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At least 37 records · Page 2

Artificial Gravity: Will it Preserve Bone Health on Long-Duration Missions?

Prolonged microgravity exposure disrupts bone, muscle, and cardiovascular homeostasis, sensory-motor coordination, immune function, and behavioral performance. Bone loss, in particular, remains a serious impediment to the success of exploration-class missions by increasing the risks of bone fracture and renal stone formation for crew members. Current countermeasures, consisting primarily of resistive and aerobic exercise, have not yet proven fully successful for preventing bone loss during long-duration spaceflight. While other bone-specific countermeasures, such as pharmacological therapy and dietary modifications, are under consideration, countermeasure approaches that simultaneously address multiple physiologic systems may be more desirable for exploration-class missions, particularly if they can provide effective protection at reduced mission resource requirements (up-mass, power, crew time, etc). The most robust of the multi-system approaches under consideration, artificial gravity (AG), could prevent all of the microgravity-related physiological changes from occurring. The potential methods for realizing an artificial gravity countermeasure are reviewed, as well as selected animal and human studies evaluating the effects of artificial gravity on bone function. Future plans for the study of the multi-system effects of artificial gravity include a joint, cooperative international effort that will systematically seek an optimal prescription for intermittent AG to preserve bone, muscle, and cardiovascular function in human subjects deconditioned by 6 degree head-down-tilt-bed rest. It is concluded that AG has great promise as a multi-system countermeasure, but that further research is required to determine the appropriate parameters for implementation of such a countermeasure for exploration-class missions.

Davis-Street, Janis↗

Priority scheme planning for the robust SSM/PMAD testbed

Whenever mixing priorities of manually controlled resources with those of autonomously controlled resources, the space station module power management and distribution (SSM/PMAD) environment requires cooperating expert system interaction between the planning function and the priority manager. The elements and interactions of the SSM/PMAD planning and priority management functions are presented. Their adherence to cooperating for common achievement are described. In the SSM/PMAD testbed these actions are guided by having a system planning function, KANT, which has insight to the executing system and its automated database. First, the user must be given access to all information which may have an effect on the desired outcome. Second, the fault manager element, FRAMES, must be informed as to the change so that correct diagnoses and operations take place if and when faults occur. Third, some element must engage as mediator for selection of resources and actions to be added or removed at the user's request. This is performed by the priority manager, LPLMS. Lastly, the scheduling mechanism, MAESTRO, must provide future schedules adhering to the user modified resource base.

Elges, Michael R.↗

A 'user friendly' geographic information system in a color interactive digital image processing system environment

NASA's Eastern Regional Remote Sensing Applications Center (ERRSAC) has recognized the need to accommodate spatial analysis techniques in its remote sensing technology transfer program. A computerized Geographic Information System to incorporate remotely sensed data, specifically Landsat, with other relevant data was considered a realistic approach to address a given resource problem. Questions arose concerning the selection of a suitable available software system to demonstrate, train, and undertake demonstration projects with ERRSAC's user community. The very specific requirements for such a system are discussed. The solution found involved the addition of geographic information processing functions to the Interactive Digital Image Manipulation System (IDIMS). Details regarding the functions of the new integrated system are examined along with the characteristics of the software.

Campbell, W. J.↗

Construction and Resource Utilization Explorer (CRUX): Implementing Instrument Suite Data Fusion to Characterize Regolith Hydrogen Resources

CRUX is a modular suite of geophysical and borehole instruments combined with display and decision support system (MapperDSS) tools to characterize regolith resources, surface conditions, and geotechnical properties. CRUX is a NASA-funded Technology Maturation Program effort to provide enabling technology for Lunar and Planetary Surface Operations (LPSO). The MapperDSS uses data fusion methods with CRUX instruments, and other available data and models, to provide regolith properties information needed for LPSO that cannot be determined otherwise. We demonstrate the data fusion method by showing how it might be applied to characterize the distribution and form of hydrogen using a selection of CRUX instruments: Borehole Neutron Probe and Thermal Evolved Gas Analyzer data as a function of depth help interpret Surface Neutron Probe data to generate 3D information. Secondary information from other instruments along with physical models improves the hydrogen distribution characterization, enabling information products for operational decision-making.

in situ resource utilization (ISRU)↗

Space Station Furnace Facility. Volume 2: Summary of technical reports

The Space Station Furnace Facility (SSFF) is a modular facility for materials research in the microgravity environment of the Space Station Freedom (SSF). The SSFF is designed for crystal growth and solidification research in the fields of electronic and photonic materials, metals and alloys, and glasses and ceramics, and will allow for experimental determination of the role of gravitational forces in the solidification process. The facility will provide a capability for basic scientific research and will evaluate the commercial viability of low-gravity processing of selected technologically important materials. In order to accommodate the furnace modules with the resources required to operate, SSFF developed a design that meets the needs of the wide range of furnaces that are planned for the SSFF. The system design is divided into subsystems which provide the functions of interfacing to the SSF services, conditioning and control for furnace module use, providing the controlled services to the furnace modules, and interfacing to and acquiring data from the furnace modules. The subsystems, described in detail, are as follows: Power Conditioning and Distribution Subsystem; Data Management Subsystem; Software; Gas Distribution Subsystem; Thermal Control Subsystem; and Mechanical Structures Subsystem.

Source record↗

The EOSDIS Products Usability for Disaster Response

The focus of the study is to categorize both NRT and standard data products based on applicability to the SDR-defined disaster types. This will identify which datasets from current NASA satellite missions instruments are best suited for disaster response. The distribution metrics of the products that have been used for studying various selected disasters that have occurred over last 5 years will be analyzed that include volume, number of files, number of users, user domains, user country, etc. This data usage analysis will provide information to the data centers staff that can help them develop the functionality and allocate the resources needed for enhanced access and timely availability of the data products that are critical for the time-sensitive analyses.

LANCE↗

Exploration Laboratory Analysis FY13

The Exploration Laboratory Analysis (ELA) project supports the Exploration Medical Capability (ExMC) risk, which is stated as the Risk of Inability to Adequately Treat an Ill or Injured Crew Member, and ExMC Gap 4.05: Lack of minimally invasive in-flight laboratory capabilities with limited consumables required for diagnosing identified Exploration Medical Conditions. To mitigate this risk, the availability of inflight laboratory analysis instrumentation has been identified as an essential capability in future exploration missions. Mission architecture poses constraints on equipment and procedures that will be available to treat evidence-based medical conditions according to the Space Medicine Exploration Medical Conditions List (SMEMCL), and to perform human research studies on the International Space Station (ISS) that are supported by the Human Health and Countermeasures (HHC) element. Since there are significant similarities in the research and medical operational requirements, ELA hardware development has emerged as a joint effort between ExMC and HHC. In 2012, four significant accomplishments were achieved towards the development of exploration laboratory analysis for medical diagnostics. These achievements included (i) the development of high priority analytes for research and medical operations, (ii) the development of Level 1 functional requirements and concept of operations documentation, (iii) the selection and head-to-head competition of in-flight laboratory analysis instrumentation, and (iv) the phase one completion of the Small Business Innovation Research (SBIR) projects under the topic Smart Phone Driven Blood-Based Diagnostics. To utilize resources efficiently, the associated documentation and advanced technologies were integrated into a single ELA plan that encompasses ExMC and HHC development efforts. The requirements and high priority analytes was used in the selection of the four in-flight laboratory analysis performers. Based upon the competition results, a down select process will be performed in the upcoming year. Looking ahead, this unified effort has positioned each element for an in-flight lab analysis demonstration of select diagnostics measurements in the 2015 timeframe.

Krihak, Michael↗

NASA Pilot-Engaged Expert Response Using IBM Watson Technology: Prototype Evaluation of Knowledge Retrieval System

NASA Langley Research Center and IBM have been investigating the use of IBM Watson technology in aerospace research and development. One application of Watson technology is the Pilot-Engaged Expert Response (PEER) use case. The PEER system is envisioned as an in-cockpit advisor that will act as a source of situationally-relevant information for pilots and other flight crew members to assist in decision making about real-time events and situations that arise in the course of aircraft operations. PEER will make available vast stores of knowledge and information quickly and directly, putting important informational resources where they are needed most. IBM has worked with NASA to develop an architecture and articulate a roadmap for the development of the PEER system. That vision is built around Watson Discovery Advisor (WDA) software solution, derived from IBM's Jeopardy!-winning automatic question answering system. PEER makes use of WDA's sophisticated question-answering capabilities as its core, adding important User Interface components and other customizations for the cockpit environment, including communication with flight systems and other external data sources. The development plan for PEER includes four development stages, with the current project constituting the first phase. In this project, a prototype instance of PEER was successfully adapted to the aviation domain, enabling users to ask questions about aviation topics and receive useful and accurate answers to these questions. Major tasks accomplished include the development of procedures for domain adaptation through automatic lexicon extraction from domain glossaries; generation of question-answer training data which was used to train the system; and assessment of the effectiveness of domain adaptation, which showed a dramatic improvement in the ability of the PEER system to answer domain-relevant questions. In addition, the vision for the PEER system was pushed forward by the articulation of a plan for the automatic enhancement of question-answering with contextual information. This initial phase focused on two main goals: 1) the targeted domain adaptation of the underlying WDA system to the aviation domain; and, 2) the design of the software systems needed to leverage flight-contextual data. Domain adaptation of the WDA system proceeds via three main activities: Domain data ingestion, lexical customization and model training. A textual corpus consisting of 1,147 individual documents with more than 7.5 million words of text was ingested into the system and this served as the basis of all further development. A domain lexicon of over 3,500 aviation-domain terms was semi-automatically generated from domain documents and used to train the system. In addition, a set of over 500 question-answer (QA) pairs relevant to the PEER use case was developed; these were used to train and assess the system. These important first steps established the basis for the PEER system. In addition, steps were taken towards the integration of the PEER system into the cockpit environment with the development of a functional design for the Contextual Data Augmentation (CDA) subsystem. This subsystem brings to bear contextual data to improve system responses. It has three main submodules: the Contextual Data Collection module, the Contextual Data Selection module, and the Contextual QA Augmentation module. These modules form a processing pipeline that addresses the problems associated with automatically integrating information from external resources into the knowledge-retrieval mechanism.

Machine learning↗

Regional Rates of Young US Forest Growth Estimated From Annual Landsat Disturbance History and IKONOS Stereo Imagery

Forests of the Contiguous United States (CONUS) have been found to be a large contributor to the global atmospheric carbon sink. The magnitude and nature of this sink is still uncertain and recent studies have sought to define the dynamics that control its strength and longevity. The Landsat series of satellites has been a vital resource to understand the long-term changes in land cover that can impact ecosystem function and terrestrial carbonstock. We combine annual Landsat forest disturbance history from 1985 to 2011 with single date IKONOS stereoimagery to estimate the change in young forest canopy height and above ground live dry biomass accumulation for selected sites in the CONUS. Our approach follows an approximately linear growth rate following clearing over short intervals and does not estimate the distinct non-linear growth rate over longer intervals.We produced canopy height models by differencing digital surface models estimated from IKONOS stereo pairs with national elevation data (NED). Correlations between height and biomass were established independently using airborne LiDAR, and then applied to the IKONOS-estimated canopy height models. Graphing current biomass against time since disturbance provided biomass accumulation rates. For 20 study sites distributed across five regions of the CONUS, 19 showed statistically significant recovery trends (p is less than 0.001) with canopy growth from 0.26 m yr-1to 0.73 m yr-1. Above ground live dry biomass (AGB) density accumulation ranged from 1.31 t/ha yr-1 to 12.47 t/ha yr-1. Mean forest AGB accumulationwas 6.31 t/ha yr-1 among all sites with significant growth trends. We evaluated the accuracy of our estimates by comparing to field estimated site index curves of growth, airborne LiDAR data, and independent model predictions of C accumulation. Growth estimates found with this approach are consistent with site index curves and total biomass estimates fall within the range of field estimates. This is aviable approach to estimate forest biomass accumulation in regions with clear-cut harvest disturbances.

Neigh, Christopher S. R.↗

Modification of the International Space Station USOS to Support Installation and Activation of the Node 3 Element

The International Space Station (ISS) program is nearing an assembly complete configuration with the addition of the final resource node module in early 2010. The Node 3 module will provide critical functionality in support of permanent long duration crews aboard ISS. The new module will permanently house the regenerative Environment Control and Life Support Systems (ECLSS) and will also provide important habitability functions such as waste management and exercise facilities. The ISS program has selected the Port side of the Node 1 "Unity" module as the permanent location for Node 3 which will necessitate architecture changes to provide the required interfaces. The USOS ECLSS fluid and ventilation systems, Internal Thermal Control Systems, and Avionics Systems require significant modifications in order to support Node 3 interfaces at the Node 1 Port location since it was not initially designed for that configuration. This paper outlines the design, development, certification, and implementation of these changes in support of ISS assembly complete.

Link, Dwight E., Jr.↗

Methods and circuitry for reconfigurable SEU/SET tolerance

A device is disclosed in one embodiment that has multiple identical sets of programmable functional elements, programmable routing resources, and majority voters that correct errors. The voters accept a mode input for a redundancy mode and a split mode. In the redundancy mode, the programmable functional elements are identical and are programmed identically so the voters produce an output corresponding to the majority of inputs that agree. In a split mode, each voter selects a particular programmable functional element output as the output of the voter. Therefore, in the split mode, the programmable functional elements can perform different functions, operate independently, and/or be connected together to process different parts of the same problem.

Shuler, Jr., Robert L.↗

Aeroelastic Tailoring of Transport Aircraft Wings: State-of-the-Art and Potential Enabling Technologies

This paper provides a brief overview of the state-of-the-art for aeroelastic tailoring of subsonic transport aircraft and offers additional resources on related research efforts. Emphasis is placed on aircraft having straight or aft swept wings. The literature covers computational synthesis tools developed for aeroelastic tailoring and numerous design studies focused on discovering new methods for passive aeroelastic control. Several new structural and material technologies are presented as potential enablers of aeroelastic tailoring, including selectively reinforced materials, functionally graded materials, fiber tow steered composite laminates, and various nonconventional structural designs. In addition, smart materials and structures whose properties or configurations change in response to external stimuli are presented as potential active approaches to aeroelastic tailoring.

Jutte, Christine↗

Snow cover, snowmelt and runoff in the Himalayan River basins

Not withstanding the seasonal vagaries of both rainfall amount and snowcover extent, the Himalayan rivers retain their basic perennial character. However, it is the component of snowmelt yield that accounts for some 60 to 70 percent of the total annual flow volumes from Hamilayan watersheds. On this large hydropotential predominantly depends the temporal performance of hydropower generation and major irrigation projects. The large scale effects of Himalayan snowcover on the hydrologic responses of a few selected catchments in western Himalayas was studied. The antecedent effects of snowcover area on long and short term meltwater yields can best be analyzed by developing appropriate hydrologic models forecasting the pattern of snowmelt as a function of variations in snowcover area. It is hoped that these models would be of practical value in the management of water resources. The predictability of meltwater for the entire snowmelt season was studied, as was the concurrent flow variation in adjacent watersheds, and their hydrologic significance. And the applicability of the Snowmelt-Runoff Model for real time forecast of daily discharges during the major part of the snowmelt season is examined.

Dey, B.↗

Resource Allocation Planning Helper (RALPH): Lessons learned

The current task of Resource Allocation Process includes the planning and apportionment of JPL's Ground Data System composed of the Deep Space Network and Mission Control and Computing Center facilities. The addition of the data driven, rule based planning system, RALPH, has expanded the planning horizon from 8 weeks to 10 years and has resulted in large labor savings. Use of the system has also resulted in important improvements in science return through enhanced resource utilization. In addition, RALPH has been instrumental in supporting rapid turn around for an increased volume of special what if studies. The status of RALPH is briefly reviewed and important lessons learned from the creation of an highly functional design team are focused on through an evolutionary design and implementation period in which an AI shell was selected, prototyped, and ultimately abandoned, and through the fundamental changes to the very process that spawned the tool kit. Principal topics include proper integration of software tools within the planning environment, transition from prototype to delivered to delivered software, changes in the planning methodology as a result of evolving software capabilities and creation of the ability to develop and process generic requirements to allow planning flexibility.

Durham, Ralph↗

Turning Limitations into Opportunities in the Development of the Orion Medical System: Incorporation of mHealth Devices

INTRODUCTION: Selection of medical devices for the Orion medical system is a complex task which is dependent on the current state of terrestrial technology. In this work we review the interplay between NASA requirements, constraints, and opportunities for synergy during the development of the Orion medical system. METHODS: The “plan to treat” list of conditions, and subsequently the medical resource list for the Orion Artemis II lunar flyby mission was completed using semi-quantitative methods. During this process, some medical resources were excluded to comply with mass and volume limits, while other resources applicable to multiple medical requirements were prioritized for inclusion. Choices were also examined considering NASA level of care standards for the Artemis design reference missions. As a means to optimize capabilities in spite of mass and volume constraints, ideas for integration of multiple devices into a single platform were explored, including a ‘hackathon’ challenge which was conducted to generate and evaluate concepts for combining medical devices into a single app-based mobile device (ultrasound, ECG, etc.). RESULTS: The Orion team identified 128 medical conditions that we “plan to treat”, with 139 unique medical resources to address these conditions, including 5 digital diagnostic devices (ECG, otoscope, stethoscope, pulse oximeter, and blood pressure monitor). During selection of these digital devices the team noted that miniaturized medical devices often use mobile device platforms (mHealth), some displaying and transmitting data exclusively via mobile device. Of the 5 initially selected devices, all are capable of mobile connection, one which cannot function without a mobile device (ECG). Furthermore, only one of these devices connects natively to a Windows platform, which is currently the only operating system available on Orion. DISCUSSION: Significant savings in mass and volume as well as training and usability improvements can be achieved by leveraging mHealth technologies. However, the platform presents significant challenges for deployment within the Artemis Program including lack of internet connectivity, incompatible operating systems, and radiation concerns. Each of these drawbacks are surmountable with investment in the supporting vehicle architecture, which may become necessary to support the technology trends seen in commercially available medical devices today. Objective: Learn about the opportunities and challenges of leveraging mHealth devices in the development of medical capabilities for austere environments. Learn about the constraints of the NASA spaceflight environment with regards to digital medical device integration.

Douglas Ebert↗

Minimizing distortion in truss structures -- a Hopfield network solution

Distortions in truss structures can result from random errors in elemental lengths that are typical of a manufacturing process. These distortions may be minimized by an optimal selection of elements from those available for placement between the prescribed nodes -- a combinatorial optimization problem requiring significant investment of computational resource for all but the smallest problems. The present paper describes a formulation in which near-optimal element assignments are obtained as minimum energy, stable states, of an analogous Hopfield neural network. This requires mapping of the optimization problem into an energy function of the appropriate Lyapunov form. The computational architecture is ideally suited to a parallel processor implementation and offers significant savings in computational effort. A numerical implementation of the approach is discussed with reference to planar truss problems.

Fu, B.↗

Minimizing distortion in truss structures - A Hopfield network solution

Distortions in truss structures can result from random errors in element lengths that are typical of a manufacturing process. These distortions may be minimized by an optimal selection of elements from those available for placement between the prescribed nodes - a combinatorial optimization problem requiring significant investment of computational resource for all but the smallest problems. The present paper describes a formulation in which near-optimal element assignments are obtained as minimum-energy stable states, of an analogous Hopfield neural network. This requires mapping of the optimization problem into an energy function of the appropriate Liapunov form. The computational architecture is ideally suited to a parallel processor implementation and offers significant savings in computational effort. A numerical implementation of the approach is discussed with reference to planar truss problems.

Fu, B.↗

LACIE/ERIPS software system summary

The Earth resources interactive processing system (ERIPS) supports LACIE by classifying LANDSAT sensed data on the basis of the statistical similarity to those portions which were identified by analysts. The development and capabilities of the ERIPS software system are described with emphasis on (1) system requirements; (2) LACIE/ERIPS hardware; (3) system functions; (4) pattern recognition concept; and (5) LACIE/ERIPS data bases. Algorithms used in LACIE/ERIPS for statistics, divergence, feature selection, classification, registration, adaptive clustering, iterative clustering, clustering report functions, Sun angle correction, mean level adjustment, and bias correction are appended.

Johnson, C. L.↗