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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

Stress analysis and design considerations for Shuttle pointed autonomous research tool for astronomy /SPARTAN/

The Shuttle Pointed Autonomous Research Tool for Astronomy (SPARTAN) family of spacecraft are intended to operate with minimum interfaces with the U.S. Space Shuttle in order to increase flight opportunities. The SPARTAN I Spacecraft was designed to enhance structural capabilities and increase reliability. The approach followed results from work experience which evolved from sounding rocket projects. Structural models were developed to do the analyses necessary to satisfy safety requirements for Shuttle hardware. A loads analysis must also be performed. Stress analysis calculations will be performed on the main structural elements and subcomponents. Attention is given to design considerations and program definition, the schematic representation of a finite element model used for SPARTAN I spacecraft, details of loads analysis, the stress analysis, and fracture mechanics plan implications.

Ferragut, N. J.↗

An Analytical Thermal Model for Autonomous Soaring Research

A viewgraph presentation describing an analytical thermal model used to enable research on autonomous soaring for a small UAV aircraft is given. The topics include: 1) Purpose; 2) Approach; 3) SURFRAD Data; 4) Convective Layer Thickness; 5) Surface Heat Budget; 6) Surface Virtual Potential Temperature Flux; 7) Convective Scaling Velocity; 8) Other Calculations; 9) Yearly trends; 10) Scale Factors; 11) Scale Factor Test Matrix; 12) Statistical Model; 13) Updraft Strength Calculation; 14) Updraft Diameter; 15) Updraft Shape; 16) Smoothed Updraft Shape; 17) Updraft Spacing; 18) Environment Sink; 19) Updraft Lifespan; 20) Autonomous Soaring Research; 21) Planned Flight Test; and 22) Mixing Ratio.

Allen, Michael↗

Development of an Energy Efficient and Cost Effective Autonomous Vehicle Research Platform

Commercialization of autonomous vehicle technology is a major goal of the automotive industry, thus research in this space is rapidly expanding across the world. However, despite this high level of research activity, literature detailing a straightforward and cost-effective approach to the development of an AV research platform is sparse. To address this need, we present the methodology and results regarding the AV instrumentation and controls of a 2019 Kia Niro which was developed for a local AV pilot program. This platform includes a drive-by-wire actuation kit, Aptiv electronically scanning radar, stereo camera, MobilEye computer vision system, LiDAR, inertial measurement unit, two global positioning system receivers to provide heading information, and an in-vehicle computer for driving environment perception and path planning. Robotic Operating System software is used as the system middleware between the instruments and the autonomous application algorithms. After selection, installation, and integration of these components, our results show successful utilization of all sensors, drive-by-wire functionality, a total additional power* consumption of 242.8 Watts (*Typical), and an overall cost of $118,189 USD, which is a significant saving compared to other commercially available systems with similar functionality. This vehicle continues to serve as our primary AV research and development platform.

33 ADVANCED PROPULSION SYSTEMS↗

NASA Science Technology Development Programs for Ocean Worlds Exploration

The exploration of ocean worlds such as Europa and Enceladus supports NASA’s goal to search for life and potentially habitable regions elsewhere in the universe, and further promises to help us understand the origins, evolution, and limits of life on Earth. Over the past several years, NASA’s Planetary Science Division has funded several technology development programs to enable future surface and subsurface missions to ocean worlds. These programs include Instrument Concepts for Europa Exploration (ICEE), Concepts for Ocean Worlds Life Detection Technology (COLDTech), Scientific Exploration Subsurface Access Mechanism for Europa (SESAME), Applied Information Systems Research: Autonomous Robotics Research for Ocean Worlds (AISR:ARROW), and Astrodynamics in Support of Icy Worlds Missions. Tasks selected under these programs include the development of scientific instruments including seismometers, imagers, spectrometers, and organic analyzers, and platform technologies including drills, melt probes, through-ice communications, radiation-hard electronics, and autonomy for surface operations. This paper describes the objectives of each of these programs and provides a summary of the work that has been completed or is underway in each.

technology↗

NASA Science Technology Development Programs for Ocean Worlds Exploration

The exploration of icy satellites such as Europa and Enceladus supports NASA’s goal to search for life and potentially habitable regions elsewhere in the universe, and further promises to help us understand the origins, evolution, and limits of life on Earth. Over the past several years, NASA’s Planetary Science Division has funded several technology development programs to enable future surface and subsurface missions to ocean worlds. These programs include Instrument Concepts for Europa Exploration (ICEE), Concepts for Ocean Worlds Life Detection Technology (COLDTech), Scientific Exploration Subsurface Access Mechanism for Europa (SESAME), Applied Information Systems Research: Autonomous Robotics Research for Ocean Worlds (AISR:ARROW), and Astrodynamics in Support of Icy Worlds Missions. Tasks selected under these programs include the development of scientific instruments including seismometers, imagers, spectrometers, and organic analyzers, and also platform technologies including drills, melt probes, through-ice communications, radiation-hard electronics, and autonomy for surface operations. This paper describes the objectives of each of these programs and provides a summary of the work that has been completed or is underway in each.

science instruments↗

NASA Science Technology Development Programs for Ocean Worlds Exploration

The exploration of ocean worlds such as Europa and Enceladus supports NASA’s goal to search for life and potentially habitable regions elsewhere in the universe, and further promises to help us understand the origins, evolution, and limits of life on Earth. Over the past several years, NASA’s Planetary Science Division has funded several technology development programs to enable future surface and subsurface missions to ocean worlds. These programs include Instrument Concepts for Europa Exploration (ICEE), Concepts for Ocean Worlds Life Detection Technology (COLDTech), Scientific Exploration Subsurface Access Mechanism for Europa (SESAME), Applied Information Systems Research: Autonomous Robotics Research for Ocean Worlds (AISR:ARROW), and Astrodynamics in Support of Icy Worlds Missions. Tasks selected under these programs include the development of scientific instruments including seismometers, imagers, spectrometers, and organic analyzers, and platform technologies including drills, melt probes, through-ice communications, radiation-hard electronics, and autonomy for surface operations. This paper describes the objectives of each of these programs and provides a summary of the work that has been completed or is underway in each.

Nayar, Hari D↗

Semi-Automatic Geographic Information System Framework for Creating Photo-Realistic Digital Twin Cities to Support Autonomous Driving Research

Digital twin cities are frequently used in vehicle and traffic simulations to render realistic on-road driving scenarios under various traffic and environmental conditions. These digital twins provide a high-fidelity replica of the physical world (e.g., buildings, roads, infrastructures, traffic) to create three-dimensional (3D) virtual-physical environments to support various emerging vehicle and transportation technologies such as connected and automated vehicles. These virtual environments provide a cost-effective digital proving ground to evaluate, validate, and test emerging technologies that include control algorithms, localization, perception, and sensors. Replicating a real-world traffic scenario in a digital twin using a traditional 3D modeling approach is a time-consuming and labor-intensive effort. Here this paper presents a semi-automated spatial framework to construct realistic 3D digital twin cities to support autonomous driving research using readily available geographic information system (GIS) data and 3D prefabricated (prefab) models. We start with a comprehensive review of geospatial data sources of essential digital entities required in a 3D digital twin city and present an integrated GIS-3D modeling pipeline using customized QGIS/GDAL and Blender scripting in Python. The pipeline outputs are realistic 3D digital twin cities compatible with common vehicle simulation software, such as CARLA and IPG CarMaker. The paper closes with a showcase to demonstrate the quality and usability of a digital twin city created to replicate the Shallowford Road corridor in Chattanooga in both Unity and Unreal engine-based virtual environment. The generated digital twin city can be applied to a hardware-in-the-loop simulation environment with an actual testing vehicle to facilitate autonomous driving research.

33 ADVANCED PROPULSION SYSTEMS↗

Generic Urban Air Mobility Simulation

This research presents a simulation framework for autonomous research for a UAM vehicle using the NASA Revolutionary Vertical Lift Technology Lift+Cruise concept vehicle. Our research results were produced using the open-source, six degree of freedom, rigid-body, nonlinear generic urban air mobility (GUAM) simulation. The intent of this paper is to demonstrate the GUAM simulation and a series of Challenge Problems that our researchers have posed to the broader autonomous vehicle research community. Our team has developed the GUAM simulation for the express purpose of providing a high-fidelity transition vehicle dynamics model to foster collaboration and algorithm performance comparison across research teams. In this paper, we demonstrate some of the autonomous flight research challenges and some of our current approaches to tackling basic autonomous flight tasks (e.g., trajectory following, stationary and moving obstacle avoidance). Additionally, we propose some flight metrics to assess autonomous algorithm performance while accomplishing these basic autonomous tasks.

autonomous flight↗

Designing a Distributed Web-based Simulation Environment for Enabling Autonomous Systems Research

In the continued pursuit of creating a future with robust Urban Air Mobility (UAM) operations defined as safe and efficient air traffic operations in metropolitan environments for both piloted and autonomous systems, development of the concepts, technologies, and procedures to establish this UAM ecosystem remains an active area of research. In particular, as autonomous systems continue to grow in both complexity and use throughout UAM concepts the need for simulation environments to both test individual components and systems and to study the complex interactions between them is paramount. In this paper we address design considerations, technologies, and challenges of adapting native simulation environment application concepts to an interactive and distributed web-based framework. The proposed web-based design allows for easier and wider access for developing, testing, integrating, and studying emergent behaviors of complex autonomous systems interaction. We demonstrate the utility of the proposed approach by showing multi-agent interaction and emergent behavior in two scenarios: (1) autonomous urban air mobility vehicles flying in a convoy and (2) interaction of a convoy with a search and rescue operation.

Benjamin N Kelley↗

Development and Testing of the Phase 0 Autonomous Formation Flight Research System

The Autonomous Formation Flight (AFF) project was initiated in 1995 to demonstrate at least 10-percent drag reduction by positioning a trailing aircraft in the wingtip vortex of a leading aircraft. If successful, this technology would provide increased fuel savings, reduced emissions, and extended flight duration for fleet aircraft flying in formation. To demonstrate this technology, the AFF project at NASA Dryden Flight Research Center developed a system architecture incorporating two F-18 aircraft flying in leading-trailing formation. The system architecture has been designed to allow the trailing aircraft to maintain station-keeping position relative to the leading aircraft within +/-10 ft. Development of this architecture would be directed at the design and development of a computing system to feed surface position commands into the flight control computers, thereby controlling the longitudinal and lateral position of the trailing aircraft. In addition, modification to the instrumentation systems of both aircraft, pilot displays, and a means of broadcasting the leading aircraft inertial and global positioning system-based positional data to the trailing aircraft would be needed. This presentation focuses on the design and testing of the AFF Phase 0 research system.

Petersen, Shane↗

Improving Self-Driving Labs: Quantifying System-Level Experiment Repeatability and Broadening Instrument-Level Compatibility

Modular Autonomous Research System (MARS) is a self-driving laboratory (SDL) which performs wet-lab science with peptide-lanthanide combinations in an automated and, ultimately, an autonomous manner to aid in soil analysis for domestic lithium mining. Autonomous experimentation involves automated experimentation, experiment planning, and active learning. MARS consists of a 6-axis robotic arm (UR5e) on a linear rail, pipette robots (Opentrons 2), and microplate readers. These components transport, operate on, and collect data with chemical solutions in standard labware. For effective autonomy, MARS must perform system-level labware operations repeatably, plan experiments autonomously, and be portable between research-domains. Repeatability is evaluated by labware placement precision, such that future operations can properly locate labware, as well as the elapsed time, so that low variance mean estimates of experiment duration can inform high-level researcher decision making. Autonomous experiment planning is the next step to decouple experimentation from human management; however, there is a conflict between the ideal system-level experiment goals and the constraints imposed by instruments’ limitations. Sub-domain portability is a long-term goal to extend MARS’ research beyond the chemistry of peptide-lanthanide binding to other sub-domains without having to invest significant overhead to system retrofitting. To address these goals, we manually trained the robotic arm labware placement and modelled statistical failurerate and uncertainty Additionally, we benchmarked the duration and variance of each experiment sub-operation as a heuristic for research decision making. Next, we use a parameterized geometric program (PGP) approach to design experiments that optimize system-level objectives and satisfy instrument-level constraints. Lastly, we proposed a Python framework to maximize MARS’ extensibility to other scientific sub-domains through a JSON-based experiment specification.

36 MATERIALS SCIENCE↗

Research on an autonomous vision-guided helicopter

Integration of computer vision with on-board sensors to autonomously fly helicopters was researched. The key components developed were custom designed vision processing hardware and an indoor testbed. The custom designed hardware provided flexible integration of on-board sensors with real-time image processing resulting in a significant improvement in vision-based state estimation. The indoor testbed provided convenient calibrated experimentation in constructing real autonomous systems.

Amidi, Omead↗

An MBSE Approach for Developing an Autonomous Rover Platform

The proliferation of increasingly autonomous systems calls for new ways to address how safety is assured. As these systems become more advanced and complex, it becomes more important to model and prototype autonomous functions at the systems level and the functions that assure they are operating safely and as expected. To that effect, researchers at the National Aeronautics and Space Administration (NASA) 's Robust Software Engineering (RSE) group are working on prototyping a Research Autonomous Vehicle, commonly referred to as R-RAV. The R-RAV is an autonomous rover platform designed to act as a case study for assured autonomy research. Moreover, an overarching goal is for the R-RAV to serve as a training ground for other mission projects. In this paper, we will detail how we have used a Model-Based Systems Engineering (MBSE) approach to model a prototype of the R-RAV and test and verify its different functionalities.

MBSE↗

TETA Autoresearch [SWR-26-089]

TETA Autoresearch is a template repository based on github.com/karpathy/autoresearch for AI-assisted research science in the TETA group in the Center for Integrated Mobility Sciences (CIMS) center at the National Laboratory of the Rockies. This software is a template for running autonomous research experiments that iteratively improve an ML model for a single optimization objective. Two execution modes share one harness: LLM mode - an agent (e.g. Claude Code) edits a scaffold train.py one change at a time, tagging each experiment, logging reasoning, and pushing results. Defined by program.md. Optimizer mode - an Optuna-backed driver (TPE / CMA-ES / Random) iterates over a domain-defined search space. Defined by optimizers/. RouteE (vehicle energy prediction) is the reference domain under domains/routee/. Adding a new domain is mechanical - see EXTENDING.md.

Reinicke, Nicholas [National Laboratory of the Roc↗

Autonomous support for microorganism research in space

A preliminary design for performing on orbit, autonomous research on microorganisms and cultured cells/tissues is presented. An understanding of gravity and its effects on cells is crucial for space exploration as well as for terrestrial applications. The payload is designed to be compatible with the Commercial Experiment Transporter (COMET) launch vehicle, an orbiter middeck locker interface, and with Space Station Freedom. Uplink/downlink capabilities and sample return through controlled reentry are available for all carriers. Autonomous testing activities are preprogrammed with in-flight reprogrammability. Sensors for monitoring temperature, pH, light, gravity levels, vibrations, and radiation are provided for environmental regulation and experimental data collection. Additional experimental data acquisition includes optical density measurement, microscopy, video, and film photography. On-board full data storage capabilities are provided. A fluid transfer mechanism is utilized for inoculation, sampling, and nutrient replenishment of experiment cultures. In addition to payload design, representative experiments were developed to ensure scientific objectives remained compatible with hardware capabilities. The project is defined to provide biological data pertinent to extended duration crewed space flight including crew health issues and development of a Controlled Ecological Life Support System (CELSS). In addition, opportunities are opened for investigations leading to commercial applications of space, such as pharmaceutical development, modeling of terrestrial diseases, and material processing.

Fleet, Mary L.↗

Modular Autonomous Experimentation for Biological Applications (Full Report)

The Modular Autonomous Research System (MARS) was developed to address the pressing need for faster, more reliable, and more adaptable scientific discovery. Traditional experimentation is limited by manual labor, long cycle times, and fragmented data streams, which constrain the ability to explore complex chemical and materials design spaces. To overcome these limitations, we created an integrated, modular platform that combines laboratory robotics, diverse measurement instruments, and a central data infrastructure with artificial intelligence–driven decision-making. The system links liquid handling robots, robotic arms, and optical plate readers into a closed loop where experiments are executed automatically, data is analyzed in real time, and subsequent experimental conditions are adaptively chosen to maximize information gain. Over the course of the project, MARS was validated on two primary test cases—spectroscopic metal–ligand binding assays and peptide-directed mineralization—which highlighted the system’s ability to handle uncertainty and variability in experimental measurements. To further demonstrate modularity and extensibility, we also established additional testbeds in electrochemistry for catalyst discovery and electrolyte formulation for advanced batteries. The results show that MARS can reliably conduct autonomous campaigns with minimal human intervention, adapt to distinct scientific domains, and provide a scalable model for future self-driving laboratories. This work establishes new capabilities for modular, uncertainty-aware automation and directly supports the need for advanced, data-driven research platforms capable of accelerating discovery across a wide range of scientific and national security missions.

59 BASIC BIOLOGICAL SCIENCES↗