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Stephen Gerdts

Publications and source records attributed to Stephen Gerdts.

7 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS2022

Dusty Environment Classification and Testing: Dust Mitigation Slide Wipes & Tapes

During the Apollo missions many mechanisms, equipment, and surfaces were contaminated by lunar dust and often negatively affected. The methods used to clear these devices of dust proved ineffective, which led to premature failure in some cases. Systems being designed for upcoming missions to the Moon will need to address the performance degradation risk of dust contamination. Surfaces at risk include thermal control surfaces, solar cells, camera and sensor optics, seals, metal joints and tools, and space suit assemblies. To improve state of the art dust mitigation approaches, the dust mitigation team at NASA Glenn Research Center (GRC) explored the effects imposed on substrates during cleaning activities in the presence of lunar dust. The Uniform Dust Deposition System (UDDS) was used to conduct a study of various cleaning techniques on different substrates. Test substrates and cleaning media were selected to represent a wide range of structural and functional materials. Substrates included orthofabric, thermal radiator coating, aluminum, quartz glass, silicone rubber, aluminized Mylar, and FEP. Cleaning materials included cloth wipes, tapes, a brush, and a pliable cleaner concept. Cleaning material / substrate pairs were rated on cleaning efficiency, substrate damage, cleaning material longevity, and ease of use. The best performing cleaning method varied based on application.

lunar simulant↗
NASA NTRS2022

Characterization of Infrared Optical Motion Tracking System in NASA's Simulated Lunar Operations (SLOPE) Laboratory

This work characterizes the accuracy of a 16 camera OptiTrack motion tracking system installed in NASA Glenn Research Center's Simulated Lunar Operations (SLOPE) laboratory. The position of a rigid body mounted on a motorized linear stage is compared to its position reported by the motion tracking system as it travels through the facility's 777m$^3$ capture volume of interest. Experiments show that the mean error reported by the motion tracking system for the aggregate capture volume is in-line with independent measurements collected using the motion stage. Error within regions of the capture volume exceed the mean error reported by the motion tracking system, likely due to occlusion, and suggests that additional cameras should be used to increase measurement accuracy in these regions. Overall, results show that error values reported by the motion tracking system are representative of the measurement error in a collected data set and validates the system's use for characterizing the mobility and tractive performance of robots, rovers, and other vehicles for planetary exploration.

Motion capture↗
NASA NTRS2022

Lunar Simulant Deposition Technique for Dust Tolerance Studies

A renewed interest in lunar exploration has spawned an array of development efforts for lunar surface assets. These systems depend on the reliable operation of mechanisms and components that may be susceptible to performance degradations or failure due to dust. The Uniform Dust Deposition System was developed at the NASA Glenn Research Center to provide repeatable, uniform, and automated deposition of simulants on surfaces of interest for dust mitigation testing. The system is capable of depositing simulants on test articles up to 60 cm in diameter and 15 cm high in a dry air environment with less than 1 percent relative humidity while keeping users safe from aerosolized dust. The automation of the system allows for high testing throughput while not sacrificing test quality and allows the user to reduce data in parallel. The additional development of a simulant preparation technique complements the repeatability of the deposition physics during testing. The system includes an imaging subsystem that leverages the power of machine learning to count simulant particles and measure their size, thereby allowing for accurate predictions of surface deposition densities (coefficient of determination R^(2) = 0.93) from images alone. The coverage of dust on a surface was shown to be uniform (coefficient of variation CV < 0.11), allowing developers to accurately evaluate the performance of their technology with a prescribed amount of lunar simulant, information that can be used to develop and refine models. The accuracy of the system is currently less than desired for a single deposition run, with a standard deviation (SD) ranging from 18 to 24 mg, or 0.839 to 1.184 mg/sq. cm , for a 5-cm-diameter area. However, the accuracy can be improved by performing multiple deposition runs to build dust to a desired level. Testing has shown that a SD of 0.2 to 0.6 mg, or 0.076 to 0.227 mg/sq. cm, can be achieved for a 5-cm-diameter area using this technique.

Stephen Gerdts↗
NASA NTRSDate not supplied

Lunar Rover Optimization Platform for Wheel Traction Studies

Robotic mobility systems expand the reach of future scientific and exploration missions to celestial bodies. Understanding the traction performance of these systems is necessary knowledge that informs mission-level requirements, such as power budgets and navigation envelopes. This paper covers the design, development, and verification of the four wheeled Lunar Rover Optimization Platform (LROP). This mass optimized platform is targeted to emulate future medium class rovers weighing up to 90 kg. The LROP has the ability to conduct various wheel design experiments such as obstacle traversal, slope ascent, and drawbar pull over a wheel loading range of 4.5 to 22.7 kg. The platform also has the ability to shift its center of gravity (CG) laterally and longitudinally to explore the CG shift effects on mobility performance. This knowledge is valuable for future rover designers exploring different payload packaging solutions. In this paper results from obstacle traversal test with varying angle of attack (AOA) and longitudinal CG position are reported along with results from slope ascent testing which proved-out the LROPs capabilities.

Stephen Gerdts↗
NASA NTRSDate not supplied

Uniform Dust Deposition System for Dust Tolerance Studies

Future missions to the Moon will require mechanisms and materials to effectively and reliably operate in the presences of lunar regolith. One of the challenges of developing such technologies is terrestrial testing with lunar dust simulants. Dust has a stochastic nature of depositing and it can be difficult to accurately apply it to surfaces of interest. Deposition density, particles size distribution, and percent coverage are all factors that affect the quality of dust mitigation testing. Therefore, to enable such testing the dust mitigation and seals teams at NASA Glenn Research Center (GRC) have developed a system that can uniformly and repeatably deposit lunar simulants on a range of surfaces. Testing of the Dust Deposition System (DDS) and an associatedsimulant preparation methodology have quantified the levels of uniformity and precision for this system. Furthermore, the deposition system has been paired with automated micrograph capturing and machine learning image analysis to correlate the images of dust on a surface to deposition density (in g/cm2). This correlation alleviates the need for tested samples to be accurately weighed with milligram precision and may be a useful tool for in-situ contamination evaluation on the Moon. This paper covers the design and validation testing for the DDS.

Stephen Gerdts↗
NASA NTRSDate not supplied

Uniform Dust Deposition System for Dust Tolerance Studies

Future missions to the Moon will require mechanisms and materials to effectively and reliably operate in the presences of lunar regolith. One of the challenges of developing such technologies is terrestrial testing with lunar dust simulants. Dust has a stochastic nature of depositing and it can be difficult to accurately apply it to surfaces of interest. Deposition density, particles size distribution, and percent coverage are all factors that affect the quality of dust mitigation testing. Therefore, to enable such testing the dust mitigation and seals teams at NASA Glenn Research Center (GRC) have developed a system that can uniformly and repeatably deposit lunar simulants on a range of surfaces. Testing of the Dust Deposition System (DDS) and an associated simulant preparation methodology have quantified the levels of uniformity and precision for this system. Furthermore, the deposition system has been paired with automated micrograph capturing and machine learning image analysis to correlate the images of dust on a surface to deposition density (in g/cm2). This correlation alleviates the need for tested samples to be accurately weighed with milligram precision and may be a useful tool for in-situ contamination evaluation on the Moon. This paper covers the design and validation testing for the DDS.

Dust↗