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DOE OSTI2022

ResOpsUS, a dataset of historical reservoir operations in the contiguous United States

Abstract There are over 52,000 dams in the contiguous US ranging from 0.5 to 243 meters high that collectively hold 600,000 million cubic meters of water. These structures have dramatically affected the river dynamics of every major watershed in the country. While there are national datasets that document dam attributes, there is no national dataset of reservoir operations. Here we present a dataset of historical reservoir inflows, outflows and changes in storage for 679 major reservoirs across the US, called ResOpsUS. All of the data are provided at a daily temporal resolution. Temporal coverage varies by reservoir depending on construction date and digital data availability. Overall, the data spans from 1930 to 2020, although the best coverage is for the most recent years, particularly 1980 to 2020. The reservoirs included in our dataset cover more than half of the total storage of large reservoirs in the US (defined as reservoirs with storage greater 0.1 km 3 ). We document the assembly process of this dataset as well as its contents. Historical operations are also compared to static reservoir attribute datasets for validation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Development of a Novel Electrical Characterization Technique for Measuring Hidden Joint Contacts in Weapons Cavities (LDRD Final Report 218470)

This report summarizes research performed in the context of a REHEDS LDRD project that explores methods for measuring electrical properties of vessel joints. These properties, which include contact points and associated contact resistance, are “hidden” in the sense that they are not apparent from a computer-assisted design (CAD) description or visual inspection. As is demonstrated herein, the impact of this project is the development of electromagnetic near-field scanning capabilities that allow weapon cavity joints to be characterized with high spatial and/or temporal resolution. Such scans provide insight on the hidden electrical properties of the joint, allowing more detailed and accurate models of joints to be developed, and ultimately providing higher fidelity shielding effectiveness (SE) predictions. The capability to perform high-resolution temporal scanning of joints under vibration is also explored, using a multitone probing concept, allowing time-varying properties of joints to be characterized and the associated modulation to SE to be quantified.

42 ENGINEERING↗

NASA NTRS2010

A Two-Axis Direct Fluid Shear Stress Sensor

This innovation is a miniature or micro sized semiconductor sensor design that provides two axis direct non-intrusive measurement of skin friction or wall shear stress in fluid flow. The sensor is fabricated by micro-electro-mechanical system (MEMS) technology, enabling small size and low cost reproductions. The sensors have been fabricated by utilizing MEMS fabrication processes to bond a sensing element wafer to a fluid coupling wafer. This layering technique provides for an out of plane dimension that is on the same order of length as the inplane dimensions. The sensor design has the following characteristics: a shear force collecting plate with dimensions that can be tailored to various application specific requirements such as spatial resolution, temporal resolution and shear force range and resolution. This plate is located coplanar to both the sensor body and flow boundary, and is connected to a dual axis gimbal structure by a connecting column or lever arm. The dual axis gimbal structure has torsional hinges with embedded piezoresistive torsional strain gauges which provide a voltage output that is correlated to the applied shear stress (and excitation current) on force collection plate that is located on the flow boundary surface (hence the transduction method). This combination of design elements create a force concentration and resolution structure that enables the generation of a large stress on the strain gauge from the small shear stress on the flow boundary wall. This design as well as the use of back side electrical contacts establishes a non-intrusive method to quantitatively measure the shear force vector on aerodynamic bodies.

Adcock, Edward E.↗

NASA NTRS2011

Computation of UH-60A Airloads Using CFD/CSD Coupling on Unstructured Meshes

An unsteady Reynolds-averaged Navier-Stokes solver for unstructured grids is used to compute the rotor airloads on the UH-60A helicopter at high-speed and high thrust conditions. The flow solver is coupled to a rotorcraft comprehensive code in order to account for trim and aeroelastic deflections. Simulations are performed both with and without the fuselage, and the effects of grid resolution, temporal resolution and turbulence model are examined. Computed airloads are compared to flight data.

Biedron, Robert T.↗

NASA NTRS2022

Intrinsic Dimensionality as a Metric for the Impact of Mission Design Parameters

High-resolution space-based spectral imaging of the Earth's surface delivers critical information for monitoring changes in the Earth system as well as resource management and utilization. Orbiting spectrometers are built according to multiple design parameters, including ground sampling distance (GSD), spectral resolution, temporal resolution, and signal-to-noise ratio. Different applications drive divergent instrument designs, so optimization for wide-reaching missions is complex. The Surface Biology and Geology component of NASA's Earth System Observatory addresses science questions and meets applications needs across diverse fields, including terrestrial and aquatic ecosystems, natural disasters, and the cryosphere. The algorithms required to generate the geophysical variables from the observed spectral imagery each have their own inherent dependencies and sensitivities, and weighting these objectively is challenging. Here, we introduce intrinsic dimensionality (ID), a measure of information content, as an applications-agnostic, data-driven metric to quantify performance sensitivity to various design parameters. ID is computed through the analysis of the eigenvalues of the image covariance matrix, and can be thought of as the number of significant principal components. This metric is extremely powerful for quantifying the information content in high-dimensional data, such as spectrally resolved radiances and their changes over space and time. We find that the ID decreases for coarser GSD, decreased spectral resolution and range, less frequent acquisitions, and lower signal-to-noise levels. This decrease in information content has implications for all derived products. ID is simple to compute, providing a single quantitative standard to evaluate combinations of design parameters, irrespective of higher-level algorithms, products, applications, or disciplines.

Intrinsic dimensionality↗

NASA NTRS1987

An evaluation of observations from satellites for the study and prediction of mesoscale events and cyclone events

Quantitative observational guidelines have been developed for the study and forecasting of mesoscale events and cyclone events; many of these guidelines have resulted from major meteorological field programs. Increasingly sophisticated satellite-borne instruments in low and geosynchronous orbits have provided valuable measurements of these events. The major deficiencies in the measurements taken from geosynchronous orbit today, relative to guidelines, are (1) the lack of temperature profiles and moisture profiles below clouds, and the poor vertical resolution of these profiles; (2) the insufficient combination of spatial resolution and temporal resolution and spectral intervals available in generating images (imaging); and (3) the lack of accurate precipitation mapping. Considerably more-powerful instrumentation is possible on geosynchronous satellites that can substantially reduce these deficiencies. The capability of advanced geosynchronous observations and those expected with future instrumentation in low-orbit are evaluated with respect to tropical cyclone and severe local-storm observational guidelines. A high percentage of the guidelines are expected to be fulfilled with geosynchronous measurements: (1) using microwave instruments for imaging and for obtaining temperature profiles and moisture profiles, (2) very high spectral-resolution infrared profiling, (3) very high spatial-resolution and very high temporal-resolution imaging, and (4) ozone mapping.

Shenk, William E.↗

NASA NTRSDate not supplied

ILEOS: A Novel Intelligent Observing System Enabled by High Altitude Long Endurance Uncrewed Aerial Systems

Most major global satellite surveyors of climate-relevant trace gases have relatively coarse spatial resolution or temporal sampling. While these data can be supplemented by fine-pointing satellites and aircraft, the spatial and temporal resolutions available from crewed aircraft is not sufficient to observe stochastic, ephemeral events that take place between observations. Emerging High Altitude Long Endurance (HALE) Uncrewed Aerial Systems (UAS) can operate for months at a time and loiter over targets to provide continuous daylight geostationary-like observations, allowing these new platforms to be integrated with existing satellites as part of a New Observing Strategy (NOS).To aid in the planning of future NOS missions, NASA is developing the Intelligent Long Endurance Observing System (ILEOS), a science activity planning system. ILEOS will help scientists build plans to improve spatio-temporal resolution of climate-relevant gases by fusing coarse-grained sensor data from satellites and other sources(e.g., terrain, forecasts), and plan HALE UAS flights to obtain finer-grain (high spatio-temporal) data. ILEOS will also enable observations for longer periods and of environments not accessible through in-situ observations and crewed aircraft field campaigns.

science planning pipeline↗

NASA NTRS1996

Multi-Dimensional Measurements of Combustion Species in Flame Tube and Sector Gas Turbine Combustors

The higher temperature and pressure cycles of future aviation gas turbine combustors challenge designers to produce combustors that minimize their environmental impact while maintaining high operation efficiency. The development of low emissions combustors includes the reduction of unburned hydrocarbons, smoke, and particulates, as well as the reduction of oxides of nitrogen (NO(x)). In order to better understand and control the mechanisms that produce emissions, tools are needed to aid the development of combustor hardware. Current methods of measuring species within gas turbine combustors use extractive sampling of combustion gases to determine major species concentrations and to infer the bulk flame temperature. These methods cannot be used to measure unstable combustion products and have poor spatial and temporal resolution. The intrusive nature of gas sampling may also disturb the flow structure within a combustor. Planar laser-induced fluorescence (PLIF) is an optical technique for the measurement of combustion species. In addition to its non-intrusive nature, PLIF offers these advantages over gas sampling: high spatial resolution, high temporal resolution, the ability to measure unstable species, and the potential to measure combustion temperature. This thesis considers PLIF for in-situ visualization of combustion species as a tool for the design and evaluation of gas turbine combustor subcomponents. This work constitutes the first application of PLIF to the severe environment found in liquid-fueled, aviation gas turbine combustors. Technical and applied challenges are discussed. PLIF of OH was used to observe the flame structure within the post flame zone of a flame tube combustor, and within the flame zone of a sector combustor, for a variety of fuel injector configurations. OH was selected for measurement because it is a major combustion intermediate, playing a key role in the chemistry of combustion, and because its presence within the flame zone can serve as a qualitative marker of flame temperature. All images were taken in the environment of actual engines during flight, using actual jet fuel. The results of the PLIF study led directly to the modification of a fuel injector.

Hicks, Yolanda Royce↗

DOE OSTI2020

Quantifying Solar PV Variability at Multiple Timescales for Power Systems Studies: Preprint

Increasing penetration of solar photovoltaics (PV) has concerned power system operators about their ability to balance load and generation over multiple timescales and maintain acceptable frequency profile because of the variability and uncertainty associated with solar PV. This paper focuses on developing metrics to quantify solar PV variability at multiple temporal scales ranging from seconds to an hour to help power system operators and planners better understand and account for solar PV variability under high solar PV penetration. Fourier coefficients of solar irradiation spectrum and average size of solar irradiation ramps over a day are the two metrics that are used to quantity the variability. It is shown that by using the two metrics the days with highest and lowest solar irradiation variability can be identified, which is useful information for operations planning or long-term power system planning studies. The key findings of the paper are (i) single sensor-based variability quantification can significantly exaggerate the variability of a solar PV plant, particularly at seconds to 1-min temporal resolution, (ii) at 1-minute or lower temporal resolutions, single sensor-based variability quantification of an entire plant can be fairly accurate, with the accuracy increasing as the temporal resolution reduces from 1-minute to 1-hour, (iii) at each 1-minute and lower temporal resolutions, maximum solar irradiation ramps appear to be independent of the geographical location of the sensor, and (iv) significant reduction in solar PV plant variability over a region with multiple plants is possible at all temporal scales, but more high quality, high temporal resolution data is needed to quantify the reduction with high confidence.

photovoltaics↗

DOE OSTI2024

Super Resolving Unrolled Neural Networks for Remote Sensing

In remote sensing systems, the capabilities of the system are constrained by the complex interactions between size, weight, and power (SWAP) of potential designs. In electro-optical (EO) systems, examples of these critical parameters include the system’s sensitivity and resolution. Those parameters can be increased by ever larger optical apertures and focal planes but at the cost of more SWAP. Multi-image super resolution (MISR) techniques allow resolution to be enhanced via computation rather than more sophisticated optical hardware. These algorithms combine multiple images together into a single, higher resolution image, trading temporal resolution and computation for spatial resolution. Fielded MISR techniques, such as Drizzle, can require several hundred images to create a single super resolved image, implying reduced temporal resolution, increased data acquisition load, and limiting mission applications. Iterative techniques, such as model-based image reconstruction and compressive sensing, have been shown to create super resolved images using fewer images than Drizzle. They do this by posing an optimization problem that balances accuracy between a highly accurate physical model and an image model. In the case of super resolution, the physical model is defined by the relation between low resolution input images and the desired high resolution output image. The image model encodes some assumptions about the super resolved image. These assumptions are meant to suppress reconstruction artifacts that arise due to deterministic physical model error, stochastic measurement noise, and potential undersampling. In practice, the performance of iterative methods are limited by imaging models compatible with optimization. Deep learning-based methods can effectively learn image models of arbitrary complexity, but lack the theoretical explainability and robustness of iterative techniques. Consensus equilibrium (CE) generalizes the iterative techniques beyond optimization, enabling blackbox algorithms such as traditional and neural image denoisers to be used as the image model. CE-based approaches retain much of the explainability and robustness of iterative techniques while allowing the expressiveness of machine learning image models to be used. Additionally, by unrolling iterations of CE with an embedded image denoiser, the image denoiser can be further trained and specialized to the specific application with potentially higher quality reconstructions. Under this project, we demonstrated the feasibility of training an unrolled neural network based upon CE. While we didn’t train one, we showed that the CE process is differentiable and its gradient can be tractably computed. We also explored the usage of a variants of CE akin to generative neural works. Most importantly, we applied the CE framework to a number of problems including non-blind deconvolution, upsampling, single-image super resolution, MISR, event-based sensing, and saturated deconvolution. Our MISR prototype creates high quality reconstructions with an order of magnitude fewer images than previous approaches and, critically, produces these reconstructions fast enough for practical usage.

47 OTHER INSTRUMENTATION↗

DOE OSTI2021

Effect of Auger recombination on transient optical properties in XUV and soft X-ray irradiated silicon nitride

Spatially encoded measurements of transient optical transmissivity became a standard tool for temporal diagnostics of free-electron-laser (FEL) pulses, as well as for the arrival time measurements in X-ray pump and optical probe experiments. The modern experimental techniques can measure changes in optical coefficients with a temporal resolution better than 10 fs. This, in an ideal case, would imply a similar resolution for the temporal pulse properties and the arrival time jitter between the FEL and optical laser pulses. However, carrier transport within the material and out of its surface, as well as carrier recombination may, in addition, significantly decrease the number of carriers. This would strongly affect the transient optical properties, making the diagnostic measurement inaccurate. Below we analyze in detail the effects of those processes on the optical properties of XUV and soft X-ray irradiated Si 3 N 4 , on sub-picosecond timescales. Si 3 N 4 is a wide-gap insulating material widely used for FEL pulse diagnostics. Theoretical predictions are compared with the published results of two experiments at FERMI and LCLS facilities, and with our own recent measurement. The comparison indicates that three body Auger recombination strongly affects the optical response of Si 3 N 4 after its collisional ionization stops. By deconvolving the contribution of Auger recombination, in future applications one could regain a high temporal resolution for the reconstruction of the FEL pulse properties measured with a Si 3 N 4 -based diagnostics tool.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

NASA NTRS1991

Geostationary orbit Earth science platform concepts for global change monitoring

Functionality of a geostationary spacecraft to support Earth science regional process research is identified. Most regional process studies require high spatial and temporal resolution. These high temporal resolutions are on the order of 30 minutes and may be achievable with instruments positioned in a geostationary orbit. A complement of typical existing or near term instruments are identified to take advantage of this altitude. This set of instruments is listed, and the requirements these instruments impose on a spacecraft are discussed. A brief description of the geostationary spacecraft concepts which support these instruments is presented.

Farmer, Jeffery T.↗

DOE OSTI2020

Exploring the Use of DSCOVR/EPIC Satellite Observations to Monitor Vegetation Phenology

Vegetation phenology plays a pivotal role in regulating several ecological processes and has profound impacts on global carbon exchange. Large-scale vegetation phenology monitoring mostly relies on Low-Earth-Orbit satellite observations with low temporal resolutions, leaving gaps in data that are important for monitoring seasonal vegetation phenology. High temporal resolution satellite observations have the potential to fill this gap by frequently collecting observations on a global scale, making it easier to study change over time. This study explored the potential of using the Earth Polychromatic Imaging Camera (EPIC) onboard the Deep Space Climate Observatory (DSCOVR) satellite, which captures images of the entire sunlit face of the Earth at a temporal resolution of once every 1–2 h, to observe vegetation phenology cycles in North America. We assessed the strengths and shortcomings of EPIC-based phenology information in comparison with the Moderate-resolution Imaging Spectroradiometer (MODIS), Enhanced Thematic Mapper (ETM+) onboard Landsat 7, and PhenoCam ground-based observations across six different plant functional types. Our results indicated that EPIC could capture and characterize seasonal changes of vegetation across different plant functional types and is particularly consistent in the estimated growing season length. Our results also provided new insights into the complementary features and benefits of the four datasets, which is valuable for improving our understanding of the complex response of vegetation to global climate variability and other disturbances and the impact of phenology changes on ecosystem productivity and global carbon exchange.

Weber, Maridee A.↗

DOE OSTI2023

Exploring Mission Design for Imaging Spectroscopy Retrievals for Land and Aquatic Ecosystems

The retrieval algorithms used for optical remote sensing satellite data to estimate Earth's geophysical properties have specific requirements for spatial resolution, temporal revisit, spectral range and resolution, and instrument signal-to-noise ratio (SNR) performance to meet biogeoscience objectives. Studies to estimate surface properties from hyperspectral data use a range of algorithms sensitive to various sources of spectroscopic uncertainty, which are in turn influenced by mission architecture choices. Retrieval algorithms vary across scientific fields and may be more or less sensitive to mission architecture choices that affect spectral, spatial, or temporal resolutions and spectrometer SNR. We used representative remote sensing algorithms across terrestrial and aquatic study domains to inform aspects of mission design that are most important for impacting accuracy in each scientific area. We simulated the propagation of uncertainties in the retrieval process including the effects of different instrument configuration choices. We found that retrieval accuracy and information content degrade consistently at >10 nm spectral resolution, >30 m spatial resolution, and >8-day revisit. In these studies, the noise reduction associated with lower spatial resolution improved accuracy vis à vis high spatial resolution measurements. The interplay between spatial resolution, temporal revisit, and SNR can be quantitatively assessed for imaging spectroscopy missions and used to identify key components of algorithm performance and mission observing criteria.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2023

Exploring Mission Design for Imaging Spectroscopy Retrievals for Land and Aquatic Ecosystems

A. M. Raiho↗

DOE OSTI2022

Capturing the interactions between ice sheets, sea level and the solid Earth on a range of timescales: a new “time window” algorithm

Retreat and advance of ice sheets perturb the gravitational field, solid surface and rotation of the Earth, leading to spatially variable sea-level changes over a range of timescales $\textit{O}$ (10 0–6 years), which in turn feed back onto ice-sheet dynamics. Coupled ice-sheet–sea-level models have been developed to capture the interactive processes between ice sheets, sea level and the solid Earth, but it is computationally challenging to capture short-term interactions $\textit{O}$ (10 0–2 years) precisely within longer $\textit{O}$ (10 3–6 years) simulations. The standard forward sea-level modelling algorithm assigns a uniform temporal resolution in the sea-level model, causing a quadratic increase in total CPU time with the total number of input ice history steps, which increases with either the length or temporal resolution of the simulation. In this study, we introduce a new “time window” algorithm for 1D pseudo-spectral sea-level models based on the normal mode method that enables users to define the temporal resolution at which the ice loading history is captured during different time intervals before the current simulation time. Utilizing the time window, we assign a fine temporal resolution $\textit{O}$ (10 0–2 years) for the period of ongoing and recent history of surface ice and ocean loading changes and a coarser temporal resolution $\textit{O}$ (10 3–6 years) for earlier periods in the simulation. This reduces the total CPU time and memory required per model time step while maintaining the precision of the model results. We explore the sensitivity of sea-level model results to the model temporal resolution and show how this sensitivity feeds back onto ice-sheet dynamics in coupled modelling. We apply the new algorithm to simulate sea-level changes in response to global ice-sheet evolution over two glacial cycles and the rapid collapse of marine sectors of the West Antarctic Ice Sheet in the coming centuries and provide appropriate time window profiles for each application. The time window algorithm reduces the total CPU time by ~ 50 % in each of these examples and changes the trend of the total CPU time increase from quadratic to linear. This improvement would increase with longer simulations than those considered here. Our algorithm also allows for coupling time intervals of annual temporal scale for coupled ice-sheet–sea-level modelling of regions such as West Antarctica that are characterized by rapid solid Earth response to ice changes due to the thin lithosphere and low mantle viscosities.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Extend an innovative HPC-Compatible Multiple Temporal-spatial Resolution Concurrent Finite Element Modeling Approach to Guide Laser Powder Bed Fusion Additive

Laser power bed fusing (PBF) additive manufacturing is a key enabling technology to manufacture highly complex and integrated automotive structures. However, the geometric complexity of PBF-AM technique also leads to highly non-uniform heating and cooling rate in the manufactured part, which may cause flaw formation and produce excessive and nonuniform residual stresses, which increase quality uncertainties and manufacture issues, leading to increases in cost and energy consumption in the form of rejected parts. In this research project, we developed an innovative Multi-Spatial-Temporal-Resolution Finite Element (MUST-FE) method and completed the corresponding high performance computation (HPC) platform-based in-house code, which enables high accuracy prediction of temperature and residual stress fields for component-scale PBF-AM manufacture in efficient computation time. The MUST-FE model is calibrated and validated with a “2D pad” AlSi10Mg experiments by matching the melt pool shape and dimension, and with a “XY-cross” AlSi10Mg experiment by matching the thermal distortion and residual stress. The innovative multi-resolution and concurrent modeling approach adopted in this code ensures accuracy and computational efficiency, which will enable energy-efficient and high-yield, low-cost manufacturing of optimized, qualifiable automotive structures and contribute towards reaching technical targets outlined in AMO’s Program Plan to develop additive manufacturing systems that deliver consistently reliable parts with predictable properties.

36 MATERIALS SCIENCE↗

NASA NTRS1976

Real-time video compression algorithm for Hadamard transform processing

A real-time digital video processor using Hadamard transform techniques to reduce video bandwidth is described. The processor can be programmed with different parameters to investigate various algorithms for bandwidth compression. The processor is also adaptive in that it can select different parameter sets to tradeoff spatial resolution for temporal resolution in the regions of the picture that are moving. Algorithms used in programming the system are described along with results achieved at various levels of compression. The algorithms relate to spatial compression, temporal compression, and the adaptive selection of parameter sets.

Knauer, S. C.↗