The Gulf of Bothnia consists of two sub-basins in the northern Baltic Sea: the Bothnian Sea (salinity 4-5‰) and Bothnian Bay (salinity 2-3‰). Changing nutrient concentrations and signs of eutrophication has recently been observed in the Gulf of Bothnia. Many rivers enter this sea area, and potentially river inflows constitute a source of nutrient pollution via waste-water emissions. The aim of this study was to elucidate effects of waste-water emissions in four rivers in northern Sweden, Luleå, Skellefteå, Umeå and Söderhamn. My approach was to compare nutrient concentrations at upstream and downstream sampling stations related to the position of waste-water treatment plants. Temporal data from 2006 to 2021 were used and statistically analyzed using non-parametric tests to establish spatial and temporal patterns for nutrient discharged to the coast. The results showed that there are statistically differences in dissolved inorganic phosphorus (DIP) in the form of phosphate (PO4), ammonia (NH4) and total nitrogen (TotN) between the upstream and downstream of Luleå and Umeå wastewater treatment plants. No statistically significant differences were observed in the upstream and downstream data for Söderhamn and Skellefteå. This suggest that better management and mitigation of nutrient loading from wastewater treatment plants that serve higher populations is paramount to achieve the zero-eutrophication goal in the Gulf of Bothnia.

Friction Stir Welding (FSW) is an emerging joining technology in which basic process understanding is still inadequate. Knowledge of FSW parameter relationships is needed to better understand the process and implement proper machine control. This study utilized a 3-factor, 3-level factorial design of experiments to investigate relationships between key process inputs and measured output parameters. All experiments utilized 7075-T7 aluminum and a threaded pin tool with a 25.4 mm shoulder diameter, 4.76 mm pin length, and 7.9 mm pin diameter. Spindle speed, feed rate, and tool depth were varied throughout 54 welds while X, Y, and Z forces, X torque, three tool temperatures, and motor power were measured. Empirical models were developed to relate outputs to inputs. The relationships between inputs and outputs are nonlinear and require, at a minimum, a quadratic equation to reasonably model them. These models were further analyzed to explore possible control schemes. Tool depth was found to be the most fundamental means of controlling weld forces and tool temperatures. This research describes the input/output relationships enumerated above for FSW as well as a discussion of possible control schemes.

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With the proliferation of unmanned aircraft designed for national security and commercial purposes, opportunities exist to create high-fidelity aerodynamic models with flight test techniques developed specifically for remotely piloted aircraft. Then, highly maneuverable unmanned aircraft can be employed to their greatest potential in a safe manner using advanced control laws. In this dissertation, novel techniques are used to identify nonlinear, coupled, aerodynamic models for fixed-wing, unmanned aircraft from flight test data alone. Included are quasi-steady and unsteady nominal flight models, aero-propulsive models, and spinning flight models. A novel flight test technique for unmanned aircraft, excitation with remote uncorrelated pilot inputs, is developed for use in nominal and nonlinear flight regimes. Orthogonal phase-optimized multisine excitation signals are also used as inputs while collecting gliding, aero-propulsive, and spinning flight data. A novel vector decomposition of explanatory variables leads to an elegant model structure for stall spin flight data analysis and spin aerodynamic modeling. Results for each model developed show good agreement between model predictions and validation flight data. Two novel applications of aerodynamic modeling are discussed including energy-based nonlinear directional control and a spin flight path control law for use as a flight termination system. Experimental and simulation results from these applications demonstrate the utility of high-fidelity models developed from flight data. / Doctor of Philosophy / This dissertation presents flight test experiments conducted using a small remotely controlled airplane to determine mathematical equations and parameter values, called models, to describe the airplane's motion. Then, the models are applied to control the path of the airplane. The process to develop the models and predict an airplane's motion using flight data is described. New techniques are presented for data collection and analysis for unusual flight conditions, including a spinning descent. Results show the techniques can predict the airplane's motion very well. Two experiments are presented demonstrating new applications and the usefulness of the mathematical models.

本研究採用1995-2009年的WIOD 資料庫 World Input-Output Table(WIOT)、WIOD Socio Economic Accounts (SEAs)資料，將勞工使用教育程度分成三種技術勞工:高技術勞工、中技術勞工、低技術勞工與資本，五種要素的貿易要素內涵(Factor Content of Trade, FCT)，利用sign test檢測貿易要素內涵假說Vanek prediction，而不同於其他文獻，本文進一步討論貿易要素內涵假說Vanek prediction的sign test檢測結果與產業比例、貿易壁壘、國家地區別等因素之間的關聯性。實證結果為當討論貿易要素內涵時，將勞工要素使用教育程度細分，會與單一勞工要素有不同的影響，而地區的人力資本特性也是影響貿易要素內涵假說檢測結果之因素，美、歐洲相較於亞洲，對於勞工的貿易要素內涵假說檢測結果有正向的影響，區域性之經濟問題與貿易壁壘皆對於檢測結果有負向的影響，而供給面的附加價值中間投入使用量造成貿易要素內涵假說檢測結果正確性影響與預測有些許差異，此外，資本因要素特性移動自由性較高，不受到開放程度、做生意難易程度變數的影響，相反之，開放程度越高以及做生意難易度越容易，皆能增加勞工貿易要素內涵假說檢測結果的正確性；資本只易受到供給面影響，而勞工則供給面及需求面的因素皆會對其貿易要素內涵造成影響。

System identification is used in engineering sciences to build mathematical models from data. A common issue in system identification problems is that the true inputs to the system are not fully known. In this thesis, existing approaches to unknown input problems are classified and some of their properties are analyzed.  A new indirect framework is proposed to treat system identification problems with unknown inputs. The effects of the unknown inputs are assumed to be measured through possibly unknown dynamics. Furthermore, the measurements may also be dependent on other known or measured inputs and can in these cases be called indirect input measurements. Typically, these indirect input measurements can arise when a subsystem of a larger system is of interest and only a limited set of sensors is available. Two examples are when it is desired to estimate parts of a mechanical system or parts of a dynamic network without full knowledge of the signals in the system. The input measurements can be used to eliminate the unknown inputs from a mathematical model of the system through algebraic manipulations. The resulting indirect model structure only depends on known and measured signals and can be used to estimate the desired dynamics or properties. The effects of using the input measurements are analyzed in terms of identifiability, consistency and variance properties. It is shown that cancelation of shared dynamics can occur and that the resulting estimation problem is similar to errors-in-variables and closed-loop estimation problems because of the noisy inputs used in the model. In fact, the indirect framework unifies a number of already existing system identification problems that are contained as special cases. For completeness, an instrumental variable method is proposed as one possibility for estimating the indirect model. It is shown that multiple datasets can be used to overcome certain identifiability issues and two approaches, the multi-stage and the joint identification approach, are suggested to utilize multiple datasets for estimation of models. Furthermore, the benefits of using the indirect model in filtering and for control synthesis are briefly discussed.  To show the applicability, the framework is applied to the roll dynamics of a ship for tracking of the loading conditions. The roll dynamics is very sensitive to changes in these conditions and a worst-case scenario is that the ship will capsize.  It is assumed that only motion measurements from an inertial measurement unit (IMU) together with measurements of the rudder angle are available. The true inputs are thus not available, but the measurements from the IMU can be used to form an indirect model from a well-established ship model. It is shown that only a subset of the unknown parameters can be estimated simultaneously. Data was collected in experiments with a scale ship model in a basin and the joint identification approach was selected for this application due to the properties of the model. The approach was applied to the collected data and gave promising results. / Till skillnad från många andra industrier där avancerade styrsystem har haft en omfattande utveckling under de senaste decennierna så har styrsystem för skepps- och marinindustrin inte alls utvecklats i samma utsträckning. Det är framförallt under de senaste 10 åren som lagkrav och stigande driftskostnader har ökat intresset för effektivitet och säkerhet genom användning av styrsystem. Rederier och den marina industrin är nu intresserade av hur de avancerade styrsystem som används inom andra områden kan tillämpas för marina ändamål. Huvudmålet är typiskt att minska den totala energianvändningen, och därmed också bränsleförbrukningen, genom att hela tiden planera om hur skeppet skall användas med hjälp av ny information samt styra skeppet och dess ingående system på ett sätt som maximerar effektiviteten. För många av dessa avancerade styrsystem är det grundläggande att ha en god förståelse för beteendet hos det systemet som skall styras. Ofta används matematiska modeller av systemet för detta ändamål. Sådana modeller kan skapas genom att observera hur systemet reagerar på yttre påverkan och använda dessa observationer för att finna eller skatta den modell som bäst beskriver observationerna. Observationerna är mätningar som görs med så kallade sensorer och tekniken att skapa modeller från mätningarna kallas för systemidentifiering. Detta är i grunden ett utmanande problem och det kan försvåras ytterligare om de sensorer som behövs inte finns tillgängliga eller är för dyra att installera. I denna avhandling föreslås en ny teknik där de mätningar som finns tillgängliga används på ett nytt och annorlunda sätt. Detta kan minska mängden nödvändiga sensorer eller möjliggöra användandet av alternativa sensorer i modell-framtagningen. Med hjälp av denna nya teknik kan enkla sensorer användas för att skatta en matematisk modell för en del av skeppet på ett sätt som inte är möjligt med traditionella metoder. Genom att skatta denna modell kan fysikaliska egenskaper hos skeppet, så som dess massa och hur massan är fördelad över skeppet, övervakas för att upptäcka förändringar. Just dessa två egenskaper har stor inverkan på hur skeppet beter sig och om skeppet är fellastat kan det i värsta fall kapsejsa. Vetskapen om dessa fysikaliska egenskaper kan alltså utöver effektivisering användas för att varna besättningen eller påverka styrsystemen så att farliga manövrar undviks. För att visa att tekniken fungerar i verkligheten har den använts på mätningar som har samlats in från ett skalenligt modellskepp. Experimenten utfördes i bassäng och resultaten visar att tekniken fungerar. Denna nya teknik är inte specifik för marint bruk utan kan också vara användbar i andra typer av tillämpningar. Även i dessa tillämpningar möjliggörs användandet av färre eller alternativa sensorer för att skatta modeller. Tekniken kan vara speciellt användbar när en modell av ett system eller process som verkar i ett nätverk av många system är av intresse, något som också diskuteras i avhandlingen.

Sugarcane cropping is an important component of the Brazil´s economy. As the main feedstock used to produce ethanol, the area occupied with this crop has meaningfully increased in the last years and continues to expand in order to attend to the national and international demand of this biofuel. Despite that it has been demonstrated that land-use transition into sugarcane can negatively impact the soil carbon (C) dynamics, little is known about the effect of those land use changes (LUC) processes on the distribution of soil organic carbon (SOC) within particle-size classes, and how management practices in sugarcane can contribute to the C restoration. In this sense the main objective of this study was to evaluate through a modelling application the SOC dynamics in the sugarcane crop in response to LUC and different management scenarios. For a better understanding of LUC impact on C content in both particulate organic matter and mineral-associated fraction, we performed physical soil C fractionation in 34 study areas involving the three major land-use systems affected by sugarcane expansion. Also, biometric measurements were executed in sugarcane plant and ratoon crop in order to use those data in the model parameterization as well as to recalculate the payback time of the C debt through C conversion ratio reported in the literature. Finally, we parameterized and validate the CENTURY ecosystem model for sugarcane, pastures and annual cropland by using a data-set previously collected by the Laboratório de Biogeoquímica Ambiental (CENA-USP); then different scenarios of sugarcane management were simulated: i) SC1 - Green harvesting; ii) SC2 - Green harvesting plus organic amendments and iii) Green harvesting + low N inputs. Our results showed that the C content depletion for conversion from native vegetation and pastures to sugarcane is caused by C losses in the labile fraction (37%) as wells as in the stabilized pool associated to the mineral fraction (30%). Above and belowground biomass quantification indicated a total sugarcane carbon inputs ranging from 29.6 Mg C ha-1 to 30.6 Mg C ha-1. Considering a C retention rate of 13% we estimated net carbon changes of 0.58 to 0.6 Mg C ha-1 year-1, which contribute to reduce the payback times for sugarcane biofuel carbon debts in 3.3 and 1.2 years for Cerrado wooded and pasture conversions into sugarcane respectively. The modelling study supported the Century model as a tool to access the SOC dynamics following land-use conversion and different soil management in in sugarcane. Long-term simulations suggested that changes in the sugarcane harvest from burning to green harvesting increase the soil C stock in an average of 0.21 Mg ha-1 year-1; however the potential of C accumulation is still higher when organic amendments as vinasse and filter cake are add to the soil, with mean values varying between 0.34 and 0.37 Mg ha-1 year-1 in SC2 and SC1 respectively. By analyzing the SOC dynamic at each scenario simulated, we estimated a time span of 17 and 24 years for soil C restoration in clay and sandy soils under pastures with priority suitability (SC3). The number of years was projected to be higher in clay soils with regular suitability (40 years). / A cultura da cana-de-açúcar é uma comodity importante para a economia no Brasil. Como a principal matéria prima para a produção de etanol, a área plantada com esta cultura tem incrementado significativamente nos últimos anos e a tendência é de continuar se expandindo para atender a demanda nacional e internacional deste biocombustível. Embora tenha sido demostrado que a mudança de uso da terra (MUT) para cana-de-açúcar pode afetar negativamente a dinâmica do carbono (C) no solo, há pouca informação disponível acerca do impacto dessa MUT na distribuição do C nas frações da matéria orgânica do solo, e como as praticas de manejo da cana-de-açúcar podem contribuir para o acumulo de C no solo. Nesse contexto o principal objetivo desta pesquisa foi avaliar, através da modelagem matemática, a dinâmica do carbono orgânico do solo (COS) na cultura da cana-de-açúcar em resposta a mudança de uso da terra e diferentes cenários de manejo agrícola. Fracionamento físico para separar o C associado à matéria orgânica partícula (POM) do C ligado à fração mineral do solo (<53 um) foi realizado em amostras de solo de 34 áreas de estudo envolvendo os três principais sistemas de uso da terra afetados pela expansão da cana-de-açúcar. Adicionalmente, foram realizadas avaliações biométricas da cana-de-açúcar (cana planta e soca) que objetivaram a parametrização do modelo matemático assim como recalcular o tempo de reposição do debito de C gerado. Finalmente, o modelo CENTURY foi parametrizado e devidamente validado, para posteriormente proceder à simulação de diferentes cenários futuros de manejo da cana de açúcar: i) SC1 - Colheita de cana crua (sem queima); ii) SC2 - Colheita de cana crua e adição de adubos orgânicos (vinhaça e torta de filtro); iii) Colheita de cana crua e redução da adubação nitrogenada. Os resultados indicaram que a redução do conteúdo de C devido à conversão de vegetação nativa e pastagem para cana-de-açúcar foi causada pela perda de C tanto na fração lábil (37%) quanto na fração mais estável associada a fração mineral do solo (30%). A quantificação da biomassa aérea e radicular indicou entradas de C variando de 29,6 Mg C ha-1 a 30,6 Mg C ha-1, os quais resultariam em uma taxa de acumulo liquido de 0,58 a 0,6 Mg C ha-1 ano-1, que quando considerado contribui a redução do \"payback time\" do debito de C do etanol causado pela conversão de Cerrado e pastagem em 3,3 e 2 anos respectivamente. Os resultados obtidos no estudo de modelagem matemática suportaram o uso do modelo CENTURY como uma ferramenta para avaliar a influencia da MUT e das práticas de manejo na dinâmica do COS. As simulações em longo prazo sugeriram que a supressão da queima na colheita incrementa o estoque de C em 0,21 Mg ha-1 ano-1. No entanto o potencial de acúmulo de C é ainda maior quando adubação orgânica é realizada, com valores entre 0,34 e 0,37 Mg ha-1 ano-1 respectivamente. A análise da dinâmica do COS em cada cenário de manejo simulado permitiu estimar o tempo médio de recuperação do C do solo perdido pela MUT em áreas de pastagens. Os resultados indicaram um período de 17 anos para condições de cultivo sob solos argilosos e 24 anos para solos arenosos (SC3) em áreas de alta aptidão para expansão. O modelo projetou um maior número de anos em solo argiloso sob áreas de pastagem com aptidão média (40 anos).

Dans un modèle qui peut s'avérer complexe et fortement non linéaire, les paramètres d'entrée, parfois en très grand nombre, peuvent être à l'origine d'une importante variabilité de la sortie. L'analyse de sensibilité globale est une approche stochastique permettant de repérer les principales sources d'incertitude du modèle, c'est-à-dire d'identifier et de hiérarchiser les variables d'entrée les plus influentes. De cette manière, il est possible de réduire la dimension d'un problème, et de diminuer l'incertitude des entrées. Les indices de Sobol, dont la construction repose sur une décomposition de la variance globale du modèle, sont des mesures très fréquemment utilisées pour atteindre de tels objectifs. Néanmoins, ces indices se basent sur la décomposition fonctionnelle de la sortie, aussi connue soue le nom de décomposition de Hoeffding. Mais cette décomposition n'est unique que si les variables d'entrée sont supposées indépendantes. Dans cette thèse, nous nous intéressons à l'extension des indices de Sobol pour des modèles à variables d'entrée dépendantes. Dans un premier temps, nous proposons une généralisation de la décomposition de Hoeffding au cas où la forme de la distribution des entrées est plus générale qu'une distribution produit. De cette décomposition généralisée aux contraintes d'orthogonalité spécifiques, il en découle la construction d'indices de sensibilité généralisés capable de mesurer la variabilité d'un ou plusieurs facteurs corrélés dans le modèle. Dans un second temps, nous proposons deux méthodes d'estimation de ces indices. La première est adaptée à des modèles à entrées dépendantes par paires. Elle repose sur la résolution numérique d'un système linéaire fonctionnel qui met en jeu des opérateurs de projection. La seconde méthode, qui peut s'appliquer à des modèles beaucoup plus généraux, repose sur la construction récursive d'un système de fonctions qui satisfont les contraintes d'orthogonalité liées à la décomposition généralisée. En parallèle, nous mettons en pratique ces différentes méthodes sur différents cas tests. / A mathematical model aims at characterizing a complex system or process that is too expensive to experiment. However, in this model, often strongly non linear, input parameters can be affected by a large uncertainty including errors of measurement of lack of information. Global sensitivity analysis is a stochastic approach whose objective is to identify and to rank the input variables that drive the uncertainty of the model output. Through this analysis, it is then possible to reduce the model dimension and the variation in the output of the model. To reach this objective, the Sobol indices are commonly used. Based on the functional ANOVA decomposition of the output, also called Hoeffding decomposition, they stand on the assumption that the incomes are independent. Our contribution is on the extension of Sobol indices for models with non independent inputs. In one hand, we propose a generalized functional decomposition, where its components is subject to specific orthogonal constraints. This decomposition leads to the definition of generalized sensitivity indices able to quantify the dependent inputs' contribution to the model variability. On the other hand, we propose two numerical methods to estimate these constructed indices. The first one is well-fitted to models with independent pairs of dependent input variables. The method is performed by solving linear system involving suitable projection operators. The second method can be applied to more general models. It relies on the recursive construction of functional systems satisfying the orthogonality properties of summands of the generalized decomposition. In parallel, we illustrate the two methods on numerical examples to test the efficiency of the techniques.