14 resultados para Optimization of oil production
em Universidade do Minho
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In this work, the optimization of an extrusion die designed for the production of a wood–plastic composite (WPC) decking profile is investigated. The optimization was performed with the help of numerical tools, more precisely, by solving the continuity and momentum conservation equations that govern such flow, and aiming to balance properly the flow distribution at the extrusion die flow channel outlet. To capture the rheological behavior of the material, we used a Bird-Carreau model with parameters obtained from a fit to the (shear viscosity versus shearrate) experimental data, collected from rheological tests. To yield a balanced output flow, several numerical runs were performed by adjusting the flow restriction at different regions of the flow-channel parallel zone crosssection. The simulations were compared with the experimental results and an excellent qualitative agreement was obtained, allowing, in this way, to attain a good balancing of the output flow and emphasizing the advantages of using numerical tools to aid the design of profile extrusion dies.
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Palm oil (PO) is a very important commodity for many countries and especially Indonesia and Malaysia who are the predominant producers. PO is used in ca. 30% of supermarket foods, cosmetics, cooking and as biodiesel. The growth of oil palms in plantations is controversial as the production methods contribute to climate change and cause environmental damage [1]. The plant is subjected to a devastating disease in these two countries caused by the white rot fungus Ganoderma. There are no satisfactory methods to diagnose the disease in the plant as they are too slow and/or inaccurate. The lipid compound ergosterol is unique to fungi and is used to measure growth especially in solid substrates. We report here on the use of ergosterol to measure the growth of Ganoderma in oil palms using HPLC and TLC methods [2]. The method is rapid and correlates well with other methods and is capable of being used on-site, hence improving the speed of analysis and allowing remedial action. Climate change will affect the health of OP [1] and rapid detection methods will be increasingly required to control the disease. [1] Paterson, RRM, Kumar, L, Taylor, S, Lima N. Future climate effects on suitability for growth of oil palms in Malaysia and Indonesia. Scientific Reports, 5, 2015, 14457. [2] Muniroh, MS, Sariah M, Zainal Abidin, MA, Lima, N, Paterson, RRM. Rapid detection of Ganoderma-infected oil palms by microwave ergosterol extraction with HPLC and TLC. Journal of Microbiological Methods, 100, 2014, 143–147.
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Tese de Doutoramento em Engenharia de Materiais.
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Kinetic models have a great potential for metabolic engineering applications. They can be used for testing which genetic and regulatory modifications can increase the production of metabolites of interest, while simultaneously monitoring other key functions of the host organism. This work presents a methodology for increasing productivity in biotechnological processes exploiting dynamic models. It uses multi-objective dynamic optimization to identify the combination of targets (enzymatic modifications) and the degree of up- or down-regulation that must be performed in order to optimize a set of pre-defined performance metrics subject to process constraints. The capabilities of the approach are demonstrated on a realistic and computationally challenging application: a large-scale metabolic model of Chinese Hamster Ovary cells (CHO), which are used for antibody production in a fed-batch process. The proposed methodology manages to provide a sustained and robust growth in CHO cells, increasing productivity while simultaneously increasing biomass production, product titer, and keeping the concentrations of lactate and ammonia at low values. The approach presented here can be used for optimizing metabolic models by finding the best combination of targets and their optimal level of up/down-regulation. Furthermore, it can accommodate additional trade-offs and constraints with great flexibility.
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[Excerpt] Bioethanol from lignocellulosic materials (LCM), also called second generation bioethanol, is considered a promising alternative to first generation bioethanol. An efficient production process of lignocellulosic bioethanol involves an effective pretreatment of LCM to improve the accessibility of cellulose and thus enhance the enzymatic saccharification. One interesting approach is to use the whole slurry from treatment, since allows economical and industrial benefits: washing steps are avoided, water consumption is lower and the sugars from liquid phase can be used, increasing ethanol concentration [1]. However, during the pretreatment step some compounds (such as furans, phenolic compounds and weak acids) are produced. These compounds have an inhibitory effect on the microorganisms used for hydrolysate fermentation [2]. To overcome this, the use of a robust industrial strain together with agro-industrial by-products as nutritional supplementation was proposed to increase the ethanol productivities and yields. (...)
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Earthworks tasks aim at levelling the ground surface at a target construction area and precede any kind of structural construction (e.g., road and railway construction). It is comprised of sequential tasks, such as excavation, transportation, spreading and compaction, and it is strongly based on heavy mechanical equipment and repetitive processes. Under this context, it is essential to optimize the usage of all available resources under two key criteria: the costs and duration of earthwork projects. In this paper, we present an integrated system that uses two artificial intelligence based techniques: data mining and evolutionary multi-objective optimization. The former is used to build data-driven models capable of providing realistic estimates of resource productivity, while the latter is used to optimize resource allocation considering the two main earthwork objectives (duration and cost). Experiments held using real-world data, from a construction site, have shown that the proposed system is competitive when compared with current manual earthwork design.
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This Letter reports evidence of triple gauge boson production pp→W(ℓν)γγ+X, which is accessible for the first time with the 8 TeV LHC data set. The fiducial cross section for this process is measured in a data sample corresponding to an integrated luminosity of 20.3 fb−1, collected by the ATLAS detector in 2012. Events are selected using the W boson decay to eν or μν as well as requiring two isolated photons. The measured cross section is used to set limits on anomalous quartic gauge couplings in the high diphoton mass region.
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This Letter reports a measurement of the exclusive γγ→ℓ+ℓ−(ℓ=e,μ) cross-section in proton--proton collisions at a centre-of-mass energy of 7 TeV by the ATLAS experiment at the LHC, based on an integrated luminosity of 4.6 fb−1. For the electron or muon pairs satisfying exclusive selection criteria, a fit to the dilepton acoplanarity distribution is used to extract the fiducial cross-sections. The cross-section in the electron channel is determined to be σexcl.γγ→e+e−=0.428±0.035(stat.)±0.018(syst.) pb for a phase-space region with invariant mass of the electron pairs greater than 24 GeV, in which both electrons have transverse momentum pT>12 GeV and pseudorapidity |η|<2.4. For muon pairs with invariant mass greater than 20 GeV, muon transverse momentum pT>10 GeV and pseudorapidity |η|<2.4, the cross-section is determined to be σexcl.γγ→μ+μ−=0.628±0.032(stat.)±0.021(syst.) pb. When proton absorptive effects due to the finite size of the proton are taken into account in the theory calculation, the measured cross-sections are found to be consistent with the theory prediction.
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A measurement of W boson production in lead-lead collisions at sNN−−−√=2.76 TeV is presented. It is based on the analysis of data collected with the ATLAS detector at the LHC in 2011 corresponding to an integrated luminosity of 0.14 nb−1 and 0.15 nb−1 in the muon and electron decay channels, respectively. The differential production cross-sections and lepton charge asymmetry are each measured as a function of the average number of participating nucleons ⟨Npart⟩ and absolute pseudorapidity of the charged lepton. The results are compared to predictions based on next-to-leading-order QCD calculations. These measurements are, in principle, sensitive to possible nuclear modifications to the parton distribution functions and also provide information on scaling of W boson production in multi-nucleon systems.
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The production of a Z boson in association with a J/ψ meson in proton--proton collisions probes the production mechanisms of quarkonium and heavy flavour in association with vector bosons, and allows studies of multiple parton scattering. Using 20.3fb−1 of data collected with the ATLAS experiment at the LHC, in pp collisions at s√=8 TeV, the first measurement of associated Z+J/ψ production is presented for both prompt and non-prompt J/ψ production, with both signatures having a significance in excess of 5σ. The inclusive production cross-sections for Z boson production (in μ+μ− or e+e− decay modes) in association with prompt and non-prompt J/ψ(→μ+μ−) are measured relative to the inclusive production rate of Z bosons in the same fiducial volume to be (88±16±6)×10−8 and (157±22±10)×10−8 respectively. Normalised differential production cross-sections are also determined as a function of the J/ψ transverse momentum. The fraction of signal events arising from single and double parton scattering is estimated, and a lower limit of 5.3 (3.7)mb at 68 (95) confidence level is placed on the effective cross-section regulating double parton interactions.
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Rational manipulation of mRNA folding free energy allows rheostat control of pneumolysin production by Streptococcus pneumoniae
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This Letter presents measurements of correlated production of nearby jets in Pb+Pb collisions at sNN−−−√=2.76 TeV using the ATLAS detector at the Large Hadron Collider. The measurement was performed using 0.14 nb−1 of data recorded in 2011. The production of correlated jet pairs was quantified using the rate, RΔR, of ``neighbouring'' jets that accompany ``test'' jets within a given range of angular distance, ΔR, in the pseudorapidity--azimuthal angle plane. The jets were measured in the ATLAS calorimeter and were reconstructed using the anti-kt algorithm with radius parameters d=0.2, 0.3, and 0.4. RΔR was measured in different Pb+Pb collision centrality bins, characterized by the total transverse energy measured in the forward calorimeters. A centrality dependence of RΔR is observed for all three jet radii with RΔR found to be lower in central collisions than in peripheral collisions. The ratios formed by the RΔR values in different centrality bins and the values in the 40--80 % centrality bin are presented.
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Dissertação de mestrado integrado em Engenharia Mecânica
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Fluorescence in situ hybridization (FISH) is a molecular technique widely used for the detection and characterization of microbial populations. FISH is affected by a wide variety of abiotic and biotic variables and the way they interact with each other. This is translated into a wide variability of FISH procedures found in the literature. The aim of this work is to systematically study the effects of pH, dextran sulfate and probe concentration in the FISH protocol, using a general peptide nucleic acid (PNA) probe for the Eubacteria domain. For this, response surface methodology was used to optimize these 3 PNA-FISH parameters for Gram-negative (Escherichia coli and Pseudomonas fluorescens) and Gram-positive species (Listeria innocua, Staphylococcus epidermidis and Bacillus cereus). The obtained results show that a probe concentration higher than 300 nM is favorable for both groups. Interestingly, a clear distinction between the two groups regarding the optimal pH and dextran sulfate concentration was found: a high pH (approx. 10), combined with lower dextran sulfate concentration (approx. 2% [w/v]) for Gram-negative species and near-neutral pH (approx. 8), together with higher dextran sulfate concentrations (approx. 10% [w/v]) for Gram-positive species. This behavior seems to result from an interplay between pH and dextran sulfate and their ability to influence probe concentration and diffusion towards the rRNA target. This study shows that, for an optimum hybridization protocol, dextran sulfate and pH should be adjusted according to the target bacteria.