bluuebunny/crossref_metadata_2025_split huggingface dataset:
A possible quantitative Mueller matrix transformation technique for anisotropic scattering media/Eine mögliche quantitative Müller-Matrix-Transformations-Technik für anisotrope streuende Medien
Authors: He Honghui , Zeng Nan , Du E , Guo Yihong , Li Dongzhi , Liao Ran , Ma Hui 
Published: February 2013

AbstractBy conducting both the experiments on samples containing well-aligned fibers and Monte Carlo simulations based on the sphere cylinder scattering model (SCSM), we present a Mueller matrix transformation (MMT) method for quantitatively characterizing the properties of anisotropic scattering media. We obtained a set of parameters by fitting the Mueller matrix elements to trigonometric curves in polar coordinates. These new parameters can be expressed as analytical functions of the Mueller matrix elements and display simple relationships to the structural and optical properties of the anisotropic scattering media, such as the anisotropy, the direction of the fibers, and the sizes of the scatterers. Experimental results on biological tissues show that these new parameters can be used in biomedical research. However, further studies are still necessary to correlate the MMT parameters to pathological features.
Influence of Lightweight Deflectometer Characteristics on Deflection Measurement
Authors: Stamp David H. , Mooney Michael A. 
Published: February 2013

Abstract
The lightweight deflectometer (LWD) is currently not standardized; as a result, there are a number of commercially available LWD designs that yield different deflection and elastic modulus values. This proves problematic because transportation agencies are beginning to prescribe target deflections and/or elastic modulus values during earthwork construction. This paper presents the results of a comprehensive investigation into the influence of LWD design characteristics on measured deflection. The influence of the sensor type (accelerometer versus geophone), sensing configuration (measurement of plate versus ground surface), LWD rigidity, and applied load pulse were investigated through field testing and finite element analysis. The investigation revealed that the sensing configuration (i.e., the measurement of plate versus ground surface response) is the predominant cause of differences between the Zorn and Prima LWD responses (deflection normalized by peak force). Vertical plate deflection exceeded ground surface deflection by 65 % to 310 % on soils and by 20 % on asphalt. The relative influences of the sensor type (accelerometer versus geophone), plate rigidity, and load pulse each led to relatively small differences (&lt;10 %) between Zorn and Prima LWD responses. The results of this investigation illustrate that each of the two LWD configurations will always produce different deflection and elastic modulus values for the same ground conditions, and that the differences will be difficult to predict.
Crystal structure of phosphido-tris-(triphenylphosphine)copper(I)acetone solvate, C57H51CuOP4
Authors: Hill Tania N. 
Published: February 2013

Abstract C57H51CuOP4, triclinic, P1̄ (no. 2), a = 11.2814(8) Å, b = 13.585(1) Å, c = 15.666(1) Å, α = 88.785(4)°, β = 84.288(3)°, γ = 85.103(3)°, V = 2380.1 Å3, Z = 2, Rgt(F) = 0.0444, wRref(F2) = 0.1159, T = 100 K.
Ab-initio structure determination of novel strontium-containing layered silicate AES-18 synthesized using mechanochemical reaction
Authors: Ikeda Takuji , Ideta Chiaki , Yamamoto Katsutoshi 
Published: February 2013

Abstract
A new strontium-containing layered silicate, alkaline earth-containing silicate (AES)-18 [chemical composition: Si16O24(OH)16 · {Sr(OH)2}8 · (KOH)2], was synthesized utilizing a mechanochemical reaction in which an admixture of strontium hydroxide, which unfavorably precipitates in conventional syntheses, and a fumed silica (Aerosil) was allowed to react in the solid phase. The crystal structure of AES-18 was elucidated by the charge-flipping method using powder X-ray diffraction data, and the obtained structure was refined by a combination with the Rietveld method and the maximum entropy method (MEM). The structure analyses showed a tetragonal symmetry with a = 0.912738(3) nm, c = 1.628120(8) nm, and the space group P42/mnc. Two silicate layers composed of Q3 local structure [(—SiO)3Si—OH], 7-coordinated Sr2+ catäions, and K+ cations were included in a unit cell, and a Sr4(OH)17 cluster was formed between adjacent silicate layers. The framework topology of AES-18 containing 4- and 8-Si-membered rings was similar to that of paracelsian.
Investigation of biocompatibility on nitrogen-doped a-C:H film coating scaffold surface in in-vivo and in-vitro tests
Authors: Ohgoe Yasuharu , Wada Tomoaki , Shiraishi Yasuyuki , Miura Hidekazu , Hirakuri Kenji K. , Funakubo Akio , Yambe Tomoyuki , Fukui Yasuhiro 
Published: February 2013

ABSTRACTIn this study, in order to investigate biocompatibility of nitrogen-doped hydrogenated amorphous carbon (a-C:H:N) film coating segmented polyurethane (SPU) scaffold fiber sheet (a-C:H:N-Scaffold) in in-vitro test, mouse fibroblasts (NIH 3T3) cells were grown on the a-C:H:N-Scaffold. The cell behavior was monitored by time-lapse imaging system. Additionally, the a-C:H:N-Scaffold was implanted at partial aorta descendens of a goat for 35 days. The surface morphology, composition, and wettability of the a-C:H:N-scaffold was estimated by Scanning Electron Microscope (SEM), X-ray photoelectron spectrometer (XPS), and contact angle measurement. In in-vitro test, it was observed that a-C:H:N film coating had a facilitatory effect on cell motility and cell growth. In in-vivo test, it was observed that the a-C:H:N-Scaffold surface was uniformly covered by neointima. The a-C:H:N-Scaffold surface had no thrombus formation as an inflammatory reaction and it was shown that the a-C:H:N film coating had a good blood compatibility. These results suggest that a-C:H:N film coating has good cytocompatibility and blood compatibility and it is a promising approach for improvement of biocompatibility of biomaterial surfaces.
Crystal Structure of Non-Doped and Sn-Doped α-(GaFe)2O3Thin Films.
Authors: Kaneko Kentaro , Akaiwa Kazuaki , Fujita Shizuo 
Published: February 2013

ABSTRACTCorundum structured α-(GaFe)2O3alloy thin films were obtained on c-plane sapphire substrates by the mist chemical vapor deposition method. Wide range of X-ray diffraction 2θ/θ scanning measurements indicated that these crystals were epitaxially grown on c-plane sapphire substrates and these are no other crystal oriented phase. The cross-sectional and plane-view transmission electron microscope images showed the growth along the c-axis of α-(GaFe)2O3thin films on sapphire substrates, forming joint of columnar structure. The non-doped α-(GaFe)2O3thin films showed ferromagnetic properties at 300 K, though the origin of ferromagnetism still remained unresolved. In order to enhance the spin-carrier interaction, Sn doped α-(GaFe)2O3alloy thin films were fabricated on c-plane sapphire substrates. X-ray diffraction 2θ/θ and ω scanning measurement results indicated that the highly-crystalline films were epitaxially grown on substrates in spite of the Sn-doping.
A Review of the Role of Excess si in SIO2 at the Growing Oxide Interface.
Authors: Jaccodine Ralph 
Published: February 2013

AbstractThis paper discusses the issues that arise when ab excess of Si or SiO flux is used to adjust the Deal -Grove model to match the observed growth in the early stages of oxidation. The author uses the insight gained from the modeling of the oxidation of Si-Ge alloys as a background to the discussion. A recent simulation of the thin oxide problem by M. Uematsu et.al. invokes the role of “excess Si” near the interface to adjust the D&G reaction coefficient and also add additional flux to the growing oxide.This paper assesses some of the points in this model as well as the relation with sub bonded Si and/or the reaction barrier layer to oxidationmechanism. A recent proposal by Pasquarello et.al opens new insight into the way the interface may adjust to the growing oxide which challenges our previous mechanistic notions.
A Critical Assessment of Several Reservoir Simulators for Modeling Chemical Enhanced Oil Recovery Processes
Authors: Goudarzi Ali , Delshad Mojdeh , Sepehrnoori Kamy 
Published: February 2013

Abstract
Interest in chemical enhanced oil recovery (CEOR) processes has intensified in recent years because of rising oil prices as well as the advancement in chemical formulations and injection techniques. Polymer (P), surfactant/polymer (SP), and alkaline/surfactant/polymer (ASP) are techniques for improving sweep and displacement efficiencies with the aim of improving oil production in both secondary and tertiary floods. Chemical flooding has much broader range of applicability than the past. These include high temperature reservoirs, formations with extreme salinity and hardness, naturally fractured carbonates, and sandstone reservoirs with heavy and viscous crude oils.
More oil reservoirs are reaching maturity where secondary polymer floods and tertiary surfactant methods have become increasingly important. This significance has added to the industry's interest in using reservoir simulator as a tool for reservoir evaluation and management to minimize costs and increase the process efficiency. Reservoir simulators with special features are needed to represent coupled chemical and physical processes present in CEOR processes. The simulators need to be first validated against well controlled lab and pilot scale experiments to have reliable predictions of the full field implementations.
The available data from laboratory scale include 1) phase behavior and rheological data, 2) results of secondary and tertiary coreflood experiments for P, SP, and ASP floods under reservoir conditions, i.e. chemical retentions, pressure drop, and oil recovery. Data collected from corefloods are used as benchmark tests comparing numerical reservoir simulators with CEOR modeling capabilities such as STARS of CMG, ECLIPSE-100 of Schlumberger, REVEAL of Petroleum Experts, and UTCHEM from The University of Texas at Austin. The research UTCHEM simulator is included since it has been the benchmark for chemical flooding simulation for over 25 years.
The results of this benchmark comparison will be utilized to improve chemical design for field-scale studies using commercial simulators. The benchmark tests illustrate the potential of commercial simulators for chemical flooding projects and provide a comprehensive table of strength and limitation of each simulator for a given CEOR process. Mechanistic simulations of chemical EOR processes will provide predictive capability and can aid in optimization of the field injection projects. The objective of this paper is not to compare the computational efficiency and solution algorithms and only focus on the process modeling comparison.
An Ensemble Based Nonlinear Orthogonal Matching Pursuit Algorithm for Sparse History Matching of Reservoir Models
Authors: Elsheikh Ahmed H. , Wheeler Mary F. , Hoteit Ibrahim 
Published: February 2013

Abstract
A nonlinear orthogonal matching pursuit (NOMP) for sparse calibration of reservoir models is presented. Sparse calibration is a challenging problem as the unknowns are both the non-zero components of the solution and their associated weights. NOMP is a greedy algorithm that discovers at each iteration the most correlated components of the basis functions with the residual. The discovered basis (aka support) is augmented across the nonlinear iterations. Once the basis functions are selected from the dictionary, the solution is obtained by applying Tikhonov regularization. The proposed algorithm relies on approximate gradient estimation using an iterative stochastic ensemble method (ISEM). ISEM utilizes an ensemble of directional derivatives to efficiently approximate gradients. In the current study, the search space is parameterized using an overcomplete dictionary of basis functions built using the K-SVD algorithm.
Multiscale Simulation of CHOPS Wormhole Networks
Authors: Vanderheyden Brian , Jayaraman Balaji , Ma Xia , Zhang Duan 
Published: February 2013

Abstract
Cold Heavy Oil Production with Sand (CHOPS) is a well-known primary heavy oil recovery method. In CHOPS, a key mechanism of production is the formation of wormholes. Wormholes are believed to be nearly cylindrical zones of high permeability that originate from production wells when sand is produced along with the oil. A multi-scale modelling approach based on the multiphase material point method (MMPM) has been applied to the problem of developing a general predictive capability for CHOPS and wormhole growth. The MMPM is a Lagrangian-Eulerian methodology which permits simulation of multiphase flow problems with fluid-structure interaction in which there is substantial material deformation, damage and failure. MMPM is applied to the problem of simulating the growth of a wormhole in unconsolidated sand with live oil including the effect of foamy oil and sand failure. The simulation results show general features such as asymmetry and slugging. Comparison with experimental data for wormhole length with time was favourable. Up-scaling of the method is required to make predictions on the well to field scale. For this purpose, an up-scaled pressure-field-driven scheme has been developed to predict wormhole network structure. It is hypothesized that a pressure-field-based approached is adequate for a macroscopic simulation with resolution above the length scale of the wormhole tips at which the tensor nature of the failure mechanics are more important. The model includes a generalized sand failure criterion that couples with a non-linear pressure equation and foamy oil and sand flow equations. The model resolves separate wormhole regions emerging from the CHOPS pilot well. Robust history matching of commercial pilot production data is provided as partial model validation.
Nonlinear Complexity Reduction for Fast Simulation of Flow in Heterogeneous Porous Media
Authors: Gildin Eduardo , Ghasemi Mohammadreza , Romanovskay Anastasiya , Efendiev Yalchin 
Published: February 2013

Abstract
Reduced order modeling techniques have been investigated in the context of reservoir simulation and optimization in the past decade in order to mitigate the computational cost associated with the large-scale nature of the reservoir models. Although great progress has been made in basically two fronts, namely, upscaling and model reduction, there has not been a consensus which method (or methods) is preferable in terms of the trade-offs between accuracy and robustness, and if they indeed, result in large computational savings. In the particular case of model reduction, such as the proper orthogonal decomposition (POD), in order to capture the nonlinear behavior of such models, many simulations or experiments are needed prior to the actual online computations and there in not a clear way to deal with the projection of the reduced basis onto the nonlinear terms for fast implementations.
This paper presents a step forward to reduced-order modeling in the reservoir simulation framework. In order to overcome the issues with the nonlinear projections, we proposed to use the POD-DEIM algorithm, based on POD combined with the discrete em- pirical interpolation method (DEIM) proposed for the solution of large-scale partial differential equations. The DEIM is based on the approximation of the nonlinear terms by means of an interpolatory projection of few selected snapshots of the nonlinear terms. In this case, computational savings can be obtained in a forward run of nonlinear models.
Also, in order to incorporate information from the multiple length of scales, especially in the case of highly heterogeneous porous media, we suggest the local-global model reduction framework using the multiscale modeling framework. In this case, we will extend the use of the balanced truncation formulation and show how to couple both frameworks.
Beyond Dual-Porosity Modeling for the Simulation of Complex Flow Mechanisms in Shale Reservoirs
Authors: Yan Bicheng , Wang Yuhe , Killough John E. 
Published: February 2013

Abstract
The state of the art of modeling fluid flow in shale reservoirs is dominated by dual porosity models which divide the reservoirs into matrix blocks that significantly contribute to fluid storage and fracture networks which principally control flow capacity. However, recent extensive microscopic studies reveal that there exist massive micro- and nano-pore systems in shale matrices. Because of this, the actual flow mechanisms in shale reservoirs are considerably more complex than can be simulated by the conventional dual porosity models and Darcy’s Law. Therefore, a model capturing multiple pore scales and flow can provide a better understanding of complex flow mechanisms occurring in these reservoirs.
Through the use of a unique simulator this paper presents a micro-scale multiple-porosity model for fluid flow in shale reservoirs by capturing the dynamics occurring in three separate porosity systems: organic matter (mainly kerogen), inorganic matter, natural fractures. Inorganic and organic portions of shale matrix are treated as sub-blocks with different attributes, such as wettability and pore structures. In the organic matter or kerogen, gas desorption and diffusion are the dominant physics. Since the flow regimes are sensitive to pore size, the effects of nanopores and vugs in kerogen are incorporated into the simulator. The separate inorganic sub-blocks mainly contribute to the ability to better model dynamic water behavior. The multiple porosity model is built upon a unique tool for simulating general multiple porosity systems in which several porosity systems may be tied to each other through arbitrary transfer functions and connectivities. This new model allows us to better understand complex flow mechanisms and in turn is extended into the reservoir scale considering hydraulic fractures through upscaling techniques. Sensitivity studies on the contributions of the different flow mechanisms and kerogen properties give some insight as to their importance. Results also include a comparison of the conventional dual porosity treatment and show that significant differences in fluid distributions and dynamics are obtained with the improved multiple porosity simulation. Finally a case for reservoir-scale model covering organic matter, inorganic matter, natural fractures and hydraulic fractures is presented and will allow operators to better predict ultimate recovery from shale reservoirs.
A New Lattice Boltzmann Equation to Simulate Density-Driven Convection of Carbon Dioxide
Authors: Allen Rebecca , Reis Tim , Sun Shuyu 
Published: February 2013

Abstract
The storage of CO2 in fluid-filled geological formations has been carried out for more than a decade in locations around the world. After CO2 has been injected into the aquifer and has moved laterally under the aquifer’s cap-rock, density-driven convection becomes an important transport process to model. However, the challenge lies in simulating this transport process accurately with high spatial resolution and low CPU cost. This issue can be addressed by using the lattice Boltzmann equation (LBE) to formulate a model for a similar scenario when a solute diffuses into a fluid and density differences lead to convective mixing. The LBE is a promising alternative to the traditional methods of computational fluid dynamics. Rather than discretizing the system of partial differential equations of classical continuum mechanics directly, the LBE is derived from a velocity-space truncation of the Boltzmann equation of classical kinetic theory.
We propose an extension to the LBE, which can accurately predict the transport of dissolved CO2 in water, as a step towards fluid-filled porous media simulations. This is achieved by coupling two LBEs, one for the fluid flow and one for the convection and diffusion of CO2. Unlike existing lattice Boltzmann equations for porous media flow, our model is derived from a system of moment equations and a Crank-Nicolson discretization of the velocity-truncated Boltzmann equation. The forcing terms are updated locally without the need for additional central difference approximation. Therefore our model preserves all the computational advantages of the single-phase lattice Boltzmann equation and is formally second-order accurate in both space and time. Our new model also features a novel implementation of boundary conditions, which is simple to implement and does not suffer from the grid-dependent error that is present in the standard "bounce-back" condition.
The significance of using the LBE in this work lies in the ability to efficiently simulate density-driven convection of CO2 through water. From an implementation viewpoint, the locality of our algorithm exploits massively parallel modern computer architectures, including graphics processing units (GPUs), which would lead to very fast computations that scale linearly with the number of processors.
Efficient Markov Chain Monte Carlo Sampling Using Polynomial Chaos Expansion
Authors: Bazargan Hamid , Christie Mike , Tchelepi Hamdi 
Published: February 2013

Abstract
Markov Chain Monte Carlo (MCMC) methods are often used to probe the posterior probability distribution in inverse problems. This allows for computation of estimates of uncertain system responses conditioned on given observation data by means of approximate integration. However, these methods suffer from the computational complexities in reservoir simulation. It is hence of great interest to propose a sparse approximation technique to represent the posterior probability density function and conditional expectations given the data.
Polynomial Chaos Expansion (PCE) is a powerful tool to quantify uncertainty in dynamical systems when there is probabilistic uncertainty in the system parameters. In reservoir simulation it has been shown to be more accurate and efficient compared with traditional experimental design (ED). PCEs have a significant advantage over other response surfaces as the convergence to the true probability distribution when the order of the PCE is increased can be proved. PCEs as applied with Non-Intrusive Spectral Projection (NISP) to compute the coefficients, have successfully and efficiently approximated the distribution of output random variables of interest such as cumulative oil production. Accordingly polynomial chaos proxy can be used as the pseudo-simulator to represent the probability density function of the uncertain variables.
We propose the application of polynomial chaos proxy as applied with the MCMC method to efficiently sample from the posterior probability density function of the system parameters. We present a two dimensional example of fluvial channels to demonstrate that with a few hundred trial runs of the actual reservoir simulator, it is feasible to construct a polynomial chaos proxy which accurately approximates the posterior distribution of the high permeability zones, in an analytical form. We show that precision improves as the order of PCE and the number of trial runs used to calculate the PCE coefficients is increased. Then we use Markov Chain Monte Carlo methods to sample from this sparse analytical representation of the posterior distribution.