Catalytic Hydrocracking of a Bitumen‐Derived Asphaltene over NiMo/γ‐Al2O3 at Various Temperatures

Hydrocracking of a bitumen‐derived asphaltene over NiMo/γ‐Al₂O₃ was investigated in a microbatch reactor at varying temperatures. The molar kinetics of asphaltene cracking reaction was examined by fitting the experimental data. Below a defined temperature, the molar reaction showed the first‐order kinetic feature while at higher temperatures secondary reactions such as coke formation became significant, causing deviation of the reaction behavior from the proposed first‐order kinetic model. Selectivity analysis proved that dominant products varied from gases to liquids to gases with increasing temperature, shifting the dominant reaction from C–S bonds cleavage to C–C bonds cleavage.     

Hazelett生产线熔炼工艺探讨

探讨了采用Hazelett生产线,从原料到合格铝液各道工序的操作要求;特别是采用电解铝液,对每道工序操作时间和铝液质量控制提出严格要求。通过实际生产,对现有熔炼炉配置、设备台数、精炼设备配置作了详细阐述,对每道工序要达到的铝液净化参数提出严格要求,经过6次净化提纯,基本满足Hazelett铸机要求,并对熔炼设备配置的不足提出合理化建议。     

Image and Feature Space Based Domain Adaptation for Vehicle Detection

The application of deep learning in the field of object detection has experienced much progress. However, due to the domain shift problem, applying an off-the-shelf detector to another domain leads to a significant performance drop. A large number of ground truth labels are required when using another domain to train models, demanding a large amount of human and financial resources. In order to avoid excessive resource requirements and performance drop caused by domain shift, this paper proposes a new domain adaptive approach to cross-domain vehicle detection. Our approach improves the cross-domain vehicle detection model from image space and feature space. We employ objectives of the generative adversarial network and cycle consistency loss for image style transfer in image space. For feature space, we align feature distributions between the source domain and the target domain to improve the detection accuracy. Experiments are carried out using the method with two different datasets, proving that this technique effectively improves the accuracy of vehicle detection in the target domain.     

A Novel Beam Search to Improve Neural Machine Translation for English-Chinese

Neural Machine Translation (NMT) is an end-to-end learning approach for automated translation, overcoming the weaknesses of conventional phrase-based translation systems. Although NMT based systems have gained their popularity in commercial translation applications, there is still plenty of room for improvement. Being the most popular search algorithm in NMT, beam search is vital to the translation result. However, traditional beam search can produce duplicate or missing translation due to its target sequence selection strategy. Aiming to alleviate this problem, this paper proposed neural machine translation improvements based on a novel beam search evaluation function. And we use reinforcement learning to train a translation evaluation system to select better candidate words for generating translations. In the experiments, we conducted extensive experiments to evaluate our methods. CASIA corpus and the 1,000,000 pairs of bilingual corpora of NiuTrans are used in our experiments. The experiment results prove that the proposed methods can effectively improve the English to Chinese translation quality.     

Development of mobile miniature natural gas liquefiers

With increasing consumption of natural gas (NG), small NG reservoirs, such as coalbed methane and oil field associated gas, have recently drawn significant attention. Owing to their special characteristics (e.g., scattered distribution and small output), small-scale NG liquefiers are highly required. Similarly, the mixed refrigerant cycle (MRC) is suitable for small-scale liquefaction systems due to its moderate complexity and power consumption. In consideration of the above, this paper reviews the development of mobile miniature NG liquefiers in Technical Institute of Physics and Chemistry (TIPC), China. To effectively liquefy the scattered NG and overcome the drawbacks of existing technologies, three main improvements, i.e., low-pressure MRC process driven by oil-lubricated screw compressor, compact cold box with the new designed heat exchangers, and standardized equipment manufacturing and integrated process technology have been made. The development pattern of “rapid cluster application and flexible liquefaction center” has been eventually proposed. The small-scale NG liquefier developed by TIPC has reached a minimum liquefaction power consumption of about 0.35 kW·h/Nm³. It is suitable to exploit small remote gas reserves which can also be used in boil-off gas reliquefaction and distributed peak-shaving of pipe networks.