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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 91 records · Page 5

A Model of Large Scale Electrochemical Direct Ocean Capture Under Variable Power

Since limiting warming to 1.5 degrees C by 2100 will not only require an energy transition but also billions of tons of carbon dioxide (CO2) removal per year, it is essential to expand these efforts. This can be done offshore via electrochemical direct ocean capture (eChem DOC) which extracts CO2 from seawater that can later be stored underground or converted to products. Deployments of eChem DOC will be powered by renewable energy and therefore need to function with variable power inputs. This project aims to support future large-scale deployments by developing a model of eChem DOC operation, informed by industry and literature, and assessing its performance under variable power and varying designs. Initial analysis suggests that discretizing the eChem system has a higher impact on increasing overall capture than storing the chemical solutions to continue capture during periods of lower power availability, but this is likely situation dependent. Future work will use more realistic power profiles.

direct ocean capture↗

The Intrinsic 150‐Day Periodicity of the Southern Hemisphere Extratropical Large‐Scale Atmospheric Circulation

Abstract The variability of the Southern Hemisphere (SH) extratropical large‐scale circulation is dominated by the Southern Annular Mode (SAM), whose timescale is extensively used as a key metric in evaluating state‐of‐the‐art climate models. Past observational and theoretical studies suggest that the SAM lacks any internally generated (intrinsic) periodicity. Here, we show, using observations and a climate model hierarchy, that the SAM has an intrinsic 150‐day periodicity. This periodicity is robustly detectable in the power spectra and principal oscillation patterns (aka dynamical mode decomposition) of the zonal‐mean circulation, and in hemispheric‐scale precipitation and ocean surface wind stress. The 150‐day period is consistent with the predictions of a new reduced‐order model for the SAM, which suggests that this periodicity is associated with a complex interaction of turbulent eddies and zonal wind anomalies, as the latter propagate from low to high latitudes. These findings present a rare example of periodic oscillations arising from the internal dynamics of the extratropical turbulent circulations. Based on these findings, we further propose a new metric for evaluating climate models, and show that some of the previously reported shortcomings and improvements in simulating SAM's variability connect to the models' ability in reproducing this periodicity. We argue that this periodicity should be considered in evaluating climate models and understanding the past, current, and projected Southern Hemisphere climate variability.

54 ENVIRONMENTAL SCIENCES↗

Antarctic shelf ocean warming and sea ice melt affected by projected El Niño changes

Antarctic shelf ocean warming affects melt of ice shelf/sheets and sea ice but projected changes vary vastly across climate models. A projected increase in El Niño variability has been found to slow future mid-latitude Southern Ocean warming but how this impacts the Antarctic shelf ocean is unknown. Here we show that a projected increase in El Niño variability accelerates Antarctic shelf ocean warming, hastening ice shelf/sheet melt but slowing sea ice reduction.

54 ENVIRONMENTAL SCIENCES↗

Microgrid-Integrated Solar-Storage Technology (MISST)

Microgrid-Integrated Solar-Storage Technology (MISST) project addresses availability and variability issues inherent in the solar photovoltaic (PV) technology by utilizing smart inverters for solar PV/battery storage and working synergistically with other components within a microgrid community. A key contribution of this project to the state-of-the-art is the practical implementation of seamless and coordinated control between the previously developed and DOE-funded Microgrid Master Controller (MMC) and the MISST controller, the latter is a dedicated solar-storage controller to manage high penetration of solar PV and energy storage systems.

14 SOLAR ENERGY↗

Annual Scientific Focus Area Report for the Energy Exascale Earth System Model Project: Phase II

The project's long-term goal is to assert and maintain an international scientific leadership position in the development of Earth system models that address the grand challenge of actionable predictions of Earth system variability and change, with an emphasis on the most critical scientific questions facing the nation and DOE. The grand challenge will be addressed by overcoming three major limitations: Pushing the high-resolution frontier of Earth system modeling through a combination of strategic model development and computational advances targeting exascale computers and beyond. Bridging the gap in scales and processes by developing a new class of models that couple the natural, managed, and man-made systems across scales to address energy sector vulnerability to variability and change. The project will achieve its goal through four intersecting project elements: A series of prediction and simulation experiments addressing scientific questions and mission needs; A well-documented and tested, continuously advancing, evolving, and improving system of model codes that comprise the E3SM Earth system model; The ability to use effectively leading (and “bleeding”) edge computational facilities soon after their deployment at DOE national laboratories; and An infrastructure to support code development, hypothesis testing, simulation execution, and analysis of results. To achieve the Grand Challenge of actionable Earth system predictions to address the most critical scientific questions facing our nation and DOE, the E3SM project defined its strategy in a fifteen-year roadmap with four intersecting project elements: A series of prediction and simulation experiments addressing scientific questions and mission needs; A well-documented and tested, continuously advancing, evolving, and improving system of model codes that comprise the E3SM Earth system model ; The ability to use effectively leading (and “bleeding”) edge computational facilities soon after their deployment at DOE national laboratories; and An infrastructure to support code development, hypothesis testing, simulation execution, and analysis of results. Figure 1 depicts the E3SM Project Roadmap, showing the relationships among the first three major project elements: the simulations, the modeling system to perform those simulations, and the machines on which they will be executed. Unlike the other three elements that have distinct but overlapping phases, the fourth element, the infrastructure, will evolve continuously based on the requirements imposed by project needs.

54 ENVIRONMENTAL SCIENCES↗

Enhancing integrated analysis of national and global goal pursuit by endogenizing economic productivity

Analysis with integrated assessment models (IAMs) and multisector dynamics models (MSDs) of global and national challenges and opportunities, including pursuit of Sustainable Development Goals (SDGs), requires projections of economic growth. In turn, the pursuit of multiple interacting goals affects economic productivity and growth, generating complex feedback loops among actions and objectives. Yet, most analysis uses either exogenous projections of productivity and growth or specifications endogenously enriched with a very small set of drivers. Extending endogenous treatment of productivity to represent two-way interactions with a significant set of goal-related variables can considerably enhance analysis. Among such variables incorporated in this project are aspects of human development (e.g., education, health, poverty reduction), socio-political change (e.g., governance capacity and quality), and infrastructure (e.g. water and sanitation and modern energy access), all in conditional interaction with underlying technological advance and economic convergence among countries. Using extensive datasets across countries and time, this project broadly endogenizes total factor productivity (TFP) within a large-scale, multi-issue IAM, the International Futures (IFs) model system. We demonstrate the utility of the resultant open system via comparison of new TFP projections with those produced for Shared Socioeconomic Pathways (SSP) scenarios, via integrated analysis of economic growth potential, and via multi-scenario analysis of progress toward the SDGs. We find that the integrated system can reproduce existing SSP projections, help anticipate differential economic progress across countries, and facilitate extended, integrated analysis of trade-offs and synergies in pursuit of the SDGs.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Future projections of wind patterns in California with the variable-resolution CESM: a clustering analysis approach

Wind energy production is expected to be affected by shifts in wind patterns that will accompany climate change. However, many questions remain on the magnitude and character of this impact, especially on regional scales. In this study, clustering is used to group and analyze large-scale wind patterns in California using model simulations from the variable-resolution Community Earth System Model (VR-CESM). Specifically, simulations have been produced that cover historical (1980–2000), mid-century (2030–2050), and end-of-century (2080–2100) time periods. Once clustered, observed changes to wind patterns can be analyzed in terms of both the change in frequency of those clusters and changes to winds within-clusters. Statistically significant capacity factors changes have been found at all five wind plant sites. Further, decomposition of the capacity factor changes into frequency changes and within-cluster changes enables a better understanding of their drivers. A further examination of the synoptic-scale fields associated with each cluster then provides a better understanding of how changes to large-scale meteorological fields are important for driving changes in localized wind speeds.

17 WIND ENERGY↗

Intrinsic Century-Scale Variability in Tropical Pacific Sea Surface Temperatures and Their Influence on Western US Hydroclimate

Hydroclimate variability of the southwest United States (SWUS) is influenced by the tropical Pacific Ocean, particularly through the teleconnection to El Nino/Southern Oscillation (ENSO), which is expected to be altered by climate change. Natural variability in this teleconnection has not been robustly quantified, complicating the detection of anthropogenic climate change. Here, we use a linear inverse model (LIM) to quantify natural variability in the ENSO-SWUS teleconnection. The LIM yields realistic teleconnection patterns with century-scale variability comparable to simulations from the Last Millennium Ensemble project and the Climate Model Intercomparison Project Phases 5 and 6. The variability quantified by the LIM illuminates two aspects of our understanding of ENSO and its impacts: the inherent statistics of the observable system can produce century-long periods with a wide range of correlations to SWUS hydroclimate, including nonsignificant correlations, and thus that detecting changes in ENSO-related hydroclimate variability is challenging in a changing climate.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Study on Closely Related Citrus CMMs based on Chemometrics and Prediction of Components-Targets-Diseases Network by Ingenuity Pathway Analysis

As the representatives of closely related Chinese medicinal materials (CMMs) originated from Rutaceae family, Aurantii fructus immaturus (AFI), Aurantii fructus (AF), Citri reticulatae pericarpium viride (CRPV), and Citri reticulatae pericarpium (CRP) have better functions in regulating qi and promoting gastrointestinal motility. However, differences in the quality of closely related Citrus CMMs have not yet been revealed until now. Herein, this study focused on the systematic differentiation and in-depth understanding of closely related Citrus CMMs by a strategy integrating chemometrics and network pharmacology. Determined by ultra performance liquid chromatography, the content of nine flavonoids showed obvious fluctuations in the decoction pieces from different species (Citrus aurantium Linnaeus and Citrus reticulate Blanco) with decreasing levels in the samples of ripe fruits. Decoction pieces from the different species and ripening stages were well distinguished by orthogonal projection to latent structure-discriminate analysis (OPLS-DA) and cluster analysis. As a result, four active components including narirutin, naringenin, hesperidin, and 3,5,6,7,8,3′,4′-heptemthoxyflavone were filtered out by variable importance for the projection (VIP) value (VIP > 1.0), which were regarded as chemotaxonomic markers. Furthermore, a components-targets-diseases network was constructed via ingenuity pathway analysis (IPA), and the correlations were predicted between four chemotaxonomic markers, 223 targets, and three diseases including colitis, breast cancer, and colorectal cancer. The obtained results will be of great significance for identifying closely related Citrus CMMs and conduce to improving the resource utilization of CMMs.

Mu, Qixuan↗

Customer outcomes in Pay-As-You-Save programs

We review the energy and financial outcomes of households participating in several programs based on successive versions of the Pay As You Save¯ (PAYS¯) system. PAYS¯ programs offer non-debt financing for energy efficiency (and sometimes other technologies) in residential buildings through a tariff attached to the home’s utility meter, designed to be offset by project savings. We find that the five programs we study generally serve customers living in zip codes with levels of income and education below the national average and unemployment rates above the national average, demonstrating their potential to improve equity in energy efficiency adoption. Using weather-normalized analysis of energy consumption data, we show that most customers of Midwest Energy’s program reduce annual electricity and gas consumption, averaging 15% and 26% reductions respectively. Changes in energy consumption calculated using this method represent a combination of project effects and changes in occupant behavior. These results are similar to existing analyses of PAYS¯ programs in North Carolina, Arkansas, and Tennessee. About half of participating Midwest households generate sufficient energy cost savings to cover their monthly tariff. Various factors, including changes in occupant behavior, program error, causes independent of the customer or program, or some combination thereof may explain lower-than-expected cost reductions in some projects. Given the inherent variability in annual household electricity consumption, we feel these programs are enabling energy efficiency improvements and their attendant co-benefits, including occupant health and comfort and reduced carbon emissions, while reasonably balancing energy savings and tariff costs. Pairing PAYS¯ with additional financial assistance, as well as promoting cost-effective measures such as air and duct sealing, could further broaden program participation by enabling additional projects to meet PAYS¯ program eligibility rules.

Deason, Jeff↗

Estimated capital costs of fish exclusion technologies for hydropower facilities

Hydropower is a reliable source of renewable energy, and its future expansion is likely to be in the form of either smaller new stream development (NSD) projects or powering existing non-powered dams. Thresholds for entrainment risk to fish and the requirements for fish exclusion at hydropower facilities often differ depending on the species involved, the characteristics of the facility, and the goals of stakeholders, but little quantitative information is present within the literature regarding the specific costs of fish exclusion measures. Cost data associated with protection, mitigation, and enhancement (PM&E) measures related to positive barrier screening were identified using keyword searches of an existing environmental mitigation cost data set and manual extraction from regulatory licensing documents available in the Federal Energy Regulatory Commission (FERC) eLibrary. This approach yielded a total of 50 p.m.&E mitigation measures with estimated capital construction costs pertaining to positive barrier screens and represented <10% of the 171 total FERC project dockets available in the data set. These data were highly skewed toward conventional relicensing projects, as <7% were associated with NSD projects. Results indicate highly variable costs are associated with fish screening, with flow-normalized costs one to two orders of magnitude higher for screening with the highest exclusion capability (≤0.09 in. spacing) compared with coarser screening (1–2 in.). These data provide an initial baseline for estimating exclusion costs for hydropower development and may help developers consider options for more fish-friendly generation technologies, though gaps remain relating to a lack of data, particularly for NSD projects.

13 HYDRO ENERGY↗

Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw: Modeling Archive

This Modeling Archive is in support of a NGEE Arctic publication in review "Drying of tundra landscapes will limit subsidence-induced acceleration of permafrost thaw". The study used a cryohydrology model to assess the potential risk of abrupt permafrost thaw triggered by melting ground ice, a key open question associated with permafrost response to a warming Arctic. The spatially resolved simulations are for a small catchment 465 ice-wedge polygons in polygonal tundra near Utqiagvik, Alaska in the high-emissions RCP8.5 climate scenario. The simulations are compared to runoff, evapotranspiration and subsidence in the current climate and agree well. The study used the ATS code configured as an intermediate-scale cryohydrology model (Advanced Terrestrial Simulator, Version v2). The archive includes input files for spinup (1985 to 2005) and projections (2006 to 2100 - the manuscript reports 2006 to 2098). Three of the projections include the effects of subsidence and microtopography change with different depth profiles of ice content corresponding to the median, 20th percentile and 80th percentile. The fourth projection has subsidence turnoff and uses the reference case (median) ice content. Spatially averaged or aggregated output variables are included for the projections. Selected checkpoint files for the projections and postprocessing scripts are also included. Files included are *.xml; *.h5; *.exo; *.py; *.sh, *. nb, mesh files, and one file in the original Excel format plus *.csv and *.pdf to conserve formatting contained in the original file. 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↗

Partitioning uncertainty in projections of Arctic sea ice

Abstract Improved knowledge of the contributing sources of uncertainty in projections of Arctic sea ice over the 21st century is essential for evaluating impacts of a changing Arctic environment. Here, we consider the role of internal variability, model structure and emissions scenario in projections of Arctic sea-ice area (SIA) by using six single model initial-condition large ensembles and a suite of models participating in Phase 5 of the Coupled Model Intercomparison Project. For projections of September Arctic SIA change, internal variability accounts for as much as 40%–60% of the total uncertainty in the next decade, while emissions scenario dominates uncertainty toward the end of the century. Model structure accounts for 60%–70% of the total uncertainty by mid-century and declines to 30% at the end of the 21st century in the summer months. For projections of wintertime Arctic SIA change, internal variability contributes as much as 50%–60% of the total uncertainty in the next decade and impacts total uncertainty at longer lead times when compared to the summertime. In winter, there exists a considerable scenario dependence of model uncertainty with relatively larger model uncertainty under strong forcing compared to weak forcing. At regional scales, the contribution of internal variability can vary widely and strongly depends on the calendar month and region. For wintertime SIA change in the Greenland-Iceland-Norwegian and Barents Seas, internal variability contributes 60%–70% to the total uncertainty over the coming decades and remains important much longer than in other regions. We further find that the relative contribution of internal variability to total uncertainty is state-dependent and increases as sea ice volume declines. These results demonstrate that internal variability is a significant source of uncertainty in projections of Arctic sea ice.

Bonan, David B. (ORCID:0000000338676009)↗

Calibrating hypersonic turbulence flow models with the HIFiRE-1 experiment using data-driven machine-learned models.

In this paper we study the efficacy of combining machine-learning methods with projection-based model reduction techniques for creating data-driven surrogate models of computationally expensive, high-fidelity physics models. Such surrogate models are essential for many-query applications e.g., engineering design optimization and parameter estimation, where it is necessary to invoke the high-fidelity model sequentially, many times. Surrogate models are usually constructed for individual scalar quantities. However there are scenarios where a spatially varying field needs to be modeled as a function of the model’s input parameters. Here we develop a method to do so, using projections to represent spatial variability while a machine-learned model captures the dependence of the model’s response on the inputs. The method is demonstrated on modeling the heat flux and pressure on the surface of the HIFiRE-1 geometry in a Mach 7.16 turbulent flow. The surrogate model is then used to perform Bayesian estimation of freestream conditions and parameters of the SST (Shear Stress Transport) turbulence model embedded in the high-fidelity (Reynolds-Averaged Navier–Stokes) flow simulator, using shock-tunnel data. The paper provides the first-ever Bayesian calibration of a turbulence model for complex hypersonic turbulent flows. We find that the primary issues in estimating the SST model parameters are the limited information content of the heat flux and pressure measurements and the large model-form error encountered in a certain part of the flow.

42 ENGINEERING↗

Derivative-based SINDy (DSINDy): Addressing the challenge of discovering governing equations from noisy data

Recent advances in the field of data-driven dynamics allow for the discovery of ODE systems using state measurements. One approach, known as Sparse Identification of Nonlinear Dynamics (SINDy), assumes the dynamics are sparse within a predetermined basis in the states and finds the expansion coefficients through linear regression with sparsity constraints. This approach requires an accurate estimation of the state time derivatives, which is not necessarily possible in the high-noise regime without additional constraints. We present an approach called Derivative-based SINDy (DSINDy) that combines two novel methods to improve ODE recovery at high-noise levels. First, we denoise the state variables by applying a projection operator that leverages the assumed basis for the system dynamics. Second, we use a second order cone program (SOCP) to find the derivative and governing equations simultaneously. We derive theoretical results for the projection-based denoising step, which allow us to estimate the values of hyperparameters used in the SOCP formulation. This underlying theory helps limit the number of required user-specified parameters. Finally, we present results demonstrating that our approach leads to improved system recovery for the Van der Pol oscillator, the Duffing oscillator, the Rössler attractor, and the Lorenz 96 model.

97 MATHEMATICS AND COMPUTING↗

Complementing Dynamical Downscaling With Super‐Resolution Convolutional Neural Networks

Despite advancements in Artificial Intelligence (AI) methods for climate downscaling, significant challenges remain for their practicality in climate research. Current AI-methods exhibit notable limitations, such as limited application in downscaling Global Climate Models (GCMs), and accurately representing extremes. To address these challenges, we implement an AI-based methodology using super-resolution convolutional neural networks (SRCNN), trained and evaluated on 40 years of daily precipitation data from a reanalysis and a high-resolution dynamically downscaled counterpart. The dynamical downscaled simulations, constrained using spectral nudging, enable the replication of historical events at a higher resolution. This allows the SRCNN to emulate dynamical downscaling effectively. Modifications, such as incorporating elevation data and data pre-processing enhances overall model performance, while using exponential and quantile loss functions improve the simulation of extremes. Our findings show SRCNN models efficiently and skillfully downscale precipitation from GCMs. Future work will expand this methodology to downscale additional variables for future climate projections.

54 ENVIRONMENTAL SCIENCES↗

Enhanced jet stream waviness induced by suppressed tropical Pacific convection during boreal summer

Abstract Consensus on the cause of recent midlatitude circulation changes toward a wavier manner in the Northern Hemisphere has not been reached, albeit a number of studies collectively suggest that this phenomenon is driven by global warming and associated Arctic amplification. Here, through a fingerprint analysis of various global simulations and a tropical heating-imposed experiment, we suggest that the suppression of tropical convection along the Inter Tropical Convergence Zone induced by sea surface temperature (SST) cooling trends over the tropical Eastern Pacific contributed to the increased summertime midlatitude waviness in the past 40 years through the generation of a Rossby-wave-train propagating within the jet waveguide and the reduced north-south temperature gradient. This perspective indicates less of an influence from the Arctic amplification on the observed mid-latitude wave amplification than what was previously estimated. This study also emphasizes the need to better predict the tropical Pacific SST variability in order to project the summer jet waviness and consequent weather extremes.

54 ENVIRONMENTAL SCIENCES↗

The WISSH quasars project: X. Discovery of a multi-component and highly variable UV ultra-fast outflow in a z = 3.6 quasar

We report on the variability of a multi-component broad absorption line (BAL) system observed in the hyper-luminous quasar J1538+0855 at z = 3.6. Observations from the Sloan Digital Sky Survey (SDSS), Very Large Telescope (VLT), Large Binocular Telescope (LBT), and Subaru telescope taken at five different epochs, spanning 17 yr in the observed frame, are presented. We detect three (A, B, and C) CIV variable troughs exhibiting extreme velocities (~40 000–54 000 km s –1 ) similar to the ultra-fast outflows (UFOs) typically observed in the X-ray spectra. The A component of the BAL UFO (v ufo ~ 0.17c) shows strength variations, while B (v ufo ~ 0.15c) and C (v ufo ~ 0.13c) components show changes both in shape and strength, appearing and disappearing at different epochs. In addition, during the last observation on June 2021, the entire BAL system disappeared. The variability trends observed during the first two epochs (1.30 yr rest frame) in the CIV, SiIV, OVI, and NV absorption spectral regions are the same for B and C troughs, while the A component of the BAL varies independently.

79 ASTRONOMY AND ASTROPHYSICS↗