Experimental Study of Non-Destructive Approach on PEMFC Stack Using Tri-Axis Magnetic Sensor Probe

In this paper, the current distribution in a 300-W-class PEMFC stack was investigated in order to determine the operating state of the stack. Measurements of the magnetic field were performed on several cells in the stack. The vector of the magnetic field expressed the direction of the macroscopic current, which was from the anode side to the cathode side. This direction matched the polarity of the stack. In the measurement results, current distributions differed among cells;each cell had a different performance. Furthermore, we have tried to evaluate faults, such as flooding, by measuring the magnetic field and variations in the voltage.

Performance and Economic Study of Oxy-fuel Gas Turbine Power Plant Utilizing Nuclear Steam Generator

The authors propose a new closed cycle oxy-fuel gas turbine power plant that utilizes a nuclear heat generator. A pressurized water reactor （PWR） is designed to supply saturated steam to an oxy-fuel gas turbine for a specific power output increase The saturated steam from the reactor can have lower pressure and temperature than those of an existing PWR. In this study, the authors estimated plant performances from a heat balance model based on a conceptual design of a hybrid plant and calculated the generating costs of the proposed plant from the Japanese cost data of an existing PWR plant and an liquefied natural gas （LNG） combined cycle gas turbine plant. The generating efficiency of an oxy-fuel gas turbine plant without a nuclear steam generator is estimated to be less than 35%. Based on this efficiency, with a nuclear steam generator contributing to the power output of the proposed hybrid plant, the corresponding generating efficiency is estimated to be around 45%, even if the steam conditions are lower than in an existing PWR. The generating costs are 15-20% lower than those calculated from the weighted heat performances of both an oxy-fuel gas turbine plant without a nuclear steam generator and an existing PWR plant.

A tree detection method based on trunk point cloud section in dense plantation forest using drone Li DAR data

Single-tree detection is one of the main research topics in quantifying the structural properties of forests. Drone Li DAR systems and terrestrial laser scanning systems produce high-density point clouds that offer great promise for forest inventories in limited areas. However, most studies have focused on the upper canopy layer and neglected the lower forest structure. This paper describes an innovative tree detection method using drone Li DAR data from a new perspective of the under-canopy structure. This method relies on trunk point clouds, with undercanopy sections split into heights ranging from 1 to 7 m, which were processed and compared, to determine a suitable height threshold to detect trees. The method was tested in a dense cedar plantation forest in the Aichi Prefecture, Japan, which has a stem density of 1140 stems·ha^(-1) and an average tree age of 42 years. Dense point cloud data were generated from the drone Li DAR system and terrestrial laser scanning with an average point density of 5000 and 6500 points·m^(-2), respectively. Tree detection was achieved by drawing point-cloud section projections of tree trunks at different heights and calculating the center coordinates. The results show that this trunk-section-based method significantly reduces the difficulty of tree detection in dense plantation forests with high accuracy(F1-Score=0.9395). This method can be extended to different forest scenarios or conditions by changing section parameters.

Low Steam Condition Heat Generator Combined with Advanced Oxy-Fuel Combustion LNG Gas Turbine for Power Generation

We propose a novel concept for power generation that involves the combination of a LSCHG （low-steam-condition heat generator）, such as a light water nuclear reactor or a biomass combustion boiler, with an advanced closed-cycle oxy-fuel combustion gas turbine-a type of complex and efficient oxy-fuel gas turbine. In this study, a LSCHG is designed to heat water to saturated steam of a few MPa, to assist in the generation of the main working fluids, instead of a compressor used in the advanced oxy-fuel gas turbine. This saturated steam can have a lower pressure and temperature than those of an existing nuclear power plant or biomass-fired power plant. We estimated plant performances in LHV （lower heating value） basis from a heat balance model based on a conceptual design of a plant for different gas turbine inlet pressures and temperatures of 1,300 ℃ and 1,500 ℃, taking into account the work to produce O2 and capture CO2. While the net power generating efficiencies of a reference plant are estimated to be about 52.0% and 56.0% at 1,300 ℃ and 1,500 ℃, respectively, and conventional LSCHG power plant is assumed to have an efficiency of about 35% or less for pressures of 2.5-6.5 MPa, the proposed hybrid plant achieved 42.8%-44.7% at 1,300 ℃ and 47.8%-49.2% at 1,500 ℃. In the proposed plant, even supposing that the generating efficiency of the LNG system in the proposed plant remains equal to that of the reference plant, the efficiency of LSCHG system can be estimated 37.4% for 6.5 MPa and 33.2% for 2.5 MPa, even though the LSHCG system may be regarded as consisting of fewer plant facilities than a conventional LSCHG power plant.

New Exact Traveling Wave Solutions of the Unstable Nonlinear Schrdinger Equations

The present paper studies the unstable nonlinear Schr¨odinger equations, describing the time evolution of disturbances in marginally stable or unstable media. More precisely, the unstable nonlinear Schr¨odinger equation and its modified form are analytically solved using two efficient distinct techniques, known as the modified Kudraysov method and the sine-Gordon expansion approach. As a result, a wide range of new exact traveling wave solutions for the unstable nonlinear Schr¨odinger equation and its modified form are formally obtained.

Computational Complexity of a Solution for Directed Graph Cooperative Games

Abstrac Khmelnitskaya et al.have recently proposed the average covering tree value as a new solution concept for cooperative transferable utility games with directed graph structure.The average covering tree value is defined as the average of marginal contribution vectors corresponding to the specific set of rooted trees,and coincides with the Shapley value when the game has complete communication structure.In this paper,we discuss the computational complexity of the average covering tree value.We show that computation of the average covering tree value is#P-complete even if the characteristic function of the game is{0,1}-valued.We prove this by a reduction from counting the number of all linear extensions of a partial order,which has been shown by Brightwell et al.to be a#P-complete counting problem.The implication of this result is that an efficient algorithm to calculate the average covering tree value is unlikely to exist.

Characteristics of House Removal and Resettlement Programs in Historic Areas of Beijing Old City Determined by Analyses on Family Registration Data

1. Objectives of Study and Back-groundFacing expansion and development de-mands, the Beijing Municipal City Plan-ning Commission (BMCPC) devised a plan to conserve the townscape of tra-ditional courtyard houses in the historic center of Beijing, and 25 districts

Performance analysis for power generating system by using matrix method

We verified that the matrix method, a process analysis method used mainly for life cycle inventory analysis, has several advantages in the analysis of power systems, which have recently become more complex to enhance efficiency and to reduce C02 emissions. While designing a conceptual thermodynamic model of a complex power system, the matrix method provides a definite procedure and facilitates calculations, even if there is a recttrsive loop between the upstream and downstream processes. Similarly, in the case of partial modification to the constructed model, the matrix method can potentially reduce the time and effort required to calculate the thermodynamic balances, even if the constructed model is designed by others. In this study, we obtained mass flow and energy balances of example model power systems by the matrix method from the common thermodynamic conditions including temperatures and pressures which are set on the basis of an existing industrial steam power system. While analyzing the environmental impact of complex multiproduct power systems, such as carbon emissions, the matrix method can be used to easily derive the environmental impact of each final product. We could verify the efficacy of the matrix method in accurately deriving that of an example model power system.

Top-k Outlier Detection from Uncertain Data

Uncertain data are common due to the increasing usage of sensors, radio frequency identification(RFID), GPS and similar devices for data collection. The causes of uncertainty include limitations of measurements, inclusion of noise, inconsistent supply voltage and delay or loss of data in transfer. In order to manage, query or mine such data, data uncertainty needs to be considered. Hence,this paper studies the problem of top-k distance-based outlier detection from uncertain data objects. In this work, an uncertain object is modelled by a probability density function of a Gaussian distribution. The naive approach of distance-based outlier detection makes use of nested loop. This approach is very costly due to the expensive distance function between two uncertain objects. Therefore,a populated-cells list(PC-list) approach of outlier detection is proposed. Using the PC-list, the proposed top-k outlier detection algorithm needs to consider only a fraction of dataset objects and hence quickly identifies candidate objects for top-k outliers. Two approximate top-k outlier detection algorithms are presented to further increase the efficiency of the top-k outlier detection algorithm.An extensive empirical study on synthetic and real datasets is also presented to prove the accuracy, efficiency and scalability of the proposed algorithms.

New exact solutions for the time fractional coupled Boussinesq-Burger equation and approximate long water wave equation in shallow water

The aim of the article is to construct exact solutions for the time fractional coupled Boussinesq-Burger and approximate long water wave equations by using the generalized Kudryashov method.The fractional differential equation is converted into ordinary differential equations with the help of fractional complex transform and the modified Riemann-Liouville derivative sense.Applying the generalized Kudryashov method through with symbolic computer maple package,numerous new exact solutions are successfully obtained.All calculations in this study have been established and verified back with the aid of the Maple package program.The executed method is powerful,effective and straightforward for solving nonlinear partial differential equations to obtain more and new solutions with the integer and fractional order.

A QUANTITATIVE MODEL FOR INTRADAY STOCK PRICE CHANGES BASED ON ORDER FLOWS

This paper proposes a double Markov model of the double continuous auction for describing intra-day price changes. The model splits intra-day price changes as the repetition of one tick price moves and assumes order arrivals are independent Poisson random processes. The dynamic process of price formation is described by a birth-death process of the double M/M/1 server queue corresponding to the best bid/ask. The initial depths of the best bid and ask are defined as different constants depending on the last price change. Thus, the price changes in the model follow a first-order Markov process. As the initial depth of the best bid/ask is originally larger than that of the opposite side when the last price is down/up, the model may explain the negative autocorrelations of the price of the best bid/ask. The estimated parameters are based on the real tick-by-tick data of the Nikkei 225 futures listed in Osaka Stock Exchanges. The authors find the model accurately predicts the returns of Osaka Stock Exchange average.