Results for “REMOTE AREAS” — Page 12

NASA NTRSDate not supplied

The Potential of Medical Drones: An Analysis of Current and Future Use Cases

Modern Application of Medical-Based Drone Delivery Drones have been used advantageously by militaries for nearly a century, but their uses in civilian life are still mostly cutting-edge, if not theoretical. After a decade of bold proclamations, Amazon’s “PrimeAir” drone delivery system is still in the stage of “preparing” for deliveries, while the public awaits for start ups like SkyDrop (formerly Flirtey) to follow through on impressive promises. Despite the well-publicized disappointment so far in commercial drone delivery, medical drone delivery has already proven itself practical and cheap in several countries, and it promises to expand in the coming years. Drones are uniquely suited to make valuable and urgent deliveries to remote areas, quickly transporting medical supplies where road transportation is prohibitively slow or not available at all. Drones have been used notably to deliver AEDs for out-of-hospital cardiac arrest, frequently beating first-responders to the scene; to deliver blood when there is none on hand at hospitals; to deliver vaccines to an island nation with little transportation infrastructure; and to respond flexibly to medical emergencies in a war zone. Economics make the delivery of food and other cheap goods by drone unattractive in the near-term, but the value and time-sensitivity of medical deliveries mean that drones are already saving lives in healthcare. “We believe the value of new technology is most valuable where it is clearly needed...that’s why we wanted to focus on drones delivering medicine and not delivering pizzas, ”said one executive of a drone system manufacturer. The immediate prospects for the expansion of medical drone use are many; however, they do not exist without their own drawbacks and challenges. Most obvious is the limited range of current commercially-available drones, most of which are isolated to a perimeter of roughly 18 miles. Technological know-how presents another barrier to integration of medical drones on a larger scale. Reports from the United Nations frequently cite a“skill deficit”—a prohibitively low number of qualified drone operators in low-and moderate-income countries (LMICs). Another perhaps more discreet speed bump in global drone development and usage are the various regulations on drone usage. Drone technology has developed so quickly that many states, out of an excess of caution, have nearly snuffed out the fledgling industry with regulation. There also exist significant concerns over the security of private citizens, the efficacy of medical deliveries, and the costs of drone operation. It is these last three barriers which this study will seek to overcome. Put simply, the prospect for human development in LMICs from drone-based medical delivery is far too great to disregard. As of 2020, 3.4 billion people live in rural communities, containing fewer than 5,000 people/km^2. Often lacking infrastructure, these communities are largely isolated from their more populated, urban counterparts. In drones lies the potential to reshape the geographic and developmental distinctions that divide the global population. This development must, therefore, begin first and foremost with advancement in regional well-being and life expectancy. Life expectancy makes up a key facet of human development. The United Nations relies on it as a key indicator of a state’s health. Lars Kunze of the Dortmund University Department of Economic sex plains this as a matter of physical capital accumulation. The longer people live, the more they save as opposed to spend. The more they save, the more which eventually gets invested in themselves and the community as a whole. In providing medical products via drone, it is the intention of this study to enable communities with the means and incentives for long-run savings and investment for future economic development. Through a close analysis of Vanuatu, Rwanda, Tanzania, and Ukraine—four states where drones are currently used to deliver medical supplies—this study develops a framework that LMICs in general and Mexico and particular can adopt and to use medical drones in difficult-to-reach communities for the sake of long-run human developmental initiatives.

Ryan Teoh↗

NASA NTRSDate not supplied

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

J Lemery↗

NASA NTRS2024

Earth Independent Medical Operations (EIMO) Datascope: Challenges and Potential Solutions

Data flows and storage/retrieval capacity are severely constrained during missions in space and challenges will become even greater during exploration class missions. There is a need for an artificial intelligence (AI)-based clinical decision support system (CDSS) to monitor and analyze data to provide real-time consultative support for crew medical officer (CMO) decision-making. EIMO is defined as the gradual transition of medical care and decision making from terrestrial to space-based assets, enabling support of astronaut health and performance and reducing overall mission risk. While a hallmark of this paradigm shift from low-earth orbit is that on-board care will increasingly become the responsibility of the astronauts for primary management and decision making, terrestrial assets will continue to be paramount in pre-mission screening and planning, as well as prevention, health maintenance and long-term care contingencies. New capabilities and systems that enable progressively more robust and resilient systems and crews will be necessary to reduce risk and increase probability of deep space exploration mission success. An aspiration for EIMO is to develop AI-enhanced solutions for analysis of crew health & performance data and to facilitate clinical decision support for autonomous medical operations. A “system of systems” approach is envisioned whereby EIMO will deploy AI-supported natural language processing and machine learning (ML) techniques to utilize embedded reference databases and real-time data streams [input vectors] from multiple data sources. Constituent input vectors may include environmental controls, countermeasures data, behavioral data, physiologic wearables, point-of-care laboratory tests, personalized medical records, inventory trade space risk assessments, COTS medical databases, and ground support inputs. An ideal AI capability would possess trained fusion algorithms to cross reference input vectors with medical ‘knowledge’ [cultivated database] to stratify relevant data streams for predictive and actionable capabilities. In addition, EIMO will feature mobility, in that it can be accessed and can push/pull data within and between multiple vehicles/habitats. Large amounts and variable sources of data can be leveraged to diagnose, inform treatment strategies, and potentially predict medical events and performance decrements. Inclusion of advanced training tools using extended reality will enable increasingly autonomous medical care to aid a CMO when ground support is unavailable or time-delayed beyond required action window, e.g., emergent medical situations. EIMO CDSS would require very large datasets to train pre-flight and significant amounts of data are needed to support ML via in-flight CDSS operations. An additional challenge will be to find sufficient data to train a model relevant to astronaut demographics. The rapid, accelerating evolution of this field creates a propitious solution space to leverage multi-modal AI through public-private partnership(s). The status of multi-modal AI systems today would preclude their use for long duration missions as they remain unreliable and are subject to “digital hallucinations” and other errors that could pose operational risk. A federated labs structure is being considered to test and optimize data flow from the multiple input vectors leading to field testing in suitable ground/flight analogs. Critical to the success of an EIMO CDSS will be integration and interoperability and success will be defined by a system that can serve as an in-flight medical consult for the CMO providing critical support during medical contingencies. Benefits to terrestrial medicine may be significant as an outflow of the EIMO medical system, particularly for remote areas and communities lacking significant infrastructure, personnel and resources.

Medical Operations↗

NASA NTRS2024

Communications System Concept of Operations (ConOp) for Supporting Second Shift (SS) Operations

Wildland fires take place most often in remote areas without access to communications infrastructure. Communication during wildfire operations is crucial for safe and effective command and control of air assets, ground-based firefighters, and fire management. Without connectivity, Incident Command (IC) cannot exchange information, receive alerts or work with all parties involved in the wildfire suppression operation. Current policy directs IC to use voice radio communications, which require no prior infrastructure, to provide information needed for the command, control and safety of personnel and resources. Cellular communications are used only for logistical purposes unless no other method is available. To address some of the shortcomings of the current state of communications, the Advanced Capabilities for Emergency Response Operations (ACERO) Second Shift (SS) technical team is developing characteristics of an air-to-ground Mesh Radio System (MRS) and preparing for a future demonstration. The MRS will allow air and ground assets to automatically join a radio network without relying on existing infrastructure and exchange information critical to maintaining situation awareness and air traffic management by the onsite IC. The MRS will also give users more options for communications in addition to voice communications.

David Fuller↗

DOE OSTI2020

Functional and Operating Requirements for the Microreactor Agile Non-Nuclear Experimental Test Bed (MAGNET)

Microreactors, or small, transportable reactors with a capacity of < 20 MWTH, are sought to provide heat and power for myriad applications in remote areas, military installations, emergency operations, humanitarian missions and disaster relief zones as illustrated in Figure 1. These small, transportable reactor designs, while offering many advantages, are largely untested and unproven. System and component testing is needed to demonstrate to regulators that these designs are safe and to convince customers that the systems are robust, reliable, and efficient. The microreactor agile non-nuclear experimental test bed (MAGNET) is being constructed at Idaho National Laboratory to assist with the development, demonstration, and validation of microreactor components and systems. MAGNET will support technology maturation to reduce uncertainty and risk relative to the operation and deployment of this unique class of systems. Stakeholders for this test bed include microreactor developers, energy users, and regulators. Regulators will be engaged early in the design and testing to expedite regulatory approval and licensing. Within MAGNET, systems and components can be safely tested, providing valuable information on operating regimes, failure modes, and thresholds. Since there are various types of microreactors being proposed, which can be classified according to their core cooling method, heat-pipes, gas-cooled (pebble bed or prismatic), molten salt, light water, or light water, the goal is to provide a test bed that is broadly applicable to multiple microreactor concepts. Each reactor type poses a different set of design and operational challenges and performance claims stated by commercial vendors have not been independently verified through rigorous testing. The initial set of tests to be performed in MAGNET are targeted towards demonstrating the feasibility and performance of heat-pipe cooled reactors, since this concept is unique to very small nuclear reactors. However, the testbed will be constructed to accommodate other designs in addition to heat-pipe cooled reactors.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Preliminary Observations on the Hydrogen Redistribution Feedback in YH-Moderated Monolithic Microreactors.

Nuclear microreactors promise to open new markets for nuclear industry. This is due to their potential competitive cost in non-traditional market segments, e.g., mines, forward military basis, extraterrestrial surfaces and remote areas, and inherently safe characteristics that make them deployable where other power sources are not available or difficult to exploit. Transition metal dihydrides have been considered among the most promising candidates for moderating nuclear microreactors. In particular, yttrium hydride (YH\textsubscript{x}) has been selected for high temperature applications due to its high thermal stability and relatively high hydrogen retention at temperatures exceeding $870^\circ C$. One of the main issues associated with the use of hydrides is that, when exposed to temperature, stress, or concentration gradients, the hydrogen contained in the metallic matrix tends to redistribute and leak from the moderating elements, potentially leading to reactivity losses and power swings. The purpose of this paper is to gain a better physical understanding of the neutronic feedback associated with the hydrogen redistribution in YH\textsubscript{x}, by using Griffin and Bison. This feedback is inherently multiphysics, since the hydrogen distribution is strongly dependent on the moderator temperature spatial distribution. In particular, we want to understand the sign (+/-) of the neutronic feedback, its order of magnitude, and its underlying physical causes.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2022

Development of Non-Nuclear Microreactor Experimental Capability

Microreactors, or small, transportable reactors with a capacity of 20 MWTH or less, are sought to provide heat and power for myriad applications in remote areas, military installations, emergency operations, humanitarian missions, and disaster relief zones. These small, transportable reactor designs, while offering many advantages, are largely untested and unproven. A non-nuclear system and component testing capability is needed to demonstrate to regulators that these designs are safe and to convince customers that the systems are robust, reliable, and efficient. Idaho National Laboratory has constructed the microreactor agile non-nuclear experimental test bed (MAGNET) to assist with the development, demonstration, and validation of microreactor components and systems. MAGNET will support microreactor technology maturation to reduce uncertainty and risk relative to the operation and deployment of this unique class of systems. Stakeholders for this test bed include microreactor developers, energy users, and regulators. Regulators will be engaged early in the design and testing to expedite regulatory approval and licensing.

42 ENGINEERING↗

DOE OSTI2023

2022 Prototype Manufacture and Installation Awardee: Sonsight Wind

The Sonsight Wind 3.5-kilowatt (kW) prototype turbine is designed to compete with solar power, meeting energy needs for a wide range of smaller-scale applications, such as powering individual homes and irrigation systems on farms and ranches in remote areas. The technology's innovative high-torque, low-rotations-per-minute generator permits the use of longer blades that, at moderate wind speed sites, generate the energy of a 5-kW turbine with lower thrust forces than similarly rated turbines. The 3.5-kW turbine is projected to ofer greater durability at a signifcantly lower levelized cost of energy. Sonsight Wind advanced the development of the prototype with a previous Competitiveness Improvement Project (CIP) funding award.

competitiveness improvement project↗

DOE OSTI2024

Webinar: Modular Nuclear Power: The Microreactor Revolution

Many times smaller than traditional nuclear reactors, microreactors can be made in a factory and shipped wherever needed. This innovative approach to energy production has huge potential to bring electricity to remote areas, support regions affected by natural disasters, and provide right-sized, scalable power to our energy grid. Learn what they are, how they work, and their benefits in this webinar, featuring Piyush Sabharwall, distinguished staff nuclear research scientist and technical area lead for the DOE Office of Nuclear Energy's Microreactor R&D Program at Idaho National Laboratory.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Select Proliferation Studies on TRISO-fueled, Heat-Pipe-cooled Microreactors

Nuclear microreactors carry the potential to open up new markets for the nuclear industry, as their expected cost competitiveness in non-traditional market segments (e.g., mines, military bases, extraterrestrial surfaces, and remote areas), and their inherent safety features make them deployable when other power sources are unavailable or difficult to exploit. For countries that have not traditionally participated in nuclear power, microreactors represent a clean energy solution [1]. However, their use, especially in non-weapons states, may entail challenges in terms of maintaining international nuclear safeguards [2]. Furthermore, the deployment locations where microreactors may prove most cost competitive would be difficult to access by state and International Atomic Energy Agency (IAEA) inspectors [3]. In addition to the isolated nature of potential deployment sites, the low-power characteristic of microreactors suggests that numerous microreactors would need to be deployed to meet energy demands. That, coupled with the unique physics of many current microreactor designs, opens up a new area of research with respect to nonproliferation and safeguards concerns [2]. Whereas traditional facilities are inspected as isolated cases when looking for signs of diversion or misuse; microreactors may need to be assessed in the context of the entire fleet to which they belong. International safeguards necessitate timely detection of any significant quantities (SQs) of material that are being diverted (e.g., 1 SQ of special nuclear material diverted over the course of a 1-year period) [4]. For low-enriched uranium, the IAEA defines 1 SQ as corresponding to 75 kg of 235U. The purpose of the present paper is to explore the detectability threshold for material diversion in microreactors by relying on critical control drum angles, excess reactivity, and the reactor lifetime as the selected operational parameters. For this assessment, a heat-pipe-cooled microreactor was regarded as the base design. While the conclusions reached in this paper are not readily extendable to the design of actual microreactors, the analysis herein enables conclusions to be drawn regarding the level of accuracy needed for reference calculations in order to detect diversion scenarios by utilizing the selected operational parameters (i.e., mainly control drum angles, critical insertion angle, and the reactor lifetime).

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

NASA NTRS1968

Remote sensing and the study and planning of urban areas

Aerial remote imagery for urban planning

Marble, D. F.↗

NASA NTRS2004

Increasing Access and Usability of Remote Sensing Data: The NASA Protected Area Archive

Although remote sensing data are now widely available, much of it at low or no-cost, many managers of protected conservation areas do not have the expertise or tools to view or analyze it. Thus access to it by the protected area management community is effectively blocked. The Protected Area Archive will increase access to remote sensing data by creating collections of satellite images of protected areas and packaging them with simple-to-use visualization and analytical tools. The user can easily locate the area and image of interest on a map, then display, roam, and zoom the image. A set of simple tools will be provided so the user can explore the data and employ it to assist in management and monitoring of their area. The 'Phase 1 ' version requires only a Windows-based computer and basic computer skills, and may be of particular help to protected area managers in developing countries.

remote sensing↗

NASA NTRS1971

Remote sensing for mined area reclamation: Application inventory

Applications of aerial remote sensing to coal mined area reclamation are documented, and information concerning available data banks for coal producing areas in the east and midwest is given. A summary of mined area information requirements to which remote sensing methods might contribute is included.

Source record↗

NASA NTRS2019

Assimilation of Remotely Sensed Leaf Area Index into the Noah-MP Land Surface Model: Impacts on Water and Carbon Fluxes and States over the Continental U.S.

Accurate representation of vegetation states is required for the modeling of terrestrial water-energy-carbon exchanges and the characterization of the impacts of natural and anthropogenic vegetation changes on the land surface. This study presents a comprehensive evaluation of the impact of assimilating remote sensing-based Leaf Area Index (LAI) retrievals over the Continental U.S. in the Noah-MP land surface model, during a time period of 2000 to 2017. The results demonstrate that the assimilation has a beneficial impact on the simulation of key water budget terms such as soil moisture, evapotranspiration, snow depth, terrestrial water storage and streamflow, when compared with a large suite of reference datasets. In addition, the assimilation of LAI is also found to improve the carbon fluxes of Gross Primary Production (GPP) and Net Ecosystem Exchange (NEE). Most prominent improvements in the water and carbon variables are observed over the agricultural areas of the U.S., where assimilation improves the representation of vegetation seasonality impacted by cropping schedules. The systematic, added improvements from assimilation in a configuration that employs high quality boundary conditions highlight the significant utility of LAI data assimilation in capturing the impacts of vegetation changes.

anthropogenic vegetation↗

NASA NTRS1985

Relationship between convective clouds and precipitation over the Qinghai-Xizang Plateau area from satellite remote sensing and ground-based observations

Results of this study show that heavy rainfall in the Qinghai-Xizang Plateau area is usually preceded by a high growth rate of the convective clouds followed by a rapid collapse of the cloud top. The tops of the convective clouds associated with heavy rainfall over the plateau usually lie between the altitudes of the two tropopauses which exist over the plateau. Undoubtedly the double tropopause restricts the vertical growth of the clouds and this may be the reason why tornadoes rarely occur there.

Hung, R. J.↗

NASA NTRS1980

The remote-controlled spectrograph, area scanner, and spectropolarimeter for the Lick 3-m telescope

A Cassegrain spectrograph used in conjunction with an image-tube, image-dissector scanner (ITS) is discussed with reference to its design features and operation. The spectrograph has a remote control feature, and its parameters, such as slit width, decker position, filter selection, focus, and grating selection, can be easily changed by computer command or a hard-wired control box. The discussion also includes the area scanner modification which allows raster scanning and limited picture taking. Finally, the design of a two-channel polarization analyzer is presented which allows simultaneous sky and sky-plus-star observations and faint-object polarimetry.

Miller, J. S.↗

NASA NTRS2022

Assimilation of Remotely Sensed Leaf Area Index Enhances the Estimation of Anthropogenic Irrigation Water Use

Representation of irrigation in Earth System Models has advanced over the past decade, yet large uncertainties persist in the effective simulation of irrigation practices, particularly over locations where the on-ground practices and climate impacts are less reliably known. Here we investigate the utility of assimilating remotely sensed vegetation data for improving irrigation water use and associated fluxes within a land surface model. We show that assimilating optical sensor-based leaf area index estimates significantly improves the simulation of irrigation water use when compared to the USGS ground reports. For heavily irrigated areas, assimilation improves the evaporative fluxes and gross primary production (GPP) simulations, with the median correlation increasing by 0.1–1.1 and 0.3–0.6, respectively, as compared to the reference datasets. Further, bias improvements in the range of 14–35 mm mo^(−1) and 10–82 g m^(-2)mo^(−1) are obtained in evaporative fluxes and GPP as a result of incorporating vegetation constraints, respectively. These results demonstrate that the use of remotely sensed vegetation data is an effective, observation-informed, globally applicable approach for simulating irrigation and characterizing its impacts on water and carbon states.

Earth System Models↗

NASA NTRS1984

Irrigated rice area estimation using remote sensing techniques: Project's proposal and preliminary results

The development of a methodology for annual estimates of irrigated rice crop in the State of Rio Grande do Sul, Brazil, using remote sensing techniques is proposed. The project involves interpretation, digital analysis, and sampling techniques of LANDSAT imagery. Results are discussed from a preliminary phase for identifying and evaluating irrigated rice crop areas in four counties of the State, for the crop year 1982/1983. This first phase involved just visual interpretation techniques of MSS/LANDSAT images.

Parada, N. D. J.↗