite concentrations and reaction free energies in the absence of prior knowledge of reaction directions, while accounting for uncertainties in thermodynamic estimates. We applied TMFA to a genome-scale network reconstruction of Escherichia coli and examined the effect of thermodynamic constraints on the flux space. We also assessed the predictive performance of TMFA against gene essentiality and quantitative metabolomics data, under both aerobic and anaerobic, and optimal and suboptimal growth conditions. Based on these results, we propose that TMFA is a useful tool for validating phenotypes and generating hypotheses, and that additional types of data and constraints can improve predictions of metabolite concentrations. Copyright © 2013 Biophysical Society. Published by Elsevier Inc. All rights reserved.
International Nuclear Information System (INIS)
Dash, Satyakam; Mueller, Thomas J.; Venkataramanan, Keerthi P.; Papoutsakis, Eleftherios T.; Maranas, Costas D.
2014-01-01
Clostridia are anaerobic Gram-positive Firmicutes containing broad and flexible systems for substrate utilization, which have been used successfully to produce a range of industrial compounds. Clostridium acetobutylicum has been used to produce butanol on an industrial scale through acetone-butanol-ethanol (ABE) fermentation. A genome-scale metabolic (GSM) model is a powerful tool for understanding the metabolic capacities of an organism and developing metabolic engineering strategies for strain development. The integration of stress related specific transcriptomics information with the GSM model provides opportunities for elucidating the focal points of regulation
International Nuclear Information System (INIS)
Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.
2011-01-01
The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species, multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The
Fang, Yilin; Scheibe, Timothy D; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E; Lovley, Derek R
2011-03-25
The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The
Fang, Yilin; Scheibe, Timothy D.; Mahadevan, Radhakrishnan; Garg, Srinath; Long, Philip E.; Lovley, Derek R.
2011-03-01
The activity of microorganisms often plays an important role in dynamic natural attenuation or engineered bioremediation of subsurface contaminants, such as chlorinated solvents, metals, and radionuclides. To evaluate and/or design bioremediated systems, quantitative reactive transport models are needed. State-of-the-art reactive transport models often ignore the microbial effects or simulate the microbial effects with static growth yield and constant reaction rate parameters over simulated conditions, while in reality microorganisms can dynamically modify their functionality (such as utilization of alternative respiratory pathways) in response to spatial and temporal variations in environmental conditions. Constraint-based genome-scale microbial in silico models, using genomic data and multiple-pathway reaction networks, have been shown to be able to simulate transient metabolism of some well studied microorganisms and identify growth rate, substrate uptake rates, and byproduct rates under different growth conditions. These rates can be identified and used to replace specific microbially-mediated reaction rates in a reactive transport model using local geochemical conditions as constraints. We previously demonstrated the potential utility of integrating a constraint-based microbial metabolism model with a reactive transport simulator as applied to bioremediation of uranium in groundwater. However, that work relied on an indirect coupling approach that was effective for initial demonstration but may not be extensible to more complex problems that are of significant interest (e.g., communities of microbial species and multiple constraining variables). Here, we extend that work by presenting and demonstrating a method of directly integrating a reactive transport model (FORTRAN code) with constraint-based in silico models solved with IBM ILOG CPLEX linear optimizer base system (C library). The models were integrated with BABEL, a language interoperability tool. The
Agren, Rasmus; Liu, Liming; Shoaie, Saeed; Vongsangnak, Wanwipa; Nookaew, Intawat; Nielsen, Jens
2013-01-01
We present the RAVEN (Reconstruction, Analysis and Visualization of Metabolic Networks) Toolbox: a software suite that allows for semi-automated reconstruction of genome-scale models. It makes use of published models and/or the KEGG database, coupled with extensive gap-filling and quality control features. The software suite also contains methods for visualizing simulation results and omics data, as well as a range of methods for performing simulations and analyzing the results. The software is a useful tool for system-wide data analysis in a metabolic context and for streamlined reconstruction of metabolic networks based on protein homology. The RAVEN Toolbox workflow was applied in order to reconstruct a genome-scale metabolic model for the important microbial cell factory Penicillium chrysogenum Wisconsin54-1255. The model was validated in a bibliomic study of in total 440 references, and it comprises 1471 unique biochemical reactions and 1006 ORFs. It was then used to study the roles of ATP and NADPH in the biosynthesis of penicillin, and to identify potential metabolic engineering targets for maximization of penicillin production. PMID:23555215
Directory of Open Access Journals (Sweden)
Katsunori Yoshikawa
Full Text Available Arthrospira (Spirulina platensis is a promising feedstock and host strain for bioproduction because of its high accumulation of glycogen and superior characteristics for industrial production. Metabolic simulation using a genome-scale metabolic model and flux balance analysis is a powerful method that can be used to design metabolic engineering strategies for the improvement of target molecule production. In this study, we constructed a genome-scale metabolic model of A. platensis NIES-39 including 746 metabolic reactions and 673 metabolites, and developed novel strategies to improve the production of valuable metabolites, such as glycogen and ethanol. The simulation results obtained using the metabolic model showed high consistency with experimental results for growth rates under several trophic conditions and growth capabilities on various organic substrates. The metabolic model was further applied to design a metabolic network to improve the autotrophic production of glycogen and ethanol. Decreased flux of reactions related to the TCA cycle and phosphoenolpyruvate reaction were found to improve glycogen production. Furthermore, in silico knockout simulation indicated that deletion of genes related to the respiratory chain, such as NAD(PH dehydrogenase and cytochrome-c oxidase, could enhance ethanol production by using ammonium as a nitrogen source.
Giguere, Andrew T.; Murthy, Ganti S.; Bottomley, Peter J.; Sayavedra-Soto, Luis A.
2018-01-01
ABSTRACT Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, emits nitrogen (N) oxide gases (NO, NO2, and N2O), which are potentially hazardous compounds that contribute to global warming. To better understand the dynamics of nitrification-derived N oxide production, we conducted culturing experiments and used an integrative genome-scale, constraint-based approach to model N oxide gas sources and sinks during complete nitrification in an aerobic coculture of two model nitrifying bacteria, the ammonia-oxidizing bacterium Nitrosomonas europaea and the nitrite-oxidizing bacterium Nitrobacter winogradskyi. The model includes biotic genome-scale metabolic models (iFC578 and iFC579) for each nitrifier and abiotic N oxide reactions. Modeling suggested both biotic and abiotic reactions are important sources and sinks of N oxides, particularly under microaerobic conditions predicted to occur in coculture. In particular, integrative modeling suggested that previous models might have underestimated gross NO production during nitrification due to not taking into account its rapid oxidation in both aqueous and gas phases. The integrative model may be found at https://github.com/chaplenf/microBiome-v2.1. IMPORTANCE Modern agriculture is sustained by application of inorganic nitrogen (N) fertilizer in the form of ammonium (NH4+). Up to 60% of NH4+-based fertilizer can be lost through leaching of nitrifier-derived nitrate (NO3−), and through the emission of N oxide gases (i.e., nitric oxide [NO], N dioxide [NO2], and nitrous oxide [N2O] gases), the latter being a potent greenhouse gas. Our approach to modeling of nitrification suggests that both biotic and abiotic mechanisms function as important sources and sinks of N oxides during microaerobic conditions and that previous models might have underestimated gross NO production during nitrification. PMID:29577088
Mellbye, Brett L; Giguere, Andrew T; Murthy, Ganti S; Bottomley, Peter J; Sayavedra-Soto, Luis A; Chaplen, Frank W R
2018-01-01
Nitrification, the aerobic oxidation of ammonia to nitrate via nitrite, emits nitrogen (N) oxide gases (NO, NO 2 , and N 2 O), which are potentially hazardous compounds that contribute to global warming. To better understand the dynamics of nitrification-derived N oxide production, we conducted culturing experiments and used an integrative genome-scale, constraint-based approach to model N oxide gas sources and sinks during complete nitrification in an aerobic coculture of two model nitrifying bacteria, the ammonia-oxidizing bacterium Nitrosomonas europaea and the nitrite-oxidizing bacterium Nitrobacter winogradskyi . The model includes biotic genome-scale metabolic models (iFC578 and iFC579) for each nitrifier and abiotic N oxide reactions. Modeling suggested both biotic and abiotic reactions are important sources and sinks of N oxides, particularly under microaerobic conditions predicted to occur in coculture. In particular, integrative modeling suggested that previous models might have underestimated gross NO production during nitrification due to not taking into account its rapid oxidation in both aqueous and gas phases. The integrative model may be found at https://github.com/chaplenf/microBiome-v2.1. IMPORTANCE Modern agriculture is sustained by application of inorganic nitrogen (N) fertilizer in the form of ammonium (NH 4 + ). Up to 60% of NH 4 + -based fertilizer can be lost through leaching of nitrifier-derived nitrate (NO 3 - ), and through the emission of N oxide gases (i.e., nitric oxide [NO], N dioxide [NO 2 ], and nitrous oxide [N 2 O] gases), the latter being a potent greenhouse gas. Our approach to modeling of nitrification suggests that both biotic and abiotic mechanisms function as important sources and sinks of N oxides during microaerobic conditions and that previous models might have underestimated gross NO production during nitrification.
Lu, Hongzhong; Cao, Weiqiang; Ouyang, Liming; Xia, Jianye; Huang, Mingzhi; Chu, Ju; Zhuang, Yingping; Zhang, Siliang; Noorman, Henk
2017-03-01
Aspergillus niger is one of the most important cell factories for industrial enzymes and organic acids production. A comprehensive genome-scale metabolic network model (GSMM) with high quality is crucial for efficient strain improvement and process optimization. The lack of accurate reaction equations and gene-protein-reaction associations (GPRs) in the current best model of A. niger named GSMM iMA871, however, limits its application scope. To overcome these limitations, we updated the A. niger GSMM by combining the latest genome annotation and literature mining technology. Compared with iMA871, the number of reactions in iHL1210 was increased from 1,380 to 1,764, and the number of unique ORFs from 871 to 1,210. With the aid of our transcriptomics analysis, the existence of 63% ORFs and 68% reactions in iHL1210 can be verified when glucose was used as the only carbon source. Physiological data from chemostat cultivations, 13 C-labeled and molecular experiments from the published literature were further used to check the performance of iHL1210. The average correlation coefficients between the predicted fluxes and estimated fluxes from 13 C-labeling data were sufficiently high (above 0.89) and the prediction of cell growth on most of the reported carbon and nitrogen sources was consistent. Using the updated genome-scale model, we evaluated gene essentiality on synthetic and yeast extract medium, as well as the effects of NADPH supply on glucoamylase production in A. niger. In summary, the new A. niger GSMM iHL1210 contains significant improvements with respect to the metabolic coverage and prediction performance, which paves the way for systematic metabolic engineering of A. niger. Biotechnol. Bioeng. 2017;114: 685-695. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
Ye, Chao; Xu, Nan; Dong, Chuan; Ye, Yuannong; Zou, Xuan; Chen, Xiulai; Guo, Fengbiao; Liu, Liming
2017-04-07
Genome-scale metabolic models (GSMMs) constitute a platform that combines genome sequences and detailed biochemical information to quantify microbial physiology at the system level. To improve the unity, integrity, correctness, and format of data in published GSMMs, a consensus IMGMD database was built in the LAMP (Linux + Apache + MySQL + PHP) system by integrating and standardizing 328 GSMMs constructed for 139 microorganisms. The IMGMD database can help microbial researchers download manually curated GSMMs, rapidly reconstruct standard GSMMs, design pathways, and identify metabolic targets for strategies on strain improvement. Moreover, the IMGMD database facilitates the integration of wet-lab and in silico data to gain an additional insight into microbial physiology. The IMGMD database is freely available, without any registration requirements, at http://imgmd.jiangnan.edu.cn/database.
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Kim Pan-Jun
2011-08-01
Full Text Available Abstract Background Solventogenic clostridia offer a sustainable alternative to petroleum-based production of butanol--an important chemical feedstock and potential fuel additive or replacement. C. beijerinckii is an attractive microorganism for strain design to improve butanol production because it (i naturally produces the highest recorded butanol concentrations as a byproduct of fermentation; and (ii can co-ferment pentose and hexose sugars (the primary products from lignocellulosic hydrolysis. Interrogating C. beijerinckii metabolism from a systems viewpoint using constraint-based modeling allows for simulation of the global effect of genetic modifications. Results We present the first genome-scale metabolic model (iCM925 for C. beijerinckii, containing 925 genes, 938 reactions, and 881 metabolites. To build the model we employed a semi-automated procedure that integrated genome annotation information from KEGG, BioCyc, and The SEED, and utilized computational algorithms with manual curation to improve model completeness. Interestingly, we found only a 34% overlap in reactions collected from the three databases--highlighting the importance of evaluating the predictive accuracy of the resulting genome-scale model. To validate iCM925, we conducted fermentation experiments using the NCIMB 8052 strain, and evaluated the ability of the model to simulate measured substrate uptake and product production rates. Experimentally observed fermentation profiles were found to lie within the solution space of the model; however, under an optimal growth objective, additional constraints were needed to reproduce the observed profiles--suggesting the existence of selective pressures other than optimal growth. Notably, a significantly enriched fraction of actively utilized reactions in simulations--constrained to reflect experimental rates--originated from the set of reactions that overlapped between all three databases (P = 3.52 × 10-9, Fisher's exact test
Broddrick, Jared T.; Rubin, Benjamin E.; Welkie, David G.; Du, Niu; Mih, Nathan; Diamond, Spencer; Lee, Jenny J.; Golden, Susan S.; Palsson, Bernhard O.
2016-01-01
The model cyanobacterium, Synechococcus elongatus PCC 7942, is a genetically tractable obligate phototroph that is being developed for the bioproduction of high-value chemicals. Genome-scale models (GEMs) have been successfully used to assess and engineer cellular metabolism; however, GEMs of phototrophic metabolism have been limited by the lack of experimental datasets for model validation and the challenges of incorporating photon uptake. Here, we develop a GEM of metabolism in S. elongatus using random barcode transposon site sequencing (RB-TnSeq) essential gene and physiological data specific to photoautotrophic metabolism. The model explicitly describes photon absorption and accounts for shading, resulting in the characteristic linear growth curve of photoautotrophs. GEM predictions of gene essentiality were compared with data obtained from recent dense-transposon mutagenesis experiments. This dataset allowed major improvements to the accuracy of the model. Furthermore, discrepancies between GEM predictions and the in vivo dataset revealed biological characteristics, such as the importance of a truncated, linear TCA pathway, low flux toward amino acid synthesis from photorespiration, and knowledge gaps within nucleotide metabolism. Coupling of strong experimental support and photoautotrophic modeling methods thus resulted in a highly accurate model of S. elongatus metabolism that highlights previously unknown areas of S. elongatus biology. PMID:27911809
In silico method for modelling metabolism and gene product expression at genome scale
Energy Technology Data Exchange (ETDEWEB)
Lerman, Joshua A.; Hyduke, Daniel R.; Latif, Haythem; Portnoy, Vasiliy A.; Lewis, Nathan E.; Orth, Jeffrey D.; Rutledge, Alexandra C.; Smith, Richard D.; Adkins, Joshua N.; Zengler, Karsten; Palsson, Bernard O.
2012-07-03
Transcription and translation use raw materials and energy generated metabolically to create the macromolecular machinery responsible for all cellular functions, including metabolism. A biochemically accurate model of molecular biology and metabolism will facilitate comprehensive and quantitative computations of an organism's molecular constitution as a function of genetic and environmental parameters. Here we formulate a model of metabolism and macromolecular expression. Prototyping it using the simple microorganism Thermotoga maritima, we show our model accurately simulates variations in cellular composition and gene expression. Moreover, through in silico comparative transcriptomics, the model allows the discovery of new regulons and improving the genome and transcription unit annotations. Our method presents a framework for investigating molecular biology and cellular physiology in silico and may allow quantitative interpretation of multi-omics data sets in the context of an integrated biochemical description of an organism.
DEFF Research Database (Denmark)
Sanchez, Benjamin J.; Zhang, Xi-Cheng; Nilsson, Avlant
2017-01-01
, which act as limitations on metabolic fluxes, are not taken into account. Here, we present GECKO, a method that enhances a GEM to account for enzymes as part of reactions, thereby ensuring that each metabolic flux does not exceed its maximum capacity, equal to the product of the enzyme's abundance...... and turnover number. We applied GECKO to a Saccharomyces cerevisiae GEM and demonstrated that the new model could correctly describe phenotypes that the previous model could not, particularly under high enzymatic pressure conditions, such as yeast growing on different carbon sources in excess, coping...... with stress, or overexpressing a specific pathway. GECKO also allows to directly integrate quantitative proteomics data; by doing so, we significantly reduced flux variability of the model, in over 60% of metabolic reactions. Additionally, the model gives insight into the distribution of enzyme usage between...
Data-driven integration of genome-scale regulatory and metabolic network models
Imam, Saheed; Schäuble, Sascha; Brooks, Aaron N.; Baliga, Nitin S.; Price, Nathan D.
2015-01-01
Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription, and signaling) have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert—a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system. PMID:25999934
Data-driven integration of genome-scale regulatory and metabolic network models
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Saheed eImam
2015-05-01
Full Text Available Microbes are diverse and extremely versatile organisms that play vital roles in all ecological niches. Understanding and harnessing microbial systems will be key to the sustainability of our planet. One approach to improving our knowledge of microbial processes is through data-driven and mechanism-informed computational modeling. Individual models of biological networks (such as metabolism, transcription and signaling have played pivotal roles in driving microbial research through the years. These networks, however, are highly interconnected and function in concert – a fact that has led to the development of a variety of approaches aimed at simulating the integrated functions of two or more network types. Though the task of integrating these different models is fraught with new challenges, the large amounts of high-throughput data sets being generated, and algorithms being developed, means that the time is at hand for concerted efforts to build integrated regulatory-metabolic networks in a data-driven fashion. In this perspective, we review current approaches for constructing integrated regulatory-metabolic models and outline new strategies for future development of these network models for any microbial system.
DEFF Research Database (Denmark)
Liu, Guodong; Marras, Antonio; Nielsen, Jens
2014-01-01
regulatory information is necessary to improve the accuracy and predictive ability of metabolic models. Here we review the strategies for the reconstruction of a transcriptional regulatory network (TRN) for yeast and the integration of such a reconstruction into a flux balance analysis-based metabolic model......Metabolism is regulated at multiple levels in response to the changes of internal or external conditions. Transcriptional regulation plays an important role in regulating many metabolic reactions by altering the concentrations of metabolic enzymes. Thus, integration of the transcriptional....... While many large-scale TRN reconstructions have been reported for yeast, these reconstructions still need to be improved regarding the functionality and dynamic property of the regulatory interactions. In addition, mathematical modeling approaches need to be further developed to efficiently integrate...
Genome-Scale Analysis of Translation Elongation with a Ribosome Flow Model
Meilijson, Isaac; Kupiec, Martin; Ruppin, Eytan
2011-01-01
We describe the first large scale analysis of gene translation that is based on a model that takes into account the physical and dynamical nature of this process. The Ribosomal Flow Model (RFM) predicts fundamental features of the translation process, including translation rates, protein abundance levels, ribosomal densities and the relation between all these variables, better than alternative (‘non-physical’) approaches. In addition, we show that the RFM can be used for accurate inference of various other quantities including genes' initiation rates and translation costs. These quantities could not be inferred by previous predictors. We find that increasing the number of available ribosomes (or equivalently the initiation rate) increases the genomic translation rate and the mean ribosome density only up to a certain point, beyond which both saturate. Strikingly, assuming that the translation system is tuned to work at the pre-saturation point maximizes the predictive power of the model with respect to experimental data. This result suggests that in all organisms that were analyzed (from bacteria to Human), the global initiation rate is optimized to attain the pre-saturation point. The fact that similar results were not observed for heterologous genes indicates that this feature is under selection. Remarkably, the gap between the performance of the RFM and alternative predictors is strikingly large in the case of heterologous genes, testifying to the model's promising biotechnological value in predicting the abundance of heterologous proteins before expressing them in the desired host. PMID:21909250
Predicting growth of the healthy infant using a genome scale metabolic model
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Nilsson, Avlant; Mardinoglu, Adil; Nielsen, Jens
2017-01-01
to simulate the mechanisms of growth and integrate data about breast-milk intake and composition with the infant's biomass and energy expenditure of major organs. The model predicted daily metabolic fluxes from birth to age 6 months, and accurately reproduced standard growth curves and changes in body...
Modeling Method for Increased Precision and Scope of Directly Measurable Fluxes at a Genome-Scale
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McCloskey, Douglas; Young, Jamey D.; Xu, Sibei
2016-01-01
pathways of traditional MFA models and also covers the additional pathways of purine, pyrimidine, isoprenoid, methionine, riboflavin, coenzyme A, and folate, as well as other biosynthetic pathways. When evaluating the iDM2014 using a set of measured intracellular intermediate and cofactor mass isotopomer...
DEFF Research Database (Denmark)
Liu, Joanne K.; O’Brien, Edward J.; Lerman, Joshua A.
2014-01-01
Background: Membranes play a crucial role in cellular functions. Membranes provide a physical barrier, control the trafficking of substances entering and leaving the cell, and are a major determinant of cellular ultra-structure. In addition, components embedded within the membrane participate...... the computation of cellular phenotypes through an integrated computation of proteome composition, abundance, and activity in four cellular compartments (cytoplasm, periplasm, inner and outer membrane). Reconstruction and validation of the model has demonstrated that the iJL1678-ME is capable of capturing...
Brown, Patrick O.
2013-01-01
Background High throughput molecular-interaction studies using immunoprecipitations (IP) or affinity purifications are powerful and widely used in biology research. One of many important applications of this method is to identify the set of RNAs that interact with a particular RNA-binding protein (RBP). Here, the unique statistical challenge presented is to delineate a specific set of RNAs that are enriched in one sample relative to another, typically a specific IP compared to a non-specific control to model background. The choice of normalization procedure critically impacts the number of RNAs that will be identified as interacting with an RBP at a given significance threshold – yet existing normalization methods make assumptions that are often fundamentally inaccurate when applied to IP enrichment data. Methods In this paper, we present a new normalization methodology that is specifically designed for identifying enriched RNA or DNA sequences in an IP. The normalization (called adaptive or AD normalization) uses a basic model of the IP experiment and is not a variant of mean, quantile, or other methodology previously proposed. The approach is evaluated statistically and tested with simulated and empirical data. Results and Conclusions The adaptive (AD) normalization method results in a greatly increased range in the number of enriched RNAs identified, fewer false positives, and overall better concordance with independent biological evidence, for the RBPs we analyzed, compared to median normalization. The approach is also applicable to the study of pairwise RNA, DNA and protein interactions such as the analysis of transcription factors via chromatin immunoprecipitation (ChIP) or any other experiments where samples from two conditions, one of which contains an enriched subset of the other, are studied. PMID:23349766
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Tyler W. H. Backman
2018-01-01
Full Text Available Determination of internal metabolic fluxes is crucial for fundamental and applied biology because they map how carbon and electrons flow through metabolism to enable cell function. 13 C Metabolic Flux Analysis ( 13 C MFA and Two-Scale 13 C Metabolic Flux Analysis (2S- 13 C MFA are two techniques used to determine such fluxes. Both operate on the simplifying approximation that metabolic flux from peripheral metabolism into central “core” carbon metabolism is minimal, and can be omitted when modeling isotopic labeling in core metabolism. The validity of this “two-scale” or “bow tie” approximation is supported both by the ability to accurately model experimental isotopic labeling data, and by experimentally verified metabolic engineering predictions using these methods. However, the boundaries of core metabolism that satisfy this approximation can vary across species, and across cell culture conditions. Here, we present a set of algorithms that (1 systematically calculate flux bounds for any specified “core” of a genome-scale model so as to satisfy the bow tie approximation and (2 automatically identify an updated set of core reactions that can satisfy this approximation more efficiently. First, we leverage linear programming to simultaneously identify the lowest fluxes from peripheral metabolism into core metabolism compatible with the observed growth rate and extracellular metabolite exchange fluxes. Second, we use Simulated Annealing to identify an updated set of core reactions that allow for a minimum of fluxes into core metabolism to satisfy these experimental constraints. Together, these methods accelerate and automate the identification of a biologically reasonable set of core reactions for use with 13 C MFA or 2S- 13 C MFA, as well as provide for a substantially lower set of flux bounds for fluxes into the core as compared with previous methods. We provide an open source Python implementation of these algorithms at https://github.com/JBEI/limitfluxtocore.
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Shivendra G. Tewari
2017-08-01
Full Text Available Chloroquine, long the default first-line treatment against malaria, is now abandoned in large parts of the world because of widespread drug-resistance in Plasmodium falciparum. In spite of its importance as a cost-effective and efficient drug, a coherent understanding of the cellular mechanisms affected by chloroquine and how they influence the fitness and survival of the parasite remains elusive. Here, we used a systems biology approach to integrate genome-scale transcriptomics to map out the effects of chloroquine, identify targeted metabolic pathways, and translate these findings into mechanistic insights. Specifically, we first developed a method that integrates transcriptomic and metabolomic data, which we independently validated against a recently published set of such data for Krebs-cycle mutants of P. falciparum. We then used the method to calculate the effect of chloroquine treatment on the metabolic flux profiles of P. falciparum during the intraerythrocytic developmental cycle. The model predicted dose-dependent inhibition of DNA replication, in agreement with earlier experimental results for both drug-sensitive and drug-resistant P. falciparum strains. Our simulations also corroborated experimental findings that suggest differences in chloroquine sensitivity between ring- and schizont-stage P. falciparum. Our analysis also suggests that metabolic fluxes that govern reduced thioredoxin and phosphoenolpyruvate synthesis are significantly decreased and are pivotal to chloroquine-based inhibition of P. falciparum DNA replication. The consequences of impaired phosphoenolpyruvate synthesis and redox metabolism are reduced carbon fixation and increased oxidative stress, respectively, both of which eventually facilitate killing of the parasite. Our analysis suggests that a combination of chloroquine (or an analogue and another drug, which inhibits carbon fixation and/or increases oxidative stress, should increase the clearance of P
2012-01-01
Background Over the last decade, the genome-scale metabolic models have been playing increasingly important roles in elucidating metabolic characteristics of biological systems for a wide range of applications including, but not limited to, system-wide identification of drug targets and production of high value biochemical compounds. However, these genome-scale metabolic models must be able to first predict known in vivo phenotypes before it is applied towards these applications with high confidence. One benchmark for measuring the in silico capability in predicting in vivo phenotypes is the use of single-gene mutant libraries to measure the accuracy of knockout simulations in predicting mutant growth phenotypes. Results Here we employed a systematic and iterative process, designated as Reconciling In silico/in vivo mutaNt Growth (RING), to settle discrepancies between in silico prediction and in vivo observations to a newly reconstructed genome-scale metabolic model of the fission yeast, Schizosaccharomyces pombe, SpoMBEL1693. The predictive capabilities of the genome-scale metabolic model in predicting single-gene mutant growth phenotypes were measured against the single-gene mutant library of S. pombe. The use of RING resulted in improving the overall predictive capability of SpoMBEL1693 by 21.5%, from 61.2% to 82.7% (92.5% of the negative predictions matched the observed growth phenotype and 79.7% the positive predictions matched the observed growth phenotype). Conclusion This study presents validation and refinement of a newly reconstructed metabolic model of the yeast S. pombe, through improving the metabolic model’s predictive capabilities by reconciling the in silico predicted growth phenotypes of single-gene knockout mutants, with experimental in vivo growth data. PMID:22631437
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Dorines Rosario
2018-06-01
Full Text Available Dysbiosis in the gut microbiome composition may be promoted by therapeutic drugs such as metformin, the world’s most prescribed antidiabetic drug. Under metformin treatment, disturbances of the intestinal microbes lead to increased abundance of Escherichia spp., Akkermansia muciniphila, Subdoligranulum variabile and decreased abundance of Intestinibacter bartlettii. This alteration may potentially lead to adverse effects on the host metabolism, with the depletion of butyrate producer genus. However, an increased production of butyrate and propionate was verified in metformin-treated Type 2 diabetes (T2D patients. The mechanisms underlying these nutritional alterations and their relation with gut microbiota dysbiosis remain unclear. Here, we used Genome-scale Metabolic Models of the representative gut bacteria Escherichia spp., I. bartlettii, A. muciniphila, and S. variabile to elucidate their bacterial metabolism and its effect on intestinal nutrient pool, including macronutrients (e.g., amino acids and short chain fatty acids, minerals and chemical elements (e.g., iron and oxygen. We applied flux balance analysis (FBA coupled with synthetic lethality analysis interactions to identify combinations of reactions and extracellular nutrients whose absence prevents growth. Our analyses suggest that Escherichia sp. is the bacteria least vulnerable to nutrient availability. We have also examined bacterial contribution to extracellular nutrients including short chain fatty acids, amino acids, and gasses. For instance, Escherichia sp. and S. variabile may contribute to the production of important short chain fatty acids (e.g., acetate and butyrate, respectively involved in the host physiology under aerobic and anaerobic conditions. We have also identified pathway susceptibility to nutrient availability and reaction changes among the four bacteria using both FBA and flux variability analysis. For instance, lipopolysaccharide synthesis, nucleotide sugar
Zuñiga, Cristal; Li, Chien-Ting; Huelsman, Tyler; Levering, Jennifer; Zielinski, Daniel C; McConnell, Brian O; Long, Christopher P; Knoshaug, Eric P; Guarnieri, Michael T; Antoniewicz, Maciek R; Betenbaugh, Michael J; Zengler, Karsten
2016-09-01
The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. © 2016 American Society of Plant Biologists. All rights reserved.
Zuñiga, Cristal; Li, Chien-Ting; Zielinski, Daniel C.; Guarnieri, Michael T.; Antoniewicz, Maciek R.; Zengler, Karsten
2016-01-01
The green microalga Chlorella vulgaris has been widely recognized as a promising candidate for biofuel production due to its ability to store high lipid content and its natural metabolic versatility. Compartmentalized genome-scale metabolic models constructed from genome sequences enable quantitative insight into the transport and metabolism of compounds within a target organism. These metabolic models have long been utilized to generate optimized design strategies for an improved production process. Here, we describe the reconstruction, validation, and application of a genome-scale metabolic model for C. vulgaris UTEX 395, iCZ843. The reconstruction represents the most comprehensive model for any eukaryotic photosynthetic organism to date, based on the genome size and number of genes in the reconstruction. The highly curated model accurately predicts phenotypes under photoautotrophic, heterotrophic, and mixotrophic conditions. The model was validated against experimental data and lays the foundation for model-driven strain design and medium alteration to improve yield. Calculated flux distributions under different trophic conditions show that a number of key pathways are affected by nitrogen starvation conditions, including central carbon metabolism and amino acid, nucleotide, and pigment biosynthetic pathways. Furthermore, model prediction of growth rates under various medium compositions and subsequent experimental validation showed an increased growth rate with the addition of tryptophan and methionine. PMID:27372244
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Bushell Michael E
2011-05-01
Full Text Available Abstract Background Constraint-based approaches facilitate the prediction of cellular metabolic capabilities, based, in turn on predictions of the repertoire of enzymes encoded in the genome. Recently, genome annotations have been used to reconstruct genome scale metabolic reaction networks for numerous species, including Homo sapiens, which allow simulations that provide valuable insights into topics, including predictions of gene essentiality of pathogens, interpretation of genetic polymorphism in metabolic disease syndromes and suggestions for novel approaches to microbial metabolic engineering. These constraint-based simulations are being integrated with the functional genomics portals, an activity that requires efficient implementation of the constraint-based simulations in the web-based environment. Results Here, we present Acorn, an open source (GNU GPL grid computing system for constraint-based simulations of genome scale metabolic reaction networks within an interactive web environment. The grid-based architecture allows efficient execution of computationally intensive, iterative protocols such as Flux Variability Analysis, which can be readily scaled up as the numbers of models (and users increase. The web interface uses AJAX, which facilitates efficient model browsing and other search functions, and intuitive implementation of appropriate simulation conditions. Research groups can install Acorn locally and create user accounts. Users can also import models in the familiar SBML format and link reaction formulas to major functional genomics portals of choice. Selected models and simulation results can be shared between different users and made publically available. Users can construct pathway map layouts and import them into the server using a desktop editor integrated within the system. Pathway maps are then used to visualise numerical results within the web environment. To illustrate these features we have deployed Acorn and created a
Fang, Yilin; Yabusaki, Steven B.; Lipton, Mary S.; Long, Philip E.
2012-01-01
Accurately predicting the interactions between microbial metabolism and the physical subsurface environment is necessary to enhance subsurface energy development, soil and groundwater cleanup, and carbon management. This study was an initial attempt to confirm the metabolic functional roles within an in silico model using environmental proteomic data collected during field experiments. Shotgun global proteomics data collected during a subsurface biostimulation experiment were used to validate a genome-scale metabolic model of Geobacter metallireducens—specifically, the ability of the metabolic model to predict metal reduction, biomass yield, and growth rate under dynamic field conditions. The constraint-based in silico model of G. metallireducens relates an annotated genome sequence to the physiological functions with 697 reactions controlled by 747 enzyme-coding genes. Proteomic analysis showed that 180 of the 637 G. metallireducens proteins detected during the 2008 experiment were associated with specific metabolic reactions in the in silico model. When the field-calibrated Fe(III) terminal electron acceptor process reaction in a reactive transport model for the field experiments was replaced with the genome-scale model, the model predicted that the largest metabolic fluxes through the in silico model reactions generally correspond to the highest abundances of proteins that catalyze those reactions. Central metabolism predicted by the model agrees well with protein abundance profiles inferred from proteomic analysis. Model discrepancies with the proteomic data, such as the relatively low abundances of proteins associated with amino acid transport and metabolism, revealed pathways or flux constraints in the in silico model that could be updated to more accurately predict metabolic processes that occur in the subsurface environment. PMID:23042184
Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models
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Joseph A. Wayman
2015-03-01
Full Text Available Cell-free systems offer many advantages for the study, manipulation and modeling of metabolism compared to in vivo processes. Many of the challenges confronting genome-scale kinetic modeling can potentially be overcome in a cell-free system. For example, there is no complex transcriptional regulation to consider, transient metabolic measurements are easier to obtain, and we no longer have to consider cell growth. Thus, cell-free operation holds several significant advantages for model development, identification and validation. Theoretically, genome-scale cell-free kinetic models may be possible for industrially important organisms, such as E. coli, if a simple, tractable framework for integrating allosteric regulation with enzyme kinetics can be formulated. Toward this unmet need, we present an effective biochemical network modeling framework for building dynamic cell-free metabolic models. The key innovation of our approach is the integration of simple effective rules encoding complex allosteric regulation with traditional kinetic pathway modeling. We tested our approach by modeling the time evolution of several hypothetical cell-free metabolic networks. We found that simple effective rules, when integrated with traditional enzyme kinetic expressions, captured complex allosteric patterns such as ultrasensitivity or non-competitive inhibition in the absence of mechanistic information. Second, when integrated into network models, these rules captured classic regulatory patterns such as product-induced feedback inhibition. Lastly, we showed, at least for the network architectures considered here, that we could simultaneously estimate kinetic parameters and allosteric connectivity from synthetic data starting from an unbiased collection of possible allosteric structures using particle swarm optimization. However, when starting with an initial population that was heavily enriched with incorrect structures, our particle swarm approach could converge
International Nuclear Information System (INIS)
Kimpland, R.H.
1996-01-01
A normalized form of the point kinetics equations, a prompt jump approximation, and the Nordheim-Fuchs model are used to model nuclear systems. Reactivity feedback mechanisms considered include volumetric expansion, thermal neutron temperature effect, Doppler effect and void formation. A sample problem of an excursion occurring in a plutonium solution accidentally formed in a glovebox is presented
Oxidative desulfurization: kinetic modelling.
Dhir, S; Uppaluri, R; Purkait, M K
2009-01-30
Increasing environmental legislations coupled with enhanced production of petroleum products demand, the deployment of novel technologies to remove organic sulfur efficiently. This work represents the kinetic modeling of ODS using H(2)O(2) over tungsten-containing layered double hydroxide (LDH) using the experimental data provided by Hulea et al. [V. Hulea, A.L. Maciuca, F. Fajula, E. Dumitriu, Catalytic oxidation of thiophenes and thioethers with hydrogen peroxide in the presence of W-containing layered double hydroxides, Appl. Catal. A: Gen. 313 (2) (2006) 200-207]. The kinetic modeling approach in this work initially targets the scope of the generation of a superstructure of micro-kinetic reaction schemes and models assuming Langmuir-Hinshelwood (LH) and Eley-Rideal (ER) mechanisms. Subsequently, the screening and selection of above models is initially based on profile-based elimination of incompetent schemes followed by non-linear regression search performed using the Levenberg-Marquardt algorithm (LMA) for the chosen models. The above analysis inferred that Eley-Rideal mechanism describes the kinetic behavior of ODS process using tungsten-containing LDH, with adsorption of reactant and intermediate product only taking place on the catalyst surface. Finally, an economic index is presented that scopes the economic aspects of the novel catalytic technology with the parameters obtained during regression analysis to conclude that the cost factor for the catalyst is 0.0062-0.04759 US $ per barrel.
Oxidative desulfurization: Kinetic modelling
International Nuclear Information System (INIS)
Dhir, S.; Uppaluri, R.; Purkait, M.K.
2009-01-01
Increasing environmental legislations coupled with enhanced production of petroleum products demand, the deployment of novel technologies to remove organic sulfur efficiently. This work represents the kinetic modeling of ODS using H 2 O 2 over tungsten-containing layered double hydroxide (LDH) using the experimental data provided by Hulea et al. [V. Hulea, A.L. Maciuca, F. Fajula, E. Dumitriu, Catalytic oxidation of thiophenes and thioethers with hydrogen peroxide in the presence of W-containing layered double hydroxides, Appl. Catal. A: Gen. 313 (2) (2006) 200-207]. The kinetic modeling approach in this work initially targets the scope of the generation of a superstructure of micro-kinetic reaction schemes and models assuming Langmuir-Hinshelwood (LH) and Eley-Rideal (ER) mechanisms. Subsequently, the screening and selection of above models is initially based on profile-based elimination of incompetent schemes followed by non-linear regression search performed using the Levenberg-Marquardt algorithm (LMA) for the chosen models. The above analysis inferred that Eley-Rideal mechanism describes the kinetic behavior of ODS process using tungsten-containing LDH, with adsorption of reactant and intermediate product only taking place on the catalyst surface. Finally, an economic index is presented that scopes the economic aspects of the novel catalytic technology with the parameters obtained during regression analysis to conclude that the cost factor for the catalyst is 0.0062-0.04759 US $ per barrel
Modeling chemical kinetics graphically
Heck, A.
2012-01-01
In literature on chemistry education it has often been suggested that students, at high school level and beyond, can benefit in their studies of chemical kinetics from computer supported activities. Use of system dynamics modeling software is one of the suggested quantitative approaches that could
Directory of Open Access Journals (Sweden)
Yali eWang
2015-06-01
Full Text Available Actinoplanes sp. SE50/110 produces the -glucosidase inhibitor acarbose, which is used to treat type 2 diabetes mellitus. To obtain a comprehensive understanding of its cellular metabolism, a genome-scale metabolic model of strain SE50/110, iYLW1028, was reconstructed on the bases of the genome annotation, biochemical databases, and extensive literature mining. Model iYLW1028 comprises 1028 genes, 1128 metabolites and 1219 reactions. 122 and 81 genes were essential for cell growth on acarbose synthesis and sucrose media, respectively, and the acarbose biosynthetic pathway in SE50/110 was expounded completely. Based on model predictions, the addition of arginine and histidine to the media increased acarbose production by 78% and 59%, respectively. Additionally, dissolved oxygen has a great effect on acarbose production based on model predictions. Furthermore, genes to be overexpressed for the overproduction of acarbose were identified, and the deletion of treY eliminated the formation of by-product component C. Model iYLW1028 is a useful platform for optimizing and systems metabolic engineering for acarbose production in Actinoplanes sp. SE50/110.
LLNL Chemical Kinetics Modeling Group
Energy Technology Data Exchange (ETDEWEB)
Pitz, W J; Westbrook, C K; Mehl, M; Herbinet, O; Curran, H J; Silke, E J
2008-09-24
The LLNL chemical kinetics modeling group has been responsible for much progress in the development of chemical kinetic models for practical fuels. The group began its work in the early 1970s, developing chemical kinetic models for methane, ethane, ethanol and halogenated inhibitors. Most recently, it has been developing chemical kinetic models for large n-alkanes, cycloalkanes, hexenes, and large methyl esters. These component models are needed to represent gasoline, diesel, jet, and oil-sand-derived fuels.
Knies, David; Wittmüß, Philipp; Appel, Sebastian; Sawodny, Oliver; Ederer, Michael; Feuer, Ronny
2015-10-28
The coccolithophorid unicellular alga Emiliania huxleyi is known to form large blooms, which have a strong effect on the marine carbon cycle. As a photosynthetic organism, it is subjected to a circadian rhythm due to the changing light conditions throughout the day. For a better understanding of the metabolic processes under these periodically-changing environmental conditions, a genome-scale model based on a genome reconstruction of the E. huxleyi strain CCMP 1516 was created. It comprises 410 reactions and 363 metabolites. Biomass composition is variable based on the differentiation into functional biomass components and storage metabolites. The model is analyzed with a flux balance analysis approach called diurnal flux balance analysis (diuFBA) that was designed for organisms with a circadian rhythm. It allows storage metabolites to accumulate or be consumed over the diurnal cycle, while keeping the structure of a classical FBA problem. A feature of this approach is that the production and consumption of storage metabolites is not defined externally via the biomass composition, but the result of optimal resource management adapted to the diurnally-changing environmental conditions. The model in combination with this approach is able to simulate the variable biomass composition during the diurnal cycle in proximity to literature data.
Directory of Open Access Journals (Sweden)
David Knies
2015-10-01
Full Text Available The coccolithophorid unicellular alga Emiliania huxleyi is known to form large blooms, which have a strong effect on the marine carbon cycle. As a photosynthetic organism, it is subjected to a circadian rhythm due to the changing light conditions throughout the day. For a better understanding of the metabolic processes under these periodically-changing environmental conditions, a genome-scale model based on a genome reconstruction of the E. huxleyi strain CCMP 1516 was created. It comprises 410 reactions and 363 metabolites. Biomass composition is variable based on the differentiation into functional biomass components and storage metabolites. The model is analyzed with a flux balance analysis approach called diurnal flux balance analysis (diuFBA that was designed for organisms with a circadian rhythm. It allows storage metabolites to accumulate or be consumed over the diurnal cycle, while keeping the structure of a classical FBA problem. A feature of this approach is that the production and consumption of storage metabolites is not defined externally via the biomass composition, but the result of optimal resource management adapted to the diurnally-changing environmental conditions. The model in combination with this approach is able to simulate the variable biomass composition during the diurnal cycle in proximity to literature data.
DEFF Research Database (Denmark)
Irani, Zahra Azimzadeh; Kerkhoven, Eduard J.; Shojaosadati, Seyed Abbas
2016-01-01
prediction of protein yield, demonstrates the effect of the different types of N-glycosylation of protein yield, and can be used to predict potential targets for strain improvement. The model represents a step towards a more complete description of protein production in P. pastoris, which is required...... for using these models to understand and optimize protein production processes....
Directory of Open Access Journals (Sweden)
Ankita Chatterjee
2017-11-01
Full Text Available To combat decrease in rice productivity under different stresses, an understanding of rice metabolism is needed. Though there are different genome scale metabolic models (GSMs of Oryza sativa japonica, no GSM with gene-protein-reaction association exist for Oryza sativa indica. Here, we report a GSM, OSI1136 of O.s. indica, which includes 3602 genes and 1136 metabolic reactions and transporters distributed across the cytosol, mitochondrion, peroxisome, and chloroplast compartments. Flux balance analysis of the model showed that for varying RuBisCO activity (Vc/Vo (i the activity of the chloroplastic malate valve increases to transport reducing equivalents out of the chloroplast under increased photorespiratory conditions and (ii glyceraldehyde-3-phosphate dehydrogenase and phosphoglycerate kinase can act as source of cytosolic ATP under decreased photorespiration. Under increasing light conditions we observed metabolic flexibility, involving photorespiration, chloroplastic triose phosphate and the dicarboxylate transporters of the chloroplast and mitochondrion for redox and ATP exchanges across the intracellular compartments. Simulations under different enzymatic cost conditions revealed (i participation of peroxisomal glutathione-ascorbate cycle in photorespiratory H2O2 metabolism (ii different modes of the chloroplastic triose phosphate transporters and malate valve, and (iii two possible modes of chloroplastic Glu–Gln transporter which were related with the activity of chloroplastic and cytosolic isoforms of glutamine synthetase. Altogether, our results provide new insights into plant metabolism.
International Nuclear Information System (INIS)
Augusiak, R; Cucchietti, F M; Lewenstein, M; Haake, F
2010-01-01
In this paper, we introduce a quantum generalization of classical kinetic Ising models (KIM), described by a certain class of quantum many-body master equations. Similarly to KIMs with detailed balance that are equivalent to certain Hamiltonian systems, our models reduce to a set of Hamiltonian systems determining the dynamics of the elements of the many-body density matrix. The ground states of these Hamiltonians are well described by the matrix product, or pair entangled projected states. We discuss critical properties of such Hamiltonians, as well as entanglement properties of their low-energy states.
Cordes, Henrik; Thiel, Christoph; Baier, Vanessa; Blank, Lars M; Kuepfer, Lars
2018-01-01
Drug-induced perturbations of the endogenous metabolic network are a potential root cause of cellular toxicity. A mechanistic understanding of such unwanted side effects during drug therapy is therefore vital for patient safety. The comprehensive assessment of such drug-induced injuries requires the simultaneous consideration of both drug exposure at the whole-body and resulting biochemical responses at the cellular level. We here present a computational multi-scale workflow that combines whole-body physiologically based pharmacokinetic (PBPK) models and organ-specific genome-scale metabolic network (GSMN) models through shared reactions of the xenobiotic metabolism. The applicability of the proposed workflow is illustrated for isoniazid, a first-line antibacterial agent against Mycobacterium tuberculosis , which is known to cause idiosyncratic drug-induced liver injuries (DILI). We combined GSMN models of a human liver with N-acetyl transferase 2 (NAT2)-phenotype-specific PBPK models of isoniazid. The combined PBPK-GSMN models quantitatively describe isoniazid pharmacokinetics, as well as intracellular responses, and changes in the exometabolome in a human liver following isoniazid administration. Notably, intracellular and extracellular responses identified with the PBPK-GSMN models are in line with experimental and clinical findings. Moreover, the drug-induced metabolic perturbations are distributed and attenuated in the metabolic network in a phenotype-dependent manner. Our simulation results show that a simultaneous consideration of both drug pharmacokinetics at the whole-body and metabolism at the cellular level is mandatory to explain drug-induced injuries at the patient level. The proposed workflow extends our mechanistic understanding of the biochemistry underlying adverse events and may be used to prevent drug-induced injuries in the future.
Razmilic, Valeria; Castro, Jean F; Andrews, Barbara; Asenjo, Juan A
2018-07-01
The first genome scale model (GSM) for Streptomyces leeuwenhoekii C34 was developed to study the biosynthesis pathways of specialized metabolites and to find metabolic engineering targets for enhancing their production. The model, iVR1007, consists of 1,722 reactions, 1,463 metabolites, and 1,007 genes, it includes the biosynthesis pathways of chaxamycins, chaxalactins, desferrioxamines, ectoine, and other specialized metabolites. iVR1007 was validated using experimental information of growth on 166 different sources of carbon, nitrogen and phosphorous, showing an 83.7% accuracy. The model was used to predict metabolic engineering targets for enhancing the biosynthesis of chaxamycins and chaxalactins. Gene knockouts, such as sle03600 (L-homoserine O-acetyltransferase), and sle39090 (trehalose-phosphate synthase), that enhance the production of the specialized metabolites by increasing the pool of precursors were identified. Using the algorithm of flux scanning based on enforced objective flux (FSEOF) implemented in python, 35 and 25 over-expression targets for increasing the production of chaxamycin A and chaxalactin A, respectively, that were not directly associated with their biosynthesis routes were identified. Nineteen over-expression targets that were common to the two specialized metabolites studied, like the over-expression of the acetyl carboxylase complex (sle47660 (accA) and any of the following genes: sle44630 (accA_1) or sle39830 (accA_2) or sle27560 (bccA) or sle59710) were identified. The predicted knockouts and over-expression targets will be used to perform metabolic engineering of S. leeuwenhoekii C34 and obtain overproducer strains. © 2018 Wiley Periodicals, Inc.
Yabusaki, S.; Fang, Y.; Wilkins, M. J.; Long, P.; Rifle IFRC Science Team
2011-12-01
A series of field experiments in a shallow alluvial aquifer at a former uranium mill tailings site have demonstrated that indigenous bacteria can be stimulated with acetate to catalyze the conversion of hexavalent uranium in a groundwater plume to immobile solid-associated uranium in the +4 oxidation state. While this bioreduction of uranium has been shown to lower groundwater concentrations below actionable standards, a viable remediation methodology will need a mechanistic, predictive and quantitative understanding of the microbially-mediated reactions that catalyze the reduction of uranium in the context of site-specific processes, properties, and conditions. At the Rifle IFRC site, we are investigating the impacts on uranium behavior of pulsed acetate amendment, acetate-oxidizing iron and sulfate reducing bacteria, seasonal water table variation, spatially-variable physical (hydraulic conductivity, porosity) and geochemical (reactive surface area) material properties. The simulation of three-dimensional, variably saturated flow and biogeochemical reactive transport during a uranium bioremediation field experiment includes a genome-scale in silico model of Geobacter sp. to represent the Fe(III) terminal electron accepting process (TEAP). The Geobacter in silico model of cell-scale physiological metabolic pathways is comprised of hundreds of intra-cellular and environmental exchange reactions. One advantage of this approach is that the TEAP reaction stoichiometry and rate are now functions of the metabolic status of the microorganism. The linkage of in silico model reactions to specific Geobacter proteins has enabled the use of groundwater proteomic analyses to assess the accuracy of the model under evolving hydrologic and biogeochemical conditions. In this case, the largest predicted fluxes through in silico model reactions generally correspond to high abundances of proteins linked to those reactions (e.g. the condensation reaction catalyzed by the protein
Tajparast, Mohammad; Frigon, Dominic
2013-01-01
Studying storage metabolism during feast-famine cycles of activated sludge treatment systems provides profound insight in terms of both operational issues (e.g., foaming and bulking) and process optimization for the production of value added by-products (e.g., bioplastics). We examined the storage metabolism (including poly-β-hydroxybutyrate [PHB], glycogen, and triacylglycerols [TAGs]) during feast-famine cycles using two genome-scale metabolic models: Rhodococcus jostii RHA1 (iMT1174) and Escherichia coli K-12 (iAF1260) for growth on glucose, acetate, and succinate. The goal was to develop the proper objective function (OF) for the prediction of the main storage compound produced in activated sludge for given feast-famine cycle conditions. For the flux balance analysis, combinations of three OFs were tested. For all of them, the main OF was to maximize growth rates. Two additional sub-OFs were used: (1) minimization of biochemical fluxes, and (2) minimization of metabolic adjustments (MoMA) between the feast and famine periods. All (sub-)OFs predicted identical substrate-storage associations for the feast-famine growth of the above-mentioned metabolic models on a given substrate when glucose and acetate were set as sole carbon sources (i.e., glucose-glycogen and acetate-PHB), in agreement with experimental observations. However, in the case of succinate as substrate, the predictions depended on the network structure of the metabolic models such that the E. coli model predicted glycogen accumulation and the R. jostii model predicted PHB accumulation. While the accumulation of both PHB and glycogen was observed experimentally, PHB showed higher dynamics during an activated sludge feast-famine growth cycle with succinate as substrate. These results suggest that new modeling insights between metabolic predictions and population ecology will be necessary to properly predict metabolisms likely to emerge within the niches of activated sludge communities. Nonetheless
The OME Framework for genome-scale systems biology
Energy Technology Data Exchange (ETDEWEB)
Palsson, Bernhard O. [Univ. of California, San Diego, CA (United States); Ebrahim, Ali [Univ. of California, San Diego, CA (United States); Federowicz, Steve [Univ. of California, San Diego, CA (United States)
2014-12-19
The life sciences are undergoing continuous and accelerating integration with computational and engineering sciences. The biology that many in the field have been trained on may be hardly recognizable in ten to twenty years. One of the major drivers for this transformation is the blistering pace of advancements in DNA sequencing and synthesis. These advances have resulted in unprecedented amounts of new data, information, and knowledge. Many software tools have been developed to deal with aspects of this transformation and each is sorely needed [1-3]. However, few of these tools have been forced to deal with the full complexity of genome-scale models along with high throughput genome- scale data. This particular situation represents a unique challenge, as it is simultaneously necessary to deal with the vast breadth of genome-scale models and the dizzying depth of high-throughput datasets. It has been observed time and again that as the pace of data generation continues to accelerate, the pace of analysis significantly lags behind [4]. It is also evident that, given the plethora of databases and software efforts [5-12], it is still a significant challenge to work with genome-scale metabolic models, let alone next-generation whole cell models [13-15]. We work at the forefront of model creation and systems scale data generation [16-18]. The OME Framework was borne out of a practical need to enable genome-scale modeling and data analysis under a unified framework to drive the next generation of genome-scale biological models. Here we present the OME Framework. It exists as a set of Python classes. However, we want to emphasize the importance of the underlying design as an addition to the discussions on specifications of a digital cell. A great deal of work and valuable progress has been made by a number of communities [13, 19-24] towards interchange formats and implementations designed to achieve similar goals. While many software tools exist for handling genome-scale
Crystallization Kinetics within a Generic Modelling Framework
DEFF Research Database (Denmark)
Meisler, Kresten Troelstrup; von Solms, Nicolas; Gernaey, Krist
2013-01-01
An existing generic modelling framework has been expanded with tools for kinetic model analysis. The analysis of kinetics is carried out within the framework where kinetic constitutive models are collected, analysed and utilized for the simulation of crystallization operations. A modelling...... procedure is proposed to gain the information of crystallization operation kinetic model analysis and utilize this for faster evaluation of crystallization operations....
Integrated stoichiometric, thermodynamic and kinetic modelling of steady state metabolism.
Fleming, R M T; Thiele, I; Provan, G; Nasheuer, H P
2010-06-07
The quantitative analysis of biochemical reactions and metabolites is at frontier of biological sciences. The recent availability of high-throughput technology data sets in biology has paved the way for new modelling approaches at various levels of complexity including the metabolome of a cell or an organism. Understanding the metabolism of a single cell and multi-cell organism will provide the knowledge for the rational design of growth conditions to produce commercially valuable reagents in biotechnology. Here, we demonstrate how equations representing steady state mass conservation, energy conservation, the second law of thermodynamics, and reversible enzyme kinetics can be formulated as a single system of linear equalities and inequalities, in addition to linear equalities on exponential variables. Even though the feasible set is non-convex, the reformulation is exact and amenable to large-scale numerical analysis, a prerequisite for computationally feasible genome scale modelling. Integrating flux, concentration and kinetic variables in a unified constraint-based formulation is aimed at increasing the quantitative predictive capacity of flux balance analysis. Incorporation of experimental and theoretical bounds on thermodynamic and kinetic variables ensures that the predicted steady state fluxes are both thermodynamically and biochemically feasible. The resulting in silico predictions are tested against fluxomic data for central metabolism in Escherichia coli and compare favourably with in silico prediction by flux balance analysis. Copyright (c) 2010 Elsevier Ltd. All rights reserved.
Chemical kinetics and combustion modeling
Energy Technology Data Exchange (ETDEWEB)
Miller, J.A. [Sandia National Laboratories, Livermore, CA (United States)
1993-12-01
The goal of this program is to gain qualitative insight into how pollutants are formed in combustion systems and to develop quantitative mathematical models to predict their formation rates. The approach is an integrated one, combining low-pressure flame experiments, chemical kinetics modeling, theory, and kinetics experiments to gain as clear a picture as possible of the process in question. These efforts are focused on problems involved with the nitrogen chemistry of combustion systems and on the formation of soot and PAH in flames.
Modeling the isochronal crystallization kinetics
International Nuclear Information System (INIS)
Sahay, S.S.; Krishnan, Karthik
2004-01-01
The classical Johnson-Mehl-Avrami-Kolmogorov (JMAK) model, originally formulated for the isothermal condition, is often used in conjunction with additivity principle for modeling the non-isothermal crystallization kinetics. This approach at times results in significant differences between the model prediction and experimental data. In this article, a modification to this approach has been imposed via an additional functional relationship between the activation energy and heating rate. The methodology has been validated with experimental isochronal crystallization kinetic data in Se 71 Te 20 Sb 9 glass and Ge 20 Te 80 systems. It has been shown that the functional relationship between heating rate and activation energy, ascribed to the reduction in apparent activation energy due to increasing non-isothermality, provides better phenomenological description and therefore improves the prediction capability of the JMAK model under isochronal condition
Reimonn, Thomas M; Park, Seo-Young; Agarabi, Cyrus D; Brorson, Kurt A; Yoon, Seongkyu
2016-09-01
Genome-scale flux balance analysis (FBA) is a powerful systems biology tool to characterize intracellular reaction fluxes during cell cultures. FBA estimates intracellular reaction rates by optimizing an objective function, subject to the constraints of a metabolic model and media uptake/excretion rates. A dynamic extension to FBA, dynamic flux balance analysis (DFBA), can calculate intracellular reaction fluxes as they change during cell cultures. In a previous study by Read et al. (2013), a series of informed amino acid supplementation experiments were performed on twelve parallel murine hybridoma cell cultures, and this data was leveraged for further analysis (Read et al., Biotechnol Prog. 2013;29:745-753). In order to understand the effects of media changes on the model murine hybridoma cell line, a systems biology approach is applied in the current study. Dynamic flux balance analysis was performed using a genome-scale mouse metabolic model, and multivariate data analysis was used for interpretation. The calculated reaction fluxes were examined using partial least squares and partial least squares discriminant analysis. The results indicate media supplementation increases product yield because it raises nutrient levels extending the growth phase, and the increased cell density allows for greater culture performance. At the same time, the directed supplementation does not change the overall metabolism of the cells. This supports the conclusion that product quality, as measured by glycoform assays, remains unchanged because the metabolism remains in a similar state. Additionally, the DFBA shows that metabolic state varies more at the beginning of the culture but less by the middle of the growth phase, possibly due to stress on the cells during inoculation. © 2016 American Institute of Chemical Engineers Biotechnol. Prog., 32:1163-1173, 2016. © 2016 American Institute of Chemical Engineers.
Genome-Scale Reconstruction of the Human Astrocyte Metabolic Network
Mart?n-Jim?nez, Cynthia A.; Salazar-Barreto, Diego; Barreto, George E.; Gonz?lez, Janneth
2017-01-01
Astrocytes are the most abundant cells of the central nervous system; they have a predominant role in maintaining brain metabolism. In this sense, abnormal metabolic states have been found in different neuropathological diseases. Determination of metabolic states of astrocytes is difficult to model using current experimental approaches given the high number of reactions and metabolites present. Thus, genome-scale metabolic networks derived from transcriptomic data can be used as a framework t...
A kinetic model for hydrodesulfurisation
Energy Technology Data Exchange (ETDEWEB)
Sau, M.; Narasimhan, C.S.L.; Verma, R.P. [Indian Oil Corporation Limited, Research and Development Centre, Faridabad (India)
1997-07-01
Due to stringent environmental considerations and related insistence on low sulfur fuels, hydrodesulfurisation has emerged as an important component of any refining scheme globally. The process is used ranging from Naphta/Kerosine hydrotreating to heavy oil hydrotreating. Processes such as Deep gas oil desulfurisation aiming at reduction of sulfur levels to less than 500 ppm have emerged as major players in the scenario. Hydrodesulfurisation (HDS) involves parallel desulfurisation of different organo-sulfur compounds present in the complex petroleum mixtures. In order to design, monitor, optimise and control the HDS reactor, it is necessary to have a detailed, yet simple model which follows the reaction chemistry accurately. In the present paper, a kinetic model is presented for HDS using continuum theory of lumping. The sulfur distribution in the reaction mixture is treated as continuum and parallel reaction networks are devised for kinetic modelling using continuum theory of lumping approach. The model based on the above approach follows the HDS chemistry reasonably well and hence the model parameters are almost feed invariant. Methods are also devised to incorporate heat and pressure effects into the model. The model has been validated based on commercial kero-HDS data. It is found that the model predictions agree with the experimental/commercial data. 17 refs.
Kinetic modelling of enzymatic starch hydrolysis
Bednarska, K.A.
2015-01-01
Kinetic modelling of enzymatic starch hydrolysis – a summary
K.A. Bednarska
The dissertation entitled ‘Kinetic modelling of enzymatic starch hydrolysis’ describes the enzymatic hydrolysis and kinetic modelling of liquefaction and saccharification of wheat starch.
Genome scale engineering techniques for metabolic engineering.
Liu, Rongming; Bassalo, Marcelo C; Zeitoun, Ramsey I; Gill, Ryan T
2015-11-01
Metabolic engineering has expanded from a focus on designs requiring a small number of genetic modifications to increasingly complex designs driven by advances in genome-scale engineering technologies. Metabolic engineering has been generally defined by the use of iterative cycles of rational genome modifications, strain analysis and characterization, and a synthesis step that fuels additional hypothesis generation. This cycle mirrors the Design-Build-Test-Learn cycle followed throughout various engineering fields that has recently become a defining aspect of synthetic biology. This review will attempt to summarize recent genome-scale design, build, test, and learn technologies and relate their use to a range of metabolic engineering applications. Copyright © 2015 International Metabolic Engineering Society. Published by Elsevier Inc. All rights reserved.
Genome-scale neurogenetics: methodology and meaning.
McCarroll, Steven A; Feng, Guoping; Hyman, Steven E
2014-06-01
Genetic analysis is currently offering glimpses into molecular mechanisms underlying such neuropsychiatric disorders as schizophrenia, bipolar disorder and autism. After years of frustration, success in identifying disease-associated DNA sequence variation has followed from new genomic technologies, new genome data resources, and global collaborations that could achieve the scale necessary to find the genes underlying highly polygenic disorders. Here we describe early results from genome-scale studies of large numbers of subjects and the emerging significance of these results for neurobiology.
Kinetics model for lutate dosimetry
International Nuclear Information System (INIS)
Lima, M.F.; Mesquita, C.H.
2013-01-01
The use of compartmental analysis to predict the behavior of drugs in the organism is considered the better option among numerous methods employed in pharmacodynamics. A six compartments model was developed to determinate the kinetic constants of 177Lu-DOTATATO biodistribution using data from one published study with 67 patients treated by PRRT (Peptide receptor radionuclide therapy) and followed by CT during 68,25 hours. The compartmental analysis was made using the software AnaComp®. The influence of the time pos-injection over the dose assessment was studied taking into account the renal excretion management by aminoacid coinfusion, whose direct effects persist in the first day. The biodistribution curve was split in five sectors: 0-0.25h; 0-3.25h; 3.25-24.25h; 24.25-68.25h and 3.25-68.25h. After the examination of that influence, the study was concentrated in separate the biodistribution curve in two phases. Phase 1: governed by uptake from the blood, considering the time pos-injection until 3.25h and phase 2: governed by renal excretion, considering the time pos-injection from 3.25h to 68.25h. The model considered the organs and tissues superposition in the CT image acquisition by sampling parameters as the contribution of the the activity concentration in blood and relation between the sizes of the whole body and measured organs. The kinetic constants obtained from each phase (1 and 2) were used in dose assessment to patients in 26 organs and tissues described by MIRD. Dosimetry results were in agreement with the available results from literature, restrict to whole body, kidneys, bone marrow, spleen and liver. The advantage of the proposed model is the compartmental method quickness and power to estimate dose in organs and tissues, including tumor that, in the most part, were not discriminate by voxels of phantoms built using CT images. (author)
Kinetics model for lutate dosimetry
Energy Technology Data Exchange (ETDEWEB)
Lima, M.F.; Mesquita, C.H., E-mail: mflima@ipen.br, E-mail: chmesqui@ipen.br [Instituto de Pesquisas Energeticas (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)
2013-11-01
The use of compartmental analysis to predict the behavior of drugs in the organism is considered the better option among numerous methods employed in pharmacodynamics. A six compartments model was developed to determinate the kinetic constants of 177Lu-DOTATATO biodistribution using data from one published study with 67 patients treated by PRRT (Peptide receptor radionuclide therapy) and followed by CT during 68,25 hours. The compartmental analysis was made using the software AnaComp Registered-Sign . The influence of the time pos-injection over the dose assessment was studied taking into account the renal excretion management by aminoacid coinfusion, whose direct effects persist in the first day. The biodistribution curve was split in five sectors: 0-0.25h; 0-3.25h; 3.25-24.25h; 24.25-68.25h and 3.25-68.25h. After the examination of that influence, the study was concentrated in separate the biodistribution curve in two phases. Phase 1: governed by uptake from the blood, considering the time pos-injection until 3.25h and phase 2: governed by renal excretion, considering the time pos-injection from 3.25h to 68.25h. The model considered the organs and tissues superposition in the CT image acquisition by sampling parameters as the contribution of the the activity concentration in blood and relation between the sizes of the whole body and measured organs. The kinetic constants obtained from each phase (1 and 2) were used in dose assessment to patients in 26 organs and tissues described by MIRD. Dosimetry results were in agreement with the available results from literature, restrict to whole body, kidneys, bone marrow, spleen and liver. The advantage of the proposed model is the compartmental method quickness and power to estimate dose in organs and tissues, including tumor that, in the most part, were not discriminate by voxels of phantoms built using CT images. (author)
Crystallization Kinetics within a Generic Modeling Framework
DEFF Research Database (Denmark)
Meisler, Kresten Troelstrup; von Solms, Nicolas; Gernaey, Krist V.
2014-01-01
of employing a well-structured model library for storage, use/reuse, and analysis of the kinetic models are highlighted. Examples illustrating the application of the modeling framework for kinetic model discrimination related to simulation of specific crystallization scenarios and for kinetic model parameter......A new and extended version of a generic modeling framework for analysis and design of crystallization operations is presented. The new features of this framework are described, with focus on development, implementation, identification, and analysis of crystallization kinetic models. Issues related...... to the modeling of various kinetic phenomena like nucleation, growth, agglomeration, and breakage are discussed in terms of model forms, model parameters, their availability and/or estimation, and their selection and application for specific crystallization operational scenarios under study. The advantages...
Modeling composting kinetics: A review of approaches
Hamelers, H.V.M.
2004-01-01
Composting kinetics modeling is necessary to design and operate composting facilities that comply with strict market demands and tight environmental legislation. Current composting kinetics modeling can be characterized as inductive, i.e. the data are the starting point of the modeling process and
Chemical Kinetic Modeling of 2-Methylhexane Combustion
Mohamed, Samah Y.
2015-03-30
Accurate chemical kinetic combustion models of lightly branched alkanes (e.g., 2-methylalkanes) are important for investigating the combustion behavior of diesel, gasoline, and aviation fuels. Improving the fidelity of existing kinetic models is a necessity, as new experiments and advanced theories show inaccuracy in certain portions of the models. This study focuses on updating thermodynamic data and kinetic model for a gasoline surrogate fuel, 2-methylhexane, with recently published group values and rate rules. These update provides a better agreement with rapid compression machine measurements of ignition delay time, while also strengthening the fundamental basis of the model.
A mathematical model for iodine kinetics
International Nuclear Information System (INIS)
Silva, E.A.T. da.
1976-01-01
A mathematical model for the iodine kinetics in thyroid is presented followed by its analytical solution. An eletroanalogical model is also developed for a simplified stage and another is proposed for the main case [pt
Chemical Kinetic Modeling of 2-Methylhexane Combustion
Mohamed, Samah Y.; Sarathy, Mani
2015-01-01
necessity, as new experiments and advanced theories show inaccuracy in certain portions of the models. This study focuses on updating thermodynamic data and kinetic model for a gasoline surrogate fuel, 2-methylhexane, with recently published group values
New types of experimental data shape the use of enzyme kinetics for dynamic network modeling.
Tummler, Katja; Lubitz, Timo; Schelker, Max; Klipp, Edda
2014-01-01
Since the publication of Leonor Michaelis and Maude Menten's paper on the reaction kinetics of the enzyme invertase in 1913, molecular biology has evolved tremendously. New measurement techniques allow in vivo characterization of the whole genome, proteome or transcriptome of cells, whereas the classical enzyme essay only allows determination of the two Michaelis-Menten parameters V and K(m). Nevertheless, Michaelis-Menten kinetics are still commonly used, not only in the in vitro context of enzyme characterization but also as a rate law for enzymatic reactions in larger biochemical reaction networks. In this review, we give an overview of the historical development of kinetic rate laws originating from Michaelis-Menten kinetics over the past 100 years. Furthermore, we briefly summarize the experimental techniques used for the characterization of enzymes, and discuss web resources that systematically store kinetic parameters and related information. Finally, describe the novel opportunities that arise from using these data in dynamic mathematical modeling. In this framework, traditional in vitro approaches may be combined with modern genome-scale measurements to foster thorough understanding of the underlying complex mechanisms. © 2013 FEBS.
Kinetic equations for the collisional plasma model
International Nuclear Information System (INIS)
Rij, W.I. Van; Meier, H.K.; Beasley, C.O. Jr.; McCune, J.E.
1977-01-01
Using the Collisional Plasma Model (CPM) representation, expressions are derived for the Vlasov operator, both in its general form and in the drift-kinetic approximation following the recursive derivation by Hazeltine. The expressions for the operators give easily calculated couplings between neighbouring components of the CPM representation. Expressions for various macroscopic observables in the drift-kinetics approximation are also given. (author)
Kinetic Model of Growth of Arthropoda Populations
Ershov, Yu. A.; Kuznetsov, M. A.
2018-05-01
Kinetic equations were derived for calculating the growth of crustacean populations ( Crustacea) based on the biological growth model suggested earlier using shrimp ( Caridea) populations as an example. The development cycle of successive stages for populations can be represented in the form of quasi-chemical equations. The kinetic equations that describe the development cycle of crustaceans allow quantitative prediction of the development of populations depending on conditions. In contrast to extrapolation-simulation models, in the developed kinetic model of biological growth the kinetic parameters are the experimental characteristics of population growth. Verification and parametric identification of the developed model on the basis of the experimental data showed agreement with experiment within the error of the measurement technique.
Levering, J.; Fiedler, T.; Sieg, A.; van Grinsven, K.W.A.; Hering, S.; Veith, N.; Olivier, B.G.; Klett, L.; Hugenholtz, J.; Teusink, B.; Kreikemeyer, B.; Kummer, U.
2016-01-01
Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes
In Silico Genome-Scale Reconstruction and Validation of the Staphylococcus aureus Metabolic Network
Heinemann, Matthias; Kümmel, Anne; Ruinatscha, Reto; Panke, Sven
2005-01-01
A genome-scale metabolic model of the Gram-positive, facultative anaerobic opportunistic pathogen Staphylococcus aureus N315 was constructed based on current genomic data, literature, and physiological information. The model comprises 774 metabolic processes representing approximately 23% of all
Modeling the degradation kinetics of ascorbic acid.
Peleg, Micha; Normand, Mark D; Dixon, William R; Goulette, Timothy R
2018-06-13
Most published reports on ascorbic acid (AA) degradation during food storage and heat preservation suggest that it follows first-order kinetics. Deviations from this pattern include Weibullian decay, and exponential drop approaching finite nonzero retention. Almost invariably, the degradation rate constant's temperature-dependence followed the Arrhenius equation, and hence the simpler exponential model too. A formula and freely downloadable interactive Wolfram Demonstration to convert the Arrhenius model's energy of activation, E a , to the exponential model's c parameter, or vice versa, are provided. The AA's isothermal and non-isothermal degradation can be simulated with freely downloadable interactive Wolfram Demonstrations in which the model's parameters can be entered and modified by moving sliders on the screen. Where the degradation is known a priori to follow first or other fixed order kinetics, one can use the endpoints method, and in principle the successive points method too, to estimate the reaction's kinetic parameters from considerably fewer AA concentration determinations than in the traditional manner. Freeware to do the calculations by either method has been recently made available on the Internet. Once obtained in this way, the kinetic parameters can be used to reconstruct the entire degradation curves and predict those at different temperature profiles, isothermal or dynamic. Comparison of the predicted concentration ratios with experimental ones offers a way to validate or refute the kinetic model and the assumptions on which it is based.
Thermodynamic and kinetic modelling: creep resistant materials
DEFF Research Database (Denmark)
Hald, John; Korcakova, L.; Danielsen, Hilmar Kjartansson
2008-01-01
The use of thermodynamic and kinetic modelling of microstructure evolution in materials exposed to high temperatures in power plants is demonstrated with two examples. Precipitate stability in martensitic 9–12%Cr steels is modelled including equilibrium phase stability, growth of Laves phase part...
Kinetics model of bainitic transformation with stress
Zhou, Mingxing; Xu, Guang; Hu, Haijiang; Yuan, Qing; Tian, Junyu
2018-01-01
Thermal simulations were conducted on a Gleeble 3800 simulator. The main purpose is to investigate the effects of stress on the kinetics of bainitic transformation in a Fe-C-Mn-Si advanced high strength bainitic steel. Previous studies on modeling the kinetics of stress affected bainitic transformation only considered the stress below the yield strength of prior austenite. In the present study, the stress above the yield strength of prior austenite is taken into account. A new kinetics model of bainitic transformation dependent on the stress (including the stresses below and above the yield strength of prior austenite) and the transformation temperature is proposed. The new model presents a good agreement with experimental results. In addition, it is found that the acceleration degree of stress on bainitic transformation increases with the stress whether its magnitude is below or above the yield strength of austenite, but the increasing rate gradually slows down when the stress is above the yield strength of austenite.
Chemical Kinetic Models for Advanced Engine Combustion
Energy Technology Data Exchange (ETDEWEB)
Pitz, William J. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Mehl, Marco [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States); Westbrook, Charles K. [Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
2014-10-22
The objectives for this project are as follows: Develop detailed chemical kinetic models for fuel components used in surrogate fuels for compression ignition (CI), homogeneous charge compression ignition (HCCI) and reactivity-controlled compression-ignition (RCCI) engines; and Combine component models into surrogate fuel models to represent real transportation fuels. Use them to model low-temperature combustion strategies in HCCI, RCCI, and CI engines that lead to low emissions and high efficiency.
Directory of Open Access Journals (Sweden)
Liu Lili
2013-06-01
Full Text Available Understanding how metabolic reactions translate the genome of an organism into its phenotype is a grand challenge in biology. Genome-wide association studies (GWAS statistically connect genotypes to phenotypes, without any recourse to known molecular interactions, whereas a molecular mechanistic description ties gene function to phenotype through gene regulatory networks (GRNs, protein-protein interactions (PPIs and molecular pathways. Integration of different regulatory information levels of an organism is expected to provide a good way for mapping genotypes to phenotypes. However, the lack of curated metabolic model of rice is blocking the exploration of genome-scale multi-level network reconstruction. Here, we have merged GRNs, PPIs and genome-scale metabolic networks (GSMNs approaches into a single framework for rice via omics’ regulatory information reconstruction and integration. Firstly, we reconstructed a genome-scale metabolic model, containing 4,462 function genes, 2,986 metabolites involved in 3,316 reactions, and compartmentalized into ten subcellular locations. Furthermore, 90,358 pairs of protein-protein interactions, 662,936 pairs of gene regulations and 1,763 microRNA-target interactions were integrated into the metabolic model. Eventually, a database was developped for systematically storing and retrieving the genome-scale multi-level network of rice. This provides a reference for understanding genotype-phenotype relationship of rice, and for analysis of its molecular regulatory network.
Kinetic modeling of reactions in Foods
Boekel, van M.A.J.S.
2008-01-01
The level of quality that food maintains as it travels down the production-to-consumption path is largely determined by the chemical, biochemical, physical, and microbiological changes that take place during its processing and storage. Kinetic Modeling of Reactions in Foods demonstrates how to
A MODEL FOR POSTRADIATION STEM CELL KINETICS,
In polycythemic rats observed for 17 days postradiation (300 R, 250 KVP X-rays) it was noted that stem cell release diminished to 8 percent of the...correlate these findings with a kinetic model of erythropoiesis. It was suggested that the initial depression in stem cell release might be due to cellular
Kinetic mechanism for modeling of electrochemical reactions.
Cervenka, Petr; Hrdlička, Jiří; Přibyl, Michal; Snita, Dalimil
2012-04-01
We propose a kinetic mechanism of electrochemical interactions. We assume fast formation and recombination of electron donors D- and acceptors A+ on electrode surfaces. These mediators are continuously formed in the electrode matter by thermal fluctuations. The mediators D- and A+, chemically equivalent to the electrode metal, enter electrochemical interactions on the electrode surfaces. Electrochemical dynamics and current-voltage characteristics of a selected electrochemical system are studied. Our results are in good qualitative agreement with those given by the classical Butler-Volmer kinetics. The proposed model can be used to study fast electrochemical processes in microsystems and nanosystems that are often out of the thermal equilibrium. Moreover, the kinetic mechanism operates only with the surface concentrations of chemical reactants and local electric potentials, which facilitates the study of electrochemical systems with indefinable bulk.
Kinetics model development of cocoa bean fermentation
Kresnowati, M. T. A. P.; Gunawan, Agus Yodi; Muliyadini, Winny
2015-12-01
Although Indonesia is one of the biggest cocoa beans producers in the world, Indonesian cocoa beans are oftenly of low quality and thereby frequently priced low in the world market. In order to improve the quality, adequate post-harvest cocoa processing techniques are required. Fermentation is the vital stage in series of cocoa beans post harvest processing which could improve the quality of cocoa beans, in particular taste, aroma, and colours. During the fermentation process, combination of microbes grow producing metabolites that serve as the precursors for cocoa beans flavour. Microbial composition and thereby their activities will affect the fermentation performance and influence the properties of cocoa beans. The correlation could be reviewed using a kinetic model that includes unstructured microbial growth, substrate utilization and metabolic product formation. The developed kinetic model could be further used to design cocoa bean fermentation process to meet the expected quality. Further the development of kinetic model of cocoa bean fermentation also serve as a good case study of mixed culture solid state fermentation, that has rarely been studied. This paper presents the development of a kinetic model for solid-state cocoa beans fermentation using an empirical approach. Series of lab scale cocoa bean fermentations, either natural fermentations without starter addition or fermentations with mixed yeast and lactic acid bacteria starter addition, were used for model parameters estimation. The results showed that cocoa beans fermentation can be modelled mathematically and the best model included substrate utilization, microbial growth, metabolites production and its transport. Although the developed model still can not explain the dynamics in microbial population, this model can sufficiently explained the observed changes in sugar concentration as well as metabolic products in the cocoa bean pulp.
Modeling inhomogeneous DNA replication kinetics.
Directory of Open Access Journals (Sweden)
Michel G Gauthier
Full Text Available In eukaryotic organisms, DNA replication is initiated at a series of chromosomal locations called origins, where replication forks are assembled proceeding bidirectionally to replicate the genome. The distribution and firing rate of these origins, in conjunction with the velocity at which forks progress, dictate the program of the replication process. Previous attempts at modeling DNA replication in eukaryotes have focused on cases where the firing rate and the velocity of replication forks are homogeneous, or uniform, across the genome. However, it is now known that there are large variations in origin activity along the genome and variations in fork velocities can also take place. Here, we generalize previous approaches to modeling replication, to allow for arbitrary spatial variation of initiation rates and fork velocities. We derive rate equations for left- and right-moving forks and for replication probability over time that can be solved numerically to obtain the mean-field replication program. This method accurately reproduces the results of DNA replication simulation. We also successfully adapted our approach to the inverse problem of fitting measurements of DNA replication performed on single DNA molecules. Since such measurements are performed on specified portion of the genome, the examined DNA molecules may be replicated by forks that originate either within the studied molecule or outside of it. This problem was solved by using an effective flux of incoming replication forks at the model boundaries to represent the origin activity outside the studied region. Using this approach, we show that reliable inferences can be made about the replication of specific portions of the genome even if the amount of data that can be obtained from single-molecule experiments is generally limited.
A stochastic model of enzyme kinetics
Stefanini, Marianne; Newman, Timothy; McKane, Alan
2003-10-01
Enzyme kinetics is generally modeled by deterministic rate equations, and in the simplest case leads to the well-known Michaelis-Menten equation. It is plausible that stochastic effects will play an important role at low enzyme concentrations. We have addressed this by constructing a simple stochastic model which can be exactly solved in the steady-state. Throughout a wide range of parameter values Michaelis-Menten dynamics is replaced by a new and simple theoretical result.
Compartmental modeling and tracer kinetics
Anderson, David H
1983-01-01
This monograph is concerned with mathematical aspects of compartmental an alysis. In particular, linear models are closely analyzed since they are fully justifiable as an investigative tool in tracer experiments. The objective of the monograph is to bring the reader up to date on some of the current mathematical prob lems of interest in compartmental analysis. This is accomplished by reviewing mathematical developments in the literature, especially over the last 10-15 years, and by presenting some new thoughts and directions for future mathematical research. These notes started as a series of lectures that I gave while visiting with the Division of Applied ~1athematics, Brown University, 1979, and have developed in to this collection of articles aimed at the reader with a beginning graduate level background in mathematics. The text can be used as a self-paced reading course. With this in mind, exercises have been appropriately placed throughout the notes. As an aid in reading the material, the e~d of a ...
MODELING STYRENE HYDROGENATION KINETICS USING PALLADIUM CATALYSTS
Directory of Open Access Journals (Sweden)
G. T. Justino
Full Text Available Abstract The high octane number of pyrolysis gasoline (PYGAS explains its insertion in the gasoline pool. However, its use is troublesome due to the presence of gum-forming chemicals which, in turn, can be removed via hydrogenation. The use of Langmuir-Hinshelwood kinetic models was evaluated for hydrogenation of styrene, a typical gum monomer, using Pd/9%Nb2O5-Al2O3 as catalyst. Kinetic models accounting for hydrogen dissociative and non-dissociative adsorption were considered. The availability of one or two kinds of catalytic sites was analyzed. Experiments were carried out in a semi-batch reactor at constant temperature and pressure in the absence of transport limitations. The conditions used in each experiment varied between 16 - 56 bar and 60 - 100 ºC for pressure and temperature, respectively. The kinetic models were evaluated using MATLAB and EMSO software. Models using adsorption of hydrogen and organic molecules on the same type of site fitted the data best.
A kinetic model for chemical neurotransmission
Ramirez-Santiago, Guillermo; Martinez-Valencia, Alejandro; Fernandez de Miguel, Francisco
Recent experimental observations in presynaptic terminals at the neuromuscular junction indicate that there are stereotyped patterns of cooperativeness in the fusion of adjacent vesicles. That is, a vesicle in hemifusion process appears on the side of a fused vesicle and which is followed by another vesicle in a priming state while the next one is in a docking state. In this talk we present a kinetic model for this morphological pattern in which each vesicle state previous to the exocytosis is represented by a kinetic state. This chain states kinetic model can be analyzed by means of a Master equation whose solution is simulated with the stochastic Gillespie algorithm. With this approach we have reproduced the responses to the basal release in the absence of stimulation evoked by the electrical activity and the phenomena of facilitation and depression of neuromuscular synapses. This model offers new perspectives to understand the underlying phenomena in chemical neurotransmission based on molecular interactions that result in the cooperativity between vesicles during neurotransmitter release. DGAPA Grants IN118410 and IN200914 and Conacyt Grant 130031.
Kinetic modeling in PET imaging of hypoxia
Li, Fan; Joergensen, Jesper T; Hansen, Anders E; Kjaer, Andreas
2014-01-01
Tumor hypoxia is associated with increased therapeutic resistance leading to poor treatment outcome. Therefore the ability to detect and quantify intratumoral oxygenation could play an important role in future individual personalized treatment strategies. Positron Emission Tomography (PET) can be used for non-invasive mapping of tissue oxygenation in vivo and several hypoxia specific PET tracers have been developed. Evaluation of PET data in the clinic is commonly based on visual assessment together with semiquantitative measurements e.g. standard uptake value (SUV). However, dynamic PET contains additional valuable information on the temporal changes in tracer distribution. Kinetic modeling can be used to extract relevant pharmacokinetic parameters of tracer behavior in vivo that reflects relevant physiological processes. In this paper, we review the potential contribution of kinetic analysis for PET imaging of hypoxia. PMID:25250200
Integration of expression data in genome-scale metabolic network reconstructions
Directory of Open Access Journals (Sweden)
Anna S. Blazier
2012-08-01
Full Text Available With the advent of high-throughput technologies, the field of systems biology has amassed an abundance of omics data, quantifying thousands of cellular components across a variety of scales, ranging from mRNA transcript levels to metabolite quantities. Methods are needed to not only integrate this omics data but to also use this data to heighten the predictive capabilities of computational models. Several recent studies have successfully demonstrated how flux balance analysis (FBA, a constraint-based modeling approach, can be used to integrate transcriptomic data into genome-scale metabolic network reconstructions to generate predictive computational models. In this review, we summarize such FBA-based methods for integrating expression data into genome-scale metabolic network reconstructions, highlighting their advantages as well as their limitations.
MATHEMATICAL MODELING OF ORANGE SEED DRYING KINETICS
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Daniele Penteado Rosa
2015-06-01
Full Text Available Drying of orange seeds representing waste products from juice processing was studied in the temperatures of 40, 50, 60 and 70 °C and drying velocities of 0.6, 1.0 and 1.4 m/s. Experimental drying kinetics of orange seeds were obtained using a convective air forced dryer. Three thin-layer models: Page model, Lewis model, and the Henderson-Pabis model and the diffusive model were used to predict the drying curves. The Henderson-Pabis and the diffusive models show the best fitting performance and statistical evaluations. Moreover, the temperature dependence on the effective diffusivity followed an Arrhenius relationship, and the activation energies ranging from 16.174 to 16.842 kJ/mol
Kinetic electron model for plasma thruster plumes
Merino, Mario; Mauriño, Javier; Ahedo, Eduardo
2018-03-01
A paraxial model of an unmagnetized, collisionless plasma plume expanding into vacuum is presented. Electrons are treated kinetically, relying on the adiabatic invariance of their radial action integral for the integration of Vlasov's equation, whereas ions are treated as a cold species. The quasi-2D plasma density, self-consistent electric potential, and electron pressure, temperature, and heat fluxes are analyzed. In particular, the model yields the collisionless cooling of electrons, which differs from the Boltzmann relation and the simple polytropic laws usually employed in fluid and hybrid PIC/fluid plume codes.
Chemical kinetics and modeling of planetary atmospheres
Yung, Yuk L.
1990-01-01
A unified overview is presented for chemical kinetics and chemical modeling in planetary atmospheres. The recent major advances in the understanding of the chemistry of the terrestrial atmosphere make the study of planets more interesting and relevant. A deeper understanding suggests that the important chemical cycles have a universal character that connects the different planets and ultimately link together the origin and evolution of the solar system. The completeness (or incompleteness) of the data base for chemical kinetics in planetary atmospheres will always be judged by comparison with that for the terrestrial atmosphere. In the latter case, the chemistry of H, O, N, and Cl species is well understood. S chemistry is poorly understood. In the atmospheres of Jovian planets and Titan, the C-H chemistry of simple species (containing 2 or less C atoms) is fairly well understood. The chemistry of higher hydrocarbons and the C-N, P-N chemistry is much less understood. In the atmosphere of Venus, the dominant chemistry is that of chlorine and sulfur, and very little is known about C1-S coupled chemistry. A new frontier for chemical kinetics both in the Earth and planetary atmospheres is the study of heterogeneous reactions. The formation of the ozone hole on Earth, the ubiquitous photochemical haze on Venus and in the Jovian planets and Titan all testify to the importance of heterogeneous reactions. It remains a challenge to connect the gas phase chemistry to the production of aerosols.
Kinetic modelling of the Maillard reaction between proteins and sugars
Brands, C.M.J.
2002-01-01
Keywords: Maillard reaction, sugar isomerisation, kinetics, multiresponse modelling, brown colour formation, lysine damage, mutagenicity, casein, monosaccharides, disaccharides, aldoses, ketoses
The aim of this thesis was to determine the kinetics of the Maillard reaction between
Thermodynamically consistent model calibration in chemical kinetics
Directory of Open Access Journals (Sweden)
Goutsias John
2011-05-01
Full Text Available Abstract Background The dynamics of biochemical reaction systems are constrained by the fundamental laws of thermodynamics, which impose well-defined relationships among the reaction rate constants characterizing these systems. Constructing biochemical reaction systems from experimental observations often leads to parameter values that do not satisfy the necessary thermodynamic constraints. This can result in models that are not physically realizable and may lead to inaccurate, or even erroneous, descriptions of cellular function. Results We introduce a thermodynamically consistent model calibration (TCMC method that can be effectively used to provide thermodynamically feasible values for the parameters of an open biochemical reaction system. The proposed method formulates the model calibration problem as a constrained optimization problem that takes thermodynamic constraints (and, if desired, additional non-thermodynamic constraints into account. By calculating thermodynamically feasible values for the kinetic parameters of a well-known model of the EGF/ERK signaling cascade, we demonstrate the qualitative and quantitative significance of imposing thermodynamic constraints on these parameters and the effectiveness of our method for accomplishing this important task. MATLAB software, using the Systems Biology Toolbox 2.1, can be accessed from http://www.cis.jhu.edu/~goutsias/CSS lab/software.html. An SBML file containing the thermodynamically feasible EGF/ERK signaling cascade model can be found in the BioModels database. Conclusions TCMC is a simple and flexible method for obtaining physically plausible values for the kinetic parameters of open biochemical reaction systems. It can be effectively used to recalculate a thermodynamically consistent set of parameter values for existing thermodynamically infeasible biochemical reaction models of cellular function as well as to estimate thermodynamically feasible values for the parameters of new
The Genome-Scale Integrated Networks in Microorganisms
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Tong Hao
2018-02-01
Full Text Available The genome-scale cellular network has become a necessary tool in the systematic analysis of microbes. In a cell, there are several layers (i.e., types of the molecular networks, for example, genome-scale metabolic network (GMN, transcriptional regulatory network (TRN, and signal transduction network (STN. It has been realized that the limitation and inaccuracy of the prediction exist just using only a single-layer network. Therefore, the integrated network constructed based on the networks of the three types attracts more interests. The function of a biological process in living cells is usually performed by the interaction of biological components. Therefore, it is necessary to integrate and analyze all the related components at the systems level for the comprehensively and correctly realizing the physiological function in living organisms. In this review, we discussed three representative genome-scale cellular networks: GMN, TRN, and STN, representing different levels (i.e., metabolism, gene regulation, and cellular signaling of a cell’s activities. Furthermore, we discussed the integration of the networks of the three types. With more understanding on the complexity of microbial cells, the development of integrated network has become an inevitable trend in analyzing genome-scale cellular networks of microorganisms.
Modeling in applied sciences a kinetic theory approach
Pulvirenti, Mario
2000-01-01
Modeling complex biological, chemical, and physical systems, in the context of spatially heterogeneous mediums, is a challenging task for scientists and engineers using traditional methods of analysis Modeling in Applied Sciences is a comprehensive survey of modeling large systems using kinetic equations, and in particular the Boltzmann equation and its generalizations An interdisciplinary group of leading authorities carefully develop the foundations of kinetic models and discuss the connections and interactions between model theories, qualitative and computational analysis and real-world applications This book provides a thoroughly accessible and lucid overview of the different aspects, models, computations, and methodology for the kinetic-theory modeling process Topics and Features * Integrated modeling perspective utilized in all chapters * Fluid dynamics of reacting gases * Self-contained introduction to kinetic models * Becker–Doring equations * Nonlinear kinetic models with chemical reactions * Kinet...
Enumeration of smallest intervention strategies in genome-scale metabolic networks.
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Axel von Kamp
2014-01-01
Full Text Available One ultimate goal of metabolic network modeling is the rational redesign of biochemical networks to optimize the production of certain compounds by cellular systems. Although several constraint-based optimization techniques have been developed for this purpose, methods for systematic enumeration of intervention strategies in genome-scale metabolic networks are still lacking. In principle, Minimal Cut Sets (MCSs; inclusion-minimal combinations of reaction or gene deletions that lead to the fulfilment of a given intervention goal provide an exhaustive enumeration approach. However, their disadvantage is the combinatorial explosion in larger networks and the requirement to compute first the elementary modes (EMs which itself is impractical in genome-scale networks. We present MCSEnumerator, a new method for effective enumeration of the smallest MCSs (with fewest interventions in genome-scale metabolic network models. For this we combine two approaches, namely (i the mapping of MCSs to EMs in a dual network, and (ii a modified algorithm by which shortest EMs can be effectively determined in large networks. In this way, we can identify the smallest MCSs by calculating the shortest EMs in the dual network. Realistic application examples demonstrate that our algorithm is able to list thousands of the most efficient intervention strategies in genome-scale networks for various intervention problems. For instance, for the first time we could enumerate all synthetic lethals in E.coli with combinations of up to 5 reactions. We also applied the new algorithm exemplarily to compute strain designs for growth-coupled synthesis of different products (ethanol, fumarate, serine by E.coli. We found numerous new engineering strategies partially requiring less knockouts and guaranteeing higher product yields (even without the assumption of optimal growth than reported previously. The strength of the presented approach is that smallest intervention strategies can be
Genome scale metabolic network reconstruction of Spirochaeta cellobiosiphila
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Bharat Manna
2017-10-01
Full Text Available Substantial rise in the global energy demand is one of the biggest challenges in this century. Environmental pollution due to rapid depletion of the fossil fuel resources and its alarming impact on the climate change and Global Warming have motivated researchers to look for non-petroleum-based sustainable, eco-friendly, renewable, low-cost energy alternatives, such as biofuel. Lignocellulosic biomass is one of the most promising bio-resources with huge potential to contribute to this worldwide energy demand. However, the complex organization of the Cellulose, Hemicellulose and Lignin in the Lignocellulosic biomass requires extensive pre-treatment and enzymatic hydrolysis followed by fermentation, raising overall production cost of biofuel. This encourages researchers to design cost-effective approaches for the production of second generation biofuels. The products from enzymatic hydrolysis of cellulose are mostly glucose monomer or cellobiose unit that are subjected to fermentation. Spirochaeta genus is a well-known group of obligate or facultative anaerobes, living primarily on carbohydrate metabolism. Spirochaeta cellobiosiphila sp. is a facultative anaerobe under this genus, which uses a variety of monosaccharides and disaccharides as energy sources. However, most rapid growth occurs on cellobiose and fermentation yields significant amount of ethanol, acetate, CO2, H2 and small amounts of formate. It is predicted to be promising microbial machinery for industrial fermentation processes for biofuel production. The metabolic pathways that govern cellobiose metabolism in Spirochaeta cellobiosiphila are yet to be explored. The function annotation of the genome sequence of Spirochaeta cellobiosiphila is in progress. In this work we aim to map all the metabolic activities for reconstruction of genome-scale metabolic model of Spirochaeta cellobiosiphila.
Optimal knockout strategies in genome-scale metabolic networks using particle swarm optimization.
Nair, Govind; Jungreuthmayer, Christian; Zanghellini, Jürgen
2017-02-01
Knockout strategies, particularly the concept of constrained minimal cut sets (cMCSs), are an important part of the arsenal of tools used in manipulating metabolic networks. Given a specific design, cMCSs can be calculated even in genome-scale networks. We would however like to find not only the optimal intervention strategy for a given design but the best possible design too. Our solution (PSOMCS) is to use particle swarm optimization (PSO) along with the direct calculation of cMCSs from the stoichiometric matrix to obtain optimal designs satisfying multiple objectives. To illustrate the working of PSOMCS, we apply it to a toy network. Next we show its superiority by comparing its performance against other comparable methods on a medium sized E. coli core metabolic network. PSOMCS not only finds solutions comparable to previously published results but also it is orders of magnitude faster. Finally, we use PSOMCS to predict knockouts satisfying multiple objectives in a genome-scale metabolic model of E. coli and compare it with OptKnock and RobustKnock. PSOMCS finds competitive knockout strategies and designs compared to other current methods and is in some cases significantly faster. It can be used in identifying knockouts which will force optimal desired behaviors in large and genome scale metabolic networks. It will be even more useful as larger metabolic models of industrially relevant organisms become available.
Acceleration transforms and statistical kinetic models
International Nuclear Information System (INIS)
LuValle, M.J.; Welsher, T.L.; Svoboda, K.
1988-01-01
For a restricted class of problems a mathematical model of microscopic degradation processes, statistical kinetics, is developed and linked through acceleration transforms to the information which can be obtained from a system in which the only observable sign of degradation is sudden and catastrophic failure. The acceleration transforms were developed in accelerated life testing applications as a tool for extrapolating from the observable results of an accelerated life test to the dynamics of the underlying degradation processes. A particular concern of a physicist attempting to interpreted the results of an analysis based on acceleration transforms is determining the physical species involved in the degradation process. These species may be (a) relatively abundant or (b) relatively rare. The main results of this paper are a theorem showing that for an important subclass of statistical kinetic models, acceleration transforms cannot be used to distinguish between cases a and b, and an example showing that in some cases falling outside the restrictions of the theorem, cases a and b can be distinguished by their acceleration transforms
MODELLING OF KINETICS OF FLUORINE ADSORPTION ONTO MODIFIED DIATOMITE
Directory of Open Access Journals (Sweden)
VEACESLAV ZELENTSOV
2017-03-01
Full Text Available The paper presents kinetics modelling of adsorption of fluorine onto modified diatomite, its fundamental characteristics and mathematical derivations. Three models of defluoridation kinetics were used to fit the experimental results on adsorption fluorine onto diatomite: the pseudo-first order model Lagergren, the pseudo-second order model G. McKay and H.S. Ho and intraparticle diffusion model of W.J. Weber and J.C. Morris. Kinetics studies revealed that the adsorption of fluorine followed second-order rate model, complimented by intraparticle diffusion kinetics. The adsorption mechanism of fluorine involved three stages – external surface adsorption, intraparticle diffusion and the stage of equilibrium.
Holographic kinetic k-essence model
Energy Technology Data Exchange (ETDEWEB)
Cruz, Norman [Departamento de Fisica, Facultad de Ciencia, Universidad de Santiago de Chile, Casilla 307, Santiago (Chile)], E-mail: ncruz@lauca.usach.cl; Gonzalez-Diaz, Pedro F.; Rozas-Fernandez, Alberto [Colina de los Chopos, Instituto de Fisica Fundamental, Consejo Superior de Investigaciones Cientificas, Serrano 121, 28006 Madrid (Spain)], E-mail: a.rozas@cfmac.csic.es; Sanchez, Guillermo [Departamento de Matematica y Ciencia de la Computacion, Facultad de Ciencia, Universidad de Santiago de Chile, Casilla 307, Santiago (Chile)], E-mail: gsanchez@usach.cl
2009-08-31
We consider a connection between the holographic dark energy density and the kinetic k-essence energy density in a flat FRW universe. With the choice c{>=}1, the holographic dark energy can be described by a kinetic k-essence scalar field in a certain way. In this Letter we show this kinetic k-essential description of the holographic dark energy with c{>=}1 and reconstruct the kinetic k-essence function F(X)
Kinetic depletion model for pellet ablation
International Nuclear Information System (INIS)
Kuteev, Boris V.
2001-11-01
A kinetic model for depletion effect, which determines pellet ablation when the pellet passes a rational magnetic surface, is formulated. The model predicts a moderate decrease of the ablation rate compared with the earlier considered monoenergy versions [1, 2]. For typical T-10 conditions the ablation rate reduces by a reactor of 2.5 when the 1-mm pellet penetrates through the plasma center. A substantial deceleration of pellets -about 15% per centimeter of low shire rational q region; is predicted. Penetration for Low Field Side and High Field Side injections is considered taking into account modification of the electron distribution function by toroidal magnetic field. It is shown that Shafranov shift and toroidal effects yield the penetration length for HFS injection higher by a factor of 1.5. This fact should be taken into account when plasma-shielding effects on penetration are considered. (author)
Chockalingam, Sriram; Aluru, Maneesha; Aluru, Srinivas
2016-09-19
Pre-processing of microarray data is a well-studied problem. Furthermore, all popular platforms come with their own recommended best practices for differential analysis of genes. However, for genome-scale network inference using microarray data collected from large public repositories, these methods filter out a considerable number of genes. This is primarily due to the effects of aggregating a diverse array of experiments with different technical and biological scenarios. Here we introduce a pre-processing pipeline suitable for inferring genome-scale gene networks from large microarray datasets. We show that partitioning of the available microarray datasets according to biological relevance into tissue- and process-specific categories significantly extends the limits of downstream network construction. We demonstrate the effectiveness of our pre-processing pipeline by inferring genome-scale networks for the model plant Arabidopsis thaliana using two different construction methods and a collection of 11,760 Affymetrix ATH1 microarray chips. Our pre-processing pipeline and the datasets used in this paper are made available at http://alurulab.cc.gatech.edu/microarray-pp.
Kinetic model of excess activated sludge thermohydrolysis.
Imbierowicz, Mirosław; Chacuk, Andrzej
2012-11-01
Thermal hydrolysis of excess activated sludge suspensions was carried at temperatures ranging from 423 K to 523 K and under pressure 0.2-4.0 MPa. Changes of total organic carbon (TOC) concentration in a solid and liquid phase were measured during these studies. At the temperature 423 K, after 2 h of the process, TOC concentration in the reaction mixture decreased by 15-18% of the initial value. At 473 K total organic carbon removal from activated sludge suspension increased to 30%. It was also found that the solubilisation of particulate organic matter strongly depended on the process temperature. At 423 K the transfer of TOC from solid particles into liquid phase after 1 h of the process reached 25% of the initial value, however, at the temperature of 523 K the conversion degree of 'solid' TOC attained 50% just after 15 min of the process. In the article a lumped kinetic model of the process of activated sludge thermohydrolysis has been proposed. It was assumed that during heating of the activated sludge suspension to a temperature in the range of 423-523 K two parallel reactions occurred. One, connected with thermal destruction of activated sludge particles, caused solubilisation of organic carbon and an increase of dissolved organic carbon concentration in the liquid phase (hydrolysate). The parallel reaction led to a new kind of unsolvable solid phase, which was further decomposed into gaseous products (CO(2)). The collected experimental data were used to identify unknown parameters of the model, i.e. activation energies and pre-exponential factors of elementary reactions. The mathematical model of activated sludge thermohydrolysis appropriately describes the kinetics of reactions occurring in the studied system. Copyright © 2012 Elsevier Ltd. All rights reserved.
Ren, Xiu'e; Chen, Jianbiao; Li, Gang; Wang, Yanhong; Lang, Xuemei; Fan, Shuanshi
2018-08-01
The study concerned the thermal oxidative degradation kinetics of agricultural residues, peanut shell (PS) and sunflower shell (SS). The thermal behaviors were evaluated via thermogravimetric analysis and the kinetic parameters were determined by using distributed activation energy model (DAEM) and global kinetic model (GKM). Results showed that thermal oxidative decomposition of two samples processed in three zones; the ignition, burnout, and comprehensive combustibility between two agricultural residues were of great difference; and the combustion performance could be improved by boosting heating rate. The activation energy ranges calculated by the DAEM for the thermal oxidative degradation of PS and SS were 88.94-145.30 kJ mol -1 and 94.86-169.18 kJ mol -1 , respectively. The activation energy obtained by the GKM for the oxidative decomposition of hemicellulose and cellulose was obviously lower than that for the lignin oxidation at identical heating rate. To some degree, the determined kinetic parameters could acceptably simulate experimental data. Copyright © 2018 Elsevier Ltd. All rights reserved.
A discontinuous Galerkin method on kinetic flocking models
Tan, Changhui
2014-01-01
We study kinetic representations of flocking models. They arise from agent-based models for self-organized dynamics, such as Cucker-Smale and Motsch-Tadmor models. We prove flocking behavior for the kinetic descriptions of flocking systems, which indicates a concentration in velocity variable in infinite time. We propose a discontinuous Galerkin method to treat the asymptotic $\\delta$-singularity, and construct high order positive preserving scheme to solve kinetic flocking systems.
Maldonado, Elaina M; Leoncikas, Vytautas; Fisher, Ciarán P; Moore, J Bernadette; Plant, Nick J; Kierzek, Andrzej M
2017-11-01
The scope of physiologically based pharmacokinetic (PBPK) modeling can be expanded by assimilation of the mechanistic models of intracellular processes from systems biology field. The genome scale metabolic networks (GSMNs) represent a whole set of metabolic enzymes expressed in human tissues. Dynamic models of the gene regulation of key drug metabolism enzymes are available. Here, we introduce GSMNs and review ongoing work on integration of PBPK, GSMNs, and metabolic gene regulation. We demonstrate example models. © 2017 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics.
Thermoluminescence of zircon: a kinetic model
Turkin, A A; Vainshtein, D I; Hartog, H W D
2003-01-01
The mineral zircon, ZrSiO sub 4 , belongs to a class of promising materials for geochronometry by means of thermoluminescence (TL) dating. The development of a reliable and reproducible method for TL dating with zircon requires detailed knowledge of the processes taking place during exposure to ionizing radiation, long-term storage, annealing at moderate temperatures and heating at a constant rate (TL measurements). To understand these processes one needs a kinetic model of TL. This paper is devoted to the construction of such a model. The goal is to study the qualitative behaviour of the system and to determine the parameters and processes controlling TL phenomena of zircon. The model considers the following processes: (i) Filling of electron and hole traps at the excitation stage as a function of the dose rate and the dose for both (low dose rate) natural and (high dose rate) laboratory irradiation. (ii) Time dependence of TL fading in samples irradiated under laboratory conditions. (iii) Short time anneali...
Reflected kinetics model for nuclear space reactor kinetics and control scoping calculations
Energy Technology Data Exchange (ETDEWEB)
Washington, K.E.
1986-05-01
The objective of this research is to develop a model that offers an alternative to the point kinetics (PK) modelling approach in the analysis of space reactor kinetics and control studies. Modelling effort will focus on the explicit treatment of control drums as reactivity input devices so that the transition to automatic control can be smoothly done. The proposed model is developed for the specific integration of automatic control and the solution of the servo mechanism problem. The integration of the kinetics model with an automatic controller will provide a useful tool for performing space reactor scoping studies for different designs and configurations. Such a tool should prove to be invaluable in the design phase of a space nuclear system from the point of view of kinetics and control limitations.
Reflected kinetics model for nuclear space reactor kinetics and control scoping calculations
International Nuclear Information System (INIS)
Washington, K.E.
1986-05-01
The objective of this research is to develop a model that offers an alternative to the point kinetics (PK) modelling approach in the analysis of space reactor kinetics and control studies. Modelling effort will focus on the explicit treatment of control drums as reactivity input devices so that the transition to automatic control can be smoothly done. The proposed model is developed for the specific integration of automatic control and the solution of the servo mechanism problem. The integration of the kinetics model with an automatic controller will provide a useful tool for performing space reactor scoping studies for different designs and configurations. Such a tool should prove to be invaluable in the design phase of a space nuclear system from the point of view of kinetics and control limitations
Supercritical kinetic analysis in simplified system of fuel debris using integral kinetic model
International Nuclear Information System (INIS)
Tuya, Delgersaikhan; Obara, Toru
2016-01-01
Highlights: • Kinetic analysis in simplified weakly coupled fuel debris system was performed. • The integral kinetic model was used to simulate criticality accidents. • The fission power and released energy during simulated accident were obtained. • Coupling between debris regions and its effect on the fission power was obtained. - Abstract: Preliminary prompt supercritical kinetic analyses in a simplified coupled system of fuel debris designed to roughly resemble a melted core of a nuclear reactor were performed using an integral kinetic model. The integral kinetic model, which can describe region- and time-dependent fission rate in a coupled system of arbitrary geometry, was used because the fuel debris system is weakly coupled in terms of neutronics. The results revealed some important characteristics of coupled systems, such as the coupling between debris regions and the effect of the coupling on the fission rate and released energy in each debris region during the simulated criticality accident. In brief, this study showed that the integral kinetic model can be applied to supercritical kinetic analysis in fuel debris systems and also that it can be a useful tool for investigating the effect of the coupling on consequences of a supercritical accident.
Fully implicit kinetic modelling of collisional plasmas
International Nuclear Information System (INIS)
Mousseau, V.A.
1996-05-01
This dissertation describes a numerical technique, Matrix-Free Newton Krylov, for solving a simplified Vlasov-Fokker-Planck equation. This method is both deterministic and fully implicit, and may not have been a viable option before current developments in numerical methods. Results are presented that indicate the efficiency of the Matrix-Free Newton Krylov method for these fully-coupled, nonlinear integro-differential equations. The use and requirement for advanced differencing is also shown. To this end, implementations of Chang-Cooper differencing and flux limited Quadratic Upstream Interpolation for Convective Kinematics (QUICK) are presented. Results are given for a fully kinetic ion-electron problem with a self consistent electric field calculated from the ion and electron distribution functions. This numerical method, including advanced differencing, provides accurate solutions, which quickly converge on workstation class machines. It is demonstrated that efficient steady-state solutions can be achieved to the non-linear integro-differential equation, obtaining quadratic convergence, without incurring the large memory requirements of an integral operator. Model problems are presented which simulate plasma impinging on a plate with both high and low neutral particle recycling typical of a divertor in a Tokamak device. These model problems demonstrate the performance of the new solution method
Kinetic modeling of cell metabolism for microbial production.
Costa, Rafael S; Hartmann, Andras; Vinga, Susana
2016-02-10
Kinetic models of cellular metabolism are important tools for the rational design of metabolic engineering strategies and to explain properties of complex biological systems. The recent developments in high-throughput experimental data are leading to new computational approaches for building kinetic models of metabolism. Herein, we briefly survey the available databases, standards and software tools that can be applied for kinetic models of metabolism. In addition, we give an overview about recently developed ordinary differential equations (ODE)-based kinetic models of metabolism and some of the main applications of such models are illustrated in guiding metabolic engineering design. Finally, we review the kinetic modeling approaches of large-scale networks that are emerging, discussing their main advantages, challenges and limitations. Copyright © 2015 Elsevier B.V. All rights reserved.
Kinetic modeling in pre-clinical positron emission tomography
Energy Technology Data Exchange (ETDEWEB)
Kuntner, Claudia [AIT Austrian Institute of Technology GmbH, Seibersdorf (Austria). Biomedical Systems, Health and Environment Dept.
2014-07-01
Pre-clinical positron emission tomography (PET) has evolved in the last few years from pure visualization of radiotracer uptake and distribution towards quantification of the physiological parameters. For reliable and reproducible quantification the kinetic modeling methods used to obtain relevant parameters of radiotracer tissue interaction are important. Here we present different kinetic modeling techniques with a focus on compartmental models including plasma input models and reference tissue input models. The experimental challenges of deriving the plasma input function in rodents and the effect of anesthesia are discussed. Finally, in vivo application of kinetic modeling in various areas of pre-clinical research is presented and compared to human data.
Kinetic models of cell growth, substrate utilization and bio ...
African Journals Online (AJOL)
Bio-decolorization kinetic studies of distillery effluent in a batch culture were conducted using Aspergillus fumigatus. A simple model was proposed using the Logistic Equation for the growth, Leudeking-Piret kinetics for bio-decolorization, and also for substrate utilization. The proposed models appeared to provide a suitable ...
Genome-scale reconstruction of metabolic networks of Lactobacillus casei ATCC 334 and 12A.
Directory of Open Access Journals (Sweden)
Elena Vinay-Lara
Full Text Available Lactobacillus casei strains are widely used in industry and the utility of this organism in these industrial applications is strain dependent. Hence, tools capable of predicting strain specific phenotypes would have utility in the selection of strains for specific industrial processes. Genome-scale metabolic models can be utilized to better understand genotype-phenotype relationships and to compare different organisms. To assist in the selection and development of strains with enhanced industrial utility, genome-scale models for L. casei ATCC 334, a well characterized strain, and strain 12A, a corn silage isolate, were constructed. Draft models were generated from RAST genome annotations using the Model SEED database and refined by evaluating ATP generating cycles, mass-and-charge-balances of reactions, and growth phenotypes. After the validation process was finished, we compared the metabolic networks of these two strains to identify metabolic, genetic and ortholog differences that may lead to different phenotypic behaviors. We conclude that the metabolic capabilities of the two networks are highly similar. The L. casei ATCC 334 model accounts for 1,040 reactions, 959 metabolites and 548 genes, while the L. casei 12A model accounts for 1,076 reactions, 979 metabolites and 640 genes. The developed L. casei ATCC 334 and 12A metabolic models will enable better understanding of the physiology of these organisms and be valuable tools in the development and selection of strains with enhanced utility in a variety of industrial applications.
Performance of neutron kinetics models for ADS transient analyses
International Nuclear Information System (INIS)
Rineiski, A.; Maschek, W.; Rimpault, G.
2002-01-01
Within the framework of the SIMMER code development, neutron kinetics models for simulating transients and hypothetical accidents in advanced reactor systems, in particular in Accelerator Driven Systems (ADSs), have been developed at FZK/IKET in cooperation with CE Cadarache. SIMMER is a fluid-dynamics/thermal-hydraulics code, coupled with a structure model and a space-, time- and energy-dependent neutronics module for analyzing transients and accidents. The advanced kinetics models have also been implemented into KIN3D, a module of the VARIANT/TGV code (stand-alone neutron kinetics) for broadening application and for testing and benchmarking. In the paper, a short review of the SIMMER and KIN3D neutron kinetics models is given. Some typical transients related to ADS perturbations are analyzed. The general models of SIMMER and KIN3D are compared with more simple techniques developed in the context of this work to get a better understanding of the specifics of transients in subcritical systems and to estimate the performance of different kinetics options. These comparisons may also help in elaborating new kinetics models and extending existing computation tools for ADS transient analyses. The traditional point-kinetics model may give rather inaccurate transient reaction rate distributions in an ADS even if the material configuration does not change significantly. This inaccuracy is not related to the problem of choosing a 'right' weighting function: the point-kinetics model with any weighting function cannot take into account pronounced flux shape variations related to possible significant changes in the criticality level or to fast beam trips. To improve the accuracy of the point-kinetics option for slow transients, we have introduced a correction factor technique. The related analyses give a better understanding of 'long-timescale' kinetics phenomena in the subcritical domain and help to evaluate the performance of the quasi-static scheme in a particular case. One
Bayesian inference of chemical kinetic models from proposed reactions
Galagali, Nikhil; Marzouk, Youssef M.
2015-01-01
© 2014 Elsevier Ltd. Bayesian inference provides a natural framework for combining experimental data with prior knowledge to develop chemical kinetic models and quantify the associated uncertainties, not only in parameter values but also in model
A kinetic model for the penicillin biosynthetic pathway in
DEFF Research Database (Denmark)
Nielsen, Jens; Jørgensen, Henrik
1996-01-01
A kinetic model for the first two steps in the penicillin biosynthetic pathway, i.e. the ACV synthetase (ACVS) and the isopenicillin N synthetase (IPNS) is proposed. The model is based on Michaelis-Menten type kinetics with non-competitive inhibition of the ACVS by ACV, and competitive inhibition...... of the IPNS by glutathione. The model predicted flux through the pathway corresponds well with the measured rate of penicillin biosynthesis. From the kinetic model the elasticity coefficients and the flux control coefficients are calculated throughout a fed-batch cultivation, and it is found...
Kinetics and hybrid kinetic-fluid models for nonequilibrium gas and plasmas
International Nuclear Information System (INIS)
Crouseilles, N.
2004-12-01
For a few decades, the application of the physics of plasmas has appeared in different fields like laser-matter interaction, astrophysics or thermonuclear fusion. In this thesis, we are interested in the modeling and the numerical study of nonequilibrium gas and plasmas. To describe such systems, two ways are usually used: the fluid description and the kinetic description. When we study a nonequilibrium system, fluid models are not sufficient and a kinetic description have to be used. However, solving a kinetic model requires the discretization of a large number of variables, which is quite expensive from a numerical point of view. The aim of this work is to propose a hybrid kinetic-fluid model thanks to a domain decomposition method in the velocity space. The derivation of the hybrid model is done in two different contexts: the rarefied gas context and the more complicated plasmas context. The derivation partly relies on Levermore's entropy minimization approach. The so-obtained model is then discretized and validated on various numerical test cases. In a second stage, a numerical study of a fully kinetic model is presented. A collisional plasma constituted of electrons and ions is considered through the Vlasov-Poisson-Fokker-Planck-Landau equation. Then, a numerical scheme which preserves total mass and total energy is presented. This discretization permits in particular a numerical study of the Landau damping. (author)
A balance principle approach for modeling phase transformation kinetics
International Nuclear Information System (INIS)
Lusk, M.; Krauss, G.; Jou, H.J.
1995-01-01
A balance principle is offered to model volume fraction kinetics of phase transformation kinetics at a continuum level. This microbalance provides a differential equation for transformation kinetics which is coupled to the differential equations governing the mechanical and thermal aspects of the process. Application here is restricted to diffusive transformations for the sake of clarity, although the principle is discussed for martensitic phase transitions as well. Avrami-type kinetics are shown to result from a special class of energy functions. An illustrative example using a 0.5% C Chromium steel demonstrates how TTT and CCT curves can be generated using a particularly simple effective energy function. (orig.)
Kinetic models in spin chemistry. 1. The hyperfine interaction
DEFF Research Database (Denmark)
Mojaza, M.; Pedersen, J. B.
2012-01-01
Kinetic models for quantum systems are quite popular due to their simplicity, although they are difficult to justify. We show that the transformation from quantum to kinetic description can be done exactly for the hyperfine interaction of one nuclei with arbitrary spin; more spins are described w...... induced enhancement of the reaction yield. (C) 2012 Elsevier B.V. All rights reserved....
One-dimensional reactor kinetics model for RETRAN
International Nuclear Information System (INIS)
Gose, G.C.; Peterson, C.E.; Ellis, N.L.; McClure, J.A.
1981-01-01
This paper describes a one-dimensional spatial neutron kinetics model that was developed for the RETRAN code. The RETRAN -01 code has a point kinetics model to describe the reactor core behavior during thermal-hydraulic transients. A one-dimensional neutronics model has been developed for RETRAN-02. The ability to account for flux shape changes will permit an improved representation of the thermal and hydraulic feedback effects for many operational transients. 19 refs
Lumping procedure for a kinetic model of catalytic naphtha reforming
Directory of Open Access Journals (Sweden)
H. M. Arani
2009-12-01
Full Text Available A lumping procedure is developed for obtaining kinetic and thermodynamic parameters of catalytic naphtha reforming. All kinetic and deactivation parameters are estimated from industrial data and thermodynamic parameters are calculated from derived mathematical expressions. The proposed model contains 17 lumps that include the C6 to C8+ hydrocarbon range and 15 reaction pathways. Hougen-Watson Langmuir-Hinshelwood type reaction rate expressions are used for kinetic simulation of catalytic reactions. The kinetic parameters are benchmarked with several sets of plant data and estimated by the SQP optimization method. After calculation of deactivation and kinetic parameters, plant data are compared with model predictions and only minor deviations between experimental and calculated data are generally observed.
COMPARATIVE ANALYSIS OF SOME EXISTING KINETIC MODELS ...
African Journals Online (AJOL)
The biosorption of three heavy metal ions namely; Zn2+, Cu2+ and Mn2+ using five microorganisms namely; Bacillus circulans, Pseudomonas aeruginosa, Staphylococcus xylosus, Streptomyces rimosus and Yeast (Saccharomyces sp.) were studied. In this paper, the effectiveness of six existing and two proposed kinetic ...
A critical look at the kinetic models of thermoluminescence-II. Non-first order kinetics
International Nuclear Information System (INIS)
Sunta, C M; Ayta, W E F; Chubaci, J F D; Watanabe, S
2005-01-01
Non-first order (FO) kinetics models are of three types; second order (SO), general order (GO) and mixed order (MO). It is shown that all three of these have constraints in their energy level schemes and their applicable parameter values. In nature such restrictions are not expected to exist. The thermoluminescence (TL) glow peaks produced by these models shift their position and change their shape as the trap occupancies change. Such characteristics are very unlike those found in samples of real materials. In these models, in general, retrapping predominates over recombination. It is shown that the quasi-equilibrium (QE) assumption implied in the derivation of the TL equation of these models is quite valid, thus disproving earlier workers' conclusion that QE cannot be held under retrapping dominant conditions. However notwithstanding their validity, they suffer from the shortcomings as stated above and have certain lacunae. For example, the kinetic order (KO) parameter and the pre-exponential factor which are assumed to be the constant parameters of the GO kinetics expression turn out to be variables when this expression is applied to plausible physical models. Further, in glow peak characterization using the GO expression, the quality of fit is found to deteriorate when the best fitted value of KO parameter is different from 1 and 2. This means that the found value of the basic parameter, namely the activation energy, becomes subject to error. In the MO kinetics model, the value of the KO parameter α would change with dose, and thus in this model also, as in the GO model, no single value of KO can be assigned to a given glow peak. The paper discusses TL of real materials having characteristics typically like those of FO kinetics. Theoretically too, a plausible physical model of TL emission produces glow peaks which have characteristics of FO kinetics under a wide variety of parametric combinations. In the background of the above findings, it is suggested that
comparative analysis of some existing kinetic models with proposed
African Journals Online (AJOL)
IGNATIUS NWIDI
two statistical parameters namely; linear regression coefficient of correlation (R2) and ... Keynotes: Heavy metals, Biosorption, Kinetics Models, Comparative analysis, Average Relative Error. 1. ... If the flow rate is low, a simple manual batch.
Improved Kinetic Models for High-Speed Combustion Simulation
National Research Council Canada - National Science Library
Montgomery, C. J; Tang, Q; Sarofim, A. F; Bockelie, M. J; Gritton, J. K; Bozzelli, J. W; Gouldin, F. C; Fisher, E. M; Chakravarthy, S
2008-01-01
Report developed under an STTR contract. The overall goal of this STTR project has been to improve the realism of chemical kinetics in computational fluid dynamics modeling of hydrocarbon-fueled scramjet combustors...
Physical characterization and kinetic modelling of matrix tablets of ...
African Journals Online (AJOL)
release mechanisms were characterized by kinetic modeling. Analytical ... findings demonstrate that both the desired physical characteristics and drug release profiles were obtained ..... on the compression, mechanical, and release properties.
Study of growth kinetic and modeling of ethanol production by ...
African Journals Online (AJOL)
... coefficient (0.96299). Based on Leudking-Piret model, it could be concluded that ethanol batch fermentation is a non-growth associated process. Key words: Kinetic parameters, simulation, cell growth, ethanol, Saccharomyces cerevisiae.
Analysis of a kinetic multi-segment foot model part II: kinetics and clinical implications.
Bruening, Dustin A; Cooney, Kevin M; Buczek, Frank L
2012-04-01
Kinematic multi-segment foot models have seen increased use in clinical and research settings, but the addition of kinetics has been limited and hampered by measurement limitations and modeling assumptions. In this second of two companion papers, we complete the presentation and analysis of a three segment kinetic foot model by incorporating kinetic parameters and calculating joint moments and powers. The model was tested on 17 pediatric subjects (ages 7-18 years) during normal gait. Ground reaction forces were measured using two adjacent force platforms, requiring targeted walking and the creation of two sub-models to analyze ankle, midtarsal, and 1st metatarsophalangeal joints. Targeted walking resulted in only minimal kinematic and kinetic differences compared with walking at self selected speeds. Joint moments and powers were calculated and ensemble averages are presented as a normative database for comparison purposes. Ankle joint powers are shown to be overestimated when using a traditional single-segment foot model, as substantial angular velocities are attributed to the mid-tarsal joint. Power transfer is apparent between the 1st metatarsophalangeal and mid-tarsal joints in terminal stance/pre-swing. While the measurement approach presented here is limited to clinical populations with only minimal impairments, some elements of the model can also be incorporated into routine clinical gait analysis. Copyright © 2011 Elsevier B.V. All rights reserved.
Molecular Dynamics Simulations of Kinetic Models for Chiral Dominance in Soft Condensed Matter
DEFF Research Database (Denmark)
Toxvaerd, Søren
2001-01-01
Molecular dynamics simulation, models for isomerization kinetics, origin of biomolecular chirality......Molecular dynamics simulation, models for isomerization kinetics, origin of biomolecular chirality...
A mixed-integer linear programming approach to the reduction of genome-scale metabolic networks.
Röhl, Annika; Bockmayr, Alexander
2017-01-03
Constraint-based analysis has become a widely used method to study metabolic networks. While some of the associated algorithms can be applied to genome-scale network reconstructions with several thousands of reactions, others are limited to small or medium-sized models. In 2015, Erdrich et al. introduced a method called NetworkReducer, which reduces large metabolic networks to smaller subnetworks, while preserving a set of biological requirements that can be specified by the user. Already in 2001, Burgard et al. developed a mixed-integer linear programming (MILP) approach for computing minimal reaction sets under a given growth requirement. Here we present an MILP approach for computing minimum subnetworks with the given properties. The minimality (with respect to the number of active reactions) is not guaranteed by NetworkReducer, while the method by Burgard et al. does not allow specifying the different biological requirements. Our procedure is about 5-10 times faster than NetworkReducer and can enumerate all minimum subnetworks in case there exist several ones. This allows identifying common reactions that are present in all subnetworks, and reactions appearing in alternative pathways. Applying complex analysis methods to genome-scale metabolic networks is often not possible in practice. Thus it may become necessary to reduce the size of the network while keeping important functionalities. We propose a MILP solution to this problem. Compared to previous work, our approach is more efficient and allows computing not only one, but even all minimum subnetworks satisfying the required properties.
Directory of Open Access Journals (Sweden)
Krivtcova Nadezhda
2016-01-01
Full Text Available Modelling of sulfur compounds kinetics was performed, including kinetics of benzothiophene and dibenzothiophene homologues. Modelling is based on experimental data obtained from monitoring of industrial hydrotreating set. Obtained results include kinetic parameters of reactions.
Krivtsova, Nadezhda Igorevna; Tataurshikov, A.; Kotkova, Elena
2016-01-01
Modelling of sulfur compounds kinetics was performed, including kinetics of benzothiophene and dibenzothiophene homologues. Modelling is based on experimental data obtained from monitoring of industrial hydrotreating set. Obtained results include kinetic parameters of reactions.
Wang, Zhandong; Zhao, Long; Wang, Yu; Bian, Huiting; Zhang, Lidong; Zhang, Feng; Li, Yuyang; Sarathy, Mani; Qi, Fei
2015-01-01
species were evaluated, and good agreement was observed between the PIMS and GC data sets. Furthermore, a fuel-rich burner-stabilized laminar premixed ECH/O2/Ar flame at 30Torr was studied using synchrotron VUV PIMS. A detailed kinetic model for ECH high
Detailed Chemical Kinetic Modeling of Hydrazine Decomposition
Meagher, Nancy E.; Bates, Kami R.
2000-01-01
The purpose of this research project is to develop and validate a detailed chemical kinetic mechanism for gas-phase hydrazine decomposition. Hydrazine is used extensively in aerospace propulsion, and although liquid hydrazine is not considered detonable, many fuel handling systems create multiphase mixtures of fuels and fuel vapors during their operation. Therefore, a thorough knowledge of the decomposition chemistry of hydrazine under a variety of conditions can be of value in assessing potential operational hazards in hydrazine fuel systems. To gain such knowledge, a reasonable starting point is the development and validation of a detailed chemical kinetic mechanism for gas-phase hydrazine decomposition. A reasonably complete mechanism was published in 1996, however, many of the elementary steps included had outdated rate expressions and a thorough investigation of the behavior of the mechanism under a variety of conditions was not presented. The current work has included substantial revision of the previously published mechanism, along with a more extensive examination of the decomposition behavior of hydrazine. An attempt to validate the mechanism against the limited experimental data available has been made and was moderately successful. Further computational and experimental research into the chemistry of this fuel needs to be completed.
A new mathematical model for coal flotation kinetics
Guerrero-Pérez, Juan Sebastián; Barraza-Burgos, Juan Manuel
2017-01-01
Abstract This study describes the development and formulation of a novel mathematical model for coal flotation kinetic. The flotation rate was considered as a function of chemical, operating and petrographic parameters for a global flotation order n. The equation for flotation rate was obtained by dimensional analysis using the Rayleigh method. It shows the dependency of flotation kinetic on operating parameters, such as air velocity and particle size; chemical parameters, such as reagents do...
Modelling opinion formation by means of kinetic equations
Boudin , Laurent; Salvarani , Francesco
2010-01-01
In this chapter, we review some mechanisms of opinion dynamics that can be modelled by kinetic equations. Beside the sociological phenomenon of compromise, naturally linked to collisional operators of Boltzmann kind, many other aspects, already mentioned in the sociophysical literature or no, can enter in this framework. While describing some contributions appeared in the literature, we enlighten some mathematical tools of kinetic theory that can be useful in the context of sociophysics.
Wang, Zhandong
2015-07-01
Ethylcyclohexane (ECH) is a model compound for cycloalkanes with long alkyl side-chains. A preliminary investigation on ECH (Wang et al., Proc. Combust. Inst., 35, 2015, 367-375) revealed that an accurate ECH kinetic model with detailed fuel consumption mechanism and aromatic growth pathways, as well as additional ECH pyrolysis and oxidation data with detailed species concentration covering a wide pressure and temperature range are required to understand the ECH combustion kinetics. In this work, the flow reactor pyrolysis of ECH at various pressures (30, 150 and 760Torr) was studied using synchrotron vacuum ultraviolet (VUV) photoionization mass spectrometry (PIMS) and gas chromatography (GC). The mole fraction profiles of numerous major and minor species were evaluated, and good agreement was observed between the PIMS and GC data sets. Furthermore, a fuel-rich burner-stabilized laminar premixed ECH/O2/Ar flame at 30Torr was studied using synchrotron VUV PIMS. A detailed kinetic model for ECH high temperature pyrolysis and oxidation was developed and validated against the pyrolysis and flame data performed in this work. Further validation of the kinetic model is presented against literature data including species concentrations in jet-stirred reactor oxidation, ignition delay times in a shock tube, and laminar flame speeds at various pressures and equivalence ratios. The model well predicts the consumption of ECH, the growth of aromatics, and the global combustion properties. Reaction flux and sensitivity analysis were utilized to elucidate chemical kinetic features of ECH combustion under various reaction conditions. © 2015 The Combustion Institute.
Chemical kinetic modeling of H{sub 2} applications
Energy Technology Data Exchange (ETDEWEB)
Marinov, N.M.; Westbrook, C.K.; Cloutman, L.D. [Lawrence Livermore National Lab., CA (United States)] [and others
1995-09-01
Work being carried out at LLNL has concentrated on studies of the role of chemical kinetics in a variety of problems related to hydrogen combustion in practical combustion systems, with an emphasis on vehicle propulsion. Use of hydrogen offers significant advantages over fossil fuels, and computer modeling provides advantages when used in concert with experimental studies. Many numerical {open_quotes}experiments{close_quotes} can be carried out quickly and efficiently, reducing the cost and time of system development, and many new and speculative concepts can be screened to identify those with sufficient promise to pursue experimentally. This project uses chemical kinetic and fluid dynamic computational modeling to examine the combustion characteristics of systems burning hydrogen, either as the only fuel or mixed with natural gas. Oxidation kinetics are combined with pollutant formation kinetics, including formation of oxides of nitrogen but also including air toxics in natural gas combustion. We have refined many of the elementary kinetic reaction steps in the detailed reaction mechanism for hydrogen oxidation. To extend the model to pressures characteristic of internal combustion engines, it was necessary to apply theoretical pressure falloff formalisms for several key steps in the reaction mechanism. We have continued development of simplified reaction mechanisms for hydrogen oxidation, we have implemented those mechanisms into multidimensional computational fluid dynamics models, and we have used models of chemistry and fluid dynamics to address selected application problems. At the present time, we are using computed high pressure flame, and auto-ignition data to further refine the simplified kinetics models that are then to be used in multidimensional fluid mechanics models. Detailed kinetics studies have investigated hydrogen flames and ignition of hydrogen behind shock waves, intended to refine the detailed reactions mechanisms.
RELAP5 kinetics model development for the Advanced Test Reactor
International Nuclear Information System (INIS)
Judd, J.L.; Terry, W.K.
1990-01-01
A point-kinetics model of the Advanced Test Reactor has been developed for the RELAP5 code. Reactivity feedback parameters were calculated by a three-dimensional analysis with the PDQ neutron diffusion code. Analyses of several hypothetical reactivity insertion events by the new model and two earlier models are discussed. 3 refs., 10 figs., 6 tabs
A tool model for predicting atmospheric kinetics with sensitivity analysis
Institute of Scientific and Technical Information of China (English)
无
2001-01-01
A package( a tool model) for program of predicting atmospheric chemical kinetics with sensitivity analysis is presented. The new direct method of calculating the first order sensitivity coefficients using sparse matrix technology to chemical kinetics is included in the tool model, it is only necessary to triangularize the matrix related to the Jacobian matrix of the model equation. The Gear type procedure is used to integrate amodel equation and its coupled auxiliary sensitivity coefficient equations. The FORTRAN subroutines of the model equation, the sensitivity coefficient equations, and their Jacobian analytical expressions are generated automatically from a chemical mechanism. The kinetic representation for the model equation and its sensitivity coefficient equations, and their Jacobian matrix is presented. Various FORTRAN subroutines in packages, such as SLODE, modified MA28, Gear package, with which the program runs in conjunction are recommended.The photo-oxidation of dimethyl disulfide is used for illustration.
Branco Dos Santos, Filipe; Olivier, Brett G; Boele, Joost; Smessaert, Vincent; De Rop, Philippe; Krumpochova, Petra; Klau, Gunnar W; Giera, Martin; Dehottay, Philippe; Teusink, Bas; Goffin, Philippe
2017-08-25
Whooping cough is a highly-contagious respiratory disease caused by Bordetella pertussi s. Despite vaccination, its incidence has been rising alarmingly, and yet, the physiology of B. pertussis remains poorly understood. We combined genome-scale metabolic reconstruction, a novel optimization algorithm and experimental data to probe the full metabolic potential of this pathogen, using strain Tohama I as a reference. Experimental validation showed that B. pertussis secretes a significant proportion of nitrogen as arginine and purine nucleosides, which may contribute to modulation of the host response. We also found that B. pertussis can be unexpectedly versatile, being able to metabolize many compounds while displaying minimal nutrient requirements. It can grow without cysteine - using inorganic sulfur sources such as thiosulfate - and it can grow on organic acids such as citrate or lactate as sole carbon sources, providing in vivo demonstration that its TCA cycle is functional. Although the metabolic reconstruction of eight additional strains indicates that the structural genes underlying this metabolic flexibility are widespread, experimental validation suggests a role of strain-specific regulatory mechanisms in shaping metabolic capabilities. Among five alternative strains tested, three were shown to grow on substrate combinations requiring a functional TCA cycle, but only one could use thiosulfate. Finally, the metabolic model was used to rationally design growth media with over two-fold improvements in pertussis toxin production. This study thus provides novel insights into B. pertussis physiology, and highlights the potential, but also limitations of models solely based on metabolic gene content. IMPORTANCE The metabolic capabilities of Bordetella pertussis - the causative agent of whooping cough - were investigated from a systems-level perspective. We constructed a comprehensive genome-scale metabolic model for B. pertussis , and challenged its predictions
DEFF Research Database (Denmark)
Kjeldsen, Kjeld Raunkjær; Nielsen, J.
2009-01-01
A genome-scale metabolic model of the Gram-positive bacteria Corynebacterium glutamicum ATCC 13032 was constructed comprising 446 reactions and 411 metabolite, based on the annotated genome and available biochemical information. The network was analyzed using constraint based methods. The model...... was extensively validated against published flux data, and flux distribution values were found to correlate well between simulations and experiments. The split pathway of the lysine synthesis pathway of C. glutamicum was investigated, and it was found that the direct dehydrogenase variant gave a higher lysine...... yield than the alternative succinyl pathway at high lysine production rates. The NADPH demand of the network was not found to be critical for lysine production until lysine yields exceeded 55% (mmol lysine (mmol glucose)(-1)). The model was validated during growth on the organic acids acetate...
Reactor kinetics revisited: a coefficient based model (CBM)
International Nuclear Information System (INIS)
Ratemi, W.M.
2011-01-01
In this paper, a nuclear reactor kinetics model based on Guelph expansion coefficients calculation ( Coefficients Based Model, CBM), for n groups of delayed neutrons is developed. The accompanying characteristic equation is a polynomial form of the Inhour equation with the same coefficients of the CBM- kinetics model. Those coefficients depend on Universal abc- values which are dependent on the type of the fuel fueling a nuclear reactor. Furthermore, such coefficients are linearly dependent on the inserted reactivity. In this paper, the Universal abc- values have been presented symbolically, for the first time, as well as with their numerical values for U-235 fueled reactors for one, two, three, and six groups of delayed neutrons. Simulation studies for constant and variable reactivity insertions are made for the CBM kinetics model, and a comparison of results, with numerical solutions of classical kinetics models for one, two, three, and six groups of delayed neutrons are presented. The results show good agreements, especially for single step insertion of reactivity, with the advantage of the CBM- solution of not encountering the stiffness problem accompanying the numerical solutions of the classical kinetics model. (author)
Zea mays iRS1563: A Comprehensive Genome-Scale Metabolic Reconstruction of Maize Metabolism
Saha, Rajib; Suthers, Patrick F.; Maranas, Costas D.
2011-01-01
The scope and breadth of genome-scale metabolic reconstructions have continued to expand over the last decade. Herein, we introduce a genome-scale model for a plant with direct applications to food and bioenergy production (i.e., maize). Maize annotation is still underway, which introduces significant challenges in the association of metabolic functions to genes. The developed model is designed to meet rigorous standards on gene-protein-reaction (GPR) associations, elementally and charged balanced reactions and a biomass reaction abstracting the relative contribution of all biomass constituents. The metabolic network contains 1,563 genes and 1,825 metabolites involved in 1,985 reactions from primary and secondary maize metabolism. For approximately 42% of the reactions direct literature evidence for the participation of the reaction in maize was found. As many as 445 reactions and 369 metabolites are unique to the maize model compared to the AraGEM model for A. thaliana. 674 metabolites and 893 reactions are present in Zea mays iRS1563 that are not accounted for in maize C4GEM. All reactions are elementally and charged balanced and localized into six different compartments (i.e., cytoplasm, mitochondrion, plastid, peroxisome, vacuole and extracellular). GPR associations are also established based on the functional annotation information and homology prediction accounting for monofunctional, multifunctional and multimeric proteins, isozymes and protein complexes. We describe results from performing flux balance analysis under different physiological conditions, (i.e., photosynthesis, photorespiration and respiration) of a C4 plant and also explore model predictions against experimental observations for two naturally occurring mutants (i.e., bm1 and bm3). The developed model corresponds to the largest and more complete to-date effort at cataloguing metabolism for a plant species. PMID:21755001
Kinetic computer modeling of microwave surface-wave plasma production
International Nuclear Information System (INIS)
Ganachev, Ivan P.
2004-01-01
Kinetic computer plasma modeling occupies an intermediate position between the time consuming rigorous particle dynamic simulation and the fast but rather rough cold- or warm-plasma fluid models. The present paper reviews the kinetic modeling of microwave surface-wave discharges with accent on recent kinetic self-consistent models, where the external input parameters are reduced to the necessary minimum (frequency and intensity of the applied microwave field and pressure and geometry of the discharge vessel). The presentation is limited to low pressures, so that Boltzmann equation is solved in non-local approximation and collisional electron heating is neglected. The numerical results reproduce correctly the bi-Maxwellian electron energy distribution functions observed experimentally. (author)
RETRAN-02 one-dimensional kinetics model: a review
International Nuclear Information System (INIS)
Gose, G.C.; McClure, J.A.
1986-01-01
RETRAN-02 is a modular code system that has been designed for one-dimensional, transient thermal-hydraulics analysis. In RETRAN-02, core power behavior may be treated using a one-dimensional reactor kinetics model. This model allows the user to investigate the interaction of time- and space-dependent effects in the reactor core on overall system behavior for specific LWR operational transients. The purpose of this paper is to review the recent analysis and development activities related to the one dimensional kinetics model in RETRAN-02
Vibrational kinetics in CO electric discharge lasers - Modeling and experiments
Stanton, A. C.; Hanson, R. K.; Mitchner, M.
1980-01-01
A model of CO laser vibrational kinetics is developed, and predicted vibrational distributions are compared with measurements. The experimental distributions were obtained at various flow locations in a transverse CW discharge in supersonic (M = 3) flow. Good qualitative agreement is obtained in the comparisons, including the prediction of a total inversion at low discharge current densities. The major area of discrepancy is an observed loss in vibrational energy downstream of the discharge which is not predicted by the model. This discrepancy may be due to three-dimensional effects in the experiment which are not included in the model. Possible kinetic effects which may contribute to vibrational energy loss are also examined.
A two-point kinetic model for the PROTEUS reactor
International Nuclear Information System (INIS)
Dam, H. van.
1995-03-01
A two-point reactor kinetic model for the PROTEUS-reactor is developed and the results are described in terms of frequency dependent reactivity transfer functions for the core and the reflector. It is shown that at higher frequencies space-dependent effects occur which imply failure of the one-point kinetic model. In the modulus of the transfer functions these effects become apparent above a radian frequency of about 100 s -1 , whereas for the phase behaviour the deviation from a point model already starts at a radian frequency of 10 s -1 . (orig.)
Modeling Kinetics of Distortion in Porous Bi-layered Structures
DEFF Research Database (Denmark)
Tadesse Molla, Tesfaye; Frandsen, Henrik Lund; Bjørk, Rasmus
2013-01-01
because of different sintering rates of the materials resulting in undesired distortions of the component. An analytical model based on the continuum theory of sintering has been developed to describe the kinetics of densification and distortion in the sintering processes. A new approach is used...... to extract the material parameters controlling shape distortion through optimizing the model to experimental data of free shrinkage strains. The significant influence of weight of the sample (gravity) on the kinetics of distortion is taken in to consideration. The modeling predictions indicate good agreement...
A multi water bag model of drift kinetic electron plasma
International Nuclear Information System (INIS)
Morel, P.; Dreydemy Ghiro, F.; Berionni, V.; Gurcan, O.D.; Coulette, D.; Besse, N.
2014-01-01
A Multi Water Bag model is proposed for describing drift kinetic plasmas in a magnetized cylindrical geometry, relevant for various experimental devices, solar wind modeling... The Multi Water Bag (MWB) model is adapted to the description of a plasma with kinetic electrons as well as an arbitrary number of kinetic ions. This allows to describe the kinetic dynamics of the electrons, making possible the study of electron temperature gradient (ETG) modes, in addition to the effects of non adiabatic electrons on the ion temperature gradient (ITG) modes, that are of prime importance in the magnetized plasmas micro-turbulence [X. Garbet, Y. Idomura, L. Villard, T.H. Watanabe, Nucl. Fusion 50, 043002 (2010); J.A. Krommes, Ann. Rev. Fluid Mech. 44, 175 (2012)]. The MWB model is shown to link kinetic and fluid descriptions, depending on the number of bags considered. Linear stability of the ETG modes is presented and compared to the existing results regarding cylindrical ITG modes [P. Morel, E. Gravier, N. Besse, R. Klein, A. Ghizzo, P. Bertrand, W. Garbet, Ph. Ghendrih, V. Grandgirard, Y. Sarazin, Phys. Plasmas 14, 112109 (2007)]. (authors)
Computer-Aided Construction of Chemical Kinetic Models
Energy Technology Data Exchange (ETDEWEB)
Green, William H. [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States)
2014-12-31
The combustion chemistry of even simple fuels can be extremely complex, involving hundreds or thousands of kinetically significant species. The most reasonable way to deal with this complexity is to use a computer not only to numerically solve the kinetic model, but also to construct the kinetic model in the first place. Because these large models contain so many numerical parameters (e.g. rate coefficients, thermochemistry) one never has sufficient data to uniquely determine them all experimentally. Instead one must work in “predictive” mode, using theoretical rather than experimental values for many of the numbers in the model, and as appropriate refining the most sensitive numbers through experiments. Predictive chemical kinetics is exactly what is needed for computer-aided design of combustion systems based on proposed alternative fuels, particularly for early assessment of the value and viability of proposed new fuels before those fuels are commercially available. This project was aimed at making accurate predictive chemical kinetics practical; this is a challenging goal which requires a range of science advances. The project spanned a wide range from quantum chemical calculations on individual molecules and elementary-step reactions, through the development of improved rate/thermo calculation procedures, the creation of algorithms and software for constructing and solving kinetic simulations, the invention of methods for model-reduction while maintaining error control, and finally comparisons with experiment. Many of the parameters in the models were derived from quantum chemistry calculations, and the models were compared with experimental data measured in our lab or in collaboration with others.
Ab initio and kinetic modeling studies of formic acid oxidation
DEFF Research Database (Denmark)
Marshall, Paul; Glarborg, Peter
2015-01-01
A detailed chemical kinetic model for oxidation of formic acid (HOCHO) in flames has been developed, based on theoretical work and data from literature. Ab initio calculations were used to obtain rate coefficients for reactions of HOCHO with H, O, and HO2. Modeling predictions with the mechanism...
Modeling the kinetics of volatilization from glass melts
Beerkens, R.G.C.
2001-01-01
A model description for the evaporation kinetics from glass melts in direct contact with static atmospheres or flowing gas phases is presented. The derived models and equations are based on the solution of the second Ficks' diffusion law and quasi-steady-state mass transfer relations, taking into
A mathematical model of combustion kinetics of municipal solid ...
African Journals Online (AJOL)
Municipal Solid Waste has become a serious environmental problem troubling many cities. In this paper, a mathematical model of combustion kinetics of municipal solid waste with focus on plastic waste was studied. An analytical solution is obtained for the model. From the numerical simulation, it is observed that the ...
Simplified kinetic models of methanol oxidation on silver
DEFF Research Database (Denmark)
Andreasen, A.; Lynggaard, H.; Stegelmann, C.
2005-01-01
Recently the authors developed a microkinetic model of methanol oxidation on silver [A. Andreasen, H. Lynggaard, C. Stegelmann, P. Stoltze, Surf. Sci. 544 (2003) 5-23]. The model successfully explains both surface science experiments and kinetic experiments at industrial conditions applying...
Kinetic modelling for zinc (II) ions biosorption onto Luffa cylindrica
International Nuclear Information System (INIS)
Oboh, I.; Aluyor, E.; Audu, T.
2015-01-01
The biosorption of Zinc (II) ions onto a biomaterial - Luffa cylindrica has been studied. This biomaterial was characterized by elemental analysis, surface area, pore size distribution, scanning electron microscopy, and the biomaterial before and after sorption, was characterized by Fourier Transform Infra Red (FTIR) spectrometer. The kinetic nonlinear models fitted were Pseudo-first order, Pseudo-second order and Intra-particle diffusion. A comparison of non-linear regression method in selecting the kinetic model was made. Four error functions, namely coefficient of determination (R 2 ), hybrid fractional error function (HYBRID), average relative error (ARE), and sum of the errors squared (ERRSQ), were used to predict the parameters of the kinetic models. The strength of this study is that a biomaterial with wide distribution particularly in the tropical world and which occurs as waste material could be put into effective utilization as a biosorbent to address a crucial environmental problem
Sum rule limitations of kinetic particle-production models
International Nuclear Information System (INIS)
Knoll, J.; CEA Centre d'Etudes Nucleaires de Grenoble, 38; Guet, C.
1988-04-01
Photoproduction and absorption sum rules generalized to systems at finite temperature provide a stringent check on the validity of kinetic models for the production of hard photons in intermediate energy nuclear collisions. We inspect such models for the case of nuclear matter at finite temperature employed in a kinetic regime which copes those encountered in energetic nuclear collisions, and find photon production rates which significantly exceed the limits imposed by the sum rule even under favourable concession. This suggests that coherence effects are quite important and the production of photons cannot be considered as an incoherent addition of individual NNγ production processes. The deficiencies of present kinetic models may also apply for the production of probes such as the pion which do not couple perturbatively to the nuclear currents. (orig.)
Toward the automated generation of genome-scale metabolic networks in the SEED.
DeJongh, Matthew; Formsma, Kevin; Boillot, Paul; Gould, John; Rycenga, Matthew; Best, Aaron
2007-04-26
Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis). We have implemented our tools and database within the SEED, an open-source software environment for comparative genome annotation and analysis. Our method sets the
Toward the automated generation of genome-scale metabolic networks in the SEED
Directory of Open Access Journals (Sweden)
Gould John
2007-04-01
Full Text Available Abstract Background Current methods for the automated generation of genome-scale metabolic networks focus on genome annotation and preliminary biochemical reaction network assembly, but do not adequately address the process of identifying and filling gaps in the reaction network, and verifying that the network is suitable for systems level analysis. Thus, current methods are only sufficient for generating draft-quality networks, and refinement of the reaction network is still largely a manual, labor-intensive process. Results We have developed a method for generating genome-scale metabolic networks that produces substantially complete reaction networks, suitable for systems level analysis. Our method partitions the reaction space of central and intermediary metabolism into discrete, interconnected components that can be assembled and verified in isolation from each other, and then integrated and verified at the level of their interconnectivity. We have developed a database of components that are common across organisms, and have created tools for automatically assembling appropriate components for a particular organism based on the metabolic pathways encoded in the organism's genome. This focuses manual efforts on that portion of an organism's metabolism that is not yet represented in the database. We have demonstrated the efficacy of our method by reverse-engineering and automatically regenerating the reaction network from a published genome-scale metabolic model for Staphylococcus aureus. Additionally, we have verified that our method capitalizes on the database of common reaction network components created for S. aureus, by using these components to generate substantially complete reconstructions of the reaction networks from three other published metabolic models (Escherichia coli, Helicobacter pylori, and Lactococcus lactis. We have implemented our tools and database within the SEED, an open-source software environment for comparative
A kinetic approach to magnetospheric modeling
International Nuclear Information System (INIS)
Whipple, E.C. Jr.
1979-01-01
The earth's magnetosphere is caused by the interaction between the flowing solar wind and the earth's magnetic dipole, with the distorted magnetic field in the outer parts of the magnetosphere due to the current systems resulting from this interaction. It is surprising that even the conceptually simple problem of the collisionless interaction of a flowing plasma with a dipole magnetic field has not been solved. A kinetic approach is essential if one is to take into account the dispersion of particles with different energies and pitch angles and the fact that particles on different trajectories have different histories and may come from different sources. Solving the interaction problem involves finding the various types of possible trajectories, populating them with particles appropriately, and then treating the electric and magnetic fields self-consistently with the resulting particle densities and currents. This approach is illustrated by formulating a procedure for solving the collisionless interaction problem on open field lines in the case of a slowly flowing magnetized plasma interacting with a magnetic dipole
A kinetic approach to magnetospheric modeling
Whipple, E. C., Jr.
1979-01-01
The earth's magnetosphere is caused by the interaction between the flowing solar wind and the earth's magnetic dipole, with the distorted magnetic field in the outer parts of the magnetosphere due to the current systems resulting from this interaction. It is surprising that even the conceptually simple problem of the collisionless interaction of a flowing plasma with a dipole magnetic field has not been solved. A kinetic approach is essential if one is to take into account the dispersion of particles with different energies and pitch angles and the fact that particles on different trajectories have different histories and may come from different sources. Solving the interaction problem involves finding the various types of possible trajectories, populating them with particles appropriately, and then treating the electric and magnetic fields self-consistently with the resulting particle densities and currents. This approach is illustrated by formulating a procedure for solving the collisionless interaction problem on open field lines in the case of a slowly flowing magnetized plasma interacting with a magnetic dipole.
Kinetic models for irreversible processes on a lattice
International Nuclear Information System (INIS)
Wolf, N.O.
1979-04-01
The development and application of kinetic lattice models are considered. For the most part, the discussions are restricted to lattices in one-dimension. In Chapter 1, a brief overview of kinetic lattice model formalisms and an extensive literature survey are presented. A review of the kinetic models for non-cooperative lattice events is presented in Chapter 2. The development of cooperative lattice models and solution of the resulting kinetic equations for an infinite and a semi-infinite lattice are thoroughly discussed in Chapters 3 and 4. The cooperative models are then applied to the problem of theoretically dtermining the sticking coefficient for molecular chemisorption in Chapter 5. In Chapter 6, other possible applications of these models and several model generalizations are considered. Finally, in Chapter 7, an experimental study directed toward elucidating the mechanistic factors influencing the chemisorption of methane on single crystal tungsten is reported. In this it differs from the rest of the thesis which deals with the statistical distributions resulting from a given mechanism
Kinetic models for irreversible processes on a lattice
Energy Technology Data Exchange (ETDEWEB)
Wolf, N.O.
1979-04-01
The development and application of kinetic lattice models are considered. For the most part, the discussions are restricted to lattices in one-dimension. In Chapter 1, a brief overview of kinetic lattice model formalisms and an extensive literature survey are presented. A review of the kinetic models for non-cooperative lattice events is presented in Chapter 2. The development of cooperative lattice models and solution of the resulting kinetic equations for an infinite and a semi-infinite lattice are thoroughly discussed in Chapters 3 and 4. The cooperative models are then applied to the problem of theoretically dtermining the sticking coefficient for molecular chemisorption in Chapter 5. In Chapter 6, other possible applications of these models and several model generalizations are considered. Finally, in Chapter 7, an experimental study directed toward elucidating the mechanistic factors influencing the chemisorption of methane on single crystal tungsten is reported. In this it differs from the rest of the thesis which deals with the statistical distributions resulting from a given mechanism.
Directory of Open Access Journals (Sweden)
Amit Ghosh
Full Text Available Biofuels derived from lignocellulosic biomass offer promising alternative renewable energy sources for transportation fuels. Significant effort has been made to engineer Saccharomyces cerevisiae to efficiently ferment pentose sugars such as D-xylose and L-arabinose into biofuels such as ethanol through heterologous expression of the fungal D-xylose and L-arabinose pathways. However, one of the major bottlenecks in these fungal pathways is that the cofactors are not balanced, which contributes to inefficient utilization of pentose sugars. We utilized a genome-scale model of S. cerevisiae to predict the maximal achievable growth rate for cofactor balanced and imbalanced D-xylose and L-arabinose utilization pathways. Dynamic flux balance analysis (DFBA was used to simulate batch fermentation of glucose, D-xylose, and L-arabinose. The dynamic models and experimental results are in good agreement for the wild type and for the engineered D-xylose utilization pathway. Cofactor balancing the engineered D-xylose and L-arabinose utilization pathways simulated an increase in ethanol batch production of 24.7% while simultaneously reducing the predicted substrate utilization time by 70%. Furthermore, the effects of cofactor balancing the engineered pentose utilization pathways were evaluated throughout the genome-scale metabolic network. This work not only provides new insights to the global network effects of cofactor balancing but also provides useful guidelines for engineering a recombinant yeast strain with cofactor balanced engineered pathways that efficiently co-utilizes pentose and hexose sugars for biofuels production. Experimental switching of cofactor usage in enzymes has been demonstrated, but is a time-consuming effort. Therefore, systems biology models that can predict the likely outcome of such strain engineering efforts are highly useful for motivating which efforts are likely to be worth the significant time investment.
Transperitoneal transport of creatinine. A comparison of kinetic models
DEFF Research Database (Denmark)
Fugleberg, S; Graff, J; Joffe, P
1994-01-01
Six kinetic models of transperitoneal creatinine transport were formulated and validated on the basis of experimental results obtained from 23 non-diabetic patients undergoing peritoneal dialysis. The models were designed to elucidate the presence or absence of diffusive, non-lymphatic convective...... including all three forms of transport is superior to other models. We conclude that the best model of transperitoneal creatinine transport includes diffusion, non-lymphatic convective transport and lymphatic convective transport....
Computer models for kinetic equations of magnetically confined plasmas
International Nuclear Information System (INIS)
Killeen, J.; Kerbel, G.D.; McCoy, M.G.; Mirin, A.A.; Horowitz, E.J.; Shumaker, D.E.
1987-01-01
This paper presents four working computer models developed by the computational physics group of the National Magnetic Fusion Energy Computer Center. All of the models employ a kinetic description of plasma species. Three of the models are collisional, i.e., they include the solution of the Fokker-Planck equation in velocity space. The fourth model is collisionless and treats the plasma ions by a fully three-dimensional particle-in-cell method
Norsigian, Charles J; Kavvas, Erol; Seif, Yara; Palsson, Bernhard O; Monk, Jonathan M
2018-01-01
Acinetobacter baumannii has become an urgent clinical threat due to the recent emergence of multi-drug resistant strains. There is thus a significant need to discover new therapeutic targets in this organism. One means for doing so is through the use of high-quality genome-scale reconstructions. Well-curated and accurate genome-scale models (GEMs) of A. baumannii would be useful for improving treatment options. We present an updated and improved genome-scale reconstruction of A. baumannii AYE, named iCN718, that improves and standardizes previous A. baumannii AYE reconstructions. iCN718 has 80% accuracy for predicting gene essentiality data and additionally can predict large-scale phenotypic data with as much as 89% accuracy, a new capability for an A. baumannii reconstruction. We further demonstrate that iCN718 can be used to analyze conserved metabolic functions in the A. baumannii core genome and to build strain-specific GEMs of 74 other A. baumannii strains from genome sequence alone. iCN718 will serve as a resource to integrate and synthesize new experimental data being generated for this urgent threat pathogen.
Bio-succinic acid production: Escherichia coli strains design from genome-scale perspectives
Directory of Open Access Journals (Sweden)
Bashir Sajo Mienda
2017-10-01
Full Text Available Escherichia coli (E. coli has been established to be a native producer of succinic acid (a platform chemical with different applications via mixed acid fermentation reactions. Genome-scale metabolic models (GEMs of E. coli have been published with capabilities of predicting strain design strategies for the production of bio-based succinic acid. Proof-of-principle strains are fundamentally constructed as a starting point for systems strategies for industrial strains development. Here, we review for the first time, the use of E. coli GEMs for construction of proof-of-principles strains for increasing succinic acid production. Specific case studies, where E. coli proof-of-principle strains were constructed for increasing bio-based succinic acid production from glucose and glycerol carbon sources have been highlighted. In addition, a propose systems strategies for industrial strain development that could be applicable for future microbial succinic acid production guided by GEMs have been presented.
A systems approach to predict oncometabolites via context-specific genome-scale metabolic networks.
Directory of Open Access Journals (Sweden)
Hojung Nam
2014-09-01
Full Text Available Altered metabolism in cancer cells has been viewed as a passive response required for a malignant transformation. However, this view has changed through the recently described metabolic oncogenic factors: mutated isocitrate dehydrogenases (IDH, succinate dehydrogenase (SDH, and fumarate hydratase (FH that produce oncometabolites that competitively inhibit epigenetic regulation. In this study, we demonstrate in silico predictions of oncometabolites that have the potential to dysregulate epigenetic controls in nine types of cancer by incorporating massive scale genetic mutation information (collected from more than 1,700 cancer genomes, expression profiling data, and deploying Recon 2 to reconstruct context-specific genome-scale metabolic models. Our analysis predicted 15 compounds and 24 substructures of potential oncometabolites that could result from the loss-of-function and gain-of-function mutations of metabolic enzymes, respectively. These results suggest a substantial potential for discovering unidentified oncometabolites in various forms of cancers.
Gyrofluid Modeling of Turbulent, Kinetic Physics
Despain, Kate Marie
2011-12-01
Gyrofluid models to describe plasma turbulence combine the advantages of fluid models, such as lower dimensionality and well-developed intuition, with those of gyrokinetics models, such as finite Larmor radius (FLR) effects. This allows gyrofluid models to be more tractable computationally while still capturing much of the physics related to the FLR of the particles. We present a gyrofluid model derived to capture the behavior of slow solar wind turbulence and describe the computer code developed to implement the model. In addition, we describe the modifications we made to a gyrofluid model and code that simulate plasma turbulence in tokamak geometries. Specifically, we describe a nonlinear phase mixing phenomenon, part of the E x B term, that was previously missing from the model. An inherently FLR effect, it plays an important role in predicting turbulent heat flux and diffusivity levels for the plasma. We demonstrate this importance by comparing results from the updated code to studies done previously by gyrofluid and gyrokinetic codes. We further explain what would be necessary to couple the updated gyrofluid code, gryffin, to a turbulent transport code, thus allowing gryffin to play a role in predicting profiles for fusion devices such as ITER and to explore novel fusion configurations. Such a coupling would require the use of Graphical Processing Units (GPUs) to make the modeling process fast enough to be viable. Consequently, we also describe our experience with GPU computing and demonstrate that we are poised to complete a gryffin port to this innovative architecture.
DEFF Research Database (Denmark)
Kavvas, Erol S.; Seif, Yara; Yurkovich, James T.
2018-01-01
previous M. tuberculosis H37Rv genome-scale reconstructions. We functionally assess iEK1011 against previous models and show that the model increases correct gene essentiality predictions on two different experimental datasets by 6% (53% to 60%) and 18% (60% to 71%), respectively. We compared simulations...
Kinetic k-essence ghost dark energy model
International Nuclear Information System (INIS)
Rozas-Fernández, Alberto
2012-01-01
A ghost dark energy model has been recently put forward to explain the current accelerated expansion of the Universe. In this model, the energy density of ghost dark energy, which comes from the Veneziano ghost of QCD, is proportional to the Hubble parameter, ρ D =αH. Here α is a constant of order Λ QCD 3 where Λ QCD ∼100 MeV is the QCD mass scale. We consider a connection between ghost dark energy with/without interaction between the components of the dark sector and the kinetic k-essence field. It is shown that the cosmological evolution of the ghost dark energy dominated Universe can be completely described a kinetic k-essence scalar field. We reconstruct the kinetic k-essence function F(X) in a flat Friedmann-Robertson-Walker Universe according to the evolution of ghost dark energy density.
Bayesian inference of chemical kinetic models from proposed reactions
Galagali, Nikhil
2015-02-01
© 2014 Elsevier Ltd. Bayesian inference provides a natural framework for combining experimental data with prior knowledge to develop chemical kinetic models and quantify the associated uncertainties, not only in parameter values but also in model structure. Most existing applications of Bayesian model selection methods to chemical kinetics have been limited to comparisons among a small set of models, however. The significant computational cost of evaluating posterior model probabilities renders traditional Bayesian methods infeasible when the model space becomes large. We present a new framework for tractable Bayesian model inference and uncertainty quantification using a large number of systematically generated model hypotheses. The approach involves imposing point-mass mixture priors over rate constants and exploring the resulting posterior distribution using an adaptive Markov chain Monte Carlo method. The posterior samples are used to identify plausible models, to quantify rate constant uncertainties, and to extract key diagnostic information about model structure-such as the reactions and operating pathways most strongly supported by the data. We provide numerical demonstrations of the proposed framework by inferring kinetic models for catalytic steam and dry reforming of methane using available experimental data.
Continuum-Kinetic Models and Numerical Methods for Multiphase Applications
Nault, Isaac Michael
This thesis presents a continuum-kinetic approach for modeling general problems in multiphase solid mechanics. In this context, a continuum model refers to any model, typically on the macro-scale, in which continuous state variables are used to capture the most important physics: conservation of mass, momentum, and energy. A kinetic model refers to any model, typically on the meso-scale, which captures the statistical motion and evolution of microscopic entitites. Multiphase phenomena usually involve non-negligible micro or meso-scopic effects at the interfaces between phases. The approach developed in the thesis attempts to combine the computational performance benefits of a continuum model with the physical accuracy of a kinetic model when applied to a multiphase problem. The approach is applied to modeling a single particle impact in Cold Spray, an engineering process that intimately involves the interaction of crystal grains with high-magnitude elastic waves. Such a situation could be classified a multiphase application due to the discrete nature of grains on the spatial scale of the problem. For this application, a hyper elasto-plastic model is solved by a finite volume method with approximate Riemann solver. The results of this model are compared for two types of plastic closure: a phenomenological macro-scale constitutive law, and a physics-based meso-scale Crystal Plasticity model.
Modeling uptake kinetics of cadmium by field-grown lettuce
Energy Technology Data Exchange (ETDEWEB)
Chen Weiping [Department of Environmental Sciences, University of California, 900 University Avenue, Riverside, CA 92521 (United States)], E-mail: chenweip@yahoo.com.cn; Li Lianqing [Institute of Resources, Ecosystem and Environment of Agriculture, Nanjing Agricultural University, Nanjing 210095 (China); Chang, Andrew C.; Wu Laosheng [Department of Environmental Sciences, University of California, 900 University Avenue, Riverside, CA 92521 (United States); Kwon, Soon-Ik [Agricultural Environmental and Ecology Division, National Institute of Agricultural Science and Technology, Suwon 441-707 (Korea, Republic of); Bottoms, Rick [Desert Research and Extension Center, 1004 East Holton Road, El Centro, CA 92243 (United States)
2008-03-15
Cadmium uptake by field grown Romaine lettuce treated with P-fertilizers of different Cd levels was investigated over an entire growing season. Results indicated that the rate of Cd uptake at a given time of the season can be satisfactorily described by the Michaelis-Menten kinetics, that is, plant uptake increases as the Cd concentration in soil solution increases, and it gradually approaches a saturation level. However, the rate constant of the Michaelis-Menten kinetics changes over the growing season. Under a given soil Cd level, the cadmium content in plant tissue decreases exponentially with time. To account for the dynamic nature of Cd uptake, a kinetic model integrating the time factor was developed to simulate Cd plant uptake over the growing season: C{sub Plant} = C{sub Solution} . PUF{sub max} . exp[-b . t], where C{sub Plant} and C{sub Solution} refer to the Cd content in plant tissue and soil solution, respectively, PUF{sub max} and b are kinetic constants. - A kinetic model was developed to evaluate the uptake of Cd under field conditions.
Modeling uptake kinetics of cadmium by field-grown lettuce
International Nuclear Information System (INIS)
Chen Weiping; Li Lianqing; Chang, Andrew C.; Wu Laosheng; Kwon, Soon-Ik; Bottoms, Rick
2008-01-01
Cadmium uptake by field grown Romaine lettuce treated with P-fertilizers of different Cd levels was investigated over an entire growing season. Results indicated that the rate of Cd uptake at a given time of the season can be satisfactorily described by the Michaelis-Menten kinetics, that is, plant uptake increases as the Cd concentration in soil solution increases, and it gradually approaches a saturation level. However, the rate constant of the Michaelis-Menten kinetics changes over the growing season. Under a given soil Cd level, the cadmium content in plant tissue decreases exponentially with time. To account for the dynamic nature of Cd uptake, a kinetic model integrating the time factor was developed to simulate Cd plant uptake over the growing season: C Plant = C Solution . PUF max . exp[-b . t], where C Plant and C Solution refer to the Cd content in plant tissue and soil solution, respectively, PUF max and b are kinetic constants. - A kinetic model was developed to evaluate the uptake of Cd under field conditions
Experimental and modeling investigation on structure H hydrate formation kinetics
International Nuclear Information System (INIS)
Mazraeno, M. Seyfi; Varaminian, F.; Vafaie sefti, M.
2013-01-01
Highlights: • Applying affinity model for the formation kinetics of sH hydrate and two stage kinetics. • Performing the experiments of hydrate formation of sH with MCP. • A unique path for the SH hydrate formation. - Abstract: In this work, the kinetics of crystal H hydrate and two stage kinetics formation is modeled by using the chemical affinity model for the first time. The basic idea is that there is a unique path for each experiment by which the crystallization process decays the affinity. The experiments were performed at constant temperatures of 274.15, 275.15, 275.65, 276.15 and 277.15 K. The initial pressure of each experiment is up to 25 bar above equilibrium pressure of sI. Methylcyclohexane (MCH), methylcyclopentane (MCP) and tert-butyl methyl ether (TBME) are used as sH former and methane is used as a help gas. The parameters of the affinity model (A r and t k ) are determined and the results show that the parameter of (A r )/(RT) has not a constant value when temperature changes in each group of experiments. The results indicate that this model can predict experimental data very well at several conditions
Kinetics of steel slag leaching: Batch tests and modeling
International Nuclear Information System (INIS)
De Windt, Laurent; Chaurand, Perrine; Rose, Jerome
2011-01-01
Reusing steel slag as an aggregate for road construction requires to characterize the leaching kinetics and metal releases. In this study, basic oxygen furnace (BOF) steel slag were subjected to batch leaching tests at liquid to solid ratios (L/S) of 10 and 100 over 30 days; the leachate chemistry being regularly sampled in time. A geochemical model of the steel slag is developed and validated from experimental data, particularly the evolution with leaching of mineralogical composition of the slag and trace element speciation. Kinetics is necessary for modeling the primary phase leaching, whereas a simple thermodynamic equilibrium approach can be used for secondary phase precipitation. The proposed model simulates the kinetically-controlled dissolution (hydrolysis) of primary phases, the precipitation of secondary phases (C-S-H, hydroxide and spinel), the pH and redox conditions, and the progressive release of major elements as well as the metals Cr and V. Modeling indicates that the dilution effect of the L/S ratio is often coupled to solubility-controlled processes, which are sensitive to both the pH and the redox potential. A sensitivity analysis of kinetic uncertainties on the modeling of element releases is performed.
Modeling intrinsic kinetics in immobilized photocatalytic microreactors
Visan, Aura; Rafieian Boroujeni, Damon; Ogieglo, Wojciech; Lammertink, Rob G.H.
2014-01-01
The article presents a simple model for immobilized photocatalytic microreactors following a first order reaction rate with either light independency or light dependency described by photon absorption carrier generation semiconductor physics. Experimental data obtained for various residence times,
Kinetic and thermodynamic modelling of TBP synthesis processes
International Nuclear Information System (INIS)
Azzouz, A.; Attou, M.
1989-02-01
The present paper deals with kinetic and thermodynamic modellisation of tributylphosphate (TBP) synthesis processes. Its aim consists in a purely comparative study of two different synthesis ways i.e. direct and indirect estirification of butanol. The methodology involves two steps. The first step consists in approximating curves which describe the process evolution and their dependence on the main parameters. The results gave a kinetic model of the process rate yielding in TBP. Further, on the basis of thermodynamic data concerning the various involved compounds a theoretical model was achieved. The calculations were carried out in Basic language and an interpolation mathematical method was applied to approximate the kinetic curves. The thermodynamic calculations were achieved on the basis of GIBBS' free energy using a VAX type computer and a VT240 terminal. The calculations accuracy was reasonable and within the norms. For each process, the confrontation of both models leads to an appreciable accord. In the two processes, the thermodynamic models were similar although the kinetic equations present different reaction orders. Hence the reaction orders were determined by a mathematical method which conists in searching the minimal difference between an empiric relation and a kinetic model with fixed order. This corresponds in fact in testing the model proposed at various reaction order around the suspected value. The main idea which results from such a work is that this kind of processes is well fitting with the model without taking into account the side chain reactions. The process behaviour is like that of a single reaction having a quasi linear dependence of the rate yielding and the reaction time for both processes
Hoyermann, Karlheinz; Mauß, Fabian; Olzmann, Matthias; Welz, Oliver; Zeuch, Thomas
2017-07-19
Partially oxidized intermediates play a central role in combustion and atmospheric chemistry. In this perspective, we focus on the chemical kinetics of alkoxy radicals, peroxy radicals, and Criegee intermediates, which are key species in both combustion and atmospheric environments. These reactive intermediates feature a broad spectrum of chemical diversity. Their reactivity is central to our understanding of how volatile organic compounds are degraded in the atmosphere and converted into secondary organic aerosol. Moreover, they sensitively determine ignition timing in internal combustion engines. The intention of this perspective article is to provide the reader with information about the general mechanisms of reactions initiated by addition of atomic and molecular oxygen to alkyl radicals and ozone to alkenes. We will focus on critical branching points in the subsequent reaction mechanisms and discuss them from a consistent point of view. As a first example of our integrated approach, we will show how experiment, theory, and kinetic modeling have been successfully combined in the first infrared detection of Criegee intermediates during the gas phase ozonolysis. As a second example, we will examine the ignition timing of n-heptane/air mixtures at low and intermediate temperatures. Here, we present a reduced, fuel size independent kinetic model of the complex chemistry initiated by peroxy radicals that has been successfully applied to simulate standard n-heptane combustion experiments.
Kinetic modelling and thermodynamic studies on purification of ...
African Journals Online (AJOL)
Adsorbent capacities have been determined by mathematical fitting of equilibrium data using the most common isotherms: Freundlich isotherm and Langmuir isotherm. Several kinetic models have been applied to the process. Thermodynamic parameters: △So, △Ho, △Go and Ea (kJ/mol) have been determined.
Development of simple kinetic models and parameter estimation for ...
African Journals Online (AJOL)
In order to describe and predict the growth and expression of recombinant proteins by using a genetically modified Pichia pastoris, we developed a number of unstructured models based on growth kinetic equation, fed-batch mass balance and the assumptions of constant cell and protein yields. The growth of P. pastoris on ...
Modelling of thermal degradation kinetics of ascorbic acid in ...
African Journals Online (AJOL)
Ascorbic acid (vitamin C) loss in thermally treated pawpaw and potato was modelled mathematically. Isothermal experiments in the temperature range of 50 -80 oC for the drying of pawpaw and 60 -100 oC for the blanch-drying of potato were utilized to determine the kinetics of ascorbic acid loss in both fruit and vegetable.
DEFF Research Database (Denmark)
Saa, Pedro A.; Nielsen, Lars K.
2017-01-01
Kinetic models are critical to predict the dynamic behaviour of metabolic networks. Mechanistic kinetic models for large networks remain uncommon due to the difficulty of fitting their parameters. Recent modelling frameworks promise new ways to overcome this obstacle while retaining predictive ca...
Chemical kinetics and combustion modelling with CFX 4
Energy Technology Data Exchange (ETDEWEB)
Stopford, P [AEA Technology, Computational Fluid Dynamics Services Harwell, Oxfordshire (United Kingdom)
1998-12-31
The presentation describes some recent developments in combustion and kinetics models used in the CFX software of AEA Technology. Three topics are highlighted: the development of coupled solvers in a traditional `SIMPLE`-based CFD code, the use of detailed chemical kinetics mechanism via `look-up` tables and the application of CFD to large-scale multi-burner combustion plant. The aim is identify those physical approximations and numerical methods that are likely to be most useful in the future and those areas where further developments are required. (author) 6 refs.
Chemical kinetics and combustion modelling with CFX 4
Energy Technology Data Exchange (ETDEWEB)
Stopford, P. [AEA Technology, Computational Fluid Dynamics Services Harwell, Oxfordshire (United Kingdom)
1997-12-31
The presentation describes some recent developments in combustion and kinetics models used in the CFX software of AEA Technology. Three topics are highlighted: the development of coupled solvers in a traditional `SIMPLE`-based CFD code, the use of detailed chemical kinetics mechanism via `look-up` tables and the application of CFD to large-scale multi-burner combustion plant. The aim is identify those physical approximations and numerical methods that are likely to be most useful in the future and those areas where further developments are required. (author) 6 refs.
A flexible multipurpose model for normal and transient cell kinetics
International Nuclear Information System (INIS)
Toivonen, Harri.
1979-07-01
The internal hypothetical compartments within the different phases of the cell cycle have been adopted as the basis of models dealing with various specific problems in cell kinetics. This approach was found to be of more general validity, extending from expanding cell populations to complex maturation processes. The differential equations describing the system were solved with an effective, commercially available library subroutine. Special attention was devoted to analysis of transient and feedback kinetics of cell populations encountered in diverse environmental and exposure conditions, for instance in cases of wounding and radiation damage. (author)
Kinetics and modeling of anaerobic digestion process
DEFF Research Database (Denmark)
Gavala, Hariklia N.; Angelidaki, Irini; Ahring, Birgitte Kiær
2003-01-01
Anaerobic digestion modeling started in the early 1970s when the need for design and efficient operation of anaerobic systems became evident. At that time not only was the knowledge about the complex process of anaerobic digestion inadequate but also there were computational limitations. Thus...
Laplace transform in tracer kinetic modeling
Energy Technology Data Exchange (ETDEWEB)
Hauser, Eliete B., E-mail: eliete@pucrs.br [Instituto do Cerebro (InsCer/FAMAT/PUC-RS), Porto Alegre, RS, (Brazil). Faculdade de Matematica
2013-07-01
The main objective this paper is to quantify the pharmacokinetic processes: absorption, distribution and elimination of radiopharmaceutical(tracer), using Laplace transform method. When the drug is administered intravenously absorption is complete and is available in the bloodstream to be distributed throughout the whole body in all tissues and fluids, and to be eliminated. Mathematical modeling seeks to describe the processes of distribution and elimination through compartments, where distinct pools of tracer (spatial location or chemical state) are assigned to different compartments. A compartment model is described by a system of differential equations, where each equation represents the sum of all the transfer rates to and from a specific compartment. In this work a two-tissue irreversible compartment model is used for description of tracer, [{sup 18}F]2-fluor-2deoxy-D-glucose. In order to determine the parameters of the model, it is necessary to have information about the tracer delivery in the form of an input function representing the time-course of tracer concentration in arterial blood or plasma. We estimate the arterial input function in two stages and apply the Levenberg-Marquardt Method to solve nonlinear regressions. The transport of FDG across de arterial blood is very fast in the first ten minutes and then decreases slowly. We use de Heaviside function to represent this situation and this is the main contribution of this study. We apply the Laplace transform and the analytical solution for two-tissue irreversible compartment model is obtained. The only approach is to determinate de arterial input function. (author)
Ensemble Kinetic Modeling of Metabolic Networks from Dynamic Metabolic Profiles
Directory of Open Access Journals (Sweden)
Gengjie Jia
2012-11-01
Full Text Available Kinetic modeling of metabolic pathways has important applications in metabolic engineering, but significant challenges still remain. The difficulties faced vary from finding best-fit parameters in a highly multidimensional search space to incomplete parameter identifiability. To meet some of these challenges, an ensemble modeling method is developed for characterizing a subset of kinetic parameters that give statistically equivalent goodness-of-fit to time series concentration data. The method is based on the incremental identification approach, where the parameter estimation is done in a step-wise manner. Numerical efficacy is achieved by reducing the dimensionality of parameter space and using efficient random parameter exploration algorithms. The shift toward using model ensembles, instead of the traditional “best-fit” models, is necessary to directly account for model uncertainty during the application of such models. The performance of the ensemble modeling approach has been demonstrated in the modeling of a generic branched pathway and the trehalose pathway in Saccharomyces cerevisiae using generalized mass action (GMA kinetics.
Gyrofluid turbulence models with kinetic effects
International Nuclear Information System (INIS)
Dorland, W.; Hammett, G.W.
1992-12-01
Nonlinear gyrofluid equations are derived by taking moments of the nonlinear, electrostatic gyrokinetic equation. The principal model presented includes evolution equations for the guiding center n, u parallel, T parallel, and T perpendicular along with an equation expressing the quasineutrality constraint. Additional evolution equations for higher moments are derived which may be used if greater accuracy is desired. The moment hierarchy is closed with a Landau-damping model which is equivalent to a multi-pole approximation to the plasma dispersion function, extended to include finite Larmor radius effects. In particular, new dissipative, nonlinear terms are found which model the perpendicular phase-mixing of the distribution function along contours of constant electrostatic potential. These ''FLR phase-mixing'' terms introduce a hyperviscosity-like damping ∝ k perpendicular 2 |Φ rvec k rvec k x rvec k'| which should provide a physics-based damping mechanism at high k perpendicular ρ which is potentially as important as the usual polarization drift nonlinearity. The moments are taken in guiding center space to pick up the correct nonlinear FLR terms and the gyroaveraging of the shear. The equations are solved with a nonlinear, three dimensional initial value code. Linear results are presented, showing excellent agreement with linear gyrokinetic theory
A Kinetic Model Describing Injury-Burden in Team Sports.
Fuller, Colin W
2017-12-01
Injuries in team sports are normally characterised by the incidence, severity, and location and type of injuries sustained: these measures, however, do not provide an insight into the variable injury-burden experienced during a season. Injury burden varies according to the team's match and training loads, the rate at which injuries are sustained and the time taken for these injuries to resolve. At the present time, this time-based variation of injury burden has not been modelled. To develop a kinetic model describing the time-based injury burden experienced by teams in elite team sports and to demonstrate the model's utility. Rates of injury were quantified using a large eight-season database of rugby injuries (5253) and exposure (60,085 player-match-hours) in English professional rugby. Rates of recovery from injury were quantified using time-to-recovery analysis of the injuries. The kinetic model proposed for predicting a team's time-based injury burden is based on a composite rate equation developed from the incidence of injury, a first-order rate of recovery from injury and the team's playing load. The utility of the model was demonstrated by examining common scenarios encountered in elite rugby. The kinetic model developed describes and predicts the variable injury-burden arising from match play during a season of rugby union based on the incidence of match injuries, the rate of recovery from injury and the playing load. The model is equally applicable to other team sports and other scenarios.
Developments in kinetic modelling of chalcocite particle oxidation
Energy Technology Data Exchange (ETDEWEB)
Jaervi, J; Ahokainen, T; Jokilaakso, A [Helsinki Univ. of Technology, Otaniemi (Finland). Lab. of Materials Processing and Powder Metallurgy
1998-12-31
A mathematical model for simulating chalcocite particle oxidation is presented. Combustion of pure chalcocite with oxygen is coded as a kinetic module which can be connected as a separate part of commercial CFD-package, PHOENICS. Heat transfer, fluid flow and combustion phenomena can be simulated using CFD-calculation together with the kinetic model. Interaction between gas phase and particles are taken into account by source terms. The aim of the kinetic model is to calculate the particle temperature, contents of species inside the particle, oxygen consumption and formation of sulphur dioxide. Four oxidation reactions are considered and the shrinking core model is used to describe the rate of the oxidation reactions. The model is verified by simulating the particle oxidation reactions in a laboratory scale laminar-flow furnace under different conditions and the model predicts the effects of charges correctly. In the future, the model validation will be done after experimental studies in the laminar flow-furnace. (author) 18 refs.
Developments in kinetic modelling of chalcocite particle oxidation
Energy Technology Data Exchange (ETDEWEB)
Jaervi, J.; Ahokainen, T.; Jokilaakso, A. [Helsinki Univ. of Technology, Otaniemi (Finland). Lab. of Materials Processing and Powder Metallurgy
1997-12-31
A mathematical model for simulating chalcocite particle oxidation is presented. Combustion of pure chalcocite with oxygen is coded as a kinetic module which can be connected as a separate part of commercial CFD-package, PHOENICS. Heat transfer, fluid flow and combustion phenomena can be simulated using CFD-calculation together with the kinetic model. Interaction between gas phase and particles are taken into account by source terms. The aim of the kinetic model is to calculate the particle temperature, contents of species inside the particle, oxygen consumption and formation of sulphur dioxide. Four oxidation reactions are considered and the shrinking core model is used to describe the rate of the oxidation reactions. The model is verified by simulating the particle oxidation reactions in a laboratory scale laminar-flow furnace under different conditions and the model predicts the effects of charges correctly. In the future, the model validation will be done after experimental studies in the laminar flow-furnace. (author) 18 refs.
One-dimensional reactor kinetics model for RETRAN
International Nuclear Information System (INIS)
Gose, G.C.; Peterson, C.E.; Ellis, N.L.; McClure, J.A.
1981-01-01
Previous versions of RETRAN have had only a point kinetics model to describe the reactor core behavior during thermal-hydraulic transients. The principal assumption in deriving the point kinetics model is that the neutron flux may be separated into a time-dependent amplitude funtion and a time-independent shape function. Certain types of transients cannot be correctly analyzed under this assumption, since proper definitions for core average quantities such as reactivity or lifetime include the inner product of the adjoint flux with the perturbed flux. A one-dimensional neutronics model has been included in a preliminary version of RETRAN-02. The ability to account for flux shape changes will permit an improved representation of the thermal and hydraulic feedback effects. This paper describes the neutronics model and discusses some of the analyses
Environmental versatility promotes modularity in genome-scale metabolic networks.
Samal, Areejit; Wagner, Andreas; Martin, Olivier C
2011-08-24
The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Our work shows that modularity in metabolic networks can be a by-product of functional constraints, e.g., the need to sustain life in multiple
Environmental versatility promotes modularity in genome-scale metabolic networks
Directory of Open Access Journals (Sweden)
Wagner Andreas
2011-08-01
Full Text Available Abstract Background The ubiquity of modules in biological networks may result from an evolutionary benefit of a modular organization. For instance, modularity may increase the rate of adaptive evolution, because modules can be easily combined into new arrangements that may benefit their carrier. Conversely, modularity may emerge as a by-product of some trait. We here ask whether this last scenario may play a role in genome-scale metabolic networks that need to sustain life in one or more chemical environments. For such networks, we define a network module as a maximal set of reactions that are fully coupled, i.e., whose fluxes can only vary in fixed proportions. This definition overcomes limitations of purely graph based analyses of metabolism by exploiting the functional links between reactions. We call a metabolic network viable in a given chemical environment if it can synthesize all of an organism's biomass compounds from nutrients in this environment. An organism's metabolism is highly versatile if it can sustain life in many different chemical environments. We here ask whether versatility affects the modularity of metabolic networks. Results Using recently developed techniques to randomly sample large numbers of viable metabolic networks from a vast space of metabolic networks, we use flux balance analysis to study in silico metabolic networks that differ in their versatility. We find that highly versatile networks are also highly modular. They contain more modules and more reactions that are organized into modules. Most or all reactions in a module are associated with the same biochemical pathways. Modules that arise in highly versatile networks generally involve reactions that process nutrients or closely related chemicals. We also observe that the metabolism of E. coli is significantly more modular than even our most versatile networks. Conclusions Our work shows that modularity in metabolic networks can be a by-product of functional
Metabolite coupling in genome-scale metabolic networks
Directory of Open Access Journals (Sweden)
Palsson Bernhard Ø
2006-03-01
metabolites. Conclusion The coupling of metabolites is an important topological property of metabolic networks. By computing coupling quantitatively for the first time in genome-scale metabolic networks, we provide insight into the basic structure of these networks.
Kinetic modeling of Nernst effect in magnetized hohlraums
Joglekar, A. S.; Ridgers, Christopher Paul; Kingham, R J; Thomas, A. G. R.
2016-01-01
We present nanosecond time-scale Vlasov-Fokker-Planck-Maxwell modeling of magnetized plasma transport and dynamics in a hohlraum with an applied external magnetic field, under conditions similar to recent experiments. Self-consistent modeling of the kinetic electron momentum equation allows for a complete treatment of the heat flow equation and Ohm's law, including Nernst advection of magnetic fields. In addition to showing the prevalence of nonlocal behavior, we demonstrate that effects such...
A kinetic-MHD model for low frequency phenomena
International Nuclear Information System (INIS)
Cheng, C.Z.
1991-07-01
A hybrid kinetic-MHD model for describing low-frequency phenomena in high beta anisotropic plasmas that consist of two components: a low energy core component and an energetic component with low density. The kinetic-MHD model treats the low energy core component by magnetohydrodynamic (MHD) description, the energetic component by kinetic approach such as the gyrokinetic equation, and the coupling between the dynamics of these two components through plasma pressure in the momentum equation. The kinetic-MHD model optimizes both the physics contents and the theoretical efforts in studying low frequency MHD waves and transport phenomena in general magnetic field geometries, and can be easily modified to include the core plasma kinetic effects if necessary. It is applicable to any magnetized collisionless plasma system where the parallel electric field effects are negligibly small. In the linearized limit two coupled eigenmode equations for describing the coupling between the transverse Alfven type and the compressional Alfven type waves are derived. The eigenmode equations are identical to those derived from the full gyrokinetic equation in the low frequency limit and were previously analyzed both analytically nd numerically to obtain the eigenmode structure of the drift mirror instability which explains successfully the multi-satellite observation of antisymmetric field-aligned structure of the compressional magnetic field of Pc 5 waves in the magnetospheric ring current plasma. Finally, a quadratic form is derived to demonstrate the stability of the low-frequency transverse and compressional Alfven type instabilities in terms of the pressure anisotropy parameter τ and the magnetic field curvature-pressure gradient parameter. A procedure for determining the stability of a marginally stable MHD wave due to wave-particle resonances is also presented
Kinetic modeling of Nernst effect in magnetized hohlraums.
Joglekar, A S; Ridgers, C P; Kingham, R J; Thomas, A G R
2016-04-01
We present nanosecond time-scale Vlasov-Fokker-Planck-Maxwell modeling of magnetized plasma transport and dynamics in a hohlraum with an applied external magnetic field, under conditions similar to recent experiments. Self-consistent modeling of the kinetic electron momentum equation allows for a complete treatment of the heat flow equation and Ohm's law, including Nernst advection of magnetic fields. In addition to showing the prevalence of nonlocal behavior, we demonstrate that effects such as anomalous heat flow are induced by inverse bremsstrahlung heating. We show magnetic field amplification up to a factor of 3 from Nernst compression into the hohlraum wall. The magnetic field is also expelled towards the hohlraum axis due to Nernst advection faster than frozen-in flux would suggest. Nonlocality contributes to the heat flow towards the hohlraum axis and results in an augmented Nernst advection mechanism that is included self-consistently through kinetic modeling.
Kinetic models for historical processes of fast invasion and aggression
Aristov, Vladimir V.; Ilyin, Oleg V.
2015-04-01
In the last few decades many investigations have been devoted to theoretical models in new areas concerning description of different biological, sociological, and historical processes. In the present paper we suggest a model of the Nazi Germany invasion of Poland, France, and the USSR based on kinetic theory. We simulate this process with the Cauchy boundary problem for two-element kinetic equations. The solution of the problem is given in the form of a traveling wave. The propagation velocity of a front line depends on the quotient between initial forces concentrations. Moreover it is obtained that the general solution of the model can be expressed in terms of quadratures and elementary functions. Finally it is shown that the front-line velocities agree with the historical data.
Reproducing Phenomenology of Peroxidation Kinetics via Model Optimization
Ruslanov, Anatole D.; Bashylau, Anton V.
2010-06-01
We studied mathematical modeling of lipid peroxidation using a biochemical model system of iron (II)-ascorbate-dependent lipid peroxidation of rat hepatocyte mitochondrial fractions. We found that antioxidants extracted from plants demonstrate a high intensity of peroxidation inhibition. We simplified the system of differential equations that describes the kinetics of the mathematical model to a first order equation, which can be solved analytically. Moreover, we endeavor to algorithmically and heuristically recreate the processes and construct an environment that closely resembles the corresponding natural system. Our results demonstrate that it is possible to theoretically predict both the kinetics of oxidation and the intensity of inhibition without resorting to analytical and biochemical research, which is important for cost-effective discovery and development of medical agents with antioxidant action from the medicinal plants.
Chemistry resolved kinetic flow modeling of TATB based explosives
Vitello, Peter; Fried, Laurence E.; William, Howard; Levesque, George; Souers, P. Clark
2012-03-01
Detonation waves in insensitive, TATB-based explosives are believed to have multiple time scale regimes. The initial burn rate of such explosives has a sub-microsecond time scale. However, significant late-time slow release in energy is believed to occur due to diffusion limited growth of carbon. In the intermediate time scale concentrations of product species likely change from being in equilibrium to being kinetic rate controlled. We use the thermo-chemical code CHEETAH linked to an ALE hydrodynamics code to model detonations. We term our model chemistry resolved kinetic flow, since CHEETAH tracks the time dependent concentrations of individual species in the detonation wave and calculates EOS values based on the concentrations. We present here two variants of our new rate model and comparison with hot, ambient, and cold experimental data for PBX 9502.
Comparisons of hydrodynamic beam models with kinetic treatments
International Nuclear Information System (INIS)
Boyd, J.K.; Mark, J.W.; Sharp, W.M.; Yu, S.S.
1983-01-01
Hydrodynamic models have been derived by Mark and Yu and by others to describe energetic self-pinched beams, such as those used in ion-beam fusion. The closure of the Mark-Yu model is obtained with adiabatic assumptions mathematically analogous to those of Chew, Goldberger, and Low for MHD. The other models treated here use an ideal gas closure and a closure by Newcomb based on an expansion in V/sub th//V/sub z/. Features of these hydrodynamic beam models are compared with a kinetic treatment
Focuss algorithm application in kinetic compartment modeling for PET tracer
International Nuclear Information System (INIS)
Huang Xinrui; Bao Shanglian
2004-01-01
Molecular imaging is in the process of becoming. Its application mostly depends on the molecular discovery process of imaging probes and drugs, from the mouse to the patient, from research to clinical practice. Positron emission tomography (PET) can non-invasively monitor . pharmacokinetic and functional processes of drugs in intact organisms at tracer concentrations by kinetic modeling. It has been known that for all biological systems, linear or nonlinear, if the system is injected by a tracer in a steady state, the distribution of the tracer follows the kinetics of a linear compartmental system, which has sums of exponential solutions. Based on the general compartmental description of the tracer's fate in vivo, we presented a novel kinetic modeling approach for the quantification of in vivo tracer studies with dynamic positron emission tomography (PET), which can determine a parsimonious model consisting with the measured data. This kinetic modeling technique allows for estimation of parametric images from a voxel based analysis and requires no a priori decision about the tracer's fate in vivo, instead determining the most appropriate model from the information contained within the kinetic data. Choosing a set of exponential functions, convolved with the plasma input function, as basis functions, the time activity curve of a region or a pixel can be written as a linear combination of the basis functions with corresponding coefficients. The number of non-zero coefficients returned corresponds to the model order which is related to the number of tissue compartments. The system macro parameters are simply determined using the focal underdetermined system solver (FOCUSS) algorithm. The FOCUSS algorithm is a nonparametric algorithm for finding localized energy solutions from limited data and is a recursive linear estimation procedure. FOCUSS algorithm usually converges very fast, so demands a few iterations. The effectiveness is verified by simulation and clinical
Stepwise kinetic equilibrium models of quantitative polymerase chain reaction
Directory of Open Access Journals (Sweden)
Cobbs Gary
2012-08-01
Full Text Available Abstract Background Numerous models for use in interpreting quantitative PCR (qPCR data are present in recent literature. The most commonly used models assume the amplification in qPCR is exponential and fit an exponential model with a constant rate of increase to a select part of the curve. Kinetic theory may be used to model the annealing phase and does not assume constant efficiency of amplification. Mechanistic models describing the annealing phase with kinetic theory offer the most potential for accurate interpretation of qPCR data. Even so, they have not been thoroughly investigated and are rarely used for interpretation of qPCR data. New results for kinetic modeling of qPCR are presented. Results Two models are presented in which the efficiency of amplification is based on equilibrium solutions for the annealing phase of the qPCR process. Model 1 assumes annealing of complementary targets strands and annealing of target and primers are both reversible reactions and reach a dynamic equilibrium. Model 2 assumes all annealing reactions are nonreversible and equilibrium is static. Both models include the effect of primer concentration during the annealing phase. Analytic formulae are given for the equilibrium values of all single and double stranded molecules at the end of the annealing step. The equilibrium values are then used in a stepwise method to describe the whole qPCR process. Rate constants of kinetic models are the same for solutions that are identical except for possibly having different initial target concentrations. Analysis of qPCR curves from such solutions are thus analyzed by simultaneous non-linear curve fitting with the same rate constant values applying to all curves and each curve having a unique value for initial target concentration. The models were fit to two data sets for which the true initial target concentrations are known. Both models give better fit to observed qPCR data than other kinetic models present in the
Stepwise kinetic equilibrium models of quantitative polymerase chain reaction.
Cobbs, Gary
2012-08-16
Numerous models for use in interpreting quantitative PCR (qPCR) data are present in recent literature. The most commonly used models assume the amplification in qPCR is exponential and fit an exponential model with a constant rate of increase to a select part of the curve. Kinetic theory may be used to model the annealing phase and does not assume constant efficiency of amplification. Mechanistic models describing the annealing phase with kinetic theory offer the most potential for accurate interpretation of qPCR data. Even so, they have not been thoroughly investigated and are rarely used for interpretation of qPCR data. New results for kinetic modeling of qPCR are presented. Two models are presented in which the efficiency of amplification is based on equilibrium solutions for the annealing phase of the qPCR process. Model 1 assumes annealing of complementary targets strands and annealing of target and primers are both reversible reactions and reach a dynamic equilibrium. Model 2 assumes all annealing reactions are nonreversible and equilibrium is static. Both models include the effect of primer concentration during the annealing phase. Analytic formulae are given for the equilibrium values of all single and double stranded molecules at the end of the annealing step. The equilibrium values are then used in a stepwise method to describe the whole qPCR process. Rate constants of kinetic models are the same for solutions that are identical except for possibly having different initial target concentrations. Analysis of qPCR curves from such solutions are thus analyzed by simultaneous non-linear curve fitting with the same rate constant values applying to all curves and each curve having a unique value for initial target concentration. The models were fit to two data sets for which the true initial target concentrations are known. Both models give better fit to observed qPCR data than other kinetic models present in the literature. They also give better estimates of
Tracer kinetic modelling of receptor data with mathematical metabolite correction
International Nuclear Information System (INIS)
Burger, C.; Buck, A.
1996-01-01
Quantitation of metabolic processes with dynamic positron emission tomography (PET) and tracer kinetic modelling relies on the time course of authentic ligand in plasma, i.e. the input curve. The determination of the latter often requires the measurement of labelled metabilites, a laborious procedure. In this study we examined the possibility of mathematical metabolite correction, which might obviate the need for actual metabolite measurements. Mathematical metabilite correction was implemented by estimating the input curve together with kinetic tissue parameters. The general feasibility of the approach was evaluated in a Monte Carlo simulation using a two tissue compartment model. The method was then applied to a series of five human carbon-11 iomazenil PET studies. The measured cerebral tissue time-activity curves were fitted with a single tissue compartment model. For mathematical metabolite correction the input curve following the peak was approximated by a sum of three decaying exponentials, the amplitudes and characteristic half-times of which were then estimated by the fitting routine. In the simulation study the parameters used to generate synthetic tissue time-activity curves (K 1 -k 4 ) were refitted with reasonable identifiability when using mathematical metabolite correciton. Absolute quantitation of distribution volumes was found to be possible provided that the metabolite and the kinetic models are adequate. If the kinetic model is oversimplified, the linearity of the correlation between true and estimated distribution volumes is still maintained, although the linear regression becomes dependent on the input curve. These simulation results were confirmed when applying mathematical metabolite correction to the 11 C iomazenil study. Estimates of the distribution volume calculated with a measured input curve were linearly related to the estimates calculated using mathematical metabolite correction with correlation coefficients >0.990. (orig./MG)
Kinetic models of gene expression including non-coding RNAs
Energy Technology Data Exchange (ETDEWEB)
Zhdanov, Vladimir P., E-mail: zhdanov@catalysis.r
2011-03-15
In cells, genes are transcribed into mRNAs, and the latter are translated into proteins. Due to the feedbacks between these processes, the kinetics of gene expression may be complex even in the simplest genetic networks. The corresponding models have already been reviewed in the literature. A new avenue in this field is related to the recognition that the conventional scenario of gene expression is fully applicable only to prokaryotes whose genomes consist of tightly packed protein-coding sequences. In eukaryotic cells, in contrast, such sequences are relatively rare, and the rest of the genome includes numerous transcript units representing non-coding RNAs (ncRNAs). During the past decade, it has become clear that such RNAs play a crucial role in gene expression and accordingly influence a multitude of cellular processes both in the normal state and during diseases. The numerous biological functions of ncRNAs are based primarily on their abilities to silence genes via pairing with a target mRNA and subsequently preventing its translation or facilitating degradation of the mRNA-ncRNA complex. Many other abilities of ncRNAs have been discovered as well. Our review is focused on the available kinetic models describing the mRNA, ncRNA and protein interplay. In particular, we systematically present the simplest models without kinetic feedbacks, models containing feedbacks and predicting bistability and oscillations in simple genetic networks, and models describing the effect of ncRNAs on complex genetic networks. Mathematically, the presentation is based primarily on temporal mean-field kinetic equations. The stochastic and spatio-temporal effects are also briefly discussed.
Comparison of kinetic model for biogas production from corn cob
Shitophyta, L. M.; Maryudi
2018-04-01
Energy demand increases every day, while the energy source especially fossil energy depletes increasingly. One of the solutions to overcome the energy depletion is to provide renewable energies such as biogas. Biogas can be generated by corn cob and food waste. In this study, biogas production was carried out by solid-state anaerobic digestion. The steps of biogas production were the preparation of feedstock, the solid-state anaerobic digestion, and the measurement of biogas volume. This study was conducted on TS content of 20%, 22%, and 24%. The aim of this research was to compare kinetic models of biogas production from corn cob and food waste as a co-digestion using the linear, exponential equation, and first-kinetic models. The result showed that the exponential equation had a better correlation than the linear equation on the ascending graph of biogas production. On the contrary, the linear equation had a better correlation than the exponential equation on the descending graph of biogas production. The correlation values on the first-kinetic model had the smallest value compared to the linear and exponential models.
Modelling reveals kinetic advantages of co-transcriptional splicing.
Directory of Open Access Journals (Sweden)
Stuart Aitken
2011-10-01
Full Text Available Messenger RNA splicing is an essential and complex process for the removal of intron sequences. Whereas the composition of the splicing machinery is mostly known, the kinetics of splicing, the catalytic activity of splicing factors and the interdependency of transcription, splicing and mRNA 3' end formation are less well understood. We propose a stochastic model of splicing kinetics that explains data obtained from high-resolution kinetic analyses of transcription, splicing and 3' end formation during induction of an intron-containing reporter gene in budding yeast. Modelling reveals co-transcriptional splicing to be the most probable and most efficient splicing pathway for the reporter transcripts, due in part to a positive feedback mechanism for co-transcriptional second step splicing. Model comparison is used to assess the alternative representations of reactions. Modelling also indicates the functional coupling of transcription and splicing, because both the rate of initiation of transcription and the probability that step one of splicing occurs co-transcriptionally are reduced, when the second step of splicing is abolished in a mutant reporter.
Modelling reveals kinetic advantages of co-transcriptional splicing.
Aitken, Stuart; Alexander, Ross D; Beggs, Jean D
2011-10-01
Messenger RNA splicing is an essential and complex process for the removal of intron sequences. Whereas the composition of the splicing machinery is mostly known, the kinetics of splicing, the catalytic activity of splicing factors and the interdependency of transcription, splicing and mRNA 3' end formation are less well understood. We propose a stochastic model of splicing kinetics that explains data obtained from high-resolution kinetic analyses of transcription, splicing and 3' end formation during induction of an intron-containing reporter gene in budding yeast. Modelling reveals co-transcriptional splicing to be the most probable and most efficient splicing pathway for the reporter transcripts, due in part to a positive feedback mechanism for co-transcriptional second step splicing. Model comparison is used to assess the alternative representations of reactions. Modelling also indicates the functional coupling of transcription and splicing, because both the rate of initiation of transcription and the probability that step one of splicing occurs co-transcriptionally are reduced, when the second step of splicing is abolished in a mutant reporter.
Progress in Chemical Kinetic Modeling for Surrogate Fuels
Energy Technology Data Exchange (ETDEWEB)
Pitz, W J; Westbrook, C K; Herbinet, O; Silke, E J
2008-06-06
Gasoline, diesel, and other alternative transportation fuels contain hundreds to thousands of compounds. It is currently not possible to represent all these compounds in detailed chemical kinetic models. Instead, these fuels are represented by surrogate fuel models which contain a limited number of representative compounds. We have been extending the list of compounds for detailed chemical models that are available for use in fuel surrogate models. Detailed models for components with larger and more complicated fuel molecular structures are now available. These advancements are allowing a more accurate representation of practical and alternative fuels. We have developed detailed chemical kinetic models for fuels with higher molecular weight fuel molecules such as n-hexadecane (C16). Also, we can consider more complicated fuel molecular structures like cyclic alkanes and aromatics that are found in practical fuels. For alternative fuels, the capability to model large biodiesel fuels that have ester structures is becoming available. These newly addressed cyclic and ester structures in fuels profoundly affect the reaction rate of the fuel predicted by the model. Finally, these surrogate fuel models contain large numbers of species and reactions and must be reduced for use in multi-dimensional models for spark-ignition, HCCI and diesel engines.
Mechanisms and kinetics models for ultrasonic waste activated sludge disintegration.
Wang, Fen; Wang, Yong; Ji, Min
2005-08-31
Ultrasonic energy can be applied as pre-treatment to disintegrate sludge flocs and disrupt bacterial cells' walls, and the hydrolysis can be improved, so that the rate of sludge digestion and methane production is improved. In this paper, by adding NaHCO3 to mask the oxidizing effect of OH, the mechanisms of disintegration are investigated. In addition, kinetics models for ultrasonic sludge disintegration are established by applying multi-variable linear regression method. It has been found that hydro-mechanical shear forces predominantly responsible for the disintegration, and the contribution of oxidizing effect of OH increases with the amount of the ultrasonic density and ultrasonic intensity. It has also been inferred from the kinetics model which dependent variable is SCOD+ that both sludge pH and sludge concentration significantly affect the disintegration.
A kinetic model for the first stage of pygas upgrading
Directory of Open Access Journals (Sweden)
J. L. de Medeiros
2007-03-01
Full Text Available Pyrolysis gasoline - PYGAS - is an intermediate boiling product of naphtha steam cracking with a high octane number and high aromatic/unsaturated contents. Due to stabilization concerns, PYGAS must be hydrotreated in two stages. The first stage uses a mild trickle-bed conversion for removing extremely reactive species (styrene, dienes and olefins prior to the more severe second stage where sulfured and remaining olefins are hydrogenated in gas phase. This work addresses the reaction network and two-phase kinetic model for the first stage of PYGAS upgrading. Nonlinear estimation was used for model tuning with kinetic data obtained in bench-scale trickle-bed hydrogenation with a commercial Pd/Al2O3 catalyst. On-line sampling experiments were designed to study the influence of variables - temperature and spatial velocity - on the conversion of styrene, dienes and olefins.
Polar Coordinate Lattice Boltzmann Kinetic Modeling of Detonation Phenomena
International Nuclear Information System (INIS)
Lin Chuan-Dong; Li Ying-Jun; Xu Ai-Guo; Zhang Guang-Cai
2014-01-01
A novel polar coordinate lattice Boltzmann kinetic model for detonation phenomena is presented and applied to investigate typical implosion and explosion processes. In this model, the change of discrete distribution function due to local chemical reaction is dynamically coupled into the modified lattice Boltzmann equation which could recover the Navier—Stokes equations, including contribution of chemical reaction, via the Chapman—Enskog expansion. For the numerical investigations, the main focuses are the nonequilibrium behaviors in these processes. The system at the disc center is always in its thermodynamic equilibrium in the highly symmetric case. The internal kinetic energies in different degrees of freedom around the detonation front do not coincide. The dependence of the reaction rate on the pressure, influences of the shock strength and reaction rate on the departure amplitude of the system from its local thermodynamic equilibrium are probed. (electromagnetism, optics, acoustics, heat transfer, classical mechanics, and fluid dynamics)
Kinetics approach to modeling of polymer additive degradation in lubricants
Institute of Scientific and Technical Information of China (English)
llyaI.KUDISH; RubenG.AIRAPETYAN; Michael; J.; COVITCH
2001-01-01
A kinetics problem for a degrading polymer additive dissolved in a base stock is studied.The polymer degradation may be caused by the combination of such lubricant flow parameters aspressure, elongational strain rate, and temperature as well as lubricant viscosity and the polymercharacteristics (dissociation energy, bead radius, bond length, etc.). A fundamental approach tothe problem of modeling mechanically induced polymer degradation is proposed. The polymerdegradation is modeled on the basis of a kinetic equation for the density of the statistical distribu-tion of polymer molecules as a function of their molecular weight. The integrodifferential kineticequation for polymer degradation is solved numerically. The effects of pressure, elongational strainrate, temperature, and lubricant viscosity on the process of lubricant degradation are considered.The increase of pressure promotes fast degradation while the increase of temperature delaysdegradation. A comparison of a numerically calculated molecular weight distribution with an ex-perimental one obtained in bench tests showed that they are in excellent agreement with eachother.
Kinetic modelling of radiochemical ageing of ethylene-propylene copolymers
International Nuclear Information System (INIS)
Colin, Xavier; Richaud, Emmanuel; Verdu, Jacques; Monchy-Leroy, Carole
2010-01-01
A non-empirical kinetic model has been built for describing the general trends of radiooxidation kinetics of ethylene-propylene copolymers (EPR) at low γ dose rate and low temperature. It is derived from a radical chain oxidation mechanism composed of 30 elementary reactions: 19 relative to oxidation of methylene and methyne units plus 11 relative to their eventual cooxidation. The validity of this model has been already checked successfully elsewhere for one homopolymer: polyethylene (PE) (; ). In the present study, it is now checked for polypropylene (PP) and a series of three EPR differing essentially by their mole fraction of ethylene (37%, 73% and 86%) and their crystallinity degree (0%, 5% and 26%). Predicted values of radiation-chemical yields are in good agreement with experimental ones published in the last half past century.
Kinetic modeling and exploratory numerical simulation of chloroplastic starch degradation
Directory of Open Access Journals (Sweden)
Nag Ambarish
2011-06-01
Full Text Available Abstract Background Higher plants and algae are able to fix atmospheric carbon dioxide through photosynthesis and store this fixed carbon in large quantities as starch, which can be hydrolyzed into sugars serving as feedstock for fermentation to biofuels and precursors. Rational engineering of carbon flow in plant cells requires a greater understanding of how starch breakdown fluxes respond to variations in enzyme concentrations, kinetic parameters, and metabolite concentrations. We have therefore developed and simulated a detailed kinetic ordinary differential equation model of the degradation pathways for starch synthesized in plants and green algae, which to our knowledge is the most complete such model reported to date. Results Simulation with 9 internal metabolites and 8 external metabolites, the concentrations of the latter fixed at reasonable biochemical values, leads to a single reference solution showing β-amylase activity to be the rate-limiting step in carbon flow from starch degradation. Additionally, the response coefficients for stromal glucose to the glucose transporter kcat and KM are substantial, whereas those for cytosolic glucose are not, consistent with a kinetic bottleneck due to transport. Response coefficient norms show stromal maltopentaose and cytosolic glucosylated arabinogalactan to be the most and least globally sensitive metabolites, respectively, and β-amylase kcat and KM for starch to be the kinetic parameters with the largest aggregate effect on metabolite concentrations as a whole. The latter kinetic parameters, together with those for glucose transport, have the greatest effect on stromal glucose, which is a precursor for biofuel synthetic pathways. Exploration of the steady-state solution space with respect to concentrations of 6 external metabolites and 8 dynamic metabolite concentrations show that stromal metabolism is strongly coupled to starch levels, and that transport between compartments serves to
A Consensus Genome-scale Reconstruction of Chinese Hamster Ovary Cell Metabolism
Hefzi, Hooman
2016-11-23
Chinese hamster ovary (CHO) cells dominate biotherapeutic protein production and are widely used in mammalian cell line engineering research. To elucidate metabolic bottlenecks in protein production and to guide cell engineering and bioprocess optimization, we reconstructed the metabolic pathways in CHO and associated them with >1,700 genes in the Cricetulus griseus genome. The genome-scale metabolic model based on this reconstruction, iCHO1766, and cell-line-specific models for CHO-K1, CHO-S, and CHO-DG44 cells provide the biochemical basis of growth and recombinant protein production. The models accurately predict growth phenotypes and known auxotrophies in CHO cells. With the models, we quantify the protein synthesis capacity of CHO cells and demonstrate that common bioprocess treatments, such as histone deacetylase inhibitors, inefficiently increase product yield. However, our simulations show that the metabolic resources in CHO are more than three times more efficiently utilized for growth or recombinant protein synthesis following targeted efforts to engineer the CHO secretory pathway. This model will further accelerate CHO cell engineering and help optimize bioprocesses.
A model for recovery kinetics of aluminum after large strain
DEFF Research Database (Denmark)
Yu, Tianbo; Hansen, Niels
2012-01-01
A model is suggested to analyze recovery kinetics of heavily deformed aluminum. The model is based on the hardness of isothermal annealed samples before recrystallization takes place, and it can be extrapolated to longer annealing times to factor out the recrystallization component of the hardness...... for conditions where recovery and recrystallization overlap. The model is applied to the isothermal recovery at temperatures between 140 and 220°C of commercial purity aluminum deformed to true strain 5.5. EBSD measurements have been carried out to detect the onset of discontinuous recrystallization. Furthermore...
An experimental and kinetic modeling study of glycerol pyrolysis
International Nuclear Information System (INIS)
Fantozzi, F.; Frassoldati, A.; Bartocci, P.; Cinti, G.; Quagliarini, F.; Bidini, G.; Ranzi, E.M.
2016-01-01
Highlights: • Glycerol pyrolysis can produce about 44–48%v hydrogen at 750–800 °C. • A simplified 452 reactions kinetic model of glycerol pyrolysis has been developed. • The model has good agreement with experimental data. • Non condensable gas yields can reach 70%. - Abstract: Pyrolysis of glycerol, a by-product of the biodiesel industry, is an important potential source of hydrogen. The obtained high calorific value gas can be used either as a fuel for combined heat and power (CHP) generation or as a transportation fuel (for example hydrogen to be used in fuel cells). Optimal process conditions can improve glycerol pyrolysis by increasing gas yield and hydrogen concentration. A detailed kinetic mechanism of glycerol pyrolysis, which involves 137 species and more than 4500 reactions, was drastically simplified and reduced to a new skeletal kinetic scheme of 44 species, involved in 452 reactions. An experimental campaign with a batch pyrolysis reactor was properly designed to further validate the original and the skeletal mechanisms. The comparisons between model predictions and experimental data strongly suggest the presence of a catalytic process promoting steam reforming of methane. High pyrolysis temperatures (750–800 °C) improve process performances and non-condensable gas yields of 70%w can be achieved. Hydrogen mole fraction in pyrolysis gas is about 44–48%v. The skeletal mechanism developed can be easily used in Computational Fluid Dynamic software, reducing the simulation time.
Modelling of individual subject ozone exposure response kinetics.
Schelegle, Edward S; Adams, William C; Walby, William F; Marion, M Susan
2012-06-01
A better understanding of individual subject ozone (O(3)) exposure response kinetics will provide insight into how to improve models used in the risk assessment of ambient ozone exposure. To develop a simple two compartment exposure-response model that describes individual subject decrements in forced expiratory volume in one second (FEV(1)) induced by the acute inhalation of O(3) lasting up to 8 h. FEV(1) measurements of 220 subjects who participated in 14 previously completed studies were fit to the model using both particle swarm and nonlinear least squares optimization techniques to identify three subject-specific coefficients producing minimum "global" and local errors, respectively. Observed and predicted decrements in FEV(1) of the 220 subjects were used for validation of the model. Further validation was provided by comparing the observed O(3)-induced FEV(1) decrements in an additional eight studies with predicted values obtained using model coefficients estimated from the 220 subjects used in cross validation. Overall the individual subject measured and modeled FEV(1) decrements were highly correlated (mean R(2) of 0.69 ± 0.24). In addition, it was shown that a matrix of individual subject model coefficients can be used to predict the mean and variance of group decrements in FEV(1). This modeling approach provides insight into individual subject O(3) exposure response kinetics and provides a potential starting point for improving the risk assessment of environmental O(3) exposure.
Kinetic modeling of ethylbenzene dehydrogenation over hydrotalcite catalysts
Atanda, Luqman
2011-07-01
Kinetics of ethylbenzene dehydrogenation to styrene was investigated over a series of quaternary mixed oxides of Mg3Fe0.25Me0.25Al0.5 (Me=Co, Mn and Ni) catalysts prepared by calcination of hydrotalcite-like compounds and compared with commercial catalyst. The study was carried out in the absence of steam using a riser simulator at 400, 450, 500 and 550°C for reaction times of 5, 10, 15 and 20s. Mg3Fe0.25Mn0.25Al0.5 afforded the highest ethylbenzene conversion of 19.7% at 550°C. Kinetic parameters for the dehydrogenation process were determined using the catalyst deactivation function based on reactant conversion model. The apparent activation energies for styrene production were found to decrease as follows: E1-Ni>E1-Co>E1-Mn. © 2011 Elsevier B.V.
Kinetic modelling and mechanism of dye adsorption on unburned carbon
Energy Technology Data Exchange (ETDEWEB)
Wang, S.B.; Li, H.T. [Curtin University of Technology, Perth, WA (Australia). Dept. of Chemical Engineering
2007-07-01
Textile dyeing processes are among the most environmentally unfriendly industrial processes by producing coloured wastewaters. The adsorption method using unburned carbon from coal combustion residue was studied for the decolourisation of typical acidic and basic dyes. It was discovered that the unburned carbon showed high adsorption capacity at 1.97 x 10{sup -4} and 5.27 x 10{sup -4} mol/g for Basic Violet 3 and Acid Black 1, respectively. The solution pH, particle size and temperature significantly influenced the adsorption capacity. Higher solution pH favoured the adsorption of basic dye while reduced the adsorption of acid dye. The adsorption of dye increased with increasing temperature but decreased with increasing particle size. Sorption kinetic data indicated that the adsorption kinetics followed the pseudo-second-order model. The adsorption mechanism consisted of two processes, external diffusion and intraparticle diffusion, and the external diffusion was the dominating process.
A neural model of border-ownership from kinetic occlusion.
Layton, Oliver W; Yazdanbakhsh, Arash
2015-01-01
Camouflaged animals that have very similar textures to their surroundings are difficult to detect when stationary. However, when an animal moves, humans readily see a figure at a different depth than the background. How do humans perceive a figure breaking camouflage, even though the texture of the figure and its background may be statistically identical in luminance? We present a model that demonstrates how the primate visual system performs figure-ground segregation in extreme cases of breaking camouflage based on motion alone. Border-ownership signals develop as an emergent property in model V2 units whose receptive fields are nearby kinetically defined borders that separate the figure and background. Model simulations support border-ownership as a general mechanism by which the visual system performs figure-ground segregation, despite whether figure-ground boundaries are defined by luminance or motion contrast. The gradient of motion- and luminance-related border-ownership signals explains the perceived depth ordering of the foreground and background surfaces. Our model predicts that V2 neurons, which are sensitive to kinetic edges, are selective to border-ownership (magnocellular B cells). A distinct population of model V2 neurons is selective to border-ownership in figures defined by luminance contrast (parvocellular B cells). B cells in model V2 receive feedback from neurons in V4 and MT with larger receptive fields to bias border-ownership signals toward the figure. We predict that neurons in V4 and MT sensitive to kinetically defined figures play a crucial role in determining whether the foreground surface accretes, deletes, or produces a shearing motion with respect to the background. Copyright © 2014 Elsevier Ltd. All rights reserved.
The modelling of direct chemical kinetic effects in turbulent flames
Energy Technology Data Exchange (ETDEWEB)
Lindstet, R.P. [Imperial College of Science, Technology and Medicine, London (United Kingdom). Dept. of Mechanical Engineering
2000-06-01
Combustion chemistry-related effects have traditionally been of secondary importance in the design of gas turbine combustors. However, the need to deal with issues such as flame stability, relight and pollutant emissions has served to bring chemical kinetics and the coupling of finite rate chemistry with turbulent flow fields to the centre of combustor design. Indeed, improved cycle efficiency and more stringent environmental legislation, as defined by the ICAO, are current key motivators in combustor design. Furthermore, lean premixed prevaporized (LPP) combustion systems, increasingly used for power generation, often operate close to the lean blow-off limit and are prone to extinction/reignition type phenomena. Thus, current key design issues require that direct chemical kinetic effects be accounted for accurately in any simulation procedure. The transported probability density function (PDF) approach uniquely offers the potential of facilitating the accurate modelling of such effects. The present paper thus assesses the ability of this technique to model kinetically controlled phenomena, such as carbon monoxide emissions and flame blow-off, through the application of a transported PDF method closed at the joint scalar level. The closure for the velocity field is at the second moment level, and a key feature of the present work is the use of comprehensive chemical kinetic mechanisms. The latter are derived from recent work by Lindstedt and co-workers that has resulted in a compact 141 reactions and 28 species mechanism for LNG combustion. The systematically reduced form used here features 14 independent C/H/O scalars, with the remaining species incorporated via steady state approximations. Computations have been performed for hydrogen/carbon dioxide and methane flames. The former (high Reynolds number) flames permit an assessment of the modelling of flame blow-off, and the methane flame has been selected to obtain an indication of the influence of differential
An enhanced Brinson model with modified kinetics for martensite transformation
Energy Technology Data Exchange (ETDEWEB)
Kim, Young-Jin; Lee, Jung Ju [Korea Advanced Institute of Science and Technology, Daejeon (Korea, Republic of); Jeong, Ju-Won [Korea Aerospace Research Institute, Daejeon (Korea, Republic of); Lim, Jae Hyuk [Chonbuk National University, Jeonju (Korea, Republic of)
2017-03-15
We propose an enhanced Brinson model with modified kinetics for martensite transformation. Two additional material constants are considered to follow the stress-temperature diagram above austenite start temperature (As) along with treatment to keep the continuity of the martensite volume fraction and the path dependency of the phase transformation. To demonstrate the performance of the proposed model, we implement this algorithm into ABAQUS user subroutine, then conduct several numerical simulations and compare their results with SMA wire experiments as well as those of three-dimensional SMA constitutive models. From the results, it turns out that the proposed model is as accurate as the three-dimensional models and shows better accuracy over original Brinson model in terms of recovery stress.
A physiologically based kinetic model for bacterial sulfide oxidation.
Klok, Johannes B M; de Graaff, Marco; van den Bosch, Pim L F; Boelee, Nadine C; Keesman, Karel J; Janssen, Albert J H
2013-02-01
In the biotechnological process for hydrogen sulfide removal from gas streams, a variety of oxidation products can be formed. Under natron-alkaline conditions, sulfide is oxidized by haloalkaliphilic sulfide oxidizing bacteria via flavocytochrome c oxidoreductase. From previous studies, it was concluded that the oxidation-reduction state of cytochrome c is a direct measure for the bacterial end-product formation. Given this physiological feature, incorporation of the oxidation state of cytochrome c in a mathematical model for the bacterial oxidation kinetics will yield a physiologically based model structure. This paper presents a physiologically based model, describing the dynamic formation of the various end-products in the biodesulfurization process. It consists of three elements: 1) Michaelis-Menten kinetics combined with 2) a cytochrome c driven mechanism describing 3) the rate determining enzymes of the respiratory system of haloalkaliphilic sulfide oxidizing bacteria. The proposed model is successfully validated against independent data obtained from biological respiration tests and bench scale gas-lift reactor experiments. The results demonstrate that the model is a powerful tool to describe product formation for haloalkaliphilic biomass under dynamic conditions. The model predicts a maximum S⁰ formation of about 98 mol%. A future challenge is the optimization of this bioprocess by improving the dissolved oxygen control strategy and reactor design. Copyright © 2012 Elsevier Ltd. All rights reserved.
Small velocity and finite temperature variations in kinetic relaxation models
Markowich, Peter; Jü ngel, Ansgar; Aoki, Kazuo
2010-01-01
A small Knuden number analysis of a kinetic equation in the diffusive scaling is performed. The collision kernel is of BGK type with a general local Gibbs state. Assuming that the flow velocity is of the order of the Knudsen number, a Hilbert expansion yields a macroscopic model with finite temperature variations, whose complexity lies in between the hydrodynamic and the energy-transport equations. Its mathematical structure is explored and macroscopic models for specific examples of the global Gibbs state are presented. © American Institute of Mathematical Sciences.
Levering, Jennifer; Fiedler, Tomas; Sieg, Antje; van Grinsven, Koen W A; Hering, Silvio; Veith, Nadine; Olivier, Brett G; Klett, Lara; Hugenholtz, Jeroen; Teusink, Bas; Kreikemeyer, Bernd; Kummer, Ursula
2016-08-20
Genome-scale metabolic models comprise stoichiometric relations between metabolites, as well as associations between genes and metabolic reactions and facilitate the analysis of metabolism. We computationally reconstructed the metabolic network of the lactic acid bacterium Streptococcus pyogenes M49. Initially, we based the reconstruction on genome annotations and already existing and curated metabolic networks of Bacillus subtilis, Escherichia coli, Lactobacillus plantarum and Lactococcus lactis. This initial draft was manually curated with the final reconstruction accounting for 480 genes associated with 576 reactions and 558 metabolites. In order to constrain the model further, we performed growth experiments of wild type and arcA deletion strains of S. pyogenes M49 in a chemically defined medium and calculated nutrient uptake and production fluxes. We additionally performed amino acid auxotrophy experiments to test the consistency of the model. The established genome-scale model can be used to understand the growth requirements of the human pathogen S. pyogenes and define optimal and suboptimal conditions, but also to describe differences and similarities between S. pyogenes and related lactic acid bacteria such as L. lactis in order to find strategies to reduce the growth of the pathogen and propose drug targets. Copyright © 2016 Elsevier B.V. All rights reserved.
Norepinephrine metabolism in humans. Kinetic analysis and model
International Nuclear Information System (INIS)
Linares, O.A.; Jacquez, J.A.; Zech, L.A.; Smith, M.J.; Sanfield, J.A.; Morrow, L.A.; Rosen, S.G.; Halter, J.B.
1987-01-01
The present study was undertaken to quantify more precisely and to begin to address the problem of heterogeneity of the kinetics of distribution and metabolism of norepinephrine (NE) in humans, by using compartmental analysis. Steady-state NE specific activity in arterialized plasma during [ 3 H]NE infusion and postinfusion plasma disappearance of [ 3 H]NE were measured in eight healthy subjects in the supine and upright positions. Two exponentials were clearly identified in the plasma [ 3 H]NE disappearance curves of each subject studied in the supine (r = 0.94-1.00, all P less than 0.01) and upright (r = 0.90-0.98, all P less than 0.01) positions. A two-compartment model was the minimal model necessary to simultaneously describe the kinetics of NE in the supine and upright positions. The NE input rate into the extravascular compartment 2, estimated with the minimal model, increased with upright posture (1.87 +/- 0.08 vs. 3.25 +/- 0.2 micrograms/min per m2, P less than 0.001). Upright posture was associated with a fall in the volume of distribution of NE in compartment 1 (7.5 +/- 0.6 vs. 4.7 +/- 0.3 liters, P less than 0.001), and as a result of that, there was a fall in the metabolic clearance rate of NE from compartment 1 (1.80 +/- 0.11 vs. 1.21 +/- 0.08 liters/min per m2, P less than 0.001). We conclude that a two-compartment model is the minimal model that can accurately describe the kinetics of distribution and metabolism of NE in humans
Simultaneous removal of sulfide, nitrate and acetate: Kinetic modeling
International Nuclear Information System (INIS)
Wang Aijie; Liu Chunshuang; Ren Nanqi; Han Hongjun; Lee Duujong
2010-01-01
Biological removal of sulfide, nitrate and chemical oxygen demand (COD) simultaneously from industrial wastewaters to elementary sulfur (S 0 ), N 2 , and CO 2 , or named the denitrifying sulfide (DSR) process, is a cost effective and environmentally friendly treatment process for high strength sulfide and nitrate laden organic wastewater. Kinetic model for the DSR process was established for the first time on the basis of Activated Sludge Model No. 1 (ASM1). The DSR experiments were conducted at influent sulfide concentrations of 200-800 mg/L, whose results calibrate the model parameters. The model correlates well with the DSR process dynamics. By introducing the switch function and the inhibition function, the competition between autotrophic and heterotrophic denitrifiers is quantitatively described and the degree of inhibition of sulfide on heterotrophic denitrifiers is realized. The model output indicates that the DSR reactor can work well at 0.5 1000 mg/L influent sulfide, however, the DSR system will break down.
3D CFD Modeling of the LMF System: Desulfurization Kinetics
Cao, Qing; Pitts, April; Zhang, Daojie; Nastac, Laurentiu; Williams, Robert
A fully transient 3D CFD modeling approach capable of predicting the three phase (gas, slag and steel) fluid flow characteristics and behavior of the slag/steel interface in the argon gas bottom stirred ladle with two off-centered porous plugs (Ladle Metallurgical Furnace or LMF) has been recently developed. The model predicts reasonably well the fluid flow characteristics in the LMF system and the observed size of the slag eyes for both the high-stirring and low-stirring conditions. A desulfurization reaction kinetics model considering metal/slag interface characteristics is developed in conjunction with the CFD modeling approach. The model is applied in this study to determine the effects of processing time, and gas flow rate on the efficiency of desulfurization in the studied LMF system.
Simulation of styrene polymerization reactors: kinetic and thermodynamic modeling
Directory of Open Access Journals (Sweden)
A. S. Almeida
2008-06-01
Full Text Available A mathematical model for the free radical polymerization of styrene is developed to predict the steady-state and dynamic behavior of a continuous process. Special emphasis is given for the kinetic and thermodynamic models, where the most sensitive parameters were estimated using data from an industrial plant. The thermodynamic model is based on a cubic equation of state and a mixing rule applied to the low-pressure vapor-liquid equilibrium of polymeric solutions, suitable for modeling the auto-refrigerated polymerization reactors, which use the vaporization rate to remove the reaction heat from the exothermic reactions. The simulation results show the high predictive capability of the proposed model when compared with plant data for conversion, average molecular weights, polydispersity, melt flow index, and thermal properties for different polymer grades.
Experimental kinetic study and modeling of calcium oxide carbonation
International Nuclear Information System (INIS)
Rouchon, L.
2012-01-01
Anthropogenic carbon dioxide (CO 2 ) emissions, major contributors to the greenhouse effect, are considered as the main cause of global warming. So, decrease of CO 2 emitted by large industrial combustion sources or power plants, is an important scientific goal. One of the approaches is based on CO 2 separation and capture from flue gas, followed by sequestration in a wide range of geological formations. In this aim, CO 2 is captured by sorbents like calcium oxide (CaO) in multi-cycle process of carbonation/de-carbonation. However, it was shown that the most important limitations of such process are related to the reversibility of reaction. CaO rapidly loses activity towards CO 2 , so the maximum extent of carbonation decreases as long as the number of cycles increases. In order to well understand the processes and parameters influencing the capture capacity of CaO-based sorbents, it appears important to get details on the kinetic law governing the reaction, which have not been really studied up to now. To investigate this reaction, CaO carbonation kinetics was followed by means of thermogravimetric analysis (TGA) on divided materials. Special care was given to the validation of the usual kinetic assumptions such as steady state and rate-determining step assumptions. The aim was to obtain a model describing the reaction in order to explain the influence of intensive variables such as carbonation temperature and CO 2 partial pressure. TGA curves obtained under isothermal and isobaric conditions showed an induction period linked to the nucleation process and a strong slowing down of the reaction rate once a given fractional conversion was reached. Both phenomena were observed to depend on carbonation temperature and CO 2 partial pressure. To explain these results, the evolution of texture and microstructure of the solid during the reaction was regarded as essential. Reaction at the grain scale induces a volume increase from CaO to CaCO 3 which causes a change in the
Detailed Modelling of Kinetic Biodegradation Processes in a Laboratory Mmicrocosm
Watson, I.; Oswald, S.; Banwart, S.; Mayer, U.
2003-04-01
Biodegradation of organic contaminants in soil and groundwater usually takes places via different redox processes happening sequentially as well as simultaneously. We used numerical modelling of a long-term lab microcosm experiment to simulate the dynamic behaviour of fermentation and respiration in the aqueous phase in contact with the sandstone material, and to develop a conceptual model describing these processes. Aqueous speciation, surface complexation, mineral dissolution and precipitation were taken into account also. Fermentation can be the first step of the degradation process producing intermediate species, which are subsequently consumed by TEAPs. Microbial growth and substrate utilisation kinetics are coupled via a formulation that also includes aqueous speciation and other geochemical reactions including surface complexation, mineral dissolution and precipitation. Competitive exclusion between TEAPs is integral to the conceptual model of the simulation, and the results indicate that exclusion is not complete, but some overlap is found between TEAPs. The model was used to test approaches like the partial equilibrium approach that currently make use of hydrogen levels to diagnose prevalent TEAPs in groundwater. The observed pattern of hydrogen and acetate concentrations were reproduced well by the simulations, and the results show the relevance of kinetics, lag times and inhibition, and especially that intermediate products play a key role.
Modeling texture kinetics during thermal processing of potato products.
Moyano, P C; Troncoso, E; Pedreschi, F
2007-03-01
A kinetic model based on 2 irreversible serial chemical reactions has been proposed to fit experimental data of texture changes during thermal processing of potato products. The model links dimensionless maximum force F*(MAX) with processing time. Experimental texture changes were obtained during frying of French fries and potato chips at different temperatures, while literature data for blanching/cooking of potato cubes have been considered. A satisfactory agreement between experimental and predicted values was observed, with root mean square values (RMSs) in the range of 4.7% to 16.4% for French fries and 16.7% to 29.3% for potato chips. In the case of blanching/cooking, the proposed model gave RMSs in the range of 1.2% to 17.6%, much better than the 6.2% to 44.0% obtained with the traditional 1st-order kinetics. The model is able to predict likewise the transition from softening to hardening of the tissue during frying.
Modeling of subtle kinetic processes in plasma simulation
International Nuclear Information System (INIS)
Sydora, R.D.; Decyk, V.K.; Dawson, J.M.
1988-01-01
A new diagnostic method for plasma simulation models is presented which enables one to probe the subtle dielectric properties of the plasma medium. The procedure involves the removal of the background plasma response in order to isolate the effects of small perturbing influences which are externally added. We have found the technique accurately describes fundamental kinetic plasma behavior such as the shielding of individual test charges and currents. Wave emission studies and drag of test particles has been carried out in explicit particle algorithms as well as large time step implicit and gyrokinetic models. Accurate plasma behavior is produced and it is possible to investigate in detail, processes which can be compared with plasma kinetic theory. The technique of subtraction is not only limited to particle simulation models but also can be used in MHD or fluid models where resolution is difficult due to the intensity of the background response relative to the phenomena one is interested in measuring, such as a weakly grouwing instability or nonlinear mode coupling effect. (author)
Mathematical Modeling of Conversion Kinetics during Vitrification of Nuclear Waste
International Nuclear Information System (INIS)
Pokorny, Richard; Pierce, David A.; Chun, Jae Hun; Hrma, Pavel
2012-01-01
The last part of the high-level waste (HLW) glass melter that has not yet been fully understood, not to mention mathematically modeled, is the cold cap. Cold cap is a layer of dry melter feed, a mixture of the HLW with glass forming and modifying additives. It floats on the pool of molten glass from which it receives the heat necessary for melting. Mathematical modeling of the cold cap solves differential equations that express the mass and energy balances for the feed-to-glass conversion within the cold cap. The feed-to-glass conversion consists of multiple chemical reactions and phase transitions. Reaction enthalpies and mass losses to gases evolved provide an important input for the cold cap modeling. In this study, we measured the kinetics of cold cap reactions using the non-isothermal thermo-gravimetric analysis (TGA) and differential scanning calorimetry (DSC). These thermoanalytical techniques show multiple overlapping peaks, necessitating the development of a deconvolution method for the determination of the kinetics of major reactions needed for cold cap modeling. Assuming that the cold cap reactions are independent, we expressed the overall rate as a sum of rates of individual reactions that we treat as Arrheniustype processes with a power-law based kinetics. Accordingly, we fitted to experimental data the following equation: dx/dT=1/Φ N Σ 1 w i A i (1-x i ) ni exp(-B i /T) (1) where x is the fraction of material reacted, T is temperature, Φ is the heating rate, wi the weight of the i th reaction (the fraction of the total mass loss caused by the i th reaction), Ai is the i th reaction pre-exponential factor, B i is the i th reaction activation energy, and n i is the i th reaction (apparent) reaction order. Because HLW melter feeds contain a large number of constituents, such as oxides, acids, hydroxides, oxyhydrates, and ionic salts, the number of cold cap reactions is very large indeed. For example, hydroxides, oxyhydrates, boric acid, and various
Improved point-kinetics model for the BWR control rod drop accident
International Nuclear Information System (INIS)
Neogy, P.; Wakabayashi, T.; Carew, J.F.
1985-01-01
A simple prescription to account for spatial feedback weighting effects in RDA (rod drop accident) point-kinetics analyses has been derived and tested. The point-kinetics feedback model is linear in the core peaking factor, F/sub Q/, and in the core average void fraction and fuel temperature. Comparison with detailed spatial kinetics analyses indicates that the improved point-kinetics model provides an accurate description of the BWR RDA
Bona Fide Thermodynamic Temperature in Nonequilibrium Kinetic Ising Models
Sastre, Francisco; Dornic, Ivan; Chaté, Hugues
2003-01-01
We show that a nominal temperature can be consistently and uniquely defined everywhere in the phase diagram of large classes of nonequilibrium kinetic Ising spin models. In addition, we confirm the recent proposal that, at critical points, the large-time ``fluctuation-dissipation ratio'' $X_\\infty$ is a universal amplitude ratio and find in particular $X_\\infty \\approx 0.33(2)$ and $X_\\infty = 1/2$ for the magnetization in, respectively, the two-dimensional Ising and voter universality classes.
Application of Detailed Chemical Kinetics to Combustion Instability Modeling
2016-01-04
Clearance Number 15692 Clearance Date 12/3/2015 14. ABSTRACT A comparison of a single step global reaction and the detailed GRI -Mech 1.2 for combustion...comparison of a single step global reaction and the detailed GRI -Mech 1.2 for com- bustion instability modeling in a methane-fueled longitudinal-mode...methane as the fuel. We use the GRI -Mech 1.2 kinetics mechanism for methane oxidation.11 The GRI -Mech 1.2 was chosen over 2.11 because the only
Ensembl Genomes: an integrative resource for genome-scale data from non-vertebrate species.
Kersey, Paul J; Staines, Daniel M; Lawson, Daniel; Kulesha, Eugene; Derwent, Paul; Humphrey, Jay C; Hughes, Daniel S T; Keenan, Stephan; Kerhornou, Arnaud; Koscielny, Gautier; Langridge, Nicholas; McDowall, Mark D; Megy, Karine; Maheswari, Uma; Nuhn, Michael; Paulini, Michael; Pedro, Helder; Toneva, Iliana; Wilson, Derek; Yates, Andrew; Birney, Ewan
2012-01-01
Ensembl Genomes (http://www.ensemblgenomes.org) is an integrative resource for genome-scale data from non-vertebrate species. The project exploits and extends technology (for genome annotation, analysis and dissemination) developed in the context of the (vertebrate-focused) Ensembl project and provides a complementary set of resources for non-vertebrate species through a consistent set of programmatic and interactive interfaces. These provide access to data including reference sequence, gene models, transcriptional data, polymorphisms and comparative analysis. Since its launch in 2009, Ensembl Genomes has undergone rapid expansion, with the goal of providing coverage of all major experimental organisms, and additionally including taxonomic reference points to provide the evolutionary context in which genes can be understood. Against the backdrop of a continuing increase in genome sequencing activities in all parts of the tree of life, we seek to work, wherever possible, with the communities actively generating and using data, and are participants in a growing range of collaborations involved in the annotation and analysis of genomes.
Construction and analysis of a genome-scale metabolic network for Bacillus licheniformis WX-02.
Guo, Jing; Zhang, Hong; Wang, Cheng; Chang, Ji-Wei; Chen, Ling-Ling
2016-05-01
We constructed the genome-scale metabolic network of Bacillus licheniformis (B. licheniformis) WX-02 by combining genomic annotation, high-throughput phenotype microarray (PM) experiments and literature-based metabolic information. The accuracy of the metabolic network was assessed by an OmniLog PM experiment. The final metabolic model iWX1009 contains 1009 genes, 1141 metabolites and 1762 reactions, and the predicted metabolic phenotypes showed an agreement rate of 76.8% with experimental PM data. In addition, key metabolic features such as growth yield, utilization of different substrates and essential genes were identified by flux balance analysis. A total of 195 essential genes were predicted from LB medium, among which 149 were verified with the experimental essential gene set of B. subtilis 168. With the removal of 5 reactions from the network, pathways for poly-γ-glutamic acid (γ-PGA) synthesis were optimized and the γ-PGA yield reached 83.8 mmol/h. Furthermore, the important metabolites and pathways related to γ-PGA synthesis and bacterium growth were comprehensively analyzed. The present study provides valuable clues for exploring the metabolisms and metabolic regulation of γ-PGA synthesis in B. licheniformis WX-02. Copyright © 2016 Institut Pasteur. Published by Elsevier Masson SAS. All rights reserved.
Directory of Open Access Journals (Sweden)
Hong Yang
2014-09-01
Full Text Available Transposon mutagenesis, in combination with parallel sequencing, is becoming a powerful tool for en-masse mutant analysis. A probability generating function was used to explain observed miniHimar transposon insertion patterns, and gene essentiality calls were made by transposon insertion frequency analysis (TIFA. TIFA incorporated the observed genome and sequence motif bias of the miniHimar transposon. The gene essentiality calls were compared to: 1 previous genome-wide direct gene-essentiality assignments; and, 2 flux balance analysis (FBA predictions from an existing genome-scale metabolic model of Shewanella oneidensis MR-1. A three-way comparison between FBA, TIFA, and the direct essentiality calls was made to validate the TIFA approach. The refinement in the interpretation of observed transposon insertions demonstrated that genes without insertions are not necessarily essential, and that genes that contain insertions are not always nonessential. The TIFA calls were in reasonable agreement with direct essentiality calls for S. oneidensis, but agreed more closely with E. coli essentiality calls for orthologs. The TIFA gene essentiality calls were in good agreement with the MR-1 FBA essentiality predictions, and the agreement between TIFA and FBA predictions was substantially better than between the FBA and the direct gene essentiality predictions.
A new kinetic model for human iodine metabolism
International Nuclear Information System (INIS)
Ficken, V.J.; Allen, E.W.; Adams, G.D.
1985-01-01
A new kinetic model of iodine metabolism incorporating preferential organification of tyrosil (TYR) residues of thyroglobulin is developed and evaluated for euthyroid (n=5) and hyperthyroid (n=11) subjects. Iodine and peripheral T4 metabolims were measured with oral /sup 131/I-NaI and intravenous /sup 125/I-74 respectively. Data (obtained over 10 days) and kinetic model are analyzed using the SAAM27 program developed by Berman (1978). Compartment rate constants (mean rate per hour +- ISD) are tabulated in this paper. Thyroid and renal iodide clearance compare favorably with values reported in the literature. TYR rate constants were not unique; however, values obtained are within the range of rate constants determined from the invitro data reported by others. Intraluminal iodine as coupled TYR is predicted to be 21% for euthyroid and 59% for hyperthyroid subjects compared to analytical chemical methods of 30% and 51% respectively determined elsewhere. The authors plan to evaluate this model as a method of predicting the thyroid radiation dose from orally administered I/sup 131/
Genome-scale metabolic analysis of Clostridium thermocellum for bioethanol production
Directory of Open Access Journals (Sweden)
Brooks J Paul
2010-03-01
Full Text Available Abstract Background Microorganisms possess diverse metabolic capabilities that can potentially be leveraged for efficient production of biofuels. Clostridium thermocellum (ATCC 27405 is a thermophilic anaerobe that is both cellulolytic and ethanologenic, meaning that it can directly use the plant sugar, cellulose, and biochemically convert it to ethanol. A major challenge in using microorganisms for chemical production is the need to modify the organism to increase production efficiency. The process of properly engineering an organism is typically arduous. Results Here we present a genome-scale model of C. thermocellum metabolism, iSR432, for the purpose of establishing a computational tool to study the metabolic network of C. thermocellum and facilitate efforts to engineer C. thermocellum for biofuel production. The model consists of 577 reactions involving 525 intracellular metabolites, 432 genes, and a proteomic-based representation of a cellulosome. The process of constructing this metabolic model led to suggested annotation refinements for 27 genes and identification of areas of metabolism requiring further study. The accuracy of the iSR432 model was tested using experimental growth and by-product secretion data for growth on cellobiose and fructose. Analysis using this model captures the relationship between the reduction-oxidation state of the cell and ethanol secretion and allowed for prediction of gene deletions and environmental conditions that would increase ethanol production. Conclusions By incorporating genomic sequence data, network topology, and experimental measurements of enzyme activities and metabolite fluxes, we have generated a model that is reasonably accurate at predicting the cellular phenotype of C. thermocellum and establish a strong foundation for rational strain design. In addition, we are able to draw some important conclusions regarding the underlying metabolic mechanisms for observed behaviors of C. thermocellum
Kinetic modeling of ethane pyrolysis at high conversion.
Xu, Chen; Al Shoaibi, Ahmed Sultan; Wang, Chenguang; Carstensen, Hans-Heinrich; Dean, Anthony M
2011-09-29
The primary objective of this study is to develop an improved first-principle-based mechanism that describes the molecular weight growth kinetics observed during ethane pyrolysis. A proper characterization of the kinetics of ethane pyrolysis is a prerequisite for any analysis of hydrocarbon pyrolysis and oxidation. Flow reactor experiments were performed with ~50/50 ethane/nitrogen mixtures with temperatures ranging from 550 to 850 °C at an absolute pressure of ~0.8 atm and a residence time of ~5 s. These conditions result in ethane conversions ranging from virtually no reaction to ~90%. Comparisons of predictions using our original mechanism to these data yielded very satisfactory results in terms of the temperature dependence of ethane conversion and prediction of the major products ethylene and hydrogen. However, there were discrepancies in some of the minor species concentrations that are involved in the molecular weight growth kinetics. We performed a series of CBS-QB3 analyses for the C(3)H(7), C(4)H(7), and C(4)H(9) potential energy surfaces to better characterize the radical addition reactions that lead to molecular weight growth. We also extended a published C(6)H(9) PES to include addition of vinyl to butadiene. The results were then used to calculate pressure-dependent rate constants for the multiple reaction pathways of these addition reactions. Inclusion of the unadjusted rate constants resulting from these analyses in the mechanism significantly improved the description of several of the species involved in molecular weight growth kinetics. We compare the predictions of this improved model to those obtained with a consensus model recently published as well as to ethane steam cracking data. We find that a particularly important reaction is that of vinyl addition to butadiene. Another important observation is that several radical addition reactions are partially equilibrated. Not only does this mean that reliable thermodynamic parameters are essential
Characterizing steady states of genome-scale metabolic networks in continuous cell cultures.
Directory of Open Access Journals (Sweden)
Jorge Fernandez-de-Cossio-Diaz
2017-11-01
Full Text Available In the continuous mode of cell culture, a constant flow carrying fresh media replaces culture fluid, cells, nutrients and secreted metabolites. Here we present a model for continuous cell culture coupling intra-cellular metabolism to extracellular variables describing the state of the bioreactor, taking into account the growth capacity of the cell and the impact of toxic byproduct accumulation. We provide a method to determine the steady states of this system that is tractable for metabolic networks of arbitrary complexity. We demonstrate our approach in a toy model first, and then in a genome-scale metabolic network of the Chinese hamster ovary cell line, obtaining results that are in qualitative agreement with experimental observations. We derive a number of consequences from the model that are independent of parameter values. The ratio between cell density and dilution rate is an ideal control parameter to fix a steady state with desired metabolic properties. This conclusion is robust even in the presence of multi-stability, which is explained in our model by a negative feedback loop due to toxic byproduct accumulation. A complex landscape of steady states emerges from our simulations, including multiple metabolic switches, which also explain why cell-line and media benchmarks carried out in batch culture cannot be extrapolated to perfusion. On the other hand, we predict invariance laws between continuous cell cultures with different parameters. A practical consequence is that the chemostat is an ideal experimental model for large-scale high-density perfusion cultures, where the complex landscape of metabolic transitions is faithfully reproduced.
Rotational and divergent kinetic energy in the mesoscale model ALADIN
Directory of Open Access Journals (Sweden)
V. Blažica
2013-03-01
Full Text Available Kinetic energy spectra from the mesoscale numerical weather prediction (NWP model ALADIN with horizontal resolution 4.4 km are split into divergent and rotational components which are then compared at horizontal scales below 300 km and various vertical levels. It is shown that about 50% of kinetic energy in the free troposphere in ALADIN is divergent energy. The percentage increases towards 70% near the surface and in the upper troposphere towards 100 hPa. The maximal percentage of divergent energy is found at stratospheric levels around 100 hPa and at scales below 100 km which are not represented by the global models. At all levels, the divergent energy spectra are characterised by shallower slopes than the rotational energy spectra, and the difference increases as horizontal scales become larger. A very similar vertical distribution of divergent energy is obtained by using the standard ALADIN approach for the computation of spectra based on the extension zone and by applying detrending approach commonly used in mesoscale NWP community.
Kinetic Models for Topological Nearest-Neighbor Interactions
Blanchet, Adrien; Degond, Pierre
2017-12-01
We consider systems of agents interacting through topological interactions. These have been shown to play an important part in animal and human behavior. Precisely, the system consists of a finite number of particles characterized by their positions and velocities. At random times a randomly chosen particle, the follower, adopts the velocity of its closest neighbor, the leader. We study the limit of a system size going to infinity and, under the assumption of propagation of chaos, show that the limit kinetic equation is a non-standard spatial diffusion equation for the particle distribution function. We also study the case wherein the particles interact with their K closest neighbors and show that the corresponding kinetic equation is the same. Finally, we prove that these models can be seen as a singular limit of the smooth rank-based model previously studied in Blanchet and Degond (J Stat Phys 163:41-60, 2016). The proofs are based on a combinatorial interpretation of the rank as well as some concentration of measure arguments.
Determining the control circuitry of redox metabolism at the genome-scale.
Directory of Open Access Journals (Sweden)
Stephen Federowicz
2014-04-01
Full Text Available Determining how facultative anaerobic organisms sense and direct cellular responses to electron acceptor availability has been a subject of intense study. However, even in the model organism Escherichia coli, established mechanisms only explain a small fraction of the hundreds of genes that are regulated during electron acceptor shifts. Here we propose a qualitative model that accounts for the full breadth of regulated genes by detailing how two global transcription factors (TFs, ArcA and Fnr of E. coli, sense key metabolic redox ratios and act on a genome-wide basis to regulate anabolic, catabolic, and energy generation pathways. We first fill gaps in our knowledge of this transcriptional regulatory network by carrying out ChIP-chip and gene expression experiments to identify 463 regulatory events. We then interfaced this reconstructed regulatory network with a highly curated genome-scale metabolic model to show that ArcA and Fnr regulate >80% of total metabolic flux and 96% of differential gene expression across fermentative and nitrate respiratory conditions. Based on the data, we propose a feedforward with feedback trim regulatory scheme, given the extensive repression of catabolic genes by ArcA and extensive activation of chemiosmotic genes by Fnr. We further corroborated this regulatory scheme by showing a 0.71 r(2 (p<1e-6 correlation between changes in metabolic flux and changes in regulatory activity across fermentative and nitrate respiratory conditions. Finally, we are able to relate the proposed model to a wealth of previously generated data by contextualizing the existing transcriptional regulatory network.
Generalized kinetic model of reduction of molecular oxidant by metal containing redox
International Nuclear Information System (INIS)
Kravchenko, T.A.
1986-01-01
Present work is devoted to kinetics of reduction of molecular oxidant by metal containing redox. Constructed generalized kinetic model of redox process in the system solid redox - reagent solution allows to perform the general theoretical approach to research and to obtain new results on kinetics and mechanism of interaction of redox with oxidants.
A Global Modeling Framework for Plasma Kinetics: Development and Applications
Parsey, Guy Morland
The modern study of plasmas, and applications thereof, has developed synchronously with com- puter capabilities since the mid-1950s. Complexities inherent to these charged-particle, many- body, systems have resulted in the development of multiple simulation methods (particle-in-cell, fluid, global modeling, etc.) in order to both explain observed phenomena and predict outcomes of plasma applications. Recognizing that different algorithms are chosen to best address specific topics of interest, this thesis centers around the development of an open-source global model frame- work for the focused study of non-equilibrium plasma kinetics. After verification and validation of the framework, it was used to study two physical phenomena: plasma-assisted combustion and the recently proposed optically-pumped rare gas metastable laser. Global models permeate chemistry and plasma science, relying on spatial averaging to focus attention on the dynamics of reaction networks. Defined by a set of species continuity and energy conservation equations, the required data and constructed systems are conceptually similar across most applications, providing a light platform for exploratory and result-search parameter scan- ning. Unfortunately, it is common practice for custom code to be developed for each application-- an enormous duplication of effort which negatively affects the quality of the software produced. Presented herein, the Python-based Kinetic Global Modeling framework (KGMf) was designed to support all modeling phases: collection and analysis of reaction data, construction of an exportable system of model ODEs, and a platform for interactive evaluation and post-processing analysis. A symbolic ODE system is constructed for interactive manipulation and generation of a Jacobian, both of which are compiled as operation-optimized C-code. Plasma-assisted combustion and ignition (PAC/PAI) embody the modernization of burning fuel by opening up new avenues of control and optimization
A kinetic model for the burst phase of processive cellulases
DEFF Research Database (Denmark)
Præstgaard, Eigil; Olsen, Jens Elmerdahl; Murphy, Leigh
2011-01-01
. This approach generally accounts well for the initial time course (approximately 1 h) of the hydrolysis. We suggest that the models will be useful in attempts to rationalize the initial kinetics of processive cellulases, and demonstrate their application to some open questions, including the effect of repeated......Cellobiohydrolases (exocellulases) hydrolyze cellulose processively, i.e. by sequential cleaving of soluble sugars from one end of a cellulose strand. Their activity generally shows an initial burst, followed by a pronounced slowdown, even when substrate is abundant and product accumulation...... of the model, which can be solved analytically, shows that the burst and slowdown can be explained by the relative rates of the sequential reactions in the hydrolysis process and the occurrence of obstacles for the processive movement along the cellulose strand. More specifically, the maximum enzyme activity...
Combined kinetic and transport modeling of radiofrequency current drive
International Nuclear Information System (INIS)
Dumont, R.; Giruzzi, G.; Barbato, E.
2000-07-01
A numerical model for predictive simulations of radiofrequency current drive in magnetically confined plasmas is developed. It includes the minimum requirements for a self consistent description of such regimes, i.e., a 3-D ,kinetic equation for the electron distribution function, 1-D heat and current transport equations, and resonant coupling between velocity space and configuration space dynamics, through suitable wave propagation equations. The model finds its full application in predictive studies of complex current profile control scenarios in tokamaks, aiming at the establishment of internal transport barriers by the simultaneous use of various radiofrequency current drive methods. The basic properties of this non-linear numerical system are investigated and illustrated by simulations applied to reversed magnetic shear regimes obtained by Lower Hybrid and Electron Cyclotron current drive for parameters typical of the Tore Supra tokamak. (authors)
Genome-scale reconstruction of the metabolic network in Yersinia pestis, strain 91001
Energy Technology Data Exchange (ETDEWEB)
Navid, A; Almaas, E
2009-01-13
The gram-negative bacterium Yersinia pestis, the aetiological agent of bubonic plague, is one the deadliest pathogens known to man. Despite its historical reputation, plague is a modern disease which annually afflicts thousands of people. Public safety considerations greatly limit clinical experimentation on this organism and thus development of theoretical tools to analyze the capabilities of this pathogen is of utmost importance. Here, we report the first genome-scale metabolic model of Yersinia pestis biovar Mediaevalis based both on its recently annotated genome, and physiological and biochemical data from literature. Our model demonstrates excellent agreement with Y. pestis known metabolic needs and capabilities. Since Y. pestis is a meiotrophic organism, we have developed CryptFind, a systematic approach to identify all candidate cryptic genes responsible for known and theoretical meiotrophic phenomena. In addition to uncovering every known cryptic gene for Y. pestis, our analysis of the rhamnose fermentation pathway suggests that betB is the responsible cryptic gene. Despite all of our medical advances, we still do not have a vaccine for bubonic plague. Recent discoveries of antibiotic resistant strains of Yersinia pestis coupled with the threat of plague being used as a bioterrorism weapon compel us to develop new tools for studying the physiology of this deadly pathogen. Using our theoretical model, we can study the cell's phenotypic behavior under different circumstances and identify metabolic weaknesses which may be harnessed for the development of therapeutics. Additionally, the automatic identification of cryptic genes expands the usage of genomic data for pharmaceutical purposes.
Elementary Processes and Kinetic Modeling for Hydrogen and Helium Plasmas
Directory of Open Access Journals (Sweden)
Roberto Celiberto
2017-05-01
Full Text Available We report cross-sections and rate coefficients for excited states colliding with electrons, heavy particles and walls useful for the description of H 2 /He plasma kinetics under different conditions. In particular, the role of the rotational states in resonant vibrational excitations of the H 2 molecule by electron impact and the calculation of the related cross-sections are illustrated. The theoretical determination of the cross-section for the rovibrational energy exchange and dissociation of H 2 molecule, induced by He atom impact, by using the quasi-classical trajectory method is discussed. Recombination probabilities of H atoms on tungsten and graphite, relevant for the determination of the nascent vibrational distribution, are also presented. An example of a state-to-state plasma kinetic model for the description of shock waves operating in H 2 and He-H 2 mixtures is presented, emphasizing also the role of electronically-excited states in affecting the electron energy distribution function of free electrons. Finally, the thermodynamic properties and the electrical conductivity of non-ideal, high-density hydrogen plasma are finally discussed, in particular focusing on the pressure ionization phenomenon in high-pressure high-temperature plasmas.
Pyrolysis Kinetic Modelling of Wheat Straw from the Pannonian Region
Directory of Open Access Journals (Sweden)
Ivan Pešenjanski
2016-01-01
Full Text Available The pyrolysis/devolatilization is a basic step of thermochemical processes and requires fundamental characterization. In this paper, the kinetic model of pyrolysis is specified as a one-step global reaction. This type of reaction is used to describe the thermal degradation of wheat straw samples by measuring rates of mass loss of solid matter at a linear increase in temperature. The mentioned experiments were carried out using a derivatograph in an open-air environment. The influence of different factors was investigated, such as particle size, humidity levels, and the heating rate in the kinetics of devolatilization. As the measured values of mass loss and temperature functions transform in Arrhenius coordinates, the results are shown in the form of saddle curves. Such characteristics cannot be approximated with one equation in the form of Arrhenius law. For use in numerical applications, transformed functions can be approximated by linear regression for three separate intervals. Analysis of measurement resulting in granulation and moisture content variations shows that these factors have no significant influence. Tests of heating rate variations confirm the significance of this impact, especially in warmer regions. The influence of this factor should be more precisely investigated as a general variable, which should be the topic of further experiments.
Discrete kinetic models from funneled energy landscape simulations.
Directory of Open Access Journals (Sweden)
Nicholas P Schafer
Full Text Available A general method for facilitating the interpretation of computer simulations of protein folding with minimally frustrated energy landscapes is detailed and applied to a designed ankyrin repeat protein (4ANK. In the method, groups of residues are assigned to foldons and these foldons are used to map the conformational space of the protein onto a set of discrete macrobasins. The free energies of the individual macrobasins are then calculated, informing practical kinetic analysis. Two simple assumptions about the universality of the rate for downhill transitions between macrobasins and the natural local connectivity between macrobasins lead to a scheme for predicting overall folding and unfolding rates, generating chevron plots under varying thermodynamic conditions, and inferring dominant kinetic folding pathways. To illustrate the approach, free energies of macrobasins were calculated from biased simulations of a non-additive structure-based model using two structurally motivated foldon definitions at the full and half ankyrin repeat resolutions. The calculated chevrons have features consistent with those measured in stopped flow chemical denaturation experiments. The dominant inferred folding pathway has an "inside-out", nucleation-propagation like character.
Kinetic modeling of methyl butanoate in shock tube.
Huynh, Lam K; Lin, Kuang C; Violi, Angela
2008-12-25
An increased necessity for energy independence and heightened concern about the effects of rising carbon dioxide levels have intensified the search for renewable fuels that could reduce our current consumption of petrol and diesel. One such fuel is biodiesel, which consists of the methyl esters of fatty acids. Methyl butanoate (MB) contains the essential chemical structure of the long-chain fatty acids and a shorter, but similar, alkyl chain. This paper reports on a detailed kinetic mechanism for MB that is assembled using theoretical approaches. Thirteen pathways that include fuel decomposition, isomerization, and propagation steps were computed using ab initio calculations [J. Org. Chem. 2008, 73, 94]. Rate constants from first principles for important reactions in CO(2) formation, namely CH(3)OCO=CH(3) + CO(2) (R1) and CH(3)OCO=CH(3)O + CO (R2) reactions, are computed at high levels of theory and implemented in the mechanism. Using the G3B3 potential energy surface together with the B3LYP/6-31G(d) gradient, Hessian and geometries, the rate constants for reactions R1 and R2 are calculated using the Rice-Ramsperger-Kassel-Marcus theory with corrections from treatments for tunneling, hindered rotation, and variational effects. The calculated rate constants of reaction R1 differ from the data present in the literature by at most 20%, while those of reaction R2 are about a factor of 4 lower than the available values. The new kinetic model derived from ab initio simulations is combined with the kinetic mechanism presented by Fisher et al. [Proc. Combust. Inst. 2000, 28, 1579] together with the addition of the newly found six-centered unimolecular elimination reaction that yields ethylene and methyl acetate, MB = C(2)H(4) + CH(3)COOCH(3). This latter pathway requires the inclusion of the CH(3)COOCH(3) decomposition model suggested by Westbrook et al. [Proc. Combust. Inst. 2008, accepted]. The newly composed kinetic mechanism for MB is used to study the CO(2) formation
Analysis of Aspergillus nidulans metabolism at the genome-scale
DEFF Research Database (Denmark)
David, Helga; Ozcelik, İlknur Ş; Hofmann, Gerald
2008-01-01
of relevant secondary metabolites, was reconstructed based on detailed metabolic reconstructions available for A. niger and Saccharomyces cerevisiae, and information on the genetics, biochemistry and physiology of A. nidulans. Thereby, it was possible to identify metabolic functions without a gene associated...... a function. Results: In this work, we have manually assigned functions to 472 orphan genes in the metabolism of A. nidulans, by using a pathway-driven approach and by employing comparative genomics tools based on sequence similarity. The central metabolism of A. nidulans, as well as biosynthetic pathways......, in an objective and systematic manner. The functional assignments served as a basis to develop a mathematical model, linking 666 genes (both previously and newly annotated) to metabolic roles. The model was used to simulate metabolic behavior and additionally to integrate, analyze and interpret large-scale gene...
A model of aerosol evaporation kinetics in a thermodenuder
Directory of Open Access Journals (Sweden)
C. D. Cappa
2010-05-01
Full Text Available Aerosol thermodenuders provide a measure of particle volatility. The information provided by a thermodenuder is fundamentally related to the kinetics of evaporation and condensation within the device. Here, a time-dependent, multi-component model of particle and gas-phase mass transfer in a thermodenuder is described. This model empirically accounts for the temperature profile along the length of a typical thermodenuder and distinguishes between the influence of the heating section and of the adsorbent denuder section. It is shown that "semi-volatile" aerosol is particularly sensitive to the inclusion of an adsorbent denuder in the model. As expected, the mass loss from evaporation of particles as they pass through the thermodenuder is directly related to the compound vapor pressure, although the assumptions regarding the enthalpy of vaporization are shown to also have a large influence on the overall calculated mass thermograms. The model has been validated by comparison with previously measured mass thermograms for single-component aerosols and is shown to provide reasonable semi-quantitative agreement. The model that has been developed here can be used to provide quantitative understanding of aerosol volatility measurements of single and multi-component aerosol made using thermodenuders that include adsorbent denuder sections.
Simultaneous removal of sulfide, nitrate and acetate: Kinetic modeling
Energy Technology Data Exchange (ETDEWEB)
Wang Aijie, E-mail: waj0578@hit.edu.cn [State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology (SKLUWRE, HIT), Harbin 150090 (China); Liu Chunshuang; Ren Nanqi; Han Hongjun [State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology (SKLUWRE, HIT), Harbin 150090 (China); Lee Duujong [State Key Laboratory of Urban Water Resource and Environment, Harbin Institute of Technology (SKLUWRE, HIT), Harbin 150090 (China); Department of Chemical Engineering, National Taiwan University, Taipei 10617, Taiwan (China)
2010-06-15
Biological removal of sulfide, nitrate and chemical oxygen demand (COD) simultaneously from industrial wastewaters to elementary sulfur (S{sup 0}), N{sub 2}, and CO{sub 2}, or named the denitrifying sulfide (DSR) process, is a cost effective and environmentally friendly treatment process for high strength sulfide and nitrate laden organic wastewater. Kinetic model for the DSR process was established for the first time on the basis of Activated Sludge Model No. 1 (ASM1). The DSR experiments were conducted at influent sulfide concentrations of 200-800 mg/L, whose results calibrate the model parameters. The model correlates well with the DSR process dynamics. By introducing the switch function and the inhibition function, the competition between autotrophic and heterotrophic denitrifiers is quantitatively described and the degree of inhibition of sulfide on heterotrophic denitrifiers is realized. The model output indicates that the DSR reactor can work well at 0.5 < C/S < 3.0 with influent sulfide concentration of 400-1000 mg/L. At >1000 mg/L influent sulfide, however, the DSR system will break down.
Incorporation of chemical kinetic models into process control
International Nuclear Information System (INIS)
Herget, C.J.; Frazer, J.W.
1981-01-01
An important consideration in chemical process control is to determine the precise rationing of reactant streams, particularly when a large time delay exists between the mixing of the reactants and the measurement of the product. In this paper, a method is described for incorporating chemical kinetic models into the control strategy in order to achieve optimum operating conditions. The system is first characterized by determining a reaction rate surface as a function of all input reactant concentrations over a feasible range. A nonlinear constrained optimization program is then used to determine the combination of reactants which produces the specified yield at minimum cost. This operating condition is then used to establish the nominal concentrations of the reactants. The actual operation is determined through a feedback control system employing a Smith predictor. The method is demonstrated on a laboratory bench scale enzyme reactor
Energetic Mapping of Ni Catalysts by Detailed Kinetic Modeling
DEFF Research Database (Denmark)
Bjørgum, Erlend; Chen, De; Bakken, Mari G.
2005-01-01
Temperature-programmed desorption (TPD) of CO has been performed on supported and unsupported nickel catalysts. The unsupported Ni catalyst consists of a Ni(14 13 13) single crystal which has been studied under ultrahigh vacuum conditions. The desorption energy for CO at low CO surface coverage...... was found to be 119 kJ/mol, and the binding energy of C to the Ni(111) surface of the crystal was 703 kJ/mol. The supported catalysts consist of nickel supported on hydrotalcite-like compounds with three different Mg2+/Al3+ ratios. The experimental results show that for the supported Ni catalysts TPD of CO...... precursor seems to result in more steplike sites, kinks, and defects for carbon monoxide dissociation. A detailed kinetic modeling of the TPO results based on elementary reaction steps has been conducted to give an energetic map of supported Ni catalysts. Experimental results from the ideal Ni surface fit...
Formulation and kinetic modeling of curcumin loaded intranasal mucoadhesive microemulsion
Directory of Open Access Journals (Sweden)
B Mikesh Patel
2012-01-01
Full Text Available It is a challenge to develop the optimum dosage form of poorly water-soluble drugs and to target them due to limited bioavailability, intra and inter subject variability. In this investigation, mucoadhesive microemulsion of curcumin was developed by water titration method taking biocompatible components for intranasal delivery and was characterized. Nasal ciliotoxicity studies were carried out using excised sheep nasal mucosa. in vitro release studies of formulations and PDS were performed. Labrafil M 1944 CS based microemulsion was transparent, stable and nasal non-ciliotoxic having particle size 12.32±0.81nm (PdI=0.223 and from kinetic modeling, the release was found to be Fickian diffusion for mucoadhesive microemulsion.
Effective-field theory on the kinetic Ising model
International Nuclear Information System (INIS)
Shi Xiaoling; Wei Guozhu; Li Lin
2008-01-01
As an analytical method, the effective-field theory (EFT) is used to study the dynamical response of the kinetic Ising model in the presence of a sinusoidal oscillating field. The effective-field equations of motion of the average magnetization are given for the square lattice (Z=4) and the simple cubic lattice (Z=6), respectively. The dynamic order parameter, the hysteresis loop area and the dynamic correlation are calculated. In the field amplitude h 0 /ZJ-temperature T/ZJ plane, the phase boundary separating the dynamic ordered and the disordered phase has been drawn, and the dynamical tricritical point has been observed. We also make the compare results of EFT with that given by using the mean field theory (MFT)
Testing a dissipative kinetic k-essence model
Energy Technology Data Exchange (ETDEWEB)
Cardenas, Victor H.; Villanueva, J.R. [Universidad de Valparaiso, Instituto de Fisica y Astronomia, Valparaiso (Chile); Centro de Astrofisica de Valparaiso, Valparaiso (Chile); Cruz, Norman [Universidad de Santiago de Chile, Departamento de Fisica, Santiago (Chile)
2015-04-01
In thiswork,we present a study of a purely kinetic k-essence model, characterized basically by a parameter α in presence of a bulk dissipative term, whose relationship between viscous pressure Π and energy density ρ of the background follows a polytropic type law, Π ∝ ρ{sup λ+1/2}, where λ, in principle, is a parameter without restrictions. Analytical solutions for the energy density of the k-essence field are found in two specific cases: λ = 1/2 and λ = (1 - α)/2α, and then we show that these solutions possess the same functional form as the non-viscous counterpart. Finally, both approaches are contrasted with observational data from type Ia supernova, and the most recent Hubble parameter measurements, and therefore, the best values for the parameters of the theory are found. (orig.)
Genome-scale metabolic representation of Amycolatopsis balhimycina
DEFF Research Database (Denmark)
Vongsangnak, Wanwipa; Figueiredo, L. F.; Förster, Jochen
2012-01-01
Infection caused by methicillin‐resistant Staphylococcus aureus (MRSA) is an increasing societal problem. Typically, glycopeptide antibiotics are used in the treatment of these infections. The most comprehensively studied glycopeptide antibiotic biosynthetic pathway is that of balhimycin...... to reconstruct a genome‐scale metabolic model for the organism. Here we generated an almost complete A. balhimycina genome sequence comprising 10,562,587 base pairs assembled into 2,153 contigs. The high GC‐genome (∼69%) includes 8,585 open reading frames (ORFs). We used our integrative toolbox called SEQTOR...
Mechanism of nitric acid reduction and kinetic modelling
International Nuclear Information System (INIS)
Sicsic, David; Balbaud-Celerier, Fanny; Tribollet, Bernard
2014-01-01
In France, the recycling of nuclear waste fuels involves the use of hot concentrated nitric acid. The understanding and prediction of the behaviour of the structural materials (mainly austenitic stainless steels) requires the determination and modelling of the nitric acid reduction process. Nitric acid is indirectly reduced by an autocatalytic mechanism depending on the cathodic overpotential and acid concentration. This mechanism has been widely studied. All the authors agree on its autocatalytic nature, characterized by the predominant role of the reduction products. It is also generally admitted that neither nitric acid nor the nitrate ion is the electro-active species. However, the nature of the electro-active species, the place where the catalytic species regenerates and the thermodynamic and kinetic behaviour of the reaction intermediates remain uncertain. The aim of this study was to clarify some of these uncertainties by performing an electrochemical investigation of the reduction of 4 M nitric acid at 40 C at an inert electrode (platinum or gold). An inert electrode was chosen as the working electrode in a first step to avoid its oxidation and focus the research on the reduction mechanism. This experimental work enabled us to suggest a coherent sequence of electrochemical and chemical reactions. Kinetic modelling of this sequence was then carried out for a gold rotating disk electrode. A thermodynamic study at 25 C allowed the composition of the liquid and gaseous phases of nitric acid solutions in the concentration range 0.5-22 M to be evaluated. The kinetics of the reduction of 4 M nitric acid was investigated by cyclic voltammetry and chrono-amperometry at an inert electrode at 40 C. The coupling of chrono-amperometry and FTIR spectroscopy in the gaseous phase led to the identification of the gaseous reduction products as a function of the cathodic overpotential. The results showed that the reduction process is autocatalytic for potentials between 0
High fidelity kinetic modeling of magnetic reconnection in laboratory plasma
Stanier, A.; Daughton, W. S.
2017-12-01
Over the past decade, a great deal of progress has been made towards understanding the physics of magnetic reconnection in weakly collisional regimes of relevance to both fusion devices, and to space and astrophysical plasmas. However, there remain some outstanding unsolved problems in reconnection physics, such as the generation and influence of plasmoids (flux ropes) within reconnection layers, the development of magnetic turbulence, the role of current driven and streaming instabilities, and the influence of electron pressure anisotropy on the layer structure. Due to the importance of these questions, new laboratory reconnection experiments are being built to allow controlled and reproducible study of such questions with the simultaneous acquisition of high time resolution measurements at a large number of spatial points. These experiments include the FLARE facility at Princeton University and the T-REX experiment at the University of Wisconsin. To guide and interpret these new experiments, and to extrapolate the results to space applications, new investments in kinetic modeling tools are required. We have recently developed a cylindrical version of the VPIC Particle-In-Cell code with the capability to perform first-principles kinetic simulations that approach experimental device size with more realistic geometry and drive coils. This cylindrical version inherits much of the optimization work that has been done recently for the next generation many-cores architectures with wider vector registers, and achieves comparable conservation properties as the Cartesian code. Namely it features exact discrete charge conservation, and a so-called "energy-conserving" scheme where the energy is conserved in the limit of continuous time, i.e. without contribution from spatial discretization (Lewis, 1970). We will present initial results of modeling magnetic reconnection in the experiments mentioned above. Since the VPIC code is open source (https
Orestes Kinetics Model for the Electra KrF Laser
Giuliani, J. L.; Kepple, P.; Lehmberg, R. H.; Myers, M. C.; Sethian, J. D.; Petrov, G.; Wolford, M.; Hegeler, F.
2003-10-01
Orestes is a first principles simulation code for the electron deposition, plasma chemistry, laser transport, and amplified spontaneous emission (ASE) in an e-beam pumped KrF laser. Orestes has been benchmarked against results from Nike at NRL and the Keio laser facility. The modeling tasks are to support ongoing oscillator experiments on the Electra laser ( 500 J), to predict performance of Electra as an amplifier, and to develop scaling relations for larger systems such as envisioned for an inertial fusion energy power plant. In Orestes the energy deposition of the primary beam electrons is assumed to be spatially uniform, but the excitation and ionization of the Ar/Kr/F2 target gas by the secondary electrons is determined from the energy distribution function as calculated by a Boltzmann code. The subsequent plasma kinetics of 23 species subject to over 100 reactions is followed with 1-D spatial resolution along the lasing axis. In addition, the vibrational relaxation among excited electronic states of the KrF molecule are included in the kinetics since lasing at 248 nm can occur from several vibrational lines of the B state. Transport of the lasing photons is solved by the method of characteristics. The time dependent ASE is calculated in 3-D using a ``local look-back'' scheme with discrete ordinates and includes specular reflection off the side walls and rear mirror. Gain narrowing is treated by multi-frequency transport of the ASE. Calculations for the gain, saturation intensity, extraction efficiency, and laser output from the Orestes model will be presented and compared with available data from Electra operated as an oscillator. Potential implications for the difference in optimal F2 concentration will be discussed along with the effects of window transmissivity at 248 nm.
Mechanistic kinetic models of enzymatic cellulose hydrolysis-A review.
Jeoh, Tina; Cardona, Maria J; Karuna, Nardrapee; Mudinoor, Akshata R; Nill, Jennifer
2017-07-01
Bioconversion of lignocellulose forms the basis for renewable, advanced biofuels, and bioproducts. Mechanisms of hydrolysis of cellulose by cellulases have been actively studied for nearly 70 years with significant gains in understanding of the cellulolytic enzymes. Yet, a full mechanistic understanding of the hydrolysis reaction has been elusive. We present a review to highlight new insights gained since the most recent comprehensive review of cellulose hydrolysis kinetic models by Bansal et al. (2009) Biotechnol Adv 27:833-848. Recent models have taken a two-pronged approach to tackle the challenge of modeling the complex heterogeneous reaction-an enzyme-centric modeling approach centered on the molecularity of the cellulase-cellulose interactions to examine rate limiting elementary steps and a substrate-centric modeling approach aimed at capturing the limiting property of the insoluble cellulose substrate. Collectively, modeling results suggest that at the molecular-scale, how rapidly cellulases can bind productively (complexation) and release from cellulose (decomplexation) is limiting, while the overall hydrolysis rate is largely insensitive to the catalytic rate constant. The surface area of the insoluble substrate and the degrees of polymerization of the cellulose molecules in the reaction both limit initial hydrolysis rates only. Neither enzyme-centric models nor substrate-centric models can consistently capture hydrolysis time course at extended reaction times. Thus, questions of the true reaction limiting factors at extended reaction times and the role of complexation and decomplexation in rate limitation remain unresolved. Biotechnol. Bioeng. 2017;114: 1369-1385. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.
Detailed kinetic modeling study of n-pentanol oxidation
Heufer, Karl Alexander; Sarathy, Mani; Curran, Henry J.; Davis, Alexander C.; Westbrook, Charles K.; Pitz, William J.
2012-01-01
To help overcome the world's dependence upon fossil fuels, suitable biofuels are promising alternatives that can be used in the transportation sector. Recent research on internal combustion engines shows that short alcoholic fuels (e.g., ethanol or n-butanol) have reduced pollutant emissions and increased knock resistance compared to fossil fuels. Although higher molecular weight alcohols (e.g., n-pentanol and n-hexanol) exhibit higher reactivity that lowers their knock resistance, they are suitable for diesel engines or advanced engine concepts, such as homogeneous charge compression ignition (HCCI), where higher reactivity at lower temperatures is necessary for engine operation. The present study presents a detailed kinetic model for n-pentanol based on modeling rules previously presented for n-butanol. This approach was initially validated using quantum chemistry calculations to verify the most stable n-pentanol conformation and to obtain C-H and C-C bond dissociation energies. The proposed model has been validated against ignition delay time data, speciation data from a jet-stirred reactor, and laminar flame velocity measurements. Overall, the model shows good agreement with the experiments and permits a detailed discussion of the differences between alcohols and alkanes. © 2012 American Chemical Society.
Bayesian inference for hybrid discrete-continuous stochastic kinetic models
International Nuclear Information System (INIS)
Sherlock, Chris; Golightly, Andrew; Gillespie, Colin S
2014-01-01
We consider the problem of efficiently performing simulation and inference for stochastic kinetic models. Whilst it is possible to work directly with the resulting Markov jump process (MJP), computational cost can be prohibitive for networks of realistic size and complexity. In this paper, we consider an inference scheme based on a novel hybrid simulator that classifies reactions as either ‘fast’ or ‘slow’ with fast reactions evolving as a continuous Markov process whilst the remaining slow reaction occurrences are modelled through a MJP with time-dependent hazards. A linear noise approximation (LNA) of fast reaction dynamics is employed and slow reaction events are captured by exploiting the ability to solve the stochastic differential equation driving the LNA. This simulation procedure is used as a proposal mechanism inside a particle MCMC scheme, thus allowing Bayesian inference for the model parameters. We apply the scheme to a simple application and compare the output with an existing hybrid approach and also a scheme for performing inference for the underlying discrete stochastic model. (paper)
Detailed kinetic modeling study of n-pentanol oxidation
Heufer, Karl Alexander
2012-10-18
To help overcome the world\\'s dependence upon fossil fuels, suitable biofuels are promising alternatives that can be used in the transportation sector. Recent research on internal combustion engines shows that short alcoholic fuels (e.g., ethanol or n-butanol) have reduced pollutant emissions and increased knock resistance compared to fossil fuels. Although higher molecular weight alcohols (e.g., n-pentanol and n-hexanol) exhibit higher reactivity that lowers their knock resistance, they are suitable for diesel engines or advanced engine concepts, such as homogeneous charge compression ignition (HCCI), where higher reactivity at lower temperatures is necessary for engine operation. The present study presents a detailed kinetic model for n-pentanol based on modeling rules previously presented for n-butanol. This approach was initially validated using quantum chemistry calculations to verify the most stable n-pentanol conformation and to obtain C-H and C-C bond dissociation energies. The proposed model has been validated against ignition delay time data, speciation data from a jet-stirred reactor, and laminar flame velocity measurements. Overall, the model shows good agreement with the experiments and permits a detailed discussion of the differences between alcohols and alkanes. © 2012 American Chemical Society.
Directory of Open Access Journals (Sweden)
Alina Żogała
2014-01-01
Originality/value: This paper presents state of art in the field of coal gasification modeling using kinetic and computational fluid dynamics approach. The paper also presents own comparative analysis (concerned with mathematical formulation, input data and parameters, basic assumptions, obtained results etc. of the most important models of underground coal gasification.
Genome-scale analysis of aberrant DNA methylation in colorectal cancer
Hinoue, Toshinori; Weisenberger, Daniel J.; Lange, Christopher P.E.; Shen, Hui; Byun, Hyang-Min; Van Den Berg, David; Malik, Simeen; Pan, Fei; Noushmehr, Houtan; van Dijk, Cornelis M.; Tollenaar, Rob A.E.M.; Laird, Peter W.
2012-01-01
Colorectal cancer (CRC) is a heterogeneous disease in which unique subtypes are characterized by distinct genetic and epigenetic alterations. Here we performed comprehensive genome-scale DNA methylation profiling of 125 colorectal tumors and 29 adjacent normal tissues. We identified four DNA methylation–based subgroups of CRC using model-based cluster analyses. Each subtype shows characteristic genetic and clinical features, indicating that they represent biologically distinct subgroups. A CIMP-high (CIMP-H) subgroup, which exhibits an exceptionally high frequency of cancer-specific DNA hypermethylation, is strongly associated with MLH1 DNA hypermethylation and the BRAFV600E mutation. A CIMP-low (CIMP-L) subgroup is enriched for KRAS mutations and characterized by DNA hypermethylation of a subset of CIMP-H-associated markers rather than a unique group of CpG islands. Non-CIMP tumors are separated into two distinct clusters. One non-CIMP subgroup is distinguished by a significantly higher frequency of TP53 mutations and frequent occurrence in the distal colon, while the tumors that belong to the fourth group exhibit a low frequency of both cancer-specific DNA hypermethylation and gene mutations and are significantly enriched for rectal tumors. Furthermore, we identified 112 genes that were down-regulated more than twofold in CIMP-H tumors together with promoter DNA hypermethylation. These represent ∼7% of genes that acquired promoter DNA methylation in CIMP-H tumors. Intriguingly, 48/112 genes were also transcriptionally down-regulated in non-CIMP subgroups, but this was not attributable to promoter DNA hypermethylation. Together, we identified four distinct DNA methylation subgroups of CRC and provided novel insight regarding the role of CIMP-specific DNA hypermethylation in gene silencing. PMID:21659424
Estimating phylogenetic trees from genome-scale data.
Liu, Liang; Xi, Zhenxiang; Wu, Shaoyuan; Davis, Charles C; Edwards, Scott V
2015-12-01
The heterogeneity of signals in the genomes of diverse organisms poses challenges for traditional phylogenetic analysis. Phylogenetic methods known as "species tree" methods have been proposed to directly address one important source of gene tree heterogeneity, namely the incomplete lineage sorting that occurs when evolving lineages radiate rapidly, resulting in a diversity of gene trees from a single underlying species tree. Here we review theory and empirical examples that help clarify conflicts between species tree and concatenation methods, and misconceptions in the literature about the performance of species tree methods. Considering concatenation as a special case of the multispecies coalescent model helps explain differences in the behavior of the two methods on phylogenomic data sets. Recent work suggests that species tree methods are more robust than concatenation approaches to some of the classic challenges of phylogenetic analysis, including rapidly evolving sites in DNA sequences and long-branch attraction. We show that approaches, such as binning, designed to augment the signal in species tree analyses can distort the distribution of gene trees and are inconsistent. Computationally efficient species tree methods incorporating biological realism are a key to phylogenetic analysis of whole-genome data. © 2015 New York Academy of Sciences.
Exploring massive, genome scale datasets with the genometricorr package
Favorov, Alexander; Mularoni, Loris; Cope, Leslie M.; Medvedeva, Yulia; Mironov, Andrey A.; Makeev, Vsevolod J.; Wheelan, Sarah J.
2012-01-01
We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. Availability and implementation: The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor. © 2012 Favorov et al.
Exploring massive, genome scale datasets with the genometricorr package
Favorov, Alexander
2012-05-31
We have created a statistically grounded tool for determining the correlation of genomewide data with other datasets or known biological features, intended to guide biological exploration of high-dimensional datasets, rather than providing immediate answers. The software enables several biologically motivated approaches to these data and here we describe the rationale and implementation for each approach. Our models and statistics are implemented in an R package that efficiently calculates the spatial correlation between two sets of genomic intervals (data and/or annotated features), for use as a metric of functional interaction. The software handles any type of pointwise or interval data and instead of running analyses with predefined metrics, it computes the significance and direction of several types of spatial association; this is intended to suggest potentially relevant relationships between the datasets. Availability and implementation: The package, GenometriCorr, can be freely downloaded at http://genometricorr.sourceforge.net/. Installation guidelines and examples are available from the sourceforge repository. The package is pending submission to Bioconductor. © 2012 Favorov et al.
Treatment of polymer surfaces in plasma Part I. Kinetic model
International Nuclear Information System (INIS)
Tabaliov, N A; Svirachev, D M
2006-01-01
The surface tension of the polymer materials depends on functional groups over its surface. As a result from the plasma treatment the kind and concentration of the functional groups can be changed. In the present work, the possible kinetic reactions are defined. They describe the interaction between the plasma and the polymer surface of polyethylene terephthalate (PET). Basing on these reactions, the systems of differential kinetic equations are suggested. The solutions are obtained analytically for the system kinetic equations at defined circumstances
Directory of Open Access Journals (Sweden)
Kim Tae
2011-06-01
Full Text Available Abstract Background Ralstonia eutropha H16, found in both soil and water, is a Gram-negative lithoautotrophic bacterium that can utillize CO2 and H2 as its sources of carbon and energy in the absence of organic substrates. R. eutropha H16 can reach high cell densities either under lithoautotrophic or heterotrophic conditions, which makes it suitable for a number of biotechnological applications. It is the best known and most promising producer of polyhydroxyalkanoates (PHAs from various carbon substrates and is an environmentally important bacterium that can degrade aromatic compounds. In order to make R. eutropha H16 a more efficient and robust biofactory, system-wide metabolic engineering to improve its metabolic performance is essential. Thus, it is necessary to analyze its metabolic characteristics systematically and optimize the entire metabolic network at systems level. Results We present the lithoautotrophic genome-scale metabolic model of R. eutropha H16 based on the annotated genome with biochemical and physiological information. The stoichiometic model, RehMBEL1391, is composed of 1391 reactions including 229 transport reactions and 1171 metabolites. Constraints-based flux analyses were performed to refine and validate the genome-scale metabolic model under environmental and genetic perturbations. First, the lithoautotrophic growth characteristics of R. eutropha H16 were investigated under varying feeding ratios of gas mixture. Second, the genome-scale metabolic model was used to design the strategies for the production of poly[R-(--3hydroxybutyrate] (PHB under different pH values and carbon/nitrogen source uptake ratios. It was also used to analyze the metabolic characteristics of R. eutropha when the phosphofructokinase gene was expressed. Finally, in silico gene knockout simulations were performed to identify targets for metabolic engineering essential for the production of 2-methylcitric acid in R. eutropha H16. Conclusion The
Model of SNARE-mediated membrane adhesion kinetics.
Directory of Open Access Journals (Sweden)
Jason M Warner
Full Text Available SNARE proteins are conserved components of the core fusion machinery driving diverse membrane adhesion and fusion processes in the cell. In many cases micron-sized membranes adhere over large areas before fusion. Reconstituted in vitro assays have helped isolate SNARE mechanisms in small membrane adhesion-fusion and are emerging as powerful tools to study large membrane systems by use of giant unilamellar vesicles (GUVs. Here we model SNARE-mediated adhesion kinetics in SNARE-reconstituted GUV-GUV or GUV-supported bilayer experiments. Adhesion involves many SNAREs whose complexation pulls apposing membranes into contact. The contact region is a tightly bound rapidly expanding patch whose growth velocity v(patch increases with SNARE density Gamma(snare. We find three patch expansion regimes: slow, intermediate, fast. Typical experiments belong to the fast regime where v(patch ~ (Gamma(snare(2/3 depends on SNARE diffusivities and complexation binding constant. The model predicts growth velocities ~10 - 300 microm/s. The patch may provide a close contact region where SNAREs can trigger fusion. Extending the model to a simple description of fusion, a broad distribution of fusion times is predicted. Increasing SNARE density accelerates fusion by boosting the patch growth velocity, thereby providing more complexes to participate in fusion. This quantifies the notion of SNAREs as dual adhesion-fusion agents.
Modelling and parallel calculation of a kinetic boundary layer
International Nuclear Information System (INIS)
Perlat, Jean Philippe
1998-01-01
This research thesis aims at addressing reliability and cost issues in the calculation by numeric simulation of flows in transition regime. The first step has been to reduce calculation cost and memory space for the Monte Carlo method which is known to provide performance and reliability for rarefied regimes. Vector and parallel computers allow this objective to be reached. Here, a MIMD (multiple instructions, multiple data) machine has been used which implements parallel calculation at different levels of parallelization. Parallelization procedures have been adapted, and results showed that parallelization by calculation domain decomposition was far more efficient. Due to reliability issue related to the statistic feature of Monte Carlo methods, a new deterministic model was necessary to simulate gas molecules in transition regime. New models and hyperbolic systems have therefore been studied. One is chosen which allows thermodynamic values (density, average velocity, temperature, deformation tensor, heat flow) present in Navier-Stokes equations to be determined, and the equations of evolution of thermodynamic values are described for the mono-atomic case. Numerical resolution of is reported. A kinetic scheme is developed which complies with the structure of all systems, and which naturally expresses boundary conditions. The validation of the obtained 14 moment-based model is performed on shock problems and on Couette flows [fr
Directory of Open Access Journals (Sweden)
Daugherty Sean
2009-09-01
Full Text Available Abstract Background Rhodoferax ferrireducens is a metabolically versatile, Fe(III-reducing, subsurface microorganism that is likely to play an important role in the carbon and metal cycles in the subsurface. It also has the unique ability to convert sugars to electricity, oxidizing the sugars to carbon dioxide with quantitative electron transfer to graphite electrodes in microbial fuel cells. In order to expand our limited knowledge about R. ferrireducens, the complete genome sequence of this organism was further annotated and then the physiology of R. ferrireducens was investigated with a constraint-based, genome-scale in silico metabolic model and laboratory studies. Results The iterative modeling and experimental approach unveiled exciting, previously unknown physiological features, including an expanded range of substrates that support growth, such as cellobiose and citrate, and provided additional insights into important features such as the stoichiometry of the electron transport chain and the ability to grow via fumarate dismutation. Further analysis explained why R. ferrireducens is unable to grow via photosynthesis or fermentation of sugars like other members of this genus and uncovered novel genes for benzoate metabolism. The genome also revealed that R. ferrireducens is well-adapted for growth in the subsurface because it appears to be capable of dealing with a number of environmental insults, including heavy metals, aromatic compounds, nutrient limitation and oxidative stress. Conclusion This study demonstrates that combining genome-scale modeling with the annotation of a new genome sequence can guide experimental studies and accelerate the understanding of the physiology of under-studied yet environmentally relevant microorganisms.
Heterogeneous kinetic modeling of the catalytic conversion of cycloparaffins
Al-Sabawi, Mustafa N.
catalytic conversions respectively, are reported. Using these data, heterogeneous kinetic models accounting for intracrystallite molecular transport, adsorption and thermal and catalytic cracking of both cycloparaffin reactants are established. Results show that undesirable hydrogen transfer reactions are more pronounced and selectively favoured against other reactions at lower reaction temperatures, while the desirable ring-opening and cracking reactions predominate at the higher reaction temperatures. Moreover, results of the present work show that while crystallite size may have an effect on the overall conversion in some situations, there is a definite effect on the selectivity of products obtained during the cracking of MCH and decalin and the cracking of MCH in a mixture with co-reactants such as 1,3,5-triisopropylbenzene. Keywords. cycloparaffins, naphthenes, fluid catalytic cracking, kinetic modeling, Y-zeolites, diffusion, adsorption, ring-opening, hydrogen transfer, catalyst selectivity.
Satl model lesson in chemical kinetics | Nazir | African Journal of ...
African Journals Online (AJOL)
Studies in order to pursue kinetics and mechanism of chemical reactions are a vital component of chemical literature. SATL literature is still not available for promoting this vital aspect of chemistry teaching. A lesson pertaining to this important issue has been developed and various parameters of kinetic studies are ...
Chemical kinetic model uncertainty minimization through laminar flame speed measurements
Park, Okjoo; Veloo, Peter S.; Sheen, David A.; Tao, Yujie; Egolfopoulos, Fokion N.; Wang, Hai
2016-01-01
Laminar flame speed measurements were carried for mixture of air with eight C3-4 hydrocarbons (propene, propane, 1,3-butadiene, 1-butene, 2-butene, iso-butene, n-butane, and iso-butane) at the room temperature and ambient pressure. Along with C1-2 hydrocarbon data reported in a recent study, the entire dataset was used to demonstrate how laminar flame speed data can be utilized to explore and minimize the uncertainties in a reaction model for foundation fuels. The USC Mech II kinetic model was chosen as a case study. The method of uncertainty minimization using polynomial chaos expansions (MUM-PCE) (D.A. Sheen and H. Wang, Combust. Flame 2011, 158, 2358–2374) was employed to constrain the model uncertainty for laminar flame speed predictions. Results demonstrate that a reaction model constrained only by the laminar flame speed values of methane/air flames notably reduces the uncertainty in the predictions of the laminar flame speeds of C3 and C4 alkanes, because the key chemical pathways of all of these flames are similar to each other. The uncertainty in model predictions for flames of unsaturated C3-4 hydrocarbons remain significant without considering fuel specific laminar flames speeds in the constraining target data set, because the secondary rate controlling reaction steps are different from those in the saturated alkanes. It is shown that the constraints provided by the laminar flame speeds of the foundation fuels could reduce notably the uncertainties in the predictions of laminar flame speeds of C4 alcohol/air mixtures. Furthermore, it is demonstrated that an accurate prediction of the laminar flame speed of a particular C4 alcohol/air mixture is better achieved through measurements for key molecular intermediates formed during the pyrolysis and oxidation of the parent fuel. PMID:27890938
Modeling turbulence structure. Chemical kinetics interaction in turbulent reactive flows
Energy Technology Data Exchange (ETDEWEB)
Magnussen, B F [The Norwegian Univ. of Science and Technology, Trondheim (Norway)
1998-12-31
The challenge of the mathematical modelling is to transfer basic physical knowledge into a mathematical formulation such that this knowledge can be utilized in computational simulation of practical problems. The combustion phenomena can be subdivided into a large set of interconnected phenomena like flow, turbulence, thermodynamics, chemical kinetics, radiation, extinction, ignition etc. Combustion in one application differs from combustion in another area by the relative importance of the various phenomena. The difference in fuel, geometry and operational conditions often causes the differences. The computer offers the opportunity to treat the individual phenomena and their interactions by models with wide operational domains. The relative magnitude of the various phenomena therefore becomes the consequence of operational conditions and geometry and need not to be specified on the basis of experience for the given problem. In mathematical modelling of turbulent combustion, one of the big challenges is how to treat the interaction between the chemical reactions and the fluid flow i.e. the turbulence. Different scientists adhere to different concepts like the laminar flamelet approach, the pdf approach of the Eddy Dissipation Concept. Each of these approaches offers different opportunities and problems. All these models are based on a sound physical basis, however none of these have general validity in taking into consideration all detail of the physical chemical interaction. The merits of the models can only be judged by their ability to reproduce physical reality and consequences of operational and geometric conditions in a combustion system. The presentation demonstrates and discusses the development of a coherent combustion technology for energy conversion and safety based on the Eddy Dissipation Concept by Magnussen. (author) 30 refs.
Modeling turbulence structure. Chemical kinetics interaction in turbulent reactive flows
Energy Technology Data Exchange (ETDEWEB)
Magnussen, B.F. [The Norwegian Univ. of Science and Technology, Trondheim (Norway)
1997-12-31
The challenge of the mathematical modelling is to transfer basic physical knowledge into a mathematical formulation such that this knowledge can be utilized in computational simulation of practical problems. The combustion phenomena can be subdivided into a large set of interconnected phenomena like flow, turbulence, thermodynamics, chemical kinetics, radiation, extinction, ignition etc. Combustion in one application differs from combustion in another area by the relative importance of the various phenomena. The difference in fuel, geometry and operational conditions often causes the differences. The computer offers the opportunity to treat the individual phenomena and their interactions by models with wide operational domains. The relative magnitude of the various phenomena therefore becomes the consequence of operational conditions and geometry and need not to be specified on the basis of experience for the given problem. In mathematical modelling of turbulent combustion, one of the big challenges is how to treat the interaction between the chemical reactions and the fluid flow i.e. the turbulence. Different scientists adhere to different concepts like the laminar flamelet approach, the pdf approach of the Eddy Dissipation Concept. Each of these approaches offers different opportunities and problems. All these models are based on a sound physical basis, however none of these have general validity in taking into consideration all detail of the physical chemical interaction. The merits of the models can only be judged by their ability to reproduce physical reality and consequences of operational and geometric conditions in a combustion system. The presentation demonstrates and discusses the development of a coherent combustion technology for energy conversion and safety based on the Eddy Dissipation Concept by Magnussen. (author) 30 refs.
Kinetic Modeling of a Heterogeneous Fenton Oxidative Treatment of Petroleum Refining Wastewater
Basheer Hasan, Diya'uddeen; Abdul Raman, Abdul Aziz; Wan Daud, Wan Mohd Ashri
2014-01-01
The mineralisation kinetics of petroleum refinery effluent (PRE) by Fenton oxidation were evaluated. Within the ambit of the experimental data generated, first-order kinetic model (FKM), generalised lumped kinetic model (GLKM), and generalized kinetic model (GKM) were tested. The obtained apparent kinetic rate constants for the initial oxidation step (k 2′), their final oxidation step (k 1′), and the direct conversion to endproducts step (k 3′) were 10.12, 3.78, and 0.24 min−1 for GKM; 0.98, 0.98, and nil min−1 for GLKM; and nil, nil, and >0.005 min−1 for FKM. The findings showed that GKM is superior in estimating the mineralization kinetics. PMID:24592152
Electron kinetics modeling in a weakly ionized gas
International Nuclear Information System (INIS)
Boeuf, Jean-Pierre
1985-01-01
This work presents some features of electron kinetics in a weakly ionized gas. After a summary of the basis and recent developments of the kinetic theory, and a review of the most efficient numerical techniques for solving the Boltzmann equation, several aspects of electron motion in gases are analysed. Relaxation phenomena toward equilibrium under a uniform electric field, and the question of the existence of the hydrodynamic regime are first studied. The coupling between electron kinetics and chemical kinetics due to second kind collisions in Nitrogen is then analysed; a quantitative description of the evolution of the energy balance, accounting for electron-molecule as well as molecule-molecule energy transfer is also given. Finally, electron kinetics in space charge distorted, highly non uniform electric fields (glow discharges, streamers propagation) is investigated with microscopic numerical methods based on Boltzmann and Poisson equations. (author) [fr
Water sorption kinetics of damaged beans: GAB model
Directory of Open Access Journals (Sweden)
Fernanda M. Baptestini
Full Text Available ABSTRACT The objective of this study was to model the water sorption kinetics of damaged beans. Grains with initial moisture content of 53.85%, dry basis (d.b., were used. One portion of the grains was used to obtain desorption isotherms, while the other was subjected to drying until the moisture content of 5.26% (d.b., so that it was subjected to the adsorption. For the induction of damage, a Stein Breakage Tester was used. To obtain the equilibrium moisture content, grains were placed in a climatic chamber at 20, 30, 40 and 50 ± 1 °C combined with relative humidity of 30, 40, 50, 70 and 90 ± 3%. The GAB model fitted well to the equilibrium moisture experimental data of damaged grains and control. With increasing temperature, the monolayer moisture contents decreased in adsorption and desorption processes, ranging from 9.84 to 5.10% d.b. The lower moisture content in the monolayer in damaged grains indicates that lower moisture content is necessary to ensure their conservation.
A Kinetics Model for KrF Laser Amplifiers
Giuliani, J. L.; Kepple, P.; Lehmberg, R.; Obenschain, S. P.; Petrov, G.
1999-11-01
A computer kinetics code has been developed to model the temporal and spatial behavior of an e-beam pumped KrF laser amplifier. The deposition of the primary beam electrons is assumed to be spatially uniform and the energy distribution function of the nascent electron population is calculated to be near Maxwellian below 10 eV. For an initial Kr/Ar/F2 composition, the code calculates the densities of 24 species subject to over 100 reactions with 1-D spatial resolution (typically 16 zones) along the longitudinal lasing axis. Enthalpy accounting for each process is performed to partition the energy into internal, thermal, and radiative components. The electron as well as the heavy particle temperatures are followed for energy conservation and excitation rates. Transport of the lasing photons is performed along the axis on a dense subgrid using the method of characteristics. Amplified spontaneous emission is calculated using a discrete ordinates approach and includes contributions to the local intensity from the whole amplifier volume. Specular reflection off side walls and the rear mirror are included. Results of the model will be compared with data from the NRL NIKE laser and other published results.
Challenges for the kinetic unified dark matter model
International Nuclear Information System (INIS)
Giannakis, Dimitrios; Hu, Wayne
2005-01-01
Given that the dark matter and dark energy in the Universe affect cosmological observables only gravitationally, their phenomenology may be described by a single stress-energy tensor. True unification however requires a theory that reproduces the successful phenomenology of ΛCDM and that requirement places specific constraints on the stress structure of the matter. We show that a recently proposed unification through an offset quadratic kinetic term for a scalar field is exactly equivalent to a fluid with a closed-form barotropic equation of state plus cosmological constant. The finite pressure at high densities introduces a cutoff in the linear power spectrum, which may alleviate the dark matter substructure problem; we provide a convenient fitting function for such studies. Given that sufficient power must remain to reionize the Universe, the equation of state today is nonrelativistic with p∝ρ 2 and a Jeans scale in the parsec regime for all relevant densities. Structure may then be evolved into the nonlinear regime with standard hydrodynamic techniques. In fact, the model is equivalent to the well-studied collisional dark matter with negligible mean free path. If recent observations of the triaxiality of dark matter halos and ram pressure stripping in galaxy clusters are confirmed, this model will be ruled out
Mesoscopic kinetic Monte Carlo modeling of organic photovoltaic device characteristics
Kimber, Robin G. E.; Wright, Edward N.; O'Kane, Simon E. J.; Walker, Alison B.; Blakesley, James C.
2012-12-01
Measured mobility and current-voltage characteristics of single layer and photovoltaic (PV) devices composed of poly{9,9-dioctylfluorene-co-bis[N,N'-(4-butylphenyl)]bis(N,N'-phenyl-1,4-phenylene)diamine} (PFB) and poly(9,9-dioctylfluorene-co-benzothiadiazole) (F8BT) have been reproduced by a mesoscopic model employing the kinetic Monte Carlo (KMC) approach. Our aim is to show how to avoid the uncertainties common in electrical transport models arising from the need to fit a large number of parameters when little information is available, for example, a single current-voltage curve. Here, simulation parameters are derived from a series of measurements using a self-consistent “building-blocks” approach, starting from data on the simplest systems. We found that site energies show disorder and that correlations in the site energies and a distribution of deep traps must be included in order to reproduce measured charge mobility-field curves at low charge densities in bulk PFB and F8BT. The parameter set from the mobility-field curves reproduces the unipolar current in single layers of PFB and F8BT and allows us to deduce charge injection barriers. Finally, by combining these disorder descriptions and injection barriers with an optical model, the external quantum efficiency and current densities of blend and bilayer organic PV devices can be successfully reproduced across a voltage range encompassing reverse and forward bias, with the recombination rate the only parameter to be fitted, found to be 1×107 s-1. These findings demonstrate an approach that removes some of the arbitrariness present in transport models of organic devices, which validates the KMC as an accurate description of organic optoelectronic systems, and provides information on the microscopic origins of the device behavior.
Disposition of smoked cannabis with high [Delta]9-tetrahydrocannabinol content: A kinetic model.
Hunault, C.C.; van Eijkeren, J.C.; Mensinga, T.T.; de Vries, I.; Leenders, M.E.C.; Meulenbelt, J.
2010-01-01
Introduction No model exists to describe the disposition and kinetics of inhaled cannabis containing a high THC dose. We aimed to develop a kinetic model providing estimates of the THC serum concentrations after smoking cannabis cigarettes containing high THC doses (up to 69 mg THC).Methods
A kinetic model for the glucose/glycine Maillard reaction pathways
Martins, S.I.F.S.; Boekel, van M.A.J.S.
2005-01-01
A comprehensive kinetic model for the glucose/glycine Maillard reaction is proposed based on an approach called multiresponse kinetic modelling. Special attention was paid to reactants, intermediates and end products: -fructose, N-(1-deoxy--fructos-1-yl)-glycine (DFG), 1-deoxy-2,3-hexodiulose and
Dsc cure kinetics of an unsaturated polyester resin using empirical kinetic model
International Nuclear Information System (INIS)
Abdullah, I.
2015-01-01
In this paper, the kinetics of curing of unsaturated polyester resin initiated with benzoyl peroxide was studied. In case of unsaturated polyester (UP) resin, isothermal test alone could not predict correctly the curing time of UP resin. Therefore, isothermal kinetic analysis through isoconventional adjustment was used to correctly predict the curing time and temperature of UP resin. Isothermal kinetic analysis through isoconversional adjustment indicated that 97% of UP resin cures in 33 min at 120 degree C. Curing of UP resin through microwaves was also studied and found that 67% of UP resin cures in 1 min at 120 degree C. The crosslinking reaction of UP resin is so fast at 120 degree C that it becomes impossible to predict correctly the curing time of UP resin using isothermal test and the burial of C=C bonds in microgels makes it impossible to be fully cured by microwaves at 120 degree C. The rheological behaviour of unsaturated polyester resin was also studied to observe the change in viscosity with respect to time and temperature. (author)
Genome-scale cold stress response regulatory networks in ten Arabidopsis thaliana ecotypes
DEFF Research Database (Denmark)
Barah, Pankaj; Jayavelu, Naresh Doni; Rasmussen, Simon
2013-01-01
available from Arabidopsis thaliana 1001 genome project, we further investigated sequence polymorphisms in the core cold stress regulon genes. Significant numbers of non-synonymous amino acid changes were observed in the coding region of the CBF regulon genes. Considering the limited knowledge about......BACKGROUND: Low temperature leads to major crop losses every year. Although several studies have been conducted focusing on diversity of cold tolerance level in multiple phenotypically divergent Arabidopsis thaliana (A. thaliana) ecotypes, genome-scale molecular understanding is still lacking....... RESULTS: In this study, we report genome-scale transcript response diversity of 10 A. thaliana ecotypes originating from different geographical locations to non-freezing cold stress (10°C). To analyze the transcriptional response diversity, we initially compared transcriptome changes in all 10 ecotypes...
A protocol for generating a high-quality genome-scale metabolic reconstruction.
Thiele, Ines; Palsson, Bernhard Ø
2010-01-01
Network reconstructions are a common denominator in systems biology. Bottom-up metabolic network reconstructions have been developed over the last 10 years. These reconstructions represent structured knowledge bases that abstract pertinent information on the biochemical transformations taking place within specific target organisms. The conversion of a reconstruction into a mathematical format facilitates a myriad of computational biological studies, including evaluation of network content, hypothesis testing and generation, analysis of phenotypic characteristics and metabolic engineering. To date, genome-scale metabolic reconstructions for more than 30 organisms have been published and this number is expected to increase rapidly. However, these reconstructions differ in quality and coverage that may minimize their predictive potential and use as knowledge bases. Here we present a comprehensive protocol describing each step necessary to build a high-quality genome-scale metabolic reconstruction, as well as the common trials and tribulations. Therefore, this protocol provides a helpful manual for all stages of the reconstruction process.
A kinetic model for runaway electrons in the ionosphere
Directory of Open Access Journals (Sweden)
G. Garcia
2006-09-01
Full Text Available Electrodynamic models and measurements with satellites and incoherent scatter radars predict large field aligned current densities on one side of the auroral arcs. Different authors and different kinds of studies (experimental or modeling agree that the current density can reach up to hundreds of µA/m2. This large current density could be the cause of many phenomena such as tall red rays or triggering of unstable ion acoustic waves. In the present paper, we consider the issue of electrons moving through an ionospheric gas of positive ions and neutrals under the influence of a static electric field. We develop a kinetic model of collisions including electrons/electrons, electrons/ions and electrons/neutrals collisions. We use a Fokker-Planck approach to describe binary collisions between charged particles with a long-range interaction. We present the essential elements of this collision operator: the Langevin equation for electrons/ions and electrons/electrons collisions and the Monte-Carlo and null collision methods for electrons/neutrals collisions. A computational example is given illustrating the approach to equilibrium and the impact of the different terms (electrons/electrons and electrons/ions collisions on the one hand and electrons/neutrals collisions on the other hand. Then, a parallel electric field is applied in a new sample run. In this run, the electrons move in the z direction parallel to the electric field. The first results show that all the electron distribution functions are non-Maxwellian. Furthermore, runaway electrons can carry a significant part of the total current density, up to 20% of the total current density.
A kinetic model for runaway electrons in the ionosphere
Directory of Open Access Journals (Sweden)
G. Garcia
2006-09-01
Full Text Available Electrodynamic models and measurements with satellites and incoherent scatter radars predict large field aligned current densities on one side of the auroral arcs. Different authors and different kinds of studies (experimental or modeling agree that the current density can reach up to hundreds of µA/m^{2}. This large current density could be the cause of many phenomena such as tall red rays or triggering of unstable ion acoustic waves. In the present paper, we consider the issue of electrons moving through an ionospheric gas of positive ions and neutrals under the influence of a static electric field. We develop a kinetic model of collisions including electrons/electrons, electrons/ions and electrons/neutrals collisions. We use a Fokker-Planck approach to describe binary collisions between charged particles with a long-range interaction. We present the essential elements of this collision operator: the Langevin equation for electrons/ions and electrons/electrons collisions and the Monte-Carlo and null collision methods for electrons/neutrals collisions. A computational example is given illustrating the approach to equilibrium and the impact of the different terms (electrons/electrons and electrons/ions collisions on the one hand and electrons/neutrals collisions on the other hand. Then, a parallel electric field is applied in a new sample run. In this run, the electrons move in the z direction parallel to the electric field. The first results show that all the electron distribution functions are non-Maxwellian. Furthermore, runaway electrons can carry a significant part of the total current density, up to 20% of the total current density.
Comparison of kinetic and fluid neutral models for attached and detached state
International Nuclear Information System (INIS)
Furubayashi, M.; Hoshino, K.; Toma, M.; Hatayama, A.; Coster, D.; Schneider, R.; Bonnin, X.; Kawashima, H.; Asakura, N.; Suzuki, Y.
2009-01-01
Neutral behavior has an important role in the transport simulations of the edge plasma. Most of the edge plasma transport codes treat neutral particles by a simple fluid model or a kinetic model. The fluid model allows faster calculations. However, the applicability of the fluid model is limited. In this study, simulation results of JT-60U from kinetic neutral model and fluid neutral model are compared under the attached and detached state, using the 2D edge plasma code package, SOLPS5.0. In the SOL region, no significant differences are observed in the upstream plasma profiles between kinetic and fluid neutral models. However, in the divertor region, large differences are observed in plasma and neutral profiles. Therefore, further optimization of the fluid neutral model should be performed. Otherwise kinetic neutral model should be used to analyze the divertor region.
Kinetic transport model for the ELMO Bumpy Torus
International Nuclear Information System (INIS)
Jaeger, E.F.; Hedrick, C.L.; Tolliver, J.S.
1978-05-01
A bounce-averaged drift kinetic equation is solved for the toroidal plasma in the ELMO Bumpy Torus (EBT). The distribution function is assumed isotropic in pitch angle and calculated as a function of radius and speed using finite differences on a two-dimensional grid. A Fokker-Planck representation of the collision operator includes Coulomb, microwave, ionizing, and charge-exchange collisions. Ion and electron fluxes, computed as integrals of the distribution function, are of comparable magnitude for ambipolar potentials which are approximately self-consistent. Initial results assume an unperturbed distribution function which is Maxwellian; however, this is not a necessary assumption in the model. Careful accounting of loss regions where electric and magnetic poloidal drifts cancel (super banana particle orbits) leads to ion loss rates which are in some cases two orders of magnitude greater than electron rates. In these cases, radially inward pointing self-consistent electric fields occur with potentials on the order of a few times the ion temperature. These negative field results are in approximate agreement with experiment and appear to be stable to the electric field runaway encountered in positive field cases
Kinetic model of the bichromatic dark trap for atoms
Krasnov, I. V.
2017-08-01
A kinetic model of atom confinement in a bichromatic dark trap (BDT) is developed with the goal of describing its dissipative properties. The operating principle of the deep BDT is based on using the combination of multiple bichromatic cosine-Gaussian optical beams (CGBs) for creating high-potential barriers, which is described in our previous work (Krasnov 2016 Laser Phys. 26 105501). In the indicated work, particle motion in the BDT is described in terms of classical trajectories. In the present study, particle motion is analyzed by means of the Wigner function (phase-space distribution function (DF)), which allows one to properly take into account the quantum fluctuations of optical forces. Besides, we consider an improved scheme of the BDT, where CGBs create, apart from plane potential barriers, a narrow cooling layer. We find an asymptotic solution of the Fokker-Planck equation for the DF and show that the DF of particles deeply trapped in a BDT with a cooling layer is the Tsallis distribution with the effective temperature, which can be considerably lower than in a BDT without a cooling layer. Moreover, it can be adjusted by slightly changing the CGBs’ radii. We also study the effect of particle escape from the trap due to the scattering of resonant photons and show that the particle lifetime in a BDT can exceed several tens of hours when it is limited by photon scattering.
KINETIC MODELS STUDY OF HYDRODESULPHURIZATION VACUUM DISTILLATE REACTION
Directory of Open Access Journals (Sweden)
AbdulMunem A. Karim
2013-05-01
Full Text Available This study deals with kinetics of hydrodesulphurization (HDS reaction of vacuum gas oil (611-833 K which was distillated from Kirkuk crude oil and which was obtained by blending the fractions, light vacuum gas oil (611 - 650 K, medium vacuum gas oil (650-690 K, heavy vacuum gas oil (690-727 K and very heavy vacuum gas oil (727-833 K. The vacuum gas oil was hydrotreated on a commercial cobalt-molybdenum alumina catalyst presulfied at specified conditions in a laboratory trickle bed reactor. The reaction temperature range (583-643 K,liquid hourly space velocity range (1.5-3.75 h-1 and hydrogen pressure was kept constant at 3.5 MPa with hydrogen to oil ratio about 250 lt/lt. The conversion results for desulphurization reaction appeared to obey the second order reaction. According to this model, the rate constants for desulphurization reaction were determined. Finally, the apparent activation energy (Ea, enthalpy of activation ( H* and entropy ( S* were calculated based on the values of rate constant (k2 and were equal 80.3792 KJ/mole, 75.2974 KJ/mole and 197.493 J/mole, respectively.
MIDAS/PK code development using point kinetics model
International Nuclear Information System (INIS)
Song, Y. M.; Park, S. H.
1999-01-01
In this study, a MIDAS/PK code has been developed for analyzing the ATWS (Anticipated Transients Without Scram) which can be one of severe accident initiating events. The MIDAS is an integrated computer code based on the MELCOR code to develop a severe accident risk reduction strategy by Korea Atomic Energy Research Institute. In the mean time, the Chexal-Layman correlation in the current MELCOR, which was developed under a BWR condition, is appeared to be inappropriate for a PWR. So as to provide ATWS analysis capability to the MIDAS code, a point kinetics module, PKINETIC, has first been developed as a stand-alone code whose reference model was selected from the current accident analysis codes. In the next step, the MIDAS/PK code has been developed via coupling PKINETIC with the MIDAS code by inter-connecting several thermal hydraulic parameters between the two codes. Since the major concern in the ATWS analysis is the primary peak pressure during the early few minutes into the accident, the peak pressure from the PKINETIC module and the MIDAS/PK are compared with the RETRAN calculations showing a good agreement between them. The MIDAS/PK code is considered to be valuable for analyzing the plant response during ATWS deterministically, especially for the early domestic Westinghouse plants which rely on the operator procedure instead of an AMSAC (ATWS Mitigating System Actuation Circuitry) against ATWS. This capability of ATWS analysis is also important from the view point of accident management and mitigation
Kinetic modeling of formic acid pulping of bagasse.
Tu, Qiliang; Fu, Shiyu; Zhan, Huaiyu; Chai, Xinsheng; Lucia, Lucian A
2008-05-14
Organic solvent or organosolv pulping processes are alternatives to soda or kraft pulping to delignify lignocellulosic materials for the production of paper pulp. Formic acid, a typical organosolv system, has been presently examined under atmospheric pressure to pulp bagasse fibers. It was shown that efficient bagasse pulping was achieved when the formic acid concentration was limited to 90% (v/v). A statistical kinetic model based on the experimental results for the delignification of bagasse during formic acid pulping was developed that can be described as follows: D (delignification) = 0.747 x C(formicacid) (1.688) x (1 - e(-0.05171t)), an equation that can be used to predict the lignin content in formic acid during the pulping process. The delignification of bagasse by 90% formic acid was almost completed after approximately 80 min, while extended pulping did not improve the delignification but tended to degrade the carbohydrates in bagasse, especially the hemicelluloses, which were rapidly hydrolyzed at the onset of pulping.
Kinetic modelling of runaway electron avalanches in tokamak plasmas
International Nuclear Information System (INIS)
Nilsson, E; Peysson, Y; Saint-Laurent, F; Decker, J; Granetz, R S; Vlainic, M
2015-01-01
Runaway electrons can be generated in tokamak plasmas if the accelerating force from the toroidal electric field exceeds the collisional drag force owing to Coulomb collisions with the background plasma. In ITER, disruptions are expected to generate runaway electrons mainly through knock-on collisions (Hender et al 2007 Nucl. Fusion 47 S128–202), where enough momentum can be transferred from existing runaways to slow electrons to transport the latter beyond a critical momentum, setting off an avalanche of runaway electrons. Since knock-on runaways are usually scattered off with a significant perpendicular component of the momentum with respect to the local magnetic field direction, these particles are highly magnetized. Consequently, the momentum dynamics require a full 3D kinetic description, since these electrons are highly sensitive to the magnetic non-uniformity of a toroidal configuration. For this purpose, a bounce-averaged knock-on source term is derived. The generation of runaway electrons from the combined effect of Dreicer mechanism and knock-on collision process is studied with the code LUKE, a solver of the 3D linearized bounce-averaged relativistic electron Fokker–Planck equation (Decker and Peysson 2004 DKE: a fast numerical solver for the 3D drift kinetic equation Report EUR-CEA-FC-1736, Euratom-CEA), through the calculation of the response of the electron distribution function to a constant parallel electric field. The model, which has been successfully benchmarked against the standard Dreicer runaway theory now describes the runaway generation by knock-on collisions as proposed by Rosenbluth (Rosenbluth and Putvinski 1997 Nucl. Fusion 37 1355–62). This paper shows that the avalanche effect can be important even in non-disruptive scenarios. Runaway formation through knock-on collisions is found to be strongly reduced when taking place off the magnetic axis, since trapped electrons can not contribute to the runaway electron population. Finally
Elimination kinetic model for organic chemicals in earthworms.
Dimitrova, N.; Dimitrov, S.; Georgieva, D.; van Gestel, C.A.M.; Hankard, P.; Spurgeon, D.J.; Li, H.; Mekenyan, O.
2010-01-01
Mechanistic understanding of bioaccumulation in different organisms and environments should take into account the influence of organism and chemical depending factors on the uptake and elimination kinetics of chemicals. Lipophilicity, metabolism, sorption (bioavailability) and biodegradation of
Modelling of the enzymatic kinetically controlled synthesis of cephalexin
Schroën, C.G.P.H.; Fretz, C.B.; Bruin, de V.H.; Berendsen, W.; Moody, H.M.; Roos, E.C.; Roon, van J.L.; Kroon, P.J.; Strubel, M.; Janssen, A.E.M.; Tramper, J.
2002-01-01
In this study the influence of diffusion limitation on enzymatic kinetically controlled cephalexin synthesis from phenylglycine amide and 7-aminodeacetoxycephalosporinic acid (7-ADCA) was investigated systematically. It was found that if diffusion limitation occurred, both the synthesis/hydrolysis
Extended symmetries of the kinetic plasma theory models
International Nuclear Information System (INIS)
Taranov, V.B.
2005-01-01
Symmetry extension of the kinetic theory of collisionless plasma containing particles with equal charge to mass ratio is considered. It is shown that this symmetry allows us to reduce the number of equations. Symmetries obtained for the integro-differential equations of the kinetic theory by the indirect algorithm are compared to those obtained by direct methods. The importance of additional conditions - positiveness and integrability of distribution functions, existence of their moments - is underlined
DEFF Research Database (Denmark)
Chambon, Julie Claire Claudia; Bjerg, Poul Løgstrup; Scheutz, Charlotte
2013-01-01
Reductive dechlorination is a major degradation pathway of chlorinated ethenes in anaerobic subsurface environments, and reactive kinetic models describing the degradation process are needed in fate and transport models of these contaminants. However, reductive dechlorination is a complex biologi...
Decarboxylation of Δ 9-tetrahydrocannabinol: Kinetics and molecular modeling
Perrotin-Brunel, Helene; Buijs, Wim; van Spronsen, Jaap; van Roosmalen, Maaike J. E.; Peters, Cor J.; Verpoorte, Rob; Witkamp, Geert-Jan
2011-02-01
Efficient tetrahydrocannabinol (Δ 9-THC) production from cannabis is important for its medical application and as basis for the development of production routes of other drugs from plants. This work presents one of the steps of Δ 9-THC production from cannabis plant material, the decarboxylation reaction, transforming the Δ 9-THC-acid naturally present in the plant into the psychoactive Δ 9-THC. Results of experiments showed pseudo-first order reaction kinetics, with an activation barrier of 85 kJ mol -1 and a pre-exponential factor of 3.7 × 10 8 s -1. Using molecular modeling, two options were identified for an acid catalyzed β-keto acid type mechanism for the decarboxylation of Δ 9-THC-acid. Each of these mechanisms might play a role, depending on the actual process conditions. Formic acid proved to be a good model for a catalyst of such a reaction. Also, the computational idea of catalysis by water to catalysis by an acid, put forward by Li and Brill, and Churchev and Belbruno was extended, and a new direct keto-enol route was found. A direct keto-enol mechanism catalyzed by formic acid seems to be the best explanation for the observed activation barrier and the pre-exponential factor of the decarboxylation of Δ 9-THC-acid. Evidence for this was found by performing an extraction experiment with Cannabis Flos. It revealed the presence of short chain carboxylic acids supporting this hypothesis. The presented approach is important for the development of a sustainable production of Δ 9-THC from the plant.
Study and discretization of kinetic models and fluid models at low Mach number
International Nuclear Information System (INIS)
Dellacherie, Stephane
2011-01-01
This thesis summarizes our work between 1995 and 2010. It concerns the analysis and the discretization of Fokker-Planck or semi-classical Boltzmann kinetic models and of Euler or Navier-Stokes fluid models at low Mach number. The studied Fokker-Planck equation models the collisions between ions and electrons in a hot plasma, and is here applied to the inertial confinement fusion. The studied semi-classical Boltzmann equations are of two types. The first one models the thermonuclear reaction between a deuterium ion and a tritium ion producing an α particle and a neutron particle, and is also in our case used to describe inertial confinement fusion. The second one (known as the Wang-Chang and Uhlenbeck equations) models the transitions between electronic quantified energy levels of uranium and iron atoms in the AVLIS isotopic separation process. The basic properties of these two Boltzmann equations are studied, and, for the Wang-Chang and Uhlenbeck equations, a kinetic-fluid coupling algorithm is proposed. This kinetic-fluid coupling algorithm incited us to study the relaxation concept for gas and immiscible fluids mixtures, and to underline connections with classical kinetic theory. Then, a diphasic low Mach number model without acoustic waves is proposed to model the deformation of the interface between two immiscible fluids induced by high heat transfers at low Mach number. In order to increase the accuracy of the results without increasing computational cost, an AMR algorithm is studied on a simplified interface deformation model. These low Mach number studies also incited us to analyse on cartesian meshes the inaccuracy at low Mach number of Godunov schemes. Finally, the LBM algorithm applied to the heat equation is justified
Large scale structures in the kinetic gravity braiding model that can be unbraided
International Nuclear Information System (INIS)
Kimura, Rampei; Yamamoto, Kazuhiro
2011-01-01
We study cosmological consequences of a kinetic gravity braiding model, which is proposed as an alternative to the dark energy model. The kinetic braiding model we study is characterized by a parameter n, which corresponds to the original galileon cosmological model for n = 1. We find that the background expansion of the universe of the kinetic braiding model is the same as the Dvali-Turner's model, which reduces to that of the standard cold dark matter model with a cosmological constant (ΛCDM model) for n equal to infinity. We also find that the evolution of the linear cosmological perturbation in the kinetic braiding model reduces to that of the ΛCDM model for n = ∞. Then, we focus our study on the growth history of the linear density perturbation as well as the spherical collapse in the nonlinear regime of the density perturbations, which might be important in order to distinguish between the kinetic braiding model and the ΛCDM model when n is finite. The theoretical prediction for the large scale structure is confronted with the multipole power spectrum of the luminous red galaxy sample of the Sloan Digital Sky survey. We also discuss future prospects of constraining the kinetic braiding model using a future redshift survey like the WFMOS/SuMIRe PFS survey as well as the cluster redshift distribution in the South Pole Telescope survey
Analysis of a kinetic multi-segment foot model. Part I: Model repeatability and kinematic validity.
Bruening, Dustin A; Cooney, Kevin M; Buczek, Frank L
2012-04-01
Kinematic multi-segment foot models are still evolving, but have seen increased use in clinical and research settings. The addition of kinetics may increase knowledge of foot and ankle function as well as influence multi-segment foot model evolution; however, previous kinetic models are too complex for clinical use. In this study we present a three-segment kinetic foot model and thorough evaluation of model performance during normal gait. In this first of two companion papers, model reference frames and joint centers are analyzed for repeatability, joint translations are measured, segment rigidity characterized, and sample joint angles presented. Within-tester and between-tester repeatability were first assessed using 10 healthy pediatric participants, while kinematic parameters were subsequently measured on 17 additional healthy pediatric participants. Repeatability errors were generally low for all sagittal plane measures as well as transverse plane Hindfoot and Forefoot segments (median<3°), while the least repeatable orientations were the Hindfoot coronal plane and Hallux transverse plane. Joint translations were generally less than 2mm in any one direction, while segment rigidity analysis suggested rigid body behavior for the Shank and Hindfoot, with the Forefoot violating the rigid body assumptions in terminal stance/pre-swing. Joint excursions were consistent with previously published studies. Copyright © 2012 Elsevier B.V. All rights reserved.
Modelling of elementary kinetics of H2 and CO oxidation on ceria pattern cells
International Nuclear Information System (INIS)
Patel, HC; Tabish, AN; Aravind, PV
2015-01-01
Elementary kinetic mechanisms of fuel oxidation on ceria have not been dealt with in detail in literature. An elementary kinetic model is developed considering charge transfer and adsorption steps for electrochemical H 2 and CO oxidation on ceria. The reaction chemistry is solved by fitting previously obtained impedance spectra for H 2 and CO oxidation on ceria. The rate determining step is found to be the charge transfer rather than the adsorption for both H 2 and CO. A method is presented to extend the kinetics obtained from pattern anodes to macroscopic simulations in which the activation overvoltage can be calculated on the basis of elementary kinetics.
A detailed chemical kinetic model for pyrolysis of the lignin model compound chroman
Directory of Open Access Journals (Sweden)
James Bland
2013-12-01
Full Text Available The pyrolysis of woody biomass, including the lignin component, is emerging as a potential technology for the production of renewable fuels and commodity chemicals. Here we describe the construction and implementation of an elementary chemical kinetic model for pyrolysis of the lignin model compound chroman and its reaction intermediate ortho-quinone methide (o-QM. The model is developed using both experimental and theoretical data, and represents a hybrid approach to kinetic modeling that has the potential to provide molecular level insight into reaction pathways and intermediates while accurately describing reaction rates and product formation. The kinetic model developed here can replicate all known aspects of chroman pyrolysis, and provides new information on elementary reaction steps. Chroman pyrolysis is found to proceed via an initial retro-Diels–Alder reaction to form o-QM + ethene (C2H4, followed by dissociation of o-QM to the C6H6 isomers benzene and fulvene (+ CO. At temperatures of around 1000–1200 K and above fulvene rapidly isomerizes to benzene, where an activation energy of around 270 kJ mol-1 is required to reproduce experimental observations. A new G3SX level energy surface for the isomerization of fulvene to benzene supports this result. Our modeling also suggests that thermal decomposition of fulvene may be important at around 950 K and above. This study demonstrates that theoretical protocols can provide a significant contribution to the development of kinetic models for biomass pyrolysis by elucidating reaction mechanisms, intermediates, and products, and also by supplying realistic rate coefficients and thermochemical properties.
Modeling of hydrogen production methods: Single particle model and kinetics assessment
Energy Technology Data Exchange (ETDEWEB)
Miller, R.S.; Bellan, J. [California Institute of Technology, Pasadena, CA (United States)
1996-10-01
The investigation carried out by the Jet Propulsion Laboratory (JPL) is devoted to the modeling of biomass pyrolysis reactors producing an oil vapor (tar) which is a precursor to hydrogen. This is an informal collaboration with NREL whereby JPL uses the experimentally-generated NREL data both as initial and boundary conditions for the calculations, and as a benchmark for model validation. The goal of this investigation is to find drivers of biomass fast-pyrolysis in the low temperature regime. The rationale is that experimental observations produce sparse discrete conditions for model validation, and that numerical simulations produced with a validated model are an economic way to find control parameters and an optimal operation regime, thereby circumventing costly changes in hardware and tests. During this first year of the investigation, a detailed mathematical model has been formulated for the temporal and spatial accurate modeling of solid-fluid reactions in biomass particles. These are porous particles for which volumetric reaction rate data is known a priori and both the porosity and the permeability of the particle are large enough to allow for continuous gas phase flow. The methodology has been applied to the pyrolysis of spherically symmetric biomass particles by considering previously published kinetics schemes for both cellulose and wood. The results show that models which neglect the thermal and species boundary layers exterior to the particle will generally over predict both the pyrolysis rates and experimentally obtainable tar yields. An evaluation of the simulation results through comparisons with experimental data indicates that while the cellulose kinetics is reasonably accurate, the wood pyrolysis kinetics is not accurate; particularly at high reactor temperatures. Current effort in collaboration with NREL is aimed at finding accurate wood kinetics.
Rout, Bapin Kumar; Brooks, Geoffrey; Akbar Rhamdhani, M.; Li, Zushu; Schrama, Frank N. H.; Overbosch, Aart
2018-03-01
In a previous study by the authors (Rout et al. in Metall Mater Trans B 49:537-557, 2018), a dynamic model for the BOF, employing the concept of multizone kinetics was developed. In the current study, the kinetics of decarburization reaction is investigated. The jet impact and slag-metal emulsion zones were identified to be primary zones for carbon oxidation. The dynamic parameters in the rate equation of decarburization such as residence time of metal drops in the emulsion, interfacial area evolution, initial size, and the effects of surface-active oxides have been included in the kinetic rate equation of the metal droplet. A modified mass-transfer coefficient based on the ideal Langmuir adsorption equilibrium has been proposed to take into account the surface blockage effects of SiO2 and P2O5 in slag on the decarburization kinetics of a metal droplet in the emulsion. Further, a size distribution function has been included in the rate equation to evaluate the effect of droplet size on reaction kinetics. The mathematical simulation indicates that decarburization of the droplet in the emulsion is a strong function of the initial size and residence time. A modified droplet generation rate proposed previously by the authors has been used to estimate the total decarburization rate by slag-metal emulsion. The model's prediction shows that about 76 pct of total carbon is removed by reactions in the emulsion, and the remaining is removed by reactions at the jet impact zone. The predicted bath carbon by the model has been found to be in good agreement with the industrially measured data.
Rout, Bapin Kumar; Brooks, Geoffrey; Akbar Rhamdhani, M.; Li, Zushu; Schrama, Frank N. H.; Overbosch, Aart
2018-06-01
In a previous study by the authors (Rout et al. in Metall Mater Trans B 49:537-557, 2018), a dynamic model for the BOF, employing the concept of multizone kinetics was developed. In the current study, the kinetics of decarburization reaction is investigated. The jet impact and slag-metal emulsion zones were identified to be primary zones for carbon oxidation. The dynamic parameters in the rate equation of decarburization such as residence time of metal drops in the emulsion, interfacial area evolution, initial size, and the effects of surface-active oxides have been included in the kinetic rate equation of the metal droplet. A modified mass-transfer coefficient based on the ideal Langmuir adsorption equilibrium has been proposed to take into account the surface blockage effects of SiO2 and P2O5 in slag on the decarburization kinetics of a metal droplet in the emulsion. Further, a size distribution function has been included in the rate equation to evaluate the effect of droplet size on reaction kinetics. The mathematical simulation indicates that decarburization of the droplet in the emulsion is a strong function of the initial size and residence time. A modified droplet generation rate proposed previously by the authors has been used to estimate the total decarburization rate by slag-metal emulsion. The model's prediction shows that about 76 pct of total carbon is removed by reactions in the emulsion, and the remaining is removed by reactions at the jet impact zone. The predicted bath carbon by the model has been found to be in good agreement with the industrially measured data.
Modelling fungal solid-state fermentation: The role of inactivation kinetics
Smits, J.P.; Sonsbeek, H.M. van; Knol, W.; Tramper, J.; Geelhoed, W.; Peeters, M.; Rinzema, A.
1999-01-01
The theoretical mathematical models described in this paper are used to evaluate the effects of fungal biomass inactivation kinetics on a non- isothermal tray solid-state fermentation (SSF). The inactivation kinetics, derived from previously reported experiments done under isothermal conditions and
Kinetic model for an up-flow anaerobic packed bed bioreactor: Dairy ...
African Journals Online (AJOL)
Kinetic studies of anaerobic digestion process of cheese whey were conducted in a pilot-scale up-flow anaerobic packed bed bioreactor (UAPB). An influent COD concentration of 59419 mg/l was utilized at steady state condition. Logistic and Monod kinetic models were employed to describe microbial activities of cheese ...
DEFF Research Database (Denmark)
Price, Jason Anthony; Nordblad, Mathias; Woodley, John
2014-01-01
This paper demonstrates the added benefits of using uncertainty and sensitivity analysis in the kinetics of enzymatic biodiesel production. For this study, a kinetic model by Fedosov and co-workers is used. For the uncertainty analysis the Monte Carlo procedure was used to statistically quantify...
Seldam, C.A. ten; Groot, S.R. de
1952-01-01
From Jensen's and Gombás' modification of the statistical Thomas-Fermi atom model, a theory for compressed atoms is developed by changing the boundary conditions. Internal kinetic energy and polarizability of argon are calculated as functions of pressure. At 1000 atm. an internal kinetic energy of
Lee, Eunyoung; Cumberbatch, Jewel; Wang, Meng; Zhang, Qiong
2017-03-01
Anaerobic co-digestion has a potential to improve biogas production, but limited kinetic information is available for co-digestion. This study introduced regression-based models to estimate the kinetic parameters for the co-digestion of microalgae and Waste Activated Sludge (WAS). The models were developed using the ratios of co-substrates and the kinetic parameters for the single substrate as indicators. The models were applied to the modified first-order kinetics and Monod model to determine the rate of hydrolysis and methanogenesis for the co-digestion. The results showed that the model using a hyperbola function was better for the estimation of the first-order kinetic coefficients, while the model using inverse tangent function closely estimated the Monod kinetic parameters. The models can be used for estimating kinetic parameters for not only microalgae-WAS co-digestion but also other substrates' co-digestion such as microalgae-swine manure and WAS-aquatic plants. Copyright © 2016 Elsevier Ltd. All rights reserved.
Comparative evaluation of kinetic, equilibrium and semi-equilibrium models for biomass gasification
Energy Technology Data Exchange (ETDEWEB)
Buragohain, Buljit [Center for Energy, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India); Chakma, Sankar; Kumar, Peeush [Department of Chemical Engineering, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India); Mahanta, Pinakeswar [Center for Energy, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India); Department of Mechanical Engineering, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India); Moholkar, Vijayanand S. [Center for Energy, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India); Department of Chemical Engineering, Indian Institute of Technology Guwahati, Guwahati – 781 039, Assam (India)
2013-07-01
Modeling of biomass gasification has been an active area of research for past two decades. In the published literature, three approaches have been adopted for the modeling of this process, viz. thermodynamic equilibrium, semi-equilibrium and kinetic. In this paper, we have attempted to present a comparative assessment of these three types of models for predicting outcome of the gasification process in a circulating fluidized bed gasifier. Two model biomass, viz. rice husk and wood particles, have been chosen for analysis, with gasification medium being air. Although the trends in molar composition, net yield and LHV of the producer gas predicted by three models are in concurrence, significant quantitative difference is seen in the results. Due to rather slow kinetics of char gasification and tar oxidation, carbon conversion achieved in single pass of biomass through the gasifier, calculated using kinetic model, is quite low, which adversely affects the yield and LHV of the producer gas. Although equilibrium and semi-equilibrium models reveal relative insensitivity of producer gas characteristics towards temperature, the kinetic model shows significant effect of temperature on LHV of the gas at low air ratios. Kinetic models also reveal volume of the gasifier to be an insignificant parameter, as the net yield and LHV of the gas resulting from 6 m and 10 m riser is same. On a whole, the analysis presented in this paper indicates that thermodynamic models are useful tools for quantitative assessment of the gasification process, while kinetic models provide physically more realistic picture.
International Nuclear Information System (INIS)
Mieussens, Luc
2013-01-01
The unified gas kinetic scheme (UGKS) of K. Xu et al. (2010) [37], originally developed for multiscale gas dynamics problems, is applied in this paper to a linear kinetic model of radiative transfer theory. While such problems exhibit purely diffusive behavior in the optically thick (or small Knudsen) regime, we prove that UGKS is still asymptotic preserving (AP) in this regime, but for the free transport regime as well. Moreover, this scheme is modified to include a time implicit discretization of the limit diffusion equation, and to correctly capture the solution in case of boundary layers. Contrary to many AP schemes, this method is based on a standard finite volume approach, it does neither use any decomposition of the solution, nor staggered grids. Several numerical tests demonstrate the properties of the scheme
Evaluation of kinetic uncertainty in numerical models of petroleum generation
Peters, K.E.; Walters, C.C.; Mankiewicz, P.J.
2006-01-01
Oil-prone marine petroleum source rocks contain type I or type II kerogen having Rock-Eval pyrolysis hydrogen indices greater than 600 or 300-600 mg hydrocarbon/g total organic carbon (HI, mg HC/g TOC), respectively. Samples from 29 marine source rocks worldwide that contain mainly type II kerogen (HI = 230-786 mg HC/g TOC) were subjected to open-system programmed pyrolysis to determine the activation energy distributions for petroleum generation. Assuming a burial heating rate of 1??C/m.y. for each measured activation energy distribution, the calculated average temperature for 50% fractional conversion of the kerogen in the samples to petroleum is approximately 136 ?? 7??C, but the range spans about 30??C (???121-151??C). Fifty-two outcrop samples of thermally immature Jurassic Oxford Clay Formation were collected from five locations in the United Kingdom to determine the variations of kinetic response for one source rock unit. The samples contain mainly type I or type II kerogens (HI = 230-774 mg HC/g TOC). At a heating rate of 1??C/m.y., the calculated temperatures for 50% fractional conversion of the Oxford Clay kerogens to petroleum differ by as much as 23??C (127-150??C). The data indicate that kerogen type, as defined by hydrogen index, is not systematically linked to kinetic response, and that default kinetics for the thermal decomposition of type I or type II kerogen can introduce unacceptable errors into numerical simulations. Furthermore, custom kinetics based on one or a few samples may be inadequate to account for variations in organofacies within a source rock. We propose three methods to evaluate the uncertainty contributed by kerogen kinetics to numerical simulations: (1) use the average kinetic distribution for multiple samples of source rock and the standard deviation for each activation energy in that distribution; (2) use source rock kinetics determined at several locations to describe different parts of the study area; and (3) use a weighted
Point kinetics model with one-dimensional (radial) heat conduction formalism
International Nuclear Information System (INIS)
Jain, V.K.
1989-01-01
A point-kinetics model with one-dimensional (radial) heat conduction formalism has been developed. The heat conduction formalism is based on corner-mesh finite difference method. To get average temperatures in various conducting regions, a novel weighting scheme has been devised. The heat conduction model has been incorporated in the point-kinetics code MRTF-FUEL. The point-kinetics equations are solved using the method of real integrating factors. It has been shown by analysing the simulation of hypothetical loss of regulation accident in NAPP reactor that the model is superior to the conventional one in accuracy and speed of computation. (author). 3 refs., 3 tabs
International Nuclear Information System (INIS)
De-Santiago, Josue; Cervantes-Cota, Jorge L.
2011-01-01
We study a unification model for dark energy, dark matter, and inflation with a single scalar field with noncanonical kinetic term. In this model, the kinetic term of the Lagrangian accounts for the dark matter and dark energy, and at early epochs, a quadratic potential accounts for slow roll inflation. The present work is an extension to the work by Bose and Majumdar [Phys. Rev. D 79, 103517 (2009).] with a more general kinetic term that was proposed by Chimento in Phys. Rev. D 69, 123517 (2004). We demonstrate that the model is viable at the background and linear perturbation levels.
Behaviour of defective CANDU fuel: fuel oxidation kinetic and thermodynamic modelling
International Nuclear Information System (INIS)
Higgs, J.
2005-01-01
The thermal performance of operating CANDU fuel under defect conditions is affected by the ingress of heavy water into the fuel element. A mechanistic model has been developed to predict the extent of fuel oxidation in defective fuel and its affect on fuel thermal performance. A thermodynamic treatment of such oxidized fuel has been performed as a basis for the boundary conditions in the kinetic model. Both the kinetic and thermodynamic models have been benchmarked against recent experimental work. (author)
Energy Technology Data Exchange (ETDEWEB)
Kruse, A.; Keskin, M.; Faquir, M.; Dahmen, N. [Inst. fuer Technische Chemie, Forschungszentrum Karlsruhe (Germany)
2008-07-01
Hydrothermal biomass gasification is a promising technology to produce hydrogen from wet biomass, i.e. a water content of at least 50 %. This process allows the utilization of agricultural wastes or residuals from biochemical conversions. Since the reaction is highly kinetically controlled, it should be possible to optimimize gas yield and composition with respect to a maximum hydrogen yield. The paper describes the simulation of the process using a kinetic reaction model and experimental data from appropriate test facilities. Experiments were performed for several reactor types and a variety of model systems, like glucose, methane and hydroxy methyl furfural, that were identified as intermediate product for the hydrothermal hydrogen production. The influence of different additive 'catalysts' was tested. It was shown that the biomass composition has an important influence on the gas yield. Alkaline salts can be added to increase the yield. A fast heating and agitation of the biomass are also increasing the gas yield.
Relations between the kinetic equation and the Langevin models in two-phase flow modelling
International Nuclear Information System (INIS)
Minier, J.P.; Pozorski, J.
1997-05-01
The purpose of this paper is to discuss PDF and stochastic models which are used in two-phase flow modelling. The aim of the present analysis is essentially to try to determine relations and consistency between different models. It is first recalled that different approaches actually correspond to PDF models written either in terms of the process trajectories or in terms of the PDF itself. The main difference lies in the choice of the independent variables which are retained. Two particular models are studied, the Kinetic Equation and the Langevin Equation model. The latter uses a Langevin equation to model the fluid velocities seen along particle trajectories. The Langevin model is more general since it contains an additional variable. It is shown that, in certain cases, this variable can be summed up exactly to retrieve the Kinetic Equation model as a marginal PDF. A joint fluid and solid particle PDF which includes the characteristics of both phases is proposed at the end of the paper. (author)
Ordering kinetics in model systems with inhibited interfacial adsorption
DEFF Research Database (Denmark)
Willart, J.-F.; Mouritsen, Ole G.; Naudts, J.
1992-01-01
. The results are related to experimental work on ordering processes in orientational glasses. It is suggested that the experimental observation of very slow ordering kinetics in, e.g., glassy crystals of cyanoadamantane may be a consequence of low-temperature activated processes which ultimately lead...
Calcite growth kinetics: Modeling the effect of solution stoichiometry
Wolthers, M.; Nehrke, G.; Gustafsson, J.P.; Van Cappellen, P.
2012-01-01
Until recently the influence of solution stoichiometry on calcite crystal growth kinetics has attracted little attention, despite the fact that in most aqueous environments calcite precipitates from non-stoichiometric solution. In order to account for the dependence of the calcite crystal growth
Unanimous Model for Describing the Fast Bioluminescence Kinetics of Ca
Eremeeva, Elena V.; Bartsev, Sergey I.; Berkel, van Willem J.H.; Vysotski, Eugene S.
2017-01-01
Upon binding their metal ion cofactors, Ca2+-regulated photoproteins display a rapid increase of light signal, which reaches its peak within milliseconds. In the present study, we investigate bioluminescence kinetics of the entire photoprotein family. All five recombinant hydromedusan Ca2+-regulated
Unravelling the Maillard reaction network by multiresponse kinetic modelling
Martins, S.I.F.S.
2003-01-01
The Maillard reaction is an important reaction in food industry. It is responsible for the formation of colour and aroma, as well as toxic compounds as the recent discovered acrylamide. The knowledge of kinetic parameters, such as rate constants and activation energy, is necessary to predict its
Dynamic Modeling of Cell-Free Biochemical Networks Using Effective Kinetic Models
2015-03-03
based whole-cell models of E. coli [6]. Conversely , highly abstracted kinetic frameworks, such as the cybernetic framework, represented a paradigm shift...metabolic objective function has been the optimization of biomass formation [18], although other metabolic objectives have also been estimated [19...experimental data. Toward these questions, we explored five hypothetical cell-free networks. Each network shared the same enzymatic connectivity, but
Rout, Bapin Kumar; Brooks, Geoff; Rhamdhani, M. Akbar; Li, Zushu; Schrama, Frank N. H.; Sun, Jianjun
2018-04-01
A multi-zone kinetic model coupled with a dynamic slag generation model was developed for the simulation of hot metal and slag composition during the basic oxygen furnace (BOF) operation. The three reaction zones (i) jet impact zone, (ii) slag-bulk metal zone, (iii) slag-metal-gas emulsion zone were considered for the calculation of overall refining kinetics. In the rate equations, the transient rate parameters were mathematically described as a function of process variables. A micro and macroscopic rate calculation methodology (micro-kinetics and macro-kinetics) were developed to estimate the total refining contributed by the recirculating metal droplets through the slag-metal emulsion zone. The micro-kinetics involves developing the rate equation for individual droplets in the emulsion. The mathematical models for the size distribution of initial droplets, kinetics of simultaneous refining of elements, the residence time in the emulsion, and dynamic interfacial area change were established in the micro-kinetic model. In the macro-kinetics calculation, a droplet generation model was employed and the total amount of refining by emulsion was calculated by summing the refining from the entire population of returning droplets. A dynamic FetO generation model based on oxygen mass balance was developed and coupled with the multi-zone kinetic model. The effect of post-combustion on the evolution of slag and metal composition was investigated. The model was applied to a 200-ton top blowing converter and the simulated value of metal and slag was found to be in good agreement with the measured data. The post-combustion ratio was found to be an important factor in controlling FetO content in the slag and the kinetics of Mn and P in a BOF process.
Phase-field modeling of corrosion kinetics under dual-oxidants
Wen, You-Hai; Chen, Long-Qing; Hawk, Jeffrey A.
2012-04-01
A phase-field model is proposed to simulate corrosion kinetics under a dual-oxidant atmosphere. It will be demonstrated that the model can be applied to simulate corrosion kinetics under oxidation, sulfidation and simultaneous oxidation/sulfidation processes. Phase-dependent diffusivities are incorporated in a natural manner and allow more realistic modeling as the diffusivities usually differ by many orders of magnitude in different phases. Simple free energy models are then used for testing the model while calibrated free energy models can be implemented for quantitative modeling.
Carlsson, Philip T. M.; Zeuch, Thomas
2018-03-01
We have developed a new model utilizing our existing kinetic gas phase models to simulate experimental particle size distributions emerging in dry supersaturated H2SO4 vapor homogeneously produced by rapid oxidation of SO2 through stabilized Criegee-Intermediates from 2-butene ozonolysis. We use a sectional method for simulating the particle dynamics. The particle treatment in the model is based on first principles and takes into account the transition from the kinetic to the diffusion-limited regime. It captures the temporal evolution of size distributions at the end of the ozonolysis experiment well, noting a slight underrepresentation of coagulation effects for larger particle sizes. The model correctly predicts the shape and the modes of the experimentally observed particle size distributions. The predicted modes show an extremely high sensitivity to the H2SO4 evaporation rates of the initially formed H2SO4 clusters (dimer to pentamer), which were arbitrarily restricted to decrease exponentially with increasing cluster size. In future, the analysis presented in this work can be extended to allow a direct validation of quantum chemically predicted stabilities of small H2SO4 clusters, which are believed to initiate a significant fraction of atmospheric new particle formation events. We discuss the prospects and possible limitations of the here presented approach.
Rapid prototyping of microbial cell factories via genome-scale engineering.
Si, Tong; Xiao, Han; Zhao, Huimin
2015-11-15
Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. Copyright © 2014 Elsevier Inc. All rights reserved.
Rapid Prototyping of Microbial Cell Factories via Genome-scale Engineering
Si, Tong; Xiao, Han; Zhao, Huimin
2014-01-01
Advances in reading, writing and editing genetic materials have greatly expanded our ability to reprogram biological systems at the resolution of a single nucleotide and on the scale of a whole genome. Such capacity has greatly accelerated the cycles of design, build and test to engineer microbes for efficient synthesis of fuels, chemicals and drugs. In this review, we summarize the emerging technologies that have been applied, or are potentially useful for genome-scale engineering in microbial systems. We will focus on the development of high-throughput methodologies, which may accelerate the prototyping of microbial cell factories. PMID:25450192
Experimental and Chemical Kinetic Modeling Study of Dimethylcyclohexane Oxidation and Pyrolysis
Eldeeb, Mazen A.; Jouzdani, Shirin; Wang, Zhandong; Sarathy, Mani; Akih-Kumgeh, Benjamin
2016-01-01
A combined experimental and chemical kinetic modeling study of the high-temperature ignition and pyrolysis of 1,3-dimethylcyclohexane (13DMCH) is presented. Ignition delay times are measured behind reflected shock waves over a temperature range
Experimental and Kinetic Modeling Study of Ethyl Levulinate Oxidation in a Jet-Stirred Reactor
Wang, Jui-Yang
2017-01-01
levulinate chemical kinetic model was first developed by Dr. Stephen Dooley, Trinity College Dublin, and simulated under the same conditions, using the Perfect-Stirred Reactor code in Chemkin software. In comparing the simulation results with experimental
Jia, X.; Slavin, J.; Chen, Y.; Poh, G.; Toth, G.; Gombosi, T.
2018-05-01
We present results from state-of-the-art global models of Mercury's space environment capable of self-consistently simulating the induction effect at the core and resolving kinetic physics important for magnetic reconnection.
New Procedure to Develop Lumped Kinetic Models for Heavy Fuel Oil Combustion
Han, Yunqing; Elbaz, Ayman M.; Roberts, William L.; Im, Hong G.
2016-01-01
A new procedure to develop accurate lumped kinetic models for complex fuels is proposed, and applied to the experimental data of the heavy fuel oil measured by thermogravimetry. The new procedure is based on the pseudocomponents representing
Wang, Weicheng; Natelson, Robert H.; Stikeleather, Larry F.; Roberts, William L.
2013-01-01
A chemical kinetic model has been developed for the transient stage of the continuous countercurrent hydrolysis of triglycerides to free fatty acids and glycerol. Departure functions and group contribution methods were applied to determine
Temperature-Dependent Kinetics of Grape Seed Phenolic Compounds Extraction: Experiment and Model
Czech Academy of Sciences Publication Activity Database
Bucic´-Kojic´, A.; Sovová, Helena; Planinic´, M.; Tomas, S.
2013-01-01
Roč. 136, 3-4 (2013), s. 1136-1140 ISSN 0308-8146 Institutional support: RVO:67985858 Keywords : kinetics modelling * temperature * grape seed Subject RIV: CI - Industrial Chemistry, Chemical Engineering Impact factor: 3.259, year: 2013
Chu, Khim Hoong
2017-11-09
Surface diffusion coefficients may be estimated by fitting solutions of a diffusion model to batch kinetic data. For non-linear systems, a numerical solution of the diffusion model's governing equations is generally required. We report here the application of the classic Langmuir kinetics model to extract surface diffusion coefficients from batch kinetic data. The use of the Langmuir kinetics model in lieu of the conventional surface diffusion model allows derivation of an analytical expression. The parameter estimation procedure requires determining the Langmuir rate coefficient from which the pertinent surface diffusion coefficient is calculated. Surface diffusion coefficients within the 10 -9 to 10 -6 cm 2 /s range obtained by fitting the Langmuir kinetics model to experimental kinetic data taken from the literature are found to be consistent with the corresponding values obtained from the traditional surface diffusion model. The virtue of this simplified parameter estimation method is that it reduces the computational complexity as the analytical expression involves only an algebraic equation in closed form which is easily evaluated by spreadsheet computation.
Oxygen reduction kinetics on mixed conducting SOFC model cathodes
Energy Technology Data Exchange (ETDEWEB)
Baumann, F.S.
2006-07-01
The kinetics of the oxygen reduction reaction at the surface of mixed conducting solid oxide fuel cell (SOFC) cathodes is one of the main limiting factors to the performance of these promising systems. For ''realistic'' porous electrodes, however, it is usually very difficult to separate the influence of different resistive processes. Therefore, a suitable, geometrically well-defined model system was used in this work to enable an unambiguous distinction of individual electrochemical processes by means of impedance spectroscopy. The electrochemical measurements were performed on dense thin film microelectrodes, prepared by PLD and photolithography, of mixed conducting perovskite-type materials. The first part of the thesis consists of an extensive impedance spectroscopic investigation of La0.6Sr0.4Co0.8Fe0.2O3 (LSCF) microelectrodes. An equivalent circuit was identified that describes the electrochemical properties of the model electrodes appropriately and enables an unambiguous interpretation of the measured impedance spectra. Hence, the dependencies of individual electrochemical processes such as the surface exchange reaction on a wide range of experimental parameters including temperature, dc bias and oxygen partial pressure could be studied. As a result, a comprehensive set of experimental data has been obtained, which was previously not available for a mixed conducting model system. In the course of the experiments on the dc bias dependence of the electrochemical processes a new and surprising effect was discovered: It could be shown that a short but strong dc polarisation of a LSCF microelectrode at high temperature improves its electrochemical performance with respect to the oxygen reduction reaction drastically. The electrochemical resistance associated with the oxygen surface exchange reaction, initially the dominant contribution to the total electrode resistance, can be reduced by two orders of magnitude. This &apos
Directory of Open Access Journals (Sweden)
John P Miller
Full Text Available A genome-scale RNAi screen was performed in a mammalian cell-based assay to identify modifiers of mutant huntingtin toxicity. Ontology analysis of suppressor data identified processes previously implicated in Huntington's disease, including proteolysis, glutamate excitotoxicity, and mitochondrial dysfunction. In addition to established mechanisms, the screen identified multiple components of the RRAS signaling pathway as loss-of-function suppressors of mutant huntingtin toxicity in human and mouse cell models. Loss-of-function in orthologous RRAS pathway members also suppressed motor dysfunction in a Drosophila model of Huntington's disease. Abnormal activation of RRAS and a down-stream effector, RAF1, was observed in cellular models and a mouse model of Huntington's disease. We also observe co-localization of RRAS and mutant huntingtin in cells and in mouse striatum, suggesting that activation of R-Ras may occur through protein interaction. These data indicate that mutant huntingtin exerts a pathogenic effect on this pathway that can be corrected at multiple intervention points including RRAS, FNTA/B, PIN1, and PLK1. Consistent with these results, chemical inhibition of farnesyltransferase can also suppress mutant huntingtin toxicity. These data suggest that pharmacological inhibition of RRAS signaling may confer therapeutic benefit in Huntington's disease.
Topological and kinetic determinants of the modal matrices of dynamic models of metabolism.
Directory of Open Access Journals (Sweden)
Bin Du
Full Text Available Large-scale kinetic models of metabolism are becoming increasingly comprehensive and accurate. A key challenge is to understand the biochemical basis of the dynamic properties of these models. Linear analysis methods are well-established as useful tools for characterizing the dynamic response of metabolic networks. Central to linear analysis methods are two key matrices: the Jacobian matrix (J and the modal matrix (M-1 arising from its eigendecomposition. The modal matrix M-1 contains dynamically independent motions of the kinetic model near a reference state, and it is sparse in practice for metabolic networks. However, connecting the structure of M-1 to the kinetic properties of the underlying reactions is non-trivial. In this study, we analyze the relationship between J, M-1, and the kinetic properties of the underlying network for kinetic models of metabolism. Specifically, we describe the origin of mode sparsity structure based on features of the network stoichiometric matrix S and the reaction kinetic gradient matrix G. First, we show that due to the scaling of kinetic parameters in real networks, diagonal dominance occurs in a substantial fraction of the rows of J, resulting in simple modal structures with clear biological interpretations. Then, we show that more complicated modes originate from topologically-connected reactions that have similar reaction elasticities in G. These elasticities represent dynamic equilibrium balances within reactions and are key determinants of modal structure. The work presented should prove useful towards obtaining an understanding of the dynamics of kinetic models of metabolism, which are rooted in the network structure and the kinetic properties of reactions.
DEFF Research Database (Denmark)
Chen, B. H.; Micheletti, M.; Baganz, F.
2009-01-01
-erythrulose. Experiments were performed using automated microwell studies at the 150 or 800 mu L scale. The derived kinetic parameters were then verified in a second round of experiments where model predictions showed excellent agreement with experimental data obtained under conditions not included in the original......Reliable models of enzyme kinetics are required for the effective design of bioconversion processes. Kinetic expressions of the enzyme-catalysed reaction rate however, are frequently complex and establishing accurate values of kinetic parameters normally requires a large number of experiments....... These can be both time consuming and expensive when working with the types of non-natural chiral intermediates important in pharmaceutical syntheses. This paper presents ail automated microscale approach to the rapid and cost effective generation of reliable kinetic models useful for bioconversion process...
Kinetic model for transformation from nano-sized amorphous $TiO_2$ to anatase
Madras, Giridhar; McCoy, Benjamin J
2006-01-01
We propose a kinetic model for the transformation of nano-sized amorphous $TiO_2$ to anatase with associated coarsening by coalescence. Based on population balance (distribution kinetics) equations for the size distributions, the model applies a first-order rate expression for transformation combined with Smoluchowski coalescence for the coarsening particles. Size distribution moments (number and mass of particles) lead to dynamic expressions for extent of reaction and average anatase particl...
The quasi-invariant limit for a kinetic model of sociological collective behavior
Boudin , Laurent; Salvarani , Francesco
2009-01-01
International audience; The paper is devoted to the study of the asymptotic behaviour of a kinetic model proposed to forecast the phenomenon of opinion formation, with both effect of self-thinking and compromise between individuals. By supposing that the effects of self-thinking and compromise are very weak, we deduce, asymptotically, some simpler models who lose the kinetic structure. We explicitly characterize the asymptotic state of the limiting equation and study the speed of convergence ...
Investigation of binary solid phases by calorimetry and kinetic modelling
Matovic, M.
2007-01-01
The traditional methods for the determination of liquid-solid phase diagrams are based on the assumption that the overall equilibrium is established between the phases. However, the result of the crystallization of a liquid mixture will typically be a non-equilibrium or metastable state of the solid. For a proper description of the crystallization process the equilibrium approach is insufficient and a kinetic approach is actually required. In this work, we show that during slow crystallizatio...
Cell kinetic modelling and the chemotherapy of cancer
Knolle, Helmut
1988-01-01
During the last 30 years, many chemical compounds that are active against tumors have been discovered or developed. At the same time, new methods of testing drugs for cancer therapy have evolved. nefore 1964, drug testing on animal tumors was directed to observation of the incfease in life span of the host after a single dose. A new approach, in which the effects of multiple doses on the proliferation kinetics of the tumor in vivo as well as of cell lines in vitro are investigated, has been outlined by Skipper and his co-workers in a series of papers beginning in 1964 (Skipper, Schabel and Wilcox, 1964 and 1965). They also investigated the influence of the time schedule in the treatment of experimental tumors. Since the publication of those studies, cell population kinetics cannot be left out of any discussion of the rational basis of chemotherapy. When clinical oncologists began to apply cell kinetic concepts in practice about 15 years ago, the theoretical basis was still very poor, in spite of Skipper's pro...
Semi-continuous and multigroup models in extended kinetic theory
International Nuclear Information System (INIS)
Koller, W.
2000-01-01
The aim of this thesis is to study energy discretization of the Boltzmann equation in the framework of extended kinetic theory. In case that external fields can be neglected, the semi- continuous Boltzmann equation yields a sound basis for various generalizations. Semi-continuous kinetic equations describing a three component gas mixture interacting with monochromatic photons as well as a four component gas mixture undergoing chemical reactions are established and investigated. These equations reflect all major aspects (conservation laws, equilibria, H-theorem) of the full continuous kinetic description. For the treatment of the spatial dependence, an expansion of the distribution function in terms of Legendre polynomials is carried out. An implicit finite differencing scheme is combined with the operator splitting method. The obtained numerical schemes are applied to the space homogeneous study of binary chemical reactions and to spatially one-dimensional laser-induced acoustic waves. In the presence of external fields, the developed overlapping multigroup approach (with the spline-interpolation as its extension) is well suited for numerical studies. Furthermore, two formulations of consistent multigroup approaches to the non-linear Boltzmann equation are presented. (author)
Sazhin, Sergei S.; Xie, Jianfei; Shishkova, Irina N.; Elwardani, Ahmed Elsaid; Heikal, Morgan Raymond
2013-01-01
The previously developed kinetic model for droplet heating and evaporation into a high pressure air is generalised to take into account the combined effects of inelastic collisions between molecules in the kinetic region, a non-unity evaporation
International Nuclear Information System (INIS)
Lin Feng; Meyer, Christian
2009-01-01
A hydration kinetics model for Portland cement is formulated based on thermodynamics of multiphase porous media. The mechanism of cement hydration is discussed based on literature review. The model is then developed considering the effects of chemical composition and fineness of cement, water-cement ratio, curing temperature and applied pressure. The ultimate degree of hydration of Portland cement is also analyzed and a corresponding formula is established. The model is calibrated against the experimental data for eight different Portland cements. Simple relations between the model parameters and cement composition are obtained and used to predict hydration kinetics. The model is used to reproduce experimental results on hydration kinetics, adiabatic temperature rise, and chemical shrinkage of different cement pastes. The comparisons between the model reproductions and the different experimental results demonstrate the applicability of the proposed model, especially for cement hydration at elevated temperature and high pressure.
Tosun, Ismail
2012-03-01
The adsorption isotherm, the adsorption kinetics, and the thermodynamic parameters of ammonium removal from aqueous solution by using clinoptilolite in aqueous solution was investigated in this study. Experimental data obtained from batch equilibrium tests have been analyzed by four two-parameter (Freundlich, Langmuir, Tempkin and Dubinin-Radushkevich (D-R)) and four three-parameter (Redlich-Peterson (R-P), Sips, Toth and Khan) isotherm models. D-R and R-P isotherms were the models that best fitted to experimental data over the other two- and three-parameter models applied. The adsorption energy (E) from the D-R isotherm was found to be approximately 7 kJ/mol for the ammonium-clinoptilolite system, thereby indicating that ammonium is adsorbed on clinoptilolite by physisorption. Kinetic parameters were determined by analyzing the nth-order kinetic model, the modified second-order model and the double exponential model, and each model resulted in a coefficient of determination (R(2)) of above 0.989 with an average relative error lower than 5%. A Double Exponential Model (DEM) showed that the adsorption process develops in two stages as rapid and slow phase. Changes in standard free energy (∆G°), enthalpy (∆H°) and entropy (∆S°) of ammonium-clinoptilolite system were estimated by using the thermodynamic equilibrium coefficients.
Directory of Open Access Journals (Sweden)
İsmail Tosun
2012-03-01
Full Text Available The adsorption isotherm, the adsorption kinetics, and the thermodynamic parameters of ammonium removal from aqueous solution by using clinoptilolite in aqueous solution was investigated in this study. Experimental data obtained from batch equilibrium tests have been analyzed by four two-parameter (Freundlich, Langmuir, Tempkin and Dubinin-Radushkevich (D-R and four three-parameter (Redlich-Peterson (R-P, Sips, Toth and Khan isotherm models. D-R and R-P isotherms were the models that best fitted to experimental data over the other two- and three-parameter models applied. The adsorption energy (E from the D-R isotherm was found to be approximately 7 kJ/mol for the ammonium-clinoptilolite system, thereby indicating that ammonium is adsorbed on clinoptilolite by physisorption. Kinetic parameters were determined by analyzing the nth-order kinetic model, the modified second-order model and the double exponential model, and each model resulted in a coefficient of determination (R2 of above 0.989 with an average relative error lower than 5%. A Double Exponential Model (DEM showed that the adsorption process develops in two stages as rapid and slow phase. Changes in standard free energy (∆G°, enthalpy (∆H° and entropy (∆S° of ammonium-clinoptilolite system were estimated by using the thermodynamic equilibrium coefficients.
Modeling capsid kinetics assembly from the steady state distribution of multi-sizes aggregates
Energy Technology Data Exchange (ETDEWEB)
Hozé, Nathanaël; Holcman, David
2014-01-24
The kinetics of aggregation for particles of various sizes depends on their diffusive arrival and fusion at a specific nucleation site. We present here a mean-field approximation and a stochastic jump model for aggregates at equilibrium. This approach is an alternative to the classical Smoluchowski equations that do not have a close form and are not solvable in general. We analyze these mean-field equations and obtain the kinetics of a cluster formation. Our approach provides a simplified theoretical framework to study the kinetics of viral capsid formation, such as HIV from the self-assembly of the structural proteins Gag.
A feasible kinetic model for the hydrogen oxidation on ruthenium electrodes
International Nuclear Information System (INIS)
Rau, M.S.; Gennero de Chialvo, M.R.; Chialvo, A.C.
2010-01-01
The hydrogen oxidation reaction (hor) was studied on a polycrystalline ruthenium electrode in H 2 SO 4 solution at different rotation rates (ω). The experimental polarization curves recorded on steady state show the existence of a maximum current with a non-linear dependence of the current density on ω 1/2 . On the basis of the Tafel-Heyrovsky-Volmer kinetic mechanism, coupled with a process of inhibition of active sites by the reversible electroadsorption of hydroxyl species, it was possible to appropriately describe the origin of the maximum current. The corresponding set of kinetic parameters was also calculated from the correlation of the experimental results with the proposed kinetic model.
A kinetic model for the transport of electrons in a graphene layer
Energy Technology Data Exchange (ETDEWEB)
Fermanian Kammerer, Clotilde, E-mail: Clotilde.Fermanian@u-pec.fr [Laboratoire d' Analyse et de Mathématiques Appliquées, Université Paris Est and CNRS, 61, avenue du Général de Gaulle, 94010 Créteil Cedex (France); Méhats, Florian, E-mail: florian.mehats@univ-rennes1.fr [Institut de Recherche Mathématique de Rennes, IPSO Inria team, Université Rennes 1 and CNRS, Campus de Beaulieu, 35042 Rennes cedex (France)
2016-12-15
In this article, we propose a new numerical scheme for the computation of the transport of electrons in a graphene device. The underlying quantum model for graphene is a massless Dirac equation, whose eigenvalues display a conical singularity responsible for non-adiabatic transitions between the two modes. We first derive a kinetic model which takes the form of two Boltzmann equations coupled by a collision operator modeling the non-adiabatic transitions. This collision term includes a Landau–Zener transfer term and a jump operator whose presence is essential in order to ensure a good energy conservation during the transitions. We propose an algorithmic realization of the semi-group solving the kinetic model, by a particle method. We give analytic justification of the model and propose a series of numerical experiments studying the influences of the various sources of errors between the quantum and the kinetic models.
Wang, Weicheng
2013-11-01
A chemical kinetic model has been developed for the transient stage of the continuous countercurrent hydrolysis of triglycerides to free fatty acids and glycerol. Departure functions and group contribution methods were applied to determine the equilibrium constants of the four reversible reactions in the kinetic model. Continuous countercurrent hydrolysis of canola oil in subcritical water was conducted experimentally in a lab-scale reactor over a range of temperatures and the concentrations of all neutral components were quantified. Several of the rate constants in the model were obtained by modeling this experimental data, with the remaining determined from calculated equilibrium constants. Some reactions not included in the present, or previous, hydrolysis modeling efforts were identified from glycerolysis kinetic studies and may explain the slight discrepancy between model and experiment. The rate constants determined in this paper indicate that diglycerides in the feedstock accelerate the transition from "emulsive hydrolysis" to "rapid hydrolysis". © 2013 Elsevier Ltd.
Group-kinetic theory and modeling of atmospheric turbulence
Tchen, C. M.
1989-01-01
A group kinetic method is developed for analyzing eddy transport properties and relaxation to equilibrium. The purpose is to derive the spectral structure of turbulence in incompressible and compressible media. Of particular interest are: direct and inverse cascade, boundary layer turbulence, Rossby wave turbulence, two phase turbulence; compressible turbulence, and soliton turbulence. Soliton turbulence can be found in large scale turbulence, turbulence connected with surface gravity waves and nonlinear propagation of acoustical and optical waves. By letting the pressure gradient represent the elementary interaction among fluid elements and by raising the Navier-Stokes equation to higher dimensionality, the master equation was obtained for the description of the microdynamical state of turbulence.
Statistical approach to LHCD modeling using the wave kinetic equation
International Nuclear Information System (INIS)
Kupfer, K.; Moreau, D.; Litaudon, X.
1993-04-01
Recent work has shown that for parameter regimes typical of many present day current drive experiments, the orbits of the launched LH rays are chaotic (in the Hamiltonian sense), so that wave energy diffuses through the stochastic layer and fills the spectral gap. We have analyzed this problem using a statistical approach, by solving the wave kinetic equation for the coarse-grained spectral energy density. An interesting result is that the LH absorption profile is essentially independent of both the total injected power and the level of wave stochastic diffusion
Döntgen, Malte; Schmalz, Felix; Kopp, Wassja A; Kröger, Leif C; Leonhard, Kai
2018-06-13
An automated scheme for obtaining chemical kinetic models from scratch using reactive molecular dynamics and quantum chemistry simulations is presented. This methodology combines the phase space sampling of reactive molecular dynamics with the thermochemistry and kinetics prediction capabilities of quantum mechanics. This scheme provides the NASA polynomial and modified Arrhenius equation parameters for all species and reactions that are observed during the simulation and supplies them in the ChemKin format. The ab initio level of theory for predictions is easily exchangeable and the presently used G3MP2 level of theory is found to reliably reproduce hydrogen and methane oxidation thermochemistry and kinetics data. Chemical kinetic models obtained with this approach are ready-to-use for, e.g., ignition delay time simulations, as shown for hydrogen combustion. The presented extension of the ChemTraYzer approach can be used as a basis for methodologically advancing chemical kinetic modeling schemes and as a black-box approach to generate chemical kinetic models.
Experimental and Chemical Kinetic Modeling Study of Dimethylcyclohexane Oxidation and Pyrolysis
Eldeeb, Mazen A.
2016-08-30
A combined experimental and chemical kinetic modeling study of the high-temperature ignition and pyrolysis of 1,3-dimethylcyclohexane (13DMCH) is presented. Ignition delay times are measured behind reflected shock waves over a temperature range of 1049–1544 K and pressures of 3.0–12 atm. Pyrolysis is investigated at average pressures of 4.0 atm at temperatures of 1238, 1302, and 1406 K. By means of mid-infrared direct laser absorption at 3.39 μm, fuel concentration time histories are measured under ignition and pyrolytic conditions. A detailed chemical kinetic model for 13DMCH combustion is developed. Ignition measurements show that the ignition delay times of 13DMCH are longer than those of its isomer, ethylcyclohexane. The proposed chemical kinetic model predicts reasonably well the effects of equivalence ratio and pressure, with overall good agreement between predicted and measured ignition delay times, except at low dilution levels and high pressures. Simulated fuel concentration profiles agree reasonably well with the measured profiles, and both highlight the influence of pyrolysis on the overall ignition kinetics at high temperatures. Sensitivity and reaction pathway analyses provide further insight into the kinetic processes controlling ignition and pyrolysis. The work contributes toward improved understanding and modeling of the oxidation and pyrolysis kinetics of cycloalkanes.
Gering, Kevin L.
2013-01-01
A system includes an electrochemical cell, monitoring hardware, and a computing system. The monitoring hardware samples performance characteristics of the electrochemical cell. The computing system determines cell information from the performance characteristics. The computing system also analyzes the cell information of the electrochemical cell with a Butler-Volmer (BV) expression modified to determine exchange current density of the electrochemical cell by including kinetic performance information related to pulse-time dependence, electrode surface availability, or a combination thereof. A set of sigmoid-based expressions may be included with the modified-BV expression to determine kinetic performance as a function of pulse time. The determined exchange current density may be used with the modified-BV expression, with or without the sigmoid expressions, to analyze other characteristics of the electrochemical cell. Model parameters can be defined in terms of cell aging, making the overall kinetics model amenable to predictive estimates of cell kinetic performance along the aging timeline.
Modelling the role of compositional fluctuations in nucleation kinetics
International Nuclear Information System (INIS)
Ženíšek, J.; Kozeschnik, E.; Svoboda, J.; Fischer, F.D.
2015-01-01
The classical nucleation theory of precipitate nucleation in interstitial/substitutional alloys is applied to account for the influence of spatial A–B composition fluctuations in an A–B–C matrix on the kinetics of nucleation of (A,B) 3 C precipitates. A and B are substitutional elements in the matrix and C is an interstitial component, assumed to preferentially bind to B atoms. All lattice sites are considered as potential nucleation sites. The fluctuations of chemical composition result in a local variation of the nucleation probability. The nucleation sites are eliminated from the system if they are located in a C-depleted diffusion zone belonging to an already nucleated and growing precipitate. The chemistry is that of an Fe–Cr–C system, and the specific interface energy is treated as a free parameter. Random, regular and homogeneous A–B distributions in the matrix are simulated and compared for various values of the interface energy. An increasing enhancement of the role of compositional fluctuations on nucleation kinetics with increasing interface energy and decreasing chemical driving force is observed
Modeling physiological processes in plankton on enzyme kinetic principles
Directory of Open Access Journals (Sweden)
Ted Packard
2004-04-01
Full Text Available Many ecologically important chemical transformations in the ocean are controlled by biochemical enzyme reactions in plankton. Nitrogenase regulates the transformation of N2 to ammonium in some cyanobacteria and serves as the entryway for N2 into the ocean biosphere. Nitrate reductase controls the reduction of NO3 to NO2 and hence new production in phytoplankton. The respiratory electron transfer system in all organisms links the carbon oxidation reactions of intermediary metabolism with the reduction of oxygen in respiration. Rubisco controls the fixation of CO2 into organic matter in phytoplankton and thus is the major entry point of carbon into the oceanic biosphere. In addition to these, there are the enzymes that control CO2 production, NH4 excretion and the fluxes of phosphate. Some of these enzymes have been recognized and researched by marine scientists in the last thirty years. However, until recently the kinetic principles of enzyme control have not been exploited to formulate accurate mathematical equations of the controlling physiological expressions. Were such expressions available they would increase our power to predict the rates of chemical transformations in the extracellular environment of microbial populations whether this extracellular environment is culture media or the ocean. Here we formulate from the principles of bisubstrate enzyme kinetics, mathematical expressions for the processes of NO3 reduction, O2 consumption, N2 fixation, total nitrogen uptake.
In silico modelling and analysis of ribosome kinetics and aa-tRNA competition
Bošnački, D.; Pronk, T.E.; de Vink, E.P.
2008-01-01
We present a formal analysis of ribosome kinetics using probabilistic model checking and the tool Prism. We compute different parameters of the model, like probabilities of translation errors and average insertion times per codon. The model predicts strong correlation to the quotient of the
International Nuclear Information System (INIS)
Lietzke, M.H.
1977-01-01
The results of applying a kinetic model to the chlorination data supplied by Commonwealth Edison on the once-through cooling system at the Quad Cities Nuclear Station provide a validation of the model. The two examples given demonstrate that the model may be applied to either once-through cooling systems or to cooling systems involving cooling towers
A two-phase kinetic model for fungal growth in solid-state cultivation
Hamidi-Esfahani, Z.; Hejazi, P.; Abbas Shojaosadati, S.; Hoogschagen, M.J.; Vasheghani-Farahani, E.; Rinzema, A.
2007-01-01
A new two-phase kinetic model including exponential and logistic models was applied to simulate the growth rate of fungi at various temperatures. The model parameters, expressed as a function of temperature, were determined from the oxygen consumption rate of Aspergillus niger during cultivation on
International Nuclear Information System (INIS)
Lim, T.H.
1978-06-01
The purpose of this study is to investigate whether a valid index of chromium (III) nutritional status can be determined with satisfaction through in vivo kinetic analysis. Three normal subjects and three patients suffering from hemochromatosis were periodically scanned with the Donner Laboratory computerized whole body scanners, starting seconds after radiochromium(III) was administered intravenously, up to a period of 84 days. The activity in the liver, adipose and muscle tissues, spleen and bone was quantitated and corrected, by subtraction of the blood circulation activity in that organ; the major concentration was found in the liver and spleen. From the series of scan images, a kinetic model for the radiochromium(III) metabolic pathway was constructed. Computer analysis showed a significant difference between the two classes of subjects in organs as well as whole body radiochromium(III) transfer. Interpretation of these results showed that in patients with excessive iron stores, a smaller amount of chromium bound to plasma protein was found and a corresponding decrease in transfer of chromium into stores in the liver and other tissues was also found
Kinetic study of corn straw pyrolysis: comparison of two different three-pseudocomponent models.
Li, Zhengqi; Zhao, Wei; Meng, Baihong; Liu, Chunlong; Zhu, Qunyi; Zhao, Guangbo
2008-11-01
With heating rates of 20, 50 and 100 K min(-1), the thermal decomposition of corn straw samples (corn stalks skins, corn stalks cores, corn bracts and corn leaves) were studied using thermogravimetric analysis. The maximum pyrolysis rates increased with the heating rate increasing and the temperature at the peak pyrolysis rate also increased. Assuming the addition of three independent parallel reactions, corresponding to three pseudocomponents linked to the hemicellulose, cellulose and lignin, two different three-pseudocomponent models were used to simulate the corn straw pyrolysis. Model parameters of pyrolysis were given. It was found that the three-pseudocomponent model with n-order kinetics was more accurate than the model with first-order kinetics at most cases. It showed that the model with n-order kinetics was more accurate to describe the pyrolysis of the hemicellulose.
Schunk, R. W.; Barakat, A. R.; Eccles, V.; Karimabadi, H.; Omelchenko, Y.; Khazanov, G. V.; Glocer, A.; Kistler, L. M.
2014-12-01
A Kinetic Framework for the Magnetosphere-Ionosphere-Plasmasphere-Polar Wind System is being developed in order to provide a rigorous approach to modeling the interaction of hot and cold particle interactions. The framework will include ion and electron kinetic species in the ionosphere, plasmasphere and polar wind, and kinetic ion, super-thermal electron and fluid electron species in the magnetosphere. The framework is ideally suited to modeling ion outflow from the ionosphere and plasmasphere, where a wide range for fluid and kinetic processes are important. These include escaping ion interactions with (1) photoelectrons, (2) cusp/auroral waves, double layers, and field-aligned currents, (3) double layers in the polar cap due to the interaction of cold ionospheric and hot magnetospheric electrons, (4) counter-streaming ions, and (5) electromagnetic wave turbulence. The kinetic ion interactions are particularly strong during geomagnetic storms and substorms. The presentation will provide a brief description of the models involved and discuss the effect that kinetic processes have on the ion outflow.
A resource facility for kinetic analysis: modeling using the SAAM computer programs.
Foster, D M; Boston, R C; Jacquez, J A; Zech, L
1989-01-01
Kinetic analysis and integrated system modeling have contributed significantly to understanding the physiology and pathophysiology of metabolic systems in humans and animals. Many experimental biologists are aware of the usefulness of these techniques and recognize that kinetic modeling requires special expertise. The Resource Facility for Kinetic Analysis (RFKA) provides this expertise through: (1) development and application of modeling technology for biomedical problems, and (2) development of computer-based kinetic modeling methodologies concentrating on the computer program Simulation, Analysis, and Modeling (SAAM) and its conversational version, CONversational SAAM (CONSAM). The RFKA offers consultation to the biomedical community in the use of modeling to analyze kinetic data and trains individuals in using this technology for biomedical research. Early versions of SAAM were widely applied in solving dosimetry problems; many users, however, are not familiar with recent improvements to the software. The purpose of this paper is to acquaint biomedical researchers in the dosimetry field with RFKA, which, together with the joint National Cancer Institute-National Heart, Lung and Blood Institute project, is overseeing SAAM development and applications. In addition, RFKA provides many service activities to the SAAM user community that are relevant to solving dosimetry problems.
Energy Technology Data Exchange (ETDEWEB)
Lan, Shuiquan [Department of Mechanical Engineering, Eindhoven University of Technology, Den Dolech 2, 5612AZ Eindhoven (Netherlands); Zondag, Herbert [Department of Mechanical Engineering, Eindhoven University of Technology, Den Dolech 2, 5612AZ Eindhoven (Netherlands); Energy research Center of the Netherlands – ECN, P.O. Box 1, 1755ZG Petten (Netherlands); Steenhoven, Anton van [Department of Mechanical Engineering, Eindhoven University of Technology, Den Dolech 2, 5612AZ Eindhoven (Netherlands); Rindt, Camilo, E-mail: c.c.m.rindt@tue.nl [Department of Mechanical Engineering, Eindhoven University of Technology, Den Dolech 2, 5612AZ Eindhoven (Netherlands)
2015-12-10
Highlights: • Kinetics of Li{sub 2}SO{sub 4}·H{sub 2}O single crystals were modeled based on elementary processes. • Kinetics of nucleation and nuclei growth were studied by using optical microscopy. • A novel experiment was designed to visualize the reaction front into crystal bulk. • Fractional conversion was calculated and compared with TGA-experiments. - Abstract: Simulation of gas–solid reactions occurring in industrial processes requires a robust kinetic model to be applicable in a wide range of complicated reaction conditions. However, in literature it is often seen that even the same reaction under specific controlled conditions is interpreted with different kinetic models. In the present work, a phenomenological model based on nucleation and nuclei growth processes is presented to study the kinetics of the dehydration reaction of lithium sulfate monohydrate single crystals. The two elementary processes of the reaction, nucleation and nuclei growth, are characterized and quantified as a function of temperature by using optical microscopy experiments. The in-situ measured characteristics of the dehydration reaction provided confirmatory evidence that the rate of nucleation obeys an exponential law and the rate of nuclei growth is approximately constant. With knowledge acquired from the optical observations as inputs of the kinetic model, the fractional conversion of the dehydration reaction was calculated and compared with experimental results from thermogravimetric analysis (TGA). A satisfactory comparison was found both in isothermal and non-isothermal conditions. It is demonstrated that this knowledge-based model has a great potential to represent the gas–solid reaction kinetics in a wide range of process conditions regarding temperature, pressure and particle geometry.
Energy Technology Data Exchange (ETDEWEB)
Pradhan, Santosh K., E-mail: santosh@aerb.gov.in [Nuclear Safety Analysis Division, Atomic Energy Regulatory Board, Mumbai 400094 (India); Obaidurrahman, K. [Nuclear Safety Analysis Division, Atomic Energy Regulatory Board, Mumbai 400094 (India); Iyer, Kannan N. [Department of Mechanical Engineering, IIT Bombay, Mumbai 400076 (India); Gaikwad, Avinash J. [Nuclear Safety Analysis Division, Atomic Energy Regulatory Board, Mumbai 400094 (India)
2016-04-15
Highlights: • A multi-point kinetics model is developed for RELAP5 system thermal hydraulics code. • Model is validated against extensive 3D kinetics code. • RELAP5 multi-point kinetics formulation is used to investigate critical break for LOCA in PHWR. - Abstract: Point kinetics approach in system code RELAP5 limits its use for many of the reactivity induced transients, which involve asymmetric core behaviour. Development of fully coupled 3D core kinetics code with system thermal-hydraulics is the ultimate requirement in this regard; however coupling and validation of 3D kinetics module with system code is cumbersome and it also requires access to source code. An intermediate approach with multi-point kinetics is appropriate and relatively easy to implement for analysis of several asymmetric transients for large cores. Multi-point kinetics formulation is based on dividing the entire core into several regions and solving ODEs describing kinetics in each region. These regions are interconnected by spatial coupling coefficients which are estimated from diffusion theory approximation. This model offers an advantage that associated ordinary differential equations (ODEs) governing multi-point kinetics formulation can be solved using numerical methods to the desired level of accuracy and thus allows formulation based on user defined control variables, i.e., without disturbing the source code and hence also avoiding associated coupling issues. Euler's method has been used in the present formulation to solve several coupled ODEs internally at each time step. The results have been verified against inbuilt point-kinetics models of RELAP5 and validated against 3D kinetics code TRIKIN. The model was used to identify the critical break in RIH of a typical large PHWR core. The neutronic asymmetry produced in the core due to the system induced transient was effectively handled by the multi-point kinetics model overcoming the limitation of in-built point kinetics model
Directory of Open Access Journals (Sweden)
Zixiang Xu
Full Text Available Gene knockout has been used as a common strategy to improve microbial strains for producing chemicals. Several algorithms are available to predict the target reactions to be deleted. Most of them apply mixed integer bi-level linear programming (MIBLP based on metabolic networks, and use duality theory to transform bi-level optimization problem of large-scale MIBLP to single-level programming. However, the validity of the transformation was not proved. Solution of MIBLP depends on the structure of inner problem. If the inner problem is continuous, Karush-Kuhn-Tucker (KKT method can be used to reformulate the MIBLP to a single-level one. We adopt KKT technique in our algorithm ReacKnock to attack the intractable problem of the solution of MIBLP, demonstrated with the genome-scale metabolic network model of E. coli for producing various chemicals such as succinate, ethanol, threonine and etc. Compared to the previous methods, our algorithm is fast, stable and reliable to find the optimal solutions for all the chemical products tested, and able to provide all the alternative deletion strategies which lead to the same industrial objective.
Determination of Model Kinetics for Forced Unsteady State Operation of Catalytic CH4 Oxidation
Directory of Open Access Journals (Sweden)
Effendy Mohammad
2016-01-01
Full Text Available The catalytic oxidation of methane for abating the emission vented from coal mine or natural gas transportation has been known as most reliable method. A reverse flow reactor operation has been widely used to oxidize this methane emission due to its capability for autothermal operation and heat production. The design of the reverse flow reactor requires a proper kinetic rate expression, which should be developed based on the operating condition. The kinetic rate obtained in the steady state condition cannot be applied for designing the reactor operated under unsteady state condition. Therefore, new approach to develop the dynamic kinetic rate expression becomes indispensable, particularly for periodic operation such as reverse flow reactor. This paper presents a novel method to develop the kinetic rate expression applied for unsteady state operation. The model reaction of the catalytic methane oxidation over Pt/-Al2O3 catalyst was used with kinetic parameter determined from laboratory experiments. The reactor used was a fixed bed, once-through operation, with a composition modulation in the feed gas. The switching time was set at 3 min by varying the feed concentration, feed flow rate, and reaction temperature. The concentrations of methane in the feed and product were measured and analysed using gas chromatography. The steady state condition for obtaining the kinetic rate expression was taken as a base case and as a way to judge its appropriateness to be applied for dynamic system. A Langmuir-Hinshelwood reaction rate model was developed. The time period during one cycle was divided into some segments, depending on the ratio of CH4/O2. The experimental result shows that there were kinetic regimes occur during one cycle: kinetic regime controlled by intrinsic surface reaction and kinetic regime controlled by external diffusion. The kinetic rate obtained in the steady state operation was not appropriate when applied for unsteady state operation
Explicit equilibria in a kinetic model of gambling
Bassetti, F.; Toscani, G.
2010-06-01
We introduce and discuss a nonlinear kinetic equation of Boltzmann type which describes the evolution of wealth in a pure gambling process, where the entire sum of wealths of two agents is up for gambling, and randomly shared between the agents. For this equation the analytical form of the steady states is found for various realizations of the random fraction of the sum which is shared to the agents. Among others, the exponential distribution appears as steady state in case of a uniformly distributed random fraction, while Gamma distribution appears for a random fraction which is Beta distributed. The case in which the gambling game is only conservative-in-the-mean is shown to lead to an explicit heavy tailed distribution.
On coupling fluid plasma and kinetic neutral physics models
Directory of Open Access Journals (Sweden)
I. Joseph
2017-08-01
Full Text Available The coupled fluid plasma and kinetic neutral physics equations are analyzed through theory and simulation of benchmark cases. It is shown that coupling methods that do not treat the coupling rates implicitly are restricted to short time steps for stability. Fast charge exchange, ionization and recombination coupling rates exist, even after constraining the solution by requiring that the neutrals are at equilibrium. For explicit coupling, the present implementation of Monte Carlo correlated sampling techniques does not allow for complete convergence in slab geometry. For the benchmark case, residuals decay with particle number and increase with grid size, indicating that they scale in a manner that is similar to the theoretical prediction for nonlinear bias error. Progress is reported on implementation of a fully implicit Jacobian-free Newton–Krylov coupling scheme. The present block Jacobi preconditioning method is still sensitive to time step and methods that better precondition the coupled system are under investigation.
International Nuclear Information System (INIS)
Njikam, Eloh; Schiewer, Silke
2012-01-01
Graphical abstract: Cadmium was completely and quickly desorbed from grapefruit peels using 0.01 M HNO 3 . The kinetics followed a novel 1st or 2nd order kinetic model, related to the remaining metal bound as the rate-determining reactant concentration. For 0.001 M HNO 3 , desorption was incomplete and the model fit less perfect. Highlights: ► Metal desorption was over 90% complete within 50 min for most desorbents. ► Models for biosorbent desorption kinetics were developed. ► Desorption kinetics best fit a novel first-order model related to remaining metal bound. ► Cd uptake after desorption by HNO 3 was similar to the original uptake. ► The optimal desorbent was 0.1 or 0.01 M acid, being fast, efficient and cheap. - Abstract: Citrus peel biosorbents are efficient in removing heavy metals from wastewater. Heavy metal recovery and sorbent regeneration are important for the financial competitiveness of biosorption with other processes. The desorbing agents HNO 3 , NaNO 3 , Ca(NO 3 ) 2 , EDTA, S, S-EDDS, and Na-Citrate were studied at different concentrations to optimize cadmium elution from orange or grapefruit peels. In most cases, desorption was fast, being over 90% complete within 50 min. However sodium nitrate and 0.001 M nitric acid were less efficient. Several new models for desorption kinetics were developed. While zero-, first- and second-order kinetics are commonly applied for modeling adsorption kinetics, the present study adapts these models to describe desorption kinetics. The proposed models relate to the number of metal-filled binding sites as the rate-determining reactant concentration. A model based on first order kinetics with respect to the remaining metal bound performed best. Cd bound in subsequent adsorption after desorption was similar to the original amount bound for desorption by nitric acid, but considerably lower for calcium nitrate as the desorbent. While complexing agents were effective desorbents, their cost is higher than that
Kumar, B Shiva; Venkateswarlu, Ch
2014-08-01
The complex nature of biological reactions in biofilm reactors often poses difficulties in analyzing such reactors experimentally. Mathematical models could be very useful for their design and analysis. However, application of biofilm reactor models to practical problems proves somewhat ineffective due to the lack of knowledge of accurate kinetic models and uncertainty in model parameters. In this work, we propose an inverse modeling approach based on tabu search (TS) to estimate the parameters of kinetic and film thickness models. TS is used to estimate these parameters as a consequence of the validation of the mathematical models of the process with the aid of measured data obtained from an experimental fixed-bed anaerobic biofilm reactor involving the treatment of pharmaceutical industry wastewater. The results evaluated for different modeling configurations of varying degrees of complexity illustrate the effectiveness of TS for accurate estimation of kinetic and film thickness model parameters of the biofilm process. The results show that the two-dimensional mathematical model with Edward kinetics (with its optimum parameters as mu(max)rho(s)/Y = 24.57, Ks = 1.352 and Ki = 102.36) and three-parameter film thickness expression (with its estimated parameters as a = 0.289 x 10(-5), b = 1.55 x 10(-4) and c = 15.2 x 10(-6)) better describes the biofilm reactor treating the industry wastewater.
The instability in the long-time regime of a kinetic model: II
International Nuclear Information System (INIS)
Sanda, F
2003-01-01
The kinetic model of an open system, which embodies an instability in long time regime behaviour, is referred. This result questions some approximations which are standardly used in open system treatments. The deficiency in kinetic treatments was recently referred to as mainly a mathematical curiosity; however, in the present work the application for a physically comprehensive situation is shown. We simplified the previously treated model, which enables us to proceed easily with just pen and paper and to omit numerical modelling whose justification causes difficulties to the reader. We draw some consequences on the found instability, both with respect to the perturbative origin of kinetic equations and also concerning the very philosophy of physical modelling
Stoichio-Kinetic Modeling of Fenton Chemistry in a Meat-Mimetic Aqueous-Phase Medium.
Oueslati, Khaled; Promeyrat, Aurélie; Gatellier, Philippe; Daudin, Jean-Dominique; Kondjoyan, Alain
2018-05-31
Fenton reaction kinetics, which involved an Fe(II)/Fe(III) oxidative redox cycle, were studied in a liquid medium that mimics meat composition. Muscle antioxidants (enzymes, peptides, and vitamins) were added one by one in the medium to determine their respective effects on the formation of superoxide and hydroxyl radicals. A stoichio-kinetic mathematical model was used to predict the formation of these radicals under different iron and H 2 O 2 concentrations and temperature conditions. The difference between experimental and predicted results was mainly due to iron reactivity, which had to be taken into account in the model, and to uncertainties on some of the rate constant values introduced in the model. This stoichio-kinetic model will be useful to predict oxidation during meat processes, providing it can be completed to take into account the presence of myoglobin in the muscle.
Kinetic modelling of anaerobic hydrolysis of solid wastes, including disintegration processes
Energy Technology Data Exchange (ETDEWEB)
García-Gen, Santiago [Department of Chemical Engineering, Institute of Technology, University of Santiago de Compostela, 15782 Santiago de Compostela (Spain); Sousbie, Philippe; Rangaraj, Ganesh [INRA, UR50, Laboratoire de Biotechnologie de l’Environnement, Avenue des Etangs, Narbonne F-11100 (France); Lema, Juan M. [Department of Chemical Engineering, Institute of Technology, University of Santiago de Compostela, 15782 Santiago de Compostela (Spain); Rodríguez, Jorge, E-mail: jrodriguez@masdar.ac.ae [Department of Chemical Engineering, Institute of Technology, University of Santiago de Compostela, 15782 Santiago de Compostela (Spain); Institute Centre for Water and Environment (iWater), Masdar Institute of Science and Technology, PO Box 54224 Abu Dhabi (United Arab Emirates); Steyer, Jean-Philippe; Torrijos, Michel [INRA, UR50, Laboratoire de Biotechnologie de l’Environnement, Avenue des Etangs, Narbonne F-11100 (France)
2015-01-15
Highlights: • Fractionation of solid wastes into readily and slowly biodegradable fractions. • Kinetic coefficients estimation from mono-digestion batch assays. • Validation of kinetic coefficients with a co-digestion continuous experiment. • Simulation of batch and continuous experiments with an ADM1-based model. - Abstract: A methodology to estimate disintegration and hydrolysis kinetic parameters of solid wastes and validate an ADM1-based anaerobic co-digestion model is presented. Kinetic parameters of the model were calibrated from batch reactor experiments treating individually fruit and vegetable wastes (among other residues) following a new protocol for batch tests. In addition, decoupled disintegration kinetics for readily and slowly biodegradable fractions of solid wastes was considered. Calibrated parameters from batch assays of individual substrates were used to validate the model for a semi-continuous co-digestion operation treating simultaneously 5 fruit and vegetable wastes. The semi-continuous experiment was carried out in a lab-scale CSTR reactor for 15 weeks at organic loading rate ranging between 2.0 and 4.7 g VS/L d. The model (built in Matlab/Simulink) fit to a large extent the experimental results in both batch and semi-continuous mode and served as a powerful tool to simulate the digestion or co-digestion of solid wastes.
Comparison of the kinetics of different Markov models for ligand binding under varying conditions
International Nuclear Information System (INIS)
Martini, Johannes W. R.; Habeck, Michael
2015-01-01
We recently derived a Markov model for macromolecular ligand binding dynamics from few physical assumptions and showed that its stationary distribution is the grand canonical ensemble [J. W. R. Martini, M. Habeck, and M. Schlather, J. Math. Chem. 52, 665 (2014)]. The transition probabilities of the proposed Markov process define a particular Glauber dynamics and have some similarity to the Metropolis-Hastings algorithm. Here, we illustrate that this model is the stochastic analog of (pseudo) rate equations and the corresponding system of differential equations. Moreover, it can be viewed as a limiting case of general stochastic simulations of chemical kinetics. Thus, the model links stochastic and deterministic approaches as well as kinetics and equilibrium described by the grand canonical ensemble. We demonstrate that the family of transition matrices of our model, parameterized by temperature and ligand activity, generates ligand binding kinetics that respond to changes in these parameters in a qualitatively similar way as experimentally observed kinetics. In contrast, neither the Metropolis-Hastings algorithm nor the Glauber heat bath reflects changes in the external conditions correctly. Both converge rapidly to the stationary distribution, which is advantageous when the major interest is in the equilibrium state, but fail to describe the kinetics of ligand binding realistically. To simulate cellular processes that involve the reversible stochastic binding of multiple factors, our pseudo rate equation model should therefore be preferred to the Metropolis-Hastings algorithm and the Glauber heat bath, if the stationary distribution is not of only interest
Comparison of the kinetics of different Markov models for ligand binding under varying conditions
Energy Technology Data Exchange (ETDEWEB)
Martini, Johannes W. R., E-mail: jmartin2@gwdg.de [Max Planck Institute for Developmental Biology, Tübingen (Germany); Felix Bernstein Institute for Mathematical Statistics in the Biosciences, University of Göttingen, Göttingen (Germany); Habeck, Michael, E-mail: mhabeck@gwdg.de [Felix Bernstein Institute for Mathematical Statistics in the Biosciences, University of Göttingen, Göttingen (Germany); Max Planck Institute for Biophysical Chemistry, Göttingen (Germany)
2015-03-07
We recently derived a Markov model for macromolecular ligand binding dynamics from few physical assumptions and showed that its stationary distribution is the grand canonical ensemble [J. W. R. Martini, M. Habeck, and M. Schlather, J. Math. Chem. 52, 665 (2014)]. The transition probabilities of the proposed Markov process define a particular Glauber dynamics and have some similarity to the Metropolis-Hastings algorithm. Here, we illustrate that this model is the stochastic analog of (pseudo) rate equations and the corresponding system of differential equations. Moreover, it can be viewed as a limiting case of general stochastic simulations of chemical kinetics. Thus, the model links stochastic and deterministic approaches as well as kinetics and equilibrium described by the grand canonical ensemble. We demonstrate that the family of transition matrices of our model, parameterized by temperature and ligand activity, generates ligand binding kinetics that respond to changes in these parameters in a qualitatively similar way as experimentally observed kinetics. In contrast, neither the Metropolis-Hastings algorithm nor the Glauber heat bath reflects changes in the external conditions correctly. Both converge rapidly to the stationary distribution, which is advantageous when the major interest is in the equilibrium state, but fail to describe the kinetics of ligand binding realistically. To simulate cellular processes that involve the reversible stochastic binding of multiple factors, our pseudo rate equation model should therefore be preferred to the Metropolis-Hastings algorithm and the Glauber heat bath, if the stationary distribution is not of only interest.
Moving image analysis to the cloud: A case study with a genome-scale tomographic study
Energy Technology Data Exchange (ETDEWEB)
Mader, Kevin [4Quant Ltd., Switzerland & Institute for Biomedical Engineering at University and ETH Zurich (Switzerland); Stampanoni, Marco [Institute for Biomedical Engineering at University and ETH Zurich, Switzerland & Swiss Light Source at Paul Scherrer Institut, Villigen (Switzerland)
2016-01-28
Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures.
Moving image analysis to the cloud: A case study with a genome-scale tomographic study
International Nuclear Information System (INIS)
Mader, Kevin; Stampanoni, Marco
2016-01-01
Over the last decade, the time required to measure a terabyte of microscopic imaging data has gone from years to minutes. This shift has moved many of the challenges away from experimental design and measurement to scalable storage, organization, and analysis. As many scientists and scientific institutions lack training and competencies in these areas, major bottlenecks have arisen and led to substantial delays and gaps between measurement, understanding, and dissemination. We present in this paper a framework for analyzing large 3D datasets using cloud-based computational and storage resources. We demonstrate its applicability by showing the setup and costs associated with the analysis of a genome-scale study of bone microstructure. We then evaluate the relative advantages and disadvantages associated with local versus cloud infrastructures
Genome-scale analysis of positional clustering of mouse testis-specific genes
Directory of Open Access Journals (Sweden)
Lee Bernett TK
2005-01-01
Full Text Available Abstract Background Genes are not randomly distributed on a chromosome as they were thought even after removal of tandem repeats. The positional clustering of co-expressed genes is known in prokaryotes and recently reported in several eukaryotic organisms such as Caenorhabditis elegans, Drosophila melanogaster, and Homo sapiens. In order to further investigate the mode of tissue-specific gene clustering in higher eukaryotes, we have performed a genome-scale analysis of positional clustering of the mouse testis-specific genes. Results Our computational analysis shows that a large proportion of testis-specific genes are clustered in groups of 2 to 5 genes in the mouse genome. The number of clusters is much higher than expected by chance even after removal of tandem repeats. Conclusion Our result suggests that testis-specific genes tend to cluster on the mouse chromosomes. This provides another piece of evidence for the hypothesis that clusters of tissue-specific genes do exist.
Targeted and genome-scale methylomics reveals gene body signatures in human cell lines
Ball, Madeleine Price; Li, Jin Billy; Gao, Yuan; Lee, Je-Hyuk; LeProust, Emily; Park, In-Hyun; Xie, Bin; Daley, George Q.; Church, George M.
2012-01-01
Cytosine methylation, an epigenetic modification of DNA, is a target of growing interest for developing high throughput profiling technologies. Here we introduce two new, complementary techniques for cytosine methylation profiling utilizing next generation sequencing technology: bisulfite padlock probes (BSPPs) and methyl sensitive cut counting (MSCC). In the first method, we designed a set of ~10,000 BSPPs distributed over the ENCODE pilot project regions to take advantage of existing expression and chromatin immunoprecipitation data. We observed a pattern of low promoter methylation coupled with high gene body methylation in highly expressed genes. Using the second method, MSCC, we gathered genome-scale data for 1.4 million HpaII sites and confirmed that gene body methylation in highly expressed genes is a consistent phenomenon over the entire genome. Our observations highlight the usefulness of techniques which are not inherently or intentionally biased in favor of only profiling particular subsets like CpG islands or promoter regions. PMID:19329998
Evaluation of rate law approximations in bottom-up kinetic models of metabolism
DEFF Research Database (Denmark)
Du, Bin; Zielinski, Daniel C.; Kavvas, Erol S.
2016-01-01
mass action rate law that removes the role of the enzyme from the reaction kinetics. We utilized in vivo data for the human red blood cell to compare the effect of rate law choices against the backdrop of physiological flux and concentration differences. We found that the Michaelis-Menten rate law......Background: The mechanistic description of enzyme kinetics in a dynamic model of metabolism requires specifying the numerical values of a large number of kinetic parameters. The parameterization challenge is often addressed through the use of simplifying approximations to form reaction rate laws....... These approximate rate laws were: 1) a Michaelis-Menten rate law with measured enzyme parameters, 2) a Michaelis-Menten rate law with approximated parameters, using the convenience kinetics convention, 3) a thermodynamic rate law resulting from a metabolite saturation assumption, and 4) a pure chemical reaction...
A kinetic model for citric acid productionfrom apple pomac by ...
African Journals Online (AJOL)
STORAGESEVER
2008-10-06
Oct 6, 2008 ... system. The model can provide useful suggestions for the analysis, design and operation of a fermenter. Fer- mentation models are normally ... Structured model seems complicated for normal use. (Jian-Zhong et al., 2002).
DEFF Research Database (Denmark)
Nießen, Frank; Tiedje, Niels Skat; Hald, John
2017-01-01
The kinetics model for multi-component diffusion DICTRA was applied to analyze the formation and retainment of δ-ferrite during solidification and cooling of GX4-CrNiMo-16-5-1 cast supermartensitic stainless steel. The obtained results were compared with results from the Schaeffler diagram......, equilibrium calculations and the Scheil model in Thermo-Calc, and validated by using microscopy and energy dispersive X-ray spectroscopy for chemical analysis on a cast ingot. The kinetics model showed that micro-segregation from solidification homogenizes within 2–3 s (70 °C) of cooling, and that retained δ...
Model-fitting approach to kinetic analysis of non-isothermal oxidation of molybdenite
International Nuclear Information System (INIS)
Ebrahimi Kahrizsangi, R.; Abbasi, M. H.; Saidi, A.
2007-01-01
The kinetics of molybdenite oxidation was studied by non-isothermal TGA-DTA with heating rate 5 d eg C .min -1 . The model-fitting kinetic approach applied to TGA data. The Coats-Redfern method used of model fitting. The popular model-fitting gives excellent fit non-isothermal data in chemically controlled regime. The apparent activation energy was determined to be about 34.2 kcalmol -1 With pre-exponential factor about 10 8 sec -1 for extent of reaction less than 0.5
Systematic identification of crystallization kinetics within a generic modelling framework
DEFF Research Database (Denmark)
Abdul Samad, Noor Asma Fazli Bin; Meisler, Kresten Troelstrup; Gernaey, Krist
2012-01-01
A systematic development of constitutive models within a generic modelling framework has been developed for use in design, analysis and simulation of crystallization operations. The framework contains a tool for model identification connected with a generic crystallizer modelling tool-box, a tool...
Parameter Estimates in Differential Equation Models for Chemical Kinetics
Winkel, Brian
2011-01-01
We discuss the need for devoting time in differential equations courses to modelling and the completion of the modelling process with efforts to estimate the parameters in the models using data. We estimate the parameters present in several differential equation models of chemical reactions of order n, where n = 0, 1, 2, and apply more general…
Global fully kinetic models of planetary magnetospheres with iPic3D
Gonzalez, D.; Sanna, L.; Amaya, J.; Zitz, A.; Lembege, B.; Markidis, S.; Schriver, D.; Walker, R. J.; Berchem, J.; Peng, I. B.; Travnicek, P. M.; Lapenta, G.
2016-12-01
We report on the latest developments of our approach to model planetary magnetospheres, mini magnetospheres and the Earth's magnetosphere with the fully kinetic, electromagnetic particle in cell code iPic3D. The code treats electrons and multiple species of ions as full kinetic particles. We review: 1) Why a fully kinetic model and in particular why kinetic electrons are needed for capturing some of the most important aspects of the physics processes of planetary magnetospheres. 2) Why the energy conserving implicit method (ECIM) in its newest implementation [1] is the right approach to reach this goal. We consider the different electron scales and study how the new IECIM can be tuned to resolve only the electron scales of interest while averaging over the unresolved scales preserving their contribution to the evolution. 3) How with modern computing planetary magnetospheres, mini magnetosphere and eventually Earth's magnetosphere can be modeled with fully kinetic electrons. The path from petascale to exascale for iPiC3D is outlined based on the DEEP-ER project [2], using dynamic allocation of different processor architectures (Xeon and Xeon Phi) and innovative I/O technologies.Specifically results from models of Mercury are presented and compared with MESSENGER observations and with previous hybrid (fluid electrons and kinetic ions) simulations. The plasma convection around the planets includes the development of hydrodynamic instabilities at the flanks, the presence of the collisionless shocks, the magnetosheath, the magnetopause, reconnection zones, the formation of the plasma sheet and the magnetotail, and the variation of ion/electron plasma flows when crossing these frontiers. Given the full kinetic nature of our approach we focus on detailed particle dynamics and distribution at locations that can be used for comparison with satellite data. [1] Lapenta, G. (2016). Exactly Energy Conserving Implicit Moment Particle in Cell Formulation. arXiv preprint ar
Growth Kinetics and Modeling of Direct Oxynitride Growth with NO-O2 Gas Mixtures
Energy Technology Data Exchange (ETDEWEB)
Everist, Sarah; Nelson, Jerry; Sharangpani, Rahul; Smith, Paul Martin; Tay, Sing-Pin; Thakur, Randhir
1999-05-03
We have modeled growth kinetics of oxynitrides grown in NO-O_{2} gas mixtures from first principles using modified Deal-Grove equations. Retardation of oxygen diffusion through the nitrided dielectric was assumed to be the dominant growth-limiting step. The model was validated against experimentally obtained curves with good agreement. Excellent uniformity, which exceeded expected walues, was observed.
Kinetic Models for Adiabatic Reversible Expansion of a Monatomic Ideal Gas.
Chang, On-Kok
1983-01-01
A fixed amount of an ideal gas is confined in an adiabatic cylinder and piston device. The relation between temperature and volume in initial/final phases can be derived from the first law of thermodynamics. However, the relation can also be derived based on kinetic models. Several of these models are discussed. (JN)
Development of the kinetic model of platinum catalyzed ammonia oxidation in a microreactor
Rebrov, E.V.; Croon, de M.H.J.M.; Schouten, J.C.
2002-01-01
The ammonia oxidation reaction on supported polycrystalline platinum catalyst was investigated in an aluminum-based microreactor. An extensive set of reactions was included in the chemical reactor modeling to facilitate the construction of a kinetic model capable of satisfactory predictions for a
Equilibrium and kinetic models for colloid release under transient solution chemistry conditions
We present continuum models to describe colloid release in the subsurface during transient physicochemical conditions. Our modeling approach relates the amount of colloid release to changes in the fraction of the solid surface area that contributes to retention. Equilibrium, kinetic, equilibrium and...
A single grain approach applied to modelling recrystallization kinetics in a single-phase metal
Chen, S.P.; Zwaag, van der S.
2004-01-01
A comprehensive model for the recrystallization kinetics is proposed which incorporates both microstructure and the textural components in the deformed state. The model is based on the single-grain approach proposed previously. The influence of the as-deformed grain orientation, which affects the
A MATHEMATICAL MODEL FOR THE KINETICS OF THE MALE REPRODUCTIVE ENDOCRINE SYSTEM
In this presentation a model for the hormonal regulation of the reproductive endocrine system in the adult male rat will be discussed. The model includes a description of the kinetics of the androgenic hormones testosterone and dihydrotestosterone, as well as the receptor-mediate...
Empiric model for mean generation time adjustment factor for classic point kinetics equations
Energy Technology Data Exchange (ETDEWEB)
Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C., E-mail: david.goes@poli.ufrj.br, E-mail: aquilino@lmp.ufrj.br, E-mail: alessandro@con.ufrj.br [Coordenacao de Pos-Graduacao e Pesquisa de Engenharia (COPPE/UFRJ), Rio de Janeiro, RJ (Brazil). Departamento de Engenharia Nuclear
2017-11-01
Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)
Empiric model for mean generation time adjustment factor for classic point kinetics equations
International Nuclear Information System (INIS)
Goes, David A.B.V. de; Martinez, Aquilino S.; Goncalves, Alessandro da C.
2017-01-01
Point reactor kinetics equations are the easiest way to observe the neutron production time behavior in a nuclear reactor. These equations are derived from the neutron transport equation using an approximation called Fick's law leading to a set of first order differential equations. The main objective of this study is to review classic point kinetics equation in order to approximate its results to the case when it is considered the time variation of the neutron currents. The computational modeling used for the calculations is based on the finite difference method. The results obtained with this model are compared with the reference model and then it is determined an empirical adjustment factor that modifies the point reactor kinetics equation to the real scenario. (author)
Multigroup perturbation model for kinetic analysis of nuclear reactors
International Nuclear Information System (INIS)
Souza, G.M.
1989-01-01
The scope of this work is the development of a multigroup perturbation theory for the purpose of Kinetic and dynamic analysis of nuclear reactors. The equations that describe the reactor behavior were presented in all generality and written in the shorthand notation of matrices and vectors. In the derivation of those equations indetermined operators and discretizing factors were introduced and then determined by comparision with conventional equations. Fick's Law was developed in higher orders for neutron and importance current density. The solution of the direct and adjoint fields were represented by combination of the eigenfunctions of the B and B* operators and the eigenvalue modulus equality was established mathematically. In the derivation of the reactivity expression the B operator perturbation was split in two non coupled to the flux form and level. The prompt neutrons effective mean life was derived from reactor equations and importance conservation. The establishment of the Nordheim's equation, although modified, was based on Gandini. Finally, a mathematical interpretation of the flux-trap region was avented. (author)
Kinetics of conformational changes of fibronectin adsorbed onto model surfaces.
Baujard-Lamotte, L; Noinville, S; Goubard, F; Marque, P; Pauthe, E
2008-05-01
Fibronectin (FN), a large glycoprotein found in body fluids and in the extracellular matrix, plays a key role in numerous cellular behaviours. We investigate FN adsorption onto hydrophilic bare silica and hydrophobic polystyrene (PS) surfaces using Fourier transform infrared spectroscopy-attenuated total reflection (FTIR-ATR) in aqueous medium. Adsorption kinetics using different bulk concentrations of FN were followed for 2h and the surface density of adsorbed FN and its time-dependent conformational changes were determined. When adsorption occurs onto the hydrophilic surface, FN molecules keep their native conformation independent of the adsorption conditions, but the amount of adsorbed FN increases with time and the bulk concentration. Although the protein surface density is the same on the hydrophobic PS surface, this has a strong impact on the average conformation of the adsorbed FN layer. Indeed, interfacial hydration changes induced by adsorption onto the hydrophobic surface lead to a decrease in unhydrated beta-sheet content and cause an increase in hydrated beta-strand and hydrated random domain content of adsorbed FN. This conformational change is mainly dependent on the bulk concentration. Indeed, at low bulk concentrations, the secondary structures of adsorbed FN molecules undergo strong unfolding, allowing an extended and hydrated conformation of the protein. At high bulk concentrations, the molecular packing reduces the unfolding of the stereoregular structures of the FN molecules, preventing stronger spreading of the protein.
Kinetic models and parameters estimation study of biomass and ...
African Journals Online (AJOL)
compaq
2017-01-11
Jan 11, 2017 ... Unstructured models were proposed using the logistic equation for growth, the ... analysis of variance (ANOVA) was also used to validate the proposed models. ... production but their choice depends on the cost and the.
Kinetic models of cell growth, substrate utilization and bio ...
African Journals Online (AJOL)
STORAGESEVER
2008-05-02
May 2, 2008 ... Aspergillus fumigatus. A simple model was proposed using the Logistic Equation for the growth, ... costs and also involved in less sophisticated fermentation ... apply and they are accurately proved that the model can express ...
Effects of different per translational kinetics on the dynamics of a core circadian clock model.
Nieto, Paula S; Revelli, Jorge A; Garbarino-Pico, Eduardo; Condat, Carlos A; Guido, Mario E; Tamarit, Francisco A
2015-01-01
Living beings display self-sustained daily rhythms in multiple biological processes, which persist in the absence of external cues since they are generated by endogenous circadian clocks. The period (per) gene is a central player within the core molecular mechanism for keeping circadian time in most animals. Recently, the modulation PER translation has been reported, both in mammals and flies, suggesting that translational regulation of clock components is important for the proper clock gene expression and molecular clock performance. Because translational regulation ultimately implies changes in the kinetics of translation and, therefore, in the circadian clock dynamics, we sought to study how and to what extent the molecular clock dynamics is affected by the kinetics of PER translation. With this objective, we used a minimal mathematical model of the molecular circadian clock to qualitatively characterize the dynamical changes derived from kinetically different PER translational mechanisms. We found that the emergence of self-sustained oscillations with characteristic period, amplitude, and phase lag (time delays) between per mRNA and protein expression depends on the kinetic parameters related to PER translation. Interestingly, under certain conditions, a PER translation mechanism with saturable kinetics introduces longer time delays than a mechanism ruled by a first-order kinetics. In addition, the kinetic laws of PER translation significantly changed the sensitivity of our model to parameters related to the synthesis and degradation of per mRNA and PER degradation. Lastly, we found a set of parameters, with realistic values, for which our model reproduces some experimental results reported recently for Drosophila melanogaster and we present some predictions derived from our analysis.
Childers, W Lee; Kogler, Géza F
2014-01-01
People with amputation move asymmetrically with regard to kinematics (joint angles) and kinetics (joint forces and moments). Clinicians have traditionally sought to minimize kinematic asymmetries, assuming kinetic asymmetries would also be minimized. A cycling model evaluated locomotor asymmetries. Eight individuals with unilateral transtibial amputation pedaled with 172 mm-length crank arms on both sides (control condition) and with the crank arm length shortened to 162 mm on the amputated side (CRANK condition). Pedaling kinetics and limb kinematics were recorded. Joint kinetics, joint angles (mean and range of motion [ROM]), and pedaling asymmetries were calculated from force pedals and with a motion capture system. A one-way analysis of variance with tukey post hoc compared kinetics and kinematics across limbs. Statistical significance was set to p Pedaling asymmetries did not differ and were 23.0% +/= 9.8% and 23.2% +/= 12% for the control and CRANK conditions, respectively. Our results suggest that minimizing kinematic asymmetries does not relate to kinetic asymmetries as clinically assumed. We propose that future research should concentrate on defining acceptable asymmetry.
Association of footprint measurements with plantar kinetics: a linear regression model.
Fascione, Jeanna M; Crews, Ryan T; Wrobel, James S
2014-03-01
The use of foot measurements to classify morphology and interpret foot function remains one of the focal concepts of lower-extremity biomechanics. However, only 27% to 55% of midfoot variance in foot pressures has been determined in the most comprehensive models. We investigated whether dynamic walking footprint measurements are associated with inter-individual foot loading variability. Thirty individuals (15 men and 15 women; mean ± SD age, 27.17 ± 2.21 years) walked at a self-selected speed over an electronic pedography platform using the midgait technique. Kinetic variables (contact time, peak pressure, pressure-time integral, and force-time integral) were collected for six masked regions. Footprints were digitized for area and linear boundaries using digital photo planimetry software. Six footprint measurements were determined: contact area, footprint index, arch index, truncated arch index, Chippaux-Smirak index, and Staheli index. Linear regression analysis with a Bonferroni adjustment was performed to determine the association between the footprint measurements and each of the kinetic variables. The findings demonstrate that a relationship exists between increased midfoot contact and increased kinetic values in respective locations. Many of these variables produced large effect sizes while describing 38% to 71% of the common variance of select plantar kinetic variables in the medial midfoot region. In addition, larger footprints were associated with larger kinetic values at the medial heel region and both masked forefoot regions. Dynamic footprint measurements are associated with dynamic plantar loading kinetics, with emphasis on the midfoot region.
International Nuclear Information System (INIS)
Shadbahr, Jalil; Khan, Faisal; Zhang, Yan
2017-01-01
Highlights: • Deeper understanding of saccharification and fermentation process. • A new kinetic model for dynamic analysis of the simultaneous saccharification and fermentation. • Testing and validation of kinetic model. - Abstract: Kinetic modeling and dynamic analysis of the simultaneous saccharification and fermentation (SSF) of cellulose to ethanol was carried out in this study to determine the key reaction kinetics parameters and product inhibition features of the process. To obtain the more reliable kinetic parameters which can be applied for a wide range of operating conditions, batch SSF experiments were carried out at three enzyme loadings (10, 15 and 20 FPU/g cellulose) and two levels of initial concentrations of fermentable sugars (glucose and mannose). Results indicated that the maximum ethanol yield and concentration were achieved at high level of sugar concentrations with intermediate enzyme loading (15 FPU/g cellulose). Dynamic analysis of the acquired experimental results revealed that cellulase inhibition by cellobiose plays the most important role at high level of enzyme loading and low level of initial sugar concentrations. The inhibition of glucose becomes significant when high concentrations of sugars were present in the feedstock. Experimental results of SSF process also reveal that an efficient mixing between the phases helps to improve the ethanol yield significantly.
Kinetic modeling of antimony(III) oxidation and sorption in soils.
Cai, Yongbing; Mi, Yuting; Zhang, Hua
2016-10-05
Kinetic batch and saturated column experiments were performed to study the oxidation, adsorption and transport of Sb(III) in two soils with contrasting properties. Kinetic and column experiment results clearly demonstrated the extensive oxidation of Sb(III) in soils, and this can in return influence the adsorption and transport of Sb. Both sorption capacity and kinetic oxidation rate were much higher in calcareous Huanjiang soil than in acid red Yingtan soil. The results indicate that soil serve as a catalyst in promoting oxidation of Sb(III) even under anaerobic conditions. A PHREEQC model with kinetic formulations was developed to simulate the oxidation, sorption and transport of Sb(III) in soils. The model successfully described Sb(III) oxidation and sorption data in kinetic batch experiment. It was less successful in simulating the reactive transport of Sb(III) in soil columns. Additional processes such as colloid facilitated transport need to be quantified and considered in the model. Copyright © 2016 Elsevier B.V. All rights reserved.
Thermodynamic modelling and kinetics of hydrogen absorption associated with phase transformations
International Nuclear Information System (INIS)
Gondor, G.; Lexcellent, Ch.
2007-01-01
The intermetallic are used for hydrogen pressure containers in order to avoid leaks in the case of an hybrid container. The hydrogen atoms are absorbed by the intermetallic which act as a hydrogen sponge. This hydrogen absorption must be modelled for the container design. The Pressure-composition isotherms describe the equilibrium. Out of this equilibrium the kinetics are controlled by different processes, without taking into account the phase transformations. The author presents a new model of the p-c isotherms with the hydrogen absorption kinetics. (A.L.B.)
An experimental and kinetic modeling study of premixed nitroethane flames at low pressure
DEFF Research Database (Denmark)
Zhang, Kuiwen; Zhang, Lidong; Xie, Mingfeng
2013-01-01
An experimental and kinetic modeling study is reported on three premixed nitroethane/oxygen/argon flames at low pressure (4.655kPa) with the equivalence ratios (Φ) of 1.0, 1.5 and 2.0. Over 30 flame species were identified with tunable synchrotron vacuum ultraviolet photoionization mass spectrome......An experimental and kinetic modeling study is reported on three premixed nitroethane/oxygen/argon flames at low pressure (4.655kPa) with the equivalence ratios (Φ) of 1.0, 1.5 and 2.0. Over 30 flame species were identified with tunable synchrotron vacuum ultraviolet photoionization mass...
DEFF Research Database (Denmark)
Hereu, A.; Dalgaard, Paw; Garriga, M.
2012-01-01
High pressure (HP) inactivation curves of Listeria monocytogenes CTC1034 (ca. 107CFU/g) on sliced RTE cooked meat products (ham and mortadella) were obtained at pressures from 300 to 800MPa. A clear tail shape was observed at pressures above 450MPa and the log-linear with tail primary model...... provided the best fit to the HP-inactivation kinetics. The relationships between the primary kinetic parameters (log kmax and log Nres) and pressure treatments were described by a polynomial secondary model. To estimate HP-inactivation of L. monocytogenes in log (N/N0) over time, a one-step global fitting...
Kinetic extensions of magnetohydrodynamic models for axisymmetric toroidal plasmas
International Nuclear Information System (INIS)
Cheng, C.Z.
1989-04-01
A nonvariational kinetic-MHD stability code (NOVA-K) has been developed to integrate a set of non-Hermitian integro-differential eigenmode equations due to energetic particles for axisymmetric toroidal plasmas in a general flux coordinate system with an arbitrary Jacobian. The NOVA-K code employs the Galerkin method involving Fourier expansions in the generalized poloidal angle θ and generalized toroidal angle /zeta/ directions, and cubic-B spline finite elements in the radial /Psi/ direction. Extensive comparisons with the existing variational ideal MHD codes show that the ideal MHD version of the NOVA-K code converges faster and gives more accurate results. The NOVA-K code is employed to study the effects of energetic particles on MHD-type modes: the stabilization of ideal MHD internal kink modes and the excitation of ''fishbone'' internal kink modes; and the alpha particle destabilization of toroidicity-induced Alfven eigenmodes (TAE) via transit resonances. Analytical theories are also presented to help explain the NOVA-K results. For energetic trapped particles generated by neutral beam injection (NBI) or ion cyclotron resonant heating (ICRH), a stability window for the n = 1 internal kink mode in the hot particle beta space exists even in the absence of the core ion finite Larmor radius effect. On the other hand, the trapped alpha particles are found to have negligible effects on the stability of the n = 1 internal kink mode, but the circulating alpha particles can strongly destabilize TAE modes via inverse Landau damping associated with the spatial gradient of the alpha particle pressure. 60 refs., 24 figs., 1 tab
Energy Technology Data Exchange (ETDEWEB)
Perelson, Alan S [Los Alamos National Laboratory; Shudo, Emi [Los Alamos National Laboratory; Ribeiro, Ruy M [Los Alamos National Laboratory
2008-01-01
Mathematical models have proven helpful in analyzing the virological response to antiviral therapy in hepatitis C virus (HCY) infected subjects. Objective: To summarize the uses and limitations of different models for analyzing HCY kinetic data under pegylated interferon therapy. Methods: We formulate mathematical models and fit them by nonlinear least square regression to patient data in order estimate model parameters. We compare the goodness of fit and parameter values estimated by different models statistically. Results/Conclusion: The best model for parameter estimation depends on the availability and the quality of data as well as the therapy used. We also discuss the mathematical models that will be needed to analyze HCV kinetic data from clinical trials with new antiviral drugs.
Measurement and modeling of diffusion kinetics of a lipophilic molecule across rabbit cornea.
Gupta, Chhavi; Chauhan, Anuj; Mutharasan, Raj; Srinivas, Sangly P
2010-04-01
To develop a kinetic model for representing the diffusion and partitioning of Rhodamine B (RhB), a fluorescent lipophilic molecule, across the cornea for gaining insights into pharmacokinetics of topical drugs to the eye. Rabbit corneas mounted underneath a custom-built scanning microfluorometer were perfused with Ringers on both sides of the tissue. After a step change in RhB on the tear side, transients of trans-corneal fluorescence of RhB were measured at a depth resolution approximately 8 microm. RhB distribution exhibited discontinuities at the interface between epithelium and stroma, and between stroma and endothelium. In each of the layers, fluorescence was non-uniform. Fluorescence was elevated in the epithelium and endothelium relative to the stroma. Modeling of RhB transport by diffusion in each layer and stipulation of partitioning of RhB at the cellular interfaces were required to account for trans-corneal penetration kinetics of RhB. The model parameters, estimated using the unsteady state trans-corneal RhB profiles, were found to be sensitive, and the model predicted the experimental profiles accurately. Conventional pharmacokinetic models that depict cornea as a single compartment do not predict the depth-dependent kinetics of RhB penetration. The proposed model incorporates realistic transport mechanisms and thereby highlights the influence of physicochemical properties of drugs on trans-corneal kinetics.
Directory of Open Access Journals (Sweden)
Antonio Tripodi
2017-05-01
Full Text Available Process simulation represents an important tool for plant design and optimization, either applied to well established or to newly developed processes. Suitable thermodynamic packages should be selected in order to properly describe the behavior of reactors and unit operations and to precisely define phase equilibria. Moreover, a detailed and representative kinetic scheme should be available to predict correctly the dependence of the process on its main variables. This review points out some models and methods for kinetic analysis specifically applied to the simulation of catalytic processes, as a basis for process design and optimization. Attention is paid also to microkinetic modelling and to the methods based on first principles, to elucidate mechanisms and independently calculate thermodynamic and kinetic parameters. Different case studies support the discussion. At first, we have selected two basic examples from the industrial chemistry practice, e.g., ammonia and methanol synthesis, which may be described through a relatively simple reaction pathway and the relative available kinetic scheme. Then, a more complex reaction network is deeply discussed to define the conversion of bioethanol into syngas/hydrogen or into building blocks, such as ethylene. In this case, lumped kinetic schemes completely fail the description of process behavior. Thus, in this case, more detailed—e.g., microkinetic—schemes should be available to implement into the simulator. However, the correct definition of all the kinetic data when complex microkinetic mechanisms are used, often leads to unreliable, highly correlated parameters. In such cases, greater effort to independently estimate some relevant kinetic/thermodynamic data through Density Functional Theory (DFT/ab initio methods may be helpful to improve process description.
International Nuclear Information System (INIS)
Wuebbles, D.J.
1981-09-01
Since the LLNL one-dimensional coupled transport and chemical kinetics model of the troposphere and stratosphere was originally developed in 1972 (Chang et al., 1974), there have been many changes to the model's representation of atmospheric physical and chemical processes. A brief description is given of the current LLNL one-dimensional coupled transport and chemical kinetics model of the troposphere and stratosphere
The fractional diffusion limit of a kinetic model with biochemical pathway
Perthame, Benoît; Sun, Weiran; Tang, Min
2018-06-01
Kinetic-transport equations that take into account the intracellular pathways are now considered as the correct description of bacterial chemotaxis by run and tumble. Recent mathematical studies have shown their interest and their relations to more standard models. Macroscopic equations of Keller-Segel type have been derived using parabolic scaling. Due to the randomness of receptor methylation or intracellular chemical reactions, noise occurs in the signaling pathways and affects the tumbling rate. Then comes the question to understand the role of an internal noise on the behavior of the full population. In this paper we consider a kinetic model for chemotaxis which includes biochemical pathway with noises. We show that under proper scaling and conditions on the tumbling frequency as well as the form of noise, fractional diffusion can arise in the macroscopic limits of the kinetic equation. This gives a new mathematical theory about how long jumps can be due to the internal noise of the bacteria.
Kinetic modeling of the photocatalytic degradation of clofibric acid in a slurry reactor.
Manassero, Agustina; Satuf, María Lucila; Alfano, Orlando Mario
2015-01-01
A kinetic study of the photocatalytic degradation of the pharmaceutical clofibric acid is presented. Experiments were carried out under UV radiation employing titanium dioxide in water suspension. The main reaction intermediates were identified and quantified. Intrinsic expressions to represent the kinetics of clofibric acid and the main intermediates were derived. The modeling of the radiation field in the reactor was carried out by Monte Carlo simulation. Experimental runs were performed by varying the catalyst concentration and the incident radiation. Kinetic parameters were estimated from the experiments by applying a non-linear regression procedure. Good agreement was obtained between model predictions and experimental data, with an error of 5.9 % in the estimations of the primary pollutant concentration.
Modeling of scale-dependent bacterial growth by chemical kinetics approach.
Martínez, Haydee; Sánchez, Joaquín; Cruz, José-Manuel; Ayala, Guadalupe; Rivera, Marco; Buhse, Thomas
2014-01-01
We applied the so-called chemical kinetics approach to complex bacterial growth patterns that were dependent on the liquid-surface-area-to-volume ratio (SA/V) of the bacterial cultures. The kinetic modeling was based on current experimental knowledge in terms of autocatalytic bacterial growth, its inhibition by the metabolite CO2, and the relief of inhibition through the physical escape of the inhibitor. The model quantitatively reproduces kinetic data of SA/V-dependent bacterial growth and can discriminate between differences in the growth dynamics of enteropathogenic E. coli, E. coli JM83, and Salmonella typhimurium on one hand and Vibrio cholerae on the other hand. Furthermore, the data fitting procedures allowed predictions about the velocities of the involved key processes and the potential behavior in an open-flow bacterial chemostat, revealing an oscillatory approach to the stationary states.
Modeling of Scale-Dependent Bacterial Growth by Chemical Kinetics Approach
Directory of Open Access Journals (Sweden)
Haydee Martínez
2014-01-01
Full Text Available We applied the so-called chemical kinetics approach to complex bacterial growth patterns that were dependent on the liquid-surface-area-to-volume ratio (SA/V of the bacterial cultures. The kinetic modeling was based on current experimental knowledge in terms of autocatalytic bacterial growth, its inhibition by the metabolite CO2, and the relief of inhibition through the physical escape of the inhibitor. The model quantitatively reproduces kinetic data of SA/V-dependent bacterial growth and can discriminate between differences in the growth dynamics of enteropathogenic E. coli, E. coli JM83, and Salmonella typhimurium on one hand and Vibrio cholerae on the other hand. Furthermore, the data fitting procedures allowed predictions about the velocities of the involved key processes and the potential behavior in an open-flow bacterial chemostat, revealing an oscillatory approach to the stationary states.
Kocadağlı, Tolgahan; Gökmen, Vural
2016-11-15
The study describes the kinetics of the formation and degradation of α-dicarbonyl compounds in glucose/wheat flour system heated under low moisture conditions. Changes in the concentrations of glucose, fructose, individual free amino acids, lysine and arginine residues, glucosone, 1-deoxyglucosone, 3-deoxyglucosone, 3,4-dideoxyglucosone, 5-hydroxymethyl-2-furfural, glyoxal, methylglyoxal and diacetyl concentrations were determined to form a multiresponse kinetic model for isomerisation and degradation reactions of glucose. Degradation of Amadori product mainly produced 1-deoxyglucosone. Formation of 3-deoxyglucosone proceeded directly from glucose and also Amadori product degradation. Glyoxal formation was predominant from glucosone while methylglyoxal and diacetyl originated from 1-deoxyglucosone. Formation of 5-hydroxymethyl-2-furfural from fructose was found to be a key step. Multi-response kinetic modelling of Maillard reaction and caramelisation simultaneously indicated quantitatively predominant parallel and consecutive pathways and rate limiting steps by estimating the reaction rate constants. Copyright © 2016 Elsevier Ltd. All rights reserved.
DEFF Research Database (Denmark)
Erlandsen, Mogens; Martinussen, Christoffer; Gravholt, Claus Højbjerg
2018-01-01
AbstractBackground and objectives Modeling of glucose kinetics has to a large extent been based on models with plasma insulin as a known forcing function. Furthermore, population-based statistical methods for parameter estimation in these models have mainly addressed random inter-individual varia......AbstractBackground and objectives Modeling of glucose kinetics has to a large extent been based on models with plasma insulin as a known forcing function. Furthermore, population-based statistical methods for parameter estimation in these models have mainly addressed random inter......-individual variations and not intra-individual variations in the parameters. Here we present an integrated whole-body model of glucose and insulin kinetics which extends the well-known two-compartment glucose minimal model. The population-based estimation technique allow for quantification of both random inter......- and intra-individual variation in selected parameters using simultaneous data series on glucose and insulin. Methods We extend the two-compartment glucose model into a whole-body model for both glucose and insulin using a simple model for the pancreas compartment which includes feedback of glucose on both...
Modelling kinetics of plant canopy architecture: concepts and applications
Birch, C.J.; Andrieu, B.; Fournier, C.; Vos, J.; Room, P.
2003-01-01
Most crop models simulate the crop canopy as an homogeneous medium. This approach enables modelling of mass and energy transfer through relatively simple equations, and is useful for understanding crop production. However, schematisation of an homogeneous medium cannot address the heterogeneous
Directory of Open Access Journals (Sweden)
Ali eKhodayari
2015-01-01
Full Text Available Computational strain design prediction accuracy has been the focus for many recent efforts through the selective integration of kinetic information into metabolic models. In general, kinetic model prediction quality is determined by the range and scope of genetic and/or environmental perturbations used during parameterization. In this effort, we apply the k-OptForce procedure on a kinetic model of E. coli core metabolism constructed using the Ensemble Modeling (EM method and parameterized using multiple mutant strains data under aerobic respiration with glucose as the carbon source. Minimal interventions are identified that improve succinate yield under both aerobic and anaerobic conditions to test the fidelity of model predictions under both genetic and environmental perturbations. Under aerobic condition, k-OptForce identifies interventions that match existing experimental strategies pointing at a number of unexplored flux redirections such as routing glyoxylate flux through the glycerate metabolism to improve succinate yield. Many of the identified interventions rely on the kinetic descriptions and would not be discoverable by a purely stoichiometric description. In contrast, under fermentative (anaerobic conditions, k-OptForce fails to identify key interventions including up-regulation of anaplerotic reactions and elimination of competitive fermentative products. This is due to the fact that the pathways activated under anaerobic conditions were not properly parameterized as only aerobic flux data were used in the model construction. This study shed light on the importance of condition-specific model parameterization and provides insight onto how to augment kinetic models so as to correctly respond to multiple environmental perturbations.