Results for “Platforms” — Page 16

DOE OSTI2025

Initial Characterization of the NREL Large-Amplitude Motion Platform

The Large Amplitude Motion Platform (LAMP) at NREL represents a significant advancement in the controlled testing of Wave Energy Converters (WECs) under laboratory conditions. Originally designed by E2M as a six-degree-of-freedom (DOF) Stewart platform for flight simulation, LAMP has been adapted by NREL to facilitate the mounting and evaluation of WECs. This adaptation enables dry testing of WECs using motion profiles similar to the ocean, facilitating the iterative design, testing, and validation of WEC performance prior to ocean deployments. This report presents the initial work completed to characterize LAMP, with particular emphasis on its stability and operational capabilities across various single and multi-degree-of-freedom (DOF) motion profiles. The report includes planned comparisons at three distinct mass payloads, aimed at assessing the platform's positional accuracy, frequency response, and endurance over extended runtime periods. These experimental tests are critical for establishing the platform's limitations and ensuring that the data generated during WEC validation is both accurate and reproducible. The outcomes of this study not only contribute to a deeper understanding of LAMP's capabilities but also lay the groundwork for future advancements in WEC testing methodologies. By providing robust and reliable performance data within a controlled laboratory setting, the findings are expected to significantly enhance the development and commercialization of marine energy technologies. This report presents the initial findings of the LAMP Characterization work and proposed steps to further understand and characterize LAMP. Data collected during this work can be found on MHKDR at: https://mhkdr.openei.org/submissions/602 Note that this report shares the measured/found instantaneous maximum operating range of LAMP. For most applications the maximum operating range cannot be used for system health and longevity. The operating range and capabilities of LAMP will be evaluated on a case-by-case basis, single-DOF position, velocity, and acceleration values presented in Table 4a-c, and Table 5 should be taken as instantaneous absolute maximum values. Future use of LAMP will likely be limited to smaller values.

16 TIDAL AND WAVE POWER↗

DOE OSTI2018

Rules of the rooftop: Platform design and price reductions in an online solar photovoltaic marketplace in the United States

Residential solar photovoltaic (PV) customers typically obtain price quotes directly from installers, a process with high consumer search costs that enable price dispersion and can discourage adoption. Recently, however, customers are increasingly shopping for PV using third-party online platforms that make it easier to obtain and compare quotes from multiple installers. While early evidence indicates that these platforms make the PV market more transparent and lower prices, the literature suggests that market outcomes are critically linked to detailed aspects of platform design. In this study, we econometrically analyze a unique dataset of quotes offered in the online PV marketplace EnergySage to investigate how four changes to the platform design have influenced quote prices and transaction prices. We find that the largest reductions in quote prices ($0.11/ W) and transaction prices ($0.15/W) were associated with the introduction of a price guidance information feature for installers. While educating and informing customers has repeatedly emerged as a policy priority for bolstering PV markets, these results suggest that the same should be true on the supply side. We also find that customers are willing to pay higher transaction prices for systems with higher-quality panels, dispelling concerns that online PV marketplaces lead to a 'race to the bottom' phenomenon by emphasizing price at the expense of quality.

14 SOLAR ENERGY↗

DOE OSTI2020

Large eddy simulations of offshore wind turbine wakes for two floating platform types

The growing prospect for large farms of floating offshore wind turbines requires a better understanding of wake effects for floating turbines. In this work, large eddy simulations with an actuator line model are used to study the wake of the NREL 5 MW reference turbine mounted on the OC3-UMaine spar and OC4-DeepCwind semi-submersible platforms. The simulations are carried out in the Simulator fOr Wind Farm Applications (SOWFA) coupled with OpenFAST for the platform and turbine motion. The wake location, deficit, and turbulence levels are compared for the two floating platforms and equivalent fixed-turbine cases. The effects of neutral versus stable atmospheric conditions are also compared. Most notably, floating-turbine wakes are deflected upwards compared to fixed-turbine wakes, because of mean platform pitch. The spar wake deflects upwards more than the semi-submersible, while the stable atmosphere increases this vertical deflection compared to the neutral. The time-varying rotor motions do not significantly affect the mid-to-far wake, though the stable atmosphere shows larger fixed-floating differences in horizontal wake fluctuations.

17 WIND ENERGY↗

DOE OSTI2018

Material platforms for optical metasurfaces

Optical metasurfaces are judicously engineered electromagnetic interfaces that can control and manipulate many of light’s quintessential properties, such as amplitude, phase, and polarization. These artificial surfaces are composed of subwavelength arrays of optical antennas that experience resonant light-matter interaction with incoming electromagnetic radiation. Their ability to arbitrarily engineer optical interactions has generated considerable excitement and interest in recent years and is a promising methodology for miniaturizing optical components for applications in optical communication systems, imaging, sensing, and optical manipulation. However, development of optical metasurfaces requires progress and solutions to inherent challenges, namely large losses often associated with the resonant structures; large-scale, complementary metal-oxide-semiconductor-compatible nanofabrication techniques; and incorporation of active control elements. Furthermore, practical metasurface devices require robust operation in high-temperature environments, caustic chemicals, and intense electromagnetic fields. Although these challenges are substantial, optical metasurfaces remain in their infancy, and novel material platforms that offer resilient, low-loss, and tunable metasurface designs are driving new and promising routes for overcoming these hurdles. In this review, we discuss the different material platforms in the literature for various applications of metasurfaces, including refractory plasmonic materials, epitaxial noble metal, silicon, graphene, phase change materials, and metal oxides. We identify the key advantages of each material platform and review the breakthrough devices that were made possible with each material. Finally, we provide an outlook for emerging metasurface devices and the new material platforms that are enabling such devices.

36 MATERIALS SCIENCE↗

DOE OSTI2024

UAS remote sensing (AltaX platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance (Level 0 data), Seward Peninsula, Alaska, 2023

Airborne remote sensing data collected using Brookhaven National Laboratory’s (BNL) heavy-lift unoccupied aerial system (UAS) AltaX platform on the Seward Peninsula, Alaska, USA. This package includes raw (L0) data from 11 flights flown over the NGEE-Arctic Kougarok mile marker 64 (MM64) and Teller MM 27 sites in July, 2023. The AltaX is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface “skin” temperature imagery, as well as near-surface surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350 – 1000 nm. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), binary (*.dat, *.ulg), tabular (*.csv), geospatial (*.kml. *kmz), image (*.jpg, *.png, *.tif) and pdf formats. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the L0 data and the file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

UAS remote sensing (AltaX platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance (Level 0 data), Seward Peninsula, Alaska, 2022

Airborne remote sensing data collected using Brookhaven National Laboratory’s (BNL) heavy-lift unoccupied aerial system (UAS) AltaX platform on the Seward Peninsula, Alaska, USA. This package includes raw (L0) data from 10 flights flown over the NGEE-Arctic Kougarok mile marker 64 (MM64) and Teller MM 27 sites in July, 2022. The AltaX is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface “skin” temperature imagery, as well as near-surface surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350 – 1000 nm. This package provides the Level 0 (raw, unprocessed) data collected by the platform and sensors. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), binary (*.dat, *.ulg), tabular (*.csv), geospatial (*.kml. *kmz), image (*.jpg, *.png, *.tif) and pdf formats. The metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the L0 data and the file naming scheme.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2019

Programmable Electrofluidics for Ionic Liquid Based Neuromorphic Platform

Due to the limit in computing power arising from the Von Neumann bottleneck, computational devices are being developed that mimic neuro-biological processing in the brain by correlating the device characteristics with the synaptic weight of neurons. This platform combines ionic liquid gating and electrowetting for programmable placement/connectivity of the ionic liquid. In this platform, both short-term potentiation (STP) and long-term potentiation (LTP) are realized via electrostatic and electrochemical doping of the amorphous indium gallium zinc oxide (aIGZO), respectively, and pulsed bias measurements are demonstrated for lower power considerations. While compatible with resistive elements, we demonstrate a platform based on transitive amorphous indium gallium zinc oxide (aIGZO) pixel elements. Using a lithium based ionic liquid, we demonstrate both potentiation (decrease in device resistance) and depression (increase in device resistance), and propose a 2D platform array that would enable a much higher pixel count via Active Matrix electrowetting.

36 MATERIALS SCIENCE↗

DOE OSTI2025

Hydrogen-Battery Hybrid Energy System on Repurposed Offshore Platforms for Efficient Clean-Energy Transition

Due to the rising global energy demand and enhanced awareness of the environmental impact of fossil fuels, the Gulf of Mexico, traditionally known for oil extraction, offers a distinct chance to repurpose the existing offshore infrastructure. With the depletion of oil reserves, it is feasible to adapt previously utilized floating platforms for extraction to generate renewable energy, specifically through wind-generated power and hydrogen production. This adaptation seeks to promote a transport system that is more ecologically friendly in the future. Offshore wind turbines serve as the main energy source, with help from battery storage and hydrogen production to enhance the overall system performance, hydrogen creation, fuel, and electricity delivery for sustainable energy production. The system is divided into two distinct cases, each evaluated for cost, performance, and feasibility, with a focus on minimizing both the Levelized Cost of Energy (LCOE) and the Levelized Cost of Hydrogen (LCOH). The first case examines the integration of offshore wind turbines with hydrogen production. Excess electricity generated by wind turbines is directed toward hydrogen production via electrolysis. The hydrogen produced can be used as fuel for vehicles or transported to the shore via pipelines. The second case investigates a technology that combines wind turbines with battery storage. The batteries possess an ability to supply electricity for a continuous duration of 4 hours maximum each day. The main objective is to reduce the LCOE by considering the battery's charging and discharging cycles, together with the uncertain attributes of wind power and battery deterioration. The produced energy can be distributed for onshore applications or utilized for the purpose of offsetting offshore loads such as subsea oil and gas production, transportation, etc. The offshore hydrogen-battery hybrid system is improved via three advanced algorithms, Particle Swarm Optimization (PSO), and Grey Wolf Optimizer (GWO). In Case 1, PSO improves hydrogen production by efficiently managing the electrolyzer’s power consumption, decreasing production costs significantly. Particle Swarm Optimization (PSO) is applied to improve the efficiency of the electrolyzer, reducing production costs and achieving an optimized CAPEX of $240.00 million (from an initial $300.00 million) and OPEX of $9.60 million per year. This system produces 4,720,000 kg of hydrogen annually, with a Levelized Cost of Hydrogen (LCOH) of $6.40/kg and an annual profit of $9.27 million. In Case 2, GWO effectively reduces the overall energy cost by improving the charge-discharge management of batteries, which extends battery life and optimizes their use. The second case focuses on integrating battery storage, optimized using the Grey Wolf Optimizer (GWO), which enhances battery charge-discharge cycles, extending battery life and lowering costs. This system achieves an optimized CAPEX of $204.80 million (from an initial $256.00 million) and OPEX of $9.29 million per year, producing 310883.39 MWh of electricity annually at a Levelized Cost of Energy (LCOE) of $86.13/MWh, with an annual profit of $6.25 million. The implementation of a comprehensive strategy results in a substantial reduction in costs, improved energy efficiency, and a dependable supply of both electric power and hydrogen, emphasizing the benefits of converting offshore oil platforms for clean energy transition. This study explores a clean strategy to enable cost-effective repurposing of offshore O&G platforms. Both cases highlight the economic and technical feasibility of transitioning offshore oil platforms to clean energy systems, demonstrating substantial cost reductions and reliable energy and hydrogen supplies for sustainable energy production.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2024

UAS remote sensing (Osprey platform): Red-green-blue (RGB) imagery, thermal infrared (TIR) imagery, and canopy reflectance, Seward Peninsula, Alaska, 2017

Airborne remote sensing data collected using the Brookhaven National Laboratory's (BNL) heavy-lift unoccupied aerial system (UAS) octocopter platform - the Osprey - operated by the Terrestrial Ecosystem Science and Technology (TEST) group (https://www.bnl.gov/testgroup). This package includes raw (L0) data from 14 flights flown over the NGEE-Arctic Council Mile Marker 71 (MM71), Kougarok MM64, and Teller MM 27 sites in August, 2017. The Osprey is a multi-sensor UAS platform that simultaneously measures very high spatial resolution optical red/green/blue (RGB) and thermal infrared (TIR) surface "skin" temperature imagery, as well as near-surface surface reflectance at 1 nm intervals in the visible to near-infrared spectral range from ~350-1000 nm measured at regular intervals along each flight path. This package provides the Level 0 (raw, unprocessed) data collected by the Osprey platform. Ancillary aircraft data, flight mission parameters, and general flight conditions provided by the onboard flight and data collection computers are also included. Data and metadata are provided as text (*.txt, *.json), tabular (*.dat, *.csv, *.waypoint), and image (*.jpg) formats. This metadata documents contain flight campaign, platform, sensor, flight and file metadata, along with a description of the L0 data and the file naming scheme. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a 15-year research effort (2012-2027) to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

NASA NTRSDate not supplied

Near-term Persistent Platform Orbital Testbed: Three Candidate Architecture Options

On-orbit Servicing, Assembly, and Manufacturing (OSAM) will revolutionize the space industry by transforming the concept of operations of space systems and enabling new, radically different system implementations. These new implementations will benefit from a novel persistent asset design paradigm which focuses on evolvable designs that are tailored to the operational environment, not the launch environment. In addition, the ability to launch sub-systems independently enable future persistent assets to economically expand in capability and size, achieving cost effective and productive operations lasting for decades like terrestrial observatories. With few exceptions (International Space Station, Hubble Space Telescope, Mission Extension Vehicle customers), current space systems are not visited once they are operational. Leveraging emerging low cost commercial launch provides the ability to repeatedly and routinely revisit space systems. Thus, revolutionary new approaches for space system design are possible, creating completely new opportunities for small businesses and accelerating the growth of already established space industries. To usher in the revolutionary new operational paradigm, two things are needed. First, to build confidence in the technology and new paradigm, there must be a leading example, a bellwether persistent asset, that demonstrates the reliability and maturity of the new persistent asset paradigm (where repeated visits are common). Second, in order to rapidly advance and validate OSAM capabilities, an efficient means is required to conduct tests in the space environment. A persistent platform testbed satisfies both these needs. The space environment exhibits a plethora of characteristics that are difficult and costly to accurately simulate for a full system in a terrestrial laboratory, such as near zero gravity, a wide range of ionizing radiation types, atomic oxygen, and micro-meteoroids and space debris traveling at high velocity. In addition, since persistent assets range in mass from a few grams to several metric tons, it is difficult to accurately simulate interactions between these systems and visiting vehicles (that also exhibit a wide range of varying masses and capabilities). These interactions include the transmission of forces and/or exchanging mass (in the form of instruments, fuel, robotic assets, etc.). Thus, a rapid, versatile and cost efficient in-space testing capability that includes a persistent test platform and a surrounding in-space test zone is needed to mature technologies through experimentation. The testbed can provide common services, such as: power, thermal control, vibration isolation, data transmission between experiments and terrestrial experimenters, station-keeping, pointing, and robotic agents that can be leveraged by customer experiments. The onboard robotic agents can be used to provide payload handling services, such as: assembly, change out or upgrade, relocation, connecting/disconnecting utilities, inspection, repair or servicing, etc. Since the persistent platform cost will be amortized over many hosted payloads, its services can eventually be offered at a price much lower than if one were to design a unique and dedicated spacecraft and mission for those few experiments. The key to achieving an effective testbed is providing efficient cost effective access and infrastructure to a variety of commercial, academic and government customers coupled with extensibility, in the capability of an individual persistent platform test bed or replication of the test bed in a different operational regime. Three potential options for implementing a test bed were developed and evaluated in this study.

Persistent Platform↗

NASA NTRSDate not supplied

Near-term Persistent Platform Orbital Testbed: Three Candidate Architecture Options

On-orbit Servicing, Assembly, and Manufacturing (OSAM) will revolutionize the space industry by transforming the concept of operations of space systems and enabling new, radically different system implementations. These new implementations will benefit from a novel persistent asset design paradigm which focuses on evolvable designs that are tailored to the operational environment, not the launch environment. In addition, the ability to launch sub-systems independently enable future persistent assets to economically expand in capability and size, achieving cost effective and productive operations lasting for decades like terrestrial observatories. With few exceptions (International Space Station, Hubble Space Telescope, Mission Extension Vehicle customers), current space systems are not visited once they are operational. Leveraging emerging low cost commercial launch provides the ability to repeatedly and routinely revisit space systems. Thus, revolutionary new approaches for space system design are possible, creating completely new opportunities for small businesses and accelerating the growth of already established space industries. To usher in the revolutionary new operational paradigm, two things are needed. First, to build confidence in the technology and new paradigm, there must be a leading example, a bellwether persistent asset, that demonstrates the reliability and maturity of the new persistent asset paradigm (where repeated visits are common). Second, in order to rapidly advance and validate OSAM capabilities, an efficient means is required to conduct tests in the space environment. A persistent platform testbed satisfies both these needs. The space environment exhibits a plethora of characteristics that are difficult and costly to accurately simulate for a full system in a terrestrial laboratory, such as near zero gravity, a wide range of ionizing radiation types, atomic oxygen, and micro-meteoroids and space debris traveling at high velocity. In addition, since persistent assets range in mass from a few grams to several metric tons, it is difficult to accurately simulate interactions between these systems and visiting vehicles (that also exhibit a wide range of varying masses and capabilities). These interactions include the transmission of forces and/or exchanging mass (in the form of instruments, fuel, robotic assets, etc.). Thus, a rapid, versatile and cost efficient in-space testing capability that includes a persistent test platform and a surrounding in-space test zone is needed to mature technologies through experimentation. The testbed can provide common services, such as: power, thermal control, vibration isolation, data transmission between experiments and terrestrial experimenters, station-keeping, pointing, and robotic agents that can be leveraged by customer experiments. The onboard robotic agents can be used to provide payload handling services, such as: assembly, change out or upgrade, relocation, connecting/disconnecting utilities, inspection, repair or servicing, etc. Since the persistent platform cost will be amortized over many hosted payloads, its services can eventually be offered at a price much lower than if one were to design a unique and dedicated spacecraft and mission for those few experiments. The key to achieving an effective testbed is providing efficient cost effective access and infrastructure to a variety of commercial, academic and government customers coupled with extensibility, in the capability of an individual persistent platform test bed or replication of the test bed in a different operational regime. Three potential options for implementing a test bed were developed and evaluated in this study.

Persistent Platform↗

NASA NTRSDate not supplied

Small Spacecraft Technologies: The Evolution of CubeSat Spacecraft Platforms

The maturity of small spacecraft technology is indicated by the continued growth in the number of missions, mission complexity, and the expansion of smallsat subsystem capability. The inception of the CubeSat platform has incentivized the space industry to achieve a broad collection of science for less cost, and there is an evolving trend in the overall utilization of the CubeSat platform seen in the last decade. CubeSats’ initial purpose was to serve as a platform to demonstrate specific technologies while also serving as an educational platform for students and professional engineers alike. In the ten years since, CubeSats are being designed for more complex science missions around the Moon, Sun, or to deep space, and the projection for 10 years from now is that CubeSats will be performing more complex deep space missions. The progress of overall small spacecraft technology development is captured in the most recent 2020 Small Spacecraft Technology State-of-the-Art (SoA) report, the objective of which is to assess and provide an overview on the current development status across all subsystem architectures. The SoA report summarizes the results of a variety of surveys covering device performance, capabilities, and flight history, as presented in publicly available literature. The focus of these surveys is on devices or systems that can be commercially procured or appear on a path towards being commercial availability. The work toward the 2020 edition of the SoA report was managed by NASA’s Small Spacecraft Systems Virtual Institute (S3VI) and performed by several contractor staff. The S3VI is jointly funded by NASA’s Space Technology Mission Directorate and Science Mission Directorate.

Small Spacecraft Technologies↗

NASA NTRS2021

The Evolution of CubeSat Spacecraft Platforms

The maturity of small spacecraft technology is indicated by the continued growth in the number of missions, mission complexity, and the expansion of smallsat subsystem capability. The inception of the CubeSat platform has incentivized the space industry to achieve a broad collection of science for less cost, and there is an evolving trend in the overall utilization of the CubeSat platform seen in the last decade. CubeSats’ initial purpose was to serve as a platform to demonstrate specific technologies while also serving as an educational platform for students and professional engineers alike. In the ten years since, CubeSats are being designed for more complex science missions around the Moon, Sun, or to deep space, and the projection for 10 years from now is that CubeSats will be performing more complex deep space missions. The progress of overall small spacecraft technology development is captured in the most recent 2020 Small Spacecraft Technology State-of-the-Art (SoA) report, the objective of which is to assess and provide an overview on the current development status across all subsystem architectures. The SoA report summarizes the results of a variety of surveys covering device performance, capabilities, and flight history, as presented in publicly available literature. The focus of these surveys is on devices or systems that can be commercially procured or appear on a path towards being commercial availability.

Small Spacecraft Technology↗

NASA NTRSDate not supplied

The Evolution of CubeSat Spacecraft Platforms

The maturity of small spacecraft technology is indicated by the continued growth in the number of missions, mission complexity, and the expansion of smallsat subsystem capability. The inception of the CubeSat platform has incentivized the space industry to achieve a broad collection of science for less cost, and there is an evolving trend in the overall utilization of the CubeSat platform seen in the last decade. The initial purpose of CubeSats’ was to serve as a platform to demonstrate specific technologies while also serving as an educational platform for students and professional engineers alike. In the ten years since, CubeSats have been designed for more complex science missions around the Moon, Sun, or to deep space, and the projection for ten years from now is that CubeSats will be performing more complex deep space missions. The progress of overall small spacecraft technology development is captured in the most recent 2021 Small Spacecraft Technology State-of-the-Art (SoA) report, the objective of which is to assess and provide an overview on the current development status across all subsystem architectures. The SoA report summarizes the results of a variety of surveys covering device performance, capabilities, and flight history, as presented in publicly available literature. The focus of these surveys is on devices or systems that can be commercially procured or appear on a path toward becoming commercially available.

Small Spacecraft Technology↗

NASA NTRSDate not supplied

DIP - Digital Information Platform

Brief updates of Digital Information Platform (DIP) plans for platform-enabled sustainable aviation services. DIP will provide the capability to integrate key flight information from multiple sources and make it easier to access data critical to developing services using advanced techniques such as machine learning. NASA will share ML-based microservices on the platform for industry to use as reference implementations. The platform will support an ecosystem to share reusable services and promote innovation for digital information.

DIP update↗

NASA NTRS2023

NASA’s Digital Information Platform to Accelerate the Transformation of the National Airspace System

In order to accelerate the digital transformation of airspace operations, a foundational framework and infrastructure for providing sustainable, data-driven, and cohesive decision-making digital services for both traditional and emergent air vehicles is being developed. The reference implementation of Digital Information Platform builds an ecosystem for the aviation community by providing access to a secure and trusted source of aviation data and services. Several key features and services have been implemented to enable secure data sharing, communication, and service registration on the Platform. The technical approach used to implement these features is presented here. NASA-developed integrated aviation data and machine learning based prediction services to optimize airspace operations are available on the Platform. These services are being evaluated in an operational environment by flight operators and the real-world benefits are being captured. The Platform fosters collaboration among industry and researchers to develop complex aviation services and the aim is to make it publicly accessible for consumption by the aviation community.

Digital Transformation↗

NASA NTRSDate not supplied

NASA’s Digital Information Platform to Accelerate the Transformation of the National Airspace System

In order to accelerate the digital transformation of airspace operations, a foundational framework and infrastructure for providing sustainable, data-driven, and cohesive decision-making digital services for both traditional and emergent air vehicles is being developed. The reference implementation of Digital Information Platform builds an ecosystem for the aviation community by providing access to a secure and trusted source of aviation data and services. Several key features and services have been implemented to enable secure data sharing, communication, and service registration on the Platform. The technical approach used to implement these features is presented here. NASA-developed integrated aviation data and machine learning based prediction services to optimize airspace operations are available on the Platform. These services are being evaluated in an operational environment by flight operators and the real-world benefits are being captured. The Platform fosters collaboration among industry and researchers to develop complex aviation services and the aim is to make it publicly accessible for consumption by the aviation community.

Digital Transformation↗

DOE OSTI2012

VOLTTRON: An Agent Execution Platform for the Electric Power System

Volttron is an agent execution platform that is engineered for use in the electric power system. Volttron provides resource guarantees for agents and the platform including memory and processor utilization; authentication and authorization services; directory services for agent and resource location; and agent mobility. Unlike most other agent platforms, Volttron does not depend on a single agent authoring language. Instead, we chose to design and implement Volttron as a platform service and framework that is decoupled from the agent execution environment. A prototype implementation of Volttron has been written in Python (using Python v2.7.2) and we have executed agents written in Python and Java and as shell scripts. The intended use of Volttron is in the power distribution system for managing distributed generation, demand-response, and plug-in electric vehicles.

Multi-Agent Systems↗