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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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At least 73 records · Page 4
All sourcesNASA NTRSDOE OSTI
NASA NTRS2016

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post - Bed Rest and Spaceflight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. These alterations may disrupt crewmembers' ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts would be affected would improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual spaceflight, which crewmembers are likely to experience the greatest challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures. Our approach includes: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features, using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; and 3) assessment of genotypic markers of genetic polymorphisms in the catechol-O-methyl transferase, dopamine receptor D2, and brain-derived neurotrophic factor genes and genetic polymorphisms of alpha2-adrenergic receptors that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate that these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration spaceflight and exposure to an analog bed rest environment. We will be conducting a retrospective study, leveraging data already collected from relevant ongoing or completed bed rest and spaceflight studies. These data will be combined with predictor metrics that will be collected prospectively (as described for behavioral, brain imaging and genomic measures) from these returning subjects to build models for predicting post-mission (bed rest - non-astronauts or space flight - astronauts) adaptive capability as manifested in their outcome measures. To date we have completed a study on 15 normal subjects with all of the above measures. In this presentation we will discuss the optimized set of tests for predictive metrics to be used for evaluating post mission adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive capacity, brain structure and functional capacities, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to ensure expected outcomes.

Mulavara, A. P.↗
NASA NTRS2017

Behavioral, Brain Imaging and Genomic Measures to Predict Functional Outcomes Post-Bed Rest and Space Flight

Astronauts experience sensorimotor disturbances during their initial exposure to microgravity and during the re-adaptation phase following a return to an Earth-gravitational environment. These alterations may disrupt crewmembers' ability to perform mission critical functional tasks requiring ambulation, manual control and gaze stability. Interestingly, astronauts who return from spaceflight show substantial differences in their abilities to readapt to a gravitational environment. The ability to predict the manner and degree to which individual astronauts are affected will improve the effectiveness of countermeasure training programs designed to enhance sensorimotor adaptability. For such an approach to succeed, we must develop predictive measures of sensorimotor adaptability that will allow us to foresee, before actual spaceflight, which crewmembers are likely to experience greater challenges to their adaptive capacities. The goals of this project are to identify and characterize this set of predictive measures. Our approach includes: 1) behavioral tests to assess sensory bias and adaptability quantified using both strategic and plastic-adaptive responses; 2) imaging to determine individual brain morphological and functional features, using structural magnetic resonance imaging (MRI), diffusion tensor imaging, resting state functional connectivity MRI, and sensorimotor adaptation task-related functional brain activation; and 3) assessment of genetic polymorphisms in the catechol-O-methyl transferase, dopamine receptor D2, and brain-derived neurotrophic factor genes and genetic polymorphisms of alpha2-adrenergic receptors that play a role in the neural pathways underlying sensorimotor adaptation. We anticipate that these predictive measures will be significantly correlated with individual differences in sensorimotor adaptability after long-duration spaceflight and exposure to an analog bed rest environment. We will be conducting a retrospective study, leveraging data already collected from relevant ongoing or completed bed rest and spaceflight studies. This data will be combined with predictor metrics that will be collected prospectively (as described for behavioral, brain imaging and genomic measures) from these returning subjects to build models for predicting post spaceflight and bed rest adaptive capability. In this presentation we will discuss the optimized set of tests for predictive metrics to be used for evaluating post mission adaptive capability as manifested in their outcome measures. Comparisons of model performance will allow us to better design and implement sensorimotor adaptability training countermeasures against decrements in post-mission adaptive capability that are customized for each crewmember's sensory biases, adaptive ability, brain structure, brain function, and genetic predispositions. The ability to customize adaptability training will allow more efficient use of crew time during training and will optimize training prescriptions for astronauts to mitigate the deleterious effects of spaceflight.

Mulavara, A. P.↗
NASA NTRS2011

Systems, methods and apparatus for quiesence of autonomic safety devices with self action

Systems, methods and apparatus are provided through which in some embodiments an autonomic environmental safety device may be quiesced. In at least one embodiment, a method for managing an autonomic safety device, such as a smoke detector, based on functioning state and operating status of the autonomic safety device includes processing received signals from the autonomic safety device to obtain an analysis of the condition of the autonomic safety device, generating one or more stay-awake signals based on the functioning status and the operating state of the autonomic safety device, transmitting the stay-awake signal, transmitting self health/urgency data, and transmitting environment health/urgency data. A quiesce component of an autonomic safety device can render the autonomic safety device inactive for a specific amount of time or until a challenging situation has passed.

Hinchey, Michael G.↗
NASA NTRS2001

Saturation: An efficient iteration strategy for symbolic state-space generation

This paper presents a novel algorithm for generating state spaces of asynchronous systems using Multi-valued Decision Diagrams. In contrast to related work, the next-state function of a system is not encoded as a single Boolean function, but as cross-products of integer functions. This permits the application of various iteration strategies to build a system's state space. In particular, this paper introduces a new elegant strategy, called saturation, and implements it in the tool SMART. On top of usually performing several orders of magnitude faster than existing BDD-based state-space generators, the algorithm's required peak memory is often close to the nal memory needed for storing the overall state spaces.

Ciardo, Gianfranco↗
NASA NTRS1993

Robust controllers for the Middeck Active Control Experiment using Popov controller synthesis

Recent work in robust control with real parameter uncertainties has focused on absolute stability and its connections to real mu theory. In particular, the research has investigated the Popov stability criterion and its associated Lur'e-Postnikov Liapunov functions. State space representations of this Popov stability analysis tests are included in an H2 design formulation to provide a powerful technique for robust controller synthesis. This synthesis approach uses a state space optimization procedure to design controllers that minimize an overbound of an H2 cost functional and satisfy stability analysis tests based on the Popov multiplier. The controller and stability multiplier coefficients are optimized simultaneously, which avoids the iteration and curve-fitting procedures required by the D-K algorithm of mu synthesis. While previous work has demonstrated this synthesis approach on benchmark control problems, the purpose of this paper is to use Popov controller synthesis to design robust compensators for the Middeck Active Control Experiment (MACE).

How, Jonathan P.↗
NASA NTRS1980

Role of the middle ear muscle apparatus in mechanisms of speech signal discrimination

A method of impedance reflexometry was used to examine 101 students with hearing impairment in order to clarify the interrelation between speech discrimination and the state of the middle ear muscles. Ability to discriminate speech signals depends to some extent on the functional state of intraaural muscles. Speech discrimination was greatly impaired in the absence of stapedial muscle acoustic reflex, in the presence of low thresholds of stimulation and in very small values of reflex amplitude increase. Discrimination was not impeded in positive AR, high values of relative thresholds and normal increase of reflex amplitude in response to speech signals with augmenting intensity.

Moroz, B. S.↗
NASA NTRS2017

Generating Real-Time Robotics Control Software from SysML

In this paper, we outline an approach for autogenerating real-time robotics control code from hierarchical state machines and hardware configurations encoded in Systems Modeling Language (SysML). We propose a software architecture that provides an abstract SysML layer with access to device state information and a set of primitive device commands, such as move actuator and release brake, allowing a user to build up a complete functional state machine directly in SysML. The SysML diagram is then exported to a standard SCXML file format and subsequently used to auto-generate hardware control code. Once this architecture is in place, the only explicit code elements that need to be written are the primitive device commands, which can be easily unit tested and reused across different systems. The motivation for this work was the need for a test bed that enables the rapid prototyping of mechanisms and control algorithms for a spacecraft that could ultimately be used for preparing Martian rock samples for their return to Earth. To this end, our software system was also designed to allow for the run-time specification of the hardware layout in SysML, with the hardware-level control functions kept agnostic to the specific parameters or communication bus of any particular device. Further, we outline a system for specifying both the state machine and hardware configuration in the MagicDraw IDE in such a way that the system can be simulated before any code is generated. The resultant software system is easy to debug, understand, and allows users to choose how much information is encoded as a visual or text-based representation.

Godart, Peter↗
NASA NTRS1996

Long-term modifications of synaptic efficacy in the human inferior and middle temporal cortex

The primate temporal cortex has been demonstrated to play an important role in visual memory and pattern recognition. It is of particular interest to investigate whether activity-dependent modification of synaptic efficacy, a presumptive mechanism for learning and memory, is present in this cortical region. Here we address this issue by examining the induction of synaptic plasticity in surgically resected human inferior and middle temporal cortex. The results show that synaptic strength in the human temporal cortex could undergo bidirectional modifications, depending on the pattern of conditioning stimulation. High frequency stimulation (100 or 40 Hz) in layer IV induced long-term potentiation (LTP) of both intracellular excitatory postsynaptic potentials and evoked field potentials in layers II/III. The LTP induced by 100 Hz tetanus was blocked by 50-100 microM DL-2-amino-5-phosphonovaleric acid, suggesting that N-methyl-D-aspartate receptors were responsible for its induction. Long-term depression (LTD) was elicited by prolonged low frequency stimulation (1 Hz, 15 min). It was reduced, but not completely blocked, by DL-2-amino-5-phosphonovaleric acid, implying that some other mechanisms in addition to N-methyl-DL-aspartate receptors were involved in LTD induction. LTD was input-specific, i.e., low frequency stimulation of one pathway produced LTD of synaptic transmission in that pathway only. Finally, the LTP and LTD could reverse each other, suggesting that they can act cooperatively to modify the functional state of cortical network. These results suggest that LTP and LTD are possible mechanisms for the visual memory and pattern recognition functions performed in the human temporal cortex.

NASA Discipline Neuroscience↗
NASA NTRS1972

Miniature biotelemeter giving 10 channels of wideband biomedical data.

A miniature biotelemeter has been developed for sensing and transmitting multiple channels of wideband biomedical data over a radio link. Its small size and weight make it capable of being carried by free-moving laboratory animals as small as rats. Ten data channels each of 5-kHz data bandwidth are provided to permit monitoring of a wide variety of physiological signals. Multichannel telemetry of electroencephalograms, electrocardiograms, electromyograms, state functions, and dynamic processes such as blood flow and body chemistry are possible applications. Utilization of newly available monolithic chip components, low-power COS/MOS MSI digital logic, and state-of-the-art hybrid mounting techniques makes this novel device useful for both research and clinical bioinstrumentation.

Carraway, J.↗
NASA NTRS2018

Modeling Spacecraft Safe Mode Events

Spacecraft enter a ‘safe mode’ to protect the vehicle when a potentially harmful anomaly occurs. This minimally functioning state isolates faults, establishes contact with Earth, and orients the vehicle into a power positive attitude until operators intervene. Though ‘safings’ are inherently unpredictable, mission teams build in time margin during operations to determine root causes and restore functionality. Planning and managing this margin is both critical and enabling on mission architectures dependent on near-continuous operability – such as a low-thrust electric propulsion mission. To better quantify the occurrences and severity of safe mode anomalies, the Jet Propulsion Laboratory (JPL) has assembled a database of safings from past and active missions. Currently nearly 240 records are captured from 21 beyond-Earth missions, stemming from a collaboration between teams at JPL, Ames Research Center, Goddard Space Flight Center, and the Johns Hopkins University Applied Physics Laboratory. This paper discusses the event database, explores a statistical approach in modeling the occurrences and severity of safing events, presents a simulation technique, and details recommendations and future work to benefit future concepts.

Nicholas, Austin↗
NASA NTRSDate not supplied

Adaptive Learning for Reliability Analysis using Support Vector Machines

A novel algorithm is presented for adaptive learning of an unknown function that separates two regions of a domain.In the context of reliability analysis these two regions represent the failure domain, where a set of constraints or requirements are violated, and a safe domain where they are satisfied. The Limit State Function (LSF) separates these two regions. Evaluating the constraints for a given parameter point requires the evaluation of a computational model that may well be expensive. For this reason we wish to construct a meta-model that can estimate the LSFas accurately as possible, using only a limited amount of training data. This work presents an adaptive strategy employing a Support Vector Machine (SVM) as a meta-model to provide a semi-algebraic approximation of the LSF.We describe an optimization process that is used to select informative parameter points to add to training data at each iteration to improve the accuracy of this approximation. A formulation is introduced for bounding the predictions of the meta-model; in this way we seek to incorporate this aspect of Gaussian Process Models (GPMs) within anSVM meta-model. Finally, we apply our algorithm to two benchmark test cases, demonstrating performance that is comparable with, if not superior, to a standard technique for reliability analysis that employs GPMs

Adaptive learning↗
NASA NTRS1975

Physiological mechanisms of the effect of weightlessness on the body

Experimental data show that physiological reactions observed under weightlessness conditions are caused by: (1) The direct effect of weightlessness, as a consequence of decrease (""disappearance'') of the weight of body tissues and organs; and (2) the mediated effect of weightlessness, as a result of changes in the functional state of the central nervous system and the cooperative work of the analyzers. The human body adopts to weightless conditions under the prolonged effects of it. In this case, four periods can be distinguished: The first period, a transitional process lasting from 1 to 24 hours; second period, initial adaptation to conditions of weightlessness and readjustment of all functional systems of the body; the third period, adaptation to the unusual mechanical conditions of the external environment, lasting from 3 to 8 days and more; and the fourth period, the stage of possible imbalance of the functions and the systems of some astronauts, as a result of the prolonged effect of weightlessness.

Kasyan, I. I.↗
NASA NTRS1997

Efficient Evaluation and Optimization of Structural Reliability

Use of approximations for calculating the structural failure probability under uncertainties is a necessary aspect. But efficient use of suitable approximations at different stages of reliability prediction and design makes this valuable tool practical for many large scale structures. This research addresses the modern approximation concepts and their utility in structural reliability estimation. Emphasis is placed on building higher order approximations using intervening variables to closely represent the nonlinear limit state functions. Several test problems with highly nonlinear performance functions are used to demonstrate the accuracy of the proposed method. Many of the structural problems are modeled and simulated using the finite element methods (FEM) for obtaining a detailed structural response. FEM is a computationally intensive numerical procedure with a large number of degrees of freedom. With an increase in the complexity of the structural model and the multidisciplinary nature of analyses, the number of limit states and their computation increases very significantly. The requirement of frequent repetitive analysis of the structure hinders the utility of any tool and discourages that approach from being used. One particular tool which faces this difficulty is the computation of the structural reliability under parametric uncertainties.

Grandhi, Ramana V.↗