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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Data and scripts associated with “Non-random processes impacting organic matter chemistry are maximized in mid-order streams”

NOTE: The manuscript associated with this data package is currently in review. The data may be revised based on reviewer feedback. Upon manuscript acceptance, this data package will be updated with the final dataset and additional metadata. This data package is associated with the publication “Non-random processes impacting organic matter chemistry are maximized in mid-order streams” submitted to Limnology and Oceanography (L&O) by Danczak et al. (in review). This package contains data and scripts used to investigate dissolved organic matter (DOM) molecular chemistry and diversification processes across 47 surface-water sampling sites in the Yakima River Basin, Washington, USA, during an August 2021 sampling campaign. The package contains analyses of ultrahigh-resolution Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), geochemical measurements, geospatial attributes, molecular diversity, and meta-metabolome ecological null models needed to reproduce the main manuscript results. The underlying field data were pulled from exising data packages at https://doi.org/10.15485/1892052 (Fulton et al., 2022) and https://doi.org/10.15485/1898914 (Grieger et al., 2022). For details on how to navigate data packages generated by this project, see https://data.ess-dive.lbl.gov/portals/PNNLRiverCorridorSFA/About. We thank the following organizations for providing access to field locations for sample collection: the United States Forest Service, Washington Department of Fish and Wildlife, Washington Department of Natural Resources, the Confederated Tribes and Bands of the Yakama Nation, and the Cowiche Canyon Conservatory. Research was conducted under Washington State Parks and Recreation Commission Scientific Research Permit #210901. We are grateful to the Yakama Nation Tribal Council and Yakama Nation Fisheries for their collaboration in facilitating sample collection and ensuring data usage aligns with their values and worldview. This data package contains an R-Markdown file for analyses and five folders: (1) Data, (2) Geospatial Data, (3) Supplemental_Files, (5) Figures_pdf, (4) and src. The Data folder contains tabular inputs and derived files used in the manuscript analysis. The Geospatial Data folder contains climate and water-balance, hydrologic, land-cover, population/regional water-use, stream, topographic, and stream-order attribute CSV files. The src folder contains scripts used to process data, run analyses, and generate figures. The Figures_pdf folder contains manuscript figure outputs. The Supplemental_Files folder contains supplemental analysis products. All files are .csv, .pdf, .html, .png, .R, .Rmd, .svg, or .tre. This data package is associated with the rcfsa-RC2-SPS_Null_Modeling repository found at https://github.com/river-corridors-sfa/rcfsa-RC2-SPS_Null_Modeling.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Electronic transport and phonon properties of maximally disordered alloys: From binaries to high-entropy alloys

Recent discoveries of multicomponent concentrated solid-solution alloys hold promise for enhanced properties—such as enhanced mechanical properties, radiation tolerance, high temperature strength, corrosion resistance and some novel functional properties, provide a new strategy for alloy design using extreme disorder. Yet, deep understanding of these intriguing properties is complicated by the very effects of disorder that make them interesting. All the desirable properties of these alloys ultimately originate from the disorder-induced properties of underlying electronic structure, lattice dynamics, and thermodynamics. Therefore, understanding the disorder-induced fundamental physical properties is prerequisite for the science-based design of this class of alloys for practical applications. Furthermore, we elucidate the role of extreme (maximal) substitutional disorder plays in the fundamental physics of disordered alloys and review the recently developed theoretical methodologies in modeling the basic physical properties, particularly electronic structure, magnetism, electrical transport, and lattice vibrations in multicomponent concentrated solid-solution alloys.

36 MATERIALS SCIENCE↗
DOE OSTI2019

Use of a New Analytical Model To Match Production Data and Identify Opportunities To Maximize Well Productivity in the Tuscaloosa Marine Shale Reservoir

The low productivity of the oil wells in the Tuscaloosa Marine Shale (TMS) Trend, located in Louisiana and Mississippi, is a mystery. Production data from 55 wells in the TMS Trend were analyzed to identify possible means of enhancing well productivity. The -1/2 slope in a log–log plot for reservoir linear flow (RLF) was observed for some wells, but not all, and the -1 slope for boundary–dominated flow (BDF) has not been seen in the past 5 years of production. The behavior of the TMS wells is attributed to the ultralow permeability of the TMS matrix and the decline of fracture conductivity, both of which delay the BDF. On the basis of the concept of the distance of investigation, derived from the radius–of–investigation concept, the matrix permeability of the seven TMS wells was estimated to be between 34 and 65 nd, with an average of 51 nd. A new mathematical model for production decline of multifractured horizontal wells was developed taking into consideration the time–dependent fracture conductivity during the BDF period. This model fits TMS–well production data, with an average error of 6.12% and an R2 value of 0.96. Assuming constant matrix permeability, fitting the new model to the production data in the BDF period gives a rate of fracture–conductivity decline of between 0.20 and 0.74% per month. The new mathematical model reveals opportunities to optimize well completion to enhance well productivity in the TMS Trend. For a given amount of fracture proppant allocated to a well, the shortest possible fracture spacing should be used to maximize well productivity. If the number of fractures is fixed as a constraint of well completion design, well productivity is inversely proportional to the square root of fracture spacing (i.e., if the fracture spacing is shortened by fourfold, well productivity is expected to double). If the horizontal wellbore length is fixed as a constraint of well completion, well productivity is inversely proportional to fracture spacing (i.e., if the fracture spacing is shortened by 50%, well productivity is expected to double).

Engineering↗
DOE OSTI2025

Spectral anomalies and broken symmetries in maximally chaotic quantum maps

Spectral statistics such as the level spacing statistics and spectral form factor (SFF) are widely expected to accurately identify “ergodicity,” including the presence of underlying macroscopic symmetries, in generic quantum systems ranging from quantized chaotic maps to interacting many-body systems. By studying various quantizations of maximally chaotic maps that break a discrete classical symmetry upon quantization, we demonstrate that this approach can be misleading and fail to detect macroscopic symmetries. Notably, the same classical map can exhibit signatures of different random matrix symmetry classes in short-range spectral statistics depending on the quantization. While the long-range spectral statistics encoded in the early time ramp of the SFF are more robust and correctly identify macroscopic symmetries in several common quantizations, we also demonstrate analytically and numerically that the presence of Berry-like phases in the quantization leads to spectral anomalies, which break this correspondence. Finally, we provide numerical evidence that long-range spectral rigidity remains directly correlated with ergodicity in the quantum dynamical sense of visiting a complete orthonormal basis.

Shou, Laura [Univ. of Maryland, College Park, MD (↗
DOE OSTI2019

Maximizing Revenue from Electrical Energy Storage Paired with Community Solar Projects in NYISO Markets

The New York State Public Service Commission recently made significant changes to the compensation mechanisms for distributed energy resources, such as solar generation. The new mechanisms, called the Value of Distributed Energy Resources (VDER), alter the value proposition of potential installations. In particular, multiple time-of-generation based pricing alternatives were established, which could lead to potential benefits from pairing energy storage systems with solar installations. This paper presents the calculations to maximize revenue from a solar photovoltaic and energy storage system installation operating under the VDER pricing structures. Two systems in two different zones within the New York Independent System Operator area were modeled. The impact of AC versus DC energy storage system interconnections with solar generation resources was also explored. The results show that energy storage systems could generate significant revenue depending on the pricing alternative being targeted and the zone selected for the project.

14 SOLAR ENERGY↗
DOE OSTI2022

Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities

Improvements in process monitoring and control at water resource recovery facilities (WRRFs) could result in reductions in electricity consumption, chemical inputs, and greenhouse gas emissions, as well as improved energy recovery. Many current WRRF data collection, monitoring, and control approaches use 20th century process monitoring and control systems, which require large design safety factors to ensure reliability in the absence of more advanced, precise controls. Implementation of more modern data-driven control tools could lead to more efficient operations that provide intrinsic reliability with better overall process performance at full-scale. This presentation provides an overview of a recently initiated project "Crossing the Finish Line: Integration of Data-Driven Process Control for Maximization of Energy and Resource Efficiency in Advanced Water Resource Recovery Facilities" which will (1) develop and demonstrate data-driven process controls at full-scale facilities for five promising WRRF Applications (i.e., process technologies) that provide whole-plant approaches and offer substantial energy and resource recovery benefits, and (2) create a toolbox of new process control approaches and an implementation guide including five examples for application at utilities. The presentation also provides a detailed overview of the research approach and progress being made on one of the five Applications, namely Application 2: Biological Nutrient Removal (BNR): ammonium-based aeration control (ABAC) / ammonia vs. NOx (AvN) + partial denitration with anammox (PdNA), which is being implemented at Hampton Roads Sanitation District. This project is a collaboration of work being conducted by DC Water, Hampton Roads Sanitation District, Metro Water Recovery, University of Michigan, Northwestern University, US Military Academy - West Point, Black & Veatch, and Oak Ridge National Laboratory. Research partner: U.S. Department of Energy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Design of an Integrated Solids Handling System to Maximize Syngas Process Reliability (Cooperative Research and Development Final Report)

The National Renewable Energy Laboratory (NREL), in partnership with Wonderful Renewable Energy (WRE) and Idaho National Laboratory (INL), plans to develop a general methodology for designing integrated biorefinery solids preprocessing, handling, and feeding systems based on the chemical, physical, and mechanical attributes of the starting biomass material. This attribute-driven approach will include detailed feedstock property measurements, iterative computational modeling, and bench-scale testing to design systems for preprocessing, handling, and reactor in-feed, up to and including the selection of the conversion reactor. The initial tests and system design will be conducted using waste material from almond and pistachio growing and production operations (shells, hulls, and wood), targeting the conversion of this material to syngas for electricity production. The methodology will then be generalized to other feedstocks. The purpose of this project is to design an integrated solids handling system to maximize the process reliability of converting almond and pistachio waste to electricity. The design methodology and workflow developed from this example will then be applied to the Feedstock Conversion Interface Consortium (FCIC) benchmark loblolly pine residues, thus demonstrating the robustness of the overall design approach and providing insight and guidance for future conversion systems. V-Grid Energy Systems was brought on as a subcontractor to provide gasifiers and labor to complete gasifier runs.

09 BIOMASS FUELS↗
DOE OSTI2024

Rational Design of Electrocatalysts for Maximizing CO2 Electrolysis Performance

This virtual invited talk in the session " Electrocatalysis and Energy”) at the International Conference on Catalysis Science and Chemical Engineering (CatScience 2024) will briefly overview diverse research areas of NETL to advance energy and environmental sustainability along with carbon management to achieve net zero emissions by 2050. Subsequently, the talk will primarily discuss how rational design of novel electrocatalysts would maximize the CO2 conversion in different cell configurations.

Nguyen Phan, Thuy Duong↗
DOE OSTI2024

Rational Design of Electrocatalysts for Maximizing CO2 Electrolysis Performance

This presentation will briefly overview diverse research areas of NETL to advance energy and environmental sustainability along with carbon management to achieve net zero emissions by 2050. Subsequently, the talk will primarily discuss how rational design of novel electrocatalysts would maximize the CO2 conversion in different cell configurations.

Nguyen Phan, Thuy Duong↗
DOE OSTI2024

How much is surface dopant enough to maximize CO2-to-liquid chemicals conversion at industrially relevant current density?

This invited talk will be presented at the symposium "Waste Feedstock to Fuels and Petrochemicals”, Fuels and Petrochemical Division at the 2024 AIChE Annual Meeting. In this study, we will discuss how minute amount of surface heteroatoms would maximize CO2 reduction to formate/formic acid at industrially relevant current densities and high selectivity which was validated by both experimental and computational studies. The outstanding performance of the best-in-class catalysts in both H-cell and full-cell electrolyzer cell is also demonstrated. Our findings would provide additional design concepts of high performance CO2R electrocatalysts.

Nguyen Phan, Thuy Duong↗
DOE OSTI2022

Optimization-Based Resiliency Verification in Microgrids via Maximal Adversarial Set Characterization

Critical energy infrastructures are increasingly relying on advanced sensing and control technologies for efficient and optimal utilization of flexible energy resources. Algorithmic procedures are needed to ensure that such systems are designed to be resilient to a wide range of cyber-physical adversarial events. This paper provides a robust optimization framework to quantify the largest adversarial perturbation that a system can accommodate without violating pre-specified resiliency metrics. We formulate the maximal adversarial set characterization as a bi-level optimization problem which is solved via Lagrangian relaxations.We illustrate the proposed algorithm on an islanded microgrid example: a modified IEEE 123-node feeder with distributed energy resources. Simulations are carried out to characterize the tolerable adversarial perturbations for varying levels of available flexibility (energy reserves).

Nazir, Mohammad Nawaf↗
DOE OSTI2021

Probabilistic Data Association for Orbital-Element Estimation Using Multistage Expectation–Maximization

Tracking space objects is important for managing space traffic and predicting collisions, but is difficult in part due to data association and orbit model uncertainty. Expectation–maximization (EM) is a commonly used tracking method that has not been widely considered for tracking space objects. The technique consists of iteratively computing data association probabilities with a set of current element estimates, and updating estimates of the elements by solving a nonlinear weighted least-squares regression problem where the weights are the data association probabilities. In this paper, we demonstrate the use of EM for probabilistic data association and orbital-element estimation by applying the technique to simulated data from two angles-only tracking scenarios. In both scenarios, EM provides correct data associations and accurate maximum likelihood estimates of orbital elements. One scenario considers tracking a single object in clutter and quantifies the improvement of the orbital-element estimates and data associations as the detection probability increases. However, standard application of EM requires knowing the number of objects or may fail when a large number of objects are present. To address these issues, this paper employs a multistage version of EM that is applicable when there are a large and possibly unknown number of objects.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Greenhouse gas emissions reduction strategies that maximize portfolio-wide life cycle cost reduction, resilience, and environmental justice benefits

While strategies to achieve net-zero emissions at an individual site are well understood, new analysis methods are required for organizations seeking to achieve net-zero across multiple facilities, each with concurrent priority goals. At a portfolio level, distinct locations present varied challenges that cannot be addressed through singular solutions, and competing goals can take precedence with the assumption that net-zero emissions strategies deter from energy resilience and cost savings, therefore negatively impacting nearby communities. This study tests these assumptions by analyzing 16 diverse sites (varying in size, climate, and energy use) to identify strategies that reduce emissions and assess the impact these strategies have on life cycle costs, resilience, and communities with environmental justice concerns. Methods were developed to approximate missing information essential to net-zero evaluation. Established methods were augmented to evaluate life cycle costs, resilience, and environmental justice impacts across a set of strategies and accommodate the multi-criteria analyses. Potential benefits from identified strategies were quantified using site characteristics and a set of corresponding metrics. The net-zero analysis found that 11 sites could use on-site strategies to eliminate all but 2% of emissions generated. The remaining emissions can be offset, for instance through sequestration, executed at the portfolio scale. On-site carbon-free energy was found to reduce 51% of emissions across all sites; efficiency reduced 19% of emissions; sequestration 16%; procured carbon-free energy 15%; fuel switching 1.6%; and fleet electrification 1.3%. Building electrification, however, increased emissions by 4.4%. Different strategies also provide cost, resilience, and/or environmental justice benefits—the degree to which varies with individual site conditions. The findings indicate an advantage to considering the strategies as a comprehensive set, which leads to co-benefits, both in the ability to achieve net-zero goals and in advancing other goals. The results present the case for comprehensive advanced planning at the portfolio level to prioritize investments that will balance the minimization of emissions and life cycle cost with the maximization of resilience and environmental justice benefits. The novel methods for evaluation and integration, valuation of benefits, and consideration at the portfolio scale allow organizations to select investments that simultaneously address multiple key priorities.

Net-Zero Emissions↗
DOE OSTI2023

An approach to learn regulation to maximize growth and entropy production rates in metabolism

Elucidating cell regulation remains a challenging task due to the complexity of metabolism and the difficulty of experimental measurements. Here we present a method for prediction of cell regulation to maximize cell growth rate while maintaining the solvent capacity of the cell. Prediction is formulated as an optimization problem using a thermodynamic framework that can leverage experimental data. We develop a formulation and variable initialization procedure that allows for computing solutions of the optimization with an interior point method. The approach is applied to photoheterotrophic growth of Rhodospirilium rubrum using ethanol as a carbon source, which has applications to biosynthesis of ethylene production. Growth is captured as the rate of synthesis of amino acids into proteins, and synthesis of nucleotide triphoshaptes into RNA and DNA. The method predicts regulation that produces a high rate of protein and RNA synthesis while DNA synthesis is reduced close to zero in agreement with production of DNA being turned off for much of the cell cycle.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

The Maximal Entanglement Limit in Statistical and High-energy Physics

These lectures advocate the idea that quantum entanglement provides a unifying foundation for both statistical physics and high-energy interactions. I argue that, at sufficiently long times or high energies, most quantum systems approach a Maximal Entanglement Limit (MEL) in which phases of quantum states become unobservable, reduced density matrices acquire a thermal form, and probabilistic descriptions emerge without invoking ergodicity or classical randomness. Within this framework, the emergence of probabilistic parton model, thermalization in the break-up of confining strings and in high-energy collisions, and the universal small-x behavior of structure functions arise as direct consequences of entanglement and geometry of high-dimensional Hilbert space.

36 MATERIALS SCIENCE↗