Michell cantilevers constructed within a half strip. Tabulation of selected benchmark results

The paper delivers the benchmark results for the Michell cantilevers constructed within a half strip, for selected values of the σ _T /σ _C ratio, σ _T , σ _C being the admissible stresses in tension and compression, respectively.     

Chaotic self-adaptive particle swarm optimization algorithm for dynamic economic dispatch problem with valve-point effects

This paper presents a chaotic self-adaptive particle swarm optimization algorithm (CSAPSO) to solve dynamic economic dispatch problem (DED) with value-point effects. The proposed algorithm takes PSO as the main evolution method. The velocity, a sensitive parameter of PSO, is adjusted dynamically to increase the precision of PSO. To overcome the drawback of premature in PSO, chaotic local search is imported into proposed algorithm. Moreover, a new strategy is proposed to handle the various constraints of DED problem in this paper, the results solved by proposed strategy can satisfy the constraints of DED problem well. Finally, the high feasibility and effectiveness of proposed CSAPSO algorithm is validated by three test systems consisting of 10 and extended 30 generators while compared with the experimental results calculated by the other methods reported in this literature.     

Impact of ZnO gate interfacial layer on piezoelectric response of AlGaN/GaN C-HEMT based ring gate capacitor

We report on a piezoelectric response investigation of AlGaN/GaN circular high electron mobility transistor (C-HEMT) based ring gate capacitor as a new stress sensor device to be potentially applied for dynamic high-pressure sensing. A ring gate capacitor of C-HEMT with an additional ZnO gate interfacial layer was used to measure the changes in the piezoelectric charge induced directly by the variation of piezoelectric polarization of both gate piezoelectric layers (AlGaN, ZnO) for harmonic loading at different excitation frequences. Our experimental results show that about 10 nm thick piezoelectric ZnO layer grown on ring gate/AlGaN interface of C-HEMT can yield almost a 60% increase in the piezoelectric detection sensitivity of the device due to its higher piezoelectric coefficient. A three-dimensional CoventorWare simulation is carried out to confirm the increase in the measured piezoelectric response of ZnO based ring gate capacitor of C-HEMT.     

DFT and TD-DFT theoretical studies on photo-induced electron transfer process on [Cefamandole].C60 nano-complex

The C₆₀ fullerene displays a considerable electronegativity. It has a unique photophysical and electrochemical behavior that can be used as a suitable drug carrier. In the present study, the interaction of C₆₀ fullerene as an electron recipient with the Cefamandole antibiotic was investigated in both ground and excited states using DFT and TD-DFT methods. The study of the interaction of C₆₀ and Cefamandole via electron localization function (ELF) and reduced density gradient (RDG) revealed that the complex formation is of van der Waals type. The data from natural bonding orbitals (NBO) analysis also confirmed the interaction type. The study of absorption and emission spectrum via CAM-B3LYP in the TD-SCF state showed that the emission peak of C₆₀ fullerene in the 591.73 nm after the complex formation results in the extinction of this emission spectrum due to charge transfer (CT) from chelator to fluorophore. The photoinduced electron transfer (PET) process was investigated using the electron hole theory.     

Prediction of landslide displacement with controlling factors using extreme learning adaptive neuro-fuzzy inference system (ELANFIS)

Landslide is a major geo-environmental hazard which imparts serious threat to lives and properties. The slope failures are due to adverse inherent geological conditions triggered by an external factor. This paper proposes a new method for the prediction of displacement of step-like landslides, by accounting the controlling factors, using recently proposed extreme learning adaptive neuro-fuzzy inference system (ELANFIS) with empirical mode decomposition (EMD) technique. ELANFIS reduces the computational complexity of conventional ANFIS by incorporating the theoretical idea of extreme learning machines (ELM). The rainfall data and reservoir level elevation data are also integrated into the study. The nonlinear original landslide displacement series, rainfall data, and reservoir level elevation data are first converted into a limited number of intrinsic mode functions (IMF) and one residue. Then decomposed displacement data are predicted by using appropriate ELANFIS model. Final prediction is obtained by the summation of outputs of all ELANFIS sub models. The performance of proposed the technique is tested for the prediction Baishuihe and Shiliushubao landslides. The results show that ELANFIS with EMD model outperforms other methods in terms of generalization performance.     

Improved learning of I2C distance and accelerating the neighborhood search for image classification

Image-to-class (I2C) distance is a novel measure for image classification and has successfully handled datasets with large intra-class variances. However, due to the lack of a training phase, the performance of this distance is easily affected by irrelevant local features that may hurt the classification accuracy. Besides, the success of this I2C distance relies heavily on the large number of local features in the training set, which requires expensive computation cost for classifying test images. On the other hand, if there are small number of local features in the training set, it may result in poor performance.In this paper, we propose a distance learning method to improve the classification accuracy of this I2C distance as well as two strategies for accelerating its NN search. We first propose a large margin optimization framework to learn the I2C distance function, which is modeled as a weighted combination of the distance from every local feature in an image to its nearest-neighbor (NN) in a candidate class. We learn these weights associated with local features in the training set by constraining the optimization such that the I2C distance from image to its belonging class should be less than that to any other class. We evaluate the proposed method on several publicly available image datasets and show that the performance of I2C distance for classification can significantly be improved by learning a weighted I2C distance function. To improve the computation cost, we also propose two methods based on spatial division and hubness score to accelerate the NN search, which is able to largely reduce the on-line testing time while still preserving or even achieving a better classification accuracy.     

Optimization for limited angle tomography in medical image processing

This paper aims to reduce the problems of incomplete data in computed tomography, which happens frequently in medical image process and analysis, e.g., when the high-density region of objects can only be penetrated by X-rays at a limited angular range. As the projection data are available only in an angular range, the incomplete data problem can be attributed to the limited angle problem, which is an ill-posed inverse problem. Image reconstruction based on total variation (TV) reduces the problem and gives better performance on edge-preserving reconstruction; however, the artificial parameter can only be determined through considerable experimentation. In this paper, an effective TV objective function is proposed to reduce the inverse problem in the limited angle tomography. This novel objective function provides a robust and effective reconstruction without any artificial parameter in the iterative processes, using the TV as a multiplicative constraint. The results demonstrate that this reconstruction strategy outperforms some previous ones.     

A finite element scheme with a high order absorbing boundary condition for elastodynamics

A high-order absorbing boundary condition (ABC) is devised on an artificial boundary for time-dependent elastic waves in unbounded domains. The configuration considered is that of a two-dimensional elastic waveguide. In the exterior domain, the unbounded elastic medium is assumed to be isotropic and homogeneous. The proposed ABC is an extension of the Hagstrom–Warburton ABC which was originally designed for acoustic waves, and is applied directly to the displacement field. The order of the ABC determines its accuracy and can be chosen to be arbitrarily high. The initial boundary value problem including this ABC is written in second-order form, which is convenient for geophysical finite element (FE) analysis. A special variational formulation is constructed which incorporates the ABC. A standard FE discretization is used in space, and a Newmark-type scheme is used for time-stepping. A long-time instability is observed, but simple means are shown to dramatically postpone its onset so as to make it harmless during the simulation time of interest. Numerical experiments demonstrate the performance of the scheme.     

Prediction of rank deficiency in partition of unity-based methods with plane triangular or quadrilateral meshes

In the partition of unity (PU)-based methods, the global approximation is built by multiplying a partition of unity by local approximations. Within this framework, high-order approximations are achieved by directly adopting high-order polynomials as local approximations, and therefore nodes along sides or inside elements, which are usually adopted in the conventional finite element methods, are no more required. However, the PU-based approximation constructed in this way may suffer from rank deficiency due to the linear dependence of the global degrees of freedom. In this paper, the origin of the rank deficiency in the PU-based approximation space is first dissected at an element level, and then an approach to predict the rank deficiency for a mesh is proposed together with the principle of the increase of rank deficiency. Finally, examples are investigated to validate the present approach. The current work indicates such a fact that the rank deficiency is an unrelated issue to the nullity of the global matrix. It can be resolved in its own manner.     

Meshfree simulations of spall fracture

Shock wave induced spall fracture is a complex multiscale phenomenon, and it is a challenge to build a constitutive and computational model that can capture essential features of the spall fracture. In this work, we present a computational micro-mechanics model to simulate spall fracture by utilizing the multiscale micro-mechanics theory proposed by Wright and Ramesh [36] and a RKPM meshfree method. The focus of this work is to develop and demonstrate a simulation tool that is capable of simulations of spall fracture in engineering application. First, based on a well-known empirical formula, we relate the macroscale spall strength to the kinematics of micro void growth in a Representative Volume Element (RVE). The connection between micro void growth and overall kinematics of the RVE is made through the conservation of mass in the micro to macro transition process. Second, we develop a set of meshfree void growth algorithms that is tailored to represent kinematics of void nucleation, growth and coalescence, and these algorithms retain the conservation of mass, momentum, and energy during simulations of ductile spall fracture. Third, based on the Johnson–Cook model, we developed a meshfree computational formulation, and we have carried out simulations of the spall fracture of a Ti–6Al plate under impact loads to validate the model. From the simulation, we find that the interaction between the first two inelastic wave pulses plays an important role in the mechanism of spall fracture. The numerical results show that the proposed method can capture some features of the spall fracture, and it may be used to simulate the spall fracture in engineering applications.