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At least 1,009 records · Page 56

Virtual Infrastructure Twins: Software Testing Platforms for Computing-Instrument Ecosystems

Science ecosystems are being built by federating computing systems and instruments located at geographically distributed sites over wide-area networks. These computing-instrument ecosystems are expected to support complex workflows that incorporate remote, automated AI-driven science experiments. Their realization, however, requires various designs to be explored and software components to be developed, in order to support the orchestration of distributed computations and experiments. It is often too expensive, infeasible, or disruptive for the entire ecosystem to be available during the typically long software development and testing periods. We propose a Virtual Infrastructure Twin (VIT) of the ecosystem that emulates its network and computing components, and incorporates its instrument software simulators. It provides a software environment nearly identical to the ecosystem to support early development and testing, and design space exploration. We present a brief overview of previous digital infrastructure twins that culminated in the VIT concept, including (i) the virtual science network environment for developing software-defined networking solutions, and (ii) the virtual federated science instrument environment for testing the federation software stack and remote instrument control software. We briefly describe VITs for Nion microscope steering and access to GPU systems.

Rao, Nageswara↗

CIMATS - A correlation interferometer for the measurement of atmospheric trace species

A multigas correlation interferometer, based on the previously developed and tested COPE instrument, has been designed and fabricated and is presently undergoing laboratory testing. The CIMATS instrument has the capability to remotely measure densities of selected gaseous atmospheric species in the spectral range 2 to 2.5 and 4 to 10 microns. The sensor has been designed for both nadir viewing and earth limb viewing. As presently configured the sensor is capable of measuring ammonia, nitrous oxide, and carbon monoxide in the nonthermal infrared spectral region and carbon monoxide and sulfur dioxide in the thermal infrared. Other gaseous species can be measured by inclusion of additional narrow band filters.

Goldstein, H. W.↗

Virtual Infrastructure Twins: Software Testing Platforms for Computing-Instrument Ecosystems

Science ecosystems are being built by federating computing systems and instruments located at geographically distributed sites over wide-area networks. These computing-instrument ecosystems are expected to support complex workflows that incorporate remote, automated AI-driven science experiments. Their realization, however, requires various designs to be explored and software components to be developed, in order to support the orchestration of distributed computations and experiments. It is often too expensive, infeasible, or disruptive for the entire ecosystem to be available during the typically long software development and testing periods. We propose a Virtual Infrastructure Twin (VIT) of the ecosystem that emulates its network and computing components, and incorporates its instrument software simulators. It provides a software environment nearly identical to the ecosystem to support early development and testing, and design space exploration. We present a brief overview of previous digital infrastructure twins that culminated in the VIT concept, including (i) the virtual science network environment for developing software-defined networking solutions, and (ii) the virtual federated science instrument environment for testing the federation software stack and remote instrument control software. We briefly describe VITs for Nion microscope steering and access to GPU systems.

Rao, Nageswara↗

Earth feature identification for onboard multispectral data editing: Computational experiments

A computational model of the processes involved in multispectral remote sensing and data classification is developed as a tool for designing smart sensors which can process, edit, and classify the data that they acquire. An evaluation of sensor system performance and design tradeoffs involves classification rates and errors as a function of number and location of spectral channels, radiometric sensitivity and calibration accuracy, target discrimination assignments, and accuracy and frequency of compensation for imaging conditions. This model provides a link between the radiometric and statistical properties of the signals to be classified and the performance characteristics of electro-optical sensors and data processing devices. Preliminary computational results are presented which illustrate the editing performance of several remote sensing approaches.

Aherron, R. M.↗

NASA Land Information System (LIS) Water Availability to Support Reclamation ET Estimation

The U.S. Bureau of Reclamation identified the remote sensing of evapotranspiration (ET) as an important water flux for study and designated a test site in the Lower Colorado River basin. A consortium of groups will work together with the goal to develop more accurate and cost effective techniques using the enhanced spatial and temporal coverage afforded by remote sensing. ET is a critical water loss flux where improved estimation should lead to better management of Reclamation responsibilities. There are several areas where NASA satellite and modeling data may be useful to meet Reclamation's objectives for improved ET estimation. In this paper we outline one possible contribution to use NASA's data integration capability of the Land Information System (LIS) to provide a merger of observational (in situ and satellite) with physical process models to provide estimates of ET and other water availability outputs (e.g., runoff, soil moisture) retrospectively, in near real-time, and also providing short-term predictions.

Toll, David↗

An automated approach to the design of decision tree classifiers

The classification of large dimensional data sets arising from the merging of remote sensing data with more traditional forms of ancillary data is considered. Decision tree classification, a popular approach to the problem, is characterized by the property that samples are subjected to a sequence of decision rules before they are assigned to a unique class. An automated technique for effective decision tree design which relies only on apriori statistics is presented. This procedure utilizes a set of two dimensional canonical transforms and Bayes table look-up decision rules. An optimal design at each node is derived based on the associated decision table. A procedure for computing the global probability of correct classfication is also provided. An example is given in which class statistics obtained from an actual LANDSAT scene are used as input to the program. The resulting decision tree design has an associated probability of correct classification of .76 compared to the theoretically optimum .79 probability of correct classification associated with a full dimensional Bayes classifier. Recommendations for future research are included.

Argentiero, P.↗

Remote Diagnosis of the International Space Station Utilizing Telemetry Data

Modern systems such as fly-by-wire aircraft, nuclear power plants, manufacturing facilities, battlefields, etc., are all examples of highly connected network enabled systems. Many of these systems are also mission critical and need to be monitored round the clock. Such systems typically consist of embedded sensors in networked subsystems that can transmit data to central (or remote) monitoring stations. Moreover, many legacy are safety systems were originally not designed for real-time onboard diagnosis, but a critical and would benefit from such a solution. Embedding additional software or hardware in such systems is often considered too intrusive and introduces flight safety and validation concerns. Such systems can be equipped to transmit the sensor data to a remote-processing center for continuous health monitoring. At Qualtech Systems, we are developing a Remote Diagnosis Server (RDS) that can support multiple simultaneous diagnostic sessions from a variety of remote subsystems.

Deb, Somnath↗

Ground System for Solar Dynamics Observatory (SDO) Mission

NASA s Goddard Space Flight Center (GSFC) has recently completed its Critical Design Review (CDR) of a new dual Ka and S-band ground system for the Solar Dynamics Observatory (SDO) Mission. SDO, the flagship mission under the new Living with a Star Program Office, is one of GSFC s most recent large-scale in-house missions. The observatory is scheduled for launch in August 2008 from the Kennedy Space Center aboard an Atlas-5 expendable launch vehicle. Unique to this mission is an extremely challenging science data capture requirement. The mission is required to capture 99.99% of available science over 95% of all observation opportunities. Due to the continuous, high volume (150 Mbps) science data rate, no on-board storage of science data will be implemented on this mission. With the observatory placed in a geo-synchronous orbit at 36,000 kilometers within view of dedicated ground stations, the ground system will in effect implement a "real-time" science data pipeline with appropriate data accounting, data storage, data distribution, data recovery, and automated system failure detection and correction to keep the science data flowing continuously to three separate Science Operations Centers (SOCs). Data storage rates of approx. 45 Tera-bytes per month are expected. The Mission Operations Center (MOC) will be based at GSFC and is designed to be highly automated. Three SOCs will share in the observatory operations, each operating their own instrument. Remote operations of a multi-antenna ground station in White Sands, New Mexico from the MOC is part of the design baseline.

Tann, Hun K.↗

Human-Automation Allocations for Current Robotic Space Operations

Within the Human Research Program, one risk delineates the uncertainty surrounding crew working with automation and robotics in spaceflight. The Risk of Inadequate Design of Human and Automation/Robotic Integration (HARI) is concerned with the detrimental effects on crew performance due to ineffective user interfaces, system designs and/or functional task allocation, potentially compromising mission success and safety. Risk arises because we have limited experience with complex automation and robotics. One key gap within HARI, is the gap related to functional allocation. The gap states: We need to evaluate, develop, and validate methods and guidelines for identifying human-automation/robot task information needs, function allocation, and team composition for future long duration, long distance space missions. Allocations determine the human-system performance as it identifies the functions and performance levels required by the automation/robotic system, and in turn, what work the crew is expected to perform and the necessary human performance requirements. Allocations must take into account each of the human, automation, and robotic systems capabilities and limitations. Some functions may be intuitively assigned to the human versus the robot, but to optimize efficiency and effectiveness, purposeful role assignments will be required. The role of automation and robotics will significantly change in future exploration missions, particularly as crew becomes more autonomous from ground controllers. Thus, we must understand the suitability of existing function allocation methods within NASA as well as the existing allocations established by the few robotic systems that are operational in spaceflight. In order to evaluate future methods of robotic allocations, we must first benchmark the allocations and allocation methods that have been used. We will present 1) documentation of human-automation-robotic allocations in existing, operational spaceflight systems; and 2) To gather existing lessons learned and best practices in these role assignments, from spaceflight operational experience of crew and ground teams that may be used to guide development for future systems. NASA and other space agencies have operational spaceflight experience with two key Human-Automation-Robotic (HAR) systems: heavy lift robotic arms and planetary robotic explorers. Additionally, NASA has invested in high-fidelity rover systems that can carry crew, building beyond Apollo's lunar rover. The heavy lift robotic arms reviewed are: Space Station Remote Manipulator System (SSRMS), Japanese Remote Manipulator System (JEMRMS), and the European Robotic Arm (ERA, designed but not deployed in space). The robotic rover systems reviewed are: Mars Exploration Rovers, Mars Science Laboratory rover, and the high-fidelity K10 rovers. Much of the design and operational feedback for these systems have been communicated to flight controllers and robotic design teams. As part of the mitigating the HARI risk for future human spaceflight operations, we must document function allocations between robots and humans that have worked well in practice.

robotic allocation↗

Development and testing of a 180-volt dc electronic circuit breaker with a 335-ampere carry and 1200-ampere interrupt rating

NASA Lewis Research Center and associated contractors have conducted a program to assess the potential requirements for a high-current switch to conceptually design a switch using the best existing technology, and to build and demonstrate a breadboard which meets the requirements. The result is the high current remote bus isolator (HRBI). The HRBI is rated at 180 V dc, 335 A continuous with a 1200 A interrupt rating. It also incorporates remote-control and protective features called for by the Space Station Freedom PMAD dc test bed design. Two breadboard 335 A circuit breakers were built and tested that demonstrate a promising concept of paralleled current-limiting modules. The units incorporated all control and protective features required by advanced aerospace power systems. Component stresses in each unit were determined by design, and are consistent with a life of many thousands of fault operations.

Brush, A. S.↗

Virtual reality robotic telesurgery simulations using MEMICA haptic system

The authors conceived a haptic mechanism called MEMICA (Remote Mechanical Mirroring using Controlled stiffness and Actuators) that can enable the design of high dexterity, rapid response, and large workspace haptic system. The development of a novel MEMICA gloves and virtual reality models are being explored to allow simulation of telesurgery and other applications. The MEMICA gloves are being designed to provide intuitive mirroring of the conditions at a virtual site where a robot simulates the presence of a human operator. The key components of MEMICA are miniature electrically controlled stiffness (ECS) elements and electrically controlled force and stiffness (ECFS) actuators that are based on the use of Electro-Rheological Fluids (ERF. In this paper the design of the MEMICA system and initial experimental results are presented.

Haptic interfaces↗

The decision tree classifier - Design and potential

A new classifier has been developed for the computerized analysis of remote sensor data. The decision tree classifier is essentially a maximum likelihood classifier using multistage decision logic. It is characterized by the fact that an unknown sample can be classified into a class using one or several decision functions in a successive manner. The classifier is applied to the analysis of data sensed by Landsat-1 over Kenosha Pass, Colorado. The classifier is illustrated by a tree diagram which for processing purposes is encoded as a string of symbols such that there is a unique one-to-one relationship between string and decision tree.

Hauska, H.↗

Design parameters for a stereoptic television system based on direct vision depth perception cues

Remotely controlled systems which use television for visual feedback require that depth cues be available to the operator. A number of techniques have been developed to provide stereoptic video. An analysis of parameters of such systems as related to the depth cues of convergence and retinal disparity was carried out. Parameter requirements were determined for the provision of natural and exaggerated stereoptic cues and expressions were developed for range resolution limits based on the retinal disparity threshold. An empirical study was conducted using a stereoptic video system to determine threshold values

Shields, N. L., Jr.↗

Design and Build a Compact Raman Sensor for Identification of Chemical Composition

A compact remote Raman sensor system was developed at NASA Langley Research Center. This sensor is an improvement over the previously reported system, which consisted of a 532 nm pulsed laser, a 4-inch telescope, a spectrograph, and an intensified charge-coupled devices (CCD) camera. One of the attractive features of the previous system was its portability, thereby making it suitable for applications such as planetary surface explorations, homeland security and defense applications where a compact portable instrument is important. The new system was made more compact by replacing bulky components with smaller and lighter components. The new compact system uses a smaller spectrograph measuring 9 x 4 x 4 in. and a smaller intensified CCD camera measuring 5 in. long and 2 in. in diameter. The previous system was used to obtain the Raman spectra of several materials that are important to defense and security applications. Furthermore, the new compact Raman sensor system is used to obtain the Raman spectra of a diverse set of materials to demonstrate the sensor system's potential use in the identification of unknown materials.

Garcia, Christopher S.↗

An investigation of current and future satellite and in-situ data for the remote sensing of the land surface energy balance

This final report from the University of Wisconsin-Madison Cooperative Institute for Meteorological Satellite Studies (CIMSS) summarizes a research program designed to improve our knowledge of the water and energy balance of the land surface through the application of remote sensing and in-situ data sources. The remote sensing data source investigations to be detailed involve surface radiometric ('skin') temperatures and also high-spectral-resolution infrared radiance data from atmospheric sounding instruments projected to be available at the end of the decade, which have shown promising results for evaluating the land-surface water and energy budget. The in-situ data types to be discussed are measurements of the temporal changes of the height of the planetary boundary layer and measurements of air temperature within the planetary boundary layer. Physical models of the land surface, planetary boundary layer and free atmosphere have been used as important tools to interpret the in-situ and remote sensing signals of the surface energy balance. A prototype 'optimal' system for combining multiple data sources into a three-dimensional estimate of the surface energy balance was developed and first results from this system will be detailed. Potential new sources of data for this system and suggested continuation research will also be discussed.

Diak, George R.↗

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗

A Cognitive Walkthrough of Multiple Drone Delivery Operations

Advances of early twenty-first century aviation and transportation technologies provide opportunities for enhanced aerial projects, and the overall integration of unmanned aircraft systems (UAS) into the National Airspace System (NAS) has applications across a wide range of operations. Through these, remote operators have learned to manage several UAS at the same time in a variety of operational environments. The present work details a component piece of an ongoing body of research into multi-UAS operations. Beginning in early 2020, NASA has collaborated with Uber Technologies to design and develop concepts of operations, roles and responsibilities, and ground control station (GCS) concepts to enable food delivery operations via multiple, small UAS (sUAS). A cognitive walkthrough was chosen as the method for data collection. This allowed information to be gathered from UAS subject matter experts (SMEs) that could further mature designs for future human-in-the-loop (HITL) simulations; in addition, it allowed information to be collected remotely during the stringent restrictions of the COVID-19 pandemic. Consequently, the described cognitive walkthrough activity utilized remote data collection protocols mediated through the usage of programs designed for presentation and telecommunications. Scenarios were designed, complete with airspace, contingencies, and remedial actions, to be presented to the SMEs. Information was collected using a combination of rating scales and open-ended questions. Results received from the SMEs revealed expected hazards, workloads, and information concerns inherent in the contingency scenarios. SMEs also provided insight into the design of GCS tools and displays as well as the duties and relationships of human operators (i.e., monitors) and automation (i.e., informers and flight managers). Implications of these findings are discussed.

unmanned aircraft systems↗