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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 1,135 records · Page 63

MacroAlgae Cultivation MODeling System (MACMODS)

PI Kristen Davis is transferring from a position at the University of California, Irvine to Stanford University, therefore this project will terminate at UC Irvine as of June 30, 2024 and will be transferred to Stanford University. This report describes progress made on the MACMODS project during the period of performance from May 2018 through June 2024.

09 BIOMASS FUELS↗

Misfit layer compounds and ferecrystals: Model systems for thermoelectric nanocomposites

A basic summary of thermoelectric principles is presented in a historical context, following the evolution of the field from initial discovery to modern day high-zT materials. A specific focus is placed on nanocomposite materials as a means to solve the challenges presented by the contradictory material requirements necessary for efficient thermal energy harvest. Misfit layer compounds are highlighted as an example of a highly ordered anisotropic nanocomposite system. Their layered structure provides the opportunity to use multiple constituents for improved thermoelectric performance, through both enhanced phonon scattering at interfaces and through electronic interactions between the constituents. Recently, a class of metastable, turbostratically-disordered misfit layer compounds has been synthesized using a kinetically controlled approach with low reaction temperatures. The kinetically stabilized structures can be prepared with a variety of constituent ratios and layering schemes, providing an avenue to systematically understand structure-function relationships not possible in the thermodynamic compounds. We summarize the work that has been done to date on these materials. The observed turbostratic disorder has been shown to result in extremely low cross plane thermal conductivity and in plane thermal conductivities that are also very small, suggesting the structural motif could be attractive as thermoelectric materials if the power factor could be improved. The first 10 compounds in the [(PbSe) 1+δ ] m (TiSe₂) n family (m, n ≤ 3) are reported as a case study. As n increases, the magnitude of the Seebeck coefficient is significantly increased without a simultaneous decrease in the in-plane electrical conductivity, resulting in an improved thermoelectric power factor.

36 MATERIALS SCIENCE↗

Modeling Systems’ Disruption and Social Acceptance—A Proof-of-Concept Leveraging Reinforcement Learning

As the need for a just and equitable energy transition accelerates, disruptive clean energy technologies are becoming more visible to the public. Clean energy technologies, such as solar photovoltaics and wind power, can substantially contribute to a more sustainable world and have been around for decades. However, the fast pace at which they are projected to be deployed in the United States (US) and the world poses numerous technical and nontechnical challenges, such as in terms of their integration into the electricity grid, public opposition and competition for land use. For instance, as more land-based wind turbines are built across the US, contention risks may become more acute. This article presents a methodology based on reinforcement learning (RL) that minimizes contention risks and maximizes renewable energy production during siting decisions. As a proof-of-concept, the methodology is tested on a case study of wind turbine siting in Illinois during the 2022–2035 period. Results show that using RL halves potential delays due to contention compared to a random decision process. This approach could be further developed to study the acceptance of offshore wind projects or other clean energy technologies.

17 WIND ENERGY↗

Controls on terrestrial carbon feedbacks by productivity versus turnover in the CMIP5 Earth System Models

To better understand sources of uncertainty in projections of terrestrial carbon cycle feedbacks, we present an approach to separate the controls on modeled carbon changes. We separate carbon changes into four categories using a linearized, equilibrium approach: those arising from changed inputs (productivity-driven changes), and outputs (turnover-driven changes), of both the live and dead carbon pools. Using Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations for five models, we find that changes to the live pools are primarily explained by productivity-driven changes, with only one model showing large compensating changes to live carbon turnover times. For dead carbon pools, the situation is more complex as all models predict a large reduction in turnover times in response to increases in productivity. This response arises from the common representation of a broad spectrum of decomposition turnover times via a multi-pool approach, in which flux-weighted turnover times are faster than mass-weighted turnover times. This leads to a shift in the distribution of carbon among dead pools in response to changes in inputs, and therefore a transient but long-lived reduction in turnover times. Since this behavior, a reduction in inferred turnover times resulting from an increase in inputs, is superficially similar to priming processes, but occurring without the mechanisms responsible for priming, we call the phenomenon "false priming", and show that it masks much of the intrinsic changes to dead carbon turnover times as a result of changing climate. These patterns hold across the fully coupled, biogeochemically coupled, and radiatively coupled 1 % yr -1 increasing CO 2 experiments. We disaggregate inter-model uncertainty in the globally integrated equilibrium carbon responses to initial turnover times, initial productivity, fractional changes in turnover, and fractional changes in productivity. For both the live and dead carbon pools, inter-model spread in carbon changes arising from initial conditions is dominated by model disagreement on turnover times, whereas inter-model spread in carbon changes from fractional changes to these terms is dominated by model disagreement on changes to productivity in response to both warming and CO 2 fertilization. However, the lack of changing turnover time control on carbon responses, for both live and dead carbon pools, in response to the imposed forcings may arise from a common lack of process representation behind changing turnover times (e.g., allocation and mortality for live carbon; permafrost, microbial dynamics, and mineral stabilization for dead carbon), rather than a true estimate of the importance of these processes.

54 ENVIRONMENTAL SCIENCES↗

The Brazilian Earth System Model ocean–atmosphere (BESM-OA) version 2.5: evaluation of its CMIP5 historical simulation

The performance of the coupled ocean–atmosphere component of the Brazilian Earth SystemModel version 2.5 (BESM-OA2.5) was evaluated in simulating the historical period1850–2005. After a climate model validation procedure in which the main atmospheric andoceanic variabilities were evaluated against observed and reanalysis datasets, theevaluation specifically focused on the mean climate state and the most importantlarge-scale climate variability patterns simulated in the historical run, which wasforced by the observed greenhouse gas concentration. The most significant upgrades in themodel's components are also briefly presented here. BESM-OA2.5 could reproduce the mostimportant large-scale variabilities, particularly over the Atlantic Ocean (e.g., theNorth Atlantic Oscillation, the Atlantic Meridional Mode, and the Atlantic MeridionalOverturning Circulation), and the extratropical modes that occur in both hemispheres. Themodel's ability to simulate such large-scale variabilities supports its usefulness forseasonal climate prediction and in climate change studies.

58 GEOSCIENCES↗

Combining regional mesh refinement with vertically enhanced physics to target marine stratocumulus biases as demonstrated in the Energy Exascale Earth System Model version 1

Abstract. In this paper we develop a novel framework aimed to significantly reduce biases related to marine stratocumulus clouds in general circulation models (GCMs) while circumventing excessive computational cost requirements. Our strategy is to increase the horizontal resolution using a regionally refined mesh (RRM) over our region of interest in addition to using the Framework for Improvement by Vertical Enhancement (FIVE) to increase the vertical resolution only for specific physical processes that are important for stratocumulus. We apply the RRM off the coast of Peru in the southeastern Pacific, a region that climatologically contains the most marine stratocumulus in the subtropics. We find that our new modeling framework is able to replicate the results of our high-resolution benchmark simulation with much fidelity, while reducing the computational cost by several orders of magnitude. In addition, this framework is able to greatly reduce the long-standing biases associated with marine stratocumulus in GCMs when compared to the standard-resolution control simulation.

54 ENVIRONMENTAL SCIENCES↗