Modeling unaccounted-for gas among residential natural gas consumers using a comprehensive fuzzy cognitive map

Residential natural gas consumption depends on several factors. Available tools and methods to identify, categorize, and validate effective factors have some limitations, making consumption modeling more complex. Once a comprehensive model of effective consumption factors is developed for residential gas consumers, it can predict consumption. In addition, such a model could be used to verify the accuracy of measuring devices in order to reduce unaccounted for gas (UFG). The key factors affecting residential gas consumption were identified based on previous studies and their mutual effects were analyzed using a fuzzy cognitive mapping (FCM) method. The most significant factors and their effects on natural gas consumption in the residential sector were determined. In this study, for the first time, the expected consumption for each consumer was estimated using a consumption index. Generally, if the estimated consumption is significantly different from the amount recorded by the meter, it could suggest a potential source of UFG. The proposed method was applied to the data collected from the residential gas consumers of a small region in Iran (Dasht-e Arjan region, Fars province), and the results demonstrate the effectiveness of the proposed method.     

Design of geocell reinforced roads through fragility modeling

Several studies have confirmed the geocell reinforcement system as potential road material. However, there is a wide gap between the number of research studies evaluating the geocell in the laboratory and those dealing with road design methods using the geocell. Due to this gap, the geocell system has not reached its full potential in highways. The present study proposes fragility modeling to design low volume roads by considering the geocell reinforced layer's modulus. A predictive model was developed to estimate the geocell layer's modulus using laboratory and finite element analysis results. The results indicate that geocell reinforcement reduces the stresses on the underlying road layers. The developed fragility approach is then used to examine three road designs for Texas's low volume road involving different geocell reinforced layers. The obtained fragility curves indicate the reliability of each of the three road designs against the traffic load and can thereby assist decision-makers in selecting the optimum design. By designing geocell reinforced roads via fragility modeling, highway officials will be able to integrate any uncertainties in the design inputs and check designs against road performance criteria such as rutting and fatigue cracking, and against decision criteria such as cost, emissions, etc.     

Two-dimensional temperature distribution estimation for a cross-flow planar solid oxide fuel cell stack

The uniform temperature distribution of a cross-flow planar solid oxide fuel cell (SOFC) stack plays an essential role in stack thermal safety and electrical property. However, because of the strict requirements in stack sealing struture, it is hard to acquire the temperature inside the stack using thermal detection devices within an acceptable cost. Therefore, accurately estimating the two-dimensional (2-D) temperature distribution of the cross-flow stack is crucial for its thermal management. In this paper, Firstly, a 2-D mechanism model of a cross-flow planar SOFC stack is established. The stack is divided into 5*5 nodes along the gas flow directions, which can reflect the stack states with moderate computational burden. Then, experimental test data is utilized to modify and validate the stack model, guaranteeing the model accuracy as well as the reliability of model-based state estimator design. Finally, easily-measured stack inputs and outputs are selected, and a temperature distribution estimator combined with unscented kalman filter (UFK) approach is developed to achieve accurate and fast temperature distribution estimation of a cross-flow SOFC stack. Simulation results demonstrate that the UKF-based temperature distribution estimator can precisely and quickly achieve the temperature distribution estimation of the cross-flow stack under both static state and dynamic state changes and is applicable to cross-flow stacks with different size or cell number as well, the maximum estimated absolute error is less than 0.15 K with an absolute error rate of 0.015%, which indicates the developed estimator has good estimation performances.     

超超临界二次再热1000MW机组回热系统优化

1000MW超超临界二次再热机组按照常规回热系统设置,加热器中过热蒸汽与给水存在很大的传热温差,不可逆损失使回热系统热能有效利用率下降。本文采用EPSILON软件分别对外置式蒸汽冷却器和双机回热系统建立热力性能分析计算模型,比较两种系统布置方式的热经济性,对同类型机组回热系统优化具有借鉴意义。     

Conversion of biodiesel synthesis waste to hydrogen in membrane reactor: Theoretical study of glycerol steam reforming

Hydrogen production from waste glycerol, mainly producible as a by-product of biodiesel synthesis, is investigated as an attractive opportunity for exploiting renewable energy sources for further applications. Glycerol steam reforming using membrane technology was modeled by taking into accounts the maim transport phenomena, thermodynamic criteria and chemical process kinetics. A sensitivity analysis of operating conditions was made for key performance metrics such as glycerol conversion, hydrogen yield and hydrogen recovery. Glycerol conversion intensifies with enhancement of operating pressure and temperature, whereas high feed molar ratio and sweep ratio have limiting effect. Hydrogen permeation and subsequently, hydrogen recovery facilitates with increasing sweep gas ratio and sweep gas temperature. Hydrogen recovery enhances from 70% to 99% with increasing temperature from 350 to 500 °C at feed molar ratio of 3. Also, hydrogen recovery improves from 50% to 71% with increasing sweep ratio from 0 to 20 at 350 °C and 1 bar.     

Development of a Hydrogen Refueling Station Design Tool

In the last couple of decades, there has been a growing concern in what effects fossil fuels are having on the environment, resulting in governments and governing organizations issuing stringent emission standards in an effort to curve their environmental damage. To meet these new standards, the transportation industry has been conducting research into alternative fuels, such as hydrogen, but one critical problem utilizing hydrogen is that there is almost no infrastructure. A network of hydrogen refueling stations similar to modern gasoline stations will be required to be constructed to meet future demand. The hydrogen refueling station model was created to aid in designing hydrogen facilities, thus accelerating their development while reducing design cost. A model was created using Simulink consisting of an electrolyzer that generates hydrogen, a compressor, numerous storage tanks, a dispensing unit that transfers hydrogen, and a vehicle component that consumes hydrogen fuel. The model was validated using data from existing hydrogen refueling stations, and the data obtained from testing the previous version of the hydrogen refueling station model to determine model accuracy and if the model has improved. The model has demonstrated that it can produce reasonable results for a station's performance and has improved compared to the previous version.     

A terrain risk assessment method for military surveillance applications for mobile assets

This study proposes an analytical and flexible terrain risk assessment method for military surveillance applications for mobile assets. Considering the risk as the degree of possibility of insurgent presence, the assessment method offers an efficient evaluation of risk in the surrounding terrain for military combat operating posts or observation posts. The method is designed for unmanned aerial vehicles as the surveillance assets of choice to improve the effectiveness of their use. Starting with the area map and geographical data, the target terrain is first digitized for space representation. Then the data of nine geographical parameters are used to formulate five contributing risk factors. These factors are incorporated in an analytical framework to generate a composite map with risk scores that reveal the potential high-risk spots in the terrain. The proposed method is also applied to a real-life case study of COP Kahler in Afghanistan, which was a target for insurgent attacks in 2008. The results confirm that when evaluated with the developed method, the region that the insurgents used to approach COP Kahler has high concentration of high-risk cells.     

Modeling and analysis of passive worm propagation in the P2P file-sharing network

A number of worms, named P2P (peer-to-peer) passive worms, have recently surfaced, which propagate in P2P file-sharing networks and have posed heavy threats to these networks. In contrast to the majority of Internet worms, it is by exploiting users’ legitimate activities instead of vulnerabilities of networks in which P2P passive worms propagate. This feature evidently slows down their propagation, which results in them not attracting an adequate amount of attention in literature. Meanwhile, this feature visibly increases the difficulty of detecting them, which makes it very possible for them to become epidemic. In this paper, we propose an analytical model for P2P passive worm propagation by adopting epidemiological approaches so as to identify their behaviors and predict the tendency of their propagation accurately. Compared with a few existing models, dynamic characteristics of P2P networks are taken into account. Based on this proposed model, the sufficient condition for the global stability of the worm free equilibrium is derived by applying epidemiological theories. Large scale simulation experiments have validated both the proposed model and the condition.     

Complementary characterization methods for Lithium-ion Polymer secondary battery modeling

This paper deals with the electrical modeling of Lithium-ion Polymer battery, from complementary characterization tests. The first aim of this work is to understand the electrical behavior of this battery through experimentations in the same environmental conditions as the final application’s ones. The second goal of this work is to identify battery models with different precision levels and to implement them in specific models of the considered aircraft electrical network. In this paper, two equivalent electrical circuit models are presented: a quasi-static model, which is functional and sufficient for the electrical energy management in the aircraft; a dynamic model, which is behavioral and necessary for the analysis of the embedded network quality. The identification of their parameters is carried out with adapted characterization tests, such as chronopotentiometry at constant current and Electrochemical Impedance Spectroscopy at different temperatures. The complementarity of these tests is particularly underlined in this paper because it is useful for the parameter identification. The results from model simulation and from experimentation are compared through a mission profile and are analyzed. Eventually, this paper presents complete experimental data for a commercial 4.8 Ah Lithium-ion Polymer battery including the temperature influence.     

Review of pulsed thermal NDT: Physical principles,theory and data processing

This paper summarizes the basics of pulsed thermal nondestructive testing (TNDT) including theoretical solutions, data processing algorithms and practical implementation. Typical defects are discussed along with 1D analytical and multi-dimensional numerical solutions. Special emphasis is focused on defect characterization by the use of inverse solutions. A list of TNDT terms is provided. Applications of active TNDT, mainly in the aerospace industry, are discussed briefly, and some trends in the further development of this technique are described.