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At least 127 records · Page 7

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NASA NTRS2000

Mid-Infrared Spectroscopy of Persistent Leonid Trains

The first infrared spectroscopy in the 3-13 micron region has been obtained of several persistent Leonid meteor trains with two different instrument types, one at a desert ground-based site and the other on-board a high-flying aircraft. The spectra exhibit common structures assigned to enhanced emissions of warm CH4, CO2, CO and H2O which may originate from heated trace air compounds or materials created in the wake of the meteor. This is the first time that any of these molecules has been observed in the spectra of persistent trains. Hence, the mid-IR observations offer a new perspective on the physical processes that occur in the path of the meteor at some time after the meteor itself has passed by. Continuum emission is observed also, but its origin has not yet been established. No 10 micron dust emission feature has been observed.

Russell, Ray W.↗

NASA NTRS1975

Remote terminal system evaluation

An Earth Resources Data Processing System was developed to evaluate the system for training, technology transfer, and data processing. In addition to the five sites included in this project two other sites were connected to the system under separate agreements. The experience of these two sites is discussed. The results of the remote terminal project are documented in seven reports: one from each of the five project sites, Purdue University, and an overview report summarizing the other six reports.

Phillips, T. L.↗

NASA NTRS1994

Meeting the challenges of installing a mobile robotic system

The challenges of integrating a mobile robotic system into an application environment are many. Most problems inherent to installing the mobile robotic system fall into one of three categories: (1) the physical environment - location(s) where, and conditions under which, the mobile robotic system will work; (2) the technological environment - external equipment with which the mobile robotic system will interact; and (3) the human environment - personnel who will operate and interact with the mobile robotic system. The successful integration of a mobile robotic system into these three types of application environment requires more than a good pair of pliers. The tools for this job include: careful planning, accurate measurement data (as-built drawings), complete technical data of systems to be interfaced, sufficient time and attention of key personnel for training on how to operate and program the robot, on-site access during installation, and a thorough understanding and appreciation - by all concerned - of the mobile robotic system's role in the security mission at the site, as well as the machine's capabilities and limitations. Patience, luck, and a sense of humor are also useful tools to keep handy during a mobile robotic system installation. This paper will discuss some specific examples of problems in each of three categories, and explore approaches to solving these problems. The discussion will draw from the author's experience with on-site installations of mobile robotic systems in various applications. Most of the information discussed in this paper has come directly from knowledge learned during installations of Cybermotion's SR2 security robots. A large part of the discussion will apply to any vehicle with a drive system, collision avoidance, and navigation sensors, which is, of course, what makes a vehicle autonomous. And it is with these sensors and a drive system that the installer must become familiar in order to foresee potential trouble areas in the physical, technical, and human environment.

Decorte, Celeste↗

NASA NTRS2007

Crew/Robot Coordinated Planetary EVA Operations at a Lunar Base Analog Site

Under the direction of NASA's Exploration Technology Development Program, robots and space suited subjects from several NASA centers recently completed a very successful demonstration of coordinated activities indicative of base camp operations on the lunar surface. For these activities, NASA chose a site near Meteor Crater, Arizona close to where Apollo Astronauts previously trained. The main scenario demonstrated crew returning from a planetary EVA (extra-vehicular activity) to a temporary base camp and entering a pressurized rover compartment while robots performed tasks in preparation for the next EVA. Scenario tasks included: rover operations under direct human control and autonomous modes, crew ingress and egress activities, autonomous robotic payload removal and stowage operations under both local control and remote control from Houston, and autonomous robotic navigation and inspection. In addition to the main scenario, participants had an opportunity to explore additional robotic operations: hill climbing, maneuvering heaving loads, gathering geo-logical samples, drilling, and tether operations. In this analog environment, the suited subjects and robots experienced high levels of dust, rough terrain, and harsh lighting.

Diftler, M. A.↗

NASA NTRS2017

NASA Sample Return Missions: Recovery Operations

The Utah Test and Training Range (UTTR), southwest of Salt Lake City, Utah, is the site of all NASA unmanned sample return missions. To date these missions include the Genesis solar wind samples (2004) and Stardust cometary and interstellar dust samples (2006). NASA’s OSIRIS-REx Mission will return its first asteroid sample at UTTR in 2023.

Pace, L. F.↗

NASA NTRSDate not supplied

Mapping Post-fire Conifer Regeneration using Snow-on Imagery

The 2000 Jasper Fire in the Black Hills of South Dakota was the largest wildfire to date in the region, burning over 83,000 acres of ponderosa pine forest. In collaboration with partners from the United States Forest Service (USFS) Black Hills Experimental Forest, USFS Rocky Mountain Research Station, and United States Geological Survey Geosciences and Environmental Change Science Center, we characterized post-fire forest regeneration within high severity burn patches. We accomplished this by implementing novel conifer detection techniques using a snow index mask to create a winter, snow-on image composite from Landsat 8 Operational Land Imager (OLI) and Sentinel-2 Multispectral Instrument (MSI) data. We utilized 2015 USFS stem maps of field-observed regeneration plots and ocularly sampled reforestation sites planted from 2001–2013. The field data and imagery were used to train a Random Forest (RF) model in Google Earth Engine. The RF model classified conifer regeneration density as low, medium, or high across the high-severity burn area with an overall accuracy of 81.3% for 2021. Approximately 45.9% of the high-severity burn area had low or no regeneration (0-40 trees per acre) 20 years post-fire. Given our partners' desire to find easily accessible low conifer regeneration zones, we identified 4,079 acres of priority planting sites that were within 1,500 feet of roads, had not been planted previously, and were larger than 50 acres. This method supports the use of snow-on imagery as a successful technique to identify conifer regeneration in a post-wildfire landscape.

Yeshey Seldon↗

NASA NTRSDate not supplied

From Simulation to Reality With Random Noise

The challenging environment of autonomous vehicle (AV) navigation necessitates certain functions be performed by deep neural networks. Optimizing these models involves collecting vast quantities of domain-specific training data and ensuring that the dataset is representative of expected conditions. High-fidelity simulation plays a vital role in making this process feasible, allowing a wide range of scenarios to be explored at low cost. However, learning from simulation introduces subtle biases into models, which can degrade real-world performance in unpredictable ways. This effect can be mitigated with learning schemes specialized to bridge distributional shifts (transfer learning). Given the complex nature of these methods, the underlying models, and their environments, meaningfully evaluating performance is notstraight forward. Many unrelated factors can effect an improvement in generalization accuracy, but a full ablation analysis is often difficult. To tease out signal from noise, it is necessary to understand how transfer learning performance is affected by noise itself. The goals of this paper are (i) to establish a domain randomization baseline for a simple classification transfer learning task and (ii) to validate the RRAV testbed as a platform for further research in sim-to-real learning. We generate imagery from a simulation of NASA Ames Research Center and train a small convolutional neural network (ConvNet) to classify position relative to a centerline. Further models are trained with different types of noise progressively added to the data. The models are deployed aboard the on-site test vehicle to test real-world performance. In our experiments, we find that such naive domain randomization raises sim-to-real accuracy from 64% to 79%, while training directly on real data yields an 89% accuracy ceiling. These results suggest that the isolated mechanism of domain randomization can significantly improve generalization.

simulation↗

NASA NTRS2017

Medical Support for ISS Crewmember Training in Star City, Russia

Medical support of spaceflight training operations across international lines is a unique circumstance with potential applications to other aerospace medicine support scenarios. KBRwyle's Star City Medical Support Group (SCMSG) has fulfilled this role since the Mir-Shuttle era, with extensive experience and updates to share with the greater AsMA community. OVERVIEW: The current Soyuz training flow for assigned ISS crewmembers takes place in Star City, Russia. Soyuz training flow involves numerous activities that pose potential physical and occupational risks to crewmembers, including centrifuge runs and pressurized suit simulations at ambient and hypobaric pressures. In addition, Star City is a relatively remote location in a host nation with variable access to reliable, Western-standard medical care. For these reasons, NASA's Human Health & Performance contract allocates full-time physician support to assigned ISS crewmembers training in Star City. The Star City physician also treats minor injuries and illnesses as needed for both long- and short-term NASA support personnel traveling in the area, while working to develop and maintain relationships with local health care resources in the event of more serious medical issues that cannot be treated on-site. The specifics of this unique scope of practice will be discussed. SIGNIFICANCE: ISS crewmembers training in Star City are at potential physical and occupational risk of trauma or dysbarism during nominal Soyuz training flow, requiring medical support from an on-duty aerospace medicine specialist. This support maintains human health and performance by preserving crewmember safety and well-being for mission success; sharing information regarding this operational model may contribute to advances in other areas of international, military, and civilian operational aerospace medicine.

Chough, Natacha↗

NASA NTRS2017

Medical Support for ISS Crewmember Training in Star City, Russia

Chough, Natacha↗

NASA NTRS2014

Global Land Survey Impervious Mapping Project Web Site

The Global Land Survey Impervious Mapping Project (GLS-IMP) aims to produce the first global maps of impervious cover at the 30m spatial resolution of Landsat. The project uses Global Land Survey (GLS) Landsat data as its base but incorporates training data generated from very high resolution commercial satellite data and using a Hierarchical segmentation program called Hseg. The web site contains general project information, a high level description of the science, examples of input and output data, as well as links to other relevant projects.

Impervious cover↗

NASA NTRS1978

Payload integration and operations

Integration and operation of Spacelab payloads presents major challenges to engineering disciplines in areas of ground operations and flight mission operations. The integration of ground operations encompasses activities performed by the instrument developers and principal investigators and by the centralized payload integration site and launch site. The payload will be operated on orbit by a payload crew trained in payload experimentation and by a payload operations control center where investigator science groups and operations personnel are prepared to provide support. The payload mission planning, control center, data processing facility and operations are developed and verified prior to realtime flight operations. The mission management approach to minimize program costs and impacts to payloads and the Space Transportation System/Spacelab accommodations is presented.

Hall, R. R.↗

NASA NTRS1996

Practice Oriented Master's in Optics

This award provides support for the development and initial implementation of an interdisciplinary Master's Program with a concentration in Optics and Photonics Technology. This program is a collaboration between the University of Alabama in Huntsville, Alabama A and M University, Northwest Shoals Community College, the NASA Marshall Space Flight Center, the U.S. Army Missile Command, Oak Ridge National Laboratory, the National Institute for Standards and Technology, Advanced Optical Systems Inc., Dynetics, Inc., Hughes Danbury Optical Systems, Inc., Nichols Research Corp., SCI Inc., and Speedring Inc. These organizations have been participating fully in the design, development and implementation of the program. This program is directed at both traditional students as well as government and defense workers who desire specialty education in practical optics and optical systems design and manufacturing. It is intended to produce highly trained graduates who can solve practical problems, and includes an on-site practicum at a manufacturing location. The broad curriculum of this program emphasizes the fundamentals of optics, optical systems manufacturing and testing, and the principles of design and manufacturing-to-cost for commercial optical products. The degrees offered are the MS in Physics and the MSE in Electrical Engineering with concentration in Optics and Photonics Technology through the Physics and Electrical and Computer Engineering departments of UAH with support from and in consultation with the Steering Committee composed of representatives from each of the participating organizations plus a student representative.

Dimmock, John O.↗

NASA NTRS1997

Practice Oriented Master's in Optics

This award provides support for the development and initial implementation of an interdisciplinary Master's Program with a concentration in Optics and Photonics Technology. This program is a collaboration between the University of Alabama in Huntsville, Alabama A&M University, Northwest Shoals Community College, the NASA Marshall Space Flight Center, the U. S. Army Missile Command, Oak Ridge National Laboratory, the National Institute for Standards and Technology, Advanced Optical Systems Inc., Dynetics, Inc., Hughes Danbury Optical Systems, Inc., Nichols Research Corp., SCI Inc., and Speedring Inc. These organizations have been participating fully in the design, development and implementation of the program. This program is directed at both traditional students as well as government and defense workers who desire specialty education in practical optics and optical systems design and manufacturing. It is intended to produce highly trained graduates who can solve practical problems, and includes an on-site practicum at a manufacturing location. The broad curriculum of this program emphasizes the fundamentals of optics, optical systems manufacturing and testing, and the principles of design and manufacturing-to-cost for commercial optical products. The degrees offered are the MS in Physics and the MSE in Electrical Engineering with concentration in Optics and Photonics Technology through the Physics and Electrical and Computer Engineering departments of UAH with support from and in consultation with the Steering Committee composed of representatives from each of the participating organizations plus a student representative.

Dimmock, John O.↗

NASA NTRS2012

NASA's Lunar Polar Ice Prospector, RESOLVE: Mission Rehearsal in Apollo Valley

After the completion of the Apollo Program, space agencies didn't visit the moon for many years. But then in the 90's, the Clementine and Lunar Prospector missions returned and showed evidence of water ice at the poles. Then in 2009 the Lunar Crater Observation and Sensing Satellite indisputably showed that the Cabeus crater contained water ice and other useful volatiles. Furthermore, instruments aboard the Lunar Reconnaissance Orbiter (LRO) show evidence that the water ice may also be present in areas that receive several days of continuous sunlight each month. However, before we can factor this resource into our mission designs, we must understand the distribution and quantity of ice or other volatiles at the poles and whether it can be reasonably harvested for use as propellant or mission consumables. NASA, in partnership with the Canadian Space Agency (CSA), has been developing a payload to answer these questions. The payload is named RESOLVE. RESOLVE is on a development path that will deliver a tested flight design by the end of 2014. The team has developed a Design Reference Mission using LRO data that has RESOLVE landing near Cabeus Crater in May of2016. One of the toughest obstacles for RESOLVE's solar powered mission is its tight timeline. RESOLVE must be able to complete its objectives in the 5-7 days of available sunlight. The RESOLVE team must be able to work around obstacles to the mission timeline in real time. They can't afford to take a day off to replan as other planetary missions have done. To insure that this mission can be executed as planned, a prototype version of RESOLVE was developed this year and tested at a lunar analog site on Hawaii, known as Apollo Valley, which was once used to train the Apollo astronauts. The RESOLVE team planned the mission with the same type of orbital imagery that would be available from LRO. The simulation team prepositioned a Lander in Apollo Valley with RESOLVE on top mounted on its CSA rover. Then the mission simulation began as the operations team's consoles came alive with data and images. They executed the mission just like the real mission with lunar communications delays and limited bandwidth and a realistic remote mission control room. This paper will describe the RESOLVE payload in detail and describe the results of the mission simulation in Hawaii.

Larson, William E.↗

NASA NTRS2014

Upgrading Custom Simulink Library Components for Use in Newer Versions of Matlab

The Spaceport Command and Control System (SCCS) at Kennedy Space Center (KSC) is a control system for monitoring and launching manned launch vehicles. Simulations of ground support equipment (GSE) and the launch vehicle systems are required throughout the life cycle of SCCS to test software, hardware, and procedures to train the launch team. The simulations of the GSE at the launch site in conjunction with off-line processing locations are developed using Simulink, a piece of Commercial Off-The-Shelf (COTS) software. The simulations that are built are then converted into code and ran in a simulation engine called Trick, a Government off-the-shelf (GOTS) piece of software developed by NASA. In the world of hardware and software, it is not uncommon to see the products that are utilized be upgraded and patched or eventually fade away into an obsolete status. In the case of SCCS simulation software, Matlab, a MathWorks product, has released a number of stable versions of Simulink since the deployment of the software on the Development Work Stations in the Linux environment (DWLs). The upgraded versions of Simulink has introduced a number of new tools and resources that, if utilized fully and correctly, will save time and resources during the overall development of the GSE simulation and its correlating documentation. Unfortunately, simply importing the already built simulations into the new Matlab environment will not suffice as it will produce results that may not be expected as they were in the version that is currently being utilized. Thus, an upgrade execution plan was developed and executed to fully upgrade the simulation environment to one of the latest versions of Matlab.

Matlab Simulation↗

NASA NTRS2014

Identification of Medical Training Methods for Exploration Missions

As the National Aeronautics and Space Administration (NASA) and its international partner agencies anticipate eventual exploration missions of longer duration, there is a need to plan for the medical capabilities necessary to maximize crew health and provide the best likelihood of mission success. Current spaceflights consist of 5- to 6-month excursions to the International Space Station (ISS) in low-Earth orbit (LEO), and a 12-month ISS mission is currently in planning stages. However, missions to a near-Earth asteroid (NEA), a return to the moon, or even a mission to Mars will demand unprecedented medical capabilities, particularly relating to the training of the crew medical officers (CMOs). In its attempts to address the questions about medical preparation for spaceflight beyond LEO, the Exploration Medical Capability (ExMC) element within NASA's Human Research Program (HRP) defines a series of gaps. These gaps are shortcomings in knowledge, training, or technology that require resolution before an exploration mission can be undertaken. The ExMC element maintains current information about measures to close these gaps while developing plans for further investigation and research. Data pertaining to the gaps and their present status are available to the general public on the NASA Human Research Wiki and the NASA Human Research Roadmap Web sites (34, 36). One such gap, Gap 3.01, identifies a lack of knowledge about the optimal training methods for in-flight medical conditions identified on the Exploration Medical Condition List (EMCL), taking into account the crew medical officer s (CMOs) clinical background (33). This broad statement encompasses several related issues with the current methods of training CMOs and the medical ground support staff, specifically flight surgeons and biomedical engineers (BMEs) located in mission control, in addition to questions pertaining to the ways in which training will need to be adapted for the medical contingencies unique to exploration missions. To determine the optimal methods of medical training for an exploration medical crew and their ground support team, the historical context of medical operations, the current CMO training methods, and potential alternative training methods were identified.

Long duration space flight↗

NASA NTRS1985

Evolution of area access safety training required for gaining access to Space Shuttle launch and landing facilities

Assuring personnel and equipment are fully protected during the Space Shuttle launch and landing operations has been a primary concern of NASA and its associated contractors since the inception of the program. A key factor in support of this policy has been the area access safety training requirements for badging of employees assigned to work on Space Shuttle Launch and Facilities. This requirement was targeted for possible cost savings and the transition of physical on-site walkdowns to the use of television tapes has realized program cost savings while continuing to fully satisfy the area access safety training requirements.

Willams, M. C.↗

NASA NTRS2017

Probabilistic Forecasting of Surface Ozone with a Novel Statistical Approach

The recent change in the Environmental Protection Agency's surface ozone regulation, lowering the surface ozone daily maximum 8-h average (MDA8) exceedance threshold from 75 to 70 ppbv, poses significant challenges to U.S. air quality (AQ) forecasters responsible for ozone MDA8 forecasts. The forecasters, supplied by only a few AQ model products, end up relying heavily on self-developed tools. To help U.S. AQ forecasters, this study explores a surface ozone MDA8 forecasting tool that is based solely on statistical methods and standard meteorological variables from the numerical weather prediction (NWP) models. The model combines the self-organizing map (SOM), which is a clustering technique, with a step wise weighted quadratic regression using meteorological variables as predictors for ozone MDA8. The SOM method identifies different weather regimes, to distinguish between various modes of ozone variability, and groups them according to similarity. In this way, when a regression is developed for a specific regime, data from the other regimes are also used, with weights that are based on their similarity to this specific regime. This approach, regression in SOM (REGiS), yields a distinct model for each regime taking into account both the training cases for that regime and other similar training cases. To produce probabilistic MDA8 ozone forecasts, REGiS weighs and combines all of the developed regression models on the basis of the weather patterns predicted by an NWP model. REGiS is evaluated over the San Joaquin Valley in California and the northeastern plains of Colorado. The results suggest that the model performs best when trained and adjusted separately for an individual AQ station and its corresponding meteorological site.

Ozone variables↗