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In a pressurized water reactor (PWR), pressurized water flows over fuel rods containing radioactive uranium. Potential failure of these nuclear fuel rods is a primary concern, as fuel rod failure typically results in power generation losses and reactor downtime. Thermal parameters such as critical heat flux have traditionally been utilized as performance metrics to ensure that the reactor core remains stable even during failure events. Recently, fuel leaking events have occurred which have resulted in excess debris buildup on fuel rods and fuel grid array mixing devices. Understanding the flow field surrounding these nuclear fuel rods is critical in predicting where crud could deposit. Although CFD simulations have been conducted to characterize the fluid flow around fuel rod bundles, limited experimental data characterizing the mechanics of this fluid flow exists in the current literature. This study will present experimental data collected detailing the fluid flow around a rod bundle geometry using a novel matched refractive index particle tracking velocimetry (PTV) technique over a 3D volume cross section of a prototypical nuclear fuel rod bundle. Velocimetry tracking will be performed in order to characterize the mechanics of the fluid flow. Using optical distortion mitigation techniques and various image processing methods, data from multiple cameras was used to assemble 3-dimensional velocity information of a turbulent fluid region. Results are compared to the solution of a k-epsilon unsteady RANS numerical simulation.

A particle tracking velocimetry (PTV) system is used to investigate the turbulent properties at the free surface of shallow shear flows and a shallow vortex street (VS) wake flow. The resolution of the PTV system enables information to be gathered regarding the large-scale turbulent structure of these flows, and also enables analysis to proceed in both the temporal and spatial domains. Statistical tools such as the probability density function (PDF), autocorrelation and power spectral density (PSD) are utilised to characterise the turbulent properties at the flow surface. Two supercritical flows and one subcritical shallow shear flow are analysed. Taylor's frozen turbulence hypothesis is shown to be valid for these flows, and the integral length scales indicate that 2D isotropic structures with scales larger than the flow depth are present at the free surface. Such large-scale structures at the free surface are consistent with observations from dye visualisation experiments and with "spiral eddies" identified by Kumar, et al (1998). The longitudinal extent of near and intermediate wake fields for the shallow VS wake flow is well defined by the integral wake length scale specified by v.Carmer (2005). The near wake region is characterised by high rates of exchange between the mean flow and large-scale 2D coherent structures (2DCS). In the intermediate field, the rate of decay of the turbulent stress components greatly diminishes as the 2DCS are stabilised and dissipated under the action of bed friction. Multiple peaks are observed in the power spectral density of the turbulent fluctuations. The periodic shedding of 2DCS behind the circular cylinder is characterised by an energy peak at a Strouhal number of 0.21, and further energy peaks are observed in the near-wake region. The PSD estimates are consistent with the findings of v.Carmer (2005) in which a -5/3 decay law to high frequencies is observed, and no evidence of an inverse energy cascade is present.

Heidelberg, Univ., Diplomarb., 2000.

Mammalian cells are known to respond to both extra- and intra- cellular forces as well as the physical properties of the surrounding tissue. There is increasing evidence to support the fundamental role of force, applied to or generated within cells, in maintaining proper tissue function. The mechanical integration from the exterior of a cell to the interior of the nucleus is crucial for cellular sensing of, and response to, the physical environment. Further, misregulation of this mechanosensitive ability can lead to the development or propagation of many diseases such as cancers, cardiovascular diseases, and tissue fibrosis. In this thesis, we investigate the role of various proteins in regulating the mechanical properties of mammalian cells. We also develop techniques to examine the propagation of forces through cells and multicell systems with the aim of elucidating critical biophysical factors involved in regulating cell function. The idea that the genome can be regulated through changes in forces applied to cells or changes in the propagation of forces through a cell, (i.e. mechanotransduction) is becoming widely accepted. The complex interplay between biochemical and biophysical mechanisms that ultimately control mechanotransduction are beginning to be uncovered; however, a true understanding of this remarkable cellular process has not yet been achieved. By investigating multiple factors which impact mechanosensitivity (such as protein expression, cell-cell and cell-environment connections, cell generated contractions, and physical connections through the cellular interior), we aim to further the understanding of potential pathways of mechanotransduction. Through novel studies and technological advances, the field of cellular biomechanics will continue to grow as we hope to uncover the physical mechanisms that regulate cell function or lead to disease.

Connectivity is an important component of coral reef studies for its role in the enhancement of ecosystem resilience. Previous genetic structure and physical circulation studies in the Red Sea reveal a homogeneity within the coral reef complexes in the central and northern parts of the basin. Yet, genetic isolation and relatively low connectivity has been observed in the southern Red Sea. Raitsos et al. (2017) recently hypothesized that coral reefs in the southern Red Sea are more connected with regions outside the basin, rather than with the central and northern Red Sea. Using a physical circulation approach based on a 3-D backward particle tracking simulation, we further investigate this hypothesis. A long-term (> 10 years), very high resolution (1km) MITgcm simulation is used to provide detailed information on velocity in the complex coastal regions of the Red Sea and the adjacent narrow Bab-El-Mandeb Strait. The particle tracking simulation results support the initial hypothesis that the coastal regions in the southern Red Sea exhibit a consistently higher connectivity with the regions outside the Bab-El-Mandeb Strait, than with the central and northern Red Sea. Substantially high levels of connectivity, facilitated by the circulation and eddies, is observed with the coastal regions in the Gulf of Aden. A strong seasonality in connectivity, related to the monsoon-driven circulation, is also evident with the regions outside of the Red Sea. The winter surface intrusion plays a leading role in transporting the particles from the Gulf of Aden and the Indian Ocean into the Red Sea, while the summer subsurface intrusion also supports the transport of particles into the Red Sea in the intermediate layer. In addition, the connectivity with the central and northern Red Sea is more affected by the intensity of the eddies. Evidence also suggests that potential connectivity exists between the coastal southern Red Sea and the coasts of Oman, Socotra, Somalia, Kenya, Tanzania and the north coast of the Madagascar.

The biological effects of charged particles is of interest in particle therapy, radiation protection and space radiation science and known to be dependent on both absorbed dose and radiation quality or LET. Microdosimetry is a technique which uses a tissue equivalent gas to simulate microscopic tissue sites of the order of cellular dimensions and the principles of gas ionization devices to measure deposited energy. The Gas Electron Multiplier (GEM) has been used since 1997 for tracking particles and for the determination of particle energy. In general, the GEM detector works in either tracking or energy deposition mode. The instrument proposed here is a combination of both, for the purpose of determining the energy deposition in simulated microscopic sites over the charged particle range and in particular at the end of the range where local energy deposition increases in the so‐called Bragg‐peak region. The detector is designed to track particles of various energies for 5 cm in one dimension, while providing the particle energy deposition every 0.5 cm of its track. The reconfiguration of the detector for different particle energies is very simple and achieved by adjusting the pressure of the gas inside the detector and resistor chain. In this manner, the detector can be used to study various ion beams and their dose distributions to tissues. Initial work is being carried out using an isotopic source of alpha particles and this thesis will describe the construction of the GEM‐based detector, computer modelling of the expected gas‐gain and performance of the device as well as comparisons with experimentally measured data of segmented energy deposition. / UOIT

Theoretical and numerical studies of chaotic mixing are performed to circumvent the difficulties of efficient mixing, which come from the lack of turbulence in microfluidic devices. In order to carry out efficient and accurate parametric studies and to identify a fully chaotic state, a spectral element algorithm for solution of the incompressible Navier-Stokes and species transport equations is developed. Using Taylor series expansions in time marching, the new algorithm employs an algebraic factorization scheme on multi-dimensional staggered spectral element grids, and extends classical conforming Galerkin formulations to nonconforming spectral elements. Lagrangian particle tracking methods are utilized to study particle dispersion in the mixing device using spectral element and fourth order Runge-Kutta discretizations in space and time, respectively. Comparative studies of five different techniques commonly employed to identify the chaotic strength and mixing efficiency in microfluidic systems are presented to demonstrate the competitive advantages and shortcomings of each method. These are the stirring index based on the box counting method, Poincare sections, finite time Lyapunov exponents, the probability density function of the stretching field, and mixing index inverse, based on the standard deviation of scalar species distribution. Series of numerical simulations are performed by varying the Peclet number (Pe) at fixed kinematic conditions. The mixing length (lm) is characterized as function of the Pe number, and lm ∝ ln(Pe) scaling is demonstrated for fully chaotic cases. Employing the aforementioned techniques, optimum kinematic conditions and the actuation frequency of the stirrer that result in the highest mixing/stirring efficiency are identified in a zeta potential patterned straight micro channel, where a continuous flow is generated by superposition of a steady pressure driven flow and time periodic electroosmotic flow induced by a stream-wise AC electric field. Finally, it is shown that the invariant manifold of hyperbolic periodic point determines the geometry of fast mixing zones in oscillatory flows in two-dimensional cavity.

<p>The work is focused on experimental study and modelling of spacer grid influence on single- and two-phase flow. In the experimental study a mock-up of a realistic fuel bundle with five spacer grids of thin plate spring construction was investigated. A special pressure measuring technique was used to measure pressure distribution inside the spacer. Five pressure taps were drilled in one of the rods, which could exchange position with other rods, in this way providing a large degree of freedom. Laser Doppler Velocimetry was used to measure mean local axial velocity and its fluctuating component upstream and downstream of the spacer in several subchannels with differing spacer part. The experimental study revealed an interesting behaviour. Subchannels from the interior part of the bundle display a different effect on the flow downstream of the spacer compared to subchannels close to the box wall, even if the spacer part is the same. This behaviour is not reflected in modern correlations. The modelling part, first, consisted in comparing the present experimental data to Computational Fluid Dynamics calculations. It was shown that stand-alone subchannel models could predict the local velocity, but are unreliable in prediction of turbulence enhancement due to spacer. The second part of the modelling consisted in developing a deposition model for increase due to spacer. In this study Lagrangian Particle Tracking (LPT) coupled to Discrete Random Walk (DRW) technique was used to model droplet movements through turbulent flow. The LPT technique has an advantage to model the influence of turbulence structure effect on droplet deposition, in this way presenting a generalized model in view of spacer geometry change. The verification of the applicability of LPT DRW method to model deposition in annular flow at Boiling Water Reactor conditions proved that the method is unreliable in its present state. The model calculations compare reasonably well to air-water deposition data, but display a wrong trend if the fluids have a different density ratio than air-water.</p>

Geologic sequestration of CO₂ in deep saline aquifers has been studied extensively over the past two decades as a viable method of reducing anthropological carbon emissions. The monitoring and prediction of the movement of injected CO₂ is important for assessing containment of the gas within the storage volume, and taking corrective measures if required. Given the uncertainty in geologic architecture of the storage aquifers, it is reasonable to depict our prior knowledge of the project area using a vast suite of aquifer models. Simulating such a large number of models using traditional numerical flow simulators to evaluate uncertainty is computationally expensive. A novel stochastic workflow for characterizing the plume migration, based on a model selection algorithm developed by Mantilla in 2011, has been implemented. The approach includes four main steps: (1) assessing the connectivity/dynamic characteristics of a large prior ensemble of models using proxies; (2) model clustering using the principle component analysis or multidimensional scaling coupled with the k-mean clustering approach; (3) model selection using the Bayes' rule on the reduced model space, and (4) model expansion using an ensemble pattern-based matching scheme. In this dissertation, two proxies have been developed based on particle tracking in order to assess the flow connectivity of models in the initial set. The proxies serve as fast approximations of finite-difference flow simulation models, and are meant to provide rapid estimations of connectivity of the aquifer models. Modifications have also been implemented within the model selection workflow to accommodate the particular problem of application to a carbon sequestration project. The applicability of the proxies is tested both on synthetic models and real field case studies. It is demonstrated that the first proxy captures areal migration to a reasonable extent, while failing to adequately capture vertical buoyancy-driven flow of CO₂. This limitation of the proxy is addressed in the second proxy, and its applicability is demonstrated not only in capturing horizontal migration but also in buoyancy-driven flow. Both proxies are tested both as standalone approximations of numerical simulation and within the larger model selection framework. / text