Results for “infrastructure optimization” — Page 8

NASA NTRS2017

A PCR Based Microbial Monitoring Alternative Method of Detection and Identification of Microbes Aboard ISS

Previous research has shown that microorganisms and potential human pathogens have been detected on the International Space Station (ISS) with additional introduction of new microflora occurring with every exchange of crew or addition of equipment and supplies. These microbes are readily transferred between crew and subsystems (i.e. ECLSS, environmental control and life support systems). As this can be detrimental to astronaut health and optimal performance of ISS systems, monitoring of systems such as ECLSS to include identification of microbial contaminants could prevent adverse effects on human health and life support systems. Current monitoring on ISS is laborious and utilizes culture based methods followed by sample return to Earth for complete analysis. Future, long-distance spaceflight missions will require real-time monitoring capabilities that enable efficient and rapid assessments of the microbial environment allowing for expedited decisions and more targeted response to cope with anomalies. Polymerase chain reaction (PCR), a molecular microbial monitoring method was chosen and numerous PCR instruments investigated for their potential to perform in microgravity conditions. Using ISS as a test bed for PCR verification in microgravity will enable NASA to assess whether molecular based microbiological sensors may be components of reliable, closed-loop life support and habitation systems in spacecraft, enhancing infrastructure capabilities through increased efficiency, reliability, and time savings by enabling sample analysis on orbit. NASA selected the Water Monitoring Suite as one of the rapid spaceflight hardware demonstration activities utilizing a streamlined process to minimize the time required to fly experimental flight hardware. The RAZOR EX (BioFire Defense, Salt Lake City, UT) system was part of the water monitoring suite and is a commercial off-the-shelf (COTS) real-time PCR instrument designed for field work. The RAZOR EX was originally designed for Department of Defense (DoD) under a small business innovative research (SBIR) grant and is ruggedized, compact and provides a rapid, sample to answer in less than an hour. PCR assays using a fluorescent probe were optimized and spiked with known concentrations of DNA (Pseudomonas aeruginosa) ranging from 0.002 to 20 ng. PCR reagents were lyophilized and configured in customized pouches and tested for flight readiness. Three types of water were used to rehydrate the reagents and demonstrate the fidelity of the PCR reaction in microgravity. Molecular grade deionized water served as a control while filtered and unfiltered ISS potable water served to test for chemical or biological inhibitors. All three types were compared to parallel ground test results. Nine tests were run on ISS (3 of each water type) and the critical threshold cycle (Ct) was compared to parallel ground tests completed at Kennedy Space Center, FL and Johnson Space Center, TX. All concentrations of Pseudomonas aeruginosa DNA were detected. A comparison of the Ct produced in real time PCR indicated similarity between flight and ground samples. There appeared to be no significant difference between flight or ground PCR reactions or between any of the three water types. This testing demonstrated the ability to perform molecular testing during spaceflight operations with similar sensitivity. It will allow for future ground development of molecular protocols and minimize the need for spaceflight testing. Future testing will include development of additional targets including environmental and health related organisms.

Christina Khodadad↗

NASA NTRS2023

Plasma Activated Water: A Technology for Acid Generation and Space Crop Production

As humanity returns to the moon and onward to Mars, sustainable space travel becomes essential for cost and independence from Earth. Astronaut activities in low Earth orbit resupply consumable materials and can require alternative technologies if transportation of chemicals is deemed hazardous. Plasma technology and applications are able to generate commodities that assist in achieving Earth independence. Plasma interaction with water generates acid in-situ using on-board resources of electricity and breathable air without the need for large infrastructure. At Kennedy Space Center, researchers have shown that plasma is able to produce nitric acid, and therefore nitrates, in a plant-usable form in water. In this report, the team presents results on acid generation in g/kW-hr as well as provides results on plasma activated water for plant growth assistance. Plasma was generated utilizing DC, AC, and pulsed power supplies in order to determine optimizing parameters for generation of this useful commodity.

Plasma↗

NASA NTRSDate not supplied

Plasma Activated Water: A Technology for Acid Generation and Space Crop Production

As humanity returns to the moon and onward to Mars, sustainable space travel becomes essential for cost and independence from Earth. Astronaut activities in low Earth orbit resupply consumable materials and can require alternative technologies if transportation of chemicals is deemed hazardous. Plasma technology and applications are able to generate commodities that assist in achieving Earth independence. Plasma interaction with water generates acid in-situ using on-board resources of electricity and breathable air without the need for large infrastructure. At Kennedy Space Center, researchers have shown that plasma is able to produce nitric acid, and therefore nitrates, in a plant-usable form in water. In this report, the team presents results on acid generation in g/kW-hr as well as provides results on plasma activated water for plant growth assistance. Plasma was generated utilizing DC, AC, and pulsed power supplies in order to determine optimizing parameters for generation of this useful commodity.

Plasma↗

NASA NTRS2012

Linked-List-Based Multibody Dynamics (MBDyn) Engine

This new release of MBDyn is a software engine that calculates the dynamics states of kinematic, rigid, or flexible multibody systems. An MBDyn multibody system may consist of multiple groups of articulated chains, trees, or closed-loop topologies. Transient topologies are handled through conservation of energy and momentum. The solution for rigid-body systems is exact, and several configurable levels of nonlinear term fidelity are available for flexible dynamics systems. The algorithms have been optimized for efficiency and can be used for both non-real-time (NRT) and real-time (RT) simulations. Interfaces are currently compatible with NASA's Trick Simulation Environment. This new release represents a significant advance in capability and ease of use. The two most significant new additions are an application programming interface (API) that clarifies and simplifies use of MBDyn, and a link-list infrastructure that allows a single MBDyn instance to propagate an arbitrary number of interacting groups of multibody top ologies. MBDyn calculates state and state derivative vectors for integration using an external integration routine. A Trickcompatible interface is provided for initialization, data logging, integration, and input/output.

MacLean, John↗

NASA NTRS1993

The enhanced Software Life Cyle Support Environment (ProSLCSE): Automation for enterprise and process modeling

In this paper, we have introduced a comprehensive method for enterprise modeling that addresses the three important aspects of how an organization goes about its business. FirstEP includes infrastructure modeling, information modeling, and process modeling notations that are intended to be easy to learn and use. The notations stress the use of straightforward visual languages that are intuitive, syntactically simple, and semantically rich. ProSLCSE will be developed with automated tools and services to facilitate enterprise modeling and process enactment. In the spirit of FirstEP, ProSLCSE tools will also be seductively easy to use. Achieving fully managed, optimized software development and support processes will be long and arduous for most software organizations, and many serious problems will have to be solved along the way. ProSLCSE will provide the ability to document, communicate, and modify existing processes, which is the necessary first step.

Milligan, James R.↗

NASA NTRS2015

Alternative to Nitric Acid Passivation

The Ground Systems Development and Operations (GSDO) Program at NASA John F. Kennedy Space Center (KSC), Florida, has the primary objective of modernizing and transforming the launch and range complex at KSC to benefit current and future NASA programs along with other emerging users. Described as the launch support and infrastructure modernization program in the NASA Authorization Act of 2010, the GSDO Program will develop and implement shared infrastructure and process improvements to provide more flexible, affordable, and responsive capabilities to a multi-user community. In support of NASA and the GSDO Program, the objective of this project is to qualify citric acid as an environmentally-preferable alternative to nitric acid for passivation of stainless steel alloys. This project is a direct follow-on to United Space Alliance (USA) work at KSC to optimize the parameters for the use of citric acid and verify effectiveness. This project will build off of the USA study to further evaluate citric acids effectiveness and suitability for corrosion protection of a number of stainless steels alloys used by NASA, the Department of Defense (DoD), and the European Space Agency (ESA).

stainless steel↗

NASA NTRS2019

Solid Fuel Ignition and Extinction (SoFIE) Project on ISS

The Solid Fuel Ignition and Extinction (SoFIE) project studies ignition and flammability of solid spacecraft materials (fuels) in practical geometries and realistic atmospheric conditions. It is an experiment insert designed for use within the existing Combustion Integrated Rack (CIR). The CIR chamber provides a level of containment and permits testing at variable oxygen concentrations and pressures representative of current and planned NASA Space Exploration Atmospheres. The applications of SoFIE include: (1) Determining safer selection of cabin materials and validating NASA materials flammability selection using 1-g test protocols for low-gravity fires, (2) Improving understanding of early fire growth behavior, (3) Validating material flammability numerical models, (4) Determining optimal suppression techniques for burning materials by diluents, flow reduction, and venting, (5) Obtaining burning behavior of actual engineering materials planned for spacecraft, (6) Developing corresponding models of microgravity flame spread, flammability, and extinction, and use the results to improve normal gravity combustion models for terrestrial applications. The hardware permits a wide range of solid-material combustion and fire suppression studies. It supports multiple investigations using common infrastructure including sample holders, flow control, test sections, external radiant heaters, igniters, and diagnostics. SoFIE has been developed to meet the requirements of five unique investigations. It is currently being built and slated to begin operations on the ISS in July 2021. Given the general capabilities of the hardware insert, it is intended to be used as a facility for future researchers who can propose to NASA for related solid combustion studies.

Ferkul, Paul↗

NASA NTRS1999

Aerospace Systems Design in NASA's Collaborative Engineering Environment

Past designs of complex aerospace systems involved an environment consisting of collocated design teams with project managers, technical discipline experts, and other experts (e.g. manufacturing and systems operations). These experts were generally qualified only on the basis of past design experience and typically had access to a limited set of integrated analysis tools. These environments provided less than desirable design fidelity, often lead to the inability of assessing critical programmatic and technical issues (e.g., cost risk, technical impacts), and generally derived a design that was not necessarily optimized across the entire system. The continually changing, modern aerospace industry demands systems design processes that involve the best talent available (no matter where it resides) and access to the best design and analysis tools. A solution to these demands involves a design environment referred to as collaborative engineering. The collaborative engineering environment evolving within the National Aeronautics and Space Administration (NASA) is a capability that enables the Agency's engineering infrastructure to interact and use the best state-of-the-art tools and data across organizational boundaries. Using collaborative engineering, the collocated team is replaced with an interactive team structure where the team members are geographically distributed and the best engineering talent can be applied to the design effort regardless of physical location. In addition, a more efficient, higher quality design product is delivered by bringing together the best engineering talent with more up-to-date design and analysis tools. These tools are focused on interactive, multidisciplinary design and analysis with emphasis on the complete life cycle of the system, and they include nontraditional, integrated tools for life cycle cost estimation and risk assessment. NASA has made substantial progress during the last two years in developing a collaborative engineering environment. NASA is planning to use this collaborative engineering infrastructure to provide better aerospace systems life cycle design and analysis, which includes analytical assessment of the technical and programmatic aspects of a system from "cradle to grave." This paper describes the recent NASA developments in the area of collaborative engineering, the benefits (realized and anticipated) of using the developed capability, and the long-term plans for implementing this capability across the Agency.

Monell, Donald W.↗

NASA NTRS2000

Aerospace Systems Design in NASA's Collaborative Engineering Environment

Past designs of complex aerospace systems involved an environment consisting of collocated design teams with project managers, technical discipline experts, and other experts (e.g., manufacturing and systems operation). These experts were generally qualified only on the basis of past design experience and typically had access to a limited set of integrated analysis tools. These environments provided less than desirable design fidelity, often lead to the inability of assessing critical programmatic and technical issues (e.g., cost, risk, technical impacts), and generally derived a design that was not necessarily optimized across the entire system. The continually changing, modern aerospace industry demands systems design processes that involve the best talent available (no matter where it resides) and access to the the best design and analysis tools. A solution to these demands involves a design environment referred to as collaborative engineering. The collaborative engineering environment evolving within the National Aeronautics and Space Administration (NASA) is a capability that enables the Agency's engineering infrastructure to interact and use the best state-of-the-art tools and data across organizational boundaries. Using collaborative engineering, the collocated team is replaced with an interactive team structure where the team members are geographical distributed and the best engineering talent can be applied to the design effort regardless of physical location. In addition, a more efficient, higher quality design product is delivered by bringing together the best engineering talent with more up-to-date design and analysis tools. These tools are focused on interactive, multidisciplinary design and analysis with emphasis on the complete life cycle of the system, and they include nontraditional, integrated tools for life cycle cost estimation and risk assessment. NASA has made substantial progress during the last two years in developing a collaborative engineering environment. NASA is planning to use this collaborative engineering engineering infrastructure to provide better aerospace systems life cycle design and analysis, which includes analytical assessment of the technical and programmatic aspects of a system from "cradle to grave." This paper describes the recent NASA developments in the area of collaborative engineering, the benefits (realized and anticipated) of using the developed capability, and the long-term plans for implementing this capability across Agency.

Monell, Donald W.↗

NASA NTRS2013

Space Telecommunications Radio System STRS Cognitive Radio

Radios today are evolving from awareness toward cognition. A software defined radio (SDR) provides the most capability for integrating autonomic decision making ability and allows the incremental evolution toward a cognitive radio. This cognitive radio technology will impact NASA space communications in areas such as spectrum utilization, interoperability, network operations, and radio resource management over a wide range of operating conditions. NASAs cognitive radio will build upon the infrastructure being developed by Space Telecommunication Radio System (STRS) SDR technology. This paper explores the feasibility of inserting cognitive capabilities in the NASA STRS architecture and the interfaces between the cognitive engine and the STRS radio. The STRS architecture defines methods that can inform the cognitive engine about the radio environment so that the cognitive engine can learn autonomously from experience, and take appropriate actions to adapt the radio operating characteristics and optimize performance.

Briones, Janette C.↗

NASA NTRS2016

NextGen Far-Term Concept Exploration for Integrated Gate-to-Gate Trajectory-Based Operations

NASA is currently conducting concept exploration studies toward the definition of a far-term, gate-to-gate concept for Trajectory-Based Operations. This paper presents a basic architectural framework for the far-term concept and discusses some observations about implementation of trajectory-based operations in the National Airspace System. Within the concept, operators and service providers collaboratively negotiate aircraft trajectories, providing agile, optimized, aircraft-specific routing to meet service provider gate-to-gate flow-management constraints and increasing capacity by smoothly and effectively combining flight-deck-based and ground-based metering, merging, and spacing in a mixed-equipage environment. The far-term TBO concept is intended to influence the direction of mid-term TBO research and to inform the definition of stable requirements and standards for TBO communications infrastructure and user equipage.

Johnson, Sally C.↗

NASA NTRS2004

Laser Ranging to the Moon, Mars and Beyond

Current and future optical technologies will aid exploration of the Moon and Mars while advancing fundamental physics research in the solar system. Technologies and possible improvements in the laser-enabled tests of various physical phenomena are considered along with a space architecture that could be a cornerstone for robotic and human exploration in the solar system. In particular, accurate ranging to the Moon and Mars would not only lead to construction of a new space communication infrastructure enabling improved navigational accuracy, but would provide a significant improvement in several tests of gravitational theory: the equivalence principle, geodetic precession, PPN parameters beta and gamma, and the constancy of the gravitational constant G. Other tests would become possible with an optical architecture that would allow proceeding from cm to mm to sub-mm range accuracies. Looking to future exploration, what characteristics are desired for the next generation of ranging devices, what is the optimal architecture that would benefit both space exploration and fundamental physics, and what fundamental questions can be investigated?

Turyshev, Slava G.↗

NASA NTRSDate not supplied

Web-based Visualization and Analytics of Petascale Data: Equity as a Tide that Lifts All Boats

Scientists generate petabytes of data daily to help uncover environmental trends or behaviors that are hard to predict. For example, understanding climate simulations based on the long-term average of temperature, precipitation, and other environmental variables is essential to predicting and establishing root causes of future undesirable scenarios and assessing possible mitigation strategies. While supercomputer centers provide a powerful infrastructure for generating petabytes of simulation output, accessing and analyzing these datasets interactively remains challenging on multiple fronts. This paper presents an approach to managing, visualizing, and analyzing petabytes of data within a browser on equipment ranging from the top NASA supercomputer to commodity hardware like a laptop. Our novel data fabric abstraction layer allows user-friendly querying of scientific information while hid-ing the complexities of dealing with file systems or cloud services.We also optimize network utilization while streaming from petas-cale repositories through state-of-the-art progressive compression algorithms. Based on this abstraction, we provide customizable dashboards that can be accessed from any device with any inter-net connection, enabling interactive visual analysis of vast amounts of data to a wide range of users - from top scientists with access to leadership-class computing environments to undergraduate students of disadvantaged backgrounds from minority-serving institutions. We focus on NASA’s use of petascale climate datasets as an example of particular societal impact and, therefore, a case where achieving equity in science participation is critical. We validate our approach by improving the ability of climate scientists to visually explore their data via two fully interactive dashboards. We further validate our approach by deploying the dashboards and simplified training materials in the classroom at a minority-serving institution.These dashboards, released in simplified form to the general public, contribute significantly to a broader push to democratize the access and use of climate data.

Data visualization↗

NASA NTRS2004

Adaptive Bio-Inspired Wireless Network Routing for Planetary Surface Exploration

Wireless mobile networks suffer connectivity loss when used in a terrain that has hills, and valleys when line of sight is interrupted or range is exceeded. To resolve this problem and achieve acceptable network performance, we have designed an adaptive, configurable, hybrid system to automatically route network packets along the best path between multiple geographically dispersed modules. This is very useful in planetary surface exploration, especially for ad-hoc mobile networks, where computational devices take an active part in creating a network infrastructure, and can actually be used to route data dynamically and even store data for later transmission between networks. Using inspiration from biological systems, this research proposes to use ant trail algorithms with multi-layered information maps (topographic maps, RF coverage maps) to determine the best route through ad-hoc network at real time. The determination of best route is a complex one, and requires research into the appropriate metrics, best method to identify the best path, optimizing traffic capacity, network performance, reliability, processing capabilities and cost. Real ants are capable of finding the shortest path from their nest to a food source without visual sensing through the use of pheromones. They are also able to adapt to changes in the environment using subtle clues. To use ant trail algorithms, we need to define the probability function. The artificial ant is, in this case, a software agent that moves from node to node on a network graph. The function to calculate the fitness (evaluate the better path) includes: length of the network edge, the coverage index, topology graph index, and pheromone trail left behind by other ant agents. Each agent modifies the environment in two different ways: 1) Local trail updating: As the ant moves between nodes it updates the amount of pheromone on the edge; and 2) Global trail updating: When all ants have completed a tour the ant that found the shortest route updates the edges in its path.

Alena, Richard I.↗

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 NTRS2019

Optical Communication Link Atmospheric Attenuation Model

The Space Communications and Navigation (SCaN) Center for Networking, Integration, and Communications (SCENIC) user interface, which provides web accessible space mission simulation and communication system analysis capabilities using verified and validated analysis algorithms, can execute analyses including, but not limited to, line-of-sight, orbit propagation, and dynamic link budget calculations between sets of missions and/or assets. SCENIC's purpose is to provide NASA civil servants and contractors a user-friendly tool, integrated with model data, that can simulate and analyze a range of space mission architectures without the need for repeated and redundant modeling. Given the abundance and further future development of free space optical (FSO) communication channels within modern space infrastructure, the availability of a reliable optical link analysis capability is crucial for SCENIC users. The efforts outlined in this paper aim to provide a model for atmospheric attenuation of FSO communication links, both due to absorption/scattering and turbulence, to increase the accuracy of SCENIC's optical link assessment capabilities. A previous model existed for optical absorption/scattering within the SCaN Link Budget Tool, but it was not location specific for the Earth ground-based nodes, nor was the model optimized for run-time. The new model utilizes years of National Oceanic and Atmospheric Administration (NOAA) visibility data from ground station locations around the world. Visibility, along with the wavelength of the optical signal, are input parameters to calculate the optical specific attenuation, which is a parameter in the calculation of the slant-path attenuation. A final FSO atmospheric attenuation value is comprised of the absorption/scattering attenuation and the turbulence attenuation. A run-time efficient algorithm for the model was then developed and programmed in MATLAB ® . Due to the simple model and vectorization possible in MATLAB, the algorithm has an average run-time of less than one fourth of the run-time of the previous implementation.

Jack L Green↗

NASA NTRS2015

Precision Time Protocol-Based Trilateration for Planetary Navigation

Progeny Systems Corporation has developed a high-fidelity, field-scalable, non-Global Positioning System (GPS) navigation system that offers precision localization over communications channels. The system is bidirectional, providing position information to both base and mobile units. It is the first-ever wireless use of the Institute of Electrical and Electronics Engineers (IEEE) Precision Time Protocol (PTP) in a bidirectional trilateration navigation system. The innovation provides a precise and reliable navigation capability to support traverse-path planning systems and other mapping applications, and it establishes a core infrastructure for long-term lunar and planetary occupation. Mature technologies are integrated to provide navigation capability and to support data and voice communications on the same network. On Earth, the innovation is particularly well suited for use in unmanned aerial vehicles (UAVs), as it offers a non-GPS precision navigation and location service for use in GPS-denied environments. Its bidirectional capability provides real-time location data to the UAV operator and to the UAV. This approach optimizes assisted GPS techniques and can be used to determine the presence of GPS degradation, spoofing, or jamming.

Murdock, Ron↗