A Review of Variational Multiscale Methods for the Simulation of Turbulent Incompressible Flows

Various realizations of variational multiscale (VMS) methods for simulating turbulent incompressible flows have been proposed in the past fifteen years. All of these realizations obey the basic principles of VMS methods: they are based on the variational formulation of the incompressible Navier–Stokes equations and the scale separation is defined by projections. However, apart from these common basic features, the various VMS methods look quite different. In this review, the derivation of the different VMS methods is presented in some detail and their relation among each other and also to other discretizations is discussed. Another emphasis consists in giving an overview about known results from the numerical analysis of the VMS methods. A few results are presented in detail to highlight the used mathematical tools. Furthermore, the literature presenting numerical studies with the VMS methods is surveyed and the obtained results are summarized.     

Ionic liquids for absorption and separation of gases: An extensive database and a systematic screening method

Ionic liquids (ILs) have attracted considerable attention in both the academic and industrial communities for absorbing and separating gases. However, a data‐rich and well‐structured systematic database has not yet been established, and screening for highly efficient ILs meeting various requirements remains a challenging task. In this study, an extensive database of estimated Henry's law constants of twelve gases in more than ten thousand ILs at 313.15 K is established using the COSMO‐RS method. Based on the database, a new systematic and efficient screening method for IL selection for the absorption and separation of gases subject to important target properties is proposed. Application of the database and the screening method is highlighted through case studies involving two important gases separation problems (CO₂ from CH₄ and C₂H₂ from C₂H₄). The results demonstrate the effectiveness of using the screening method together with the database to explore and screen novel ILs meeting specific requirements for the absorption and separation of gases. © 2017 American Institute of Chemical Engineers AIChE J, 63: 1353–1367, 2017     

Modeling of Moisture Diffusion in Microwave Drying of Hardwood

A one-dimensional mathematical model was developed to predict temperature and moisture content profiles in red maple (Acer rubrum L.) and white oak (Quercus alba) during microwave drying. The model was solved using the finite element analysis with MATLAB software. The predictions for temperature and moisture content agreed favorably well with the experimental data. The diffusion coefficients of the red maple and the white oak in microwave drying conditions were calculated and analyzed. Equations of the diffusion coefficient in longitudinal and transverse directions based on input microwave power level are presented in this article. In microwave drying of hardwood, the red maple was heated more efficiently than the white oak because of higher absorbing efficiency of the microwave power.     

Probabilistic opposition-based particle swarm optimization with velocity clamping

A probabilistic opposition-based Particle Swarm Optimization algorithm with Velocity Clamping and inertia weights (OvcPSO) is designed for function optimization—to accelerate the convergence speed and to optimize solution’s accuracy on standard benchmark functions. In this work, probabilistic opposition-based learning for particles is incorporated with PSO to enhance the convergence rate—it uses velocity clamping and inertia weights to control the position, speed and direction of particles to avoid premature convergence. A comprehensive set of 58 complex benchmark functions including a wide range of dimensions have been used for experimental verification. It is evident from the results that OvcPSO can deal with complex optimization problems effectively and efficiently. A series of experiments have been performed to investigate the influence of population size and dimensions upon the performance of different PSO variants. It also outperforms FDR-PSO, CLPSO, FIPS, CPSO-H and GOPSO on various benchmark functions. Last but not the least, OvcPSO has also been compared with opposition-based differential evolution (ODE); it outperforms ODE on lower swarm population and higher-dimensional functions.     

Automatic generation of multiple choice questions using dependency-based semantic relations

In this paper, we present an unsupervised dependency-based approach to extract semantic relations to be applied in the context of automatic generation of multiple choice questions (MCQs). MCQs also known as multiple choice tests provide a popular solution for large-scale assessments as they make it much easier for test-takers to take tests and for examiners to interpret their results. Manual generation of MCQs is a very expensive and time-consuming task and yet they often need to be produced on a large scale and within short iterative cycles. We approach the problem of automated MCQ generation with the help of unsupervised relation extraction, a technique used in a number of related natural language processing problems. The goal of Unsupervised relation extraction is to identify the most important named entities and terminology in a document and then recognise semantic relations between them, without any prior knowledge as to the semantic types of the relations or their specific linguistic realisation. We use these techniques to process instructional texts and identify those facts (terminology, entities, and semantic relations between them) that are likely to be important for assessing test-takers’ familiarity with the instructional material. We investigate an approach to learn semantic relations between named entities by employing a dependency tree model. Our findings show that an optimised configuration of our MCQ generation system is capable of attaining high precision rates, which are much more important than recall in the automatic generation of MCQs. We also carried out a user-centric evaluation of the system, where subject domain experts evaluated automatically generated MCQ items in terms of readability, usefulness of semantic relations, relevance, acceptability of questions and distractors and overall MCQ usability. The results of this evaluation make it possible for us to draw conclusions about the utility of the approach in practical e-Learning applications.     

Feature-Preserved 3D Canonical Form

Measuring the dissimilarity between non-rigid objects is a challenging problem in 3D shape retrieval. One potential solution is to construct the models’ 3D canonical forms (i.e., isometry-invariant representations in 3D Euclidean space) on which any rigid shape matching algorithm can be applied. However, existing methods, which are typically based on embedding procedures, result in greatly distorted canonical forms, and thus could not provide satisfactory performance to distinguish non-rigid models. In this paper, we present a feature-preserved canonical form for non-rigid 3D watertight meshes. The basic idea is to naturally deform original models against corresponding initial canonical forms calculated by Multidimensional Scaling (MDS). Specifically, objects are first segmented into near-rigid subparts, and then, through properly-designed rotations and translations, original subparts are transformed into poses that correspond well with their positions and directions on MDS canonical forms. Final results are obtained by solving nonlinear minimization problems for optimal alignments and smoothing boundaries between subparts. Experiments on two non-rigid 3D shape benchmarks not only clearly verify the advantages of our algorithm against existing approaches, but also demonstrate that, with the help of the proposed canonical form, we can obtain significantly better retrieval accuracy compared to the state of the art.     

CM-BOF: visual similarity-based 3D shape retrieval using Clock Matching and Bag-of-Features

Content-based 3D object retrieval has become an active topic in many research communities. In this paper, we propose a novel visual similarity-based 3D shape retrieval method (CM-BOF) using Clock Matching and Bag-of-Features. Specifically, pose normalization is first applied to each object to generate its canonical pose, and then the normalized object is represented by a set of depth-buffer images captured on the vertices of a given geodesic sphere. Afterwards, each image is described as a word histogram obtained by the vector quantization of the image’s salient local features. Finally, an efficient multi-view shape matching scheme (i.e., Clock Matching) is employed to measure the dissimilarity between two models. When applying the CM-BOF method in non-rigid 3D shape retrieval, multidimensional scaling (MDS) should be utilized before pose normalization to calculate the canonical form for each object. This paper also investigates several critical issues for the CM-BOF method, including the influence of the number of views, codebook, training data, and distance function. Experimental results on five commonly used benchmarks demonstrate that: (1) In contrast to the traditional Bag-of-Features, the time-consuming clustering is not necessary for the codebook construction of the CM-BOF approach; (2) Our methods are superior or comparable to the state of the art in applications of both rigid and non-rigid 3D shape retrieval.     

Electron beam melting of gamma titanium aluminide and investigating the effect of EBM layer orientation on milling performance

Electron beam melting (EBM) is one of the growing processes of additive manufacturing technology (AMT) to fabricate 3D parts from various difficult-to-process materials such as titanium alloys. A major limitation of the EBM process is the poor surface finish of the produced parts which ultimately demands a subsequent subtractive method (secondary finishing operation) to improve the surface finish for shaping the part to be fit for-end use applications where high surface finish is commonly required. With respect to the EBM layer build direction, the fabricated part has different orientations with varying surface characteristics. Therefore, in order to perform secondary finishing operation (e.g., milling) there are different choices of EBM part orientation to select the direction of tool feed. In this research, 3D parts of titanium alloy (gamma titanium aluminide; γ-TiAl) are additively manufactured through EBM process. The effect of EBM layer/part orientation on the milling performance is further investigated in terms of surface finish improvement and edge chipping evaluation. It has been observed that the EBM layer/part orientation with respect to milling tool feed direction (TFD) plays a vital role in milling performance. Thus, a care must be taken to select the appropriate tool feed direction and layer/part orientation in order to achieve maximum surface finish with minimum edge chipping. The results revealed the vertical milling can be adopted as a secondary finishing operation to be performed on EBM produced parts of γ-TiAl and it allows to significantly improve the poor surface finish generated by EBM (R_a 31 μm). Furthermore, among the available part orientation choices, the part orientation in which the milling tool is fed across the EBM layer build direction is the best orientation resulting into high surface finish (R_a 0.12 μm) with relatively smooth edges (minimum chipping-off).     

Effect of Cathode Designs on Radiation Emission of Compact Diode (CD) Device

A comparative study on the radiation emission such as X-ray yield and efficiency has been carried out in compact diode device. Two different designs of cathode having sharp-edged razor blade (of 0.5 mm thickness with width 2 mm) and a sewing machine needle (of 0.5 mm diameter at tip with length of 39 mm) have been tested for this study. The radiation emission (X-ray yield) was determined by employing two set of PIN diodes at fixed positions. The maximum X-ray yield depends on cathode designs and electrodes separation in few mm. The yield of X-ray is small in the case of sharp-edged razor blade cathode than the sewing machine needle cathode. The X-ray yield, measured by 4π-geometry, shows its dependence on the cathode designs. The maximum X-ray yield is found to be 939.2 ± 65.7 mJ with efficiency of 0.4142 ± 0.0289%. This study indicates that the compact diode device could be optimized to a great extent for optimal X-ray yield by using an appropriate cathode design.     

Nature-inspired heuristic paradigms for parameter estimation of control autoregressive moving average systems

Neural Computing and Applications - Aim of this research is to explore the strength of evolutionary and swarm intelligence techniques for parameter identification of control autoregressive moving...