化学品船液货管系的设计与检验

化学品液货种类繁多,不少船东在化学品船设计、建造之初,并不十分清晰将来装载哪些货品,加之为了节省成本,在建造材料的选择上又往往趋向低端,导致成船可以运载的货源大大受限,最终对船舶营运效益造成严重影响。如何才能避免类似情况发生呢?     

Assessing the representativeness of a smartphone-based household travel survey in Dar es Salaam,Tanzania

The household travel survey (HTS) finds itself in the midst of rapid technological change. Traditional methods are increasingly being sidelined by digital devices and computational power—for tracking movements, automatically detecting modes and activities, facilitating data collection, etc.. Smartphones have recently emerged as the latest technological enhancement. FMS is a smartphone-based prompted-recall HTS platform, consisting of an app for sensor data collection, a backend for data processing and inference, and a user interface for verification of inferences (e.g., modes, activities, times, etc.). FMS, has been deployed in several cities of the global north, including Singapore. This paper assesses the first use of FMS in a city of the global south, Dar es Salaam. FMS in Dar was implemented over a 1-month period, among 581 adults chosen from 300 randomly selected households. Individuals were provided phones with data plans and the FMS app preloaded. Verification of the collected data occurred every 3 days, via a phone interview. The experiment reveals various social and technical challenges. Models of individual likelihood to participate suggest little bias. Several socioeconomic and demographic characteristics apparently do influence, however, the number of days fully verified per individual. Similar apparent biases emerge when predicting the likelihood of a given day being verified. Some risk of non-random, non-response is, thus, evident.     

Optimal Threshold Policies for Robust Data Center Control

With the simultaneous rise of energy costs and demand for cloud computing, efficient control of data centers becomes crucial. In the data center control problem, one needs to plan at every time step how many servers to switch on or off in order to meet stochastic job arrivals while trying to minimize electricity consumption. This problem becomes particularly challenging when servers can be of various types and jobs from different classes can only be served by certain types of server, as it is often the case in real data centers. We model this problem as a robust Markov decision process (i.e., the transition function is not assumed to be known precisely). We give sufficient conditions (which seem to be reasonable and satisfied in practice) guaranteeing that an optimal threshold policy exists. This property can then be exploited in the design of an efficient solving method, which we provide. Finally, we present some experimental results demonstrating the practicability of our approach and compare with a previous related approach based on model predictive control.     

Research on Web Page Classification Method Based on Query Log

Web page classification is an important application in many fields of Internet information retrieval, such as providing directory classification and vertical search. Methods based on query log which is a light weight version of Web page classification can avoid Web content crawling, making it relatively high in efficiency, but the sparsity of user click data makes it difficult to be used directly for constructing a classifier. To solve this problem, we explore the semantic relations among different queries through word embedding, and propose three improved graph structure classification algorithms. To reflect the semantic relevance between queries, we map the user query into the low-dimensional space according to its query vector in the first step. Then, we calculate the uniform resource locator (URL) vector according to the relationship between the query and URL. Finally, we use the improved label propagation algorithm (LPA) and the bipartite graph expansion algorithm to classify the unlabeled Web pages. Experiments show that our methods make about 20% more increase in F1-value than other Web page classification methods based on query log.     

Modeling and simulation of a counter-rotating turbine system for underwater vehicles

The structure of a counter-rotating turbine of an underwater vehicle is designed by adding the counter-rotating second-stage turbine disk after the conventional single-stage turbine. The available kinetic energy and the absorption power of the auxiliary system are calculated at different working conditions, and the results show that the power of the main engine and auxiliary system at the counter-rotating turbine system matches well with each other. The experimental simulation of the lubricating oil loop, fuel loop, and seawater loop are completed right before the technology scheme of the counter-rotating turbine system is proposed. The simulation results indicate that the hydraulic transmission system can satisfy the requirements for an underwater vehicle running at a steady sailing or variable working conditions.     

冰区核电平台系泊设计及影响研究

本文根据冰区浮式核电平台的主要功能及外部环境条件,确定平台的基本形式,并在此基础上进行了系泊系统的优化设计.与以往研究不同的是,考虑到冰区海洋的特殊性,除计算风、浪、流作用情况外,还运用Sdem软件构造了海冰离散单元模型,对海冰与海洋系泊结构物的相互作用过程进行了数值模拟.在此基础上,结合系泊分析软件ANSYS-AQWA的二次开发功能,对平台运动及其系泊系统进行了时域耦合分析,研究了平台在不同环境载荷作用下的运动响应;进行了系泊参数研究,分析一般规律,最终提出了一种满足规范要求且性能优良的系泊方案.研究结果表明:本文提出的冰区核电平台系泊系统可抵抗恶劣的环境影响;通过合理选择系泊缆数量、夹角、预张力大小及顶端倾角等系泊参数,可减小平台运动响应.     

Real-Time Fault Diagnosis for Gas Turbine Blade Based on Output-Hidden Feedback Elman Neural Network

In order to remotely monitor and maintain large-scale complex equipment in real time, China Telecom plans to create a total solution that integrates remote data collection, transmission, storage, analysis and prediction. This solution can provide manufacturers with proactive, systematic, integrated operation and maintenance service, and the data analysis and health forecasting are the most important part. This paper conducts health management for the turbine blades. Elman neural network, and improved Elman neural network, i.e., outputhidden feedback (OHF) Elman neural network are studied as the main research methods. The results verify the applicability of OHF Elman neural network.     

假设检验在汽车排放实验室质量监控中的应用研究

设备比对作为一种有效的质量监控方法,在汽车检测行业得到了广泛应用.众所周知,影响整车排放检测结果的因素较多,试验结果的偏差较大;但因排放检测设备价值昂贵,具备两套及以上排放检测设备的实验室较少,因此,在进行质量监控时,受检测设备数量的限制,难以选择设备比对的方式.本文以5家实验室比对的数据为例,选择其中的极端数据模拟进行两套设备间的设备比对,得出了假设检验用于设备比对的分析方法,并给出了试验数据的置信区间.与实验室间比对结果相比,使用该方法进行两套设备间的比对,比对结果可信.