The tribological behavior of 1.41 wt% C ultrahigh-carbon steel (UHCS-1.41C) was investigated in comparison with a GCr15 bearing steel with a pin-on-disk and a two-disk tribometer at varying applied loads in ambient conditions. The wear surfaces of the specimens were examined with an optical microscope, EDX, and SEM. The retained austenite was measured by XRD. The results show that the friction coefficient of UHCS-1.41C is higher than that of GCr15 at a low load (6 N); however, it becomes lower than that of GCr15 at higher loads (10 N, 20 N). The wear rate of UHCS-1.41C is always lower than that of GCr15 according to the results of the two-disk test. UHCS-1.41C exhibits a stronger work hardening ability, which results in a higher resistance to wear than that of GCr15 during the two-disk test.
Ti-V Based / High-Rate Dischargeability / Hydrogen StorageThe phase structure and electrochemical properties of TiV 2.1 Ni 0.4 Zr 0.06 Cu 0.03 Cr 0.1 alloys as anode materials for nickel-metal-hydride batteries treated at different temperatures were investigated. The alloys mainly consist of a bcc (V,Ti)H 0.81 main phase and a network structure of hcp C14 laves phase, along the grain boundaries of the main phase. The lattice distortion is induced to a large extent for the sample treated at 1123 K. The electrochemical measurements indicate that the maximum discharge capacity of this sample is decreased, but improved cycling stability and high-rate dischargeability (HRD) are achieved. The deterioration behavior of the HRD for Ti-V-based alloys is discussed in the paper.
Critical heat flux (CHF) is one of the important design criteria of water cooled nuclear reactors and plays a key role for the safety and economics of nuclear power plants (NPPs). One of the goals of nuclear reactor design is to receive maximum efficiency under full power and its efficiency would be improved when the core exit temperature increases. From this perspective, the design of a nuclear reactor needs to take into account the appropriate thermal margin to ensure that the fuel design limits are within acceptable limits for any normal operating conditions. However, in general, CHF limits the heat flux from the fuel rods and the power capacity of the nuclear reactor. CHF refers to the transition from nucleate boiling to film boiling and causes an abrupt rise of the fuel rod surface temperature. Therefore, prediction of CHF is vital to the design and safety analysis of water cooled nuclear reactors. During the last five decades, large efforts have been carried out on the CHF prediction by many researchers. Generally, CHF prediction can be achieved in three main ways: empirical correlations, look-up tables and phenomenological models. Due to the complex nature of CHF, there is no deterministic theory for the prediction of CHF. Even the look-up tables and the empirical correlations have their own application ranges and limitations. To overcome these limitations, some computational intelligence (CI) techniques have been developed for the prediction of CHF by many researchers in the last two decades. This paper provides a brief overview of CI techniques for prediction of CHF. In this paper, the reviewed CI techniques mainly include artificial neural networks (ANNs), genetic algorithms (GAs), support vector machines (SVMs), and their hybrid models. This review also compares the strengths and weaknesses of several CI techniques and provides basic technical support for future selection of appropriate methods by those involved in the field.
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