按工作寿命优先或最大转矩优先设计V带传动

本文介绍一种优先保证V带工作寿命或传递最大转矩来设计V带传动的方法。这种方法以滑动曲线和寿命曲线为基础,初拉力和其它一些参数具有可选择性。论文阐述了提出这种方法的理由和优点,介绍了所使用的试验台和试验结果。     

探索未来制造的战略和优先发展的技术

在过去20年，中国的制造发生了根本的变化，而这种变化是快速和不停顿的，在未来，涌动的经济，社会与政治的变迁和商务的新途径将使世界企业与今天的状况显著地不同，制造将在2010－2020年保持作了创造财富的基本手段，由激烈竞争刺激起来的新制造技术的出现将导致新产品和新过程，根本的是中国要为及时实施先进制造方法作好准备，本文介绍中国制造企业的优势与面对的挑战、战略、优先发展的技术和支持的研究。     

ODS ferritic steels produced by an alternative route (STARS): microstructural characterisation after atomisation,HIPping and heat treatments

The conventional PM ODS Ferritic Steel (FS) processing route includes gas atomisation of steel powder and its mechanical alloying (MA) with Y₂O₃ powder particles to dissolve yttrium and form, during consolidation, a dispersion of oxide nanoparticles (Y–Ti–O) in a nanostructured matrix. This work presents an alternative route to produce ODS steels avoiding MA: STARS (Surface Treatment of gas Atomized powder followed by Reactive Synthesis). STARS FS powders with composition Fe–14Cr–2W–0.3Ti–0.23Y, already containing the nanoparticles precursors, were gas-atomized. Oxygen, Y and Ti contents were tailored to the required values to form Y–Ti–O nanoparticles during processing. Powders were HIPped at 900, 1220 and 1300°C. Specimens HIPped at 900 and 1220°C were heat treated (HT) at temperatures ranging from 1200 to 1320°C. The microstructural evolution with HIP and HT temperatures, including characterisation of nanoparticles and feasibility of achieving complete dissolution of prior particle boundaries (PPBs) were assessed.     

Metallographic techniques for the determination of the austenite grain size in medium-carbon microalloyed steels

Different techniques have been investigated to seek the best procedure to reveal the prior-austenite grain boundaries in three medium-carbon microalloyed steels. This study has been carried out over a wide range of temperatures (950–1250°C) and it has been found that thermal etching (TE) is the best technique to reveal the prior-austenite grain boundaries in these steels.     

Risk and threat factors in prior representations of driving situations among powered two-wheeler riders and car drivers

Our research objective is to contribute to gaining a better understanding of the difficulties inherent to managing interactions between power two-wheeler riders and car drivers. 132 power two-wheeler riders and 94 car drivers have been asked what they perceive as being riskiest in driving situations for the representatives of their generic reference group. From all the answers produced, only those which provide information on risk factors related to the other and the occurrence of interferences due to the dynamic situation have been retained and analysed. The results provide a partial explanation of the difficulties related to the two types of users’ taking each other into account. On the one hand, the frequency with which the other is mentioned as a source of risk is linked to the concept of conspicuity. This interpretation is related to the relative frequency of the interactions and the difference of real and perceived vulnerability between the users. On the other hand, the specific risk factors attributed to the other illustrates a mutual misunderstanding or ignorance of the driving situation's determinants. These include various practices among users which can be related to the physical and dynamic characteristics of their vehicle and their level of familiarity with other users. The potential road safety consequences of prior representations of risk factors among users are presented and suggestions for improving road user safety are proposed.     

Novel Approaches to Probabilistic Neural Networks Through Bagging and Evolutionary Estimating of Prior Probabilities

In this contribution, novel approaches are proposed for the improvement of the performance of Probabilistic Neural Networks as well as the recently proposed Evolutionary Probabilistic Neural Networks. The Evolutionary Probabilistic Neural Network’s matrix of spread parameters is allowed to have different values in each class of neurons, resulting in a more flexible model that fits the data better and Particle Swarm Optimization is also employed for the estimation of the Probabilistic Neural Networks’s prior probabilities of each class. Moreover, the bagging technique is used to create an ensemble of Evolutionary Probabilistic Neural Networks in order to further improve the model’s performance. The above approaches have been applied to several well-known and widely used benchmark problems with promising results.      

布匹检验中无疵点数据处理

本文在泊松分布前提下，利用贝叶斯估计给出布匹定长截尾疵点检验中，布匹额定长度质量可靠性Ｒ（τ）的一个估计值．其结果是可靠的．     

Removing prior particle boundaries in a powder superalloy based on the interaction between pulsed electric current and chain-like structure

The chain-like prior particle boundaries (PPBs) as a kind of stubborn harmful precipitate will hinder atomic diffusion and particle connection.They can only be broken into nanoscale through thermal defor-mation (1160-1200 ℃).Here,treated by the pulsed electric current at 800 ℃,PPBs were dissolved quickly as a result of the interaction between the pulsed electric current and the chain-like structure.According to the electromigration theory and the calculation results,the high current density regions will be mainly produced at the gaps due to the conductivity difference between the precipitates and the matrix.The atomic diffusion flux caused by the pulsed electric current is proportional to the current density.There-fore,the existence of a large number of gaps in the chain-like PPBs will make the high current density regions play a more positive role in fast-dissolution.