Eulerian two-phase flow simulation and experimental validation of semisolid slurry generation process using cooling slope

Experimental and numerical studies of slurry generation using a cooling slope are presented in the paper. The slope having stainless steel body has been designed and constructed to produce semisolid A356 Al alloy slurry. The pouring temperature of molten metal, slope angle of the cooling slope and slope wall temperature were varied during the experiment. A multiphase numerical model, considering liquid metal and air, has been developed to simulate the liquid metal flow along the cooling channel using an Eulerian two-phase flow approach. Solid fraction evolution of the solidifying melt is tracked at different locations of the cooling channel following Schiel's equation. The continuity, momentum and energy equations are solved considering thin wall boundary condition approach. During solidification of the melt, based on the liquid fraction and latent heat of the alloy, temperature of the alloy is modified continuously by introducing a modified temperature recovery method. Numerical simulations has been carried out for semisolid slurry formation by varying the process parameters such as angle of the cooling slope, cooling slope wall temperature and melt superheat temperature, to understand the effect of process variables on cooling slope semisolid slurry generation process such as temperature distribution, velocity distribution and solid fraction of the solidifying melt. Experimental validation performed for some chosen cases reveals good agreement with the numerical simulations.

Engagement of CF3 Group in N-H center dot center dot center dot F-C Hydrogen Bond in the Solution State: NMR Spectroscopy and MD Simulation Studies

Unambiguous evidence for the engagement of CF3 group in N-H center dot center dot center dot F-C hydrogen bond in a low polarity solvent, the first observation of its kind, is reported. The presence of such weak molecular interactions in the solution state is convincingly established by one and two-dimensional H-1, F-19, and natural abundant N-15 NMR spectroscopic studies. The strong and direct evidence is derived by the observation of through-space couplings, such as, (1h)J(FH), (1h)J(FN), and (2h)J(FF), where the spin polarization is transmitted through hydrogen bond. In an interesting example of a molecule containing two CF3 groups getting simultaneously involved in hydrogen bond, where hydrogen bond mediated couplings are not reflected in the NMR spectrum, F-19-F-19 NOESY experiment yielded confirmatory evidence. Significant deviations in the strengths of (1)J(NH), variable temperature, and the solvent induced perturbations yielded additional support. The NMR results are corroborated by both DFT calculations and MD simulations, where the quantitative information on different ways of involvement of fluorine in two and three centered hydrogen bonds, their percentage of occurrences, and geometries have been obtained. The hydrogen bond interaction energies have also been calculated.

Investigation of selective sensing of a diamine for aldehyde by experimental and simulation studies

An organic molecule-o-phenylene diamine (OPD)-is selected as an aldehyde sensing material. It is studied for selectivity to aldehyde vapours both by experiment and simulation. A chemiresistor based sensor for detection of aldehyde vapours is fabricated. An o-phenylene diamine-carbon black composite is used as the sensing element. The amine groups in the OPD would interact with the carbonyl groups of the aldehydes. The selectivity and cross-sensitivity of the OPD-CB sensor to VOCs aldehyde, ketone and alcohol-are studied. The sensor shows good response to aldehydes compared to other VOCs. The higher response for aldehydes is attributed to the interaction of the carbonyl oxygen of aldehydes with-NH2 groups of OPD. The surface morphology of the sensing element is studied by scanning electron microscopy. The OPD-CB sensor is responsive to 10 ppm of formaldehyde. The interaction of the VOCs with the OPD-CB nanocomposite is investigated by molecular dynamics studies. The interaction energies of the analyte with the OPD-CB nanocomposite were calculated. It is observed that the interaction energies for aldehydes are higher than those for other analytes. Thus the OPD-CB sensor shows selectivity to aldehydes. The simulated radial distribution function is calculated for the O-H pair of analyte and OPD which further supports the finding that the amine groups are involved in the interaction. These results suggest that it is important and easy to identify appropriate sensing materials based on the understanding of analyte interaction properties.

Experimental study and simulation principles of an oil-gas multiphase transportation system

Presented is an experimental study on the performance of an oil-gas multiphase transportation system, especially on the multiphase flow patterns, multiphase pumping and multiphase metering of the system. A dynamic simulation analysis is conducted to deduce simulation parameters of the system and similarity criteria under simplified conditions are obtained. The reliability and feasibility of two-phase flow experiment with oil and natural gas simulated by water and air are discussed by using the similarity criteria.

A Generalized Soft-Sphere for Monte Carlo Simulation

A new collision model, called the generalized soft-sphere (GSS) model, is introduced. It has the same total cross section as the generalized hard-sphere model [Phys. Fluids A 5, 738 (1993)], whereas the deflection angle is calculated by the soft-sphere scattering model [Phys. Fluids A 3, 2459 (1991)]. In virtue of a two-term formula given to fit the numerical solutions of the collision integrals for the Lennard-Jones (6-12) potential and for the Stockmayer potential, the parameters involved in the GSS model are determined explicitly that may fully reproduce the transport coefficients under these potentials. Coefficients of viscosity, self-diffusion and diffusion for both polar and nonpolar molecules given by the GSS model and experiment are in excellent agreement over a wide range of temperature from low to high.

A simulation model of a floating half zone

A simulation model of a floating half zone was suggested by steady numerical simulation and experiment respectively, in the previous papers [Q.S. Chen, W.R. Hu, Int. J. Mass Heat Transfer 40 (1997) 757; J.H. Han, Y. Ar, R. Zhou, W.R. Hue, Int. J. Mass Heat Transfer 40 (1997) 2671]. In the present paper, the simulation model is studied by using the method of unsteady and three-dimensional numerical simulation, and the transient process from steady convection to oscillatory convection is especially analyzed. Comparison of onsets of oscillation for both simulation model and the usual model were obtained, and the results show that the critical Marangoni number of the simulation model is obviously smaller than that of the usual model for the same slender liquid bridge. This implies that the usual model of a floating half zone gives a lower estimation on the onset of oscillation for floating zone convection.

Numerical Simulation of Particle Separation in An Oil-Sand Separator

The gathering systems of crude oil are greatly endangered by the fine sand and soil in oil. Up to now , how to separate sand from the viscid oil is still a technical problem for oil production home or abroad. Recently , Institute of Mechanics in Chinese Academy of Sciences has developed a new type of oil-sand separator , which has been applied successfully in oil field in situ. In this paper, the numerical method of vortex-stream function is used to predict the liquid-solid separating course and the efficiency for this oil-sand separator. Results show that the viscosity and particle diameter have much influence on the particle motion. The calculating separating efficiency is compared with that of experiment and indicates that this method can be used to model the complex two-phase flow in the separator.

Two-dimensional simulation of inductive plasma sources with self-consistent power deposition

A time averaged two-dimensional fluid model including an electromagnetic module with self-consistent power deposition was developed to simulate the transport of a low pressure radio frequency inductively coupled plasma source. Comparsions with experiment and previous simulation results show, that the fluid model is feasible in a certain range of gas pressure. In addition, the effects of gas pressure and power input have been discussed.

Online exercise for the design and simulation of PCR and PCR-RFLP experiments

[EN] Background: Polymerase Chain Reaction (PCR) and Restriction Fragment Length Polymorphism of PCR products (PCR-RFLP) are extensively used molecular biology techniques. An exercise for the design and simulation of PCR and PCR-RFLP experiments will be a useful educational tool. Findings: An online PCR and PCR-RFLP exercise has been create that requires users to find the target genes,compare them, design primers, search for restriction endonucleases, and finally to simulate the experiment. Each user of the service is randomly assigned a gene from Escherichia coli; to complete the exercise, users must design an experiment capable of distinguishing among E. coli strains. By applying the experimental procedure to all completely sequenced E. coli, a basic understanding of strain comparison and clustering can also be acquired. Comparison of results obtained in different experiments is also very instructive. Conclusions: The exercise is freely available at http://insilico.ehu.es/edu.

Monte Carlo simulation of cooling induced by parametric resonance

We demonstrate that the parametric resonance in a magnetic quadrupole trap can be exploited to cool atoms by using Bird's method. In our programme the parametric resonance was realized by anisotropically modulating the trap potential. The modulation frequency dependences of temperature and fraction of the trapped atoms are explored. Furthermore, the temperature after the modulation as functions of the modulation amplitude and the mean elastic collision time are also studied. These results are valuable for the experiment of parametric resonance in a quadrupole trap.

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.

Optical near-field simulation of Sb thin film thermal lens and its application in optical recording

Using the finite-difference-time-domain method, the near-field optical distribution and properties of Sb thin film thermal lens are calculated and simulated. The results show as follows. Within the near-field distance to the output plane of thermal lens, the spot size is approximately 100 nm, and its intensity is greatly enhanced, which is higher than that of incident light. The spot shape gradually changes from ellipse to round at the distance of more than 12 nm to the output plane. The above-simulated results are further demonstrated by the static optical recording experiment. (C) 2005 American Institute of Physics.

Making experiment station results more useful to African fish farmers

Rather than using more or less ideal conditions for setting experimental controls, the use of conditions similar to those likely to be encountered by farmers should produce research results which are realistically achievable on the farm. ICLARM has developed an approach to farmer-led experimentation which utilizes a spreadsheet to collate and analyze data collected from participating farmers. The simulation of actual management practices utilized by farmers produced results in replicated on-station trials which were within 11% of net yields on-farm. In addition to giving researchers a tool for comparing farm and station management practices, giving farmers a realistic indication of what yields will be if a technology is adopted should help overcome the problems of disillusionment often encountered when farm results fall below those expected by researchers on the basis of experiment station studies.

Vortex filament simulation of trailing vortex merger

Aircraft in high-lift configuration shed multiple vortices. These generally merge to form a downstream wake consisting of two counter-rotating vortices of equal strength. The understanding of the merger of two co-rotating trailing vortices is important in evaluating the separation criteria for different aircraft to prevent wake vortex hazards during landing and take-off. There is no existing theoretical method on the basis of which such norms can be set. The present study is aimed at gaining a better understanding of the behaviour of wake vortices behind the aircraft. Two dimensional studies are carried out using the vortex blob method and compared with Bertenyi's experiment. It is shown that inviscid two dimensional effects are insufficient to explain the observations. Three dimensional studies, using the vortex filament method, are applied to the same test case. Two Lamb-Oseen profile vortices of the same dimensions and initial separation as the experiment are allowed to evolve from a straight starting condition until a converged steady flow is achieved. The results obtained show good agreement with the experimental distance to merger. Core radius and separation behaviour is qualitatively similar to experiment, with the exception of rapid increases at first. This may be partially attributable to the choice of filament-element length, and recommended further work includes a convergence study for this parameter. Copyright © 2005 by the American Institute of Aeronautics and Astronautics, Inc. All rights reserved.

A flame surface density approach to large-eddy simulation of premixed turbulent combustion

The flame surface density approach to the modeling of premixed turbulent combustion is well established in the context of Reynolds-averaged simulations. For the future, it is necessary to consider large-eddy simulation (LES), which is likely to offer major advantages in terms of physical accuracy, particularly for unsteady combustion problems. LES relies on spatial filtering for the removal of unresolved phenomena whose characteristic length scales are smaller than the computational grid scale. Thus, there is a need for soundly based physical modeling at the subgrid scales. The aim of this paper is to explore the usefulness of the flame surface density concept as a basis for LES modeling of premixed turbulent combustion. A transport equation for the filtered flame surface density is presented, and models are proposed for unclosed terms. Comparison with Reynolds-averaged modeling is shown to reveal some interesting similarities and differences. These were exploited together with known physics and statistical results from experiment and from direct numerical stimulation in order to gain insight and refine the modeling. The model has been implemented in a combustion LES code together with standard models for scalar and momentum transport. Computational results were obtained for a simple three-dimensional flame propagation test problem, and the relative importance of contributing terms in the modeled equation for flame surface density was assessed. Straining and curvature are shown to have a major influence at both the resolved and subgrid levels.