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  • Solution of Algebraic Lyapunov Equation on Positive-Definite Hermitian Matrices by Using Extended Hamiltonian Algorithm
  • Abstract This communique is opted to study the approximate solution of the Algebraic Lyapunov equation on the manifold of positive-definite Hermitian matrices. We choose the geodesic distance between -AHX - XA and P as the cost function, and put forward the Extended Hamiltonian algorithm (EHA) and Natural gradient algorithm (NGA) for the solution. Finally, several numerical experiments give you an idea about the effectiveness of the proposed algorithms. We also show the comparison between these two algorithms EHA and NGA. Obtained results are provided and analyzed graphically. We also conclude that the extended Hamiltonian algorithm has better convergence speed than the…
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  • Joint Bearing Mechanism of Coal Pillar and Backfilling Body in Roadway Backfilling Mining Technology
  • Abstract In the traditional mining technology, the coal resources trapped beneath surface buildings, railways, and water bodies cannot be mined massively, thereby causing the lower coal recovery and dynamic disasters. In order to solve the aforementioned problems, the roadway backfilling mining technology is developed and the joint bearing mechanism of coal pillar and backfilling body is presented in this paper. The mechanical model of bearing system of coal pillar and backfilling body is established, by analyzing the basic characteristics of overlying strata deformation in roadway backfilling mining technology. According to the Ritz method in energy variation principle, the elastic solution expression…
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  • Prediction of Compressive Strength of Various SCC Mixes Using Relevance Vector Machine
  • Abstract This paper discusses the applicability of relevance vector machine (RVM) based regression to predict the compressive strength of various self compacting concrete (SCC) mixes. Compressive strength data various SCC mixes has been consolidated by considering the effect of water cement ratio, water binder ratio and steel fibres. Relevance vector machine (RVM) is a machine learning technique that uses Bayesian inference to obtain parsimonious solutions for regression and classification. The RVM has an identical functional form to the support vector machine, but provides probabilistic classification and regression. RVM is based on a Bayesian formulation of a linear model with an appropriate…
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  • The Interface Stress Field in the Elastic System Consisting of the Hollow Cylinder and Surrounding Elastic Medium Under 3D Non-axisymmetric Forced Vibration
  • Abstract The paper develops and employs analytical-numerical solution method for the study of the time-harmonic dynamic stress field in the system consisting of the hollow cylinder and surrounding elastic medium under the non-axisymmetric forced vibration of this system. It is assumed that in the interior of the hollow cylinder the point-located with respect to the cylinder axis, non-axisymmetric with respect to the circumferential direction and uniformly distributed time-harmonic forces act. Corresponding boundary value problem is solved by employing of the exponential Fourier transformation with respect to the axial coordinate and by employing of the Fourier series expansion of these transformations. Numerical…
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  • Seepage-Stress-Damage Coupled Model of Coal Under Geo-Stress Influence
  • Abstract In the seepage-stress-damage coupled process, the mechanical properties and seepage characteristics of coal are distinctly different between pre-peak stage and post-peak stage. This difference is mainly caused by damage of coal. Therefore, in the process of seepage and stress analysis of coal under the influence of excavation or mining, we need to consider the weakening of mechanical properties and the development of fractures of damaged coal. Based on this understanding, this paper analyzes the influence of damage on mechanics and seepage behavior of coal. A coupled model is established to analyze the seepage-stress-damage coupled process of coal. This model implemented…
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  • Lower Bound Limit Analysis of Anisotropic Soils
  • Abstract Previous approaches can only tackle anisotropic problems with cohesion varying with direction. A novel linearization of the Mohr-Coulomb yield criterion associated with plane strain problem has been achieved by simulating the Mohr’s circle with orientation lines in σ-τ space, which allows for lower bound solution of soils with cohesion and friction coefficient varying with direction. The finite element lower limit analysis formulation using the modified anisotropic yield criterion is then developed. Several examples are given to illustrate the capability and effectiveness of the proposed numerical procedure for computing rigorous lower bounds for anisotropic soils.
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  • Three Phase Composite Cylinder Assemblage Model for Analyzing the Elastic Behavior of MWCNT-Reinforced Polymers
  • Abstract Evolution of computational modeling and simulation has given more emphasis on the research activities related to carbon nanotube (CNT) reinforced polymer composites recently. This paper presents the composite cylinder assemblage (CCA) approach based on continuum mechanics for investigating the elastic properties of a polymer resin reinforced by multi-walled carbon nanotubes (MWCNTs). A three-phase cylindrical representative volume element (RVE) model is employed based on CCA technique to elucidate the effects of inter layers, chirality, interspacing, volume fraction of MWCNT, interphase properties and temperature conditions on the elastic modulus of the composite. The interface region between CNT and polymer matrix is modeled…
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  • Fingerprint Liveness Detection from Different Fingerprint Materials Using Convolutional Neural Network and Principal Component Analysis
  • Abstract Fingerprint-spoofing attack often occurs when imposters gain access illegally by using artificial fingerprints, which are made of common fingerprint materials, such as silicon, latex, etc. Thus, to protect our privacy, many fingerprint liveness detection methods are put forward to discriminate fake or true fingerprint. Current work on liveness detection for fingerprint images is focused on the construction of complex handcrafted features, but these methods normally destroy or lose spatial information between pixels. Different from existing methods, convolutional neural network (CNN) can generate high-level semantic representations by learning and concatenating low-level edge and shape features from a large amount of labeled…
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Displaying 9651-9660 on page 966 of 10058. Per Page