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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 235 records · Page 13
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

The enduring role of contracts for difference in risk management and market creation for renewables

Governments procure renewables through a variety of mechanisms. Contracts for difference (CfDs) have been used for more than 50% of the global offshore wind supply. The payments awarded through CfDs are sometimes labelled subsidies, suggesting that they support uneconomic activity. Here, in this study, we argue that the primary role of CfDs is rather risk management by creating a market for electricity supply at stable long-term prices. Similar to its use in other sectors of the economy, this contract type transforms a variable to a fixed price to reallocate volatility risks. Such long-term contracts are often necessary for renewables financing due to limited hedging options in existing markets. Our perspective could imply a shift in perception towards CfDs as a fundamental and lasting market feature. We hope to stimulate a timely discussion about the impact of greater CfD diffusion on electricity market mechanisms, risk allocation and the potential for combining fragmented streams of energy finance, market and policy research.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2026

Identifying materials-level sources of performance variation in superconducting transmon qubits

The Superconducting Quantum Materials and Systems Center, a U. S. Department of Energy National Quantum Information Science Research Center, has conducted a comprehensive and coordinated study using superconducting transmon qubit chips with known performance metrics to identify the underlying materials-level sources of device-to-device performance variation. Following qubit coherence measurements, these qubits of varying base superconducting metals and substrates have been examined with various non-destructive and invasive material characterization techniques at Northwestern University, Ames National Laboratory, and Fermilab as part of a blind study. We find trends in variations of the depth of the etched substrate trench, the thickness of the surface oxide, and the geometry of the sidewall, which when combined, lead to correlations with the T1 lifetime across different qubits on the same chip. In addition, we provide a list of features that varied from device to device, for which the impact on performance requires further studies. Finally, we identify two low-temperature characterization techniques that may potentially serve as proxy tools for qubit measurements. These insights provide materials-oriented solutions to not only reduce performance variations across neighboring devices but also to engineer and fabricate devices with optimal geometries to achieve performance metrics beyond the state-of-the-art values.

Murthy, Akshay A. [Fermilab] (ORCID:00000001767768↗
DOE OSTI2023

TROPHY: A Topologically Robust Physics-Informed Tracking Framework for Tropical Cyclones

Tropical cyclones (TCs) are among the most destructive weather systems. Realistically and efficiently detecting and tracking TCs are critical for assessing their impacts and risks. In particular, the eye is a signature feature of a mature TC. Therefore, knowing the eyes’ locations and movements is crucial for both operational weather forecasts and climate risk assessments. Recently, a multilevel robustness framework has been introduced to study the critical points of time-varying vector fields. The framework quantifies the robustness (i.e., structural stability) of critical points across varying neighborhoods. By relating the multilevel robustness with critical point tracking, the framework has demonstrated its potential in cyclone tracking. An advantage is that it identifies cyclonic features using only 2D wind vector fields, which is encouraging as most tracking algorithms require multiple dynamic and thermodynamic variables at different altitudes. A disadvantage is that the framework does not scale well computationally for datasets containing a large number of cyclones. Herein this paper introduces a topologically robust physics-informed tracking framework (TROPHY) for TC tracking. The main idea is to integrate physical knowledge of TC to drastically improve the computational efficiency of multilevel robustness framework for large-scale climate datasets. First, during preprocessing, we propose a physics-informed feature selection strategy to filter 90% of critical points that are short-lived and have low stability, thus preserving good candidates for TC tracking. Second, during in-processing, we impose constraints during the multilevel robustness computation to focus only on physics-informed neighborhoods of TCs. We apply TROPHY to 30 years of 2D wind fields from reanalysis data in ERA5 and generate a number of TC tracks. In comparison with the observed tracks, we demonstrate that TROPHY can capture TC characteristics (e.g., frequency, intensity, duration, latitudes with maximum intensity, and genesis) that are comparable to and sometimes even better than a well-validated TC tracking algorithm that requires multiple dynamic and thermodynamic scalar fields.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2020

The influence of irregular terrain on infrasonic propagation in the troposphere

The relations describing the reflection of three-dimensional acoustic ray paths impinging on a non-flat surface are derived and used to approximate the propagation of infrasonic signals over irregular terrain in the geometric limit. The influence of non-flat ground is strongest for those paths that reflect off the surface multiple times, such as those in the tropospheric waveguide; however, notable differences in source and receiver elevations for stratospheric and thermospheric paths can produce notable differences in travel times and arrival amplitudes. The interaction of ray paths with topographical features is investigated using a simple hill to demonstrate the impact of topography on propagation within an azimuthal plane, as well as cases in which the ground surface interaction deflects the path out of the azimuthal plane. Finally, broadband waveform predictions are compared with observations for an event in the western U.S., and a statistical analysis of scattering losses due to interaction with topography in the limit of geometric acoustics is used to improve the agreement between predicted and observed infrasonic signals.

47 OTHER INSTRUMENTATION↗
DOE OSTI2025

STZ: A High Quality and High Speed Streaming Lossy Compression Framework for Scientific Data

Error-bounded lossy compression is one of the most efficient solutions to reduce the volume of scientific data. For lossy compression, progressive decompression and random-access decompression are critical features that enable on-demand data access and flexible analysis workflows. However, these features can severely degrade compression quality and speed. To address these limitations, we propose a novel streaming compression framework that supports both progressive decompression and random-access decompression while maintaining high compression quality and speed. Our contributions are three-fold: (1) we design the first compression framework that simultaneously enables both progressive decompression and random-access decompression; (2) we introduce a hierarchical partitioning strategy to enable both streaming features, along with a hierarchical prediction mechanism that mitigates the impact of partitioning and achieves high compression quality—even comparable to state-of-the-art (SOTA) non-streaming compressor SZ3; and (3) our framework delivers high compression and decompression speed, up to 6.7 × faster than SZ3.

Wang, Daoce [University of Nebraska, Omaha]↗
DOE OSTI2025

Physics-driven Explosions of Stripped High-mass Stars: Synthetic Light Curves and Spectra of Stripped-envelope Supernovae with Broad Light Curves

Stripped-envelope supernovae (SESNe) represent a significant fraction of core-collapse supernovae, arising from massive stars that have shed their hydrogen and, in some cases, helium envelopes. The origins and explosion mechanisms of SESNe remain a topic of active investigation. In this work, we employ radiative-transfer simulations to model the light curves and spectra of a set of explosions of single, solar-metallicity, massive Wolf–Rayet stars with ejecta masses ranging from 4 to 11 M ⊙ , which were computed from a turbulence-aided and neutrino-driven explosion mechanism. We analyze these synthetic observables to explore the impact of varying ejecta mass and helium content on observable features. We find that the light curve shape of these progenitors with high ejecta masses is consistent with observed SESNe with broad light curves but not the peak luminosities. The commonly used analytic formula based on rising bolometric light curves overestimates the ejecta mass of these high-initial-mass progenitor explosions by a factor of up to 2.6. In contrast, the calibrated method by Haynie et al., which relies on late-time decay tails, reduces uncertainties to an average of 20% within the calibrated ejecta mass range. Spectroscopically, the He I 1.083 μm line remains prominent even in models with as little as 0.02 M ⊙ of helium. However, the strength of the optical He I lines is not directly proportional to the helium mass but instead depends on a complex interplay of factors such as the 56 Ni distribution, composition, and radiation field. Thus, producing realistic helium features requires detailed radiative transfer simulations for each new hydrodynamic model.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2021

xSDK: Building an ecosystem of highly efficient math libraries for exascale

Current efforts to build increasingly powerful computer architectures are opening up new avenues for more complex and higher fidelity simulations coupled with data analytics and learning, leading to new scientific insights and deeper understanding. At one extreme, exascale computers will be much faster than previous computer generations (performing 10 18 operations per second—that is, 1,000 times faster than petascale). To achieve these performance improvements, computer architectures are becoming increasingly complex, with deep memory hierarchies, very high node and core counts, and heterogeneous features such as graphics processing units (GPUs). Such architectural changes impact the full breadth of computing scales, as heterogeneity pervades even current-generation laptops, workstations, and moderate-sized clusters. While emerging advanced architectures provide unprecedented opportunities, they also present significant challenges for developers of scientific applications, such as multiphysics and multiscale codes, who must adapt their software to handle disruptive changes in architectures and new programming models that have not yet stabilized. Developers must consider increasing concurrency while reducing communication and synchronization, and other complexities such as the potential for using mixed precision to leverage the compute power available in low-precision tensor cores. On one hand, developers must implement new scientific capabilities, which in turn increase code complexity. On the other hand, the codes must be ported to new architectures, requiring the inclusion of new programming models and the restructuring of code to achieve good performance. Addressing these issues is beyond the capability of any single person or team—leading to the need for collaboration among many teams, who encapsulate their expertise in reusable software and work together to create sustainable software ecosystems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2024

Simulator Data Analysis to Inform Digitalized Environment Impacts on Human Reliability

The U.S. Nuclear Regulatory Commission (NRC) has developed a human reliability analysis (HRA) method, termed the Integrated Human Event Analysis System for Event and Condition Assessment (IDHEAS-ECA), in order to estimate human error probabilities (HEPs) in risk-informed regulatory applications. To update the quantification part of IDHEAS-ECA, the NRC required human performance and error data from fully digitalized main control rooms (MCRs); therefore, it requested that Idaho National Laboratory (INL) revisit previous data collection studies and investigate how the following three factors impact human reliability: self-checking, peer-checking, and automation. The HRA data collection studies revisited were the Human Reliability Data Extraction (HuREX) project, developed by the Korea Atomic Energy Research Institute (KAERI), and the Simplified Human Error Experimental Program (SHEEP), developed by INL. HuREX is a representative HRA data collection study that collects human reliability data from full-scope simulators staffed by licensed operators. SHEEP, on the other hand, has been proposed to complement such full-scope studies by collecting data via simplified simulators staffed by non-licensed student operators. In the HuREX study, KAERI collected HRA data from fully digitalized MCRs for the Advanced Power Reactor (APR)–1400. The SHEEP data were obtained from simplified simulators that partially mimicked the features of digitalized MCRs. The present report mainly discusses how the impacts of the aforementioned three factors on human errors were derived from these two data collection studies.

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2020

Multi-Temporal Predictive Modelling of Sorghum Biomass Using UAV-Based Hyperspectral and LiDAR Data

High-throughput phenotyping using high spatial, spectral, and temporal resolution remote sensing (RS) data has become a critical part of the plant breeding chain focused on reducing the time and cost of the selection process for the “best” genotypes with respect to the trait(s) of interest. In this paper, the potential of accurate and reliable sorghum biomass prediction using visible and near infrared (VNIR) and short-wave infrared (SWIR) hyperspectral data as well as light detection and ranging (LiDAR) data acquired by sensors mounted on UAV platforms is investigated. Predictive models are developed using classical regression-based machine learning methods for nine experiments conducted during the 2017 and 2018 growing seasons at the Agronomy Center for Research and Education (ACRE) at Purdue University, Indiana, USA. The impact of the regression method, data source, timing of RS and field-based biomass reference data acquisition, and the number of samples on the prediction results are investigated. R2 values for end-of-season biomass ranged from 0.64 to 0.89 for different experiments when features from all the data sources were included. Geometry-based features derived from the LiDAR point cloud to characterize plant structure and chemistry-based features extracted from hyperspectral data provided the most accurate predictions. Evaluation of the impact of the time of data acquisition during the growing season on the prediction results indicated that although the most accurate and reliable predictions of final biomass were achieved using remotely sensed data from mid-season to end-of-season, predictions in mid-season provided adequate results to differentiate between promising varieties for selection. The analysis of variance (ANOVA) of the accuracies of the predictive models showed that both the data source and regression method are important factors for a reliable prediction; however, the data source was more important with 69% significance, versus 28% significance for the regression method.

09 BIOMASS FUELS↗
DOE OSTI2020

A Partial Coupling Method to Isolate the Roles of the Atmosphere and Ocean in Coupled Climate Simulations

This study describes the formulation and application of a partial coupling method that disentangles the coupling between the atmosphere and ocean and isolates the atmosphere- and ocean-driven components of the coupled climate interactions. In contrast to strategies using stand-alone simulations with prescribed atmosphere or ocean states, the climate components in the partially coupled method remain coupled, but the impact of ocean circulation changes is removed from the air-sea interaction using temperature-like tracers. The partially coupled simulation thereby suppresses the ocean-driven interaction and isolates an atmosphere-driven interaction only. The ocean-driven component can be inferred by comparing climate response in the partially coupled simulation with that of a standard fully coupled one. The partial coupling approach is applied to decompose the fully coupled climate response to CO 2 quadrupling into atmosphere- and ocean-driven components. The linearity of the decomposition is validated by simulating the ocean-driven response using another complimentary partially coupled simulation forced only with the atmosphere-driven anomalous surface fluxes. A comparison of the two partially coupled simulations with the fully coupled simulation indicates that the sum of the atmosphere- and ocean-driven components accurately describes the fully coupled response. The decomposition identifies several robust atmosphere- and ocean-driven features of the global warming and provides new insights into the impacts of atmospheric feedbacks on the Atlantic overturning circulation and sea ice response to CO 2 increase.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Blockage and speedup in the proximity of an onshore wind farm: A scanning wind LiDAR experiment

To maximize the profitability of wind power plants, wind farms are often characterized by high wind turbine density leading to operations with reduced turbine spacing. As a consequence, the overall wind farm power capture is hindered by complex flow features associated with flow modifications induced by the various wind turbine rotors. In addition to the generation of wakes, the velocity of the incoming wind field can reduce due to the increased pressure in the proximity of a single turbine rotor (named induction); a similar effect occurs at the wind-farm level (global blockage), which can have a noticeable impact on power production. On the other hand, intra-wind-farm regions featuring increased velocity compared to the freestream (speedups) have also been observed, which can be a source for a potential power boost. To quantify these rotor-induced effects on the incoming wind velocity field, three profiling LiDARs and one scanning wind LiDAR were deployed both before and after the construction of an onshore wind turbine array. The different wind conditions are classified according to the ambient turbulence intensity and streamwise/spanwise spacing among wind turbines. The analysis of the mean velocity field reveals enhanced induction and speedup under stably stratified atmospheric conditions. Additionally, a reduced horizontal area between adjacent turbines has a small impact on the induction zone but increases significantly the speedup between adjacent rotors.

17 WIND ENERGY↗
DOE OSTI2023

The Impact of Inherited Morphology on Sandbar Migration During Mild Wave Seasons

Sandbars are ubiquitous morphologic features found in the nearshore environment throughout the world, yet predictive capabilities of their evolution remain limited. In order to provide new insights on the relevant processes controlling sandbar morphodynamics, this study uses a 41-year record of 637 monthly cross-shore profiles from Duck, North Carolina, USA, to derive complex empirical orthogonal functions representative of the two dominant modes of sandbar migrations: offshore and onshore propagation. Interference of these two modes produces commonly observed sandbar states. While mild wave energies are traditionally assumed to drive onshore sandbar migration, the offshore mode is repeatedly seen to dominate sandbar migration in mild wave seasons following anomalously high late-winter wave energy and when the inherited morphology is composed of a single bar or terrace, as opposed to a more common two-bar state. A data-derived conceptual model is presented synthesizing the effect of antecedent morphology and wave climate chronology on interannual trends in net offshore sandbar migration.

58 GEOSCIENCES↗
DOE OSTI2023

Novel features of attractors and transseries in nonconformal Bjorken flows

In this work we investigate the impact of conformal symmetry breaking on hydrodynamization of a far-from-equilibrium fluid. We find a new kind of transseries solutions for the nonconformal hydrodynamic equations of a longitudinal boost invariant expanding plasma. The new transseries solutions unveil a rich physical structure which arises due to the interplay of different physical scales. In the perfect fluid case the nonconformal speed of sound slows down the cooling of the temperature due to the emergence of logarithmic corrections that depends on the mass of the particle. Further, these terms propagate into the perturbative and nonperturbative sectors of the transseries once viscous corrections are included. The logarithmic mass contributions increase the asymptotic value of the Knudsen number while decreasing the damping rate of the transient nonhydrodynamic modes and thus, yielding to an extremely slow hydrodynamization process where flow lines merge to their forward attractor at extremely late times. The early time free streaming expansion is modified and receives logarithmic mass corrections induced by the shear-bulk couplings. The global flow structure and numerical analyses carried out in our work demonstrate the existence of local attraction at early and late times for the shear viscous tensor and bulk viscous pressure.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2023

Daytime convective development over land: the role of surface forcing

Water availability at the Earth surface determines the portioning of the surface heat flux into its sensible and latent components, that is, the surface heat flux Bowen ratio. The two components affect differently the surface buoyancy flux and thus the development and growth of the convective boundary layer. As a result, the Bowen ratio has a strong impact on the daytime dry and moist convection development over land. Here, we use two canonical modeling test cases, one for the shallow convection and one for the shallow-to-deep convection transition, to document the impact of the surface Bowen ratio on daytime convection development. A simple approach is used where results from simulations featuring the original setup are contrasted with simulations where surface sensible heat flux takes on values of the latent heat flux and vice versa. Such a change illustrates the key impact of the surface water availability without changing the total surface heat flux. Because of the larger surface buoyancy flux, simulations with the reversed surface heat fluxes feature faster deepening of the convective boundary layer and wider clouds once moist convection develops. Mean cloud base width of cumulus clouds increases with the boundary layer depth. For shallow-to-deep convection transition, comparison of simulations with the observed large-scale flow that feature substantial lower-tropospheric shear with simulations with no mean horizontal flow suggests that the organization of convective circulations within the boundary layer strongly affects initial size and organization of shallow convection, as well as the subsequent width increase once convection deepens and eventually transitions to deep precipitating convection. A simple explanation is provided of why deeper well-mixed convective subcloud layer results in wider clouds. The key is the larger width of boundary layer coherent updraft structures when the mixed layer is deeper.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

SALT2 versus SALT3: updated model surfaces and their impacts on type Ia supernova cosmology

ABSTRACT For the past decade, SALT2 has been the most common model used to fit Type Ia supernova (SN Ia) light curves for dark energy analyses. Recently, the SALT3 model was released, which upgraded a number of model features but has not yet been used for measurements of dark energy. Here, we evaluate the impact of switching from SALT2 to SALT3 for a SN cosmology analysis. We train SALT2 and SALT3 on an identical training sample of 1083 well-calibrated Type Ia supernovae, ensuring that any differences found come from the underlying model framework. We publicly release the results of this training (the SALT ‘surfaces’). We then run a cosmology analysis on the public Dark Energy Survey 3-Yr Supernova data sample (DES-SN3YR), and on realistic simulations of those data. We provide the first estimate of the SN + CMB systematic uncertainty arising from the choice of SALT model framework (i.e. SALT2 versus SALT3), Δw = + 0.001 ± 0.005 – a negligible effect at the current level of dark energy analyses. We also find that the updated surfaces are less sensitive to photometric calibration uncertainties than previous SALT2 surfaces, with the average spectral energy density dispersion reduced by a factor of two over optical wavelengths. This offers an opportunity to reduce the contribution of calibration errors to SN cosmology uncertainty budgets.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

Reactivity-initiated accidents in two pressurized water reactor high burnup core designs

Here, this paper presents a safety analysis of two proposed core loadings for 24-month Pressurized Water Reactor (PWR) fuel cycles. This analysis focuses on reactivity-initiated accidents (RIAs) and evaluates core safety performance impacts of rod-averaged burnup limits up to 75 GWD/MTU and less than 7 % enriched UO 2 . The capabilities of Polaris, PARCS, and RELAP5-3D are leveraged to evaluate the core neutronic and thermal–hydraulic behavior for normal-operation, uncontrolled control rod withdrawal (CRW) transients, and control rod ejection (CRE) accidents. The two core designs are compared to identify features of realistic high burnup/extended enrichment core design approaches which have significant safety impact, identify experimental data needs for high-fidelity predictive modeling, and provide recommendations for future high burnup core designs. The first core design evaluated in this study was developed by Southern Nuclear Company and used an ZrB 2 Integral Fuel Burnable Absorber (IFBA) and B 4 C Wet-Annular Burnable Absorber (WABA)-based burnable poison strategy. The second core design assessed in this work used a Gd 2 O 3 -doped UO 2 burnable poison, similar to that used in boiling water reactors or French PWRs. Results indicate that fuel thermal limits are maintained for limiting CRW and hot full power (HFP) CRE transients. Cladding failure is predicted for the highest energy deposition rods in each core during limiting hot zero power (HZP) CRE accidents (where maximum radially averaged enthalpy exceeds 120 cal/g), though licensing may be permissible with a limited number of failed rods. While concerns exist regarding high critical boron concentration during steady state for the IFBA core and large plenum pressures for the gadolinia core design, the analysis demonstrates adequate safety performance during limiting RIA accident scenarios for two representative high burnup core designs. Design changes limiting plenum pressures and implementation of accident tolerant fuel (ATF) cladding features which minimize hydriding and susceptibility to pellet-cladding mechanical interaction (PCMI) are recommended for future high burnup fuel concepts. To support the technical basis for burnup limit increases, high-fidelity fuel performance models are needed to address physical effects not considered in this analysis, and high burnup irradiated fuel tests are required to extend applicability of the fuel failure limits and validate existing and future models.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Nonlinear dimension reduction for surrogate modeling using gradient information

We introduce a method for the nonlinear dimension reduction of a high-dimensional function $u:{\mathbb{R}}^d\rightarrow{\mathbb{R}}$, $d\gg 1$. Our objective is to identify a nonlinear feature map $g:{\mathbb{R}}^d\rightarrow{\mathbb{R}}^m$, with a prescribed intermediate dimension $m\ll d$, so that $u$ can be well approximated by $f\circ g$ for some profile function $f:{\mathbb{R}}^m\rightarrow{\mathbb{R}}$. We propose to build the feature map by aligning the Jacobian $\nabla g$ with the gradient $\nabla u$, and we theoretically analyze the properties of the resulting $g$. Once $g$ is built, we construct $f$ by solving a gradient-enhanced least squares problem. Our practical algorithm uses a sample $\{{\textbf{x}}^{(i)},u({\textbf{x}}^{(i)}),\nabla u({\textbf{x}}^{(i)})\}_{i=1}^N$ and builds both $g$ and $f$ on adaptive downward-closed polynomial spaces, using cross validation to avoid overfitting. We numerically evaluate the performance of our algorithm across different benchmarks, and explore the impact of the intermediate dimension $m$. We show that building a nonlinear feature map $g$ can permit more accurate approximation of $u$ than a linear $g$, for the same input data set.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2023

Numerical and Experimental Study of an Aircraft Igniter Plasma Jet Discharge

The spark discharge of an aircraft plasma jet igniter is studied using high-fidelity numerical simulations and X-ray radiography measurements. The target problem here features the thermal expansion of hot gas introduced by the electric spark within a confined igniter cavity, which eventually evolves into a pulsed jet of a high-temperature kernel. A comprehensive set of models adapted from existing strategies for internal combustion engine spark plug discharge is extended to the target problem, including the modeling of energy deposition, plasma reactions, thermodynamic properties, and heat losses. A series of validation and parameter studies are performed and presented. The kernel size is found to be sensitive to heat losses arising from radiation and hot gas remained within the discharge cavity, rather than heat conduction to the wall in the discharge cavity. Depending on the enforced shape of the post-breakdown electric arc, the spark kernel can be off-centered, tilted, and considerably asymmetric. These features have been previously not considered when studying such igniter configurations and may have a first-order impact on the ignition process. Provided a proper setup of the heat loss models and electric arc shape, the numerical results are quantitatively comparable to the experimental results in terms of the kernel size, shape, and velocity throughout different stages after the spark discharge.

Tang, Yihao↗