基于粗糙集理论和动态时序模型的日负荷曲线预测新方法

作者提出了一种短期日负荷曲线预测新方法.该方法首先采用日最小负荷对日负荷曲线进行规范化,再将日负荷曲线预测转化为对日最小负荷的预测和对日规范化负荷曲线的预测.对日最小负荷预测应用动态时序模型;对日规范负荷曲线应用专家系统进行推理预测,专家系统中的推理规则应用粗糙集理论从历史数据中获取.采用上海电网数据对该预测方法进行了测试,结果表明该方法便于对各种影响因素进行分析处理,能够更有效地利用历史数据所包含的信息.     

Assessment of the radiation impact of steam generator dismantling on the workers,public and environment

Prediction of the exposure of workers and the impact on the public and environment is necessary for the planning of the decommissioning tasks. Planning and realisation of the dismantling process have to take into account many factors. This results in the creation of possible dismantling scenarios. Moreover, the input data such as nuclide composition and activity content often vary. In the case of a steam generator, the contamination level can differ even within the same nuclear power plant. The paper describes and applies the methodology used for complex analysis of the steam generator dismantling process in nuclear power plants using the VVER-440 reactor types.     

Self-lubricating mechanisms via the in situ formed tribo-film of sintered ceramics with hBN addition in a high humidity environment

Sliding wear tests against monolithic Si₃N₄ and austenitic stainless steel, respectively, were performed on Si₃N₄ ceramic with the addition of hBN solid lubricants. The friction coefficients and wear rates were measured. The wear surface features were examined by scanning electron microscopy (SEM) and laser scanning microscopy (LSM), and the chemical characterization of worn surface was made by Energy disperse spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS). Results showed that the friction coefficient and the wear rate decreased with the increase of hBN up to 20 vol% at high relative humidity (RH95%). When Si₃N₄-hBN ceramic composites sliding against stainless steel, with further increases in hBN content, the wear rate increased rapidly. The mechanism responsible were determined to be an in-situ formed tribo-chemical film composed of B-O and Si-O compounds between the pin-disc sliding couple. SEM observations showed that a black surface film is formed on the wear surface depending on the hBN content. The surface film associated with small friction coefficient of 0.03 and low wear rate with the magnitude of 10^− 6 mm³/Nm was formed by the releasing and smearing of the tribo-chemical reaction products of hBN and moisture on the wear surface when with 20 vol%hBN content. This tribo-chemical film acted as solid lubricant film between the sliding couple, and thus the couple entered to a state of boundary lubrication. Hence, the friction coefficient and the wear rate were significantly reduced. For Si₃N₄-hBN/stainless steel sliding pair, even at high relative humidity, no tribo-chemical film was observed on samples with 30 vol%hBN content, just because of a large degradation of mechanical properties of the composite with higher hBN content. At low relative humidity (RH25%), the wear mechanism for Si₃N₄-hBN sliding couple was mainly dominated by mechanical wear (abrasive or adhesive wear) due to the absence of tribo-chemical film on the wear surfaces, and higher friction coefficient and wear rate were obtained.     

Response time and mechanism of Pd modified TiO2 gas sensor

In this work, gas response properties of Pd modified TiO₂ sensing films are discussed when exposed to H₂ and O₂. TiO₂ films are surface modified in PdCl₂-containing solution by the dipping method and treated for different treatment times to get different surface states. X-ray diffraction (XRD), X-ray photoelectron spectroscopy (XPS), scanning electron microscopy (SEM) and Kröger–Vink defect theory are used to characterize the sensing films. The gas response properties indicate that the sensor response time which related to the rate of change of sensor resistance is affected by the activation energy (E). In particular, the sensor treated at 900 °C for 2 h exhibits a response time of about 20–240 ms when exposed to H₂ and 40–130 ms when exposed to O₂ at 500–800 °C.     

Scattering perspectives on nanostructural inhomogeneity in polymer network gels

Scattering methods based on spatial and temporal contrast fluctuations in polymer-network gels, which originate from polymer-segmental density fluctuations, reveal rich insight into different types and levels of nanostructural inhomogeneity in these soft materials. Complementary contrasting as provided by light, neutron, and X-ray scattering allows such information to be obtained on nano- to micrometer length scales. On top of that, complementary use of static and dynamic scattering methods allows the interplay and effect of these inhomogeneities to be unraveled. This article interrelates a multitude of studies on the application of scattering techniques for analytical assessment of structural inhomogeneity in polymer-network gels conducted since the 1970s.     

Terrific effect of H2 on 3D free convection MHD flow of C2H6O2H2O hybrid base fluid to dissolve Cu nanoparticles in a porous space considering the thermal radiation and nanoparticle shapes effects

In this article, the physical aspects of natural convection magnetohydrodynamic flow of Cu/Ethylene glycol-water nanofluid past a porosity vertical stretching sheet under impact of thermal radiation, shape and slip factor and suction/injection process has been analyzed using Runge- Kutta Fehlberg fifth order (RKF 5) numerical method. The influence of variable, different parameters such as nanoparticles shape factor, named hexahedron and Lamina on temperature and velocity profiles are exemplified quantitatively through graphs. Outputs demonstrate thermal radiation impact causes to produce heat and increase the temperature profile by increasing nanofluid molecules energy. Lamina shape nanoparticle has a greater effect on increasing Nusselt number (Nu) compared to hexahedron.     

A new high-pressure clearance seal with flexible laddered piston assembly in oil-free miniature compressor for potential hydrogen applications and investigation on its dynamic sealing efficiency

In this paper, a new flexible laddered piston assembly of clearance seal without any soft seal part was proposed for a long life time run of high-pressure stage in oil-free miniature compressor for potential hydrogen applications. In this assembly, the functions of radial load bearing and gas sealing were undertaken independently by large and small piston. The dynamic sealing performance evaluation was carried out by comprehensively considering the real-time variation of gas properties and piston motion with thermodynamic process in the compression chamber. Simulation study shows that the introduced clearance gap has a great influence on the expansion, compression and discharge process. Leakage through the clearance would lead to the in-cylinder pressure drop during the discharge process and bring about oscillation and earlier closure of the discharge valve. Sealing clearance exert more significant influence on the sealing efficiency in the high-pressure stage compared to sealing length and shaft speed.     

Process simulation and integration of IGCC systems for H2/syngas/electricity generation with control on CO2 emissions

IGCC is a pre-combustion technology that can be effectively used to produce both hydrogen and electricity while reducing the greenhouse gas (GHG) emissions. Two process models are developed in Aspen Plus^® software and are compared techno-economically. The conventional design of IGCC process is taken as case 1, whereas, case 2 represents the conceptual design of sequential integration of reforming model with the gasification unit to enhance the syngas yield. The case 2 utilizes the steam generated in the gasification process to sustain the methane reforming process which consequently enhances both the H₂ production capacity and cold gas efficiency. It has been analyzed from results that case 2 can enhance the process performance by 4.77% and economics in terms of cost of electricity by 5.9% compared to the conventional process. However, the utilization of natural gas in the case 2 is considered as a standalone fuel so the process performance of NGCC power plants has been also incorporated to ensure the realistic analysis. The results also showed that case 2 design offers 3.9% higher process performance than the cumulative (IGCC + NGCC) processes, respectively. Moreover, the CO₂ specific emissions and LCOE for the case 2 is also lower than the case.     

A non-invasive methodology for the grade identification of astrocytoma using image processing and artificial intelligence techniques

Brain tumor grade identification is an invasive technique and clinicians rely on biopsy and spinal tap method. The proposed method takes an effort to develop a non-invasive method for the tumor grade (Low/High) identification using magnetic resonant images. The process involves preprocessing, image segmentation, tumor isolation, feature extraction, feature selection and classification. An analysis on the performance of the segmentation techniques, feature extraction methods, automatic feature selection (SFLA) and constructed classifiers (support vector machines, learning vector quantization and Naives Bayes) is done on the basis of accuracy, efficiency and elapsed time. This analysis motivates towards the accurate determination of tumor grade from MR images instead of depending on magnetic resonant spectroscopy and biopsy. Fuzzy c-means segmentation outperformed other segmentation techniques, shape and size based textural feature promoted the demarcation of tumor grades, Naive Bayes classifier succeeded in terms of efficiency, error and elapse time when compared with SVM and LVQ. The study was carried out with 200 images consisting training set (164 images) and testing set (36 images). The results revealed that the system is robust and accurate (91%), consumed less time in grade identification, an alternative for biopsy and MRS in the brain tumor grade identification diagnosis procedure.     

A method for the compound fault diagnosis of gearboxes based on morphological component analysis

An improved morphological component analysis (MCA) method is proposed for the compound fault diagnosis of gearboxes. When gear fault and bearing fault occur simultaneously, the compound fault signal of the gearbox contains meshing components (related to the gear fault) and periodic impulse components (related to the bearing fault). The corresponding fault characteristics can be separated by MCA according to the morphological differences of the components. In the proposed method, the optimal dictionary, which can represent the characteristics of bearing faults, is first selected based on the principle of minimum information entropy. Then, the compound fault signal is decomposed into the meshing component and the periodic impulse component using MCA. Finally, the separated components are subjected to the Hilbert envelope spectrum analysis. The faults of the gear and the bearing can be diagnosed according to the envelope spectra of the separated fault signal components. Simulation and experimental studies validate the effectiveness of the proposed method for the compound fault diagnosis of gearboxes.