海洋探测无人艇:平台设计及应用

海洋探测无人艇应用范围广泛,但无人艇姿态易受风、浪、流、漂浮垃圾等环境因素影响,导致结构损坏、观测数据精度下降等问题。设计了无人艇双体宽甲板平台,多波束测深系统安装在升降机构上,保障最佳航行姿态和换能器安全,提高了采集数据的精度。2020年,该无人艇参与江西应急抗洪救灾堤坝勘察任务,在水流湍急、水质浑浊、漂浮垃圾多等不利环境下,圆满完成14 km堤坝底质勘察任务,共发现4处堤坝风险位置点,为抗洪抢险提供了重要的数据支撑。     

Socio economic influences on the restoration and maintenance of the water environment

Protection of the water environment has become a modern socio economic issue in which the sociological pressures for a healthy water environment must be balanced with affordability. Reconciliation of these aspects requires clear political thinking and rigorous methodologies. It also requires a shift in mind-set which considers members of the public as customers.Water utilities are the major users of the water environment and potentially its greatest threat - so good delivery of water services is very important. The presentation addresses the topic through the experience of Anglian Water, a privatised water utility serving Eastern England.     

Experimental studies on the effects of sheet resistance and wettability of catalyst layer on electro-catalytic activities for oxygen evolution reaction in proton exchange membrane electrolysis cells

As the most important part of electrochemical reaction in proton exchange membrane electrolysis cells (PEMECs) for water splitting, oxygen evolution reaction (OER) occurs at the anode catalyst layer (CL). The distribution of the OER site is affected by many factors, such as properties of CL, operation parameters, procedures, etc. To study the effects of properties of CLs on the distribution of OER site on the CL, and consequently affect the performance of PEMECs, CLs with different sheet resistances are tested under different operation conditions. The phenomena of OER on CLs are captured by a high-speed and micro-scale visualization system in-situ and analysed coupled with electrochemical results. The results show that both sheet resistance and wettability of CLs have significant impact on the distribution of the OER site, which can help optimize the design of membrane electrode assembly and improve the operating parameters for electrochemical devices.     

A new method of predicting the saturation pressure of oil reservoir and its application

Saturation pressure is a vital parameter of oil reservoir which can reflect the oilfield characteristics and determine the oilfield development process, and it is determined by experiments in the laboratory in general. However, there was only one well with saturation pressure test in this target reservoir, and it is necessary to determine whether this parameter is right or not.In this work, we present a new method for quickly determining saturation pressure using machine learning algorithms, including random forest regressor (RF), support vector machine (SVM), decision trees (DT), and artificial neural network (ANN or NN). Using these approaches, saturation pressure was obtained by using the initial solution gas-oil ratio (GOR), temperature, API gravity and other reservoir-fluid data available in the oilfields. Compared with the empirical formula for saturation pressure calculation, the calculated result shows that the accuracy given from machine learning is higher than that from other formulas at home and abroad, and has a good match with the lab test. On the basis of the calculated saturation pressure, it can determine whether the reservoir enters into the stage of dissolved gas drive or not, which also provides the basis for maintaining the reservoir pressure by water injection in advance, rational development decision-making and work over measures.This approach above can provide technical guidance for predicting the saturation pressure in the development of different kinds of reservoirs, including the sandstone reservoirs and carbonate reservoirs.     

Road following by artificial vision using neural network

It has been developed, built and tested an artificial vision based system to follow roads, which provides control signals, in a short time, by means of a joint of artificial neural nets. The image is segmented in “road” or “not road.” The obtained segmentation is the input for two neural nets, a classic architecture net (NN), and a TDNN (Time Delay Neural Network) one. The outputs provided by both nets, with a trajectory estimation, are introduced to a decision-making block, which selects the alternative containing less error. The classifier parameters are updated according to the current segmentation.     

A convolution algorithm for linear-sweep voltammetric data at unequally spaced times

A convolution algorithm is derived that applies to unequally spaced current-time or current-potential data, under the assumption of linear variation of the current in each individual interval.     

低功耗海上仪器回收通信信标的研制

可靠的回收系统是海洋仪器进行有效观测和获取数据的关键一环,其中仪器在海面上与科考船 之间的通信信标是回收系统中的重要组成部分。该文设计的低功耗海上仪器回收通信信标是一套可用于 海洋仪器回收的轻量化信标机——集成了全球定位系统(GPS)定位模块和 Lora 低功耗远距离通信模块, 浮出海面后可自动切换为待机模式。该系统在低功耗待机模式下理论待机时间长达 5 年,正常工作模式 下可连续工作不少于 48 h。仪器上浮后可以将位置信息发送至客户端,有效通信距离达到 7 km,并满足 9 000 m 水深的深海适用要求。功耗测试与通信测试表明,该设备具有功耗低、定位精度高、可靠性高、 通信距离较远的优点。