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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 937 records · Page 52
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

ELM model simulations of Plum Island Ecosystems LTER low marsh site 2018-2020

Model simulations using the Department of Energy's Energy Exascale Earth System Model (E3SM) land model (ELM) with improved capabilities to represent vegetation response to salinity and inundation. The simulations were conducted for a tidal salt marsh at Plum Island Ecosystems Long Term Ecological Research (LTER) site near Rowley, Massachusetts, USA; the site is a low marsh dominated by Spartina alterniflora. The model was forced with site-specific meteorology, salinity and tidal cycles from 2018-2020. Four sets of model simulations are included and described below:1. Parameterization of the salinity response function. These simulations tested different combinations of values for optimal salinity and salinity tolerance.2. Model evaluation. This comparison conducted simulations using the default model, the salinity function only, the submergence function only, and both the salinity and submergence functions. 3. Salinity scenarios. These simulations used the 2018 salinity input data varied by -5 to +10 ppt salinity.4. Water level scenarios. These simulations used the tide height varied by -10 to +50 cm. These simulations were used to demonstrate how the salinity and submergence functions better represent carbon uptake by tidal salt marshes.The data package includes netCDF files used as forcing files for tide height and salinity, one for each year 2018-2020 at observed salinity concentrations, and an additional three forcing files in which salinity concentrations were varied 5 ppt lower, 5 ppt higher, and 10 ppt higher than the measured 2018 time series. Also included are python scripts for creating forcing files, plain text parameter and command files for running simulations, model outputs in netCDF format, and python scripts for visualizing outputs. Code for the modified E3SM model is archived in Sulman et al 2023 at doi:10.15485/1991625. More detail about files is provided in the README.md file.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

EXCHANGE Campaign Degradation (ECD): Understanding Decomposition Dynamics Across Mid-Atlantic and Great Lakes Coastal Ecosystems

The EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Degradation Experiment (EXCHANGE-D) is an in situ experiment designed to assess organic matter decomposition rates across coastal terrestrial-aquatic interfaces (TAIs), from coastal uplands through transition zones to wetlands. Through a network of partner scientists and coastal sites, we are testing how environmental gradients shape decomposition and carbon dynamics across terrestrial-aquatic interfaces. Using standardized tea bag substrates deployed across a network of diverse coastal sites, we compare decomposition rates at different fresh- and salt-water TAIs to develop transferable knowledge that improves the representation of organic matter degradation in coastal ecosystem models. For more information, please see https://compass.pnnl.gov/FME/EXCHANGE. This is Version 1 of the data package, which includes: ecd_README.pdf flmd.csv dd.csv ecd_soil_weom_L2.csv ecd_soil_ph_conductivity_L2.csv ecd_soil_gwc_L2.csv ecd_soil_teabag_degradation_L2.csv ecd_readme.pdf

coastal soils↗
DOE OSTI2025

AmeriFlux US-GCE Georgia Coastal Ecosystems LTER Flux Tower

This is the AmeriFlux version of the carbon flux data for the site US-GCE Georgia Coastal Ecosystems LTER Flux Tower. Site Description - Spartina alterniflora-dominated salt marsh on the interior of Sapelo Island, a barrier island on the Georgia Coast. The GCE-LTER research program was initiated in September 2000, and the eddy covariance flux tower was deployed in the salt marsh in July 2013. Septmber - March has North-northeast winds has SURFACE_HOMOGENEITY of 270m.

Mishra, Deepak [University of Georgia]↗
DOE OSTI2025

kokkos-fft: A shared-memory FFT for the Kokkos ecosystem

kokkos-fft provides a unified, performance-portable interface for Fast Fourier Transforms (FFTs) within the Kokkos ecosystem (C. Trott et al., 2021). It seamlessly integrates with leading local FFT libraries including FFTW, cuFFT, rocFFT, and oneMKL. Designed for simplicity and efficiency, kokkos-fft offers a user experience akin to numpy.fft for in-place and out-of-place transforms, while leveraging the raw speed of vendor-optimized libraries. A demonstration solving 2D Hasegawa-Wakatani turbulence with the Fourier spectral method illustrates how kokkos-fft can deliver significant speedups over Python-based alternatives without drastically increasing code complexity, empowering researchers to perform high-performance FFTs simply and effectively.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

Modeled and Measured Ecosystem Respiration in Maize-Soybean Systems Over 10 Years

Crop residue is an abundant resource for the potential production of biofuels, but a better understanding of its use on net carbon emissions must be developed to mitigate climate change. This analysis combines two established crop growth models (Hybrid-Maize and Soysim) with a simple soil and crop residue respiration model to estimate daily ecosystem respiration (ERe) from maize and soybean; ERe was estimated to be the sum of CO 2 emissions from the oxidation of the growing crop, crop residue, and soil organic carbon (SOC). Model-estimated CO 2 fluxes from irrigated continuous maize and irrigated maize–soybean cropping systems in eastern Nebraska were compared with tower eddy covariance measurements of CO 2 fluxes from 2001 to 2010 from those fields. Modeled C emissions closely estimated measured seasonal patterns of CO 2 dynamics and measured daily ERe ( R 2 : 0.87, 0.84). Measured and modeled annual ERe values were also compared and better agreement was found in maize compared to soybean. As there are limited comparisons of modeled soil emissions with eddy covariance measured CO 2 fluxes, this study is important for the validation of these types of models and to support their potential use in quantifying emissions from crop residue for biofuels.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Final Report “Physiological, demographic, competitive and biogeochemical controls on the response of California’s ecosystems to environmental change”

The Loma Ridge Global Change Experiment is a large, well-replicated water and nitrogen input manipulation in the Santa Ana Mountain foothills that operated with DOE support from 2006 to 2015. The experiment considers the effects of increased and decreased water input and increased N input on two adjacent ecosystem types: California Annual Grassland (GL), which is dominated by exotic, Eurasian grasses and forbs, and Coastal Sage Shrubland (CSS), which is dominated by native, drought deciduous, perennial shrubs. The experiment proceeded in two phases: "Phase I Severe treatment", and "Phase II Return to ambient". Phase I showed very rapid change in species composition or ANPP with altered water or N input (low resistance), whereas Phase II showed a very rapid return to initial conditions once ambient water or N input were restored (high resilience). The severe drought treatment killed most of the shrubs in the dry plots and opened the canopy to herbaceous species, but this damage was ephemeral, and the shrubland community is recovering through the mechanisms and patterns that more typically mediate recovery from crown fire. The pattern of low resistance and high resilience carries implications for other "global change experiments", which have often also seen large and rapid treatment effects (low resistance), but have less frequently considered the subsequent recovery or resilience of the system.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Pajarito Aerosol Couplings to Ecosystems (PACE) Field Campaign Report

Laboratory (LANL) worked on the Pajarito Aerosol Couplings to Ecosystems (PACE) intensive operational period (IOP). PACE’s primary goal was to demonstrate routine Mobile Aerosol Observing System (MAOS) field operations and improve instrumental and operational performance. LANL operated the instruments efficiently and effectively with remote guidance by the instrument mentors. This was the first time a complex suite of instruments had been operated under the ARM model and it proved to be a very successful and cost-effective model to build upon.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Columbia Estuary Ecosystem Restoration Program: Restoration Design Challenges for Topographic Mounds, Channel Outlets, and Reed Canarygrass

The purpose of this study was to provide science-based information to practitioners and managers of restoration projects in the Columbia Estuary Ecosystem Restoration Program (CEERP) regarding aspects of restoration techniques that currently pose known challenges and uncertainties. The CEERP is a program of the Bonneville Power Administration (BPA) and the U.S. Army Corps of Engineers (Corps), Portland District, in collaboration with the National Marine Fisheries Service and five estuary sponsors implementing restoration. The estuary sponsors are Columbia Land Trust, Columbia River Estuary Study Taskforce, Cowlitz Tribe, Lower Columbia Estuary Partnership, and Washington Department of Fish and Wildlife. The scope of the research conducted during federal fiscal year 2015 included three aspects of hydrologic reconnection that were selected based on available scientific information and feedback from restoration practitioners during project reviews: the design of mounds (also called hummocks, peninsulas, or berms); the control of reed canarygrass (Phalaris arundinaceae); and aspects of channel network design related to habitat connectivity for juvenile salmonids.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2016

Fluxes of CO 2 , CH 4 , CO, BVOCs, NOx, and O 3 in an Old Growth Amazonian Forest: Ecosystem Processes, Carbon Cycle, Atmospheric Chemistry, and Feedbacks on Climate

A comprehensive, merged data set of trace gases (NO, NO 2 , CO 2 , CH 4 and O 3 ) along with has been tabulated and subjected to meticulous quality assurance and quality control (QA/QC). The merged data set is being submitted to the ARM website dedicated to the Green Ocean Experiment: https://www.arm.gov/research/campaigns/amf2014goamazon Analysis using the final data set is in progress to determine the magnitudes of the fluxes for CH 4 , H 2 O, CO 2 , O 3 , NO x , sensible and latent heat, momentum, and their seasonal variations. Here are summary statements, from the discussion above: Total NO fluxes were calculated following Keller et al., 1986. A vertical gradient is established in the mixing ratio of NO because it is emitted at the soil surface and mixed upward in the atmosphere (see above). Once in the atmosphere, the NO reacts rapidly with O 3 to produce NO 2 (NO + O 3 → NO 2 + O 2 ). Therefore, if the vertical profiles of the mixing ratios of NO and O 3 are known, the surface flux of NO may be determined. If any other reaction removes NO (e.g., deposition on leaves), FNO should estimate the lower limit to the NO flux from the soil in this forest. Our preliminary results show fluxes of NO averaged 133 x 10 9 molecules cm -2 s -1 , a factor of 4 higher than fluxes previously observed in white sand soils in the Amazon, and a factor of 3 to 14 higher than fluxes observed for yellow clay soils (Bakwin et al., 1990 and references therein). The soil in the km 67 site is predominately oxisol with pockets of sandy ultisols, both having low reduced nutrient contents, mostly due to efficient microorganism decomposition and acid leaching by rain water. Oxisols contain both oxidized and reduced forms of nitrogen, of which concentrations vary independently of leaching (Jordan et al., 1982), with most part of the cycling processes occurring in the top layers. Methane fluxes showed no statistical difference between 2015 wet and dry seasons, and the forest at this site appear to be a methane sink throughout the year. The vertical profiles suggest that if a methane source exists in this forest, it might be in the canopy. Next steps include modeling and analysis using the Master Chemical Mechanism (Jenkin et al., 1997; Saunders et al., 2003 (A/B); http://mcm.leeds.ac.uk/MCM/) and the Ecosystem Demography-2 (ED-2) model. A final manuscript with the results from this work is in preparation and expected to be submitted for publication within the next several months. Publications to date are listed below.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2016

Fechamento do balanço de energia em uma floresta tropical: contribuições da troca turbulenta e armazenamento de calor ecossistema [Energy balance closure in a tropical forest: contributions of turbulent exchange and ecosystem heat storage]

The surface energy balance is rarely closed using the common half-hourly averaging period for turbulent fluxes as eddies of greater characteristic time scales often provide a non-trivial contribution to energy exchange. Here, we briefly discuss previous efforts to improve surface energy balance closure of a tropical rainforest ecosystem – the K34 site - and describe how measurements from the GoAmazon campaign can be used to improve our understanding of energy flux and storage in tropical canopies. O balanço de energia da superfície raramente é fechado usando o período médio a cada meia hora comum para fluxos turbulentos como turbilhões de maior tempo característico escalas costumam oferecer uma contribuição não-trivial para troca de energia. Aqui, discutimos brevemente os esforços anteriores para melhorar o fechamento do balanço de energia da superfície de uma floresta tropical ecossistema tropical - o site K34 - e descrever como medições da campanha GoAmazon pode ser usado para melhorar a nossa compreensão do fluxo de energia e armazenamento em copas tropicais.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2017

XVIS: Visualization for the Extreme-Scale Scientific-Computation Ecosystem Final Scientific/Technical Report

The XVis project brings together the key elements of research to enable scientific discovery at extreme scale. Scientific computing will no longer be purely about how fast computations can be performed. Energy constraints, processor changes, and I/O limitations necessitate significant changes in both the software applications used in scientific computation and the ways in which scientists use them. Components for modeling, simulation, analysis, and visualization must work together in a computational ecosystem, rather than working independently as they have in the past. The XVis project brought together collaborators from predominant DOE projects for visualization on accelerators and combining their respective features into a new visualization toolkit called VTK-m.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2017

Understanding Litter Input Controls on Soil Organic Matter Turnover and Formation are Essential for Improving Carbon-Climate Feedback Predictions for Arctic, Tundra Ecosystems

The Arctic region stored vast amounts of carbon (C) in soils over thousands of years because decomposition has been limited by cold, wet conditions. Arctic soils now contain roughly as much C that is contained in all other soils across the globe combined. However, climate warming could unlock this oil C as decomposition accelerates and permafrost thaws. In addition to temperature-driven acceleration of decomposition, several additional processes could either counteract or augment warming-induced SOM losses. For example, increased plant growth under a warmer climate will increase organic matter inputs to soils, which could fuel further soil decomposition by microbes, but will also increase the production of new SOM. Whether Arctic ecosystems store or release carbon in the future depends in part on the balance between these two counteracting processes. By differentiating SOM decomposition and formation and understanding the drivers of these processes, we will better understand how these systems function. We did not find evidence of priming under current conditions, defined as an increase in the decomposition of native SOM stocks. This suggests that decomposition is unlikely to be further accelerated through this mechanism. We did find that decomposition of native SOM did occur when nitrogen was added to these soils, suggesting that nitrogen limits decomposition in these systems. Our results highlight the resilience and extraordinary C storage capacity of these soils, and suggest shrub expansion may partially mitigate C losses from decomposition of old SOM as Arctic soils warm.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2015

Building Virtual Ecosystems: Computational Challenges for Mechanistic Modeling of Terrestrial Environments Workshop, Germantown, Maryland, March 26–27, 2014

The mission of the Climate and Environmental Sciences Division of the Office of Biological and Environmental Research (BER) within the U.S. Department of Energy’s (DOE) Office of Science is “to advance a robust, predictive understanding of Earth’s climate and environmental systems and to inform the development of sustainable solutions to the nation’s energy and environmental challenges.” This formidable challenge requires quantification of stocks and controls on states, fluxes, and residence times of water, carbon, and other key elements through all components of the terrestrial system. These components include vegetation, soils, the deep vadose zone, groundwater, and surface water. To achieve this level of predictive understanding, a new generation of multiscale, multiphysics models is needed for terrestrial systems—models that incorporate process couplings and feedbacks between various “pools” (i.e., vegetation, soils, subsurface aquifers, and surface waters) across wide ranges of spatial and temporal scales. To explore the potential of a new generation of multiscale, multiphysics models for revolutionizing the understanding of terrestrial ecosystem dynamics, BER held the Computational Challenges for Mechanistic Modeling of Terrestrial Environments workshop on March 26–27, 2014, in Germantown, Maryland. The workshop brought together 29 researchers with diverse expertise, including hydrologists, environmental scientists, ecologists, microbiologists, plant scientists, and computational scientists. Through a combination of invited talks, breakout sessions, and report-back discussions, workshop attendees identified challenges and research opportunities needed to develop a more seamless and continuous framework for mechanistic modeling of terrestrial environments extending from the bedrock to the atmospheric boundary layer and from single-plant systems to fields of crops to watersheds and river basins.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Grassland Ecosystem Management Plan for the Oak Ridge Reservation

Land managers at the Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) in East Tennessee are restoring native warm-season grasses and wildflowers to various sites across the Oak Ridge Reservation (ORR). Some of the numerous benefits to planting native grasses and forbs include improved habitat quality for wildlife, improved aesthetic values, and lower long-term maintenance costs. Native grassland restorations also help meet the goals of two recent presidential memorandums: “Incorporating Ecosystem Services into Federal Decision Making” and “Creating a Federal Strategy to Promote the Health of Honey Bees and Other Pollinators.”

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Deep learning techniques to disentangle water use efficiency, climate change, and carbon sequestration across ecosystem scales

Focal Areas: We plan to use machine learning (ML) to disentangle the impact of climate change on plant water use efficiency (WUE) across the leaf level, structured canopy, and community ecosystem scales. Due to the complex behavior of modeling plant WUE’s connection to carbon storage (and hidden co-varying interactions) we suggest that physics-based deep learning must be utilized. The second topic we propose is, based on a better understanding of WUE response to climate change, there is a need to predict how WUE will limit or enhance the recycling of water from transpiration by vegetation back to the land surface worldwide, and thus impact water storage capacity (i.e., natural and reservoirs), using machine learning optimization techniques such as genetic algorithms.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Sandia National Laboratories Ecosystem for Open Science: Metadata Schema v0.2 Description.

The Ecosystem for Open Science (eOS) initiative was established in 2019. Its objective is improving openness and sharing of data and information across Defense Nuclear Nonproliferation (DNN) Research and Development (R&D) activities. To support this initiative, the eOS team at Sandia National Laboratories (SNL) developed metadata and data standards and proposed a machine-readable metadata schema. The nuclear explosion monitoring field was selected as a focus area due to its the wide range of pertinent phenomenologies.We developed the DCAT-eOS-AP metadata schema extending the Data Catalog Vocabulary version 2 (DCATv2) standard using an application profile (AP), to fit the needs of multi-disciplinary NA-22 projects. The DCAT-eOS-AP metadata schema describes data at different levels of granularity ranging from general descriptions to more domain-specific granular metadata. Its implementation and serialization is flexible with the ability to include new file or data types. Thus, it will scale with the ever-increasing data management needs of government research. Due to the multitude of phenomenologies represented in the DCAT-eOS-AP schema, we anticipate that it will be easily extensible to various projects across many DOE mission areas. This document describes data management challenges faced within the DNN R&D portfolio and provides insight on how metadata and data standards/guidelines combined with a comprehensive metadata schema can add value to programs throughout the Department of Energy (DOE). It reviews the importance of metadata standards, FAIR (Findability, Accessibility, Interoperability, and Reusability) data principles, and metadata schemas. Additionally, it summarizes input from subject matter experts (SME) at SNL and other National Laboratories that resulted in metadata and data standards/guidelines encompassing domains relevant to NA-22 projects. Finally, we discuss the DCAT-eOS-AP metadata development. Implementation recommendations and future development directions are included for those keen on adopting the DCAT-eOS-AP metadata schema.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2021

The Highly Integrated Vehicle Ecosystem (HIVE): A Platform for Managing the Operations of On-Demand Vehicle Fleets

This paper introduces the Highly Integrated Vehicle Ecosystem (HIVE), a transportation modeling tool developed by within the Center for Integrated Mobility Sciences (CIMS) group at the National Renewable Energy Laboratory (NREL). HIVE is an agent-based supply/demand model for Mobility on Demand (MoD) which mixes agent-based modeling and centralized dispatch for automated and human-driven fleets and ride hail passengers. Research questions using HIVE span multiple categories, including intelligent fleet planning (assessing fleet, battery, and infrastructure investment decisions), intelligent fleet control (charge management, vehicle dispatching) and strategic business model decision-making (depot-based full-time drivers versus gig-based drivers, human-driven versus automated). The components of the HIVE model are explained and then HIVE is demonstrated in a case study using demand data from the New York City Taxi & Limousine Commission data set.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2021

Position Papers for the ASCR Workshop on Cybersecurity and Privacy for Scientific Computing Ecosystems

At the request of the Department of Energy's (DOE) Office of Advanced Scientific Computing Research (ASCR), this program committee has been tasked with organizing a workshop to identify basic research needs in cybersecurity and privacy to better support DOE's science and energy mission. As part of the process, the program committee is soliciting community input in the form of position papers to help identify significant use cases, facility issues, and other barriers to enabling verifiably trustworthy computational science while preserving data confidentiality as appropriate for scientific workflows of interest to DOE. The program committee will review these position papers and based on the fit of their area of expertise and interest, selected contributors will have the opportunity to participate in the workshop currently planned as a virtual event November 3-5th, 2021. The thrust areas that will be explored by this workshop are the following: (1) Algorithms for secure, scalable, privacy-enhancing technologies and frameworks, including: Federated AI/ML, Differential privacy, Randomized algorithms, Adversarial modeling & simulation, Graph algorithms, and Formal methods; (2) Platforms to support the entire scientific-computing ecosystem, including edge computing for large-scale experiments, focusing on heterogeneous systems and distributed systems, including: Heterogeneous computing systems, Distributed computing systems, and Secure data architectures; and (3) Data workflows to allow agile use of data while preserving integrity and privacy, making the important properties verifiable either at runtime or post-computation, including: Integrity and provenance and Data management infrastructure. Topics that are out-of-scope for the workshop include discussing specific proposed solutions or areas that are clearly out of DOE's fundamental and applied-sciences mission scope, e.g., cryptography, enterprise security, and general-operations technology.

97 MATHEMATICS AND COMPUTING↗