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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 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Proton-Conducting Solid Oxide Electrolysis Cells for Large-scale Hydrogen Production at Intermediate Temperatures

Proton-conducting electrolyte based SOECs offer potential for operation at low to intermediate temperatures. Although yttrium-doped barium zirconate (BZY) and ceria-doped barium zirconate (BCY) have conductivity of 0.01 and 0.017 S.cm -1 respectively at 650C in comparison to the conductivity of 0.015 S.cm -1 for 8-YSZ at 850°C, there remains technology gaps and research needs related to understanding of chemical and structural stability in oxidizing and/or reducing atmospheres at intermediate temperatures, material processing and densification techniques, high polarization losses, and electrode poisoning due to intrinsic and extrinsic gas phase contaminants. Synthesis methods have produced proton-conducting materials and cells that met degradation rate targets, showcasing stable hydrogen production. Improved performance was evident in the HSOEC cell, achieving higher hydrogen production at a lower operating temperature compared to standard cells. Collaborations with multiple research facilities ensured scaling up of synthesis processes and milestone achievements for large-scale manufacturing. Assessment of contaminants revealed their adverse effects on electrode performance and structural stability. Contaminants like Cr and Si compounds, in high humidity, degraded electrodes by forming stable silicate and chromates, inhibiting active surface reactions. Getter materials showed promise in capturing contaminants, suggesting potential for mitigation.

08 HYDROGEN↗
DOE OSTI2025

Go slow to go fast? A review of the impacts of permitting on large-scale solar project development

State and local permitting challenges could impede the ability of large-scale solar (LSS) to meet growing electricity demand in the United States. Here, we review research that explores LSS permitting and its impacts on the pace and scale of LSS project development. Research on LSS permitting is relatively scarce, such that we support our review with research in the context of wind permitting, where appropriate. Further, few studies attempt to rigorously quantify the effects of permitting on the pace and scale of LSS project development. The available evidence allows us to identify various hypotheses and identify gaps for further research. Our review suggests that differences in permitting policies, regulations, and ordinances explain relatively little variation in LSS permitting and development outcomes across jurisdictions, except where jurisdictions implement rules designed to impede LSS. The evidence suggests LSS permitting challenges largely accrue during the implementation of permitting processes. Recent research suggests that community opposition to project development is a key driver of LSS permitting challenges, given that project opponents often use permitting processes to translate opposition into legal action. We call on future researchers to more concretely describe the LSS permitting challenge and to identify the specific actors responsible for implementing solutions.

Community opposition↗
DOE OSTI2022

A nuclear-hydrogen hybrid energy system with large-scale storage: A study in optimal dispatch and economic performance in a real-world market

Here a study in optimal dispatch and economic analysis of a novel nuclear hybrid energy system (NHES) with large-scale hydrogen storage and a novel control scheme is conducted. The control scheme makes charge and discharge decisions by using the real-time electricity price relative to the historical price distribution. The pricing data is taken from the ERCOT Houston and West load zones with different price oscillations. Six case control studies with different levels of aggressiveness were chosen for each load zone for a total of 12 case studies. It is found that in a high price volatility load zone, a more aggressive control strategy maximizes revenue, while in a less oscillatory load zone, a moderate control strategy performs better. The NHES can store energy when the price is low and sell additional electricity when the price is high, as well as participate in the ancillary services market. Due to these advantages, the NHES can generate 10–40 million USD more revenue annually than a stand-alone nuclear plant. Due to higher costs, the NHES has a higher LCOE (81.36 USD/MWh) than a stand-alone plant (68.66 USD/MWh); however, the LCOE of the NHES is still comparable to other new forms of electricity generation. It is found that both the NHES and the stand-alone plant are not economical in the existing electricity market. Due to the extra revenue generated, the hybrid system has a positive annual cashflow whereas the stand-alone plant does not. It is found that the hybrid plant needs less cost subsidy than a stand-alone plant to become economical.

08 HYDROGEN↗
DOE OSTI2024

Redesigning large-scale multimodal transit networks with shared autonomous mobility services

Here, this study addresses a large-scale multimodal transit network design problem, with Shared Autonomous Mobility Services (SAMS) as both transit feeders and an origin-to-destination mode. The framework captures spatial demand and modal characteristics, considers intermodal transfers and express services, determines transit infrastructure investment and path flows, and generates transit routes. A system-optimal multimodal transit network is designed with minimum total door-to-door generalized costs of users and operators, satisfying transit origin-destination demand within a pre-set infrastructure budget. Firstly, the geography, demand, and modes in each zone are characterized with continuous approximation. The decisions of network link investment and multimodal path flows in zonal connection optimization are formulated as a minimum-cost multi-commodity network flow (MCNF) problem and solved efficiently with a mixed-integer linear programming (MILP) solver. Subsequently, the route generation problem is solved by expanding the MCNF formulation to minimize intramodal transfers. The model is illustrated through a set of experiments with the Chicago network comprised of 50 zones and seven modes, under three scenarios. The computational results present savings in traveler journey time and operator cost demonstrating the potential benefits of collaboration between multimodal transit systems and SAMS.

Autonomous vehicles↗
DOE OSTI2022

Large-scale atomistic studies of sliding friction in polycrystalline aluminum interfaces

In this work, we discuss large-scale non-equilibrium molecular dynamics (NEMD) simulations of ductile metal sliding comprising up to 1.8 × 10 9 atoms over time scales of 100 ns. The results of these simulations have identified a variety of physical mechanisms that are important in determining the steady-state frictional force for a wide range of velocities at compressed metal–metal interfaces. These include grain growth and refinement, the evolution of large plastic strains and strain rates, material mixing, and melting. These phenomena can be included in a strain, strain rate, and grain size model that gives good agreement with the NEMD simulations and can be applied to macroscopic continua.

74 ATOMIC AND MOLECULAR PHYSICS↗
DOE OSTI2021

The persistence of large scale structures. Part I. Primordial non-Gaussianity

Abstract We develop an analysis pipeline for characterizing the topology of large scale structure and extracting cosmological constraints based on persistent homology . Persistent homology is a technique from topological data analysis that quantifies the multiscale topology of a data set, in our context unifying the contributions of clusters, filament loops, and cosmic voids to cosmological constraints. We describe how this method captures the imprint of primordial local non-Gaussianity on the late-time distribution of dark matter halos, using a set of N-body simulations as a proxy for real data analysis. For our best single statistic, running the pipeline on several cubic volumes of size 40 (Gpc/h) 3 , we detect f NL loc =10 at 97.5% confidence on ~ 85% of the volumes. Additionally wetest our ability to resolve degeneracies betweenthe topological signature of f NL loc and variation of σ 8 and argue that correctly identifying nonzero f NL loc in this case is possible via an optimal template method. Our method relies on information living at $\mathcal{O}$(10) Mpc/h, a complementary scale with respect to commonly used methods such as the scale-dependent bias in the halo/galaxy power spectrum. Therefore, while still requiring a large volume, our method does not require sampling long-wavelength modes to constrain primordial non-Gaussianity. Moreover, our statistics are interpretable: we are able to reproduce previous results in certain limits and we make new predictions for unexplored observables, such as filament loops formed by dark matter halos in a simulation box.

Astronomy & Astrophysics↗
DOE OSTI2025

Materials Learning Algorithms (MALA): Scalable machine learning for electronic structure calculations in large-scale atomistic simulations

We present the Materials Learning Algorithms (MALA) package, a scalable machine learning framework designed to accelerate density functional theory (DFT) calculations suitable for large-scale atomistic simulations. Using local descriptors of the atomic environment, MALA models efficiently predict key electronic observables, including local density of states, electronic density, density of states, and total energy. The package integrates data sampling, model training and scalable inference into a unified library, while ensuring compatibility with standard DFT and molecular dynamics codes. We demonstrate MALA's capabilities with examples including boron clusters, aluminum across its solid-liquid phase boundary, and predicting the electronic structure of a stacking fault in a large beryllium slab. Scaling analyses reveal MALA's computational efficiency and identify bottlenecks for future optimization. With its ability to model electronic structures at scales far beyond standard DFT, MALA is well suited for modeling complex material systems, making it a versatile tool for advanced materials research.

Density functional theory↗
DOE OSTI2021

Facilitating Large‐Scale Snow Shedding from In‐Field Solar Arrays using Icephobic Surfaces with Low‐Interfacial Toughness

Abstract Large‐scale accrual of snow and ice on solar arrays in northern latitudes can cause significant power generation losses during winter. Depending on environmental conditions, snow can encompass a wide range in physical characteristics from dry snow (modulus ≈100 kPa and density ≈0.1 g cm −3 ) to bulk ice (modulus ≈8 GPa and density ≈0.9 g cm −3 ). This variation in snow morphology has made the development of a passive, broad‐spectrum, snow and ice‐shedding surface challenging. Here, the authors develop one of the first surfaces that simultaneously possesses both low‐interfacial strength ( τ˄ ice < 50 kPa) and toughness (Γ ice < 0.5 J m −2 ) with ice. These surfaces, fabricated via the addition of mobile polymer chains/oils to a thin polymeric coating, require extremely low detachment forces for ice, enabling its passive shedding at virtually any accretion length scale. Preliminary evidence that the new surfaces can shed different forms of snow and ice from field‐deployed solar arrays, over a range of subzero temperatures for several weeks, leading to significant increases in power generation is provided. The optically transparent surfaces are easily scalable and can be widely deployed by the solar industry in areas that see persistent snow. Other applications include automotive windshields, LIDAR covers for autonomous vehicles, and cold climate optical sensors.

Dhyani, Abhishek↗
DOE OSTI2024

Topanga: A kinetic ion plasma code for large-scale ionospheric simulations on magnetohydrodynamic timescales

Topanga is a kinetic ion code developed for simulating large-scale plasma phenomena in the Earth's ionosphere on magnetohydrodynamic timescales. It is a domain-decomposed parallel code that runs on high-performance computing platforms. Features of Topanga include spherical geometry for simplified boundary conditions and computational efficiency; a hybrid plasma model with inertia-less fluid electrons, kinetic ions, and an electric field specified via an Ohm's law; a Maxwell-FDTD (finite difference time domain) plasma model which retains the displacement current in Maxwell's equations and models electron currents in the ionosphere with a tensor conductivity; sponge-layer boundary conditions for absorption of electromagnetic and plasma waves incident on the domain boundaries; and a novel mixed-implicit algorithm for evolving the EM fields inside the Maxwell-FDTD region that is stable over many orders of magnitude in the electron–ion collision frequency. We verify the numerical methods used in Topanga on a pair of test problems. The first test involves modeling a three-dimensional collisionless shock using the hybrid set of equations. The second test involves modeling a spherical TEM mode in vacuum using the Maxwell-FDTD set of equations. Finally, we demonstrate how using the combined set of hybrid and Maxwell-FDTD equations to model the Starfish Prime high-altitude nuclear test recovers a “missing” EM signal on the ground that is not present when using only the hybrid set of equations. The magnitude of this signal in the simulation containing the Maxwell-FDTD region agrees well with the E3a portion of the magnetohydrodynamic electromagnetic pulse from Starfish Prime.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2025

Fast and robust strategies for large-scale mixed-integer SCOPF

This project develops scalable, computationally efficient algorithms to solve realistic large-scale power system optimization problems, including systems with more than 8,000 buses, as part of a larger series of competitions run by ARPA-E. These problems are critical because the secure and reliable operation of the power grid is becoming increasingly challenging, especially under conditions of increased uncertainty and variability. The economic feasibility of our methods is high, given that they are purely software-based solutions designed to operate power grids more efficiently. The technical effectiveness balances heuristics and approximations to provide a trade-off between speed and accuracy.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Dual low vacuum-ultrahigh vacuum system for large-scale production of micro-channel plate photomultipliers

Systems and methods for the batch production of large numbers of highly uniform multichannel-plate photomultiplier tubes (MCP-PMTs) for large-scale applications are provided. The systems and methods employ dual, nested low-vacuum (LV) and UHV processing in a rapid-cycling, small-footprint, scalable, batch-production facility that is capable of fabricating many MCP-PMTs simultaneously.

Frisch, Henry J.↗
DOE OSTI2022

Super-Large-Scale Hierarchically Porous Films Based on Self-Assembled Eye-Like Air Pores for High-Performance Daytime Radiative Cooling

Metal-free polymer daytime radiative cooling coatings with hierarchical eye-like air pores are proposed and fabricated with a super-large-scale film-stretching method. The hierarchically porous film (HPF) can be further coated with polymethyl methacrylate (PMMA) micro-hemispheres, forming coated HPF (cHPF), which do not dramatically change the optical or thermal properties. The cHPF is slightly better with a lower solar absorptivity (2.4%) and a higher thermal emissivity over the atmospheric transparency window (90.1%). The low solar absorptivity is due to the strong scattering of the hierarchical eye-like air pores, while the molecular vibrations and the focusing effect of the PMMA micro-hemispheres contribute to the high emissivity. Further, an average mid-day temperature reduction of 7.92 °C is achieved relative to the air temperature, and the average cooling power reaches 116.0 W m -2 , which are much better than the cooling performances of the commercial cooling cushion. During the day, the cHPF-covered simulated building is up to 6.47 and 4.84 °C cooler than the ambient and the white painted counterpart, respectively. The film is durable and resistant to chemical etching, and very promising to use globally, especially in warm and tropical regions.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Dissect two-halo galactic conformity effect for central galaxies: the dependence of star formation activities on the large-scale environment

We investigate the two-halo galactic conformity effect for central galaxies, which is the spatial correlation of the star formation activities for central galaxies to several Mpcs, by studying the dependence of the star formation activities of central galaxies on their large-scale structure in our local Universe using the SDSS data. Here we adopt a novel environment metric using only central galaxies quantified by the distance to the nth nearest central galaxy. This metric measures the environment within an aperture from ∼1 to ≳ 10 Mpc, with a median value of ∼4 Mpc. We found that two kinds of conformity effects in our local Universe. The first one is that low-mass central galaxies are more quenched in high-density regions, and we found that this effect mainly comes from low-mass centrals that are close to a more massive halo. A similar trend is also found in the IllustrisTNG simulation, which can be entirely explained by backsplash galaxies. The second conformity effect is that massive central galaxies in low-density regions are more star-forming. This population of galaxies also possesses a higher fraction of spiral morphology and lower central stellar velocity dispersion, suggesting that their low quiescent fraction is due to less-frequent major merger events experienced in the low-density regions and, as a consequence, less-massive bulges and central black holes.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2020

Blinded challenge for precision cosmology with large-scale structure: Results from effective field theory for the redshift-space galaxy power spectrum

An accurate theoretical template for the galaxy power spectrum is key for the success of ongoing and future spectroscopic surveys. We examine to what extent the effective field theory (EFT) of large-scale structure is able to provide such a template and correctly estimate cosmological parameters. To that end, we initiate a blinded challenge to infer cosmological parameters from the redshift-space power spectrum of high-resolution mock catalogs mimicking the BOSS galaxy sample but covering a 100 times larger cumulative volume. This gigantic simulation volume allows us to separate systematic bias due to theoretical modeling from the statistical error due to sample variance. The challenge is to measure three unknown input parameters used in the simulation: the Hubble constant, the matter density fraction, and the clustering amplitude. We present analyses done by two independent teams, who have fitted the mock simulation data generated by yet another independent group. This allows us to avoid any confirmation bias by analyzers and to pin down possible tuning of the specific EFT implementations. Both independent teams have recovered the true values of the input parameters within subpercent statistical errors corresponding to the total simulation volume.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2023

MEASURING THERMALLY-INDUCED DISTORTION OF LARGE-SCALE COMPOSITE PRINTED STRUCTURES USING DIGITAL IMAGE CORRELATION

Additive manufacturing (AM) gives designers the ability to create complex part geometries without several of the limitations of traditional manufacturing. Large-Scale AM (LSAM) allows the creation of large composite structures and is a popular area of composite tooling research. Fiber-reinforced polymers are common feedstock for LSAM tooling but introduce anisotropic thermomechanical properties that can lead to the warpage of tools at autoclave conditions. Digital image correlation (DIC) has been used to measure the coefficient of thermal expansion (CTE) of LSAM parts using a novel DIC Oven design. This method was utilized to measure the CTE of LSAM structures printed using different fiber-reinforced materials and multiple geometries. Specifically, glass fiber ABS (GF-ABS) and carbon fiber ABS (CF-ABS) samples were compared as well as cube and plate geometries for each material. The temperature profile over time was also evaluated to determine how rapidly the strain of the sample increased as temperature of the DIC Oven was increased. A thermal model was developed to predict temperature profiles for various samples and identify when the samples had reached thermal equilibrium.

Corum, Tyler↗