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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 685 records · Page 38

Real-time density-matrix coupled-cluster approach for closed and open systems at finite temperature

We extend the coupled-cluster method to correlated quantum dynamics of both closed and open systems at finite temperatures using the thermofield formalism. The approach expresses the time-dependent density matrix in an exponential ansatz and describes time-evolution along the Keldysh path contour. A distinct advantage of the approach is exact trace-preservation as a function of time, ensuring conservation of probability and particle number. Furthermore, the method avoids the computation of correlated bra-states, simplifying the computational implementation. We develop the method in a thermal quasiparticle representation, which allows seamless connection to the projection method and diagrammatic techniques of the traditional coupled-cluster formalism. For comparison, we also apply the thermofield framework to the density-matrix renormalization-group method to obtain reference results for closed and open systems at finite temperature. We test the singles and doubles approximation to the density-matrix coupled-cluster method on the correlated electronic dynamics of the single-impurity Anderson model, demonstrating that the new method successfully captures the correlated dynamics of both closed systems at finite temperature and driven-dissipative open systems. This encouraging performance motivates future applications to nonequilibrium quantum many-body dynamics in realistic systems.

Shushkov, Philip (ORCID:0000000266136117)↗

Patient-bounded extrapolation using low-dose priors for volume-of-interest imaging in C-arm CT

Purpose: Three-dimensional (3D) volume-of-interest (VOI) imaging with C-arm systems provides anatomical information in a predefined 3D target region at a considerably low x-ray dose. However, VOI imaging involves laterally truncated projections from which conventional reconstruction algorithms generally yield images with severe truncation artifacts. Heuristic based extrapolation methods, e.g., water cylinder extrapolation, typically rely on techniques that complete the truncated data by means of a continuity assumption and thus appear to be ad-hoc. It is our goal to improve the image quality of VOI imaging by exploiting existing patient-specific prior information in the workflow. Methods: A necessary initial step prior to a 3D acquisition is to isocenter the patient with respect to the target to be scanned. To this end, low-dose fluoroscopic x-ray acquisitions are usually applied from anterior–posterior (AP) and medio-lateral (ML) views. Based on this, the patient is isocentered by repositioning the table. In this work, we present a patient-bounded extrapolation method that makes use of these noncollimated fluoroscopic images to improve image quality in 3D VOI reconstruction. The algorithm first extracts the 2D patient contours from the noncollimated AP and ML fluoroscopic images. These 2D contours are then combined to estimate a volumetric model of the patient. Forward-projecting the shape of the model at the eventually acquired C-arm rotation views gives the patient boundary information in the projection domain. In this manner, we are in the position to substantially improve image quality by enforcing the extrapolated line profiles to end at the known patient boundaries, derived from the 3D shape model estimate. Results: The proposed method was evaluated on eight clinical datasets with different degrees of truncation. The proposed algorithm achieved a relative root mean square error (rRMSE) of about 1.0% with respect to the reference reconstruction on nontruncated data, even in the presence of severe truncation, compared to a rRMSE of 8.0% when applying a state-of-the-art heuristic extrapolation technique. Conclusions: The method we proposed in this paper leads to a major improvement in image quality for 3D C-arm based VOI imaging. It involves no additional radiation when using fluoroscopic images that are acquired during the patient isocentering process. The model estimation can be readily integrated into the existing interventional workflow without additional hardware.

60 APPLIED LIFE SCIENCES↗

Zero Power Warming (ZPW) Chamber Prototype Measurements, Utqiagvik (Barrow), Alaska, 2016

Data were collected during one season of prototyping associated with the development of a passive warming technology. An experimental chamber, the Zero Power Warming (ZPW) chamber, was fitted with apparatus to modulate venting of a field enclosure and enhance elevation of air temperature by solar radiation. The ZPW chamber was compared with a control chamber (Control) and an ambient open air plot (Ambient). The control chamber was identical to the ZPW chamber but lacked the apparatus necessary to modulate venting, the chamber vents in the control chamber were fixed open for the majority of the trial period. The three plots were located over Carex aquatilis growing in an area of moderately degraded permafrost. Chambers were placed on the same footprints that were used for a similar exercise in 2015 (no data) and therefore those plots had experienced some thaw and degradation prior to 2016. The following data were collected for 80 days at 1 minute intervals from within two chambers and an ambient plot: solar input, chamber venting, air temperature, relative humidity, soil temperature (at 5, 10 and 15 cm), soil moisture, downward and upward NIR. CO2 concentration within the chambers and of the ambient air plot was collected at 1 minute intervals over a 62 hour period in the middle of the growing season. This dataset contains six csv files and one pdf file.The documentation may refer to a ZPW-metadata.xlsx file. This file was split into two csv files: ZPW-metadata.csv and ZPW-metadata-instrumentation.csv.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Accurate Realization of GPS Vertical Global Reference Frame

The goal of this project is to improve our current understanding of GPS error sources associated with estimates of radial velocities at global scales. An improvement in the accuracy of radial global velocities would have a very positive impact on a large number of geophysical studies of current general interest such as global sea-level and climate change, coastal hazards, glacial isostatic adjustment, atmospheric and oceanic loading, glaciology and ice mass variability, tectonic deformation and volcanic inflation, and geoid variability. A set of GPS error sources relevant to this project are those related to the combination of the positions and velocities of a set of globally distributed stations as determined &om the analysis of GPS data, including possible methods of combining and defining terrestrial reference frames. This is were our research activities during this reporting period have concentrated. During this reporting period, we have researched two topics: (1) The effect of errors on the GPS satellite antenna models (or lack thereof) on global GPS vertical position and velocity estimates; (2) The effect of reference W e definition and practice on estimates of the geocenter variations.

Elosegui, Pedro↗

Upgrades at the NASA Langley Research Center National Transonic Facility

Several projects have been completed or are nearing completion at the NASA Langley Research Center (LaRC) National Transonic Facility (NTF). The addition of a Model Flow-Control/Propulsion Simulation test capability to the NTF provides a unique, transonic, high-Reynolds number test capability that is well suited for research in propulsion airframe integration studies, circulation control high-lift concepts, powered lift, and cruise separation flow control. A 1992 vintage Facility Automation System (FAS) that performs the control functions for tunnel pressure, temperature, Mach number, model position, safety interlock and supervisory controls was replaced using current, commercially available components. This FAS upgrade also involved a design study for the replacement of the facility Mach measurement system and the development of a software-based simulation model of NTF processes and control systems. The FAS upgrades were validated by a post upgrade verification wind tunnel test. The data acquisition system (DAS) upgrade project involves the design, purchase, build, integration, installation and verification of a new DAS by replacing several early 1990's vintage computer systems with state of the art hardware/software. This paper provides an update on the progress made in these efforts. See reference 1.

Paryz, Roman W.↗

Better Buildings NW Ohio

When the Toledo Lucas County Port Authority (TLCPA) filed for the Department of Energy EECBG grant in late 2009, it was part of a strategic and Board backed objective to expand the organization’s economic development and financing programs into alternative energy and energy efficiency. This plan was filed with the knowledge and support of the areas key economic development agencies. The City of Toledo was also a key partner with the Mayor designating a committee to develop a Strategic Energy Policy for the City. This would later give rise to a Community Sustainability Strategic Plan for Toledo, Lucas County and the surrounding region with energy efficiency as a key pillar. When the TLCPA signed the grant documents with the DOE in June of 2010, the geographic area was severely distressed economically, in the early stages of a recovery from over a 30% drop in business activity and high unemployment. The TLCPA and its partners began identifying potential project areas well before the filing of the application, continuing to work diligently before the formal award and signing of the grant documents. Strong implementation and actions plans and business and financing models were developed and revised throughout the 3 year grant period with the long term goal of creating a sustainable program. The TLCPA and the City of Toledo demonstrated early leadership by forming the energy improvement district and evaluating buildings under their control including transportation infrastructure and logistics, government services buildings and buildings which housed several for profit and not for profit tenants while completing significant energy efficiency projects that created public awareness and confidence and solid examples of various technologies and energy savings. As was stated in the DOE Award Summary, the undertaking was focused as a commercial program delving into Alternative Energy Utility Districts; what are referred to in Ohio Statute as Energy Special Improvement Districts or ESIDs and what is nationally known as Property Assessed Clean Energy or PACE districts and PACE financing. The project methodology followed the identify, develop, implement, monitor and measure format. These districts began in Toledo and adjoining areas and are expanding to TLCPA’s 28 county financing agency geographic footprint. What began as the Toledo Ohio Advanced Energy Improvement Corporation is now doing business as the Northwest Ohio Advanced Energy Improvement District recognizing it expansion into creating and financing other districts in NW Ohio. The program has been sought out as an advisor by major communities and states in the process of developing similar legislation and programs and has become one of the largest most successful PACE energy improvement and financing districts in the US. The program and the energy district focused on transforming energy use, delivery, conservation and renewable energy as “options of first choice”. The significant energy savings paid for many of the improvements and created a financially viable program well beyond the grant period. The program has become a model within the State of Ohio and Nationally on how to implement and finance projects in broad energy districts including how to evolve and integrate several financing methodologies. It is a unique utilization of revolving loan funds and energy bond pooling with revenue backing primarily from energy improvement special assessments on commercial properties along with some power purchase agreement (PPA) and loan agreement revenue. The program has also incorporated Qualified Energy Conservation Bonds, State of Ohio Energy Loans (SEP), utility rebates, solar and renewable energy certificates, renewable tax incentives and grants, and owner funded equity as additional program leverage and funding. Other keys to this success have been a continual simplification and refinement of the application and documentation process to make funding available easily and quickly to building owners when they are prepared to commit to the project as well as act as a trusted facilitator and advisor to both building owners and other stakeholders. Taking a flexible and pragmatic approach to project evaluation and implementation that matches time and expense to the complexity of the project has been another key learning. To date the program has closed 3 energy bond issues through the TLCPA sponsored and managed NW Ohio Bond Fund totaling $16.54 million (of which $3.34 million were QECB qualified). The program has turned over its $3.0 million revolving loan fund twice as construction financing in advance of bond issuance and currently has issued $1.25 million in revolving term loans. The program has $1.66 million of remaining capacity for QECB qualified bonds. The program can issue an additional $13.46 million in energy bonds continuing to utilize its DOE EECBG loan loss reserves. In addition, the program has available $3.6 million of loan loss reserves from the State of Ohio, as an eligible Port Authority, that can back the issuance of an additional $7.2 to $14.4 million of energy bonds. This does not include additional bond capacity is available from the NW Ohio Bond Fund. The program is the master escrow agent for $18 million of loan loss reserves from the State of Ohio for eligible Port Authorities that can be utilized to assist the formation of energy districts and financing programs in major metropolitan areas and regions around the State of Ohio. Other leveraged funds now total $10 million; placing the total project value completed and financed at over $30 million. In addition that program has generated an active pipeline of projects in various stages that total $25 – $30 million.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Selection of glasses in support of the Sludge Batch 9 variability study for coupled operation with the Salt Waste Processing Facility

Prior to the processing of Sludge Batch 9 (SB9) with Frit 803 at the Defense Waste Processing Facility (DWPF), assessments and experimental glass work were completed to support the qualification of SB9 coupled processing with streams from the Actinide Removal Process (ARP) and Modular Caustic Side Solvent Extraction Unit (MCU). This previous work did not address coupled processing with streams from the Salt Waste Processing Facility (SWPF) because the Product Composition Control System (PCCS) models limited the TiO 2 concentration in glass to 2 weight percent (wt.%). These high activity streams from SWPF include monosodium titanate (MST) and sludge solids from the Sludge Solids Receipt Tank as well as Cs-containing strip effluent. The incorporation of these SWPF streams is expected to reach TiO2 concentrations in glass greater than 2 wt.% based on an MST addition of 0.4 g MST/L of salt solution. If double strike operation is required, then the MST addition is increased to 0.8 g MST/L of salt solution. Therefore, revisions to the models contained in PCCS were completed to allow the evaluation of glasses containing greater than 2 wt.% TiO 2 , but less than 6 wt.%. To support the implementation of the revised PCCS for SB9 – Frit 803 processing at DWPF prior to SWPF startup, the applicability of the new durability models for the SB9 variability study glasses was verified. Since the initial SB9 qualification for ARP-MCU coupled operation, additional Tank 40 analyses have been completed, which served as the basis for an updated projection of the SB9 blend composition in Tank 40. To identify a frit optimized for SB9 coupled operation with SWPF, the Savannah River National Laboratory (SRNL) performed a paper-study by utilizing Measurement Acceptance Region (MAR) assessments with DWPF PCCS. Based on these MAR assessment results, Frit 625 was recommended for processing both single and double MST strike scenarios. Savannah River Remediation (SRR) requested that SRNL perform a variability study with both Frit 803 and Frit 625 for SB9 coupled operation with SWPF. The objective of the variability study is to demonstrate that the Product Consistency Test (PCT) responses of the glasses are acceptable relative to the chemical durability of the Environmental Assessment (EA) reference glass and predictable by the current DWPF PCCS models for durability. This report documents the development of a test matrix that will support the variability study. To provide operational flexibility prior to SWPF startup, the predictability of glasses within the glass region for Frit 625-SB9 coupled operation with ARP-MCU was also confirmed.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Machine learning and deep learning for mineralogy interpretation and CO 2 saturation estimation in geological carbon Storage: A case study in the Illinois Basin

Carbon capture and storage (CCS) is a promising approach to simultaneously maintaining energy security and reducing carbon dioxide (CO 2 ) emissions under the current energy portfolio that is dominated by fossil fuel energy. Pre-injection formation characterization and post-injection CO 2 monitoring are two critical tasks to guarantee storage efficiency in CCS. The CCS projects in the Illinois Basin, the first large-scale CO 2 injection into saline aquifers in the United States, employed conventional and the latest pulsed neutron logging (PNL) tools for mineralogy interpretation and CO 2 saturation estimation, which provide valuable references for future CCS projects. Because of the inherent fuzziness of petrophysical measurements and complex subsurface heterogeneity, interpreting well-logging data is time-consuming, and its accuracy can be user-biased. In recent years, data-driven methods have been widely used to capture the non-linear patterns between input features and interpretation results. This work applied and evaluated four commonly used machine learning (ML) models, including ridge regression (RR), random forest (RF), gradient boosting regression (GBR), support vector regression (SVR), and one deep learning (DL) model, the artificial neural network (ANN). We optimized the hyperparameters of the four ML models and the DL model using the simulated annealing algorithm and the grid search strategy, respectively. The input features of the mineralogy interpretation models were eleven conventional well-logging parameters, and the label data (i.e., ground truth) were the porosity and volumetric fractions of six minerals, including quartz, feldspar, dolomite, calcite, clay, and iron minerals. The results demonstrated that the GBR and RF models were superior in predicting volumetric fractions of minerals and porosity; label data with low coefficient of variation (CV) values tended to yield better performance. For CO 2 saturation estimation, the RF was the best-performing model, followed by SVR, ANN, GBR, and RR. Furthermore, we conducted feature importance ranking using the permutation importance algorithm and found that the formation sigma and well pressure were the most important features in this study. In conclusion, the study of CCS projects in the Illinois Basin bridges the gap between the limited knowledge and understanding of geological carbon storage and the increasing demand for reliable, cost-effective, and sustainable energy solutions.

58 GEOSCIENCES↗

Connected Lighting Systems Efficiency Study: PoE Cable Energy Losses, Part 2

DOE published a report in November 2017 (herein referred to as “Part 1”) summarizing the results of an exploratory study investigating power losses in Ethernet cables used between PoE switches and luminaires in PoE connected lighting systems. Testing was conducted at the Pacific Northwest National Laboratory (PNNL) Connected Lighting Test Bed (CLTB) in September 2017. The results were analyzed to explore the impact of cable selection on PoE lighting system energy efficiency, as well as the effectiveness of guidelines published by the American National Standards Institute (ANSI) C137 Lighting Systems Committee in 2017. The guidance offered in ANSI C137.3-2017 was found to be effective in limiting cable energy losses to 5% in PoE lighting applications, provided that the average cable length on a project does not exceed 50 m. This Part 2 report summarizes the results of a continued investigation of the power losses in Ethernet cables used between PoE switches and luminaires in PoE connected lighting systems. Testing was conducted at the PNNL CLTB in July-August 2018. A test setup comprising a PoE switch, a set of luminaires, and a reference meter was again used to test multiple cable models of varying design. The results were analyzed to explore the impact of cable selection and installation practices (e.g., cable bending, cable bundling, and installation in conduit) on PoE lighting system energy efficiency, as well as the effectiveness of the ANSI C137.3 guidelines. Notably, three cables—two of which were shielded—were previously excluded from the Part 1 study due to compatibility issues. All three cables were included in this Part 2 study, along with a fourth model cable introduced in Part 2. In addition, whereas no patch cords were used in Part 1, patch cords were used in some Part 2 testing. The ANSI C137.3 guidance was again shown to effectively limit power losses to less than 5% in the cables tested (varying in AWG, Category, shielding, fire rating, and manufacturer), and AWG again proved to be the most important cable design variable for energy performance, as expected. However, these findings should not be construed as being representative of all cable models and installation practices. For example, energy losses would be greater when cables are connected to patch cords, bundled in conduit, and loaded with powered devices (PDs) approaching 100 W input power. The other key finding was that with 44 W luminaires as PDs and room ambient temperatures below 30°C, cable energy losses were not substantially increased by cable bending or bundling in uninsulated conduit. However, environments with higher ambient temperatures will have greater energy losses due to increased conductor DCR. In addition, product selection and installation practices will have increased importance as PDs approaching 100 W input power—conveyed by a single Ethernet cable—are introduced following publication of the forthcoming Institute of Electrical and Electronics Engineers (IEEE) Standard 802.3bt. The report also provides recommendations and next steps, which include plans for additional PoE cable energy losses testing with higher-power PDs to more fully explore the potential of PoE lighting systems.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Reference aircraft for ICAO Working Group E

The results of an advanced supersonic transport aircraft/engine integration study to be used as a detail preliminary design case to assist in the assessment of noise standards applicable to future supersonic transports are summarized. The design considered reflects the application of the advanced technologies which are projected to be available for program initiation in the 1980-1985 time period. Suppression characteristics included were obtained in simulated forward flight in the Rolls-Royce spin rig using a small scale model. The engine size selected produces a noise no greater than 108 EPNdB at any of the three Far Part 36 (Stage 2) defined measuring points and is sized slightly larger than the optimum cruise size to meet this noise constraint condition.

Source record↗

On the Execution Control of HLA Federations using the SISO Space Reference FOM

In the Space domain the High Level Architecture (HLA) is one of the reference standard for Distributed Simulation. However, for the different organizations involved in the Space domain (e.g. NASA, ESA, Roscosmos, and JAXA) and their industrial partners, it is difficult to implement HLA simulators (called Federates) able to interact and interoperate in the context of a distributed HLA simulation (called Federation). The lack of a common FOM (Federation Object Model) for the Space domain is one of the main reasons that precludes a-priori interoperability between heterogeneous federates. To fill this lack a Product Development Group (PDG) has been recently activated in the Simulation Interoperability Standards Organization (SISO) with the aim to provide a Space Reference FOM (SRFOM) for international collaboration on Space systems simulations. Members of the PDG come from several countries and contribute experiences from projects within NASA, ESA and other organizations. Participants represent government, academia and industry. The paper presents an overview of the ongoing Space Reference FOM standardization initiative by focusing on the solution provided for managing the execution of an SRFOM-based Federation.

Moller, Bjorn↗

Real World Applications of AI/ML in Optimizing Airspace Operations

As National Airspace System (NAS) is going through the Digital Transformation journey, data science and analytics methods can significantly contribute to improving the traditional physics-based decision-making tools. The adoption of AI/ML methods will not only help accelerate Federal Aviation Administration (FAA)’s vision of Info-centric NAS but also contribute to the overall objective of sustainable aviation. AI/ML can improve the ground and airspace operations by enhancing the accuracy of current decision-making tools used by the airlines and the FAA to manage traffic on the ground and in the air. Huge amount of data that gets collected during a flight. AI/ML methods can extract information from this data and provide valuable insights to make better operational decisions. NASA has partnered with the FAA and commercial airlines such as American and Southwest Airlines on this effort and has successfully demonstrated the benefits of using ML in real world environment by reducing delays and optimizing ground operations at the US airports. In 2022 itself, NASA demonstrated real-world benefits (over 24K lbs. of fuel savings, over 76.6K lbs. CO2 emission savings, and several hours of delay savings) by deploying ML based prediction models to optimize ground operations at Dallas/Fort Worth International and Dallas Love Field Airports in Texas. These tools are being deployed on the cloud for broader deployment, adaptability, and scalability. NASA is developed a reference implementation of the cloud-based platform to significantly lower the bar to development and distribution of these digital services for aviation. In this talk, I will share information about the Digital Information Platform project, the novel AI/ML based approaches used for optimizing ground operations and the opportunities to partner with NASA on these demonstrations.

air traffic management↗

Reference Site Condition Datasets for Floating Wind Arrays in the United States

Floating offshore wind farm design is highly site-specific, requiring detailed information about the specific conditions of a project area for realistic design studies. Unfortunately, publicly available site condition data for potential floating offshore wind project sites in the United States is scarce. To support U.S. offshore wind research, we developed reference site condition datasets, including metocean and seabed information, for four potential floating wind project areas in the U.S.: Humboldt Bay, Morro Bay, the Gulf of Maine, and the Gulf of Mexico. These datasets were compiled using publicly available data. Our metocean analysis, covering wind, waves, and surface currents, utilized measurement data from 2000 to 2020. Sources included the National Renewable Energy Laboratory’s National Offshore Wind Dataset for wind data, National Data Buoy Center buoys for wave data, and the High Frequency Radar Network for surface currents. These data were integrated into hourly time series used to compute extreme return periods up to 500 years, monthly statistics, and joint probability clusters for fatigue analysis. Soil conditions were evaluated using the usSEABED database and bathymetry grids were interpolated from the NCEI Digital Elevation Model Global Mosaic. Further information on the datasets and how they were created can be found in: Biglu, M., M. Hall, E. Lozon, S. Housner. 2024. Reference Site Conditions for Floating Wind Arrays in the United States. Golden, CO: National Renewable Energy Laboratory (NREL). NREL/TP-5000-89897. The data are also available at: https://github.com/FloatingArrayDesign/SiteConditions The content of each dataset is as follows: _NOW23_wind.txt: Hourly NOW-23 wind data up to a height of 400 meter. _metocean_1hr.txt: Hourly time series including wind, wave, surface current and temperature data. _Summary.xlsx: Metocean data, including extreme values, joint probability distributions and monthly statistics. _usSEABED_soil.csv: Extract of the usSEABED database for this specific site. _bathymetry_200m.txt (and 500m, 1000m): Gridded seabed depth data.

16 TIDAL AND WAVE POWER↗

Angular-momentum projection in coupled-cluster theory: Structure of 34 Mg

Single- reference coupled-cluster theory is an accurate and affordable computational method for the nuclear many-body problem. For open-shell nuclei, the reference state typically breaks rotational invariance and angular momentum must be restored as a good quantum number. We perform angular-momentum projection after variation and employ the disentangled coupled-cluster formalism and a Hermitian approach. We compare our results with benchmarks for 8 Be and 20 Ne using a two-nucleon interaction from chiral effective field theory and for pf-shell nuclei within the traditional shell model. We compute the rotational band in the exotic nucleus 34 Mg and find agreement with data.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Studies of Front-End Electronics for High-Precision Timing Measurements with LGADs [Poster]

In Time-of-Arrival (ToA) measurements, simulations can be used to optimize precision detection and implementation methods of front-end electronics. The simulation tested in this project takes the response of a filter (in the s-domain) from a noisy input current signal from the detector, an LGAD (Low-Gain Avalanche Diode), and uses a threshold to determine the ToA value for the signal. Measuring the ToA values for a large sample of events and comparing them to a reference statistically produces the timing precision of the simulation. Here, the sub-algorithm to model LGAD events with piecewise linear (PWL) approximations (for more efficient Laplace transforms) was optimized. Using the Fourier Discrete Cosine Transform, 25 points could be selected to describe the primary behavior of the signal. Results showed that timing precision is on par with previous methods. We also found that the new algorithm is faster and equally consistent in producing accurate PWL approximations. Testi ng with larger samples is required to fully verify the new algorithm.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Geophysical and Environmental Monitoring Data, Lower Watershed, Teller Road Mile Marker 27, Seward Peninsula, Alaska, 2017-2019

This data set contains geophysical and environmental monitoring data acquired between September 2017 and 2019 at the lower Teller watershed, Seward Peninsula, Alaska. Geophysical data comprises processed resistivity data, acquired daily between Spring and Fall of 2018 and 2019, and a baseline measurement of Fall 2017. The environmental monitoring data comprises depth resolved, distributed soil moisture and soil temperature data. These measurements were obtained used Decagon 5TE sensors placed at 0.1 m, 0.2 m , 0.3 m, and 0.4 m depth. In addition, temperature data at 0.5 m, 1.0 m, and 1.5 m were acquired using Hobo temperature sensors. Data were collected to improve our understanding of the hydrological response of discontinuous permafrost systems, in particular focusing on multi-annual dynamics and short term disturbances, such as snowmelt or precipitation events. The electrical resistivity tomography (ERT) monitoring data are included as processed resistivity models, with model cells x dimension equal to the distance along the profile, and model z dimension being elevation. The start and end point of the transect are (UTM Zone 3N): E 454881.66 m, N 7178949.45 m, and E 454772.60, N 7178885.81. Locations of the soil moisture and temperature sensors are provided in the data package. This dataset is discussed in detail in the Uhlemann, S. et al 2021 paper listed in the references. This dataset includes one *.pdf user guide and 315 *.csv data files included within four zipped files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

Improving the AVHRR Long Term Data Record BRDF Correction

The Long Term Data Record (LTDR) project has the goal of developing a quality and consistent surface reflectance product from coarse resolution optical sensors. This paper focuses on the Advanced Very High Resolution Radiometer (AVHRR) part of the record, using the Moderate Resolution Imaging Spectrometer (MODIS) instrument as a reference. When a surface reflectance time series is acquired from satellites with variable observation geometry, the directional variation generates an apparent noise which can be corrected by modeling the bidirectional reflectance distribution function (BRDF). The VJB (Vermote, Justice and Bréon, 2009) method estimates a target’s BRDF shape using 5 years of observation and corrects for directional effects maintaining the high temporal resolution of the measurement using the instantaneous Normalized Difference Vegetation Index (NDVI). The method was originally established on MODIS data but its viability and optimization for AVHRR data have not been fully explored. In this study we analyze different approaches to find the most robust way of applying the VJB correction to AVHRR data, considering that high noise in the red band (B1) caused by atmospheric effect makes the VJB method unstable. Firstly, our results show that for coarse spatial resolution, where the vegetation dynamics of the target don’t change significantly, deriving BRDF parameters from 15+ years of observations reduces the average noise by up to 7% in the Near Infrared (NIR) band and 6% in the NDVI, in comparison to using 3-year windows. Secondly, we find that the VJB method can be modified for AVHRR data to improve the robustness of the correction parameters and decrease the noise by an extra 8% and 9% in the red and NIR bands with respect to using the classical VJB inversion. We do this by using the Stable method, which obtains the volumetric BRDF parameter (V) based on its NDVI dependency, and then obtains the geometric BRDF parameter (R) through the inversion of just one parameter.

LTDR↗

Building High-Energy Silicon-Containing Batteries Using Off-The-Shelf Materials

The technology of silicon anodes appears to be reaching maturity, with high-energy Si cells already in pilot-scale production. However, the performance of these systems can be difficult to replicate in academic settings, making it challenging to translate research findings into solutions that can be implemented by the battery industry. Part of this difficulty arises from the lack of access to engineered Si particles and anodes, as electrode formulations and the materials themselves have become valuable intellectual property for emerging companies. Here, we summarize the efforts by Argonne’s Cell Analysis, Modeling, and Prototyping (CAMP) Facility in developing Si-based prototypes made entirely from commercially available materials. We describe the many challenges we encountered when testing high-loading electrodes (>5 mAh cm −2 ) and discuss strategies to mitigate them. With the right electrode and electrolyte design, we show that our pouch cells containing ≥ 70 wt% SiO x can achieve 600–1,000 cycles at C/3 and meet projected energy targets of 700 Wh L −1 and 350 Wh kg −1 . These results provide a practical reference for research teams seeking to advance silicon-anode development using accessible materials.

25 ENERGY STORAGE↗