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At least 1,315 records · Page 73

Data and Code for: Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits

This repository contains the simulation outputs and processing scripts associated with the study of winter wheat traits across the United States, utilizing the Ecosys agroecosystem model. The dataset includes model results for both rainfed and irrigated winter wheat systems, supporting the findings presented in the manuscript titled "Observation-constrained agroecosystem model inversion reveals continental-scale variation of winter wheat traits." Data includes the original Ecosys simulation outputs (archived in .db format within the compressed .zip files) and extracted analysis data (stored in .pkl files for efficient processing). Python code for data processing and figure generation is provided in a Jupyter notebook. External Observational Datasets should refer to the following official repositories for the input and validation data used in this study. The eddy covariance data from the AmeriFlux network (https://ameriflux.lbl.gov/). Climate-forcing data of NLDAS-2 from NASA LDAS (https://ldas.gsfc.nasa.gov/nldas/nldas-2-forcing-data). Soil data from the Gridded Soil Survey Geographic Database (gSSURGO), available at (https://www.nrcs.usda.gov/resources/data-and-reports/gridded-soil-survey-geographic-gssurgo-database). Crop yields, planting and harvest dates from the USDA public databases (https://quickstats.nass.usda.gov/; https://webapp.rma.usda.gov/apps/actuarialinformationbrowser/CropCriteria.aspx). Satellite-derived SLOPE GPP data from ORNL DAAC (https://daac.ornl.gov/cgi-bin/dsviewer.pl?ds_id=1786). Land use and crop progress information from the USDA Crop Data Layer and Crop Progress and Condition Gridded Layers (https://www.nass.usda.gov/Research_and_Science/). The Ecosys model code is available online at https://github.com/jinyun1tang/ECOSYS.

Wheat↗

LES ARM Symbiotic Simulation and Observation Scenario for CACTI

The Large-Eddy Simulation (LES) Atmospheric Radiation Measurement (ARM) Symbiotic Simulation and Observation (LASSO) deep-convection scenario for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) field campaign. The LASSO-CACTI scenario consists of a library of mesoscale and LES simulations spanning grid spacings from 7.5 km to 100 m for convection near the Sierras de Córdoba mountain range, roughly centered on the ARM Mobile Facility. Supporting skill scores and observation comparisons complement the simulations in addition to subsets of the model output for various categories of model output variables. More information can be found at https://www.arm.gov/capabilities/modeling/lasso.

54 ENVIRONMENTAL SCIENCES↗

Improving Vertical Velocity Retrievals from Doppler Radar Observations of Convection Field Campaign Report

Our National Science Foundation (NSF)-supported project was designed to address two longstanding challenges in radar-, meso-scale-, and hydro-meteorology: (1) mitigating the effects of non-simultaneous data collection on radar data-based analysis products, and (2) improving estimates of the vertical velocity (w) field in dual-Doppler wind analyses. Errors associated with the non-simultaneous data collection introduce errors in all Doppler analyses, and impose a lower limit on the time and space scales that can be studied. For many investigations the w field is of prime meteorological importance, but it is the velocity component most difficult to accurately synthesize from dual-Doppler wind observations. Our original plan proposed for short field campaigns at the Atmospheric Radiation Measurement (ARM) user facility Southern Great Plains (SGP) Central Facility (CF) was to use multiple-Doppler radial wind data from the scanning ARM X-band radars to test and refine our multiple-Doppler wind analysis algorithms. An important part of our plan was the use of high-temporal-resolution w observations to verify the analyses. In our original plan, these data would be obtained from Doppler lidars, 915 MhZ profilers and Ka-band ARM Zenith Radar (KAZR) zenith-pointing radars at the CF and nearby ARM facilities in north-central Oklahoma. Using the data, we planned to test the utility of new spatially variable advection-correction/analysis procedures, the utility of the anelastic vertical vorticity equation as a constraint in variational multiple-Doppler wind analysis, and other Doppler wind analysis procedures. Idealized tests with numerically-simulated supercell data had suggested the vorticity constraint could help improve the vertical velocity field if the data were gathered with sufficiently high temporal resolution (e.g., volume scans completed in 30-60 sec), so we were interested in exploring the use of rapid-scan data from the X-band Scanning ARM Precipitation Radars (XSAPRs).

Southern Great Plains, convection, KAZR, XSAPR, ve↗

Observations of Short-Range Wadefield Effects in Tesla-Type Superconducting RF Cavities

The Fermilab Accelerator Science and Technology (FAST) facility has a unique configuration of a photocathode rf gun beam injecting two TESLA-type single cavities (CC1 and CC2) in series prior to the cryomodule. To investigate short-range wakefield effects, we have steered the beam to minimize the signals in the higher-order mode (HOM) detectors of CC1 and CC2 for a baseline, and then used a vertical corrector between the two cavities to steer the beam off axis at an angle into CC2. A Hamamatsu synchroscan streak camera viewing a downstream OTR screen provided an image of y-t effects within the micropulses with ~10-micron spatial resolution and 2-ps temporal resolution. At 500 pC/b, 50 b, and 4 mrad off-axis steering into CC2, we observed an ~ 100-micron head-tail centroid shift in the streak camera image y(t)-profiles. This centroid shift value is 5 times larger than the observed HOM-driven centroid oscillation within the macropulse and is consistent with a calculat ed short-range wakefield effect. Additional results for kick-angle compensations will be presented.

43 PARTICLE ACCELERATORS↗

A Tool for Evaluating Youth Engagement in an Informal STEM Setting: The WGG Observation Protocol

This paper discusses findings from the use of the Wise Guys and Gals (WGG) Observation of WGG Youth Protocol in a blended learning environment. The protocol was used to assess youth engagement when completing blended engineering design challenges at two Boys and Girls Clubs. WGG is a project funded through a grant from the National Science Foundation and which brings blended learning design challenges to middle school aged learners in informal STEM (science, technology, engineering, and mathematics) settings. This paper explores the feasibility of using the observation protocol to collect data about youth engagement, and the potential use of the protocol in other informal STEM settings.

99 GENERAL AND MISCELLANEOUS↗

Material transfers detection with seismic observations

We are exploring the use of data from a seismic network around a research nuclear reactor and isotope production facility at Oak Ridge National Laboratory to study activity patterns related to the transfer of nuclear material. A sensor network with eight seismometers was installed around the High Flux Isotope Reactor and the Radiochemical Engineering Development Center and started operating in October 2019. These data are used to detect and characterize operational events around facility. We are using those data to extract signals related to the movement of vehicles involved in the transport of nuclear materials (e.g., transportation of reactor fuel, targets, and product isotopes). Large vehicles produce mechanical energy that can be observed as seismic signals, either as the result of sound emanating from the vehicle engine or by the generation of surface waves as a response of the ground to the load of the vehicles. In particular, the station located near the entrance gate of the facility displays a clear seismic signature as vehicles cross a metal platform on the ground. This signal is characterized by sharp energy bursts that correspond to the number of axles on the vehicle. We developed and are testing an algorithm to identify sequences of energy bursts to count and characterize vehicles of different sizes. We are also exploring the use of seismic polarization analysis to measure the degree of polarization of the observed signals. These two techniques for detection and characterization of vehicles used for nuclear material transfers will be validated with seismic data from a targeted collection using different vehicles and routes similar to the ones used in real-life scenarios at the High Flux Isotope Reactor.

Marcillo, Omar↗

Observational Assessment of Metocean Conditions in the WFIP3 Region

The WFIP3 project, sponsored by the U.S. Department of Energy, is aimed at improving our understanding of the physics of the atmosphere and ocean that dictate the structure and variability of the wind resource within the MABL. As part of the project, a long-term offshore field campaign will take place along the U.S. East Coast to provide an unprecedented characterization of the MABL in the vicinity of the Massachusetts/Rhode Island wind energy lease areas. The unprecedented observational data set collected in the WFIP3 field campaign will allow intensive numerical modeling development and validation efforts. To inform the field campaign design and the preliminary studies associated with it, here we perform a characterization of the MABL and ocean conditions by leveraging available observations in the region.

lidars↗

DeepSurveySim: Simulation Software and Benchmark Challenges for Astronomical Observation Scheduling

Modern astronomical surveys have multiple competing scientific goals. Optimizing the observation schedule for these goals presents significant computational and theoretical challenges, and state-of-the-art methods rely on expensive human inspection of simulated telescope schedules. Automated methods, such as reinforcement learning, have recently been explored to accelerate scheduling. However, there do not yet exist benchmark data sets or user-friendly software frameworks for testing and comparing these methods. We present DeepSurveySim -- a high-fidelity and flexible simulation tool for use in telescope scheduling. DeepSurveySim provides methods for tracking and approximating sky conditions for a set of observations from a user-supplied telescope configuration. We envision this tool being used to produce benchmark data sets and for evaluating the efficacy of ground-based telescope scheduling algorithms, particularly for machine learning algorithms that would suffer in efficacy if limited to real data for training.We introduce three example survey configurations and related code implementations as benchmark problems that can be simulated with DeepSurveySim.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Adaptive Control for Load-Following of Boiling Water Reactors Part I: Linear Systems and Fully-Observable Dynamics

Automation control is a key strategy to improve the economic competitiveness of nuclear power plants. Not only does it help reduce operational costs, but it also extends the value proposition of these plants to nontraditional markets, including unattended operations in remote villages and space. However, the dynamics of the operating environments of nuclear reactors are subject to changes over time, and there are no widely adopted methods to ensure that the automation strategy will remain effective over the extended durations required for these applications. Adaptive control is a discipline that offers the possibility to accommodate such changes online. However, it relies on mathematical assumptions that must be respected to ensure robustness and reliability. In this work, we derive an adaptive control formulation for linear systems in which all states are observable and apply it to an instance of load-follow operation for Boiling Water Reactors. We assumed uncertainty in two factors: the temperature coefficient and the control rod worth, both of which are affected over time by the evolution of the nuclear reactor core environment. With an arbitrary penalty factor of 5, we found that the mean absolute and integral time absolute errors can be reduced by more than 90%, underscoring the strength of adaptive control. To extend the application to more challenges, different uncertainties and load-follow trajectories, as well as new formulations that include non-linearity and partial observability, are currently being developed.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Simultaneous transmission/absorption photometry of particle-laden filters from wildland fires during the Biomass Burning Observation Project (BBOP) field campaign

Transmissivity and absorptivity measurements were carried out simultaneously in the visible (wavelength of 532 nm) at laboratory conditions using particle-laden filters obtained from a three-wavelength particle/soot absorption photometer (PSAP). Here, the particles were collected on filters from wildland fires over the Pacific Northwest during the Department of Energy Biomass Burning Observation Project (BBOP) field campaign in 2013. The objective of this investigation was to apply this measurement approach, referred to as simultaneous transmission/absorption photometry (STAP), to estimate the aerosol extinction coefficient from actual field-campaign filter aerosol, and compare results with the PSAP. The STAP approach offers several advantages over the PSAP, including estimation of the extinction coefficient from temperature measurements (avoiding the complexities associated with filter reflectivity/scattering measurements), as well as determination of the filter optical properties and filter effects on particle absorption (resulting in particle absorption enhancement). The experimental arrangement included a laser probe beam impinging normal to the particle-coated surface of a vertically mounted filter, and a thermocouple placed flush in the middle of (and in thermal contact with) the filter uncoated back surface. With this simple arrangement, the transmissivity and absorptivity were determined simultaneously at a given laser beam wavelength. The measurement repeatability was better than 0.3 K (95% confidence level) for temperature and 0.4 mW for laser power. The limit of detection for the extinction coefficient was estimated to be (8–12) Mm -1 (95% confidence level) at about 1.9 mW laser power. The extinction coefficient was determined through measurement of both PSAP blank and exposed filters. Filters were obtained from nine different aircraft flights conducted during the BBOP campaign, representing different flight patterns, days, stages of burning, landscapes, and wildland fires. The STAP extinction coefficient matched the darkness of the filter coating, however the PSAP-filter results did not follow the same order. Although there were differences in transmissivity between the two techniques, the estimated values for absorption coefficient were in good agreement.

54 ENVIRONMENTAL SCIENCES↗

Experiential findings for sustainable software ecosystems to support experimental and observational science

In the search for a sustainable approach for software ecosystems that supports experimental and observational science (EOS) across Oak Ridge National Laboratory (ORNL), we conducted a survey to understand the current and future landscape of EOS software and data. This paper describes the survey design we used to identify significant areas of interest, gaps, and potential opportunities, followed by a discussion on the obtained responses. The survey formulates questions about project demographics, technical approach, and skills required for the present and the next five years. Here, the study was conducted among 38 ORNL participants between June and July of 2021 and followed the required guidelines for human subjects training. We plan to use the collected information to help guide a vision for sustainable, community-based, and reusable scientific software ecosystems that need to adapt effectively to: (i) the evolving landscape of heterogeneous hardware in the next generation of instruments and computing (e.g. edge, distributed, accelerators), and (ii) data management requirements for data-driven science using artificial intelligence.

97 MATHEMATICS AND COMPUTING↗

Thermal spray coating of Al-Cu-Fe quasicrystals: Dynamic observations and surface properties

In this study, we prepared Al-Cu-Fe quasicrystals (QCs) via thermal spray coating after optimizing the process parameters. Both in-situ XRD and in-situ TEM were used to investigate the thermal stability of QC phase. These dynamic techniques uniquely allow for a direct observation of QC growth upon heating and cooling. We show that the cubic β-Al-Cu-Fe is the dominant phase at room temperature (initial stage), but with an increase in temperature, the QC takes over at 650 °C, consistent with thermodynamic calculations. Further increasing the temperature to 800 °C, the QC phase transforms into cubic β-Al-Cu-Fe such that the β-Al-Cu-Fe phase is the only phase in existence at 870 °C. Based on this result, we annealed the sample after thermal spray deposition for one hour at 650 °C, which yielded an almost pure QC coating. The contact angle (against water) before annealing was 50°±4° but improved dramatically to 130°±5° after annealing at 650 °C for 1 h. Here, this study provides a better understanding of QC formation during heat treatment as well as that of other secondary phases. Furthermore, these results can be used to manufacture QC coatings with enhanced interfacial properties that are central to technological applications.

36 MATERIALS SCIENCE↗

Pillars of Cloud-Based Earth Observation Science Education

Earth observation (EO) is undergoing a paradigm shift with the development of cloud-based analytical platforms supporting EO data collection and access, parallel processing, easier communication of results, and expanded accessibility. As the global community of users and the diversity of applications grow, there is a clear need for expanded educational capacity to leverage these developments and increase the impact of EO research and teaching. Drawing upon extensive conversations between educators, practitioners, and researchers, we propose three pillars that must be prioritized to prepare students, researchers, and professionals to take full advantage of the cloud-based EO paradigm and guide future growth.

97 MATHEMATICS AND COMPUTING↗

Aerosol Influences on Cloud Water: Insights From ARM EPCAPE Observations With Explainable Machine Learning

This study employs an explainable machine learning (ML) framework (XGBoost-SHapley Additive exPlanations analysis) to investigate controlling factors on cloud liquid water path (LWP) using EPCAPE observations near the California coast. Aerosols are found to be the dominant factor explaining LWP variability, surpassing meteorological factors (MFs). By isolating aerosol effects from meteorological influences, the ML reveals a negative linear relationship between LWP and cloud droplet number concentration (Nd) in log space, likely driven by entrainment drying via evaporation-entrainment feedback. This aligns with the negative regime of the inverted-V relationship reported in previous studies, while no positive LWP responses are found due to a limited number of precipitating cases in EPCAPE. Furthermore, the sensitivity of LWP to Nd shows a non-linear dependence on MFs like moisture contrast between surface and free troposphere and lower-tropospheric stability. This occurs due to the interplay between the MFs' direct effects on entrainment drying and indirect effects through LWP adjustments.

EPCAPE observations↗

Gradient-Descent-Based Learning Gain for Backstepping Controller and Disturbance Observer of Nonlinear Systems

This paper proposes a gradient-descent-based learning (GL) gain for backstepping controller and disturbance observer (DOB) of nonlinear system. The proposed method consists of the GL gain update law, controller, and DOB. The GL gain update law is proposed to adapt the control gain and DOB gain according to the direction that minimizes the cost function. The mathematical analysis reveals that the GL gain always has a positive sign and upper bound. The controller is designed via a backstepping procedure to track the desired output with GL control gain. The DOB is designed to estimate the unknown external disturbance with the GL DOB gain. Because the control and DOB gains are simultaneously tuned to achieve improved performance, the time consumption for tuning can be reduced. In addition, the peaking phenomenon can be avoided initially by a small initial value of GL gains. The stability of the closed-loop system is guaranteed using the input-to-state stability property. The performance of the proposed method was validated via simulations and experiments using a DC motor.

42 ENGINEERING↗

Optimal Experimental Design for Inverse Problems in the Presence of Observation Correlations

Optimal experimental design (OED) is the general formalism of sensor placement and decisions on the data collection strategy for engineered or natural experiments. This problem is prevalent in many critical fields such as battery design, numerical weather prediction, geosciences, environmental and urban studies. State-of-the-art computational methods for experimental design do not accommodate correlation structure in observational errors produced by many expensive-to-operate devices such as X-ray machines, radars, and satellites. Discarding evident data correlations leads to biased results, higher expenses, and waste of valuable resources. We present a general formulation of the OED formalism for model-constrained large-scale Bayesian linear inverse problems, where measurement errors are generally correlated. The proposed approach utilizes the Hadamard product of matrices to formulate the weighted-likelihood, and is valid for both finite as well as infinite-dimensional Bayesian inverse problems. Extensive numerical experiments are carried out for empirical verification of the proposed approach using an advection-diffusion model, where the objective is to optimally place a small set of sensors, under a limited budget, to predict the concentration of a contaminant in a closed and bounded domain.

Correlated observations↗

Cross Validation of the Network of Ground-Based Radar with GPM during the Remote Sensing of Electrification, Lightning, And Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) Field Campaign

The cross-validation of radars in a network is important in making consistent retrievals across the domain and assuring the product quality. During the RELAMPAGO field campaign, two C-band radars, namely the Colorado State University C-band Hydrological Instrument for Volumetric Observations ( CSU-CHIVO) and the C-band Scanning ARM Precipitation Radar (CSAPR-2), were deployed near the Sierras de Cordoba in Argentina, a region known for having some of the most intense severe weather in the world. In addition to these two radars, the operational radar of the Cordoba City, the Radar Meteorologico Argentino 1 (RMA-1), adds another instrument to the RELAMPAGO network. This study presents an intercomparison between the RELAMPAGO C-band radars using the GPM spaceborne radar as a common reference ..A method to bring ground-based radars into better agreement is also proposed. Moreover, the attenuation correction for the C-band radar is studied in the context of intercomparing two radars. The attenuation coefficients are computed for the RELAMPAGO domain using the local disdrometers deployed. during the campaign. After the attenuation correction, CSU-CHIVO, CSAPR-2, and RMA-1 compare well with GPM-DPR with a high correlation and bias less than 1 dB.

54 ENVIRONMENTAL SCIENCES↗

Critical Interference Mechanisms for Marine Renewable Energy-powered Ocean Observing Platforms

Marine renewable energy devices, such as wave energy converters or tidal turbines, not only have the potential to provide clean, reliable power to the grid but may also offer new opportunities for ocean exploration by providing power for oceanographic sensors where other sources cannot. However, an important consideration in making this vision a reality is understanding whether the marine energy devices may interfere with oceanographic measurements. Interference may occur through several pathways, including sound produced by the device and the motion of the device itself. In this report, we provide an overview of interference pathways and their implications before exploring two use cases for marine energy-powered ocean observing platforms: a tidal-powered passive acoustic monitoring system and wave-powered wave measurement buoys. For each use case, we review the relevant literature and underlying physics of the systems as they are relevant to the desired measurements before making recommendations for design of such systems.

16 TIDAL AND WAVE POWER↗