structural dynamics of soluble and membrane proteins explored through molecular simulations

Otto-von-Guericke-Universität Magdeburg, Fakultät für Verfahrens- und Systemtechnik, Dissertation, 2016

PHYSICA: A multiphysics computational framework and its application to casting simulations

Metal casting is a process governed by the interaction of a range of physical phenomena. Most computational models of this process address only what are conventionally regarded as the primary phenomena – heat conduction and solidification. However, to predict other phenomena, such as porosity formation, requires modelling the interaction of the fluid flow, heat transfer, solidification and the development of stressdeformation in the solidified part of the casting. This paper will describe a modelling framework called PHYSICA[1] which has the capability to stimulate such multiphysical phenomena.

Sensibilité des simulations de neige du modèle SNOWPACK à la paramétrisation de la végétation dans la Réserve Faunique Chic-Chocs

Au Canada, les avalanches constituent le géorisque le plus dangereux en période hivernale. On enregistre annuellement d’importants coûts économiques et sociaux associés aux impacts de ce phénomène naturel. Par exemple, la fermeture de routes en cas de risque d’avalanche est estimée à 5 millions de dollars (Jamieson et Stethem, 2002). La prévision des avalanches est, de nos jours, la meilleure méthode afin d’éviter ces coûts. Au Canada, cela s’effectue de façon ponctuelle à l’aide de méthodes manuelles tel que le test de compression (CAA, 2014). Les modèles de simulation du couvert neigeux permettent d’étendre les prévisions à l’ensemble d’une région et ainsi, atteindre certains lieux difficilement accessibles pour l’homme. On tente actuellement d’adapter le modèle SNOWPACK aux conditions canadiennes et plusieurs études ont eu pour but d’améliorer les simulations produites par celui-ci. Cette étude vise donc également l’amélioration des simulations par l’intégration des paramètres de végétation. L’objectif de l’étude est de paramétrer, pour la première fois, le module de végétation de SNOWPACK avec les données récoltées dans la réserve faunique des Chic-Chocs. Nous pourrons ainsi évaluer l’impact de la végétation sur la modélisation du couvert nival. Nous avons donc, lors de sorties de terrain, recueillis les données de neige et de végétation au niveau de quatre sites d’étude. Nous avons par la suite réalisé les simulations avec SNOWPACK et comparer les résultats des simulations avec et sans végétation aux données de terrain. L’étude nous révèle que le modèle diminue la quantité de neige au sol ainsi que la densité du manteau neigeux en présence de végétation. De plus nous avons pu constater que l’inclusion du module de végétation permet d’obtenir des données qui se rapprochent davantage de ce qui a été observé sur le terrain.

Finite volumes simulations in magnetohydrodynamics

Abstract not available

Computer simulations of soft particles in flow

Understanding the dynamics of blood cells is a crucial element to discover biological mechanisms, to develop new efficient drugs, design sophisticated microfluidic devices, for diagnostics. In this work, we focus on the dynamics of red blood cells in microvascular flow. Microvascular blood flow resistance has a strong impact on cardiovascular function and tissue perfusion. The flow resistance in microcirculation is governed by flow behavior of blood through a complex network of vessels, where the distribution of red blood cells across vessel cross-sections may be significantly distorted at vessel bifurcations and junctions. We investigate the development of blood flow and its resistance starting from a dispersed configuration of red blood cells in simulations for different hematocrits, flow rates, vessel diameters, and aggregation interactions between red blood cells. Initially dispersed red blood cells migrate toward the vessel center leading to the formation of a cell-free layer near the wall and to a decrease of the flow resistance. The development of cell-free layer appears to be nearly universal when scaled with a characteristic shear rate of the flow, which allows an estimation of the length of a vessel required for full flow development, $l_c \approx 25D$, with vessel diameter $D$. Thus, the potential effect of red blood cell dispersion at vessel bifurcations and junctions on the flow resistance may be significant in vessels which are shorter or comparable to the length $l_c$. The presence of aggregation interactions between red blood cells lead in general to a reduction of blood flow resistance. The development of the cell-free layer thickness looks similar for both cases with and without aggregation interactions. Although, attractive interactions result in a larger cell-free layer plateau values. However, because the aggregation forces are short-ranged at high enough shear rates ($\bar{\dot{\gamma}} \gtrsim 50~\text{s}^{-1}$) aggregation of red blood cells does not bring a significant change to the blood flow properties. Also, we develop a simple theoretical model which is able to describe the converged cell-free-layer thickness with respect to flow rate assuming steady-state flow. The model is based on the balance between a lift force on red blood cells due to cell-wall hydrodynamic interactions and shear-induced effective pressure due to cell-cell interactions in flow. We expect that these results can also be used to better understand the flow behavior of other suspensions of deformable particles such as vesicles, capsules, and cells. Finally, we investigate segregation phenomena in blood as a two-component suspension under Poiseuille flow, consisting of red blood cells and target cells. The spatial distribution of particles in blood flow is very important. For example, in case of nanoparticle drug delivery, the particles need to come closer to microvessel walls, in order to adhere and bring the drug to a target position within the microvasculature. Here we consider that segregation can be described as a competition between shear-induced diffusion and the lift force that pushes every soft particle in a flow away from the wall. In order to investigate the segregation, on one hand, we have 2D DPD simulations of red blood cells and target cell of different sizes, on the other hand the Fokker-Planck equation for steady state. For the equation we measure force profile, particle distribution and diffusion constant across the channel. We compare simulation results with those from the Fokker-Planck equation and find a very good correspondence between the two approaches. Moreover, we investigate the diffusion behavior of target particles for different hematocrit values and shear rates. Our simulation results indicate that diffusion constant increases with increasing hematocrit and depends linearly on shear rate. The third part of the study describes development of a simulation model of complex vascular geometries. The development of the model is important to reproduce vascular systems of small pieces of tissues which might be gotten from MRI or microscope images. The simulation model of the complex vascular systems might be divided into three parts: modeling the geometry, developing in- and outflow boundary conditions, and simulation domain decomposition for an efficient computation. We have found that for the in- and outflow boundary conditions it is better to use the SDPD fluid than DPD one because of the density fluctuations along the channel of the latter. During the flow in a straight channel, it is difficult to control the density of the DPD fluid. However, the SDPD fluid has not that shortcoming even in more complex channels with many branches and in- and outflows because the force acting on particles is calculated also depending on the local density of the fluid.

Large scale parallel simulations for the assembly of a flip-chip component to a printed circuit

Abstract not available

Simulations of forest loss in North America, the Amazon, and combined using the Community Earth System Model

The netcdf files in this archive comprise climate model output from Community Earth System Model for experiments looking at forest loss over Western North America and the Amazon. For further description of the model and configuration for these experiments please see the accompanying manuscript: Synergistic ecoclimate teleconnections from forest loss in different regions structure global ecological responses Elizabeth S. Garcia, Abigail L. S. Swann, Juan C. Villegas, David D. Breshears, Darin J. Law, Scott R. Saleska, and Scott C. Stark published in PLOS ONE, 2016. Contact information in README.txt

Load balancing for aspect ratio in adaptive finite element simulations

In parallel adaptive finite element simulations the work load on the individual processors may change frequently. To (re)distribute the load evenly over the processors a load balancing heuristic is needed. Common strategies try to minimise subdomain dependencies by optimising the cutsize of the partitioning. However for certain solvers cutsize only plays a minor role, and their convergence is highly dependent on the subdomain shapes. Degenerated subdomain shapes cause them to need significantly more iterations to converge. In this work a new parallel load balancing strategy is introduced which directly addresses the problem of generating and conserving reasonably good subdomain shapes in a dynamically changing Finite Element Simulation. Geometric data is used to formulate several cost functions to rate elements in terms of their suitability to be migrated. The well known diffusive method which calculates the necessary load flow is enhanced by weighting the subdomain edges with the help of these cost functions. The proposed methods have been tested and results are presented.

Specimen generation approaches for DEM simulations.

Discrete Element Method (DEM) simulations ofelement tests cam provide significant insight into the micro-mechanics of soil response. It is well established that soil behaviour is strongly dependant on the initial density. Generation of particulate assemblies for three-dimensional DEM analyses must therefore allow for void ratio control. In this paper, different specimen generation approaches for DEM analyses are discussed. A methodology for the generation of assemblies of spherical particles with a specified initial density and stress state is presented. The effects of the different preparation methods on the specimen fabric are then considered in detail. For isotropic consolidation, it is shown that varying the coefficient of inter-particle friction allows control of the specimen void ratio at a specified confining stress. Simulations of anisotropic consolidation, from an initial isotropic stress state, to a final state where sigma(3) = K(0)sigma(1) indicated that the specimen void ratio and fabric are relatively insensitive to the intermediate stress path, provided an intermediate stress along the K(0) line was attained.

Analysis of Molecular Dynamics Simulations of Protein Folding

Microsecond long Molecular Dynamics (MD) trajectories of biomolecular processes are now possible due to advances in computer technology. Soon, trajectories long enough to probe dynamics over many milliseconds will become available. Since these timescales match the physiological timescales over which many small proteins fold, all atom MD simulations of protein folding are now becoming popular. To distill features of such large folding trajectories, we must develop methods that can both compress trajectory data to enable visualization, and that can yield themselves to further analysis, such as the finding of collective coordinates and reduction of the dynamics. Conventionally, clustering has been the most popular MD trajectory analysis technique, followed by principal component analysis (PCA). Simple clustering used in MD trajectory analysis suffers from various serious drawbacks, namely, (i) it is not data driven, (ii) it is unstable to noise and change in cutoff parameters, and (iii) since it does not take into account interrelationships amongst data points, the separation of data into clusters can often be artificial. Usually, partitions generated by clustering techniques are validated visually, but such validation is not possible for MD trajectories of protein folding, as the underlying structural transitions are not well understood. Rigorous cluster validation techniques may be adapted, but it is more crucial to reduce the dimensions in which MD trajectories reside, while still preserving their salient features. PCA has often been used for dimension reduction and while it is computationally inexpensive, being a linear method, it does not achieve good data compression. In this thesis, I propose a different method, a nonmetric multidimensional scaling (nMDS) technique, which achieves superior data compression by virtue of being nonlinear, and also provides a clear insight into the structural processes underlying MD trajectories. I illustrate the capabilities of nMDS by analyzing three complete villin headpiece folding and six norleucine mutant (NLE) folding trajectories simulated by Freddolino and Schulten [1]. Using these trajectories, I make comparisons between nMDS, PCA and clustering to demonstrate the superiority of nMDS. The three villin headpiece trajectories showed great structural heterogeneity. Apart from a few trivial features like early formation of secondary structure, no commonalities between trajectories were found. There were no units of residues or atoms found moving in concert across the trajectories. A flipping transition, corresponding to the flipping of helix 1 relative to the plane formed by helices 2 and 3 was observed towards the end of the folding process in all trajectories, when nearly all native contacts had been formed. However, the transition occurred through a different series of steps in all trajectories, indicating that it may not be a common transition in villin folding. The trajectories showed competition between local structure formation/hydrophobic collapse and global structure formation in all trajectories. Our analysis on the NLE trajectories confirms the notion that a tight hydrophobic core inhibits correct 3-D rearrangement. Only one of the six NLE trajectories folded, and it showed no flipping transition. All the other trajectories get trapped in hydrophobically collapsed states. The NLE residues were found to be buried deeply into the core, compared to the corresponding lysines in the villin headpiece, thereby making the core tighter and harder to undo for 3-D rearrangement. Our results suggest that the NLE may not be a fast folder as experiments suggest. The tightness of the hydrophobic core may be a very important factor in the folding of larger proteins. It is likely that chaperones like GroEL act to undo the tight hydrophobic core of proteins, after most secondary structure elements have been formed, so that global rearrangement is easier. I conclude by presenting facts about chaperone-protein complexes and propose further directions for the study of protein folding.