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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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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Final Technical Report for project entitled Highly Active, Durable, and Ultra-Low PGM NSTF Thin Film ORR Catalysts and Support

In this project, the objective was to develop new oxygen reduction reaction (ORR) electrocatalysts for proton exchange membrane fuel cells (PEMFCs) which could exceed all of the Department of Energy (DOE) 2020 targets listed in DE-FOA-0001224, Subtopic 1b, Table I. The expected outcome was development of one or more electrocatalysts which are substantially improved over the current state-of-the-art in terms of overall activity, durability, and cost, and are suitable for automotive traction and stationary fuel cell applications. This report summarizes this project’s progress towards meeting the stated objectives and includes a summary of key findings and conclusions. The development activities towards new highly active and durable thin film electrocatalysts has led to the discovery of several electrocatalysts which approached or exceeded several DOE 2020 targets for activity, durability, and performance in proton exchange membrane fuel cell (membrane electrode assemblies (MEAs). In this project, electrocatalyst development focused on systematic physical and electrochemical characterization of electrocatalyst activity, durability, and performance in MEAs as a function of electrocatalyst fabrication, compositional and structural variables. The project approach was to develop relationships between the catalyst functional responses (activity, durability and performance) with catalyst physical properties and catalyst fabrication methods. Additionally, the thin film catalysts were integrated onto the unique and durable 3M Nanostructured Thin Film (NSTF) support, consisting of arrays of self-assembled organic crystalline whiskers. The catalysts were evaluated against the project targets via extensive electrochemical characterization in MEA format at 3M, advanced structural and compositional microscopy at Oak Ridge National Laboratory (ORNL), and atomic structure analysis via XAFS at Argonne National Laboratory (ANL). The extensive electrochemical and physical characterization resulted in development of several trends which correlate the catalysts’ electrochemical properties to their physical properties, including composition, structure, and method of fabrication. The development was guided by density functional theory (DFT) modeling at Purdue University and kinetic Monte Carlo (kMC) modeling at Johns Hopkins University. The catalyst simulations provided key insights into the observed experimental activity and durability trends, and additionally were utilized to assess new electrocatalyst concepts prior to or coincident with physical catalyst development. This development has led to several electrocatalyst candidates with activity and durability which approach or exceed DOE targets. One class of catalysts, based on nm-scale thin layers of Pt on Ir, met or exceeded 6 of the 6 DOE targets the project addressed.

08 HYDROGEN↗
DOE OSTI2023

Fundamental Understanding of Dynamic Interfacial Phenomena in Solid State Batteries

Solid-state batteries (SSBs) are considered as one of the most promising battery technologies for resolving the intrinsic limitations of current lithium-ion batteries, such as safety and insufficient energy density. However, the degradation associated with interfaces in SSBs is still a critical issue leading to short cycle life. To get fundamental understanding of the failure mechanism of the interfaces, we first developed a comprehensive set of in situ diagnostic techniques combined with atomic/continuum modeling schemes to investigate and understand the coupled mechanical/chemical degradation associated with dynamic interfacial phenomena in SSBs. Specifically, we focused on in situ observations and characterizations of lithium plating-stripping processes, lithium dendrite formation, interphase formation, and the induced interfacial stresses, as well as the mechanical and electrochemical properties of interfaces and interphases. The final project report first gives an overview of the project background, objectives, technical approaches, and final deliverables for all the budget periods; then follows with a summary on main accomplishments based on main tasks. We particularly would like to highlight some capabilities developed from this project which can also be implemented to our advanced battery development.

25 ENERGY STORAGE↗
DOE OSTI2021

AGGREGATE: dAta-driven modelinG preservinG contRollable dEr for outaGe mAnagemenT and rEsiliency (Final Report)

The AGGREGATE project team successfully developed and validated various modules for outage management. Brief summaries of each module are provided to showcase their strength for outage management and restoration for a distribution system with a high penetration of connected distribution energy resources (DERs). In recent years, inverter-based DERs have been widely deployed in distribution system. A most of behind-the-meter (BTM) solar power generation is not visible to the utility. The data-driven DER and load estimation modules are using machine learning (ML) and artificial intelligence (AI) to manage this issue, which provides an opportunity for distribution system operators (DSOs) to operate systems and make decisions in real-time for a distribution system with a high penetration of DERs deployed. Also, the estimated DER and true load can be further leveraged in network aggregation and cold-load pick up estimation for reducing the computing complexity and providing for fast restoration. After load demand and DER power generations have been estimated, the information will support topology and state estimation (SE). The topology estimation module demonstrated the viability of mixed integer linear programming (MILP) formulation to estimate the most likely operational radial topology and outage sections using power flow measurements, historical/estimated load and DERs data and smart meter ping measurements. Formulation includes continuous (power flow, load and DERs data) and binary measurements (smart meter ping measurements) in a single formulation. Errors in continuous data and binary data are modeled as normal distribution and Bernoulli distribution, respectively. In the future distribution grid, the power injection from controllable DERs will be essential for efficient and resilient grid operation. However, determining the optimal DER injections and restoration actions is dependent on knowledge of the system states. State estimation (SE), already the cornerstone of transmission energy management systems, will become commonplace in distribution management systems as more measurements become available from deployment of automated metering infrastructure (AMI). Observability analysis is the first step in SE, as it determines the sufficiency of the available measurements for accurately estimating the current system states. A new type of pseudo-measurement called a Correlational Measurement (CM) is introduced in this module, to enhance the observability of the system to enable more accurate SE. CMs encapsulate knowledge of correlation between demand patterns for similar classes of loads as well as injection patterns for same-technology renewable DERs. During grid contingency scenarios, DERs have been traditionally disconnected, without any fault ride-through capabilities. However, with new regulations and better technology, it is feasible for these resources to contribute to the grid’s restoration after an adverse event and hence enhance resilience. The controllability module proposes a two-step restoration scheme for the power system restoration process by leveraging additional degrees of freedom in power electronics interfaced DERs for mitigating voltage problems. In a resilience mode without the utility system, the distribution grid relies on DERs to serve critical load. In such a severe event with multiple faults on the distribution feeders, actuation of various protective devices (PDs) divides the distribution system into electrical islands. The undetected actuated PDs due to fault current contributions from DERs can delay the restoration process, thereby reducing the system resilience. The Advanced Outage Management (AOM) and the Advanced Feeder Restoration (AFR) modules developed in this project provide improved system resilience with multiple DERs. AOM identifies the faulted sections and actuated PDs in a distribution system with DERs by incorporating smart meter data. The most credible outage scenario including fault locations, PD actuations, and fault indicator (FI) failures is identified by a set of binary integer linear programming incorporating hypotheses. The AFR module serves to restore a distribution system with available energy resources taking into consideration the availability of utility sources and DERs. By partitioning the system into islands, critical load will be served with the available generation resources within islands based on the solution of a MILP. When the utility systems become available, the optimal path will be determined by a spanning tree search algorithm that reconnects these islands back to substations and restores the remaining load. The transmission and distribution (T&D) co-simulation module was used to validate the effect of a control action performed on the distribution side assets as it propagates to the transmission side. This ensures that the control action performed results in a feasible operating point on both the transmission and the distribution system. In addition to validation, the team used the T&D co-simulation module to demonstrate how distribution system assets can be used to mitigate issues on the transmission system. Specifically, the team demonstrated that appropriate switching operations on the distribution side can alleviate the line overload condition on the transmission side without causing new operational constraint violations.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

High-Fluence Active Irradiation and Combined Effects Testing of Sapphire Optical Fiber Distributed Temperature Sensors - ASI Project Summary

The goal of this work is to investigate the performance of sapphire optical fiber temperature sensors and develop clad sapphire optical fibers for in-pile instrumentation. This work tests the distributed sensing performance of sapphire sensors by using optical backscatter reflectometry methods under combined radiation/temperature effects and high fluence. A series of irradiations will be completed to evaluate the effect of irradiation on sapphire optical fiber temperature sensors and to determine an operational limit for the sensors.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2023

Packaged Combined Heat and Power Technology Overview and Market Profile

Combined heat and power (CHP), sometimes referred to as cogeneration, is an efficient and clean approach to generating electric power and useful thermal energy onsite from a single fuel source, offering reliable and affordable energy services to businesses and institutions. Furthermore, CHP provides a cost effective opportunity to improve the environmental footprint and resilience of industrial and commercial facilities across the United States. CHP equipment can be custom-engineered or installed as a predesigned and assembled package. A packaged CHP system is a standardized, pre-engineered system that includes all equipment, piping, wiring, and ancillary components to deliver electricity and thermal energy to a host facility with minimal onsite engineering and design time. Packaged CHP systems can be shipped as single or multiple modules with standard interconnections (e.g., fuel; electrical; thermal—hot water, steam, and/or chilled water), which simplifies installation and reduces the costs associated with the project. Most containerized or single packaged CHP system offerings range from 10 kW to 3 MW in capacity. Packaged CHP systems are extending the operating, efficiency, and emissions benefits of CHP to nontraditional markets in commercial, institutional, multifamily, light manufacturing, government, and military applications. These markets tend to be served by smaller systems (less than 5 MW) that are conducive to pre-engineered packaging and/or modularization. Many of these sectors have limited CHP experience and technical resources to adequately evaluate, install, and maintain onsite CHP systems. The introduction of packaged CHP offerings from experienced CHP Packagers and Solution Providers has accelerated CHP adoption, lowered energy costs, reduced emissions, and strengthened energy resilience in these sectors. In 2019, the US Department of Energy (DOE) launched the Packaged CHP eCatalog to promote increased acceptance of efficient, cost-effective CHP in these applications. The Packaged CHP eCatalog is a web-based, searchable platform that hosts DOE-recognized packaged CHP systems with features designed to reduce economic and performance risks for designers, developers, owners, and facility operators interested in installing CHP. DOE established the Packaged CHP Accelerator at the same time to help launch and publicize the eCatalog, and to validate project performance, cost, and installation time of CHP packages across a variety of applications. Accelerator efforts documented installed cost reductions and installation time reductions of more than 20% for packaged CHP systems over 100 kW compared with custom-engineered systems. The Packaged CHP Accelerator and eCatalog established a peer-to-peer network connecting public and private sector partners including utilities, state energy offices, and energy efficiency program administrators interested in promoting cost-effective, efficient CHP systems, Packagers, and Solution Providers. Feedback from these partners, along with input from DOE’s CHP Technical Assistance Partnerships (CHP TAPs), was critical in understanding the current market for packaged CHP technologies, stimulating investment in these technologies, and guiding future directions for packaged CHP systems and their applications. This report provides background on packaged CHP systems, an overview of their benefits, a profile of current packaged CHP installations, and a summary of future market trends; this report is intended for facility owners, project developers, engineers, policymakers, and other stakeholders looking to increase the adoption of efficient, flexible, and resilient packaged CHP systems.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

MRCI Subtask 2.3: Developing Industrial Partnerships and Regional Technical Collaboration Final Technical Summary Report

Under the objective of regional data collection and helping accelerate deployment, MRCI collaborated with industrial stakeholders in their project planning, characterization, and analysis. Some examples of these collaborations are given below. The data and information shared by the industrial collaborations added to the regional CCS framework development and were incorporated into the overall datasets, while addressing any proprietary data requirements. Three examples of collaborative partnerships with industry that have provided geologic characterization data relevant and beneficial to the MRCI program are discussed below, including: the UIC Class II Injection Facility in Eastern Ohio, the Core Energy CO2-EOR (enhanced oil recovery) operation in Otsego County Michigan, and the Marquis ethanol plant in Hennepin Illinois.

CCS,CCUS,MRCI,Midwest USA,Technical Challenges,inj↗
DOE OSTI2021

Summary of Work on a Software Adapter for Project Requirements and MBSE

The National Reactor Innovation Center (NRIC) has funded the development of a digital pipeline to pull a project’s requirements from IBM’s Rational Dynamic Object Oriented Requirements System (DOORS), save them to Deep Lynx, then push them into the corresponding project in Innoslate. These utilities are accessible from a web browser and allow a project’s functional and business requirements to be tied to its tree of model-based systems engineering (MBSE) data.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2023

Summary Analysis of Different Offshore Wind Capacity Density Drivers in Proposed U.S. Projects and Impacts on Progress Towards State and Federal Deployment Targets

Understanding the density of offshore wind development - or the "capacity density" - is important for state and federal offshore wind planning efforts and to track progress towards policy goals. NREL has traditionally assumed a capacity density of 3 megawatts per square kilometer (MW/km2) when estimating the U.S. project pipeline (Musial et al. 2022), but capacity densities for existing European offshore wind farms ranged from 2-19 MW/km2 (Borrmann et al. 2018). We track the expected capacity densities of the proposed U.S. projects in the East Coast and make an analysis by state and by developer to identify what are the capacity density norms in the industry and whether the state in which the development efforts are taking place has some impact on capacity density. We also analyze the effects of the area occupied by station keeping systems on capacity density for lease areas dedicated to floating projects and provide a list of main capacity density drivers. This summary analysis sets a baseline to study how different capacity density drivers could impact the progress towards state and federal deployment targets. Given the currently delineated Renewable Energy Areas in the Outer Continental Shelf (OCS) and the basis from the summary analysis, we estimate the expected offshore wind deployment over time federally and by state and compare it to the state and federal deployment targets. The proposed analysis helps identify gaps and needs to meet state and federal targets, which provides sufficient information to propose strategic supply chain and policy planning with the objective of meeting deployment goals.

capacity density↗
DOE OSTI2023

Communication-Constrained Robust Control and Learning of Grid-Connected

The electric grid of things (EGoT) promises great potential for innovative grid services by tapping into vast load flexibility. However, the unique characteristics of EGoT, being a part of the cyber-physical electric power system, present both opportunities and challenges, especially concerning supply-demand balancing, stability, and communication constraints. Traditionally, centralized control was employed to ensure balance and stability in power systems. However, with the massive influx of EGoT devices, new strategies are needed to efficiently coordinate and control these distributed devices for optimal grid operations. While some studies have explored efficiency and economic models, there remains a gap in ensuring reliability under everyday operations and resilience during extreme conditions. Addressing this gap, this project develops the technology for an Energy Service Interface (ESI) that includes novel pricing, control, learning, and distributed optimization algorithms, which will enable utilities to recruit EGoT assets for crucial grid services such as load flexibility, voltage regulation, and situation-awareness. The key novelty of the proposed technology is the careful distribution of learning and control functions across utility and EGoT asset owners such that provably efficient and resilient grid operations are attained while respecting communication and information-exchange constraints. Specifically, the project team develops machine-learning enhanced load modeling methods to allow EGoT asset owners to learn their load capability and flexibility, and develops pricing-based and decentralized learning-based control so that asset owners can coordinate to meet system-wide demand-supply balance and reliability goals. For extreme situations involving high-impact, low-probability catastrophic events (termed the “black-sky” events), the team also develops (1) a “Feeder-Operating Center-on-a-Laptop” (FOCAL) software that can assist utility personnel in leveraging EGoT assets to accelerate the service recovery of damaged feeders, and (2) distributed optimization algorithms that can coordinate the operation points of EGoT devices under severe communication constraints. The proposed technology has been extensively tested and evaluated through simulations and on a testbed. In summary, as we transition into a more interconnected and digital power grid era, our project’s findings and developments offer a pivotal step toward guaranteeing both efficiency and resilience in the face of both everyday operations and rare “black-sky” events.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

PCMDI Metrics Package

The Program for Climate Model Diagnosis & Intercomparison (PCMDI) Metrics Package (PMP) is used to provide "quick-look" objective comparisons of Earth System Models (ESMs) with one another and available observations. The PMP provides a diverse suite of analysis utilities each of which produce summary statistics that gauge the consistency between climate model simulations and available observations. The primary application of the PMP is to evaluate simulations from the Coupled Model Intercomparison Project (CMIP). It can also be used to provide objective performance summaries during the model development process as well as selected research purposes.

Ullrich, PaulA [Lawrence Livermore National Labora↗
DOE OSTI2021

DOE SNF Packaging Demonstration Project: Worktable and Canister Loading Sleeve Design [Slides]

This presentation is a briefing for summer interns and others outside the project, to give them a summary of ongoing design activities. The DOE SNF Packaging Demonstration Project is an effort to develop and demonstrate the designs, technology, processes, and regulatory framework for packaging DOE-managed spent nuclear fuel (SNF) for road ready dry storage (RRDS). The project is to remotely load and seal two types of DOE-managed SNF from the CPP-603 facility into DOE Standard Canisters, place the sealed DOE Standard Canisters into commercial vendor over-canisters (equivalent to commercial MPCs), seal and place the over-canisters into commercial vendor storage overpacks, and place the storage system (over-canister and storage overpack) onto the CPP-2707 cask pad.

42 ENGINEERING↗
DOE OSTI2023

A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature: Supporting Data

This dataset was used to assess the potential of a Distributed Temperature Profiling System developed and presented in the article named "A Distributed Temperature Profiling System for Vertically and Laterally Dense Acquisition of Soil and Snow Temperature" and submitted to Cryosphere. There are three comma-delimited data files (.csv). Each of them contains snow or soil temperature with times (UTC) in the first column and temperature at various vertical distance from the ground surface (positive means in air/snow) or below the ground surface (negative means in soil). The measurements were acquired every 15 minutes. Data collected at the East River, Colorado site with two probes: 1) measuring air/snow temperature from 1.1 m above the ground surface to the ground surface (with 5 or 10 cm spacing between sensors) and 2) measuring soil temperature from the ground surface to 0.7 m depth (with 5 or 10 cm spacing between sensors). Data collected at the Teller road (mile 27) site near Nome, Alaska with one probe: measuring soil temperature from 5 cm above the ground surface to 1.05 m depth (with 5 or 10 cm spacing between sensors). Additional metadata included in *.csv and *.pdf files. NGEE Arctic Project Summary: 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↗
DOE OSTI2023

Design and License Application Development for TRISO-X (Final Scientific Technical Report)

This is the final progress report submitted by X-energy, LLC (XE) to the Department of Energy in support of cooperative agreement DE-NE0008745. This report provides a high-level summary of the work performed during the entire period of performance, running from August 24, 2018 – August 22, 2022. This span of time covers the original 3-year award and a one year no-cost extension. There were five tasks within this project: (1) project management, (2) systems engineering and studies, (3) TRISO-X Facility design, (4) facility license application development, and (5) support to application review. Detailed reporting during execution of the project was provided by a total of 16 quarterly reports, voluntary monthly update presentations, and annual summary presentations. Technical work products include 103 X-energy technical reports, 38 subcontractor (Centrus technical reports), 75 Nuclear Criticality Safety Evaluations/Calculation reports, and 272 miscellaneous design documents (e.g., Engineering Service Orders, Engineering Component Specifications, Procedures, Guidelines/Policies, Design and Interface Requirements documents, and Drawings). All 29 of the X Energy milestones/deliverables were met early or on time and are archived in the DOE Office of Nuclear Energy’s Program Information Control System: Nuclear Energy under Fiscal Year 2018, Work Breakdown Structure F.OA – Industry FOA FY 2018 Awards, F.03 – X-Energy TRISO-X Project. All other work products are available to DOE upon request.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗
DOE OSTI2024

Development of Windowless Optical Cell for In-Situ Molten Salt Characterization (Final CRADA Report)

This document serves as a summary report for the work conducted under CRADA 2021-21064 between Argonne National Laboratory and Xerion Advanced Battery Corp. As part of this project, Argonne and Xerion worked to develop a high-temperature version of the on-line optical analysis loop and evaluated its ability to facilitate Raman spectroscopy measurements on flowing molten salts relevant to Xerion’s process flowsheets. The main goals were to (1) achieve a geometrically smooth and stable meniscus at the molten salt and atmosphere interface by creating a slightly negative pressure in the flow channel at the aperture, (2) acquire Raman spectra of molten salt flowing across the aperture while maintaining consistent focus and protecting the optics from heat damage and direct contact with the molten salts, and (3) determine the impact of molten salt wicking and creep on the spectroscopy.

25 ENERGY STORAGE↗
DOE OSTI2024

Volumetric Soil Moisture Measurements at the Teller 27 Site, Seward Peninsula, Alaska, 2022-2023

The Teller 27 watershed on the Seward Peninsula, Alaska, has been well characterized by the NGEE Arctic project. The study site is underlain by discontinuous permafrost that is thawing as the climate warms. As a result, the site is experiencing a short-term wetting trend as a perched water table above the remaining permafrost provides plant available water during the growing season. Soil moisture patterns drive microbial activity and plant species compositions including plant density and height. This study aimed to understand how soil moisture patterns were influenced by tundra microtopography. To accomplish this, we placed a strategic network of soil moisture sensors in micro-highs, micro-lows, and control areas under different vegetation types within the Teller 27 watershed from summer of 2022 through fall of 2023. This data was used in conjunction with other soil data from the Teller 27 watershed to gain a more comprehensive understanding of soil moisture patterns in a rapidly thawing discontinuous permafrost region. This dataset includes six *.csv files: four of time series soil moisture data, one of field soil moisture data, and one of site conditions. The dataset also includes one *.kml file of the watershed and the soil moisture sensor sites as well as this user guide to provide details on data collection and processing methods. NGEE Arctic Project Summary 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↗
DOE OSTI2022

CO2 CH4 flux Air temperature Soil temperature and Soil moisture, Utqiagvik (Barrow), Alaska 2013 ver. 1

This dataset consists of field measurements of CO2 and CH4 flux, as well as soil properties made during 2013 in Areas A-D of Intensive Site 1 at the Next-Generation Ecosystem Experiments (NGEE) Arctic site near Barrow, Alaska. Included are i) measurements of CO2 and CH4 flux made from June to September (ii) Calculation of corresponding Gross Primary Productivity (GPP) and CH4 exchange (transparent minus opaque) between atmosphere and the ecosystem (ii) Measurements of Los Gatos Research (LGR) chamber air temperature made from June to September (ii) measurements of surface layer depth, type of surface layer, soil temperature and soil moisture from June to September. This data package contains two *.csv files and one *.pdf file. NGEE Arctic Project Summary: 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↗
DOE OSTI2021

The Importance of Freeze/Thaw Cycles on Lateral Transport in Ice-Wedge Polygons: Modeling Archive

This Modeling Archive is in support of an NGEE Arctic publication "The importance of freeze/thaw cycles on lateral transport in ice-wedge polygons". The dataset includes xml input/configuration files. These files are compatible with the ATS version 1.0 and higher. The mesh folder contains mesh files used for high-centered polygon (hcp) and low-centered polygon (lcp). The mesh files represent the transect of the polygonal tundra (Fig 1). Here we used two types of mesh with impermeable layer and without. The mesh with an impermeable layer corresponds to the synthetic permafrost (no freezeup case). The freeze up case uses mesh without impermeable layer to simulated frozen ground start at the same depth where the impermeable layer is for the no freezeup case. The meteorological data used drive the model saved in the "inputs" folder. The processed tracer flow rates are saved in the "tracer-flow-ratesCfolder. To plot figures 1 and 2, we used VisIt software. To plot all the flow rates, we used ipython notebook script. All required inputs are saved in "freezeup" and "no freezeup" folders. Each folder includes the corresponding "lcp" and "hcp" folders. The "freezeup" folder has also flat-centered polygon (fcp) case, low porosity "lpor", and low permeability "lper" cases. Included are *.xml, *.exo, *.h5, *pdf, *.ipynb, *.sh, *.py, and *.out files. NGEE Arctic Project Summary: 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↗