938 resultados para docking simulations


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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.

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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.

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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.

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We report on the construction of anatomically realistic three-dimensional in-silico breast phantoms with adjustable sizes, shapes and morphologic features. The concept of multiscale spatial resolution is implemented for generating breast tissue images from multiple modalities. Breast epidermal boundary and subcutaneous fat layer is generated by fitting an ellipsoid and 2nd degree polynomials to reconstructive surgical data and ultrasound imaging data. Intraglandular fat is simulated by randomly distributing and orienting adipose ellipsoids within a fibrous region immediately within the dermal layer. Cooper’s ligaments are simulated as fibrous ellipsoidal shells distributed within the subcutaneous fat layer. Individual ductal lobes are simulated following a random binary tree model which is generated based upon probabilistic branching conditions described by ramification matrices, as originally proposed by Bakic et al [3, 4]. The complete ductal structure of the breast is simulated from multiple lobes that extend from the base of the nipple and branch towards the chest wall. As lobe branching progresses, branches are reduced in height and radius and terminal branches are capped with spherical lobular clusters. Biophysical parameters are mapped onto the complete anatomical model and synthetic multimodal images (Mammography, Ultrasound, CT) are generated for phantoms of different adipose percentages (40%, 50%, 60%, and 70%) and are analytically compared with clinical examples. Results demonstrate that the in-silico breast phantom has applications in imaging performance evaluation and, specifically, great utility for solving image registration issues in multimodality imaging.

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Le caribou de Peary, désigné en voie de disparition, n’est pas épargné par les changements climatiques. Par le passé, des hivers successifs caractérisés par des conditions météorologiques extrêmes ont entrainé des déclins importants de population en quelques années, pouvant aller jusqu’à 98 %. L’augmentation des épisodes de redoux hivernaux et de pluies sur neige réduit les conditions d’accès à la nourriture de cette sous-espèce. Ces conditions ont pour conséquence d’augmenter la densité des couches de neige dans le manteau neigeux, ce qui empêche le caribou d’avoir accès au fourrage couvrant le sol en hiver. Dans cet esprit, l’outil de spatialisation de SNOWPACK dans l’Arctique (OSSA) développé dans Ouellet et al. (2016) permet la spatialisation des conditions d’accès à la nourriture du caribou de Peary en utilisant le modèle de simulation du couvert nival SNOWPACK. Le paramètre du couvert nival utilisé est l’épaisseur cumulée au-delà d’un seuil fixe de densité durant la saison hivernale (ECD). L'OSSA fournit un résultat d’une résolution spatiale de 32 km puisque les données météorologiques utilisées sont les données de réanalyses du North American Regional Reanalysis (NARR) qui possède une résolution de 32 km. Cette résolution grossière ne permet pas de documenter et prédire la migration locale des différentes populations sur les îles de l'archipel arctique canadien. L’objectif principal de ce projet est donc d’évaluer le potentiel d'une approche de raffinement spatial de l'OSSA à une résolution de 1 km. Afin d’affiner la résolution spatiale de la simulation de l’ECD, des données de pente et de l’albédo du sol à une résolution de 1 km ont été utilisées. Avant d’effectuer les simulations à haute résolution, la sensibilité de l’ECD à ces deux paramètres du terrain a été testée. Les simulations préliminaires ont permis de démontrer que plus la pente est élevée, plus l’ECD sera faible. Également, il a été identifié que la pente va affecter l’ECD à partir d’un seuil de 3 degré. L’albédo du sol a aussi un impact significatif sur l’ECD, mais à un niveau moins important que la pente. Finalement, la comparaison des résultats à faible et haute résolution a pu démontrer que l’approche de raffinement spatial appliquée permet d’obtenir une information plus détaillée des conditions d’accès à la nourriture du caribou de Peary. Les résultats d’ECD obtenus à 1 km de résolution montrent des écarts avec l’ECD à 32 km de résolution pouvant dépasser les 2000 cm. Finalement, cette étude montre l’intérêt d’automatiser cette approche afin de pouvoir spatialiser les conditions d’accès à la nourriture à une résolution de 1 km et de prédire certaines micro-variabilités dans les déplacements futurs des caribous de Peary en fonction des changements climatiques.

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Simulations of droplet dispersion behind cylinder wakes and downstream of icing tunnel spray bars were conducted. In both cases, a range of droplet sizes were investigated numerically with a Lagrangian particle trajectory approach while the turbulent air flow was investigated with a hybrid Reynolds-Averaged Navier-Stokes/Large-Eddy Simulations approach scheme. In the first study, droplets were injected downstream of a cylinder at sub-critical conditions (i.e. with laminar boundary layer separation). A stochastic continuous random walk (CRW) turbulence model was used to capture the effects of sub-grid turbulence. Small inertia droplets (characterized by small Stokes numbers) were affected by both the large-scale and small-scale vortex structures and closely followed the air flow, while exhibiting a dispersion consistent with that of a scalar flow field. Droplets with intermediate Stokes numbers were centrifuged by the vortices to the outer edges of the wake, yielding an increased dispersion. Large Stokes number droplets were found to be less responsive to the vortex structures and exhibited the least dispersion. Particle concentration was also correlated with vorticity distribution which yielded preferential bias effects as a function of different particle sizes. This trend was qualitatively similar to results seen in homogenous isotropic turbulence, though the influence of particle inertia was less pronounced for the cylinder wake case. A similar study was completed for droplet dispersion within the Icing Research Tunnel (IRT) at the NASA Glenn Research Center, where it is important to obtain a nearly uniform liquid water content (LWC) distribution in the test section (to recreate atmospheric icing conditions).. For this goal, droplets are diffused by the mean and turbulent flow generated from the nozzle air jets, from the upstream spray bars, and from the vertical strut wakes. To understand the influence of these three components, a set of simulations was conducted with a sequential inclusion of these components. Firstly, a jet in an otherwise quiescent airflow was simulated to capture the impact of the air jet on flow turbulence and droplet distribution, and the predictions compared well with experimental results. The effects of the spray bar wake and vertical strut wake were then included with two more simulation conditions, for which it was found that the air jets were the primary driving force for droplet dispersion, i.e. that the spray bar and vertical strut wake effects were secondary.

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Optical full-field measurement methods such as Digital Image Correlation (DIC) provide a new opportunity for measuring deformations and vibrations with high spatial and temporal resolution. However, application to full-scale wind turbines is not trivial. Elaborate preparation of the experiment is vital and sophisticated post processing of the DIC results essential. In the present study, a rotor blade of a 3.2 MW wind turbine is equipped with a random black-and-white dot pattern at four different radial positions. Two cameras are located in front of the wind turbine and the response of the rotor blade is monitored using DIC for different turbine operations. In addition, a Light Detection and Ranging (LiDAR) system is used in order to measure the wind conditions. Wind fields are created based on the LiDAR measurements and used to perform aeroelastic simulations of the wind turbine by means of advanced multibody codes. The results from the optical DIC system appear plausible when checked against common and expected results. In addition, the comparison of relative out-of-plane blade deflections shows good agreement between DIC results and aeroelastic simulations.

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Tässä työssä perehdytään soodakattiloiden vesikiertomallin rakentamiseen. Työn päätavoitteena on kehittää simulointimallia varten taulukkolaskentapohja, jonka avulla soodakattilan lämpövuotietoja on yksinkertaista ja nopeaa käsitellä ja siirtää Apros 6 -simulointiohjelmaan. Lisäksi tarkoituksena on pyrkiä automatisoimaan työvaiheet mahdollisimman pitkälle, jolloin vesikiertolaskennan tekeminen yksinkertaistuisi, yhtenäistyisi ja tarkentuisi. Tämä on mahdollista Excel- makrojen ja Apros 6:n uusien toimintojen avulla. Apros 6:ssa on nyt mahdollista hyödyntää SCL- komentotiedostoja, joiden avulla sujuva tiedonsiirto Aproksen ja Excelin välillä vodaan toteuttaa. Vesikiertolaskentaan käytettävän datan käsittely on aikaisemmin ollut työlästä ja sen tarkkuus on pitkälti riippunut mallintajasta. Tässä diplomityössä päästään hyödyntämään uusimpia ja realistisempia soodakattiloiden CFD- malleja, joiden avulla pystytään luomaan aikaisempaa tarkemmat lämpövuojakaumat soodakattilan lämpöpinnoille. Tämä muutos parantaa vesikiertolaskennan tarkkuutta. Työn kokeellisessa osassa uutta Excel laskentatyökalua ja uusia lämpövuoarvoja testataan käytännössä. Eräs vanha Apros- vesikiertomalli päivitetään uusilla lämpövuoarvoilla ja sen rakenteeseen tehdään muutoksia tarkkuuden parantamiseksi. Uuden mallin toimivuutta testataan myös 115 %:n kapasiteetilla ja tutkitaan kuinka kyseinen vesikiertopiiri reagoi suurempaan lämpötehoon. Näitä kolmea eri tilannetta vertaillaan toisiinsa ja tarkastellaan eroavaisuuksia niiden vesi-höyrypiireissä.