18 resultados para Statistical mixture-design optimization

em Universidade do Minho


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Lipid nanoballoons integrating multiple emulsions of the type water-in-oil-in-water enclose, at least in theory, a biomimetic aqueous-core suitable for housing hydrophilic biomolecules such as proteins, peptides and bacteriophage particles. The research effort entertained in this paper reports a full statistical 23x31 factorial design study (three variables at two levels and one variable at three levels) to optimize biomimetic aqueous-core lipid nanoballoons for housing hydrophilic protein entities. The concentrations of protein, lipophilic and hydrophilic emulsifiers, and homogenization speed were set as the four independent variables, whereas the mean particle hydrodynamic size (HS), zeta potential (ZP) and polydispersity index (PI) were set as the dependent variables. The V23x31 factorial design constructed led to optimization of the higher (+1) and lower (-1) levels, with triplicate testing for the central (0) level, thus producing thirty three experiments and leading to selection of the optimized processing parameters as 0.015% (w/w) protein entity, 0.75% (w/w) lipophilic emulsifier (soybean lecithin) and 0.50% (w/w) hydrophilic emulsifier (poloxamer 188). In the present research effort, statistical optimization and production of protein derivatives encompassing full stabilization of their three-dimensional structure, has been attempted via housing said molecular entities within biomimetic aqueous-core lipid nanoballoons integrating a multiple (W/O/W) emulsion.

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Firefly Algorithm is a recent swarm intelligence method, inspired by the social behavior of fireflies, based on their flashing and attraction characteristics [1, 2]. In this paper, we analyze the implementation of a dynamic penalty approach combined with the Firefly algorithm for solving constrained global optimization problems. In order to assess the applicability and performance of the proposed method, some benchmark problems from engineering design optimization are considered.

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Sandwich geometries, mainly in the form of panels and beams, are commonly applied in various transportation industries, such as aerospace, aeronautic and automotive. Sandwich geometries represent important advantages in structural applications, namely high specific stiffness, low weight, and possibility of design optimization prior to manufacturing. The aim of this paper is to uncover the influence of the number of reinforcements (ribs), and of the thickness on the mechanical behavior of all-metal sandwich panels subjected to uncoupled bending and torsion loadings. In this study, four geometries are compared. The orientation of the reinforcements and the effect of transversal ribs are also considered in this study. It is shown that the all the relations are non-linear, despite the elastic nature of the analysis in the Finite Element software ANSYS MECHANICAL APDL.

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Supplementary information available at: http://www.rsc.org/suppdata/c5/gc/c5gc02231b/c5gc02231b1.pdf

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In highway construction, earthworks refer to the tasks of excavation, transportation, spreading and compaction of geomaterial (e.g. soil, rockfill and soil-rockfill mixture). Whereas relying heavily on machinery and repetitive processes, these tasks are highly susceptible to optimization. In this context Artificial Intelligent techniques, such as Data Mining and modern optimization can be applied for earthworks. A survey of these applications shows that they focus on the optimization of specific objectives and/or construction phases being possible to identify the capabilities and limitations of the analyzed techniques. Thus, according to the pinpointed drawbacks of these techniques, this paper describes a novel intelligent earthwork optimization system, capable of integrating DM, modern optimization and GIS technologies in order to optimize the earthwork processes throughout all phases of design and construction work. This integration system allows significant savings in time, cost and gas emissions contributing for a more sustainable construction.

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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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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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PhD thesis in Bioengineering

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Shifting from chemical to biotechnological processes is one of the cornerstones of 21st century industry. The production of a great range of chemicals via biotechnological means is a key challenge on the way toward a bio-based economy. However, this shift is occurring at a pace slower than initially expected. The development of efficient cell factories that allow for competitive production yields is of paramount importance for this leap to happen. Constraint-based models of metabolism, together with in silico strain design algorithms, promise to reveal insights into the best genetic design strategies, a step further toward achieving that goal. In this work, a thorough analysis of the main in silico constraint-based strain design strategies and algorithms is presented, their application in real-world case studies is analyzed, and a path for the future is discussed.

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This paper addresses the challenging task of computing multiple roots of a system of nonlinear equations. A repulsion algorithm that invokes the Nelder-Mead (N-M) local search method and uses a penalty-type merit function based on the error function, known as 'erf', is presented. In the N-M algorithm context, different strategies are proposed to enhance the quality of the solutions and improve the overall efficiency. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm. The main goal of this paper is to use a two-level factorial design of experiments to analyze the statistical significance of the observed differences in selected performance criteria produced when testing different strategies in the N-M based repulsion algorithm.

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Dissertação de mestrado em Design e Marketing

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The sol-gel method was employed in the synthesis of di-urethane cross-linked poly( caprolactone) (PCL(530)/siloxane biohybrid ormolytes incorporating either a mixture of lithium triflate (LiCF3SO3) and the ionic liquid (IL) 1-ethyl-3-methyl imidazolium tetrafluoroborate ([Emim]BF4), or solely with [Emim]BF4 or LiCF3SO3. The ormolyte doped with [Emim]BF4 is thermally more stable and exhibits higher ionic conductivity (4 x 10-4 and 2 x 10-3 S cm-1 at 36 and 98 ºC, respectively) than those containing the LiCF3SO3/[Emim]BF4 mixture or just LiCF3SO3. The three ormolytes were employed in the production of glass/ITO/ormolyte/WO3/ITO/glass electrochromic devices (ECDs) designated as ECD@Y with Y = Li-[Emim]BF4, [Emim]BF4 and Li. The three ECDs displayed fast switching speed (ca. 30 s). ECD@Li-[Emim]BF4 exhibited an electrochromic contrast of 18.4 % and an optical density change of 0.11 in the visible region, the coloration efficiency attained at 555 nm was 159 and 80.2 cm-2 C-1 in the “on” and “off” states, respectively, and the open circuit memory was 48 hours. In the “on” state the CIE 1931 color space coordinates were x = 0.29 and y = 0.30, corresponding to blue color.

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Dissertação de mestrado integrado em Engenharia Mecânica

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Tese de Doutoramento em Engenharia de Materiais.