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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 577 records · Page 32
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Beam controlled nano-robotic device

A system and method (referred to as a method) to fabricate nanorobots. The method generates a pixel map of an atomic object and identifies portions of the atomic object that form a nanorobot. The method stores those identifications in a memory. The method adjusts an electron beam to a noninvasive operating level and images the portions of the atomic object that form the nanorobot. The method executes a plurality of scanning profiles by the electron beam to form the nanorobot and detects nanorobot characteristics and their surroundings via the electron beam in response to executing the plurality of scanning profiles.

77 NANOSCIENCE AND NANOTECHNOLOGY↗
DOE OSTI2012

Commissioning and Operation of a Robotic Arm for Waste Retrieval at Trawsfynydd NPP, North Wales - 12091

Trawsfynydd is one of the UK's first generation Magnox nuclear power plants. It started operation in 1965 and ceased generation in 1991. Before the site can enter the 'care and maintenance' phase a number of wet and dry waste stores around the site must be emptied and their contents made safe. Wet wastes include sludges and resins produced during the operating life of the NPP. The sludges and resins are stored in a number of different tanks that vary significantly in terms of size, shape, internal features and access. A dexterous long reach manipulator arm has been designed and built to facilitate tank clearance. Commissioning of the arm was carried out in parallel with Factory Acceptance Testing (FAT) at the manufacturer's site in Colorado, USA. In addition to basic functional testing this work included a full range of task based testing to ensure that the arm, tools, control system and support equipment were thoroughly exercised in representative conditions. Trawsfynydd is one of the lead sites in the UK's program for nuclear plant decommissioning. As such the lessons learned, both in terms of technology and process, will be applicable across the remainder of the fleet. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

Development of Robotic Crawlers for Inspection of Radioactive Waste Tanks and Transfer Lines - 19573

The leaks in the primary liner of Double Shell Tank (DST) 241-AY-102 have motivated a number of research efforts to develop inspection tools that can obtain information regarding the integrity of the Hanford DSTs. Recently, there have been additional concerns regarding the DST secondary liners as well various pipelines within the waste transfer system. Over the past few years, Florida International University (FIU) has developed a pneumatic pipe crawler that can navigate through 3- and 4-inch diameter pipes and provide visual feedback while traveling through pipelines in excess of 100 feet and multiple 90 degree elbows. Recent updates to the crawler include a new sensor module that can provide information regarding environmental conditions within the pipeline and a mapping of the interior surface of the line. The sensor module is a carousel type device that can rotate 360 degrees and is placed near the front of the 3- and 4- inch crawler. The module can house a number of sensors including temperature, pressure, radiation, Lidar, optical camera and an inertial measurement unit (IMU). The intent of the module is to improve the functionality of the crawler by providing environmental conditions within the pipe and internal surface topography maps that can assist in understanding potential wear, pitting or thinning of the pipe. In addition to the 3- and 4-inch crawler, FIU is developing a 6-inch crawler that utilizes the same principles as the smaller unit. The objective of this tool is to navigate through the 6-inch drain lines leading to the drain channels within the foundation underneath the secondary liner of the DSTs. This crawler will house a miniature rover that will be deployed at the end of the drain pipe, where it connects to the foundation. The miniature rover will operate upside down, via magnets, underneath the secondary liner within the drain slots and provide visual information regarding the condition of the secondary liner. Thinning of the secondary liner has been noted from the annulus of the some of the DSTs, but it is unclear if the thinning is isolated to locations near the annulus. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

R and DE Robotic Sensor Intern Team: Remote 3D Mapping Sensor Suite

The primary goal of the sensor suite is to provide an internal 3D map of the HCAEX tunnel. When looking for a sensor that would provide XYZ point cloud data for mapping the decision was between a stereo camera, a 3D Lidar, or a 2D Lidar that would need to be spun around. The issues with the stereo camera were that it does not have a large field-of-view and that its depth information was not nearly as accurate as even the baseline Lidars. The selection between Lidars is detailed. The Hokuyo UTM-30LX-EW shown provides a 270 deg. FOV with high accuracy and resolution while the largest FOV on a 3D Lidar is 40 deg.. This was the reason a 2D Lidar was chosen over the 3D Lidar. Even though the 2D Lidar requires additional components and software to generate a 3D map, its FOV advantage is too great given that the HCAEX tunnel is a relatively confined space. The rotating planar scan from the 2D Lidar can be stitched into a 3D scan as shown in the graphic below. Along with XYZ data, the Lidar provides return intensity data in color which can be used to distinguish between different materials within the tunnel. To provide visual feedback a camera system needed to be identified. The common solution for this is a high resolution camera with a small FOV mounted on a pan-tilt system. But, given the critical nature of the visual feedback we looked into solutions without the need for moving parts. Two panospheric cameras give a FOV large enough to get a full 360 deg. view.. Camera color data (RGB) can also be combined with the 3D mapping data from the Lidar and overlaid on the map to give the user the ability to see inside the entire length of the tunnel as if they were inside. Situational awareness is required for the crawler in the tunnel in order for it to be able to register the 3D scans to create a final map. For this we procured a Microstrain 3DM-GX5-25 Inertial Measurement Unit (IMU). To perform the Lidar rotation we have two servos driving the pan and tilt. The servo controls and most data processing will be performed via an onboard computer. The sensor components are to be packaged together using 3D printed mounts into a standalone unit.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2019

R and DE Robotic Sensor Intern Team: Sensor Suite Software and User Interface

The sensor tree developed for the H-Canyon tunnel inspection project produces a large quantity of camera and Lidar data. A postprocessing pipeline was created to facilitate the analysis of these data. The pipeline follows the following routine: 1) Registration - Salient local features in subsequent scans are identified and used to align the scans with one another. This allows production of a single cohesive map of the tunnel. 2) Sensor Fusion - RGB camera data is 'painted' onto the depth data created by the Lidar. 3) Segmentation - Individual surfaces from within the scene are segmented out separately for individual analysis. 4) Degradation Analysis - Automatic mapping of local deviation from the plane in position or surface normal is performed, as is detection of exposed rebar using Lidar return intensity. 5) Obstacle Detection - Lidar data is also used in real time to detect obstacles in the environment. This could give feedback to the operator to successfully drive in the tunnel. 6) Graphic User Interface - a custom GUI was created to facilitate customer use of the system. The system provides real-time feedback from both the cameras and Lidar. During alignment, local features are used to recognize points within the walls that are especially unique and noticeable (salient) based on their deviation from the expected surface of the wall. These are used as landmarks to register the clouds, which also informs precise localization of the base at each scan point. After registration, clouds are 'painted' with RGB data from the spherical cameras, as shown below. The painted clouds provide a 3D, colorized model of the environment which improves the realism of the experience for the user. Painting also labels high-resolution color imagery from the 3D cameras with depth values. Following sensor fusion, individual walls and cylindrical duct surfaces are segmented from the scene for individual analysis using a Random Sample Consensus algorithm. This algorithm allows segmentation of planar walls and cylindrical ducts. Once individual walls are identified, each point within the wall can be compared to its neighbors and the wall overall in order to detect local areas with damaged concrete. Automatic rebar detection is also performed using the contrast in Lidar return intensity between iron and concrete. The Lidar point-cloud data is also used for obstacle detection. As the Lidar spins, various algorithms are run to analyze the current 'slice' and obstacles in the environment are determined and registered on a cost-map. A Graphical User Interface (GUI) was developed to allow the user to easily command the crawler to set the rotational speed of the Lidar, perform a scan, and register and save the 3D generated cloud after a scan is done. For the good of the crawler, a critical aspect of the GUI design is to allow the user to cancel a scan any time after it is commanded and before it is saved.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2016

Dry Canister Storage System Inspection and Robotic Delivery System Development

EPRI is working to develop and demonstrate technologies capable of inspecting welded stainless steel canisters used in dry cask storage systems in situ, without the need to remove them from their concrete casks. This involves the coupling of specialized cameras and inspection devices with small remotely operated vehicles (ROVs). The objective is to demonstrate the capability to identify any presence of (or precursors to) stress corrosion cracking (SCC) and other anomalies that may require additional investigation. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

Reinforcement Learning for Energy-Movement Optimization in Arduino-Based Robotics

Our goal is to develop a learning method for an Arduino-based robotthat maximizes travel distance and minimizes energy expenditure. • Will implement State ActionReward State Action (SARSA) reinforcement learning algorithm • Learning steps informed by state of environment • Rewards good decisions and punishes bad ones.

Gilmore, Blake↗