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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 1,333 records · Page 74
All sourcesNASA NTRSDOE OSTI
DOE OSTI2025

Bayesian inference analysis of jet quenching using inclusive jet and hadron suppression measurements

The JETSCAPE Collaboration reports a new determination of the jet transport parameter $\hat{q}$ in the quark-gluon plasma (QGP) using Bayesian inference, incorporating all available inclusive hadron and jet yield suppression data measured in heavy-ion collisions at the BNL Relativistic Heavy Ion Collider (RHIC) and the CERN Large Hadron Collider (LHC). This multi-observable analysis extends the previously published JETSCAPE Bayesian inference determination of $\hat{q}$, which was based solely on a selection of inclusive hadron suppression data. jetscape is a modular framework incorporating detailed dynamical models of QGP formation and evolution, and jet propagation and interaction in the QGP. Virtuality-dependent partonic energy loss in the QGP is modeled as a thermalized weakly coupled plasma, with parameters determined from Bayesian calibration using soft-sector observables. This Bayesian calibration of $\hat{q}$ utilizes active learning, a machine-learning approach, for efficient exploitation of computing resources. The experimental data included in this analysis span a broad range in collision energy and centrality, and in transverse momentum. In order to explore the systematic dependence of the extracted parameter posterior distributions, several different calibrations are reported, based on combined jet and hadron data; on jet or hadron data separately; and on restricted kinematic or centrality ranges of the jet and hadron data. Tension is observed in comparison of these variations, providing new insights into the physics of jet transport in the QGP and its theoretical formulation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2020

A Frequency Control Method for Islanded Microgrids Using Energy Storage Systems

Islanded microgrids are vulnerable to frequency fluctuations due to the presence of low-inertia distributed energy resources (DERs). Moreover, implementation of both synchronous-based and inverter-based DERs with a significant difference in inertia leads to a power imbalance between generation and consumption during transients. This results in frequency variations which might have severe consequences such as blackouts. This paper develops a control scheme for battery energy storage systems (BESSs) to enhance the dynamic response of islanded microgrids by mitigating the frequency fluctuations. A piecewise linear-elliptic (PLE) droop characteristic is proposed and employed in BESS to achieve a faster power balance between generation and consumption during transients, resulting in enhanced frequency responses. Different case studies are carried out to validate the viability of the proposed approach in improving the dynamics of islanded microgrids.

Pilehvar, Mohsen S.↗
DOE OSTI2025

Comparing Machine Learning and Physics-Based Nanoparticle Geometry Determinations Using Far-Field Spectral Properties

Anisotropic metal nanostructures exhibit polarization-dependent light scattering, a property which has been widely studied and exploited to determine orientations of subwavelength structures using far-field microscopy. Here we explore the use of variational autoencoders (VAEs) to determine the geometries of gold nanorods (NRs) such as in-plane orientation and aspect ratio under linearly polarized dark-field illumination in an optical microscope. We enforce a shared latent space to connect two VAEs trained separately with polarized dark-field scattering spectra and electron microscopy images and achieve image prediction (shape, orientation, and size) of Au NRs using only polarized dark-field scattering spectra. We determine the geometrical parameters of orientational angle and aspect ratio quantitatively via both our dual-VAE and physics-based analysis on the input scattering spectra. We show that orientational angle prediction by dual-VAE performs well with only a small (~300 particle) training set, yielding a mean absolute error (MAE) of 14.4° and a concordance correlation coefficient (CCC) of 0.95. This performance is only marginally worse than the physics-based cos(2?) fitting approach between the scattering intensity and the polarizing angle, which achieves MAE of 8.78° and CCC of 0.99. Aspect ratio determination is also comparable for the dual-VAE and physics-based fitting comparison (MAE of 0.21 vs. 0.23 and CCC of 0.53 vs. 0.68). Here, this dual encoder-decoder architecture effectively exploits the structure-property relationships of plasmonic nanostructures to construct a cross-modal machine learning (ML) approach, providing a pathway to employ ML approaches to address other structure-property relationships in materials science.

Dark-field scattering↗
DOE OSTI2023

Revealing Variable Dependences in Hexagonal Boron Nitride Synthesis via Machine Learning

Wafer-scale monolayer two-dimensional (2D) materials have been realized by epitaxial chemical vapor deposition (CVD) in recent years. To scale up the synthesis of 2D materials, a systematic analysis of how the growth dynamics depend on the growth parameters is essential to unravel its mechanisms. However, the studies of CVD-grown 2D materials mostly adopted the control variate method and considered each parameter as an independent variable, which is not comprehensive for 2D materials growth optimization. Herein, we synthesized a representative 2D material, monolayer hexagonal boron nitride (hBN), on single-crystalline Cu (111) by epitaxial chemical vapor deposition and varied the growth parameters to regulate the hBN domain sizes. Furthermore, we explored the correlation between two growth parameters and provided the growth windows for large flake sizes by the Gaussian process. Here, this new analysis approach based on machine learning provides a more comprehensive understanding of the growth mechanism for 2D materials.

36 MATERIALS SCIENCE↗
DOE OSTI2024

Quantifying the Turbulent Entrainment‐Mixing Processes Based on Z ‐LWC Relationships of Cloud Droplets

Abstract Turbulent entrainment‐mixing processes profoundly influence the relationship between radar reflectivity factor and liquid water content ( Z ‐LWC) of cloud droplets. However, quantification of the entrainment‐mixing mechanisms based on the Z ‐LWC relationship is still lacking. To address this gap, 12,218 entrainment‐mixing cases are simulated using the Explicit Mixing Parcel Model. We examine the variations of the parameters in the power‐law relationship Z = a LWC b , and the relationship between parameter b and homogeneous mixing degree ( ψ ), a measure quantifying entrainment‐mixing processes. The results indicate that parameter b distributes within the range of 1–2, with a positive correlation between parameter b and ψ . The b ‐ ψ relationship is fitted, which connects the Z ‐LWC relationship for various entrainment‐mixing types. The results suggest the potential for employing a remote sensing approach to investigate the entrainment‐mixing mechanisms of non‐precipitating small cumulus/stratocumulus clouds, thereby overcoming the limitations of traditional observational studies that rely solely on aircraft observations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Steep sulfur gradient in CZTSSe solar cells by H 2 S-assisted rapid surface sulfurization

Sulfur/selenium grading is a widely used optimization strategy in kesterite thin-film solar cells to obtain a bandgap-graded absorber material and to optimize optical and electrical properties of the solar-cell device. In this work, we present a novel approach to introduce a [S]/([S] + [Se]) grading for Cu 2 ZnSn(S,Se) 4 solar cells. In contrast to commonly used methods with slow process dynamics, the presented approach aims to create a fast sulfurization reaction on the surface of pure selenide kesterite absorbers by using highly reactive H 2 S gas and high sulfurization temperatures in a rapid flash-type process. With a combination of X-ray photoelectron spectroscopy, X-ray emission spectroscopy, Raman spectroscopy, and Raman-shallow angle cross sections spectroscopy, we gain depth-varied information on the [S]/([S] + [Se]) ratio and discuss the impact of different process parameter variations on the material and device properties. The results demonstrate the potential of the developed process to generate a steep gradient of sulfur that is confined mainly to the surface region of the absorber film.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2023

Estimating viscosity of individual substrate-deposited particles from measurements of their height-to-width ratios

Airborne particles alter the radiative forcing of climate and have further consequences on air visibility, atmospheric chemistry, and human health. Recent studies reported the existence of highly viscous semisolid and even solid amorphous organic aerosol (OA) particles. Particle viscosity has an impact on the heterogeneous chemistry, gas-particle partitioning, and ice nucleation properties. Consequently, variations in particle viscosity must be considered when predicting the atmospheric impact of OA. Here, in this work, we use scanning electron microscopy (SEM) and scanning transmission X-ray microscopy (STXM) to estimate the viscosity of individual particles deposited on substrates based on their characteristic height-to-width ratios, which are affected by changes in morphology upon deposition. The height-to-width ratios obtained from SEM and STXM exhibit a strong correlation, demonstrating that both imaging approaches can be applied separately for viscosity assessment of the substrate-deposited particles. While these metrics are largely qualitative, this method enables rapid assessment of particle viscosity ranges, distinguishing between semisolid (>10 10 Pa·s), viscous (10 4– 10 8 Pa·s), and liquid (10°–10 1 Pa·s) particles within ensembles of ambient particles collected for microscopy studies.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Financial-technical co-design for capital-intensive, resource-responsive energy systems

Because of their capital-intensive operation, wind energy systems that are competitive in terms of the cost of the energy that they produce lead to risk-reward trade-offs that make their business cases less favorable than those of conventional energy generation technologies. However, wind energy systems tend to be designed to maximize energy production or minimize cost of energy rather than to maximize their business cases. In this work, we attempt to exploit designs specifically tailored to business cases. We develop a novel framework for analyzing energy systems that ties their design variables to monthly operating incomes using simple models and historical hourly market and resource data. Using this approach, we demonstrate that for a wind site with abundant wind resource in the California Independent System Operator market, we can control the trade-off between mean and 5th percentile monthly returns by choosing the specific power of the turbine at a fixed modeled initial capital cost. Our framework gives a measure of the risk-reward spectrum of energy generation assets that could be built at a given site with respect to the sub-annual resource/market variation.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Understanding Subsidies to Achieve Diesel Powertrain Financial Parity for Heavy-Duty Fuel Cell Electric Vehicles

The development of a long-term sustainable hydrogen energy economy for commercial vehicle transportation will need to overcome key critical technical and logistics considerations in the near term. As compared to zero-emission powertrains, fossil-fuel-based powertrains provide mission flexibility and high uptime at a comparatively low total cost of ownership (TCO). While the incumbent carbon-intensive powertrains suffer from poor efficiency and are not sustainable to support global climate change initiatives in transportation decarbonization, techno-economic challenges continue to create complex barriers to the large-scale displacement of these with highly electrified powertrains architectures. Here, this article specifically addresses opportunities that well-targeted subsidies would afford in achieving fuel cell electric powertrain financial parity with diesel powertrains in heavy-duty trucks (HDTs). It shows that a rigorous assessment of system TCO factors will be critical in designing a viable subsidy strategy. Based on powertrain component and fuel price points, subsidy variations (for both capital expenses and operating fuel expenses) are assessed and quantified to determine where and how much subsidies should be leveraged to accelerate achieving diesel system financial parity. It shows that subsidies on hydrogen fuel expenses (and associated constituents) will play an important role in achieving this goal while subsidies on capital expenses (the more typical subsidy formulation) may not always be the preferred subsidy strategy. The results provide subsidy agencies with clear guidance and a database approach to characterize and implement viable HDT hydrogen powertrain system subsidy strategies. The approach may be readily tailored for other applications and system architectures.

33 ADVANCED PROPULSION SYSTEMS↗
DOE OSTI2023

Assembly and comparative genome analysis of a Patagonian Aureobasidium pullulans isolate reveals unexpected intraspecific variation

Aureobasidium pullulans is a yeast-like fungus with remarkable phenotypic plasticity widely studied for its importance for the pharmaceutical and food industries. So far, genomic studies with strains from all over the world suggest they constitute a genetically unstructured population, with no association by habitat. However, the mechanisms by which this genome supports so many phenotypic permutations are still poorly understood. Recent works have shown the importance of sequencing yeast genomes from extreme environments to increase the repertoire of phenotypic diversity of unconventional yeasts. In this study, we present the genomic draft of A. pullulans strain from a Patagonian yeast diversity hotspot, re-evaluate its taxonomic classification based on taxogenomic approaches, and annotate its genome with high-depth transcriptomic data. Here, our analysis suggests this isolate could be considered a novel variant at an early stage of the speciation process. The discovery of divergent strains in a genomically homogeneous group, such as A. pullulans, can be valuable in understanding the evolution of the species. The identification and characterization of new variants will not only allow finding unique traits of biotechnological importance, but also optimize the choice of strains whose phenotypes will be characterized, providing new elements to explore questions about plasticity and adaptation.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

The influence of tillage and fertilizer on the flux and source of nitrous oxide with reference to atmospheric variation using laser spectroscopy

Nitrous oxide (N 2 O) is the third most important long-lived greenhouse gas and agriculture is the largest source of N 2 O emissions. Curbing N 2 O emissions requires understanding influences on the flux and sources of N 2 O. We measured flux and evaluated microbial sources of N 2 O using site preference ( S P ; the intramolecular distribution of 15 N in N 2 O) in flux chambers from a grassland tilling and agricultural fertilization experiments and atmosphere. We identified values greater than that of the average atmosphere to reflect nitrification and/or fungal denitrification and those lower than atmosphere as increased denitrification. Our spectroscopic approach was based on an extensive calibration with 18 standards that yielded S P accuracy and reproducibility of 0.7 ‰ and 1.0 ‰, respectively, without preconcentration. Chamber samples from the tilling experiment taken ~ monthly over a year showed a wide range in N 2 O flux (0–1.9 g N 2 O-N ha -1 d -1 ) and S P (- 1.8 to 25.1 ‰). Flux and S P were not influenced by tilling but responded to sampling date. Large fluxes occurred in October and May in no-till when soils were warm and moist and during a spring thaw, an event likely representing release of N 2 O accumulated under snow cover. These high fluxes could not be ascribed to a single microbial process as S P differed among chambers. However, the year-long S P and flux data for no-till showed a slight direct relationship suggesting that nitrification increased with flux. The comparative data in till showed an inverse relationship indicating that high flux events are driven by denitrification. Corn ( Zea mays ) showed high fluxes and S P values indicative of nitrification ~ 4 wk after fertilization with subsequent declines in S P indicating denitrification. Although there was no effect of fertilizer treatment on flux or S P in switchgrass ( Panicum virgatum) , high fluxes occurred ~1 month after fertilization. In both treatments, S P was indicative of denitrification in many instances, but evidence of nitrification/fungal denitrification also prevailed. At 2 m atmospheric N 2 O S P had a range of 31.1 ‰ and 14.6 ‰ in the grassland tilling and agricultural fertilization experiments, respectively. These data suggest the influence of soil microbial processes on atmospheric N 2 O and argue against the use of the global average atmospheric S P in isotopic modeling approaches.

Environmental Sciences & Ecology↗
DOE OSTI2023

A phase-field model for hydraulic fracture nucleation and propagation in porous media

Many geo-engineering applications, for example, enhanced geothermal systems, rely on hydraulic fracturing to enhance the permeability of natural formations and allow for sufficient fluid circulation. Over the past few decades, the phase-field method has grown in popularity as a valid approach to modeling hydraulic fracturing because of the ease of handling complex fracture propagation geometries. However, existing phase-field methods cannot appropriately capture nucleation of hydraulic fractures because their formulations are solely energy-based and do not explicitly take into account the strength of the material. Thus, in this work, we propose a novel phase-field formulation for hydraulic fracturing with the main goal of modeling fracture nucleation in porous media, for example, rocks. Built on the variational formulation of previous phase-field methods, the proposed model incorporates the material strength envelope for hydraulic fracture nucleation through two important steps: (i) an external driving force term, included in the damage evolution equation, that accounts for the material strength; (ii) a properly designed damage function that defines the fluid pressure contribution on the crack driving force. In conclusion, the comparison of numerical results for two-dimensional test cases with existing analytical solutions demonstrates that the proposed phase-field model can accurately model both nucleation and propagation of hydraulic fractures. Additionally, we present the simulation of hydraulic fracturing in a three-dimensional domain with various stress conditions to demonstrate the applicability of the method to realistic scenarios.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

A regularized-interface method as a unified formulation for simulations of high-pressure multiphase flows

The injection of multi-species fluids into high-pressure and high-temperature environments beyond the species' critical points is commonly found in engineering applications. At these conditions, for immiscible species, both subcritical interfacial dynamics and supercritical mixing can coexist due to variations in temperature around the mixture critical point. The modeling of these complex transcritical phenomena for large-scale configurations is so far not possible. To address this issue, we propose the Regularized-Interface Method (RIM) as a unified formulation that can describe both sub- and supercritical processes as well as the transition between them. The proposed method is derived via filtering of the nanoscale interface-resolving formulation based on van der Waals' linear gradient theory. Thus, this approach allows for the consistent modeling of interfacial dynamics that vanishes at supercritical conditions, while significantly reducing the temporal and spatial resolution constraints of the original nanoscale formulation. The resulting RIM formulation is examined in interface-capturing simulations of sub-, trans-, and supercritical fuel injection processes, involving droplets and jets. Furthermore, these results highlight the importance of resolving spatio-temporal transitions from subcritical interfacial dynamics to supercritical mixing in high-pressure multiphase simulations, in contrast to commonly employed diffused-interface methods, where interfacial dynamics are often neglected.

Interface capturing↗
DOE OSTI2025

In situ high-temperature Raman spectroscopy for online EAF slag analysis

Real-time monitoring of slag chemistry is critical for optimizing Electric Arc Furnace (EAF) steelmaking operations, where dynamic variations in slag composition directly influence slag foaming, refractory degradation, and thermal efficiency. Conventional techniques such as X-ray fluorescence (XRF), Fourier-transform infrared (FTIR), and scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM-EDS) are commonly used to analyze slag composition, but their offline nature and equipment constraints limit their applicability for online monitoring in harsh industrial environments. To address this challenge, we present an in situ, high-temperature analytical approach that integrates Raman spectroscopy with a custom designed fiber-optic probe for real-time slag characterization at 1550 °C. The system enables non destructive spectral acquisition from molten slags, providing molecular-level insights into silicate polymerization and iron oxidation states. Eight synthetic slag samples were evaluated, and key Raman features—such as Q n silicate units and FeO₄/FeO₆ coordination environments—were identified and quantitatively correlated with slag basicity and Fe₂O₃ content. The results demonstrate agreement between Raman spectral ratios and bulk slag chemistry, validating the method’s capability to track compositional and structural changes under molten temperature. This work establishes the feasibility of deploying fiber-optic Raman probe for online EAF slag monitoring and highlights their potential to support closed-loop control strategies, thereby enhancing process stability, refractory protection, and steel quality in industrial steelmaking applications.

47 OTHER INSTRUMENTATION↗
DOE OSTI2021

Mitigating Injection‐Induced Seismicity Along Basement Faults by Extraction: Application to 2016–2018 Pohang Earthquakes

Abstract The risk of induced earthquake is considered as the major obstacle for sustainable subsurface energy activities. As a mitigation approach, mechanistic risk assessment can be essential to minimize the potential of seismic hazard. Coupled hydro‐mechanical modeling approach is integrated with geomechanical analysis to better assess the occurrence of seismicity induced by injection and/or extraction, which will provide a basis to update operational conditions (e.g., number and location of mitigating wells, rate and duration of operations) for mitigating earthquake nucleation. The Coulomb stability analysis and seismicity rate estimates from this generic study indicate that simultaneous extraction can relieve injection‐induced pore‐pressure buildup, but also transfer and accumulate elastic energy along the faults. Field‐scale simulation with variation in well design for the Pohang EGS site, South Korea, show that multiple wells aligned across a preexisting fault form gradients of pressure and stress fields normal to the fault, which can enhance the direct impact of diffusion process and poroelastic stressing on the fault stability perturbation. Our mechanistic study suggests multiphysics‐oriented mitigation strategies that consider (1) possible mechanical deformation, caused by hydro‐mechanical coupling effects, and (2) proper configuration of well operations based on site‐specific geological characteristics.

Chang, K. W.↗
DOE OSTI2023

Wave-function-based emulation for nucleon-nucleon scattering in momentum space

Emulators for low-energy nuclear physics can provide fast and accurate predictions of bound-state and scattering observables for applications that require repeated calculations with different parameters, such as Bayesian uncertainty quantification. In this paper, we extend a scattering emulator based on the Kohn variational principle (KVP) to momentum space (including coupled channels) with arbitrary boundary conditions, which enable the mitigation of spurious singularities known as Kohn anomalies. We test it on a modern chiral nucleon-nucleon (N N) interaction, including emulation of the coupled channels. We provide comparisons between a Lippmann-Schwinger equation emulator and our KVP momentum-space emulator for a representative set of neutron-proton (n p) scattering observables, and also introduce a quasi-spline-based approach for the KVP-based emulator. Furthermore, our findings show that while there are some trade-offs between accuracy and speed, all three emulators perform well. Self-contained Jupyter notebooks that generate the results and figures in this paper are publicly available.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2021

Global Sensitivity Analysis of Large Distribution System with PVs using Deep Gaussian Process

Global sensitivity analysis (GSA) of the voltage to uncertain power injection variations plays an important role for appropriate Volt-VAR optimization. This paper proposes a data-driven GSA method for large-scale distribution systems with a large number of uncertain sources. Specifically, the deep Gaussian process is used to identify the mapping relationship between uncertain power injections and voltages. This allows us to resort to the analysis of variance framework to calculate the Sobol indices for GSA. Unlike the existing polynomial chaos expansion and Gaussian process-based approaches, our proposed method has much better scalability. Test results on the EPRI 1747-node K1 circuit with a different number and different probability distributions of uncertain sources demonstrate that the proposed method can achieve accurate GSA under various conditions.

14 SOLAR ENERGY↗
DOE OSTI2021

Invasion and rapid adaptation of guppies ( Poecilia reticulata ) across the Hawaiian Archipelago

How much does natural selection, as opposed to genetic drift, admixture, and gene flow, contribute to the evolution of invasive species following introduction to a new environment? Here we assess how evolution can shape biological invasions by examining population genomic variation in non-native guppies (Poecilia reticulata) introduced to the Hawaiian Islands approximately a century ago. By examining 18 invasive populations from four Hawaiian islands and four populations from the native range in northern South America, we reconstructed the history of introductions and evaluated population structure as well as the extent of ongoing gene flow across watersheds and among islands. Patterns of differentiation indicate that guppies have developed significant population structure, with little natural or human-mediated gene flow having occurred among populations following introduction. Demographic modeling and admixture graph analyses together suggest that guppies were initially introduced to O‘ahu and Maui and then translocated to Hawai‘i and Kaua‘i. We detected evidence for only one introduction event from the native range, implying that any adaptive evolution in introduced populations likely utilized the genetic variation present in the founding population. Environmental association tests accounting for population structure identified loci exhibiting signatures of adaptive variation related to predators and landscape characteristics but not nutrient regimes. When paired with high estimates of effective population sizes and detectable population structure, the presence of environment-associated loci supports the role of natural selection in shaping contemporary evolution of Hawaiian guppy populations. Our findings indicate that local adaptation may engender invasion success, particularly in species with life histories that facilitate rapid evolution. Finally, evidence of low gene flow between populations suggests that removal could be an effective approach to control invasive guppies across the Hawaiian archipelago.

59 BASIC BIOLOGICAL SCIENCES↗