A low complexity DFT-matrix based pilot allocation algorithm for sparse channel estimation in OFDM systems

The accuracy of channel estimation is very important for Orthogonal Frequency Division Multiplexing (OFDM) systems. In a high speed wideband wireless communication, the channel can be modeled as a sparse one. Therefore, the Compressed Sensing (CS) technique can be used for the estimation of the channel. In this paper, the problem of deterministic pilot allocation in OFDM systems is considered and a new criterion which is based on minimizing the summation of the correlations between the columns of the Discrete Fourier Transform (DFT) sub-matrix is proposed. It will be shown that the proposed criterion is a simple version of the well-known but complex criterion, Restricted Isometry Property (RIP). In addition, the pilot pattern design, using our proposed scheme, indicates better recovery performance than other proposed coherence based criteria in terms of the reconstruction mean square error (MSE) and successful channel recovery percentage. Simulation results confirm our analysis.     

A Method for Classification and Evaluation of Pilot’s Mental States Based on CNN

How to accurately recognize the mental state of pilots is a focus in civil aviation safety. The mental state of pilots is closely related to their cognitive ability in piloting. Whether the cognitive ability meets the standard is related to flight safety. However, the pilot's working state is unique, which increases the difficulty of analyzing the pilot's mental state. In this work, we proposed a Convolutional Neural Network (CNN) that merges attention to classify the mental state of pilots through electroencephalography (EEG). Considering the individual differences in EEG, semi-supervised learning based on improved K-Means is used in the model training to improve the generalization ability of the model. We collected the EEG data of 12 pilot trainees during the simulated flight and compared the method in this paper with other methods on this data. The method in this paper achieved an accuracy of 86.29%, which is better than 4D-aNN and HCNN etc. Negative emotion will increase the probability of fatigue appearing, and emotion recognition is also meaningful during the flight. Then we conducted experiments on the public dataset SEED, and our method achieved an accuracy of 93.68%. In addition, we combine multiple parameters to evaluate the results of the classification network on a more detailed level and propose a corresponding scoring mechanism to display the mental state of the pilots directly.     

驾驶员模型参数对横航向PI0的影响研究

随着电传操纵系统在现代飞机上的广泛应用,其动力学特性也越来越复杂。如果驾驶员的操纵与飞机性能及其外部环境不协调,则人机闭环系统稳定性下降,严重时会出现一种非期望的,不符合驾驶员意愿的闭环耦合振荡,直接影响到飞行安全,这种现象称为驾驶员诱发振荡。针对驾驶员操纵诱发横航向振荡问题,本文建立了横航向驾驶员-控制器-飞机本体组合系统的数学模型,研究驾驶员模型中诱发横航向振荡的关键参数。以空客A300飞机横航向模型进行闭环仿真分析,给出各个参数对横航向PI0的影响特性,分析结果对工程实践具有一定的指导意义。     

Entrained flow gasification of straw- and wood-derived pyrolysis oil in a pressurized oxygen blown gasifier

Fast pyrolysis oil can be used as a feedstock for syngas production. This approach can have certain advantages over direct biomass gasification. Pilot scale tests were performed to investigate the route from biomass via fast pyrolysis and entrained flow gasification to syngas. Wheat straw and clean pine wood were used as feedstocks; both were converted into homogeneous pyrolysis oils with very similar properties using in-situ water removal. These pyrolysis oils were subsequently gasified in a pressurized, oxygen blown entrained flow gasifier using a thermal load of 0.4 MW. At a pressure of 0.4 MPa and a lambda value of 0.4, temperatures around 1250 °C were obtained. Syngas volume fractions of 46% CO, 30% H₂ and 23% CO₂ were obtained for both pyrolysis oils. 2% of CH₄ remained in the product gas, along with 0.1% of both C₂H₂ and C₂H₄. Minor quantities of H₂S (3 vs. 23) cm³ m⁻³, COS (22 vs. 94) cm³ m⁻³ and benzene (310 vs. 532) cm³ m⁻³ were measured for wood- and straw derived pyrolysis oils respectively. A continuous 2-day gasification run with wood derived pyrolysis oil demonstrated full steady state operation. The experimental results show that pyrolysis oils from different biomass feedstocks can be processed in the same gasifier, and issues with ash composition and melting behaviour of the feedstocks are avoided by applying fast pyrolysis pre-treatment.     

复杂气藏型储气库先导试验方案设计方法

国内现役地下储气库(以下简称储气库)的工作气量和调峰能力等关键参数达标率偏低,究其原因有可能是未及时开展先导试验对关键参数进行现场验证与核实,对储气库高强度快速往复注采所引起的关键特性认识不清,从而降低了方案指标的可靠性。为此,参照气藏开发先导试验定义,涵盖试验依据、试验目的、实施节点、试验内容等,首次建立了复杂气藏改建储气库先导试验方案设计方法。研究结果表明:①先导试验的核心要求是"科学性、安全性、经济性";②先导试验的主要内容包括圈闭密封性验证、有效建库空间定量评价、短期高速注采气能力核实、老井封堵工艺适应性评价和低压储层建井工艺适应性验证等5项;③先导试验方案包括优选试验井、部署现场试验和配套专题研究;④现场测试涵盖产能、连通性、边界和气液界面变化;⑤配套专题研究包括地质特征、注采机理、注采效果和钻采工艺。结论认为,该方法已成功应用于中国石油吐哈油田公司和中国石油吉林油田公司,指导了储气库先导试验方案设计和现场实施,为可研方案关键指标设计提供了新的认识和科学依据,有助于提升我国复杂气藏型储气库的设计水平和建库指标的可靠性。     

采用外泄式提高先导式溢流阀的定压精度

针对节流调速回路实验中出现的先导式溢流阀定压精度低的情况,分析回路和溢流阀的结构,确定了把先导式溢流阀的内泄式改为外泄式的解决方案。并在内泄式和外泄式两种情况下对溢流阀进行了启闭特性试验。对比试验结果表明:采用外泄式可以明显改善先导式溢流阀的静态性能,提高溢流阀的定压精度。研究内容对生产实践有很好的指导意义,提供了一种简单实用的改善设备性能的方法。     

M4系列电液比例多路阀特性研究

根据M4系列电液比例多路阀工作机制,建立了其先导阀电液比例减压阀数学模型,在Simulink平台下进行了仿真,M4多路阀的先导比例减压阀具有较好的阶跃响应特性。利用功率键合图法对M4电液比例多路阀工作系统进行了建模,分析了工作回路动态特性,分析结果显示:M4多路阀工作系统具有较好的平稳性和良好的动态响应。研究结果为在工作系统中比例多路阀的选择使用提供了依据。     

Pilot plant studies of biodiesel production using Brassica carinata as raw material

In recent years, the development of alternative fuels from renewable resources, like biomass, has received considerable attention. Biodiesel is defined as fatty acid methyl or ethyl esters from vegetable oils, when it is used as fuel in diesel engines and heating systems.

In this context, the cultivation of Brassica carinata as oilseed crop for biodiesel production in the south of Europe (Spain and Italy) and north of Africa has gained special interest, since it allows the use of set-aside lands, giving higher yields per hectare than the traditional Spanish crops.

Methyl or ethyl esters are the product of transesterification of vegetable oils with alcohol (methanol/ethanol) using an alkaline catalyst. In addition, the process yields glycerol, which has large applications in the pharmaceutical, food and plastics industries.

In the present work, the process of biodiesel production for pilot plant using B. Carinata oil as raw materials with methanol and using potassium hydroxide as catalyst has been studied.

The biodiesel quality meets European specifications defined by pr EN 14214:2002 (E). The obtained results have been used for industrial scale up of the process.     

Challenges in the scale-up of particulate processes—an industrial perspective

Studies by the Rand Corporation in the 1980s identified substantial differences in the scale-up and start-up performance of plants processing particles versus those processing liquids or gases. These differences were inevitably unfavorable. Particulate process plants take longer to start up and are less likely to achieve desired production rates. Facility operators often underestimate the challenges involved. These problems generally relate to an inadequate understanding of the behavior of particle systems. Many of these behaviors are sensitive to process scale or process history in ways that would not be expected by engineers familiar only with liquid or gas systems. Empiricism must often substitute for first principles. Modeling provides some answers, but often not enough to eliminate the need to operate pilot plants. This paper reviews some of the unit operations involved in particle processing and highlights scale-up issues involved. The use of information from suppliers and other third parties is discussed, as well as scale-up strategies in competitive or regulated industries.