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At least 1,675 records · Page 93

Synthetic-Aperture Coherent Imaging From A Circular Path

Imaging algorithms based on exact point-target responses. Developed for use in reconstructing image of target from data gathered by radar, sonar, or other transmitting/receiving coherent-signal sensory apparatus following circular observation path around target. Potential applications include: Wide-beam synthetic-aperture radar (SAR) from aboard spacecraft in circular orbit around target planet; SAR from aboard airplane flying circular course at constant elevation around central ground point, toward which spotlight radar beam pointed; Ultrasonic reflection tomography in medical setting, using one transducer moving in circle around patient or else multiple transducers at fixed positions on circle around patient; and Sonar imaging of sea floor to high resolution, without need for large sensory apparatus.

Jin, Michael Y.↗

Fisheries imaging radar surveillance test /FIRST/ - Bering Sea test

A joint NOAA, U.S. Coast Guard and NASA program is being conducted to determine if a synthetic aperture radar (SAR) system, such as planned for NASA's SEASAT, can be useful in monitoring fishing vessels within the newly established 200-mile fishing limit. As part of this program, data gathering field operations were conducted over concentrations of foreign fishing vessels in the Bering Sea off Alaska in April 1976. The Jet Propulsion Laboratory developed synthetic aperture L-band radar which was flown aboard the NASA Convair 990 aircraft, with a Coast Guard cutter and C-130 aircraft simultaneously gathering data to provide both radar imagery and sea truth information on the vessels being imaged. Results indicate that synthetic aperture radar systems have potential for all weather detection, enumeration and classification of fishing vessels.

Woods, E. G.↗

Biological Carbon Sequestration for Climate and Soil Health

The United States recently launched the Net Zero World Initiative on decarbonization. As temperatures and sea levels rise, strong action is needed to mitigate high atmospheric CO 2 levels. In response to this need, a joint workshop between the US Department of Energy’s Oak Ridge National Laboratory (ORNL) and Lawrence Berkeley National Laboratory (LBNL) was convened to assess the challenges and opportunities within biological carbon (C) capture. The virtual workshop on Biological Carbon Sequestration for Climate and Soil Health focused on three aspects of biological C capture research: natural systems, engineered systems, and modeling. For this workshop, the scope of natural systems included unmanaged (e.g., grasslands, wetlands, natural forests) and managed (e.g., agricultural lands, commercial forests, forest biofuels) ecosystems. The engineered systems group covered topics in genetically modified plants and microbes, synthetic microbiomes, and altered plant–microbe interactions for enhancing C capture, storage, and utilization. The modeling group focused on computational tools and data collection to predict and assess the effectiveness of new biocarbon sequestration advances. Participant expertise included plant and microbial systems biology, synthetic biology, soil biogeochemistry, and techno-economic analysis. Together, participants outlined key scientific advances in support of biological C capture and storage. Among the major findings of the meeting were the need to better measure C flux within natural, agricultural, and fabricated ecosystems for experimentation; better understand the role of soil composition, plant roots, and the rhizosphere (i.e., the soil surrounding the plant root) in the underground storage of organic C; and design plant–microbe systems for maximal C storage.

54 ENVIRONMENTAL SCIENCES↗

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Included is an example case study: Hurricane Dolly damaging a synthetic 2000 bus test system during its landing in Southern Texas. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems including emergency asset management. We perform statistical analysis of damages and quantify topological effects on example synthetic grid. Also, we investigate loss-of-load events during two-day economic dispatch experiment. Finally, we point out various shortcomings of our method and suggest how it can be improved.

data-driven forecasting↗

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources: Preprint

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Included is an example case study: Hurricane Dolly damaging a synthetic 2000 bus test system during its landing in Southern Texas. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems including emergency asset management. We perform statistical analysis of damages and quantify topological effects on example synthetic grid. Also, we investigate loss-of-load events during two-day economic dispatch experiment. Finally, we point out various shortcomings of our method and suggest how it can be improved.

contingencies↗

A Stochastic Covariance Shrinkage Approach in Ensemble Transform Kalman Filtering

The Ensemble Kalman Filters (EnKF) employ a Monte-Carlo approach to represent covariance information, and are affected by sampling errors in operational settings where the number of model realizations is much smaller than the model state dimension. To alleviate the effects of these errors EnKF relies on model-specific heuristics such as covariance localization, which takes advantage of the spatial locality of correlations among the model variables. This work proposes an approach to alleviate sampling errors that utilizes a locally averaged-in-time dynamics of the model, described in terms of a climatological covariance of the dynamical system. We use this covariance as the target matrix in covariance shrinkage methods, and develop a stochastic covariance shrinkage approach where synthetic ensemble members are drawn to enrich both the ensemble subspace and the ensemble transformation. We additionally provide for a way in which this methodology can be localized similar to the state-of-the-art LETKF method, and that for a certain model setup, our methodology significantly outperforms it.

54 ENVIRONMENTAL SCIENCES↗

The Last Journey. I. An Extreme-scale Simulation on the Mira Supercomputer

The Last Journey is a large-volume, gravity-only, cosmological N-body simulation evolving more than 1.24 trillion particles in a periodic box with a side length of 5.025 Gpc. It was implemented using the HACC simulation and analysis framework on the BG/Q system Mira. The cosmological parameters are chosen to be consistent with the results from the Planck satellite. A range of analysis tools have been run in situ to enable a diverse set of science projects and, at the same time, keep the resulting data amount manageable. Analysis outputs have been generated starting at redshift z ~ 10 to allow for construction of synthetic galaxy catalogs using a semianalytic modeling approach in postprocessing. As part of our in situ analysis pipeline, we employ a new method for tracking halo substructures, introducing the concept of subhalo cores. The production of multiwavelength synthetic sky maps is facilitated by generating particle light cones in situ, also beginning at z ~ 10. We provide an overview of the simulation setup and generated data products; a first set of analysis results is presented. A subset of the data is publicly available.

79 ASTRONOMY AND ASTROPHYSICS↗

Groundwater Volume Loss in Mexico City Constrained by InSAR and GRACE Observations and Mechanical Models

Abstract Groundwater withdrawal can cause localized and rapid poroelastic subsidence, spatially broad elastic uplift of low amplitude, and changes in the gravity field. Constraining groundwater loss in Mexico City, we analyze data from the Gravity Recovery and Climate Experiment and its follow‐on mission (GRACE/FO) and Synthetic Aperture Radar (SAR) Sentinel‐1A/B images between 2014 and 2021. GRACE/FO observations yield a groundwater loss of 0.85–3.87 km 3 /yr for a region of ∼300 × 600 km surrounding Mexico City. Using the high‐resolution interferometric SAR data set, we measure >35 cm/yr subsidence within the city and up to 2 cm/yr of uplift in nearby areas. Attributing the long‐term subsidence to poroelastic aquifer compaction and the long‐term uplift to elastic unloading, we apply respective models informed by local geology, yielding groundwater loss of 0.86–12.57 km 3 /yr. Our results suggest Mexico City aquifers have been depleting at faster rates since 2015, exacerbating the socioeconomic and health impacts of long‐term groundwater overdrafts.

58 GEOSCIENCES↗

Analysis of Daily, Seasonal, and Interannual Changes in Hofsjokull Ice Cap, Iceland, using Satellite Data

Analysis of a time series of European Remote Sensing Satellite (ERS)-1 and -2, RADARSAT ScanSAR synthetic aperture radar (SAR) and Landsat images from 1973 to 1998, shows daily to interannual changes in Hofsjokull, a 923 sq km ice cap in central Iceland. A digital elevation model of Hofsjokull was constructed using interferometry, and then SAR backscatter coefficient (d) was plotted with elevation, and air temperature along a transect across the ice cap. Most of the a' changes measured along the transect are caused by a change in the state (frozen or thawed) of the surficial snow or ice when air temperature rises above or below about -5 to O C. Seasonal (sigma)deg patterns are identified in a 4-year time series of 57 ERS-1 and -2 images. In addition, June 1997 ScanSAR images display rapid changes in brightness that are tied closely to daily meteorological events. SAR and Landsat data were also used to measure changes in the areal extent of Hofsjokull, from 1973 to 1997, and to locate (sigma)deg and reflectance boundaries that relate to the glacier facies. Late-summer 1997 (sigma)deg and reflectance boundaries agree and are coincident with the approximate location of the fim line, and the January 1998 position of the equilibrium line as determined from ERS-2 data.

Hall, D. K.↗

Quantitative guidance for efficient vertical flow measurements at the sediment–water interface using temperature–depth profiles

Upward discharge to surface water bodies can be quantified using analytical models based on temperature–depth (T-z) profiles. The use of sediment T-z profiles is attractive as discharge estimates can be obtained using point-in-time data that are collected inexpensively and rapidly. Previous studies have identified that T-z methods can only be applied at times of the year when there is significant difference between the streambed–water interface and deeper sediment temperatures (e.g., winter and summer). However, surface water temperatures also vary diurnally, and the influence of these variations on discharge estimates from T-z methods is poorly understood. For this study, synthetic T-z profiles were generated numerically using measured streambed interface temperature data to assess the influence of diurnal temperature variations on discharge estimation and provide insight into the suitable application of T-z methods. Results show that the time of day of data collection can have a substantial influence on vertical flux estimates using T-z methods. For low groundwater discharge fluxes (e.g., 0.1 m d -1 ), daily transience in streambed temperatures led to relatively large errors in estimated flow magnitude and direction. For higher discharge fluxes (1.5 m d -1 ), the influence of transient streambed temperatures on discharge estimates was strongly reduced. Discharge estimates from point-in-time T-z profiles were most accurate when the uppermost point in the T-z profile was near the bed interface daily mean (two time periods daily). Where temperature time series data are available, daily averaged T-z profiles can produce accurate discharge estimates across a wide range of discharge rates. Seasonality in shallow groundwater temperature generally had a negligible influence on vertical flow estimates. Finally, these findings can be used to plan field campaigns and provide guidance on the optimal application of T-z methods to quantify vertical groundwater discharge to surface water bodies.

54 ENVIRONMENTAL SCIENCES↗

Database Management Module Framework for Dynamic Contingency Analysis and Visualization

The Dynamic Contingency Analysis Tool (DCAT) is being developed to mimic the response of generation dynamics, protection, and load components to extreme contingencies in power systems. Currently, DCAT generates a huge data set, with the analysis results stored in multiple subfolders using a great many files in different formats (power flow cases, time series, figures, spreadsheets). To help power system engineers thoroughly understand and analyze system behavior under many scenarios and contingencies, we developed a database management module (DBM) that enables future integration of DCAT with industry-grade Big Data analytical and interactive visualization platforms. In this paper, we demonstrate the DBM framework with interactive analytics and visualization for DCAT on the synthetic South Carolina 500-bus power system model using hurricane contingencies that capture possibilities for an extreme contingency. DCAT’s advanced data management and interactive visualization can help planning engineers to visually explore and analyze system behavior, all in one view.

Cascading, dynamic simulations, database managemen↗

Quantifying modeling uncertainty in simplified beam models for building response prediction

The use of simple models for response prediction of building structures is preferred in earthquake engineering for risk evaluations at regional scales, as they make computational studies more feasible. The primary impediment in their gainful use presently is the lack of viable methods for quantifying (and reducing upon) the modeling errors/uncertainties they bear. This study presents a Bayesian calibration method wherein the modeling error is embedded into the parameters of the model. Here, the method is specifically described for coupled shear-flexural beam models here, but it can be applied to any parametric surrogate model. The major benefit the method offers is the ability to consider the modeling uncertainty in the forward prediction of any degree-of-freedom or composite response regardless of the data used in calibration. The method is extensively verified using two synthetic examples. In the first example, the beam model is calibrated to represent a similar beam model but with enforced modeling errors. In the second example, the beam model is used to represent the detailed finite element model of a 52-story building. Both examples show the capability of the proposed solution to provide realistic uncertainty estimation around the mean prediction.

47 OTHER INSTRUMENTATION↗

Sequential Selection for Minimizing the Variance with Application to Crystallization Experiments

For many crystal-based products (e.g., pharmaceuticals, energy storage), the size uniformity is not only a key quality attribute, but sometimes also an indicator of other attributes such as solid purity. This article proposes a sequential selection approach to find a proper experimental setting that leads to high uniformity, or equivalently, small variance for crystal sizes, from the advanced slug flow reaction crystallization process of a model crystal, called manganese oxalate hydrate. The proposed sequential selection approach contains a Bayesian adaptive method to incorporate new uniformity measurements in each step and two design acquisition functions to improve the selection of the most promising experimental setting in terms of minimizing the variance. We study the performance of the proposed approach through multiple synthetic numerical studies, as well as a case study based on data from slug flow crystallization experiments. Throughout these studies, the proposed approach shows competitive performance in identifying the best experimental setting.

Expected improvement↗

Deploying MARTe2 and MDSplus for Scalable Real-Time Control Systems: A Proof-of-Concept for the SMART Tokamak

The SMART tokamak is a spherical tokamak with flexible shaping that will need a modular and high-performance real-time control system. This work presents the implementation and validation of the MARTe2 framework at the Princeton Plasma Physics Laboratory (PPPL) as a testbed for supporting SMART (University of Seville, Spain). The system integrates MARTe2, MDSplus for data archiving, and user datagram protocol (UDP)-based communication with both synthetic and physical devices. A deterministic control loop was developed using custom control algorithms, showing the system’s ability to operate under strict real-time constraints. The resulting framework is scalable, maintainable, and adaptable to experimental tokamaks like SMART.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Determining the Axes of a Range-Doppler Image

Synthetic aperture radar (SAR) images formed with dechirp-on-receive data collection and rectangular format processing algorithm are the result of a two-dimensional discrete Fourier transform (DFT) applied to sampled data. There are several steps required to compute the range and Doppler values associated with each pixel in a SAR range-Doppler image. This memo walks readers through the process.

47 OTHER INSTRUMENTATION↗

Laminar burning speed measurements for hydrogen enhanced natural gas in a spherical chamber

This work presents laminar burning speed measurements for natural gas and hydrogen enhanced natural gas in gas-turbine conditions using a spherical combustion chamber at an initial temperature and pressure of 296 K and 10 atm, respectively. Natural gas and hydrogen fuels were prepared and mixed with a synthetic air mixture comprised of oxygen, nitrogen, and helium. The experimental data collected during 10 atm ignition was used to predict the LBS at elevated pressures (30 bar) to approach gas-turbine operating conditions. A significant enhancing effect of combustion pressure on LBS was observed, as well as H2 dilution. This work provides fundamental combustion data relevant to sustainable fuels to reduce economic dependence on carbon-based fossil fuels and reduce anthropogenic climate effects through 2050.

Yovino, Louis↗

Seasat/SIR-A digital registration over Algeria

Seasat Synthetic Aperture Radar (SAR) and Shuttle Imaging Radar (SIR-A) data over northeastern Algeria have been studied using digital registration. Preliminary results of this work show that: (1) both radars delineate in the same way the same features on the ground, (2) the Seasat image shows a strong difference between the Chott Melrhir and its environment, not seen in the same way by SIR-A, and (3) SIR-A data enhance more details on the floor of the Chotts, presumably due to the look angle or due to flooding conditions which may have occurred prior to the SIR-A experiment (November 12-14, 1981).

Rebillard, P.↗