Nonlinear preconditioning for efficient and accurate interface capturing in simulation of multicomponent compressible flows

Single fluid schemes that rely on an interface function for phase identification in multicomponent compressible flows are widely used to study hydrodynamic flow phenomena in several diverse applications. Simulations based on standard numerical implementation of these schemes suffer from an artificial increase in the width of the interface function owing to the numerical dissipation introduced by an upwind discretization of the governing equations. In addition, monotonicity requirements which ensure that the sharp interface function remains bounded at all times necessitate use of low-order accurate discretization strategies. This results in a significant reduction in accuracy along with a loss of intricate flow features. In this paper we develop a nonlinear transformation based interface capturing method which achieves superior accuracy without compromising the simplicity, computational efficiency and robustness of the original flow solver. A nonlinear map from the signed distance function to the sigmoid type interface function is used to effectively couple a standard single fluid shock and interface capturing scheme with a high-order accurate constrained level set reinitialization method in a way that allows for oscillation-free transport of the sharp material interface. Imposition of a maximum principle, which ensures that the multidimensional preconditioned interface capturing method does not produce new maxima or minima even in the extreme events of interface merger or breakup, allows for an explicit determination of the interface thickness in terms of the grid spacing. A narrow band method is formulated in order to localize computations pertinent to the preconditioned interface capturing method. Numerical tests in one dimension reveal a significant improvement in accuracy and convergence; in stark contrast to the conventional scheme, the proposed method retains its accuracy and convergence characteristics in a shifted reference frame. Results from the test cases in two dimensions show that the nonlinear transformation based interface capturing method outperforms both the conventional method and an interface capturing method without nonlinear transformation in resolving intricate flow features such as sheet jetting in the shock-induced cavity collapse. The ability of the proposed method in accounting for the gravitational and surface tension forces besides compressibility is demonstrated through a model fully three-dimensional problem concerning droplet splash and formation of a crownlike feature. (C) 2014 Elsevier Inc. All rights reserved.

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.

Advances in Image Reconstruction Methods for Real-Time Magnetic Resonance Thermometry

Magnetic Resonance Imaging (MRI) has been widely used in cancer treatment planning, which takes the advantage of high-resolution and high-contrast provided by it. The raw data collected in the MRI can also be used to obtain the temperature maps and has been explored for performing MR thermometry. This review article describes the methods that are used in performing MR thermometry, with an emphasis on reconstruction methods that are useful to obtain these temperature maps in real-time for large region of interest. This article also proposes a prior-image constrained reconstruction method for temperature reconstruction in MR thermometry, and a systematic comparison using ex-vivo tissue experiments with state of the art reconstruction method is presented.

Simulation study of a two-stage adsorber system

The present study simulates a two-stage silica gel + water adsorption desalination (AD) and chiller system. The adsorber system thermally compresses the low pressure steam generated in the evaporator to the condenser pressure in two stages. Unlike a standalone adsorption chiller unit which operates in a closed cycle the present system is an open cycle wherein the condensed desalinated water is not fed back to the evaporator. The mathematical relations formulated in the current study are based on conservation of mass and energy along with isotherm relation and kinetics for RD-type silica gel + water pair. Various constitutive relations for each component namely the evaporator, adsorber and condenser are integrated in the model. The dynamics of heat exchanger are modeled using LMTD method, and LDF model is used to predict the dynamic characteristic of the adsorber bed. The system performance indicators namely, specific cooling capacity (SCC), specific daily water production (SDWP) and coefficient of performance (COP) are used as objective functions to optimize the system. The novelty of the present work is in introduction of inter-stage pressure as a new parameter for optimizing the two-stage operation of AD chiller system. (C) 2014 Elsevier Ltd. All rights reserved.

Simultaneous Perturbation Newton Algorithms for Simulation Optimization

We present a new Hessian estimator based on the simultaneous perturbation procedure, that requires three system simulations regardless of the parameter dimension. We then present two Newton-based simulation optimization algorithms that incorporate this Hessian estimator. The two algorithms differ primarily in the manner in which the Hessian estimate is used. Both our algorithms do not compute the inverse Hessian explicitly, thereby saving on computational effort. While our first algorithm directly obtains the product of the inverse Hessian with the gradient of the objective, our second algorithm makes use of the Sherman-Morrison matrix inversion lemma to recursively estimate the inverse Hessian. We provide proofs of convergence for both our algorithms. Next, we consider an interesting application of our algorithms on a problem of road traffic control. Our algorithms are seen to exhibit better performance than two Newton algorithms from a recent prior work.

Effects of refractive index mismatch in optical CT imaging of polymer gel dosimeters

Purpose: Proposing an image reconstruction technique, algebraic reconstruction technique-refraction correction (ART-rc). The proposed method takes care of refractive index mismatches present in gel dosimeter scanner at the boundary, and also corrects for the interior ray refraction. Polymer gel dosimeters with high dose regions have higher refractive index and optical density compared to the background medium, these changes in refractive index at high dose results in interior ray bending. Methods: The inclusion of the effects of refraction is an important step in reconstruction of optical density in gel dosimeters. The proposed ray tracing algorithm models the interior multiple refraction at the inhomogeneities. Jacob's ray tracing algorithm has been modified to calculate the pathlengths of the ray that traverses through the higher dose regions. The algorithm computes the length of the ray in each pixel along its path and is used as the weight matrix. Algebraic reconstruction technique and pixel based reconstruction algorithms are used for solving the reconstruction problem. The proposed method is tested with numerical phantoms for various noise levels. The experimental dosimetric results are also presented. Results: The results show that the proposed scheme ART-rc is able to reconstruct optical density inside the dosimeter better than the results obtained using filtered backprojection and conventional algebraic reconstruction approaches. The quantitative improvement using ART-rc is evaluated using gamma-index. The refraction errors due to regions of different refractive indices are discussed. The effects of modeling of interior refraction in the dose region are presented. Conclusions: The errors propagated due to multiple refraction effects have been modeled and the improvements in reconstruction using proposed model is presented. The refractive index of the dosimeter has a mismatch with the surrounding medium (for dry air or water scanning). The algorithm reconstructs the dose profiles by estimating refractive indices of multiple inhomogeneities having different refractive indices and optical densities embedded in the dosimeter. This is achieved by tracking the path of the ray that traverses through the dosimeter. Extensive simulation studies have been carried out and results are found to be matching that of experimental results. (C) 2015 American Association of Physicists in Medicine.

Image-Segmentation Technique to Analyze Deformation Profiles in Different Direct Shear Tests

Results from interface shear tests on sand-geosynthetic interfaces are examined in light of surface roughness of the interacting geosynthetic material. Three different types of interface shear tests carried out in the frame of direct shear-test setup are compared to understand the effect of parameters like box fixity and symmetry on the interface shear characteristics. Formation of shear bands close to the interface is visualized in the tests and the bands are analyzed using image-segmentation techniques in MATLAB. A woven geotextile with moderate roughness and a geomembrane with minimal roughness are used in the tests. The effect of surface roughness of the geosynthetic material on the formation of shear bands, movement of sand particles, and interface shear parameters are studied and compared through visual observations, image analyses, and image-segmentation techniques.

Super Resolution Using a Single Image Dictionary

To perform super resolution of low resolution images, state-of-the-art methods are based on learning a pair of lowresolution and high-resolution dictionaries from multiple images. These trained dictionaries are used to replace patches in lowresolution image with appropriate matching patches from the high-resolution dictionary. In this paper we propose using a single common image as dictionary, in conjunction with approximate nearest neighbour fields (ANNF) to perform super resolution (SR). By using a common source image, we are able to bypass the learning phase and also able to reduce the dictionary from a collection of hundreds of images to a single image. By adapting recent developments in ANNF computation, to suit super-resolution, we are able to perform much faster and accurate SR than existing techniques. To establish this claim, we compare the proposed algorithm against various state-of-the-art algorithms, and show that we are able to achieve b etter and faster reconstruction without any training.

Sparse coding based VLAD for efficient image retrieval

Representing images and videos in the form of compact codes has emerged as an important research interest in the vision community, in the context of web scale image/video search. Recently proposed Vector of Locally Aggregated Descriptors (VLAD), has been shown to outperform the existing retrieval techniques, while giving a desired compact representation. VLAD aggregates the local features of an image in the feature space. In this paper, we propose to represent the local features extracted from an image, as sparse codes over an over-complete dictionary, which is obtained by K-SVD based dictionary training algorithm. The proposed VLAD aggregates the residuals in the space of these sparse codes, to obtain a compact representation for the image. Experiments are performed over the `Holidays' database using SIFT features. The performance of the proposed method is compared with the original VLAD. The 4% increment in the mean average precision (mAP) indicates the better retrieval performance of the proposed sparse coding based VLAD.

SIMULATION STUDY OF THE ADSORPTION DYNAMICS OF CYLINDRICAL SILICA GEL PARTICLES

The paper presents a simulation study of loose cylindrically shaped particles packed within a copper plate and aluminum fins. The model presented solves coupled heat and mass transfer equations using the finite volume method based on ANSY S FLUENT medium. Three different arrangements of cylindrical particles are considered. The model is validated with experimental data. It is found that the arrangements which represented monolayer configurations are only marginally better in heat transfer and uptake efficiency than the tri-layer configuration in the presence of fins. However, there is an appreciable difference in the uptake curve between monoand tri-layer configurations in the absence of fins. Finally, it is found that the fin pitch also plays an important role in determining the time constant for the adsorber design.