20 resultados para Steam-navigation


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Analysis of minimally invasive surgical videos is a powerful tool to drive new solutions for achieving reproducible training programs, objective and transparent assessment systems and navigation tools to assist surgeons and improve patient safety. This paper presents how video analysis contributes to the development of new cognitive and motor training and assessment programs as well as new paradigms for image-guided surgery.

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The supercritical Rankine power cycle offers a net improvement in plant efficiency compared with a subcritical Rankine cycle. For fossil power plants the minimum supercritical steam turbine size is about 450MW. A recent study between Sandia National Laboratories and Siemens Energy, Inc., published on March 2013, confirmed the feasibility of adapting the Siemens turbine SST-900 for supercritical steam in concentrated solar power plants, with a live steam conditions 230-260 bar and output range between 140-200 MWe. In this context, this analysis is focused on integrating a line-focus solar field with a supercritical Rankine power cycle. For this purpose two heat transfer fluids were assessed: direct steam generation and molten salt Hitec XL. To isolate solar field from high pressure supercritical water power cycle, an intermediate heat exchanger was installed between linear solar collectors and balance of plant. Due to receiver selective coating temperature limitations, turbine inlet temperature was fixed 550ºC. The design-point conditions were 550ºC and 260 bar at turbine inlet, and 165 MWe Gross power output. Plant performance was assessed at design-point in the supercritical power plant (between 43-45% net plant efficiency depending on balance of plantconfiguration), and in the subcritical plant configuration (~40% net plant efficiency). Regarding the balance of plant configuration, direct reheating was adopted as the optimum solution to avoid any intermediate heat exchanger. One direct reheating stage between high pressure turbine and intermediate pressure turbine is the common practice; however, General Electric ultrasupercritical(350 bar) fossil power plants also considered doubled-reheat applications. In this study were analyzed heat balances with single-reheat, double-reheat and even three reheating stages. In all cases were adopted the proper reheating solar field configurations to limit solar collectors pressure drops. As main conclusion, it was confirmed net plant efficiency improvements in supercritical Rankine line-focus (parabolic or linear Fresnel) solar plant configurations are mainly due to the following two reasons: higher number of feed-water preheaters (up to seven)delivering hotter water at solar field inlet, and two or even three direct reheating stages (550ºC reheating temperature) in high or intermediate pressure turbines. However, the turbine manufacturer should confirm the equipment constrains regarding reheating stages and number of steam extractions to feed-water heaters.

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Abstract The development of cognitive robots needs a strong “sensorial” support which should allow it to perceive the real world for interacting with it properly. Therefore the development of efficient visual-processing software to be equipped in effective artificial agents is a must. In this project we study and develop a visual-processing software that will work as the “eyes” of a cognitive robot. This software performs a three-dimensional mapping of the robot’s environment, providing it with the essential information required to make proper decisions during its navigation. Due to the complexity of this objective we have adopted the Scrum methodology in order to achieve an agile development process, which has allowed us to correct and improve in a fast way the successive versions of the product. The present project is structured in Sprints, which cover the different stages of the software development based on the requirements imposed by the robot and its real necessities. We have initially explored different commercial devices oriented to the acquisition of the required visual information, adopting the Kinect Sensor camera (Microsoft) as the most suitable option. Later on, we have studied the available software to manage the obtained visual information as well as its integration with the robot’s software, choosing the high-level platform Matlab as the common nexus to join the management of the camera, the management of the robot and the implementation of the behavioral algorithms. During the last stages the software has been developed to include the fundamental functionalities required to process the real environment, such as depth representation, segmentation, and clustering. Finally the software has been optimized to exhibit real-time processing and a suitable performance to fulfill the robot’s requirements during its operation in real situations.

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This research on odometry based GPS-denied navigation on multirotor Unmanned Aerial Vehicles is focused among the interactions between the odometry sensors and the navigation controller. More precisely, we present a controller architecture that allows to specify a speed specified flight envelope where the quality of the odometry measurements is guaranteed. The controller utilizes a simple point mass kinematic model, described by a set of configurable parameters, to generate a complying speed plan. For experimental testing, we have used down-facing camera optical-flow as odometry measurement. This work is a continuation of prior research to outdoors environments using an AR Drone 2.0 vehicle, as it provides reliable optical flow on a wide range of flying conditions and floor textures. Our experiments show that the architecture is realiable for outdoors flight on altitudes lower than 9 m. A prior version of our code was utilized to compete in the International Micro Air Vehicle Conference and Flight Competition IMAV 2012. The code will be released as an open-source ROS stack hosted on GitHub.

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In this paper, we consider the problem of autonomous navigation of multirotor platforms in GPS-denied environments. The focus of this work is on safe navigation based on unperfect odometry measurements, such as on-board optical flow measurements. The multirotor platform is modeled as a flying object with specific kinematic constraints that must be taken into account in order to obtain successful results. A navigation controller is proposed featuring a set of configurable parameters that allow, for instance, to have a configuration setup for fast trajectory following, and another to soften the control laws and make the vehicle navigation more precise and slow whenever necessary. The proposed controller has been successfully implemented in two different multirotor platforms with similar sensoring capabilities showing the openness and tolerance of the approach. This research is focused around the Computer Vision Group's objective of applying multirotor vehicles to civilian service applications. The presented work was implemented to compete in the International Micro Air Vehicle Conference and Flight Competition IMAV 2012, gaining two awards: the Special Award on "Best Automatic Performance - IMAV 2012" and the second overall prize in the participating category "Indoor Flight Dynamics - Rotary Wing MAV". Most of the code related to the present work is available as two open-source projects hosted in GitHub.