Relevant bibliographies by topics / FBA modeling

Academic literature on the topic 'FBA modeling'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "FBA modeling"

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Gage, Nicholas A., Timothy J. Lewis, and Janine P. Stichter. "Functional Behavioral Assessment-Based Interventions for Students with or at Risk for Emotional and/or Behavioral Disorders in School: A Hierarchical Linear Modeling Meta-Analysis." Behavioral Disorders 37, no. 2 (February 2012): 55–77. http://dx.doi.org/10.1177/019874291203700201.

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Of the myriad practices currently utilized for students with disabilities, particularly students with or at risk for emotional and/or behavioral disorder (EBD), functional behavior assessment (FBA) is a practice with an emerging solid research base. However, the FBA research base relies on single-subject design (SSD) and synthesis has relied on literature review or analyses using nonparametric effect size calculations. This study was designed to examine the omnibus effect that FBA-based interventions have on problem behaviors for students with or at risk for EBD in schools using a hierarchical linear modeling meta-analytic approach to SSD synthesis. Based on a sample of 69 FBA studies, 146 subjects, and 206 outcome graphs, results indicated that, overall, FBA-based interventions reduced problem behavior by an average of 70.5% and that the procedure was effective across all student characteristics. Differences of effectiveness were evident between functional analysis and descriptive assessment procedures. Findings of this study suggest that FBA-based interventions for students with or at risk for EBD are an effective approach for the reduction of problem behaviors.
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van Pelt-KleinJan, Eunice, Daan H. de Groot, and Bas Teusink. "Understanding FBA Solutions under Multiple Nutrient Limitations." Metabolites 11, no. 5 (April 21, 2021): 257. http://dx.doi.org/10.3390/metabo11050257.

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Genome-scale stoichiometric modeling methods, in particular Flux Balance Analysis (FBA) and variations thereof, are widely used to investigate cell metabolism and to optimize biotechnological processes. Given (1) a metabolic network, which can be reconstructed from an organism’s genome sequence, and (2) constraints on reaction rates, which may be based on measured nutrient uptake rates, FBA predicts which reactions maximize an objective flux, usually the production of cell components. Although FBA solutions may accurately predict the metabolic behavior of a cell, the actual flux predictions are often hard to interpret. This is especially the case for conditions with many constraints, such as for organisms growing in rich nutrient environments: it remains unclear why a certain solution was optimal. Here, we rationalize FBA solutions by explaining for which properties the optimal combination of metabolic strategies is selected. We provide a graphical formalism in which the selection of solutions can be visualized; we illustrate how this perspective provides a glimpse of the logic that underlies genome-scale modeling by applying our formalism to models of various sizes.
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Katebi, Ataur R., and Robert L. Jernigan. "Modeling Complex between FBA and TIM: Functional Motions of FBA and TIM are Preserved in their Complex." Biophysical Journal 104, no. 2 (January 2013): 402a. http://dx.doi.org/10.1016/j.bpj.2012.11.2243.

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Covert, Markus W., Nan Xiao, Tiffany J. Chen, and Jonathan R. Karr. "Integrating metabolic, transcriptional regulatory and signal transduction models in Escherichia coli." Bioinformatics 24, no. 18 (July 10, 2008): 2044–50. http://dx.doi.org/10.1093/bioinformatics/btn352.

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AbstractMotivation: The effort to build a whole-cell model requires the development of new modeling approaches, and in particular, the integration of models for different types of processes, each of which may be best described using different representation. Flux-balance analysis (FBA) has been useful for large-scale analysis of metabolic networks, and methods have been developed to incorporate transcriptional regulation (regulatory FBA, or rFBA). Of current interest is the integration of these approaches with detailed models based on ordinary differential equations (ODEs).Results: We developed an approach to modeling the dynamic behavior of metabolic, regulatory and signaling networks by combining FBA with regulatory Boolean logic, and ordinary differential equations. We use this approach (called integrated FBA, or iFBA) to create an integrated model of Escherichia coli which combines a flux-balance-based, central carbon metabolic and transcriptional regulatory model with an ODE-based, detailed model of carbohydrate uptake control. We compare the predicted Escherichia coli wild-type and single gene perturbation phenotypes for diauxic growth on glucose/lactose and glucose/glucose-6-phosphate with that of the individual models. We find that iFBA encapsulates the dynamics of three internal metabolites and three transporters inadequately predicted by rFBA. Furthermore, we find that iFBA predicts different and more accurate phenotypes than the ODE model for 85 of 334 single gene perturbation simulations, as well for the wild-type simulations. We conclude that iFBA is a significant improvement over the individual rFBA and ODE modeling paradigms.Availability: All MATLAB files used in this study are available at http://www.simtk.org/home/ifba/.Contact: covert@stanford.eduSupplementary information: Supplementary data are available at Bioinformatics online.
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Ohno, Satoshi, Saori Uematsu, and Shinya Kuroda. "Quantitative metabolic fluxes regulated by trans-omic networks." Biochemical Journal 479, no. 6 (March 31, 2022): 787–804. http://dx.doi.org/10.1042/bcj20210596.

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Cells change their metabolism in response to internal and external conditions by regulating the trans-omic network, which is a global biochemical network with multiple omic layers. Metabolic flux is a direct measure of the activity of a metabolic reaction that provides valuable information for understanding complex trans-omic networks. Over the past decades, techniques to determine metabolic fluxes, including 13C-metabolic flux analysis (13C-MFA), flux balance analysis (FBA), and kinetic modeling, have been developed. Recent studies that acquire quantitative metabolic flux and multi-omic data have greatly advanced the quantitative understanding and prediction of metabolism-centric trans-omic networks. In this review, we present an overview of 13C-MFA, FBA, and kinetic modeling as the main techniques to determine quantitative metabolic fluxes, and discuss their advantages and disadvantages. We also introduce case studies with the aim of understanding complex metabolism-centric trans-omic networks based on the determination of metabolic fluxes.
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Zorrilla, Francisco, Filip Buric, Kiran R. Patil, and Aleksej Zelezniak. "metaGEM: reconstruction of genome scale metabolic models directly from metagenomes." Nucleic Acids Research 49, no. 21 (October 6, 2021): e126-e126. http://dx.doi.org/10.1093/nar/gkab815.

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Abstract Metagenomic analyses of microbial communities have revealed a large degree of interspecies and intraspecies genetic diversity through the reconstruction of metagenome assembled genomes (MAGs). Yet, metabolic modeling efforts mainly rely on reference genomes as the starting point for reconstruction and simulation of genome scale metabolic models (GEMs), neglecting the immense intra- and inter-species diversity present in microbial communities. Here, we present metaGEM (https://github.com/franciscozorrilla/metaGEM), an end-to-end pipeline enabling metabolic modeling of multi-species communities directly from metagenomes. The pipeline automates all steps from the extraction of context-specific prokaryotic GEMs from MAGs to community level flux balance analysis (FBA) simulations. To demonstrate the capabilities of metaGEM, we analyzed 483 samples spanning lab culture, human gut, plant-associated, soil, and ocean metagenomes, reconstructing over 14,000 GEMs. We show that GEMs reconstructed from metagenomes have fully represented metabolism comparable to isolated genomes. We demonstrate that metagenomic GEMs capture intraspecies metabolic diversity and identify potential differences in the progression of type 2 diabetes at the level of gut bacterial metabolic exchanges. Overall, metaGEM enables FBA-ready metabolic model reconstruction directly from metagenomes, provides a resource of metabolic models, and showcases community-level modeling of microbiomes associated with disease conditions allowing generation of mechanistic hypotheses.
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Karlsen, Emil, Marianne Gylseth, Christian Schulz, and Eivind Almaas. "A study of a diauxic growth experiment using an expanded dynamic flux balance framework." PLOS ONE 18, no. 1 (January 6, 2023): e0280077. http://dx.doi.org/10.1371/journal.pone.0280077.

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Flux balance analysis (FBA) remains one of the most used methods for modeling the entirety of cellular metabolism, and a range of applications and extensions based on the FBA framework have been generated. Dynamic flux balance analysis (dFBA), the expansion of FBA into the time domain, still has issues regarding accessibility limiting its widespread adoption and application, such as a lack of a consistently rigid formalism and tools that can be applied without expert knowledge. Recent work has combined dFBA with enzyme-constrained flux balance analysis (decFBA), which has been shown to greatly improve accuracy in the comparison of computational simulations and experimental data, but such approaches generally do not take into account the fact that altering the enzyme composition of a cell is not an instantaneous process. Here, we have developed a decFBA method that explicitly takes enzyme change constraints (ecc) into account, decFBAecc. The resulting software is a simple yet flexible framework for using genome-scale metabolic modeling for simulations in the time domain that has full interoperability with the COBRA Toolbox 3.0. To assess the quality of the computational predictions of decFBAecc, we conducted a diauxic growth fermentation experiment with Escherichia coli BW25113 in glucose minimal M9 medium. The comparison of experimental data with dFBA, decFBA and decFBAecc predictions demonstrates how systematic analyses within a fixed constraint-based framework can aid the study of model parameters. Finally, in explaining experimentally observed phenotypes, our computational analysis demonstrates the importance of non-linear dependence of exchange fluxes on medium metabolite concentrations and the non-instantaneous change in enzyme composition, effects of which have not previously been accounted for in constraint-based analysis.
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Ramakrishna, Ramprasad, Jeremy S. Edwards, Andrew McCulloch, and Bernhard O. Palsson. "Flux-balance analysis of mitochondrial energy metabolism: consequences of systemic stoichiometric constraints." American Journal of Physiology-Regulatory, Integrative and Comparative Physiology 280, no. 3 (March 1, 2001): R695—R704. http://dx.doi.org/10.1152/ajpregu.2001.280.3.r695.

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Mitochondrial metabolism is a critical component in the functioning and maintenance of cellular organs. The stoichiometry of biochemical reaction networks imposes constraints on mitochondrial function. A modeling framework, flux-balance analysis (FBA), was used to characterize the optimal flux distributions for maximal ATP production in the mitochondrion. The model predicted the expected ATP yields for glucose, lactate, and palmitate. Genetic defects that affect mitochondrial functions have been implicated in several human diseases. FBA can characterize the metabolic behavior due to genetic deletions at the metabolic level, and the effect of mutations in the tricarboxylic acid (TCA) cycle on mitochondrial ATP production was simulated. The mitochondrial ATP production is severely affected by TCA-cycle mutations. In addition, the model predicts the secretion of TCA-cycle intermediates, which is observed in clinical studies of mitochondriopathies such as those associated with fumarase deficiency. The model provides a systemic perspective to characterize the effect of stoichiometric constraints and specific metabolic fluxes on mitochondrial function.
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Olivier, Brett G., and Frank T. Bergmann. "The Systems Biology Markup Language (SBML) Level 3 Package: Flux Balance Constraints." Journal of Integrative Bioinformatics 12, no. 2 (June 1, 2015): 660–90. http://dx.doi.org/10.1515/jib-2015-269.

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Summary Constraint-based modeling is a well established modelling methodology used to analyze and study biological networks on both a medium and genome scale. Due to their large size, genome scale models are typically analysed using constraint-based optimization techniques. One widely used method is Flux Balance Analysis (FBA) which, for example, requires a modelling description to include: the definition of a stoichiometric matrix, an objective function and bounds on the values that fluxes can obtain at steady state.The Flux Balance Constraints (FBC) Package extends SBML Level 3 and provides a standardized format for the encoding, exchange and annotation of constraint-based models. It includes support for modelling concepts such as objective functions, flux bounds and model component annotation that facilitates reaction balancing. The FBC package establishes a base level for the unambiguous exchange of genome-scale, constraint-based models, that can be built upon by the community to meet future needs (e. g. by extending it to cover dynamic FBC models).
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Ravi, Sudharshan, and Rudiyanto Gunawan. "ΔFBA—Predicting metabolic flux alterations using genome-scale metabolic models and differential transcriptomic data." PLOS Computational Biology 17, no. 11 (November 10, 2021): e1009589. http://dx.doi.org/10.1371/journal.pcbi.1009589.

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Genome-scale metabolic models (GEMs) provide a powerful framework for simulating the entire set of biochemical reactions in a cell using a constraint-based modeling strategy called flux balance analysis (FBA). FBA relies on an assumed metabolic objective for generating metabolic fluxes using GEMs. But, the most appropriate metabolic objective is not always obvious for a given condition and is likely context-specific, which often complicate the estimation of metabolic flux alterations between conditions. Here, we propose a new method, called ΔFBA (deltaFBA), that integrates differential gene expression data to evaluate directly metabolic flux differences between two conditions. Notably, ΔFBA does not require specifying the cellular objective. Rather, ΔFBA seeks to maximize the consistency and minimize inconsistency between the predicted flux differences and differential gene expression. We showcased the performance of ΔFBA through several case studies involving the prediction of metabolic alterations caused by genetic and environmental perturbations in Escherichia coli and caused by Type-2 diabetes in human muscle. Importantly, in comparison to existing methods, ΔFBA gives a more accurate prediction of flux differences.
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Dissertations / Theses on the topic "FBA modeling"

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Ong, Wai, Trang Vu, Klaus Lovendahl, Jenna Llull, Margrethe Serres, Margaret Romine, and Jennifer Reed. "Comparisons of Shewanella strains based on genome annotations, modeling, and experiments." BioMed Central, 2014. http://hdl.handle.net/10150/610105.

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BACKGROUND:Shewanella is a genus of facultatively anaerobic, Gram-negative bacteria that have highly adaptable metabolism which allows them to thrive in diverse environments. This quality makes them an attractive bacterial target for research in bioremediation and microbial fuel cell applications. Constraint-based modeling is a useful tool for helping researchers gain insights into the metabolic capabilities of these bacteria. However, Shewanella oneidensis MR-1 is the only strain with a genome-scale metabolic model constructed out of 21 sequenced Shewanella strains.RESULTS:In this work, we updated the model for Shewanella oneidensis MR-1 and constructed metabolic models for three other strains, namely Shewanella sp. MR-4, Shewanella sp. W3-18-1, and Shewanella denitrificans OS217 which span the genus based on the number of genes lost in comparison to MR-1. We also constructed a Shewanella core model that contains the genes shared by all 21 sequenced strains and a few non-conserved genes associated with essential reactions. Model comparisons between the five constructed models were done at two levels - for wildtype strains under different growth conditions and for knockout mutants under the same growth condition. In the first level, growth/no-growth phenotypes were predicted by the models on various carbon sources and electron acceptors. Cluster analysis of these results revealed that the MR-1 model is most similar to the W3-18-1 model, followed by the MR-4 and OS217 models when considering predicted growth phenotypes. However, a cluster analysis done based on metabolic gene content revealed that the MR-4 and W3-18-1 models are the most similar, with the MR-1 and OS217 models being more distinct from these latter two strains. As a second level of comparison, we identified differences in reaction and gene content which give rise to different functional predictions of single and double gene knockout mutants using Comparison of Networks by Gene Alignment (CONGA). Here, we showed how CONGA can be used to find biomass, metabolic, and genetic differences between models.CONCLUSIONS:We developed four strain-specific models and a general core model that can be used to do various in silico studies of Shewanella metabolism. The developed models provide a platform for a systematic investigation of Shewanella metabolism to aid researchers using Shewanella in various biotechnology applications.
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Lin, Bingcan. "A new FEA modelling of porous solids." Available from the University of Aberdeen Library and Historic Collections Digital Resources, 2009. http://digitool.abdn.ac.uk:80/webclient/DeliveryManager?application=DIGITOOL-3&owner=resourcediscovery&custom_att_2=simple_viewer&pid=59600.

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Adiamah, Delali. "Genome-scale integrative modelling of gene expression and metabolic networks." Thesis, University of Manchester, 2012. https://www.research.manchester.ac.uk/portal/en/theses/genomescale-integrative-modelling-of-gene-expression-and-metabolic-networks(4fb25bda-2890-4b64-94e1-3e5b538cd1a5).html.

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The elucidation of molecular function of proteins encoded by genes is a major challenge in biology today. Genes regulate the amount of proteins (enzymes) needed to catalyse a metabolic reaction. There are several works on either the modelling of gene expression or metabolic network. However, an integrative model of both is not well understood and researched. The integration of both gene expression and metabolic network could increase our understanding of cellular functions and aid in analysing the effects of genes on metabolism. It is now possible to build genome-scale models of cellular processes due to the availability of high-throughput genomic, metabolic and fluxomic data along with thermodynamic information. Integrating biological information at various layers into metabolic models could also improve the robustness of models for in silico analysis. In this study, we provide a software tool for the in silico reconstruction of genome-scale integrative models of gene expression and metabolic network from relevant database(s) and previously existing stoichiometric models with automatic generation of kinetic equations of all reactions involved. To reduce computational complexity, compartmentalisation of the cell as well as enzyme inhibition is assumed to play a negligible role in metabolic function. Obtaining kinetic parameters needed to fully define and characterise kinetic models still remains a challenge in systems biology. Parameters are either not available in literature or unobtainable in the lab. Consequently, there have been numerous methods developed to predict biological behaviour that do not require the use of detailed kinetic parameters as well as techniques for estimation of parameter values based on experimental data. We present an algorithm for estimating kinetic parameters which uses fluxes and metabolites to constrain values. Our results show that our genetic algorithm is able to find parameters that fit a given data set and predict new biological states without having to re-estimate kinetic parameters.
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Lloyd, Joshua S. "Commercialization of Software for the Prediction of Structural and Optical Consequences Resulting from Corneal Corrective Treatments." Case Western Reserve University School of Graduate Studies / OhioLINK, 2016. http://rave.ohiolink.edu/etdc/view?acc_num=case1447778132.

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Hu, Yajie. "Thermal Barrier Coating Modeling for Stress Analysis." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42668.

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Thermal barrier coatings (TBCs) have been used widely in aerospace and land-based gas turbines. The TBC system consists of a top coat layer, a thermally grown oxide (TGO), a bond coat layer and a substrate. The growth kinetics of the TGO significantly affects the durability of TBCs. At a critical TGO thickness, the growth stresses exceed the ceramic-bond coat interface strength, resulting in TBC system failure. Regardless of the deposition method used, it is vitally important to accurately predict the TBC lifetime by investigating the determinants of the failure. The main objective of this study was to investigate the effect of oxidation stress induced by TGO layer in high temperature cycling environment through a series of reliable numerical simulations. Indeed, this oxidation stress is a known factor of interface degradation, and may result in failure of the ceramic-metal interface. A 2-D finite element model of the TBC was built via ANSYS APDL software, to conduct parametric studies of increasing complexity. The model accounted for elasticity first, before creep was integrated. Then, the model included swelling induced by phase transformation associated with oxidation, incorporating the effect of volumetric expansion of the newly grown TGO. This coupled oxidation constitutive approach was implemented for a typical air plasma spray deposited TBC coating. The interfacial radial stresses induced by the gradual oxidation were investigated. Different morphologies of the TBC interface were also considered to analyze the roughness effect on interface stresses. A complete model including swelling, creep, aging effects on the TBC layers at a given roughness was finally investigated.
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Beck, Johannes Christian. "Analysis of diurnal gene regulation and metabolic diversity in Synechocystis sp. PCC 6803 and other phototrophic cyanobacteria." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19240.

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Cyanobakterien sind meist photoautotroph lebende Prokaryoten, welche nahezu alle Biotope der Welt besiedeln. Sie gehören zu den wichtigsten Produzenten der weltweiten Nahrungskette. Um sich auf den täglichen Wechsel von Tag und Nacht einzustellen, besitzen Cyanobakterien eine innere Uhr, bestehend aus den Proteinen KaiA, KaiB und KaiC, deren biochemische Interaktionen zu einem 24-stündigen Rhythmus von Phosphorylierung und Dephosphorylierung führen. Die circadiane Genexpression im Modellorganismus Synechocystis sp. PCC 6803 habe ich mittels drei verschiedener Zeitserienexperimente untersucht, wobei ich einen genauen Zeitplan der Genaktivierung in einer Tag-Nacht-Umgebung, aber keine selbsterhaltenden Rhythmen entdecken konnte. Allerdings beobachtete ich einen überaus starken Anstieg der ribosomalen RNA in der Dunkelheit. Aufgrund ihrer hohen Wachstumsraten und der geringen Anforderungen an die Umwelt bilden Cyanobakterien eine gute Grundlage für die nachhaltige Erzeugung von Biokraftstoffen, für einen industriellen Einsatz sind aber weitere Optimierung und ein verbessertes Verständnis des Metabolismus von Nöten. Hierfür habe ich die Orthologie von verschiedenen Cyanobakterien sowie die Konservierung von Genen und Stoffwechselwegen untersucht. Mit einer neu entwickelten Methode konnte ich gemeinsam vorkommende Gene identifizieren und zeigen, dass diese Gene häufig an einem gemeinsamen biologischen Prozess beteiligt sind, und damit bisher unbekannte Beziehungen aufdecken. Zusätzlich zu den diskutierten Modulen habe ich den SimilarityViewer entwickelt, ein grafisches Computerprogramm für die Identifizierung von gemeinsam vorkommenden Partnern für jedes beliebige Gen. Des Weiteren habe ich für alle Organismen automatische Rekonstruktionen des Stoffwechsels erstellt und konnte zeigen, dass diese die Synthese von gewünschten Stoffen gut vorhersagen, was hilfreich für zukünftige Forschung am Metabolismus von Cyanobakterien sein wird.
Cyanobacteria are photoautotrophic prokaryotes populating virtually all habitats on the surface of the earth. They are one of the prime producers for the global food chain. To cope with the daily alternation of light and darkness, cyanobacteria harbor a circadian clock consisting of the three proteins KaiA, KaiB, and KaiC, whose biochemical interactions result in a phosphorylation cycle with a period of approximately 24 hours. I conducted three time-series experiments in the model organism Synechocystis sp. PCC 6803, which revealed a tight diurnal schedule of gene activation. However, I could not identify any self-sustained oscillations. On the contrary, I observed strong diurnal accumulation of ribosomal RNAs during dark periods, which challenges common assumptions on the amount of ribosomal RNAs. Due to their high growth rates and low demand on their environment, cyanobacteria emerged as a viable option for sustainable production of biofuels. For an industrialized production, however, optimization of growth and comprehensive knowledge of the cyanobacterial metabolism is inevitable. To address this issue, I analyzed the orthology of multiple cyanobacteria and studied the conservation of genes and metabolic pathways. Systematic analysis of genes shared by similar subsets of organisms indicates high rates of functional relationship in such co-occurring genes. I designed a novel approach to identify modules of co-occurring genes, which exhibit a high degree of functional coherence and reveal unknown functional relationships between genes. Complementing the precomputed modules, I developed the SimilarityViewer, a graphical toolbox that facilitates further analysis of co-occurrence with respect to specific cyanobacterial genes of interest. Simulations of automatically generated metabolic reconstructions revealed the biosynthetic capacities of individual cyanobacterial strains, which will assist future research addressing metabolic engineering of cyanobacteria.
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Qin, Dongyan. "Specificity and structural modeling of FHA domain of CHK2 and a general characterization of FHA domain of caenorhabditis elegans CHK2." The Ohio State University, 2003. http://rave.ohiolink.edu/etdc/view?acc_num=osu1061304007.

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Anwar, Aamir. "Low Frequency Finite Element Modeling of Passive Noise Attenuation in Ear Defenders." Thesis, Virginia Tech, 2005. http://hdl.handle.net/10919/31186.

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Noise levels in areas adjacent to high performance jets have increased monotonically in the past few years. When personnel are exposed to such high noise fields, the need for better hearing protection is inevitable. Adequate hearing protection may be achieved through the use of circumaural ear defenders, earplugs or both. This thesis focuses on identifying the dominant physical phenomena, responsible for the low frequency (0 â 300 Hz) acoustic response inside the earmuffs. A large volume earcup is used with the undercut seal for the study. The significance of this research is the use of finite element methods in the area of hearing protection design. The objectives of this research are to identify the dominant physical phenomena responsible for the loss of hearing protection in the lower frequency range, and develop FE models to analyze the effects of structural and acoustic modes on the acoustic pressure response inside the earcup. It is found that there are two phenomena, which are primarily responsible for the lower frequency acoustic response inside the earmuffs. These modes are recognized in this thesis as the piston mode and the Helmholtz mode. The piston mode occurs due to the dynamics of the earcup and seal at 150 Hz, which results in loss of hearing protection. The Helmholtz mode occurs due to the presence of leaks. The resonant frequency of the Helmholtz mode and the pressure response depends on the leak size.
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Schatt, Nathan A. "Finite Element Modeling of Ultrasonic Wire Bonding on Polyvinyl Acetate-Nanocomposite Substrates." Case Western Reserve University School of Graduate Studies / OhioLINK, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=case1396634471.

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Li, Jie. "High frequency power transformer modelling for frequency response analysis (FRA) diagnosis." Thesis, University of Manchester, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.538489.

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Transformer fault diagnosis through Frequency Response Analysis (FRA) has been receiving a great deal of attention in recent years. As a comparative technique, FRA has good capability and sensitivity in detecting mechanical faults that are difficult to identify by conventional condition assessment techniques. Power transformers are among the most expensive equipment owned by electric utilities, and it is not reasonable to produce deformation on actual transformers and carry out measurement sensitivity studies. On the other hand, simulation models, which can accurately reproduce transformer high frequency behaviours, are flexible tools for performing FRA deformation type sensitivity studies for deriving FRA interpretation rules. The main objective of this thesis is to develop appropriate simulation models for use in FRA diagnosis and to improve the interpretation of FRA responses through simulation studies. The transformer models developed at the University of Manchester (then UMIST) were by far the best representation of state-of-art modelling techniques; the inductance and the capacitance of the basic model unit were calculated using winding geometry and material properties, the frequency dependent conductive and dielectric losses were also included. In addition, mutual capacitive and inductive couplings between units were carefully considered to ensure the accuracy of the model. However, there is still some room for improvement on these models and during this PhD research, major contributions are made on as. follows: firstly take core effect into consideration to reproduce valid FRA characteristic representation in the low frequencies, secondly status of network terminal nodes are uniformed represented by externally connecting an impedance so that during FRA deformation sensitivity study, it is flexible to change the terminal condition, thirdly reconfigure the network node and unit relationship so that tap winding connection are precisely represented as the design, finally convert the single-phase model to a three-phase model and by developing a reduced matrix model, keep the simulation accuracy intact for a three-phase transformer up to 2 MHz, at the same time reduce computational time significantly. In detail, this PhD thesis describes the following three parts of my research: Firstly a transformer model incorporating a magnetic core based on the Principle of Duality is established to interpret low frequency characteristics of FRA responses (from 10Hz to up to 1 kHz). This model includes leakage inductances and capacitances of windings and can explain FRA low frequency differences caused by asymmetry of magnetic paths in three-limb and five-limb core transformers. Secondly, FRA characteristics were studied systematically using a component-system approach through building models for single windings, a one-phase winding set and finally the three-phase transformer. In this way the effects of winding structure, inductive and capacitive coupling among windings, among phases and terminal connection effect on FRA characteristics were studied. FinaUya complete three-phase transformer reduced matrix model is built, that can flexibly represent winding terminal connection and precisely describe tap positions. Using this modelling strategy, transmission power transformers at 2751132 kVand 275/33 kV voltage levels are simulated and numerous deformation sensitivity studies are performed, in order to gain better understanding on their FRA characteristics and to identify FRA features of different winding deformation types on these transformers. The research indicates that the overall approach used to develop these simulation models has helped in improving interpretation of FRA responses. The transformer modelling techniques being developed, with further refinement, can be a useful tool for FRA diagnosis and benefit the test engineers from the industry.
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Books on the topic "FBA modeling"

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International Workshop Ontology Based Modelling in Humanities (1st 2006 Universität Hamburg). First International Workshop Ontology Based Modelling in Humanities: 7-8 April 2006, University of Hamburg : FBI-HH-B-264/06. Edited by Hahn Walther von 1942- and Vertan Cristina. Hamburg: Universität Hamburg, Bibliothek des Departments Informatik, 2010.

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Rößler, Carina. Modelling Synthesis of Lattice Gas Cellular Automata and of Random Walk and Application to Gluing of Bulk Material. ARGESIM Vienna, 2021. http://dx.doi.org/10.11128/fbs.33.

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Seņkāns, Uģis. Development and Evaluation of Hybrid FBG Sensors and WDM-PON Fiber Optical Systems. RTU Press, 2021. http://dx.doi.org/10.7250/9789934227004.

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With the development of fiber optical data transmission technologies and infrastructure on a global scale, the use of fiber optical sensors to perform sensing functions is becoming increasingly important mainly due to their advantages, such as small size, light weight, multiplexing capabilities and others. Therefore, in order to ensure more efficient use of optical sensor technologies, it is necessary to research and search for new solutions for the integration and use of fiber optical sensors in existing and future fiber optical communication system architecture. The main goal of the Doctoral Thesis is to study and evaluate the interaction of FBG fiber optical sensor networks and WDM-PON metro-access transmission systems implemented in a single system with theoretical and experimental research. In order to evaluate their performance in a unified system, a detailed study of the interaction between the FBG optical sensor network and the fiber optic data transmission system has been performed by implementing mathematical modeling and experimental development of such systems.
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Fate and transport modeling of selected chlorinated organic compounds at Operable Unit 3, U.S. Naval Air Station, Jacksonville, Florida. Tallahassee, Fla: U.S. Dept. of the Interior, U.S. Geological Survey, 2000.

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Book chapters on the topic "FBA modeling"

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Sánchez, Carlos Eduardo García, and Rodrigo Gonzalo Torres Sáez. "Exploration of the Effect of Input Data on the Modeling of Cellular Objective in Flux Balance Analysis (FBA)." In Advances in Intelligent Systems and Computing, 57–62. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-01568-2_8.

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Zhang, Xinyuan. "Bioequivalence: Modeling and Simulation." In FDA Bioequivalence Standards, 395–417. New York, NY: Springer New York, 2014. http://dx.doi.org/10.1007/978-1-4939-1252-0_15.

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Capati, Alessandro. "Architectural Modeling in a Fab Lab." In Urban Design and Representation, 117–26. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51804-6_9.

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Costanza, Jole, Giovanni Carapezza, Claudio Angione, Pietro Liò, and Giuseppe Nicosia. "Multi-objective Optimisation, Sensitivity and Robustness Analysis in FBA Modelling." In Computational Methods in Systems Biology, 127–47. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33636-2_9.

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Piprani, Baba. "An FBM Grammar of Dimensional Modelling." In Lecture Notes in Computer Science, 122–29. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-55961-2_12.

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Ruiz-Ramos, M., and M. I. Mínguez. "Functional-Structural Modelling of Faba Bean." In Functional-Structural Plant Modelling in Crop Production, 187–97. Dordrecht: Springer Netherlands, 2007. http://dx.doi.org/10.1007/1-4020-6034-3_16.

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Mohapatra, Pradyumna, Sunita Panda, and Siba Prasada Panigrahi. "Equalizer Modeling Using FFA Trained Neural Networks." In Advances in Intelligent Systems and Computing, 569–77. Singapore: Springer Singapore, 2017. http://dx.doi.org/10.1007/978-981-10-5687-1_51.

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Bouzas, Paula R., and Nuria Ruiz-Fuentes. "Modeling and Forecasting Monotone Curves by FDA." In Contributions to Statistics, 55–61. Heidelberg: Physica-Verlag HD, 2011. http://dx.doi.org/10.1007/978-3-7908-2736-1_9.

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Powers, Maureen, and William P. Fisher. "Functional Binocular Vision: Toward a Person-Centered Metric." In Springer Series in Measurement Science and Technology, 151–64. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-07465-3_6.

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AbstractA research program investigating correctable issues in Functional Binocular Vision (FBV) related optometric variables to responses from a symptom survey and reading test results. The study was mounted with no explicit attention to measurement modeling. Data from this research program were retrospectively analyzed with the aims of evaluating the potential for learning from the existing observations, and for improving the study design in future iterations. Results suggest that the physical and psychological measurements of vision combine into a model of FBV that could be standardized and deployed for use in diagnosing significant numbers of untreated vision problems negatively impacting learning outcomes.
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Shin, Ki-Hoon, and Jin-Koo Lee. "A Method for FEA-Based Design of Heterogeneous Objects." In Geometric Modeling and Processing - GMP 2006, 663–69. Berlin, Heidelberg: Springer Berlin Heidelberg, 2006. http://dx.doi.org/10.1007/11802914_54.

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Conference papers on the topic "FBA modeling"

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Zeinabady, Danial, Christopher R. Clarkson, Samaneh Razzaghi, Sadjad Haqparast, Abdul-Latif L. Benson, and Mohammad Azad. "Fault Identification for the Purposes of Evaluating the Risk of Induced Seismicity: A Novel Application of the Flowback DFIT (DFIT-FBA)." In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/211100-ms.

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Abstract The existence of faults, pre-existing hydraulic fractures, and depleted areas can have negative impacts on the development of unconventional reservoirs using multi-fractured horizontal wells (MFHWs). For example, the triggering of fault slippage through hydraulic fracturing can create the environmental hazard known as induced seismicity (earthquakes caused by hydraulic fracturing). A premium has therefore been placed on the development of technologies that can be used to identify the locations of fault systems (particularly if they are subseismic), as well as pre-existing hydraulic fractures and depleted areas that can similarly negatively impact reservoir exploitation. The objective of this study is to develop a diagnostic tool to identify these conditions using DFIT-FBA. DFIT-FBA is a modified diagnostic fracture injection test (DFIT) whereby a sequence of injection and flowback steps are performed to estimate minimum in-situ stress, fracture surface area, reservoir pressure, and permeability in shale and tight reservoirs. The time- and cost-efficiency of the DFIT-FBA method provides an opportunity to conduct multiple field tests at a single point, or along the lateral section of a horizontal well, without significantly delaying the completion program. The proposed diagnostic tool uses an analytical model which considers critical processes and mechanisms occurring during a DFIT-FBA test, including wellbore storage, leakoff rate, and fracture stiffness development. The results of analytical modeling demonstrate that faults, pre-existing hydraulic fractures, and depleted areas of the reservoir can be identified either by implementing multiple cycles of the DFIT-FBA test at a single point, or by applying multiple DFIT-FBA tests at different points along the lateral section of a horizontal well or at different wells. The analytical model is first verified using a fully-coupled hydraulic fracture, reservoir, and wellbore simulator, and flowing pressure responses in the presence of different reservoir heterogeneities are then illustrated. Practical application of the proposed method is demonstrated using DFIT-FBA field examples performed in a tight reservoir. Analysis of the field examples results in the conclusion that a fault occurs near the toe of the horizontal lateral. This finding was confirmed by other field information and provides the opportunity to modify the main-stage hydraulic fracturing design to avoid induced seismicity events. This study proposes a novel, fast, and low-cost approach for identifying faults, pre-existing hydraulic fractures, and depleted areas using the DFIT-FBA test. The recommended approach can help engineers to characterize the reservoir quality along a horizontal well, as well as identify features/conditions that could negatively influence reservoir development, such as faults (and the possibility of creating induced seismicity), pre-existing hydraulic fractures, and reservoir depletion.
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Hanzalek, Zdenek, Pavel Hospodar, Martin Hromcik, Libor Waszniowski, and Jiri Doubrava. "Hardware in the Loop Simulation of FBW Components." In AIAA Modeling and Simulation Technologies Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2009. http://dx.doi.org/10.2514/6.2009-6131.

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Ozeki, S., K. Kimura, and T. Tomio. "Flight simulation using actual helicopter equipped with full-authority FBW system." In Modeling and Simulation Technologies Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2000. http://dx.doi.org/10.2514/6.2000-4579.

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Perhinschi, Mario, Steven Mullins, Phil Evans, and Marcello Napolitano. "Computational Environment for the Development of an FAA Compliant Flight Simulator." In AIAA Modeling and Simulation Technologies Conference. Reston, Virigina: American Institute of Aeronautics and Astronautics, 2010. http://dx.doi.org/10.2514/6.2010-7779.

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Marjani, Mehrsa, Moustafa El-Gindy, David Philipps, Fredrik Öijer, and Inge Johansson. "FEA Tire Modeling and Validation Techniques." In ASME 2015 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. American Society of Mechanical Engineers, 2015. http://dx.doi.org/10.1115/detc2015-46514.

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Recent advances in power and efficiency of computerized modeling methods has made it easier to develop accurate tire models. These newer models are now created with such accuracy that it has become easy to predict the experimental tire’s behavior and characteristics. These models are helpful with determining tire, tire-road, and tire-soil interaction properties. By creating virtual models, the overall capital for research and development can be reduced as well as replacing unavailable experimental tires for research. This research paper mainly focuses on the validation of computer generated FEA tire models which are then used for the prediction of the experimental tire’s rolling resistance, static and dynamic characteristics. Experimental data, such as rolling resistance and vertical acceleration are used in validation simulations in order to tune the virtual model to match the experimental tire’s behavior. The tire that was used for this research is a six-groove 445/50R22.5 FEA truck tire, which was constructed and validated over the course of this research.
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Shi, Chongyang, Zhendong Niu, Tao Wang, and Xiaomei Xu. "A Digital Assets Navigating System Based on FCA." In 2008 International Symposium on Knowledge Acquisition and Modeling (KAM). IEEE, 2008. http://dx.doi.org/10.1109/kam.2008.152.

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Derradji-Aouat, Ahmed, Melanie Sarzynski, and Roger Cordes. "Iceberg Ice Constitutive Modeling and FEA Validation." In OTC Arctic Technology Conference. Offshore Technology Conference, 2015. http://dx.doi.org/10.4043/25590-ms.

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Lin, Anthony C. Y., and Shuenn Chen. "Hydroformed Tube Modeling in Crash FEA Model." In SAE 2003 World Congress & Exhibition. 400 Commonwealth Drive, Warrendale, PA, United States: SAE International, 2003. http://dx.doi.org/10.4271/2003-01-0258.

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Sidhu, Navjot K., P. Abedini Sohi, S. Samadi, and M. Kahrizi. "Modeling of FBG Moisture Sensor in COMSOL." In 2018 Photonics North (PN). IEEE, 2018. http://dx.doi.org/10.1109/pn.2018.8438838.

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Stefanescu, A., D. Neculoiu, G. Konstantinidis, A. Cismaru, G. Deligeorgis, A. Stavrinidis, and A. Muller. "Sub-micron FBAR modeling including FEM simulations." In 2010 International Semiconductor Conference (CAS 2010). IEEE, 2010. http://dx.doi.org/10.1109/smicnd.2010.5650610.

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Reports on the topic "FBA modeling"

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Kimpland, Robert Herbert, and Jeffrey D. Goettee. WSMR FBR Modeling. Office of Scientific and Technical Information (OSTI), March 2017. http://dx.doi.org/10.2172/1346833.

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Rathke, P. M. FBI Fingerprint Image Capture System High-Speed-Front-End throughput modeling. Office of Scientific and Technical Information (OSTI), September 1993. http://dx.doi.org/10.2172/10186892.

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Faverjon, Céline, Angus Cameron, and Marco De Nardi. Modelling framework to quantify the risk of AMR exposure via food products - example of chicken and lettuce. Food Standards Agency, April 2022. http://dx.doi.org/10.46756/sci.fsa.qum110.

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Antimicrobial resistance (AMR) is a complex issue where microorganisms survive antimicrobial treatments, making such infections more difficult to treat. It is a global threat to public health. To increase the evidence base for AMR in the food chain, the FSA has funded several projects to collect data to monitor the trends, prevalence, emergence, spread and decline of AMR bacteria in a range of retail foods in the UK. However, this data and information from the wider literature was yet to be used to create tools to aid in the production of quantitative risk assessment to determine the risk to consumers of AMR in the food chain. To assist with this, there was a need to develop a set of modular templates of risk of AMR within foods. This sought to allow the efficient creation of reproducible risk assessments of AMR to maintain the FSA at the forefront of food safety.
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Brandt, Leslie A., Cait Rottler, Wendy S. Gordon, Stacey L. Clark, Lisa O'Donnell, April Rose, Annamarie Rutledge, and Emily King. Vulnerability of Austin’s urban forest and natural areas: A report from the Urban Forestry Climate Change Response Framework. U.S. Department of Agriculture, Northern Forests Climate Hub, October 2020. http://dx.doi.org/10.32747/2020.7204069.ch.

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The trees, developed green spaces, and natural areas within the City of Austin’s 400,882 acres will face direct and indirect impacts from a changing climate over the 21st century. This assessment evaluates the vulnerability of urban trees and natural and developed landscapes within the City Austin to a range of future climates. We synthesized and summarized information on the contemporary landscape, provided information on past climate trends, and illustrated a range of projected future climates. We used this information to inform models of habitat suitability for trees native to the area. Projected shifts in plant hardiness and heat zones were used to understand how less common native species, nonnative species, and cultivars may tolerate future conditions. We also assessed the adaptability of planted and naturally occurring trees to stressors that may not be accounted for in habitat suitability models such as drought, flooding, wind damage, and air pollution. The summary of the contemporary landscape identifies major stressors currently threatening trees and forests in Austin. Major current threats to the region’s urban forest include invasive species, pests and disease, and development. Austin has been warming at a rate of about 0.4°F per decade since measurements began in 1938 and temperature is expected to increase by 5 to 10°F by the end of this century compared to the most recent 30-year average. Both increases in heavy rain events and severe droughts are projected for the future, and the overall balance of precipitation and temperature may shift Austin’s climate to be more similar to the arid Southwest. Species distribution modeling of native trees suggests that suitable habitat may decrease for 14 primarily northern species, and increase for four more southern species. An analysis of tree species vulnerability that combines model projections, shifts in hardiness and heat zones, and adaptive capacity showed that only 3% of the trees estimated to be present in Austin based on the most recent Urban FIA estimate were considered to have low vulnerability in developed areas. Using a panel of local experts, we also assessed the vulnerability of developed and natural areas. All areas were rated as having moderate to moderate-high vulnerability, but the underlying factors driving that vulnerability differed by natural community and between East and West Austin. These projected changes in climate and their associated impacts and vulnerabilities will have important implications for urban forest management, including the planting and maintenance of street and park trees, management of natural areas, and long-term planning.
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