In this thesis structural optimization of castings and thermomechanical analysis of castings are studied. In paper I an optimization algorithm is created by using Matlab. The algorithm is linked to the commercial FE solver Abaqus by using Python script. The optimization algorithm uses the successive response surfaces methodology (SRSM) to create global response surfaces. It is shown that including residual stresses in structural optimization of castings yields an optimal shape that differs significantly from the one obtained when residual stresses are excluded. In paper II the optimization algorithm is expanded to using neural networks. It is tested on some typical bench mark problems and shows very promising results. Combining paper I and II the response surfaces can be either analytical functions, both linear and non-linear, or neural networks. The optimization is then performed by using sequential linear programming or by using a zero-order method called Complex. This is all gathered in a package called StuG-OPT. In paper III and IV focus is on the thermomechanical problem when residual stresses are calculated. In paper III a literature review is performed and some numerical simulations are performed to see where numerical simulations can be used in the industry today. In paper IV simulations are compared to real tests. Several stress lattices are casted and the residual stresses are measured. Simulations are performed by using Magmasoft and Abaqus. In Magmasoft a J2-plasticity model is used and in Abaqus two simulations are performed using either J2-plasticity or the ”Cast Iron Plasticity” available in Abaqus that takes into account the different behavior in tension and compression for grey cast iron. / <p>Report code: LIU-TEK-LIC-2007:34.</p>

<p>In this thesis structural optimization of castings and thermomechanical analysis of castings are studied.</p><p>In paper I an optimization algorithm is created by using Matlab. The algorithm is linked to the commercial FE solver Abaqus by using Python script. The optimization algorithm uses the successive response surfaces methodology (SRSM) to create global response surfaces. It is shown that including residual stresses in structural optimization of castings yields an optimal shape that differs significantly from the one obtained when residual stresses are excluded.</p><p>In paper II the optimization algorithm is expanded to using neural networks. It is tested on some typical bench mark problems and shows very promising results. Combining paper I and II the response surfaces can be either analytical functions, both linear and non-linear, or neural networks. The optimization is then performed by using sequential linear programming or by using a zero-order method called Complex. This is all gathered in a package called StuG-OPT.</p><p>In paper III and IV focus is on the thermomechanical problem when residual stresses are calculated. In paper III a literature review is performed and some numerical simulations are performed to see where numerical simulations can be used in the industry today. In paper IV simulations are compared to real tests. Several stress lattices are casted and the residual stresses are measured. Simulations are performed by using Magmasoft and Abaqus. In Magmasoft a J2-plasticity model is used and in Abaqus two simulations are performed using either J2-plasticity or the ”Cast Iron Plasticity” available in Abaqus that takes into account the different behavior in tension and compression for grey cast iron.</p> / Report code: LIU-TEK-LIC-2007:34.

Ces derniers temps, des procédés commerciaux basés sur la technologie photocatalytique, sont arrivés sur le marché, afin de satisfaire la demande croissante du traitement de l’air intérieur. L’objectif de ce présent travail est de développer une nouvelle méthodologie pour évaluer l’efficacité de ce nouveau procédé. Pour l’étude de l’application de la photocatalyse au traitement de l’air intérieur, un dispositif expérimental a été mis au point et deux méthodes analytiques ont été développées (ATD-GCMS et GC-PDHID). La performance de la dégradation photocatalytique du 2-propanol et du toluène à faibles concentrations (ppbv) a été étudiée. L’influence des différents paramètres (humidité relative, débit, concentration initiale, etc.) et leurs interactions sur la conversion, la formation des intermédiaires et la minéralisation au CO2 a été établie / Many commercial systems based in the photocatalytic technology have reached the market recently in order to address the growing demand for improve poor indoor air qualities. The present work deals with the development of a new methodology in order to evaluate the efficiency of this process. For the study of photocatalytic oxidation for indoor air applications, an experimental set-up was designed and two analytical tools (ATD-GC-MS and GC-PDHID) were developed. The performance of the photocatalytic treatment of 2-propanol and toluene at indoor air concentrations levels (ppbv) were realised. The influence of several parameters and their interactions effects on the conversion, by-product formation and mineralization to CO2 were established

In this study, the effects of bioprocess parameters on glucose isomerase roduction by Bacillus thermoantarcticus (DSMZ 9572) were investigated. For his purpose, firstly, in laboratory scale shake-bioreactors, a defined medium was designed in terms of its carbon and nitrogen sources, to achieve the highest glucose isomerase activity. Optimum concentrations of medium components were determined by a statistical approach, namely Response Surface Methodology (RSM). RSM defined the relationship between the response, glucose isomerase activity and the independent variables, medium components. The highest glucose isomerase volumetric activity was obtained as 1630 U L-1 in the optimized medium containing 10.64 kg m-3 xylan, 5.66 kg m-3 yeast extract, 5.92 kg m-3 (NH4)2SO4, 0.25 kg m-3 MgSO4.7H2O, 0.001 kg m-3 FeSO4.7H2O, 0.001 kg m-3 ZnSO4.7H2O , 0.000075 kg m-3 MnSO4. H2O, and 0.00001 kg m-3 CuSO4.5H2O at conditions: pH0= 6.0, T=55&deg / C, N=200 min-1. Then by using the designed medium, pH and oxygen transfer conditions of the bioprocess were investigated in 3.0 dm3 pilot scale bioreactor. The effect of pH was analyzed at pH=6 uncontrolled and controlled operations with the following conditions: air inlet rate of Q0/VR=0.5 vvm and agitation rate of N=500 min-1. The effects of oxygen transfer parameters were examined, at pH=6 controlled condition, at an air inlet rate of Q0/VR=0.5 vvm and the agitation rates of N=300,500,750 min-1. The variations in glucose isomerase activity, cell, amino acid and organic acid concentrations with the cell cultivation time, specific cell growth rate, the oxygen uptake rate, the liquid phase coefficient by using the dynamic method, maintenance coefficient for oxygen and yield coefficients were determined. The highest glucose isomerase volumetric activity and cell concentration, 1838 U L-1 and 2.26 kg m-3 at the 24th of the cell cultivation were attained at 0.5 vvm, 500 min 1 and pH=6 uncontrolled operation.

The main objective of this study is to evaluate the effects of microwave frying process on the quality of potato slices and to optimize the process by using different statistical optimization techniques. Use of microwave frying for food products may be considered as a new way of improving the quality of the fried foods. In the first part of the study, the effects of microwaves on quality of fried potatoes (moisture content, oil content, color and hardness) were studied and the process was optimized by using Taguchi Technique. Microwave power level (400W, 550W and 700W), frying time (2.0, 2.5, 3.0 minutes) and oil type (sunflower, corn and hazelnut oil) were the parameters used in the study. Moisture content of potatoes decreased whereas oil content, hardness and &amp / #916 / E values of the potatoes increased with increasing frying time and microwave power level. The potatoes with the highest oil content were found to be the ones that were fried in the hazelnut oil. The optimum condition was found as frying at 550W microwave power level, for 2.5 minutes in sunflower oil. The potatoes that were fried at the optimum condition were determined to have lower oil contents compared to the ones fried conventionally.In the second part of the study, osmotic dehydration was applied prior to microwave frying process in order to reduce oil uptake and to evaluate the effect of osmotic dehydration with microwaves on quality of fried potatoes. The process was optimized by using both Taguchi Technique and Response Surface Methodology. Microwave power level (400W, 550W and 700W), frying time (1.5, 2.0, 2.5 minutes) and osmotic dehydration time (15, 30, 45 minutes) were the parameters used in the study. Osmotic dehydration treatment was conducted in a salt solution of 20 % (w/w) at 30oC. Moisture content decreased whereas oil content, hardness and &amp / #916 / E value of potatoes increased with increasing frying time and microwave power level. Dehydration of potatoes osmotically prior to frying reduced the oil content of fried potatoes. The optimum condition was found as frying at 400 W microwave power level for 1.5 min after 30 min of osmotic dehydration time according to Taguchi Technique. Microwave power level and frying time were the same as Taguchi Technique but osmotic dehydration time was 39 min for the optimum condition found using response surface methodology.

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This dissertation presents an empirical approach to identifying decisions for adapting cognitive radio parameters with no a priori knowledge of the environment. Cognitively inspired radios, attempt to combine observed metrics of system performance with artificial intelligence decision-making algorithms. Current architectures trend towards hybrid combinations of heuristics, such as genetic algorithms (GA) and experiential methods, such as case-based reasoning (CBR). A weakness in the GA is its reliance on limited mathematical models for estimating bit error rate, packet error rate, throughput, and signal-to-noise ratio. The CBR approach is similarly limited by its dependency on past experiences. Both methods have potential to suffer in environments not previously encountered. In contrast, the statistical methods identify performance estimation models based on exercising defined experimental designs. This represents an experiential decision-making process formed in the present rather than the past. There are three core contributions from this empirical framework: 1) it enables a new approach to decision making based on empirical estimation models of system performance, 2) it provides a systematic method for initializing cognitive engine configuration parameters, and 3) it facilitates deeper understanding of system behavior by quantifying parameter significance, and interaction effects. Ultimately, this understanding enables simplification of system models by identifying insignificant parameters. This dissertation defines an abstract framework that enables application of statistical approaches to cognitive radio systems regardless of its platform or application space. Specifically, it assesses factorial design of experiments and response surface methodology (RSM) to an over-the-air wireless radio link. Results are compared to a benchmark GA cognitive engine. The framework is then used for identifying software-defined radio initialization settings. Taguchi designs, a related statistical method, are implemented to identify initialization settings of a GA. / Ph. D.

O aumento nos rejeitos industriais e a contínua produção de resíduos causam muitas preocupações no âmbito ambiental. Neste contexto, o descarte de pneus usados tem se tornado um grande problema por conta da pequena atenção que se dá à sua destinação final. Assim sendo, essa pesquisa propõe a produção de uma mistura polimérica com polipropileno (PP), a borracha de etileno-propileno-dieno (EPDM) e o pó de pneu (SRT). A Metodologia de Superfície de Resposta (MSR), coleção de técnicas estatísticas e matemáticas úteis para desenvolver, melhorar e optimizar processos, foi aplicada à investigação das misturas ternárias. Após o processamento adequado em extrusora de dupla rosca e a moldagem por injeção, as propriedades mecânicas de resistência à tração e resistência ao impacto foram determinadas e utilizadas como variáveis resposta. Ao mesmo tempo, a microscopia eletrônica de varredura (MEV) foi usada para a investigação da morfologia das diferentes misturas e melhor interpretação dos resultados. Com as ferramentas estatísticas específicas e um número mínimo de experimentos foi possível o desenvolvimento de modelos de superfícies de resposta e a otimização das concentrações dos diferentes componentes da mistura em função do desempenho mecânico e além disso com a modificação da granulometria conseguimos um aumento ainda mais significativo deste desempenho mecânico. / The increase in industrial waste and solid waste production cause many concerns in the environment. In this context, the disposal of used tires has become a major problem because of the little attention given to their final destination. Therefore, this research proposes the production of a polymer blend of polypropylene (PP), rubber of ethylene-propylene-diene (EPDM) and tire dust (SRT). The Response Surface Methodology (RSM), a collection of mathematical and statistical techniques useful for developing, improving and optimizing processes, was applied to the investigation of ternary mixtures. After proper processing on twin screw extrusion and injection molding, the mechanical properties of tensile and impact strength were determined and used as response variables. At the same time, scanning electron microscopy (SEM) was used to investigate the morphology of different blends and better interpretation of results. With specific statistical tools and a minimum number of experiments it was possible to develop models of response surfaces and the optimization of the concentrations of different components of the mixture depending on the mechanical performance and even with the change in particle size could increase even more significant this mechanical performance.

The first aim of this study is the development of extracellular recombinant therapeutic protease streptokinase producing Bacillus sp., and the second aim is to determine fermentation characteristics for streptokinase production. In this context, the signal (pre-) DNA sequence of B.licheniformis (DSM1969) extracellular serine alkaline protease enzyme gene (subC: Acc. No. X03341) was ligated to 5&rsquo / end of the streptokinase gene (skc: Acc. No. S46536) by SOE (Gene Splicing by Overlap Extension) method through PCR. The resulting hybrid gene pre(subC)::skc was cloned into the pUC19 plasmid. Then, the hybrid gene was sub-cloned to pMK4 plasmid which is an E. coli-Bacillus shuttle vector with high copy number and high stability. Recombinant plasmid pMK4::pre(subC)::skc was finally transferred into B. subtilis (npr- apr-) and B. licheniformis 749/C (ATCC 25972) species. Streptokinase production capacities of these two recombinant Bacillus species were compared. The highest production was observed in recombinant B. lichenifomis 749/C (ATCC 25972) strain in a defined medium which was optimized in terms of carbon and nitrogen sources by a statistical approach, namely Response Surface Methodology (RSM). RSM evaluated the streptokinase concentration as the response and the medium components as the independent variables. The highest recombinant streptokinase concentration was found as 0.0237 kgm-3 at glucose and (NH4)2HPO4 concentrations of 4.530 and 4.838 kgm-3 respectively. The fermentation and oxygen transfer characteristics of the streptokinase production were investigated in a 3 dm3 pilot scale batch bioreactor (Braun CT2-2) equipped with temperature, pH, foam, air inlet and agitation rate controls having a working volume of VR=1.65 dm3 using the production medium optimized for the recombinant B. lichenifomis 749/C (ATCC 25972) strain. Streptokinase and &amp / #946 / -lactamase activities, cell, glucose and organic acid concentrations, dissolved oxygen, pH, oxygen uptake rate, overall liquid phase mass transfer coefficient for oxygen, maintenance coefficient for oxygen, specific cell growth rate and yield coefficients were determined through the bioprocess. The bioprocess of recombinant streptokinase production was performed at uncontrolled pH of these bioreactor operation conditions: air inlet rate of Q0/VR=0.5 vvm, and the agitation rate of N=400min-1. The resulting streptokinase volumetric activity reached its maximum as 1.16 PUml-1 (0.0026 g/l streptokinase) at t=20 h.

Kitchen waste, which is collected in large amounts from cafeterias, restaurants, dining halls, food processing plants, and household kitchens, have become a valuable material for bioprocess engineering. Due to the high carbohydrate fraction, kitchen waste has great potential to be used as a potential substrate for ethanol production. Utilization of it as a raw material in ethanol fermentation would also contribute to reduction of costs. In the first part of this study, the effect of pretreatment method and enzymatic hydrolysis on glucose production was evaluated. Dry baker&rsquo / s yeast, Saccharomyces cerevisiae, was used in fermentation experiments conducted with and without fermentation medium at pH 4.5 and 30oC for 48 hours. Close values of glucose concentration were obtained from no pretreated and hot water treated samples. The fermentation results indicated that ethanol can be produced at similar concentrations in bioreactors with and without fermentation medium addition (p &gt / 0.05). Thus, it is concluded that use of kitchen wastes as is disposed and without fermentation medium in ethanol fermentation could lower the cost to a large extent. In the second part of this study, the effects of solid load, which is proportional to the glucose concentration (10% to 20% (w/w)), inoculum level of Saccharomyces cerevisiae (5% to 15% (v/v)), and fermentation time (48 to 96 h) on production of bioethanol from kitchen waste were studied using Response Surface Methodology (RSM). A three-factor Box Behnken design was used. Ethanol concentration was used as a response in the resulting experimental design. High Pressure Liquid Chromatography (HPLC) method was used to determine ethanol and glucose concentrations. The statistical analysis of the constructed model developed by RSM suggested that linear effects of solid load, inoculum level, and fermentation time and quadratic effects of inoculum level and fermentation time were all significant (p &lt / 0.05) on bioethanol production. The model was verified by additional runs, which were not present in the design matrix. It was found that the constructed model could be used to determine successfully the bioethanol concentration with &gt / 90% precision. An optimum ethanol concentration of 32.16 g/L was suggested by the model with 20% (w/w) solid load, 8.85% (v/v) inoculum level and 58.8 hours of fermentation. Further study is needed to evaluate the optimal fermentation conditions in a large scale fermentation