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At least 37 records · Page 2

Optical Sensors for Use in Propulsion Control Systems

This final technical report describes the results of a cooperative effort which was originally established between John Carroll University and the Instrumentation and Control Technology Division at NASA Lewis Research Center on November, 1982, and then continued with the Engine Sensor Technology Branch at NASA Lewis until March, 1995. All work at John Carroll University was directed by the principal investigator of this grant, Klaus Fritsch, Ph.D. For the first two years of this grant this effort was supervised at NASA by Mr. Robert J. Baumbick and for the remainder of the grant by Dr. Glenn M. Beheim. All research was carried out in close cooperation with Dr. Beheim. Electrically passive optical sensors for measurands such as pressure, temperature, position, and rotational speed are required for aircraft engine control in fly-by-light digital aircraft control systems. Fiberoptic data links and optical multiplexing techniques should be used for combining and processing the outputs from several sensors, sharing as many optical end electronic parts as possible. The overall objective of this grant was to explore techniques for designing and constructing such electrically passive optical sensors for measuring physical parameters in jet aircraft engines and for use in aircraft control systems. We have concentrated our efforts on pressure, temperature, and position sensors employing techniques which are relatively immune to transmissivity variations of the fiber links and to variations in intensity of the light source. Infrared light-emitting diodes are employed because of their longevity and immunity to vibration. We have also studied a number of multiplexing techniques. On the following pages I will give thumbnail sketches of the projects carried out under this grant and provide references to publications and John Carroll M.S. theses which resulted directly from this work and which describe these projects in greater detail.

Fritsch, Klaus↗

Decision Level Fusion: An Event Driven Approach

This study presents a technique that combines the occurrence of certain events, as observed by different sensors, in order to detect and classify objects. This technique explores the extent of dependence between features being observed by the sensors, and generates more informed probability distributions over the events. Provided some additional information about the features of the object, this fusion technique can outperform other existing decision level fusion approaches that may not take into account the relationship between different features.

47 OTHER INSTRUMENTATION↗

Practicing for Mars: The International Space Station (ISS) as a Testbed

Allows demonstration and development of exploration capabilities to help accomplish future missions sooner with less risk to crew and mission Characteristics of ISS as a testbed High fidelity human operations platform in LEO: Continuously operating habitat and active laboratory. High fidelity systems. Astronauts as test subjects. Highly experienced ground operations teams. Offers a controlled test environment.: Consequences to systems performance and decision making not offered in ground analogs International participation. Continuously improving system looking for new technology and ideas to improve operations. Technology Demos & Critical Systems Maturation. Human Health and Performance. Operations Simulations and Techniques. Exploration prep testing on ISS has been ongoing since 2012. Number of tests increasing with each ISS expedition. One Year Crew Expedition starting in Spring 2015. ROSCOSMOS and NASA are partnering on the Participating Crew are Mikhail Kornienko and Scott Kelly Majority of testing is an extension of current Human Biomedical Research investigations Plan for extending & expanding upon current operations techniques and tech demo studies ESA 10 Day Mission in Fall 2015 ESA astronaut focus on testing exploration technologies Many more opportunities throughout the life of ISS! 4/24/2014 david.h.korth@nasa.gov 4 Exploration testing

Korth, David H.↗

Geologic hydrogen: a review of resource potential, subsurface dynamics, exploration, production, transportation, and research opportunities

Hydrogen is a versatile resource with critical roles in decarbonization, industrial manufacturing, and energy integration. However, most hydrogen today is produced from fossil fuels, resulting in high emissions and energy consumption. Although low-carbon hydrogen production methods, such as steam methane reforming with carbon capture and renewable-powered electrolysis, are advancing, their high costs hinder large-scale deployment. Identifying alternative pathways for producing low-cost, low-emission hydrogen is therefore essential. Geologic hydrogen, referring to natural and stimulated hydrogen generated in the Earth's subsurface, has attracted growing attention as a potential source of sustainable, economically viable, and environmentally favorable hydrogen. This paper provides a comprehensive review of geologic hydrogen, covering its resource potential, origins, migration and trapping mechanisms, exploration techniques, production strategies, and pipeline transportation. It also identifies key knowledge gaps and proposes a roadmap for future research. The review indicates that geologic hydrogen has vast resource potential and can leverage existing subsurface technologies and geophysical exploration methods. However, major challenges persist, including uncertain hydrogen generation rates, limited understanding and control of serpentinization processes, costly transportation infrastructure, the lack of validated techno-economic analysis, and potential social and environmental issues. As the field is still in its early stages, progress will require interdisciplinary collaboration spanning geoscience, engineering, economics, environmental science, and policy and regulation.

42 ENGINEERING↗

Mothers of Invention: Hubble Engineers Push Robotic 'Evolution' to Save Telescope, Enable New Exploration

Robotic technology being developed out of necessity to keep the Hubble Space Telescope operating could also lead to new levels of man-machine team-work in deep-space exploration down the road-if it survives the near-term scramble for funding. Engineers here who have devoted their NASA careers to the concept of humans servicing the telescope in orbit are planning modifications to International Space Station (ISS) robots that would leave the humans on the ground. The work. forced by post-Columbia flight rules that killed a planned shuttle-servicing mission to Hubble, marks another step in the evolution of robot-partners for human space explorers. "Hubble has always been a pathfider for this agency," says Mike Weiss. Hubble deputy program manager technical. "When the space station was flown and assembled, Hubble was the pathfinder. not just for modularity, but for operations, for assembly techniques. Exploration is the next step. Things we're going to do on Hubble are going to be applied to exploration. It's not just putting a robot in space. It's operating a robot in space. It's adapting that robot to what needs to be done the next time you're up there."

Morring, Frank, Jr.↗

Application of Raman Spectroscopy to Determine Uranium Content in ADUN Solution

The work presented in this report is part of the ongoing efforts to address the nuclear material control and accounting needs for advanced reactor fuel fabrication facilities. This work was supported by the Materials Protection, Accounting, and Control Technologies (MPACT) program under the US Department of Energy Office of Nuclear Energy‘s Nuclear Fuel Cycle and Supply Chain program. The activities and engagements under the MPACT program are designed to support a robust US civilian nuclear energy enterprise. In the work described in this report, we supported MPACT objectives by developing measurement techniques that could be used for material accounting and process monitoring and by working with industry partners to identify existing gaps and areas for improvement. Oak Ridge National Laboratory has been working with commercial tristructural isotropic (TRISO) fuel fabricators such as Standard Nuclear to develop technology for rapid and cost-effective uranium content assessment. This work has focused on demonstrating advanced measurement techniques (e.g., Raman spectroscopy) that can be used for rapid, reliable, and cost-effective routine measurements of uranium content in feed solutions and liquid waste streams as well as for monitoring in-line process measurements and product streams. Specifically, this report explores techniques for accurately determining uranium content in acid-deficient uranyl nitrate (ADUN) solutions and detecting low uranium concentrations in ammonia solutions. Developing such measurement techniques will benefit TRISO fuel fabrication facilities, facilities involved in other parts of the fuel cycle that require online monitoring of aqueous solutions, and potentially molten salt fuel reactors. This work supports developing Raman spectroscopy procedures to determine uranium concentrations in ADUN solutions, which are used as feedstock in the sol–gel process for creating TRISO fuel. Some additional benefits of using Raman spectroscopy for uranium quantification in fabrication facilities include enabling online monitoring of the chemical process, which would provide near real-time feedback; eliminating the need for sample transfers, preparation, or dilution; providing nondestructive measurements; and user friendliness. In this fiscal year, FY25, we determined the identity of the unknown Raman band at approximately 853 cm−1 that was discovered in ADUN Raman spectra in FY24, created calibration curves and determined uranium concentrations of two ADUN solutions, and compared the Raman results to results obtained from inductively coupled plasma mass spectrometry and Davies–Gray titration. Furthermore, we have identified focus areas for experimentation in future fiscal years. A key result is that the accuracy of using Raman can provide accuracy comparable to destructive analysist techniques, With a well-developed calibration curve, using standards and a large number of samples (more than five samples), uncertainty on the order of 1%–3% is achievable. Given that the uncertainties achieved by Raman spectroscopy were on the order of the uncertainties achieved using ICP-MS, we conclude that with a well-developed procedure Raman spectroscopy can be used to determine uranium concentrations in ADUN solutions for NMC&A applications. The benefits of such an approach are that the time and effort will be less than that of comparable destructive analysis techniques, with approximately the same level of technical expertise. This will be attractive to operators of fuel fabrication facilities as it will lower costs and improve efficiencies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

NEEMO 15: Evaluation of Human Exploration Systems for Near-Earth Asteroids

The NASA Extreme Environment Mission Operations (NEEMO) 15 mission was focused on near-Earth Asteroid (NEA) exploration techniques evaluation. It began with a University of Delaware autonomous underwater vehicle (AUV) systematically mapping the coral reef for hundreds of meters surrounding the Aquarius habitat. This activity is akin to the type of "far field survey" approach that may be used by a robotic precursor in advance of a human mission to a NEA. Data from the far-field survey were then examined by the NEEMO science team and follow-up exploration traverses were planned, which used Deepworker single-person submersibles. Science traverses at NEEMO 15 were planned according to a prioritized list of scientific objectives developed by the science team based on review and discussion of previous related marine science research including previous marine science saturation missions conducted at the Aquarius habitat. AUV data was used to select several areas of scientific interest. The Deepworker science traverses were then executed at these areas of interest during 4 days of the NEEMO 15 mission and provided higher resolution data such as coral species distribution and mortality. These traverses are analogous to the "near field survey" approach that is expected to be performed by a multi mission space exploration vehicle (MMSEV) during a human mission to a NEA before conducting extravehicular activities (EVA)s. In addition to the science objectives that were pursued, the NEEMO 15 science traverses provided an opportunity to test newly developed software and techniques. Sample collection and instrument deployment on the NEA surface by EVA crew would follow the "near field survey" in a human NEA mission. Sample collection was not necessary for the purposes of the NEEMO science objectives; however, the engineering and operations objectives during NEEMO 15 were to evaluate different combinations of vehicles, crewmembers, tools, and equipment that could be used to perform these tasks on a NEA. Specifically, the productivity and acceptability of simulated NEA exploration activities were systematically quantified and compared when operating with different combinations of crew sizes and exploration systems including MMSEVs, EVA jet packs, and EVA translation devices.

Chappell, Steven P.↗

Model Exploration of an Information-Based Healthcare Intervention Using Parallelization and Active Learning

This paper describes the application of a large-scale active learning method to characterize the parameter space of a computational agent-based model developed to investigate the impact of CommunityRx, a clinical information-based health intervention that provides patients with personalized information about local community resources to meet basic and self-care needs. Additionally, the diffusion of information about community resources and their use is modeled via networked interactions and their subsequent effect on agents' use of community resources across an urban population. A random forest model is iteratively fitted to model evaluations to characterize the model parameter space with respect to observed empirical data. We demonstrate the feasibility of using high-performance computing and active learning model exploration techniques to characterize large parameter spaces; by partitioning the parameter space into potentially viable and non-viable regions, we rule out regions of space where simulation output is implausible to observed empirical data. We argue that such methods are necessary to enable model exploration in complex computational models that incorporate increasingly available micro-level behavior data. We provide public access to the model and high-performance computing experimentation code.

97 MATHEMATICS AND COMPUTING↗

Developing Methods for Exercise System Kinematics Tracking

BACKGROUND How to quantify the load and forces produced by exercise equipment and their Vibration Isolation and Stabilization (VIS) platforms in-flight is an active area of investigation. Kinematic tracking paired with system modeling can provide insights as well as verification and validation of simulations used for system design and development. Traditional motion capture methods can require significant cost in equipment procurement and crew-time, but newer lessons learned can be leveraged [1]. The VIS systems of current and future exercise hardware on the International Space Station (ISS) such as the Cycle Ergometer with Vibration Isolation System (CEVIS) and the European Enhanced Exploration Exercise Device (E4D) are not currently outfitted with IMUs or similar measurement devices. Video-based methods would enable use of multi-purpose, crew-familiar flight equipment. An initial exploration of video-based solutions was performed utilizing 2-camera video from crew cycling on Teal-CEVIS on the ISS. METHODS AND RESULTS Our group has scoped a variety of video-based object tracking methods. To date, we have primarily investigated computer vision toolkits such as openCV. Techniques explored include key-point detection, background subtraction, region-of interest tracking, color-based tracking, tag masking and tracking, and corner detection. Although object-tracking and 6D pose estimation is a rich field, space applications are a unique problem that are challenging for existing software and toolkits. The majority of the existing object-tracking applications involve vehicles/pedestrians and household objects with simple backgrounds. We have identified the following features which pose particular challenges for on-station exercise equipment tracking: Busy and visually cluttered background Low-textured tracking object with relatively small motions Occlusions and motion by human subject and loose, floating objects Limited number of video cameras with no fixed global references Limited ability to add tags, markers, or visual references to the tracking object Lack of training data for Machine Learning (ML) algorithms CONCLUSION We will summarize the efficacy of techniques tested for a ground mock-trial and the on-station exercise trial. It is likely that human-in-loop feedback or a conglomerate of methods is required. ML-based methods, like those implemented for human body tracking [2], may still be a viable option, but more training data and validation is needed.

L B Nilsson↗

Developing Methods for Exercise System Kinematic Tracking

BACKGROUND How to quantify the load and forces produced by exercise equipment and their Vibration Isolation and Stabilization (VIS) platforms in-flight is an active area of investigation. Kinematic tracking paired with system modeling can provide insights as well as verification and validation of simulations used for system design and development. Traditional motion capture methods can require significant cost in equipment procurement and crew-time, but newer lessons learned can be leveraged [1]. The VIS systems of current and future exercise hardware on the International Space Station (ISS) such as the Cycle Ergometer with Vibration Isolation System (CEVIS) and the European Enhanced Exploration Exercise Device (E4D) are not currently outfitted with IMUs or similar measurement devices. Video-based methods would enable use of multi-purpose, crew-familiar flight equipment. An initial exploration of video-based solutions was performed utilizing 2-camera video from crew cycling on Teal-CEVIS on the ISS. METHODS AND RESULTS Our group has scoped a variety of video-based object tracking methods. To date, we have primarily investigated computer vision toolkits such as open CV. Techniques explored include key-point detection, background subtraction, region-of interest tracking, color-based tracking, tag masking and tracking, and corner detection. Although object-tracking and 6D pose estimation is a rich field, space applications are a unique problem that are challenging for existing software and toolkits. The majority of the existing object-tracking applications involve vehicles/pedestrians and household objects with simple backgrounds. We have identified the following features which pose particular challenges for on-station exercise equipment tracking: 1. Busy and visually cluttered background 2. Low-textured tracking object with relatively small motions 3. Occlusions and motion by human subject and loose, floating objects 4. Limited number of video cameras with no fixed global references 5. Limited ability to add tags, markers, or visual references to the tracking object 6. Lack of training data for Machine Learning (ML) algorithms CONCLUSION We will summarize the efficacy of techniques tested for a ground mock-trial and the on-station exercise trial. It is likely that human-in-loop feedback or a conglomerate of methods is required. ML-based methods, like those implemented for human body tracking [2], may still be a viable option, but more training data and validation is needed.

L Nilsson↗

Human exploration of Mars

A systems study is underway of astronaut missions to Mars that could be accomplished over the next four decades. In addition to an emphasis on the transportation and facility infrastructure required for such missions, other relevant technologies and mission constraints are also being considered. These induce on-orbit assembly, trajectory type, launch opportunities, propellant storage, crew size, cabin pressure, artificial gravity, life-support systems, radiation hazards, power/energy storage, thermal control, human factors, communications, abort scenarios, landing techniques, exploration strategies, and science activities. A major objective of the study is to identify enabling and significantly enhancing technologies for accomplishing the goal of the human exploration of Mars.

Clark, Benton C.↗

Remote sensing in hydrology: A survey of applications with selected bibliography and abstracts

Remote infrared sensing as a water exploration technique is demonstrated. Various applications are described, demonstrating that infrared sensors can locate aquifers, geothermal water, water trapped by faults, springs and water in desert regions. The potentiality of airborne IR sensors as a water prospecting tool is considered. Also included is a selected bibliography with abstracts concentrating on those publications which will better acquaint the hydrologist with investigations using thermal remote sensors as applied to water exploration.

Sers, S. W.↗

A method for diagnosing time dependent faults using model-based reasoning systems

This paper explores techniques to apply model-based reasoning to equipment and systems which exhibit dynamic behavior (that which changes as a function of time). The model-based system of interest is KATE-C (Knowledge based Autonomous Test Engineer) which is a C++ based system designed to perform monitoring and diagnosis of Space Shuttle electro-mechanical systems. Methods of model-based monitoring and diagnosis are well known and have been thoroughly explored by others. A short example is given which illustrates the principle of model-based reasoning and reveals some limitations of static, non-time-dependent simulation. This example is then extended to demonstrate representation of time-dependent behavior and testing of fault hypotheses in that environment.

Goodrich, Charles H.↗

9Cr steel visualization and predictive modeling

The goals of this work were to develop tools to visualize and characterize materials information, to explore new alloy compositions and/or processing, to better predict tensile strength and other mechanical properties. The 9–12 wt% Cr (9Cr) steel test data were compiled from several sources. About 3000 records with 30 predictor variables represent 82 unique steel alloy compositions, variations of thermo-mechanical processing steps and temperatures (homogenization, normalization and tempering cycles), test conditions and outcomes. Detailed data processing steps such as visualization and exploratory analysis, including univariate and bivariate analysis, different clustering techniques used to segment the data, statistical post-hoc analysis to verify significance of the findings, feature engineering to identify predictors of importance, and predictive modeling with cross-validation were performed. The outcome of analysis at each step was reviewed in the context of the domain knowledge of this class of steel, to see if there were underlying physical mechanisms that explain statistical relationships. Data analytics techniques and their parameters were fine-tuned to facilitate interpretation of the results as aligned with the insights from domain experts. Here, the ensemble predictive modeling using Random Forest regressor and post-hoc means comparison corroborated domain knowledge on the role of Co which is known to increase strength of steel alloys through solid-solution strengthening and to affect diffusion of alloying elements and precipitates. Alloys with Co content of 0.7–8 wt% had significantly higher mean strength than the ones without (while having Cr locked within 10–11 wt% range in either group and keeping other compositional element ratios fixed). End products of the computational techniques exploration are presented as the tools that can be used in iterative workflow of materials development and testing.

36 MATERIALS SCIENCE↗

Fermilab Booster loss modelling and rebalancing using Bayesian methods

Fermilab Booster is being upgraded for the PIP-II project to support 20Hz ramp rate at higher intensities. Loss trip limits determine the achievable peak power. To meet PIP-II requirements, losses need to be halved as compared to current levels. Losses primarily occur at injection and transition crossing, with both gradually increasing and threshold-like intensity-dependent behaviors. The existing simulation models are not yet good enough for quantitative loss predictions. In practice, it will be necessary to tune up the Booster using iterative methods and operator intuition. In this paper we present an effort to systematically model Booster losses using active learning (Bayesian exploration) techniques, and subsequently to rebalance them for higher trip limit margins. We first created several sets of spatially and temporally isolated orbit and optics knobs, and trained Gaussian process models for each beam loss monitor as well as beam current. This is a complex task due to safety and timing requirements – we discuss mitigations such as uncertainty constraints and approximate fitting. Once models are stable, we perform large-scale single and multi-objective tuning using scalarized objectives made up of critical beam loss locations. Our results demonstrate significant rebalancing of losses, increasing trip margins, as well as an overall improvement in beam transmission efficiency. We are exploring how to combine existing simulations with experimental data and automate the collection procedure so that more advanced surrogate models can be created over time.

Kuklev, Nikita [Fermilab]↗

Measuring the Chemical Potential of the Martian Regolith to Generate and Sustain Life

A critical component for identifying chemical biosignatures is the ability to assess in-situ the potential of an aqueous geochemical environment to generate and sustain life. On Mars or other solar bodies, in-situ chemical characterization could provide evidence as to whether the chemical composition of the regolith or evaporites in suspected ancient water bodies have been biologically influenced or possess the chemical parameters within which life may have existed, or may still exist. A variety of analytical techniques have been proposed for use in detecting and identify signatures of past or present life. These techniques fall into two groups; visual observation with instruments such as cameras or optical/atomic-force microscopes; or elemental chemical analysis with such instruments as X-ray fluorescence (XRF) and diffraction (XRD), a-proton backscatter (APX), y-ray, Mossbauer, Raman, IR, UV/VIS spectroscopies, gas chromatography (GC), or mass spectrometry (MS). Direct observation of an identifiable lifeform by the first set of instruments in a single sample is highly unlikely, especially for extinct organisms or on the surface. The later instruments can provide vital data as to the elemental mineralogy and geological history of the planet, but are highly inadequate for understanding the chemistry of the planet in terms of indigenous life or interactions with human explorers. Techniques such as XRD, XRF, and APX, provide elemental composition at high limits of detection. Some of this data can be extrapolated or interpolated to provide chemical parameters such as oxidation state or composition. Gas chromatography (GC) without standards and non-specific detectors, has little chance of identifying a mixture of unknown components. Combined with GC or by itself, mass spectrometry (MS) can provide identification of compounds, but in both cases the sample must be appropriately prepared for accurate and reliable analysis. Life as we know it, and probably identify it as such, requires an aqueous environment. Deciphering die chemical speciation of this aqueous environment is the key to recognizing therein the biosignatures of any extinct or present life forms. Identifying the soluble (ionic and nonionic) components by reacting a currently dormant environment can provide a "picture" of the thermodynamics and chemical components of a possibly bioactive environment. The only devices which can provide such information are electrochemical sensors based on the potentiometric ion selective electrodes (ISEs) and on dynamic techniques such as cyclic voltammetry (CV) and stripping voltammetry (SV). Such an array of devices can provide not only the chemical composition of a water-soluble Martian soil sample, but also several other vital chemical parameters such as pH, conductivity, redox potential, and dissolved gases. To address these issues we have been investigating the possible use of an electrochemically-based ion sensor array as a new integrated approach to quantitative analytical and chemometric electrochemical measurements. The sensor array will consist of specific and semispecific ion selective and amperometric transducers, which can simultaneously and continuously identify and semiquantitatively determine over 50 organic and inorganic analytes in water-based environments. Several individual sensors, based on the same principle, have been flight-tested and have been installed as part of the MECA instrumentation on the Mars 2001 Lander for in-situ analyses. However, the microfabrication, integration and multiplexing of such a large number of these sensors on a single substrate have not been previously attempted.

Kounaves, S. P.↗

Using Dark Fiber and Distributed Acoustic Sensing to Characterize a Geothermal System in the Imperial Valley, Southern California

The Imperial Valley, CA, is a tectonically active transtensional basin located south of the Salton Sea; the area hosts numerous geothermal fields, including significant hidden hydrothermal resources without surface manifestations. Development of inexpensive, rugged, and highly sensitive exploration techniques for undiscovered geothermal systems is critical for accelerating geothermal power deployment as well as unlocking a low-carbon energy future. We present a case study utilizing distributed acoustic sensing (DAS) and ambient noise interferometry for geothermal reservoir imaging, utilizing unlit fiber-optic telecommunication infrastructure (dark fiber). The study exploits two days of passive DAS data acquired in early November 2020 over a ~28-km section of fiber from Calipatria, CA to Imperial, CA. We apply ambient noise interferometry to retrieve coherent signals from DAS records and develop a bin stacking technique to attenuate the effects from persistent localized noise sources and to enhance retrieval of coherent surface waves. As a result, we are able to obtain high-resolution two-dimensional (2D) S wave velocity ($V_s$) structure to 3 km depth, based on joint inversion of both the fundamental and higher overtones. We observe a previously unmapped high $V_s$ and low $V_p$/$V_s$ ratio feature beneath the Brawley geothermal system, which we interpret to be a zone of hydrothermal mineralization and lower porosity. This interpretation is consistent with a host of other measurements including surface heat flow, gravity anomalies, and available borehole wireline data. These results demonstrate the potential utility of DAS deployed on dark fiber for geothermal system exploration and characterization in the appropriate geological settings.

Vp/Vs imaging↗