Techniques for augmenting the visualisation of dynamic raster surfaces

Despite their aesthetic appeal and condensed nature, dynamic raster surface representations such as a temporal series of a landform and an attribute series of a socio-economic attribute of an area, are often criticised for the lack of an effective information delivery and interactivity.In this work, we readdress some of the earlier raised reasons for these limitations -information-laden quality of surface datasets, lack of spatial and temporal continuity in the original data, and a limited scope for a real-time interactivity. We demonstrate with examples that the use of four techniques namely the re-expression of the surfaces as a framework of morphometric features, spatial generalisation, morphing, graphic lag and brushing can augment the visualisation of dynamic raster surfaces in temporal and attribute series

Large Eddy Simulation of Boundary Layer Combustion

Numerical simulations of turbulent non-premixed flames occurring in the presence of solid surfaces is a prevalent topic of interest due to the complexity of the near wall physics and the technical modeling challenges it presents. Near wall combustion phenomena is relevant in a variety of combusting environments including but not limited to the occurrence of fire spread, as a result of a heating load to a flammable wall leading to fire growth in enclosure settings; and in engine combustion configurations where the interaction with a cooled surface combined with occurrences of short flame wall distances can lead to extinction events adversely affecting combustion performance. The interaction between the flame and surface can result in a reduction of flame strength near the cold wall region while gas phase heat fluxes can take peak values at flame contact. To address the aforementioned modeling challenges, an advanced computational fluid dynamics (CFD) solver has been developed by adapting a preexisting numerical simulation solver from a boundary layer code to a code with variable mass density and combustion capabilities to produce high-fidelity simulations of turbulent non-premixed wall-flames. A series of verification studies have been developed using several benchmark laminar flow problems for the following canonical configurations: a binary diffusion controlled mixing problem, Poiseuille flow with heat transfer, and classical Blasius boundary layer flow. The turbulence LES modeling capability is validated by performing wall-resolved heated/non-heated turbulent channel flow and transpired boundary layer simulations to capture the effects of heat and mass transfer on the turbulent eddy structure and statistics. Lastly, an application of a simplified non-premixed wall flame configuration is presented in which the fuel corresponds to pyrolysis products supplied by a thermally-degrading flat sample of polymethyl methacrylate (PMMA) and the oxidizer corresponds to a cross-flow of ambient air with controlled mean velocity and turbulence intensities. Comparisons between numerical results and experimental data are made in terms of flame length, wall surface heat flux and flame structure and the ability of the solver in modeling non-premixed turbulent wall-flames is successfully demonstrated. The solver extends the present state of the art in fire modeling (limited to laminar flows) by providing a high quality numerical tool to study the heat transfer aspects of turbulent wall flame phenomen

Novel Algorithms for Merging Computational Fluid Dynamics and 4D Flow MRI

Time-resolved three-dimensional spatial encoding combined with three-directional velocity-encoded phase contrast magnetic resonance imaging (termed as 4D flow MRI), can provide valuable information for diagnosis, treatment, and monitoring of vascular diseases. The accuracy of this technique, however, is limited by errors in flow estimation due to acquisition noise as well as systematic errors. Furthermore, available spatial resolution is limited to 1.5mm - 3mm and temporal resolution is limited to 30-40ms. This is often grossly inadequate to resolve flow details in small arteries, such as those in cerebral circulation. Recently, there have been efforts to address the limitations of the spatial and temporal resolution of MR flow imaging through the use of computational fluid dynamics (CFD). While CFD is capable of providing essentially unlimited spatial and temporal resolution, numerical results are very sensitive to errors in estimation of the flow boundary conditions. In this work, we present three novel techniques that combine CFD with 4D flow MRI measurements in order to address the resolution and noise issues. The first technique is a variant of the Kalman Filter state estimator called the Ensemble Kalman Filter (EnKF). In this technique, an ensemble of patient-specific CFD solutions are used to compute filter gains. These gains are then used in a predictor-corrector scheme to not only denoise the data but also increase its temporal and spatial resolution. The second technique is based on proper orthogonal decomposition and ridge regression (POD-rr). The POD method is typically used to generate reduced order models (ROMs) in closed control applications of large degree of freedom systems that result from discretization of governing partial differential equations (PDE). The POD-rr process results in a set of basis functions (vectors), that capture the local space of solutions of the PDE in question. In our application, the basis functions are generated from an ensemble of patient-specific CFD solutions whose boundary conditions are estimated from 4D flow MRI data. The CFD solution that should be most closely representing the actual flow is generated by projecting 4D flow MRI data onto the basis vectors followed by reconstruction in both MRI and CFD resolution. The rr algorithm was used for between resolution mapping. Despite the accuracy of using rr as the mapping step, due to manual adjustment of a coefficient in the algorithm we developed the third algorithm. In this step, the rr algorithm was substituded with a dynamic mode decomposition algorithm to preserve the robustness. These algorithms have been implemented and tested using a numerical model of the flow in a cerebral aneurysm. Solutions at time intervals corresponding to the 4D flow MRI temporal resolution were collected and downsampled to the spatial resolution of the imaging data. A simulated acquisition noise was then added in k-space. Finally, the simulated data affected by noise were used as an input to the merging algorithms. Rigorous comparison to state-of-the-art techniques were conducted to assess the accuracy and performance of the proposed method. The results provided denoised flow fields with less than 1\% overall error for different signal-to-noise ratios. At the end, a small cohort of three patients were corrected and the data were reconstructed using different methods, the wall shear stress (WSS) was calculated using different reconstructed data and the results were compared. As it has been shown in chapter 5, the calculated WSS using different methods results in mutual high and low shear stress regions, however, the exact value and patterns are significantly different

Volumetric velocimetry for fluid flows

In recent years, several techniques have been introduced that are capable of extracting 3D three-component velocity fields in fluid flows. Fast-paced developments in both hardware and processing algorithms have generated a diverse set of methods, with a growing range of applications in flow diagnostics. This has been further enriched by the increasingly marked trend of hybridization, in which the differences between techniques are fading. In this review, we carry out a survey of the prominent methods, including optical techniques and approaches based on medical imaging. An overview of each is given with an example of an application from the literature, while focusing on their respective strengths and challenges. A framework for the evaluation of velocimetry performance in terms of dynamic spatial range is discussed, along with technological trends and emerging strategies to exploit 3D data. While critical challenges still exist, these observations highlight how volumetric techniques are transforming experimental fluid mechanics, and that the possibilities they offer have just begun to be explored.SD was partially supported under Grant No. DPI2016-79401-R funded by the Spanish State Research Agency (SRA) and the European Regional Development Fund (ERDF). FC was partially supported by the U.S. National Science Foundation (Chemical, Bioengineering, Environmental, and Transport Systems, Grant No. 1453538)

Large-eddy simulations of flow and heat transfer for jet impingement on static and vibrating surfaces

The present numerical work serves to understand the flow and thermal characteristics of a turbulent impinging air jet under dynamic flow and geometric conditions using Large-eddy Simulations (LES). A clear relationship between the large-scale structures and resulting heat transfer on the impingement surface exists and was demonstrated through highly-resolved LES of both static and dynamic surface configurations

Numerical Evaluation of Pathline Predicates of the Benguela Upwelling System

Using simulation data of a regional ocean model, Nardini et al. applied pathline predicates for a detailed post-hoc analysis of the Benguela upwelling system. In this work, we evaluate the accuracy of this technique. Using different temporal samplings, we aim at finding minimum requirements for the temporal resolution of the flow data in the context of retroactive particle pathline techniques. Besides the flow field, our simulation data contains synthetic tracer fields for different tracer source regions. Using the flow data, dense trajectories are computed to enable deriving ”emulated tracer fields” based on the local ratio of pathline particles originating from tracer source regions to other ones, which can then be compared to the original tracer fields. We find that the emulated tracer concentrations are overestimated in comparison to the original ones. However, the shape of the regions with high tracer concentration can be reproduced

An Oscillatory Contractile Pole-Force Component Dominates the Traction Forces Exerted by Migrating Amoeboid Cells

We used principal component analysis to dissect the mechanics of chemotaxis of amoeboid cells into a reduced set of dominant components of cellular traction forces and shape changes. The dominant traction force component in wild-type cells accounted for ~40% of the mechanical work performed by these cells, and consisted of the cell attaching at front and back contracting the substrate towards its centroid (pole-force). The time evolution of this pole-force component was responsible for the periodic variations of cell length and strain energy that the cells underwent during migration. We identified four additional canonical components, reproducible from cell to cell, overall accounting for an additional ~20% of mechanical work, and associated with events such as lateral protrusion of pseudopodia. We analyzed mutant strains with contractility defects to quantify the role that non-muscle Myosin II (MyoII) plays in amoeboid motility. In MyoII essential light chain null cells the polar-force component remained dominant. On the other hand, MyoII heavy chain null cells exhibited a different dominant traction force component, with a marked increase in lateral contractile forces, suggesting that cortical contractility and/or enhanced lateral adhesions are important for motility in this cell line. By compressing the mechanics of chemotaxing cells into a reduced set of temporally-resolved degrees of freedom, the present study may contribute to refined models of cell migration that incorporate cell-substrate interactions