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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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All sourcesNASA NTRSDOE OSTI
NASA NTRSDate not supplied

Towards Autonomous Lunar Resource Excavation via Deep Reinforcement Learning

To support sustainable infrastructure on the Moon, NASA needs to leverage lunar resources for in-situ processing and construction. NASA’s Regolith Advanced Surface Systems Operations Robot (RASSOR) is principally designed to mine and deliver regolith for these tasks. To reliably perform these operations on the lunar surface, RASSOR's sensors and control systems need to be robust and maximize information extracted from a reduced sensor payload. Herein, we present our findings from the Intelligent Capabilities Enhanced RASSOR project. We created reduced-order simulation environments in which we applied reinforcement learning algorithms to learn autonomous trenching controllers and produced state estimation architectures. We developed two simulations: a 2D excavation simulation used to facilitate parameter selection, and a 3D simulation developed using a game physics engine to simulate simplified soil interactions and incorporate robotic agents parameterized by dynamic models. Within these simulations, we learned autonomous excavation routines that exceed excavation efficiency measures as compared against RASSOR's existing control and teleoperation-based methods.

RASSOR↗
NASA NTRSDate not supplied

ISRU Pilot Excavator - Development of Autonomous Excavation Algorithms

The ISRU Pilot Excavator (IPEx) is a Space Technology Mission Directorate (STMD) Game Changing Development (GCD) project to develop a robotic excavator to demonstrate excavation of up to 10 metric tons of lunar regolith. IPEx is based on the Regolith Advanced Surface Systems Operations Robot (RASSOR) excavator developed at NASA Kennedy Space Center (KSC) and utilizes a counter rotating bucket drum concept to balance excavation forces for use on reduced gravity planetary bodies. To take advantage of the counter rotating bucket drum mechanism, work is being done to develop new autonomous excavation strategies and algorithms. Referred to as “Auto-dig”, these algorithms will allow IPEx to excavate, drive, and deliver its target mass of 10 metric tons of lunar regolith during an 11-day mission semi-autonomously. Due to bandwidth and latency constraints teleoperation will be kept to a minimum, with operators periodically confirming and verifying the excavator’s high-level tasks and operations. While the work to develop optimized autodig solutions is ongoing at KSC, early tests have yielded interesting results that have led to the discovery of additional risks that need to be mitigated in autonomous excavation. Testing has also encouraged the development of new software and visualization tools that provide real-time insight into excavation loads during operation, allowing faster development and helping build better intuition to the excavation process. These tools will help in the pursuit to develop fully optimized digging algorithms that are robust enough to handle hazards such as rocks or irregular terrain.

B. C. Buckles↗
NASA NTRSDate not supplied

ISRU Pilot Excavator (IPEx) Technology Readiness Level 5 Design Overview

This paper details the mechanical and mechatronic design of the Technology Readiness Level (TRL)-5 In-Situ Resource Utilization (ISRU) Pilot Excavator (IPEx). IPEx is a robotic excavator designed for a technology demonstration of regolith mining in the lunar south -pole region. The novel design uses pairs of counter-acting excavation tools called bucket drums, that dig at the same time in opposing directions to reduce the reaction force needed, thereby enabling mining with a small, low-mass, robotic system. IPEx builds on the prior work of the Regolith Advanced Surface Systems Operations Robot (RASSOR), which is the TRL-4 implementation of this concept. The TRL-5 IPEx subsystems that are discussed in this paper include: Regolith Delivery Subsystem (RDS), Mobility Subsystem (MS), Cameras and Dust Mitigation Subsystem (CDMS), and Thermal Control Subsystem (TCS). Each subsystem is described in detail with rationale for design selections. Dust tolerance is a key feature for IPEx and this paper details a thermal control system with an actuated radiator cover and phase change material as well as camera modules with removable electrodynamic dust shields (EDS). Additional components such as actuators, wheels, and bucket drums are discussed in detail. Due to their complexity, the avionics and software subsystems will be discussed in a separate publication.

RASSOR↗
NASA NTRS1991

Thermal-structural panel buckling tests

A titanium-matrix-composite (TMC) hat-stiffened panel of 61 cm sq area and 3.175 cm thick was nondestructively tested to 649 C to examine its buckling characteristics. Compressive loads were applied to the panel in a 978.6 kN uniaxial load frame system. High-temperature testing was performed using quartz lamp heating. A single-strain-age force/stiffness buckling prediction technique was developed to predict panel buckling loads. For the monolithic panel, these test predictions correlated within 10 percent with a finite-element buckling analyses performed elsewhere. Comparisons between force/stiffness predictions and analyses for the TMC panel are in progress.

Thompson, Randolph C.↗
NASA NTRS1994

Probabilistic progressive buckling of trusses

A three-bay, space, cantilever truss is probabilistically evaluated to describe progressive buckling and truss collapse in view of the numerous uncertainties associated with the structural, material, and load variables that describe the truss. Initially, the truss is deterministically analyzed for member forces, and members in which the axial force exceeds the Euler buckling load are identified. These members are then discretized with several intermediate nodes, and a probabilistic buckling analysis is performed on the truss to obtain its probabilistic buckling loads and the respective mode shapes. Furthermore, sensitivities associated with the uncertainties in the primitive variables are investigated, margin of safety values for the truss are determined, and truss end node displacements are noted. These steps are repeated by sequentially removing buckled members until onset of truss collapse is reached. Results show that this procedure yields an optimum truss configuration for a given loading and for a specified reliability.

PROBABILISTIC BUCKLING ANALYSI↗
NASA NTRS1975

Preferential concentration of certain elements in smaller aerosols emitted from aircraft engines

Aerosols from aircraft engines were collected with an eight-stage cascade sampler for a period of 24 h. The aerosol samples from each stage were analyzed for their elemental composition using the proton-induced X-ray emission (PIXE) technique. Seventeen elements (Si, P, S, Cl, K, Ca, Ti, V, Fe, Ni, Cu, Zn, Br, Sr, Nb, Sn, and Pb) were positively identified and quantitated at each stage. Six elements (S, Ca, Fe, Zn, Sn, and Pb) showed a fractional concentration increase with decreasing aerosol size. Similar, but less well-defined, trends were also observed for V and Ni. Silicon and chlorine, on the other hand, showed an opposite trend. Neutron-activation analysis of bulk aerosol samples collected every 2 h over the same period showed a correlation between concentration of Si, Ca, V, Ti, Zn, Br, and Sn and the density of air traffic at the airport. Analysis of the aviation-fuel samples by PIXE indicates that major fractions of Pb, Sn, Br, Zn, Ni, Fe, V, Ca, and S observed in these aerosol studies come from the aircraft engine exhaust.

Jolly, R. K.↗
NASA NTRS1990

Ocean feature recognition using genetic algorithms with fuzzy fitness functions (GA/F3)

A model for genetic algorithms with semantic nets is derived for which the relationships between concepts is depicted as a semantic net. An organism represents the manner in which objects in a scene are attached to concepts in the net. Predicates between object pairs are continuous valued truth functions in the form of an inverse exponential function (e sub beta lxl). 1:n relationships are combined via the fuzzy OR (Max (...)). Finally, predicates between pairs of concepts are resolved by taking the average of the combined predicate values of the objects attached to the concept at the tail of the arc representing the predicate in the semantic net. The method is illustrated by applying it to the identification of oceanic features in the North Atlantic.

Ankenbrandt, C. A.↗
NASA NTRS2014

Cold Water Vapor in the Barnard 5 Molecular Cloud

After more than 30 yr of investigations, the nature of gas-grain interactions at low temperatures remains an unresolved issue in astrochemistry. Water ice is the dominant ice found in cold molecular clouds; however, there is only one region where cold ((is) approximately 10 K) water vapor has been detected-L1544. This study aims to shed light on ice desorption mechanisms under cold cloud conditions by expanding the sample. The clumpy distribution of methanol in dark clouds testifies to transient desorption processes at work-likely to also disrupt water ice mantles. Therefore, the Herschel HIFI instrument was used to search for cold water in a small sample of prominent methanol emission peaks. We report detections of the ground-state transition of o-H2O (J = 110-101) at 556.9360 GHz toward two positions in the cold molecular cloud, Barnard 5. The relative abundances of methanol and water gas support a desorption mechanism which disrupts the outer ice mantle layers, rather than causing complete mantle removal.

ISM: molecules↗
NASA NTRS2018

Zero Launch Mass Three Dimensional Print Head

NASA's strategic goal is to put humans on Mars in the 2030's. The NASA Human Spaceflight Architecture Team (HAT) and NASA Mars Design Reference Architecture (DRA) 5.0 has determined that in-situ resource utilization (ISRU) is an essential technology to accomplish this mission. Additive construction technology using in-situ materials from planetary surfaces will reduce launch mass, allow structures to be three dimensionally (3D) printed on demand, and will allow building designs to be transmitted digitally from Earth and printed in space. This will ultimately lead to elimination of reliance on structural materials launched from Earth (zero launch mass of construction consumables). The zero launch mass (ZLM) 3D print head project addressed this need by developing a system that 3D prints using a mixture of in-situ regolith and polymer as feedstock, determining the optimum mixture ratio and regolith particle size distribution, developing software to convert g-code into motion instructions for a FANUC robotic arm, printing test samples, performing materials testing, and printing a reduced scale habitable structure concept. This paper will focus on the ZLM 3D Print Head design, materials selection, software development, and lessons learned from operating the system in the NASA KSC Swamp Works Granular Mechanics & Regolith Operations (GMRO) Laboratory.

3D print↗
NASA NTRS2018

Zero Launch Mass Three Dimensional Print Head

NASA's strategic goal is to put humans on Mars in the 2030s. The NASA Human Spaceflight Architecture Team (HAT) and NASA Mars Design Reference Architecture (DRA) 5.0 has determined that in-situ resource utilization (ISRU) is an essential technology to accomplish this mission. Additive construction technology using in-situ materials from planetary surfaces will reduce launch mass, allow structures to be three dimensionally (3D) printed on demand, and will allow building designs to be transmitted digitally from Earth and printed in space. This will ultimately lead to elimination of reliance on structural materials launched from Earth (zero launch mass of construction consumables). The zero launch mass (ZLM) 3D print head project addressed this need by developing a system that 3D prints using a mixture of in-situ regolith and polymer as feedstock, determining the optimum mixture ratio and regolith particle size distribution, developing software to convert g-code into motion instructions for a FANUC robotic arm, printing test samples, performing materials testing, and printing a reduced scale habitable structure concept. This paper will focus on the ZLM 3D Print Head design, materials selection, software development, and lessons learned from operating the system in the NASA KSC Swamp Works Granular Mechanics & Regolith Operations (GMRO) Laboratory.

Regolith↗
NASA NTRSDate not supplied

Machine Learning for Dynamic Test Sensor Placement

There are multiple different algorithms to perform modal test sensor placement optimization: effective independence, residual kinetic energy, iterative Guyan reduction, genetic algorithms, or a brute-force methodology. However, any of these methods may be computationally expensive, especially for structural models with a large number of degrees of freedom. Given the high-cost and the need to optimize the solution, modal sensor placement is a great application for machine learning (ML) algorithms. In this paper, we will apply ML algorithms to determine the optimal sensor locations for simple and complex structures. We will also discuss the benefits and drawbacks of using machine learning over other sensor placement algorithms.

Kelsey Buckles↗