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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 793 records · Page 44
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

The impact and mitigation of broad-absorption-line quasars in Lyman α forest correlations

ABSTRACT Correlations in and with the flux transmission of the Lyman α (Ly α) forest in the spectra of high-redshift quasars are powerful cosmological tools, yet these measurements can be compromised if the intrinsic quasar continuum is significantly uncertain. One particularly problematic case is broad-absorption-line (BAL) quasars, which exhibit blueshifted absorption associated with many spectral features that are consistent with outflows of up to ∼0.1c. As these absorption features can both fall in the forest region and be difficult to distinguish from Ly α absorption, cosmological analyses eliminate the ∼12–16 per cent of quasars that exhibit BALs. In this paper, we explore an alternate approach that includes BALs in the Ly α autocorrelation function, with the exception of the expected locations of the BAL absorption troughs. This procedure returns over 95 per cent of the path-length that is lost by the exclusion of BALs, as well as increasing the density of sightlines. We show that including BAL quasars reduces the fractional uncertainty in the covariance matrix and correlation function by 12 per cent and does not significantly change the shape of the correlation function relative to analyses that exclude BAL quasars. We also evaluate different definitions of BALs, masking strategies, and potential differences in the quasar continuum in the forest region for BALs with different amounts of absorption.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Molecular Characterization of Organosulfate-Dominated Aerosols over Agricultural Fields from the Southern Great Plains by High-Resolution Mass Spectrometry

The molecular composition of organic aerosols, especially for day/nighttime variations of organosulfates above agricultural fields, is not well understood despite profound impacts on regional climate, crop production, air quality, and human health. Here, nanospray desorption electrospray ionization with high-resolution mass spectrometry (nano-DESI-HRMS) is used to interrogate the molecular composition of organic aerosols collected at the Southern Great Plains, located in an agricultural region of Oklahoma. Identified molecular formulae featured carbon, hydrogen, oxygen (CHO), nitrogen (CHNO), and/or sulfur (CHOS, CHNOS), with higher organosulfate proportions during daytime (41%) compared to nighttime (30%). In this work, nighttime aerosols featured increases in CHO, CHNO, and extremely low volatility organic carbon (ELVOC) species. However, due to high relative humidity, the nighttime aerosols phase state was found to be more liquid-like than daytime aerosols using parametrized glass transition temperatures. Aerosol molecular composition from an anthropogenically influenced plume (southerly winds) showed significant increases in CHOS and ELVOC species. By comparison with chamber studies, CHOS species are suspected to be of mixed biogenic and anthropogenic origin, whereas CHNOS species (not identified in the southerly winds) are suggested to predominately be of biogenic origin. Overall, this study provides key insight into organosulfates above agricultural fields, demonstrating dependence upon day/night cycles and episodic anthropogenic emissions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2025

Geometric control of hyperbolic exciton-polariton condensate dimers

Coupled many-body quantum systems exhibit rich emergent physics with diverse stationary and dynamical behaviours. By engineering platforms with tunable and distinct coupling mechanisms, new insights emerge into the collective behaviour of coupled many body systems. Particles can be exchanged via evanescent or ballistic coupling: the former, based on proximity, yields large spectral splitting, while the latter requires strict phase-matching, analogous to phase-coupled harmonic oscillators and has a smaller impact on the energy landscape. We demonstrate an all-optically tunable quantum fluid dimer based on exciton-polariton condensates in a photonic crystal waveguide with hyperbolic (saddle-like) dispersion. Varying the dimer’s angle relative to the grating tunes the coupling from evanescent to ballistic. We directly observe spectral features and mass flow shaped by the saddle dispersion. This work highlights photonic crystals as powerful platforms to explore condensed matter phenomena lying at the interface between delay-coupled nonlinear oscillators and tight binding physics.

Georgakilas, Ioannis [IBM Research-Zurich, Rüschli↗
DOE OSTI2021

Development of Explainable, Knowledge-Guided AI Models to Enhance the E3SM Land Model Development and Uncertainty Quantification

Focal Area(s): (2)Predictive modeling using AI techniques and AI-derived model components; use of AI and other tools to design a prediction system comprising of a hierarchy of models. (3) Insight gleaned from complex data (both observed and simulated) using AI, big data analytics, and other advanced methods, including explainable AI and physics- or knowledge- guided AI. Science Challenge: The Energy Exascale Earth System Model (E3SM) is a fully coupled, state-of-the-science Earth system model that uses code optimized for DOE's advanced computers to address the most critical scientific questions facing our nation and society (Golaz et al., 2019). The E3SM Land model (ELM) is designed to understand how the changes in terrestrial land surfaces will interact with other Earth system components and has been used to understand hydrologic cycles, biogeophysics, and ecosystem dynamics. In spite of great successes, the ELM has several known issues that restrain rapid improvements. For example, the ELM uses equilibrium models to simulate dynamic land-climate interactions and it requires long model spin-up time to identify suitable initial conditions for transient simulations. The ELM lacks built-in uncertainty mechanisms that can improve the robustness of model predictions. The ELM is a holistic, deterministic model system with a rigid design, and in many situations, it is hard to modify the ELM system to incorporate new theory/hypothesis and new data across scales to address emerging science problems (such as predicting the impacts of water cycle extremes). In addition, The ELM is technically optimized for traditional CPU-centric computers and it cannot fully utilize the current and incoming leadership computers for model simulations and uncertainty quantification (UQ). The success of artificial intelligence (AI) has inspired scientists to use AI models to discover intrinsic features from simulation data (Chattopadhyay et al., 2020) and observational data (Reichstein et al., 2019) to gain further process understanding of Earth science problems. However, autonomous AI model training through deep learning usually requires a huge amount of annotated data. To overcome the limitations from the data and computing resources, knowledge-guided AI models are necessary where human-knowledge is ingested in model construction (Banino et al., 2018) and training process (Silver et al., 2016) for efficient learning. Herein, we present a new way that leverages the process understanding from the ELM to guide AI model development for the ELM enhancement and UQ. We hope this study can inspire further Earth and environmental system model developments and transformations.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Strategic Petroleum Reserve Cavern Leaching Monitoring CY21

Th e U.S. Strategic Petroleum Reserve (SPR) is a crude oil storage system administered by the U.S. Department of Energy. The reserve consists of 60 active storage caverns located in underground salt domes spread across four sites in Louisiana and Texas, near the Gulf of Mexico. Beginning in 2016, the SPR started executing C ongressionally mandated oil sales. The configuration of the reserve, with a total capacity of greater than 700 million barrels ( MMB ) , re quires that unsaturated water (referred to herein as ?raw? water) is injected into the storage caverns to displace oil for sales , exchanges, and drawdowns . As such, oil sales will produce cavern growth to the extent that raw water contacts the salt cavern walls and dissolves (leaches) the surrounding salt before reaching brine saturation. SPR injected a total of over 45 MMB of raw water into twenty - six caverns as part of oil sales in CY21 . Leaching effects were monitored in these caverns to understand how the sales operations may impact the long - term integrity of the caverns. While frequent sonars are the most direct means to monitor changes in cavern shape, they can be resource intensive for the number of caverns involved in sales and exchanges. An interm ediate option is to model the leaching effects and see if any concerning features develop. The leaching effects were modeled here using the Sandia Solution Mining Code , SANSMIC . The modeling results indicate that leaching - induced features do not raise co ncern for the majority of the caverns, 15 of 26. Eleven caverns, BH - 107, BH - 110, BH - 112, BH - 113, BM - 109, WH - 11, WH - 112, WH - 114, BC - 17, BC - 18, and BC - 19 have features that may grow with additional leaching and should be monitored as leaching continues in th ose caverns. Additionally, BH - 114, BM - 4, and BM - 106 were identified in previous leaching reports for recommendation of monitoring. Nine caverns had pre - and post - leach sonars that were compared with SANSMIC results. Overall, SANSMIC was able to capture the leaching well. A deviation in the SANSMIC and sonar cavern shapes was observed near the cavern floor in caverns with significant floor rise, a process not captured by SANSMIC. These results validate that SANSMIC continues to serve as a useful tool for mon itoring changes in cavern shape due to leaching effects related to sales and exchanges.

02 PETROLEUM↗
DOE OSTI2023

Downregulation of barley ferulate 5-hydroxylase dramatically alters straw lignin structure without impact on mechanical properties

Barley is a major cereal crop for temperate climates, and a diploid genetic model for polyploid wheat. Cereal straw biomass is an attractive source of feedstock for green technologies but lignin, a key determinant of feedstock recalcitrance, complicates bio-conversion processes. However, manipulating lignin content to improve the conversion process could negatively affect agronomic traits. An alternative approach is to manipulate lignin composition which influences the physical and chemical properties of straw. This study validates the function of a barley ferulate 5-hydroxylase gene and demonstrates that its downregulation using the RNA-interference approach substantially impacts lignin composition. We identified five barley genes having putative ferulate 5-hydroxylase activity. Downregulation of HvF5H1 substantially reduced the lignin syringyl/guaiacyl (S/G) ratio in straw while the lignin content, straw mechanical properties, plant growth habit, and grain characteristics all remained unaffected. Metabolic profiling revealed significant changes in the abundance of 173 features in the HvF5H1-RNAi lines. The drastic changes in the lignin polymer of transgenic lines highlight the plasticity of barley lignification processes and the associated potential for manipulating and improving lignocellulosic biomass as a feedstock for green technologies. On the other hand, our results highlight some differences between the lignin biosynthetic pathway in barley, a temperate climate grass, and the warm climate grass, rice, and underscore potential diversity in the lignin biosynthetic pathways in grasses.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

A quantitative risk assessment framework for fault reactivation in underground hydrogen storage: Coupled simulation and deep learning approach

Underground hydrogen storage (UHS) is emerging as a critical solution for large-scale energy storage. However, like all subsurface fluid injection activities, UHS poses the risk of injection-induced fault reactivation. Accurate risk assessment is essential to ensuring the safety and efficiency of UHS operations. This study presents the development of deep-learning surrogate models for fault reactivation prediction in UHS, trained on a comprehensive database of fully coupled fluid flow-geomechanics simulations. Our findings reveal that analytical models often yield unreliable estimates, with errors up to 54% in the allowable injection pressure, potentially leading to a 40% reduction in UHS operational capacity. The developed surrogate models were incorporated into a quantitative risk assessment (QRA) framework, enabling probabilistic evaluation of fault reactivation risk while accounting for uncertainties in the input variables. Site-specific features, such as horizontal stress gradients, fault’s dip and strike angles, and operational parameters like bottom-hole injection pressure and well-fault distance, were identified as the primary drivers of fault reactivation across various stress regimes. Whereas other hydraulic, geological, and poroelastic reservoir properties were found to have a secondary impact. Notably, we observed that the risk of fault reactivation for a critically oriented fault with a static friction coefficient greater than 0.55 remains below 10% in a normal faulting stress regime. However, the risk significantly increases as the stress regime transitions from normal to strike-slip and ultimately to reverse faulting conditions. These findings underscore the importance of rigorous site characterization and comprehensive QRA evaluations to optimize UHS performance and minimize geomechanical risks.

25 ENERGY STORAGE↗
DOE OSTI2022

Cryogenic electronics for noble liquid neutrino detectors

In this paper we present the general features of cryogenic (or “cold”) electronics for noble liquid time projection chambers, with design principles and details for neutrino physics, a brief history of the technology and details of recent research and development that is driving the design of the detectors under construction. Finally, some comments on future R&D envisioned and the impact of this work on other fields is described. “Cold” in the context of this work applies to CMOS devices operated at 77 K and above, at liquids temperatures of LAr (89 K), LKr (125 K) and LXe (165 K), with most of the tests performed in, or at LN 2 (77 K). Additionally, the paper is concentrated on the design of cold electronics for large liquid argon TPCs, those that have been successfully operated, MicroBooNE and ProtoDUNE, and those designed or under construction, such as SBND and DUNE first and second 10 kton modules. The high performance achieved with MicroBooNE and ProtoDUNE – a high signal-to-noise ratio combined with high stability of response – is mainly due to the integral approach to design and construction of sensing electrodes with cold readout electronics in a modular approach with the cryostat signal feed-throughs incorporating warm interface electronics into a Faraday cage with the cryostat. The integral concept is described in some detail in this paper.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗
DOE OSTI2025

Primitive Cubic Cation-Disordered Niobium Tungsten Oxides

In recent years, metastable cation-disordered oxides have had a significant impact on both fundamental and application-driven materials science research. Along this direction, developing new and simple structural types that can accommodate cation disorder at the same crystallographic site has yet to receive extensive research focus. In this work, we use niobium tungsten oxides (NbWOs), a series of materials encompassing diverse structural features, as a material platform to explore new cation-disordered structural types. Relying on mechanochemistry, we realized primitive cubic cation-disordered NbWOs with a ReO 3 -type structure, featuring unique electronic and vibrational properties. Furthermore, when applied as a Li-ion battery anode, the materials undergo a unique perovskite-rock salt structural change mechanism, different from that of complex ordered NbWOs. All these advancements suggest a rich opportunity in developing other new material structural types and realizing new material properties based on the methodology of the work.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2019

Extreme Wet-Bulb Temperatures in China: The Significant Role of Moisture

This paper investigates the extreme wet bulb temperatures (TWs) in China, with a focus on understanding the relative contributions of temperature and moisture to the extremes. Analysis of station observations shows that daily extreme temperatures (T), specific humidity (q) and TWs generally co-occur in southeastern China while extreme TW and T rarely overlap in the arid and semi-arid North and Northwest China. Overall, q contributes more than T to extreme TWs, especially in North and Northwest China. Based on the relative contributions of q and T, regional extreme TW events are classified as q-dominated and T-dominated, respectively, to study their large-scale environment. Cluster analysis of global reanalysis data shows that extreme TWs are generally accompanied by increased surface air temperature and humidity, concomitant with anomalous high-pressure and notable water vapor flux convergence. However, important differences are also seen in the large-scale environment during q-dominated and T-dominated extreme TWs. During q-dominated extreme TWs, the large-scale environment favors convection, as indicated by ascending motions, decreased downward solar radiation (DSR) as well as increased precipitable water and near surface relative humidity. In contrast, during T-dominated extreme TWs, convection is inhibited by the large-scale environment that features descending motion and increased DSR, decreased precipitable water as well as decreased relative humidity. Consistent with the contrasting environments, we demonstrate that T-dominated extreme TWs tend to last longer than q-dominated extremes. Given the significant role of moisture in extreme TWs, more research is needed to understand its impacts on heat stress now and in the future.

extreme wet bulb temperatures, Moisture, synoptic ↗
DOE OSTI2023

Unusual magnetotransport in twisted bilayer graphene from strain-induced open Fermi surfaces

Anisotropic hopping in a toy Hofstadter model was recently invoked to explain a rich and surprising Landau spectrum measured in twisted bilayer graphene away from the magic angle. Suspecting that such anisotropy could arise from unintended uniaxial strain, we extend the Bistritzer–MacDonald model to include uniaxial heterostrain and present a detailed analysis of its impact on band structure and magnetotransport. We find that such strain strongly influences band structure, shifting the three otherwise-degenerate van Hove points to different energies. Coupled to a Boltzmann magnetotransport calculation, this reproduces previously unexplained nonsaturating B 2 magnetoresistance over broad ranges of density near filling ν = ± 2 and predicts subtler features that had not been noticed in the experimental data. In contrast to these distinctive signatures in longitudinal resistivity, the Hall coefficient is barely influenced by strain, to the extent that it still shows a single sign change on each side of the charge neutrality point—surprisingly, this sign change no longer occurs at a van Hove point. The theory also predicts a marked rotation of the electrical transport principal axes as a function of filling even for fixed strain and for rigid bands. More careful examination of interaction-induced nematic order versus strain effects in twisted bilayer graphene could thus be in order.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Addressing Market Issues in Electrical Power Systems with Large Shares of Variable Renewable Energy

This paper reports recent findings from IEA Wind TCP Task 25, which compiles international experiences and research related to large-scale integration of wind and other renewable energy. In the paper, we address the main challenges for market integration of variable renewable energy, relating to price formation, cost recovery, balancing and other grid services. The paper gives an overview of recent scenario studies on electricity price impacts of (1) various generation, energy storage and demand types in different markets, and (2) different market designs and energy/climate policies. Studying markets with very high shares of variable renewable energy requires an improved set of analysis tools for forecasting market outcomes, estimating flexibility needs and sources, and assessing resource adequacy. Key market features need to be investigated within these improved analytical capabilities for systems transitioning to high shares of variable renewable energy, storage and flexible demand. System services that can be supported by markets will likely need to be revisited. Finally, this paper identifies open questions and suggested future market design work for supporting systems with very high shares of variable renewable energy, which are to be addressed in follow-up work of Task 25 collaborative research.

cost recovery↗
DOE OSTI2022

Sim-Situ: A Framework for the Faithful Simulation of in situ Processing

The amount of data generated by numerical simulations in various scientific domains led to a fundamental redesign of how the analysis and visualization of simulation outputs are performed. The throughput and capacity of storage subsystems have not evolved as fast as the computing power in extreme-scale supercomputers, making the classical post-hoc approach highly inefficient. In situ processing has then emerged as a solution in which simulation and data analysis/visualization are intertwined for better performance and greater interactivity.Determining the best allocation, i.e., how many resources to allocate to simulation and analysis respectively, mapping, i.e., where and at which frequency to run the analysis/visualization, and data transfer mode is a complex task whose performance assessment is crucial to the efficient execution of in situ processing. However, such a performance evaluation of different strategies usually relies either on directly running them on the targeted execution environments, which can rapidly become extremely time- and resource-consuming, or on resorting to simplified models of the components of an in situ application, which can lack of realism. In both cases, the validity of the performance evaluation is limited.In this paper, we present Sim-Situ, a simulation-based framework for the faithful performance evaluation of in situ processing strategies. We designed Sim-Situ to reflect the typical features of in situ processing systems. Thanks to its modular design, Sim-situ has the necessary flexibility to easily and faithfully evaluate the behavior and performance of various allocation, mapping, and data transfer strategies. We illustrate the simulation capabilities of Sim-Situ on a Molecular Dynamics use case. We study the impact of different strategies on performance and show how users can leverage Sim-Situ to determine interesting tradeoffs when adding analysis/visualization components to their application.

Honoré, Valentin↗
DOE OSTI2021

Role of sphingosine‐1‐phosphate receptors in vascular injury of inflammatory bowel disease

Abstract Sphingosine‐1‐phosphate receptors (S1PRs) have an impact on the intestinal inflammation of inflammatory bowel disease (IBD) by regulating lymphocyte migration and differentiation. S1PR modulators as an emerging therapeutic approach are being investigated for the treatment of IBD. However, the role of S1PRs in intestinal vessels has not drawn much attention. Intestinal vascular damage is one of the major pathophysiological features of IBD, characterized by increased vascular density and impaired barrier function. S1PRs have pleiotropic effects on vascular endothelial cells, including proliferation, migration, angiogenesis and barrier homeostasis. Mounting evidence shows that S1PRs are abnormally expressed on intestinal vascular endothelial cells in IBD. Unexpectedly, S1PR modulators may damage intestinal vasculature, for example increase intestinal bleeding; therefore, S1PRs are thought to be involved in the regulation of intestinal vascular function in IBD. However, little is understood about how S1PRs regulate intestinal vascular function and participate in the initiation and progression of IBD. In this review, we summarize the pathogenic role of S1PRs in and the underlying mechanisms behind the intestinal vascular injury in IBD in order for improving IBD practice including S1PR‐targeted therapies.

Wang, Xuewen↗
DOE OSTI2023

The Potential Roles of Preexisting Airmass Boundaries on a Tornadic Supercell Observed by TORUS on 28 May 2019

On 28 May 2019, a tornadic supercell, observed as part of Targeted Observation by UAS and Radars of Supercells (TORUS) produced an EF-2 tornado near Tipton, Kansas. The supercell was observed to interact with multiple preexisting airmass boundaries. These boundaries and attendant air masses were examined using unoccupied aircraft system (UAS), mobile mesonets, radiosondes, and dual-Doppler analyses derived from TORUS mobile radars. The cool-side air mass of one of these boundaries was found to have higher equivalent potential temperature and backed winds relative to the warm-side air mass; features associated with mesoscale air masses with high theta-e (MAHTEs). It is hypothesized that these characteristics may have facilitated tornadogenesis. The two additional boundaries were produced by a nearby supercell and appeared to weaken the tornadic supercell. This work represents the first time that UAS have been used to examine the impact of preexisting airmass boundaries on a supercell, and it provides insights into the influence environmental heterogeneities can have on the evolution of a supercell.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

A Two-Level Model Predictive Control-Based Approach for Building Energy Management including Photovoltaics, Energy Storage, Solar Forecasting and Building Loads

This paper uses a two-level model predictive control-based approach for the coordinated control and energy management of an integrated system that includes photovoltaic (PV) generation, energy storage, and building loads. Novel features of the proposed local controller include (1) the ability to simultaneously manage building loads and energy storage to achieve different operational objectives such as energy efficiency, economic cost efficiency, demand response and grid optimization through the design of specific power trajectory tracking performance functionals, (2) an energy trim function that minimizes the impact of solar forecasting errors on system performance, and (3) the design of a state of charge controller that uses day-ahead forecast of solar power and building loads to intialize energy storage at the start of each day. The local controller is tested in simulation using an exemplary system with PV generation, energy storage and dispatchable building loads. Two sample days with different PV forecasts and multiple case scenarios are considered, and the performance of the algorithm in managing the real and reactive net building load trajectories and the ramp rate of PV injections into the utility network are evaluated. The simulations are based on actual forecasted and measured PV data, and the results show that the local controller meets the tracking requirements for real and reactive power within the operating constraints of the building.

14 SOLAR ENERGY↗
DOE OSTI2021

The Challenge of Disproportionate Importance of Temporal Features in Predicting HPC Power Consumption

In this work, we demonstrate the challenges in predicting HPC cluster power consumption in the face of significant temporal skew in power consumption behavioral patterns. Predicting large power swings that extend several megawatts has significant operational value for HPC centers, however, prediction is challenging due to the relative rarity of such events and also due to the abrupt or disjoint deviation from the average power consumption levels. To study the impact of this challenge, we have trained a recurrent neural network (RNN) as a reasonably sophisticated model to predict power consumption of the one-year worth of node power consumption data from the Summit supercomputer located in the Oak Ridge Leadership Computing Facility. By studying the prediction results, we have found that although simple usage of RNN models can provide good results on average power consumption levels, it would fail at predicting the power swings that have more operational value. With such results, we discuss potential next steps in addressing such issues aiming towards a robust usage of power prediction techniques in HPC operations.

Li, Chengcheng↗
DOE OSTI2025

Effect of Stoichiometry on the Structure and Polarization of BaTiO 3

Barium titanate (BaTiO 3 ) is a material of interest for photonic device applications due to its strong optical non-linearity. However, BaTiO 3 -based devices have not found widespread adoption, in part due to the challenges associated with synthesizing high quality thin-films. Here, high-resolution scanning transmission electron microscope (STEM) imaging is used to investigate the atomic structure of both on- and off-stoichiometric BaTiO 3 synthesized by molecular beam epitaxy (MBE). Here, this investigation reveals an asymmetry in the way the BaTiO 3 atomic lattice accommodates off-stoichiometry growth and unveils features beyond what is expected from diffraction or surface characterization techniques. Excess titanium incorporates into the BaTiO 3 lattice to form pervasive defects despite titanium-rich films having a low surface roughness and high-quality appearance in diffraction. Excess barium forms a rough, water-soluble surface layer but does not significantly impact the quality of the BaTiO 3 lattice. STEM is used to map titanium atom displacement in real-space. The average displacement distance is 30–60 pm in the strained thin-films, higher than the <20 pm displacement in bulk BaTiO 3 . Additionally, the titanium atom displacement direction deviates from the c-axis of the unit cell, which may have implications for the material's electro-optic tensor and thus for electro-optic device design.

Cavanagh, Ashley E. [Harvard Univ., Cambridge, MA ↗