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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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345 records · Page 20

Development Unit for In-Space Pneumatic Helium Transfer Compressor

High-pressure gaseous helium (GHe) plays a critical role in spacecraft propulsion due to its near exclusive use for pressurization of propellant tanks. Several different designs for helium compressor technologies have been developed for use on Earth; however, significant design changes are required to meet the power, thermal/heat dissipation, vacuum, vibration/shock, size, mass, and efficiency requirements needed for space and launch environments. Currently, no capability exists for mass efficient on-orbit GHe (or xenon) transfer, nor has it ever been attempted. This effort proposed several challenging requirements for the vendor to develop a one-of-a-kind pneumatic compressor prototype. In order to develop a compressor prototype at a TRL 4, a partnership with Air Squared, Inc. was established. This CIF project concluded with the receipt of a prototype along with a proposed design for a flight unit; however, it will not be built due to funding limitations. The vendor had moderate success with initial testing of the prototype at lower pressures (with shimming configured for low pressure). There were delays with testing since the unit was built for higher pressures and the low pressure shimming was challenging to implement. It was found that operation of the compressor at lower pressures caused increased friction on the motor shaft which resulted in the unit drawing more power (current). This was initially thought to be a motor or controller defect. Subsequent high pressure testing at KSC showed that the friction was reduced for the optimal design point (with a high pressure shimming configuration) and the motor (and controller) performed nominally. Following the vendor testing, the unit was tuned/shimmed for a nominal inlet pressure and shipped to KSC for high pressure testing using the custom-designed setup in the Vehicle Assembly Building. The unit performed well, showing the capability to achieve over higher pressure of compression. The pressure differential could likely increase, however, the maximum output of the power supply used for testing was reached, limiting the compressor motor’s capability. Following the GN2 testing, the test setup was converted to GHe with at high pressure. It was shown that although the unit was unable to achieve similar high pressure differentials due to reverse leakage of the GHe through the scroll tip seals, it did achieve the desired GHe compression. This may still be useful for some applications, however, for the purpose of on-orbit GHe transfer, the single stage design would need to be changed to include multiple stages to achieve the compression goals initially proposed by the project.

Brian Nufer↗

Hardware Autonomy for Space Infrastructure

NASA prioritizes autonomous systems development with the expectation that it will continue to drive significant improvements in human and science exploration capability. Crew operations benefit from a spectrum of machine assistance to complete replacement of dangerous or highly repetitive tasks. Many science operations have a teleoperation component, and similarly benefit from a range of autonomy implementations that make long distance applications feasible. As we consider longer duration deep space missions, we also consider higher levels of autonomy in order meet emergent safety, maintenance, and logistics needs. One of the challenges within this scope is installation and maintenance of infrastructure, such as large scale instrumentation and communications equipment, crew habitats, and operational facilities. We describe how a programmable meta-material architecture may shift the paradigm of how we design, build, and operate future space infrastructure and assets. A primary objective of this strategy is to free the design space from launch vehicle constraints and fundamentally shift how a mission is designed and conducted. This integrates advances in materials (mechanical meta-materials), manufacturing (cooperative mobile robotics), and autonomy (multi-agent planning algorithms). Engineering systems that utilize a modular and reconfiguration building block approach, such as digital communication and computation systems, currently lead in terms of size and complexity scalability. NASA is extending the benefits and flexibility of digital systems to hardware systems, to optimize materials life-cycle management and expand our space exploration mission capabilities to meet long duration and deep space infrastructure needs, in accordance with long term NASA goals of "in-space reliance" and "mass-less exploration."

In space assembly↗

Modeling Deformable Linear Objects for Autonomous Robotic Outfitting of Lunar Surface Systems

This paper presents structural models of deformable linear objects (DLOs). DLOs are a subclass of deformable objects that encompasses common outfitting elements such as cables and ropes. Models are validated through hardware experiments, and integration in a robotic autonomy architecture for space environments is discussed. A persistent human presence on the lunar surface is one of the next major milestones in space exploration. This requires the development of robust extraplanetary construction technologies including structures and materials modeling and robotic systems. Previous robotic construction technology development has primarily focused on structural assembly, with significantly less focus on robotically performed outfitting tasks to instantiate subsystems providing power, data, life support, etc. These tasks involve manipulation of highly flexible elements, which are difficult to model, such as cable harnesses, ropes, and hoses. Robotic manipulation of DLOs, especially cable harnesses, is an active area of research as cable harnesses are essential for providing power and data to space assets. DLO models that can be used for robot manipulator trajectory generation are necessary for autonomous operation of lunar infrastructure. There are many proposed methods for modeling DLOs, and they primarily fall into three types: 1) discrete model-based, 2) continuum model-based, and 3) Neural Network-based. These types each have pros and cons, and the tradeoff between model accuracy and computational speed informs which type should be used. An understanding of this trade-off is imperative for real-time control of autonomous systems. High computational requirements reduce the speed of the model, making real-time control difficult, while accuracy is critical to preventing collisions. Discrete models, such as a mass-spring multibody representation, require relatively few calculations, and accuracy is directly tied to the step size of the discretization. Continuum models, such as a B-spline representation or a Cosserat rod model (a mix of continuous and discrete), are more informed of the structural properties of the cable and are much more accurate than a rigid body mass-spring model, but at significant computational cost. A Neural Network approach can provide an online solution with very few computational steps, but properly generating training data can be difficult and validation for an in-space application is not trivial. This paper explores the trade-off between different modeling approaches and compares accuracy and computational speed/complexity of the three types mentioned above. Model accuracy is evaluated using a cable in a static configuration. True cable shape is obtained using a depth camera for RGB images and point-cloud segmentation. The purpose of this experiment is to evaluate the trade-offs of different approaches to the DLO modeling problem. Understanding the tradeoffs between different cable modeling techniques paves the way for developing robotic control and planning architectures necessary for real-time manipulation of DLOs for lunar infrastructure outfitting. Real-time control is required for robotic systems to be able to actively manipulate a cable in a harsh environment where model and sensor errors compound, and environmental conditions can cause significant disturbances. Cable routing must be performed in areas with high density of objects/obstacles: through truss structures, near solar panels or mirror arrays, next to bundles of electrical equipment. Understanding the best way to plan and manipulate a cable without disrupting the environment or damaging the cable is imperative to robotic outfitting operations on the lunar surface.

Amy M Quartaro↗