Cílem mé disertační práce je analyzovat a vyvinout parametrizační metodu pro 2D a 3D tvarové optimalizace v kontextu průmyslového aerodynamického návrhu letounu založeném na CFD simulacích. Aerodynamická tvarová optimalizace je efektivní nástroj, který si klade za cíl snížení nákladů na návrh letounů. Nástroj založený na automatickém hledání optimálního tvaru. Klíčovou částí úspěšného optimalizačního procesu je použití vhodné parametrizační metody, metody schopné garantovat možnost dosažení optimálního tvaru. Parametrizační metody obecně používané v oblasti aerodynamické tvarové optimalizace momentálně nejsou připravený na komplikované průmyslové aplikace vyskytující se u moderních dopravních letounů, které mají šípová zalomená křídla s winglety a motorovými gondolami, přechodové prvky spojující např. trup s křídlem atd.. Existuje tedy potřeba nalezení obecné parametrizační metody, která bude aplikovatelná na širokou škálu různých geometrických tvarů. Free-Form Deformation (FFD[1]) parametrizace může, vzhledem ke svým schopnostem při zacházení s geometrií, být odpovědí na tuto potřebu. Adaptivní parametrizace by se měla být schopna automaticky přizpůsobit danému tvaru tak, aby byly její kontrolní body vhodně rozmístěny. Což umožní dostatečnou kontrolu deformací objektu, která zaručí možnost vytvoření optimálního tvaru objektu a splnění geometrických omezení. Primární aplikací takové parametrizační metody je deformace tvaru objektu. Dalším navrhovaným cílem je modifikace FFD parametrizační metody pro současné deformace tvaru objektu a CFD výpočetní sítě, umožnující velké deformace objektu při zachování kvality výpočetní sítě.

京都大学 / 0048 / 新制・論文博士 / 博士(理学) / 乙第13108号 / 論理博第1556号 / 新制||理||1620(附属図書館) / (主査)准教授 重 尚一, 教授 余田 成男, 教授 石川 裕彦 / 学位規則第4条第2項該当 / Doctor of Science / Kyoto University / DGAM

Turbulence is important since it affects the exchange of momentum, heat, and trace gases between the atmosphere and the ocean. However, measuring oceanic turbulence is not straightforward and that is why parameterizations that describe turbulence events are important. In this thesis turbulence data from the Baltic Sea is investigated and compared to already existing parameterizations.  The thesis considers turbulence in the ocean surface boundary layer (OSBL) and how atmospheric parameters act as driving mechanisms. Turbulence creates mixing that enables the dispersion of various particles and a more efficient gas transfer at the air-sea interface. This thesis aimed to investigate the connection between the drivers of oceanic turbulence, wind, waves, and buoyancy fluxes and how they contribute to the formation of enhanced turbulence events. To investigate this, turbulence data from the Baltic Sea from June to August 2020, collected by an ADCP (Acoustic Doppler Current Profiler), was used to find connections to meteorological data during the same time period. Since turbulence is difficult to measure, three already existing parameterizations were compared to the observed turbulence to investigate their performance. The results showed that conditions with higher wind speeds with corresponding waves gave a better correlation between surface turbulence and wind and waves. The parameterization that included wind and waves gave results closest to the observed turbulence at the surfaces, compared to when only wind shear was included. It was also detected that the parameterized turbulence was in almost all cases under-predicted in comparison to the observed turbulence. To clarify why this is the case, a more detailed analysis would be needed to find what parameters are missing for better predictions of the surface turbulence.

Grasslands cover 40% of the earth’s land area and provide numerous valuable ecosystem services. However, climate change, global land use change and increasing intensive anthropogenic interventions make grasslands to one of the most endangered ecosystem types in the world. Effective protection in the future requires a fundamental understanding of the dynamics of grasslands and their major drivers. Field experiments have been conducted for impact analyses, for example, with different management intensities, plant community composition and altered climatic conditions. Complementary, ecological models allow to extend the analysis to long-term effects of changes as well as to a deeper understanding of the underlying ecological processes. In this thesis, an individual-based grassland model and network science were applied to understand the community structure and dynamics emerging from individual plant interactions – in relation to plant traits, ecological processes, environmental and anthropogenic impacts, and the small-scale spatial distribution of plants. In the first study, an individual-based process-oriented grassland model was parameterized to simulate field data of a local biodiversity experiment using the concept of plant functional types. The influence of various functional plant traits and ecological processes on grassland productivity and functional composition were analyzed. Different functional plant traits showed partly contrasting effects on plant growth. With regard to the modeled ecological processes, competition for space between plants affected grassland productivity more than shading of plants. In the second study, the parameterized grassland model was used to analyze the impact of functional diversity, mowing frequency and air temperature on ecological processes that lead to changes in grassland productivity. The model reproduced the increase of biomass yields with functional diversity as observed in the field experiment. Modeled plant competition for space showed to be the dominant process and was responsible for an increase in biomass yields in more frequently mown grasslands. In the third study, an approach to generate a regionally transferable parameterization of the grassland model is presented. The impact of management, environment and climate change on productivity and functional composition of grasslands was analyzed within a German-wide scenario analysis. Management intensity had more influence on grassland productivity than environmental factors and correlations of productivity with environmental factors become stronger in less managed grasslands. Climate change showed to have only a minor influence on simulated vegetation attributes. In the fourth study, network science was applied to forest megaplots to quantify the spatial neighborhood structure of species-rich ecosystems. Networks at the individual-tree and tree-species levels revealed similar structures at three investigated forest sites. Tropical tree species coexisted in small-scale networks and only up to 51% of all possible connections between species pairs were realized. A null community analysis showed that details on the tree position and tree size have no major influence on the network structures identified. In summary, this thesis presents the development of advanced methods and analysis tools as well as their application to vegetation ecosystems with high diversity. Thereby, complex structures and dynamics of ecological systems could be systematically explored by combining ecological models with extensive field measurements.

As a conventional transportation modality, bicycles have been gradually electrified to meet the desire for convenient and green commuting patterns, especially in developed urban areas. The electric bicycle battery pack and its management system are core elements that determine key performance metrics such as electric range and output power. With respect to electric bicycle applications, focused research on the battery, its management system, and performance has received less attention compared to other energy storage applications. In this thesis, a well-developed conversion kit produced by BionX is studied. A data collecting system is first installed to record both mechanical and electrical data, such as speed, power and voltage; this enables defining two standard riding cycles at different riding conditions. Two benchmarking tests are performed to investigate the battery life in pure electric mode and at different threshold levels of optimal assistance. A novel quadratic programming based fitting algorithm is derived and applied in both time and frequency domain parameter identification tests. The proposed algorithm is able to fit single/multiple pulses by applying a masking vector. Sensitivity study and experimental results show the high robustness and fast computation time of the approach compared to existing and commonly used methods, such as fmincon. The comparison between hybrid power pulse characterization (HPPC) and electrochemical impedance spectrum (EIS) tests are performed in terms of extracted internal resistance. A second-order RC battery model is developed using parameters extracted from HPPC tests. The model is validated by experimental riding cycles and used to generate the reference SOC profiles that are employed in a SOC estimation study. Four estimation strategies, including extended Kalman Filter (EKF), Sigma point Kalman Filter (SPKF), Cubature Kalman Filter (CKF), and joint extended Kalman Filter (JEKF), are compared systematically in terms of accuracy, robustness and computation complexity. / Thesis / Master of Applied Science (MASc)

Yes

In this work, the development of parameters for a series of imidazolium-based ionic liquids molecules, now included in the AMOEBA force field, is discussed. The quality of obtained parameters is tested in a variety of calculations to reproduce structural, thermodynamic, and transport properties. First, it is proposed a novel method to parameterize in a faster, and more efficient way parameters for the AMOEBA force field that can be applied to any imidazolim-based cation. Second, AMOEBA-IL polarizable force field is applied to study the N-tert-butyloxycarbonylation of aniline reaction mechanism in water/[EMIM][BF4] solvent via QM/MM approach and compared with the reaction carried out in gas-phase and implicit solvent media. Third, AMOEBA-IL force field is applied in alchemical calculations. Free energies of solvation for selected solutes solvated in [EMIm][OTf] are calculated via BAR method implemented in TINKER considering the effect of polarization as well as the methodology to perform the sampling of the alchemical process. Finally, QM/MM calculations using AMOEBA to get more insights into the catalytic reaction mechanism of horseradish peroxidase enzyme, particularly the structures involved in the transition from Cp I to Cp II.

Computational fluid dynamics (CFD) modeling is possibly the best available technique in designing and predicting the performance of Stirling and pulse tube refrigerators (PTR). One of the limitations of CFD modeling of these systems, however, is that it requires closure relations for the micro porous materials housed within their regenerators and heat exchangers. Comprehensive prediction of fluid-solid interaction through this media can be obtained only by direct pore level simulation, a process which is time consuming and impractical for system level examination. Through the application of empirical correlations including the Darcy permeability and Forchheimer's inertial coefficient, the microscopic momentum equations governing fluid behavior within the porous structure can be recast as viable macroscopic governing equations. With these constitutive relationships, CFD can be an efficient and powerful tool for system modeling and optimization. The purpose of this study is to determine the hydrodynamic parameters of two mesh fillers relevant to miniature PTRs; stacked screens of 635 mesh stainless steel and 325 mesh phosphor-bronze wire cloth. Experimental setups were designed and fabricated to measure steady and oscillatory pressures and mass flow rates of the working fluid, research-grade helium. Hydrodynamic parameters for the two mesh fillers were determined for steady-state and steady periodic flow in both the axial and radial directions for a range of flow rates, operating frequencies and charge pressures. The effect of average pressure on the steady axial flow hydrodynamic parameters of other common PTR filler materials was also investigated. The determination of sample hydrodynamic parameters and their subsequent computational and experimental methodologies utilized are explained.

No description available.

Energy consumption has increased drastically during the last century. Currently, the worldwide energy consumption is about 17.4 TW and is predicted to reach 25 TW by 2035. Solar energy has emerged as one of the potential renewable energy sources. Since its first physical recognition in 1887 by Adams and Day till nowadays, research in solar energy is continuously developing. This has lead to many achievements and milestones that introduced it as one of the most reliable and sustainable energy sources. Recently, the International Energy Agency declared that solar energy is predicted to be one of the major electricity production energy sources by 2035. Enhancing the efficiency and lifecycle of photovoltaic (PV) modules leads to significant cost reduction. Reducing the temperature of the PV module improves its efficiency and enhances its lifecycle. To better understand the PV module performance, it is important to study the interaction between the output power and the temperature. A model that is capable of predicting the PV module temperature and its effects on the output power considering the individual contribution of the solar spectrum wavelengths significantly advances the PV module designs toward higher efficiency. In this work, a thermoelectrical model is developed to predict the effects of the solar spectrum wavelengths on the PV module performance. The model is characterized and validated under real meteorological conditions where experimental temperature and output power of the PV module measurements are shown to agree with the predicted results. The model is used to validate the concept of active optical filtering. Since this model is wavelength-based, it is used to design an active optical filter for PV applications. Applying this filter to the PV module is expected to increase the output power of the module by filtering the spectrum wavelengths. The active filter performance is optimized, where different cutoff wavelengths are used to maximize the module output power. It is predicted that if the optimized active optical filter is applied to the PV module, the module efficiency is predicted to increase by about 1%. Different technologies are considered for physical implementation of the active optical filter.