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NASA NTRS2005

Forecasting Lightning at Kennedy Space Center/Cape Canaveral Air Force Station, Florida

The Applied Meteorology Unit (AMU) developed a set of statistical forecast equations that provide a probability of lightning occurrence on Kennedy Space Center (KSC) I Cape Canaveral Air Force Station (CCAFS) for the day during the warm season (May September). The 45th Weather Squadron (45 WS) forecasters at CCAFS in Florida include a probability of lightning occurrence in their daily 24-hour and weekly planning forecasts, which are briefed at 1100 UTC (0700 EDT). This information is used for general scheduling of operations at CCAFS and KSC. Forecasters at the Spaceflight Meteorology Group also make thunderstorm forecasts for the KSC/CCAFS area during Shuttle flight operations. Much of the current lightning probability forecast at both groups is based on a subjective analysis of model and observational data. The objective tool currently available is the Neumann-Pfeffer Thunderstorm Index (NPTI, Neumann 1971), developed specifically for the KSCICCAFS area over 30 years ago. However, recent studies have shown that 1-day persistence provides a better forecast than the NPTI, indicating that the NPTI needed to be upgraded or replaced. Because they require a tool that provides a reliable estimate of the daily thunderstorm probability forecast, the 45 WS forecasters requested that the AMU develop a new lightning probability forecast tool using recent data and more sophisticated techniques now possible through more computing power than that available over 30 years ago. The equation development incorporated results from two research projects that investigated causes of lightning occurrence near KSCICCAFS and over the Florida peninsula. One proved that logistic regression outperformed the linear regression method used in NPTI, even when the same predictors were used. The other study found relationships between large scale flow regimes and spatial lightning distributions over Florida. Lightning, probabilities based on these flow regimes were used as candidate predictors in the equation development. Fifteen years (1 989-2003) of warm season data were used to develop the forecast equations. The data sources included a local network of cloud-to-ground lightning sensors called the Cloud-to-Ground Lightning Surveillance System (CGLSS), 1200 UTC Florida synoptic soundings, and the 1000 UTC CCAFS sounding. Data from CGLSS were used to determine lightning occurrence for each day. The 1200 UTC soundings were used to calculate the synoptic-scale flow regimes and the 1000 UTC soundings were used to calculate local stability parameters, which were used as candidate predictors of lightning occurrence. Five logistic regression forecast equations were created through careful selection and elimination of the candidate predictors. The resulting equations contain five to six predictors each. Results from four performance tests indicated that the equations showed an increase in skill over several standard forecasting methods, good reliability, an ability to distinguish between non-lightning and lightning days, and good accuracy measures and skill scores. Given the overall good performance the 45 WS requested that the equations be transitioned to operations and added to the current set of tools used to determine the daily lightning probability of occurrence.

Lambert, Winfred↗

NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.

Artificial Intelligence↗

NASA NTRSDate not supplied

BRAINSTACK – A Platform for Artificial Intelligence & Machine Learning Collaborative Experiments on a Nano-Satellite

Artificial Intelligence↗

NASA NTRS1989

Ames life science telescience testbed evaluation

Eight surrogate spaceflight mission specialists participated in a real-time evaluation of remote coaching using the Ames Life Science Telescience Testbed facility. This facility consisted of three remotely located nodes: (1) a prototype Space Station glovebox; (2) a ground control station; and (3) a principal investigator's (PI) work area. The major objective of this project was to evaluate the effectiveness of telescience techniques and hardware to support three realistic remote coaching science procedures: plant seed germinator charging, plant sample acquisition and preservation, and remote plant observation with ground coaching. Each scenario was performed by a subject acting as flight mission specialist, interacting with a payload operations manager and a principal investigator expert. All three groups were physically isolated from each other yet linked by duplex audio and color video communication channels and networked computer workstations. Workload ratings were made by the flight and ground crewpersons immediately after completing their assigned tasks. Time to complete each scientific procedural step was recorded automatically. Two expert observers also made performance ratings and various error assessments. The results are presented and discussed.

Haines, Richard F.↗

NASA NTRS1979

GEOS 3 STDN S band Doppler tracking investigation

GEOS 3S Doppler band and laser ranging data, acquired from August 1975 to March 1976 in the spacecraft altimeter calibration area, are examined. An evaluation of two-way and three-way Doppler data, for the positioning of Spaceflight Tracking and Data Network S band stations is presented, as well as the Goddard Space Flight Center laser system that is used to reference the exact position of the Doppler stations. The two-way and three-way Doppler tracking devices, situated at Rosman and Bermuda, have yielded data for the recovery of GEOS 3 arc height with an uncertainty of only 1 m. Attention is given to the effects of beacon signal frequency instability, controlled by a temperature sensitive auxiliary crystal oscillator on board the spacecraft, and to the one-way range rate tracking noise that was found to be within a range of 2 to 10 cm/s. 1- and 2-way passes and their different arc meters are graphed, showing the Doppler tracking interval. It was concluded that other accurate computations and recovery of station coordinates could be performed employing tracking data from S band stations.

Rosenbaum, B.↗

NASA NTRSDate not supplied

GL4U: Using Space Biology Omics Data to Provide Bioinformatics Training for Students and Educators

NASA’s GeneLab project provides researchers open access to space-relevant multi-omics data via the Open Science Data Repository (OSDR) that can be mined to understand the effects of spaceflight on biological systems. To maximize the number of scientists who understand and utilize GeneLab data and data processing pipelines, GeneLab created GeneLab for Colleges and Universities (GL4U). GL4U provides space biology-relevant training in bioinformatics to the next generation of scientists through direct (training students) and indirect (training educators) approaches. The GL4U pilot programs were conducted in June 2021 (direct training) and 2022 (indirect training). During the pilots, students and educators at Historically Black Colleges and Universities (HBCUs) and Minority Serving Institutions (MSIs) participated in a week-long (direct training) or two-week-long (indirect training) bootcamp consisting of space biology-specific lectures and hands-on instruction using Jupyter Notebooks to analyze space biology RNA sequencing data from OSDR. During the educator pilot, participants received materials, training, and the necessary compute resources to enable them to run the bootcamp at their home institutions, thereby extending the reach of this initiative. In July 2023, GeneLab is partnering with JPL to expand GL4U to include amplicon sequencing (Amp-Seq) analysis training. During the GL4U Amp-Seq bootcamp, student and educator participants will receive training on how to analyze and interpret Amp-Seq data using the NASA GeneLab data processing pipeline. All bootcamp material, including instructions for requesting compute resources, will be made publicly available on GitHub for educators to teach the GL4U content in subsequent semesters. GL4U provides undergraduate students from underrepresented groups the opportunity to learn about NASA and Space Biology, and to enhance their career prospects by gaining hands-on experience analyzing omics data, a skillset that is highly applicable and marketable in the life sciences. We present results from pre- and post-training surveys completed by all participants of the Amp-Seq bootcamp.

Amanda M Saravia-Butler↗

NASA NTRS2014

Space Shuttle and Hypersonic Entry

Fifty years of human spaceflight have been characterized by the aerospace operations of the Soyuz, of the Space Shuttle and, more recently, of the Shenzhou. The lessons learned of this past half decade are important and very significant. Particularly interesting is the scenario that is downstream from the retiring of the Space Shuttle. A number of initiatives are, in fact, emerging from in the aftermath of the decision to terminate the Shuttle program. What is more and more evident is that a new era is approaching: the era of the commercial usage and of the commercial exploitation of space. It is probably fair to say, that this is the likely one of the new frontiers of expansion of the world economy. To make a comparison, in the last 30 years our economies have been characterized by the digital technologies, with examples ranging from computers, to cellular phones, to the satellites themselves. Similarly, the next 30 years are likely to be characterized by an exponential increase of usage of extra atmospheric resources, as a result of more economic and efficient way to access space, with aerospace transportation becoming accessible to commercial investments. We are witnessing the first steps of the transportation of future generation that will drastically decrease travel time on our Planet, and significantly enlarge travel envelope including at least the low Earth orbits. The Steve Jobs or the Bill Gates of the past few decades are being replaced by the aggressive and enthusiastic energy of new entrepreneurs. It is also interesting to note that we are now focusing on the aerospace band, that lies on top of the aeronautical shell, and below the low Earth orbits. It would be a mistake to consider this as a known envelope based on the evidences of the flights of Soyuz, Shuttle and Shenzhou. Actually, our comprehension of the possible hypersonic flight regimes is bounded within really limited envelopes. The achievement of a full understanding of the hypersonic flight regimes will be a key enabler to facilitate the consolidation of the new emerging scenarios. The objective of this symposium is therefore to focus on lesson learned, to then analyze the main elements of those new scenarios, both from Institutional and Private sectors; and finally provide the leads for future collaboration opportunities between Italy, the United States and international partners, so to join profitably the opportunities offered by this new era of the aerospace technologies.

Campbell, Charles H.↗

NASA NTRS2010

Squat Ground Reaction Force on a Horizontal Squat Device, Free Weights, and Smith Machine

Bed rest is an analog to spaceflight and advancement of exercise countermeasures is dependent on the development of exercise equipment that closely mimic actual upright exercise. The Horizontal Squat Device (HSD) was developed to allow a supine exerciser to perform squats that mimic upright squat exercise. PURPOSE: To compare vertical ground reaction force (GRFv) on the HSD with Free Weight (FW) or Smith Machine (SM) during squat exercise. METHODS: Subjects (3F, 3M) performed sets of squat exercise with increasing loads up to 1-repetition (rep) maximum. GRF data were collected and compared with previous GRF data for squat exercise performed with FW & SM. Loads on the HSD were adjusted to magnitudes comparable with FW & SM by subtracting the subject s body weight (BW). Peak GRFv for 45-, 55-, 64-, & 73-kg loads above BW were calculated. Percent (%) difference between HSD and the two upright conditions were computed. Effect size was calculated for the 45-kg load. RESULTS: Most subjects were unable to lift >45 kg on the HSD; however, 1 subject completed all loads. Anecdotal evidence suggested that most subjects shoulders or back failed before their legs. The mean % difference are shown. In the 45-kg condition, effect sizes were 0.37 & 0.83 (p>0.05) for HSD vs. FW and HSD vs. SM, respectively, indicating no differences between exercise modes. CONCLUSION: When BW was added to the target load, results indicated that vertical forces were similar to those in FW and SM exercise. The exercise prescription for the HSD should include a total external resistance equivalent to goal load plus subject BW. The HSD may be used as an analog to upright exercise in bed rest studies, but because most subjects were unable to lift >45 kg, it may be necessary to prescribe higher reps and lower loads to better target the leg musculature

Scott-Pandorf, Melissa M.↗

NASA NTRS2007

Situational Lightning Climatologies for Central Florida, Phase 2, Part 3

The threat of lightning is a daily concern during the warm season in Florida. The forecasters at the Spaceflight Meteorology Group (SMG) at Johnson Spaceflight Center in Houston, TX consider lightning in their landing forecasts for space shuttles at the Kennedy Space Center (KSC), FL Shuttle Landing Facility (SLF). The forecasters at the National Weather Service in Melbourne, FL (NWS MLB) do the same in their routine Terminal Aerodrome Forecasts (TAFs) for seven airports in the NWS MLB County Warning Area (CWA). The Applied Meteorology Unit created flow regime climatologies of lightning probability in the 5-, 10-, 20-, and 30-n mi circles surrounding the Shuttle Landing Facility (SLF) and all airports in the NWS MLB county warning area in 1-, 3-, and 6-hour increments. The results were presented in tabular and graphical format and incorporated into a web-based graphical user interface so forecasters could easily navigate through the data and to make the GUI usable in any web browser on computers with different operating systems.

Bauman, William H., III↗

NASA NTRSDate not supplied

The BioMole Facility: Advancement of In Situ Microbiome Analysis for the International Space Station

Characterization of the International Space Station (ISS) microbiome has been enabled by sample return and Earth-based analysis. As human exploration pushes beyond low-Earth orbit, microbial-related crew health, planetary protection, and space research requires in situ capabilities. Steps toward reducing Earth-dependence for complex sample analysis began in 2016 with the amplification of DNA within the miniPCR thermal cycler and DNA sequencing with the MinION sequencer onboard the ISS; for both, samples were prepared on Earth. In 2017, these platforms synergistically enabled the in-situ identification of unknown bacteria collected and cultured from ISS surfaces, thereby shifting the paradigm that microbial cultures had to be returned to Earth. The following year, a culture-independent, swab-to-sequencer method further advanced spaceflight microbiology, demonstrating that culturing could be excluded and provided enhanced insight into the bacterial profile of ISS surfaces. Based on the success of these payloads in confirming the ability to meet crew health identification requirements and the benefits accompanying a culture-independent method, the BioMole Facility was established by the medical operations Crew Health Care Systems team. BioMole is the set of hardware, consumables, and procedures required to support sample preparation and nanopore sequencing onboard the ISS. BioMole goals include expanding sample sources, comparing data to previous methods, demonstrating onboard data analytics, and validating new hardware. To date, comparative surface analysis, molecular- and culture-based, has been completed. Additionally, the demonstration of a sample-to-answer process was achieved when BioMole data was processed onboard using the IBM Open Data and AI Edge software platform installed on the ISS-residing Spaceborne Computer-2. The taxonomic profiles generated from the edge analysis were as expected and paralleled that of the downlinked processed data. Future BioMole efforts involve microbial profiling of the ISS water system, ISS validation of the MinION Mk1C, and an expansion to a research facility available to investigators.

Sarah L. Castro-Wallace↗

NASA NTRSDate not supplied

Biological Research and Space Health Enabled by Machine Learning to Support Deep Space Missions

A key science goal of the NASA “Moon to Mars” campaign is to understand how biology responds to the Lunar, Martian, and deep space environments in order to advance fundamental knowledge and support human space missions. Through artificial intelligence (AI) and machine learning (ML), a paradigm shift has begun in space biosciences and engineered astronaut health systems, to enable Earth-independence and mission operations autonomy. We describe current AI/ML methods to support 1) fundamental biology, 2) in situ analytics, 3) high performance computing, 4) automated science, 5) self-driving labs, 6) remote data management, 7) integrated mission biomonitoring, and 8) a Precision Space Health system. AI/ML approaches that can be integrated to support these domains include active learning, explainable AI, adaptive learning, causal inference, knowledge graphs, federated learning, transfer learning, and large language models. Finally, we present results from several current ML projects that are underway in the space biology field to address key challenges of small sample n, high feature count, heterogeneity, and sparse data. These include 1) connecting omics to phenotypic data using an ensemble model to infer causality of rodent liver health disruption, 2) usage of explainable ML to interrogate muscular underpinnings of muscle atrophy, 3) ML models analyzing and determining directed acyclic graphs of human health risk leveraging rodent bone datasets, 4) usage of large pre-trained models connecting biomedical knowledgebases with small spaceflight datasets to understand gene-to-gene interactions, and 5) a suite of benchmarked open science datasets enabling programmers to identify best algorithms to answer space biology questions.

space biology↗

NASA NTRSDate not supplied

Developing a Genetic Variant Calling Pipeline for Quantifying the Complex Mutagenic Load Accumulated in BioNutrients-1 Production Pack Samples

Microorganisms hold great promise for on demand production of labile nutrients and pharmaceuticals as well recycling and in situ resource utilization. The utilization of microorganisms for such tasks on space missions is hindered by the limited data on how microbes respond to spaceflight. For example, the genetic stability of microorganisms, and the genomic engineered traits added to deliver desired functions, over long-term storage in the spacecraft environment is poorly understood. The BioNutrients-1 (BN-1) mission conducted a 5-year study of desiccated storage in Low Earth Orbit (LEO) to evaluate the suitability of eight synthetic biology chassis organisms for long-duration space missions. We are employing high-depth, whole genome sequencing (WGS) to determine the mutagenic load that accumulated during long-term storage. Mutation analysis pipelines are well established for homogenous culture grown from a single colony, but the mutational landscape of the BN-1 samples present a unique analysis challenge, as every cell in the BN-1 samples had a unique genetic journey of DNA damage and repair. Consequently, sequence variants are expected at low allele frequency within samples. To address this genetic complexity, we apply two distinct computational approaches to identify mutations in pre-existing WGS data collected from populations of Chlamydomonas reinhardtii that were exposed to UV mutagenesis and growth in LEO. For reference genome free mutation detection, we utilized DiscoSNP++, which is a de Bruijn graph approach. For reference genome-based mutation detection we utilize GATK for Microbes, which is a Bayesian probabilistic approach. We will benchmark these approaches against the mutations originally identified using CRISP, a method optimized for pooled samples. Ultimately, quantifying the mutation load imposed by storage or growth on the ISS will help identify chassis organisms with both high levels of genome stability and viability, which are desirable traits for implementation of bioproduction in long-duration missions.

SNP↗

NASA NTRS2005

DEVELOPMENT OF AN INFLIGHT COUNTERMEASURE TO MITIGATE POSTFLIGHT GAIT DYSFUNCTION

Following spaceflight crewmembers experience gait and postural instabilities due to inflight adaptive alterations in sensorimotor function. These changes can pose a risk to crew safety if nominal or emergency vehicle egress is required immediately following long-duration spaceflight. At present, no operational countermeasure is available to mitigate postflight locomotor disturbances. Therefore, the goal of this study is to develop an inflight training regimen that facilitates the recovery of locomotor function after long-duration spaceflight. The countermeasure we are developing is based on the concept of variable practice. During this type of training the subject gains experience producing the appropriate adaptive motor behavior under a variety of sensory conditions and response constraints. This countermeasure is built around current ISS treadmill exercise activities. Crewmembers will conduct their nominal inflight treadmill exercise while being exposed to variations in visual flow patterns. These variations will challenge the postural and locomotor systems repeatedly, thereby promoting adaptive reorganization in locomotor behavior. As a result of this training a subject learns to solve a class of motor problems, rather than a specific motor solution to one problem, Le., the subject learns response generalizability or the ability to "learn to learn" under a variety of environmental constraints. We anticipate that this training will accelerate recovery of postural and locomotor function during readaptation to gravitational environments following spaceflight facilitating neural adaptation to unit (Earth) and partial (Mars) gravity after long-duration spaceflight. The study calls for one group of subjects to perform the inflight treadmill training regimen while a control group of subjects performs only the nominal exercise procedures. Locomotor function in both groups is assessed before and after spaceflight using two tests of gait function: The Integrated Treadmill Locomotion Test (ITLT) and the Functional Mobility Test (FMT). The ITLT characterizes alterations in the integrated function of multiple sensorimotor subsystems responsible for the control of locomotion. This test calls for subjects to walk on a motorized treadmill while we assess changes in dynamic postural stability, head-trunk coordination, short-latency head stabilization responses, dynamic visual acuity, lower limb coordination strategies and gait cycle timing. To make these assessments we measure the following parameters while subjects walk on the treadmill: 1) full body 3-dimensional kinematics using a motion capture system (Motion Analysis Corp., Santa Rosa, CA); 2) the shock-wave transmitted from heel-strike to the head using triaxial accelerometers placed on the tibia and head (Entran, Fairfield, NJ); 3) vertical forces using an instrumented treadmill (Kistler Instrument Corp., Amherst, NY); 4) Dynamic visual acuity using Landolt Cs presented on a laptop computer located 4m from the eyes and 5) Gait cycle timing using foot-switches (Motion Lab Systems, Inc., Baton Rouge, LA) attached to the plantar surface of each shoe at the heel and toe. The FMT evaluates a subject's ability to perform challenging locomotor maneuvers similar to those encountered during an egress from a space vehicle. Subjects step over and duck under obstacles along with negotiating a series of pylons set up on a base of 10 cm thick medium density foam. The dependent measures for the FMT are time to complete the course and the number of obstacles touched. To date, we have collected pre and postflight locomotion data from Expeditions 5-9 who will serve as part of the control group for this study. Preliminary results comparing the recovery rates in gait control sub-systems obtained from the ITLT and FMT performance showed two recovery patterns: 1) a concordant recovery trend between gait control parameters and FMT performance indicating a restitution pattern of recovery and 2) gait controecovery that lagged recovery in FMT performance suggesting that improvement in locomotor function was attained through a pattern of substitution. These data suggest that recovery of postflight locomotor function may occur through adaptive mechanisms that lead to either restitution or substitution of function. Understanding the modes of postflight readaptation has implications for countermeasure development and testing and in astronaut postflight rehabilitation.

Bloomberg, J. J.↗

NASA NTRS2005

Development of an Inflight Countermeasure to Mitigate Postflight Gait Dysfunction

Following spaceflight crewmembers experience gait and postural instabilities due to inflight adaptive alterations in sensorimotor function. These changes can pose a risk to crew safety if nominal or emergency vehicle egress is required immediately following long-duration spaceflight. At present, no operational countermeasure is available to mitigate postflight locomotor disturbances. Therefore, the goal of this study is to develop an inflight training regimen that facilitates the recovery of locomotor function after long-duration spaceflight. The countermeasure we are developing is based on the concept of variable practice. During this type of training the subject gains experience producing the appropriate adaptive motor behavior under a variety of sensory conditions and response constraints. This countermeasure is built around current ISS treadmill exercise activities. Crewmembers will conduct their nominal inflight treadmill exercise while being exposed to variations in visual flow patterns. These variations will challenge the postural and locomotor systems repeatedly, thereby promoting adaptive reorganization in locomotor behavior. As a result of this training a subject learns to solve a class of motor problems, rather than a specific motor solution to one problem, Le., the subject learns response generalizability or the ability to "learn to learn" under a variety of environmental constraints. We anticipate that this training will accelerate recovery of postural and locomotor function during readaptation to gravitational environments following spaceflight facilitating neural adaptation to unit (Earth) and partial (Mars) gravity after long-duration spaceflight. The study calls for one group of subjects to perform the inflight treadmill training regimen while a control group of subjects performs only the nominal exercise procedures. Locomotor function in both groups is assessed before and after spaceflight using two tests of gait function: The Integrated Treadmill Locomotion Test (ITLT) and the Functional Mobility Test (FMT). The ITLT characterizes alterations in the integrated function of multiple sensorimotor subsystems responsible for the control of locomotion. This test calls for subjects to walk on a motorized treadmill while we assess changes in dynamic postural stability, head-trunk coordination, short-latency head stabilization responses, dynamic visual acuity, lower limb coordination strategies and gait cycle timing. To make these assessments we measure the following parameters while subjects walk on the treadmill: 1) full body 3-dimensional kinematics using a motion capture system (Motion Analysis Corp., Santa Rosa, CA); 2) the shock-wave transmitted from heel-strike to the head using triaxial accelerometers placed on the tibia and head (Entran, Fairfield, NJ); 3) vertical forces using an instumented treadmill (Kistler Instrument Corp., Amherst, NY); 4) Dynamic visual acuity using Landolt Cs presented on a laptop computer located 4m from the eyes and 5) Gait cycle timing using foot-switches (Motion Lab Systems, Inc., Baton Rouge, LA) attached to the plantar surface of each shoe at the heel and toe. The FMT evaluates s. subject's ability to perform challenging locomotor maneuvers similar to those encountered during an egress from a space vehicle. Subjects step over and duck under obstacles along with negotiating a series of pylons set up on a base of 10 cm thick medium density foam. The dependent measures for the FMT are time to complete the course and the number of obstacles touched. To date, we have collected pre and postflight locomotion data from Expeditions 5-9 who will serve as part of the control group for this study. Preliminary results comparing the recovery rates in gait control sub-systems obtained from the ITLT and FMT performance showed two recovery patterns: 1) a concordant recovery trend between gait control parameters and FMT performance indicating a restitution pattern of recovery and 2) gait controecovery that lagged recovery in FMT performance suggesting that improvement in locomotor function was attained through a pattern of substitution. These data suggest that recovery of postflight locomotor function may occur through adaptive mechanisms that lead to either restitution or substitution of function. Understanding the modes of postflight readaptation has implications for countermeasure development and testing and in astronaut postflight rehabilitation.

Bloomberg, J. J.↗

NASA NTRS1992

Spaceflight optical disk recorder development

Mass memory systems based on rewriteable optical disk media are expected to play an important role in meeting the data system requirements for future NASA spaceflight missions. NASA has established a program to develop a high performance (high rate, large capacity) optical disk recorder focused on use aboard unmanned Earth orbiting platforms. An expandable, adaptable system concept is proposed based on disk drive modules and a modular controller. Drive performance goals are 10 gigabyte capacity, 300 megabit/s transfer rate, 10 exp -12 corrected bit error rate, and 150 millisec access time. This performance is achieved by writing eight data tracks in parallel on both sides of a 14 in. optical disk using two independent heads. System goals are 160 gigabyte capacity, 1.2 gigabits/s data rate with concurrent I/O, 250 millisec access time, and two to five year operating life on orbit. The system can be configured to meet various applications. This versatility is provided by the controller. The controller provides command processing, multiple drive synchronization, data buffering, basic file management, error processing, and status reporting. Technology developments, design concepts, current status including a computer model of the system and a Controller breadboard, and future plans for the Drive and Controller are presented.

Jurczyk, Stephen G.↗

NASA NTRS2019

The Cognition and Fine Motor Skills Test Batteries: Normative Data and Interdependencies

Space mission success and safety relies upon astronaut functional state. Since spaceflight stressors affect cognitive processing and fine motor skills, NASA requires that measures of performance of these things remain within clinically accepted values (NASA STD 3001). NASA is in the process of developing two test batteries for the assessment of crew cognitive and fine motor skills before, during and after spaceflight. Toward that goal, the current project collected normative scores in 91 “astronaut-like” military and civilian pilots. The Cognition Test Battery (CTB) contains ten sub-tests that measure a range of cognitive abilities. For five of the ten CTB sub-tests, we propose scores to improve the battery’s sensitivity. Among the ten sub-tests, response times were more highly correlated than accuracy scores. Principle component analysis of the correlations revealed that the first response time factor could explain over 40% of the total variance and appeared to represent the tendency of observers to try to respond more quickly. The first accuracy factor (explaining only 20%) gave a high weight to the higher level cognitive sub-tests and a negative weight to tasks associated with motor and lower level cognitive processing. The Fine Motor Skills (FMS) test battery contains four sub-tests (Tracking, Pointing, Tracing, Rotating) performed on an Apple iPad tablet computer. Principle component analysis on the sub-test response time correlations revealed that the first two factors accounted for ~80% of the variance in performance. The first component captured overall speed on all four of the sub-tests. The second factor separated the sub-tasks into two groups (Drag-Point vs Trace-Rotate). Previous work found the first group response times correlated with that of a standard peg board task, while those of the other group did not. Correlations were computed between the first FMS factor and the response time and accuracy scores from each CTB sub-task. Performing fine motor behaviors rapidly was significantly correlated with the ability to perform many of the CTB sub-tests rapidly. This ability cannot be simple motor speed since scores on the Psychomotor Vigilance Test (PVT) subtask did not correlate with the ability to perform the other tasks rapidly. Speed on fine motor skills correlated significantly with accuracy on the short-term-memory sub-test. We hypothesize that eye movements, which can be regarded as a fine motor skill, may explain this relationship.

cognition↗

NASA NTRS2016

Simulation of Mission Phases

This position with the Simulation and Graphics Branch (ER7) at Johnson Space Center (JSC) provided an introduction to vehicle hardware, mission planning, and simulation design. ER7 supports engineering analysis and flight crew training by providing high-fidelity, real-time graphical simulations in the Systems Engineering Simulator (SES) lab. The primary project assigned by NASA mentor and SES lab manager, Meghan Daley, was to develop a graphical simulation of the rendezvous, proximity operations, and docking (RPOD) phases of flight. The simulation is to include a generic crew/cargo transportation vehicle and a target object in low-Earth orbit (LEO). Various capsule, winged, and lifting body vehicles as well as historical RPOD methods were evaluated during the project analysis phase. JSC core mission to support the International Space Station (ISS), Commercial Crew Program (CCP), and Human Space Flight (HSF) influenced the project specifications. The simulation is characterized as a 30 meter +V Bar and/or -R Bar approach to the target object's docking station. The ISS was selected as the target object and the international Low Impact Docking System (iLIDS) was selected as the docking mechanism. The location of the target object's docking station corresponds with the RPOD methods identified. The simulation design focuses on Guidance, Navigation, and Control (GNC) system architecture models with station keeping and telemetry data processing capabilities. The optical and inertial sensors, reaction control system thrusters, and the docking mechanism selected were based on CCP vehicle manufacturer's current and proposed technologies. A significant amount of independent study and tutorial completion was required for this project. Multiple primary source materials were accessed using the NASA Technical Report Server (NTRS) and reference textbooks were borrowed from the JSC Main Library and International Space Station Library. The Trick Simulation Environment and User Training Materials version 2013.0 release was used to complete the Trick tutorial. Multiple network privilege and repository permission requests were required in order to access previous simulation models. The project was also an introduction to computer programming and the Linux operating system. Basic C++ and Python syntax was used during the completion of the Trick tutorial. Trick's engineering analysis and Monte Carlo simulation capabilities were observed and basic space mission planning procedures were applied in the conceptual design phase. Multiple professional development opportunities were completed in addition to project duties during this internship through the System for Administration, Training, and Education Resources for NASA (SATERN). Topics include: JSC Risk Management Workshop, CCP Risk Management, Basic Radiation Safety Training, X-Ray Radiation Safety, Basic Laser Safety, JSC Export Control, ISS RISE Ambassador, Basic SharePoint 2013, Space Nutrition and Biochemistry, and JSC Personal Protective Equipment. Additionally, this internship afforded the opportunity for formal project presentation and public speaking practice. This was my first experience at a NASA center. After completing this internship I have a much clearer understanding of certain aspects of the agency's processes and procedures, as well as a deeper appreciation from spaceflight simulation design and testing. I will continue to improve my technical skills so that I may have another opportunity to return to NASA and Johnson Space Center.

Carlstrom, Nicholas Mercury↗

NASA NTRS2012

NASA Tech Briefs, November 2012

The topics include: Visual System for Browsing, Analysis, and Retrieval of Data (ViSBARD); Time-Domain Terahertz Computed Axial Tomography NDE System; Adaptive Sampling of Time Series During Remote Exploration; A Tracking Sun Photometer Without Moving Parts; Surface Temperature Data Analysis; Modular, Autonomous Command and Data Handling Software with Built-In Simulation and Test; In-Situ Wire Damage Detection System; Amplifier Module for 260-GHz Band Using Quartz Waveguide Transitions; Wideband Agile Digital Microwave Radiometer; Buckyball Nucleation of HiPco Tubes; FACT, Mega-ROSA, SOLAROSA; An Integrated, Layered-Spinel Composite Cathode for Energy Storage Applications; Engineered Multifunctional Surfaces for Fluid Handling; Polyolefin-Based Aerogels; Adjusting Permittivity by Blending Varying Ratios of SWNTs; Gravity-Assist Mechanical Simulator for Outreach; Concept for Hydrogen-Impregnated Nanofiber/Photovoltaic Cargo Stowage System; DROP: Durable Reconnaissance and Observation Platform; Developing Physiologic Models for Emergency Medical Procedures Under Microgravity; Spectroscopic Chemical Analysis Methods and Apparatus; Low Average Sidelobe Slot Array Antennas for Radiometer Applications; Motion-Corrected 3D Sonic Anemometer for Tethersondes and Other Moving Platforms; Water Treatment Systems for Long Spaceflights; Microchip Non-Aqueous Capillary Electrophoresis (MicronNACE) Method to Analyze Long-Chain Primary Amines; Low-Cost Phased Array Antenna for Sounding Rockets, Missiles, and Expendable Launch Vehicles; Mars Science Laboratory Engineering Cameras; Seismic Imager Space Telescope; Estimating Sea Surface Salinity and Wind Using Combined Passive and Active L-Band Microwave Observations; A Posteriori Study of a DNS Database Describing Super critical Binary-Species Mixing; Scalable SCPPM Decoder; QuakeSim 2.0; HURON (HUman and Robotic Optimization Network) Multi-Agent Temporal Activity Planner/Scheduler; MPST Software: MoonKommand

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