A small arc-heated plasma testing facility for thermal protection materials

Experimental research on a 150 kW arc-heated plasma testing facility was conducted. Stable plasma jets with different gas compositions, temperatures and velocities were obtained at chamber pressure between 400 Pa – 100 kPa. Stagnation ablation experiments were conducted on samples of typical super alloys used for thermal protection systems. The microstructure and hardness of alloys before and after ablation were compared.

Injection locked Fabry-Perot laser diodes for WDM passive optical network spare function

In this paper, a protection scheme for transmitters in wavelength-division-multiplexing passive optical network (WDM-PON) has been proposed and demonstrated. If any downstream transmitter encounters problems at the central office (CO), the interrupted communication can be restored immediately by injecting a Fabry-Perot laser diode (FP-LD) with the upstream lightwave corresponding to the failure transmitter. Compared with the conventional methods, this proposed architecture provides a cost-effective and reliable protection scheme employing a common FP-LD. In the experiment, a 1 36 protection capability was implemented with a 2.5 Gbit/s downstream transmission capability. (C) 2009 Elsevier B.V. All rights reserved.

Heat Transfer Problems Induced By Multi-shocks Interaction

Numerical simulations of the multi-shock interactions observable around hypersonic vehicles were carried out by solving Navier-Stokes equations with the AUSMPW scheme and the new type of the IV interaction created by two incident shock waves was investigated in detail. Numerical results show that the intersection point of the second incident shock with the bow shock plays important role on the flow pattern, peak pressures and heat fluxes. In the case of two incident shocks interacting with the bow shock at the same position, the much higher peak pressure and more severe heat transfer rate are induced than the classical IV interaction. The phenomenon is referred to as the multi-shock interaction and higher requirements will be imposed on thermal protection systems.

Processing network models of energy/environment systems

Processing networks are a variant of the standard linear programming network model which are especially useful for optimizing industrial energy/environment systems. Modelling advantages include an intuitive diagrammatic representation and the ability to incorporate all forms of energy and pollutants in a single integrated linear network model. Added advantages include increased speed of solution and algorithms supporting formulation. The paper explores their use in modelling the energy and pollution control systems in large industrial plants. The pollution control options in an ethylene production plant are analyzed as an example. PROFLOW, a computer tool for the formulation, analysis, and solution of processing network models, is introduced.

network and device-level impacts: performance and reliability of active i/o storage systems

中国计算机学会

Effect of network modifiers on spectroscopic properties of erbium-doped phosphate glasses

The integrated absorption cross section Sigma(abs), I peak emission cross section sigma(cmi), Judd-Ofeld intensity parameters Omega(iota) ( t = 2,4,6), and spontaneous emission probability A(R) of Er3+ ions were determined for Erbium doped alkali and alkaline earth phosphate glasses. It is found the compositional dependence of sigma(emi) 5 almost similar to that of Sigma(abs), which is determined by the sum, of Omega(1) (3 Omega(2) + 10 Omega(4) + 21 Omega(6)). In addition, the compositional dependence of Omega(1) was studied in these glass systems. As a result, compared with. Omega(4) and Omega(6) the Omega(2) has a stronger compositional dependence on the ionic radius and content of modifers. The covalency of Er-O bonds in phosphate glass is weaker than that in silicate glass, germanate glass, aluminate glass, and tellurate glass, since Omega(6) of phosphate glass is relatively large. A(R) is affected by the covalency of the Er3+ ion sites and corresponds to the Omega(6) value.

The response of antioxidant systems in Nostoc sphaeroides against UV-B radiation and the protective effects of exogenous antioxidants

UV radiation is one of many harmful factors found in space that are detrimental to organisms on earth in space exploration. In the present work, we examined the role of antioxidant system in Nostoc sphaeroides Kutz (Cyanobacterium) and the effects of exogenously applied antioxidant molecules on its photosynthetic rate under UV-B radiation. It was found that UV-B radiation promoted the activity of antioxidant system to protect photosystem 11 (PSII) and exogenously applied antioxidant: sodium nitroprusside (SNP) and N-acetylcysteine (NAC) had an obvious protection on PSII activity under UV-B radiation. The activity of superoxide dismutase (SOD, EC 1.15.1.1), catalase (CAT, EC 1.11.1.6), peroxidase (POD, EC 1.11.1.7) and content of NIDA (malondialdehyde) and ASC (ascorbate) were improved by 0.5 mM and 1 mM SNP, but 0.1 mM SNP decreased the activity of antioxidant system. Addition of exogenous NAC decreased the activity of SOD, POD, CAT and the content MDA and ASC. In contrast, exogenously applied NAC increased GSH content. The results suggest that exogenous SNP and NAC may protect algae by different mechanisms: SNP may play double roles as both sources of reactive free radicals as well as ROS scavengers in mediating the protective role of PSII on algae under UV-B radiation. On the other hand, NAC functions as an antioxidant or precursor of glutathione, which could protect PSII directly from UV-B radiation. (c) 2007 COSPAR, Published by Elsevier Ltd. All rights reserved.

Fabrication and characterization of active and sequential circuits utilizing Schottky-wrap-gate-controlled GaAs hexagonal nanowire network structures

For realization of hexagonal BDD-based digital systems, active and sequential circuits including inverters, flip flops and ring oscillators are designed and fabricated on GaAs-based hexagonal nanowire networks controlled by Schottky wrap gates (WPGs), and their operations are characterized. Fabricated inverters show comparatively high transfer gain of more than 10. Clear and correct operation of hexagonal set-reset flip flops (SR-FFs) is obtained at room temperature. Fabricated hexagonal D-type flip flop (D-FF) circuits integrating twelve WPG field effect transistors (FETs) show capturing input signal by triggering although the output swing is small. Oscillatory output is successfully obtained in a fabricated 7-stage hexagonal ring oscillator. Obtained results confirm that a good possibility to realize practical digital systems can be implemented by the present circuit approach.

Determining of the delay time for a heating ventilating and air-conditioning plant using two weighted neural network approach

This paper presents an two weighted neural network approach to determine the delay time for a heating, ventilating and air-conditioning (HVAC) plan to respond to control actions. The two weighted neural network is a fully connected four-layer network. An acceleration technique was used to improve the General Delta Rule for the learning process. Experimental data for heating and cooling modes were used with both the two weighted neural network and a traditional mathematical method to determine the delay time. The results show that two weighted neural networks can be used effectively determining the delay time for AVAC systems.

The design algorithm of an associative memory neural network

A design algorithm of an associative memory neural network is proposed. The benefit of this design algorithm is to make the designed associative memory model can implement the hoped situation. On the one hand, the designed model has realized the nonlinear association of infinite value pattern from n dimension space to m dimension space. The result has improved the ones of some old associative memory neural network. On the other hand, the memory samples are in the centers of the fault-tolerant. In average significance the radius of the memory sample fault-tolerant field is maximum.

The image coding scheme based on neural network and SVM

This paper applies data coding thought, which based on the virtual information source modeling put forward by the author, to propose the image coding (compression) scheme based on neural network and SVM. This scheme is composed by "the image coding (compression) scheme based oil SVM" embedded "the lossless data compression scheme based oil neural network". The experiments show that the scheme has high compression ratio under the slightly damages condition, partly solve the contradiction which 'high fidelity' and 'high compression ratio' cannot unify in image coding system.

Lossless data compression scheme based on neural network and SVM

First, the compression-awaited data are regarded Lis character strings which are produced by virtual information source mapping M. then the model of the virtual information source M is established by neural network and SVM. Last we construct a lossless data compression (coding) scheme based oil neural network and SVM with the model, an integer function and a SVM discriminant. The scheme differs from the old entropy coding (compressions) inwardly, and it can compress some data compressed by the old entropy coding.

Ground target detection, classification and sensor fusion in distributed fiber seismic sensor network - art. no. 683015

This paper describes the ground target detection, classification and sensor fusion problems in distributed fiber seismic sensor network. Compared with conventional piezoelectric seismic sensor used in UGS, fiber optic sensor has advantages of high sensitivity and resistance to electromagnetic disturbance. We have developed a fiber seismic sensor network for target detection and classification. However, ground target recognition based on seismic sensor is a very challenging problem because of the non-stationary characteristic of seismic signal and complicated real life application environment. To solve these difficulties, we study robust feature extraction and classification algorithms adapted to fiber sensor network. An united multi-feature (UMF) method is used. An adaptive threshold detection algorithm is proposed to minimize the false alarm rate. Three kinds of targets comprise personnel, wheeled vehicle and tracked vehicle are concerned in the system. The classification simulation result shows that the SVM classifier outperforms the GMM and BPNN. The sensor fusion method based on D-S evidence theory is discussed to fully utilize information of fiber sensor array and improve overall performance of the system. A field experiment is organized to test the performance of fiber sensor network and gather real signal of targets for classification testing.

Structure approximate based on double weighted neural network

Double weighted neural network; is a kind of new general used neural network, which, compared with BP and RBF network, may approximate the training samples with a move complicated geometric figure and possesses a even greater approximation. capability. we study structure approximate based on double weighted neural network and prove its rationality.

Dynamic power management approaches based on neural network

Dynamic Power Management (DPM) is a technique to reduce power consumption of electronic system. by selectively shutting down idle components. In this article we try to introduce back propagation network and radial basis network into the research of the system-level policies. We proposed two PAY policies-Back propagation Power Management (BPPM) and Radial Basis Function Power management (RBFPM) which are based on Artificial Neural Networks (ANN). Our experiments show that the two power management policies greatly lowered the system-level power consumption and have higher performance than traditional Power Management(PM) techniques-BPPM is 1.09-competitive and RBFPM is 1.08-competitive vs. 1.79,145,1.18-competitive separately for traditional timeout PM, adaptive predictive PM and stochastic PM.