A Dynamic Comprehensive Method for Landslide Control

A slope failure is developed due to progressive external loads and deteriorations of slope geomaterials, thus forming a progressive and dynamic development and occurrence of landslides. Site geological properties and other active factors such as hydrodynamic load and human activities are complex and usually unknown, thus this dynamic development and occurrence of landslides can only be understood through the progressive accumulation of knowledge on the landslides. For such a progressive process, this paper proposes a dynamic comprehensive control method for landslide control. This control method takes full advantage of updated monitoring data and site investigations of landslides, and emphasizes the implementation of possible measures for landslide control at reasonable stages and in different groups. These measures are to prevent the occurrence of a landslide disaster. As a case study, a landslide project at the Panluo open-pit iron mine is analyzed to illustrate this dynamic comprehensive control method.

Simulation of Coal Combustion by AUSM Turbulence-Chemistry Char Combustion Model and a Full Two-Fluid Model

An algebraic unified second-order moment (AUSM) turbulence-chemistry model of char combustion is introduced in this paper, to calculate the effect of particle temperature fluctuation on char combustion. The AUSM model is used to simulate gas-particle flows, in coal combustion in a pulverized coal combustor, together with a full two-fluid model for reacting gas-particle flows and coal combustion, including the sub-models as the k-epsilon-k(p) two-phase turbulence niodel, the EBU-Arrhenius volatile and CO combustion model, and the six-flux radiation model. A new method for calculating particle mass flow rate is also used in this model to correct particle outflow rate and mass flow rate for inside sections, which can obey the principle of mass conservation for the particle phase and can also speed up the iterating convergence of the computation procedure effectively. The simulation results indicate that, the AUSM char combustion model is more preferable to the old char combustion model, since the later totally eliminate the influence of particle temperature fluctuation on char combustion rate.

Parasitic feedthrough cancellation techniques for enhanced electrical characterization of electrostatic microresonators

Capacitive parasitic feedthrough is an impediment that is inherent to all electrically interfaced micron scale resonant devices, resulting in increased challenges to their integration in more complex circuits, particularly as devices are scaled to operate at higher frequencies for RF applications. In this paper, a technique to cancel the undesirable effects of capacitive feedthrough that was previously proposed is here developed for an on-chip implementation. The method reported in this paper benefits from the simplicity of its implementation, and its effectiveness is demonstrated in this paper. This technique is demonstrated for two disk-plate resonators that have been excited in the wine glass mode at 5.4 MHz, though applicable to almost any electrically interfaced resonator. Measurements of the electrical transmission from these resonators show that the magnitude of the frequency response of the system is enhanced by up to 19 dB, while the phase is found to shift through a full 180° about the resonant frequency. This method is proposed as a useful addition to other techniques for enhancing the measured response of electrostatic micromechanical resonators. © 2009 Elsevier B.V. All rights reserved.

Dissimilar autogenous full penetration welding of superalloy K418 and 42CrMo steel by a high power CWNd : YAG laser

Experiments of autogenous laser full penetration welding between dissimilar cast Ni-based superalloy K418 and alloy steel 42CrMo flat plates with 3.5 mm thickness were conducted using a 3 kW continuous wave (CW) Nd:YAG laser. The influences of laser welding velocity, flow rate of side-blow shielding gas, defocusing distance were investigated. Microstructure of the welded seam was characterized by optical microscopy (OM), scanning electron microscopy (SEM) and X-ray diffraction (XRD) and energy dispersive spectrometer (EDS). Mechanical properties of the welded seam were evaluated by microhardness and tensile strength testing. Results show that high quality full penetration laser-welded joint can be obtained by optimizing the welding velocity, flow rate of shielding gas and defocusing distance. The laser-welded seam have non-equilibrium solidified microstructures consisting of gamma-FeCr0.29Ni0.16C0.06 austenite solid solution dendrites as the dominant and very small amount of super-fine dispersed Ni3Al gamma' phase and Laves particles as well as MC needle-like carbides distributed in the interdendritic regions. Although the microhardness of the laser-welded seam was lower than that of the base metal, the strength of the joint was equal to that of the base metal and the fracture mechanism showed fine ductility. (c) 2007 Elsevier B.V. All rights reserved.

Convergence of the auxiliary particle implementation of the PHD filter

Optimal Bayesian multi-target filtering is in general computationally impractical owing to the high dimensionality of the multi-target state. The Probability Hypothesis Density (PHD) filter propagates the first moment of the multi-target posterior distribution. While this reduces the dimensionality of the problem, the PHD filter still involves intractable integrals in many cases of interest. Several authors have proposed Sequential Monte Carlo (SMC) implementations of the PHD filter. However, these implementations are the equivalent of the Bootstrap Particle Filter, and the latter is well known to be inefficient. Drawing on ideas from the Auxiliary Particle Filter (APF), a SMC implementation of the PHD filter which employs auxiliary variables to enhance its efficiency was proposed by Whiteley et. al. Numerical examples were presented for two scenarios, including a challenging nonlinear observation model, to support the claim. This paper studies the theoretical properties of this auxiliary particle implementation. $\mathbb{L}_p$ error bounds are established from which almost sure convergence follows.

Auxiliary particle implementation of the probability hypothesis density filter

Optimal Bayesian multi-target filtering is, in general, computationally impractical owing to the high dimensionality of the multi-target state. The Probability Hypothesis Density (PHD) filter propagates the first moment of the multi-target posterior distribution. While this reduces the dimensionality of the problem, the PHD filter still involves intractable integrals in many cases of interest. Several authors have proposed Sequential Monte Carlo (SMC) implementations of the PHD filter. However, these implementations are the equivalent of the Bootstrap Particle Filter, and the latter is well known to be inefficient. Drawing on ideas from the Auxiliary Particle Filter (APF), we present a SMC implementation of the PHD filter which employs auxiliary variables to enhance its efficiency. Numerical examples are presented for two scenarios, including a challenging nonlinear observation model.