964 resultados para Non-Linear Optimization
Resumo:
This paper gives a detailed presentation of the Substitution-Newton-Raphson method, suitable for large sparse non-linear systems. It combines the Successive Substitution method and the Newton-Raphson method in such way as to take the best advantages of both, keeping the convergence features of the Newton-Raphson with the low requirements of memory and time of the Successive Substitution schemes. The large system is solved employing few effective variables, using the greatest possible part of the model equations in substitution fashion to fix the remaining variables, but maintaining the convergence characteristics of the Newton-Raphson. The methodology is exemplified through a simple algebraic system, and applied to a simple thermodynamic, mechanical and heat transfer modeling of a single-stage vapor compression refrigeration system. Three distinct approaches for reproducing the thermodynamic properties of the refrigerant R-134a are compared: the linear interpolation from tabulated data, the use of polynomial fitted curves and the use of functions derived from the Helmholtz free energy.
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In this work, image based estimation methods, also known as direct methods, are studied which avoid feature extraction and matching completely. Cost functions use raw pixels as measurements and the goal is to produce precise 3D pose and structure estimates. The cost functions presented minimize the sensor error, because measurements are not transformed or modified. In photometric camera pose estimation, 3D rotation and translation parameters are estimated by minimizing a sequence of image based cost functions, which are non-linear due to perspective projection and lens distortion. In image based structure refinement, on the other hand, 3D structure is refined using a number of additional views and an image based cost metric. Image based estimation methods are particularly useful in conditions where the Lambertian assumption holds, and the 3D points have constant color despite viewing angle. The goal is to improve image based estimation methods, and to produce computationally efficient methods which can be accomodated into real-time applications. The developed image-based 3D pose and structure estimation methods are finally demonstrated in practise in indoor 3D reconstruction use, and in a live augmented reality application.
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The acceleration of solar energetic particles (SEPs) by flares and coronal mass ejections (CMEs) has been a major topic of research for the solar-terrestrial physics and geophysics communities for decades. This thesis discusses theories describing first-order Fermi acceleration of SEPs through repeated crossings at a CME-driven shock. We propose that particle trapping occurs through self-generated Alfvén waves, leading to a turbulent trapping region in front of the shock. Decelerating coronal shocks are shown to be capable of efficient SEP acceleration, provided seed particle injection is sufficient. Quasi-parallel shocks are found to inject thermal particles with good efficiency. The roles of minimum injection velocities, cross-field diffusion, downstream scattering efficiency and cross-shock potential are investigated in detail, with downstream isotropisation timescales having a major effect on injection efficiency. Accelerated spectra of heavier elements up to iron are found to exhibit significantly harder spectra than protons. Accelerated spectra cut-off energies are found to scale proportional to (Q/A)1.5, which is explained through analysis of the spectral shape of amplified Alfvénic turbulence. Acceleration times to different threshold energies are found to be non-linear, indicating that self-consistent time-dependent simulations are required in order to expose the full extent of acceleration dynamics. The well-established quasilinear theory (QLT) of particle scattering is investigated by comparing QLT scattering coefficients with those found via full-orbit simulations. QLT is found to overemphasise resonance conditions. This finding supports the simplifications implemented in the presented coronal shock acceleration (CSA) simulation software. The CSA software package is used to simulate a range of acceleration scenarios. The results are found to be in agreement with well-established particle acceleration theory. At the same time, new spatial and temporal dynamics of particle population trapping and wave evolution are revealed.
Resumo:
Nykyinen Eurocode 3 suunnitteluohjeen rakenneputkiliitoksia käsittelevä osio vaatii S500 suurlujuusteräksestä valmistettujen liitosten mitoituksen yhteydessä käytettäväksi reduk-tiokerrointa 0.8. Tämä on varsin konservatiivinen mitoituspa, joka vähentää merkittävästi lujemman teräslaadun käyttämisestä saavutettavaa hyötyä. Tämän työn pääasiallinen ta-voite on laboratoriotestein selvittää S500 lujuusluokan rakenneputkiliitosten todellinen äärikapasiteetti ja verrata sitä nykyisen mitoitusohjeen mukaiseen kapasiteettiin. Tässä työssä tutkitut liitokset ovat valmistettu poikkileikkaukseltaan nelikulmaisista kyl-mämuovatuista rakenneputkista. Koesarja koostui kahdeksasta X-liitoksesta, sekä kymme-nestä K-liitoksesta. Kaikki testit suoritettiin huoneenlämmössä, LUT Koneen teräsrakenne-laboratoriossa. Laboratoriotestien lisäksi rakenteen käyttäytymistä tutkittiin epälineaarisen elementtimenetelmän avulla ja näitä tuloksia verrattiin kokeellisiin tuloksiin. Sekä testien että FE–analyysin perusteella voidaan todeta, että S500 lujuusluokan terästä käytettäessä ei Eurocode 3:n mukaisen reduktiokertoimen käytölle ole perusteita.
Resumo:
This work aimed to evaluate the uptake and translocation of quinclorac in function of application sites (shoot or roots) by Echinochloa crusgalli biotypes resistant and susceptible to this herbicide. The treatments consisted of quinclorac doses (0; 0.5; 1; 2; 4; 16 and 64 ppm), applied on the shoot or roots of seedlings of barnyardgrass biotypes. The experimental units consisted of plastic cups containing 250 cm³ of sand. The treatments were applied 10 days after emergence, when barnyardgrass plants reached a 2- to 3- leaf growth stage. The barnyardgrass biotypes were irrigated with nutritive solution weekly and maintained for 40 days after emergence, when length, fresh and dry matter of shoot and roots were evaluated. Variance analysis was carried out using the F test at 5% probability, and in case of significance, a non-linear regression analysis was also carried out using a three-parameter logistic model. In the susceptible biotype, quinclorac was more absorbed by the roots than by the shoot. Comparing dry mass production of the different plant parts of the susceptible biotype per application site, it was verified that quinclorac action is higher when applied to the plant roots. However, for the resistant biotype, it was not possible to determine the dose causing 50% reduction in dry mass accumulation (GR50) and in the resistance index (RI) between both biotypes, due to its high resistance to quinclorac (128 times the recommended dosage). The results showed that quinclorac resistance by the evaluated biotype is not due to differences in the absorption site, strongly suggesting that the resistance acquired by the biotype may result from alteration in the target site.
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The purpose of this study was to investigate the suitability of the Finnish Defence Forces’ NH90 helicopter for parachuting operations with the T-10 static line parachute system. The work was based on the Army Command’s need to compensate for the reduction in the outsourced flight hours for the military static line parachuting training. The aim of the research was to find out the procedures and limitations with which the NH90 IOC+ or FOC version helicopter could be used for static line parachutist training with the T- 10B/MC1-1C parachutes. The research area was highly complicated and non-linear. Thus analytical methods could not be applied with sufficient confidence, even with present-day computing power. Therefore an empirical research method was selected, concentrating on flight testing supported with literature study and some calculated estimations. During three flights and 4.5 flight hours in Utti, Finland on 17−20 September 2012, a total of 44 parachute drops were made. These consisted of 16 dummy drops and 28 paratrooper jumps. The test results showed that when equipped with the floor mounted PASI-1 anchor line, the deflector bar of the NHIndustries’ Parachuting Kit and Patria’s floor protection panels the Finnish NH90 variant could be safely used for T-10B/MC1-1C static line parachuting operations from the right cabin door at airspeed range of 50−80 KIAS (∼90–150 km/h). The ceiling mounted anchor lines of the NHI’s Parachuting Kit were not usable with the T-10 system. This was due to the static lines’ unsafe behaviour in slipstream when connected to the cabin ceiling level. In conclusion, the NH90 helicopter can be used to meet the Army Command’s requirement for an additional platform for T-10 static line parachutist training. Material dropping, the effect of additional equipment and jumping from the rear ramp should be further studied.
Resumo:
Asymmetric synthesis using modified heterogeneous catalysts has gained lots of interest in the production of optically pure chemicals, such as pharmaceuticals, nutraceuticals, fragrances and agrochemicals. Heterogeneous modified catalysts capable of inducing high enantioselectivities are preferred in industrial scale due to their superior separation and handling properties. The topic has been intensively investigated both in industry and academia. The enantioselective hydrogenation of ethyl benzoylformate (EBF) to (R)-ethyl mandelate over (-)-cinchonidine (CD)-modified Pt/Al2O3 catalyst in a laboratory-scale semi-batch reactor was studied as a function of modifier concentration, reaction temperature, stirring rate and catalyst particle size. The main product was always (R)-ethyl mandelate while small amounts of (S)-ethyl mandelate were obtained as by product. The kinetic results showed higher enantioselectivity and lower initial rates approaching asymptotically to a constant value as the amount of modifier was increased. Additionally, catalyst deactivation due to presence of impurities in the feed was prominent in some cases; therefore activated carbon was used as a cleaning agent of the raw material to remove impurities prior to catalyst addition. Detailed characterizations methods (SEM, EDX, TPR, BET, chemisorption, particle size distribution) of the catalysts were carried out. Solvent effects were also studied in the semi-batch reactor. Solvents with dielectric constant (e) between 2 and 25 were applied. The enantiomeric excess (ee) increased with an increase of the dielectric coefficient up to a maximum followed by a nonlinear decrease. A kinetic model was proposed for the enantioselectivity dependence on the dielectric constant based on the Kirkwood treatment. The non-linear dependence of ee on (e) successfully described the variation of ee in different solvents. Systematic kinetic experiments were carried out in the semi-batch reactor. Toluene was used as a solvent. Based on these results, a kinetic model based on the assumption of different number of sites was developed. Density functional theory calculations were applied to study the energetics of the EBF adsorption on pure Pt(1 1 1). The hydrogenation rate constants were determined along with the adsorption parameters by non-linear regression analysis. A comparison between the model and the experimental data revealed a very good correspondence. Transient experiments in a fixed-bed reactor were also carried out in this work. The results demonstrated that continuous enantioselective hydrogenation of EBF in hexane/2-propanol 90/10 (v/v) is possible and that continuous feeding of (-)-cinchonidine is needed to maintain a high steady-state enantioselectivity. The catalyst showed a good stability and high enantioselectivity was achieved in the fixed-bed reactor. Chromatographic separation of (R)- and (S)-ethyl mandelate originating from the continuous reactor was investigated. A commercial column filled with a chiral resin was chosen as a perspective preparative-scale adsorbent. Since the adsorption equilibrium isotherms were linear within the entire investigated range of concentrations, they were determined by pulse experiments for the isomers present in a post-reaction mixture. Breakthrough curves were measured and described successfully by the dispersive plug flow model with a linear driving force approximation. The focus of this research project was the development of a new integrated production concept of optically active chemicals by combining heterogeneous catalysis and chromatographic separation technology. The proposed work is fundamental research in advanced process technology aiming to improve efficiency and enable clean and environmentally benign production of enantiomeric pure chemicals.
Resumo:
Specific knowledge about the dormancy, germination, and emergence patterns of weed species aids the development of integrated management strategies. Laboratory studies were conducted to determine the effect of several environmental factors on seed germination and seedling emergence of Cyperus difformis. Germination of freshly harvested seeds was inhibited by darkness; however, when seeds were subsequently transferred to complete light they germinated readily. Our results showed that 2 wk of cold stratification overcome the light requirement for germination. Seeds of C. difformis were able to germinate over a broad range of temperatures (25/15, 30/20, 35/25, and 40/30 ºC day/night). The response of germination rate to temperature was described as a non-linear function. Based on model outputs, the base, the optimum and the ceiling temperatures were estimated as 14.81, 37.72 and 45 ºC, respectively. A temperature of 120 ºC for a 5 min was required to inhibit 50% of maximum germination. The osmotic potential and salinity required for 50% inhibition of maximum germination were -0.47 MPa and 135.57 mM, respectively. High percentage of seed germination (89%) was observed at pH=6 and decreased to 12% at alkaline medium (pH 9) pH. Seeds sown on the soil surface gave the greatest percentage of seedling emergence, and no seedlings emerged from seeds buried in soil at depths of 1 cm.
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The ALS-inhibiting herbicides, especially metsulfuron-methyl, are widely used for weed control, mainly wheat and barley in southern Brazil. Raphanus raphanistrum is a major weed of winter crops. However, in recent years, R.raphanistrum, after being treated with metsulfuron, has shown no symptoms of toxicity, possibly due to herbicide resistance. Aiming to evaluate the existence of R.raphanistrum biotypes resistant to metsulfuron, an experiment was conducted in a greenhouse, in a completely randomized design with four replications. The plots consisted of pots with six plants. The treatments consisted of the interaction of resistant R. raphanistrum (biotype R) and susceptible R. raphanistrum (biotypes S) with ten doses of the herbicide (0.0; 0.6; 1.2; 2.4; 4.8; 9.6; 19.2; 38.4; 76.8 and 153.6 g i.a. ha-1). The application of the test herbicides occurred when the crop was at the stage of 3 to 4 true leaves. The variables analyzed were control and dry matter accumulation. Statistical analysis of dose-response curves was performed by non linear regression. Biotype S was susceptible to the herbicide even at doses below the recommended. Biotype R was insensitive to the herbicide obtaining values of resistance factor (F) higher than 85. The dose-response curve confirmed the existence of R. raphanistrum biotypes with high level of resistance to metsulfuron-methyl.
Resumo:
Emex australis and E. spinosa are significant weed species in wheat and other crops. Information on the extent of competition of the Emex species will be helpful to access yield losses in wheat. Field experiments were conducted to quantify the interference of tested weed densities each as single or mixture of both at 1:1 on their growth and yield, wheat yield components and wheat grain yield losses in two consecutive years. Dry weight of both weed species increased from 3-6 g m-2 with every additional plant of weed, whereas seed number and weight per plant decreased with increasing density of either weed. Both weed species caused considerable decrease in yield components like spike bearing tillers, number of grains per spike, 1000-grain weight of wheat with increasing density population of the weeds. Based on non-linear hyperbolic regression model equation, maximum yield loss at asymptotic weed density was estimated to be 44 and 62% with E. australis, 56 and 70% with E. spinosa and 63 and 72% with mixture of both species at 1:1 during both year of study, respectively. It was concluded that E. spinosa has more competition effects on wheat crop as compared to E. australis.
Resumo:
Lignin, after cellulose, is the second most abundant biopolymer on Earth, accounting for 30% of the organic carbon in the biosphere. It is considered an important evolutionary adaptation of plants during their transition from the aquatic environment to land, since it bestowed the early tracheophytes with physical support to stand upright and enabled long-distance transport of water and solutes by waterproofing the vascular tissue. Although essential for plant growth and development, lignin is the major plant cell wall component responsible for biomass recalcitrance to industrial processing. The fact that lignin is a non-linear aromatic polymer built with chemically diverse and poorly reactive linkages and a variety of monomer units precludes the ability of any single enzyme to properly recognize and degrade it. Consequently, the use of lignocellulosic feedstock as a renewable and sustainable resource for the production of biofuels and bio-based materials will depend on the identification and characterization of the factors that determine plant biomass recalcitrance, especially the highly complex phenolic polymer lignin. Here, we summarize the current knowledge regarding lignin metabolism in plants, its effect on biomass recalcitrance and the emergent strategies to modify biomass recalcitrance through metabolic engineering of the lignin pathway. In addition, the potential use of sugarcane as a second-generation biofuel crop and the advances in lignin-related studies in sugarcane are discussed.
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Heart rate variability is a relevant predictor of cardiovascular risk in humans. A significant genetic influence on heart rate variability is suggested, although the genes involved are ill-defined. The Mas-protooncogene encodes a G-protein-coupled receptor with seven transmembrane domains highly expressed in testis and brain. Since this receptor is supposed to interact with the signaling of angiotensin II, which is an important regulator of cardiovascular homeostasis, heart rate and blood pressure were analyzed in Mas-deficient mice. Using a femoral catheter the blood pressure of mice was measured for a period of 30 min and 250 data values per second were recorded. The mean values and range of heart rate and blood pressure were then calculated. Neither heart rate nor blood pressure were significantly different between knockout mice and controls. However, high resolution recording of these parameters and analysis of the data by non-linear dynamics revealed significant alterations in cardiovascular variability in Mas-deficient animals. In particular, females showed a strong reduction of heart rate variability. Furthermore, the data showed an increased sympathetic tone in knockout animals of both genders. The marked alterations detected in Mas-deficient mice of both genders suggest that the Mas-protooncogene is an important determinant of heart rate and blood pressure variability.
Resumo:
This thesis is concerned with the state and parameter estimation in state space models. The estimation of states and parameters is an important task when mathematical modeling is applied to many different application areas such as the global positioning systems, target tracking, navigation, brain imaging, spread of infectious diseases, biological processes, telecommunications, audio signal processing, stochastic optimal control, machine learning, and physical systems. In Bayesian settings, the estimation of states or parameters amounts to computation of the posterior probability density function. Except for a very restricted number of models, it is impossible to compute this density function in a closed form. Hence, we need approximation methods. A state estimation problem involves estimating the states (latent variables) that are not directly observed in the output of the system. In this thesis, we use the Kalman filter, extended Kalman filter, Gauss–Hermite filters, and particle filters to estimate the states based on available measurements. Among these filters, particle filters are numerical methods for approximating the filtering distributions of non-linear non-Gaussian state space models via Monte Carlo. The performance of a particle filter heavily depends on the chosen importance distribution. For instance, inappropriate choice of the importance distribution can lead to the failure of convergence of the particle filter algorithm. In this thesis, we analyze the theoretical Lᵖ particle filter convergence with general importance distributions, where p ≥2 is an integer. A parameter estimation problem is considered with inferring the model parameters from measurements. For high-dimensional complex models, estimation of parameters can be done by Markov chain Monte Carlo (MCMC) methods. In its operation, the MCMC method requires the unnormalized posterior distribution of the parameters and a proposal distribution. In this thesis, we show how the posterior density function of the parameters of a state space model can be computed by filtering based methods, where the states are integrated out. This type of computation is then applied to estimate parameters of stochastic differential equations. Furthermore, we compute the partial derivatives of the log-posterior density function and use the hybrid Monte Carlo and scaled conjugate gradient methods to infer the parameters of stochastic differential equations. The computational efficiency of MCMC methods is highly depend on the chosen proposal distribution. A commonly used proposal distribution is Gaussian. In this kind of proposal, the covariance matrix must be well tuned. To tune it, adaptive MCMC methods can be used. In this thesis, we propose a new way of updating the covariance matrix using the variational Bayesian adaptive Kalman filter algorithm.
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Tutkielman tavoitteena on selvittää osinkosuhteen, osinkotuoton ja omavaraisuusasteen vaikutus osakkeesta saatavaan kokonaistuottoon Suomenosakemarkkinoilla vuosina 2002–2013. Muuttujien kausaliteettisuhde kokonaistuottoon selvitetään regressioanalyysilla. Portfolioanalyysin avulla tutkitaan valittujen tunnuslukujen toimivuutta sijoitusstrategiana. Tutkimuksessa muodostetaan myös osinkosuhteen ja osinkotuoton yhdistelmänä tunnusluku, jolla pyritään maksimoimaan sijoittajan saama tuotto. Empiiriset tulokset osoittivat, että sijoittaja pystyy saavuttamaan ylituottoja hyödyntämällä edellä mainittuja tunnuslukuja osakevalinnassa. Osinkotuoton ja osakkeen kokonaistuoton välillä havaittiin positiivinen lineaarinen korrelaatio. Portfolioanalyysin perusteella sekä omavaraisuusasteen että osinkosuhteen osalta vaikutus sijoittajan saamaan riskisuhteutettuun kokonaistuottoon on ei-lineaarinen. Valittuja tunnuslukuja ja menetelmiä hyödyntäen sijoittaja saa parhaimman riskisuhteutetun tuoton valitsemalla sijoitussalkkuunsa osakkeita, joiden osinkosuhteen arvo sijoittuu toiseksi ylimpään kvartiiliin sekä osakkeita, joiden osinkotuotto on korkea ja omavaraisuusaste on samanaikaisesti alhainen.
Resumo:
The estimation of losses plays a key role in the process of building any electrical machine. How to estimate those losses while designing any machine; by obtaining the characteristic of the electrical steel from the catalogue and calculate the losses. However, this way is inaccurate since the electrical steel performs several manufacturing processes during the process of building any machine, which affects directly the magnetic property of the electrical steel and accordingly the characteristic of the electrical steel will be affected. That means the B–H curve of the steel that was obtained from the catalogue will be changed. Moreover, during loading and rotating the machine, some important changes occur to the B–H characteristic of the electrical steel such as the stress on the laminated iron. Accordingly, the pre-estimated losses are completely far from the actual losses because they were estimated based on the data of the electrical steel obtained from the catalogue. So in order to estimate the losses precisely significant factors of the manufacturing processes must be included. The paper introduces the systematic estimation of the losses including the effect of one of the manufacturing factors. Similarly, any other manufacturing factor can be included in the pre-designed losses estimations.