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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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NASA NTRS2019

Simultaneous Localization and Mapping for Satellite Rendezvous and Proximity Operations using Random Finite Sets

Future space missions require that spacecraft have the capability to autonomously navigate non-cooperative environments for rendezvous and proximity operations (RPO). Current relative navigation filters can have difficulty in these situations, diverging due to complications with data association, high measurement uncertainty, and clutter, particularly when detailed a priori maps of the target object or spacecraft do not exist. The goal of this work is to demonstrate the feasibility of random finite set (RFS) filters for spacecraft relative navigation and pose estimation. The approach is to formulate satellite relative navigation and pose estimation as a simultaneous localization and mapping (SLAM) problem, in which an observer spacecraft seeks to simultaneously estimate the location of features on a target object or spacecraft as well as its relative position, velocity and attitude. This work utilizes a filter developed using the framework of RFS which are well suited to multi-target SLAM operations, avoiding data association entirely. Relevant RPO scenarios with simulated flash LIDAR measurements are tested with a Probability Hypothesis Density (PHD) RFS filter embedded in a particle filter to obtain a feature map of a target and a relative pose estimate between the target and observer. Preliminary results show that an RFS-based filter can successfully perform SLAM in a spacecraft relative navigation scenario with no a priori map of the target. These results demonstrate the feasibility of RFS filtering for spacecraft relative navigation and motivate future studies which may expand to tracking space objects for space situational awareness, as well as relative navigation around small bodies.

Schlenker, Lauren↗

NASA NTRSDate not supplied

Mobile Lidar as A Tool for Terrestrial and Planetary Cave Exploration and Mapping

The Kinematic Navigation and Cartography Knapsack (KNaCK) team at NASA’s Marshall Space Flight Center in Huntsville, Alabama is developing tools that enable ultra-high resolution terrain mapping and navigation using mobile LiDAR (Light Detection and Ranging) and SLAM (Simultaneous Localization and Mapping) algorithms in fully GPS-denied and unilluminated environments [1,2]. The backpack mounted LiDAR instrument under development by our team demonstrates the potential of mobile SLAM LiDAR for use in challenging lunar and planetary surface environments as well as for lunar, planetary, and terrestrial cave exploration, study, and utilization.

Lunar Skylight↗

NASA NTRSDate not supplied

Caves as Terrestrial Analogs for Mapping and Exploration in Planetary Surface and Subsurface Environments.

The Kinematic Navigation and Cartography Knapsack (KNaCK) team is developing tools that will enable ultra-high resolution terrain mapping and navigation at the lunar surface. KNaCK uses mobile light detection and ranging (LiDAR) and simultaneous localization and mapping (SLAM) algorithms to operate in fully GPS-denied and unilluminated environments. Testing in relevant analogs is key to perfecting this technology for planetary applications. After utilizing desert and volcanic environments for multiple tests, the team is now using caves as an additional proving ground. Tests in terrestrial caves have demonstrated the potential of mobile SLAM LiDAR for use in challenging surface environments such as steep walled craters and permanently shadowed regions as well as for lunar, planetary, and terrestrial cave exploration, study, and utilization.

LiDAR↗

DOE OSTI2025

Evaluation of antifouling surfaces using a method that employs mussel larvae settlement quantified by machine learning

Antifouling coating development requires extensive performance testing. Coatings that prevent aquatic larval settlement are of interest because many forms of macrofouling begin at the larval stage. However, field testing can be time consuming and poorly controlled. Herein is reported a screening tool, Settlement of Larvae Assay using Mussels (SLAM), for down-selecting materials prior to field testing. The method entails using a dense concentration of mussel larvae that are allowed to settle on submerged test surfaces. Settled larvae are then quantified to provide a measure of antifouling performance. The SLAM test differentiated coatings with only slight differences in formulation. To enable efficient quantification of dense larvae settlement, an automated counting method was developed that combines two analyses: a color thresholding identifies larvae clumps, and a machine learning algorithm identifies non-clumped larvae. Finally, this automated ‘hybrid’ approach rapidly quantifies settled larvae as effectively as manual counting but in a fraction of the time.

Mytilus↗

DOE OSTI2024

300_underground robot (final research report)

Recent advancements in mobile robotics have displayed impressive capabilities in traversing and accessing areas that are inaccessible to humans either due to the characteristics of the environment or potential hazards. Furthermore, these advancements within the field of mobile robotics, more specifically uncrewed ground vehicles (UGVs), give the ability to potentially survey, observe, and map these inaccessible areas for humans. However, one of the most challenging areas to implement this technology is underground environments. The main challenge with implementing this technology in underground environments is the dependence on either GPS or RF communication for UGVs to navigate properly. Therefore, in order to properly demonstrate the mapping capabilities of the UGV this challenge must be resolved. The overall goal of this study is to demonstrate the mapping capabilities of a UGV while addressing this challenge and documenting the implementation and testing phase of the robot. The proposed solution to this challenge is to implement a SLAM algorithm onto the main computational device of the UGV utilizing the Robot Operating System (ROS). The algorithm is the open-source software package Slam Toolbox developed by Steve Macenski. Furthermore, the sllidar_ros2 package from Slamtec will be used to gather the lidar data from an A3M1 2D lidar. A separate program will be created to gather odometry information for our UGV robot. All of these software packages will run together in a Docker environment. Through working on this project I have developed a better understanding of the world of robotics/autonomous systems, especially with applications such as navigation and mapping. Furthermore, through this project, I have been given exposure to how research is conducted within a DOE lab setting. As robotics/autonomous systems become more advanced it's important to pursue more avenues of research such as this project as it will ensure the development of our capabilities.

42 ENGINEERING↗

DOE OSTI2025

Development of a Multi-Robot System for Autonomous Inspection of Nuclear Waste Tank Pits

This paper introduces the overall design plan, development timeline, and preliminary progress of the Autonomous Pit Exploration System project. This project aims to develop an advanced multi-robot system for the efficient inspection of nuclear waste-storage tank pits. The project is structured into three phases: Phase 1 involves data collection and interface definition in collaboration with Hanford Site experts and university partners, focusing on tank riser geometry and hardware solutions. Phase 2 includes the selection of sensors and robot components, detailed mechanical design, and prototyping. Phase 3 integrates all components into a cohesive system managed by a master control package which also incorporates digital twin and surrogate models, and culminates in comprehensive testing and validation at a simulated tank pit at the Idaho National Laboratory. Additionally, the system’s communication design ensures coordinated operation through shared data, power, and control signals. For transportation and deployment, an electric vehicle (EV) is chosen to support the system for a full 10 h shift with better regulatory compliance for field deployment. A telescopic arm design is selected for its simple configuration and superior reach capability and controllability. Preliminary testing utilizes an educational robot to demonstrate the feasibility of splitting computational tasks between edge and cloud computers. Successful simultaneous localization and mapping (SLAM) tasks validate our distributed computing approach. More design considerations are also discussed, including radiation hardness assurance, SLAM performance, software transferability, and digital twinning strategies.

Nuclear waste management↗

DOE OSTI2021

A Method to Preserve Wetland Roots and Rhizospheres for Elemental Imaging

Roots extensively interact with their soil environment but visualizing such interactions between roots and the surrounding rhizosphere is challenging. The rhizosphere chemistry of wetland plants is particularly challenging to capture because of steep oxygen gradients from the roots to the bulk soil. Here a protocol is described that effectively preserves root structure and rhizosphere chemistry of wetland plants through slam-freezing and freeze drying. Slam-freezing, where the sample is frozen between copper blocks pre-cooled with liquid nitrogen, minimizes root damage and sample distortion that can occur with flash-freezing while still minimizing chemical speciation changes. While sample distortion is still possible, the ability to obtain multiple samples quickly and with minimal cost increases the potential to obtain satisfactory samples and optimizes imaging time. The data show that this method is successful in preserving reduced arsenic species in rice roots and rhizospheres associated with iron plaques. This method can be adopted for studies of plant-soil relationships in a wide variety of wetland environments that span concentration ranges from trace-element cycling to phytoremediation applications.

59 BASIC BIOLOGICAL SCIENCES↗

NASA NTRS1981

Ultrasonic scanning of multilayer ceramic chip capacitors

Ultrasonic scanning is compared to neutron radiography and scanning laser acoustic microscopy (SLAM). Data show that SLAM and ultrasonic scanning evaluations are in good agreement. There is poor agreement between N-ray and both ultrasonic techniques because N-ray is insensitive to all but the grossest delaminations. Statistical analysis show a good correlation between ultrasonic scanning and destructive physical analysis.

Bradley, F. N.↗

NASA NTRS1983

System analysis for the Huntsville Operational Support Center distributed computer system

A simulation model was developed and programmed in three languages BASIC, PASCAL, and SLAM. Two of the programs are included in this report, the BASIC and the PASCAL language programs. SLAM is not supported by NASA/MSFC facilities and hence was not included. The statistical comparison of simulations of the same HOSC system configurations are in good agreement and are in agreement with the operational statistics of HOSC that were obtained. Three variations of the most recent HOSC configuration was run and some conclusions drawn as to the system performance under these variations.

Ingels, E. M.↗

NASA NTRS1982

Comparison of NDE techniques for sintered-SiC components

High frequency, bulk-wave ultrasonics detected defects in manufactured SiC components. In addition, gas-turbine blades and vanes were examined by scanning laser acoustic microscopy (SLAM). Comparative results obtained on simple shapes such as disks and bars by microfocus X-ray radiography, ultrasonics, scanning photoacoustic spectroscopy, and SLAM are discussed.

Srinivasan, M.↗

NASA NTRS1986

Reliability of scanning laser acoustic microscopy for detecting internal voids in structural ceramics

The reliability of 100 MHz scanning laser acoustic microscopy (SLAM) for detecting internal voids in sintered specimens of silicon nitride and silicon carbide was evaluated. The specimens contained artificially implanted voids and were positioned at depths ranging up to 2 mm below the specimen surface. Detection probability of 0.90 at a 0.95 confidence level was determined as a function of material, void diameter, and void depth. The statistical results presented for void detectability indicate some of the strengths and limitations of SLAM as a nondestructive evaluation technique for structural ceramics.

Roth, D. J.↗

NASA NTRS1986

Factors that affect reliability of nondestructive detection of flaws in structural ceramics

The factors that affect reliability of nondestructive detection of flaws in structural ceramics by microfocus radiography and scanning laser acoustic microscopy (SLAM) were investigated. Reliability of void detection in silicon nitride and silicon carbide by microfocus X-rays was affected by photon energy level, material chemistry in the immediate vicinity of the void, and the presence of loose powder aggregates inside the void cavity. The sensitivity of SLAM to voids was affected by material microstructure, the level of porosity, and the condition of the specimen surfaces. Statistical results are presented in the form of probability of detection as a function of void diameter for green compacts and sintered materials.

Klima, S. J.↗

NASA NTRS1986

Quantitative void characterization in structural ceramics using scanning laser acoustic microscopy

The ability of scanning laser acoustic microscopy (SLAM) to characterize artificially seeded voids in sintered silicon nitride structural ceramic specimens was investigated. Using trigonometric relationships and Airy's diffraction theory, predictions of internal void depth and size were obtained from acoustic diffraction patterns produced by the voids. Agreement was observed between actual and predicted void depths. However, predicted void diameters were generally much greater than actual diameters. Precise diameter predictions are difficult to obtain due to measurement uncertainty and the limitations of 100 MHz SLAM applied to typical ceramic specimens.

Roth, D. J.↗

NASA NTRS1986

Reliability of scanning laser acoustic microscopy for detecting internal voids in structural ceramics

Roth, D. J.↗

NASA NTRS1987

Nondestructive evaluation of structural ceramics

A review is presented on research and development of techniques for nondestructive evaluation and characterization of advanced ceramics for heat engine applications. Highlighted in this review are Lewis Research Center efforts in microfocus radiography, scanning laser acoustic microscopy (SLAM), scanning acoustic microscopy (SAM), scanning electron acoustic microscopy (SEAM), and photoacoustic microscopy (PAM). The techniques were evaluated by applying them to research samples of green and sintered silicon nitride and silicon carbide in the form of modulus-of-rupture bars containing seeded voids. Probabilities of detection of voids were determined for diameters as small as 20 microns for microfucus radiography, SLAM, and SAM. Strengths and limitations of the techniques for ceramic applications are identified. Application of ultrasonics for characterizing ceramic microstructures is also discussed.

Klima, Stanley J.↗

NASA NTRS1987

Quantitative void characterization in structural ceramics by use of scanning laser acoustic microscopy

Roth, D. J.↗

NASA NTRS1988

Flaw characterization in structural ceramics using scanning laser acoustic microscopy

The ability of scanning laser acoustic microscopy (SLAM) to characterize artifically seeded voids in sintered silicon nitride structural ceramic specimens was investigated. The voids ranged from 20 to 430 microns in diameter and were embedded up to 2 mm beneath the surface of the specimens. Probability of detection was determined as a function of void depth and size. Trigonometric relationships and Airy's diffraction theory were used to obtain predictions of void depth and size from acoustic diffraction patterns produced by the voids. Agreement was observed between actual and predicted void depths. However, predicted void diameters were generally much greater than actual diameters. Precise diameter predictions are difficult to obtain because of measurement uncertainty and the limitations of the 100 MHz SLAM applied to typical ceramic specimens.

Roth, Don J.↗

NASA NTRS1994

Floating shock fitting via Lagrangian adaptive meshes

In recent works we have formulated a new approach to compressible flow simulation, combining the advantages of shock-fitting and shock-capturing. Using a cell-centered Roe scheme discretization on unstructured meshes, we warp the mesh while marching to steady state, so that mesh edges align with shocks and other discontinuities. This new algorithm, the Shock-fitting Lagrangian Adaptive Method (SLAM) is, in effect, a reliable shock-capturing algorithm which yields shock-fitted accuracy at convergence. Shock-capturing algorithms like this, which warp the mesh to yield shock-fitted accuracy, are new and relatively untried. However, their potential is clear. In the context of sonic booms, accurate calculation of near-field sonic boom signatures is critical to the design of the High Speed Civil Transport (HSCT). SLAM should allow computation of accurate N-wave pressure signatures on comparatively coarse meshes, significantly enhancing our ability to design low-boom configurations for high-speed aircraft.

Vanrosendale, John↗