Deep-sea reverse osmosis desalination for energy efficient low salinity enhanced oil recovery

The decrease in the oil discoveries fuels the development of innovative and more efficient extraction processes. It has been demonstrated that Enhanced Oil Recovery (EOR, or tertiary recovery technique) offers prospects for producing 30 to 60% of the oil originally trapped in the reservoir. Interestingly, oil extraction is significantly enhanced by the injection of low salinity water into oilfields, which is known as one of the EOR techniques. Surface Reverse Osmosis (SRO) plants have been adopted to provide the large and continuous amount of low salinity water for this EOR technique, especially in offshore sites. In this article, we outline an original solution for producing low salinity water for offshore EOR processes, and we demonstrate its energy convenience. In fact, the installation of reverse osmosis plants under the sea level (Deep-Sea Reverse Osmosis, DSRO) is found to have significant potential energy savings (up to 50%) with respect to traditional SRO ones. This convenience mainly arises from the non-ideality of reverse osmosis membranes and hydraulic machines, and it is especially evident - from both energy and technological point of view - when the permeate is kept pressurized at the outlet of the reverse osmosis elements. In perspective, DSRO may be a good alternative to improve the sustainability of low salinity EOR

DAS Over Multimode Fibers With Reduced Fading by Coherent Averaging of Spatial Modes

We investigate the performance of distributed acoustic sensing over multi-mode fibers based on heterodyne phase-sensitive optical time-domain reflectometry. We report a mathematical model describing the relation between phase variation and applied strain in the presence of multi-mode propagation that supports the feasibility of distributed acoustic measurements over multi-mode fibers. We also propose a novel coherent averaging method that achieves up to a three-fold reduction of the noise floor compared to state-of-the-art methods

A Full-Stack Open-Source Framework for Antenna and Beamforming Evaluation in mmWave 5G NR

Millimeter wave (mmWave) communication represents one of the main innovations of the next generation of wireless technologies, allowing users to reach unprecedented data rates. To overcome the high path loss at mmWave frequencies, these systems make use of directional antennas able to focus the transmit power into narrow beams using BeamForming (BF) techniques, thus making the communication directional. This new paradigm opens up a set of challenges for the design of efficient wireless systems, in which antenna and BF components play an important role also at the higher layer of the protocol stack. For this reason, accurate modeling of these components in a full-stack simulation is of primary importance to understand the overall system behavior.This paper proposes a novel framework for the end-to-end simulation of 5G mmWave cellular networks, including a raytracing based channel model and accurate models for antenna arrays and BF schemes. We showcase this framework by evaluating the performance of different antenna and BF configurations considering both link-level and end-to-end metrics and present the obtained results

Autonomous underwater vehicle guidance by integrating neural networks and geometric reasoning

This paper presents a method for guiding an autonomous underwater vehicle (AUV) during sea bottom inspection missions. The vehicle is equipped with several sensors (optical, sonar, acoustic) and is able to detect and follow a pipeline placed on the sea bottom. Neural networks and geometric reasoning methods are integrated to perform a real-time identification of pipeline borders in a complex underwater environment. Different scenarios characterized by both obstacles and/or artifacts (due to reflections of artificial light sources used by the vehicle to illuminate the scene) have been considered. Results focus on pipeline detection accuracy and on AUV missions in the absence or presence of down stream and/or obstacles. (C) 1999 John Wiley & Sons, Inc

Open-MBIC: an Open-Source Android Library for Multiple Simultaneous Bluetooth Low Energy Connections

Internet of Things (IoT) are being pervasively deployed within diverse application fields, such as smart homes, smart industry, smart cities, etc. Finding practical solutions to the connection challenges in these real-world scenarios is of key importance and Bluetooth Low Energy (BLE) is, in many cases, the most appropriate communication system to wirelessly connect smart objects and sensors. In this work, we introduce Open-MBIC (Multiple Ble for Iot Connections), an open-source library for Android devices that is conceived to manage multiple BLE connections simultaneously and effectively. Open-MBIC is designed to operate in a general IoT setup and to be easily customizable to suit particular scenarios. As a practical use case, a remote-monitoring system for clinical applications exploiting wearable sensors is here presented

Development of an image recognition system for RFX first wall maintenance

Since the beginning of the machine operation a remote handling system (RHS) has been used to carry out maintenance tasks inside the RFX vacuum vessel, such as tile replacement, first wall inspection and graphite fragment removal. In order to speed up the tile replacement operations and to increase their reliability and safety, it was envisaged to develop a monoscopic vision system capable of recognizing the tile clamping system components on which the end-effector must act to dismount/mount the tiles. The vision system has now been realized and it is described in the paper along with end-effector modifications and executed tests