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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
NASA NTRS2008

Human Factors in Training

Future space missions will be significantly longer than current Shuttle missions and new systems will be more complex than current systems. Increasing communication delays between crews and Earth-based support means that astronauts need to be prepared to handle the unexpected on their own. As crews become more autonomous, their potential span of control and required expertise must grow to match their autonomy. It is not possible to train for every eventuality ahead of time on the ground, or to maintain trained skills across long intervals of disuse. To adequately prepare NASA personnel for these challenges, new training approaches, methodologies, and tools are required. This research project aims at developing these training capabilities. Training efforts in FY07 strongly focused on crew medical training, but also began exploring how Space Flight Resource Management training for Mission Operations Directorate (MOD) Flight Controllers could be integrated with systems training for optimal Mission Control Center operations. Beginning in January 2008, the training research effort will include team training prototypes and tools. The Training Task addresses Program risks that lie at the intersection of the following three risks identified by the Project: 1) Risk associated with poor task design; 2) Risk of error due to inadequate information; 3) Risk associated with reduced safety and efficiency due to poor human factors design.

Barshi, Immanuel↗
NASA NTRS2010

The Right Stuff: A Look Back at Three Decades of Flight Controller Training for Space Shuttle Mission Operations

This paper will summarize the thirty-year history of Space Shuttle operations from the perspective of training in NASA Johnson Space Center's Mission Control Center. It will focus on training and development of flight controllers and instructors, and how training practices have evolved over the years as flight experience was gained, new technologies developed, and programmatic needs changed. Operations of human spaceflight systems is extremely complex, therefore the training and certification of operations personnel is a critical piece of ensuring mission success. Mission Control Center (MCC-H), at the Lyndon B. Johnson Space Center, in Houston, Texas manages mission operations for the Space Shuttle Program, including the training and certification of the astronauts and flight control teams. This paper will give an overview of a flight control team s makeup and responsibilities during a flight, and details on how those teams are trained and certified. The training methodology for developing flight controllers has evolved significantly over the last thirty years, while the core goals and competencies have remained the same. In addition, the facilities and tools used in the control center have evolved. These changes have been driven by many factors including lessons learned, technology, shuttle accidents, shifts in risk posture, and generational differences. Flight controllers will share their experiences in training and operating the Space Shuttle throughout the Program s history. A primary method used for training Space Shuttle flight control teams is by running mission simulations of the orbit, ascent, and entry phases, to truly "train like you fly." The audience will learn what it is like to perform a simulation as a shuttle flight controller. Finally, we will reflect on the lessons learned in training for the shuttle program, and how those could be applied to future human spaceflight endeavors.

Dittemore, Gary D.↗
NASA NTRS2015

The Evolution of On-Board Emergency Training for the International Space Station Crew

The crew of the International Space Station (ISS) receives extensive ground‐training in order to safely and effectively respond to any potential emergency event while on‐orbit, but few people realize that their training is not concluded when they launch into space. The evolution of the emergency On‐ Board Training events (OBTs) has recently moved from paper "scripts" to an intranet‐based software simulation that allows for the crew, as well as the flight control teams in Mission Control Centers across the world, to share in an improved and more realistic training event. This emergency OBT simulator ensures that the participants experience the training event as it unfolds, completely unaware of the type, location, or severity of the simulated emergency until the scenario begins. The crew interfaces with the simulation software via iPads that they keep with them as they translate through the ISS modules, receiving prompts and information as they proceed through the response. Personnel in the control centers bring up the simulation via an intranet browser at their console workstations, and can view additional telemetry signatures in simulated ground displays in order to assist the crew and communicate vital information to them as applicable. The Chief Training Officers and emergency instructors set the simulation in motion, choosing the type of emergency (rapid depressurization, fire, or toxic atmosphere) and specific initial conditions to emphasize the desired training objectives. Project development, testing, and implementation was a collaborative effort between ISS emergency instructors, Chief Training Officers, Flight Directors, and the Crew Office using commercial off the shelf (COTS) hardware along with simulation software created in‐house. Due to the success of the Emergency OBT simulator, the already‐developed software has been leveraged and repurposed to develop a new emulator used during fire response ground‐training to deliver data that the crew receives from the handheld Compound Specific Analyzer for Combustion Products (CSA‐CP). This CSA‐CP emulator makes use of a portion of codebase from the Emergency OBT simulator dealing with atmospheric contamination during fire scenarios, and feeds various data signatures to crew via an iPod Touch with a flight‐like CSA‐CP display. These innovative simulations, which make use of COTS hardware with custom in‐house software, have yielded drastic improvements to emergency training effectiveness and risk reduction for ISS crew and flight control teams during on‐orbit and ground training events.

LaBuff, Skyler↗
NASA NTRSDate not supplied

Shoulder Postures in EVA Training in Reduced Gravity Analogues

Shoulder Postures in EVA Training in Reduced Gravity Analogues K. Guhl1, L. Vu2, H. Kim3, S. Rajulu4 1KBR Inc., Houston, TX, 2Aegis Aerospace Inc., Houston, TX, 3Leidos Innovations, Houston, TX, 4NASA Johnson Space Center, Houston, TX. During extravehicular activities (EVAs) and EVA training in both the Neutral Buoyancy Laboratory (NBL) and at the Active Response Gravity Offload System (ARGOS), crewmembers perform a variety of hand-intensive tasks with frequent arm/shoulder repositioning while wearing a pressurized spacesuit. As a result, crewmembers may experience ergonomic stressors such as awkward shoulder postures. The ergonomic shoulder risk is also compounded by limited or restricted shoulder mobility of the spacesuit, extreme work positions such as overhead tasks, and tasks with heavy tools and repetitive motions. Prolonged or frequent shoulder elevation and overhead work, in particular, can lead to excessive stresses and musculoskeletal injuries of the shoulder joints. Future EVA missions, specifically lunar surface EVAs, will also be longer in duration and thus increase the exposure to awkward shoulder postures. In this study, we aimed to assess the ergonomic risk of awkward shoulder postures in simulated lunar surface EVAs by quantifying when and how long the arms are raised above the chest level. We assessed video recordings of pilot lunar EVA simulations (3 lunar trials each in the NBL and at ARGOS and 2 microgravity EVA trials in the NBL). These runs consisted of both training and engineering test objectives. Actual demands for shoulder use varied for different EVA types and analogues, but many EVA runs have common tasks and require similar motion components. A video observation and event logging software was used to document the duration and occurrence of the subject’s arms being raised throughout the video recordings of each EVA run. An arm raised instance was classified as the arm being at 90 degrees or above with relation to gravity for lunar EVA training events and with relation to the body for microgravity EVA training events. Such events included EVA hardware maintenance or heavy geology sampling tool operations. Events where the arm load was partially supported by external objects, like climbing a ladder or leaning against a surface were separately identified and excluded. Statistical analysis was performed to summarize the timing, frequency, and durations of the arm raise events and compared across the different EVA tasks and analogue types. Preliminary observations indicated that the total duration and number of arm raised instances were surprisingly smaller for lunar surface EVA training as compared to microgravity EVA training. The observed difference may be attributed to differing task demands and unique environmental characteristics found in lunar EVAs in comparison to microgravity EVAs. A detailed statistical analysis will be performed between lunar surface EVA training events and microgravity EVA training events in the final submission. Overall, this analysis is expected to provide insight into how ergonomic recommendations can be refined for lunar EVA training with pressurized suits. It may also inform task design and influence suit padding design to better protect crewmembers during future lunar training.

Kaitlyn Lea Guhl↗
NASA NTRS1992

Human torque velocity adaptations to sprint, endurance, or combined modes of training

We had groups of athletes perform sprint and endurance run training independently or concurrently for 8 weeks to examine the voluntary in vivo mechanical responses to each type of training. Pre- and posttraining angle-specific peak torque during knee extension and flexion were determined at 0, 0.84, 1.65, 2.51, 3.35, 4.19, and 5.03 radian.sec-1 and normalized for lean body mass. Knee extension torque in the sprint-trained group increased across all test velocities, the endurance-trained group increased at 2.51, 3.34, 4.19, and 5.03 radian.sec-1, and the group performing the combined training showed no change at any velocity. Knee flexion torque of the sprint and combined groups decreased at 0.84, 1.65, and 2.51 radian.sec-1. Knee flexion torque in the sprint-trained group also decreased at 0 radian.sec-1 and in the combined group at 3.34 radian.sec-1. Knee flexion torque in the endurance-trained group showed no change at any velocity of contraction. Mean knee flexion:extension ratios across the test velocities significantly decreased in the sprint-trained group. Knee extension endurance during 30 seconds of maximal contractions significantly increased in all groups. Only the sprint-trained group showed a significant increase in endurance of the knee flexors. These data suggest that changes in the voluntary in vivo mechanical characteristics of knee extensor and flexor skeletal muscles are specific to the type of run training performed.

NASA Discipline Musculoskeletal↗
DOE OSTI2020

Active Learning A Neural Network Model For Gold Clusters & Bulk From Sparse First Principles Training Data

Small metal clusters are of fundamental scientific interest and of tremendous significance in catalysis. These nanoscale clusters display diverse geometries and structural motifs depending on the cluster size; a knowledge of this size-dependent structural motifs and their dynamical evolution has been of longstanding interest. Given the high computational cost of first-principles calculations, molecular modeling and atomistic simulations such as molecular dynamics (MD) has proven to be an important complementary tool to aid this understanding. Classical MD typically employ predefined functional forms which limits their ability to capture such complex size-dependent structural and dynamical transformation. Neural Network (NN) based potentials represent flexible alternatives and in principle, well-trained NN potentials can provide high level of flexibility, transferability and accuracy on-par with the reference model used for training. A major challenge, however, is that NN models are interpolative and requires large quantities (similar to 10 4 or greater) of training data to ensure that the model adequately samples the energy landscape both near and far-from-equilibrium. A highly desirable goal is minimize the number of training data, especially if the underlying reference model is first-principles based and hence expensive. In this work, we introduce an active learning (AL) scheme that trains a NN model on-the-fly with minimal amount of first-principles based training data. Our AL workflow is initiated with a sparse training dataset (similar to 1 to 5 data points) and is updated on-the-fly via a Nested Ensemble Monte Carlo scheme that iteratively queries the energy landscape in regions of failure and updates the training pool to improve the network performance. Using a representative system of gold clusters, we demonstrate that our AL workflow can train a NN with similar to 500 total reference calculations. Using an extensive DFT test set of similar to 1100 configurations, we show that our AL-NN is able to accurately predict both the DFT energies and the forces for clusters of a myriad of different sizes. Our NN predictions are within 30 meV/atom and 40 meV/angstrom of the reference DFT calculations. Moreover, our AL-NN model also adequately captures the various size-dependent structural and dynamical properties of gold clusters in excellent agreement with DFT calculations and available experiments. We finally show that our AL-NN model also captures bulk properties reasonably well, even though they were not included in the training data.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2022

The impacts of training on change deafness and build-up in a flicker task

Performance on auditory change detection tasks can be improved by training. We examined the stimulus specificity of these training effects in behavior and ERPs. A flicker change detection task was employed in which spatialized auditory scenes were alternated until a "change" or "same" response was made. For half of the trials, scenes were identical. The other half contained changes in the spatial locations of objects from scene to scene. On Day 1, participants were either trained on this auditory change detection task (trained group), or trained on a non-auditory change detection task (control group). On Day 2, all participants were tested on the flicker task while EEG was recorded. The trained group showed greater change detection accuracy than the control group. They were less biased to respond "same" and showed full generalization of learning from trained to novel auditory objects. ERPs for "change" compared to "same" trials showed more negative going P1, N1, and P2 amplitudes, as well as a larger P3b amplitude. The P3b amplitude also differed between the trained and control group, with larger amplitudes for the trained group. Analysis of ERPs to scenes viewed prior to a decision revealed build-up of a difference between "change" and "same" trials in N1 and P2. Results demonstrate that training has an impact early in the "same" versus "change" decision-making process, and that the flicker paradigm combined with the ERP method can be used to study the build-up of change detection in auditory scenes.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2020

How Low Can You Go? Using Synthetic 3D Imagery to Drastically Reduce Real-World Training Data for Object Detection

Deep convolutional neural networks (DCNNs) currently provide state-of-the-art performance on image classification and object detection tasks, and there are many global security mission areas where such models could be extremely useful. Crucially, the success of these models is driven in large part by the widespread availability of high-quality open source data sets such as Image Net, Common Objects in Context (COCO), and KITTI, which contain millions of images with thousands of unique labels. However, global security relevant objects-of-interest can be difficult to obtain: relevant events are low frequency and high consequence; the content of relevant images is sensitive; and adversaries and proliferators seek to obscure their activities. For these cases where exemplar data is hard to come-by, even fine-tuning an existing model with available data can be effectively impossible. Recent work demonstrated that models can be trained using a combination of real-world and synthetic images generated from 3D representations; that such models can exceed the performance of models trained using real-world data alone; and that the generated images need not be perfectly realistic (Tremblay, et al., 2018). However, this approach still required hundreds to thousands of real-world images for training and fine tuning, which for sparse, global security-relevant datasets can be an unrealistic hurdle. In this research, we validate the performance and behavior of DCNN models as we drive the number of real-world images used for training object detection tasks down to a minimal set. We perform multiple experiments to identify the best approach to train DCNNs from an extremely small set of real-world images. In doing so, we: Develop state-of-the-art, parameterized 3D models based on real-world images and sample from their parameters to increase the variance in synthetic image training data; Use machine learning explainability techniques to highlight and correct through targeted training the biases that result from training using completely synthetic images; and Validate our results by comparing the performance of the models trained on synthetic data to one another, and to a control model created by fine-tuning an existing ImageNet-trained model with a limited number (hundreds) of real-world images.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

The effects of 8-week complex training on lower-limb strength and power of Chinese elite female modern pentathlon athletes

Complex training (CT) is a combination training method that alternates between performing high-load resistance training (RT) and plyometric training within one single session. The study aimed to examine the effects of CT on lower-limb strength and power of elite female modern pentathlon athletes under the new modern pentathlon format and competition rules. Ten female participants (age: 23.55 ± 2.22 years, weight: 60.59 ± 3.87 kg, height: 169.44 ± 4.57 cm, and training experience: 6.90 ± 2.08 years) of the national modern pentathlon team completed 8 weeks of RT as followed by 8 weeks of CT, with 2 weeks of break. Then, the participants conducted 8 weeks of CT, which included RT combined with plyometric training (e.g., drop jump and continuous jump). All stages of training were designed by the linear strength training period theories, requiring participants to train twice for the first 4 weeks and three times for the second 4 weeks. The one-repetition maximum (1RM) of squat, isometric mid-thigh pull (IMTP), counter-movement jump (CMJ), squat jump (SJ), pre-stretch augmentation percentage (PSAP), and reaction strength index (RSI) were assessed before and after both RT and CT training. One-way repeated-measure ANOVA models revealed that the 1RM of squat was significantly improved ( p < 0.001) after RT as compared to pre-RT. No significant improvement in IMTP ( p = 0.055), CMJ ( p = 0.194), SJ ( p = 0.692), PSAP ( p = 0.087), and RSI ( p = 0.238) was not observed. After CT, 1RM of squat ( p < 0.001), IMTP ( p < 0.035), CMJ ( p < 0.001), SJ ( p < 0.008), RSI ( p < 0.006) were significant improved as compared to pre-RT, post-RT and pre-CT, while significant improvements in PSAP were observed as compared to pre-RT ( p = 0.003) and pre-CT ( p = 0.027), but not to post-RT ( p = 0.156). This pilot study showed the promise of CT following RT to improve lower-limb strength and power in elite female modern pentathlon athletes. The findings are worthwhile to be confirmed in future studies with larger sample size and randomized design.

Qiao, Zining↗
DOE OSTI2024

Improving Photometric Redshift Estimates with Training Sample Augmentation

Abstract Large imaging surveys will rely on photometric redshifts (photo- z 's), which are typically estimated through machine-learning methods. Currently planned spectroscopic surveys will not be deep enough to produce a representative training sample for Legacy Survey of Space and Time (LSST), so we seek methods to improve the photo- z estimates that arise from nonrepresentative training samples. Spectroscopic training samples for photo- z 's are biased toward redder, brighter galaxies, which also tend to be at lower redshift than the typical galaxy observed by LSST, leading to poor photo- z estimates with outlier fractions nearly 4 times larger than for a representative training sample. In this Letter, we apply the concept of training sample augmentation, where we augment simulated nonrepresentative training samples with simulated galaxies possessing otherwise unrepresented features. When we select simulated galaxies with ( g - z ) color, i -band magnitude, and redshift outside the range of the original training sample, we are able to reduce the outlier fraction of the photo- z estimates for simulated LSST data by nearly 50% and the normalized median absolute deviation (NMAD) by 56%. When compared to a fully representative training sample, augmentation can recover nearly 70% of the degradation in the outlier fraction and 80% of the degradation in NMAD. Training sample augmentation is a simple and effective way to improve training samples for photo- z 's without requiring additional spectroscopic samples.

Moskowitz, Irene (ORCID:0000000222068589)↗
NASA NTRS1985

Mark 4A project training evaluation

A participant evaluation of a Deep Space Network (DSN) is described. The Mark IVA project is an implementation to upgrade the tracking and data acquisition systems of the dSN. Approximately six hundred DSN operations and engineering maintenance personnel were surveyed. The survey obtained a convenience sample including trained people within the population in order to learn what training had taken place and to what effect. The survey questionnaire used modifications of standard rating scales to evaluate over one hundred items in four training dimensions. The scope of the evaluation included Mark IVA vendor training, a systems familiarization training seminar, engineering training classes, a on-the-job training. Measures of central tendency were made from participant rating responses. Chi square tests of statistical significance were performed on the data. The evaluation results indicated that the effects of different Mark INA training methods could be measured according to certain ratings of technical training effectiveness, and that the Mark IVA technical training has exhibited positive effects on the abilities of DSN personnel to operate and maintain new Mark IVA equipment systems.

Stephenson, S. N.↗
NASA NTRS1991

Intelligent computer-aided training and tutoring

Specific autonomous training systems based on artificial intelligence technology for use by NASA astronauts, flight controllers, and ground-based support personnel that demonstrate an alternative to current training systems are described. In addition to these specific systems, the evolution of a general architecture for autonomous intelligent training systems that integrates many of the features of traditional training programs with artificial intelligence techniques is presented. These Intelligent Computer-Aided Training (ICAT) systems would provide, for the trainee, much of the same experience that could be gained from the best on-the-job training. By integrating domain expertise with a knowledge of appropriate training methods, an ICAT session should duplicate, as closely as possible, the trainee undergoing on-the-job training in the task environment, benefitting from the full attention of a task expert who is also an expert trainer. Thus, the philosophy of the ICAT system is to emulate the behavior of an experienced individual devoting his full time and attention to the training of a novice - proposing challenging training scenarios, monitoring and evaluating the actions of the trainee, providing meaningful comments in response to trainee errors, responding to trainee requests for information, giving hints (if appropriate), and remembering the strengths and weaknesses displayed by the trainee so that appropriate future exercises can be designed.

Loftin, R. Bowen↗
NASA NTRS1992

Training evaluation final report

In the area of management training, 'evaluation' refers both to the specific evaluation instrument used to determine whether a training effort was considered effective, and to the procedures followed to evaluate specific training requests. This report recommends to evaluate new training requests in the same way new procurement or new projects are evaluated. This includes examining training requests from the perspective of KSC goals and objectives, and determining expected ROI of proposed training program (does training result in improved productivity, through savings of time, improved outputs, and/or personnel reduction?). To determine whether a specific training course is effective, a statement of what constitutes 'good performance' is required. The user (NOT the Training Branch) must define what is 'required level of performance'. This 'model' will be the basis for the design and development of an objective, performance-based, training evaluation instrument.

Sepulveda, Jose A.↗
NASA NTRS1995

The effects of Crew Resource Management (CRM) training in airline maintenance: Results following three year's experience

An airline maintenance department undertook a CRM training program to change its safety and operating culture. In 2 1/2 years this airline trained 2200 management staff and salaried professionals. Participants completed attitude surveys immediately before and after the training, as well as two months, six months, and one year afterward. On-site interviews were conducted to test and confirm the survey results. Comparing managers' attitudes immediately after their training with their pretraining attitudes showed significant improvement for three attitudes. A fourth attitude, assertiveness, improved significantly above the pretraining levels two months after training. The expected effect of the training on all four attitude scales did not change significantly thereafter. Participants' self-reported behaviors and interview comments confirmed their shift from passive to more active behaviors over time. Safety, efficiency, and dependability performance were measured before the onset of the training and for some 30 months afterward. Associations with subsequent performance were strongest with positive attitudes about sharing command (participation), assertiveness, and stress management when those attitudes were measured 2 and 12 months after the training. The two month follow-up survey results were especially strong and indicate that active behaviors learned from the CRM training consolidate and strengthen in the months immediately following training.

Taylor, J. C.↗
NASA NTRS1999

Transition to Glass: Pilot Training for High-Technology Transport Aircraft

This report examines the activities of a major commercial air carrier between 1993 and late 1996 as it acquired an advanced fleet of high-technology aircraft (Boeing 757). Previously, the airline's fleet consisted of traditional (non-glass) aircraft, and this report examines the transition from a traditional fleet to a glass one. A total of 150 pilots who were entering the B-757 transition training volunteered for the study, which consisted of three query phases: (1) first day of transition training, (2) 3 to 4 months after transition training, and (3) 12 to 14 months after initial operating experience. Of these initial 150 pilots, 99 completed all three phases of the study, with each phase consisting of probes on attitudes and experiences associated with their training and eventual transition to flying the line. In addition to the three questionnaires, 20 in-depth interviews were conducted. Although the primary focus of this study was on the flight training program, additional factors such as technical support, documentation, and training aids were investigated as well. The findings generally indicate that the pilot volunteers were highly motivated and very enthusiastic about their training program. In addition, the group had low levels of apprehension toward automation and expressed a high degree of satisfaction toward their training. However, there were some concerns expressed regarding the deficiencies in some of the training aids and lack of a free-play flight management system training device.

Wiener, Earl L.↗
NASA NTRS2003

Strength training reduces arterial blood pressure but not sympathetic neural activity in young normotensive subjects

The effects of resistance training on arterial blood pressure and muscle sympathetic nerve activity (MSNA) at rest have not been established. Although endurance training is commonly recommended to lower arterial blood pressure, it is not known whether similar adaptations occur with resistance training. Therefore, we tested the hypothesis that whole body resistance training reduces arterial blood pressure at rest, with concomitant reductions in MSNA. Twelve young [21 +/- 0.3 (SE) yr] subjects underwent a program of whole body resistance training 3 days/wk for 8 wk. Resting arterial blood pressure (n = 12; automated sphygmomanometer) and MSNA (n = 8; peroneal nerve microneurography) were measured during a 5-min period of supine rest before and after exercise training. Thirteen additional young (21 +/- 0.8 yr) subjects served as controls. Resistance training significantly increased one-repetition maximum values in all trained muscle groups (P < 0.001), and it significantly decreased systolic (130 +/- 3 to 121 +/- 2 mmHg; P = 0.01), diastolic (69 +/- 3 to 61 +/- 2 mmHg; P = 0.04), and mean (89 +/- 2 to 81 +/- 2 mmHg; P = 0.01) arterial blood pressures at rest. Resistance training did not affect MSNA or heart rate. Arterial blood pressures and MSNA were unchanged, but heart rate increased after 8 wk of relative inactivity for subjects in the control group (61 +/- 2 to 67 +/- 3 beats/min; P = 0.01). These results indicate that whole body resistance exercise training might decrease the risk for development of cardiovascular disease by lowering arterial blood pressure but that reductions of pressure are not coupled to resistance exercise-induced decreases of sympathetic tone.

NASA Discipline Neuroscience↗
NASA NTRS2009

Muscle Volume Increases Following 16 Weeks of Resistive Exercise Training with the Advanced Resistive Exercise Device (ARED) and Free Weights

Space flight-induced muscle atrophy, particularly in the postural and locomotorymuscles, may impair task performance during long-duration space missions and planetary exploration. High intensity free weight (FW) resistive exercise training has been shown to prevent atrophy during bed rest, a space flight analog. NASA developed the Advanced Resistive Exercise Device (ARED) to simulate the characteristics of FW exercise (i.e. constant mass, inertial force) and to be used as a countermeasure during International Space Station (ISS) missions. PURPOSE: To compare the efficacy of ARED and FW training to induce hypertrophy in specific muscle groups in ambulatory subjects prior to deploying ARED on the ISS. METHODS: Twenty untrained subjects were assigned to either the ARED (8 males, 3 females) or FW (6 males, 3 females) group and participated in a periodizedtraining protocol consisting of squat (SQ), heel raise (HR), and deadlift(DL) exercises 3 d wk-1 for 16 wks. SQ, HR, and DL muscle strength (1RM) was measured before, after 8 wks, and after 16 wks of training to prescribe exercise and measure strength changes. Muscle volume of the vastigroup (V), hamstring group (H), hip adductor group (ADD), medial gastrocnemius(MG), lateral gastrocnemius(LG), and deep posterior muscles including soleus(DP) was measured using MRI pre-and post-training. Consecutive cross-sectional images (8 mm slices with a 2 mm gap) were analyzed and summed. Anatomical references insured that the same muscle sections were analyzed pre-and post-training. Two-way repeated measures ANOVAs (p<0.05) were used to test for differences in muscle strength and volume between training devices. RESULTS: SQ, HR, and DL 1RM increased in both FW (SQ: 49+/-6%, HR: 12+/-2%, DL: 23+/-4%) and ARED (SQ: 31+/-4%, HR: 18+/-2%, DL: 23+/-3%) groups. Both groups increased muscle volume in the V (FW: 13+/-2%, ARED: 10+/-2%), H (FW: 3+/-1%, ARED: 3+/-1 %), ADD (FW: 15=/-2%, ARED: 10+/-1%), LG (FW: 7+/-2%, ARED: 4+/-1%), MG (FW: 7+/-2%, ARED: 5+/-2%), and DP (FW: 2+/-1%; ARED: 2+/-1%) after training. There were no between group differences in muscle strength or volume. CONCLUSIONS: The increase in muscle volume and strength following ARED training is not different than FW training. With the training effects similar to FW and a 600 lb load capacity, ARED likely will protect against muscle atrophy in microgravity.

Nash, R. E.↗
NASA NTRS2009

Growing a Training System and Culture for the Ares I Upper Stage Project

In roughly two years time, Marshall Space Flight Center s (MSFC) Mission Operations Laboratory (MOL) has incubated a personnel training and certification program for about 1000 learners and multiple phases of the Ares I Upper Stage (US) project. Previous MOL-developed training programs focused on about 100 learners with a focus on operations, and had enough full-time training staff to develop courseware and provide training administration. This paper discusses 1) the basics of MOL's training philosophy, 2) how creation of a broad, structured training program unfolded as feedback from more narrowly defined tasks, 3) how training philosophy, development methods, and administration are being simplified and tailored so that many Upper Stage organizations can "grow their own" training yet maintain consistency, accountability, and traceability across the project, 4) interfacing with the production contractor's training system and staff, and 5) reaping training value from existing materials and events.

Scott, David W.↗