Graphics Processing Units for the Real-time Linear Elastostatic Simulation of Liver

Biomedical engineering solutions like surgical simulators need High Performance Computing (HPC) to achieve real-time performance. Graphics Processing Units (GPUs) offer HPC capabilities at low cost and low power consumption. In this work, it is demonstrated that a liver which is discretized by about 2500 finite element nodes, can be graphically simulated in realtime, by making use of a GPU. Present work takes into consideration the time needed for the data transfer from CPU to GPU and back from GPU to CPU. Although behaviour of liver is very complicated, present computer simulation assumes linear elastostatics. One needs to use the commercial software ANSYS to obtain the global stiffness matrix of the liver. Results show that GPUs are useful for the real-time graphical simulation of liver, which in turn is needed in simulators that are used for training surgeons in laparoscopic surgery. Although the computer simulation should involve rendering also, neither rendering, nor the time needed for rendering and displaying the liver on a screen, is considered in the present work. The present work is just a demonstration of a concept; the concept is not really implemented and validated. Future work is to develop software which can accomplish real-time and very realistic graphical simulation of liver, with rendered image of liver on the screen changing in real-time according to the position of the surgical tool tip approximated as the mouse cursor in 3D.

Modelling, simulation, and graphical user interface for industrial gas carburising process

A mathematical model has been developed for the gas carburising (diffusion) process using finite volume method. The computer simulation has been carried out for an industrial gas carburising process. The model's predictions are in good agreement with industrial experimental data and with data collected from the literature. A study of various mass transfer and diffusion coefficients has been carried out in order to suggest which correlations should be used for the gas carburising process. The model has been interfaced in a Windows environment using a graphical user interface. In this way, the model is extremely user friendly. The sensitivity analysis of various parameters such as initial carbon concentration in the specimen, carbon potential of the atmosphere, temperature of the process, etc. has been carried out using the model.

Layerwise decomposition of water dynamics in reverse micelles: A simulation study of two-dimensional infrared spectrum

We present computer simulation study of two-dimensional infrared spectroscopy (2D-IR) of water confined in reverse micelles (RMs) of various sizes. The present study is motivated by the need to understand the altered dynamics of confined water by performing layerwise decomposition of water, with an aim to quantify the relative contributions of different layers water molecules to the calculated 2D-IR spectrum. The 0-1 transition spectra clearly show substantial elongation, due to in-homogeneous broadening and incomplete spectral diffusion, along the diagonal in the surface water layer of different sized RMs. Fitting of the frequency fluctuation correlation functions reveal that the motion of the surface water molecules is sub-diffusive and indicate the constrained nature of their dynamics. This is further supported by two peak nature of the angular analogue of van Hove correlation function. With increasing system size, the water molecules become more diffusive in nature and spectral diffusion almost completes in the central layer of the larger size RMs. Comparisons between experiments and simulations establish the correspondence between the spectral decomposition available in experiments with the spatial decomposition available in simulations. Simulations also allow a quantitative exploration of the relative role of water, sodium ions, and sulfonate head groups in vibrational dephasing. Interestingly, the negative cross correlation between force on oxygen and hydrogen of O-H bond in bulk water significantly decreases in the surface layer of each RM. This negative cross correlation gradually increases in the central water pool with increasing RMs size and this is found to be partly responsible for the faster relaxation rate of water in the central pool. (C) 2013 AIP Publishing LLC.

Numerical Simulation of the Flow Field and Concentration Distribution in the Bulk Growth of Silicon Carbide Crystals

The physical vapor transport (PVT) method is being widely used to grow large-size single SiC crystals. The growth process is associated with heat and mass transport in the growth chamber, chemical reactions among multiple species as well as phase change at the crystal/gas interface. The current paper aims at studying and verifying the transport mechanism and growth kinetics model by demonstrating the flow field and species concentration distribution in the growth system. We have developed a coupled model, which takes into account the mass transport and growth kinetics. Numerical simulation is carried out by employing an in-house developed software based on finite volume method. The results calculated are in good agreement with the experimental observation.

Molecular dynamics simulation on dislocation emission process

A correlative reference model for a computer simulation of molecular dynamics is proposed in this paper. Based on this model, a flexible displacement boundary scheme is naturally introduced and the dislocations emitted from a crack tip are presumed to continuously pass through the border of an inner discrete atomic region to pile up at an outer continuum region. The simulations for a Mo crystal show that the interaction between a crack and emitted dislocations results in the decrease in local stress intensity factor gradually.

Molecular dynamics simulation of interaction of a dislocation array from a crack tip with grain boundaries

The interaction of a dislocation array emitted from a crack tip under mode II loading with asymmetric tilt grain boundaries (GBs) is analysed by the molecular dynamics method. The GBs can generally be described by planar and linear matching zones and unmatching zones. All GBs are observed to emit dislocations. The GBs migrated easily due to their planar and linear matching structure and asymmetrical type. The diffusion induced by stress concentration is found to promote the GB migration. The transmissions of dislocations are either along the matched plane or along another plane depending on tilt angle theta. Alternate processes of stress concentration and stress relaxation take place ahead of the pileup. The stress concentration can be released either by transmission of dislocations, by atom diffusion along GBs, or by migration of GBs by formation of twinning bands. The simulated results also unequivocally demonstrate two processes, i.e. asymmetrical GBs evolving into symmetrical ones and unmatching zones evolving into matching ones during the loading process.

TUNPOP: A simulation of the dynamics and structure of the yellowfin tuna stock and surface fishery of the Eastern Pacific Ocean

ENGLISH: Three distinct versions of TUNP0P, an age-structured computer simulation model of the eastern Pacific yellowfin tuna, Thunnus albacores, stock and surface tuna fishery, are used to reveal mechanisms which appear to have a significant effect on the fishery dynamics. Real data on this fishery are used to make deductions on the distribution of the fish and to show how that distribution might influence events in the fishery. The most important result of the paper is that the concept of the eastern Pacific yellowfin tuna stock as a homogeneous unit is inadequate to represent the recent history of the fishery. Inferences are made on the size and distribution of the underlying stock as well as its potential yield to the surface fishery as a result of alterations in the level and distribution of the effort. SPANISH: Se han empleado tres versiones diferentes de TUNP0P, un modelo de simulación de la computadora (basado en la estructura de la edad) de la población y la pesca epipelágica del atún aleta amarilla, Tbunnus albacares, del Pacífico oriental, para revelar los mecanismos que parecen tener un efecto importante en la dinámica pesquera. Se emplean los datos verdaderos de esta pesca para hacer deducciones sobre la distribución de los peces y para mostrar cómo puede influir esta distribución en los eventos de pesca. La conclusión más importante de este estudio es que el concepto de que la población del aleta amarilla del Pacífico oriental es una unidad homogénea, es inadecuado para representar la historia reciente de pesca. Se teoriza sobre la talla y distribución de la población subyacente como también sobre su producción potencial en la pesca epipelágica al cambiar el nivel y distribución del esfuerzo.

Temporal characteristic simulation for stimulated emission depletion microscopy

The imaging technology of stimulated emission depletion (STED) utilizes the nonlinearity relationship between the fluorescence saturation and the excited state stimulated depletion. It implements three-dimensional (3D) imaging and breaks the diffraction barrier of far-field light microscopy by restricting fluorescent molecules at a sub-diffraction spot. In order to improve the resolution which attained by this technology, the computer simulation on temporal behavior of population probabilities of the sample was made in this paper, and the optimized parameters such as intensity, duration and delay time of the STED pulse were given.

Advanced Monte Carlo Simulation and Machine Learning for Frequency Domain Optical Coherence Tomography

Optical Coherence Tomography(OCT) is a popular, rapidly growing imaging technique with an increasing number of bio-medical applications due to its noninvasive nature. However, there are three major challenges in understanding and improving an OCT system: (1) Obtaining an OCT image is not easy. It either takes a real medical experiment or requires days of computer simulation. Without much data, it is difficult to study the physical processes underlying OCT imaging of different objects simply because there aren't many imaged objects. (2) Interpretation of an OCT image is also hard. This challenge is more profound than it appears. For instance, it would require a trained expert to tell from an OCT image of human skin whether there is a lesion or not. This is expensive in its own right, but even the expert cannot be sure about the exact size of the lesion or the width of the various skin layers. The take-away message is that analyzing an OCT image even from a high level would usually require a trained expert, and pixel-level interpretation is simply unrealistic. The reason is simple: we have OCT images but not their underlying ground-truth structure, so there is nothing to learn from. (3) The imaging depth of OCT is very limited (millimeter or sub-millimeter on human tissues). While OCT utilizes infrared light for illumination to stay noninvasive, the downside of this is that photons at such long wavelengths can only penetrate a limited depth into the tissue before getting back-scattered. To image a particular region of a tissue, photons first need to reach that region. As a result, OCT signals from deeper regions of the tissue are both weak (since few photons reached there) and distorted (due to multiple scatterings of the contributing photons). This fact alone makes OCT images very hard to interpret.

This thesis addresses the above challenges by successfully developing an advanced Monte Carlo simulation platform which is 10000 times faster than the state-of-the-art simulator in the literature, bringing down the simulation time from 360 hours to a single minute. This powerful simulation tool not only enables us to efficiently generate as many OCT images of objects with arbitrary structure and shape as we want on a common desktop computer, but it also provides us the underlying ground-truth of the simulated images at the same time because we dictate them at the beginning of the simulation. This is one of the key contributions of this thesis. What allows us to build such a powerful simulation tool includes a thorough understanding of the signal formation process, clever implementation of the importance sampling/photon splitting procedure, efficient use of a voxel-based mesh system in determining photon-mesh interception, and a parallel computation of different A-scans that consist a full OCT image, among other programming and mathematical tricks, which will be explained in detail later in the thesis.

Next we aim at the inverse problem: given an OCT image, predict/reconstruct its ground-truth structure on a pixel level. By solving this problem we would be able to interpret an OCT image completely and precisely without the help from a trained expert. It turns out that we can do much better. For simple structures we are able to reconstruct the ground-truth of an OCT image more than 98% correctly, and for more complicated structures (e.g., a multi-layered brain structure) we are looking at 93%. We achieved this through extensive uses of Machine Learning. The success of the Monte Carlo simulation already puts us in a great position by providing us with a great deal of data (effectively unlimited), in the form of (image, truth) pairs. Through a transformation of the high-dimensional response variable, we convert the learning task into a multi-output multi-class classification problem and a multi-output regression problem. We then build a hierarchy architecture of machine learning models (committee of experts) and train different parts of the architecture with specifically designed data sets. In prediction, an unseen OCT image first goes through a classification model to determine its structure (e.g., the number and the types of layers present in the image); then the image is handed to a regression model that is trained specifically for that particular structure to predict the length of the different layers and by doing so reconstruct the ground-truth of the image. We also demonstrate that ideas from Deep Learning can be useful to further improve the performance.

It is worth pointing out that solving the inverse problem automatically improves the imaging depth, since previously the lower half of an OCT image (i.e., greater depth) can be hardly seen but now becomes fully resolved. Interestingly, although OCT signals consisting the lower half of the image are weak, messy, and uninterpretable to human eyes, they still carry enough information which when fed into a well-trained machine learning model spits out precisely the true structure of the object being imaged. This is just another case where Artificial Intelligence (AI) outperforms human. To the best knowledge of the author, this thesis is not only a success but also the first attempt to reconstruct an OCT image at a pixel level. To even give a try on this kind of task, it would require fully annotated OCT images and a lot of them (hundreds or even thousands). This is clearly impossible without a powerful simulation tool like the one developed in this thesis.

Motion simulation of annular polishing

Based on the Coulomb friction model, the frictional motion model of workpiece relating to the polishing pad was presented in annular polishing. By the dynamic analysis software, the model was simulated and analysed. The conclusions from the results were that the workpiece did not rotate steadily. When the angular velocity of ring and the direction were the same as that of the polishing pad, the angular velocity of workpiece hoicked at the beginning and at the later stage were the same as that of the polishing pad before contacting with the ring. The angular velocity of workpiece vibrated at the moment of contacting with the ring. After that the angular velocity of workpiece increased gradually and fluctuated at a given value, while the angular velocity of ring decreased gradually and also fluctuated at a given value. Since the contact between the workpiece and the ring was linear, their linear velocities and directions should be the same. But the angular velocity of workpiece was larger than that of the polishing pad on the condition that the radius of the workpiece was less than that of the ring. This did not agree with the pure translation principle and the workpiece surface could not be flat, either. Consequently, it needed to be controlled with the angular velocity of ring and the radii of the ring and the workpiece, besides friction to make the angular velocity of workpiece equal to that of the polishing pad for obtaining fine surface flatness of the workpiece. Copyright © 2007 Inderscience Enterprises Ltd.}

Optimisation of the first principle code Octopus for massive parallel architectures: application to light harvesting complexes

150 p.

Machine learning for predictive condensed-phase simulation

We show how machine learning techniques based on Bayesian inference can be used to reach new levels of realism in the computer simulation of molecular materials, focusing here on water. We train our machine-learning algorithm using accurate, correlated quantum chemistry, and predict energies and forces in molecular aggregates ranging from clusters to solid and liquid phases. The widely used electronic-structure methods based on density-functional theory (DFT) give poor accuracy for molecular materials like water, and we show how our techniques can be used to generate systematically improvable corrections to DFT. The resulting corrected DFT scheme gives remarkably accurate predictions for the relative energies of small water clusters and of different ice structures, and greatly improves the description of the structure and dynamics of liquid water.

Numerical simulation of nc-Si : H/c-Si heterojunction solar cells

AMPS simulator, which was developed by Pennsylvania State University, has been used to simulate photovoltaic performances of nc-Si:H/c-Si solar cells. It is shown that interface states are essential factors prominently influencing open circuit voltages (V-OC) and fill factors (FF) of these structured solar cells. Short circuit current density (J(SC)) or spectral response seems more sensitive to the thickness of intrinsic a-Si:H buffer layers inserted into n(+)-nc-Si:H layer and p-c-Si substrates. Impacts of bandgap offset on solar cell performances have also been analyzed. As DeltaE(C) increases, degradation of VOC and FF owing to interface states are dramatically recovered. This implies that the interface state cannot merely be regarded as carrier recombination centres, and impacts of interfacial layer on devices need further investigation. Theoretical maximum efficiency of up to 31.17% (AM1.5,100mW/cm(2), 0.40-1.1mum) has been obtained with BSF structure, idealized light-trapping effect(R-F=0, R-B=1) and no interface states.

Brownian dynamics simulation of the crystallization dynamics of charged colloidal particles

Crystal formation process of charged colloidal particles is investigated using Brownian dynamics (BD) simulations. The particles are assumed to interact with the pair-additive repulsive Yukawa potential. The time evolution of crystallization process and the crystal structure during the simulation are characterized by means of the radial distribution functions (RDF) and mean square displacement (MSD). The simulations show that when the interaction is featured with long-range, particles can spontaneously assemble into body-centered-cubic (BCC) arrays at relatively low particle number density. When the interaction is short-ranged, with increasing the number density particles become trapped into a stagnant disordered configuration before the crystallization could be actualized. The simulations further show that as long as the trapped configurations are bypassed, the face-centered-cubic (FCC) structures can be achieved and are actually more stable than BCC structures. (C) 2010 Elsevier Inc. All rights reserved.

Simulation Study of Aggregate Morphologies Formed by ABC Linear Triblock Copolymers in a Selective Solvent Through the Self-Consistent Field Theory

The effect of the hydrophobic properties of blocks B and C on the aggregate morphologies formed by ABC linear triblock copolymers in selective solvent was studied through the self-consistent field theory. Five typical micelles, such as core-shell-corona, hamburger-like, segmented-wormlike, were obtained by changing the hydrophobic properties of blocks B and C. The simulation results indicate that the shape and size of micelle are basically controlled by the hydrophobic degree of the middle block B, whereas the type of micelle is mainly determined by the hydrophobic degree of the end block C.