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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Detection of the large-scale tidal field with galaxy multiplet alignment in the DESI Y1 spectroscopic survey

We explore correlations between the orientations of small galaxy groups, or ‘multiplets’, and the large-scale gravitational tidal field. Using data from the Dark Energy Spectroscopic Instrument (DESI) Y1 survey, we detect the intrinsic alignment (IA) of multiplets to the galaxy-traced matter field out to separations of $100\,h^{-1}$ Mpc. Unlike traditional IA measurements of individual galaxies, this estimator is not limited by imaging of galaxy shapes and allows for direct IA detection beyond redshift $z=1$. Multiplet alignment is a form of higher order clustering, for which the scale-dependence traces the underlying tidal field and amplitude is a result of small-scale ($\lt 1h^{-1}$ Mpc) dynamics. Within samples of bright galaxies, luminous red galaxies (LRG) and emission-line galaxies, we find similar scale-dependence regardless of intrinsic luminosity or colour. This is promising for measuring tidal alignment in galaxy samples that typically display no IA. DESI’s LRG mock galaxy catalogues created from the A BACUS S UMMIT N -body simulations produce a similar alignment signal, though with a 33 per cent lower amplitude at all scales. An analytic model using a non-linear power spectrum (NLA) only matches the signal down to 20 $h^{-1}$ Mpc. Our detection demonstrates that galaxy clustering in the non-linear regime of structure formation preserves an interpretable memory of the large-scale tidal field. Multiplet alignment complements traditional two-point measurements by retaining directional information imprinted by tidal forces, and contains additional line-of-sight information compared to weak lensing. This is a more effective estimator than the alignment of individual galaxies in dense, blue, or faint galaxy samples.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

What to expect when you're expecting engagement: Delivering procedural justice in large-scale solar energy deployment

Community engagement in the planning process to build large-scale solar (LSS) projects can win local support and advance procedural justice. However, an understanding of community engagement in current LSS development is lacking. Using responses from a U.S. nationwide survey (n = 979) of residential neighbors living within 3 miles (4.8 km) of completed LSS projects (i.e. “solar neighbors”) and project details from the U.S. Large-Scale Solar Photovoltaic Database (USPVDB), this study seeks to answer the following questions: How are solar neighbors' perceptions of community engagement associated with their attitudes toward their LSS projects? How do solar neighbors' perceptions of community engagement compare to their expectations? And, how do neighbors explain what they perceived about the planning process? We answer these questions using mixed methods, including regression modeling, a new gap analysis technique, and qualitative coding. We find that higher perceived engagement is associated with more positive attitudes toward the project, even when controlling for respondents who acted in opposition. Supporters and opponents alike expect more engagement than they perceived and information about projects both before construction and after operation is lacking. Awareness and engagement expectations increase at certain project size and proximity thresholds. However, most neighbors expect the public to offer input during engagement, but not make decisions. We contextualize these findings with explanatory comments from respondents.

14 SOLAR ENERGY↗
DOE OSTI2022

Forecasting the potential of weak lensing magnification to enhance LSST large-scale structure analyses

ABSTRACT Recent works have shown that weak lensing magnification must be included in upcoming large-scale structure analyses, such as for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST), to avoid biasing the cosmological results. In this work, we investigate whether including magnification has a positive impact on the precision of the cosmological constraints, as well as being necessary to avoid bias. We forecast this using an LSST mock catalogue and a halo model to calculate the galaxy power spectra. We find that including magnification has little effect on the precision of the cosmological parameter constraints for an LSST galaxy clustering analysis, where the halo model parameters are additionally constrained by the galaxy luminosity function. In particular, we find that for the LSST gold sample (i < 25.3) including weak lensing magnification only improves the galaxy clustering constraint on Ωm by a factor of 1.03, and when using a very deep LSST mock sample (i < 26.5) by a factor of 1.3. Since magnification predominantly contributes to the clustering measurement and provides similar information to that of cosmic shear, this improvement would be reduced for a combined galaxy clustering and shear analysis. We also confirm that not modelling weak lensing magnification will catastrophically bias the cosmological results from LSST. Magnification must therefore be included in LSST large-scale structure analyses even though it does not significantly enhance the precision of the cosmological constraints.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Large-Scale CO2 Storage and Reservoir Management Strategies: Case Studies

This poster describes large-scale CO2 storage and reservoir management case studies for presentation at the AGU2024 conference. The analysis in this study provides a wealth of details on the designs and strategies that can lead to an optimal solution for pressure and CO2 plume management under critical constraints. These findings not only promise a reduction in the CO2 storage footprint but also hold the potential to create a more environmentally friendly ecosystem. Furthermore, this research offers valuable insights into the decision-making process when considering multi-project deployment in a shared basin for large-scale and gigatons of CO2 storage, paving the way for a more sustainable future. Poster presented (virtual) at the 2024 AGU Conference, December 9-13, 2024, Washington, D.C.

Liu, Guoxiang [NETL]↗
DOE OSTI2025

The Atacama Cosmology Telescope: Large-scale velocity reconstruction with the kinematic Sunyaev-Zel'dovich effect and DESI LRGs

The kinematic Sunyaev-Zel'dovich (kSZ) effect induces a non-zero density-density-temperature bispectrum, which we can use to reconstruct the large-scale velocity field from a combination of cosmic microwave background (CMB) and galaxy density measurements, in a procedure known as “kSZ velocity reconstruction”. This method has been forecast to constrain large-scale modes with future galaxy and CMB surveys, improving their measurement beyond what is possible with the galaxy surveys alone. Such measurements will enable tighter constraints on large-scale signals such as primordial non-Gaussianity, deviations from homogeneity, and modified gravity. In this work, we demonstrate a statistically significant measurement of kSZ velocity reconstruction for the first time, by applying quadratic estimators to the combination of the ACT DR6 CMB+kSZ map and the DESI LRG galaxies (with photometric redshifts) in order to reconstruct the velocity field. We do so using a formalism appropriate for the 2-dimensional projected galaxy fields that we use, which naturally incorporates the curved-sky effects important on the largest scales. We find evidence for the signal by cross-correlating with an external estimate of the velocity field from the spectroscopic BOSS survey and rejecting the null (no-kSZ) hypothesis at 3.8σ. Our work presents a first step towards the use of this observable for cosmological analyses.

Sunyaev-Zeldovich effect↗
DOE OSTI2024

Epitaxial Growth of Large-Scale 2D CrTe 2 Films on Amorphous Silicon Wafers With Low Thermal Budget

2D van der Waals (vdW) magnets open landmark horizons in the development of innovative spintronic device architectures. However, their fabrication with large scale poses challenges due to high synthesis temperatures (>500 °C) and difficulties in integrating them with standard complementary metal-oxide semiconductor (CMOS) technology on amorphous substrates such as silicon oxide (SiO 2 ) and silicon nitride (SiN x ). Here, a seeded growth technique for crystallizing CrTe 2 films on amorphous SiN x /Si and SiO 2 /Si substrates with a low thermal budget is presented. This fabrication process optimizes large-scale, granular atomic layers on amorphous substrates, yielding a substantial coercivity of 11.5 kilo-oersted, attributed to weak intergranular exchange coupling. Field-driven Néel-type stripe domain dynamics explain the amplified coercivity. Moreover, the granular CrTe 2 devices on Si wafers display significantly enhanced magnetoresistance, more than doubling that of single-crystalline counterparts. Current-assisted magnetization switching, enabled by a substantial spin–orbit torque with a large spin Hall angle (85) and spin Hall conductivity (1.02 × 10 7 ℏ/2e Ω -1 m -1 ), is also demonstrated. These observations underscore the proficiency in manipulating crystallinity within integrated 2D magnetic films on Si wafers, paving the way for large-scale batch manufacturing of practical magnetoelectronic and spintronic devices, heralding a new era of technological innovation.

2D magnetic thin films↗
DOE OSTI2026

Spaced out: An economic framework to explore the impacts of PV panel spacing on large-scale farming in Colorado

CONTEXT Agrivoltaic systems co-locate solar technologies with agricultural operations on an integrated plot of land and potentially provide benefits to both energy and agricultural systems. To date, large-scale (>5-MW) agrivoltaic projects in the United States have been limited to grazing and ecovoltaic applications, raising questions about the impact and scalability of agrivoltaic crop systems. Many agrivoltaic designs raise the height of the solar panels to accommodate agricultural practices while keeping energy density high. However, raising the panels results in increased photovoltaic (PV) development costs, which often are higher than the economic returns of crop production underneath the panels. This leads to unfavorable project economics and the need for other agrivoltaic solutions than raising panels. OBJECTIVE To explore other solutions, we perform an initial feasibility analysis for an agrivoltaic solution that can integrate with large-scale farming practices by increasing the row spacing in between panels. Increased PV row spacing is a low-cost approach for scaling agrivoltaics to accommodate crop production and this spacing can be tailored to required crop equipment for different regions. Increasing row spacing will reduce the power density (PV installed per acre), but in areas that are not land limited, these agrivoltaic designs could be economically feasible. Our analysis establishes a framework for a feasibility analysis for where and with what crops spaced out panel agrivoltaic solutions might be economical. METHODS Using a case study for large-scale agriculture crops in Colorado, we establish a framework for wide-row agrivoltaic economic feasibility analysis. We utilized the System Advisor Model to calculate technoeconomic metrics to compare different row spacing solutions and capture tradeoffs of these system designs. RESULTS AND CONCLUSIONS We find that, in some circumstances, wider row agrivoltaic solutions that allow for continued mechanized crop production can provide economic benefits over a traditional utility-scale PV system. For most crops examined in this analysis, roughly $\$$200/acre in agricultural profit justified spacing out the panels to at least 31.7 ft. to accommodate agrivoltaic configurations versus PV only configurations. Additionally, opportunities for increased agricultural revenue with agrivoltaic systems allow PV project economics to tolerate a larger range of CAPEX variability while remaining economically viable relative to the PV only configurations. SIGNIFICANCE This framework can be adapted for a wide variety of crops and regions and allows for examination of economically favorable sites for future agrivoltaic systems that utilize different configuration and expand opportunities for agrivoltaics.

14 SOLAR ENERGY↗
DOE OSTI2026

Constraints on Large-Scale White Noise in the Cosmic Density Field

We present observational constraints on large-scale white noise (LSWN) in the cosmic density field, a phenomenon predicted to arise from non-linear mode coupling during cosmological evolution. Building on the theoretical framework of Paper I, where we demonstrated that non-linearities inevitably redistribute power from small to large scales through mode mixing, we confront these predictions with current cosmological data. We modify the CLASS Boltzmann code to incorporate a white noise component $k_\mathrm{BH}/k$ in the primordial power spectrum and perform parameter estimation using current cosmological data. The non-detection of excess power on the largest observable scales places stringent upper bounds: $k_\mathrm{BH} \leq 1.80 \times 10^{-13}~\mathrm{Mpc}^{-1}$ at 99% confidence. These constraints imply the primordial power spectrum must deviate from perfect scale invariance on small scales, either through a cutoff at $k_{\mathrm{cut}} \lesssim 3~\mathrm{pc}^{-1}$ or through running of the spectral index with $α_s \lesssim -0.015$. Our results demonstrate that LSWN provides a powerful probe of the primordial spectrum at scales orders of magnitude smaller than directly observable, offering unique constraints on early-universe physics.

Barenboim, Gabriela [Valencia U., IFIC; Valencia U↗
DOE OSTI2023

A Robust Parallel Distributed State Estimation for Large Scale Distribution Systems

The growing need and interest in real-time monitoring of large distribution networks motivated by the rapid population of renewable sources, EVs and etc. demand a computationally efficient state estimation framework. Furthermore, this paper presents an improved computational framework for implementing a robust state estimator using a multi-core processor. The main contribution of the paper is the proposed computational framework along with two partitioning strategies which enable fast and robust state estimation for large scale radial and/or meshed distribution systems. Formulation of the proposed method and its implementation are described in detail. Performance of the estimator is tested by simulations first using a small 84-bus radial distribution system. Then the method’s scalability is demonstrated by simulations on two very large scale distribution networks one configured radially and the other meshed each containing over 12,500 buses.

42 ENGINEERING↗
DOE OSTI2020

Investigating the effect of different shielding gas mixtures on microstructure and mechanical properties of 410 stainless steel fabricated via large scale additive manufacturing

Metal Big Area Additive Manufacturing (mBAAM) offers the potential to fabricate large scale tools at high deposition rates (15 lb/h+). 410 martensitic steel is a potential tooling material, owing to its low cost, good machinability and reasonable printability. During the mBAAM process, the shielding gas can have a significant impact on the material properties as well as the process cost. Therefore, the current study aims to understand the effect of different shielding gas mixtures on large-scale additive manufacturing of 410 martensitic stainless steel. We show that an argon mixture with 3% nitrogen gas produced the best performance in terms of maximum hardness and tensile strength, with much less scatter in tensile strength. He-Ar-CO 2 or tri-mix shielded samples showed a low tensile strength with wide scatter, due to stabilized delta ferrite in microstructure during printing. Both tri-mix and Ar-CO 2 shielded samples showed slightly higher porosity. Thus, we recommend the use of argon-3% nitrogen as a shielding gas mixture for processing 410 steel for tool applications, based on the relatively low cost of this gas mixture and the resulting higher hardness, higher dimensional stability, and lower porosity.

36 MATERIALS SCIENCE↗
DOE OSTI2022

Large-scale homogeneity in the distribution of quasars in the Hercules-Corona Borealis Great Wall region

In light of recent debates on the existence of a gigaparsec-scale structure traced by gamma-ray bursts, namely the Hercules-Corona Borealis Great Wall (HCBGW), we revisit large-scale homogeneity in the spatial distribution of quasars. Our volume-limited sample of quasars in the redshift range 1:6 < z ≤ 2:1, which is constructed from the data release 7 of the Sloan Digital Sky Survey quasar catalogue, covers about half of the suspected HCBGW region. We analyze the sample in two complementary ways: fractal analysis of determining the average scale of homogeneity and friends- of-friends analysis of identifying specific large-scale structures. The quasar distribution on average reaches homogeneity at rh = 136 ± 38h-1 Mpc and the richness and comoving size frequencies of large (> ~ 150h-1 Mpc) quasar groups are consistent with the prediction of homogeneous distribution. These results put constraints on the spatial extent of the HCBGW but do not contradict its existence since our quasar sample does not cover the entire HCBGW region.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Physics‐Informed Machine Learning Method for Large‐Scale Data Assimilation Problems

Abstract We develop a physics‐informed machine learning approach for large‐scale data assimilation and parameter estimation and apply it for estimating transmissivity and hydraulic head in the two‐dimensional steady‐state subsurface flow model of the Hanford Site given synthetic measurements of said variables. In our approach, we extend the physics‐informed conditional Karhunen‐Loéve expansion (PICKLE) method to modeling subsurface flow with unknown flux (Neumann) and varying head (time‐dependent Dirichlet) boundary conditions. We demonstrate that the PICKLE method is comparable in accuracy with the standard maximum a posteriori (MAP) method, but is significantly faster than MAP for large‐scale problems. Both methods use a mesh to discretize the computational domain. In MAP, the parameters and states are discretized on the mesh; therefore, the size of the MAP parameter estimation problem directly depends on the mesh size. In PICKLE, the mesh is used to evaluate the residuals of the governing equation, while the parameters and states are approximated by the truncated conditional Karhunen‐Loéve expansions with the number of parameters controlled by the smoothness of the parameter and state fields, and not by the mesh size. For a considered example, we demonstrate that the computational cost of PICKLE increases near linearly (as N 1.15 ) with the number of grid nodes N , while that of MAP increases much faster (as N 3.28 ). We also show that once trained for one set of Dirichlet boundary conditions (i.e., one river stage), the PICKLE method provides accurate estimates of the hydraulic head for any value of the Dirichlet boundary conditions (i.e., for any river stage).

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Probing large-scale UV background inhomogeneity associated with quasars using metal absorption

ABSTRACT We study large-scale UV background inhomogeneity in three-dimensions associated with the observed quasar populations at high redshift. We do this by measuring metal absorption through quasar absorption spectrum stacking as a function distance to closest quasar in SDSS-IV/eBOSS on 10 s of comoving megaparsec scales. We study both intergalactic medium absorbers and mixed circumgalactic medium absorbers and probe absorption in O vi, C iv, and Si iv, and Si iii. Overall, stronger high ionization species absorption is seen closer to quasars at 2.4 < z < 3.1. O vi absorption shows a particularly strong change, with effects in C iv evident in some cases, and more marginal effects in Si iii and Si iv. We further study 2.05 < z < 2.4 (with weak signs of increasing homogeneity with time) and explore the study of metal absorption as a function of integrated SDSS-r band flux quasar flux (yielding consistent but less significant results). While the metal absorption does show sensitivity to large-scale 3D quasar proximity, the current incomplete quasar samples limit detailed interpretation. This work does, however, demonstrate that UV background inhomogeneities exist on scales of several 10 s of comoving megaparsecs associated with quasars and that they can be measured with precision by examining metal absorption in the intergalactic medium.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2026

Analyzing Land Characteristics Associated with Historical Large-Scale Solar Photovoltaic Deployment in the United States

Large-scale solar (LSS) deployment has accelerated rapidly across the United States, yet comprehensive understanding of its siting patterns remains limited. Here, we present a national-scale geospatial assessment of land characteristics converted for LSS development and apply statistical analyses to evaluate whether installations are disproportionately concentrated within specific land types. We find that siting patterns are strongly correlated with high solar irradiance, underscoring the role of resource quality in shaping deployment decisions. LSS projects are disproportionately concentrated on agricultural lands and shrubland. Within agricultural areas, installations predominantly occur on croplands and are strongly associated with irrigated systems. Notably, more than 90% of projects are deployed on agricultural land with Productive, Versatile, and Resilient (PVR) index values of land quality exceeding the national median. These findings highlight the need for strategic siting frameworks that reconcile solar development with the conservation of agriculturally valuable land.

14 SOLAR ENERGY↗
DOE OSTI2020

Characterizing material transitions in large-scale Additive Manufacturing

Integrating Multiple Materials (MM) into large-scale Additive Manufacturing (AM) is a key for various industrial applications wishing to incorporate site-specific properties into geometrically complex designs that are difficult to manufacture with traditional techniques. Printing with multiple materials is typically accomplished by using layers as natural material boundaries, but having the capability to switch between materials within a single layer without pausing would further expand MM possibilities. This study used Cincinnati Incorporated’s Big Area Additive Manufacturing (BAAM) system to explore material transitions with a novel dual-hopper that enables in-situ material blending of a pelletized feedstock. Constructing MM and functionally graded material (FGM) structures requires depositing a specific material composition at a specific geometric location to achieve a desired performance. Furthermore, accurately implementing this with the BAAM’s blended extrusion system requires a thorough understanding of the transition between distinct material compositions. This study characterizes a step-change transition between neat acrylonitrile butadiene styrene (ABS) and carbon fiber-reinforced ABS. Three distinct techniques were compared for analyzing the fiber content, and the transition zone between materials was characterized as a function of transition direction. The transition process was consistent to within 0.7 wt% carbon fiber variation between different layers and prints. The transition between materials was found to be directionally dependent, with ABS to CF/ABS having a transition length of 3.5 m compared to 3.2 m for CF/ABS to ABS. Furthermore, the transition from Material A to Material B was found to be repeatable with a possible variance in transition length of 0.3 m.

36 MATERIALS SCIENCE↗
DOE OSTI2024

ytopt: Autotuning Scientific Applications for Energy Efficiency at Large Scales

As we enter the exascale computing era, efficiently utilizing power and optimizing the performance of scientific applications under power and energy constraints has become critical and challenging. We propose a low-overhead autotuning framework to autotune performance and energy for various hybrid MPI/OpenMP scientific applications at large scales and to explore the tradeoffs between application runtime and power/energy for energy efficient application execution, then use this framework to autotune four ECP proxy applications—XSBench, AMG, SWFFT, and SW4lite. Our approach uses Bayesian optimization with a Random Forest surrogate model to effectively search parameter spaces with up to 6 million different configurations on two large-scale HPC production systems, Theta at Argonne National Laboratory and Summit at Oak Ridge National Laboratory. The experimental results show that our autotuning framework at large scales has low overhead and achieves good scalability. Using the proposed autotuning framework to identify the best configurations, we achieve up to 91.59% performance improvement, up to 21.2% energy savings, and up to 37.84% EDP (energy delay product) improvement on up to 4096 nodes.

Autotuning↗
DOE OSTI2022

sCO2 Primary Power Large-Scale Pilot Plant FEED Summary

Echogen Power Systems and its project partners the Electric Power Research Institute, CDM Smith, Riley Power Inc. (a Babcock Power Inc. company), and the University of Missouri completed the Front-End Engineering Design (FEED) study of a nominal 10 MWe supercritical carbon dioxide (sCO2) large-scale pilot plant based on Recompression Brayton Cycle (RCBC) architecture. The FEED study was completed under Phase II of the U.S. Department of Energy Fossil Fuel Large-Scale Pilots program. The FEED study scope included the preliminary design of the combustion and environmental control systems, the primary heater, the sCO2 power cycle and its associated turbomachinery, and the balance of plant equipment to determine accurate cost and schedule requirements for fabrication and installation of the system at the University of Missouri’s Combined Cooling, Heat, and Power Plant, located in Columbia, Missouri. The RCBC sCO2 cycle presents superior thermodynamic efficiency compared to steam-Rankine cycles and is adaptable to a broad range of heat sources. The risk aversion of the power generation industry requires a successful large-scale pilot plant demonstration to enable financing and deployment of commercial-scale plants. Therefore, successful construction and demonstration of a 10 MWe RCBC sCO2 power plant would empower a transformational step forward for the efficiency of the next generation of utility power plants. This paper provides details on the primary heater, environmental control systems, and sCO2 power cycle design and performance.

01 COAL, LIGNITE, AND PEAT↗
DOE OSTI2023

Linking repeat lidar with Landsat products for large scale quantification of fire-induced permafrost thaw settlement in interior Alaska

The permafrost–fire–climate system has been a hotspot in research for decades under a warming climate scenario. Surface vegetation plays a dominant role in protecting permafrost from summer warmth, thus, any alteration of vegetation structure, particularly following severe wildfires, can cause dramatic top–down thaw. A challenge in understanding this is to quantify fire-induced thaw settlement at large scales (>1000 km 2 ). In this study, we explored the potential of using Landsat products for a large-scale estimation of fire-induced thaw settlement across a well-studied area representative of ice-rich lowland permafrost in interior Alaska. Six large fires have affected ~1250 km 2 of the area since 2000. We first identified the linkage of fires, burn severity, and land cover response, and then developed an object-based machine learning ensemble approach to estimate fire-induced thaw settlement by relating airborne repeat lidar data to Landsat products. The model delineated thaw settlement patterns across the six fire scars and explained ~65% of the variance in lidar-detected elevation change. Our results indicate a combined application of airborne repeat lidar and Landsat products is a valuable tool for large scale quantification of fire-induced thaw settlement.

54 ENVIRONMENTAL SCIENCES↗