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NASA NTRS2017

The Evolution of Planetary Protection Implementation on Mars Landed Missions

NASA has developed requirements dedicated to the prevention of forward and backward contamination during space exploration. Historically, international agreements provided guidelines to prevent contamination of the Moon and other celestial bodies, as well as the Earth (e.g., sample return missions). The UN Outer Space Treaty was established in 1967 and the Committee on Space Research (COSPAR) maintains a planetary protection policy complying with Article IX of this treaty. By avoiding forward contamination, the integrity of scientific exploration is preserved. Planetary Protection mission requirements are levied on missions to control contamination. These requirements are dependent on the science of the mission and on the celestial bodies encountered or targeted along the way. Consequently, categories are assigned to missions, and specific implementation plans are developed to meet the planetary protection requirements. NASA missions have evolved over time with increasingly more demanding scientific objectives and more complex flight systems to achieve those objectives and, thus, planetary protection methods and processes used for implementation have become much more intricate, complicated, and challenging. Here, we will portray the evolution of planetary protection implementation at JPL in several important areas throughout the course of NASA sponsored robotic Mars lander or rover missions, starting from Mars Pathfinder through the beginning of Mars 2020. Highlighted in the discussion will be process changes in planetary protection requirements development and flow down. Development and implementation of new and improved methods used in the reduction of spacecraft bioburden will be discussed as well as approaches and challenges that come along with setting up remote laboratories to perform bioassays. The consequences and forward planning of delays on missions will be highlighted as well as lessons learned on the impact of communication and training in achieving planetary protection requirements. The evolution of methods used for the detection of microbial bioburden on spacecraft hardware will be considered. These methods use standard microbiology as well as the adaptation of advances in biotechnology, molecular biology, and bioinformatics. Technical approaches developed for the prevention of contamination and recontamination of hardware during Assembly, Test, and Launch Operations will be discussed.

Kazarians, Gayane A.↗
NASA NTRS2010

Radiation Beamline Testbeds for the Simulation of Planetary and Spacecraft Environments for Human and Robotic Mission Risk Assessment

The Center for Radiation Engineering and Science for Space Exploration (CRESSE) at Prairie View A&M University, Prairie View, Texas, USA, is establishing an integrated, multi-disciplinary research program on the scientific and engineering challenges faced by NASA and the international space community caused by space radiation. CRESSE focuses on space radiation research directly applicable to astronaut health and safety during future long term, deep space missions, including Martian, lunar, and other planetary body missions beyond low earth orbit. The research approach will consist of experimental and theoretical radiation modeling studies utilizing particle accelerator facilities including: 1. NASA Space Radiation Laboratory (NSRL) at Brookhaven National Laboratory; 2. Proton Synchrotron at Loma Linda University Medical Center; and 3. Los Alamos Neutron Science Center (LANSCE) at Los Alamos National Laboratory. Specifically, CRESSE investigators are designing, developing, and building experimental test beds that simulate the lunar and Martian radiation environments for experiments focused on risk assessment for astronauts and instrumentation. The testbeds have been designated the Bioastronautics Experimental Research Testbeds for Environmental Radiation Nostrum Investigations and Education (BERT and ERNIE). The designs of BERT and ERNIE will allow for a high degree of flexibility and adaptability to modify experimental configurations to simulate planetary surface environments, planetary habitats, and spacecraft interiors. In the nominal configuration, BERT and ERIE will consist of a set of experimental zones that will simulate the planetary atmosphere (Solid CO2 in the case of the Martian surface.), the planetary surface, and sub-surface regions. These experimental zones can be used for dosimetry, shielding, biological, and electronic effects radiation studies in support of space exploration missions. BERT and ERNIE are designed to be compatible with the experimental areas associated with the above facilities. CRESSE has broad expertise in space radiation in the areas of space radiation environment modeling, Monte-Carlo radiation transport modeling, space radiation instrumentation and dosimetry, radiation effects on electronics, and multi-functional composite shielding materials. The BERT and ERNIE testbeds will be utilized in individual and collaborative research incorporating this expertise. The research goal is to maximize the technical readiness level (TRL) of radiation instrumentation for human and robotic missions, optimizing the return value of CRESSE for NASA exploration and international co-operative missions. Outcomes and knowledge from research utilizing BERT and ERNIE will be applied to a variety of scientific and engineering disciplines vital for safe and reliable execution of future space exploration missions, which can be negatively impacted by the space radiation environment. The testbeds will be central to a variety of university educational activities and educational goals of NASA. Specifically, BERT and ERNIE will enhance educational opportunities in science, technology, engineering and mathematics (STEM) disciplines for engineering and science students at PVAMU, a historically black college/university. Preliminary data on prototype testbed configurations, including simulated lunar regolith (JSC-1A stimulant based on Apollo 11 samples), regolith/polyethylene composites, and dry ice, will be presented to demonstrate the usefulness of BERT and ERNIE in radiation beam line experiments.

Wilkins, Richard↗
NASA NTRS2006

Generating Control Commands From Gestures Sensed by EMG

An effort is under way to develop noninvasive neuro-electric interfaces through which human operators could control systems as diverse as simple mechanical devices, computers, aircraft, and even spacecraft. The basic idea is to use electrodes on the surface of the skin to acquire electromyographic (EMG) signals associated with gestures, digitize and process the EMG signals to recognize the gestures, and generate digital commands to perform the actions signified by the gestures. In an experimental prototype of such an interface, the EMG signals associated with hand gestures are acquired by use of several pairs of electrodes mounted in sleeves on a subject s forearm (see figure). The EMG signals are sampled and digitized. The resulting time-series data are fed as input to pattern-recognition software that has been trained to distinguish gestures from a given gesture set. The software implements, among other things, hidden Markov models, which are used to recognize the gestures as they are being performed in real time. Thus far, two experiments have been performed on the prototype interface to demonstrate feasibility: an experiment in synthesizing the output of a joystick and an experiment in synthesizing the output of a computer or typewriter keyboard. In the joystick experiment, the EMG signals were processed into joystick commands for a realistic flight simulator for an airplane. The acting pilot reached out into the air, grabbed an imaginary joystick, and pretended to manipulate the joystick to achieve left and right banks and up and down pitches of the simulated airplane. In the keyboard experiment, the subject pretended to type on a numerical keypad, and the EMG signals were processed into keystrokes. The results of the experiments demonstrate the basic feasibility of this method while indicating the need for further research to reduce the incidence of errors (including confusion among gestures). Topics that must be addressed include the numbers and arrangements of electrodes needed to acquire sufficient data; refinements in the acquisition, filtering, and digitization of EMG signals; and methods of training the pattern- recognition software. The joystick and keyboard simulations were chosen for the initial experiments because they are familiar to many computer users. It is anticipated that, ultimately, interfaces would utilize EMG signals associated with movements more nearly natural than those associated with joysticks or keyboards. Future versions of the pattern-recognition software are planned to be capable of adapting to the preferences and day-today variations in EMG outputs of individual users; this capability for adaptation would also make it possible to select gestures that, to a given user, feel the most nearly natural for generating control signals for a given task (provided that there are enough properly positioned electrodes to acquire the EMG signals from the muscles involved in the gestures).

Wheeler, Kevin R.↗
NASA NTRS2018

Reliability of the Danish Aerospace Corporation Portable Pulmonary Function System

Metabolic gas analysis is a critical component of investigations that measure cardio-pulmonary exercise responses during and after long-duration spaceflight. The primary purpose of the current study was to determine the reliability and intra-subject repeatability of a metabolic gas analysis device, the Portable Pulmonary Function System (PPFS), designed for use on the International Space Station (ISS). The second objective of this study was to directly compare PPFS measurements of expired oxygen and carbon dioxide (FEO2 and FECO2) to values obtained from a well-validated clinical metabolic gas analysis system (ParvoMedics TrueOne (c) [PM]). Eight subjects performed four peak cycle tests to maximal exertion. The first test was used to prescribe work rates for the subsequent test sessions. Metabolic gas analysis for this test was performed by the PM, but samples of FEO2 and FECO2 also were simultaneously collected for analysis by the PPFS. Subjects then performed three additional peak cycle tests, consisting of three 5-min stages designed to elicit 25%, 50%, and 75% maximal oxygen consumption (VO2max) followed by stepwise increases of 25 W/min until subjects reached volitional exhaustion. Metabolic gas analysis was performed using the PPFS for these tests. Intraclass correlation coefficients (ICC), within-subject standard deviations (WS SD), and coefficients of variation (CV%) were calculated for the repeated exercise tests. Mixed model regression analysis was used to compare paired FEO2 and FECO2 values obtained from the PPFS and the PM during the initial test. The ICC values for oxygen consumption (VO2), carbon dioxide production (VCO2), and ventilation (VE) indicate that the PPFS is highly reliable (0.79 to 0.99) for all exercise levels tested; however, ICCs for respiratory exchange ratio (RER) were low ( 0.11 - 0.51), indicating poor agreement between trials during submaximal and maximal exercise. Overall, CVs ranged from 1.6% to 6.7% for all measurements, a finding consistent with reported values that were obtained using other metabolic gas analysis techniques. The PPFS and PM produced comparable FEO2 data; however, there was less agreement between measures of FECO2 obtained from the two devices, particularly at lower CO2 concentrations. The PPFS appears, in practically all respects, to yield highly reliable metabolic gas analysis data. Lower reliability of RER measurements reported in the literature and likely is not a function of the PPFS device. Further examination of PPFS CO2 data is warranted to better understand the limitations of these PPFS measurements. Overall, the PPFS when used for repeated measures of cardio-pulmonary exercise should provide accurate and reliable data for studies of human adaptation to spaceflight.

Portable Pulmonary Function System (PPFS)↗
DOE OSTI2024

Miniaturized Magnetoelastic Sensor System

This article describes the design, assembly, and implementation of a hand-held, magnetic-field-based sensor system that can be adapted for a variety of sensing applications. The miniaturized system is based on Chemical Identification by Magneto-Elastic Sensing (ChIMES) technology, which uses three concentric solenoid coils to wirelessly interrogate a sensor body comprised of a response material coupled to a magnetoelastic wire. The response material expands when it encounters a target, imposing mechanical stress on the wire and altering its magnetic permeability. The sensor bodies are passive, requiring no external power source, and they are small, measuring about 15 mm in length and 3.0 mm in diameter. Up to four sensor bodies can be configured as an evenly-spaced linear array. The sensor system operates by applying a low-frequency, current-stabilized, filtered triangle wave to a uniform-density excitation coil to switch the magnetic domains within the wire. Further, the responses from the sensors are picked up by a detection coil as stress-induced changes in the Faraday voltage, and the strong magnetic field induced by the excitation coil in the detection coil is nullified by a cancellation coil reverse-wound in series with the detection coil. The responses of the sensors in an array are separated in time by a linear gradient dc biasing coil. The sensors can be interrogated through metallic and nonmetallic barriers. The signals from the detection coil and the excitation coil are digitized by a pair of bipolar analog-to-digital converters (ADCs). A Raspberry Pi single-board computer (SBC) and associated software perform data acquisition and control all aspects of the sensor system hardware. The program allows the user to select the number of sensors in the array, the type of signal that is being collected, and the number of samples to take. The program also allows for signal processing of the sensor data, such as baseline correction. The program can differentiate sensor peaks from each other and calculate the magnitude of each sensor response with less than 1% error. The data are then displayed along with a graph of the signal.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Degradable Biocomposite Thermoplastic Polyurethanes

In this project, the team developed tough and degradable biocomposite thermoplastic polyurethanes (TPUs) by incorporating bacterial spores into TPUs as a biofunctional living filler. The team screened various bacteria and selected the Bacillus subtilis ATCC 6633 strain as the final candidate, primarily due to its genomic availability, sporulation ability and TPU assimilation activity. The heat-shock tolerance of ATCC 6633 spores was further improved through evolutionary engineering via Adaptive Laboratory Evolution (ALE), demonstrating a 17.7-fold enhanced germination efficiency post heat-shock treatment compared to the wild-type strain (WT). The team fabricated biocomposite TPUs by incorporating lyophilized powder of heat-shock tolerized (HST) spores during the hot melt extrusion (HME) of TPU at 135 °C. The baseline TPU used in this project is a commercially available soft-grade TPU (BCF45) manufactured by BASF. Colony forming unit (CFU) assays quantified that WT and HST spores in the TPU matrix retained approximately 20% and 100% survivability, respectively, after HME. Tensile testing demonstrated that the spores behaved as a polymer-reinforcing filler, positively affecting the overall tensile properties of the biocomposite TPU. For example, biocomposite TPU with WT and HST spores (BC TPU WT and BC TPU HST , respectively) exhibited up to 25% and 37% improved toughness, respectively, compared to TPU without spores. BC TPU HST showed remarkably improved disintegration in autoclaved compost (92% mass loss in 5 months), which simulated a microbially poor environment for TPU degradation. When compared to TPU without spores (44% mass loss in 5 months) the acceleration of degradation is marked. Respirometry confirmed that 72% of BC TPU HST was biomineralized into CO2 within 6 months, indicating that spores in the biocomposite TPU were germinated by utilizing nutrients in the autoclaved compost, facilitating TPU degradation at the end of the material's life. The team demonstrated the scale-up of biocomposite TPU fabrication using continuous extrusion and injection molding techniques. Processing conditions optimized in a lab-scale microcompounder were successfully transferred to a continuous extruder with a 30-fold increased throughput. Biocomposite TPUs prepared using these industry-relevant processes showed comparable toughness improvements to samples prepared in the lab-scale extruder. Excitingly, following compounding in the pilot-extruder the composite material could be injection molded, while retaining high spore viability and similar toughness improvements. The team also found that spores in biocomposite TPU served as antioxidants, preventing toughness decay during the recycled extrusion of BC TPU HST . Long-term storage tests over one year showed that the addition of spores had no negative effect on the longevity of the TPU. Furthermore, the team demonstrated the fabrication of spore-bearing biocomposite polymers with other polyesters such as PBAT, PLA, and PCL. We obtained promising preliminary data that showed overall toughness improvements for all polymers with spore addition. Finally, life cycle assessment (LCA) and techno-economic analysis (TEA) were carried out, which indicated minimal additional cost of fabrication. Overall, a tough and degradable biocomposite thermoplastic was successfully developed through this project, with all tasks completed successfully, achieving >100% of the objectives.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

42 ENGINEERING↗
DOE OSTI2023

Reprint of: Explainable AI (XAI)-driven vibration sensing scheme for surface quality monitoring in a smart surface grinding process

Local Interpretable and Model-agnostic Explanation (LIME), an explainable artificial intelligence (XAI) approach is adapted to identify the globally important time-frequency bands for predicting average surface roughness (Ra) in a smart grinding process. The smart grinding setup consisted of a Supertech CNC precision surface grinding machine, instrumented with a Dytran piezoelectric accelerometer attached to the tailstock quill along the tangential direction (Y-axis). For every grinding pass, vibration signatures were captured, and the ground truth surface roughness values were recorded using a Mahr Marsurf M300C portable surface roughness profilometer. The roughness values ranged from 0.06 to 0.14 microns over the complete set of experiments. Time-frequency domain spectrogram frames were extracted for each of the vibration signals collected during the grinding process. Convolutional Neural Networks (CNNs) were modeled to predict the surface roughness based on these spectrogram frames and their image augmentations. The best CNN model was able to predict the roughness values with an overall R2-score of 0.95, training R2-score of 0.99, and testing R2-score of 0.81 with only 80 sets of vibration signals corresponding to 4 experiments with 20 trials each. Although the data size is not large enough to guarantee such performance metrics in real-world scenarios, one can extract statistically consistent explanations underlying the relationships these complex deep learning models capture. Further, the LIME methodology was implemented on the developed surface roughness CNN model to identify the important time-frequency bands (i.e., the superpixels of a spectrogram) influencing the predictions. Based on the identified important regions on the spectrogram frames, the corresponding frequency characteristics were determined that influence the surface roughness predictions. The important frequency range based on LIME results was approximately 11.7 to 19.1 kHz. The power of XAI was demonstrated by cutting down the sampling rate from 160 kHz to 30, 20, 10, and 5 kHz based on the important frequency range and considering Nyquist criteria. Separate CNN models were developed for these ranges by only extracting time-frequency contents below their corresponding Nyquist cut-offs. A proper data acquisition strategy is proposed by comparing the model performances to argue the selection of a sufficient sampling rate to capture the grinding process successfully and robustly.

47 OTHER INSTRUMENTATION↗
NASA NTRSDate not supplied

Lessons for Future In-Space Telerobotic Servicing from Robotic Refueling Mission

The Robotic Refueling Mission (RRM) was a multi-phased technology development effort by the National Aeronautics & Space Administration (NASA) and the Canadian Space Agency (CSA). The program leveraged the existing robotic systems and expertise of the International Space Station (ISS) program and the tool design and satellite servicing expertise of NASA’s Exploration & In-space Services (NExIS) Projects Division at Goddard Space Flight Center (GSFC) to evaluate new hardware and techniques for on-orbit telerobotic servicing. Between 2011 and 2021, two external ISS payloads housed over a dozen robotic tools and adapters designed to service a variety of existing and novel satellite interfaces. Robot operators at NASA’s Johnson Space Center (JSC) and CSA used the Special Purpose Dexterous Manipulator (SPDM) to retrieve and operate these tools for tasks such as cutting wires or multi-layer insulation blanketing, removing valve caps, mating electrical connectors, transferring fluids, and performing visual inspections inside a vehicle. Each phase of RRM involved years of preparation. Tool and interface designs were prototyped and evaluated using both NASA and Canadian ground robotic systems. Procedures were developed by GSFC engineers and vetted in partnership with JSC and CSA robot operators. GSFC engineers were trained to provide real-time support during on-orbit operations. These preparatory efforts and the successful on-orbit evaluations yielded an array of lessons for future in-space telerobotic missions. Designing robotic tools for the space environment requires special consideration of materials, indicators, and differences between ground and flight use cases and environments. When there is a limited window for on-orbit operations, devoting time and high-fidelity hardware to ground testing can be critical. Needs during potential troubleshooting are more essential to camera view quality, frame rate, and position requirements more than nominal operations. Detailed hardware manuals, nominal and contingency procedures, along with clearly defined operations team roles and protocols are vital for efficiency. RRM also demonstrated how the ISS can be utilized to increase the technology readiness levels required for future missions and led to additional technology partnerships between NExIS and the ISS program. The lessons from RRM are currently being applied to designs, operations concepts, and ground test methodology for missions such as On-orbit Servicing, Assembly, and Manufacturing1(OSAM-1)and Mars Sample Return.

Zakiya Tomlinson↗
NASA NTRS2013

ISSM: Ice Sheet System Model

In order to have the capability to use satellite data from its own missions to inform future sea-level rise projections, JPL needed a full-fledged ice-sheet/iceshelf flow model, capable of modeling the mass balance of Antarctica and Greenland into the near future. ISSM was developed with such a goal in mind, as a massively parallelized, multi-purpose finite-element framework dedicated to ice-sheet modeling. ISSM features unstructured meshes (Tria in 2D, and Penta in 3D) along with corresponding finite elements for both types of meshes. Each finite element can carry out diagnostic, prognostic, transient, thermal 3D, surface, and bed slope simulations. Anisotropic meshing enables adaptation of meshes to a certain metric, and the 2D Shelfy-Stream, 3D Blatter/Pattyn, and 3D Full-Stokes formulations capture the bulk of the ice-flow physics. These elements can be coupled together, based on the Arlequin method, so that on a large scale model such as Antarctica, each type of finite element is used in the most efficient manner. For each finite element referenced above, ISSM implements an adjoint. This adjoint can be used to carry out model inversions of unknown model parameters, typically ice rheology and basal drag at the ice/bedrock interface, using a metric such as the observed InSAR surface velocity. This data assimilation capability is crucial to allow spinning up of ice flow models using available satellite data. ISSM relies on the PETSc library for its vectors, matrices, and solvers. This allows ISSM to run efficiently on any parallel platform, whether shared or distrib- ISSM: Ice Sheet System Model NASA's Jet Propulsion Laboratory, Pasadena, California uted. It can run on the largest clusters, and is fully scalable. This allows ISSM to tackle models the size of continents. ISSM is embedded into MATLAB and Python, both open scientific platforms. This improves its outreach within the science community. It is entirely written in C/C++, which gives it flexibility in its design, and the power/speed that C/C++ allows. ISSM is svn (subversion) hosted, on a JPL repository, to facilitate its development and maintenance. ISSM can also model propagation of rifts using contact mechanics and mesh splitting, and can interface to the Dakota software. To carry out sensitivity analysis, mesh partitioning algorithms are available, based on the Scotch, Chaco, and Metis partitioners that ensure equal area mesh partitions can be done, which are then usable for sampling and local reliability methods.

Larour, Eric↗
NASA NTRSDate not supplied

MULTI-OMICS ANALYSIS OF THE IMPACT OF CHRONIC LOW-DOSE RADIATION AND HINDLIMB SUSPENSION ON MURINE BRAIN AND RETINA

The space environment includes hazards like radiation and microgravity which can adversely affect biological systems. We assessed multi-omics multi-tissue NASA GeneLab datasets where 6-month-old female mice were gamma irradiated (IR) and/or hindlimb unloaded (HLU) for 21 days. Whole transcriptome shotgun sequencing (RNA-Seq) and reduced representation bisulfite sequencing (RRBS) of brain and retina samples collected at 4 months post-exposure was performed to better characterize the retinal and neurological responses to spaceflight. We compared epigenomic and transcriptomic profiles within each exposure group for both tissue types to identify correlation (Pearson’s correlation test; p-value < 0.05) between gene expression and DNA methylation levels that may be related to transcriptional regulation. We then obtained genes with methylation-expression correlation that also showed differences in mean expression or dispersion between exposed and control groups (adjusted p-value < 0.25; relaxed to denote ‘hypothesis’) in the brain (37 genes in HLU, 4 in IR, and 156 in HLU+IR) or retina (92 genes in HLU, 1 in IR, and 55 in HLU+IR). Enriched Gene Ontology (GO) terms for these genes are listed in Table 1 for HLU and HLU+IR for both tissue types. No enriched terms and only a few genes were detected with IR-only exposure in the brain (Chmp1a, Limd1, Rab40b, Ubc) and retina (retinoblastoma binding protein Rbbp7). Cellular components related to synapse were enriched in both tissue types. Previous analysis of differentially expressed genes in the retina after 1 month of HLU+IR showed enrichment in the somatodendritic compartment of the neuron, which was also observed in the brain 4 months post-exposure. Interestingly, genes related to ubiquitination showed correlation between methylation and expression and were differentially expressed or dispersed in different exposure groups indicating that this pathway may play an important role in multi-stressor response (Figure 1). The current multi-omics and multi-tissue analysis interrogates the epigenomic and transcriptomic impacts of radiation and hindlimb unloading, in isolation and in combination, on the retina and the brain. The results provide insight into the adaptive response to individual spaceflight hazard analogs and their interplay, as well as hypotheses to be further tested for understanding spaceflight-induced neurological and vision effects.

Prachi Kothiyal↗
DOE OSTI2025

Rapid Bayesian High Entropy Alloy Designs Fabricated via Wire Arc Additive Manufacturing

Purpose: This project seeks to demonstrate a new high-throughput (rapid) alloy design technique applied to creating new high entropy alloys (HEAs) for extreme environments. High entropy alloys shift the design paradigm from being focused on a single principal element (e.g. nickel-based alloys) to target alloys that include high atomic fractions (X >10%) of multiple elements. These HEA materials can exhibit sluggish diffusion and enhanced corrosion resistance, ideal for potential applications in advanced ultra supercritical (A-USC) steam cycles for power generation. Scope: The addition of multiple elements in high atomic fractions creates an enormous design space that cannot easily be investigated by traditional material design strategies such as designed of experiments (DOE). This project utilizes a Bayesian machine learning algorithm that has been modified to work with calculation of phase diagrams (CALPHAD) software. This Bayesian algorithm reduces manual inputs and increase the likelihood of achieving an optimal solution. Compositional inputs to this algorithm will be assessed using existing material property models for high temperature strength and corrosion resistance. The target for alloy performance will be a 15% (~100 ⁰C) increase in allowable service temperature beyond heat-resistant stainless steels while maintaining or improving alloy cost and corrosion resistance. Haynes 230 was selected as a baseline, which is 57 wt% Ni with 22 wt% Cr 14 wt% W, and 2 wt% Mo as solid solution strengtheners. In addition to rapid design via Bayesian machine learning, the alloys were rapidly fabricated using a multi-wire arc additive manufacturing (mWAAM) technique which allows for precise control of alloy composition and assessing of alloy design “windows” to study composition effects. Build speeds for wire-arc additive processes are among the highest for additive technologies enabling rapid and reliable sample fabrication when compared to conventional methods such as arc button melting. The mWAAM samples will be rapidly characterized via instrumented indentation for room temperature modulus and strength and for elevated temperature strength via hot hardness tests. After being screened with hardness testing, potential alloys will be further evaluated with conventional microscopy techniques including scanning electron microscopy (SEM) and transmission electron microscopy (TEM) to assess agreement with modeling results. The most promising compositions will also be evaluated by printing full sized tensile specimens for mechanical behavior tests at elevated temperatures. Results: Bayesian machine learning of a single performance function was initially used to optimize five performance metrics: 1) single phase stability, 2) yield strength, 3) creep resistance (low diffusion coefficient), 4) freezing range (weldability), and 5) material cost. The single performance function was suboptimal as assumptions had to be made about the results while formulating the optimization. A goal-oriented Bayesian optimization strategy (Hanaoka, 2021) was implemented with CALPHAD for use with the five metrics above. This multi-objective Bayesian optimization (MOBO) enabled the design of NiCrCoFe alloys with V and W additions. A base composition of NiCoCr was selected as Ni provides a stable FCC matrix, Cr aids corrosion/oxidation resistance, and Co is a solid-solutions strengthener that also improves creep by increasing the activation energy. Fe helps reduce diffusion coefficients and cost. Finally, V and W were selected for their reasonable solubility and high atomic misfit to aid in solid solution strengthening. Cracking of the mWAAM specimens was an early issue, and the Easton solidification cracking model (Easton et al., 2014a) was selected for addition to the MOBO function. High performing alloys fabricated by mWAAM included Ni 28 Cr 25 Co 26 Fe 15 V 8 and Ni 62 Cr 18 Co 1 Fe 3 W 15 . It was observed that even after adapting the mWAAM process for W, the W did not fully dissolve. To fully evaluate the Ni 62 Cr 18 Co 1 Fe 3 W 15 composition, a cored wire (80-20 NiCr sheath/powder core) was manufactured and printed via WAAM, and HIP’ing was utilized to homogenize and densify the printed alloy. The V and W alloys produced met metrics 1 (solid solution), 4 (solidification cracking), and 5 (cost). However, an unmodeled mechanism of thermal stress cracking was identified in the WAAM produced materials, perhaps exacerbated by the lack of grain boundary strengthening elements (B, C). Conclusions & Recommendations: A high-throughput (rapid) alloy design technique was applied to designing and manufacturing new high entropy alloys (HEAs) for extreme environments utilizing MOBO and mWAAM. The developed process was rapid and effective in addressing the mechanisms included in the model. The lack of grain boundary strengthening element additions (e.g., B, C) was a simplification that likely produced thermal stress cracking that turned into a large part of the investigation. Additions on the order of 0.005 wt% B and 0.05 wt% C likely would have minimized thermal stress grain boundary cracking. Overall, the high throughput design strategy is promising for rapid design of metrics-driven alloys for advanced ultra supercritical (A-USC) steam cycles for power generation. The MOBO and mWAAM process could be commercialized to accelerate metrics-driven alloy design. In addition, the cored-wire process utilized for scale-up is a promising high-volume process for WAAM alloy development and scale-up.

36 MATERIALS SCIENCE↗
NASA NTRSDate not supplied

Cleanroom Microbes Survive Drying, Vacuum, and Proton Irradiation

Introduction : The goal of planetary protection at NASA is to mitigate the risk of contaminating sensitive target bodies with biological life. While many cleaning procedures have been put in place to reduce bioburden on spacecraft, microbes are experts at evolving to survive harsh conditions. Specifically, the dry, low-nutrient environment of a cleanroom (commonly used for assembly of spacecraft) can represent an environment where extremophiles can survive. Methods : Scientists at NASA MSFC wished to gather a snapshot of the microbial population within a variety of cleanrooms on site. A study was undertaken to collect air, surface, and floor samples from clean-rooms and isolate unique morphologies. From this study, 95 isolates were collected and saved in a microbial library. About 86% of these were identified at least to a genus level. Following identification, 24 microbes were selected, based on a literature review, as potential extremophiles. These were grown in liquid cultures, diluted to a set optical density, washed with water, and then applied to a sterilized Kapton coupon. Droplets were allowed to dry overnight in a biosafety cabinet. Coupons were then installed in a pelletron and pumped down to high vacuum (~1E-6 Torr). Samples were then subjected 100 keV protons at a fluence of 2x10 15 p+/cm 2 up to 4x10 15 p+/cm 2 . Following exposure, samples were returned to the microbiology lab where they were pro-cessed by submerging in water, vortexing, and then plating either droplets or spread plates. Recovery data collected was qualitative with a ranking or +, minor, or – for growth. Some selected radiotolerant strains were sequenced using the Illumina sequencing platform. The resulting genomes were annotated with the Rapid Annotations using Subsystems Technology (RAST) server and analyzed for conserved and unique stress response relevant genomic signatures to identify clues related to specific tolerances. Results and Discussion : After five rounds of proton radiation, we narrowed our isolates to five, non-spore forming bacteria that demonstrated survival: Arthrobacter koreensis, Paenarthrobacter nitroguajacolicus, Mycetocola manganoxydans , and an Erwinia sp. Furthermore, we exposed these four microbes to 254 nm wavelength light at an intensity of 80 W/m 2 at a distance of ~18 cm for 10 minutes. Only A. koreensis demonstrated survival following UV exposure. Finally, we performed whole genome sequencing on the four strains to look for genetic markers of stress resistance. When we compared the genomes of the four strains, we found that genes coding for GGDEF and EAL domains with PAS/PAC sensors were only found in A. koreensis . These domains, modulated by PAS/PAC sensors, are hypothesized to facilitate survival under drying, desiccation, and proton irradiation. Drying and Desiccation : PAS domains sense hydration changes and modulate GGDEF and EAL domain activity to adjust c-di-GMP levels, enhancing resistance to desiccation. For instance, in Pseudomonas aeruginosa , the PAS domain of RbdA modulates activity under varying hydration conditions, affecting stress responses [1]. Proton Irradiation : Proton irradiation causes oxidative stress, leading to ROS generation. PAS domains detect this stress and modulate GGDEF and EAL domains to manage oxidative stress responses. In Shewanella , EAL domain proteins modulated by PAS sensors help bacteria adapt to extreme conditions [2]. These genes upregulate other stress response genes, protecting membrane function, protein stability, DNA repair, and antioxidant defenses. The modulation of c-di-GMP by PAS domains is crucial for bacterial adaptation to stress conditions, enabling dynamic physio-logical adjustments [3]. Understanding these mechanisms provides insights into bacterial stress responses and strategies for controlling bacterial growth [4]. Conclusions : These findings indicate that clean-rooms harbor extremophile microbes that may be able to survive conditions in deep space. Furthermore, while we identified certain stress-response genes that may be at least partly responsible for the phenotypes observed in this study, there are likely unidentified genes or characteristics about A. koreensis , and other bacteria, that may allow them to survive in harsh environments. Future studies will focus on identifying these unknown genes and characteristics, further elucidating the mechanisms of extremophile survival and potentially informing the development of new biotechnologies for space exploration and other extreme environments.

Chelsi Cassilly↗
NASA NTRS2001

EFQPSK Versus CERN: A Comparative Study

This report presents a comparative study on Enhanced Feher's Quadrature Phase Shift Keying (EFQPSK) and Constrained Envelope Root Nyquist (CERN) techniques. These two techniques have been developed in recent times to provide high spectral and power efficiencies under nonlinear amplifier environment. The purpose of this study is to gain insights into these techniques and to help system planners and designers with an appropriate set of guidelines for using these techniques. The comparative study presented in this report relies on effective simulation models and procedures. Therefore, a significant part of this report is devoted to understanding the mathematical and simulation models of the techniques and their set-up procedures. In particular, mathematical models of EFQPSK and CERN, effects of the sampling rate in discrete time signal representation, and modeling of nonlinear amplifiers and predistorters have been considered in detail. The results of this study show that both EFQPSK and CERN signals provide spectrally efficient communications compared to filtered conventional linear modulation techniques when a nonlinear power amplifier is used. However, there are important differences. The spectral efficiency of CERN signals, with a small amount of input backoff, is significantly better than that of EFQPSK signals if the nonlinear amplifier is an ideal clipper. However, to achieve such spectral efficiencies with a practical nonlinear amplifier, CERN processing requires a predistorter which effectively translates the amplifier's characteristics close to those of an ideal clipper. Thus, the spectral performance of CERN signals strongly depends on the predistorter. EFQPSK signals, on the other hand, do not need such predistorters since their spectra are almost unaffected by the nonlinear amplifier, Ibis report discusses several receiver structures for EFQPSK signals. It is observed that optimal receiver structures can be realized for both coded and uncoded EFQPSK signals with not too much increase in computational complexity. When a nonlinear amplifier is used, the bit error rate (BER) performance of the CERN signals with a matched filter receiver is found to be more than one decibel (dB) worse compared to the bit error performance of EFQPSK signals. Although channel coding is found to provide BER performance improvement for both EFQPSK and CERN signals, the performance of EFQPSK signals remains better than that of CERN. Optimal receiver structures for CERN signals with nonlinear equalization is left as a possible future work. Based on the numerical results, it is concluded that, in nonlinear channels, CERN processing leads towards better bandwidth efficiency with a compromise in power efficiency. Hence for bandwidth efficient communications needs, CERN is a good solution provided effective adaptive predistorters can be realized. On the other hand, EFQPSK signals provide a good power efficient solution with a compromise in band width efficiency.

Borah, Deva K.↗
NASA NTRSDate not supplied

Validation of Fitness for Duty Standards Using Pre- and Post-Flight Capsule Egress and Suited Functional Performance Tasks in Simulated Reduced Gravity

The transition between gravity environments will involve one of the most complex, high-risk phases of exploration missions. The reduced functional capacity caused by physiological deconditioning adaptations in microgravity coupled with the stressors of re-entry into partial gravity environments will increase risks to crew, even with rigorous adherence to inflight countermeasures. Specifically, two high-risk scenarios may be required to be performed soon after gravity transitions: 1) nominal and/or emergency unassisted capsule egress task after return to Earth, and 2) planetary extravehicular activity (EVA) soon after landing on Mars or the Moon. Quantification of crewmember’s functional performance after long-duration spaceflight is necessary to inform concepts of operations for future exploration missions. The overarching aim of this study is to quantify post-landing functional performance with deconditioning after long-duration ISS missions. This study is broken down into two phases. Phase 1 includes a pilot study to assess the overall feasibility and demonstrate the capability to perform mission-like tasks shortly after landing. Phase 2, the Egress Fitness study, which is part of the Complement of Integrated Protocols for Human Exploration Research (CIPHER), uses a task-based approach to characterize functional performance in long-duration ISS crewmembers before flight and shortly after return to Earth. The pilot and full Egress Fitness study includes pre-flight and post-flight testing of simulated emergency egress out of a functional capsule mockup and a Mars gravity EVA simulation at the Active Response Gravity Offload System (ARGOS) facility. The EVA simulation tasks include suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. The post-flight simulated capsule egress test occurs 1–4 h after landing and the planetary EVA simulation occurs 18–36 h after landing. The full CIPHER Egress Fitness study has additional pre-flight sessions, longer EVA tasks that include traverse and geology sampling, and post-flight sessions on R+1, 4, and 8 to characterize the timeframe of recovery. The Pilot Egress Fitness study has completed baseline and post-flight testing on four crewmembers. All subjects were able to complete the post-flight simulated planetary EVA; three subjects were able to complete the postflight capsule egress simulation. CIPHER study data collection is ongoing. This study will quantify post-landing functional performance in operationally relevant simulations to help inform future planetary concepts of operations shortly after landing.

egress↗
NASA NTRSDate not supplied

CIPHER: Egress Fitness

The transition between gravity environments will involve one of the most complex, high-risk phases of exploration missions. The reduced functional capacity caused by physiological deconditioning adaptations in microgravity coupled with the stressors of re-entry into partial gravity environments will increase risks to crew, even with rigorous adherence to inflight countermeasures. Specifically, two high-risk scenarios may be required to be performed soon after gravity transitions: 1) nominal and/or emergency unassisted capsule egress task after return to Earth, and 2) planetary extravehicular activity (EVA) soon after landing on Mars or the Moon. Quantification of crewmember’s functional performance after long-duration spaceflight is necessary to inform concepts of operations for future exploration missions. The overarching aim of this study is to quantify post-landing functional performance with deconditioning after long-duration ISS missions. This study is broken down into two phases. Phase 1 includes a pilot study to assess the overall feasibility and demonstrate the capability to perform mission-like tasks shortly after landing. Phase 2, the Egress Fitness study, which is part of the Complement of Integrated Protocols for Human Exploration Research (CIPHER), uses a task-based approach to characterize functional performance in long-duration ISS crewmembers before flight and shortly after return to Earth. The pilot and full Egress Fitness study includes pre-flight and post-flight testing of simulated emergency egress out of a functional capsule mockup and a Mars gravity EVA simulation at the Active Response Gravity Offload System (ARGOS) facility. The EVA simulation tasks include suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. The post-flight simulated capsule egress test occurs 1–4 h after landing and the planetary EVA simulation occurs 18–36 h after landing. The full CIPHER Egress Fitness study has additional pre-flight sessions, longer EVA tasks that include traverse and geology sampling, and post-flight sessions on R+1, 4, and 8 to characterize the timeframe of recovery. Pilot Egress Fitness has completed baseline and post-flight testing on four crewmembers. That study remains open. Originally this was to cover the Boeing CFT mission, but now also includes private astronauts on commercial spaceflights. CIPHER study data collection is ongoing with 2 subjects completed and 4 additional subjects consented. This study will quantify post-landing functional performance in operationally relevant simulations to help inform fitness for duty standards and future planetary concepts of operations shortly after landing.

Jason Norcross↗
NASA NTRSDate not supplied

Improving Efficacy and Safety of Pharmacological Treatment Through Precision Health and Pharmacogenomics

INTRODUCTION: Future spaceflight will require increased crew medical autonomy as exploration class missions expand in duration and distance from Earth, especially for Mars missions. As mission duration increases, it will be essential to have appropriate amounts of effective medication to ensure the maintenance of crew health and performance. Conversely, mass and volume constraints will become more severe as future spaceflight expands beyond low Earth orbit, where resupply is difficult or becomes impossible. These constraints thus convey an urgency to tailor medications for individual crewmembers and further examine appropriate dosing regimens. BACKGROUND: Precision Health is an exciting area of medicine focused on maintaining an individual’s health and performance through in-depth understanding of an individual’s unique clinical and environmental history, genetic makeup, and molecular profiles. This approach can be adapted to better predict, monitor, and address physiological responses to the spaceflight environment. A subset of this field is pharmacogenomics (PGX), the study of how the expressed genome impacts drug responses with the goal of prescribing the right dose of the right drug at the right time. Specifically, PGX testing provides valuable information on an individual’s precise allelic variations to guide physicians in making informed decisions on drug choice and dosing to avoid adverse events and maximize efficacy. The study goal was to identify which current space pharmacy drugs could be evaluated using PGX testing and to understand the potential impact on the health and wellness of the astronaut population. Additionally, we sought to evaluate clinically available FDA-approved PGX testing solutions to better understand its applicability. METHODS: A complete list of drugs on the ISS was analyzed for risk and likelihood of drug failure and PGX actionability. This analysis encompassed both astronauts’ personal medications, including supplements and over the counter drugs (n=151) contained in the ISS medical accessory kit (IMAK), and ISS MedKit formulary medications (n=95). Duplicate medications and different formulations were removed, which resulted in a total of 157 drugs used in the subsequent analysis. A 5x5 risk assessment table was produced by examining the likelihood of drug failure compared to the consequence of drug failure (LxC). Likelihood of individual drug failure was defined by whether existing processes are sufficient to prevent ineffective treatment or impactful side effect events, as ranked from 1 (very low, can easily be prevented) to 5 (very high, cannot be prevented) during a Mars mission. In contrast, the consequence of drug failure was defined by impact to safety, schedule, cost, or technical criteria and ranked from 1 (very low) to 5 (very high). An assessment of PGX reference laboratories is currently underway to evaluate sample requirements, benefit analysis (cost vs. utility of allele variant analysis), relevance to inflight medication usage, quality of reporting in enabling clinical application, and ease of integration into electronic medical records. RESULTS: Risk assessments (LxC 5x5 table) indicated 128 medications were in the green zone where risk is acceptable, with the remaining 29 of the medications in the yellow or red zone driven predominantly due to drug failure or safety concerns. We found that current PGX testing results could impact 21% of the total medications in the ISS MedKit and IMAK; of these, 9 medications currently have direct clinically actionable guidance available. Results of the clinical PGX solution evaluations as related to these medications will be presented. CONCLUSION: PGX testing has demonstrated clear benefits in terrestrial medicine and clinical environments for the selection of proper medications, avoiding adverse drug reactions, and maximizing drug efficacy. We propose that similar benefits would be bestowed on the astronaut and commercial spaceflight passenger population by performing preemptive preflight PGX testing to reduce risk of mission failure due to ineffective or toxic medications, improve drug efficacy, and further open the door to countermeasure research. For example, PGX results could allow tailoring of specific medications at optimal doses more precisely to each individual astronaut, particularly in areas of space motion sickness, sleep aids, and analgesics. An additional benefit is that PGX results could provide information for better planning of the components of a space pharmacy for deep space missions to be more effective and efficient in the utilization of limited pharmaceutical resources. Finally, while PGX testing of the astronaut corps is not currently conducted, this approach could provide immediate impact in support of mission success by reducing risks, optimizing astronaut performance, and providing valuable insights into long-term astronaut health. Such advancements in clinical decision making are important next steps in building dynamic individual risk profiles for astronauts, increasing selection of the best treatment choice, and providing tailored countermeasures for individual crewmembers.

Pharmacogenomics↗
NASA NTRSDate not supplied

Validation of Fitness for Duty Standards Using Pre- and Post-Flight Capsule Egress and Suited Functional Performance Tasks in Simulated Reduced Gravity

The transition between gravity environments will involve one of the most complex, high-risk phases of any mission. For example, the reduced functional capacity caused by physiological deconditioning adaptations in microgravity coupled with the stressors of re-entry into partial gravity environments will increase risks to crew, even with rigorous adherence to inflight countermeasures. Quantification of the astronauts’ post-landing functional performance is necessary to design ConOps for exploration missions. Specifically, these two high-risk scenarios may be required to be performed soon after gravity transitions: • Nominal and/or emergency unassisted capsule egress task after return to Earth • Planetary extravehicular activity (EVA) soon after landing on Mars or the Moon This study is broken down into two phases. Phase 1: A feasibility study that will assess the overall feasibility and demonstrate the capability to do these tasks shortly after landing. Phase 2: the full Egress Fitness study, which is part of the CIPHER complement. This study uses a task-based approach to characterize functional performance of these high-risk scenarios in long-duration ISS crewmembers before flight and shortly after return to Earth. Prior to any testing, each astronaut subject completes a suit fit check to ensure adequate sizing and a mobility assessment to confirm completion of the EVA tasks. Pilot Egress Fitness pre-flight and post-flight testing includes an Earth-based emergency egress out of a functional capsule mockup and a short Mars gravity EVA simulation including suit donning, hatch egress, ladder descent, task board cable operations, baggage transfer over sand/rocky regolith, alignment with a rear entry port, and suit egress. Pre-flight testing will occur at any time point prior to flight. Post-flight assessment is much more critical with the capsule egress test that will occur 1–4 hours after landing and the planetary EVA approximately 18–36 hours after landing. The CIPHER study will incorporate additional pre-flight sessions, longer EVA tasks that include traverse and geology sampling, and post-flight sessions on R+1, 4, and 8 to characterize the timeframe of recovery. Data collected for both tasks include task completion time, photo, and video. The EVA portion also includes collection of metabolic and heart rate. Pilot Egress Fitness study has completed both baseline and post-flight testing on four astronaut subjects, with all four able to complete post-flight EVA testing and three able to complete postflight capsule egress testing. Preliminary results observe individual physiological variations, which were to be expected but also suggest the need to carefully track the timeline from undock to landing to testing. Furthermore, some task performance instructions and equipment may need to be adjusted to ensure results are primarily physiological. These and other lessons learned will be addressed with minor protocol changes in the full CIPHER Egress Fitness study.

J R Norcross↗