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At least 343 records · Page 19

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DOE OSTI2021

Eco-evolutionary optimality as a means to improve vegetation and land-surface models

Global vegetation and land-surface models embody interdisciplinary scientific understanding of the behaviour of plants and ecosystems, and are indispensable to project the impacts of environmental change on vegetation and the interactions between vegetation and climate. Furthermore, systematic errors and persistently large differences among carbon and water cycle projections by different models highlight the limitations of current process formulations. In this review, focusing on core plant functions in the terrestrial carbon and water cycles, we show how unifying hypotheses derived from eco-evolutionary optimality (EEO) principles can provide novel, parameter-sparse representations of plant and vegetation processes. We present case studies that demonstrate how EEO generates parsimonious representations of core, leaf-level processes that are individually testable and supported by evidence. EEO approaches to photosynthesis and primary production, dark respiration and stomatal behaviour are ripe for implementation in global models. EEO approaches to other important traits, including the leaf economics spectrum and applications of EEO at the community level are active research areas. Independently tested modules emerging from EEO studies could profitably be integrated into modelling frameworks that account for the multiple time scales on which plants and plant communities adjust to environmental change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Downwind control of oceanic air by land: the land wake and its sensitivity to CO 2

Oceans are well-known to be directly altered by global climate forcings such as greenhouse gas changes, but how oceans are indirectly influenced by land and its response to such forcings remains less explored. Here, we assess the present-day and projected future state of a little-explored feature of the climate system—a 'land wake' in relative humidity downwind of the east coast of North America, consisting of low-humidity continental air extending roughly 1000 km over the Atlantic ocean. The wake exists throughout the year, but is supported by high continental temperatures in summer and low continental moisture in winter. The wake is well represented in an ensemble of global climate models (GCMs), qualitatively matching reanalysis data. Under increasing atmospheric CO 2 , the land wake intensifies in GCM simulations through two pathways: the radiative effects of CO 2 on surface temperatures, and the biogeochemical effect of CO 2 on terrestrial vegetation. Vegetation responses to increased CO 2 alter the summer wake from Florida to Newfoundland, and both the radiative and biogeochemical effects of CO 2 drive reductions in coastal cloud cover. These changes illustrate the potential of rapidly changing terrestrial climate to influence coastal regions and the ocean environment downwind of continents through both light conditions and the energy balance of the surface ocean.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Hydrogen Education for a Decarbonized Global Economy (H 2 EDGE) (Final Technical Report)

The energy sector is undergoing rapid growth and transformation, creating urgent demand for a skilled workforce to support emerging technologies and resilient systems. Hydrogen is an emerging solution for “hard to abate” sectors, including heavy industry and transportation that also provides optionality for the electric system and enables long‑duration energy storage. As hydrogen scales from traditional industrial uses to new applications, success depends on knowledgeable engineers, technicians, planners, and operators safely deploying hydrogen technologies across the full value chain: production, delivery, storage, and end use. The H 2 EDGE initiative, funded by the U.S. Department of Energy’s Hydrogen and Fuel Cell Technologies Office from 2020 to 2025, was launched to prepare people for careers hydrogen and related technologies. Through its interactive approach, H 2 EDGE equipped stakeholders with knowledge and tools to build a reliable and sustainable energy future together. H 2 EDGE built a national network of academic and industry partners to deliver modular training, share open-access curricula, and engage diverse talent pipelines. The program leveraged EPRI’s extensive industry membership and expanded on the train-the-trainer model of the GridEd program to connect educators, employers, and community organizations across all regions of the U.S. New methods were introduced to more systematically map hydrogen competencies and assess curricula using traditional and AI-assisted approaches. Outcomes included delivery of professional short courses, developing university curriculum, sponsoring faculty and student projects, and engaging stakeholders through workshops, site tours, and webinars.

08 HYDROGEN↗

DOE OSTI2025

STEM Professional Development Program for Nuclear Security Science and Technology Consortium

This oral presentation captures the technical and developmental aspect of the program in support of UNLV. The goal of this project is to develop a steady pipeline of STEM educated professionals in area of national and international nuclear security. The goal is to train university students at NNSS laboratories in studies motivated by global nuclear security topics ranging from nuclear emergency response and management to physics experiments for stockpile stewardship program.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2026

Port Technical Assistance Program: A Proposed Initiative to Support U.S. Ports Through Energy Innovation

This document highlights the crucial importance of the maritime sector within the United States (U.S.) economy, serving as a key node for trade and global goods transportation. U.S. ports are currently grappling with challenges posed by rising shipping demands, the health impacts of diesel fuel reliance, and the technology adoptions of global trade partners due to increasing environmental regulations. This document proposes forming a technical assistance program, led by Pacific Northwest National Laboratory (PNNL), to help U.S. ports transition to sustainable energy solutions that not only improve environmental and community outcomes, but also enhance resilience to unexpected weather events and reduce pressure on local utilities. Coordinated by PNNL, this initiative would offer a web-based platform of consolidated resources and tools for comprehensive strategic planning and cost-benefit analysis. It also seeks to establish a collaborative network between ports and national laboratories to facilitate the sharing of best practices. The document suggests that optimizing resource allocation and providing tailored support could be achieved through strategic categorization of ports within this network, with relevant attributes and examples detailed in the report. The anticipated benefits of such a program could include increased efficiency and cost savings in port operations and the advancement of scientific innovation via alternative energy research. Also, it could enhance economic growth and competitiveness in international trade by enabling ports to meet shipping demands and develop resilient critical infrastructure through informed, long-term strategies.

33 ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2021

Mid-Holocene Antarctic sea-ice increase driven by marine ice sheet retreat

Abstract. Over recent decades Antarctic sea-ice extent has increased, alongside widespread ice shelf thinning and freshening of waters along the Antarctic margin. In contrast, Earth system models generally simulate a decrease in sea ice. Circulation of water masses beneath large-cavity ice shelves is not included in current Earth System models and may be a driver of this phenomena. We examine a Holocene sediment core off East Antarctica that records the Neoglacial transition, the last major baseline shift of Antarctic sea ice, and part of a late-Holocene global cooling trend. We provide a multi-proxy record of Holocene glacial meltwater input, sediment transport, and sea-ice variability. Our record, supported by high-resolution ocean modelling, shows that a rapid Antarctic sea-ice increase during the mid-Holocene (∼ 4.5 ka) occurred against a backdrop of increasing glacial meltwater input and gradual climate warming. We suggest that mid-Holocene ice shelf cavity expansion led to cooling of surface waters and sea-ice growth that slowed basal ice shelf melting. Incorporating this feedback mechanism into global climate models will be important for future projections of Antarctic changes.

58 GEOSCIENCES↗

DOE OSTI2021

Pyomo.GDP: an ecosystem for logic based modeling and optimization development

We present three core principles for engineering-oriented integrated modeling and optimization tool sets—intuitive modeling contexts, systematic computer-aided reformulations, and flexible solution strategies—and describe how new developments in Pyomo.GDP for Generalized Disjunctive Programming (GDP) advance this vision. We describe a new logical expression system implementation for Pyomo.GDP allowing for a more intuitive description of logical propositions. The logical expression system supports automated reformulation of these logical constraints to linear constraints. We also describe two new logic-based global optimization solver implementations built on Pyomo.GDP that exploit logical structure to avoid “zero-flow” numerical difficulties that arise in nonlinear network design problems when nodes or streams disappear. These new solvers also demonstrate the capability to link to external libraries for expanded functionality within an integrated implementation. We present these new solvers in the context of a flexible array of solution paths available to GDP models. Finally, we present results on a new library of GDP models demonstrating the value of multiple solution approaches.

42 ENGINEERING↗

DOE OSTI2021

Improved natural convection heat transfer correlations for reactor cavity cooling systems of high-temperature gas-cooled reactors: From computational fluid dynamics to Pronghorn

The Reactor Cavity Cooling System (RCCS) is a common reactor safety system in High Temperature Gas Cooled Reactors (HTGR) that removes heat from the Reactor Pressure Vessel (RPV) by radiation ($\sim 80\%$) and natural convection ($\sim 20\%$). For simulation of accident scenarios of HTGRs, intermediate fidelity and system codes models must be employed for limiting the models' execution time. While accurate quantification of the radiative heat transfer is available in these models, quantification of natural convection must rely on correlations of questionable accuracy for the Nusselt number. Commonly used correlations are based in experiments performed at low Rayleigh numbers and/or using isothermal walls in simplified geometries. Here, this work improves on the accuracy of natural convection heat transfer correlations in support for HTGR designs. These correlations include both local and average Nusselt numbers as a function of the global Rayleigh number, the local Rayleigh number, and the temperature profile at the hot wall of the RCCS. In the absence of dedicated experiments and the difficulty of performing high-fidelity simulations at realistic Rayleigh numbers, the data to fit the correlations are generated with Computational Fluid Dynamics (CFD) using Reynolds Averaged Navier-Stokes (RANS) models. First, a careful selection of the RANS turbulence model is performed by comparing the results obtained with different RANS turbulence models against high fidelity simulations of natural convection at $Ra \ 1 \times 10^{11}$ in a rectangular cavity. Next, the selected model is used to perform simulations of an HTGR cavity at different high Rayleigh numbers $\in [6.1 \times 10^{11},2.9 \times 10^{13}]$ to encompass several HTGR designs, assuming an isothermal RPV wall. The results obtained are used to fit a correlation for the average and space-varying Nusselt number as a function of the global and local Rayleigh numbers via a sparsity-promoting least-squares method. The selected RANS model is then used to perform simulations of a PBMR 400 HTGR cavity with the temperature profiles at the RPV wall obtained during a PLOFC transient. We use the results obtained to fit a temperature-dependent correction to the space-varying Nusselt number with the sparsity-promoting least-squares method. The results obtained in this work, enable system-level codes, such as Pronghorn, to perform higher-fidelity simulations of the heat exchange process in the RCCS while still maintaining a low computational cost.

42 ENGINEERING↗

DOE OSTI2025

WorkflowHub: a registry for computational workflows

The rising popularity of computational workflows is driven by the need for repetitive and scalable data processing, sharing of processing know-how, and transparent methods. As both combined records of analysis and descriptions of processing steps, workflows should be reproducible, reusable, adaptable, and available. Workflow sharing presents opportunities to reduce unnecessary reinvention, promote reuse, increase access to best practice analyses for non-experts, and increase productivity. In reality, workflows are scattered and difficult to find, in part due to the diversity of available workflow engines and ecosystems, and because workflow sharing is not yet part of research practice. WorkflowHub provides a unified registry for all computational workflows that links to community repositories, and supports both the workflow lifecycle and making workflows findable, accessible, interoperable, and reusable (FAIR). By interoperating with diverse platforms, services, and external registries, WorkflowHub adds value by supporting workflow sharing, explicitly assigning credit, enhancing FAIRness, and promoting workflows as scholarly artefacts. The registry has a global reach, with hundreds of research organisations involved, and more than 800 workflows registered.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Augmenting machine learning of energy landscapes with local structural information

We present a machine learning approach for accurately predicting formation energies of binary compounds in the context of crystal structure predictions. The success of any machine learning model depends significantly on the choice of representation used to encode the relevant physical information into machine-learnable data. We test different representation schemes based on partial radial and angular distribution functions (RDF+ADF) on Al–Ni and Cd–Te structures generated using our genetic algorithm for structure prediction. We observe a remarkable improvement in predictive accuracy upon transitioning from global to atom-centered representations, resulting in a threefold decrease in prediction errors. We show that a support vector regression model using a combination of atomic radial and angular distribution functions performs best at the formation energy prediction task, providing small root mean squared errors of 3.9 meV/atom and 10.9 meV/atom for Al–Ni and Cd–Te, respectively. We test the performance of our models against common traditional descriptors and find that RDF- and ADF-based representations significantly outperform many of those in the prediction of formation energies. The high accuracy of predictions makes our machine learning models great candidates for the exploration of energy landscapes.

Honrao, Shreyas J. (ORCID:0000000166155257)↗

DOE OSTI2024

Simulations of vertical displacement oscillatory modes and global Alfvén Eigenmodes in JET geometry

Vertical Displacement Oscillatory Modes (VDOM), with frequency in the Alfvén range, are natural modes of oscillation of magnetically confined laboratory plasmas with elongated cross-section. These axisymmetric modes arise from the interaction between the plasma current, which is in equilibrium with currents flowing in external coils, and perturbed currents induced on a nearby conducting wall. The restoring force exerted by these perturbed currents on the vertical motion of the plasma column leads to its oscillatory behavior. An analytic model for VDOM was proposed based on an idealized 'straight tokamak' equilibrium with uniform equilibrium current density. This article introduces the first numerical simulations of VDOM in a realistic JET tokamak configuration, using the extended-MHD code NIMROD and drawing comparisons with Global Alfvén Eigenmodes (GAE). The results show qualitative agreement with analytic predictions regarding mode frequency and radial structure, supporting the identification of VDOM as a fundamental oscillation mode in tokamak plasmas. VDOM and GAE are modeled in a representative JET discharge, where axisymmetric perturbations with toroidal mode number n = 0 driven unstable by fast ions were observed. The two modes are examined separately using a forced oscillator within the NIMROD code, which enables a comparison of their characteristics and helps identify the experimentally observed mode possibly as a GAE.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Layered patterns of active scalar fields in a two-dimensional magnetohydrodynamic system

Here, we observe the formation of staircase patterns in the magnetic potential (𝐴) in a weakly magnetized two-dimensional magnetohydrodynamic system driven by a forced, fluctuating vortex array. Layering occurs due to inhomogeneous mixing of 𝐴 by vortex cells. Magnetic Reynolds number (𝑅 𝑚 )–dependent quenching of the turbulent diffusion of 𝐴 by weak magnetic fields increases the disparity between the (short) cell circulation time and the (long) time for intercell transport of magnetic potential. Thus, magnetic fields strengthen transport barriers between cells and reinforce the staircase, relative to its passive scalar counterpart. The analysis reveals a feedback mechanism, which promotes staircase formation. Magnetic staircases persist in both the flux expulsion (𝑅 𝑚 ⁢𝑣$^2_𝐴$/𝑈$^2_0$<1) and vortex disruption (𝑅 𝑚 ⁢𝑣$^2_𝐴$/𝑈$^2_0$≥1) limits. In the latter case, residual vortex cells homogenize 𝐴. Global layering morphology is shown to be well characterized by staircase curvature. Stochastic forcing of magnetic potential can support magnetic staircases against resistive decay.

magnetohydrodynamics↗

DOE OSTI2021

Identifying Light-Duty Vehicle Travel from Large-Scale Multimodal Wearable GPS Data with Novelty Detection Algorithms

Identifying travel mode within travel survey data sets, especially light-duty vehicle (LDV) travel, is foundational, though nontrivial, to travel behavior analysis and fuel consumption estimation. Current travel mode detection approaches require well-sampled and balanced data sets with ground truth travel mode labels. They are rarely applied and validated on large-scale, real-world data sets, which may not satisfy the data requirements. This paper proposes an LDV travel mode detection model as a supplement to current travel mode detection methods, for the case when the training set is highly (and/or completely) unbalanced, to the extent that classical machine-learning approaches become difficult or impossible to deploy. The proposed model uses a novelty detection technique-one-class support vector machines (OCSVMs)-and a novel exhaustive feature extraction (EFE) technique on continuous time series data (i.e., Global Positioning System [GPS] speed profiles) for single-mode trip trajectories. Training and validation of the model are conducted on a large-scale, real-world data set. The proposed method accurately identifies LDV trips from a broad set of multimodal trips by leveraging a wealth of preexisting in-vehicle GPS travel data. Additional sensitivity analysis sheds light on the optimal training size, which will benefit applications limited by highly imbalanced data. The paper also discusses performance comparison with regular machine-learning approaches, the model's robustness, and the potential to extend the proposed model to multimodal prediction.

47 OTHER INSTRUMENTATION↗

DOE OSTI2020

Comparing Offshore Wind Energy Procurement and Project Revenue Sources Across U.S. States

The pace of offshore wind energy procurement in the United States has rapidly accelerated in recent years. U.S. states along the Atlantic Coast have set procurement goals for offshore wind energy to meet renewable portfolio standards and serve state policy needs. By the end of 2019, projects with a total capacity of 6.4 gigawatts (GW) had established long-term contracts (or equivalent regulatory requirements) with utility off-takers. The prices established in these contracts since 2017 have been well below expectations from many industry observers, prompting stakeholders to compare price levels across U.S. states and globally. However, comparing procurement prices across projects and jurisdictions is often challenging because of differences in project parameters, support regimes, supply chains, and the applicable tax and regulatory environment. These characteristics provide critical context for understanding project revenue streams, delivery obligations, and risk allocation, which need to be accounted for when comparing across different projects. In combination, variation in these characteristics between projects results in measurable differences in project costs and revenues and, consequently, in different offer bids. In this report, we systematically analyze offshore wind energy support regimes across U.S. states. Because offshore wind energy procurement prices from U.S. projects are often compared not only among states but also with European tenders, this report also provides an overview of support regimes and taxonomy used in European offshore wind markets. The content of this report was derived from a literature review, primarily regulatory filings and summary reports, and 16 interviews with leading industry experts from state agencies, energy sector consultancies, and law practices. The comparison between U.S. states focuses on several dimensions, including statutory authority, solicitation procedures, procurement goals and awards, and the structuring of physical and transactional delivery of energy services.

17 WIND ENERGY↗

DOE OSTI2024

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This work summarizes the U.S. Department of Energy National Energy Technology Laboratory's (NETL) recent life cycle analysis (LCA) study of the U.S. natural gas supply chain. In recent years, there has been growing interest in accurate accounting of methane emissions, with a specific focus on those from natural gas infrastructure, due to its much higher global warming potential as compared to carbon dioxide.

Khutal, Harshvardhan [NETL Site Support Contractor↗

DOE OSTI2023

Medium-Range Order Resists Deformation in Metallic Liquids and Glasses

In crystals, lattice defects, such as dislocations, control mechanical deformation. Similarly, it is widely believed that even in glasses and liquids some kinds of defects, strongly disordered regions, play a major role in deformation. To identify defects researchers focused on the nature of the short-range order (SRO) in the nearest neighbor cage of atoms. However, recent results by experiment, simulation and theory raise serious questions about this assumption. They suggest that the atomic medium-range order (MRO) provides resistance against flow at the atomic level. Because the MRO is a bulk property, it implies that defects play only a limited role. This new insight is supported by the density wave theory which shows that the MRO is driven by a top-down global force, rather than being a consequence of the SRO in the bottom-up manner, and the MRO provides stiffness to resist deformation. We briefly summarize the density wave theory, show that the MRO is related to ductility of metallic glasses, and discuss the implications on the role of the MRO in the atomic-level mechanism of deformation.

36 MATERIALS SCIENCE↗

DOE OSTI2021

Drop Size Distribution Variability in Central Argentina during RELAMPAGO-CACTI

The Remote sensing of Electrification, Lightning, And Meso-scale/micro-scale Processes with Adaptive Ground Observations (RELAMPAGO) and the Cloud, Aerosol, and Complex Terrain Interactions Experiment Proposal (CACTI) field campaigns provided an unprecedented thirteen-disdrometer dataset in Central Argentina during the Intensive (IOP, 15 November to 15 December 2018) and Extended (EOP, 15 October 2018 to 30 April 2019) Observational Periods. The drop size distribution (DSD) parameters and their variability were analyzed across the region of interest, which was divided into three subregions characterized by the differing proximity to the Sierras de Córdoba (SDC), in order to assess the impact of complex terrain on the DSD parameters. A rigorous quality control of the data was first performed. The frequency distributions of DSD-derived parameters were analyzed, including the normalized intercept parameter (logN w ), the mean volume diameter (D 0 ), the mean mass diameter (D m ), the shape parameter (μ), the liquid water content (LWC), and the rain rate (R). The region closest to the SDC presented higher values of logN w , lower D 0 , and higher μ, while the opposite occurred in the farthest region, i.e., the concentration of small drops decreased while the concentration of bigger drops increased with the distance to the east of the SDC. Furthermore, the region closest to the SDC showed a bimodal distribution of D 0 : the lower values of D 0 were associated with higher values of logN w and were found more frequently during the afternoon, while the higher D 0 were associated with lower logN w and occurred more frequently during the night. The data were analyzed in comparison to the statistical analysis of Dolan et al. 2018 and sorted according to the classification proposed in the cited study. The logN w -D 0 and LWC-D 0 two-dimensional distributions allowed further discussion around the applicability of other mid-latitude and global precipitation classification schemes (startiform/convection) in the region of interest. Finally, three precipitation case studies were analyzed with supporting polarimetric radar data in order to relate the DSD characteristics to the precipitation type and the microphysical processes involved in each case.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Nuclear Communication Certification - Summary

Given the increasing threat of climate change and demanding global energy needs, nuclear energy should be an active component of clean energy conversations. Yet, public acceptance and support is severly lacking. It is hypothesized that the culture of nuclear scientists and engineers steering away from associations with the industry plays an important role in the public's associations with nuclear power. A certification has been constructed with communication research and rhetorical theory to equip scientists and engineers with the tools and tactics to take on any type of public interaction, positive or otherwise. A five module program provides a holistic overview of science communication as appiled to nuclear in order to encourage nuclear experts to form relationships and built trust with the public, ultimately helping to rewrite the current nuclear narrative.

99 GENERAL AND MISCELLANEOUS↗