Determination of heat transfer coefficient for hot stamping process

© 2015 The Authors.The selection of the heat transfer coefficient is one of the most important factors that determine the reliability of FE simulation results of a hot stamping process, in which the formed component is held within cold dies until fully quenched. The quenching process could take up to 10. seconds. In order to maximise the production rate, the optimised quenching parameters should be identified to achieve the highest possible quenching rate and to reduce the quenching time. For this purpose, a novel-testing rig for the Gleeble 3800 thermo- mechanical simulator was designed and manufactured, with an advanced control system for temperature and contact pressure. The effect of contact pressure on the heat transfer coefficient was studied. The findings of this research will provide useful guidelines for the selection of the heat transfer coefficient in simulations of hot stamping processes and useful information for the design of hot stamping processes

Determinations of upper critical field in continuous Ginzburg-Landau model

Novel procedures to determine the upper critical field $B_{c2}$ have been proposed within a continuous Ginzburg-Landau model. Unlike conventional methods, where $B_{c2}$ is obtained through the determination of the smallest eigenvalue of an appropriate eigen equation, the square of the magnetic field is treated as eigenvalue problems so that the upper critical field can be directly deduced. The calculated $B_{c2}$ from the two procedures are consistent with each other and in reasonably good agreement with existing theories and experiments. The profile of the order parameter associated with $B_{c2}$ is found to be Gaussian-like, further validating the methodology proposed. The convergences of the two procedures are also studied.Comment: Revtex4, 8 pages, 4 figures, references modified, figures and table embedde

Channel Parameters Estimation Algorithm Based on The Characteristic Function under Impulse Noise Environment

Under communication environments, such as wireless sensor networks, the noise observed usually exhibits impulsive as well as Gaussian characteristics. In the initialization of channel iterative decoder, such as low density parity check codes, it is required in advance to estimate the channel parameters to obtain the prior information from the received signals. In this paper, a blind channel parameters estimator under impulsive noise environment is proposed, which is based on the empirical characteristic function in MPSK/MQAM higher-order modulation system. Simulation results show that for various MPSK/MQAM modulations, the estimator can obtain a more accurate unbiased estimation even though we do not know which kind of higher-order modulation is used

Analysis on the evolution and governance of the biotechnology industry of China

The past twenty years have witnessed the high-speed growth of China’s biotechnology industry, and this presents an excellent opportunity to examine the changes that have taken place, especially, to carry out overall evaluation and governance analysis from the perspective of technology policies. Although China’s biotechnology industry has achieved tremendous extension both in scale and structure, the strengths it gained from basic research have been significantly weakened by commercialization. This has resulted in the comparatively limited scale of the whole industry, innovation-lacking products, poor output from research and development and scarcity of industrial resources. A large range of literature regarding China’s biotechnology industry attributes these outcomes to vague and even inappropriate governance, findings supported mainly by analyses based on the linear model of impact of government policies on industrial development. In these analyses, government, enterprises and companies as well as R&D organizations are either put on the opposite poles or in a straight line. After examining the nature of China’s biotechnology industry, and in particular the dynamic procedures in research and development, the authors of this paper argue that besides government, enterprises and R&D organizations, a diverse array of factors should be taken into account as we tackle issues emerging in understanding the development of China’s biotechnology industry. Furthermore, these factors, human or nonhuman, should not be arranged as opposing poles or linearly connected points on a straight line. They are in fact all knitted in networks and act as both knitters and knots. China’s biotechnology industry gains its strength to develop and evolve from these networks, thus its governance must be aimed at improving their stability and quality. Although the main disciplinary perspectives of this research are historical and sociological (including identification of the three development stages of biotechnology in China since 1978 to present days), a large number of concepts and ideas from management studies as well as an interdisciplinary approach are also incorporated into the analysis. The main model used in this research is Actor Network Theory, which is employed as a basic theoretical frame. From this starting point the authors attempt to make a closer examination of China’s biotechnology industry both at the level of technology research and development and at the level of commercialization. The modeling process in this research can be regarded as an attempt to explore the social construction of China’s biotechnology industry. The paper reveals how China’s biotechnology industry develops in the form of networks within the country’s social context and what kinds of relationships exist among the relevant factors; therefore, providing guiding insights for improving the governance of China’s biotechnology industry both in policy and management