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Active Laser Ranging Along with Lasercom: Field Emulation
In summary, this work has: (1) Demonstrated the real-time active laser ranging using a method applicable to interplanetary distances (2) Sub-millimeter ranging accuracy has been achieved with the systems built from off-the-shelf commercial components, demonstrating the robustness of the scheme (3) The experimental results indicate that active laser ranging can be implemented for interplanetary distances to meet the goal of 1mm ranging accuracy, including the effects of the Earth's atmosphere (4) Paves the way for advances in the study of fundamental physics and solar system dynamics.
Towards Validation of an Adaptive Flight Control Simulation Using Statistical Emulation
Traditional validation of flight control systems is based primarily upon empirical testing. Empirical testing is sufficient for simple systems in which a.) the behavior is approximately linear and b.) humans are in-the-loop and responsible for off-nominal flight regimes. A different possible concept of operation is to use adaptive flight control systems with online learning neural networks (OLNNs) in combination with a human pilot for off-nominal flight behavior (such as when a plane has been damaged). Validating these systems is difficult because the controller is changing during the flight in a nonlinear way, and because the pilot and the control system have the potential to co-adapt in adverse ways traditional empirical methods are unlikely to provide any guarantees in this case. Additionally, the time it takes to find unsafe regions within the flight envelope using empirical testing means that the time between adaptive controller design iterations is large. This paper describes a new concept for validating adaptive control systems using methods based on Bayesian statistics. This validation framework allows the analyst to build nonlinear models with modal behavior, and to have an uncertainty estimate for the difference between the behaviors of the model and system under test.
Time-Filtered Navier-Stokes Approach and Emulation of Turbulence-Chemistry Interaction
This paper describes the time-filtered Navier-Stokes approach capable of capturing unsteady flow structures important for turbulent mixing and an accompanying subgrid model directly accounting for the major processes in turbulence-chemistry interaction. They have been applied to the computation of two-phase turbulent combustion occurring in a single-element lean-direct-injection combustor. Some of the preliminary results from this computational effort are presented in this paper.
Emulating an Optical Planetary Access Link with an Aircraft
Video imagery was streamed from the ground to an aircraft using a free-space laser communication link. The link operated at 270 Mb/s over slant ranges of 5-9 km in day and night time background conditions. The experiment was designed to demonstrate autonomous link acquisition and served as a first proof-of-concept for a planetary access link between a surface asset and an orbiter at Mars. System parameters monitored during the link demonstration including acquisition and tracking and communication performance are discussed.
A Crop Yield Change Emulator for Use in GCAM and Similar Models: Persephone v1.0
Future changes in Earth system state will impact agricultural yields and, through these changed yields, can have profound impacts on the global economy. Global gridded crop models estimate the influence of these Earth system changes on future crop yields but are often too computationally intensive to dynamically couple into global multisector economic models, such as the Global Change Assessment Model (GCAM) and other similar-in-scale models. Yet, generalizing a faster site-specific crop model’s results to be used globally will introduce inaccuracies, and the question of which model to use is unclear given the wide variation in yield response across crop models. To examine the feedback loop among socioeconomics, Earth system changes, and crop yield changes, rapidly generated yield responses with some quantification of crop response uncertainty are desirable. The Persephone v1.0 response functions presented in this work are based on the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Climate-Crop Modeling Project (C3MP) sensitivity test data set and are focused on providing GCAM and similar models with a tractable number of rapid to evaluate dynamic yield response functions corresponding to a range of the yield response sensitivities seen in the C3MP data set. With the Persephone response functions, a new variety of agricultural impact experiments will be open to GCAM and other economic models: for example, examining the economic impacts of a multi-year drought in a key agricultural region and how economic changes in response to the drought can, in turn, impact the drought.
Embedded passives emulator FY2003 interim report
The National Aeronautics and Space Administration Electronic Parts and Packaging (NEPP) Program has been evaluating state-of-the-art Embedded Passive Technology for the printed circuit board (PCB) industry for the past several years and has conducted its own testing on embedded passive coupons (resistors and capacitors). This document is a progress report of the work performed through fiscal year 2008 by NASA and the Navy to convert an existing PWB (printed wiring board) design to a design that incorporates embedded passive components. The work is being performed through a memorandum of understanding (MOU) between the NEPP Program (NASA) and the Naval Surface Warfare Center (NSWC) Crane Emerging Critical Interconnect Technology (ECIT) Program. NSWC Crane’s ECIT Program has funding to convert two PCB designs from the military and aerospace industry to a PCB design with embedded passives. ECIT will provide a design team that will take a well characterized design and convert it to an embedded design. They will also provide electrical modeling and layout expertise as well as build the PWB in their facility in Indiana. NEPP, through the Jet Propulsion Laboratory (JPL), will assemble any passives deemed not suitable for embedding and the active components and electrically test the new design to the existing (non-embedded) design
Chapter 4: Packings, simulation, and big data--artificial intelligence emulation of soft matter
At the suggestion of NASA’s Physical Science Research Program in the Space Life and Physical Science Research and Application Division, Paul Chaikin, Noel Clark, and Sidney Nagel organized a focus session and workshop for the 2020 American Physical Society (APS) March meeting under the auspices of the Division of Soft Matter. Three overarching themes emerged from the workshop and are presented with additional details: • Machines made out of machines • Scalable self-sustaining ecosystems • Active materials and metamaterials This report lays out only some of the potential directions for soft matter dynamics over the next two decades. It also lays out the role that gravity plays in the organization of the basic building blocks of matter. Not only will research on soft matter have tremendous application towards understanding its behavior in our terrestrial environment, but also potentially in other NASA programs such as planetary science, exploration, robotics, etc. Attached is a White Paper for the Decadal Survey that consists of an extended Title along with the previous Introduction and Chapter 2.4 from NASA/CP-20205010493.
Emulating the Chemistry Within A Chemical Transport Model Using A Machine Learning Surrogate Ensamble
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Pushing the Limits of Aquatic Remote Sensing: Synthetic Data and Deep Learning for Fast Inverse Emulation of A Coupled Ocean-Atmosphere Radiative Transfer Model
The inversion of electromagnetic information to physical and biological properties of the water column is a notoriously difficult problem, yet fundamental to our ability of understanding aquatic processes on large time and space scales. There is now a growing necessity to develop pragmatic approaches that allow timely and effective extrapolation of local processes, to spatially resolved global products, and to promote operational and sustainable resource policy management. This presentation will discuss research integrating advanced biological and radiative modeling, high-end computation, and machine learning to develop a portable global processor for simultaneous retrieval of atmosphere and water optics for diverse aquatic systems from the open and coastal ocean to optically extreme inland waters and harmful algal blooms. We will discuss some of the basic concepts behind the forward modeling approach including DEAP, the novel Distributed Equivalent Algal Populations model, for developing large spectral libraries of aquatic particle optics to aid in our ability to distinguish phytoplankton functional types (PFTs) and inorganic material, as well as other factors which enable comprehensive modeling from the benthos to top-of-atmosphere (TOA). This information is being used to understand how we can leverage next-generation deep learning methods for maximum information retrieval and rapid image processing, while also providing capabilities to identify minimum sensor spectral requirements necessary for certain aquatic applications. Further, I will touch on how we envision this research to enable the aquatic community for science discovery and how we are moving closer towards the capability for high-fidelity global analysis of aquatic ecosystems.
Kernel Flows-based emulation of SBG radiative transfer and other applications
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Simulation, Emulation, Navigation, Sensing, and STAR (SENSS) Laboratory: Precision Landing Research & Development
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NASA LVIS Facility: Airborne Waveform Lidar Measurements of Surface Topography, Height and 3D Structure with Multi-sensor Emulation Capability
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A 1D CNN-Based Emulator of CMAQ: Predicting NO2 Concentration over the Most Populated Urban Regions in Texas
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Fast and Accurate Emulation of the SDO/HMI Stokes Inversion with Uncertainty Quantification
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Antarctic-wide ice-shelf firn emulation reveals robust future firn air depletion signal for the Antarctic Peninsula
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