Thesis deals with problems about areas of a non-assembling diagnostics namely resonant adhesive tester according to an EUSAMA methodology. Result of the methodology is a technical condition examination of dampers. However with regard to testing of whole suspension and damping vehicle system are results distorted by influence of testing conditons and another vehical components. Goal of thesis is analysis limits of practical use resonant adhesive tester for a quality checking of mount wheels damping. Problems are solved by a virtual simulation in a program Adams/View where is created a real model of vehical axle of Skoda Roomster TDI 1.4. In the model is consequently simulated possible functional characteristics and abrasions of single components which influence the methodology. Virtual model will be using for research activity of Institute of machine and industrial design Faculty of mechanical ingeneering Brno University of technology.

The diploma thesis is focused on create an optimization methodology for CFD issues or any other computationally demanding software. Optimization method is applied on simplified model of car, where improves its aerodynamic properties

Les eaux souterraines constituent une réserve d’eau potable non négligeable, leur alimentation se fait en majeure partie par les précipitations, appelée recharge des nappes. Du fait de leur grande importance, la compréhension du fonctionnement de ces ressources en eau est plus que jamais indispensable. Celle-ci passe par l’élaboration de modèles mathématiques. Ces outils nous offrent une meilleure appréhension et une bonne prévision des phénomènes physiques. Les systèmes hydrogéologiques sont généralement très complexes et caractérisés par des dynamiques hydriques très variables dans le temps et dans l’espace. Cette complexité a attiré l’attention de nombreux hydrogéologues et un grand nombre de modèles très sophistiqués a été développé afin de décrire ces systèmes avec précision. Cependant, la prise en compte de la recharge de ces réservoirs reste toujours un défi dans la modélisation hydrogéologique. En effet, le plus souvent, les modèles hydrogéologiques simulent l’écoulement dans la nappe tout en considérant la recharge comme une constante sur le domaine et indépendante du système. De plus, elle est souvent calculée de façon simplifiée. Or, la recharge traduisant la quantité des précipitations atteignant les nappes est une composante hydrologique complexe et variable car elle interagit avec les nappes et dépend des conditions climatiques, du couvert végétal et du transfert de l’eau dans le sol. Ce présent travail vise à intégrer cette recharge variable et complexe aux modèles hydrogéologiques. À cet effet, un modèle couplé a été développé. Une première partie de ce modèle permet de calculer la recharge des nappes en modélisant les interactions précipitations-sol et l’hydrodynamique dans le sol. Cette modélisation a été effectuée en utilisant des modèles conceptuels simples basés sur des lois empiriques (Gardénia, Nash) et des modèles physiques résolvant l’équation de Richards. La recharge ainsi calculée est intégrée à la deuxième partie du modèle simulant l’hydrodynamique dans les nappes décrite par l’équation de diffusivité. Des méthodes numériques précises et robustes ont été utilisées pour résoudre les équations du modèle mathématique : les éléments finis non conformes ont été utilisés pour résoudre l’équation de diffusivité et l’équation de Richards est résolue sous sa forme mixte par une méthode itérative en temps. En somme, ce modèle couplé permet de décrire les variations de niveaux de nappe à partir des données météorologiques connaissant les paramètres caractéristiques de cet aquifère. [...] / Groundwater is the main available water resource for many countries; they are mainly replenished by water from precipitation, called groundwater recharge. Due to its great importance, management of groundwater resources is more essential than ever, and is achieved through mathematical models which offer us a better understanding of physical phenomena as well as their prediction. Hydrogeological systems are generally complex thus characterized by a highly variable dynamic over time and space. These complexities have attracted the attention of many hydrogeologists and many sophisticated models that can handle these issues and describe these systems accurately were developed. Unfortunately, modeling groundwater recharge is still a challenge in groundwater resource management. Generally, groundwater models are used to simulate aquifers flow without a good estimation of recharge and its spatial-temporal distribution. As groundwater recharge rates show spatial-temporal variability due to climatic conditions, land use, and hydrogeological heterogeneity, these methods have limitations in dealing with these characteristics. To overcome these limitations, a coupled model which simulates flow in the unsaturated zone and recharge as well as groundwater flow was developed. The flow in the unsaturated zone is solved either with resolution of Richards equation or with empirical models while the diffusivity equation governs flow in the saturated zone. Robust numerical methods were used to solve these equations: we apply non-conforming finite element to solve the diffusivity equation and we used an accurate and efficient method for solving the Richards equation. [...]

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<p>Drainage water recycling (DWR) is the practice of capturing, storing, and reusing subsurface drained agricultural water to support supplemental irrigation and has recently been proposed as a practice for improving the crop production and water quality performance in the tile-drained landscape of the U.S. Midwest. This study describes the development of a modeling framework to quantify the potential irrigation and water quality benefits of DWR systems in tile-drained landscapes and the application of the model using ten years of measured weather, tile drain flow and nutrient concentrations, water table, and soil data from two sites in the U.S. Midwest. From this modeling framework, the development and testing of an open-source online tool is also presented.</p><p></p><p>A spreadsheet model was developed to track water flows between a reservoir and drained and irrigated field area at each site. The amount of tile drain flow and associated nutrient loads that could be captured from the field and stored in the reservoir was estimated to calculate the potential water quality benefits of the system. Irrigation benefits were quantified based on the amount of applied irrigation annually. A reservoir size representing 6% to 8% of the field area with an average depth of 3.05 m was sufficient in meeting the annual irrigation requirements during the 10-year period at each site. At this reservoir size, average annual nitrate-N loads were reduced by 20% to 40% and soluble reactive phosphorus loads by 17% to 41%. Variability in precipitation within and across years, and differences in soil water characteristics, resulted in a wide range of potential benefits at the two sites.</p><p>An online tool was developed from the model, and a variance-based global sensitivity analysis was conducted to determine influential and low-sensitivity input parameters. The input parameter, depth of root zone, was the most influential input parameter suggesting that the estimation of total available water for the field water balance is a critical component of the model. Input settings describing the irrigation management and crop coefficients for the initial establishment and mid-season crop growth periods were also influential in impacting the field water balance. Reservoir seepage rate was influential in regard to the reservoir water balance, particularly at larger reservoir sizes. Sensitivity analysis results were used to develop a user-interface for the tool, Evaluating Drainage Water Recycling Decisions (EDWRD).</p><p>This study shows that DWR is capable of providing both irrigation and water quality benefits in the tile-drained landscape of the U.S. Midwest. The developed modeling framework supports future research on the development of strategies to implement and manage DWR systems, and the online tool serves as a resource for users to increase their awareness and understanding of the potential benefits of this novel practice.</p><p></p>

<div>Excessive deformation and stress of skin following reconstructive surgery plays a crucial role in wound healing, often leading to complications. Yet, despite of this concern, surgeries are still planned and executed based on each surgeon's training and experience rather than quantitative engineering tools. The limitations of current treatment planning and execution stem in part from the difficulty in predicting the mechanical behavior of skin, challenges in directly measuring stress in the operating room, and inability to predict the long term adaptation of skin following reconstructive surgery. Computational modeling of soft tissue mechanics has emerged as an ideal candidate to determine stress contours over sizable skin regions in realistic situations. Virtual surgeries with computational mechanics tools will help surgeons explore different surgeries preoperatively, make prediction of stress contours, and eventually aid the surgeon in planning for optimal wound healing. While there has been significant progress on computational modeling of both reconstructive surgery and skin mechanical and mechanobiological behavior, there remain major gaps preventing computational mechanics to be widely used in the clinical setting. At the preoperative stage, better calibration of skin mechanical properties for individual patients based on minimally invasive mechanical tests is still needed. One of the key challenges in this task is that skin is not stress-free in vivo. In many applications requiring large skin flaps, skin is further grown with the tissue expansion technique. Thus, better understanding of skin growth and the resulting stress-free state is required. The other most significant challenge is dealing with the inherent variability of mechanical properties and biological response of biological systems. Skin properties and adaptation to mechanical cues changes with patient demographic, anatomical location, and from one individual to another. Thus, the precise model parameters can never be known exactly, even if some measurements are available. Therefore, rather than expecting to know the exact model describing a patient, a probabilistic approach is needed. To bridge the gaps, this dissertation aims to advance skin biomechanics and computational mechanics tools in order to make virtual surgery for clinical use a reality in the near future. In this spirit, the dissertation constitutes three parts: skin growth and its incompatibility, acquisition of patient-specific geometry and skin mechanical properties, and uncertainty analysis of virtual surgery scenarios.</div><div>Skin growth induced by tissue expansion has been widely used to gain extra skin before reconstructive surgery. Within continuum mechanics, growth can be described with the split of the deformation gradient akin to plasticity. We propose a probabilistic framework to do uncertainty analysis of growth and remodeling of skin in tissue expansion. Our approach relies on surrogate modeling through multi-fidelity Gaussian process regression. This work is being used calibrate the computational model against animal model data. Details of the animal model and the type of data obtained are also covered in the thesis. One important aspect of the growth and remodeling process is that it leads to residual stress. It is understood that this stress arises due to the nonhomogeneous growth deformation. In this dissertation we characterize the geometry of incompatibility of the growth field borrowing concepts originally developed in the study of crystal plasticity. We show that growth produces unique incompatibility fields that increase our understanding of the development of residual stress and the stress-free configuration of tissues. We pay particular attention to the case of skin growth in tissue expansion.</div><div>Patient-specific geometry and material properties are the focus on the second part of the thesis. Minimally invasive mechanical tests based on suction have been developed which can be used in vivo, but these tests offer only limited characterization of an individual's skin mechanics. Current methods have the following limitations: only isotropic behavior can be measured, the calibration problem is done with inverse finite element methods or simple analytical calculations which are inaccurate, the calibration yields a single deterministic set of parameters, and the process ignores any previous information about the mechanical properties that can be expected for a patient. To overcome these limitations, we recast the calibration problem in a Bayesian framework. To sample from the posterior distribution of the parameters for a patient given a suction test, the method relies on an inexpensive Gaussian process surrogate. For the patient-specific geometry, techniques such as magnetic resonance imaging or computer tomography scans can be used. Such approaches, however, require specialized equipment and set up and are not affordable in many scenarios. We propose to use multi-view stereo (MVS) to capture patient-specific geometry.</div><div>The last part of the dissertation focuses on uncertainty analysis of the reconstructive procedure itself. To achieve uncertainty analysis in the clinical setting we propose to create surrogate and reduced order models, especially principal component analysis and Gaussian process regression. We first show the characterization of stress profiles under uncertainty for the three most common flap designs. For these examples we deal with idealized geometries. The probabilistic surrogates enable not only tasks such as fast prediction and uncertainty quantification, but also optimization. Based on a global sensitivity analysis we show that the direction of anisotropy of skin with respect to the flap geometry is the most important parameter controlled by the surgeon, and we show hot to optimize the flap in this idealized setting. We conclude with the application of the probabilistic surrogates to perform uncertainty analysis in patient-specific geometries. In summary, this dissertation focuses on some of the fundamental challenges that needed to be addressed to make virtual surgery models ready for clinical use. We anticipate that our results will continue to shape the way computational models continue to be incorporated in reconstructive surgery plans.</div>

The main purpose of this dissertation is to investigate directional constraint qualifications and necessary optimality conditions for nonsmooth set-constrained mathematical programs. First, we study sufficient conditions for metric subregularity of the set-constrained system. We introduce the directional version of the quasi-/pseudo-normality as a sufficient condition for metric subregularity, which is weaker than the classical quasi-/pseudo-normality, respectively. Then we apply our results to complementarity and Karush-Kuhn-Tucker systems. Secondly, we study directional optimality conditions of bilevel programs. It is well-known that the value function reformulation of bilevel programs provides equivalent single-level optimization problems， which are nonsmooth and never satisfy the usual constraint qualifications such as the Mangasarian-Fromovitz constraint qualification (MFCQ). We show that even the first-order sufficient condition for metric subregularity (which is generally weaker than MFCQ) fails at each feasible point of bilevel programs. We introduce the directional Clarke calmness condition and show that under the directional Clarke calmness condition, the directional necessary optimality condition holds. We perform directional sensitivity analysis of the value function and propose the directional quasi-normality as a sufficient condition for the directional Clarke calmness. / Graduate / 2021-07-07

’Flight’ is a program that uses flight mechanics to estimate the flight range of birds. This program, used by ornithologists, is only available for Windows OS. It requires manual imputation of body measurements and constants (one observation at a time) and this is time-consuming. Therefore, the first task is to implement the methods in R, a programming language that runs on various platforms. The resulting package named flying, has three advantages; first, it can estimate flight range of multiple bird observations, second, it makes it easier to experiment with different settings (e.g. constants) in comparison to Flight and third, it is open-source making contribution relatively easy. Uncertainty and global sen- sitivity analyses are carried out on body measurements separately and with various con- stants. In doing so, the most influential body variables and constants are discovered. This task would have been near impossible to undertake using ’Flight’. A comparison is made amongst the results from a crude partitioning method, generalized additive model, gradi- ent boosting machines and quasi-Monte Carlo method. All of these are based on Sobol’s method for variance decomposition. The results show that fat mass drives the simulations with other inputs playing a secondary role (for example mechanical conversion efficiency and body drag coefficient).

Nordost om Uppsala finns sedan 1977 en av Uppsala Vatten och Avfall AB:s mindre grundvattentäkter, och inför en tillståndsansökan om ett ökat vattenuttag behöver den befintliga kunskapen om täkten utökas. Syftet med detta arbete är att ta fram en modell för att undersöka storleken på ett hållbart vattenuttag, om enskilda avlopp kan ligga bakom mikrobiella föroreningar i vattnet och om en alternativ placering av brunnen i så fall skulle åtgärda problemet. Sveriges Geologiska Undersökning har beräknat formen på grundvattenmagasinet och dess tillrinningsområde, ett område som består av en flack lertäckt dal omgiven av morän och berg. På 1960- och 1970-talen undersöktes området med slagsondering och rörsättning tillsammans med provpumpning, vilket lade grunden för detta examensarbete. I början av arbetet genomfördes ytterligare sonderingar och rördrivningar följt av en fyra veckor lång provpumpning vars resultat användes för att kalibrera modellen. Denna modell byggdes i programmet FEFLOW som använder sig av finita element för att lösa ekvationer som beskriver flöde i porösa media. Modellen byggdes upp av lager som motsvarade jordlagerföljden, där markytan baserades på Lantmäteriets nationella höjdmodell. Bergytan och gränsen mellan friktionsmaterial och lera togs fram genom interpolering av sonderingsdata. Ytterligare vertikal uppdelning skedde utifrån jordarter och magasinform. Värden på hydraulisk konduktivitet, vattenavgivningstal och grundvattenbildning i lagren togs fram genom en litteraturstudie. Dessa parametervärden kalibrerades sedan med hjälp av mätvärden från provpumpningen, följt av en känslighetsanalys. Ett tak för storleken på ett hållbart uttag beräknades utifrån grundvattenbildningen tillsammans med areorna för jordarterna i området. Påverkansområden modellerades för det nuvarande uttaget och två hypotetiska uttag. För det nuvarande uttaget undersöktes den kortaste transporttiden från det närmast liggande bostadsområdet till dricksvattenbrunnen. Med grundvattenbildningen från den kalibrerade modellen blev taket för vattenuttaget 3 L/s, med initialvärdena blev taket i stället 4 L/s. Dessa värden är sannolikt underskattningar då den verkliga grundvattenbildningen troligtvis är högre. De beräknade påverkansområdena indikerar platser för närmare undersökning i framtiden. Det befintliga uttaget på 1,3 L/s hade pågått under lång tid utan kända negativa konsekvenser, och ligger därför sannolikt under gränsen för ett hållbart uttag. I modellen var transporttiden mellan bostadsområde och brunn dubbelt så lång som Havs- och vattenmyndighetens rekommendation. Modellen kan därför inte styrka att de mikrobiella föroreningarna skulle komma från enskilda avlopp, och någon alternativ brunnsplacering undersöktes därför inte närmare. / The Lejsta well field, located northeast of Uppsala, has supplied public drinking water since 1977 and is managed today by Uppsala Water and Waste AB. Further investigation of the aquifer is needed in preparation for increasing withdrawal of groundwater and application for required permits. The purpose of this thesis is to develop a model for investigating the size of a sustainable water yield, whether individual sewage treatment may be the source of microbial contaminants in the water and if an alternative location of the well would solve that problem. The Geological Survey of Sweden previously delineated the aquifer and its catchment basin, the basin consisting of a flat clay-covered valley surrounded by till and bedrock. In the 1960s and 70s the area was surveyed using test drilling and installation of observation wells combined with pumping tests, which laid the groundwork for this thesis. At the beginning of the project, further test drillings and installations of observation wells were carried out followed by a four-week pumping test, the result of which was used to calibrate the model. This model was built in the program FEFLOW which uses finite element analysis to solve equations for flow in porous media. The model was constructed with layers corresponding to the soil layer sequence where the ground surface was based on the Swedish Mapping, Cadastral and Land Registration Authority’s national height model. The bedrock surface and the boundary between clay and coarser material were constructed by interpolating borehole data. The layers were further divided vertically based on soil types and the aquifer delineation. Values for hydraulic conductivity, specific yield, and groundwater recharge in the layers were decided based on a literature review. These parameter values were then calibrated using measurements retrieved from the pumping test, followed by a sensitivity analysis. A limit for the size of a sustainable yield was calculated based on groundwater recharge and the areas of the different soil types. Areas of impact were modeled for the current yield and two hypothetical yields. For the current withdrawal, the shortest transport time from the nearest residential area to the drinking water well was examined. When applying the groundwater recharge of the calibrated model, the water yield limit was 3 L/s, for the initial values the limit was 4 L/s. These values are likely underestimations as the actual groundwater recharge is likely higher. The estimated areas of impact indicate locations for closer examination in the future. The current withdrawal of 1.3 L/s had been sustained without any apparent negative consequences and is therefore likely below the limit of a sustainable yield. According to the model, the shortest transport time from the residential area to the well was twice the minimum time recommended by the Swedish Agency for Marine and Water Management. The model therefore cannot support that individual sewage treatment is the source of microbial contaminants, and no alternative well location was investigated.

Real estate development investment requires a large capital funding but it has slow payback with many risks and uncertainties in the investment. The current approach by using NPV to evaluate this type of investment is not adequate anymore. This is because NPV does not thoroughly capture the uncertainties in the investment and the method ignores the management flexibility whether to postpone or abandon the project in the future. An alternative approach that addresses these issues is to use real options to evaluate this type of investment. The thesis uses the real option model that was proposed by McDonald and Siegel (1986) to evaluate real estate development investment. The model captures value and cost uncertainty in the investment and considers that managements have the flexibility to defer the investment into the future. The thesis analyzes the model critically by sensitivity analyses and shows that using the model requires the input parameters to be carefully determined, especially the ones that relate to unit rental rate.  Furthermore, the paper uses Monte Carlo simulation to determine the optimal ratio between value and cost which suggests that the investment should be deferred or invested now. The result shows that, in general, a real estate project should be invested when the value of the project doubles the cost. Also, the result from the simulation allows investors to adjust the ratio according to their risk behavior. Lastly, the thesis performs another Monte Carlo simulation in order to quantitatively identify the effect of the real option model on the investment decision. The result shows that using only the traditional NPV to evaluate the investment can lead to the wrong investment decision more than 90% of the time. Therefore, using both real options and NPV together can improve investment decisions on the real estate development project.