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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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DOE OSTI2021

Development of an Extreme Fast Charging Battery

The objective of the project is to research, develop, design, fabricate, and demonstrate extreme fast charging (XFC) Li-ion cells capable of a 10 min charge to deliver 180Wh/kg at the beginning of life (BoL) and sustain >500 XFC cycles with less than 20% capacity loss. The PI developed an asymmetric temperature modulation (ATM) charging strategy that charges a Li-ion cell at an elevated temperature of ~60oC and discharges at the ambient temperature. The elevated charging temperature eliminates Li plating, while the limited exposure time to 60oC effectively controls materials degradation, thereby enabling XFC with remarkable battery life. We developed and demonstrated 209 and 271 Wh/kg cells, both of which exceed the afore-mentioned target of delivering 180Wh/kg at BoL and sustaining 500+ XFC cycles with less than 20% loss.

25 ENERGY STORAGE↗
DOE OSTI2021

New High-Energy & Safe Battery Technology with Extreme Fast Charging Capability for Automotive Applications (Final Technical Report)

Being able to refill a cars gas tank when low on fuel is incredibly convenient and is a lacking feature for battery elective vehicles. New High-Energy & Safe Battery Technology with Extreme Fast Charging Capability for Automotive Applications was a research project designed to help correct this lacking feature by developing automotive sized Li-ion battery cells and demonstrating their ability to charge in under 10-minutes. To address the technical challenges Microvast, a cell manufacturer, was joined by Argonne National Labs, battery technology innovator, and BMW, a renown OEM, worked together to define and validate materials and cells for this project. By projects end, Microvast had successfully built and demonstrated a 240 Wh/kg, 35 Ah pouch cell that was capable of over 800 10-minute charge, full discharge cycles. From the outset of the project the plan was to use large amp-hour cells (ie automotive relevant sizes) to ensure the project findings and outcomes were most relevant for electric vehicle applications. The manufacture of cells was done using test manufacturing lines at Microvast and BMW that closely resemble the procedures of a Li-ion battery cell factory.

25 ENERGY STORAGE↗
DOE OSTI2021

Risk-Adaptive Experimental Design for High-Consequence Systems: LDRD Final Report

Constructing accurate statistical models of critical system responses typically requires an enormous amount of data from physical experiments or numerical simulations. Unfortunately, data generation is often expensive and time consuming. To streamline the data generation process, optimal experimental design determines the 'best' allocation of experiments with respect to a criterion that measures the ability to estimate some important aspect of an assumed statistical model. While optimal design has a vast literature, few researchers have developed design paradigms targeting tail statistics, such as quantiles. In this project, we tailored and extended traditional design paradigms to target distribution tails. Our approach included (i) the development of new optimality criteria to shape the distribution of prediction variances, (ii) the development of novel risk-adapted surrogate models that provably overestimate certain statistics including the probability of exceeding a threshold, and (iii) the asymptotic analysis of regression approaches that target tail statistics such as superquantile regression. To accompany our theoretical contributions, we released implementations of our methods for surrogate modeling and design of experiments in two complementary open source software packages, the ROL/OED Toolkit and PyApprox.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Report on FY 2023 Research and Development on Specially Designed Creep-fatigue Experiments on Alloy 617 in Support of Improving Creep-fatigue Evaluation Approaches

Experimental and numerical studies in support of developing the integrated Elastic–Perfectly Plastic (EPP) plus Simplified Model Test (SMT) design methodology, referred to as the EPP+SMT method, continued in FY 2023. This report focuses on the methods for extrapolating the EPP+SMT creep-fatigue life curves at long hold times and low strain ranges at elevated temperatures. In this work, the available uniaxial creep-fatigue failure data on Alloy 617 at temperatures of 950°C and 850°C were analyzed to provide a guidance on the development of the extrapolation method and the creep-fatigue failure criteria. A viscoplastic constitutive model for Alloy 617 was adopted to extrapolate the mechanical responses to low strain ranges and long hold times. A set of design curves of Alloy 617 at temperatures of 950°C, 850°C, and 800°C with tensile hold times of 1 hr, 100 hr, and 1,000 hr are developed. Furthermore, creep-fatigue testing on two notch specimen geometries, shallow-notch and sharp V-notch, on Alloy 617 was performed 950°C to understand the multiaxial stress relaxation behavior. The experimental and numerical results on the notch specimens were compared with those on the standard uniaxial smooth bar specimens. The effect of multi-axial stress state combined with elastic follow-up on the stress relaxation behavior was investigated in this report.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Deploying Purpose-Grown Energy Crops for Sustainable Aviation Fuel (Workshop Summary Report)

From June 6–7, 2023, the U.S. Department of Energy (DOE) Bioenergy Technologies Office (BETO) hosted the workshop “Deploying Purpose-Grown Energy Crops for Sustainable Aviation Fuel” in Kansas City, Missouri. The purpose of the workshop was to examine topics related to large-scale cultivation of purpose-grown energy crops—including algae—that can contribute feedstocks for the production of biofuels and bioproducts. This workshop was a means to gather a variety of stakeholders with the intent to identify elements for a potential future research strategy designed to overcome challenges and delve into the barriers related to the large-scale cultivation of purpose-grown crops. This document provides an overview and summary of the workshop’s presentations, breakout session discussions, and outcomes.

09 BIOMASS FUELS↗
DOE OSTI2024

Linac_Gen: Integrating Machine Learning and Particle-in-Cell Methods for Enhanced Beam Dynamics at Fermilab

Here, we introduce Linac_Gen, a tool developed at Fermilab, which combines machine learning algorithms with Particle-in-Cell methods to advance beam dynamics in linacs. Linac_Gen employs techniques such as Random Forest, Genetic Algorithms, Support Vector Machines, and Neural Networks, achieving a tenfold increase in speed for phase-space matching in Linacs over traditional methods, through the use of genetic algorithms. Crucially, Linac_Gen's adept handling of 3D field maps elevates the precision and realism in simulating beam instabilities and resonances, marking a key advancement in the field. Benchmarked against established codes, Linac_Gen demonstrates not only improved efficiency and precision in beam dynamics studies but also in the design and optimization of Linac systems, as evidenced in its application to Fermilab's PIP-II Linac project. This work represents a notable advancement in accelerator physics, marrying ML with PIC methods to set new standards for efficiency and accuracy in accelerator design and research. Linac_Gen exemplifies a novel approach in accelerator technology, offering substantial improvements in both theoretical and practical aspects of beam dynamics.

43 PARTICLE ACCELERATORS↗
DOE OSTI2022

Characterizing Bioavailable Soil Nutrients Across Coastal Systems: Western Lake Erie and Chesapeake Bay

Terrestrial Aquatic Interfaces (TAIs), defined as where land meets water, exhibit important hydrological, biological, and biogeochemical dynamics and play a critical role in the Earth’s carbon cycle. Current Earth System Models improperly represent this role due to the complexity of these systems and the disproportionally large impact TAIs have relative to their area. To improve our predictive capacity of coastal system dynamics, a better understanding of carbon and nutrient cycling across TAI’s is needed. Coastal Observations, Mechanisms, and Predictions Across Systems and Scales (COMPASS) aims to achieve this through field observations and laboratory incubations throughout the Western Lake Erie and Chesapeake Bay regions. Here, we report on preliminary results from a soil characterization experiment across the WLE and CB regions. This experiment was conducted as part of the 2-year field, measurements, and experiments (FME) pilot study portion of COMPASS to provide initial baseline data for the sites and to characterize the spatial variability of our analytes. Soil samples were collected from three locations along the TAI transect (upland forest, transitional forest, and wetland) and analyzed for bioavailable nutrients using three types of extractions: (a) water extractions, (b) 2M KCl extractions, and (c) 1M NH4Cl extractions to analyze (a) water soluble organic carbon (WSOC), (b) ammonium and nitrate, and (c) base cations, including Ca, Mg, Na, K, and Fe. These analyses, in conjunction with other bulk physicochemical analyses, will help establish baseline understanding of these sites to drive future research and design focused experiments that will ultimately improve our predictive understanding of these freshwater and marine coastal TAIs and their response to short and long-term changes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Search for a Cloud Phase Feedback in the Arctic Climate System

This project was motivated by a hypothesis involving the transition in lower troposphere temperatures across the freezing point of water. Specifically, at temperatures just below to about ten degrees below freezing, Arctic clouds should be in a mixed-phase, with strong influences from secondary ice production (e.g., the Hallett-Mossop process). At temperatures just above freezing, clouds should become entirely deglaciated. We hypothesized that, with multiple years of ARM data, a statistically significant change could be detected in cloud radiative properties and surface radiative fluxes that could be directly attributed to this phase change. Furthermore, in a gradually warming climate, these phase change-related responses in surface radiation would represent a cloud phase feedback as part of Arctic amplification. We designed this research project to coincide with a new ARM Arctic cloud radar product developed by Ed Luke and collaborators at BNL (Luke et al., 2021: PNAS, doi:10.1073/pnas.2021387118) that explicitly contains SIP cloud properties retrieved from radar data. This research project has successfully concluded after analysis of a much larger North Slope of Alaska (NSA) data sample than originally anticipated, and the results are quite different than originally hypothesized.

58 GEOSCIENCES↗
DOE OSTI2024

A goldilocks computational protocol for inhibitor discovery targeting DNA damage responses including replication-repair functions

While many researchers can design knockdown and knockout methodologies to remove a gene product, this is mainly untrue for new chemical inhibitor designs that empower multifunctional DNA Damage Response (DDR) networks. Here, we present a robust Goldilocks (GL) computational discovery protocol to efficiently innovate inhibitor tools and preclinical drug candidates for cellular and structural biologists without requiring extensive virtual screen (VS) and chemical synthesis expertise. By computationally targeting DDR replication and repair proteins, we exemplify the identification of DDR target sites and compounds to probe cancer biology. Our GL pipeline integrates experimental and predicted structures to efficiently discover leads, allowing early-structure and early-testing (ESET) experiments by many laboratories. By employing an efficient VS protocol to examine protein-protein interfaces (PPIs) and allosteric interactions, we identify ligand binding sites beyond active sites, leveraging in silico advances for molecular docking and modeling to screen PPIs and multiple targets. A diverse 3,174 compound ESET library combines Diamond Light Source DSI-poised, Protein Data Bank fragments, and FDA-approved drugs to span relevant chemotypes and facilitate downstream hit evaluation efficiency for academic laboratories. Two VS per library and multiple ranked ligand binding poses enable target testing for several DDR targets. This GL library and protocol can thus strategically probe multiple DDR network targets and identify readily available compounds for early structural and activity testing to overcome bottlenecks that can limit timely breakthrough drug discoveries. By testing accessible compounds to dissect multi-functional DDRs and suggesting inhibitor mechanisms from initial docking, the GL approach may enable more groups to help accelerate discovery, suggest new sites and compounds for challenging targets including emerging biothreats and advance cancer biology for future precision medicine clinical trials.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2019

Criticality Analysis of a Water Distribution System Considering Both Economic Consequences and Hydraulic Loss Using Modern Portfolio Theory

This study introduces an approach using Modern Portfolio Theory (MPT) to consider hydraulic resilience and economic consequence resilience of a water distribution system (WDS) to identify critical assets. ECLIPS (Economic Consequence Linked to Interruption in Providing Service), a way to represent loss of water provision as economic loss, is used to measure economic consequence following a reduction of WDS functionality. The approach is demonstrated using a hypothetical WDS and tested for pipe breakage and replacement scenarios using EPANET hydraulic simulations. First, the correlation between hydraulic resilience and economic consequence resilience was investigated to assess differences between two resilience measures for identifying pipe’s criticality for replacement. The results confirmed the two resilience measures exhibited differing responses (covariance = 0.2), suggesting that use of both would provide complementary insight. Results of the MPT analysis identified the benefits of balancing hydraulic and economic consequence resilience measures to yield lower risk. This study provides a practical approach to incorporate economic consequence into planning, design, and research applications identifying critical WDS assets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A model to calculate fatigue damage caused by partial waking during wind farm optimization

Abstract. Wind turbines in wind farms often operate in waked or partially waked conditions, which can greatly increase the fatigue damage. Some fatigue considerations may be included, but currently a full fidelity analysis of the increased damage a turbine experiences in a wind farm is not considered in wind farm layout optimization because existing models are too computationally expensive. In this paper, we present a model to calculate fatigue damage caused by partial waking on a wind turbine that is computationally efficient and can be included in wind farm layout optimization. The model relies on analytic velocity, turbulence, and load models commonly used in farm research and design, and it captures some of the effects of turbulence on the fatigue loading. Compared to high-fidelity simulation data, our model accurately predicts the damage trends of various waking conditions. We also perform example wind farm layout optimizations with our presented model in which we maximize the annual energy production (AEP) of a wind farm while constraining the damage of the turbines in the farm. The results of our optimization show that the turbine damage can be significantly reduced, more than 10 %, with only a small sacrifice of around 0.07 % to the AEP, or the damage can be reduced by 20 % with an AEP sacrifice of 0.6 %.

17 WIND ENERGY↗
DOE OSTI2021

The Madison plasma dynamo experiment: A facility for studying laboratory plasma astrophysics

The Madison plasma dynamo experiment (MPDX) is a novel, versatile, basic plasma research device designed to investigate flow driven magnetohydrodynamic instabilities and other high-β phenomena with astrophysically relevant parameters. A 3 m diameter vacuum vessel is lined with 36 rings of alternately oriented 4000 G samarium cobalt magnets, which create an axisymmetric multicusp that contains ∼14 m3of nearly magnetic field free plasma that is well confined and highly ionized (>50%). At present, 8 lanthanum hexaboride (LaB6) cathodes and 10 molybdenum anodes are inserted into the vessel and biased up to 500 V, drawing 40 A each cathode, ionizing a low pressure Ar or He fill gas and heating it. Up to 100 kW of electron cyclotron heating power is planned for additional electron heating. The LaB6cathodes are positioned in the magnetized edge to drive toroidal rotation through J × B torques that propagate into the unmagnetized core plasma. Dynamo studies on MPDX require a high magnetic Reynolds number Rm > 1000, and an adjustable fluid Reynolds number 10 1). Initial results from MPDX are presented along with a 0-dimensional power and particle balance model to predict the viscosity and resistivity to achieve dynamo action.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗