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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 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Irradiation Assessment of a Lightweight Industrial Robot - Towards Faster, Safer and Sooner Waste Decommissioning - 20317

Robotic systems have been successfully applied in the nuclear industry for several decades as a safe approach to minimize the exposure dose of human operators. As nuclear waste management and decommissioning gathers pace, there is an emerging interest integrating modern off-the-shelf industrial robots in nuclear robotic systems which make use of complex electronics and software to improve functionality over traditional machines. The use of the industrial robots will significantly increase the pace of development of automated waste management systems at a reduced cost, and although these off-the-shelf robots are proven robust in typical industrial environments, performance in radioactive environments is less clear. This paper investigates the performance degradation of a lightweight industrial robot (KUKA iiwa 7 LBR 800) in a controlled radiation field, aiming to simulate conditions in highly radioactive nuclear waste handling facilities. The degradation of the industrial robot's performance is identified while measuring the air kerma dose-tolerance of sensitive components, via a systematic experimental methodology. The experience from this experiment has demonstrated the significant capabilities of industrial robots, which tolerated a large gamma dose of 164 Gy before a system failure. Future tests are planned, aiming to enable faster, safer and sooner waste management and decommissioning using complex robotic systems. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2022

Flexible positioning of a large area detector using an industrial robot

The DIAD beamline for Dual Imaging and Diffraction at Diamond Light Source has opted to use an industrial robot to position its Dectris Pilatus 2M CdTe diffraction detector. This setup was chosen to enable flexible positioning of the detector in a quarter-sphere around the sample position whilst reliably holding the large weight of 139 kg of detector, detector mount and cabling in a stable position. Metrology measurements showed that the detector can be positioned with a linear repeatability of <19.7 µm and a rotational repeatability of <16.3 µrad. The detector position stays stable for a 12 h period with <10.1 µm of movement for linear displacement and <3.8 µrad for rotational displacement. X-ray diffraction from calibration samples confirmed that the robot is sufficiently stable to resolve lattice d-spacings within the instrumental broadening given by detector position and beam divergence.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Controls and process planning strategies for 5-axis laser directed energy deposition of Ti-6Al-4V using an 8-axis industrial robot and rotary motion

Interest in multi-axis additive manufacturing has grown significantly in recent years due to associated benefits that range from improved quality to support for greater geometric complexity. A method of 5-axis Laser Hot-Wire Directed Energy Deposition is developed and demonstrated in this study using an 8-axis industrial robot, comprised of a 6-axis serial link robot and a 2 degree-of-freedom positioner. Coordinated 5-axis motion is used to print Ti-6Al-4V objects predominantly through build plate rotation. Methods of slicing and toolpath generation are presented, including the use of an alternating toolpath direction philosophy and the manipulation of the CAD model surface normal vectors for determining the required build plate tilt angles for maintaining consistent deposition orientations relative to gravity. Another objective of the study was to determine the limits of conventional slicing and layer height control techniques for printing geometries with significant unsupported overhangs. A comparison is made between the behavior of normal and conformal bead alignment in this regard, and the performance of the layer height controller is reported as it relates to process stability and the limits of printing overhang geometries. Unsupported overhangs were successfully printed at 35° without build plate tilt and 45° with build plate tilt. Toolpath velocity and net-shape printing performance are reported as well, with 3D scans of the printed surfaces used for net-shape characterization. In all, the printing of three geometries is presented, including the overhang geometry, a 5-axis toolpath geometry, and a large-scale, multi-bead demonstrator part, which exceeded 500 mm in height and weighed 44 kg (97 lbs).

36 MATERIALS SCIENCE↗
DOE OSTI2022

Industrialized and Robotic Construction Advances in Terrestrial Construction and Opportunities in Space Construction

Advanced Building Construction (ABC) methods such as industrialized prefabrication and robotically controlled additive deposition are becoming promising technologies to support rapid construction of buildings at volume and scale. However, apart from the structural shell of the building, optimal integration of other systems – mechanical, electrical, plumbing, thermal, power generation, storage and distribution, is key to enabling functional buildings. Leveraging ABC methods to integrate such systems in the buildings requires the building design to be optimized for constructability constraints imposed by the industrialized and robotically controlled production setups entailing such ABC methods. The Industrialized Construction Innovation (ICI) team at the National Renewable Energy Laboratory (NREL) has been focusing on research and development of such ABC technologies and processes that can lead to production of buildings which are resilient to extreme climatic conditions at reduced cost and time. There is a potential synergy between such advancements in terrestrial construction, which can be leveraged for the benefit of space (orbital and extra-terrestrial) construction. Similarly, advances in space construction can lend itself to accelerated adoption of robotic construction methods in terrestrial construction. This presentation will give an overview of selective research efforts of the ICI team at NREL, along with a vision for potential collaborations with agencies like NASA.

3D printing↗
DOE OSTI2022

Case studies of robots and automation as health/safety interventions in small manufacturing enterprises

This article reviews the experiences of 63 case studies of small businesses (<250 employees) with manufacturing automation equipment acquired through a health/safety intervention grant program. The review scope included equipment technologies classified as industrial robots (n = 17), computer numerical control (CNC) machining (n = 29), or other programmable automation systems (n = 17). Descriptions of workers' compensation (WC) claim injuries and identified risk factors that motivated the acquisition of the equipment were extracted from grant applications. Other aspects of the employer experiences, including qualitative and quantitative assessment of effects on risk factors for musculoskeletal disorders (MSD), effects on productivity, and employee acceptance of the intervention were summarized from the case study reports. Case studies associated with a combination of large reduction in risk factors, lower cost per affected employee, and reported increases in productivity were CNC stone cutting system, CNC/vertical machining system, automated system for bottling, CNC/routing system for plastics products manufacturing, and a CNC/Cutting system for vinyl/carpet. Six case studies of industrial robots reported quantitative reductions in MSD risk factors in these diverse manufacturing industries: snack foods; photographic film, paper, plate, and chemical; machine shops; leather goods and allied products; plastic products; and iron and steel forging. Furthermore, this review of health/safety intervention case studies indicates that advanced (programmable) manufacturing automation, including industrial robots, reduced workplace musculoskeletal risk factors, and improved process productivity in most cases.

42 ENGINEERING↗
DOE OSTI2020

Machine Vision-based Robot Manipulators for Nuclear Applications - 20370

Decommissioning and dismantling of nuclear facilities are major challenges facing the nuclear industry. Robot manipulators with capabilities of restoring nuclear structures and significantly prolonging nuclear power generation in addition to their applications in decommissioning and dismantling (D and D) would immensely ease the above-mentioned challenge. Ability to remotely sense/monitor and analyze dangerous and hazardous environments such as nuclear reactors as well as performing reparatory tasks in such environments using robot manipulators require additional information from vision sensors. Structural sample collection and inspection as well as restoration require object and position information. Computer vision is used to obtain precise 3D position information. The current work uses the Sawyer robot with the integrated Cognex camera. The research presents an approach to facilitate and improve operations in a nuclear reactor using robotic vision control. The vision control system is modeled with Augmented Image Space-based visual servoing approach. Results showing accurate robot control. Object recognition is used to recognize the image and calculate it poses. To transform coordinates of the object's pose from the camera frame to the robotic frame transformation matrices are employed. Future work will employ a 3D camera (with depth information) using Denso robot. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2023

Toward three-dimensional DNA industrial nanorobots

Nanoscale industrial robots have potential as manufacturing platforms and are capable of automatically performing repetitive tasks to handle and produce nanomaterials with consistent precision and accuracy. We demonstrate a DNA industrial nanorobot that fabricates a three-dimensional (3D), optically active chiral structure from optically inactive parts. By making use of externally controlled temperature and ultraviolet (UV) light, our programmable robot, ~100 nanometers in size, grabs different parts, positions and aligns them so that they can be welded, releases the construct, and returns to its original configuration ready for its next operation. Our robot can also self-replicate its 3D structure and functions, surpassing single-step templating (restricted to two dimensions) by using folding to access the third dimension and more degrees of freedom. Our introduction of multiple-axis precise folding and positioning as a tool/technology for nanomanufacturing will open the door to more complex and useful nano- and microdevices.

Robotics↗
DOE OSTI2021

Robotic sample changers for macromolecular X-ray crystallography and biological small-angle X-ray scattering at the National Synchrotron Light Source II

In this work, we present two robotic sample changers integrated into the experimental stations for the macromolecular crystallography (MX) beamlines AMX and FMX, and the biological small-angle scattering (bioSAXS) beamline LiX. They enable fully automated unattended data collection and remote access to the beamlines. The system designs incorporate high-throughput, versatility, high-capacity, resource sharing and robustness. All systems are centered around a six-axis industrial robotic arm coupled with a force torque sensor and in-house end effectors (grippers). They have the same software architecture and the facility standard EPICS-based BEAST alarm system. The MX system is compatible with SPINE bases and Unipucks. It comprises a liquid nitrogen dewar holding 384 samples (24 Unipucks) and a stay-cold gripper, and utilizes machine vision software to track the sample during operations and to calculate the final mount position on the goniometer. The bioSAXS system has an in-house engineered sample storage unit that can hold up to 360 samples (20 sample holders) which keeps samples at a user-set temperature (277 K to 300 K). The MX systems were deployed in early 2017 and the bioSAXS system in early 2019.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Comprehension of Spatial Constraints by Neural Logic Learning from a Single RGB-D Scan

Autonomous industrial assembly relies on the precise measurement of spatial constraints as designed by computer-aided design (CAD) software such as SolidWorks. This paper proposes a framework for an intelligent industrial robot to understand the spatial constraints for model assembly. An extended generative adversary network (GAN) with a 3D long short-term memory (LSTM) network was designed to composite 3D point clouds from a single RGB-D scan. The spatial constraints of the segmented point clouds are identified by a neural-logic network that incorporates general knowledge of spatial constraints in terms of first-order logic. The model was designed to comprehend a complete set of spatial constraints that are consistent with industrial CAD software, including left, right, above, below, front, behind, parallel, perpendicular, concentric, and coincident relations. The accuracy of 3D model composition and spatial constraint identification was evaluated by the RGB-D scans and 3D models in the ABC dataset. The proposed model achieved 57.23% intersection over union (IoU) in 3D model composition, and over 99% in comprehending all spatial constraints.

Wang, Dali↗
DOE OSTI2020

Advancing Fusion with Machine Learning Research Needs Workshop Report

Abstract Machine learning and artificial intelligence (ML/AI) methods have been used successfully in recent years to solve problems in many areas, including image recognition, unsupervised and supervised classification, game-playing, system identification and prediction, and autonomous vehicle control. Data-driven machine learning methods have also been applied to fusion energy research for over 2 decades, including significant advances in the areas of disruption prediction, surrogate model generation, and experimental planning. The advent of powerful and dedicated computers specialized for large-scale parallel computation, as well as advances in statistical inference algorithms, have greatly enhanced the capabilities of these computational approaches to extract scientific knowledge and bridge gaps between theoretical models and practical implementations. Large-scale commercial success of various ML/AI applications in recent years, including robotics, industrial processes, online image recognition, financial system prediction, and autonomous vehicles, have further demonstrated the potential for data-driven methods to produce dramatic transformations in many fields. These advances, along with the urgency of need to bridge key gaps in knowledge for design and operation of reactors such as ITER, have driven planned expansion of efforts in ML/AI within the US government and around the world. The Department of Energy (DOE) Office of Science programs in Fusion Energy Sciences (FES) and Advanced Scientific Computing Research (ASCR) have organized several activities to identify best strategies and approaches for applying ML/AI methods to fusion energy research. This paper describes the results of a joint FES/ASCR DOE-sponsored Research Needs Workshop on Advancing Fusion with Machine Learning, held April 30–May 2, 2019, in Gaithersburg, MD (full report available at https://science.osti.gov/-/media/fes/pdf/workshop-reports/FES_ASCR_Machine_Learning_Report.pdf ). The workshop drew on broad representation from both FES and ASCR scientific communities, and identified seven Priority Research Opportunities (PRO’s) with high potential for advancing fusion energy. In addition to the PRO topics themselves, the workshop identified research guidelines to maximize the effectiveness of ML/AI methods in fusion energy science, which include focusing on uncertainty quantification, methods for quantifying regions of validity of models and algorithms, and applying highly integrated teams of ML/AI mathematicians, computer scientists, and fusion energy scientists with domain expertise in the relevant areas.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2023

Automated Post-Mold Operations for Wind Blade Manufacturing

Three post-mold operations performed in wind blade manufacturing include: trimming, to remove excess flashing; grinding, to shape the leading edge; and sanding, to prepare the are for bonding of over-lamination or paint. This work focuses on automating these three operations. Each operation scans the blade to build a point cloud, plans a tool path for the operation, and executes the toolpath using an industrial robot arm. The results are analyzed to determine the operational speed and the finish quality.

advanced manufacturing↗
DOE OSTI2026

Autonomous elemental characterization enabled by a low cost robotic platform built upon a generalized software architecture

Despite the rapidly growing applications of robots in industry, the use of robots to automate tasks in scientific laboratories is less prolific due to the lack of generalized methodologies and the high cost of hardware. This paper focuses on the automation of characterization tasks necessary for reducing cost while maintaining generalization and proposes a software architecture for building robotic systems in scientific laboratory environments. A dual-layer (Socket.IO and ROS) action server design is the basic building block, which facilitates the implementation of a web-based front end for user-friendly operation and the use of ROS Behavior Trees for convenient task planning and execution. A robotic platform for automating mineral and material sample characterization is built upon the architecture, with an open-source, low-cost three-axis computer numerical control gantry system serving as the main robot. A handheld laser induced breakdown spectroscopy (LIBS) analyzer is integrated with a 3D printed adapter, enabling (1) automated 2D chemical mapping and (2) autonomous sample measurement (with the support of an RGB-Depth camera). We demonstrate the utility of automated chemical mapping by scanning the surface of a spodumene-bearing pegmatite core sample with a 1071-point dense hyperspectral map acquired at a rate of 1520 bits per second. Furthermore, we showcase the autonomy of the platform in terms of perception, dynamic decision-making, and execution, through a case study of LIBS measurement of multiple mineral samples. The platform enables controlled and autonomous chemical quantification in the laboratory that complements field-based measurements acquired with the same handheld device, linking resource exploration and processing steps in the supply chain for lithium-based battery materials.

Cao, Xuan [Lawrence Berkeley National Laboratory (↗
DOE OSTI2021

Wind Turbine Blade Finishing Automation: Robotic Toolpath Generation

Wind turbine blades are now over 100 meters long and can reach heights of several meters while in the finishing area of the factory. Because of this, automation should be used to lower the manufacturing cost and make the process safer for blade manufacturing technicians. This session will present a novel method that generates a six degree of freedom robotic toolpath with 3D cameras for the finishing of wind turbine blades to drive down the levelized cost and make wind energy even more competitive in the utility scale energy generation industry.

3d imaging↗
DOE OSTI2024

Design of robot grippers for binder jet products handling

Dimension accuracy, damage minimization, and defect detection are essential in manufacturing processes, especially additive manufacturing. These types of challenges may arise either during the manufacture of a product or its use. The repeatability of the process is vital in additive manufacturing systems. However, human users may lose concentration and, thus, would be a great alternative as an assistant. Depending on the nature of work, a robot’s fingers might vary, for example, mechanical, electrical, vacuum, two-fingers, and three-fingers. In addition, the end effector plays a vital role in picking up an object in the advanced manufacturing process. However, inbuilt robotic fingers may not be appropriate in different production environments. In this research presented here considering metal binder jet additive manufacturing, the two-finger end- effectors are proposed design, analysis, and experiment to pick up an object after completing the production process from a specific location. The final designs were further printed by using a 3D metal printer and installed in the existing robotic systems. These new designs are used successfully to hold the object from the specific location by reducing the contact force that was not possible with the previously installed end effector's finger. In addition, a numerical study was conducted in order to compare the flowability of the geometric shape of finger's free areas.

42 ENGINEERING↗
DOE OSTI2026

WM26 Paper Multi-Robot Collaboration for Hazardous Environments

Hazardous nuclear and industrial facilities are rarely designed for robots. Work in these domains demand precise manipulation and robust mobility in cluttered, constrained spaces where off-the-shelf platforms struggle and “one-size-fits-all” machines become costly and complex. Idaho National Laboratory (INL) is developing an autonomous, multi-robot inspection system that coordinates task-specific platforms rather than relying on a single omni-tool robot. An electric truck serves as a power and compute hub for a custom manipulator co-developed with Florida International University (FIU), a commercial mini crawler, a pan–tilt–zoom camera, and a Nexxis Argus LiDAR mapping system. Working in concert, these robots generate spatial, radiation, and temperature maps of the pit environments at the Hanford Waste Tank Farms. These systems will capture visual records and environmental telemetry to allow for analysis post inspection. The system architecture uses Robot Operating System 2 (ROS 2) for publish/subscribe integration, NVIDIA Isaac Sim and Unity for simulation and visualization, and algorithms such as NVBlox to fuse data into unified 3D overlays. This robot-agnostic approach reduces operator burden by enabling autonomy across heterogeneous platforms and lets each robot be used where it is strongest. Having autonomous functions means operators don’t have to fully control multiple different components. The ease of use could allow for more widespread adoption of advanced robotics at waste management sites that see continued use. By coordinating simpler, purpose-built mechanisms, the approach lowers design and manufacturing complexity, reduces capital risk in contaminated settings, and improves controllability for complex inspection and manipulation tasks. We present the architecture, early results, and lessons learned from building and deploying this coordinated multi-robot system, with the goal of accelerating safe, cost-effective adoption of advanced robotics at waste-management sites.

42 - ENGINEERING↗
DOE OSTI2020

Additive Manufacturing of Controlled Porous Elastomeric Nanocomposites for Enhanced Sensing Function

Sensors manufactured using piezoresistive elastomeric nanocomposites have a wide range of applications in many fields such as structural health monitoring, robotics, and biomedical industries. Additive manufacturing of these sensors, achieved using Direct Ink Writing (DIW), has provided numerous advantages including increased sensitivity and the fabrication of complex geometry. However, solid sensors manufactured either additively or using conventional methods, display a greater level of hysteresis, especially at strains higher than 10%, which limits their sensitivity. The solid sensors also display a greater level of piezoresistive relaxation where the resistance change with time either in a static or dynamic loading environment. Porosity can be introduced in the form of varying infill patterns and densities to reduce bulk material effects. In this paper, a lattice structure with four infill densities are investigated, and the samples are printed using a grid infill pattern. The fabricated samples are characterized using a scanning electron microscope (SEM) to validate the microstructural features and layer bonding. The pressure-sensing capability of each sensor is investigated using cyclic compression loading at various strain levels. Sensing results show that an increase in sensitivity, as well as a decrease in hysteresis with an increase in porosity, compared to solid samples (100% in-fill). The highest porosity was measured to be 62.3% with a corresponding 112% increase in the gauge factor compared to the solid bulk. These results indicate that introducing porosity using DIW is a sensible strategy to improve the piezoresistive performance of nanocomposites and to allow for the tunability of sensing capacity in pressure sensors

Sukati, Musa↗
DOE OSTI2026

Synthetic Digital Environments for Training Robots on Earth & Beyond [Poster]

Creating physical replicas of real-world environments to train robots for challenging outdoor tasks, whether constructing energy infrastructure like solar farms on Earth or on the Moon and Mars, is prohibitively expensive. This project will prototype a high-fidelity digital twin framework using NVIDIA IsaacSim to create realistic digital representations of robotic systems and their operating conditions, including varied terrains and environmental factors, allowing robots to learn and adapt in a faster, safer, and more affordable way to tackle unpredictable challenges in terrestrial and extraterrestrial applications. The Robotic Space Exploration (RoSE) Lab at Colorado School of Mines focused on the development and testing of synthetic digital twins to explore multi-physics interactions between robots and unstructured environments, with emphasis on lunar conditions such as deformable regolith, reduced gravity, and terrain-robot contact dynamics. The Industrialized Construction Innovation (ICI) team at National laboratory of the Rockies (NLR), simulated robotic apparatus and construction workflows using synthetic digital twins to inform real-world deployment, targeting application-driven use cases such as robotic construction of a scaled prototype of a photovoltaic energy infrastructure. Joint efforts between RoSE and ICI are continuing to explore how environment-scale multi-physics modeling and application-level robotic system simulation could be integrated to support robotic construction of energy infrastructure in highly unstructured environments, including scenarios relevant to the Lunar South Pole.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗