A Computational Study of Thrust Vectoring Control Using Dual Throat Nozzle

Dual throat nozzle （DTN） is fast becoming a popular technique for thrust vectoring. The DTN is designed with two throats, an upstream minimum and a downstream minimum at the nozzle exit, with a cavity in between the upstream throat and exit. In the present study, a computational work has been carried out to analyze the performance of a dual throat nozzle at various mass flow rates of secondary flow and nozzle pressure ratios （NPR）. Two-dimensional, steady, compressible Navier-Stokes equations were solved using a fully implicit finite volume scheme. The present computational results were validated with available experimental data. Based on the present results, the control effectiveness of thrust-vectoring is discussed in terms of the thrust coefficient and the coefficient of discharge.     

Using the condenser effluent from a nuclear power plant for Ocean Thermal Energy Conversion (OTEC)

There has been increasing interest in clean energy over past few years. Ocean Thermal Energy Conversion (OTEC) power plants have been examined as a viable option for supplying clean energy. This paper evaluated the thermodynamic performance of the OTEC power system. Computer simulation programs were developed under the same conditions but with various working fluids for a closed system, a regeneration system, an open system, a Kalina system, and a hybrid system. The results showed that the regeneration system using R125 showed a 0.17 to 1.56% increase in system efficiency. Moreover, the system can generate electricity when the difference in temperature between the warm and cold seawater inlet temperatures is greater than 15 °C. In addition, the system efficiency of OTEC power plants using the condenser effluent from a nuclear power plant instead of surface water was increased by approximately 2%.     

CO oxidation from syngas (CO and H<Subscript>2</Subscript>) using nanoporous Pt/Al<Subscript>2</Subscript>O<Subscript>3</Subscript> catalyst

The concept of “waste-to-wealth” is spreading awareness to prevent global warming and recycle the restrictive resources. To contribute towards sustainable development, hydrogen energy is obtained from syngas (CO and H₂) generated from waste gasification, followed by CO oxidation and CO₂ removal. In H₂ generation, it is key to produce more purified H₂ from syngas using heterogeneous catalysts. In this respect, we prepared Pt/Al₂O₃ catalyst with nanoporous structure using precipitation method, and compared its catalytic activity with commercial alumina (Degussa). Based on the results of XRD and TEM, it was found that metal particles did not aggregate on the alumina surface and showed high dispersion. Optimum condition for CO conversion was 1.5 wt% Pt loaded on Al₂O₃ support, and pure hydrogen was obtained after removal of CO₂ gas.     

Development of a newly structured variable preload control device for a spindle rolling bearing by using an electromagnet

For high speed and high efficiency machining, the spindle of modern machine tools simultaneously requires high speed and high stiffness characteristics, and its range of use rotation is becoming wider. Both heavy cutting at low speed and light cutting at high speed must be carried out successively in series with a single machine tool spindle. As such, many studies are being carried out on variable preload control methods that apply a preload to a spindle rolling bearing, as an alternative to the existing fixed position preload and constant pressure preload methods. This paper introduces a newly structured variable preload control device that can arbitrarily adjust the preload applied to spindles employing a rolling bearing. The device controls the coil current on an electromagnet and thereby uses the magnetic force between the electromagnet and a magnetic substance to arbitrarily control the preload applied to the rolling bearing during operation. A prototype for the variable preload control device of the proposed structure was created and a functionality test was then carried out with a test bench prepared using a load cell. The operating principle of the proposed device was verified and the interrelationships between the coil current on the electromagnet and the preload applied to rolling bearing were analyzed through the functionality test. Lastly, the fabricated variable preload control device was applied to a prototype of a spindle system, and a rigidity test was carried out. The test results confirmed that the variable preload control device operates properly and smoothly.     

A shortcut method for the preliminary synthesis of process-technology pathways: An optimization approach and application for the conceptual design of integrated biorefineries

Synthesis and screening of technology alternatives is a key process-development activity in the process industries. Recently, this has become particularly important for the conceptual design of biorefineries. This work introduces a shortcut method for the synthesis and screening of integrated biorefineries. A structural representation (referred to as the chemical species/conversion operator) is introduced. It is used to track individual chemicals while allowing for the processing of multiple chemicals in processing technologies. The representation is used to embed potential configurations of interest. An optimization approach is developed to screen and determine optimum network configurations for various technology pathways using simple data. The solution to the optimization formulation provides a quick and effective method for screening and interconnecting the technological pathways and to distributing the flows over the network. Case studies are solved to illustrate the applicability of the proposed approach.     

LANASOL(R)染料比媒介染料更适用于羊毛染色

欧洲化学品管理局(ECHA)现已将重铬酸盐列入了高关注物质(SVHC)的名单.用含有重铬酸钾和重铬酸钠等的媒介染料染制羊毛的工厂正面临着越来越大的压力.这意味着采用这种技术的染厂未来可能要得到特别授权才能使用这种化学品.     

Red-green-blue laser emissions from dye-doped poly(vinyl alcohol) films

A microscope slide acting as a passive waveguide was coated by three separate poly(vinyl alcohol) films that were doped with Coumarin 460, Disodium Fluorescein, and Rhodamine 640 perchlorate. On collinear pumping by a nitrogen laser, these dyes furnished primary red-green-blue laser emissions that were collected and waveguided by the microscope slide but exited from both ends. Frosting the waveguide exit introduced light scattering at the glass-air interface and spatially overlaid the red-green-blue laser emissions that emerged as a uniform white-light beam.     

The electro-adsorption chiller: a miniaturized cooling cycle with applications to micro-electronics

A novel modular and miniature chiller is proposed that symbiotically combines adsorption and thermoelectric cooling devices. The seemingly low efficiency of each cycle individually is overcome by an amalgamation with the other. This electro-adsorption chiller incorporates solely existing technologies. It can attain large cooling densities at high efficiency, yet is free of moving parts and comprises harmless materials. The governing physical processes are primarily surface rather than bulk effects, or involve electron rather than fluid flow. This insensitivity to scale creates promising applications in cooling personal computers and other microelectronic appliances.     

A Sparse Sampling Algorithm for Near-Optimal Planning in Large Markov Decision Processes

A critical issue for the application of Markov decision processes (MDPs) to realistic problems is how the complexity of planning scales with the size of the MDP. In stochastic environments with very large or infinite state spaces, traditional planning and reinforcement learning algorithms may be inapplicable, since their running time typically grows linearly with the state space size in the worst case. In this paper we present a new algorithm that, given only a generative model (a natural and common type of simulator) for an arbitrary MDP, performs on-line, near-optimal planning with a per-state running time that has no dependence on the number of states. The running time is exponential in the horizon time (which depends only on the discount factor and the desired degree of approximation to the optimal policy). Our algorithm thus provides a different complexity trade-off than classical algorithms such as value iteration—rather than scaling linearly in both horizon time and state space size, our running time trades an exponential dependence on the former in exchange for no dependence on the latter.Our algorithm is based on the idea of sparse sampling. We prove that a randomly sampled look-ahead tree that covers only a vanishing fraction of the full look-ahead tree nevertheless suffices to compute near-optimal actions from any state of an MDP. Practical implementations of the algorithm are discussed, and we draw ties to our related recent results on finding a near-best strategy from a given class of strategies in very large partially observable MDPs (Kearns, Mansour, & Ng. Neural information processing systems 13, to appear).