Search

Dada a crescente demanda por água no mundo, são necessárias abordagens e/ou ações para reduzir o consumo e aumentar a demanda, o reuso de água é uma alternativa viável para aumentar a demanda de água não-potável em residências. O objetivo deste trabalho é otimizar o tratamento da água cinza, proveniente da máquina de lavar roupas, por meio da associação das soluções de sulfato de alumínio e de semente Moringa oleifera. Para tal foi realizado um experimento com a água cinza da máquina de lavar de uma residência, dividido em 4 estudos. Foi realizado o Estudo 1 de caracterização dos flocos formados para cada solução estudada, que são a Moringa oleifera extraída em nitrato de cálcio, nitrato de cálcio aquoso e sulfato de alumínio. O Estudo 2 consistiu no experimento do jar-test realizado para cada coagulante separadamente. Posteriormente foi realizado o Estudo 3, com ensaios do jar- test para a associação entre o sulfato de alumínio e a Moringa oleifera, com as combinações feitas por meio do Delineamento Composto Central Rotacional como planejamento experimental. Os dados desse ensaio foram avaliados por meio da Metodologia de Superfícies de Resposta. Por fim, no Estudo 4 foi feita a análise da desejabilidade, visando determinar a dosagem ótima para cada coagulante. Os parâmetros avaliados no experimento foram o pH, a turbidez, o volume de lodo gerado e os sólidos dissolvidos totais. Os resultados deste estudo indicam que com o tratamento que utiliza as menores dosagens de coagulante, sendo 20 ml L -1 de Moringa oleifera extraída em nitrato de cálcio e 1 ml L -1 de sulfato de alumínio, é viável o reuso da água cinza, após o tratamento, em descargas de bacias sanitárias. É possível ainda o reuso da água em atividades como lavagem de carros e outros usos que requerem contato direto com a água, desde que sejam adicionadas as etapas de filtração, para a redução no teor de sólidos dissolvidos totais, e de cloração. Para essas dosagens de coagulantes, a remoção de turbidez foi de 96,22%, o pH variou de 7,2 para 6,8, o teor de sólidos dissolvidos totais foi elevado de 360 mg L -1 para 589 mg L -1 , o teor de cloro foi reduzido de 0,54 mg L -1 para 0,10 mg L -1 e o volume de lodo produzido foi de 48,7 cm3. A associação do sulfato de alumínio com a Moringa oleifera extraída em nitrato de cálcio é viável para o tratamento por coagulação da água cinza da máquina de lavar, de forma a reduzir as dosagens de cada coagulante e atender aos critérios das normas. Given the growing demand for water in the world, approaches and/or actions are needed in order to reduce the consume and increase the demand, the water reuse is a viable alternative to increase the non-potable water demand in residences. The objective of this job is optimize the greywater treatment, from the washing machine, through the association of aluminium sulphate and Moringa oleifera seeds solutions. For this it was performed an experiment with the greywater from washing machine of a residence, dividing in 4 studies. It was realized the Study 1 of characterization of the flakes formed for each studied solution, which are Moringa oleifera extracted in aqueous calcium nitrate, aqueous calcium nitrate and aluminium sulphate. The Study 2 consisted in the jar-test experiment for each coagulant separately. Study 3 was later performed, which jar-test experiments for the association between aluminum sulphate and Moringa oleifera, with the combinations made through Central Composite Rotational Design as experimental planning. The data of this test was evaluated by the Response Surface Methodology. Lastly, in the Study 4 was made the desirability analysis, aiming to determine the optimal dosage for each coagulant. The parameters evaluated in the experiment was the pH, turbidity, sludge volume generated and total dissolved solids. The results of this study indicate that with the treatment that use the lower dosages of coagulant, being 20 ml L -1 of Moringa oleifera extracted in calcium nitrate and 1 ml L -1 of aluminium sulphate, is viable the greywater reuse, after the treatment, in toilet flush. It's still possible the water reuse in activities like car wash and other uses that require direct contact with the water, as long as added the steps of filtration, to reduce the total dissolved solids, and chlorination. For this coagulants dosages, the turbidity removal was 96,22%, the pH varied of 7,2 to 6,8, the total dissolved solids content was elevated of 360 mg L -1 to 589 mg L -1 , the chlorine content was reduced of 0,54 mg L -1 to 0,10 mg L -1 and the sludge volume generated was 48,7 cm3. The association of aluminum sulphate with Moringa oleifera extracted in aqueous calcium nitrate it is viable for coagulation treatment of greywater from washing machine, in order to reduce the dosages of each coagulant and attend standards criteria.

RESUMEN La metodología de superficies de respuesta, introducida originalmente por Box y Hunter en 1951, ha permitido el desarrollo de varios diseños, como el Diseño San Cristóbal desarrollado por Rojas en 1962, para investigación con fertilizantes (Chacín, 1998). Con la finalidad de determinar la influencia de la aplicación de niveles (0 a 360 kg ha-1) de N y P2O5 en el rendimiento de tomate y la similitud de los modelos de superficie, estimados mediante diseños de superficie de respuesta, se realizó la presente investigación en ambientes de la Universidad Nacional de San Cristóbal de Huamanga (UNSCH), en Ayacucho, Perú. Se cultivó tomate en ambiente protegido, empleando cuatro diseños de superficie (Diseño Compuesto Central Rotable: DCCR, Diseño San Cristóbal: DSC, Diseño 03 de Julio: D3J y Factorial Completo: DFC). Los resultados demuestran que los rendimientos de frutos de tomate obedecen a los modelos: Y = 12292 + 104.77794*N + 87.27649*P2O5 - 0.12524*N² - 0.13156*P2O5² - 0.05242*N*P2O5 (DCCR); Y = 13121 + 102.98407*N + 51.88371*P2O5 - 0.14659*N² - 0.02645*P2O5² + 0.00512*N*P2O5 (D3J); Y = 13255 + 120.28556*N + 97.79306*P2O5 - 0.24539*N² - 0.16289*P2O5² + 0.07365*N*P2O5 (DSC); Y = 11401 + 103.54156*N + 83.1667*P2O5 - 0.17911*N² - 0.14172*P2O5² + 0.0747*N*P2O5 (DFC). Se concluye que: 1. El N (urea) tiene mayor influencia que el P2O5 (superfosfato triple), en el rendimiento de frutos de tomate; 2. Existe mayor similitud entre los valores estimados correspondientes a los diseños DCCR y D3J, con los del DFC, manifestándose mejor a niveles medios de N y P2O5 (180 kg ha-1). ABSTRACT The methodology of response surfaces, originally introduced by Box and Hunter in 1951, has allowed the development of several designs, such as the San Cristóbal Design developed by Rojas in 1962, for research with fertilizers (Chacín, 1998). In order to determine the influence of the application of levels (0 to 360 kg ha-1) of N and P2O5 on the tomato yield and the similarity of the surface models, estimated by response surface designs, the present research in environments of the National University of San Cristóbal de Huamanga (UNSCH), in Ayacucho, Peru. Tomato was cultivated in a protected environment, using four surface designs (Central Composite Design Rotable: DCCR, Design San Cristóbal: DSC, Design July 3: D3J and Complete Factorial: DFC). The results show that the yields of tomato fruits obey the models: Y = 12292 + 104.77794*N + 87.27649*P2O5 - 0.12524*N² - 0.13156*P2O5² - 0.05242*N*P2O5 (DCCR); Y = 13121 + 102.98407*N + 51.88371*P2O5 - 0.14659*N² - 0.02645*P2O5² + 0.00512*N*P2O5 (D3J); Y = 13255 + 120.28556*N + 97.79306*P2O5 - 0.24539*N² - 0.16289*P2O5² + 0.07365*N*P2O5 (DSC); Y = 11401 + 103.54156*N + 83.1667*P2O5 - 0.17911*N² - 0.14172*P2O5² + 0.0747*N*P2O5 (DFC). It is concluded that: 1. N (urea) has a greater influence than P2O5 (triple superphosphate) on the yield of tomato fruits; 2. There is greater similarity between the estimated values corresponding to the DCCR and D3J designs, with those of the DFC, showing better results at average levels of N and P2O5 (180 kg ha-1).

A parameterized dynamics analysis model of legged lander with adaptive landing gear was established. Based on the analysis model, the landing performances under various landing conditions were analyzed by the optimized Latin hypercube experimental design method. In order to improve the landing performances, a hierarchical optimization method was proposed considering the uncertainty of landing conditions. The optimization problem was divided into a higher level (hereafter the “leader”) and several lower levels (hereafter the “follower”). The followers took conditioning factors as design variables to find out the worst landing conditions, while the leader took buffer parameters as design variables to better the landing performance under worst conditions. First of all, sensitivity analysis of landing conditioning factors was carried out according to the results of experimental design. After the sensitive factors were screened out, the response surface models were established to reflect the complicated relationships between sensitive conditioning factors, buffer parameters and landing performance indexes. Finally, the response surface model was used for hierarchical optimization iteration to improve the computational efficiency. After selecting the optimum buffer parameters from the solution set, the dynamic model with the optimum parameters was simulated again under the same landing conditions as the simulation before. After optimization, nozzle performance against damage is improved by 5.24%, the acceleration overload is reduced by 5.74%, and the primary strut improves its performance by 21.10%.

Workload control is a production planning and control system designed to overcome the trade-off between high throughput and short and stable lead time. Specifically, work-in-process is continuously...

A factorial study was conducted on basic oxygen furnace slag from a steelmaking industry with the aim of systematically identifying the individual and joint effects of the operating parameters (total pressure, CO2 concentration in the gas phase and temperature) on the CO2 sequestration yield of a direct aqueous carbonation process. Each operating parameter was varied over a range of three levels according to a 3(3) factorial design, resulting in 27 carbonation experiments. The carbonation performance and the changes in particle size and mineralogical characteristics of the slag were investigated in detail. The analysis of the experimental results indicated large effects of the operating factors on CO2 uptake, which was observed to span the range 6.7-53.6 g CO2/100 g slag. The best carbonation performance achieved was particularly significant compared to previous studies, even more considering the relative mild operating conditions adopted (P = 5 bar, C = 40% vol. CO2, T = 50 °C, t = 4 h). The analysis of the solid and liquid phases at the end of the carbonation treatment evidenced significant changes in the physical, chemical and mineralogical composition of the material. In particular, evidence was gained of other elements (Mg, Fe, Mn, Zn) in addition to Ca being intensively involved in the carbonation reactions, with a variety of carbonate phases being produced in addition to calcium carbonate forms.

Many engineering problems require the optimization of expensive, black-box functions involving multiple conflicting criteria, such that commonly used methods like multiobjective genetic algorithms are inadequate. To tackle this problem several algorithms have been developed using surrogates. However, these often have disadvantages such as the requirement of a priori knowledge of the output functions or exponentially scaling computational cost with respect to the number of objectives. In this paper a new algorithm is proposed, TSEMO, which uses Gaussian processes as surrogates. The Gaussian processes are sampled using spectral sampling techniques to make use of Thompson sampling in conjunction with the hypervolume quality indicator and NSGA-II to choose a new evaluation point at each iteration. The reference point required for the hypervolume calculation is estimated within TSEMO. Further, a simple extension was proposed to carry out batch-sequential design. TSEMO was compared to ParEGO, an expected hypervolume implementation, and NSGA-II on nine test problems with a budget of 150 function evaluations. Overall, TSEMO shows promising performance, while giving a simple algorithm without the requirement of a priori knowledge, reduced hypervolume calculations to approach linear scaling with respect to the number of objectives, the capacity to handle noise and lastly the ability for batch-sequential usage. This is a post-peer-review, pre-copyedit version of an article published in [Journal of Global Optimization ] Locked until 16.2.2019 due to copyright restrictions. The final authenticated version is available online at: https://doi.org/10.1007/s10898-018-0609-2

Orientador: Flávio Luís Schmidt Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia de Alimentos Resumo: O suco de maçã é consumido clarificado, sendo comum o uso de tratamento enzimático e de gelatina no processo de clarificação. O objetivo deste trabalho foi verificar o potencial clarificante do extrato da semente de Moringa oleifera Lamark em suco de maçã. As sementes foram beneficiadas e liofilizadas para maior conservação e extratos salinos e aquosos foram elaborados e utilizados como agentes clarificantes em ensaios preliminares. Além disso, realizou-se um DCCR, tendo como variáveis independentes, concentração de enzima e de extrato de moringa, e como respostas a transmitância, pH, acidez total titulável, sólidos solúveis totais, ratio e parâmetros de cor de suco. Um delineamento também foi realizado para as variáveis concentração de enzima e de gelatina, tradicionalmente utilizado nas indústrias. Verificou-se também o teor de polifenóis, velocidade de sedimentação dos flocos, lodo formado, o fluxo permeado e fouling do suco de maçã em filtração convencional. A partir dos resultados realizou-se estudo sensorial do suco, aceitação sensorial, diferença do controle, ordenação e análise dos comentário com o objetivo de verificar a aceitação, bem como a percepção dos consumidores para limpidez das amostras. Utilizou-se amostras comerciais nos testes sensoriais para efeito comparativo. O extrato de moringa mais eficaz foi o EXT. 0,1M, que promoveu maior transmitância. Quando o EXT. 0,1M foi aplicado após o tratamento enzimático, também promoveu melhoria da transmitância. Os resultados do DCCR mostraram que o extrato de moringa foi eficaz, promoveu melhoria significativa no suco, alcançando transmitância de até 79%, sem necessidade de tratamento enzimático prévio. Além disso, reduziu a coloração avermelhada e não alterou os demais parâmetros de qualidade. Resultados semelhantes foram obtidos para os testes com gelatina, excessão aos parâmetros transmitância e cor. O extrato de moringa reduziução o teor de compostos fenólicos, redução semelhante foi obtida com despectinização+gelatina. A velocidade de sedimentação foi semelhante entre a clarificação com extrato e a tradicional. A % de lodo formado pela clarificação com extrato de moringa foi a mesma que no processo convencional, porém mais compacto. O fluxo permeado e o fouling foram os mesmos para as três amostras, confirmando o potencial do extrato como agente clarificante. Em relação ao estudo sensorial, o extrato de moringa utilizado como agente clarificante foi importante para aceitação do produto e promoveu transmitância semelhante ás amostras clarificadas por métodos convencionais sem nenhuma referência a sabor estranho. De forma geral, os atributos positivos mais citados pelos consumidores para descrever as amostras foram a cor, a cristalinidade, a doçura, presença de partículas, a cor esverdeada, a turbidez e o sabor. Os atributos negativos apontados pelos consumidores, podem ser corrigidos durante o processo. Em relação ao limiar de percepção para limpidez, o consumidor percebeu diferenças entre as amostras, quando a diferença de transmitâncias foi alta. Dessa forma, o consumidor seria capaz de comparar diferentes marcas de suco de maçã e, dependendo da diferença de transmitância entre elas, escolher qual a mais límpida. Diante disso, concluímos que o extrato de moringa pode ser uma alternativa para clarificar suco de maçã e ao mesmo tempo atender à tendências de mercado Abstract: The apple juice is consumed clarified, being common the use of enzymatic treatment and gelatine in the process of clarification. The aim of this work was to verify the clarifying potential of the Moringa oleifera Lamark seeds extract in apple juice. The seeds were beneficiated and lyophilized for further conservation and saline and aqueous extracts were elaborated and used as clarifying agents in preliminary tests. In addition, a DCCR was performed, having as independent variables, concentration of enzyme and moringa extract, and as responses, transmittance, pH, total titratable acidity, total soluble solids, ratio and juice color parameters. A DCCR was also performed for the variables enzyme concentration and gelatin, traditionally used in industries. The content of polyphenols, sedimentation velocity of flakes, slurry formed, permeate flow and fouling of apple juice were also checked in conventional filtration. From the results, a sensory study of the juice, sensory acceptance, control difference, ordering and analysis of the comments were carried out with the purpose of verifying the acceptance, as well as the perception of the consumers for the clarity of the samples. Commercial samples were used in the sensory tests for comparative effect. The most effective moringa extract was the EXT. 0,1M, which promoted greater transmittance. When the extract 0,1M was applied after the enzymatic treatment, also promoted improved transmittance. The results of the DCCR showed that the moringa extract was effective, promoted a significant improvement in the juice, achieving transmittance of up to 79%, without previous enzymatic treatment. In addition, it reduced the reddish color and did not change the other parameters of quality. Similar results were obtained for the gelatin tests, except for transmittance and color parameters. The moringa extract reduced the content of phenolic compounds, similar reduction was obtained with depectinization + gelatin. Sedimentation velocity was similar between extract and traditional clarification. The sludge formed by clarification with moringa extract was the same as in the conventional process, but more compact. The permeate flow and fouling were the same for the samples, confirming the potential of the extract as a clarifying agent. Regarding the sensory study, the moringa extract used as clarifying agent was important for product acceptance and promoted similar transmittance to clarified samples by conventional methods with no reference to strange taste. In general, the positive attributes most frequently cited by consumers to describe the samples were color, crystallinity, sweetness, presence of particles, greenish color, turbidity and taste. Negative attributes pointed out by consumers can be corrected during the process. Regarding the perception threshold for clarity, the consumer perceived differences between the samples, when the differences in transmittance were high. In this way, the consumer would be able to compare different brands of apple juice and, depending on the difference of transmittance between them, choose which one is the most limpid. In light of this, we conclude that moringa extract may be an alternative to clarify apple juice and at the same time meet market trends Doutorado Tecnologia de Alimentos Doutora em Tecnologia de Alimentos CAPES

A multi-dimensional random number generation algorithm was used to distribute chemical concentrations of each of the alloying elements in the candidate alloys as uniformly as possible while maintaining the prescribed bounds on the minimum and maximum allowable values for the concentration of each of the alloying elements. The generated candidate alloy compositions were then examined for phase equilibria and associated magnetic properties using a thermodynamic database in the desired temperature range. These initial candidate alloys were manufactured, synthesized and tested for desired properties. Then, the experimentally obtained values of the properties were fitted with a multi-dimensional response surface. The desired properties were treated as objectives and were extremized simultaneously by utilizing a multi-objective optimization algorithm that optimized the concentrations of each of the alloying elements. This task was also performed by another conceptually different response surface and optimization algorithm for double-checking the results. A few of the best predicted Pareto optimal alloy compositions were then manufactured, synthesized and tested to evaluate their macroscopic properties. Several of these Pareto optimized alloys outperformed most of the candidate alloys on most of the objectives. This proves the efficacy of the combined meta-modeling and experimental approach in design optimization of the alloys. A sensitivity analysis of each of the alloying elements was also performed to determine which of the alloying elements contributes the least to the desired macroscopic properties of the alloy. These elements can then be replaced with other candidate alloying elements such as not-so-rare earth elements.

Orientador: Alberto Luiz Serpa Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Engenharia Mecânica Resumo: O presente trabalho representa a compilação dos resultados anteriores dessa pesquisa no campo de metamodelos combinados e otimização eficiente global (EGO), os quais foram sumetidos para publicação em periódicos especializados. Recentemente foi implementado nesse trabalho de doutorado o algoritmo LSEGO que é uma abordagem para conduzir algoritmos tipo EGO, baseando-se em metamodelos combinados através da aproximação por mínimos quadrados (metamodelos combinados LS). Através dos metamodelos combinados LS é possível estimar a incerteza da aproximação usando qualquer tipo de metamodelagem (e não somente do tipo kriging), permitindo estimar a função de expectativa de melhora para a função objetivo. Nos experimentos computacionais anteriores em problemas de otimização sem restrições, a abordagem LSEGO mostrou-se como uma alternativa viável para conduzir otimização eficiente global usando metamodelos combinados, sem se restringir a somente um ponto adicional por ciclo de otimização iterativa. Na presente tese o algoritmo LSEGO foi extendido de modo a tratar também problemas de otimização com restrições. Os resultados de testes numéricos com problemas analíticos e de referência e também em um estudo de caso de engenharia em escala industrial mostraram-se bastante promissores e competitivos em relação aos trabalhos similares encontrados na literatura Abstract: In this work we review and compile the results of our previous research in the fields of ensemble of metamodels and efficient global optimization (EGO). Recently we implemented LSEGO that is an approach to drive EGO algorithms, based on LS (least squares) ensemble of metamodels. By means of LS ensemble of metamodels, it is possible to estimate the uncertainty of the prediction by using any kind of model (not only kriging) and provide an estimate for the expected improvement function. In previous numerical experiments with unconstrained optimization problems, LSEGO approach has shown to be a feasible alternative to drive efficient global optimization by using multiple or ensemble of metamodels, not restricted to kriging approximation or single infill point per optimization cycles. In the present work we extended the previous LSEGO algorithm to handle constrained optimization problems as well. Some numerical experiments were performed with analytical benchmark functions and also for industry scale engineering problems with competitive results Doutorado Mecânica dos Sólidos e Projeto Mecânico Doutor em Engenharia Mecânica

Changing temperature regimes and precipitation patterns in the Subarctic will impact on vegetation composition and diversity including those of bryophyte and lichen communities, which are major drivers of high-latitude carbon and nutrient cycling and hydrology. 2. We investigated the relative importance of such impacts at different temporal, spatial and plant functional scales in subarctic Sphagnum fuscum-dominated peatlands, comprising both an in situ warming experiment and natural climatic and topographic gradients in northern Sweden and Norway. We applied multivariate analyses to investigate the relationships among cryptogam and vascular plant species composition and abiotic (temperature, moisture) and biotic (Sphagnum growth) regimes at various scales. 3. At the short-term temporal scale (4-year warming experiment), increased temperature yielded no clear effect on cryptogam or vascular plant species composition. Spatially, direct effects of temperature were decisive for overall species composition across regions (macro-scale) rather than within one region (meso-scale). Moisture and Sphagnum growth were drivers of species composition at all spatial scales, and Sphagnum growth itself depended on its position on the microtopographic gradient and on temperature. 4. Grouping of bryophytes and lichens at increasing scales of functional aggregation from species, growth form to the major higher taxon level (Sphagnum, other mosses, liverworts, lichens) revealed mostly increasing correlation with climate regimes and Sphagnum growth. Excluding liverworts from the analysis tended to reduce the correlation. 5. Abundances of lichens, liverworts, non-Sphagnum mosses and (to a lesser degree) vascular plants were negatively related to Sphagnum abundance. Few cryptogam and vascular plant species showed a positive relationship with Sphagnum abundance. Correspondingly, cryptogam species richness and Shannon Index on peatlands strongly declined as Sphagnum abundance increased, while indices for vascular plants showed no significant relationship. 6. Synthesis. Scale, be it spatial or functional, strongly determined which environmental drivers showed the clearest relationships with vegetation composition and diversity. Our findings will help to optimize predictions about long-term effects of climate on peatland vegetation composition, and subsequently its feedbacks to carbon and water cycles, at the regional scale. © 2009 British Ecological Society.

En este artículo se propone una metodología de modelamiento conjunto de tratamientos con niveles cuantitativos medidos en el tiempo, a través de la combinación de las metodologías de superficie de respuesta y curvas de crecimiento. Se realiza la estimación de los parámetros del modelo propuesto, los cuales miden el efecto de los factores asociados al modelo de superficie de respuesta de segundo orden a lo largo del tiempo. Se plantea y juzga las diferentes hipótesis de interés y, finalmente, con el modelo ajustado se encuentran las condiciones de optimización de un conjunto de tratamientos a través del tiempo. Por último, se presenta una aplicación, analizada mediante curvas de crecimiento por Kshirsagar and amp; Boyce (1995). A methodology is suggested to jointly model treatments with quantitative levels measured in time, by combining the response surface and the growth curve techniques. The model’s parameters are estimated; these measure the effect through time of the factors related to the second order response surface model. The hypothesis of interest are formulated and tested. Additionally, by means of the fitted model, the optimality conditions throughout time are established for a set of specific treatments. As a final step, an application previously analyzed with growth curves by Kshirsagar and amp; Boyce (1995) is now assessed with the proposed model.

Response surface methodology was employed to evaluate the effects of two technological co-adjuvants in virgin olive oil extraction from the Hojiblanca olive variety with a low ripening index: the addition of talc during the malaxation of the olive paste step, water addition during the same step and olive paste storage over a small period of time. Ranges of operation were established as follows: talc addition, 0-2 % (w/w); water addition, 0-20 % (w/w); and storage time, 0-36 h. Mathematical models and statistical analyses (ANOVA) were performed in order to evaluate the effects of theses factors on oil yield and quality of olive oils obtained. Using a confidence level of 95 %, oil yield, acidity, peroxide index, K270 and Chlorophyll contents, models are significant. The addition of talc is more effective in improving oil yield and paste storage is also useful to improve oil yield although a loss of oil quality is observed; but all the olive oil obtained may be characterized as extra virgin olive oil according to the regulations of the European Union.Se ha utilizado la metodología de superficies de respuesta para evaluar los efectos de dos coadyuvantes tecnológicos y otro factor en la extracción de aceite de oliva virgen procedente de aceitunas de la variedad Hojiblanca con bajo índice de madurez: adición de talco en la etapa de batido de la pasta, adición de agua en la misma etapa y almacenamiento de la pasta de aceituna durante un periodo corto de tiempo. Los rangos de operación han sido los siguientes: de 0% a 2% en la adición de talco, de 0% a 20% en la adición de agua y de 0 h a 36 h de tiempo de almacenamiento. Para evaluar los efectos de estos factores en el rendimiento y calidad de los aceites obtenidos se han construido modelos matemáticos y realizado análisis estadísticos (ANOVA). Para un nivel de confianza del 95%, los modelos de rendimiento en aceite, acidez, índice de peróxidos, K270 y contenido en clorofilas han resultado significativos. Con la adición de talco se consigue un mayor aumento del rendimiento de aceite, también el almacenamiento de la pasta mejora el rendimiento pero se observa una pérdida de calidad, no obstante, todos los aceites obtenidos se podrían clasificar en la categoría de aceites de oliva vírgenes extras según la normativa de la Unión Europea.

Organisms from slime moulds to humans carefully regulate their macronutrient intake to optimize a wide range of life history characters including survival, stress resistance, and reproductive success. However, life history characters often differ in their response to nutrition, forcing organisms to make foraging decisions while balancing the trade-offs between these effects. To date, we have a limited understanding of how the nutritional environment shapes the relationship between life history characters and foraging decisions. To gain insight into the problem, we used a geometric framework for nutrition to assess how the protein and carbohydrate content of the larval diet affected key life history traits in the fruit fly, Drosophila melanogaster. In no-choice assays, survival from egg to pupae, female and male body size, and ovariole number - a proxy for female fecundity - were maximized at the highest protein to carbohydrate (P:C) ratio (1.5:1). In contrast, development time was minimized at intermediate P:C ratios, around 1:2. Next, we subjected larvae to two-choice tests to determine how they regulated their protein and carbohydrate intake in relation to these life history traits. Our results show that larvae targeted their consumption to P:C ratios that minimized development time. Finally, we examined whether adult females also chose to lay their eggs in the P:C ratios that minimized developmental time. Using a three-choice assay, we found that adult females preferentially laid their eggs in food P:C ratios that were suboptimal for all larval life history traits. Our results demonstrate that D. melanogaster larvae make foraging decisions that trade-off developmental time with body size, ovariole number, and survival. In addition, adult females make oviposition decisions that do not appear to benefit the larvae. We propose that these decisions may reflect the living nature of the larval nutritional environment in rotting fruit. These studies illustrate the interaction between the nutritional environment, life history traits, and foraging choices in D. melanogaster, and lend insight into the ecology of their foraging decisions. Fundação Calouste Gulbenkian; Instituto Gulbenkian de Ciência.

The article of record as published may be found at http://dx.doi.org/10.1098/rspa.2015.0018 We propose a new framework for design under uncertainty based on stochastic computer simulations and multi-level recursive co-kriging. The proposed methodology simultaneously takes into account multi-fidelity in models, such as direct numerical simulations versus empirical formulae, as well as multi-fidelity in the probability space (e.g. sparse grids versus tensor product multi-element probabilistic collocation). We are able to construct response surfaces of complex dynamical systems by blending multiple information sources via auto-regressive stochastic modelling. A computationally efficient machine learning framework is developed based on multi-level recursive co-kriging with sparse precision matrices of Gaussian–Markov random fields. The effectiveness of the new algorithms is demonstrated in numerical examples involving a prototype problem in risk-averse design, regression of random functions, as well as uncertainty quantification in fluid mechanics involving the evolution of a Burgers equation from a random initial state, and random laminar wakes behind circular cylinders. DARPA grant HR0011-14-1-0060 AFOSR grant FA9550-12-1-0463 Argonne Leadership Computing Facility (ALCF) DARPA grant HR001-14-1-225 DARPA grant HR0011-14-1-0060 AFOSR grant FA9550-12-1-0463 DARPA grant HR001-14-1-225

This work demonstrates a novel approach to design and optimization of rare-earth free magnetic materials for targeted properties by effectively using various computational and statistical tools. From the open literature, we defined the alloying elements and bounds of their concentrations to develop a new system of Alnico alloys. Initial compositions of candidate alloys were generated using a quasi-random sequence generation algorithm. Response surface methodology approach was used to develop surrogate models to efficiently link alloy chemistry with desired macroscopic properties for these multi-component systems. The most accurate meta-models were used for multi-objective optimization of desired properties by utilizing various evolutionary approaches. Various statistical tools and pattern recognition techniques were used to determine patterns and correlations within the created dataset. Pareto-optimized candidate alloys were experimentally validated and used to improve the accuracy of the response surface generation used by the multi-objective optimizer to find the next generation of Pareto-optimal alloys. Results over the cycles show significant experimentally verified improvement in the properties of these alloys.

Application of Experimental Design techniques has proven to be essential in various research fields, due to its statistical capability of processing the effect of interactions among independent variables, known as factors, in a system’s response. Advantages of this methodology can be summarized in more resource and time efficient experimentations while providing more accurate results. This research emphasizes the quantification of 4 antioxidants extraction, at two different concentration, prepared according to an experimental procedure and measured by a Photodiode Array Detector. Experimental planning was made following a Central Composite Design, which is a type of DoE that allows to consider the quadratic component in Response Surfaces, a component that includes pure curvature studies on the model produced. This work was executed with the intention of analyzing responses, peak areas obtained from chromatograms plotted by the Detector’s system, and comprehending if the factors considered – acquired from an extensive literary review – produced the expected effect in response. Completion of this work will allow to take conclusions regarding what factors should be considered for the optimization studies of antioxidants extraction in a Oca (Oxalis tuberosa) matrix.

Multi-criteria design of complex engineering systems is methodologically and computationally demanding and time consuming process. Optimization algorithms, problem decomposition, surrogate modeling and methods for decision support are synthesis methods that are usually employed to solve the design problem. The objective of the research presented in this paper was to improve the design process of complex thin-walled ship structures through an application of surrogate modeling on this type of a problem. Methods considered are integrated into interactive computing environment for multi-criteria design in order to enable effective and efficient interaction between designer and design problem within given design timeframe. Surrogate modeling was applied for the approximation of structural responses in order to reduce a number of finite element method (FEM) calculations inside of optimization loop. Applicability of the proposed approach and suitability of different surrogate modeling methods for that purpose is extensively tested on the simple barge example. (C) 2014 Elsevier Ltd. All rights reserved.

Rising fuel prices have been inflating the operating costs of the fishing industry. Trawl doors are used to hold the fishing net open during trawling operations, and they have a great influence on the fuel consumption of vessels. Improvements in the design of trawl doors could therefore contribute significantly to increased fuel efficiency. An efficient optimization algorithm using two- and three-dimensional (2D and 3D) computational fluid dynamics (CFD) models is presented. Accurate CFD models, especially 3D, are computationally expensive. The direct use of traditional optimization algorithms, which often require a large number of evaluations, can therefore be prohibitive. The proposed method is iterative and uses low-order local response surface approximation models as surrogates for the expensive CFD model to reduce the number of iterations. The algorithm is applied to the design of two types of geometries: a typical modern trawl door, and a novel airfoil-shaped trawl door. The results from the 2D design optimization show that the hydrodynamic efficiency of the typical modern trawl door could be increased by 32%, and the novel airfoil-shaped trawl door by 13%. When the 2D optimum designs for the two geometries are compared, the novel airfoil-shaped trawl door results to be 320% more efficient than the optimized design of the typical modern trawl door. The 2D optimum designs were used as the initial designs for the 3D design optimization. The results from the 3D optimization show that the hydrodynamic efficiency could be increased by 6% for both the typical modern and novel airfoil-shaped trawl doors. Results from a 3D CFD analysis show that 3D flow effects are significant, where the values for drag are significantly underestimated in 2D CFD models.

Dissertação de Mestrado em Estatística, Matemática e Computação apresentada à Universidade Aberta A metodologia de superfícies de resposta MSR é um conjunto de técnicas estatístico-matemáticas que visa a optimização. No nosso tipo de sociedade, orientada para um mercado globalizado onde impera a lei do mais forte, qualquer ganho de produtividade, qualquer diminuição dos custos de produção, qualquer inovação, podem marcar a diferença entre o sucesso e a falência. Falar em MSR é um sonho, implementar a metodologia é antecipar o sucesso. O processo inicia-se com a interpretação do problema, definição clara do objectivo e identificação dos factores que o influenciam. Num primeiro momento, um modelo de primeira ordem é, normalmente, suficiente para modelar o processo, uma regressão múltipla estabelece a relação entre o objectivo e os factores identificados como relevantes. Verificados os pressupostos de aplicação do modelo e a linearidade do processo, urge caminhar no sentido da superfície de resposta que presumivelmente contém o ótimo (máximo ou mínimo). Para isso procuramos o máximo incremento na resposta: pelo método da máxima inclinação ascendente (steepest ascent) se procuramos um ponto de máximo, ou pelo método da máxima inclinação descendente (steepest descent) se procuramos um mínimo. Chegados à superfície de resposta ou ajustamos um novo modelo de primeira ordem ou realizamos experiências adicionais, particularmente ajustando um polinómio de ordem dois, para obter uma estimativa mais precisa do ótimo. A MSR é um processo sequencial cujo algoritmo iremos descrever através de um caso prático no âmbito da indústria cerâmica, mais concretamente no fabrico de “chávenas de porcelana”. A aplicação da metodologia de resposta tem vindo a crescer exponencialmente como o atestam o elevado número de artigos científicos publicados e a diversidade dos campos onde é implementada. Neste estudo, centramos a nossa atenção em modelos de primeira e segunda ordem, contudo a ciência não tem limite e analistas, apoiados na capacidade numérica e gráfica dos computadores, publicam já muitos trabalhos com modelos de ordem superior. The response surface methodology, MSR is a set of statistical and mathematical techniques aimed at optimization. In our kind of society, oriented towards a global market where the law of the strongest preveils, any productivity gains, any decrease in production costs, or any innovation, can make the difference between success and failure. Speaking MSR is a dream, implementing the methodology is to anticipate success. The process begins with the interpretation of the problem, clear definition of the subject and identification the factors that influence it. At first, a model of the first order is usually sufficient to model the process, a multiple regression establishes the relationship between the subject and the factors, identified as relevant. Satisfied the conditions of application of the model and the linearity of the process, it is urgent to move towards the surface response that presumably contains the optimum (maximum or minimum). For this, we look for the maximum increment in the response: at the maximum upward slope (steepest ascent) method, if we seek a point of maximum, or by the method of maximum descending slope (steepest descent) if we seek a minimum. Arriving at the response surface, or we adjust a new model of first order or we perform additional experiments , particularly adjusting a polynomial of order two, to obtain more accurate estimate of the optimal . The MSR is a sequential process by which algorithm we will describe a study case under the ceramics industry, specifically in the manufacture of "porcelain cups." The response of this methodology has been growing exponentially as a large number of scientific articles have been published and the diversity of the fields where it is implemented. In this study, we focus our attention on models of first and second order, yet science has no limit and analysts, supported by numerical and graphical capabilities of computers, many papers have been published with models of higher order.