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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

Suppressing the sample variance of DESI-like galaxy clustering with fast simulations

Ongoing and upcoming galaxy redshift surveys, such as the Dark Energy Spectroscopic Instrument (DESI) survey, will observe vast regions of sky and a wide range of redshifts. In order to model the observations and address various systematic uncertainties, N-body simulations are routinely adopted, however, the number of large simulations with sufficiently high mass resolution is usually limited by available computing time. Therefore, achieving a simulation volume with the effective statistical errors significantly smaller than those of the observations becomes prohibitively expensive. In this study, we apply the Convergence Acceleration by Regression and Pooling (CARPool) method to mitigate the sample variance of the DESI-like galaxy clustering in the AbacusSummit simulations, with the assistance of the quasi-N-body simulations FastPM. Based on the halo occupation distribution (HOD) models, we construct different FastPM galaxy catalogs, including the luminous red galaxies (LRGs), emission line galaxies (ELGs), and quasars, with their number densities and two-point clustering statistics well matched to those of AbacusSummit. We also employ the same initial conditions between AbacusSummit and FastPM to achieve high cross-correlation, as it is useful in effectively suppressing the variance. Our method of reducing noise in clustering is equivalent to performing a simulation with volume larger by a factor of 5 and 4 for LRGs and ELGs, respectively. We also mitigate the standard deviation of the LRG bispectrum with the triangular configurations k 2 = 2k 1 = 0.2 h Mpc -1 by a factor of 1.6. With smaller sample variance on galaxy clustering, we are able to constrain the baryon acoustic oscillations (BAO) scale parameters to higher precision. The CARPool method will be beneficial to better constrain the theoretical systematics of BAO, redshift space distortions (RSD) and primordial non-Gaussianity (NG).

79 ASTRONOMY AND ASTROPHYSICS↗

Harnessing Chemical Short‐Range Disorder to Improve Lithium Retention in Epitaxial LLTO Solid‐Electrolyte Thin Films

Lithium lanthanum titanate Li 3x La 2/3-x TiO 3 (LLTO) is a promising perovskite-based solid-state electrolyte for next-generation lithium-ion batteries, but controlling crystallinity and Li stoichiometry in thin-film form is challenging because high growth temperatures are required to achieve good crystallinity while Li remains strongly volatile. Here, we systematically investigate the effect of substrate temperature on epitaxial LLTO thin films grown by pulsed laser deposition. We identify a narrow growth window (750–800°C) in which LLTO films grow as c-axis oriented with atomically flat surfaces. Lower growth temperatures (<750°C) stabilize laterally extended, chemically disordered stripe domains that coexist with ordered LLTO regions, whereas higher temperatures (≥825°C) suppress these defects but promote island morphologies and Al/Ti interdiffusion. While spectroscopy measurements show that Ti remains in the 4+ oxidation state and Li is globally deficient for all films, our depth-resolved time-of-flight secondary ion mass spectrometry studies reveal that the 700°C film retains the highest Li content across its thickness. These results clarify how growth temperature controls crystallinity, chemical short-range disorder, and Li retention, and highlight moderate growth temperatures (∼700°C) as a route to mitigate Li loss in epitaxial solid-electrolyte films.

chemical short-range disorder↗

Hydrogen Equipment Enclosure Risk Reduction through Earlier Detection of Component Failures

Hydrogen component reliability and the hazard associated with failure rates is a critical area of research for the successful implementation and growth of hydrogen technology across the globe. The research team has partnered to quantify system risk reduction through earlier detection of hydrogen component failures. A model of hydrogen dispersion in a hydrogen equipment enclosure has been developed utilizing experimentally quantified hydrogen component leak rates as inputs. This model provides insight into the impact of hydrogen safety sensors and ventilation on the flammable mass within a hydrogen equipment enclosure. This model also demonstrates the change in safety sensor response time due to detector placement under various leak scenarios. The team looks to improve overall hydrogen system safety through an improved understanding of hydrogen component reliability and risk mitigation methods. This collaboration fits under the work program of IEA Hydrogen Task 43 Subtask E Hydrogen System Safety.

CFD↗

Surrogate-driven Variance-based Sensitivity Analysis of Thermal Storage Tanks in Integrated Energy Systems

Sensitivity analysis and uncertainty quantification are essential steps for enhancing the accuracy of computational models by identifying and mitigating uncertainties. This study focuses on these steps for the Thermal Energy Delivery System at Idaho National Laboratory, specifically targeting the thermocline tank. Using a Modelica/Dymola simulation model, the study perturbed various design parameters and boundary conditions, including shape factor, porosity, outlet temperature, inlet mass flow rate, and system pressure, to predict and quantify uncertainty in the tank’s ax- ial temperature. A dataset of over 1,000 simulations was generated, and surrogate models were developed using the pyMAISE (Michigan Artificial Intelligence Standard Environment) library, which is an Automatic Machine Learning library for nuclear engineering applications. The optimal model, a feedforward neural network with two hidden layers, achieved an R2 score above 0.99 and a mean absolute error below 1 Kelvin. Sensitivity analyses using Sobol indices and Fourier amplitude sensitivity testing methods on this surrogate model revealed that the inlet mass flow rate at initial timestamps and porosity significantly impacts predicted temperatures across all sensors and time steps.

22 - GENERAL STUDIES OF NUCLEAR REACTORS↗

Evaluating Linear Ion Trap for MS3-Based Multiplexed Single-Cell Proteomics

There is a growing demand to develop high-throughput and high-sensitivity mass spectrometry methods for single-cell proteomics. The commonly used isobaric labeling-based multiplexed single-cell proteomics approach suffers from distorted protein quantification due to co-isolated interfering ions during MS/MS fragmentation, also known as ratio compression. We reasoned that the use of MS3-based quantification could mitigate ratio compression and provide better quantification. However, previous studies indicated reduced proteome coverages in the MS3 method, likely due to long duty cycle time and ion losses during multilevel ion selection and fragmentation. Here, in this paper, we described an improved MS acquisition method for MS3-based single-cell proteomics by employing a linear ion trap to measure reporter ions. We demonstrated that linear ion trap can increase the proteome coverages for single-cell-level peptides with even higher gain obtained via the MS3 method. The optimized real-time search MS3 method was further applied to study the immune activation of single macrophages. Among a total of 126 single cells studied, over 1200 and 1000 proteins were quantifiable when at least 50 and 75% nonmissing data were required, respectively. Our evaluation also revealed several limitations of the low-resolution ion trap detector for multiplexed single-cell proteomics and suggested experimental solutions to minimize their impacts on single-cell analysis.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Integrated simulations of premagnetized and self-magnetizing dynamic screw pinch-driven MagLIF

Magnetically driven implosions such as in magnetized liner inertial fusion (MagLIF) on the Z accelerator suffer from magneto-Rayleigh–Taylor instabilities (MRTI) that dynamically redistribute liner mass during implosion, limiting fusion fuel compression and confinement, which ultimately degrades performance. Driving the implosion with an initially helical drive field that dynamically shifts the direction of the magnetic field surrounding the liner (i.e., a dynamic screw pinch, DSP) is a method proposed to mitigate MRTI in-flight and improve target performance. In DSPs, the axial drive magnetic field component implodes the liner and diffuses through the shocked, melted liner material into the fuel throughout the implosion. Liners can be designed to enable enough axial magnetic flux to diffuse through the liner material to effectively magnetize the fuel region without the need of an initial axial magnetic field (i.e., from external field coils). We present results from three-dimensional radiation-magnetohydrodynamic simulations of MagLIF implosions employing drive magnetic fields composed of axial and azimuthal components (a helical drive field). These simulated DSP-driven MagLIF targets demonstrate improved fuel conditions and thermonuclear yield compared to a traditional MagLIF target implosion. Synthetic x-ray radiography of the imploding liner material and x-ray emission images of the fuel region at the time of peak neutron yield rate indicate superior implosion morphology for DSP-MagLIF implosions.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

Experimental Study on Flow Condensation of Low Global Warming Potential Refrigerants in a Micro-fin Aluminum Tube

This study investigates the dynamic shifts in refrigerant technologies driven by environmental regulations, particularly emphasizing low global warming potential (GWP). Moreover, there is a rising trend in the adoption of aluminum tubes with internal axial micro-fin structures in heat exchangers to reduce costs. The research focuses on the condensation process within an expanded axial micro-fin aluminum tube with a 5.96 mm fin-tip diameter. Various refrigerants are analyzed, including both single compounds (R-32, R-1234yf, R-1234ze(E)) and zeotropic mixtures (R-454B, R-454C, R-455A). Experimental procedures cover a range of condensation temperatures (35~45 °C), reduced pressures (0.21~0.55), and mass fluxes (150~350 kg/(m² s)), providing crucial data on heat transfer coefficients (HTC) and frictional pressure gradient (FPG). This data is particularly significant for high-glide refrigerants and is instrumental in the design of advanced air conditioning and refrigeration systems aimed at mitigating global warming.

Hu, Yifeng↗

A process optimization framework for laser direct energy deposition: Densification, microstructure, and mechanical properties of an Fe-Cr alloy

Laser Direct Energy Deposition (DED) is a metal additive manufacturing technique with the ability to fabricate large and complex parts through deposition of metal powders. However, achieving high-density parts and targeted build heights using DED can be challenging due to the large number of highly sensitive process variables. This work proposes a robust fabrication parameter optimization framework to generate process maps for primary parameters in DED, including laser power, scan speed, mass flow rate, hatch spacing, and layer height. Simple single-track experiments were utilized to map out the parameter space, and a combination of geometric criteria for hatch spacing and layer height were proposed to determine parameter sets that achieve both targeted build heights and mitigate porosity formation. Using this framework, specimens with >99 % density and consistent mechanical properties were successfully fabricated over a wide range of process parameters for an Fe-9wt.%Cr (Fe9Cr) alloy, a surrogate for radiation damage-resistant reduced activation ferritic/martensitic (RAFM) steels. Processing these materials using DED is of particular interest in the development of plasma facing components for nuclear fusion applications. The microstructure and mechanical properties of as-printed Fe9Cr were characterized using optical and electron microscopy, X-ray diffraction, and uniaxial tensile tests. As-printed Fe9Cr displayed ~25 % elongation and ultimate tensile strengths of up to 475 MPa which is comparable to similar wrought alloys. Finally, the proposed framework will allow for accelerated DED parameter optimization for novel alloy systems, as well as open the possibility for local microstructure control while simultaneously mitigating defect formation.

42 ENGINEERING↗

NOvA in 10 Minutes

NOvA is a long-baseline neutrino oscillation experiment based at Fermilab, IL, USA, that observes $\nu_\mu \ (\bar{\nu}_\mu) \to \nu_\mu\ (\bar{\nu}_\mu)$ disappearance and $\nu_\mu \ (\bar{\nu}_\mu) \to \nu_e \ (\bar{\nu}_e)$ appearance oscillations from a beam of muon neutrinos (anti-neutrinos) provided by the Fermilab's NuMI beamline. The experiment consists of two functionally identical active liquid scintillattor tracking calorimeters, both situated 14.6 mrad off-axis to the beam direction. The detectors are made out of extruded PVC cells arranged in alternating horizontal and vertical planes for 3-dimensional reconstruction of neutrino events. The NOvA experiment has a wide-ranging scientific program that includes studying standard 3-flavor neutrino oscillations, resolution of neutrino mass orderings, measuring the CP-violating phase, $\delta_{CP}$, beyond standard model (BSM) phenomenon such as non-standard interactions (NSI) and sterile neutrino searches, neutrino-nucleus cross-section measurements, exotics, astrophysics and more. The NOvA experiment leverages its identical detector technology to mitigate systematic uncertainties for its neutrino oscillation analysis. This talk will provide an overview of the experiment's detector design and the data-driven techniques used by the experiment in its neutrino oscillation analysis.

Choudhary, Brajesh [Delhi U.]↗

Using Infrasound to Inform Avalanche Hazard Forecasts

Avalanches are natural hazards that occur when an unstable mass of snow breaks away from a mountain slope. It is expected that climate change will lead to increased avalanche activity, which can cause interruptions to water and power infrastructure, transportation blockages, higher risk for loss of life, and changes to ecosystems. Avalanche forecasts are key to mitigating hazards, and observations of recent avalanches comprise one of the key observations for deciding danger level. It is well understood that infrasound can be used to detect and locate snow avalanches in transitional snowpacks, even during snowstorms, but similar studies are lacking for maritime snowpacks. Here we show results from an infrasound field experiment in Tutl’uh (Turnagain Arm), Alaska, USA between January 31 – April 30 field deployment campaign. We show that (1) methods developed for transitional snowpacks can be applied to maritime snowpacks in Alaska, (2) background noise may be higher in this region due to natural and anthropogenic influences, and (3) low-cost infrasound sensors can withstand the harsh Alaskan winter and successfully collect data. We also discuss the impact of this work and a path forward.

58 GEOSCIENCES↗

Resonant acoustic monitoring of damage in plug‐screw feeders

Abstract Plug‐screw feeders are critical in many industrial processes for compressing slurry materials via a rotating plug‐screw feeder. Over time, increasing plug‐screw feeder wear will eventually lead to catastrophic mechanical failure. Early detection of the wear state can prevent unplanned catastrophic failures resulting in operational shut‐downs, costly repairs, and most importantly the health and safety of workers. We present a theoretical basis for a noninvasive, in operando acoustic resonant technique to monitor the wear state of plug‐screw feeders. The technique is based on tracking the resonant acoustic modes of the plug‐screw feeder, which are sensitive to the plug‐screw feeder geometry, material, and operating conditions. We implemented a multivariate polynomial model to estimate the plug‐screw feeder wear state using multiple acoustic resonances by simulating the acoustic resonant modes for two categories of wear (tip and thread damage) that are common in plug‐screw feeders. Fitting multiple resonances to the polynomial model, we demonstrate accurate estimation of the total mass loss, as well as characterization of the type of damage (i.e., tip vs. thread). Current approaches for monitoring plug‐screw feeder wear rely on shutting down the operation and visually inspecting the plug‐screw feeder. The presented acoustic technique offers a noninvasive, in operando measurement approach that mitigates unplanned catastrophic failures. The acoustic resonance technique presented in the paper has a broad range of industrial applications including the Pharmaceutical, Mining, Integrated Biorefineries (IBR), and Additive Manufacturing industries, to name a few.

36 MATERIALS SCIENCE↗

Signal processing and spectral modeling for the BeEST experiment

The Beryllium Electron capture in Superconducting Tunnel junctions (BeEST) experiment searches for evidence of heavy neutrino mass eigenstates in the nuclear electron capture decay of 7 Be by precisely measuring the recoil energy of the 7 Li daughter. In Phase III, the BeEST experiment has been scaled from a singl superconducting tunnel junction (STJ) sensor to a 36-pixel array to increase sensitivity and mitigate gamma-induced backgrounds. Phase III also uses a new continuous data acquisition system that greatly increases the flexibility for signal processing and data cleaning. Here, we have developed procedures for signal processing and spectral fitting that are sufficiently robust to be automated for large datasets. Furthermore, this article presents the optimized procedures before unblinding the majority of the Phase III dataset to search for physics beyond the standard model.

6 ≤ A ≤ 19↗

Robust Measurement of Stellar Streams around the Milky Way: Correcting Spatially Variable Observational Selection Effects in Optical Imaging Surveys

Observations of density variations in stellar streams are a promising probe of low-mass dark matter substructure in the Milky Way. However, survey systematics such as variations in seeing and sky brightness can also induce artificial fluctuations in the observed densities of known stellar streams. These variations arise because survey conditions affect both object detection and star–galaxy misclassification rates. To mitigate these effects, we use Balrog synthetic source injections in the Dark Energy Survey (DES) Y3 data to calculate detection rate variations and classification rates as functions of survey properties. We show that these rates are nearly separable with respect to survey properties and can be estimated with sufficient statistics from the synthetic catalogs. Applying these corrections reduces the standard deviation of relative detection rates across the DES footprint by a factor of 5, and our corrections significantly change the inferred linear density of the Phoenix stream when including faint objects. Additionally, for artificial streams with DES-like survey properties we are able to recover density power spectra with reduced bias. We also find that uncorrected power-spectrum results for Legacy Survey of Space and Time (LSST)-like data can be around 5 times more biased, highlighting the need for such corrections in future ground-based surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

Oxygen Solubility in Aqueous Amine Solvents with Common Additives Used for CO 2 Chemical Absorption

Major sources of anthropogenic CO 2 are power generation and transportation industries where researcher continue to explore CO 2 emission mitigation strategies as applied to these CO 2 sources through carbon capture, utilization, and sequestration (CCUS). The most mature CO 2 capture technology is post-combustion carbon capture (PCCC) using aqueous amine solutions/solvents, however solvent degradation and regeneration costs are slowing the widespread adoption of PCCC. Solvent degradation of the aqueous amine solutions is mainly caused from the temperature gradient between the absorber and stripper columns and common flue gas components such as SOx, NOx, and oxygen (O 2 ). The two main classifications of solvent degradation are thermal degradation, occurring when the amine reacts with itself at elevated temperatures and anaerobic conditions and oxidative degradation. Oxidative degradation reactions can occur from oxygen mass transfer and free radical oxidation. Metals, such as iron from the corrosion of steel structures used in industrial applications such as PCCC, can help to catalyze these reactions. Various oxidative degradation studies have shown how O 2 concentrations in flue gas and, to a lesser extent, temperature influence the extent of oxidative degradation. Accurately measuring the O 2 solubility, commonly referred to as dissolved oxygen (DO), in a quick, continuous, and efficient manner in aqueous amine solvents should contribute to determine the effectiveness of mitigation strategies for oxidative degradation. Knowing that commercial PCCC amine solvents contain components beyond water, amine, carbonate species and CO 2 , this investigation was conducted to determine the oxygen solubility changes of common aqueous amines solutions with commonly used and published solvent additives. The impact of carbon loadings with and without the additives was also examined. A commercial dissolved oxygen probe was used to measure the DO concentrations and compared them against standard Winkler Method titration values. The results show that antifoam shows minimal change in [DO]. MBT yielded lower DO values, and NaVO 3 showed a higher DO concentration due to interferences. These results indicate that most common amine solvent additives should be expected to minimally impact oxygen solubility and amine oxidative degradation.

60 APPLIED LIFE SCIENCES↗

Controlling Ion Uptake in Carboxylated Mixed Conductors

Organic mixed ionic‐electronic conductors (OMIECs) have garnered significant attention due to their capacity to transport both ions and electrons, making them ideal for applications in energy storage, neuromorphics, and bioelectronics. However, charge compensation mechanisms during the polymer redox process remain poorly understood, and are often oversimplified as single‐ion injection with little attention to counterion effects. To advance understanding and design strategies toward next‐generation OMIEC systems, a series of p‐channel carboxylated mixed conductors is investigated. Varying side‐chain functionality, distinctive swelling character is uncovered during electrochemical doping/dedoping with model chao‐/kosmotropic electrolytes. Carboxylic acid functionalized polymers demonstrate strong deswelling and mass reduction during doping, indicating cation expulsion, while ethoxycarbonyl counterparts exhibit prominent mass increase, pointing to an anion‐driven doping mechanism. By employing operando grazing incidence X‐ray fluorescence (GIXRF), it is revealed that the carboxyl functionalized polymer engages in robust cation interaction, whereas ester functionalization shifts the mechanism towards no cation involvement. It is demonstrated that cations are pivotal in mitigating swelling by counterbalancing anions, enabling efficient anion uptake without compromising performance. These findings underscore the transformative influence of functionality‐driven factors and side‐chain chemistry in governing ion dynamics and conduction, providing new frameworks for designing OMIECs with enhanced performance and reduced swelling.

carboxylated polythiophenes↗

DeepSZ: identification of Sunyaev–Zel’dovich galaxy clusters using deep learning

Galaxy clusters identified via the Sunyaev–Zel’dovich (SZ) effect are a key ingredient in multiwavelength cluster cosmology. In this paper, we present and compare three methods of cluster identification: the standard matched filter (MF) method in SZ cluster finding, a convolutional neural networks (CNN), and a ‘combined’ identifier. We apply the methods to simulated millimeter maps for several observing frequencies for a survey similar to SPT-3G, the third-generation camera for the South Pole Telescope. The MF requires image pre-processing to remove point sources and a model for the noise, while the CNN requires very little pre-processing of images. Additionally, the CNN requires tuning of hyperparameters in the model and takes cut-out images of the sky as input, identifying the cut-out as cluster-containing or not. We compare differences in purity and completeness. The MF signal-to-noise ratio depends on both mass and redshift. Our CNN, trained for a given mass threshold, captures a different set of clusters than the MF, some with signal-to-noise-ratio below the MF detection threshold. However, the CNN tends to mis-classify cut-out whose clusters are located near the edge of the cut-out, which can be mitigated with staggered cut-out. We leverage the complementarity of the two methods, combining the scores from each method for identification. The purity and completeness are both 0.61 for MF, and 0.59 and 0.61 for CNN. The combined method yields 0.60 and 0.77, a significant increase for completeness with a modest decrease in purity. We advocate for combined methods that increase the confidence of many low signal-to-noise clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

Flutter behavior of highly flexible blades for two- and three-bladed wind turbines

Abstract. With the progression of novel design, material, and manufacturing technologies, the wind energy industry has successfully produced larger and larger wind turbine rotor blades while driving down the levelized cost of energy (LCOE). Though the benefits of larger turbine blades are appealing, larger blades are prone to aeroelastic instabilities due to their long, slender, highly flexible nature, and this effect is accentuated as rotors further grow in size. In addition to the trend of larger rotors, non-traditional rotor concepts are emerging including two-bladed rotors and downwind configurations. In this work, we introduce a comprehensive evaluation of flutter behavior including classical flutter, edgewise vibration, and flutter mode characteristics for two-bladed, downwind rotors. Flutter speed trends and characteristics for a series of both two- and three-bladed rotors are analyzed and compared in order to illustrate the flutter behavior of two-bladed rotors relative to more well-known flutter characteristics of three-bladed rotors. In addition, we examine the important problem of blade design to mitigate flutter and present a solution to mitigate flutter in the structural design process. A study is carried out evaluating the effect of leading edge and trailing edge reinforcement on flutter speed and hence demonstrates the ability to increase the flutter speed and satisfy structural design requirements (such as fatigue) while maintaining or even reducing blade mass.

Chetan, Mayank (ORCID:0000000241978801)↗