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A simulator is described, which was designed for testing and evaluating inertial measuring units, and flight platforms. Mechanical and electrical specifications for the outer, middle, and inner axis are presented. Test results are included.
The present investigation is concerned with the results of a two-frequency (Delta k) microwave radar experiment conducted from an aircraft and aimed primarily at the development of remote sensing techniques to measure ocean surface wave spectral characteristics. The experiment was conducted as part of the Maritime Remote Sensing (MARSEN) project in the North Sea during the autumn of 1979. The objective was to demonstrate the feasibility of and study the performance of the Delta k technique from a higher altitude platform, at shallower incidence angles, and at higher Doppler velocities than earlier stationary platform experiments allowed. A quantitative engineering evaluation of the results of two comprehensive flights is provided, and the qualitative significance of the results is discussed from a geophysical point of view in terms of the existing theory.
The NEFTY SR&T grant was focused on the development of novel electric field boom systems for sounding rocket applications. A "yo-yo"-type boom that unwraps from a rotating and damped axel was analyzed through a simulation with Prof. Psiaki of Mechanical and Aerospace Engineering at Cornell University. The basic parameters of the analysis were evaluated and validated on a spinning platform prototyping system developed at Cornell University. The full "yo-yo"-type boom system is being developing for the SIERRA sounding rocket flight scheduled for a January 2002 launch. The principal results from this study were published.
The development of a robust regolith moving system for lunar and planetary processing and construction is critical to the NASA mission to the Moon and Mars. Oxygen production may require up to 200 metric tons of regolith collection per year; outpost site development may require several times this amount. This paper describes progress in the small vehicle implement development and small excavation system development. Cratos was developed as a platform for the ISRU project to evaluate the performance characteristics of a low center of gravity, small (0.75m x 0.75m x 0.3m), low-power, tracked vehicle performing excavation, load, haul, and dump operations required for lunar ISRU. It was tested on loose sand in a facility capable of producing level and inclined surfaces, and demonstrated the capability to pick up, carry, and dump sand, allowing it to accomplish the delivery of material to a site. Cratos has demonstrated the capability to pick up and deliver simulant to a bury an inflatable habitat, to supply an oxygen production plant, and to build a ramp.
A baseline configuration for the dual-aircraft platform (DAP) concept is described and evaluated in a physics-based flight dynamics simulations for two month-long missions as a communications relay in the lower stratosphere above central Florida. The DAP features two unmanned aerial vehicles connected via a long adjustable cable which effectively sail back-and-forth using wind velocity gradients and solar energy. Detailed atmospheric profiles in the vicinity of 60,000-ft derived from archived data measured by the 50-Mhz Doppler Radar Wind Profiler at Cape Canaveral are used in the flight simulations. An overview of the novel guidance and flight control strategies are provided. The energy-usage of the baseline configuration during month-long stationkeeping missions (i.e., within 150-mile radius of downtown Orlando) is characterized and compared to that of a pure solar aircraft.
In this paper, we present a novel approach and framework for run-time verication of large, safety critical messaging systems. This work was motivated by verifying the System Wide Information Management (SWIM) project of the Federal Aviation Administration (FAA). SWIM provides live air traffic, site and weather data streams for the whole National Airspace System (NAS), which can easily amount to several hundred messages per second. Such safety critical systems cannot be instrumented, therefore, verification and monitoring has to happen using a nonintrusive approach, by connecting to a variety of network interfaces. Due to a large number of potential properties to check, the verification framework needs to support efficient formulation of properties with a suitable Domain Specific Language (DSL). Our approach is to utilize a distributed system that is geared towards connectivity and scalability and interface it at the message queue level to a powerful verification engine. We implemented our approach in the tool called MESA: Message-Based System Analysis, which leverages the open source projects RACE (Runtime for Airspace Concept Evaluation) and TraceContract. RACE is a platform for instantiating and running highly concurrent and distributed systems and enables connectivity to SWIM and scalability. TraceContract is a runtime verication tool that allows for checking traces against properties specified in a powerful DSL. We applied our approach to verify a SWIM service against several requirements.We found errors such as duplicate and out-of-order messages.
Microbial monitoring of spacecraft air is critical toward assessing the efficacy of microbial controls within the environmental control and life support systems to protect both the crew and the vehicle environment. Additionally, understanding of the atmospheric microbial profiles will be essential toward Mars-forward planetary protection planning. Currently, onboard the International Space Station (ISS), the air is monitored on a quarterly basis using an impaction air sampler. With this method, bacterial and fungal cells and spores are pulled onto plates containing growth medium. Following five days of ambient incubation onboard the ISS, the crew compares the growth to density charts and provides the approximations to the ground. Upon return of the culture plates to the Johnson Space Center’s Microbiology Laboratory, the isolates present are identified for crew health risk assessments. As NASA moves beyond the low-Earth orbit of ISS, sample return will be impractical. As such, a near real-time monitoring capability for the assessment of the spacecraft atmosphere is necessary. Significant strides have been made in recent years to utilize a molecular-based method for microbial profiling of ISS surfaces. The developed method is not dependent on microbial culture, thus removing the associated risk to the crew from high microbial levels, the bias toward detecting only the culturable organisms, and eliminates the need for sample return. The work described here details the evaluation of three different air sampling platforms whose product is amenable to downstream molecular processing and nanopore sequencing. The three samplers were compared in terms of mass and power requirements, ease-of -use, and the resulting data. For the two highest ranking samplers, a basic concept of operations was developed to transfer the sample into the already established preparation and sequencing process. Using these concepts of operations, an in-depth comparison of the molecular data generated was compared to the historical culture-based method. Data from both methods detailed similar microbial profiles, while the molecular method detailed microbial identifications that could not be identified through the culture-based method. The developed method will enable the generation of near real-time microbial profiles of the spacecraft atmosphere.
Microbial monitoring of spacecraft air is critical toward assessing the efficacy of microbial controls within the environmental control and life support systems to protect the crew and vehicle environment. Currently, onboard the International Space Station (ISS), the air is monitored every quarter using an impaction air sampler. With this method, microbial cells and spores are pulled onto plates containing a growth medium. Following onboard incubation, the crew reports approximate microbial levels to the ground, but sample return is required for identification. Upon return of the plates, the isolates present are identified for crew health risk assessments. As NASA moves beyond low-Earth orbit, sample return will be impractical, and a near real-time monitoring capability is essential. Significant strides have been made in recent years to utilize a molecular-based method for microbial profiling of ISS surfaces. The developed method is independent of microbial culture, thus removing the bias toward detecting only culturable organisms, eliminating the need for sample return, and reducing the risk to crew health from exposure to high microbial levels. The work described here details the evaluation of three different air sampling platforms whose product is amenable to downstream molecular processing. The three samplers were compared in terms of mass and power requirements, ease of use, and the resulting data. For the two highest-ranking samplers, a basic concept of operations was developed to transfer the sample into the already established preparation and sequencing process. Using these concepts of operations, an in-depth comparison of the molecular data generated was compared to the historical culture-based method. Data from both methods detailed similar microbial profiles, while the molecular method detailed microbial identifications that were lacking from the culture data. The developed method will enable the generation of near real-time microbial profiles of the spacecraft atmosphere.
Connected and automated vehicles (CAVs) are increasingly being discussed as the basis for shared mobility and on-demand services to replace privately owned vehicles. The rapid growth of Transportation Networking Companies (TNCs) and their increasing investment in automated vehicle (AV) technologies attests to this. Combining the concepts of TNCs, with AVs and on-demand transit services, the term 'automated mobility district' (AMD) describes a district-scale implementation of CAV technology to realize the full benefits of a shared, fully automated vehicle service within a confined region. This research effort provides a modeling architecture for AMDs along with a preliminary analysis to quantify the mobility and energy benefits of such districts. A customized open-source microscopic mobility simulation toolkit built on the Simulation of Urban Mobility (SUMO) platform is implemented for AMD performance evaluation. Experimental scenarios are tested with different combinations of operational variables to provide insights on energy and mobility gains that can be realized in AMDs.
Connected and automated vehicles (CAVs) are increasingly being discussed as the basis for shared mobility and on-demand services to replace privately owned vehicles. The rapid growth of transportation networking companies (TNCs) and their increasing investment in automated vehicle (AV) technologies attests to this. Combining the concepts of TNCs, with AV and on-demand transit services, the term “automated mobility district” (AMD) describes a district-scale implementation of CAV technology to realize the full benefits of a shared, fully automated vehicle service within a confined region. This research effort provides a modeling architecture for AMDs along with a preliminary analysis to quantify the mobility and energy benefits of such districts. A customized open-source microscopic mobility simulation toolkit built on the simulation of urban mobility (SUMO) platform is implemented for AMD performance evaluation. Experimental scenarios are tested with different combinations of operational variables to provide insights on energy and mobility gains that can be realized in AMDs.
As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.
As space missions continue to become more ambitious, complex, and distant to Earth, the need for advanced on-board intelligent decision making to guide everything from mission operations to fault detection and recovery has become a major front of space research. While the prevalence of research on such Artificial Intelligence / Machine Learning (AI/ML) modules has exploded, the capacity to experimentally validate such modules in space in a rapid and inexpensive format has not. To this end, the Nano Orbital Workshop (NOW) group at NASA Ames Research Center has been at the forefront of performing initial flight evaluation tests of ‘commercially’ available AI/ML computational platforms via the TechEdSat (TES-n) flight series as part of what is programmatically referred to as the BRAINSTACK. BRAINSTACK will provide an orbital AI/ML evaluation laboratory where computational experiments are pre-loaded into memory prior to launch, and then executed as desired during the mission, with results reported back and program tweaks or new data sets uploaded as needed. Processors selected as part of the BRAINSTACK are of ideal size, packaging, and power consumption for easy integration into a cube satellite structure. These experiments have included the evaluation of small, high-performance GPUs and more recently, neuromorphic processors in LEO operations. Neuromorphic processors are of particular interest due to their superior computational power efficiency over GPUs. The first TES-n flight test of an Intel first-generation Loihi neuromorphic processor launched on January 13, 2022 and continues to operate in orbit despite almost no space environment modifications. The Intel Loihi Gen-1 is characterized by a 14nm 128-core Spiking Neural Network (SNN) able to support on-chip training. This experiment utilized a Loihi packaged in the ‘Kapoho Bay’ USB module, providing a relatively straight-forward interface to the bus avionics system. The Kapoho Bay was in turn managed by a host Intel Pentium single-board computer to handle scheduling of the AI/ML application payloads, and communications with the satellite vehicle manager. The recently released Intel Loihi Gen-2, able to support integer-valued spike payloads and produced using 7nm process, will form part of the basis of the evolving BRAINSTACK in the upcoming three TES-n/NOW flights. Additionally, it is planned to measure the radiation environment these processors experience to understand any degradation or computational artifacts caused by long term space radiation exposure on these novel architectures. This evolving flexible and collaborative environment involving various research teams across NASA and other organizations is intended to be a convenient orbital test platform from which many anticipated future space AI/ML applications may be initially tested.
The U.S. Department of Energy’s Office of Nuclear Energy Advanced Materials and Manufacturing Technologies (AMMT) program is pursuing qualification of laser powder bed fusion (LPBF) components for nuclear applications. A major focus of this effort is the use of in situ process monitoring and machine learning–based tools to establish real-time quality assurance. The primary objective of this report is to identify and evaluate the most relevant in situ sensor systems for LPBF, and to document the deployment of these systems across platforms critical to the AMMT program. This work demonstrates how in situ monitoring can detect process anomalies, track geometry-dependent flaws, and identify limiting combinations of processing parameters—particularly those related to energy density and complex geometries (e.g., overhanging structures). To support this goal, a diverse suite of sensor modalities was evaluated across LPBF platforms, including visible and near-infrared (NIR) imaging, fringe projection profilometry, long-wavelength infrared (LWIR) thermography, and high-speed photodiode/pyrometry systems. These sensor streams were integrated with Peregrine, a machine-agnostic software platform that, among other capabilities, can generate real-time process anomaly classification. This report documents sensor deployments on multiple AMMT flagship platforms, including the Concept Laser M2 and Renishaw AM400/AM250 systems. Calibration builds with complex, flaw-prone geometries such as unsupported overhangs, stepped features, and thin walls, were used to evaluate how well Peregrine and its associated sensors could detect process anomalies and other instabilities under varied energy densities. It will be shown how Peregrine reliably identifies common process anomalies such as recoater streaking, superelevation, etc., and can be used in post-build analysis for anomaly spatial distributions throughout the build height to better understand the impact of geometry and processing parameter choice on the build. This work demonstrates measurable progress toward the vision that components can be born-qualified by establishing a real-time monitoring framework, identifying limiting process conditions, and laying the foundation for sensor fusion–enabled prediction pipelines that are scalable across platforms and applicable to nuclear-relevant components.
NASA Langley proposed the Aerial Regional-scale Environmental Survey (ARES) of Mars science mission in response to the NASA Office of Space Science 2002 Mars Scout Opportunity. The science-driven mission proposal began with trade studies and determined that a rocket powered aircraft was the best suited platform to complete the ARES science objectives. A high fidelity six degree of freedom flight simulation was required to provide credible evidence that the aircraft design fulfilled mission objectives and to support the aircraft design process by providing performance evaluations. The aircraft was initially modeled using the aero, propulsion, and flight control system components of other aircraft models. As the proposed aircraft design evolved, the borrowed components were replaced with new models. This allowed performance evaluations to be performed as the design was maturing. Basic autopilot features were also developed for the ARES aircraft model. Altitude hold and track hold modes allowed different mission scenarios to be evaluated for both science merit and aircraft performance. Platform stability and data rate requirements were identified for each of the instruments and the aircraft performance was evaluated against those requirements. The results of the simulation evaluations indicate that the ARES design and mission profiles are sound and meet the science objectives.
The supporting research and technology, and space demonstrations required to support the 1990s operational geostationary platforms are identified. Also the requirements on and interfaces with the Space Transportation System hardware elements supporting the geostationary platform program, including the shuttle, orbital transfer vehicles, teleoperator, etc., are investigated to provide integrated support requirements. Finally, a preliminary evaluation of the practicability and capabilities of an experimental platform from the standpoint of technology, schedule, and cost is given.
The Energy Exascale Earth System Model (E3SM) Project is an ongoing, state-of-the-science Earth system modeling, simulation, and prediction project that targets efficient utilization of U.S. Department of Energy’s (DOE) supercomputers to meet the science needs of the nation and the mission needs of DOE. This work focuses on our early evaluation of the A64FX architecture on Fugaku supercomputer using E3SM benchmarks. We will present results that track hardware trends, facilitate architecture comparison and the specific impact on our workload using an atmospheric model benchmark. We have two variants of the code written in Fortran and C++/Kokkos respectively which were used to collect data on a variety of CPU and GPU platforms. Furthermore, we have conducted a comparative evaluation of the compilers on the A64FX architecture and found GNU to be the best performer for our workload. Our experience so far indicates that Fugaku/A64FX shows promising energy efficiency (performance/Watt) with further performance gains possible through architecture-aware optimization efforts.
Deep-water offshore sites are an untapped opportunity to bring large-scale offshore wind energy to coastal population centers. The primary challenge has been the projected high costs for floating offshore wind systems. This work presents a comprehensive investigation of a new opportunity for deep-water offshore wind using large-scale vertical axis wind turbines. Owing to inherent features of this technology, there is a potential transformational opportunity to address the major cost drivers for floating wind using vertical axis wind turbines. The focus of this report is to evaluate the technical potential for this new technology. The approach to evaluating this potential was to perform system design studies focused on improving the understanding of technical performance parameters while looking for cost reduction opportunities. VAWT design codes were developed in order to perform these design studies. To gain a better understanding of the design space for floating VAWT systems, a comprehensive design study of multiple rotor configuration options was carried out. Floating platforms and moorings were then sized and evaluated for each of the candidate rotor configurations. Preliminary LCOE estimates and LCOE ranges were produced based on the design study results for each of the major turbine and system components. The major outcomes of this study are a comprehensive technology assessment of VAWT performance and preliminary LCOE estimates that demonstrate that floating VAWTs may have favorable performance and costs in comparison to conventional HAWTs in the deep-water offshore environment where floating systems are required, indicating that this new technology warrants further study.
The author has identified the following significant results. Evaluation of the probe performances during the initial phase indicates that the dissolved oxygen sensor available as part of the package is not sufficiently reliable for long term operation. The turbidity probe requires frequent visits to the site to maintain it in proper operating condition. The cost of these visits would have to be weighed against the information obtained. The conductivity/salinity, temperature, pH, and depth indicators have worked extremely well over the course of the study. Monthly cleanings would maintain all these probes in top operating condition. Currently the accuracy of each measurement returned via satellite is being compared to the accuracy of the probe reading and water samples analyzed in the laboratory.