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NASA NTRS2000

CNES-NASA Studies of the Mars Sample Return Orbiter Aerocapture Phase

A Mars Sample Return (MSR) mission has been proposed as a joint CNES (Centre National d'Etudes Spatiales) and NASA effort in the ongoing Mars Exploration Program. The MSR mission is designed to return the first samples of Martian soil to Earth. The primary elements of the mission are a lander, rover, ascent vehicle, orbiter, and an Earth entry vehicle. The Orbiter has been allocated only 2700 kg on the launch phase to perform its part of the mission. This mass restriction has led to the decision to use an aerocapture maneuver at Mars for the orbiter. Aerocapture replaces the initial propulsive capture maneuver with a single atmospheric pass. This atmospheric pass will result in the proper apoapsis, but a periapsis raise maneuver is required at the first apoapsis. The use of aerocapture reduces the total mass requirement by approx. 45% for the same payload. This mission will be the first to use the aerocapture technique. Because the spacecraft is flying through the atmosphere, guidance algorithms must be developed that will autonomously provide the proper commands to reach the desired orbit while not violating any of the design parameters (e.g. maximum deceleration, maximum heating rate, etc.). The guidance algorithm must be robust enough to account for uncertainties in delivery states, atmospheric conditions, mass properties, control system performance, and aerodynamics. To study this very critical phase of the mission, a joint CNES-NASA technical working group has been formed. This group is composed of atmospheric trajectory specialists from CNES, NASA Langley Research Center and NASA Johnson Space Center. This working group is tasked with developing and testing guidance algorithms, as well as cross-validating CNES and NASA flight simulators for the Mars atmospheric entry phase of this mission. The final result will be a recommendation to CNES on the algorithm to use, and an evaluation of the flight risks associated with the algorithm. This paper will describe the aerocapture phase of the MSR mission, the main principles of the guidance algorithms that are under development, the atmospheric entry simulators developed for the evaluations, the process for the evaluations, and preliminary results from the evaluations.

Fraysse, H.↗

NASA NTRS2014

A Novel Method for Characterizing Spacesuit Mobility through Metabolic Cost

Spacesuit mobility has historically been defined and characterized by a combination of range of motion and joint torque of the individual anatomical joints when performing isolated motions meant to drive that joint only in a given orthogonal plane. While this has been the standard approach for several decades, there are numerous shortcomings that suit designers and engineers would like to see rectified. First, the lack of a standardized method for collecting both range of motion and joint torque translates to many different test setups, procedures and methods of data analysis. Second, all of these previously used methods for data collection lack some degree of repeatability, even within the same test setup and the same conductor; in addition, attempts at higher fidelity data collection techniques require high overhead and cost with minimal improvement. Lastly, isolated motions in standard anatomical planes are not representative of real‐world tasks that a crewmember would be performing during an EVA, be it microgravity or surface exploration based. To address these shortcomings, options are being explored within the Space Suit and Crew Survival Systems Branch to ascertain the feasibility of an alternative approach to defining mobility - one that is more repeatable, lower overhead, and more tied to functional EVA tasks. This paper serves to document the first attempt at such an alternative option - one that looks at the metabolic energy‐cost of a spacesuit. In other words, can we objectively compare the mobility of a spacesuit by evaluating the metabolic cost of that suit to the wearer while performing a battery of functional EVA tasks?

McFarland, Shane↗

DOE OSTI2014

Dual-energy cone-beam CT with a flat-panel detector: Effect of reconstruction algorithm on material classification

Purpose: Cone-beam CT (CBCT) with a flat-panel detector (FPD) is finding application in areas such as breast and musculoskeletal imaging, where dual-energy (DE) capabilities offer potential benefit. The authors investigate the accuracy of material classification in DE CBCT using filtered backprojection (FBP) and penalized likelihood (PL) reconstruction and optimize contrast-enhanced DE CBCT of the joints as a function of dose, material concentration, and detail size. Methods: Phantoms consisting of a 15 cm diameter water cylinder with solid calcium inserts (50–200 mg/ml, 3–28.4 mm diameter) and solid iodine inserts (2–10 mg/ml, 3–28.4 mm diameter), as well as a cadaveric knee with intra-articular injection of iodine were imaged on a CBCT bench with a Varian 4343 FPD. The low energy (LE) beam was 70 kVp (+0.2 mm Cu), and the high energy (HE) beam was 120 kVp (+0.2 mm Cu, +0.5 mm Ag). Total dose (LE+HE) was varied from 3.1 to 15.6 mGy with equal dose allocation. Image-based DE classification involved a nearest distance classifier in the space of LE versus HE attenuation values. Recognizing the differences in noise between LE and HE beams, the LE and HE data were differentially filtered (in FBP) or regularized (in PL). Both a quadratic (PLQ) and a total-variation penalty (PLTV) were investigated for PL. The performance of DE CBCT material discrimination was quantified in terms of voxelwise specificity, sensitivity, and accuracy. Results: Noise in the HE image was primarily responsible for classification errors within the contrast inserts, whereas noise in the LE image mainly influenced classification in the surrounding water. For inserts of diameter 28.4 mm, DE CBCT reconstructions were optimized to maximize the total combined accuracy across the range of calcium and iodine concentrations, yielding values of ∼88% for FBP and PLQ, and ∼95% for PLTV at 3.1 mGy total dose, increasing to ∼95% for FBP and PLQ, and ∼98% for PLTV at 15.6 mGy total dose. For a fixed iodine concentration of 5 mg/ml and reconstructions maximizing overall accuracy across the range of insert diameters, the minimum diameter classified with accuracy >80% was ∼15 mm for FBP and PLQ and ∼10 mm for PLTV, improving to ∼7 mm for FBP and PLQ and ∼3 mm for PLTV at 15.6 mGy. The results indicate similar performance for FBP and PLQ and showed improved classification accuracy with edge-preserving PLTV. A slight preference for increased smoothing of the HE data was found. DE CBCT discrimination of iodine and bone in the knee was demonstrated with FBP and PLTV at 6.2 mGy total dose. Conclusions: For iodine concentrations >5 mg/ml and detail size ∼20 mm, material classification accuracy of >90% was achieved in DE CBCT with both FBP and PL at total doses <10 mGy. Optimal performance was attained by selection of reconstruction parameters based on the differences in noise between HE and LE data, typically favoring stronger smoothing of the HE data, and by using penalties matched to the imaging task (e.g., edge-preserving PLTV in areas of uniform enhancement)

62 RADIOLOGY AND NUCLEAR MEDICINE↗

NASA NTRS1992

The Enabler: A concept for a lunar work vehicle

The Enabler is an earthbound prototype designed to model an actual lunar work vehicle and is able to perform many of the tasks that might be expected of a lunar work vehicle. The vehicle will be constructed entirely from parts made by students and from standard stock parts. The design utilizes only four distinct chassis pieces and sixteen moving parts. The Enabler has non-orthogonal articulating joints that give the vehicle a wide range of mobility and reduce the total number of parts. Composite wheels provide the primary suspension system for the vehicle.

Brazell, James W.↗

NASA NTRS1999

Interoperability Trends in Extravehicular Activity (EVA) Space Operations for the 21st Century

No other space operations in the 21 st century more comprehensively embody the challenges and dependencies of interoperability than EVA. This discipline is already functioning at an W1paralleled level of interagency, inter-organizational and international cooperation. This trend will only increase as space programs endeavor to expand in the face of shrinking budgets. Among the topics examined in this paper are hardware-oriented issues. Differences in design standards among various space participants dictate differences in the EVA tools that must be manufactured, flown and maintained on-orbit. Presently only two types of functional space suits exist in the world. However, three versions of functional airlocks are in operation. Of the three airlocks, only the International Space Station (ISS) Joint Airlock can accommodate both types of suits. Due to functional differences in the suits, completely different operating protocols are required for each. Should additional space suit or airlock designs become available, the complexity will increase. The lessons learned as a result of designing and operating within such a system are explored. This paper also examines the non-hardware challenges presented by interoperability for a discipline that is as uniquely dependent upon the individual as EVA. Operation of space suits (essentially single-person spacecrafts) by persons whose native language is not that of the suits' designers is explored. The intricacies of shared mission planning, shared control and shared execution of joint EVA's are explained. For example, once ISS is fully functional, the potential exists for two crewmembers of different nationality to be wearing suits manufactured and controlled by a third nation, while operating within an airlock manufactured and controlled by a fourth nation, in an effort to perform tasks upon hardware belonging to a fifth nation. Everything from training issues, to procedures development and writing, to real-time operations is addressed. Finally, this paper looks to the management challenges presented by interoperability in general. With budgets being reduced among all space-faring nations, the need to expand cooperation in the highly expensive field of human space operations is only going to intensify. The question facing management is not if the trend toward interoperation will continue, but how to best facilitate its doing so. Real-world EVA interoperability experience throughout the ShuttlelMir and ISS Programs is discussed to illustrate the challenges and

Miller, Gerald E.↗

DOE OSTI2024

Evaluation Of Elbow Exoskeleton in Glovebox Operations To Minimize Injuries – 25704

In nuclear facilities across the DOE, ergonomic injuries pose a significant occupational hazard for GB workers. Recent studies at Los Alamos National Laboratory (LANL) have revealed concerning trends in worker health, with approximately 50% of GB workers reporting musculoskeletal symptoms after 25 years of service [1]. The current GB design, largely unchanged since the 1960s, presents several ergonomic challenges including inappropriate finger lengths, nonexistent joint angles, and incorrect thumb placement. These design flaws directly contribute to conditions such as lateral epicondylitis (tennis elbow) and De Quervain's tenosynovitis which causes pain and inflammation in the tendons at the base of the thumb. These are examples of conditions caused by workers performing repetitive precision tasks [2].

Ramon, Rodrigo N. [Savannah River National Laborat↗

NASA NTRS2006

Development of a Countermeasure to Mitigate Postflight Locomotor Dysfunction

Astronauts returning from space flight experience locomotor dysfunction following their return to Earth. Our laboratory is currently developing a gait adaptability training program that is designed to facilitate recovery of locomotor function following a return to a gravitational environment. The training program exploits the ability of the sensorimotor system to generalize from exposure to multiple adaptive challenges during training so that the gait control system essentially learns to learn and therefore can reorganize more rapidly when faced with a novel adaptive challenge. Evidence for the potential efficacy of an adaptive generalization gait training program can be obtained from numerous studies in the motor learning literature which have demonstrated that systematically varying the conditions of training enhances the ability of the performer to learn and retain a novel motor task. These variable practice training approaches have been used in applied contexts to improve motor skills required in a number of different sports. The central nervous system (CNS) can produce voluntary movement in an almost infinite number of ways. For example, locomotion can be achieved with many different combinations of joint angles, muscle activation patterns and forces. The CNS can exploit these degrees of freedom to enhance motor response adaptability during periods of adaptive flux like that encountered during a change in gravitational environment. Ultimately, the functional goal of an adaptive generalization countermeasure is not necessarily to immediately return movement patterns back to normal. Rather the training regimen should facilitate the reorganization of available sensory and motor subsystems to achieve safe and effective locomotion as soon as possible after long duration space flight. Indeed, this approach has been proposed as a basic feature underlying effective neurological rehabilitation. We have previously confirmed that subjects participating in an adaptive generalization training program using a variety of visuomotor distortions and throwing as the dependent measure can learn to enhance their ability to adapt to a novel sensorimotor environment (Roller et al., 2001). Importantly, this increased adaptability was retained even one month after completion of the training period. Adaptive generalization has been observed in a variety of other tasks requiring sensorimotor transformations including manual control tasks and reaching (Bock et al., 2001, Seidler, 2003) and obstacle avoidance during walking (Lam and Dietz, 2004). Taken together, the evidence suggests that a training regimen exposing crewmembers to variation in locomotor conditions, with repeated transitions among states, may enhance their ability to learn how to reassemble appropriate locomotor patterns upon return from microgravity. We believe exposure to this type of training will extend crewmembers locomotor behavioral repertoires, facilitating the return of functional mobility after long duration space flight. In other words, our proposed training protocol will compel subjects to develop new behavioral solutions under varying sensorimotor demands. Over time subjects will learn to create appropriate locomotor solution more rapidly enabling acquisition of mobility sooner after long-duration space flight. A gait adaptability training program can be superimposed on nominal treadmill exercise activities thus ensuring that no additional crew time is required to perform this type of training regimen and that it can be implemented with current in-flight exercise systems available on the International Space Station.

Bloomberg, J. J.↗

DOE OSTI2025

Collaborative: in situ visual analytics technologies for extreme scale combustion simulations

This project aims to drastically enhance the usability of in situ analysis and visualization for extreme-scale scientific simulations. Current exascale computing capabilities promise to offer greater predictive ability of simulations and to further push the frontiers of science and technology. However, to validate the simulation output at extreme scale, examine the modeled phenomena, and discover previously unknowns from the output data, the output must be reduced or transformed in situ as it is being generated during the simulation such that the amount of data to examine and store is kept to a minimum. Such in situ approaches allow us to process and analyze the data and any embedded geometry to an extent that would be prohibitively expensive, if not impossible, to perform as a post hoc task. While in situ processing has been demonstrated to be a feasible and promising approach, its full potential has not yet been leveraged. In this project, we have developed comprehensive enhancements to in situ technology based on probability distributions in data. Our research focuses on jointly developing new ways of interacting with massive statistical samples while creatively utilizing new state-of-the-art computational resources to push the boundaries of in situ exploration. Moreover, we have developed new time-dependent techniques to enable previously unattainable capabilities in areas such as intelligent simulation steering and precise feature identification. We have experimentally studied our design and implementation at NERSC and OLCF, and are able to leverage existing in situ infrastructures whenever possible. While the exemplar in this project is combustion, many other fields for which turbulent transport is important, e.g., fusion, climate, astrophysics among others, encounter similar issues as simulations scale up to the exascale. This project shows its potential to generate high impact on DOE missions since the resulting technology promises to improve scientists’ ability to rapidly and correctly interpret and tune extreme-scale simulations, leading to new scientific understanding and advancements.

97 MATHEMATICS AND COMPUTING↗

NASA NTRS2008

Functional Mobility Testing: A Novel Method to Create Suit Design Requirements

This study was performed to aide in the creation of design requirements for the next generation of space suits that more accurately describe the level of mobility necessary for a suited crewmember through the use of an innovative methodology utilizing functional mobility. A novel method was utilized involving the collection of kinematic data while 20 subjects (10 male, 10 female) performed pertinent functional tasks that will be required of a suited crewmember during various phases of a lunar mission. These tasks were selected based on relevance and criticality from a larger list of tasks that may be carried out by the crew. Kinematic data was processed through Vicon BodyBuilder software to calculate joint angles for the ankle, knee, hip, torso, shoulder, elbow, and wrist. Maximum functional mobility was consistently lower than maximum isolated mobility. This study suggests that conventional methods for establishing design requirements for human-systems interfaces based on maximal isolated joint capabilities may overestimate the required mobility. Additionally, this method provides a valuable means of evaluating systems created from these requirements by comparing the mobility available in a new spacesuit, or the mobility required to use a new piece of hardware, to this newly established database of functional mobility.

England, Scott A.↗

DOE OSTI2013

IDHEAS – A NEW APPROACH FOR HUMAN RELIABILITY ANALYSIS

This paper describes a method, IDHEAS (Integrated Decision-Tree Human Event Analysis System) that has been developed jointly by the US NRC and EPRI as an improved approach to Human Reliability Analysis (HRA) that is based on an understanding of the cognitive mechanisms and performance influencing factors (PIFs) that affect operator responses. The paper describes the various elements of the method, namely the performance of a detailed cognitive task analysis that is documented in a crew response tree (CRT), and the development of the associated time-line to identify the critical tasks, i.e. those whose failure results in a human failure event (HFE), and an approach to quantification that is based on explanations of why the HFE might occur.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2026

HydraGNN_Predictive_GFM_2026 - Ensemble of predictive graph foundation models for atomistic materials modeling

This release contains data and parameters of HydraGNN-based graph foundation models trained as a result of the work published in the pre-print "Exascale Multi-Task Graph Foundation Models for Imbalanced, Multi-Fidelity Atomistic Data" by M. Lupo Pasini et al. (https://arxiv.org/abs/2604.15380). We jointly train on 16 open first-principles datasets (544+ million structures covering 85+ elements) using a multi-task architecture with per-dataset heads and a scalable ADIOS2/DDStore data pipeline. On Frontier, we execute six large-scale DeepHyper hyperparameter optimization campaigns in FP64 and promote the top-performing message-passing models to sustained 2,048-node training, yielding a PaiNN-based lead model. The version of HydraGNN used to generate the outputs provided in this release is HydraGNN v5.0 (https://github.com/ORNL/HydraGNN/releases/tag/v5.0) The list of datasets used for the training of the graph foundation model is the following: 1) Alexandria [1] 2) ANI1x [2] 3) MPTrj [3] 4) Open Catalyst 2020 (OC20) [4] 5) Open Catalyst 2022 (OC22) [5] 6) Open Catalyst 2025 (OC25) [6] 7) Open Direct ir Capture 2023 (ODAC23) [7] 8) Open Materials 2024 (OMat24) [8] 9) Open Molecules 2025 (OMol25) [9] 10) OMol25-neutral (subset of OMol25 that contains only molecules with zero total charge) 11) OMol25-non-neutral (subset of OMol25 that contains only molecules with non-zero total charge) 12) Open Polymers 2026 (OPoly2026) [10] 13) Nabla2DFT [11] 14) QCML [12] 15) QM7X [reference 13] 16) transition1x [14] Dataset references: [1] J. Schmidt et al., “A dataset of 175k stable and metastable materials calculated with the PBEsol and SCAN functionals,” Scientific Data, vol. 9, p. 64, 2022. [2] J. S. Smith et al., “The ANI-1ccx and ANI-1x data sets, coupled-cluster and density functional theory properties for molecules,” Scientific Data, vol. 7, p. 134, 2020. [Online]. Available: https: //www.nature.com/articles/s41597-020-0473-z [3] A. Jain et al., “Commentary: The Materials Project: A materials genome approach to accelerating materials innovation,” APL Materials, vol. 1, no. 1, p. 011002, 07 2013. [Online]. Available: https://doi.org/10.1063/1.4812323 [4] L. Chanussot et al., “Open catalyst 2020 (oc20) dataset and community challenges,” ACS Catalysis, vol. 11, no. 10, pp. 6059–6072, 2021. [Online]. Available: https://doi.org/10.1021/acscatal.0c04525 [5] K. Tran et al., “Open catalyst 2022 (oc22) dataset and challenges for oxidation electrocatalysts,” ACS Catalysis, vol. 13, no. 5, pp. 3066–3084, 2023. [Online]. Available: https://doi.org/10.1021/acscatal.2c05426 [6] S. J. Sahoo et al., “The open catalyst 2025 (oc25) dataset and models for solid-liquid interfaces,” arXiv preprint arXiv:2509.17862, 2025. [Online]. Available: https://arxiv.org/abs/2509.17862 [7] A. Sriram et al., “The open DAC 2023 dataset and challenges for sorbent discovery in direct air capture,” ACS Central Science, vol. 10, no. 5, pp. 923–941, 2024. [8] L. Barroso-Luque et al., “Open materials 2024 (omat24) inorganic materials dataset and models,” 2024. [Online]. Available: https://arxiv.org/abs/2410.12771 [9] D. S. Levine et al., “The open molecules 2025 (OMol25) dataset, evaluations, and models,” 2025. [Online]. Available: https://arxiv.org/abs/2505.08762 [10] D. S. Levine et al., The open polymers 2026 (OPoly26) dataset and evaluations,” arXiv preprint arXiv:2512.23117, 2025. [Online]. Available: https://arxiv.org/abs/2512.23117 [11] K. Khrabrov et al., “Nabla2dft: A universal quantum chemistry dataset of drug-like molecules and a benchmark for neural network potentials,” in NeurIPS 2024 Datasets and Benchmarks Track, 2024. [Online]. Available: https://openreview.net/forum?id=ElUrNM9U8c [12] S. Ganscha et al., “The QCML dataset, quantum chemistry reference data from 33.5M DFT and 14.7B semi-empirical calculations,” Scientific Data, vol. 12, p. 406, 2025. [13] J. Hoja et al., “QM7-X, a comprehensive dataset of quantum-mechanical properties spanning the chemical space of small organic molecules,” Scientific Data, vol. 8, p. 43, 2021. [Online]. Available: https://www.nature.com/articles/s41597-021-00812-2 [14] M. Schreiner et al., “Transition1x - a dataset for building generalizable reactive machine learning potentials,” Scientific Data, vol. 9, p. 779, 2022. The folder "datasets_ADIOS2_format" contains the set of pre-processed datasets in Adaptable I/O System (ADIOS) format (https://www.exascaleproject.org/research-project/adios/) that have been used for the development and training of GFMs in this work. The "datasets_ADIOS2_format" directory contains 2 sub-directories, one for the version "v1" of the datasets and one for the version "v2" of the datasets. The version "v1" of the datasets provides values of the total energy as they are extracted from the original data as it was released by the respective institutions. The version "v2" of the datasets provides values of the energy that have been realigned. The realignment was performed by training a linear regression model that predicts the total energy as a function of the chemical composition of the atomistic structure, and then subtract such prediction from the original value of the total energy. Both folders "v1" and "v2" contain 16 sub-directories, each corresponding to an ADIOS2-formatted dataset The folder "DeepHyper-results" contains the configurational files and model's parameters for all the 186 HPO trials that were successfully completed by the scalable hyperparameter optimization (HPO) runs on Frontier. The content of the folder "DeepHyper-results" I structured as follows: 1) task-list.txt: list of mpnn name, jobid, and deephyper task id 2) gfm_${MPNN}_${JOBID}_0.${TASKID}: run directory with checkpoint files 3) gfm_${MPNN}: deephyper summary directory (*.csv) for each specific MPNN type 4) deephyper-experiment-${JOBID}: output and error logs for each job The file "deephyper-sorted.csv" contains the details of each HydraGNN model built and tested by HPO, obtained by merging the (*.csv) filed from each HPO run executed. Out of all the HPO trials, we selected 10 to continue the training of the respective HydraGNN models. Due to limited computational budget available in the LRN070 allocation we could not complete the training till convergence for all these 10 selected models. The folder "models" contains multiple sub-folders, one per each HydraGNN model trained. Each model sub-folder contains the parameters of each HydraGNN model, with multiple checkpoint-restarts. The list of sub-folders are as follows: 1) multidataset_hpo-BEST1-fp64 2) multidataset_hpo-BEST2-fp64 3) multidataset_hpo-BEST3-fp64 4) multidataset_hpo-BEST4-fp64 5) multidataset_hpo-BEST5-fp64 6) multidataset_hpo-BEST6-fp64 7) multidataset_hpo-BEST7-fp64 8) multidataset_hpo-BEST8-fp64 9) multidataset_hpo-BEST9-fp64 10) multidataset_hpo-BEST10-fp64 Within each one of these folders, additional auxiliary log files are provided with descriptions about how the training proceeded. The lead PaiNN-model is contained inside "multidataset_hpo-BEST6-fp64". The file "mlp_branch_weights" contains the parameters of the multi-layer perceptron (MLP) used to reconcile the predictions of the 16 output decoding heads of the HydragNN architectures. The MLP takes in input the chemical composition of the atomistic structure and predicts averaging weights to linearly mix the predictions of each output decoding head toward consolidating them into a single one. The folder "1.1billion-structure-inference" contains 1.1 billion atomistic structures randomly generated. Each structures is associated with energy and forces predicted with the lead-PaiNN model combined with the MLP model for reconciliation of the multi-branch predictions generated by the 16 output decoding heads. The folder "1.1billion-structure-inference" contains 9,300 (*.tar.gz) subdirectories, one per Frontier compute node used to execute the inference at exascale. Once uncompressed, each (*.tar.gz) subdirectory contains an ADIOS2 (*.bp) file container, where each atomistic structure is stored as a PyTorch-Geometric Data object. The file "export_dataset_environment_variables.sh" contains the environment variables that need to be set before running the HydraGNN code to reproduce the results provided in this dataset release. The code that can be used to load the ADIOS2 files, load HydraGNN models, and run inference is available at: https://github.com/ORNL/HydraGNN/releases/tag/v5.0

36 MATERIALS SCIENCE↗

NASA NTRS1990

TEJAS

The Telerobotics/EVA Joint Analysis System (TEJAS) is a hypermedia information system that provides a clear, consistent, repeatable, interactive, and exchangeable multilevel mechanism for telerobotics technology development planning, based on a realistic understanding of the following: (1) Task description, assumptions, and open issues; (2) Specific task primitives (derived from generic primitives); (3) Technologies required to perform on-orbit telerobotics; (4) Planned telerobotics systems' use of those technologies; and (5) Forecast for each technology in terms of time and money. TEJAS was created in HyperCard on a Macintosh 2 personal workstation, with HyperTalk scripts providing action and relational capability. Version 1.0, consisting of more than a dozen interrelated files, will be released in Jan. 1990.

Drews, Michael↗

NASA NTRS2010

Motion Perception and Manual Control Performance During Passive Tilt and Translation Following Space Flight

This joint ESA-NASA study is examining changes in motion perception following Space Shuttle flights and the operational implications of post-flight tilt-translation ambiguity for manual control performance. Vibrotactile feedback of tilt orientation is also being evaluated as a countermeasure to improve performance during a closed-loop nulling task. METHODS. Data has been collected on 5 astronaut subjects during 3 preflight sessions and during the first 8 days after Shuttle landings. Variable radius centrifugation (216 deg/s) combined with body translation (12-22 cm, peak-to-peak) is utilized to elicit roll-tilt perception (equivalent to 20 deg, peak-to-peak). A forward-backward moving sled (24-390 cm, peak-to-peak) with or without chair tilting in pitch is utilized to elicit pitch tilt perception (equivalent to 20 deg, peak-to-peak). These combinations are elicited at 0.15, 0.3, and 0.6 Hz for evaluating the effect of motion frequency on tilt-translation ambiguity. In both devices, a closed-loop nulling task is also performed during pseudorandom motion with and without vibrotactile feedback of tilt. All tests are performed in complete darkness. PRELIMINARY RESULTS. Data collection is currently ongoing. Results to date suggest there is a trend for translation motion perception to be increased at the low and medium frequencies on landing day compared to pre-flight. Manual control performance is improved with vibrotactile feedback. DISCUSSION. The results of this study indicate that post-flight recovery of motion perception and manual control performance is complete within 8 days following short-duration space missions. Vibrotactile feedback of tilt improves manual control performance both before and after flight.

Clement, Gilles↗

NASA NTRSDate not supplied

Development of an Inertial Sensor-based Methodology for Spacesuited Geology Task Assessments during Simulated Lunar Extravehicular Activities

Lunar surface exploration during Artemis missions will require the specific skill set of geology sampling. Apollo astronauts had extensive training and used specialized tools to collect lunar rocks, core samples, pebbles, sand, and dust. The inflexibility of the pressurized Apollo spacesuits forced sampling to be taken at a standstill posture. However, new exploration spacesuits are expected to incorporate advanced materials and joint bearings, allowing for greater mobility and a wider range of functional postures. Thus, science and exploration during Artemis missions will likely involve a variety of standing, squatting, and kneeling postures. In preparation for future lunar exploration missions, NASA provides geologic training to astronauts and other mission personnel. This professional training with a spacesuit in simulated lunar environments will enhance performance and reduce risk of injury to astronauts on the lunar surface. However, anecdotally, untrained or newly trained people wearing prototype planetary spacesuits have been observed to performing motions differently than a trained geologist would when conducting the same geology sampling tasks. Therefore, a tool for evaluating geology postures at extravehicular activity (EVA) training facilities becomes required. In this paper, we introduce a novel inertial measurement unit (IMU)-based method of geology task assessments in spacesuited conditions during simulated lunar EVAs. As a case study, two subjects (one geologist and one non-geologist) participated and donned the Mark III prototype planetary spacesuit during offloading with the spreader bar gimbal in NASA’s Active Response Gravity Offload System (ARGOS). For automated geology task assessments, the spacesuit was instrumented with three wireless IMUs (APDM Opal, OR, USA): one on the chest and one each on the left and right ankle bearings. Then subjects performed geology tasks using various tools (rake, trench, hammer chisel, scoop, and drive tube) for 45 minutes each. The chest IMU measured the torso tilt angle in the sagittal plane. We used an ensemble learning method with the ankle IMUs to discriminate between standing and kneeling activities. IMU data were processed using custom MATLAB (Mathworks, MA, USA) software. In our case study, the developed method was able to discriminate differences in standing and kneeling activity levels between subjects who were all highly experienced with spacesuited testing. Our preliminary data showed one subject maintained the constant and lower range of the upper body tilt angle while both standing and kneeling, while the other subject showed more variation of the upper body tilt angle and preferred bending the upper body rather than changing from standing to kneeling posture and vice versa. While geology experience may be a factor, these results need further investigation as suit sizing and ARGOS offloading configurations have been proven to have a significant influence on suited ARGOS tasks. Also, more subjects will be needed to complete these tasks for validation. IMU-based geology task assessments can provide useful information for geology training programs. Additionally, our IMU-based posture analysis can provide new insights into how to evaluate spacesuited geology task characteristics of astronauts during simulated lunar EVAs.

Kyoung Jae Kim↗

DOE OSTI2021

International collaboration in disposal research: comparative modeling of coupled processes in the DECOVALEX project

Abstract. This presentation gives an overview of an international research collaboration for advancing the understanding and modeling of coupled thermo-hydro-mechanical-chemical (THMC) processes in geological systems. The creation of the international DECOVALEX project, now running for more than 25 years, was motivated by the recognition that prediction of these coupled effects is an essential part of the performance and safety assessment of geologic disposal systems for radioactive waste and spent nuclear fuel. DECOVALEX emphasizes joint analysis and comparative modeling of state-of-the-art field and laboratory experiments, across a range of host rock options and repository designs. Participating research teams are from radioactive waste management organizations, national research institutes, regulatory agencies, universities, and consulting groups, providing a wide range of perspectives and solutions to these complex problems. The presentation provides examples of the research contributions made collectively in past DECOVALEX tasks and also touches on the unique modeling challenges tackled in the ongoing project phase, referred to as DECOVALEX-2023. The current phase comprises 17 partner organizations, about 50 modeling teams, and 7 modeling tasks, which cover a broad portfolio from fundamental studies on gas migration to full-scale in situ heater experiments in different host rocks to performance assessment studies. Together, these examples illustrate that the insight and scientific knowledge gained within the DECOVALEX project would not have been possible if one group had studied these complex THMC modeling challenges alone rather than within a truly collaborative setting.

Birkholzer, Jens T.↗

DOE OSTI2016

MO-AB-206-00: Nuclear Medicine Physics and Testing

This education session will cover the physics and operation principles of gamma cameras and PET scanners. The first talk will focus on PET imaging. An overview of the principles of PET imaging will be provided, including positron decay physics, and the transition from 2D to 3D imaging. More recent advances in hardware and software will be discussed, such as time-of-flight imaging, and improvements in reconstruction algorithms that provide for options such as depth-of-interaction corrections. Quantitative applications of PET will be discussed, as well as the requirements for doing accurate quantitation. Relevant performance tests will also be described. Learning Objectives: Be able to describe basic physics principles of PET and operation of PET scanners. Learn about recent advances in PET scanner hardware technology. Be able to describe advances in reconstruction techniques and improvements Be able to list relevant performance tests. The second talk will focus on gamma cameras. The Nuclear Medicine subcommittee has charged a task group (TG177) to develop a report on the current state of physics testing of gamma cameras, SPECT, and SPECT/CT systems. The report makes recommendations for performance tests to be done for routine quality assurance, annual physics testing, and acceptance tests, and identifies those needed satisfy the ACR accreditation program and The Joint Commission imaging standards. The report is also intended to be used as a manual with detailed instructions on how to perform tests under widely varying conditions. Learning Objectives: At the end of the presentation members of the audience will: Be familiar with the tests recommended for routine quality assurance, annual physics testing, and acceptance tests of gamma cameras for planar imaging. Be familiar with the tests recommended for routine quality assurance, annual physics testing, and acceptance tests of SPECT systems. Be familiar with the tests of a SPECT/CT system that include the CT images for SPECT reconstructions. Become knowledgeable of items to be included in annual acceptance testing reports including CT dosimetry and PACS monitor measurements. T. Turkington, GE Healthcare.

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2016

MO-AB-206-01: PET Physics

61 RADIATION PROTECTION AND DOSIMETRY↗

DOE OSTI2016

MO-AB-206-02: Testing Gamma Cameras Based On TG177 WG Report

61 RADIATION PROTECTION AND DOSIMETRY↗