Abstract—With the developing of Low-Carbon Economy and increasing attention on environment-friendly projects, we introduce the system for mobile shopping to make lives greener and more convenient. It allows the customers to perform the purchase items through taking photos of the commodity and the system recommends customers to choose the similar items but with lower harm to environment to buy.

Abstract Recommender systems have become an important research area both in industry and academia over the last decade. Memory-based collaborative filtering methods include user-based and item-based methods have been explored in many product domains for their simplicity. Memory-based collaborative filtering methods compute the average ratings between similar users or items to predict unrated entries. As a consequence, it is difficult to find similar users or items when the rating data is sparse.

ABSTRACT In this paper a simple but efficient real-time detecting algorithm is proposed for tracking community structure of dynamic networks. Community structure is intuitively characterized as divisions of network nodes into subgroups, within which nodes are densely connected while between which they are sparsely connected. To evaluate the quality of community structure of a network, a metric called modularity is proposed and many algorithms are developed on optimizing it.

ABSTRACT Recommender systems attract growing attention recently, as they can suggest appropriate choices to users based on intelligent prediction. As one of the most popular recommender system techniques, Collaborative Filtering achieves efficiency from the similarity measurement of users and items. However, existing similarity measurement methods have reduced accuracy due to data correlation and sparsity. To overcome these problems, this paper introduces the Grey Forecast model for recommender systems.

During a severe nuclear power plant (NPP) accident, large amounts of hydrogen and steam can be produced in nuclear reactor containment. As the hydrogen concentration in the containment release rates exceed 4%, hydrogen combustion may occur when the hydrogen, air and steam reach certain concentration and a flammable source is present. In the case of hydrogen combustion, there is a possibility of producing short term pressure or detonation force. Therefore, the production of these gas species could threaten containment integrity. Although after the Three Mile Island (1979) accident, study of hydrogen distribution attracted scientists attention, it was after Fukushima (2011) accident, that modeling the gas behavior became an important topic in nuclear safety analyses. In order to mitigate these accidents, we need to understand the hydrogen behavior during NPP accident. Reliable turbulence model must be used in order to have an accurate estimate of the gas concentration distribution and other physical phenomena of the gas mixture. In this study, small scale airfountain test case is selected as a benchmark. Laminar model; standard − ; RNG − and realizable − turbulence models are addressed. The computations are performed with HYDRAGON code. The purpose of this study is to test the influence of turbulence models to the gas distribution, and to demonstrate the code thermal-hydraulic simulation capability during NPP accident. HYDRAGON code simulation results show that RNG and k-turbulence models have achieved better agreement with the experimental data on the prediction of dimensionless density distributions.

During a severe nuclear power plant (NPP) accident, large amounts of hydrogen and steam can be produced in nuclear reactor containment. In the case of hydrogen combustion, there is a possibility of producing short term pressure or detonation force. Therefore, these gas species' production could threaten containment integrity. For instance, in the past, two gas explosion accidents occurred : In 1979 Three Mile Island and in 2011 Fukushima. After these accidents, modeling the gas behavior became an important topic in nuclear safety analyses. In order to predict hydrogen behavior and other gas species transport, mixing and combustion, reliable turbulence models need to be applied. In this work, standard − , -, RNG − , Realizable − and SSTturbulence models are addressed. The computations are performed with HYDRAGON code. HYDRAGON code is a three-dimensional thermal-hydraulic code, developed to solve low-speed gas flow of compressible Navier-Stokes equations in cartesian or cylindrical coordinates or a mixture of the two coordinates. The goal of this work is to test the performance of these models by comparing the results to the benchmark. The code aims to predict containment thermal-hydraulic conditions during NPP accident.

This paper presents the gas distribution analysis by injecting air fountain into the containment and simulations with the HYDRAGON code. Turbulence models of standard k-e (SKE), re-normalization group k-e (RNG) and a realizable k-e (RLZ) are used to assess the effects on the gas distribution analysis during a severe accident in a nuclear power plant. By comparing with experimental data, the simulation results of the RNG and SKE turbulence models agree well with the experimental data on the prediction of dimensionless density distributions. The results illustrate that the turbulence model choice had a small effect on the simulation results, particularly the region near to the air fountain source.

The mitigation of hydrogen in the containment of nuclear reactor after the Loss of Coolant Accident is essential to preserve the structural reliability of the containment. This paper presents the results of the systematic work done by using the HYDRAGON code to investigate the effect of turbulence models on the concentration distribution of hydrogen and to determine the HYDRAGON code thermal-hydraulic simulation capability during a severe accident at the nuclear power plant. The HYDRAGON code is developed by the Department of Engineering Physics, Tsinghua University, which is an independent research program. The influence of various types of turbulence models, i.e. a standard k − ε model, a re-normalized group (RNG) k − ε model, and a realizable k − ε model were analyzed and the simulation results were compared with the experimental data. When simulation results were compared to experimental data, it was found that, in most compartments, the standard k − ε model generally yielded reasonable agreement with the experimental results as compared to RNG k − ε and realizable k − ε models; however, for probes P7 and P12, better trend was captured by RNG k − ε and realizable k − ε models, respectively.

Several methods have been developed in order to evaluate the best fit for nuclear data parameters, these methods relies on sequence logical steps should be followed to get accurate and reliable results, it subdivided into: (1) the physical model have been used (2) data types (3) statistical methods (4) problems. This paper will discuss the statistical methods used to evaluate the best fit for the nuclear data.

In an accelerator-driven subcritical system (ADS), a high-performance spallation neutron source is used to feed the subcritical reactor. Neutron generation depends on the proton beam intensity. If the beam intensity is increased by a given factor, the number of generated neutrons will increase. The mechanism yielding a high rate of neutron production per energy is the spallation process, and this mechanism produces very high-energy deposition in the spallation target material. Producing a high rate of neutrons is accompanied by creation of problems of decay heat cooling and radiological protection. As a first step in designing a full-scale industrial ADS, a small-scale experimental ADS, which is similar to the European experimental ADS (XADS) is analysed. The analysis presented in this paper is based on lead-bismuth eutectic (LBE) cooled XADS-type experimental reactors, designed during the European experimental (PDS-XADS) project. Computational fluid dynamics analysis has been carried out for the spallation target. Steady-state behaviour and shear stress transport turbulence model with the automatic wall treatment were applied in the present analysis.

Advanced exhaust after-treatment technology is required for heavy-duty diesel vehicles to achieve stringent Euro VI emission standards. Diesel particulate filter (DPF) is the most efficient system that is used to trap the particulate matter (PM), and particulate number (PN) emissions form diesel engines. The after-treatment system used in this study is catalyzed DPF (CDPF) downstream of diesel oxidation catalyst (DOC) with secondary fuel injection. Additional fuel is injected upstream of DOC to enhance exothermal heat which is needed to raise the CDPF temperature during the active regeneration process.

Diesel oxidation catalyst (DOC) upstream of catalyzed diesel particulate filter (CDPF) with additional diesel injection (hydrocarbon injection, HCI) were used to control the particulate matter (PM) emissions to meet stringent emission regulations for heavy-duty diesel vehicles. This study optimized the location of injector upstream of DOC by evaluating the uniformity of HC distribution on the entrance of DOC. An HCI was used in active regeneration to enhance the exothermic heat of CDPF to initiate the soot regeneration. Numerical analysis was established for the combination of after-treatment technology DOC-CDPF, and a spray model for HCI was implemented into a commercial CFD code named AVL FIRE. Different locations and orientations of the injector were tested. The results show that injector location has a significant effect on the optimal mixing between the exhaust gas and injected hydrocarbon (HC). Optimum injector location is the injector located farthest from DOC, while the long distance between injector and DOC allows enough time for injected HC to form secondary droplets, as it mixes well with exhaust gas downstream. Using HCI upstream of DOC causes the exhaust gas temperature to increase and reaches 550 ℃ at the entrance of CDPF, which is enough to initiate active DPF regeneration.

Several methods have been developed in order to evaluate the best fit for nuclear data parameters, these methods relies on sequence logical steps should be followed to get accurate and reliable results, it subdivided into: (1) the physical model have been used (2) data types (3) statistical methods (4) problems. This paper will discuss the statistical methods used to evaluate the best fit for the nuclear data.

The aim of this study is to investigate the availability and accuracy of the cross section data for 233 U to perform the calculations of the critical system. Two evaluated data libraries are available, U.S. data bank (ENDF) and the Japanese data bank (JENDL), by using BAYES method for resonance parameters available in SAMMY code and weighted least square method with nonlinear regression by using FITWR computer code. Evaluation of the 233 U has been investigated by using of SAMMY code, in order to generate a useful data base for critical calculations, the computer code FITWR for experimental -experimental data fitting show same results obtained from Bayes method included within SAMMY code, with a slight deference in the results at the evaluated cross sections due to different mathematical methods have different results

During severe accident in the nuclear power plant, a considerable amount of hydrogen can be generated by an active reaction of the fuel-cladding with steam within the pressure vessel which may be released into the containment of nuclear power plant. Hydrogen combustion may occur where there is sufficient oxygen, and the hydrogen release rates exceed 10% of the containment. During hydrogen combustion, detonation force and short term pressure may be produced. The production of these gas species can be detrimental to the structural integrity of the safety systems of the reactor and the containment. In 1979, the Three Mile Island (1979) accident occurred. This accident compelled experts and researchers to focus on the study of distribution of hydrogen inside the containment of nuclear power plant. However after the Fukushima Dai-ichi nuclear power plant accident (2011), the modeling of the gas behavior became important topic for scientists. For the stable and normal operation of the containment, it is essential to understand the behavior of hydrogen inside the containment of nuclear power plant in order to mitigate the occurrence of these types of accidents in the future. For this purpose, it is important to identify how burnable hydrogen clouds are produced in the containment of nuclear power plant. The combustion of hydrogen may occur in different modes based on geometrical complexity and gas composition. Reliable turbulence models must be used in order to obtain an accurate estimation of the concentration distribution as a function of time and other physical phenomena of the gas mixture. In this study, a small turbulence model are in reasonable agreement as compared to the benchmark experimental data.

In an accelerator-driven subcritical system (ADS), a high-performance spallation neutron source is used to feed the subcritical reactor. Neutron generation depends on the proton beam intensity. If the beam intensity is increased by a given factor, the number of generated neutrons will increase. The mechanism yielding a high rate of neutron production per energy is the spallation process, and this mechanism produces very high-energy deposition in the spallation target material. Producing a high rate of neutrons is accompanied by creation of problems of decay heat cooling and radiological protection. As a first step in designing a full-scale industrial ADS, a small-scale experimental ADS, which is similar to the European experimental ADS (XADS) is analysed. The analysis presented in this paper is based on lead-bismuth eutectic (LBE) cooled XADS-type experimental reactors, designed during the European experimental (PDS-XADS) project. Computational fluid dynamics analysis has been carried out for the spallation target. Steady-state behaviour and shear stress transport turbulence model with the automatic wall treatment were applied in the present analysis.

This paper presents the gas distribution analysis by injecting air fountain into the containment and simulations with the HYDRAGON code. Turbulence models of standard k-e (SKE), re-normalization group k-e (RNG) and a realizable k-e (RLZ) are used to assess the effects on the gas distribution analysis during a severe accident in a nuclear power plant. By comparing with experimental data, the simulation results of the RNG and SKE turbulence models agree well with the experimental data on the prediction of dimensionless density distributions. The results illustrate that the turbulence model choice had a small effect on the simulation results, particularly the region near to the air fountain source.

The mitigation of hydrogen in the containment of nuclear reactor after the Loss of Coolant Accident is essential to preserve the structural reliability of the containment. This paper presents the results of the systematic work done by using the HYDRAGON code to investigate the effect of turbulence models on the concentration distribution of hydrogen and to determine the HYDRAGON code thermal-hydraulic simulation capability during a severe accident at the nuclear power plant. The HYDRAGON code is developed by the Department of Engineering Physics, Tsinghua University, which is an independent research program. The influence of various types of turbulence models, i.e. a standard k − ε model, a re-normalized group (RNG) k − ε model, and a realizable k − ε model were analyzed and the simulation results were compared with the experimental data. When simulation results were compared to experimental data, it was found that, in most compartments, the standard k − ε model generally yielded reasonable agreement with the experimental results as compared to RNG k − ε and realizable k − ε models; however, for probes P7 and P12, better trend was captured by RNG k − ε and realizable k − ε models, respectively.

Catalysts Specifications DOC Ф10.5"x6" 400 cpsi/4 mil CDPF Ф10.5"x11" 200 cpsi/12 mil Circumferential Uniformity Test 24 thermocouples were inserted into the DPF channels to measure the inner temperature of the filter. The temperature circumferential uniformity of three different sections at the DPF length direction was analyzed.