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NASA NTRS2019

The unexpected surface of asteroid (101955) Bennu

NASA’S Origins, Spectral Interpretation, Resource Identification and Security-Regolith Explorer (OSIRIS-REx) spacecraft recently arrived at the near-Earth asteroid (101955) Bennu, a primitive body that represents the objects that may have brought prebiotic molecules and volatiles such as water to Earth1. Bennu is a low-albedo B-type asteroid2 that has been linked to organic-rich hydrated carbonaceous chondrites3. Such meteorites are altered by ejection from their parent body and contaminated by atmospheric entry and terrestrial microbes. Therefore, the primary mission objective is to return a sample of Bennu to Earth that is pristine—that is, not affected by these processes4. The OSIRIS-REx spacecraft carries a sophisticated suite of instruments to characterize Bennu’s global properties, support the selection of a sampling site and document that site at a sub-centimetre scale5,6,7,8,9,10,11. Here we consider early OSIRIS-REx observations of Bennu to understand how the asteroid’s properties compare to pre-encounter expectations and to assess the prospects for sample return. The bulk composition of Bennu appears to be hydrated and volatile-rich, as expected. However, in contrast to pre-encounter modelling of Bennu’s thermal inertia12 and radar polarization ratios13—which indicated a generally smooth surface covered by centimetre-scale particles—resolved imaging reveals an unexpected surficial diversity. The albedo, texture, particle size and roughness are beyond the spacecraft design specifications. On the basis of our pre-encounter knowledge, we developed a sampling strategy to target 50-metre-diameter patches of loose regolith with grain sizes smaller than two centimetres4. We observe only a small number of apparently hazard-free regions, of the order of 5 to 20 metres in extent, the sampling of which poses a substantial challenge to mission success.

D. S. Lauretta↗

NASA NTRS2009

In Situ Resource Utilization (ISRU) on the Moon: Moessbauer Spectroscopy as a Process Monitor for Oxygen Production

Essential consumables like oxygen must to be produced from materials on the lunar surface to enable a sustained, long-term presence of humans on the Moon. The Outpost Precursor for ISRU and Modular Architecture (OPTIMA) field test on Mauna Kea, Hawaii, facilitated by the Pacific International Space Center for Exploration Systems (PISCES) of the University of Hawaii at Hilo, was designed to test the implementation of three hardware concepts to extract oxygen from the lunar regolith: Precursor ISRU Lunar Oxygen Testbed (PILOT) developed by Lockheed Martin in Littleton, CO; Regolith & Environmental Science and Oxygen & Lunar Volatiles Extraction (RESOLVE) developed at the NASA Kennedy Space Center in Cape Canaveral, FL; and ROxygen developed at the NASA Johnson Space Center in Houston, TX. The three concepts differ in design, but all rely on the same general principle: hydrogen reduction of metal cations (primarily Fe2+) bonded to oxygen to metal (e.g., Fe0) with the production of water. The hydrogen source is residual hydrogen in the fuel tanks of lunar landers. Electrolysis of the water produces oxygen and hydrogen (which is recycled). We used the miniaturized M ssbauer spectrometer MIMOS II to quantify the yield of this process on the basis of the quantity of Fe0 produced. Iron M ssbauer spectroscopy identifies iron-bearing phases, determines iron oxidation states, and quantifies the distribution of iron between mineral phases and oxidation states. The oxygen yield can be calculated by quantitative measurements of the distribution of Fe among oxidation states in the regolith before and after hydrogen reduction. A M ssbauer spectrometer can also be used as a prospecting tool to select the optimum feedstock for the oxygen production plants (e.g., high total Fe content and easily reduced phases). As a demonstration, a MIMOS II backscatter spectrometer (SPESI, Germany) was mounted on the Cratos rover (NASA Glenn Research Center in Cleveland, OH), which is one of several rover concepts designed to excavate and transfer regolith to the stationary hydrogen reduction plants. Spaceflight versions of the MIMOS II are part of the instrument payloads of NASA s Mars Exploration Rovers and still operating five years after landing on the surface of the planet. MIMOS II was also selected for Phobos-Grunt, a Russian sample return mission to the martian moon Phobos scheduled to launch in 2009, and ESA s ExoMars rover, an exobiology mission scheduled to launch in 2013. An advanced version of the instrument is currently under development. A new detector system with a higher energy resolution will not only reduce the necessary measurement time considerably, but also allow the simultaneous acquisition of an X-ray fluorescence spectrum to determine the elemental composition of samples.

Morris, R.V.↗

NASA NTRS2010

Assessing the Health and Performance Risks of Carbon Dioxide Exposures

Carbon dioxide (CO2) is an anthropogenic gas that accumulates in spacecraft to much higher levels than earth-normal levels. Controlling concentrations of this gas to acceptable levels to ensure crew health and optimal performance demands major commitment of resources. NASA has many decades of experience monitoring and controlling CO2, yet we are uncertain of the levels at which subtle performance decrements develop. There is limited evidence from ground-based studies that visual disturbances can occur during brief exposures and visual changes have been noted in spaceflight crews. These changes may be due to CO2 alone or in combination with other known spaceflight factors such as increased intracranial pressure due to fluid shifts. Discerning the comparative contribution of each to performance decrements is an urgent issue if we hope to optimize astronaut performance aboard the ISS. Long-term, we must know the appropriate control levels for exploration-class missions to ensure that crewmembers can remain cooperative and productive in a highly stressful environment. Furthermore, we must know the magnitude of interindividual variability in susceptibility to the adverse effects of CO2 so that the most tolerant crewmembers can be identified. Ground-based studies have been conducted for many years to set exposure limits for submariners; however, these studies are typically limited and incompletely reported. Nonetheless, NASA, in cooperation with the National Research Council, has set exposure limits for astronauts using this limited database. These studies do not consider the interactions of spaceflight-induced fluid shifts and CO2 exposures. In an attempt to discern whether CO2 levels affect the incidence of headache and visual disturbances in astronauts we performed a retrospective study comparing average CO2 levels and the prevalence of headache and visual disturbances. Our goal is to narrow gaps in the risk profile for in-flight CO2 exposures. Such studies can provide no more than partial answers to the questions of environmental interactions, interindividual variability, and optimal control levels. Future prospective studies should involve assessment of astronaut well being using sophisticated measures during exposures to levels of CO2 in the range from 2 to 8 mmHg.

James, John T.↗

NASA NTRS2022

Development of a Loop Antenna Deployment System for TEM-Based Subsurface Mars Water Detection

The subsurface of Mars has the potential to harbor existing deposits of liquid water, which are of great interest both scientifically (in the search for life) and as resources for future astronauts living on the red planet. However, the depth to a potential subsurface aquifer may be kilometers deep, which is well beyond what current surface or orbital approaches can survey while also confirming the unique signature for liquid water. Inspired by critical technology for exploring deep aquifers on Earth, we are developing the Transient H2O Reconnaissance (TH2OR) instrument at NASA’s Jet Propulsion Laboratory (JPL). TH2OR operates on the principle of transient electromagnetics (TEM), which leverages induction and electromotive force to induce a current in a subsurface water body using a loop-shaped antenna that provides both transmit and receive functions when placed on the surface. On Mars, TEM may be even more effective given the relative dryness of the subsurface compared to a more conductive, saline, liquid, water body on Earth. However, to probe deep within the subsurface (below 5 km) a large enclosed antenna is needed – specifically, a 100-m diameter effective loop or a shape with roughly equivalent area that can transmit at low frequencies (kHz-Hz). The deployment of a large-scale structure on the surface is complicated by the fact that the transmit wire must be both lightweight and robust to contact with the surface. Further, TH2OR may be delivered to the surface by a non-mobile vehicle, so it is desired that the deployment can be activated from a static location. This paper provides an overview of the deployment trade study, focusing on our current, favored approach, using a projectile wire launcher. Building on past approaches in the literature, we have developed and fielded an Earth-based, gas-projectile prototype for launching a triangle-shaped antenna onto analogue terrain. Our results compare simulated launch performance to actual field tests conducted under Earth gravity and pressure conditions. We discuss how Earth performance maps to a prospective Mars deployment under reduced gravity and pressure. We also provide lessons learned and next steps towards the development of an integrated TH2OR instrument for finding water on Mars.

Stamenkovic, Vlada↗

NASA NTRS2006

Single- and Multiple-Objective Optimization with Differential Evolution and Neural Networks

Genetic and evolutionary algorithms have been applied to solve numerous problems in engineering design where they have been used primarily as optimization procedures. These methods have an advantage over conventional gradient-based search procedures became they are capable of finding global optima of multi-modal functions and searching design spaces with disjoint feasible regions. They are also robust in the presence of noisy data. Another desirable feature of these methods is that they can efficiently use distributed and parallel computing resources since multiple function evaluations (flow simulations in aerodynamics design) can be performed simultaneously and independently on ultiple processors. For these reasons genetic and evolutionary algorithms are being used more frequently in design optimization. Examples include airfoil and wing design and compressor and turbine airfoil design. They are also finding increasing use in multiple-objective and multidisciplinary optimization. This lecture will focus on an evolutionary method that is a relatively new member to the general class of evolutionary methods called differential evolution (DE). This method is easy to use and program and it requires relatively few user-specified constants. These constants are easily determined for a wide class of problems. Fine-tuning the constants will off course yield the solution to the optimization problem at hand more rapidly. DE can be efficiently implemented on parallel computers and can be used for continuous, discrete and mixed discrete/continuous optimization problems. It does not require the objective function to be continuous and is noise tolerant. DE and applications to single and multiple-objective optimization will be included in the presentation and lecture notes. A method for aerodynamic design optimization that is based on neural networks will also be included as a part of this lecture. The method offers advantages over traditional optimization methods. It is more flexible than other methods in dealing with design in the context of both steady and unsteady flows, partial and complete data sets, combined experimental and numerical data, inclusion of various constraints and rules of thumb, and other issues that characterize the aerodynamic design process. Neural networks provide a natural framework within which a succession of numerical solutions of increasing fidelity, incorporating more realistic flow physics, can be represented and utilized for optimization. Neural networks also offer an excellent framework for multiple-objective and multi-disciplinary design optimization. Simulation tools from various disciplines can be integrated within this framework and rapid trade-off studies involving one or many disciplines can be performed. The prospect of combining neural network based optimization methods and evolutionary algorithms to obtain a hybrid method with the best properties of both methods will be included in this presentation. Achieving solution diversity and accurate convergence to the exact Pareto front in multiple objective optimization usually requires a significant computational effort with evolutionary algorithms. In this lecture we will also explore the possibility of using neural networks to obtain estimates of the Pareto optimal front using non-dominated solutions generated by DE as training data. Neural network estimators have the potential advantage of reducing the number of function evaluations required to obtain solution accuracy and diversity, thus reducing cost to design.

Rai, Man Mohan↗